examples.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Oligodendrosynth Examples:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "-connectivity distributions for an roi\n",
    "\n",
    "-connections to targets\n",
    "\n",
    "-connectivity-based parcellation\n",
    "\n",
    "-comparing connectivity distributions\n",
    "\n",
    "-connectivity contrasts\n",
    "\n",
    "-network analyses\n",
    "\n",
    "-decoding with neurosynth\n",
    "\n",
    "-*evaluating whole-brain parcellations\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import nilearn.plotting as nlplt\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import nibabel as nib\n",
    "import seaborn as sns; sns.set()\n",
    "import scipy.sparse as ss\n",
    "import pandas as pd\n",
    "from test3 import ConnectivityMatrix1\n",
    "from matplotlib.colors import ListedColormap\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "matrix = ConnectivityMatrix1('testing/test.h5')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Connectivity distributions for an roi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 3.47 s, sys: 4.05 s, total: 7.52 s\n",
      "Wall time: 9.9 s\n"
     ]
    }
   ],
   "source": [
    "%time paths = matrix.sum_streamline_count('../mpfc_clusters/masks/MPFC_mask.nii.gz', output='nifti')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "paths = matrix.sum_streamline_count('../mpfc_clusters/masks/MPFC_mask.nii.gz', output='nifti')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<nilearn.plotting.displays.OrthoSlicer at 0x1c0e0e4da0>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 525.6x187.2 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nlplt.plot_stat_map(paths, draw_cross=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<nilearn.plotting.displays.OrthoSlicer at 0x2414b92ba8>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 525.6x187.2 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from nilearn.image import threshold_img\n",
    "thres_paths = threshold_img(paths, threshold='97%')\n",
    "nlplt.plot_stat_map(thres_paths, draw_cross=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Connections to targets"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also look at the connectivity from an roi to some other defined areas. As an example we can look at the connections between each of our MPFC clusters to each of the harvard-oxford labels."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "from nilearn import datasets\n",
    "dataset = datasets.fetch_atlas_harvard_oxford('cort-maxprob-thr25-2mm')\n",
    "atlas_filename = dataset.maps\n",
    "labels = np.array(dataset.labels)\n",
    "labels = np.delete(labels,0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 3.42 s, sys: 2.39 s, total: 5.81 s\n",
      "Wall time: 6.1 s\n"
     ]
    }
   ],
   "source": [
    "%time connections = matrix.connections_to_targets('../mpfc_clusters/masks/MPFC_mask.nii.gz',targets=atlas_filename,as_df=True,labels=labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "connections = matrix.connections_to_targets('../mpfc_clusters/masks/MPFC_mask.nii.gz',targets=atlas_filename,as_df=True,labels=labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(10,10))\n",
    "theta = np.linspace(0.00, 2 * np.pi, len(connections['labels']), endpoint=False)\n",
    "ax = plt.subplot(111, projection='polar')\n",
    "ax.plot(theta, connections['percent'],alpha = 0.8, linewidth=4)\n",
    "ax.set_rmax(.14)\n",
    "ax.set_rticks([0.02, 0.04, 0.06, 0.08,0.1,0.12,0.18,0.26])  # less radial ticks\n",
    "ax.set_rlabel_position(-22.5)  # get radial labels away from plotted line\n",
    "ax.grid(True)\n",
    "ax.set_xticks(theta)\n",
    "\n",
    "ax.set_rlabel_position(10)\n",
    "ax.set_xticklabels(connections['labels'], fontsize=8)\n",
    "[lab.set_fontsize(8) for lab in ax.get_yticklabels()]\n",
    "\n",
    "#ax.set_title(\"vACC cluster connectivity profile\", va='bottom')\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>connections</th>\n",
       "      <th>normalized_connections</th>\n",
       "      <th>percent</th>\n",
       "      <th>labels</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.081931e+10</td>\n",
       "      <td>7.026896e+05</td>\n",
       "      <td>0.133321</td>\n",
       "      <td>Frontal Pole</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3.913577e+07</td>\n",
       "      <td>1.671755e+04</td>\n",
       "      <td>0.003172</td>\n",
       "      <td>Insular Cortex</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>7.409524e+08</td>\n",
       "      <td>1.458568e+05</td>\n",
       "      <td>0.027673</td>\n",
       "      <td>Superior Frontal Gyrus</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>8.598062e+07</td>\n",
       "      <td>1.617393e+04</td>\n",
       "      <td>0.003069</td>\n",
       "      <td>Middle Frontal Gyrus</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.598889e+07</td>\n",
       "      <td>1.449582e+04</td>\n",
       "      <td>0.002750</td>\n",
       "      <td>Inferior Frontal Gyrus, pars triangularis</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1.294125e+07</td>\n",
       "      <td>9.350616e+03</td>\n",
       "      <td>0.001774</td>\n",
       "      <td>Inferior Frontal Gyrus, pars opercularis</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>4.324234e+07</td>\n",
       "      <td>5.044015e+03</td>\n",
       "      <td>0.000957</td>\n",
       "      <td>Precentral Gyrus</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>4.731535e+07</td>\n",
       "      <td>1.004359e+04</td>\n",
       "      <td>0.001906</td>\n",
       "      <td>Temporal Pole</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>4.863145e+06</td>\n",
       "      <td>9.334251e+03</td>\n",
       "      <td>0.001771</td>\n",
       "      <td>Superior Temporal Gyrus, anterior division</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1.733723e+07</td>\n",
       "      <td>9.473895e+03</td>\n",
       "      <td>0.001797</td>\n",
       "      <td>Superior Temporal Gyrus, posterior division</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1.282936e+06</td>\n",
       "      <td>1.512897e+03</td>\n",
       "      <td>0.000287</td>\n",
       "      <td>Middle Temporal Gyrus, anterior division</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2.521605e+07</td>\n",
       "      <td>9.986555e+03</td>\n",
       "      <td>0.001895</td>\n",
       "      <td>Middle Temporal Gyrus, posterior division</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1.359075e+07</td>\n",
       "      <td>6.781810e+03</td>\n",
       "      <td>0.001287</td>\n",
       "      <td>Middle Temporal Gyrus, temporooccipital part</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>6.930294e+06</td>\n",
       "      <td>1.071143e+04</td>\n",
       "      <td>0.002032</td>\n",
       "      <td>Inferior Temporal Gyrus, anterior division</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2.601291e+07</td>\n",
       "      <td>1.339491e+04</td>\n",
       "      <td>0.002541</td>\n",
       "      <td>Inferior Temporal Gyrus, posterior division</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>4.355408e+06</td>\n",
       "      <td>2.962863e+03</td>\n",
       "      <td>0.000562</td>\n",
       "      <td>Inferior Temporal Gyrus, temporooccipital part</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>4.851304e+07</td>\n",
       "      <td>7.035974e+03</td>\n",
       "      <td>0.001335</td>\n",
       "      <td>Postcentral Gyrus</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2.190933e+07</td>\n",
       "      <td>7.534157e+03</td>\n",
       "      <td>0.001429</td>\n",
       "      <td>Superior Parietal Lobule</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>3.404416e+06</td>\n",
       "      <td>1.954314e+03</td>\n",
       "      <td>0.000371</td>\n",
       "      <td>Supramarginal Gyrus, anterior division</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>6.315118e+06</td>\n",
       "      <td>2.795537e+03</td>\n",
       "      <td>0.000530</td>\n",
       "      <td>Supramarginal Gyrus, posterior division</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>4.604504e+06</td>\n",
       "      <td>1.911375e+03</td>\n",
       "      <td>0.000363</td>\n",
       "      <td>Angular Gyrus</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>4.095239e+08</td>\n",
       "      <td>4.187789e+04</td>\n",
       "      <td>0.007946</td>\n",
       "      <td>Lateral Occipital Cortex, superior division</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>5.879178e+07</td>\n",
       "      <td>1.437803e+04</td>\n",
       "      <td>0.002728</td>\n",
       "      <td>Lateral Occipital Cortex, inferior division</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>5.706067e+07</td>\n",
       "      <td>4.072853e+04</td>\n",
       "      <td>0.007727</td>\n",
       "      <td>Intracalcarine Cortex</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>3.296292e+08</td>\n",
       "      <td>3.377348e+05</td>\n",
       "      <td>0.064079</td>\n",
       "      <td>Frontal Medial Cortex</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>1.086311e+07</td>\n",
       "      <td>7.320156e+03</td>\n",
       "      <td>0.001389</td>\n",
       "      <td>Juxtapositional Lobule Cortex (formerly Supple...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>8.457684e+08</td>\n",
       "      <td>7.406028e+05</td>\n",
       "      <td>0.140515</td>\n",
       "      <td>Subcallosal Cortex</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>9.546055e+08</td>\n",
       "      <td>3.242546e+05</td>\n",
       "      <td>0.061521</td>\n",
       "      <td>Paracingulate Gyrus</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>4.109523e+09</td>\n",
       "      <td>1.585464e+06</td>\n",
       "      <td>0.300810</td>\n",
       "      <td>Cingulate Gyrus, anterior division</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>1.045064e+09</td>\n",
       "      <td>4.332771e+05</td>\n",
       "      <td>0.082206</td>\n",
       "      <td>Cingulate Gyrus, posterior division</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>7.970394e+08</td>\n",
       "      <td>1.417463e+05</td>\n",
       "      <td>0.026894</td>\n",
       "      <td>Precuneous Cortex</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>1.254988e+08</td>\n",
       "      <td>1.022810e+05</td>\n",
       "      <td>0.019406</td>\n",
       "      <td>Cuneal Cortex</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>1.909227e+08</td>\n",
       "      <td>6.064888e+04</td>\n",
       "      <td>0.011507</td>\n",
       "      <td>Frontal Orbital Cortex</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>3.220745e+07</td>\n",
       "      <td>2.580725e+04</td>\n",
       "      <td>0.004896</td>\n",
       "      <td>Parahippocampal Gyrus, anterior division</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>3.212743e+07</td>\n",
       "      <td>4.524990e+04</td>\n",
       "      <td>0.008585</td>\n",
       "      <td>Parahippocampal Gyrus, posterior division</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>4.321207e+07</td>\n",
       "      <td>1.278085e+04</td>\n",
       "      <td>0.002425</td>\n",
       "      <td>Lingual Gyrus</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>1.355787e+08</td>\n",
       "      <td>2.222602e+05</td>\n",
       "      <td>0.042169</td>\n",
       "      <td>Temporal Fusiform Cortex, anterior division</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>2.944135e+07</td>\n",
       "      <td>1.847011e+04</td>\n",
       "      <td>0.003504</td>\n",
       "      <td>Temporal Fusiform Cortex, posterior division</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>5.707073e+06</td>\n",
       "      <td>3.885005e+03</td>\n",
       "      <td>0.000737</td>\n",
       "      <td>Temporal Occipital Fusiform Cortex</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>2.324977e+07</td>\n",
       "      <td>1.287363e+04</td>\n",
       "      <td>0.002443</td>\n",
       "      <td>Occipital Fusiform Gyrus</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>7.979915e+05</td>\n",
       "      <td>1.161560e+03</td>\n",
       "      <td>0.000220</td>\n",
       "      <td>Frontal Operculum Cortex</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>1.176807e+06</td>\n",
       "      <td>6.239698e+02</td>\n",
       "      <td>0.000118</td>\n",
       "      <td>Central Opercular Cortex</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>5.561070e+05</td>\n",
       "      <td>4.969678e+02</td>\n",
       "      <td>0.000094</td>\n",
       "      <td>Parietal Operculum Cortex</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>7.424356e+06</td>\n",
       "      <td>9.912358e+03</td>\n",
       "      <td>0.001881</td>\n",
       "      <td>Planum Polare</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>1.768704e+06</td>\n",
       "      <td>2.928317e+03</td>\n",
       "      <td>0.000556</td>\n",
       "      <td>Heschl's Gyrus (includes H1 and H2)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>7.987332e+06</td>\n",
       "      <td>8.390055e+03</td>\n",
       "      <td>0.001592</td>\n",
       "      <td>Planum Temporale</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>3.911556e+06</td>\n",
       "      <td>1.498680e+04</td>\n",
       "      <td>0.002843</td>\n",
       "      <td>Supracalcarine Cortex</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>2.888038e+08</td>\n",
       "      <td>5.473915e+04</td>\n",
       "      <td>0.010386</td>\n",
       "      <td>Occipital Pole</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     connections  normalized_connections   percent  \\\n",
       "0   1.081931e+10            7.026896e+05  0.133321   \n",
       "1   3.913577e+07            1.671755e+04  0.003172   \n",
       "2   7.409524e+08            1.458568e+05  0.027673   \n",
       "3   8.598062e+07            1.617393e+04  0.003069   \n",
       "4   1.598889e+07            1.449582e+04  0.002750   \n",
       "5   1.294125e+07            9.350616e+03  0.001774   \n",
       "6   4.324234e+07            5.044015e+03  0.000957   \n",
       "7   4.731535e+07            1.004359e+04  0.001906   \n",
       "8   4.863145e+06            9.334251e+03  0.001771   \n",
       "9   1.733723e+07            9.473895e+03  0.001797   \n",
       "10  1.282936e+06            1.512897e+03  0.000287   \n",
       "11  2.521605e+07            9.986555e+03  0.001895   \n",
       "12  1.359075e+07            6.781810e+03  0.001287   \n",
       "13  6.930294e+06            1.071143e+04  0.002032   \n",
       "14  2.601291e+07            1.339491e+04  0.002541   \n",
       "15  4.355408e+06            2.962863e+03  0.000562   \n",
       "16  4.851304e+07            7.035974e+03  0.001335   \n",
       "17  2.190933e+07            7.534157e+03  0.001429   \n",
       "18  3.404416e+06            1.954314e+03  0.000371   \n",
       "19  6.315118e+06            2.795537e+03  0.000530   \n",
       "20  4.604504e+06            1.911375e+03  0.000363   \n",
       "21  4.095239e+08            4.187789e+04  0.007946   \n",
       "22  5.879178e+07            1.437803e+04  0.002728   \n",
       "23  5.706067e+07            4.072853e+04  0.007727   \n",
       "24  3.296292e+08            3.377348e+05  0.064079   \n",
       "25  1.086311e+07            7.320156e+03  0.001389   \n",
       "26  8.457684e+08            7.406028e+05  0.140515   \n",
       "27  9.546055e+08            3.242546e+05  0.061521   \n",
       "28  4.109523e+09            1.585464e+06  0.300810   \n",
       "29  1.045064e+09            4.332771e+05  0.082206   \n",
       "30  7.970394e+08            1.417463e+05  0.026894   \n",
       "31  1.254988e+08            1.022810e+05  0.019406   \n",
       "32  1.909227e+08            6.064888e+04  0.011507   \n",
       "33  3.220745e+07            2.580725e+04  0.004896   \n",
       "34  3.212743e+07            4.524990e+04  0.008585   \n",
       "35  4.321207e+07            1.278085e+04  0.002425   \n",
       "36  1.355787e+08            2.222602e+05  0.042169   \n",
       "37  2.944135e+07            1.847011e+04  0.003504   \n",
       "38  5.707073e+06            3.885005e+03  0.000737   \n",
       "39  2.324977e+07            1.287363e+04  0.002443   \n",
       "40  7.979915e+05            1.161560e+03  0.000220   \n",
       "41  1.176807e+06            6.239698e+02  0.000118   \n",
       "42  5.561070e+05            4.969678e+02  0.000094   \n",
       "43  7.424356e+06            9.912358e+03  0.001881   \n",
       "44  1.768704e+06            2.928317e+03  0.000556   \n",
       "45  7.987332e+06            8.390055e+03  0.001592   \n",
       "46  3.911556e+06            1.498680e+04  0.002843   \n",
       "47  2.888038e+08            5.473915e+04  0.010386   \n",
       "\n",
       "                                               labels  \n",
       "0                                        Frontal Pole  \n",
       "1                                      Insular Cortex  \n",
       "2                              Superior Frontal Gyrus  \n",
       "3                                Middle Frontal Gyrus  \n",
       "4           Inferior Frontal Gyrus, pars triangularis  \n",
       "5            Inferior Frontal Gyrus, pars opercularis  \n",
       "6                                    Precentral Gyrus  \n",
       "7                                       Temporal Pole  \n",
       "8          Superior Temporal Gyrus, anterior division  \n",
       "9         Superior Temporal Gyrus, posterior division  \n",
       "10           Middle Temporal Gyrus, anterior division  \n",
       "11          Middle Temporal Gyrus, posterior division  \n",
       "12       Middle Temporal Gyrus, temporooccipital part  \n",
       "13         Inferior Temporal Gyrus, anterior division  \n",
       "14        Inferior Temporal Gyrus, posterior division  \n",
       "15     Inferior Temporal Gyrus, temporooccipital part  \n",
       "16                                  Postcentral Gyrus  \n",
       "17                           Superior Parietal Lobule  \n",
       "18             Supramarginal Gyrus, anterior division  \n",
       "19            Supramarginal Gyrus, posterior division  \n",
       "20                                      Angular Gyrus  \n",
       "21        Lateral Occipital Cortex, superior division  \n",
       "22        Lateral Occipital Cortex, inferior division  \n",
       "23                              Intracalcarine Cortex  \n",
       "24                              Frontal Medial Cortex  \n",
       "25  Juxtapositional Lobule Cortex (formerly Supple...  \n",
       "26                                 Subcallosal Cortex  \n",
       "27                                Paracingulate Gyrus  \n",
       "28                 Cingulate Gyrus, anterior division  \n",
       "29                Cingulate Gyrus, posterior division  \n",
       "30                                  Precuneous Cortex  \n",
       "31                                      Cuneal Cortex  \n",
       "32                             Frontal Orbital Cortex  \n",
       "33           Parahippocampal Gyrus, anterior division  \n",
       "34          Parahippocampal Gyrus, posterior division  \n",
       "35                                      Lingual Gyrus  \n",
       "36        Temporal Fusiform Cortex, anterior division  \n",
       "37       Temporal Fusiform Cortex, posterior division  \n",
       "38                 Temporal Occipital Fusiform Cortex  \n",
       "39                           Occipital Fusiform Gyrus  \n",
       "40                           Frontal Operculum Cortex  \n",
       "41                           Central Opercular Cortex  \n",
       "42                          Parietal Operculum Cortex  \n",
       "43                                      Planum Polare  \n",
       "44                Heschl's Gyrus (includes H1 and H2)  \n",
       "45                                   Planum Temporale  \n",
       "46                              Supracalcarine Cortex  \n",
       "47                                     Occipital Pole  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "connections"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Connectivity-based parcellation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To do cbp, the under-the-hood operations are very simple. Firstly, we isolate the roi within the matrix resulting in an roi by rest of the brain matrix. An essential step in this data is to standardize the rows. Results won't be interpretable without this step. However, if you wish to proceed without standardization you need only include 'standardize=False' in the function call. Next we find the correlation between each of the rows resulting in an roi x roi correlation matrix. Lastly we run the any of the scikit-learn clustering algorithms or from fastcluster. It returns a nifti.   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 2min 43s, sys: 32.8 s, total: 3min 15s\n",
      "Wall time: 1min 14s\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<nibabel.nifti1.Nifti1Image at 0x2414d54320>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%time matrix.cluster_roi('../mpfc_clusters/masks/MPFC_mask.nii.gz', n_clusters=4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "clusters = matrix.cluster_roi('../mpfc_clusters/masks/MPFC_mask.nii.gz', n_clusters=4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<nilearn.plotting.displays.XSlicer at 0x2415e23400>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1310.4x165.6 with 8 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "colors = sns.color_palette('Set1', 4)\n",
    "nlplt.plot_roi(clusters, draw_cross=False, display_mode='x',cmap=ListedColormap(colors))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Comparing connectivity distributions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After we've finished clustering, or if we have some rois that we'd like to compare, we can get a vector of the connectivity distribution for each of the rois in a nifti and return a correlation matrix specifying how similar to connectivity distributions are."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 5.29 s, sys: 3.14 s, total: 8.43 s\n",
      "Wall time: 8.02 s\n"
     ]
    }
   ],
   "source": [
    "%time similarity = matrix.roi_similarity(clusters)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "similarity = matrix.roi_similarity(clusters)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x2415d79e80>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(similarity, square=True, annot=True, cbar=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Connectivity contrasts"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Another way that we can compare the connectivity of several rois is that we can contrast the connectivity of each of the rois against the rest of them to see where in the brain connectivity is greatest per roi."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 17.9 s, sys: 11.3 s, total: 29.2 s\n",
      "Wall time: 27.3 s\n"
     ]
    }
   ],
   "source": [
    "%time contrasts = matrix.connectivity_contrast(clusters)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "contrasts = matrix.connectivity_contrast(clusters)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 525.6x187.2 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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9z/mHX9Cb779f+fvZ9nF+cG3m2sqUcUiOGb28UMXDX6cmQtEJgiAIgiCoM01a0VleUCa46wb6AOHmidcLd/NEOURDKCjguS9eQbN15ovjeL8i709E9EHeBr/P1HNwvNpqxmefSSq4ghJ1fPXVV0W/0yaLdvBIwRfI+dWgQZKk//+KKyRJZ511Vo3zNSeeyBxjUTqcWx94QFL1MdP/yCOLXj/6YmXMe8g++2hZMJ93H3dFxKulqLJhjOOLQsTuOQkpRYlzxXM6euy1lyTpyZdeKpqfHB7GnDsvQ6lKDuA1dXzv3kXvo6SR2zG3mSo8d2Q9z7z790uTJ0sqXNu8ktSr8xgXjC/YZcstJUkf2bWE72+cvZ6VTeuaW1NfoBCxPa7GT8+6ljM+ucZWfT+71jJlPs/XZPlU7l6RXSvPPvvs+tmQsiDKy4MgCIIgKFviRqdeuTHry0PUgiLhEB0SdVJpsM/Pf140H7ky3NV7dODVUZ7h7+y/xx7L/DylrKSgyovojDwMlBx6hPE+lTAoOSn3XfIxPC+E6Lk55kU8+uijkgpqWYqT+/QpaXl5Sk7efI+MHSup0JPomIMOKvqcY/6Pf/xDUnX10ses5/wwVvr06CGpkHNERIuPTqr7tMP8tVVygDHreLXOutkYbS7KDlVW22V5gFTlofa6csMURcKVDMYFn6NkpD7Pu+bVlboqPO64TCUtvaq4NjpsF/uD84RrH7mGXPuZ33tjkSMFzfmaWWDF52lGjk4QBEEQBGVLWSs6VGAQ7Q0bPLjoczxAyNHxigEUmTlz5kiqHsXuuNlmkgrKiecbuKKzWdbZt6FAYSLKJo/CFR2iFFw9ifb4/mtvvy2psB+IfthOohryT+pSldVUQcnx3JD6glwIImMUHHx1GLN0oIfDundf5nK//PJLSQXVMqVueo4NcA4AY4X3UZRKZXkj/1IVMGguTst0I+fcZry4uzt4RSivuUZ4fz6uFbMzZdCrtrbOFA2yINfPpnk9qxz3z6kta2VTlBx+H0UHhTNVBcr2en7lzKzLuXuesb+8zyG9sLhGluu4qx3x6CoIgiAIgrIlbnTqxPXXV/aqxUvjjocfrnE+V1z8bpzX3K2Tz0CUjRLkVVDuOeG8/s47kqQOW29dyy2rHe2y58goTjw/RtGpyq2xnByiNHe1dQ+JlKstz6/L+fmzKwIrilTOSp5Dch749+SRyrGh2uoXhx4qSep3+OGSqlfjlArn2JgXXpBUcFAmd4fPXUkqlTwn3XLL3UEx2HbbbSVVP7d3sFwRoGrKK0C9BxT4NcCr51ByljenZnlBSaKXFuuT6i+Y8nf6PMtlc4dkPkfJ8h5vwHHAoyyQ4kYnCIIgCIIyJm50agUdef9P1u9m5GOPSZL69upV4/xeGcDUXUK52/cOvkQ53oHZFQ7me+vDDyUVqrj+Om2apIIz8orGKys8muG1V4/5lO1xrxgqfIha6FN0e9bP6UTz8AiaHg8/95ykQi8qp65VU14VBlSDcc7UltoqCZtk14QPm7iyg2LQq2vXWn2v7VprLfNzcnG4hqAaOygx69v7X9rnqePD5173udg+9yqqfyfm43PvqcU1nhwmV7HdZd5VevcdAlfBfX6ukcOHD5ckDRkyRMGKo6xudIIgCIIgaEqEolMSI0aMkCS1bdtWUqE6KpUjw3P/PLxXlGfouxIE/rtEPfSYSvWyWlHwO/7cme1yJYfP3RvCn1+j4ADfO+rAAyUVKnbYb+WQs9NQuTmNlZSSs6JAjb2iomKF/o7n8LS24/xZExmz+OZstdVWK2T5m2bdzuGTzDdq46w3GrAfF2ZTlB0UHRSWf6kYHJQX2vueWwMoPnxvfZvye+QKoeiwPJQpcmzo8ca1zitoZd9L5TKRU8bUlR2utWvlKGjNg7jRCYIgCIKgbIkbnWVyww03SKrsgi0VlANyZlAk8PTw56mucHgOC++74sFdujslf5D5zADLeffzzyUVfGv4Pnf/KxrfbpQqj2Z4nyiGKMS9M9wtNeWSimcHlTv0ZWqKPjsoObhCe2+qulJqT6vmztmnnNIgv+O5HdBUqrK4BqZ6rdEvj3OZawLnLlO/5jGfKze8/0WWQ7VBphIDyglXjLXtfZSY3bLpRdmULn8zsmkql4floABx3A7LpuTsvGivwVVqv4Z51ZQrN/63xqd77rBDYs2LGXz88UWvm7Lq3RgJZ+QgCIIgKDO++OILbbLJJpo+fXrR+3fddZd+/vOfq2PHjlVWLLVlzJgx6tixozp16lQVuC5cuFCHHXaYunTpop49e1aZkubzbc6/5afF0lRb4ibAM1kn5A022ECS1GWXXSRJ4ydNklSo2OCuO+Va6b4weE0QHQF9jHCT5XtVvjGZHw2/s4l1RX95yhRJ0l477liHrV1+yBH6yrwy2M5d27cvmn9idoLghOx9XFK5P+w/pgwxjsfnmcJ1YJbL0xRoark5XpWS5yNTX6Ce5jkzN3ZS/i3sv8YWcfMHi2uh91R76uWXJVWvInIlx518mc89wjy/0JUc33/k0pA785V9Pi6btvnfyulLv62cUqeZ9yeT5d6W+TgNz6r/2AvZ4qpydOCzhcXZQFzLUj273E8I5YaqQDzKPDeHqefuHLrvvjVuz/KOr8WLF+uYY47R1KlTNXr06Co/Jamyl+PUqVPVqlUrbb/99po4caLWsdyrvGVvt912mjhxolq2bKm9995bY8aM0ciRIzV//nxdcMEFGjFihN544w1deeWVJSwxz1NoTs7n+YSiEwRBEARlxLBhwzRkyBBtvPHG1T7baaed9NVXX+mbb77R0qVL1aJFCy1evFinnHKKunbtqs6dO+uFzLgTWrduXfX/adOmqX379lpnnXW06qqrqnPnzho/frzOPvtsnX/++ZKk2bNna8MNNyxxbb/J+bf8NMkcnfvuu0+StMUWW0iq3mWb3BB3Nk49l+74vbvd7zPjs8+KvudVWN7h16OcWfPmSSpUXaU64zYUKCxEIyhdRHmsL/sLJcejOneUBt+fKEhemYCj9D333CNJOu644+pj81YITU3JSZHnMJunYJSqBDVVJce337fXFbLGVkGIkkMvJSpLUQx67LVX0fzPvPqqpMI5zTUAxSKva7nnNTrsP6/KIqfGlcaZ2bTNZZXTvTtVTtd4pcbFVwNdhu0gJ6eNfQ7kFHlepk9TsJ/cCdm7wfv8XpVFhTDzo3YvDyNGjND666+vHj166JJLLqn2+c9+9jN16NBBLVu21JFHHqm1115b119/vdZbbz1VVFRo7ty56tq1q6ZOnaqDDjpIixYt0rx589StWze1adNGQ4cOLaoW+8lPflL1lGCVVVZR9+7dNWXKlKonLo2BJnmjEwRBEARBdW655Ra1aNFCzz77rCZNmqQTTzxRo0ePVuvWrTV58mQ99thj+uCDD9SqVSudcMIJuv/++zVlyhSNHz9eEyZMkFQZBM+dO1dPZBYirVu3rlJ5Jk+eXJXGIVWmdKz9vTSNsWPHavr06erVq5fee++9EtY4qq6K4HnfLlkuDgqF94wi1+Tvs2ZJSt99E5XgWJzKPWFKtODf5/08f5zuHTvWYmvrH6IN94pIbbf76vj+8H4udHMHFCOPbljeulk3d7w/zjzzzOXYuvolpeTkRf6NhTwlprYKRmq+ciFVbZWC+ciNGTp0aH2vUklw7myXuavnVe/Ri8xdzr37Nuqsq9euWHANQblxlZfPP54/X5LUJstj9P2NS9IrWTrGsEyKKc6SzId8Q5QjNAX363GfHPDtYntSPjnuNeaVqj4fU3q2UXXJ79QmVybFuHHjqv7frVs3DR8+vOrR01prraXVV19dq6++ulZZZRVtsMEG+sc//qFtt91Wbdu21XnnnadFixbp4osvTq7LdtttpxkzZmjevHlq1aqVxo0bp2HDhumSSy5R27Zt1a9fP7Vs2bKa91CSvOrjEhezLJrUjU4QBEEQBLXj7rvv1oIFCzRo0CANHjxYnTt31qqrrqott9xSJ510kpYuXaqBAwdqn3320fz583XaaacV3bR+lqVxSJU3wZdffrl69OihJUuWaMCAAWrTpo0GDBig/v37q6KiQt99951uvfXW0lbOa/6d1XM+L4EmVXU1KvMw2SxTDqhyQnnwu3FwHxlet8+SpfC/8bv7Uh2MU/OxHu4m6uT1fVne+b0jMXj05fvPFRm2j9cetey0+eaSpFenTq3x94CoiJylA/bcs+jzlZn3kKfkMPUIsbmxsqq6gKy8+joOeTlKKXBs5hxo6J5FN954o6SCE7LnSE146y1J1X1fUq9dyeDaSnRPhWkqFyV1DfT5qEj1nlikzl6QTamWekvLhuW8manzO2+ySdH7jJNPvvfIRUorUK5as5+4Zs3PFCpc8jn+qf3LFMiB8vxSlvv2229LkgYPHpzY4jJiUU4e5OrL//cgFJ0gCIIgCFYOedFEPSg6TeJGh9ycn2dOxN06dJBUqOohuuCu2Z+TenUUz5+nf/yxpMLdd14uChCduLNxynshBa41p2ZT8uPdY8KhRmlWNkX58wKFD7OqKVecPLryXBvmo1ps5ty5kqTNspyaPIhy3GHaKzx4n55YOCivjIoWKvlSNLRi0djx/VFqbsvyQvzruRvLe3xSOUp5oHTMyVThhnb95hqHj8vYiRMlFZSCPbbfXpL0txkziuZ3TyxXdLz7Nh5YXtFKzg2QiwN510D2M1VROCH/KZuWajnH8ds+U3L8fVe1Pfcmpew4KDok47JfPA/U/+aQ6+TXQv527Z7lWMHwu+5KbGkZ0gAX1SZxoxMEQRAEQRkSNzqVkDFOlEJ0gjLjigR3zSlXypSfDkqD331DqmNtar683J6/UWSUhalXZa6gKUXHnzePaVc5vSmTdvIsJzx6c88IX9/Z//iHpEKO0ZSZMyUVFJuUCyjRJRUg4954o3L9s/1M9PLm++8Xrc+djzwiSTrhMDrVNBwcy9Q61DYvim3uuuuu9bF6DQ7VOQdnDrN5rOhrle//f9r7KD15amiplLo99Dy7aeRISdLAvn0lFa4lJ554Ys1frGfwvOIc45zCJd6vfe4K79cGcPWa5ZDf+JG5xPs1xJUSluMqsStoLy97c0uGa1hKufHXKVzhAo4zpNziU3mirBeu+eTozJqFXh/UB03iRicIgiAIgjIkr+qqHmgSNzo8B0/1W3G3Tp+mMuC95xRKkefygFcQsHzPffGpKyNV8AD60MpJqVHkRVlu0TltKs0mUl4TKa+I1Pqmvg9EjSg6eEK4ssXxef6114peE/288+mnRb/LcqjoWBm5OaiFKe+I2ioWK1vJGfnYY5Kkvr161en7pSo5DUVq//M+Pq21Vd5KxZfrr/FvuXrECEmF3I0VBblAm1hOCooAqirrlepx5dcwV6f9mse1lGsauJJR6rXn/azx4xbrr68VAddcX1/IU+Vdvff587zXXNlhPvYj1z7GC7k/HL9mQTy6CoIgCIKgbGmAG51G7aNz3XXXSapsQiYVnHTJ/HenYlcIfOpuoMDdNlE9fTxwXvYqKs9p8SjF7/79bh/uz6KNgTtXvt7kzcppXo7O21kUxPL2z/bLu9nn79vnHnWkvC58Pvbb3Ox5+j+yqIjog+3lOHiUyPveDZ73UdYWLFggqaAYTcryCk455ZTEnlh+RmY5FawbSg6u0VT2OY3FKRhH1Twn3OZCfR0Xcn1cuWGaOjfpWUREzrnCuVTfY/nJJ5+UJK23XmXnZ85Feg79wxQMV3K8f513LfdrBK7ukz/4QFKhX12p1xZ/7QoRr7fMenbVNyg6qfV1JcrXm2sVOUV/efPNovVO9QJLeY+R34g67tVbzDcv6z+4Iq+FK53pOT4624aPThAEQRAETZXm/ugK5YYoA/KUFe+863ft7lJJNEN07515U+6fKe8Fn9+jBL53Yfb5PTlKDlR5hWTKFMoISs57X3xR4/dS+8m3x/Ht5DigfHlfHM/RYf122XLLouWiOLEdHj2h/KxIPx22iW3hN9kW3J333GGHyvez75FJgO8HmRh+rpKftO9uu9XL+rqC40pObaukyo2UAuOfp/D5U8vx3Jz7M2WFc4yKTdRQFJ67775bknT88cfnrMmyQeXeNcsBY9wi7CMKAAAgAElEQVSm1FtyPTxvkc/dyRe8t9ULr79etPw8Ui71qWvqilJycL33/EiqxUqF9X39nXckFZQY8O30buVekYqKzfv8raP7PPt9TfMpKksiGTkIgiAIgrKluSs6RNf+PJe74FTFgHsV8Bqlx3Nndth0U0kFpcEVpJQiknIazuuIy3Y8O326JOnL7Hd5v3e3bjXuD9hm48qOMDOyRmtexZQXdfl6p7aH5XgHY/88b38DTs1Eu+7GCihrK4I777xTUiFS8nwvtoFIF38LKvRQdMjl+CSbrqhz1bsbP5Z1JnbX76bCI2PHSqp+7vbq2rVelp9yas6rxkp9L89xmbHMOeJKIRF8fVVhMW5dNeVc8/HAerma7Pvf+9vxGoXwpcmTa/ydtmtR71YJvaRKreysr2qrSe+9J6mQY+fXtFlZrgukHJLB94ur22wPf4t4Td8+V1hHPVPZR539m8oLdedpfn9luMWXE436RicIgiAIgjKmuSs6Hl17f5aUgpNyvyQaKTW68Oe4qdwb8Ix5V0w8GiA6Y7147vvshAmSpP332ENSId/D80lSigz7yX/XFbLU1J/P87v+/byqLt5nPxL9vfv558tcvxWp6PAbRLoeoXqEx7EkZ6eL5eykzlHPzUGJqa1yQS4OEWKqB09jLZ5EEUP5QOFgjHq37fqirjk7vL9G4n2Hsernhrusz7ceUHWFaifOTe8yzvtMUZI8L9HHe0qB4fj5tSqlJKZycjwHCMihcdUbB+ZUVZJXdKauGam8SdbfvdJS83mPKs9xYsp5znI4b1PXSH7fr+3Adt81enSN21cWNPcbnSAIgiAIypjmmox82WWXSZK22GILSdWfl3pGO3fTRDHcTdN9G1Junt6vJU/xSCk1rB934Z9lOTRk2Ldt21ZSwbOFKIG7eO7qWT65N76+vp5EP/ze55ligmsq/kOuaKXcS/33PGfJn+OnOvd6LzFydFjflJso0Vp9Po++/fbbJRWegXskl1KnWFf31altEFJbJeehZ5+VJB2x//6Squ9bxk6ej87o559f5ucst7bKytTZs4vWJ89PBTxiJ/dj78wra0VRas6Oz7eqTam14Xve64jtY3xxbqNkVVRUSKq7L4pXB7pi4r44KErk9b3xbmWN5q7t20sq9JtLjX/PBfLcEc5px69Rnl9JXiSQH+lKB9vr+ZWu5qfyKrlWsf3TM1d5rxh1Utd69ifrxfqknjak8iX9KQPXJf4GcH503rnSZI3ctqBuNMobnSAIgiAImgHN9dEVz1s9j8IrBVK4kgOpnBZyRz7OnqPn5UGkomtXAXC/nJl1/T7qwAMlFbw3NttsM0mFSgFfTqqqi3yHOdnz7RlZj65PMwWIqABPBs+pSTk3p6rFUh2P2U734vDoMKWApXJ6+B08Q0477TQtL16dAuwD/HLod5YXka1oWC+qrqDUKqWxEydKKowFj8j9GKR468MPJRWOIZG4jx0/xttnaiKqZErl85yE+iZVNZV3bfXPGTUt7fMjswrJBzPlzJUC9hPXsiG/+IWkuis6qVwWh3HuuSsoOeTJgZ+LefmKUGpPKxQPfIXw5cHZOVXd5LlIedVjfo0mx+e5v/5VUkFZ47zw7fDv+3nCfiVXiuPMcUj97QBXrT3/0Z9STLTK3LKkud7oBEEQBEHQDGiuNzopRSevXwt3y+6ZACg9PFd2pcSj0rwcHeAunLt6XnPXT67RpZlC8dcsuji6Z09JUkXWQbtN1o18g8wllO2iYoPcm4+z58yjRo2SJO2WVfhsnD2H3jJzIiZaSLmf5lXq+PNwj8o9CkxFl+DRWkpdqM/qqxFZN2nylI7v3VtSoRqCyjZgn7CN/nlD4R5Dvo94Zu9dqhkDPPNPKVI+lsld2DYbg0SSjDnyzO574glJ0uQstybVN+7Bp5+WJL2f5YC4b5G7kJfaxbqu3clTik5qecT7qybeZ6Sj8By1776SpEeycQXsf5QcqK0viuctcm3wayTHw6uRuCZyDWy/4YaS6p636KSupZ4rQy8uxpOvv4/XVB5f6vc9b5GeX4xjfsdzq3w5KTXdFRmvDE4pQylFM/UUgNcoYUyDutEob3SCIAiCIGgGNNeqK1dquAsmOnFlh7tsOssCUQx3zR69cLfNfHmKjuO5Lh7dsl64XpKT81TW6bj7YYdJku666y5J0thHHpEkXXfHHZKkDbOoa2rm4XLBOecUfQ94zr3VVltJqu4OCu6lkXJSTuXYlBrdeK6Ok4rSXOlJVUTUBpQOpjyr5zfGvfGGpOoVe3WlroqDc8xBB0mSHn7uOUnSoZliMOaFFyQV8rQ4F6jo82OfijA914NI8sW//U1SoYIPNZEInJwH5mc9xpuS4XTLclmoOER52mijjSQVnKdd2Zk5d66kQiUjuT/48XqvsdSIyXM+Tr12Hx7P0QF0KJxwUdxS/jF/uvHGxJrWDPvrpKOOklRQzDgeXBs5/igAnPN8jm9NXu4ZeYuufucpOqk8P8/RQdlB9Wa963rO+/oxLv+ZrT/Kzk8zRWsd632VV1nr83k+oVd95eHnHcos682U8479Vp95i42G5vroKgiCIAiCZkBzvdHxu+TUXbM/t3QvhlQujd9F8z7Pi707tysb/jzWKwY8g57vE7X0zHJznsyqr1ByUGq+sC7kL2RRvCs5QDSPapHymMjrxg6eH+I5Pr6d/nup5+wpRcin3Tt2lCTdkHV8rgs33HCDpIKXEMc05YScquIolZRPC9T2XL4zGxPse3x1/Jk9qh/HnvX2btBUP7mfiecCcAyJtMmpYT2INDmHiDiJkImcXeFhDDv77befJOmOhx+WVFCSvH8b24cisXmmYjrk0KC8eJd5KLX3Fayd+B2vRWK5x+X4Ev1q0CBJ0sCBA5c5H2yaVbvh0M3xQrEg4kf5Yn9x/HjdcdttJVW/Vqaq8PJyTlI9osBzZlCgmO63++6SCn4+nv+3VevWkqS3P6GrnGr8nPHCOPXxye9xza+rw7jnzPn6pJbnfztYD/9bxPFjffkeqn19qNyNjga40Vk5tbNBEARBEAQNQKNUdFJ+Mp6ZznN9oJs3d/lEf0Sh5Bsw5e6Zu2aifp7jUilCDkpeZQHwPNxdQT1nB1ypqe1zX5QiVyXcf8gVGY/K+D2iDqIKnqez/70HFlMUsZQq4i6iXqXF+tPb693MxbUuoDB4lY+rc+5Qyjqnciug1Fwc5kMBYP5UL+u7x4ypnM/2EdViPh9j1LcLnxSqa7bOcmHoXTQ3y31xJcdV1FQfMvav5xqwXMb4o48+mtjSSp7LcpBg/8wJmnyz9pnvC8tj/ci343fZPpQccmbyupGnjmMqV8ePG8f1nzbfxtn0gGz6QDZNKUwpbr75ZknSuZny8/dZsyRVr4jkuKDscI1zr6vX33mn6HVe76pUrlee1xe4kuG5XVTxMQ651lL9l8Ld4zn+wDUEpYT94Cp+yg8qj7zv+d8Gfo9rKsfJ/4YBOVh4rwE5dCjWgwcPLml9GzXN9dFVEARBEATNgOZadeXPi7kb5m6cu2GgXw5RAUoOr4kyeZ493xyQ3W+GqMNzddwnh/c9+nA3WOZHQXJXTgcfHfIkUhx88MFF68Hv8TzevSLyKm+8nwz7ibwL9g+/x/ag5KCeEH27C7ErRUR1LM/Xs7Z5Mt8HpYNeUCgZ4M/aXRFh7OBMnOoplXpi7tU67seSgvXqf+SRy5wPZcP7l/m+c5VzSrYf7r333qLldc9ySry3UWrKGOaY837r7HcYg0dRJfTgg8vcHng2y0Viyvd3zCJfvKa86zPVWVReEiS2y6YoPGR6oKw4rvj8015D6ri7z/NMe33lyJGVy82uRVdeeaUk6ayzzqpxeV4d5MqbV6Sy392p131bINXjClLKTV6OiytAnE+c865YusKCr5MvN/V7zM/y8M3x6jNee38+Xx5Tct34m+I5TSlcyeFvF+o419SRjz1WtFyupaj0k957r+h9xs36OX5TTYrI0QmCIAiCIKg7jVLRSfVzQUEgKgDumvHYeNfcXN1LgbtrFBP35fHcGH7PoyTu6r0jrrvrepTF8npneResF5n1VFgQJR9++OGSpIezyhRAOWE9iOqIcl1R8ujKfXU8VyfVLd6rsXy7mI/tYb/wOfufqVdtpaKtUsAJ+cyTT5YkjZ80SVJhH7HOns8E/tte5VBqzUOp1TyOH5MUrkDl5RQ99fLLkqRLL710mb+LQsO5QSTpFXVMUT8918f9fVJjOA+UIM7lXXfdVVLB/dvPXRx9N8/ODY7XbtkUxWVGNuV4tLffJTsM5Qd13Y+fKzie80OnsjufeaZoO0r1beLaQbVVSj3mWoAS4OcqeA7WpplilOpl5eR5aqVyU1zR8crV1PjN6x2VWj+/Zrl7vf9+av3fyypg86qtUv38/HrC566Quncc590u2ThHmeV6hWJdFkSOThAEQRAEZUtzvdHxfh+uRHBX/ORLLxV9Dy+GlALkOTLeZ4W7a1d0fD28eghSSgp3914hw3KZ33t8Ec2R97Bv5o7LXb1XFqUckfk9j6rYHu/X4goR0R/f9+fvHC9XI/g+65fycPHOwD5fbSCyfXbChKJt88jOey355+yDHnvtVbT8vFyN2nbFdtiHV2fK1BknnVTjfH169FjmcqbOni2pcIxQDffIendNyPYPPjaMNXeq9cq9VOd5xoSreowdxvBBmePzE1m1TangJg6sV7t27Ypes34zs/yyOVluRaesR9TB2fcnsZxs6lVQpeZHeq6POyh7z+lU1VKKVB85cs6oNqIay68hecsFnJA/sfzHvK7kfk1M5dt5xawrKj5/SslBtYe3Pvxwmd93xSilKOX1N0wpOXnH0avi/G+Bz+feZECO3RtZJSrna1nQAMnIkaMTBEEQBEHZ0igVHTLTya0hWiOKpY+MR5fu2eC5KNwlczec6oLOfB4NpCoPXMlI3eV7zg5RLuvp+Q4eDRCloeSQeU8U7s/9fT3YDldumH/XzLNkysyZkgoKF7/r+9O3n/wD9iuvWU4qSvPl0i8ITjjhhBq/VxOeUwKec8M09Uy/VEpVcPLmuzmrgmIMUFmIx1KXbJ/897BhkqThWX808rl8n+2QvU9FIlUoqI4oKx6xMtY4Zu6n45Gt53Ux1qjYcwUtr5IwD5QdvK7oSs9yvQKRz5/NFJB5WV+7k7PPT+raVVJBeXGFJnXcXMlDGfIqLeLuYw+odNS5Lqu6KjX/zNXoZ159VVIhvw1flZ+1a1fDt6uTysX5ODteqfVKKRauiKRyXbyXU+oayfyM3zxc4aFKyfGK2pSik/ILcko9fu7T5dclPt/UqusApc6farCcq6++WpJ0xhlnlLQ+jZKougqCIAiCoFS+++47DRgwQHvvvbe6du2q9+zm75577tEee+yhvfbaS0OGDKl1wrckjRkzRh07dlSnTp100003Saq0DTnssMPUpUsX9ezZU19+6Q9uEyzO+VcPNEpF5/TTT5ckVVRUSCpEl7fcf78k6bDM8+PxrJ8Od+dEPZ6TwjTV/dzvtrmLZ7kprwV/zXNoV5pSOTCoD0Sd7lbrShTROP2N3K8mtV6uTOV1IuZ33Q3X+yJ5ZQcKDvO5G6nvT8/xIdq78Z57JEl9+/atcf2WBfuiW4cOkgq5DB5ZuZKT6otWV+iSTi+fFOTioOAw9d5Q3jtqyC9+UdJ64JvDviVfyh1iUQld7fRqq1QE7lUpjG2OrauphxxyiKR85+QU3hvI3cZdgULxQSX2izuXZL+ujn7++cr3szHfN3OqdX+kNWzKclCIrsn6tqWceVO4EnF4llNFfiLH4y9vvimpeuWlKx5tbT9Bm0QVTypHB1K5Oq6Q4J3FNYFrekoprCtUKXn+Jriy5OPWc3u8kjZ1jc1zlk757/jxILfOr53+tILxc/6ZZ0oqVnTGZK7pL730kl544QWde+65eiTrnbdo0SL9/ve/15QpU7TGGmvouOOO06OPPqpDDz20xvWvicWLF+ucc87RxIkT1bJlS+29997q3bu3Ro4cqQ4dOuiCCy7QiBEjdNFFF1X5RC17gSX/dJ1plDc6QRAEQRDUnsMPP7wqkJg1a1ZVYCxV3mC+/PLLRSa5q622mhYvXqwhQ4ZoxowZWrJkiS666CJ169at6nutW7euarg7bdo0tW/fvio46ty5s8aPH6+zzz676gZs9uzZRb+7smnUNzqeiT7g6KOLPkdBcI8E7po9w967e6e6k/tz2hSu2Ph6+O/43b33jCKa5y6e6JNokvlcyfHleo5SqlM3pNQM1pt+LOQD8L4v35UZ9gPb5ZU5bCfRHnkdLKc2XHPNNZKknXbaSVIhwvXKMvDIyCMm92qqLSg5D2e9nIjE4drbb5dU2Dfsg5cSkSiQs0MF3v89++yiz6+69VZJ1d24GWuuunGxwvOo1N49eRGujzUfw5yL9LbCCTkPtnvjjSu7SXmfN8d9S9zfhIKPUZmClqoM5Br0UOaUfbI5ZVO1hdJDrs7V990nqbq3VqmKoecP4odENeC4N94o2j5XreuLlF+M5zOmunUzznn9WtaLCsdrV9OXF3eO5vc6deokqXoXc586qSqrPCUn9T77Z1aWM9YuyznbwbrUe94mU3LyLkooJj/84Q/Vv39/PfTQQ3rggQeq3v/BD35QdQNy9dVXa8GCBTrggAM0fPhwrbfeeqqoqNDcuXPVtWtXTZ06VQcddJAWLVqkefPmqVu3bmrTpo2GDh1apKD+5Cc/qcqrXWWVVdS9e3dNmTJFz2TeUbk01xYQQRAEQRDUndtuu02XXnqp9thjD7311ltVwcWSJUv0m9/8Ru+8844efPBBtWjRQlOmTNH48eOrbCf+85//aO7cuVU2EK1bt656nD558uSiNkxff/11UZHB2LFjNX36dPXq1ataflCNNNdHV1dddZUkaZtttpEkHd2zZ9HnD2XR3xFZNHj7Qw9JKty9E2VwN8yU6M+jjTw32lSU61GDRzXuyeKqAnjOELk6RN987p24XSlyJ+nU77svDtDZuMPWW0sqeDZMeOutot/Z5+c/lySNnTixxu1AReBk8PXhePCaaJRKGpSs2pByCvZ97s6oqalXMdUV9sWtWVRFJIl65X3X9t57b0kFZWds9mzdSb3PPvfcGs9FYAxRucexRVnic89VyItsU5V4foz9XDwwy31hfv9dLqR0M2fq3lTgEbWrjfwuSgzr627dXsVXlY+Xfc+70ZOjc+vjjxd9z89NIuA8BQMFzH2NoGvmFA1vf/JJ0XoC3d69usersMgZoQorpVykVOHUfue48r2e2TWda5o7kC8vnqsE7H/GeV6OVH0pTL4ccqLooUVuDuvF/uI1+5Hl3J3l4czMKmS/zx133KGPPvpIv/vd77TGGmvoBz/4QdF1cPDgwfrxj3+shx9+uOp4bLvttmrbtq3OO+88LVq0SBdffHG1Pmuw3XbbacaMGZo3b55atWqlcePGadiwYbrkkkvUtm1b9evXTy1btkz+vatGc73RCYIgCIKg9hx55JE6+eST1bVrVy1evFhXXHGFRo0apQULFmi33XZTRUWFunTpUtXI96yzztLgwYM1cOBA7bPPPpo/f75OO+20optZ8nOkypvSyy+/XD169NCSJUs0YMAAtWnTRgMGDFD//v1VUVGh7777Trdmj9EbAy2W1qWh0Apm+PDhkqQddthBUiGaITpybwlXbohqiZaJyvCt4W7fO8YydQXE1QJwF0vP9/DleFTo3bxZ74+z3llsJ/2C+D3utIlmPWfGe3Klnqe72yq4GsJ6uHNxar9/9NFHRetLVOUKGOvP8WC/HLDnnpKk+bUYmqiAjBmW7c/+vSLMlY76UnKc6+64Q1L1vCvP13JvpcHHH1+r3yGHB/bJckkY2z6m6QbuKpt3JXe1NOVhxXpzbhKZbpB1gUaZQbX0McT3gFwAcnLYP4wpP8dcWeL3383USXx02C6qqAgq7xo9WlIhh8gdlz3PDGWG/ca1ynOC2D98j3Fw7LHHalnwuIAcKr9G7Zw5PuN95aoyVUgoPayX7y8nVV3l4zalXlf1isoeXfzlL38pWr/NN99cUqU6IBXGhVeJLS8PPv20JOmtTJXmbwKKIE7h30/O/T7e9Z3tS3WDL7VKza+hrBfjlapR8Fw/qsoY1yeeeGL1jW8qHJ6jmj28/LcooegEQRAEQbByaK7JyKlcGKIs7r6JTryKx91ZuWtGOUl5G7hikbob9/dTzsgp982UssN2Eb1huEQeBdGuV2ywHDob0/PL1zNV6ZGqunInZUi5i3p+BscHdYVotFfmRktlFPud4/eA9TUqhTMzP4nHs9wI77nkVVZ5jqX1jecdoUzwu0TKRLZ1qTyTCrk7KDtEnuTGuLqGcsNY8Yjd/V68msojeO9pxPIZw+BqKKoe53jK94hz2isswXNgkNxRG1ne8b17V66HivH+br589ofneKDkMMZT147U6xSHZlVmOCLz+1122aVovh0326zoNXl1sE2miE3+4ANJ1RWrVC4OuSTk7KTU7ZQLO/uJ32E/oVK7Kl3fMO6Yugs91wkfd6kctJSSCf43IvXac6Vee/vtotdeXcd+A8bp6f37S2riik44IwdBEARBENSdRqnoDB06VJL0vLmSulLA83vvn0JUR3RFNE10keqHlIpqUx4PrvyknlunFBj3RvBeW6mowr0+fL14bg/0f0m5mO6ePSfHu8EVGqIYd6B2lYRom+ODasFxIgr524wZRfO5S2kqd6gUUIU8pySVLwT1VV3hXHrddZIKY459QJ4VxzDVc4ocg6OyXJIUnpuDP43nQPgYYv94NY/P567YPjY894nvucLhfi9+rN3Fm+PJlNwe8Lw0InVfrucoUbXi2+/noP8OyhCvibS9O7Wf+37O5lV6wp2ZQkfuhucwpdhj++1rfJ9rIfvHz01IKTtUb6Xm82soxxNFhWsCXi6pHl3jJ1X2l/d8S88hQxHiOOyWVeqCV6XhRM56+rUn5WCc2t4UKfWf11S7MQ42y9zxybXi+EycPl1SYTxyLWd/lAVRdRUEQRAEQdnS3G90iOJ4fup5F0RfHh169O75EUTzHiWjaLji4p4erri4OpDq9+I5LV7545UcVIi45wbRhvcRQin5+VZbSSrk6vhzdY8q6QflUTDbxf51jxNfX6aoFe6C65VQ3q/Ic63qgvt1oCCwLl5Fs6Jh3xHBugrnVUyuMDB2b8h6JXkVlis5QJUSSo6PQX6fc4UIOS/3xnvvuFLhChpTxgbKSip3IeVUy9RzLFwR85wfz7lJ7e+U75D7AbEf2F9sD/j6+TmV12fOQXHp/T07/uXBFQ4UA85ZzheOyyeZorJxppik1OvUcWT/UN3HeUA1GFAVxn5mCqnf8+OEHw3Hm/lZ3uzsc17n5RqlpqnvpcjrO/i+NcDkmunf9/OvLGiAZOTI0QmCIAiCoGxp1IoOOTWeme9RJBC1c7ee6vvi0TydpokCiGqIxngeyt00z4PdayT1vDfl8eF39USBxx58sCTpf66+umg/sD1En94NnOXjaOyVKx6lo6R4NZp3smb9vYcX87McPvc8B6I63nfXT/ab+/HUBRQQj+BLjcBemjxZUuEYeXXLo1mvI37nhISi8l9/+pOk6jkQnu/F7zCG3LWaY8yYo7M7Xkve1bxPnz6SCr41XnXG73pOiquSfo74OZTKM+N7uJY7+H94tZlXd6V6kLkKyn5jjKWUm1S/Nx8HrrZ6Pz13J3d/HMZwylHaty8Pvk+FIt/DnXzkY49Jkvr26lXS8pyO224rSfr7rFmS0j2yPrF+db49rnSwf13F5ZryzqefFn3Pc5k8ByxVFebjw32EmJ/fRVHy8w1q27vKSVWweo6bj29XFj1HzP/mlZWi09wfXQVBEARBUMY09xsdombuxrmLdY8L3id6JvpFMeC13/UTnaee17uC5N3FmXqXdPdqSVVrefTC9Jb775ckffHFFzXO5/kRHkX5c2v3HOE1SgxRwrpZ5n+qKs3zGFwt8XwYol7eJzomX8OjYN6vq4eMVGlnLklrZvv8tlGjJFU/9ik/EN+3+JdwrH0d6ULOWPNn6K4gsG/9mHtVkFcIujqIYoNvDl2MN8mcZTlH/NjzfipXKRU5e8TO/mRMeG7H45nS5Lk13lPKz5WU4uHHjd/zPD32z2GZvT08Nm5cjdsFrJc7NbM8lAlXPNgO70XkKibrz/yuRqfAqRtfHK+OSvUjqi2p/bKx+bd8mF2T6YnFa/8++w0FzF3RU0paypvLc1xS32PqzsWsD38jPJcsb9yDn9eec+VKp4+PlNrv4z91DfeqsrIgfHSCIAiCIAjqTqNWdLjrRUkhykvlqnBX7B4L3E3PyTrFUm31yNixktLPVT2KxF3WFZ5U9JGKEhx/7urRi7/2arCUe6dvl38fvOLGHabzlByPelHgWK7vL9QKz+3h91jO8kB+k/eU8YicXIfnX3tNUvVICmfSOx5+uGhd2UfMh5s1r1HjULGofvIIkt/zLteuDHjfNpYHHFNUUNS5VMUg+BjzY+sKDtvD/mQ9PGfF/XQ8L4xzMdXvDPz73kOK9T/ygAMkSaOeeUZS4dz2c8EVI/ffYT73PWK/uPKDKsnxczU0pVwMHDhQtSHli5NSdMa98Yak6lVWKXbYdNOS5tvExp2/hhmZI7XngKWqmFK5WeDHy/EcFq+GA88VclKKTqlO165YMt5T56Gfj/T6ev2dd4qWwziDezMHeHpdNWmaawuIIAiCIAiaAc09R4eolKiKaiRyWPw5sFf58DyWu2K+DzzHHztxoqTqd+UevXnUQZTteRueq8P3iOaJYonG2D5XhlLRDYqI9/2BVL5DSoFhPbyXllf8OERP3lXd+/64kuMKnUfBRO3Lw+mnny5JuierUvK8JLaNKiBXlzyCciWHKWPU1T6vaONYcQzY9+QzuVMr+8CP/U/Mz4Su6KezyVwAACAASURBVHSM//DDDyVVz0lIVVd55Z7nqTGGOGap3lEcw5Rrt/eq+oc57KZ6SvU7/PCi96kycjUXxY39ncqPS/WfYwy7744fF8/B8u7uKcUCfFwtL4w/hxyut7LxABxfel/Vlo/M06uNqa/4wbB/U47beXmLwHGkN5lDDl2q+srHVaqHWp6Sk/LRSanmvh7gOYB4nv112jRJBS83xrFXGXK98l5rTZrI0QmCIAiCIKg7jVLRuTKrIPm/Z59d4+dEUSgoRM9EYbu2by+p0DeEPIKHn3tOUiEaJVokyklluntODHfjfXr0kFSIJoGoz/1iiCKIwlBAXMlh+9h+8g28TxC/QxTP61SFTaqvjztKsx6e15LqXM3zbqJ6VAevNHFna9QMvudK1DXXXCOpoM7UBZyEb3/ooaJtSql0ni9Vcd99kqRTjjlGknTZDTcUrbsrAK7aoVxw7PwZPvvK/VhYjnso+XJO69dPkvT/XXaZpOrH2r8HqYiTiNXVTM4ZzjW2Cz8fehkxn6urrsCwneTqeB875+Z7763xfc9xcD+Zu0aPLnrt1T8+TfW48n50KT8kH0/ef6++exSx39yXZqusp9TMrDdYSuHK42NTIoHl8Lmr2LWtYvLv7b/HHiWt3wF77ln0Gh8s/73U+qQUkTzndFd0UnmS7svUrUMHSYWnCEx5KuBKFOPNnZ5hRXV9b1Ca+6OrIAiCIAjKmOaajMxdK52bycEBokFXJHgfDw/30fEu58Ddcoett65xfZ5+5ZWi9eJum98hmiHqc68L94uhIgdVwPNG/Lk220fvKxQqoko+//Wvfy1J+uMf/yipEB17ZYsrQx6Vgkep7v3g7qJeqZLyGfJ8CI/i8zoI14b52TG79dZbJRWqozhWqf5p7FuOzR+HD5dUvaLPcwr4HsfWex7x+04qN4Yxx746sFOnGr/PepGTw++nqpTycg9Yb5QblAjvFk7voE+yXkXnnHNO0XrdeeedkgqKDz2P2F6+x9hGHWR76fHl28F6Ht2zZ437A/W21N5FkKp4zMtxAvdFYXyg7p5yyik1rm8KupenHLipsks5LXtX7JTzMZCD46RyWZxSc12A/cd+owqyruy9006SCrlJedcSPy98vWsLy/PzmOP/wFNPSZK+zHKZUj3aOH9dlcdHh1ydyNEpjUZ5oxMEQRAEQTOgud7onJ3lpjyV3f3iZTJ+0qSi1ygq3jeHKJ0olGiQaJq7Y57npqKcF15/XVLau8Fx11Z3aB42bFhJy6moqJBUiGZnZF3JyVW57rrrJEmnnXaaJOlA68KOskIuENG+52+kPFVSbp3eJ8lde1ETwD1XiDpdCSKKcX+fUt1jS+Hkk08uab5HsggaNYoxxL4Y8otfSJLGvPCCpEJOivf5YtuoxvKKM/cYYn5X6Xwfwejnny9aHvs41d8srwoFPMfEPZC+soifMZDKozrhhBMkFfKt2rVrJ0nabrvtJBV6D7399tuSqrufex4XYzPVSwsfnTwFIuVom8qBSHlUue+Q58IwhlGsakteTg/nmCtLT738ctF67LjZZstcjjscp/ZHbbt9g+8XlrNlVh1W3HFq+cGP5r1MPc8bB7V1QIbUdrpLPNcTzms/Xinn8dTfHj7/feYEf+aZZ9Y4X1BJo7zRCYIgCIKg/MmTEZb9sLU0GvWNjufcED1NnD5dUiGKJQr2ShrPnaEaC6Zm+QV5mfepTP1UB1m+589bS4Xn+CNGjJBUPVpGyUlB/giKEtF96nm1V1Gl+sB4vybPsfHu8X48vNO09wNyN136VjUkh2W5EDdk1VVsw3/96leSpPuffFJS9eoqj7xcNfOcH1fNXG1jn3tuCs/mOTc4Bl7tlOranspF8P5xHBvPFUipdHkwhi+//HJJhQgXZee8IUMkFVRs/IG8UjBVZfLQs89KyldonNQ5kaqi8W7bnt/mztAoObV1QgZycLgGksNELosfB9bzkH32qXF5z06YIKlwXMn3SykVqf2XqjYqNYcHR2WUnHbZdFY2dS33vieekCQdc9BBy1w+4Mxcaq5NXi5PqdVjwPnivbXY75y/nl/qSo+PY6q0GFfzc8Z3UyBPty/7G50gCIIgCMqXBkjRadw3OkSPRM3c7e61446SCpUERJ/eGdijQYdoOBWV0ifG+yA5qTwHV0pqy0knnVSn73kvMF8P9wBx1YEpUYm7v/rnvPbny74+nnfB1L1KOI4rg5tuuklS9Uq4P1x/vaRClQ8VgYw9Im0fc+4unfJs8m7grsJ5BM2xpHqD6iWvakpF5n4sU2OY9SCXhvWcmjm41lZ1O/fcc4ter5utH5onGUBzM/8Xd7Qmt+nRF18sWn9XVPJyKVKRvp8reb4r3j/Oq9X6ZT5HdQUlbM1sPVD06MbulaSu/Plx5ngyXlPOxSny+vmlFC7Wi67nKDn8kUN/eiCb/iW7tntukftapcBHCKdm8HFBjhDMypSS2ipBqffZvyhnnrPDuPYcHv4mpXyd+F5QGo36RicIgiAIgvKl2Ss6PIfEg4Po5bWsQoO7XaJlPAbwUHCHYMcrUqZnLq/bZlExcFfu0Zw/p3eXT3eVrS1/+tOfJEm/yvJDSsWf26cUG8/J8Yohf+3L8XwQ9g8qh3dWZnkoPKgDRCccX/ISGhL8XrxH00X/5/9IKnRDJ6Kkior5UR3ZdpQHr4YikvZKNu9ivu9uuxWt33N//aukgspJbyuqxIAqJ/d78U70Hsl7BO4eSqw/lXxsB0pDXXMF5tbxe/gioTS5olZbL6a8qhxX3hirTBkPxx13XC22ovYQ8fs569U+7pXFaz+nvarIrxmp/ZLyY0rRLqs+dCUHjs+mT2RTlBwqX3HQzlNynC2yvx3vm28N6/tBttzNs4pc1nO29WJL5eTk5YCB52165ao7trtDO1NXDsuBBvALbNw3OkEQBEEQlC8Noei0WFrqLelKhKgVT5JeXbtKKig7rjD483XPKfEoxvu0pDr7vjxliqTqXgh8z6M8PEeI9lgf7sa9sgafH9QB75OCo7K71NIT6/Isv4TtItpFXfDozpUbj/ZSyk1qP3tU6LlPrhag5KDgkNfQPesq35CgEHh+EfuYfbFxNjZQEIB9627T4K+77LJL0WvGFvue3yUHZ9asynqUh62vmkNF3sY2hlP5ah4xupLjMHYnZtUfgwYNKvrcFZ77MgWMHAVUWqZ5FYSlgk8P1wjvv+YqZp4C4b3PPKfi+OOPr/mLKwj2K7lJ5Hq4QufKzQ6bbiqpoFZzXPGZIc/Rq+1YTurcdh+hVM8vFJIUKDxzM8PwLpUCi95c5rdqz7uffy6p+nH3a9mmpkKj7PA+ztGp6j5X/jwPMpUD5r3lGHf+Pn9TyJEbPHhwiXug8TIz51zcrB5uUULRCYIgCIJgpdDsc3Tg8+xunCgG10+UEldoPKog6sHTIPU8n2kqV4dqL/fx8egcbrznnqLfI9rkbp3cnVOPPbboezw3RhliPcnL+OCDDyQVoqu7x4wpmo+KFfrj4DHC/KkOuann93mdf93F06MZ8KiH6Jj9uDJyc4B190jZc3bcY8gdi4n8fV+7epe3Hqhb07Oxhkt4Hoxxzz9LRd4p1S2leHivK3Al5+abb5Yk7ZW5mJPbg0LFsWe76JlVV7+ZvA7312dVc+TzuWLhnlveny5v+Ssa9uuz2bnMdnBtYbzuvMUWkgpq94S33pJUUNA4vuPeeENS4XgwPsir82sA+Lgqtcotxdr8p0/lZPHwmue75f77JUkDjj66pOUCXu3tM3Wba2vqQQbd3sGVHMd9k1BcyBflb4VXrnq+o1fEurLM/mY8loOSA3GjEwRBEARB2dIQychNIkcHeN5PdJjqzOw5ItwlkydA1OLRuHtiENW5o3IKlBPvk0TOzfG9e0sqeLAQtfNcfJssCthoo40kFaIi1uO9996TVFB22D5ycVBkPsyqztgO9pfn6BANomK4m67n8Ling3ucUBHk+92ru/ic/YSydfh++1Xut5U4JO/JVDivtGOdyXdiLLEvPZeDKdvO95i6wy7zeZ4XETeKx/jMIdc54ogjJEm7Zt5PrnKmel+lnJJT/j349ey77741rsfVWXUa+2XnnXeWJLXPziHOCVdQyDk4upYR+/JCXznW16uqGlvk/MADlU4zm2a5N4wnV1cZV/7alRjeZ3xwrdiAHlRWsZrq7p76nHFDF3V6auGMTMeyUZnh8ZZZ2VWx+03dWV/Fy0PR8XHv54vn0riy5eo0arT7P3mlaamVrIw/riNebcn5Xg5MylH/dokcnSAIgiAImirx6Mo4JvNQGDVqlKSCUuJKgTsjc7fsSoJXZTkoDVQ6pPrHAB2Vb8vWj+V6XgZRLc9byUH6LOvPgqJDFMD8zMdyUWR4/s7+4HtEBSguXtHjeRa85nOiRarBiGpcyfHO3KmO3K4Ysf2oFo2hbwsRmlefuGOpP0PncyIv74XFvgS23T2IWA6v8ZBi36cUHeZzp2BIVc2kcnJSDrjevdwhYmXM7rHHHpIK56xXRTGGGlrJAfrKNRU+zvIHOScZP+67hHOyKzruL+SqrbumOynFz31e/NpC7yk+RyfaK5v+O1NyFtb4q6VDT7DDunSpXG5ivlJ9cUrN0fHziu13fxyvePX9z+eu0PE3i78B5URD3OjUrTdBEARBEASNlgkTJqhbt27V3p84caK6dOmizp07q0+fPnUyHxwzZow6duyoTp06VbXNWbhwoQ477DB16dJFPXv2rApg81ic868+aFKKDuApsknmBeG5NuBRikfN/vyZKAePCeeBrEKkT48ey1y//kceKUm6M/P/OerAAyVJIx58UFIh2q1rLyvAO8SjNrab3Bt+j/2AuuAddL3buOep+Hyucng0Q/Tm+SHMjxJ1rFWdrUxQpTxvyXNqUG6AbSUiQ8nx5aBgHNipk6SC86vnzLCPGdtU2fTO8rzGZJV2+2V5TeRW5HWd9hwdSEW4nif2D3OMhSuuuKJofYcNG1b0+ZHZOREsH/QWuz+rQvK8OdRnxiOkel65Qy/jNZWbkho3jBfGiefrcV502HprSQVFh+mz9rquoOTQO42OUDgjp3JzACdlel5B6rzyakr2H/OhxLiy48fB+/551SfX8CFDhtS84cYf/vAH3XHHHdX8vpYuXaqBAwfqgQceUPv27XXzzTdr1qxZVfmhpbB48WKdc845mjhxolq2bKm9995bvXv31siRI9WhQwddcMEFGjFihC666CJdeeWVJS93RRKKThAEQRCUEVtuuWXV4+Lv884772jdddfVFVdcoX322Ufz5s3TNttso8WLF+uUU05R165d1blzZ73wwgtF32udNUmVpGnTpql9+/ZaZ511tOqqq6pz584aP368zj77bJ1//vmSKosnKJLJ4985/+qDJqnonHPOOZKk6667TlKhQoC7Yn/+meqoi+cE7qApN1jIU3IcfGzuyNxs+x1+uCTpvy+/vFbLSYG3Bx4hHoV5tEc07nkhXinh0R54l3GvrPBcHK9gYX6ik5WVl7EscOodMWKEpEIuiUd+Lvcy9lzJ8bwmps+8+qqkdK8rpuw7V1j23HNPSdXHfl7uDXiViY8Bn4/cnJNPPrnG5bG+0VW5YeDcQdkD98bK88pCiUDRYZrXIyylAOLEnAd608xsunM23SqbujNy3iMMFBwUIUbh9MxN3s8/YHvZH+6EDKncJK51nH/ut8V54b/vajrXVPfxQhGi2rFUjjrqKM3M/q59nzlz5ujll1/W1Vdfra222kqHHHKIOnTooHfeeUfrrbeeKioqNHfuXHXt2lVTp07VQQcdpEWLFmnevHnq1q2b2rRpo6FDh1b5dUmVajPXh1VWWUXdu3fXlClT9Mwzz5S0rpGMHARBEARBvbDuuuuqffv22n777SVJPXv21Ouvv66ZM2dq/PjxmjBhgqTKIHXu3Ll64onKLPHWrVtXqTyTJ08ualT99ddfV9ltSNLYsWM1ffp09erVq8oSZVnEjU4ORN/33nuvpHTXbVc4mL7x7ruSqneKffP99yUVFAmeK9cVlBx6UZ166qnLtTxn6NChkqTbbrtNUnVnYvYH76c6U/vzeu8y7rk44NGLR5OoHyg5x9SyA/HKgPwpemB5xIabNRV2KD9eYUfE5spJSvUCxi7zU9nmVWHk5rh6l6fo+Hyu5LA8zo1PP/10mcthbJx77rnLnC+oXzxX7OAsRwXnY6/89F5YriC691XKn8fnwyentryYTalnJbOLUVSqnw5/LFFyqPLi2sMfZhQSry7zylv8fkqtPvP8R6+i4ndd2WH92K+c57zGl8d7ytWVLbbYQgsWLNC7776r9u3ba/z48TrllFO02mqrqW3btjrvvPO0aNEiXXzxxVV+c852222nGTNmaN68eWrVqpXGjRunYcOG6ZJLLlHbtm3Vr18/tWzZsto1aWXSpG90giAIgiBYNnfffbcWLFigQYMGqaKiQscff7yWLl2qvfbaS7169dK3336rgQMHap999tH8+fN12mmnFT2+xPpEqgzCLr/8cvXo0UNLlizRgAED1KZNGw0YMED9+/dXRUWFvvvuu6ogMY9QdEqE54PIZ6m+RO7r4spGqkfW8nJF5r46YMCAelleiu/LiVL16M2jE+/qznzu3pvKE/G+LL6/ge+lKnYaM+Sk4KDr2+ZKjLtyp3w2eJ3qD+a+JOS+8D65QN7bKtUjx/OpwBUdH/Nc4L7Ich1SUA0UNCzHHXecpIL3FtdAFEZ3NXclI+WvA4wnrrG8pgqwfYkJpylQbMgG3Dib0vWu1D+CPp/3nuLayPnKtdH9rfz85Lzwvx3gFamu2HKe8nuem4My69eBHlmPuOXxFttss830apYLePzxx1e93717d/31r38tmvfHP/6xbr/99pKX3bt376oKUNhwww315JNP1no9G6IFRFnc6ARBEARB0PQIRadEeH45cuRISennzdxle+Y9MJ9XFdEBeI8sgQvobeVuuHyfrPcVreSAd1imgzSVOd6pOZWjAzxXzuuH5PhzfaKpxtY3qDbgoIt30f9kPZ1QqYgMU7kyrrQckFVNPfzcc0XzQUoZYvmeC+Df96oqP9b+O+4X5D22zjzzTAWNF44XCgHXPs8NS+XXkY/nai7XAJQRVziWF1xeqJp6OZvWtXaPClpyXVBC2Q4/j1I+QVyzdtp8c0nSW1n/QBQav5aSf+g5TN7Typ2ROX9ZP9Y7qF/K4kYnCIIgCIKmRyg6taRv376SKhOvpEJFilcYOJ5bkuchAe6wzPcOy/xzVjZUd6F0UTnEensFgjse+/Nqohfvbu75ISwHtaMpVFmVCqrZn//8Z0mFfegd5dnX4LkQozKPiZSDsedMuHrmlW0+9a7rqeqqvXbcUZL0atY93JWchlIjg+UDX52nMvd2PyddIWQ8ueLQLutFBlSmMs5TuWDOX96sdMLpvPPOy5yPs4ScnBnLnDsfz8VB0Tk8cxCnB9j+WQ+2v2cu+8C1D4UGUO3dqw31HiWG3011Jff8RneLZz+jGDcH4kYnCIIgCIKyJZKR6wgZ5vTZoLOzR9lEJdxV8znPqz3PgZwc7trdKfioo46q702pF1C6hg8fLqlQmeHPrXl+nHIBJqphe91vh2iICp1S+7I0RXDnRtn5Z+a7QURJ1QuRH/uIZ/yeS5FSEVNVIBwrV3ryfD9cdaPb87tZ5I4K5xV8QdPg/cwDjHHHNc0VvjwVm5wU+tFxzfNr6MzM58V9dPKUHCAXh15X+P+SAVTbaB+FEsX0yAMOKPrcVX3f7lT3dbaf8ye13zivvBKVaa+uXSVJYydOLPo+yhNVjp5vGSwfZXmjEwRBEARB46chHl21WJpKEmjGUK1E1JyKhqB///4NuHb1B94wrlC5xwbqRVB31sz2KU7KKDtH7L+/JGlMZq/OWONYUO0yZ84cSYUxudVWlV2B1ltvPUmFMZlSgPgc5WlqlpNT3y7dQePgjjvukCS1bdtWUmHceO4ICg2+OCgVjDsUHdTcn2Y5PEwZx7V1RkaxQR9aP5tShUWuTn11Trsva2WA0or/FMrTB9n5hZKJIzG5OlSj4VfE91F+mJ/zi5wdPj+6Z8+i9SFXCIWHfoiNJb+zIbkkx739d/VwixKKThAEQRAEK4VIRl5JNJcoF2+YYMWDw+kjjzwiqfqz/d7duhW9JgL1Xjip7ujeBR1S/jjNZYw3V/r16yepMN7w0kLZ8b504JWXXmmZ8mH6yHx2vPu3s4a9/iqbtrQpLK+yc8xBB0mSRj//vKSCkvPu559LkjbPlFF8eDhvXGH1vogoYCg+7jDerUOHovV48qWXiuaDmjqNB/VH3OgEQRAEQbBSiKqrICgzPHeG3BzgfXIiiLBRcNwbyntjeT8yIlOqOj7PItigeUDOB/467giMQuEKBrhfjPsx8X5tPcjQkfgj5woP79f3Y41D991XUsEfiF5d5OiQW+MKqedpunJDFSW4UvbS5MmSpL132qno/euyXKoTTjih7hvVxIlHV0EQBEEQlC1xoxMEZQYRI746rsB4t3IiR6pnqPbwyNydbz03h6qtgQMH1v9GBY2eHj16SFJVd2m8tBgf3uWcXB7GU8o7jPlRHhnXH2bVR7y/VevWReuDE/KP7DW5OIttWl/g2IwCMzvzjXIlK1W16FWN7rXmjuXgSg7Vl0ccccRybU850BA3OqXpjEEQBEEQBE2QUHSCoAGhGuaee+6RVL16iggYPw5yH6ia8Ygx5YTsjqsff/xxPW5F0FSZMaPSoWabbbaRVMgxQYlhfDF1R2Dc1F2RdKXHXeZnZX489NKqq2Jzf6ZI4XZPtRO/t/0mmxTNP+6NN4q2k6rFlLM4Sg1VZ94bzJVTP29RgNgvr739tqSCP8+nn34qSTrkkENqtd3lTCQjB0EQBEFQtkSOThCUKccdd5wk6YYbbpBUPdeByLlNmzaSqvch89wApt7Lh945TdW9O6hfzjjjDEnS1Vl37B122EFSQTlk/HjVkSs2VAUyH+MR52HeR2EhFwbfGqqdps6eLamgIPH7KEk4M7/33ntF64PiwnwoRzOy8Z7X2yul0PA971nF+cVr5uM168F6sZ84j/GvCiWnOpGjEwRBEARBsBw0OUXnscce0+9+9zt9++232mmnnVRRUVH13DUI6srSpUt10kknaccdd9SwYcMa7HcHDx68zM/vv/9+SemcHG9Vx3x0IZ81a1a9rGdQXqDswNNPPy2poFSgfKBsoLQwvlAyPIcFZYZx+X6mZKBskDOGrww9tei15d3RfXxTLcU0VeXkuHLj1Y6AIsN2p1pBur+OKzhsJ0pOc+xhVSqh6BhffvmlTj75ZD344IN6++23tcUWW+i3v/3tyl6toIkzbdo07bfffnrggQdW9qoEQRA0K/6d868+WKmKzsCBA7XBBhvo4osvliTdeeedOuOMM9SuXbtq81566aWaM2eOOnbsWNW5eejQodp555117bXXJqtPgvLmtttu04UXXqg333xTLVq00G677abf/e53uvzyy6vNe+mll1b5iXyfa6+9Vqeeeqo23XTThljlWkFuATDOfbwT0ZIrQO+cQYMGreA1DMqBAw88UFKhGhAHbpQdlBZXUFzRcYdgzzmjGziKB8vle668oBwxdSdipp7bg18Vv+++Uu7ozOfeddxzkPgdr85i+8hd+uijjyRJffv2VbBsyj4Z+Ze//KUOPvhg/fd//7d++MMf6sYbb9TIkSNr/GMkSf/7v/+rTb5XPti2bVvNnz9fX3/9dTy+aqb0799fTz/9tH7zm9/o22+/VZcuXXTiiSfqxBNPLHkZ11xzjaSCfB8EQRCUDyv1RmeXXXbR5ptvrscee0xbb721PvnkE/3gBz/QLrvsUm3eSy+9VEuWLKlRufGoN2heDB8+XDvvvLNWX311vf7663r22WdrzLNJKTqNGa+iAs8x4DW9rI499tgGWLug3KAaEHici28N1X8oISgq7tSNkuIKC69dKfEqL/8eSslPMx8er37yaiwUI/xrOI+YDwWG7UCp4vNUzo/3omM55MR98MEHkqRTTz21xu8H1Sl7RUeqVHVuueUWbb311ho0aJAOOOAATZo0qcZ5v/zyS02YMKHq9ccff6x11lmnqqQxaJ58/vnn+uabb/Ttt9/qk08+0f77758cQxdccIFGjx4tSTr00EN14YUXNuSqBkEQBN+jWdzo9OnTR7/97W81efJkTZw4cZnzHnjggfrVr36lGTNmaKutttLw4cMjm72Zs3jxYh133HG68MILtWTJEvXt21cvvfRSVaTmXHjhhU3q5sZ9P9xHB4gsP/zwwwZcu6Dc6dOnjyTp5ptvlqSq1AGUFYJMFBNyXzx3BYUHRShVNcX3UHLw0WG5XqXlOTY+9dwilgMoofw+y2O7WA+2g/lZTxTUo48+WkHdaBbOyKuuuqr69Omjzz//XOutt94y591ggw106623qk+fPvr3v/+tLbfcUrfffnsDrWnQGDnvvPO04YYbVknFDz/8sM4//3z94Q9/WMlrFgRBEDQGWixNGQU0EAsXLlTXrl117bXXas8991yZqxIEjY5nnnlGUqF7uSs65AzMzhxmDzjggIZexaAZQnXWRhttJKm6I7JPu3XoIEl6depUSQUnYx/H5NaglJBjg0KDskLvN4JjFB5+DyWG6iiUJEDZcUdkXlMd5ooSylQ4jdcfe+ZUTL9aD7coK9VH56mnntImm2yigw46KG5ygiAIgqCZsTjnX32w0hWdIAiCoGlz9913SyooLH2y6sYXXn9dUkG58e7oKCkoMHPnzpVUUE5SvaFGjRolqaDsrL322pIKOTlejcXvAct3J2QUJNbjiy++kCSdfvrpOXsgqCs75Sg6k5u6ohMEQRAEQbAiWenJyEEQBEHT5vjjjy96/eesSotea179RM4NuS8oKfjn5PlA4WODUsSDCZZHFZhX/JtT9AAAA8xJREFUSZGDg4LE75KLQ27Q2WefnbfJQT3RLKqugiAIgiBonjSEj07k6ARBEDRh7rzzTv3xj39UixYttMYaa+iqq67SbrvtJkl68MEH9T//8z/69ttv1a5dO91+++1VfazKiRtvvFGStNZaa0kqKEdUYeGkTNXWP//5T0nVu7gHDc+mOTk6syNHJwiCoPny9ttv69e//rWefPJJTZo0Sb///e915JFHSpJee+01nX766XrwwQf197//XVtvvbXOP//8lbzGQTmzZMkSDRkyRJ06dVK3bt307rvvruxVkhSKThAEQaPh2muv1U033VT1+q233lKHDh2qlIjvc+mll2qbbbbR1KlT1atXL0mVVUJt27bVggUL9Jvf/EatWrXSRRddJKnSVXju3LnaYostGmZjgmbHqFGjNHr0aI0YMUKvvvqqLrnkEj3yyCPL/M5GOYrOp/VwixI3OkEQBI2Q66+/XhUVFXrxxRdL6ue3dOlS9evXT998840eeOABHXzwwdppp500bdo0zZw5UzvuuKP+/Oc/VzXoDIL65txzz9Xuu++uvn37SpLatGmjjz/+eJnfWTfnRmduPLoKgiAoPx566CFddtllevTRR/XKK69ol112qfbvqaeeqpp/4cKFOuaYY/Tuu+9W9aVavHixxowZoxtuuEFvvPGGWrdurYEDB66sTQqaAfPnz6/Kk5Iqq+vIj0oxd+nSZf6rD6LqKgiCoBHx0ksv6Ze//KWeffZZtW7dWq1bt9akSZOS88+ePVu9e/fWdtttp+eff76qYebGG2+snXbaSa1bt5YknXzyyerevXuDbEPQPFlzzTWrSvalypwdSv1XJqHoBEEQNBKmTZumo48+Wnfffbe233773Pm//vprdevWTUceeaRGjhxZdZMjVXYef/TRR6tcfkeNGqWOHTuusHUPgr333luPP/64JOnVV1/VjjvuuJLXqJLI0QmCIGgk9OjRQ6+//ro222yzKsl/t912q3oc5VxyySX6/e9/X+0PynPPPad1111X119/va699lotWbJE7dq1+3/t2VENw0AMBUHjOATBdpyicAqgpCiqStsZBM9/K3nO85y11tfv4D89zzN777nve973neu65jiOX88SOgBAl9cVAJAldACALKEDAGQJHQAgS+gAAFlCBwDIEjoAQJbQAQCyhA4AkCV0AIAsoQMAZAkdACBL6AAAWUIHAMgSOgBAltABALKEDgCQJXQAgCyhAwBkCR0AIEvoAABZQgcAyBI6AECW0AEAsoQOAJAldACALKEDAGQJHQAg6wPERNLGun/g+QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 525.6x187.2 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 525.6x187.2 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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OO/XUQpdje1iRI2SVJRQolASqvJJ6X5U3uaLwPBWUs3r16knK7ytz9CEpZ5s33n1XUlr5sL3PoLgKBd3Lh4Vp2/DGxpDsEoQUDQ/Tp8P0w6++kiT9+GOqu9TKlSslSScdQ9ZP0dbfIUz7hCkZRihO74bpy6w/TNdHpmVNrpyHRaNrwufPlHgN/ujKcRzHcZwKwnN0HKdS8tFHH0mSWjdtKimdcxPryfPQ06mYlaoolB7bZZmIGmXHCq4oOaNCl/NeXVPREErNjqEqBsdkqrVQUsgZYr2Mg8if10kOyFaR4fsWtgPFoLIpOZAruTu1atWSJLU/4ohC57Ndv4HjVNxqJ0AxQSlpa96nlxQdoFBMjgu9uJ6aPVtSwf5bf4bcK5SakAKU11MLZQflht5bNvfm2zC1XcoL7uxVduTKeVg0/EbHcRzHcZycpexvdDxHpwK48847JaWj3UsvvbRYy3E32IpjavDL+O67VP9jHFpRcKxyw9T6l+D0akmqUkKp+emnnySlcxo4p8i1YRwoOEztZc/3UGZs1Q1dy5OIKUHZdjuvLFS1a+mRRx6RJO0XumrXrp1q4nRogwYFzv/BwoWS0jlaTUOVVmmDL/CroafU0uBATJXTojBF6cGvhmosFJZY9RNKzs5hurt5H2wPK5ybUZZwRF4YFM+d8fMJ75dXjo6lqp2HxSOpom5aidfgio7jOI7jOBWEKzo5wX333SdJ2mGHlHnDlaGPUayfCqwt4XqrRzRQMTwTcmRQVGyui1VuiJxt7ymqqWK+N/QaoprpifHjM8bB/KtWpWJWlCUccPEnQaGx47CvGTcKDwoQ62GarX+OhVwlq4CRU1RZqezX0oQJEyRJu+22m6R0rhbnwT4771zwF4vI0nDcdgnLzZarwpTcGXJ3rG8NoLSsTZgP5cb+dqIAJf2G2vkWG0UnWxYsWSJJ2q9OnSJ9L4nKft6VDgcmfP5xidfgio7jOI7jOBWEKzpVinvuuUdSOgofFDpNE20w3TxMiVrWm895baOR0npeXD2ihLJhXPCxoYcVigiKie0ZhFICzG8diLkMqb6iSorl4HNje1ah/KAs/fDDD5LSvjXk6KA02VwcXlv/ntjyGZ/tnYQyZSE3B2XIdsvGXwhFi/UzP1Vi5Crh4Hxl374Frq+kJF1jle3aGTIk1Z2paaj+IzeL4xLL0Uni+6Dc1TB5gFBURYcar3phyn5eZab2tzCJ2G8pJP3myrz+tpiKVVlT2c670iUpP+yzEq/BnZEdx3Ecpxoyc+ZMtW3btsjf27BhgwYMGKAWLVqobdu2WhiS2+HGG2/UWWedleXSfk34V3L80VUJoEPwrrvuKkm65rLLMj6PKTk8LbdRTFJUEntdVIWneno1lAz22d2jRklKKzAoJtb3BiXEKjr2tVVoUDSYooAwtVVcVolBTbRd0vFHQUlBmWH9LIftAeaLdV9HeaFKzFZ18T3eZ7/w+t4xYwpcrlWeWL517i0pMeUgdo1VtmuHHKwk5+DYdtrfDpQcsM7J9vzNFpZKdZP9bbTjyVbZSfrti6njMarTA45bb71VY8aMyfvNKArPPfec1q1bp+nTp2vGjBm66qqr9HxQZV9++WW9/PLL2mOPPbJcWtk/unJFx3Ecx3GqGfvuu6+eDa1bJGnOnDlq166d2rZtq65du+ZZVkjSqFGjdPXVV+e9fuutt9SpUydJ0lFHHaVZs1JNPRYuXKj7779fgwcPLsJI1iX8Kzmu6BQDqqi4Y7X9fWKEhrl5z6vXmGmSkmMprrIz7NFHs5zTgfsfe0xSOlfFVlehRBARWgXDKhbk8gAKhvXhscuxDsQ20iZ3hu+zPDsuFCIUF16j4LBcxkvOB+MElmdzOezr2DhYH8u1ig6wn9mukvb8ipHtNVhZlJ1so3G2a1HILasXHJQtHBewik4sZyeJuV9/LUlqvOeeGeOJKTcldSTO9rfQzpetorMk5NDVKYYaUlno2rWrFi1alPe6b9++GjlypBo3bqwRI0bo1ltv1fHHH6/rr79eS5Ys0dq1azVjxgxdeOGFWr16dV4VsZS6vn/++WddcsklevjhhzVv3rwK2KI4fqPjOI7jONWcefPm6eKLL5aUCnwaNmyoY445RpMmTdKoUaM0f/583XzzzZKkDz74IC/ok1I3whMmTNCSJUt05plnatWqVVq8eLFuvvnmDCWoYLwFRKWCnJzBAwdKyv+cORZFELtbz4ekDrmx5dnvF1XZqV+/viTlPVP99ttUpxdOcic/XNRWQbE9rYD5bM4OU6qqUGiY2pwZlAxgeUxZj63yst3PLayPnkfdTzhBUrpKilwesIqOHQdYZcvuB6voUFXF1FaLWaXLbtczwT+m6/HHF7idSWSb4xGjopWdP0fV2YCS8+3q1ZKkuttvn/H57iHn55vw2CLJUTtb7Plkyfa3L1tiClFSN3LO1ySqspITY//999fDDz+svfbaS9OmTctzfS+IVq1aady4cerevbtmzJihJk2a6PTTT9fp4enGpEmTNGzYsCxuciQZFTEfBf+EFQm/0XEcx3Gcas59992nHj165N3UjhgxIu+zXr16ZczbpUsXvfbaa2rZsqU2btyohx56qPgrLvweWCqFSn/30SmE4cOHS5K2D1FPnzPPzPg8VjlgP68bpjhakOJFBcIqFUxSVBNbv60w+OjzzyWloxXyIlaHqO6bb76RJC1bluoE899G2anoPISKZFSossLJF8WCXBiqXmLKjlU2rJJhFQyUE5QZImGm1v8mhq3KstCLit5UdrxWIXny5Zczlhf72bCKTtKU/cH2kTPEa5sjZHOQbBVQlw4dMl7TE+zcU04pcLzFJXbtLSmna4U8QXutljZfrlwpKX2ectysA3CSqj3rk08kSZ+H3yIUxLIi2yozy+Kg3KJsVTZy8rf4l4S8r61Kvs2u6DiO4ziOUzEk3X2WgqLjNzoF8FiosCGXxUaJEKvQYIpfDv1d9g5TlJyYb0622O9RzWWjKyozUHKIoqn8Ie8hFh1WdB5CRfDEE09ISu8z2xuKXBuUGhQGW5VCBGxzTFgeyg7rARQMvsf8dr6Yrwld0Z965ZUCxwWcC3b74OlXX5UkdevYMeN9cmOsQsNy7Puxqiy7Xzgn2S+2xxb7G2XHOlGjPKEYlJWSE3u/TtiuslZ2rN9RWbF3cFpe+P33kvIredlWRx2+//6SpFemlbwTdXFI+o2lispWnSWB4sV5v+eOtm+6k0g5tIb3Gx3HcRzHcSoGv9EpXx555BFJ0sXnn1+k78WOE3n5KDrk6KDolPbx3dxMl4UpUTB5JtbtNlu32eqk7Pz888+S8ldXgc0tsVVTSVVJ1n+HacwJGazPDcvp1bVrgdvBcvCbQeFhekYw/aIrus3psUoOsF2xz+Hxl17KGC/bYxWnWLUYio3NVSK/zDo68z27faVFto69Za3s2Gv29XfekZS/+zyvmzdqVKTlfxV6pu1Vs6YkqUFwf4+RbR8+lMrxU6dKkjq3bl2kcWVLUX9bbXVgtsSU0NKmOvzmliV+o+M4juM4TsWQVHVVCnjVldKVNQMvuKBUlkeuDJk93cK0Xpj+vzB9O0xLS9khB6hlmD5tlj/5/fclpT1hkvrjJJGLUQaqHjkiKApWWSGiRkHAz8Q6F1v/EavgxKqPmPY7+2xJ0oOPPy5J6hsa5T08dqwkqUeXLpLSyglKCYwOFu9W8YgpHVYJKStlJAY5NrHqLbufOE68RskgLw1Fwzooj504UVI8/y4JFIytzfuoqbidl5WiQ+lvzaC44IeEYsJ5aPPwWjZpUuhyUXLs/mW/sxwcjiFbRWfqhx9KSl8/7Q4/vMD5jj31VEnSG8Hrq6zBVwhlJ9tcG3J0bM86608UY8bHH0tKK6+tQxd6uGf0aEnSpT17SsrN31x9lqCG7etVV47jOI7jVFU8R6dsKSsvCqKb5mGKbvJlmK4x80FpHe8eYfpRmJIThBvvDyFqKym5lLODSzQRLJErEbLtAg5EpuTOWAWI753ZuXOJxoeSg3KDchFzBkaJITK3OTF8j+0horTKTXkpORDzV4nl8tgcHo4DOVZE2o+E43teUApKquSAzdnZPUwXhWlpXyPDhg2TJO2zzz6S8lepcW2j4FnfoRhfr0q5ecUUMxS1mC9Ttr9dKBaoyxWFVaCydUS2sJ84Dpxv7M8kZYjGmbaaEnJaySlHqvWNjuM4juM4FYgrOmUDPat2TagkyBbbmXe/8D6xac1QbvXywszvca+PwoOjcVGP+7IQde0cnssPCe8fEqbfhmlZVTjkgrJDZIUCQwRMpHb+aacV+L17x4yRlI7ILuzevUzHiZKR1NsJ5cP6yKDQ4IhscwtQeqwileSLYz+342O5wOcxnx4LilOspxfvW4WHykKUCbqec3yL2yMrVnXFtWyv4dK6RvjNsvvrtRkzUssPuSZsN+d1Upd3m6pp/ZtQPA7ca69ij70g3nj3XUnSsc2bJ8xZNny2dKmkoldbvfVRSi8n3xH3fJuDNz/0EWxUt65dhCSpY8uWBb4Pz7/xhiTp4YcflpSjCk85JCNXyxsdx3Ecx3EqAa7olA04HidFOdliKxCosmoYlJw1QckZH94nV6e4N7JECVRaEI38EPJFdgnRLYrScWFKVyN6bVne+/RTSVKzhg2LObKqB7k5KDJE+igFKDkoAfacIYeH71Pl1DN08S0qrMc++7c5FuSsWIUl5pRsc1wgVgVGDguKi+1izX6wuS/0lrI9pmLKSUzJseu1OU7sJ+u7Y3t8MUXRIU+N40X1GtuddNxibug2EyPWPbukkHNjOe6ooyRJb86aJSlddXVimzZZLdcqGnY/oqiVFkm+M1RbUX1l3y8uHIcPv/pKUvq8KaqPztGHHJLx+pPFiwv8vs39eXHyZEnZV7zuGHJ8krq/O4VTLW90HMdxHMepBLiiU7o8/XTKWaZO6Lw7cebMjM+JHon6gE7PSXCPfjHmGqEE47ag6EwOb88O3gvWobjpvvsWunzrucBdvu2czXkzK0z/HqZUX8UUHZ43o+wQLa8KFQRtDj200PFVxVwdtvmqfv0kpf1qiGjHPPecpHikd0G3bgW+b8k2FwWl5KFwrloFCZ8ZsIoM2PHymiox60vDOWV7/ZDjQWRvnW15DaXVWyrb/WSVHatE2NcoO7bHGN/HITqpSi7228z75NvFFJ/iwnGmaumYww7L+DzmS2Ohd1Xeb4b5TbFVbEXtAZUEvyUoUGWNrbJCKYXiOiO/v2CBpLiSynrenjNHUrKPkQXVHl+onMRvdBzHcRzHyVk8Gbl0GD58uKR0bg7VR0RF9m6cKCepBxRRAnnz41ByrgvTUP40MbycGyoiWK7Nq8A1FAXl5LZtJaWf6xJd2Q7aeeMJUenKEJ3tFF5TdbWzCoaOwkRxRHfkhSQpOZaqoOyMC0oAkT0Q+dtcDZQdcnBijrsxOMZJTsOsh9wg242bKe+zHF7brupgvwcoMLbXFYoNkSSRJedEzE/F8ul330mSGu62W1bzWxiX7SGGwoA/EDlBNjeH/W67nHP82E92f73w5puS0tca12KMmDMwSg4ZHceG5b1RxGvj3nvvlSTtt1+qppPzFkUkScmxlaFsl+0Ob/vh8VtgFRDLgiVLMpab1BsLOJ5UF911112S4rk4Q0P10SU9ehT4eQyOy//3ZSpD0laTMY59d9lFUlrxStoOm9tme7pxnu0UusDP+uQTSfmdvI844IBCl28rZqvCb2xlolrc6DiO4ziOUwnxR1elw847p7QMW7nC823usg/ff39J0jvz5klK351P+eADSXFl42z+Q5ARknXevTo1zetWHqIjmyfA1HauJl+E6JVonfmtomOjbZSdv4aogu7p74YpeQSdWrWSJL36dqr7FtHIQXvTPSv3IIIlEhv26KOS0hHUIyaipKqIY5JUnTPyqackSb3POCPj/SRlx/r1JDm2omSQV8ax55yfOTd19tleV2wnEW4s1wcFAEXAYj9n+/ANKa6SA+TK2Ooucp5QfGx1llWo2C62n6okjj+5SOxHW8XF8rg2zzPVQOS9oezE1NMvI+8nQbUV1WsoOYxnwvTpGfNRrcPxIZfq82XLJKW3E/XY+g3x22IVsRiBl+qnAAAgAElEQVTs/1iuSgz8c3D8znvf7N8OoQrQ9pLLFnJpOB+sArNfyNuEbBUp62zMdcb+Zr/Z16w3aT38TQJ+pwace25W46sS+I2O4ziO4zg5i9/olIwHHnhAklSvXr1C57N3zURF1h8nxiL+Q1iXCpKEJvB5iJqo8GFqoyeiAp7fxlxobX8ivsfzdaIHohd6Xk0Nj/EXhkIH2z3drgfXUJ5bF5XK+Bx5fIjM2fe2Yi3m7zHiySclpfd1TLEBlgf22X1SD6kH/vMfSelzw1YDsTwicXph4dhau3ZtSfkjWIi9tn45HyxMlQwmXQvZXivFBQVl1DPPSEpXZaGM2eNmq6aYzyo1XCtsL87C7A9ylNiP9riC7WbONRV+CvKuwWXRLSwccqTsa34r+E1BoYlVD3E+2d+i1aZ7N8tHQelw5JGFjo/vJfnjxEjy6UGh3N50BbddzmO5UrYqj/GWVHGktxjnhVVw+Fuyww47ZHxeXHJKySlHcvpGx3Ecx3GcSoxXXZUM6xzMlP4q2223nSSpZs2aktLPS7ONTm30llfeFKQccmFs3x2m1u3SPje2VVkx91uiIRQdojaijEnk8vwlFQ2Na5xa/2GpVCQtDss5vkWLwjY3J2Cfs49spGf3LZE+PaxQWmKR2diJEzPWg/KDgkSEjMLAsbZ+NuRQ8NqOy1bgTXrvPUnSLkF9Y3577seUHHsOxapASpuiunH36to143W23dVtdZqtyrI5V0MeekhSfnU0loNie1zZ3+5V5nVR1U7OG367bPd2uoLHKKo/DMstqn8L66HazhJTUMhNu/3BByWlrwtyjVDl2W6qr1BUrKIDb4RKVnt9F3V/xMBBnOv5559/lpTeb1zX7E/GX9q+RFUaf3TlOI7jOE7O4jc6JYO7aqIhOyVa4y77y+BYvHfwPEiiXpjmRWtBGvltSsbLfHkPNoqXmQ81wFbcWGWHz22OD1OiiLzn5t1CndVFYfwDU1NitgVhSjVWEtaboyrAvrmiTx9J6e7jsR5QKB0oOTxzj/nn8D32vc2jsk69HHObI8OxtcoNvZlQiMjFQcmxfjNWJWTKMcNLityO8u6pU1p91WK5GRb8hGzOznOvvy5JOq19e0np48T+sDkyMdh7jKOkPa4eDArHAUFhs4pEtlVIHHe2l1wX+xtj/XNQ+LLFqtHWZyaJBg1StaFcB4wX1Z3rZq/QRT3vNzyyPD63uUO2yqqooESuMvmXtvqR48P+tNfhh599lrHcJHd8S2XMgywy5XCjU7RaQMdxHMdxnCpETio6I0eOlJSODugUiz8O+QdUFVmvjSQ2M1MqKT4OPa1s95akChcUGeuzYyt1bMWIjdrt91Ef2K5vUwUrqhskG7xUp4cpys56M42BKkBUUtRopDzBCZl9dFc4R2z3a9vNmGOEP4b1YiInh2f19hxC2bG9lYBjh0MxypFVesAuHyUnljNk5yfyxH9nevBfmTBhQsZ8Nw5J2XqzvZxLKAEoSVSTMB8KSHnl+ICtekKVjJ3DNrcHRefZ116TlI7UOW62mzzY3lb2fTu+omL3MwrFYcEhGUdi6+SLPxJeWBx3q/hx/rNc3kfJSVJi5n/7bcbrmOrM+WzHFdteqyzxfcZLfqU9v+1vl1W8svXHSRonSiTeY+wn25uK/cr1YfMsma+o/kM5hT+6chzHcRwnZ/Gqq+JBpr59rk5UaiF6IVpYHKIfoolYzg4upyghKDkoPPS5sdGJ7RBs8zLAenbY/im25xVTW31VP+yHvDqIUA5WN7zkPEuKOnHZBdbP9mXbd6ciYN9ffP75ktJVG+zjHl26SEorHdbplX1uYR/j1Gt7TdmI1PbWst3PbcUcy7HfI8InsgWr8nGMONfmhmM4JuQmxWB+vh/z78CxGJ8TcinIYaAqJsmHpbQgOOTK59okjy6Wf0ZuDsqO9amhmiaWq2ODUutga8fF2VQr7N8VEeWEiJ/zz66fXBMUCFze2e8TZ86UJC0N6rVVhW21n83zyzZny6rPMVifdaMHunuTO8Z5zPZYlRrFxO5/zr/iVjdl6wrfsWWq0yFKIOPjuKGAcvy4vtku9leSVxl+Voc2aFDofFUSz9FxHMdxHMcpPjmp6NiogtwcWx3Ec2vusnn+TlSaVNGwxrzewUxRdFiPVVpshQ53+UQptt+Mfb5ro36b60M0s18YB1Htjsszx80NNeONubfi/1NUxaYiKwNefPFFSel9cfeoUZLyq2VUM4E9Nla9Ao4pitBjIRcI7LHgGKEQWOy5e2nPnpKkm4cOlSRdfcklGZ/P/uKLjOVbOKc4B5OUnI7Bcfi/L7640PkAx2K2GwUAxYkIl1wGIuDSwupsttqpsXlNZeHCyPLYX+TtcS1STWOVNXqf2Wo6fHlYL9cWvw2YqCdVOLJc2+fOVutYZ2F7HsXUXqs2W4dfcktQhlDmvlie+hFJ8gIDW23EfG/PmSMpreRYOK9XhopYxo+yFfP+YntYzyH77FPgfKWF3V7GzW8m+9nm3mWbF5qTSg54jo7jOI7jODmL3+iUDKvY4B5L1ELnWWA+ogVbYQP2uBDT/GjeXxSmRO82aiL6A+7yWa+Ngqw6EMvHsO9bB+caqcIGbRaUHaJKFCrmt9tTGXNvkrAVbjG3aeA1x8bue16jAKHk8Iw+VnXFM3rOBc7Nf4d+bCgHnBvkdvzzrrskpZUcnGOpTiFijJ1LQI7DkSEin0mEHqrFbDXRPaNHS0orSkngK4Q/DfuLHCK2j/10+nHHFbo8W9kYUz6sgrOjec25XC9M0ZPuC1O8rlCk7Hliq8n4zcB/yXaltsef9e9uxr1Y2cF6UXJQPnBIBqvy2vFzflh/HM4f5ienhO1CMXl3/vwCx2evp5hiYX+T7HgBhYdx8ptMLy72Q58zzyxwPGB/O5McuIvrCfZMqFa0PcQYp/0bYq/LpJymjz7/XFL696MqeZZlTTkkI3uOjuM4juM4OUtOKTr33HOPpHRfFNuRmI7Hz7/xhqR0lMNdN3fNRAG7hKgmBlEjsTC5LYvClKos+7w4Fn0RFcQ6JRPd2eVZF062o16Izk5lHCwohMfUFVg/oLJSEisiV8fmBICNOGM9rqxLNefKVubcsIqKzZmJRXK2ZxERNrwRzlW6NF/Zt2++bZTSEbfNKyPC/DJU5bC+448/PmM+1st2ZavkWGxPKZSkWrVqSUrn7NCF3PauskpO0rnIfFRXkZPDud3SvN80fOHtsGCUFXue2Jwbprb6if1lu2JThdcj/OaQH5etRxWgIJ114okZ7x/bvLmktBKFokbVGOO0PlGMk/MEBYfz3J6PVEcl5Stav5yYM7J9ba+7mDeYrVjNFquwxTy/YkqJ9SeyUOGLQoZnGzwxfryk/D3T2M/2dwNFyypw7FcqX49s3Fg5g1ddOY7jOI5TVP71r3+pRYsWatasmUaMGJHx2ZgxY3TwwQerdevW+T7LlgcffFCHH364jjrqqLyijyVLlqh9+/Zq3bq1unfvni9wK5D1Cf9KgZxSdGw+Ruw58KnHHitJenHy5Iz5iGJiHXZjED0ebl4/bcZl+8CA7Yxsox7rzWI9TqwChOrAObIoTENTdR0Tzj2qschrsKdkLKrmuXFZVzKUBC48Ww1hsRVr1neGz22fNHtO2WNsfUmI+HgfZWbEk09KSquOODij4ADdmYEcGs7ZT0MOAooJ29PVKDcw+N//zthOlvO3AQMKnD9bxk+dKim9H2x+GpFtUlfsJOXD5uCQA8O11zxMDwnTA0dkznhdquWVJoe3Yw7AVpmwikfsmkU9ZnxW0ckWFDlyglgvOSpWOcQPCEXNKpYxRcFWddlu3/jd4MQc21/Z+unEsL/hVtGx1zPnW+fWrTPeT7o+5yxalPH+wfXrZ8xPzk6SkzLHw/ppcfxtjppV1o4+JHWGTps9W1K8+mzKBx9Iktocemih44FJkybp7bff1rRp07R27VrddttteZ8tX75c//M//6MPPvhAO+64ozp06KD27dvnPQnJhiVLlmjIkCGaNWuW1q1bp6OPPlrHHXecbr75ZvXs2VM9evTQ4MGDdf/99+uKK64ofGGejOw4juM4TlF49dVX1aRJE3Xp0kWrV6/W//3f/+V99vnnn6tp06baKRjhNm/eXDNmzFDNmjV14YUXasWKFZKkIUOGqEm48Vq0aJHOOusszZgxQ5L0zjvvqFWrVtpiiy20xRZbqEGDBpo9e7buuOMObdy4URs2bNDXX3+thqXUtLek5OSNzvmnnVbg+zj3chfPc+4ZH38sKX/eRRIoIOTiEEUuKGBeKb8yY5/PWuxzaZtLZBUc2639+yAbnhjyCXBu3t1MLSvC+mpF+idVZiUHYr4dsSosG5HbnBxbvWIjVqu22aoWjj3n2MinnpKUiq4k6ZVQrRTDKjzk0NCzq9/ZZxf6fcvgq64q0vzZYiN99hf7A8Up227gYBUcVEiCwVVmCnkq5egwDUbU+5n5khQIjp/Fnk9E8rZazOYeZYtVVuw4bbXcC2++KUk6pV07SWllB2XIKpQ2L9EqOvY3yv52WXU6Vs0I9vpiSm6K9ZvCv4jriu+jcMX8o8hhIacllgtklRxIqm7ib4atsrLjQWmiSs7mV0Krgw+WFFeouPnIluXLl+vLL7/Uiy++qC+++EKnnHKK5s+frxo1ami//fbTxx9/rO+//17bbbedXn/9dTVs2FA33XST2rdvr4suukgLFizQBRdcoJdeekmnnnqq1q1bp7lz56pt27Zq1qyZDj300DyvLCmlXP3444+qUaOGfv/9dx1yyCFat26drrvuuuTBegsIx3Ecx3GKQq1atdSoUSNtvvnm2n///bXllltq2bJl2mWXXVSzZk3dcccd6tq1q/bYYw8ddthhql27tp555hm98cYbeuKJJySlCgl22GEHTZo0KU/RmTRpkiTphRdeyLvJk1I3fCRmb7bZZpo7d64mTpyoHj16aPLkyfnGl4E/uioaRCn2OSl330cdeGDG/EkdarPlwzAlJ6eH+TxW0RPzcLE5RkRtbJ99PxYlEzUQ/ZJDRL7+C2b8EFNyigv9o04OlSHlga0CsVNb6WZBwbG5GFYZosrFOs/yI8D6bJfiJSHXgfnIwbHKjcXOd3nv3oXOX96c2KZNge+jYNHlPVusPw5nOBWCn4aqJPZrh5ATwW8n3dkaT0lNtwlv4ELDcmN5chxXFAVbXcXxttVAtwWlzWKPV1IFIlVRXPusd/Szz0qSzuzcWVK6uofxcl4yP+cxyoN1SAZyyji/+d5bH30kSdp/95QO/Pmy1BFgP9mcGAvjoOs6Ck6syorxkbtmHcltTy7r3AxW2bFd1YuLzR2yzsdjJ06UlD7f2Q6ba/T4Sy9JSlfVxZSbol43Rx99tO666y5deeWV+u6777RmzZq8ysfff/9dM2bM0JQpU/T777+rQ4cOuummmzR58mSdd955Ouecc7R06VINHz48uvwjjjhC1157rdatW6dff/1V8+bN00EHHaSLL75YZ5xxhtq1a6ftttsuu1wtv9FxHMdxHKconHTSSZoyZYqOOOIIbdiwQUOHDtUTTzyhn3/+Wf369dPmm2+uZs2aacstt9RVV12l2rVr69prr9WFF16oBx54QKtXr9bgwYPzllevXr28/BxJqlOnjgYOHKjWrVtrw4YNuvHGG7Xllltq4MCBGjBggG644QZtsskmuvfeeytg6/OTUzc6RB/2ubJVcgAl55sQFe7xp2eORQEH4SvD1Ap1Ng/EVhTY57pEB7aqivwOojtUB6IpojOWx3xUnlwcwuNPwx30XWb88ENYTs2EHKJsiVVolCU2NyfJ58P2trLVVTYCtJEhkTI5BRwL1DYim++DLwffoyrjtvvvlyTtGqo8WB4+KuNDxA7ZKkAnnXRSxvbQvb20eWlKSjJB2bARaO8zzij0+zZ3xfrj4Nr91uKU841VyGBiUMg47o2DIgJXBzdw8tVQhmK5V1ZJsH4o9jwb+vDDGZ9zjbLch55O6b6cJzH4A7FfUEA4L09u21ZSWgnAoRsFhPHGtsc6ODOfvU5YDoqjVWys6pzkKJ7Ui81WfbFe9tPUkLsC+EBxvjFe8jAZR+umTTOWD9n2mIr56FglB8XG/sajvJGLx+dcjzbHqqi5a1CQR9mtt94anf/666/X9ddfn/FerVq19Nxzz2W9zr59+6qv8fVq1KhR3uOtrHFFx3Ecx3GcnMWTkYsGd+14SSTx6XffSUpWcn4w1VI2h2WlyaS3jszkY9joz1Zh8T7RmY3KrIcH8xP1EGVYF9M8j9sg7fwnhLO2g/NqE9UtD9EKqsK+u+yibKDCgP2wbFmsH3rpM2TIEEnS7iGXwFZ3WEXH7lOrksWqStj3RHT4xRBhotQwP8/eWc+g/v0lpSM+loMCxPr7nnWWJOnGsF3WTydJ2eHYxRyVY2RbHUQwFsvNKSrEs1xhVFG9GLqfsx+J/G3eGseX4/FoSISk+/VbYb8eEI7zk8bXxB5XrkXro2SrlZjaSkjmY7m2Ki8G54FVcYHzi/3AlN8UplZxseNkfIyXnCA73j8nnv75fesMHXMgh3fmzcsYh82BYr+zPTEnZL4Xy+1BGZn64YcZ81klKskTzI4fxYj9wfXFeLi+7e8N+5v9xfiojoNYf8Wcxp2RHcdxHMdxik9OKTpJUZIlyQF5lXmunNf1PJL/YV1IicJq1qyZsRzrDWErgmxUALbXFVFErPcV4zg9fP+4oOTYHKIfI/knbC/RIwpYXifsUNEwLjyTtUpVts/BS5OBAwdKkp4MjsP2mLBNdhrLabD7gtfsc+ujsb3JCVm1KqVJ4DlBBE0XbxuJs/xzTIXatWG7khyTLf8YNKjQz2PKjQ2yYj4wNpcG0PDwO4nlBtmqKuJ3vk83dPyIOrZMda8iJ8ieY9bPyFa9WWdam1OBosA1yrVIBB7zlbE5KLGu3dlilSMifaqfGKdVZmIOwraKLKZYsZ9s7g7nqV1ebMr3bI6b3V9W1bZVbW+99VaB+4cecP2DMmodihkvx81e79n+Ntnj2u7wVO0qXcv5beS6t/vZKshWMeY8RhG1vbKqBZ6j4ziO4zhOzuI3OkXj0ksvlSRdc9llktJeEtnm7KwwXhm2424sCoh16CXK4q7fPqe1/Y9sDytyfOz7VgEC6+LL+maF+U4Nr/EWQbFKijqJ7mwfJaJLxombp4222b7ypHv37pLSyo5VbpIivFifNLadbUZpsLkN5JKg5tWuXVtS+pjbCDbmRIv/jPXpeT4hNydJ6YFsj0ys9xSKDEqM7ZeWpOSQk8P3HwxOvrZqh/1KJG2roZJ6OlmoXsLvhP2KEhBTcmxOiPVzAXt8Y72XYliF0XZRt8u11U42h8WOi++hXKFMst22Szs9mcD2boopa7aKyzqF8xtmVfFYlZaF+RgPigvgNMxvcKybu4WeXvz2knfIeWK3n3FYhZbtsuehVeWtn04SbNfiUIVI77MqSTkkI3uOjuM4juM4OUtOKTrwSIhms1Vy6AlF1MFdONVYy8Jdus3JsdF4kiqA0mL7xdiKAaID8jtQD6zHAsvl+TqKC+oCn+8YptSWsT3WBbVOpKP04hDtsT2sJ+aREavA6VKOfjr3B18a3EBtrkDSM/pYN3IiYCJTcm+Y/9tvv5WUPtb0oHo+5BTY6hkiuMdC13L7jJ5x2jyvtkGRuC50BkbZyVbJKS1QeNaa10UFLyerSFjlxCpy5DKhzMRyRahuITcKJ+GfjO8OOSoxvxwifNvbiGvTKgQxp+UkRceenzbnhXGiwNheUDFn8FjVlfWv4f1YN22r5DDlNwzfGKqSbO6Qrbay+5vt6tatW8bnrMcqaDFQmVH3+e2yDsqW/erUkSR9EhQTflPpj2hB8bHO0zbniHGz/eeeckpW2wGT3ntPktS2WTNJ6d+NKo0/unIcx3EcJ2fxG53ikVV/DUlfBm8NPDeI0ok+uJsnymHK3TqOy58tXSopf44M2GgHTw/r6RDrv2Iz9ol2bB4BTdWI9vjecuNy+vXXX0vKH8V++NlnktKqBetDWSLKs8/vresoVVhEc6gc5QnVGE+FHBf7LB3YBz1PT9WmoQYyHxGnrZRDyWEfc0yvvzLlj33T3XdLSnePtk65dp/ZKiv7zJ7lsL49Q3flf96V8rf+n8svj+6L8iCWu5MtRKY24ueaSXJ0jvUCQrlh+RxHe01Z3xurAFrVFWw1l8X611glI0Yst8bmpKAQxrqC2/VaV3arnPG5zRWLbRewX+n6/cB//iMpv6rNbyzzs7/rhy7i5NJwfaHAWAdh9h/LYz22ezug7o+JOP/aqkIUSnp78bcg1h8xpvSUNig5+PksDX97knqmVWrcR8dxHMdxHKf45KSiQ5TCc1N7tz03KBooHNZTwnYHZz6UDRuN2Y6zO+20k6T81VZMrZsu8LmtUrJeDSgpRKFEdbEKEcZbP1T+WOjubisxbM6QVXSa1KsnSZqzaFHG8qhoGfXMM5Kkiy66qMD1lgdEfOxDG/mCrW6yfhyAamY9g3BippfRd8FzCFWLY2JzQGKwj18Mzr6cYzglo5oV1TuqskDknFfNFc55W6lnlZwhDz0kKV3FZnOerMs4WG8rW8VkFQzrN2OVIJszYtcbU3iYj/MyRlJVnq0qK2rOmfWxsQqjVVDg6/AbyPq4PlBygJ5uXHes1/aCQ8nh+uE3zG6XrYRl/7N8zhfmG/boo5KkAeeemzGu8087rcDtslWF9vxE2fn4q68K/H5ZMfn991PjCfuD437EAQdISvtMVWm8BYTjOI7jODmL5+gUD5QXoj4UC+6KiYJtHgBRB1EFSgjKC9Edy5k2e7akdJSCh8PMuXMz5rOKC6qAVZLseIiWbDRjo1+iG+vVYJ+/wyvTpkmSOrVqlTF+m29g+85YrwhA2QFUiK/KOfopiJ49U52+ng5KC/vI+lywj/qfc46ktHKAakbOAMeGc4P58Q7iWKPkoAbyPuuhGiwGx9T2LAKOUVl1I7fQJZv8Lrbj4IMPliSdftxxGfPHfrts7s41IceIc5CIlf1789ChkvIrD1wLMf+hmPdVrFrIXlux6hmOi50/poiwPttDCwfvGPYatxG9XZ5VKFFY6L7N+OlXR34i5zfLqxfOy6+C+znz2f3F+vBxAar/3gy5Mh1C7pRVQMkxOzDkOVpn4VjVmfUqY7vYDtT0/fffX5J0W6i+pLdctsTOX/Y/PbtQVuDRF16QlFxN9dqMGZLyK1d2Svf1WZ98Iile1Vel8Rwdx3Ecx3Gc4pOTik6vXr0kSS+++KKk/G6f1tOCaNLm0hDV2c7U9nOiKpQMokC+Zztk77zzzhnLQYHiub19Pm/zBYCKBKvEMC78dxrVrSspHRUcHqIdvCVsvoCNaoHtOO6ooyRJr7/zjqT0/iQXiu0577zzVFlAYbG+OhxT9vE9o0dLSu9T9jHHkuXsEiJjjrmNvP964YWS0sqQ9Vmx+VkWmy9lPZSAaqzuJ5xQ6PKKC1VodKB/PZwzwH7AsZj90/uMMwpcns2FoGdR+1AVY6uIbL6cVTSScmNijsR/GFdwe85zPthKx5gzss0RsUqRddROwv4W2OWw3phPDio2fekYF5WVnH+2p9Y3P+JopIzlWqWB7f0yVCHFHLptrlSDBg0kSY1DnzxbIZqt+7xdru1Jt1voY3hIcHT+v2HDJKX3W3GrFFk+vwsoO9bF3qrm8PacOZLy59rEeH/BAknSYfvtJyndbR1XenIBqzT+6MpxHMdxnJylHJKRa2wsalvdKsjYkF/AXTgQNdmohyjDdqgmaiDHhmjIVnRYLwiiXuvqyfeIInETRRGhcoFcI9QIpraqi6iT7VkS+rW0OfRQSfndO1k+0Yh1bmb/8L6tNCEq4XWPLl1Sy6vEpxS9r4hgUUyAXAG2lcgXnx0LqpitUuF7KC1UddUJjqscM7pxg40En3711YzxcCyIHHF+LS0mTJ8uKX1uMEWlJPcCWobxcy7f8Le/SUqfA4888oik9DXDdqMQcc7bLuNsp+3txPu2OgeKW31kcz9sdZb1o7H5b0m9rTjPzixiT6K3335bUvq8BLt+65MDdjxW+eA3hNwWex7b7eL7/EZNDI7UzxtHbpy7OV777LOPJKlhw4aS0vvXKjk2H9EeF0jqz2d7ZqE8zQ55lUnKDgrlQQcdJCl9nlmFzeZK2d5szcL2xpgfPMZQ3S1UeR24114Ffp7nqH7SSYWup1KzeUIn+d9K/vfEFR3HcRzHcSoGf3RVOnQJSkNZsX2IHvBuICqxVV4oKbhZEr3aaNc+d+d965PzzTffZIyD59KoCSg53PV/+umnktIuvnR7Ly0qs5IDdDVPggjVeiRZcFyl6soqEPS4QrlgeRxzi60esi7YEHPRLipTPvhAUv4ckpjfiO2pxZRjP2jQIEnpa4L3R4wYISmdn0a1DUrHvJDrwHZZFdF6OFmFwV4zSZG+rdaKdbO3y4tVecWOB8ob11xRQTmxSsda05/PKjk2Z8zuN7u9KEYxXx6+x3o4blYRBc7XRo0aSZL23XffjPdjVUZglRLrRIzSYVVl+322b+/wfRQXlJ1Yj7iuxx8vKe25ZvefVZps7liMRZHfky/C7wPf34frJCg5jIPzqWnYnziqV4Xf3oqkWtzoOI7jOI5T+UhK0SnYurJo+I1OKWDvph8KlTY8l7bP+22nYLDRScwNFUWIXBw6W9tqL7xP/K6/6JwaIr0hQ4YU+DnVVhZybuiSzTEkr4qqJFudQf7Y0aFK5NWQm2EjUyJS2+W8qEz98MOM5RNpk0+GR1Sr4JND9dV5Yb9cf9ttGdtlFRyw79NVHuUIZYeIf+HChRnfj+Xk2Oope63YiLu4VT02pwVQwOz3bI8ptrO47uAogfQ8A/xawPrsWMWG82XizJmS0scbVdkqkRa7X1CUyNGBTp06SUrnttQLHlsxvxir3FiHZdk4HwAAABtSSURBVMBxnO35OFSVoWKTD8l2sR10IcdPiN9kfisZf0zZYTyfh5yymNJlt6ee8cni+7Fee3Zqc3cYB1VYMdf/qkjSkyu/0XEcx3Ecp8pSDik61aPqqqIYOXKkpHSlAdVTRBNUnpCHgDJDHgfTuuGunufoKDpESUTh1tuC6MopOigPfxswoND5qLriGKLokLNDBIcyYV2weR9FxzoDg/UqKi74b1iV0CoW1jGa7fjiiy8kpfPD2O7Le/fOav3/e+edqflNtcsDDzwgKa2AcG4TqVtfI6a2y7jNqbHTWC6NVVFjSpDt/m29tKybeJ8+faL7IhuGBf8XlBGbq8X2x3JxbL6g9SOy7u22d5jNE2S7OQ9mBoWI44OSs+uuuxY4Hqt8sHyOu+2FhWrN+cZ1QY4big799ZJYaKoIZ4Uu4GPGjMmYzyo7QI4N55HN6bLXDYoS4G8UqzbD4wzlhs8PDf5DMaqyWr8qoVJyx1LYNld0HMdxHMepEMpD0fEbnTKkd4hyqTjhLt9WONioEGz0Y3tu4YHB83J6S3lOTvEZNWqUpHTkGHt2DxxTq4gQ4XKsbF8ylJ/xU6dKSvdJQ3EhsiZCpOdNcSEnx0b2EPOX4TXjRz1Ebcyr1grftzk59vXtt99e4Pj69etXpO0hDw5fIusObrcLYt3Nk6p/2E7OC5QH8uy4Bi+++OIibUcSA4Ki+HJwwOb42RwcpjFFym6H7V4OVuGL5TSxv3E45rxAlY759oDNgeK3DIWTarNYV3l7HtucMrC5Lg2C0gTvhUrUbt26SUr3xOO6v/766yVJxxx2WMZ4Y9vB+FByyInqcOSRkqSjQk5aEpxXdvstufAbXw5+gX6j4ziO4zhOxeCKTo5wYeh7BPfdd5+k9N26VXh4fsxdPRUnRGG41eJ8jNJDNJkLd/nlzejQ42rgBRdISueSWJ565RVJ6dwR+6z+zfDMn0gP5Qa/GryNgGM7+f33JaXPCSLDkio5sZycWK8oq+TwPt87vkULSdLQhx+WlD5XY1VXVAdNCTlLg6+6SlI6x6aoSg5cEI4T3HvvvZLSDr/sVxSCmD8M2Fweq3jYa7Jnz57FGndxQfVF6bPHyWKVFOufY3N3AMUxqfqK41e/fn1J+bu1x5yOrcM0iqgdt92+2Hi5vughZZ2EY47DwHV8WFBsbFUZ2KqrmGKG4oeCivJHzt6JbdoUOp4nxo+XlM5N4njwu4Ly6xQNv9FxHMdxHKdC8KqrasaDDz4oKR3N8Hz+nnvukVT6TsZOfrY3EX9Sjg6RFpFn+yOOyPicHJxYTyoUF/xzShtyF6zPCt2QLUTGMR8ZqmNw2T7//PMl5d9vdwwfLknq0KGDpLQCsHjxYklphYTlLVq0SFLJq5RiUL3EOGyfOqs0EJkT2Q9IqL4ra8hJosoIbK8t2/fOdl+31Vl8ThdtlAvrV8Ry2S9WiYlVVaFE2R5QHH/2L+cl1VS2yuieoLiikOCw3fuMMzLmmx2qwQ4OSlO2UI2FbxGVrbvvvruktF+UrfLjtVX+UNl53/or2R5l5PLx/TM7dy50vCiqXH9VmbkJVVeNverKcRzHcZyqSnkkI7ui4zh/IqbotA6KzD9CL6fKDkqOdT62fh2AkhODiPu7776TJJ167LGS8ldXxcaBDww9n1AGiGjnzp0rSeratWvhG1bKkNtj/Ysqq3r6Qsh5sn431k/H+uLEFB1bZRXL5eK8sd3bLSgWKBoodlYhRNFAwWD9VG0xPrzGUPw4fzifcOrGn4blNA89tt6dPz/jtWVByHO0yh7jYj+Q82X7EVqlC2WG5dgeXR8E52+rHNrvs36bo9QlKKS5lIf5YYKi09QVHcdxHMdxqipedeU4FUz70J382oEDM96nl9Xpxx2X8T5VRuQ+4A9CdUh5Y6tdyMWIzQcxvxCUnJvuvjvjc6vsXPOvf0lK9xLaL+QEsT9QGsjRKG8lB0rb96asQcHAkZv9aHNuqNax1VAxfxxbbWZ9byBWbQQoEvjg0NvNVn3ZqivGjbJhFSe243+MozawfBQkcuNYfwy21zoYo/TE/JVsdRjbbXOXyBli/iZBiQIckGPKWpKClguUx41OwTWEjuM4juNUOf744w/17t1brVq1Ups2bfTZZ58VOF+/fv109dVXF2sd48aNU/PmzdWiRYu8Ipo1a9bo1FNPVevWrdWpU6e8x45JrE/4Vxq4ouM4f8IqE9a3A3+d2EVMhN31+OMlSZPee69I6ycStY7L2XYrJ9cm5q+SLbbaxrp2x3JYbh46VFLVU0qqGqcFpZGqP+sbFOu2bqufLEk+OzF/Hc43qqys2zsKBfPZnmDAa6ukMI67Qv9AeqtRtUg1FlWPKF5JKagoip+EasD9Q5WV3c6Y/xIKFEoSzsf4ZlmFBidmW6XGcbM9ylh+p1atMra/MMaNGydJmjZtmiZNmqQrr7xSz5uq0fvvv19z5szRMVn+rvyZ9evX64orrtC7776rbbbZRq1atdLJJ5+sxx9/XM2aNdN1112nUaNG6Z///KfuuuuuIi+/LPAbHcdxHMfJEU477TSddNJJklINnnc1bS+mT5+uGTNmqH///pofkrXXr1+vAQMGaMGCBdqwYYP++c9/qu2fGqXWqVMnz6B23rx5atCgQV7i+NFHH62pU6fqr3/9a96jvK+++irfemN4CwjHqSBQdvBfgf/3178WOD8RJJE2Sk7bZs2yWp/144GY/04StkcVvDNvnqR0ro6ttrLVMUSo4yZNkiTdEqqULO71VD5wXhKhWwdrFIBYzzKwOTa8tjkxTG31j/2+zfHhvEWhtL5FzEd1kXWeRnmyXcFRdl6cPDlje49t3lyS9GToCcZ1iNPwY0HloA8gsF7rK7Vv6N1lHZGtQmSrx4Cqs5gztc3Jsc7dzM92gXUEj7HpppuqZ8+eGjt2bF7/LilVNTl48GCNHTtWTz75ZN77w4cPV+3atTVixAitWLFCbdq00ccff6wTTjhBv/zyi1auXKm2bduqbt26uuiii/IcpaVU3h25UH/5y1907LHHas6cOXot5DEm4cnIjuM4juMUmdGjR+uWW27RkUceqblz52qbbbbRU089peXLl6tz585asmSJ1q5dq0aNGmnOnDmaOnWqZoYmpL///rtWrFiR10y2Tp06mhSCndmzZ+fdkEqpm1OMHiXpjTfe0Pz583XiiSdG84P+jN/oOE4FgyPuf110kSRp8L//LSkdge0VeupYX5NslRwgwi0tYl27wTogW78UIk7mmxeUoIvCfrBcc9llklzRKS++Cj2d6JNnlRnOJ/u+VQxiVUXk9Njzw37fKj2cN2+8+27Ga6rAbK4O75ObQ86M9ZchB8d2YbeKh1VWrK+QVV5tt/NPg09Uw+BAnVRlZpWwCdOnZ4zP5kTFHMdtlVlJ7O3GjBmjb775Rn//+9+19dZba5NNNslbz8CBAzUwVJCOGjVK8+fPV69evbR69Wrtscceuuaaa/TLL7/oxhtvzHs0ZTnggAO0YMECrVy5Uttuu62mTJmiQYMG6V//+pf22GMPnX/++dpmm22ilXsVgd/oOI7jOE6OcPrpp+uCCy5QmzZttH79et1555169tln9fPPP0eb6Pbv3199+/bVMccco9WrV+viiy/OSMgmP0dK3ZTdfvvt6tixozZs2KDevXurbt266t27t3r27KkRI0bojz/+yGtbkoT3unKcSgJVWP8MVQREmnWC/wbKTrbVUfD6O+9ISkeANsfh6VdflSR169gxq+XhRGxzHIgYWzZpIilenUXPLXJ5vv32W0nSwuDo2r9//yy3zCkPHnnkEUnSxaHn0QtvvpnxuVUOrPOx9dfhPCEHg95gVrnhzwbVU6wHRQaFhvXYqiLb84mpdQhGyeE85DWJroy3+wknZGw3ysrxLVpkvM/1ZnvSxfgqdBG3jshsr+1tRa4POXfWAdwqVWAVnVPatcv4PJeckC2PJTgjn+POyI7jOI7jVFU8R8dxKglEVHfccYekdIRH750/VyEUBet8SsRILoF1Wk2CSJscIfw8bA6QzRmwz9Pp4kwk7UpO5eS8886TlPbRsUrAq2+/LSm/YsDU+rbY921Ojs3lsu/b6qoDg9IJOA7b89Gu3z5oQFnie7zGqdvC57bX1TbbbFPg/DHs9tmcHdsLa07oycV1G/MTYrkoVMyP8zXgS+WUDL/RcRzHcRynQnBFx3EqGVdccYUk5Tl+Eol9+eWXxVqe7XYMNsJ9eOxYSVKPLl0KXM7M0P07FimTewMxJef5N96QlO4WndQryKkc9Aq9wvA7QtHg/LGKTqyaKOYAbP1vmJ/lknNiFQt8aPbZeWdJ6Z5SOARz/tscFq4Hzk/8fKgyS1JQyUUDlBbG/dHnn0uSDtlnn0KXY6vYGI9VtshBYn+wPYzbOkZn2/uuOjiM+42O4ziO4zg5S3k4I3vVleOUAByBedb+3//935LSVVolxfp+JDHj448lpR2NLUT8tiqLXCOMwIhg+/btW4xROxXFK6+8IknaOSgo7Q4/XFL6vAAUE+uXgyKx0047SUp3m7dKj3Xe5nyKVWfxOdVJTKlaolqL1+T6oOCgLHJe7h56UjHeIxs3liR9EKoDD23QIGO880OuWaO6dSVJc7/+WlJaoaHHFXxjlEyrgFqfHPYDyhUs/P57SWmlqvGee6ogcHpeunSpJKlbt24FzpeL3JXwW3m5V105juM4jlNV8UdXjlPJwQkYZQes70VxFZ5slZxsIbLE6RiXVCc3IFeMHJ3J778vKZ0bYn1cUGDIJbE+NygoSVVYNnfF9uCyVUgoOnT9RhElxwclxy7X5hSh5ODEjDJEDpD171nwJ+M7KZ0zZLEPOuw4UHRQoHg9+4svMrbD5vbAh6E1AvuD/cByqhN+o+M4juM4Ts7izsiOk2Og7JB7QyRtu5S/NGWKJOnENm2KtPykHB3IZadVR3kdq+uGnBTr5Eu1Ezku+MtQzURuTsxvh+9ZZcfm/jC1ysWKFSskST8E52GuA9aPLw3LJ3eF1ziS215VdEtne5iyPNbTIDgrx8AROaZgoUiR84OiFHOgtlP2E8cD36q2bdsWOq5c5IYEtfs6z9FxHMdxHKeqUh5VV36j4zjlyPAnnshqvqIqObM++URS8jP+2x98sEjLdaomVO2MHz9eUv7qKZQHclhQPFAcyHWxOTxUQ6Fs2NyeWHd0lmuXU7t2bUlp5YXx2Oomlsf7VskBlFGUHdtri+2hGsoqOyg51jncPvhAyQG6qNNji5wkO26UMCA36fswnuqI5+g4juM4jpOz+I2O4+QYfc48s0yXbx2W862/T58yXb9TuViwYIEk6cCQs4Vys9VWW0nKX5WEjxKKBEoE3+O1dUqO9b5ifqsM2RygWNWXBYWIXDS+x/qaNWyYsV3W/8dWby0KuUL1atXKWK/tMcc46wcFiuoqco1QwFh+hyOPlJTulm6rtVj+cUcdJal658yVx43OJuWwDsdxHMdxnArBFR3HKUduHDJEUtrZFb+TMzp1KtFyk5Qcp3py+eWXS5JGjhwpSWoQHIOt4oEiYf11yClBubHnma22srk51n+m6b77Znwfh2JbnWWVFd5nuShPKDq2K3n7I46QlPbTaVKvnqS0j47t9YWyw/qsUoWSQ+8u1s/3re8QWAWM+ag+q85KDngysuM4juM4OYv76DhOjoKTMg6wRNj4m9DbB1+RS3v2LHR5Sf45Hjk6kvTII49Ikvbee29J6VwdlAjbswpFB+WRXB3OV6qnbI6OzY1h+Uxtjy18aVBK+Jz5vw7KD+PdcccdM8ZHzg+fs36rIH0W/HisU7FVZGz1mK0CY5wsf+zEiRnL47pm/9jvfRKqJL2XnHR+go/OmFL47fIcHcdxHMdxcpYq++jqueee0/nnn593hyxJzZo10y+//JL33Pbcc8/V3/72t4oaolOJ2bhxo3r16qUmTZpo0KBB5b5+emQl8USWvjueo+Nkw3nnnScprezstddektJKDVVA8OasWRmvyeEB65Rsq5pQQpja3BgUFOvPg7KEwslvOkpOzZo1M9bLlOoo1vfJ4sWS0t3JGS/YnlxWkaIb+ZcrV2bMh5Iz5YMPJKVzbmyODsvHL+fzzz+X5ErOn/Hy8ggLFizQoEGDMkyc1qxZo88++0zLli3LZ8rkOH9m3rx5uuSSSzRz5kw1adKkoofjOI5Tbcn5ZOS+fftql1120Y033igpFWVcdtllec+P/8wtt9yijh07au3atTrvvPN0++2365xzzsn7/J133tG2226rTp06aenSperQoYNuuummvGe2Tm4yevRo3XDDDfroo49Uo0YNHX744fr73/+u22+/Pd+8nENDhw5Vnz598qLZygyR7My5cyXl74ZsuzmTq/NZ6I588sknl99gnSoDys7o0aMlSfXr15eU7nZ+zGGHSUorHPRkAhQY63xsfXSswgFWObE5MSg6LMf67dhcIbBVTiz3i9BLylZP2Woym7KKgzLzWSdlxmVzcZi/ddOmkqR7wn7u1atXgfujOpPzis4ll1yizp076x//+Ic23XRTPfDAA3r88cfVsWPH6Hf69++v/v3762BjAf7TTz+pXbt2uuuuu7T11lvr3HPP1d///nfdeeedZb0ZTgXSs2dPTZgwQf/1X/+lX3/9Va1bt1aPHj3Uo0eP6HdIBJ4wYUJ5DdNxHMepICr0Rqdp06aqX7++XnrpJTVs2FCLFy/WJptsoqbhLvjP3HLLLfrss8+06aabqnfv3lq0aFHG56eccopOOeWUvNfXXHONTj/9dL/RqQYMGzZMhxxyiLbaaiu99957mjhxYoF5Nyg6VYmYw6uNhJmuDLkEruQ42dAzVPM9GHqg4bMD+NeQm2N7NqGE2Jwc3ud75Nqg1KDM2N5WKCQoIyzH+vQcGsb5Uch5YbmMCyWf5VllB8WFcTG168FpGeaEvzusj+1jPbzu1KqVJOn/hg2TpEIDr+pOzis6UkrVGTlypBo2bKh+/frpuOOO04cffljgvEcccYTWrl2rpk2b6rffftMvv/yipk2bavz48Xrvvfe0ww47qE1ohrhx40bP1akmfP/991q3bp1+/fVXLV68WB06dIieQ47jOE7loVrc6HTr1k1XX321Zs+erXfffbfQed8JfUMkadGiRTrooIPy/qA9//zz+t///V9NnjxZm2++uW6//XadWcZ9hZyKZ/369Tr77LN1ww03aMOGDTrrrLM0bdq0nLnJtYqOrRrhfSJJ/EZatGhRXkN0cgBbBTTqmWckpauJcB5GKbFVTjEfGpQZfHLI9SGnxfbeiuX42N5T78yblzE+5mecVgmyuTdcL9a/h/ns7we5b7anFcvh/eVBMXLfquwpj2TkCvfR2XzzzdWtWze1bNlStUOiWHHo37+/jjnmGB122GFq1KiRtt12W1133XWlOFKnMnLNNddo1113VZ8+fdSvXz/Vrl1b1157bUUPy3Ecx6kkVLgz8po1a9SmTRsNHTpURxkPB8ep7kyePFmStGuo9rB+H7A0OL62bt26HEfn5DrWSRmnbhQZlA9ybHgfpQelA+UEPxk+R4Gxy+N73377rSTpi9AtfN/gX8P3UI5iVVg2h8jm0qxatSpjinLEcqwvj60KY7uWhB5anotTdI5KcEaeUdWdkV999VXtueeeOuGEE/wmx3Ecx3GqGesT/pUGFa7oOI7jOJUblJ16oQs4vaWonkKJQZlhivKBQmOrr2JVUtZJeFnwvdlzzz0lSae1b58xPrqgk9Nju50zTpZvFRnWx/u2ioz3yTGiuvHss88uYG85ReHgBEVndlVXdBzHcRzHccoSV3Qcx3GcrLj33nslSfvss48kaaeddpKU7m6OkmO7iKOI2B5WKDC2VxY5Zz/88EPGfCgzKEt0CScXB4WGHBxydxgfCg2fM2Vctss6yhAKDlWN/fv3L3xHOVnTKEHRmV8KtygVXl7uOI7jOE71pDx8dFzRcRzHqeJs3LhRvXr1UpMmTQp0BT/99NO1++6757U/KS1sF3QUHhQdFBjbk+3AMP8HCxdKSisrK1asyJieeuqpGesbO3aspHSuDt3M8ev58ccfM9bHeMgp4n3riMz3GQc5O4tD9/OuXbtmt0OcIrNXgqLzlefoOI7jVG/mzZun9u3b6+mnny7w81tvvVVTp04t51E51ZENGzZowIABatGihdq2bauF4Ua2ovFHV47jOJWEoUOH5vWdkqS5c+eqWbNm+bqHS+nebUOHDlWfPn3yVJU/M2nSJL3yyisaMGBAXr5LaUIXdHjyySclSbvttpuktOJifWlmB18ccmHYvqQxorTgQGwVI3J1UJTIyYnl3pDTg8My6//mm28kSZdeemmh43Eyee6557Ru3TpNnz5dM2bM0FVXXaXnn3++0O9UixYQjuM4TopLLrlEl1xyiSTpvvvu04gRIzRx4sQ8g7yC4HHUhAkTMt5fvHixLr/8cr3yyiu6//77y27QjhN466231KlTJ0nSUUcdpVmzZiV+pzxaQPiNjuM4TiVj7Nixuu222zRt2jRNnz69wLwbFJ2CoAfcHXfckaeulAfdu3fPeD18+HBJUq1atSSlq5+osiJHBmdhuqnHsArSc889JymtHKHg2B5bttcWyk2263WyY/Xq1Xnu2VLqePz+++95Sl5BrCiHNGG/0XEcx6lETJs2TZdccokmTpyoOnXqqE6dOnnNi7Nl1qxZ+vzzz3XllVdKSv1B/+OPP7Ru3bq8mw/HKW223377vAapUupRYmE3OeVFxY/AcRzHkZRKLD7jjDP02GOPqXHjxsVeTosWLfI8XyRp8ODBWr58ealXXSXRp0+fMl3+aaedlvEanx9ygmyV1UUXXVSm46nutGrVSuPGjVP37t01Y8YMNWnSpKKHJMlvdBzHcSoNf/3rX/Xbb79p0KBBeY9fDj/8cFdhnCpBly5d9Nprr6lly5bauHGjHnrooYoekiT30XEcx3EcJ4dxHx3HcRzHcXIWv9FxHMdxHCdn8Rsdx3Ecx3FyFr/RcRzHcRwnZ/EbHcdxHMdxcha/0XEcx3EcJ2fxGx3HcRzHcXIWv9FxHMdxHCdn8Rsdx3Ecx3FyFr/RcRzHcRwnZ/EbHcdxHMdxcha/0XEcx3EcJ2fxGx3HcRzHcXIWv9FxHMdxHCdn8Rsdx3Ecx3FyFr/RcRzHcRwnZ/EbHcdxHMdxcha/0XEcx3EcJ2fxGx3HcRzHcXIWv9FxHMdxHCdn8Rsdx3Ecx3FyFr/RcRzHcRwnZ/EbHcdxHMdxcha/0XEcx3EcJ2fxGx3HcRzHcXIWv9FxHMdxHCdn8Rsdx3Ecx3FyFr/RcRzHcRwnZ/n/AXAUQoyhsu5MAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 525.6x187.2 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for c in contrasts:\n",
    "    nlplt.plot_stat_map(c, draw_cross=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Network analyses"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also do connectome-style network analyses. We need only pass the function a nifti we the rois. Due to the nature of fsl's fiber tracking algorithm, the resulting matrix will not be symmetrical. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4min 21s ± 1.99 s per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"
     ]
    }
   ],
   "source": [
    "%timeit network = matrix.network(atlas_filename)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [],
   "source": [
    "network = matrix.network(atlas_filename)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [],
   "source": [
    "normalize = np.array([network[i,:]/network[i,:].sum() for i in range(48)])\n",
    "normalized_network = pd.DataFrame(normalize, columns=labels, index=labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Frontal Pole</th>\n",
       "      <th>Insular Cortex</th>\n",
       "      <th>Superior Frontal Gyrus</th>\n",
       "      <th>Middle Frontal Gyrus</th>\n",
       "      <th>Inferior Frontal Gyrus, pars triangularis</th>\n",
       "      <th>Inferior Frontal Gyrus, pars opercularis</th>\n",
       "      <th>Precentral Gyrus</th>\n",
       "      <th>Temporal Pole</th>\n",
       "      <th>Superior Temporal Gyrus, anterior division</th>\n",
       "      <th>Superior Temporal Gyrus, posterior division</th>\n",
       "      <th>...</th>\n",
       "      <th>Temporal Occipital Fusiform Cortex</th>\n",
       "      <th>Occipital Fusiform Gyrus</th>\n",
       "      <th>Frontal Operculum Cortex</th>\n",
       "      <th>Central Opercular Cortex</th>\n",
       "      <th>Parietal Operculum Cortex</th>\n",
       "      <th>Planum Polare</th>\n",
       "      <th>Heschl's Gyrus (includes H1 and H2)</th>\n",
       "      <th>Planum Temporale</th>\n",
       "      <th>Supracalcarine Cortex</th>\n",
       "      <th>Occipital Pole</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Frontal Pole</th>\n",
       "      <td>0.540239</td>\n",
       "      <td>0.019950</td>\n",
       "      <td>0.026134</td>\n",
       "      <td>0.028089</td>\n",
       "      <td>0.010125</td>\n",
       "      <td>0.002167</td>\n",
       "      <td>0.015107</td>\n",
       "      <td>0.011673</td>\n",
       "      <td>0.001744</td>\n",
       "      <td>0.004643</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000709</td>\n",
       "      <td>0.003573</td>\n",
       "      <td>0.000174</td>\n",
       "      <td>0.000368</td>\n",
       "      <td>0.000443</td>\n",
       "      <td>0.003270</td>\n",
       "      <td>0.000389</td>\n",
       "      <td>0.004162</td>\n",
       "      <td>0.000488</td>\n",
       "      <td>0.045025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Insular Cortex</th>\n",
       "      <td>0.109646</td>\n",
       "      <td>0.187923</td>\n",
       "      <td>0.011673</td>\n",
       "      <td>0.015390</td>\n",
       "      <td>0.036769</td>\n",
       "      <td>0.011738</td>\n",
       "      <td>0.024770</td>\n",
       "      <td>0.044633</td>\n",
       "      <td>0.005530</td>\n",
       "      <td>0.018754</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000895</td>\n",
       "      <td>0.003754</td>\n",
       "      <td>0.011431</td>\n",
       "      <td>0.021130</td>\n",
       "      <td>0.008273</td>\n",
       "      <td>0.028629</td>\n",
       "      <td>0.010420</td>\n",
       "      <td>0.028026</td>\n",
       "      <td>0.000302</td>\n",
       "      <td>0.064000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Superior Frontal Gyrus</th>\n",
       "      <td>0.295785</td>\n",
       "      <td>0.015469</td>\n",
       "      <td>0.223198</td>\n",
       "      <td>0.089334</td>\n",
       "      <td>0.007477</td>\n",
       "      <td>0.037778</td>\n",
       "      <td>0.083915</td>\n",
       "      <td>0.002670</td>\n",
       "      <td>0.000950</td>\n",
       "      <td>0.002537</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000121</td>\n",
       "      <td>0.000216</td>\n",
       "      <td>0.000535</td>\n",
       "      <td>0.000834</td>\n",
       "      <td>0.000114</td>\n",
       "      <td>0.001279</td>\n",
       "      <td>0.000387</td>\n",
       "      <td>0.001929</td>\n",
       "      <td>0.000035</td>\n",
       "      <td>0.002559</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Middle Frontal Gyrus</th>\n",
       "      <td>0.128695</td>\n",
       "      <td>0.018168</td>\n",
       "      <td>0.099739</td>\n",
       "      <td>0.275543</td>\n",
       "      <td>0.017009</td>\n",
       "      <td>0.114954</td>\n",
       "      <td>0.140938</td>\n",
       "      <td>0.006266</td>\n",
       "      <td>0.002234</td>\n",
       "      <td>0.003518</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000192</td>\n",
       "      <td>0.000181</td>\n",
       "      <td>0.000636</td>\n",
       "      <td>0.001173</td>\n",
       "      <td>0.000162</td>\n",
       "      <td>0.002343</td>\n",
       "      <td>0.000731</td>\n",
       "      <td>0.002721</td>\n",
       "      <td>0.000014</td>\n",
       "      <td>0.003883</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Inferior Frontal Gyrus, pars triangularis</th>\n",
       "      <td>0.194912</td>\n",
       "      <td>0.113719</td>\n",
       "      <td>0.040843</td>\n",
       "      <td>0.077811</td>\n",
       "      <td>0.105305</td>\n",
       "      <td>0.041478</td>\n",
       "      <td>0.047984</td>\n",
       "      <td>0.007134</td>\n",
       "      <td>0.002611</td>\n",
       "      <td>0.017712</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000696</td>\n",
       "      <td>0.000884</td>\n",
       "      <td>0.003387</td>\n",
       "      <td>0.002615</td>\n",
       "      <td>0.001650</td>\n",
       "      <td>0.014933</td>\n",
       "      <td>0.001186</td>\n",
       "      <td>0.011893</td>\n",
       "      <td>0.000156</td>\n",
       "      <td>0.035948</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Inferior Frontal Gyrus, pars opercularis</th>\n",
       "      <td>0.050800</td>\n",
       "      <td>0.017595</td>\n",
       "      <td>0.134124</td>\n",
       "      <td>0.165971</td>\n",
       "      <td>0.023328</td>\n",
       "      <td>0.094144</td>\n",
       "      <td>0.233014</td>\n",
       "      <td>0.004759</td>\n",
       "      <td>0.004113</td>\n",
       "      <td>0.007919</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000190</td>\n",
       "      <td>0.000208</td>\n",
       "      <td>0.000904</td>\n",
       "      <td>0.002707</td>\n",
       "      <td>0.000496</td>\n",
       "      <td>0.003074</td>\n",
       "      <td>0.001406</td>\n",
       "      <td>0.006857</td>\n",
       "      <td>0.000020</td>\n",
       "      <td>0.007066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Precentral Gyrus</th>\n",
       "      <td>0.050616</td>\n",
       "      <td>0.020256</td>\n",
       "      <td>0.049989</td>\n",
       "      <td>0.062907</td>\n",
       "      <td>0.006678</td>\n",
       "      <td>0.027692</td>\n",
       "      <td>0.382989</td>\n",
       "      <td>0.003017</td>\n",
       "      <td>0.001202</td>\n",
       "      <td>0.004197</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000198</td>\n",
       "      <td>0.000345</td>\n",
       "      <td>0.000189</td>\n",
       "      <td>0.001925</td>\n",
       "      <td>0.000345</td>\n",
       "      <td>0.001350</td>\n",
       "      <td>0.000514</td>\n",
       "      <td>0.005688</td>\n",
       "      <td>0.000020</td>\n",
       "      <td>0.002513</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Temporal Pole</th>\n",
       "      <td>0.150723</td>\n",
       "      <td>0.137411</td>\n",
       "      <td>0.006563</td>\n",
       "      <td>0.008690</td>\n",
       "      <td>0.005989</td>\n",
       "      <td>0.004359</td>\n",
       "      <td>0.008111</td>\n",
       "      <td>0.108294</td>\n",
       "      <td>0.015335</td>\n",
       "      <td>0.015173</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001413</td>\n",
       "      <td>0.011402</td>\n",
       "      <td>0.001207</td>\n",
       "      <td>0.001766</td>\n",
       "      <td>0.001098</td>\n",
       "      <td>0.031483</td>\n",
       "      <td>0.002168</td>\n",
       "      <td>0.007347</td>\n",
       "      <td>0.000764</td>\n",
       "      <td>0.102068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Superior Temporal Gyrus, anterior division</th>\n",
       "      <td>0.076895</td>\n",
       "      <td>0.033631</td>\n",
       "      <td>0.013948</td>\n",
       "      <td>0.013862</td>\n",
       "      <td>0.007616</td>\n",
       "      <td>0.017554</td>\n",
       "      <td>0.012021</td>\n",
       "      <td>0.089945</td>\n",
       "      <td>0.048243</td>\n",
       "      <td>0.068463</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001847</td>\n",
       "      <td>0.001114</td>\n",
       "      <td>0.000971</td>\n",
       "      <td>0.003418</td>\n",
       "      <td>0.000848</td>\n",
       "      <td>0.023738</td>\n",
       "      <td>0.005917</td>\n",
       "      <td>0.017928</td>\n",
       "      <td>0.000068</td>\n",
       "      <td>0.144851</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Superior Temporal Gyrus, posterior division</th>\n",
       "      <td>0.097634</td>\n",
       "      <td>0.029395</td>\n",
       "      <td>0.008004</td>\n",
       "      <td>0.018248</td>\n",
       "      <td>0.041010</td>\n",
       "      <td>0.045095</td>\n",
       "      <td>0.037562</td>\n",
       "      <td>0.024196</td>\n",
       "      <td>0.024571</td>\n",
       "      <td>0.134062</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000773</td>\n",
       "      <td>0.000426</td>\n",
       "      <td>0.000605</td>\n",
       "      <td>0.001991</td>\n",
       "      <td>0.001641</td>\n",
       "      <td>0.004867</td>\n",
       "      <td>0.002281</td>\n",
       "      <td>0.023731</td>\n",
       "      <td>0.000036</td>\n",
       "      <td>0.043859</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Middle Temporal Gyrus, anterior division</th>\n",
       "      <td>0.057504</td>\n",
       "      <td>0.018949</td>\n",
       "      <td>0.002760</td>\n",
       "      <td>0.007748</td>\n",
       "      <td>0.003286</td>\n",
       "      <td>0.005651</td>\n",
       "      <td>0.007839</td>\n",
       "      <td>0.164734</td>\n",
       "      <td>0.050097</td>\n",
       "      <td>0.028632</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001401</td>\n",
       "      <td>0.005660</td>\n",
       "      <td>0.000179</td>\n",
       "      <td>0.000335</td>\n",
       "      <td>0.000174</td>\n",
       "      <td>0.014653</td>\n",
       "      <td>0.000455</td>\n",
       "      <td>0.004468</td>\n",
       "      <td>0.000613</td>\n",
       "      <td>0.145214</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Middle Temporal Gyrus, posterior division</th>\n",
       "      <td>0.099819</td>\n",
       "      <td>0.029883</td>\n",
       "      <td>0.005376</td>\n",
       "      <td>0.023195</td>\n",
       "      <td>0.025251</td>\n",
       "      <td>0.028848</td>\n",
       "      <td>0.031646</td>\n",
       "      <td>0.032324</td>\n",
       "      <td>0.008513</td>\n",
       "      <td>0.054321</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001189</td>\n",
       "      <td>0.003010</td>\n",
       "      <td>0.000321</td>\n",
       "      <td>0.000766</td>\n",
       "      <td>0.000535</td>\n",
       "      <td>0.005309</td>\n",
       "      <td>0.001489</td>\n",
       "      <td>0.006380</td>\n",
       "      <td>0.000445</td>\n",
       "      <td>0.076183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Middle Temporal Gyrus, temporooccipital part</th>\n",
       "      <td>0.105871</td>\n",
       "      <td>0.018839</td>\n",
       "      <td>0.006497</td>\n",
       "      <td>0.068535</td>\n",
       "      <td>0.015436</td>\n",
       "      <td>0.038707</td>\n",
       "      <td>0.071111</td>\n",
       "      <td>0.009774</td>\n",
       "      <td>0.002196</td>\n",
       "      <td>0.031569</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001004</td>\n",
       "      <td>0.001221</td>\n",
       "      <td>0.000137</td>\n",
       "      <td>0.000830</td>\n",
       "      <td>0.000522</td>\n",
       "      <td>0.003106</td>\n",
       "      <td>0.001844</td>\n",
       "      <td>0.006207</td>\n",
       "      <td>0.000473</td>\n",
       "      <td>0.043433</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Inferior Temporal Gyrus, anterior division</th>\n",
       "      <td>0.053041</td>\n",
       "      <td>0.017158</td>\n",
       "      <td>0.005072</td>\n",
       "      <td>0.010971</td>\n",
       "      <td>0.001210</td>\n",
       "      <td>0.002934</td>\n",
       "      <td>0.005794</td>\n",
       "      <td>0.298528</td>\n",
       "      <td>0.000366</td>\n",
       "      <td>0.002366</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000940</td>\n",
       "      <td>0.012360</td>\n",
       "      <td>0.000134</td>\n",
       "      <td>0.000143</td>\n",
       "      <td>0.000080</td>\n",
       "      <td>0.003722</td>\n",
       "      <td>0.000184</td>\n",
       "      <td>0.000846</td>\n",
       "      <td>0.000595</td>\n",
       "      <td>0.083353</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Inferior Temporal Gyrus, posterior division</th>\n",
       "      <td>0.045407</td>\n",
       "      <td>0.012744</td>\n",
       "      <td>0.002626</td>\n",
       "      <td>0.014872</td>\n",
       "      <td>0.001310</td>\n",
       "      <td>0.003115</td>\n",
       "      <td>0.008663</td>\n",
       "      <td>0.021457</td>\n",
       "      <td>0.000448</td>\n",
       "      <td>0.001829</td>\n",
       "      <td>...</td>\n",
       "      <td>0.036813</td>\n",
       "      <td>0.023305</td>\n",
       "      <td>0.000059</td>\n",
       "      <td>0.000190</td>\n",
       "      <td>0.000070</td>\n",
       "      <td>0.001797</td>\n",
       "      <td>0.000455</td>\n",
       "      <td>0.001333</td>\n",
       "      <td>0.000692</td>\n",
       "      <td>0.043847</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Inferior Temporal Gyrus, temporooccipital part</th>\n",
       "      <td>0.036927</td>\n",
       "      <td>0.010592</td>\n",
       "      <td>0.001816</td>\n",
       "      <td>0.003687</td>\n",
       "      <td>0.000692</td>\n",
       "      <td>0.000641</td>\n",
       "      <td>0.003172</td>\n",
       "      <td>0.013141</td>\n",
       "      <td>0.000545</td>\n",
       "      <td>0.001499</td>\n",
       "      <td>...</td>\n",
       "      <td>0.075928</td>\n",
       "      <td>0.044187</td>\n",
       "      <td>0.000043</td>\n",
       "      <td>0.000455</td>\n",
       "      <td>0.000098</td>\n",
       "      <td>0.001559</td>\n",
       "      <td>0.001130</td>\n",
       "      <td>0.001796</td>\n",
       "      <td>0.001349</td>\n",
       "      <td>0.040242</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Postcentral Gyrus</th>\n",
       "      <td>0.109426</td>\n",
       "      <td>0.056657</td>\n",
       "      <td>0.010456</td>\n",
       "      <td>0.025741</td>\n",
       "      <td>0.012482</td>\n",
       "      <td>0.010580</td>\n",
       "      <td>0.166839</td>\n",
       "      <td>0.006011</td>\n",
       "      <td>0.001551</td>\n",
       "      <td>0.005156</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000318</td>\n",
       "      <td>0.000657</td>\n",
       "      <td>0.000539</td>\n",
       "      <td>0.004484</td>\n",
       "      <td>0.002527</td>\n",
       "      <td>0.002952</td>\n",
       "      <td>0.002385</td>\n",
       "      <td>0.014898</td>\n",
       "      <td>0.000027</td>\n",
       "      <td>0.002602</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Superior Parietal Lobule</th>\n",
       "      <td>0.149167</td>\n",
       "      <td>0.029937</td>\n",
       "      <td>0.014923</td>\n",
       "      <td>0.044053</td>\n",
       "      <td>0.013513</td>\n",
       "      <td>0.016890</td>\n",
       "      <td>0.103239</td>\n",
       "      <td>0.004010</td>\n",
       "      <td>0.001237</td>\n",
       "      <td>0.010910</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000464</td>\n",
       "      <td>0.000779</td>\n",
       "      <td>0.000194</td>\n",
       "      <td>0.001390</td>\n",
       "      <td>0.001924</td>\n",
       "      <td>0.001790</td>\n",
       "      <td>0.002010</td>\n",
       "      <td>0.014510</td>\n",
       "      <td>0.000015</td>\n",
       "      <td>0.002209</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Supramarginal Gyrus, anterior division</th>\n",
       "      <td>0.093558</td>\n",
       "      <td>0.069604</td>\n",
       "      <td>0.006675</td>\n",
       "      <td>0.017646</td>\n",
       "      <td>0.018780</td>\n",
       "      <td>0.012841</td>\n",
       "      <td>0.059234</td>\n",
       "      <td>0.007064</td>\n",
       "      <td>0.002752</td>\n",
       "      <td>0.016675</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000204</td>\n",
       "      <td>0.000246</td>\n",
       "      <td>0.000959</td>\n",
       "      <td>0.005892</td>\n",
       "      <td>0.005972</td>\n",
       "      <td>0.004518</td>\n",
       "      <td>0.003240</td>\n",
       "      <td>0.029199</td>\n",
       "      <td>0.000023</td>\n",
       "      <td>0.002855</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Supramarginal Gyrus, posterior division</th>\n",
       "      <td>0.068577</td>\n",
       "      <td>0.019949</td>\n",
       "      <td>0.006522</td>\n",
       "      <td>0.035329</td>\n",
       "      <td>0.015965</td>\n",
       "      <td>0.031392</td>\n",
       "      <td>0.077380</td>\n",
       "      <td>0.004968</td>\n",
       "      <td>0.003636</td>\n",
       "      <td>0.037859</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000240</td>\n",
       "      <td>0.000221</td>\n",
       "      <td>0.000359</td>\n",
       "      <td>0.003590</td>\n",
       "      <td>0.002512</td>\n",
       "      <td>0.002371</td>\n",
       "      <td>0.002890</td>\n",
       "      <td>0.025294</td>\n",
       "      <td>0.000015</td>\n",
       "      <td>0.004407</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Angular Gyrus</th>\n",
       "      <td>0.057095</td>\n",
       "      <td>0.009729</td>\n",
       "      <td>0.005491</td>\n",
       "      <td>0.075454</td>\n",
       "      <td>0.007930</td>\n",
       "      <td>0.031741</td>\n",
       "      <td>0.099001</td>\n",
       "      <td>0.003447</td>\n",
       "      <td>0.002757</td>\n",
       "      <td>0.033950</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000173</td>\n",
       "      <td>0.000140</td>\n",
       "      <td>0.000109</td>\n",
       "      <td>0.001397</td>\n",
       "      <td>0.000456</td>\n",
       "      <td>0.001464</td>\n",
       "      <td>0.001493</td>\n",
       "      <td>0.009932</td>\n",
       "      <td>0.000009</td>\n",
       "      <td>0.004125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lateral Occipital Cortex, superior division</th>\n",
       "      <td>0.114433</td>\n",
       "      <td>0.036296</td>\n",
       "      <td>0.010011</td>\n",
       "      <td>0.032523</td>\n",
       "      <td>0.004985</td>\n",
       "      <td>0.005368</td>\n",
       "      <td>0.024582</td>\n",
       "      <td>0.018812</td>\n",
       "      <td>0.004950</td>\n",
       "      <td>0.014830</td>\n",
       "      <td>...</td>\n",
       "      <td>0.003926</td>\n",
       "      <td>0.001035</td>\n",
       "      <td>0.000222</td>\n",
       "      <td>0.002214</td>\n",
       "      <td>0.000524</td>\n",
       "      <td>0.005924</td>\n",
       "      <td>0.005081</td>\n",
       "      <td>0.012053</td>\n",
       "      <td>0.000121</td>\n",
       "      <td>0.041263</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lateral Occipital Cortex, inferior division</th>\n",
       "      <td>0.120507</td>\n",
       "      <td>0.034494</td>\n",
       "      <td>0.004032</td>\n",
       "      <td>0.026592</td>\n",
       "      <td>0.002731</td>\n",
       "      <td>0.004371</td>\n",
       "      <td>0.019180</td>\n",
       "      <td>0.020172</td>\n",
       "      <td>0.002417</td>\n",
       "      <td>0.005778</td>\n",
       "      <td>...</td>\n",
       "      <td>0.026395</td>\n",
       "      <td>0.015601</td>\n",
       "      <td>0.000162</td>\n",
       "      <td>0.000737</td>\n",
       "      <td>0.000179</td>\n",
       "      <td>0.006773</td>\n",
       "      <td>0.001856</td>\n",
       "      <td>0.003408</td>\n",
       "      <td>0.000132</td>\n",
       "      <td>0.083214</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Intracalcarine Cortex</th>\n",
       "      <td>0.145072</td>\n",
       "      <td>0.048827</td>\n",
       "      <td>0.011201</td>\n",
       "      <td>0.001293</td>\n",
       "      <td>0.000563</td>\n",
       "      <td>0.000305</td>\n",
       "      <td>0.001504</td>\n",
       "      <td>0.030367</td>\n",
       "      <td>0.000498</td>\n",
       "      <td>0.001136</td>\n",
       "      <td>...</td>\n",
       "      <td>0.003930</td>\n",
       "      <td>0.007642</td>\n",
       "      <td>0.000047</td>\n",
       "      <td>0.000078</td>\n",
       "      <td>0.000030</td>\n",
       "      <td>0.002762</td>\n",
       "      <td>0.000191</td>\n",
       "      <td>0.000546</td>\n",
       "      <td>0.007499</td>\n",
       "      <td>0.043894</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Frontal Medial Cortex</th>\n",
       "      <td>0.343558</td>\n",
       "      <td>0.004911</td>\n",
       "      <td>0.003640</td>\n",
       "      <td>0.001743</td>\n",
       "      <td>0.000392</td>\n",
       "      <td>0.000526</td>\n",
       "      <td>0.004143</td>\n",
       "      <td>0.017611</td>\n",
       "      <td>0.000456</td>\n",
       "      <td>0.001596</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000923</td>\n",
       "      <td>0.004842</td>\n",
       "      <td>0.000019</td>\n",
       "      <td>0.000065</td>\n",
       "      <td>0.000055</td>\n",
       "      <td>0.001091</td>\n",
       "      <td>0.000067</td>\n",
       "      <td>0.000728</td>\n",
       "      <td>0.000200</td>\n",
       "      <td>0.065386</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Juxtapositional Lobule Cortex (formerly Supplementary Motor Cortex)</th>\n",
       "      <td>0.024197</td>\n",
       "      <td>0.013420</td>\n",
       "      <td>0.171463</td>\n",
       "      <td>0.035391</td>\n",
       "      <td>0.001642</td>\n",
       "      <td>0.005476</td>\n",
       "      <td>0.257948</td>\n",
       "      <td>0.002019</td>\n",
       "      <td>0.000526</td>\n",
       "      <td>0.003259</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000120</td>\n",
       "      <td>0.000172</td>\n",
       "      <td>0.000095</td>\n",
       "      <td>0.000376</td>\n",
       "      <td>0.000076</td>\n",
       "      <td>0.000756</td>\n",
       "      <td>0.000438</td>\n",
       "      <td>0.002165</td>\n",
       "      <td>0.000047</td>\n",
       "      <td>0.001909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Subcallosal Cortex</th>\n",
       "      <td>0.228569</td>\n",
       "      <td>0.003646</td>\n",
       "      <td>0.030094</td>\n",
       "      <td>0.004775</td>\n",
       "      <td>0.000890</td>\n",
       "      <td>0.000827</td>\n",
       "      <td>0.003440</td>\n",
       "      <td>0.005607</td>\n",
       "      <td>0.000877</td>\n",
       "      <td>0.002630</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000531</td>\n",
       "      <td>0.001610</td>\n",
       "      <td>0.000062</td>\n",
       "      <td>0.000111</td>\n",
       "      <td>0.000034</td>\n",
       "      <td>0.000977</td>\n",
       "      <td>0.000249</td>\n",
       "      <td>0.000854</td>\n",
       "      <td>0.000323</td>\n",
       "      <td>0.042563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Paracingulate Gyrus</th>\n",
       "      <td>0.150409</td>\n",
       "      <td>0.001881</td>\n",
       "      <td>0.106218</td>\n",
       "      <td>0.017146</td>\n",
       "      <td>0.001157</td>\n",
       "      <td>0.003734</td>\n",
       "      <td>0.006333</td>\n",
       "      <td>0.001230</td>\n",
       "      <td>0.000223</td>\n",
       "      <td>0.000527</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000241</td>\n",
       "      <td>0.000910</td>\n",
       "      <td>0.000078</td>\n",
       "      <td>0.000132</td>\n",
       "      <td>0.000044</td>\n",
       "      <td>0.000259</td>\n",
       "      <td>0.000087</td>\n",
       "      <td>0.000359</td>\n",
       "      <td>0.000263</td>\n",
       "      <td>0.004916</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cingulate Gyrus, anterior division</th>\n",
       "      <td>0.183420</td>\n",
       "      <td>0.002418</td>\n",
       "      <td>0.086391</td>\n",
       "      <td>0.010847</td>\n",
       "      <td>0.001385</td>\n",
       "      <td>0.003195</td>\n",
       "      <td>0.019741</td>\n",
       "      <td>0.001031</td>\n",
       "      <td>0.000198</td>\n",
       "      <td>0.000647</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000157</td>\n",
       "      <td>0.000463</td>\n",
       "      <td>0.000079</td>\n",
       "      <td>0.000129</td>\n",
       "      <td>0.000055</td>\n",
       "      <td>0.000285</td>\n",
       "      <td>0.000095</td>\n",
       "      <td>0.000440</td>\n",
       "      <td>0.000444</td>\n",
       "      <td>0.003589</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cingulate Gyrus, posterior division</th>\n",
       "      <td>0.067821</td>\n",
       "      <td>0.005424</td>\n",
       "      <td>0.021018</td>\n",
       "      <td>0.003451</td>\n",
       "      <td>0.000830</td>\n",
       "      <td>0.000826</td>\n",
       "      <td>0.010483</td>\n",
       "      <td>0.004600</td>\n",
       "      <td>0.000421</td>\n",
       "      <td>0.001999</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000367</td>\n",
       "      <td>0.000639</td>\n",
       "      <td>0.000050</td>\n",
       "      <td>0.000220</td>\n",
       "      <td>0.000149</td>\n",
       "      <td>0.000716</td>\n",
       "      <td>0.000587</td>\n",
       "      <td>0.001857</td>\n",
       "      <td>0.000928</td>\n",
       "      <td>0.004638</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Precuneous Cortex</th>\n",
       "      <td>0.074117</td>\n",
       "      <td>0.015208</td>\n",
       "      <td>0.024496</td>\n",
       "      <td>0.005994</td>\n",
       "      <td>0.002784</td>\n",
       "      <td>0.001812</td>\n",
       "      <td>0.018886</td>\n",
       "      <td>0.012654</td>\n",
       "      <td>0.001665</td>\n",
       "      <td>0.009238</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001016</td>\n",
       "      <td>0.000976</td>\n",
       "      <td>0.000114</td>\n",
       "      <td>0.000715</td>\n",
       "      <td>0.001133</td>\n",
       "      <td>0.002516</td>\n",
       "      <td>0.001763</td>\n",
       "      <td>0.008652</td>\n",
       "      <td>0.002258</td>\n",
       "      <td>0.016512</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cuneal Cortex</th>\n",
       "      <td>0.141544</td>\n",
       "      <td>0.033753</td>\n",
       "      <td>0.011012</td>\n",
       "      <td>0.002722</td>\n",
       "      <td>0.000917</td>\n",
       "      <td>0.000517</td>\n",
       "      <td>0.002447</td>\n",
       "      <td>0.028372</td>\n",
       "      <td>0.001275</td>\n",
       "      <td>0.003239</td>\n",
       "      <td>...</td>\n",
       "      <td>0.003866</td>\n",
       "      <td>0.004883</td>\n",
       "      <td>0.000084</td>\n",
       "      <td>0.000292</td>\n",
       "      <td>0.000079</td>\n",
       "      <td>0.003995</td>\n",
       "      <td>0.000974</td>\n",
       "      <td>0.002019</td>\n",
       "      <td>0.007322</td>\n",
       "      <td>0.075233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Frontal Orbital Cortex</th>\n",
       "      <td>0.294702</td>\n",
       "      <td>0.097608</td>\n",
       "      <td>0.004548</td>\n",
       "      <td>0.004841</td>\n",
       "      <td>0.005013</td>\n",
       "      <td>0.002164</td>\n",
       "      <td>0.008243</td>\n",
       "      <td>0.063998</td>\n",
       "      <td>0.006753</td>\n",
       "      <td>0.007212</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001131</td>\n",
       "      <td>0.008510</td>\n",
       "      <td>0.001726</td>\n",
       "      <td>0.000958</td>\n",
       "      <td>0.000445</td>\n",
       "      <td>0.024050</td>\n",
       "      <td>0.000797</td>\n",
       "      <td>0.003388</td>\n",
       "      <td>0.000662</td>\n",
       "      <td>0.088306</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Parahippocampal Gyrus, anterior division</th>\n",
       "      <td>0.135213</td>\n",
       "      <td>0.011001</td>\n",
       "      <td>0.039613</td>\n",
       "      <td>0.007037</td>\n",
       "      <td>0.000985</td>\n",
       "      <td>0.001233</td>\n",
       "      <td>0.018175</td>\n",
       "      <td>0.034655</td>\n",
       "      <td>0.000571</td>\n",
       "      <td>0.001677</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001414</td>\n",
       "      <td>0.003488</td>\n",
       "      <td>0.000095</td>\n",
       "      <td>0.000228</td>\n",
       "      <td>0.000084</td>\n",
       "      <td>0.001126</td>\n",
       "      <td>0.000323</td>\n",
       "      <td>0.001064</td>\n",
       "      <td>0.000475</td>\n",
       "      <td>0.043790</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Parahippocampal Gyrus, posterior division</th>\n",
       "      <td>0.029328</td>\n",
       "      <td>0.006356</td>\n",
       "      <td>0.018320</td>\n",
       "      <td>0.002038</td>\n",
       "      <td>0.000594</td>\n",
       "      <td>0.000695</td>\n",
       "      <td>0.006840</td>\n",
       "      <td>0.080778</td>\n",
       "      <td>0.000417</td>\n",
       "      <td>0.001539</td>\n",
       "      <td>...</td>\n",
       "      <td>0.012787</td>\n",
       "      <td>0.015122</td>\n",
       "      <td>0.000083</td>\n",
       "      <td>0.000634</td>\n",
       "      <td>0.000074</td>\n",
       "      <td>0.000736</td>\n",
       "      <td>0.000389</td>\n",
       "      <td>0.001190</td>\n",
       "      <td>0.001010</td>\n",
       "      <td>0.025329</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lingual Gyrus</th>\n",
       "      <td>0.095418</td>\n",
       "      <td>0.050321</td>\n",
       "      <td>0.001849</td>\n",
       "      <td>0.000302</td>\n",
       "      <td>0.000441</td>\n",
       "      <td>0.000072</td>\n",
       "      <td>0.000946</td>\n",
       "      <td>0.026447</td>\n",
       "      <td>0.000239</td>\n",
       "      <td>0.000252</td>\n",
       "      <td>...</td>\n",
       "      <td>0.069370</td>\n",
       "      <td>0.074173</td>\n",
       "      <td>0.000032</td>\n",
       "      <td>0.000018</td>\n",
       "      <td>0.000007</td>\n",
       "      <td>0.002685</td>\n",
       "      <td>0.000037</td>\n",
       "      <td>0.000115</td>\n",
       "      <td>0.006158</td>\n",
       "      <td>0.029514</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Temporal Fusiform Cortex, anterior division</th>\n",
       "      <td>0.155943</td>\n",
       "      <td>0.024626</td>\n",
       "      <td>0.014844</td>\n",
       "      <td>0.010545</td>\n",
       "      <td>0.001054</td>\n",
       "      <td>0.001019</td>\n",
       "      <td>0.003927</td>\n",
       "      <td>0.037730</td>\n",
       "      <td>0.000627</td>\n",
       "      <td>0.001722</td>\n",
       "      <td>...</td>\n",
       "      <td>0.013994</td>\n",
       "      <td>0.026072</td>\n",
       "      <td>0.000135</td>\n",
       "      <td>0.000231</td>\n",
       "      <td>0.000085</td>\n",
       "      <td>0.002032</td>\n",
       "      <td>0.000504</td>\n",
       "      <td>0.001275</td>\n",
       "      <td>0.001197</td>\n",
       "      <td>0.057990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Temporal Fusiform Cortex, posterior division</th>\n",
       "      <td>0.029407</td>\n",
       "      <td>0.004403</td>\n",
       "      <td>0.004353</td>\n",
       "      <td>0.001813</td>\n",
       "      <td>0.000326</td>\n",
       "      <td>0.000378</td>\n",
       "      <td>0.001551</td>\n",
       "      <td>0.063171</td>\n",
       "      <td>0.000339</td>\n",
       "      <td>0.000687</td>\n",
       "      <td>...</td>\n",
       "      <td>0.075545</td>\n",
       "      <td>0.070511</td>\n",
       "      <td>0.000022</td>\n",
       "      <td>0.000113</td>\n",
       "      <td>0.000025</td>\n",
       "      <td>0.000548</td>\n",
       "      <td>0.000294</td>\n",
       "      <td>0.000865</td>\n",
       "      <td>0.000750</td>\n",
       "      <td>0.025571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Temporal Occipital Fusiform Cortex</th>\n",
       "      <td>0.010044</td>\n",
       "      <td>0.003351</td>\n",
       "      <td>0.000733</td>\n",
       "      <td>0.000318</td>\n",
       "      <td>0.000097</td>\n",
       "      <td>0.000092</td>\n",
       "      <td>0.001501</td>\n",
       "      <td>0.009143</td>\n",
       "      <td>0.000104</td>\n",
       "      <td>0.000197</td>\n",
       "      <td>...</td>\n",
       "      <td>0.179561</td>\n",
       "      <td>0.190387</td>\n",
       "      <td>0.000007</td>\n",
       "      <td>0.000034</td>\n",
       "      <td>0.000005</td>\n",
       "      <td>0.000280</td>\n",
       "      <td>0.000086</td>\n",
       "      <td>0.000188</td>\n",
       "      <td>0.000378</td>\n",
       "      <td>0.009349</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Occipital Fusiform Gyrus</th>\n",
       "      <td>0.104130</td>\n",
       "      <td>0.057010</td>\n",
       "      <td>0.000983</td>\n",
       "      <td>0.000482</td>\n",
       "      <td>0.000631</td>\n",
       "      <td>0.000099</td>\n",
       "      <td>0.001886</td>\n",
       "      <td>0.029274</td>\n",
       "      <td>0.000336</td>\n",
       "      <td>0.000337</td>\n",
       "      <td>...</td>\n",
       "      <td>0.118732</td>\n",
       "      <td>0.192245</td>\n",
       "      <td>0.000053</td>\n",
       "      <td>0.000017</td>\n",
       "      <td>0.000007</td>\n",
       "      <td>0.005377</td>\n",
       "      <td>0.000027</td>\n",
       "      <td>0.000062</td>\n",
       "      <td>0.000939</td>\n",
       "      <td>0.017713</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Frontal Operculum Cortex</th>\n",
       "      <td>0.084373</td>\n",
       "      <td>0.290546</td>\n",
       "      <td>0.035878</td>\n",
       "      <td>0.032956</td>\n",
       "      <td>0.054446</td>\n",
       "      <td>0.018728</td>\n",
       "      <td>0.020933</td>\n",
       "      <td>0.020364</td>\n",
       "      <td>0.006518</td>\n",
       "      <td>0.018208</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000617</td>\n",
       "      <td>0.001231</td>\n",
       "      <td>0.072283</td>\n",
       "      <td>0.028706</td>\n",
       "      <td>0.004127</td>\n",
       "      <td>0.027955</td>\n",
       "      <td>0.003540</td>\n",
       "      <td>0.024076</td>\n",
       "      <td>0.000181</td>\n",
       "      <td>0.038022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Central Opercular Cortex</th>\n",
       "      <td>0.065639</td>\n",
       "      <td>0.189820</td>\n",
       "      <td>0.015526</td>\n",
       "      <td>0.014213</td>\n",
       "      <td>0.019855</td>\n",
       "      <td>0.020650</td>\n",
       "      <td>0.037215</td>\n",
       "      <td>0.016329</td>\n",
       "      <td>0.007465</td>\n",
       "      <td>0.015022</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000720</td>\n",
       "      <td>0.000395</td>\n",
       "      <td>0.011661</td>\n",
       "      <td>0.096859</td>\n",
       "      <td>0.022890</td>\n",
       "      <td>0.018910</td>\n",
       "      <td>0.032331</td>\n",
       "      <td>0.064287</td>\n",
       "      <td>0.000040</td>\n",
       "      <td>0.011761</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Parietal Operculum Cortex</th>\n",
       "      <td>0.085382</td>\n",
       "      <td>0.185773</td>\n",
       "      <td>0.006012</td>\n",
       "      <td>0.007389</td>\n",
       "      <td>0.032238</td>\n",
       "      <td>0.018510</td>\n",
       "      <td>0.023908</td>\n",
       "      <td>0.014025</td>\n",
       "      <td>0.004987</td>\n",
       "      <td>0.020154</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000211</td>\n",
       "      <td>0.000250</td>\n",
       "      <td>0.004927</td>\n",
       "      <td>0.049979</td>\n",
       "      <td>0.076883</td>\n",
       "      <td>0.012786</td>\n",
       "      <td>0.043193</td>\n",
       "      <td>0.109177</td>\n",
       "      <td>0.000024</td>\n",
       "      <td>0.003973</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Planum Polare</th>\n",
       "      <td>0.095812</td>\n",
       "      <td>0.159756</td>\n",
       "      <td>0.008544</td>\n",
       "      <td>0.008400</td>\n",
       "      <td>0.016761</td>\n",
       "      <td>0.009873</td>\n",
       "      <td>0.012713</td>\n",
       "      <td>0.051043</td>\n",
       "      <td>0.012925</td>\n",
       "      <td>0.018465</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001748</td>\n",
       "      <td>0.001615</td>\n",
       "      <td>0.005503</td>\n",
       "      <td>0.009588</td>\n",
       "      <td>0.004983</td>\n",
       "      <td>0.039733</td>\n",
       "      <td>0.011796</td>\n",
       "      <td>0.027306</td>\n",
       "      <td>0.000132</td>\n",
       "      <td>0.103114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Heschl's Gyrus (includes H1 and H2)</th>\n",
       "      <td>0.066996</td>\n",
       "      <td>0.138735</td>\n",
       "      <td>0.006979</td>\n",
       "      <td>0.006566</td>\n",
       "      <td>0.012663</td>\n",
       "      <td>0.013575</td>\n",
       "      <td>0.016179</td>\n",
       "      <td>0.014306</td>\n",
       "      <td>0.006536</td>\n",
       "      <td>0.013457</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000734</td>\n",
       "      <td>0.000318</td>\n",
       "      <td>0.003175</td>\n",
       "      <td>0.063332</td>\n",
       "      <td>0.055714</td>\n",
       "      <td>0.015340</td>\n",
       "      <td>0.085388</td>\n",
       "      <td>0.069378</td>\n",
       "      <td>0.000026</td>\n",
       "      <td>0.007853</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Planum Temporale</th>\n",
       "      <td>0.091228</td>\n",
       "      <td>0.084514</td>\n",
       "      <td>0.011224</td>\n",
       "      <td>0.010783</td>\n",
       "      <td>0.030493</td>\n",
       "      <td>0.026985</td>\n",
       "      <td>0.030841</td>\n",
       "      <td>0.011721</td>\n",
       "      <td>0.007032</td>\n",
       "      <td>0.032117</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001051</td>\n",
       "      <td>0.000426</td>\n",
       "      <td>0.002729</td>\n",
       "      <td>0.019686</td>\n",
       "      <td>0.026142</td>\n",
       "      <td>0.008433</td>\n",
       "      <td>0.015165</td>\n",
       "      <td>0.122353</td>\n",
       "      <td>0.000029</td>\n",
       "      <td>0.010495</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Supracalcarine Cortex</th>\n",
       "      <td>0.127015</td>\n",
       "      <td>0.049678</td>\n",
       "      <td>0.006060</td>\n",
       "      <td>0.000924</td>\n",
       "      <td>0.000677</td>\n",
       "      <td>0.000196</td>\n",
       "      <td>0.001346</td>\n",
       "      <td>0.023012</td>\n",
       "      <td>0.000393</td>\n",
       "      <td>0.000920</td>\n",
       "      <td>...</td>\n",
       "      <td>0.002796</td>\n",
       "      <td>0.007269</td>\n",
       "      <td>0.000045</td>\n",
       "      <td>0.000093</td>\n",
       "      <td>0.000018</td>\n",
       "      <td>0.002357</td>\n",
       "      <td>0.000317</td>\n",
       "      <td>0.000518</td>\n",
       "      <td>0.018860</td>\n",
       "      <td>0.059660</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Occipital Pole</th>\n",
       "      <td>0.241510</td>\n",
       "      <td>0.088527</td>\n",
       "      <td>0.002870</td>\n",
       "      <td>0.002178</td>\n",
       "      <td>0.005087</td>\n",
       "      <td>0.000784</td>\n",
       "      <td>0.001025</td>\n",
       "      <td>0.025983</td>\n",
       "      <td>0.011597</td>\n",
       "      <td>0.015969</td>\n",
       "      <td>...</td>\n",
       "      <td>0.002595</td>\n",
       "      <td>0.006161</td>\n",
       "      <td>0.000419</td>\n",
       "      <td>0.000145</td>\n",
       "      <td>0.000025</td>\n",
       "      <td>0.015674</td>\n",
       "      <td>0.000181</td>\n",
       "      <td>0.000933</td>\n",
       "      <td>0.000696</td>\n",
       "      <td>0.187266</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>48 rows × 48 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    Frontal Pole  \\\n",
       "Frontal Pole                                            0.540239   \n",
       "Insular Cortex                                          0.109646   \n",
       "Superior Frontal Gyrus                                  0.295785   \n",
       "Middle Frontal Gyrus                                    0.128695   \n",
       "Inferior Frontal Gyrus, pars triangularis               0.194912   \n",
       "Inferior Frontal Gyrus, pars opercularis                0.050800   \n",
       "Precentral Gyrus                                        0.050616   \n",
       "Temporal Pole                                           0.150723   \n",
       "Superior Temporal Gyrus, anterior division              0.076895   \n",
       "Superior Temporal Gyrus, posterior division             0.097634   \n",
       "Middle Temporal Gyrus, anterior division                0.057504   \n",
       "Middle Temporal Gyrus, posterior division               0.099819   \n",
       "Middle Temporal Gyrus, temporooccipital part            0.105871   \n",
       "Inferior Temporal Gyrus, anterior division              0.053041   \n",
       "Inferior Temporal Gyrus, posterior division             0.045407   \n",
       "Inferior Temporal Gyrus, temporooccipital part          0.036927   \n",
       "Postcentral Gyrus                                       0.109426   \n",
       "Superior Parietal Lobule                                0.149167   \n",
       "Supramarginal Gyrus, anterior division                  0.093558   \n",
       "Supramarginal Gyrus, posterior division                 0.068577   \n",
       "Angular Gyrus                                           0.057095   \n",
       "Lateral Occipital Cortex, superior division             0.114433   \n",
       "Lateral Occipital Cortex, inferior division             0.120507   \n",
       "Intracalcarine Cortex                                   0.145072   \n",
       "Frontal Medial Cortex                                   0.343558   \n",
       "Juxtapositional Lobule Cortex (formerly Supplem...      0.024197   \n",
       "Subcallosal Cortex                                      0.228569   \n",
       "Paracingulate Gyrus                                     0.150409   \n",
       "Cingulate Gyrus, anterior division                      0.183420   \n",
       "Cingulate Gyrus, posterior division                     0.067821   \n",
       "Precuneous Cortex                                       0.074117   \n",
       "Cuneal Cortex                                           0.141544   \n",
       "Frontal Orbital Cortex                                  0.294702   \n",
       "Parahippocampal Gyrus, anterior division                0.135213   \n",
       "Parahippocampal Gyrus, posterior division               0.029328   \n",
       "Lingual Gyrus                                           0.095418   \n",
       "Temporal Fusiform Cortex, anterior division             0.155943   \n",
       "Temporal Fusiform Cortex, posterior division            0.029407   \n",
       "Temporal Occipital Fusiform Cortex                      0.010044   \n",
       "Occipital Fusiform Gyrus                                0.104130   \n",
       "Frontal Operculum Cortex                                0.084373   \n",
       "Central Opercular Cortex                                0.065639   \n",
       "Parietal Operculum Cortex                               0.085382   \n",
       "Planum Polare                                           0.095812   \n",
       "Heschl's Gyrus (includes H1 and H2)                     0.066996   \n",
       "Planum Temporale                                        0.091228   \n",
       "Supracalcarine Cortex                                   0.127015   \n",
       "Occipital Pole                                          0.241510   \n",
       "\n",
       "                                                    Insular Cortex  \\\n",
       "Frontal Pole                                              0.019950   \n",
       "Insular Cortex                                            0.187923   \n",
       "Superior Frontal Gyrus                                    0.015469   \n",
       "Middle Frontal Gyrus                                      0.018168   \n",
       "Inferior Frontal Gyrus, pars triangularis                 0.113719   \n",
       "Inferior Frontal Gyrus, pars opercularis                  0.017595   \n",
       "Precentral Gyrus                                          0.020256   \n",
       "Temporal Pole                                             0.137411   \n",
       "Superior Temporal Gyrus, anterior division                0.033631   \n",
       "Superior Temporal Gyrus, posterior division               0.029395   \n",
       "Middle Temporal Gyrus, anterior division                  0.018949   \n",
       "Middle Temporal Gyrus, posterior division                 0.029883   \n",
       "Middle Temporal Gyrus, temporooccipital part              0.018839   \n",
       "Inferior Temporal Gyrus, anterior division                0.017158   \n",
       "Inferior Temporal Gyrus, posterior division               0.012744   \n",
       "Inferior Temporal Gyrus, temporooccipital part            0.010592   \n",
       "Postcentral Gyrus                                         0.056657   \n",
       "Superior Parietal Lobule                                  0.029937   \n",
       "Supramarginal Gyrus, anterior division                    0.069604   \n",
       "Supramarginal Gyrus, posterior division                   0.019949   \n",
       "Angular Gyrus                                             0.009729   \n",
       "Lateral Occipital Cortex, superior division               0.036296   \n",
       "Lateral Occipital Cortex, inferior division               0.034494   \n",
       "Intracalcarine Cortex                                     0.048827   \n",
       "Frontal Medial Cortex                                     0.004911   \n",
       "Juxtapositional Lobule Cortex (formerly Supplem...        0.013420   \n",
       "Subcallosal Cortex                                        0.003646   \n",
       "Paracingulate Gyrus                                       0.001881   \n",
       "Cingulate Gyrus, anterior division                        0.002418   \n",
       "Cingulate Gyrus, posterior division                       0.005424   \n",
       "Precuneous Cortex                                         0.015208   \n",
       "Cuneal Cortex                                             0.033753   \n",
       "Frontal Orbital Cortex                                    0.097608   \n",
       "Parahippocampal Gyrus, anterior division                  0.011001   \n",
       "Parahippocampal Gyrus, posterior division                 0.006356   \n",
       "Lingual Gyrus                                             0.050321   \n",
       "Temporal Fusiform Cortex, anterior division               0.024626   \n",
       "Temporal Fusiform Cortex, posterior division              0.004403   \n",
       "Temporal Occipital Fusiform Cortex                        0.003351   \n",
       "Occipital Fusiform Gyrus                                  0.057010   \n",
       "Frontal Operculum Cortex                                  0.290546   \n",
       "Central Opercular Cortex                                  0.189820   \n",
       "Parietal Operculum Cortex                                 0.185773   \n",
       "Planum Polare                                             0.159756   \n",
       "Heschl's Gyrus (includes H1 and H2)                       0.138735   \n",
       "Planum Temporale                                          0.084514   \n",
       "Supracalcarine Cortex                                     0.049678   \n",
       "Occipital Pole                                            0.088527   \n",
       "\n",
       "                                                    Superior Frontal Gyrus  \\\n",
       "Frontal Pole                                                      0.026134   \n",
       "Insular Cortex                                                    0.011673   \n",
       "Superior Frontal Gyrus                                            0.223198   \n",
       "Middle Frontal Gyrus                                              0.099739   \n",
       "Inferior Frontal Gyrus, pars triangularis                         0.040843   \n",
       "Inferior Frontal Gyrus, pars opercularis                          0.134124   \n",
       "Precentral Gyrus                                                  0.049989   \n",
       "Temporal Pole                                                     0.006563   \n",
       "Superior Temporal Gyrus, anterior division                        0.013948   \n",
       "Superior Temporal Gyrus, posterior division                       0.008004   \n",
       "Middle Temporal Gyrus, anterior division                          0.002760   \n",
       "Middle Temporal Gyrus, posterior division                         0.005376   \n",
       "Middle Temporal Gyrus, temporooccipital part                      0.006497   \n",
       "Inferior Temporal Gyrus, anterior division                        0.005072   \n",
       "Inferior Temporal Gyrus, posterior division                       0.002626   \n",
       "Inferior Temporal Gyrus, temporooccipital part                    0.001816   \n",
       "Postcentral Gyrus                                                 0.010456   \n",
       "Superior Parietal Lobule                                          0.014923   \n",
       "Supramarginal Gyrus, anterior division                            0.006675   \n",
       "Supramarginal Gyrus, posterior division                           0.006522   \n",
       "Angular Gyrus                                                     0.005491   \n",
       "Lateral Occipital Cortex, superior division                       0.010011   \n",
       "Lateral Occipital Cortex, inferior division                       0.004032   \n",
       "Intracalcarine Cortex                                             0.011201   \n",
       "Frontal Medial Cortex                                             0.003640   \n",
       "Juxtapositional Lobule Cortex (formerly Supplem...                0.171463   \n",
       "Subcallosal Cortex                                                0.030094   \n",
       "Paracingulate Gyrus                                               0.106218   \n",
       "Cingulate Gyrus, anterior division                                0.086391   \n",
       "Cingulate Gyrus, posterior division                               0.021018   \n",
       "Precuneous Cortex                                                 0.024496   \n",
       "Cuneal Cortex                                                     0.011012   \n",
       "Frontal Orbital Cortex                                            0.004548   \n",
       "Parahippocampal Gyrus, anterior division                          0.039613   \n",
       "Parahippocampal Gyrus, posterior division                         0.018320   \n",
       "Lingual Gyrus                                                     0.001849   \n",
       "Temporal Fusiform Cortex, anterior division                       0.014844   \n",
       "Temporal Fusiform Cortex, posterior division                      0.004353   \n",
       "Temporal Occipital Fusiform Cortex                                0.000733   \n",
       "Occipital Fusiform Gyrus                                          0.000983   \n",
       "Frontal Operculum Cortex                                          0.035878   \n",
       "Central Opercular Cortex                                          0.015526   \n",
       "Parietal Operculum Cortex                                         0.006012   \n",
       "Planum Polare                                                     0.008544   \n",
       "Heschl's Gyrus (includes H1 and H2)                               0.006979   \n",
       "Planum Temporale                                                  0.011224   \n",
       "Supracalcarine Cortex                                             0.006060   \n",
       "Occipital Pole                                                    0.002870   \n",
       "\n",
       "                                                    Middle Frontal Gyrus  \\\n",
       "Frontal Pole                                                    0.028089   \n",
       "Insular Cortex                                                  0.015390   \n",
       "Superior Frontal Gyrus                                          0.089334   \n",
       "Middle Frontal Gyrus                                            0.275543   \n",
       "Inferior Frontal Gyrus, pars triangularis                       0.077811   \n",
       "Inferior Frontal Gyrus, pars opercularis                        0.165971   \n",
       "Precentral Gyrus                                                0.062907   \n",
       "Temporal Pole                                                   0.008690   \n",
       "Superior Temporal Gyrus, anterior division                      0.013862   \n",
       "Superior Temporal Gyrus, posterior division                     0.018248   \n",
       "Middle Temporal Gyrus, anterior division                        0.007748   \n",
       "Middle Temporal Gyrus, posterior division                       0.023195   \n",
       "Middle Temporal Gyrus, temporooccipital part                    0.068535   \n",
       "Inferior Temporal Gyrus, anterior division                      0.010971   \n",
       "Inferior Temporal Gyrus, posterior division                     0.014872   \n",
       "Inferior Temporal Gyrus, temporooccipital part                  0.003687   \n",
       "Postcentral Gyrus                                               0.025741   \n",
       "Superior Parietal Lobule                                        0.044053   \n",
       "Supramarginal Gyrus, anterior division                          0.017646   \n",
       "Supramarginal Gyrus, posterior division                         0.035329   \n",
       "Angular Gyrus                                                   0.075454   \n",
       "Lateral Occipital Cortex, superior division                     0.032523   \n",
       "Lateral Occipital Cortex, inferior division                     0.026592   \n",
       "Intracalcarine Cortex                                           0.001293   \n",
       "Frontal Medial Cortex                                           0.001743   \n",
       "Juxtapositional Lobule Cortex (formerly Supplem...              0.035391   \n",
       "Subcallosal Cortex                                              0.004775   \n",
       "Paracingulate Gyrus                                             0.017146   \n",
       "Cingulate Gyrus, anterior division                              0.010847   \n",
       "Cingulate Gyrus, posterior division                             0.003451   \n",
       "Precuneous Cortex                                               0.005994   \n",
       "Cuneal Cortex                                                   0.002722   \n",
       "Frontal Orbital Cortex                                          0.004841   \n",
       "Parahippocampal Gyrus, anterior division                        0.007037   \n",
       "Parahippocampal Gyrus, posterior division                       0.002038   \n",
       "Lingual Gyrus                                                   0.000302   \n",
       "Temporal Fusiform Cortex, anterior division                     0.010545   \n",
       "Temporal Fusiform Cortex, posterior division                    0.001813   \n",
       "Temporal Occipital Fusiform Cortex                              0.000318   \n",
       "Occipital Fusiform Gyrus                                        0.000482   \n",
       "Frontal Operculum Cortex                                        0.032956   \n",
       "Central Opercular Cortex                                        0.014213   \n",
       "Parietal Operculum Cortex                                       0.007389   \n",
       "Planum Polare                                                   0.008400   \n",
       "Heschl's Gyrus (includes H1 and H2)                             0.006566   \n",
       "Planum Temporale                                                0.010783   \n",
       "Supracalcarine Cortex                                           0.000924   \n",
       "Occipital Pole                                                  0.002178   \n",
       "\n",
       "                                                    Inferior Frontal Gyrus, pars triangularis  \\\n",
       "Frontal Pole                                                                         0.010125   \n",
       "Insular Cortex                                                                       0.036769   \n",
       "Superior Frontal Gyrus                                                               0.007477   \n",
       "Middle Frontal Gyrus                                                                 0.017009   \n",
       "Inferior Frontal Gyrus, pars triangularis                                            0.105305   \n",
       "Inferior Frontal Gyrus, pars opercularis                                             0.023328   \n",
       "Precentral Gyrus                                                                     0.006678   \n",
       "Temporal Pole                                                                        0.005989   \n",
       "Superior Temporal Gyrus, anterior division                                           0.007616   \n",
       "Superior Temporal Gyrus, posterior division                                          0.041010   \n",
       "Middle Temporal Gyrus, anterior division                                             0.003286   \n",
       "Middle Temporal Gyrus, posterior division                                            0.025251   \n",
       "Middle Temporal Gyrus, temporooccipital part                                         0.015436   \n",
       "Inferior Temporal Gyrus, anterior division                                           0.001210   \n",
       "Inferior Temporal Gyrus, posterior division                                          0.001310   \n",
       "Inferior Temporal Gyrus, temporooccipital part                                       0.000692   \n",
       "Postcentral Gyrus                                                                    0.012482   \n",
       "Superior Parietal Lobule                                                             0.013513   \n",
       "Supramarginal Gyrus, anterior division                                               0.018780   \n",
       "Supramarginal Gyrus, posterior division                                              0.015965   \n",
       "Angular Gyrus                                                                        0.007930   \n",
       "Lateral Occipital Cortex, superior division                                          0.004985   \n",
       "Lateral Occipital Cortex, inferior division                                          0.002731   \n",
       "Intracalcarine Cortex                                                                0.000563   \n",
       "Frontal Medial Cortex                                                                0.000392   \n",
       "Juxtapositional Lobule Cortex (formerly Supplem...                                   0.001642   \n",
       "Subcallosal Cortex                                                                   0.000890   \n",
       "Paracingulate Gyrus                                                                  0.001157   \n",
       "Cingulate Gyrus, anterior division                                                   0.001385   \n",
       "Cingulate Gyrus, posterior division                                                  0.000830   \n",
       "Precuneous Cortex                                                                    0.002784   \n",
       "Cuneal Cortex                                                                        0.000917   \n",
       "Frontal Orbital Cortex                                                               0.005013   \n",
       "Parahippocampal Gyrus, anterior division                                             0.000985   \n",
       "Parahippocampal Gyrus, posterior division                                            0.000594   \n",
       "Lingual Gyrus                                                                        0.000441   \n",
       "Temporal Fusiform Cortex, anterior division                                          0.001054   \n",
       "Temporal Fusiform Cortex, posterior division                                         0.000326   \n",
       "Temporal Occipital Fusiform Cortex                                                   0.000097   \n",
       "Occipital Fusiform Gyrus                                                             0.000631   \n",
       "Frontal Operculum Cortex                                                             0.054446   \n",
       "Central Opercular Cortex                                                             0.019855   \n",
       "Parietal Operculum Cortex                                                            0.032238   \n",
       "Planum Polare                                                                        0.016761   \n",
       "Heschl's Gyrus (includes H1 and H2)                                                  0.012663   \n",
       "Planum Temporale                                                                     0.030493   \n",
       "Supracalcarine Cortex                                                                0.000677   \n",
       "Occipital Pole                                                                       0.005087   \n",
       "\n",
       "                                                    Inferior Frontal Gyrus, pars opercularis  \\\n",
       "Frontal Pole                                                                        0.002167   \n",
       "Insular Cortex                                                                      0.011738   \n",
       "Superior Frontal Gyrus                                                              0.037778   \n",
       "Middle Frontal Gyrus                                                                0.114954   \n",
       "Inferior Frontal Gyrus, pars triangularis                                           0.041478   \n",
       "Inferior Frontal Gyrus, pars opercularis                                            0.094144   \n",
       "Precentral Gyrus                                                                    0.027692   \n",
       "Temporal Pole                                                                       0.004359   \n",
       "Superior Temporal Gyrus, anterior division                                          0.017554   \n",
       "Superior Temporal Gyrus, posterior division                                         0.045095   \n",
       "Middle Temporal Gyrus, anterior division                                            0.005651   \n",
       "Middle Temporal Gyrus, posterior division                                           0.028848   \n",
       "Middle Temporal Gyrus, temporooccipital part                                        0.038707   \n",
       "Inferior Temporal Gyrus, anterior division                                          0.002934   \n",
       "Inferior Temporal Gyrus, posterior division                                         0.003115   \n",
       "Inferior Temporal Gyrus, temporooccipital part                                      0.000641   \n",
       "Postcentral Gyrus                                                                   0.010580   \n",
       "Superior Parietal Lobule                                                            0.016890   \n",
       "Supramarginal Gyrus, anterior division                                              0.012841   \n",
       "Supramarginal Gyrus, posterior division                                             0.031392   \n",
       "Angular Gyrus                                                                       0.031741   \n",
       "Lateral Occipital Cortex, superior division                                         0.005368   \n",
       "Lateral Occipital Cortex, inferior division                                         0.004371   \n",
       "Intracalcarine Cortex                                                               0.000305   \n",
       "Frontal Medial Cortex                                                               0.000526   \n",
       "Juxtapositional Lobule Cortex (formerly Supplem...                                  0.005476   \n",
       "Subcallosal Cortex                                                                  0.000827   \n",
       "Paracingulate Gyrus                                                                 0.003734   \n",
       "Cingulate Gyrus, anterior division                                                  0.003195   \n",
       "Cingulate Gyrus, posterior division                                                 0.000826   \n",
       "Precuneous Cortex                                                                   0.001812   \n",
       "Cuneal Cortex                                                                       0.000517   \n",
       "Frontal Orbital Cortex                                                              0.002164   \n",
       "Parahippocampal Gyrus, anterior division                                            0.001233   \n",
       "Parahippocampal Gyrus, posterior division                                           0.000695   \n",
       "Lingual Gyrus                                                                       0.000072   \n",
       "Temporal Fusiform Cortex, anterior division                                         0.001019   \n",
       "Temporal Fusiform Cortex, posterior division                                        0.000378   \n",
       "Temporal Occipital Fusiform Cortex                                                  0.000092   \n",
       "Occipital Fusiform Gyrus                                                            0.000099   \n",
       "Frontal Operculum Cortex                                                            0.018728   \n",
       "Central Opercular Cortex                                                            0.020650   \n",
       "Parietal Operculum Cortex                                                           0.018510   \n",
       "Planum Polare                                                                       0.009873   \n",
       "Heschl's Gyrus (includes H1 and H2)                                                 0.013575   \n",
       "Planum Temporale                                                                    0.026985   \n",
       "Supracalcarine Cortex                                                               0.000196   \n",
       "Occipital Pole                                                                      0.000784   \n",
       "\n",
       "                                                    Precentral Gyrus  \\\n",
       "Frontal Pole                                                0.015107   \n",
       "Insular Cortex                                              0.024770   \n",
       "Superior Frontal Gyrus                                      0.083915   \n",
       "Middle Frontal Gyrus                                        0.140938   \n",
       "Inferior Frontal Gyrus, pars triangularis                   0.047984   \n",
       "Inferior Frontal Gyrus, pars opercularis                    0.233014   \n",
       "Precentral Gyrus                                            0.382989   \n",
       "Temporal Pole                                               0.008111   \n",
       "Superior Temporal Gyrus, anterior division                  0.012021   \n",
       "Superior Temporal Gyrus, posterior division                 0.037562   \n",
       "Middle Temporal Gyrus, anterior division                    0.007839   \n",
       "Middle Temporal Gyrus, posterior division                   0.031646   \n",
       "Middle Temporal Gyrus, temporooccipital part                0.071111   \n",
       "Inferior Temporal Gyrus, anterior division                  0.005794   \n",
       "Inferior Temporal Gyrus, posterior division                 0.008663   \n",
       "Inferior Temporal Gyrus, temporooccipital part              0.003172   \n",
       "Postcentral Gyrus                                           0.166839   \n",
       "Superior Parietal Lobule                                    0.103239   \n",
       "Supramarginal Gyrus, anterior division                      0.059234   \n",
       "Supramarginal Gyrus, posterior division                     0.077380   \n",
       "Angular Gyrus                                               0.099001   \n",
       "Lateral Occipital Cortex, superior division                 0.024582   \n",
       "Lateral Occipital Cortex, inferior division                 0.019180   \n",
       "Intracalcarine Cortex                                       0.001504   \n",
       "Frontal Medial Cortex                                       0.004143   \n",
       "Juxtapositional Lobule Cortex (formerly Supplem...          0.257948   \n",
       "Subcallosal Cortex                                          0.003440   \n",
       "Paracingulate Gyrus                                         0.006333   \n",
       "Cingulate Gyrus, anterior division                          0.019741   \n",
       "Cingulate Gyrus, posterior division                         0.010483   \n",
       "Precuneous Cortex                                           0.018886   \n",
       "Cuneal Cortex                                               0.002447   \n",
       "Frontal Orbital Cortex                                      0.008243   \n",
       "Parahippocampal Gyrus, anterior division                    0.018175   \n",
       "Parahippocampal Gyrus, posterior division                   0.006840   \n",
       "Lingual Gyrus                                               0.000946   \n",
       "Temporal Fusiform Cortex, anterior division                 0.003927   \n",
       "Temporal Fusiform Cortex, posterior division                0.001551   \n",
       "Temporal Occipital Fusiform Cortex                          0.001501   \n",
       "Occipital Fusiform Gyrus                                    0.001886   \n",
       "Frontal Operculum Cortex                                    0.020933   \n",
       "Central Opercular Cortex                                    0.037215   \n",
       "Parietal Operculum Cortex                                   0.023908   \n",
       "Planum Polare                                               0.012713   \n",
       "Heschl's Gyrus (includes H1 and H2)                         0.016179   \n",
       "Planum Temporale                                            0.030841   \n",
       "Supracalcarine Cortex                                       0.001346   \n",
       "Occipital Pole                                              0.001025   \n",
       "\n",
       "                                                    Temporal Pole  \\\n",
       "Frontal Pole                                             0.011673   \n",
       "Insular Cortex                                           0.044633   \n",
       "Superior Frontal Gyrus                                   0.002670   \n",
       "Middle Frontal Gyrus                                     0.006266   \n",
       "Inferior Frontal Gyrus, pars triangularis                0.007134   \n",
       "Inferior Frontal Gyrus, pars opercularis                 0.004759   \n",
       "Precentral Gyrus                                         0.003017   \n",
       "Temporal Pole                                            0.108294   \n",
       "Superior Temporal Gyrus, anterior division               0.089945   \n",
       "Superior Temporal Gyrus, posterior division              0.024196   \n",
       "Middle Temporal Gyrus, anterior division                 0.164734   \n",
       "Middle Temporal Gyrus, posterior division                0.032324   \n",
       "Middle Temporal Gyrus, temporooccipital part             0.009774   \n",
       "Inferior Temporal Gyrus, anterior division               0.298528   \n",
       "Inferior Temporal Gyrus, posterior division              0.021457   \n",
       "Inferior Temporal Gyrus, temporooccipital part           0.013141   \n",
       "Postcentral Gyrus                                        0.006011   \n",
       "Superior Parietal Lobule                                 0.004010   \n",
       "Supramarginal Gyrus, anterior division                   0.007064   \n",
       "Supramarginal Gyrus, posterior division                  0.004968   \n",
       "Angular Gyrus                                            0.003447   \n",
       "Lateral Occipital Cortex, superior division              0.018812   \n",
       "Lateral Occipital Cortex, inferior division              0.020172   \n",
       "Intracalcarine Cortex                                    0.030367   \n",
       "Frontal Medial Cortex                                    0.017611   \n",
       "Juxtapositional Lobule Cortex (formerly Supplem...       0.002019   \n",
       "Subcallosal Cortex                                       0.005607   \n",
       "Paracingulate Gyrus                                      0.001230   \n",
       "Cingulate Gyrus, anterior division                       0.001031   \n",
       "Cingulate Gyrus, posterior division                      0.004600   \n",
       "Precuneous Cortex                                        0.012654   \n",
       "Cuneal Cortex                                            0.028372   \n",
       "Frontal Orbital Cortex                                   0.063998   \n",
       "Parahippocampal Gyrus, anterior division                 0.034655   \n",
       "Parahippocampal Gyrus, posterior division                0.080778   \n",
       "Lingual Gyrus                                            0.026447   \n",
       "Temporal Fusiform Cortex, anterior division              0.037730   \n",
       "Temporal Fusiform Cortex, posterior division             0.063171   \n",
       "Temporal Occipital Fusiform Cortex                       0.009143   \n",
       "Occipital Fusiform Gyrus                                 0.029274   \n",
       "Frontal Operculum Cortex                                 0.020364   \n",
       "Central Opercular Cortex                                 0.016329   \n",
       "Parietal Operculum Cortex                                0.014025   \n",
       "Planum Polare                                            0.051043   \n",
       "Heschl's Gyrus (includes H1 and H2)                      0.014306   \n",
       "Planum Temporale                                         0.011721   \n",
       "Supracalcarine Cortex                                    0.023012   \n",
       "Occipital Pole                                           0.025983   \n",
       "\n",
       "                                                    Superior Temporal Gyrus, anterior division  \\\n",
       "Frontal Pole                                                                          0.001744   \n",
       "Insular Cortex                                                                        0.005530   \n",
       "Superior Frontal Gyrus                                                                0.000950   \n",
       "Middle Frontal Gyrus                                                                  0.002234   \n",
       "Inferior Frontal Gyrus, pars triangularis                                             0.002611   \n",
       "Inferior Frontal Gyrus, pars opercularis                                              0.004113   \n",
       "Precentral Gyrus                                                                      0.001202   \n",
       "Temporal Pole                                                                         0.015335   \n",
       "Superior Temporal Gyrus, anterior division                                            0.048243   \n",
       "Superior Temporal Gyrus, posterior division                                           0.024571   \n",
       "Middle Temporal Gyrus, anterior division                                              0.050097   \n",
       "Middle Temporal Gyrus, posterior division                                             0.008513   \n",
       "Middle Temporal Gyrus, temporooccipital part                                          0.002196   \n",
       "Inferior Temporal Gyrus, anterior division                                            0.000366   \n",
       "Inferior Temporal Gyrus, posterior division                                           0.000448   \n",
       "Inferior Temporal Gyrus, temporooccipital part                                        0.000545   \n",
       "Postcentral Gyrus                                                                     0.001551   \n",
       "Superior Parietal Lobule                                                              0.001237   \n",
       "Supramarginal Gyrus, anterior division                                                0.002752   \n",
       "Supramarginal Gyrus, posterior division                                               0.003636   \n",
       "Angular Gyrus                                                                         0.002757   \n",
       "Lateral Occipital Cortex, superior division                                           0.004950   \n",
       "Lateral Occipital Cortex, inferior division                                           0.002417   \n",
       "Intracalcarine Cortex                                                                 0.000498   \n",
       "Frontal Medial Cortex                                                                 0.000456   \n",
       "Juxtapositional Lobule Cortex (formerly Supplem...                                    0.000526   \n",
       "Subcallosal Cortex                                                                    0.000877   \n",
       "Paracingulate Gyrus                                                                   0.000223   \n",
       "Cingulate Gyrus, anterior division                                                    0.000198   \n",
       "Cingulate Gyrus, posterior division                                                   0.000421   \n",
       "Precuneous Cortex                                                                     0.001665   \n",
       "Cuneal Cortex                                                                         0.001275   \n",
       "Frontal Orbital Cortex                                                                0.006753   \n",
       "Parahippocampal Gyrus, anterior division                                              0.000571   \n",
       "Parahippocampal Gyrus, posterior division                                             0.000417   \n",
       "Lingual Gyrus                                                                         0.000239   \n",
       "Temporal Fusiform Cortex, anterior division                                           0.000627   \n",
       "Temporal Fusiform Cortex, posterior division                                          0.000339   \n",
       "Temporal Occipital Fusiform Cortex                                                    0.000104   \n",
       "Occipital Fusiform Gyrus                                                              0.000336   \n",
       "Frontal Operculum Cortex                                                              0.006518   \n",
       "Central Opercular Cortex                                                              0.007465   \n",
       "Parietal Operculum Cortex                                                             0.004987   \n",
       "Planum Polare                                                                         0.012925   \n",
       "Heschl's Gyrus (includes H1 and H2)                                                   0.006536   \n",
       "Planum Temporale                                                                      0.007032   \n",
       "Supracalcarine Cortex                                                                 0.000393   \n",
       "Occipital Pole                                                                        0.011597   \n",
       "\n",
       "                                                    Superior Temporal Gyrus, posterior division  \\\n",
       "Frontal Pole                                                                           0.004643   \n",
       "Insular Cortex                                                                         0.018754   \n",
       "Superior Frontal Gyrus                                                                 0.002537   \n",
       "Middle Frontal Gyrus                                                                   0.003518   \n",
       "Inferior Frontal Gyrus, pars triangularis                                              0.017712   \n",
       "Inferior Frontal Gyrus, pars opercularis                                               0.007919   \n",
       "Precentral Gyrus                                                                       0.004197   \n",
       "Temporal Pole                                                                          0.015173   \n",
       "Superior Temporal Gyrus, anterior division                                             0.068463   \n",
       "Superior Temporal Gyrus, posterior division                                            0.134062   \n",
       "Middle Temporal Gyrus, anterior division                                               0.028632   \n",
       "Middle Temporal Gyrus, posterior division                                              0.054321   \n",
       "Middle Temporal Gyrus, temporooccipital part                                           0.031569   \n",
       "Inferior Temporal Gyrus, anterior division                                             0.002366   \n",
       "Inferior Temporal Gyrus, posterior division                                            0.001829   \n",
       "Inferior Temporal Gyrus, temporooccipital part                                         0.001499   \n",
       "Postcentral Gyrus                                                                      0.005156   \n",
       "Superior Parietal Lobule                                                               0.010910   \n",
       "Supramarginal Gyrus, anterior division                                                 0.016675   \n",
       "Supramarginal Gyrus, posterior division                                                0.037859   \n",
       "Angular Gyrus                                                                          0.033950   \n",
       "Lateral Occipital Cortex, superior division                                            0.014830   \n",
       "Lateral Occipital Cortex, inferior division                                            0.005778   \n",
       "Intracalcarine Cortex                                                                  0.001136   \n",
       "Frontal Medial Cortex                                                                  0.001596   \n",
       "Juxtapositional Lobule Cortex (formerly Supplem...                                     0.003259   \n",
       "Subcallosal Cortex                                                                     0.002630   \n",
       "Paracingulate Gyrus                                                                    0.000527   \n",
       "Cingulate Gyrus, anterior division                                                     0.000647   \n",
       "Cingulate Gyrus, posterior division                                                    0.001999   \n",
       "Precuneous Cortex                                                                      0.009238   \n",
       "Cuneal Cortex                                                                          0.003239   \n",
       "Frontal Orbital Cortex                                                                 0.007212   \n",
       "Parahippocampal Gyrus, anterior division                                               0.001677   \n",
       "Parahippocampal Gyrus, posterior division                                              0.001539   \n",
       "Lingual Gyrus                                                                          0.000252   \n",
       "Temporal Fusiform Cortex, anterior division                                            0.001722   \n",
       "Temporal Fusiform Cortex, posterior division                                           0.000687   \n",
       "Temporal Occipital Fusiform Cortex                                                     0.000197   \n",
       "Occipital Fusiform Gyrus                                                               0.000337   \n",
       "Frontal Operculum Cortex                                                               0.018208   \n",
       "Central Opercular Cortex                                                               0.015022   \n",
       "Parietal Operculum Cortex                                                              0.020154   \n",
       "Planum Polare                                                                          0.018465   \n",
       "Heschl's Gyrus (includes H1 and H2)                                                    0.013457   \n",
       "Planum Temporale                                                                       0.032117   \n",
       "Supracalcarine Cortex                                                                  0.000920   \n",
       "Occipital Pole                                                                         0.015969   \n",
       "\n",
       "                                                         ...        \\\n",
       "Frontal Pole                                             ...         \n",
       "Insular Cortex                                           ...         \n",
       "Superior Frontal Gyrus                                   ...         \n",
       "Middle Frontal Gyrus                                     ...         \n",
       "Inferior Frontal Gyrus, pars triangularis                ...         \n",
       "Inferior Frontal Gyrus, pars opercularis                 ...         \n",
       "Precentral Gyrus                                         ...         \n",
       "Temporal Pole                                            ...         \n",
       "Superior Temporal Gyrus, anterior division               ...         \n",
       "Superior Temporal Gyrus, posterior division              ...         \n",
       "Middle Temporal Gyrus, anterior division                 ...         \n",
       "Middle Temporal Gyrus, posterior division                ...         \n",
       "Middle Temporal Gyrus, temporooccipital part             ...         \n",
       "Inferior Temporal Gyrus, anterior division               ...         \n",
       "Inferior Temporal Gyrus, posterior division              ...         \n",
       "Inferior Temporal Gyrus, temporooccipital part           ...         \n",
       "Postcentral Gyrus                                        ...         \n",
       "Superior Parietal Lobule                                 ...         \n",
       "Supramarginal Gyrus, anterior division                   ...         \n",
       "Supramarginal Gyrus, posterior division                  ...         \n",
       "Angular Gyrus                                            ...         \n",
       "Lateral Occipital Cortex, superior division              ...         \n",
       "Lateral Occipital Cortex, inferior division              ...         \n",
       "Intracalcarine Cortex                                    ...         \n",
       "Frontal Medial Cortex                                    ...         \n",
       "Juxtapositional Lobule Cortex (formerly Supplem...       ...         \n",
       "Subcallosal Cortex                                       ...         \n",
       "Paracingulate Gyrus                                      ...         \n",
       "Cingulate Gyrus, anterior division                       ...         \n",
       "Cingulate Gyrus, posterior division                      ...         \n",
       "Precuneous Cortex                                        ...         \n",
       "Cuneal Cortex                                            ...         \n",
       "Frontal Orbital Cortex                                   ...         \n",
       "Parahippocampal Gyrus, anterior division                 ...         \n",
       "Parahippocampal Gyrus, posterior division                ...         \n",
       "Lingual Gyrus                                            ...         \n",
       "Temporal Fusiform Cortex, anterior division              ...         \n",
       "Temporal Fusiform Cortex, posterior division             ...         \n",
       "Temporal Occipital Fusiform Cortex                       ...         \n",
       "Occipital Fusiform Gyrus                                 ...         \n",
       "Frontal Operculum Cortex                                 ...         \n",
       "Central Opercular Cortex                                 ...         \n",
       "Parietal Operculum Cortex                                ...         \n",
       "Planum Polare                                            ...         \n",
       "Heschl's Gyrus (includes H1 and H2)                      ...         \n",
       "Planum Temporale                                         ...         \n",
       "Supracalcarine Cortex                                    ...         \n",
       "Occipital Pole                                           ...         \n",
       "\n",
       "                                                    Temporal Occipital Fusiform Cortex  \\\n",
       "Frontal Pole                                                                  0.000709   \n",
       "Insular Cortex                                                                0.000895   \n",
       "Superior Frontal Gyrus                                                        0.000121   \n",
       "Middle Frontal Gyrus                                                          0.000192   \n",
       "Inferior Frontal Gyrus, pars triangularis                                     0.000696   \n",
       "Inferior Frontal Gyrus, pars opercularis                                      0.000190   \n",
       "Precentral Gyrus                                                              0.000198   \n",
       "Temporal Pole                                                                 0.001413   \n",
       "Superior Temporal Gyrus, anterior division                                    0.001847   \n",
       "Superior Temporal Gyrus, posterior division                                   0.000773   \n",
       "Middle Temporal Gyrus, anterior division                                      0.001401   \n",
       "Middle Temporal Gyrus, posterior division                                     0.001189   \n",
       "Middle Temporal Gyrus, temporooccipital part                                  0.001004   \n",
       "Inferior Temporal Gyrus, anterior division                                    0.000940   \n",
       "Inferior Temporal Gyrus, posterior division                                   0.036813   \n",
       "Inferior Temporal Gyrus, temporooccipital part                                0.075928   \n",
       "Postcentral Gyrus                                                             0.000318   \n",
       "Superior Parietal Lobule                                                      0.000464   \n",
       "Supramarginal Gyrus, anterior division                                        0.000204   \n",
       "Supramarginal Gyrus, posterior division                                       0.000240   \n",
       "Angular Gyrus                                                                 0.000173   \n",
       "Lateral Occipital Cortex, superior division                                   0.003926   \n",
       "Lateral Occipital Cortex, inferior division                                   0.026395   \n",
       "Intracalcarine Cortex                                                         0.003930   \n",
       "Frontal Medial Cortex                                                         0.000923   \n",
       "Juxtapositional Lobule Cortex (formerly Supplem...                            0.000120   \n",
       "Subcallosal Cortex                                                            0.000531   \n",
       "Paracingulate Gyrus                                                           0.000241   \n",
       "Cingulate Gyrus, anterior division                                            0.000157   \n",
       "Cingulate Gyrus, posterior division                                           0.000367   \n",
       "Precuneous Cortex                                                             0.001016   \n",
       "Cuneal Cortex                                                                 0.003866   \n",
       "Frontal Orbital Cortex                                                        0.001131   \n",
       "Parahippocampal Gyrus, anterior division                                      0.001414   \n",
       "Parahippocampal Gyrus, posterior division                                     0.012787   \n",
       "Lingual Gyrus                                                                 0.069370   \n",
       "Temporal Fusiform Cortex, anterior division                                   0.013994   \n",
       "Temporal Fusiform Cortex, posterior division                                  0.075545   \n",
       "Temporal Occipital Fusiform Cortex                                            0.179561   \n",
       "Occipital Fusiform Gyrus                                                      0.118732   \n",
       "Frontal Operculum Cortex                                                      0.000617   \n",
       "Central Opercular Cortex                                                      0.000720   \n",
       "Parietal Operculum Cortex                                                     0.000211   \n",
       "Planum Polare                                                                 0.001748   \n",
       "Heschl's Gyrus (includes H1 and H2)                                           0.000734   \n",
       "Planum Temporale                                                              0.001051   \n",
       "Supracalcarine Cortex                                                         0.002796   \n",
       "Occipital Pole                                                                0.002595   \n",
       "\n",
       "                                                    Occipital Fusiform Gyrus  \\\n",
       "Frontal Pole                                                        0.003573   \n",
       "Insular Cortex                                                      0.003754   \n",
       "Superior Frontal Gyrus                                              0.000216   \n",
       "Middle Frontal Gyrus                                                0.000181   \n",
       "Inferior Frontal Gyrus, pars triangularis                           0.000884   \n",
       "Inferior Frontal Gyrus, pars opercularis                            0.000208   \n",
       "Precentral Gyrus                                                    0.000345   \n",
       "Temporal Pole                                                       0.011402   \n",
       "Superior Temporal Gyrus, anterior division                          0.001114   \n",
       "Superior Temporal Gyrus, posterior division                         0.000426   \n",
       "Middle Temporal Gyrus, anterior division                            0.005660   \n",
       "Middle Temporal Gyrus, posterior division                           0.003010   \n",
       "Middle Temporal Gyrus, temporooccipital part                        0.001221   \n",
       "Inferior Temporal Gyrus, anterior division                          0.012360   \n",
       "Inferior Temporal Gyrus, posterior division                         0.023305   \n",
       "Inferior Temporal Gyrus, temporooccipital part                      0.044187   \n",
       "Postcentral Gyrus                                                   0.000657   \n",
       "Superior Parietal Lobule                                            0.000779   \n",
       "Supramarginal Gyrus, anterior division                              0.000246   \n",
       "Supramarginal Gyrus, posterior division                             0.000221   \n",
       "Angular Gyrus                                                       0.000140   \n",
       "Lateral Occipital Cortex, superior division                         0.001035   \n",
       "Lateral Occipital Cortex, inferior division                         0.015601   \n",
       "Intracalcarine Cortex                                               0.007642   \n",
       "Frontal Medial Cortex                                               0.004842   \n",
       "Juxtapositional Lobule Cortex (formerly Supplem...                  0.000172   \n",
       "Subcallosal Cortex                                                  0.001610   \n",
       "Paracingulate Gyrus                                                 0.000910   \n",
       "Cingulate Gyrus, anterior division                                  0.000463   \n",
       "Cingulate Gyrus, posterior division                                 0.000639   \n",
       "Precuneous Cortex                                                   0.000976   \n",
       "Cuneal Cortex                                                       0.004883   \n",
       "Frontal Orbital Cortex                                              0.008510   \n",
       "Parahippocampal Gyrus, anterior division                            0.003488   \n",
       "Parahippocampal Gyrus, posterior division                           0.015122   \n",
       "Lingual Gyrus                                                       0.074173   \n",
       "Temporal Fusiform Cortex, anterior division                         0.026072   \n",
       "Temporal Fusiform Cortex, posterior division                        0.070511   \n",
       "Temporal Occipital Fusiform Cortex                                  0.190387   \n",
       "Occipital Fusiform Gyrus                                            0.192245   \n",
       "Frontal Operculum Cortex                                            0.001231   \n",
       "Central Opercular Cortex                                            0.000395   \n",
       "Parietal Operculum Cortex                                           0.000250   \n",
       "Planum Polare                                                       0.001615   \n",
       "Heschl's Gyrus (includes H1 and H2)                                 0.000318   \n",
       "Planum Temporale                                                    0.000426   \n",
       "Supracalcarine Cortex                                               0.007269   \n",
       "Occipital Pole                                                      0.006161   \n",
       "\n",
       "                                                    Frontal Operculum Cortex  \\\n",
       "Frontal Pole                                                        0.000174   \n",
       "Insular Cortex                                                      0.011431   \n",
       "Superior Frontal Gyrus                                              0.000535   \n",
       "Middle Frontal Gyrus                                                0.000636   \n",
       "Inferior Frontal Gyrus, pars triangularis                           0.003387   \n",
       "Inferior Frontal Gyrus, pars opercularis                            0.000904   \n",
       "Precentral Gyrus                                                    0.000189   \n",
       "Temporal Pole                                                       0.001207   \n",
       "Superior Temporal Gyrus, anterior division                          0.000971   \n",
       "Superior Temporal Gyrus, posterior division                         0.000605   \n",
       "Middle Temporal Gyrus, anterior division                            0.000179   \n",
       "Middle Temporal Gyrus, posterior division                           0.000321   \n",
       "Middle Temporal Gyrus, temporooccipital part                        0.000137   \n",
       "Inferior Temporal Gyrus, anterior division                          0.000134   \n",
       "Inferior Temporal Gyrus, posterior division                         0.000059   \n",
       "Inferior Temporal Gyrus, temporooccipital part                      0.000043   \n",
       "Postcentral Gyrus                                                   0.000539   \n",
       "Superior Parietal Lobule                                            0.000194   \n",
       "Supramarginal Gyrus, anterior division                              0.000959   \n",
       "Supramarginal Gyrus, posterior division                             0.000359   \n",
       "Angular Gyrus                                                       0.000109   \n",
       "Lateral Occipital Cortex, superior division                         0.000222   \n",
       "Lateral Occipital Cortex, inferior division                         0.000162   \n",
       "Intracalcarine Cortex                                               0.000047   \n",
       "Frontal Medial Cortex                                               0.000019   \n",
       "Juxtapositional Lobule Cortex (formerly Supplem...                  0.000095   \n",
       "Subcallosal Cortex                                                  0.000062   \n",
       "Paracingulate Gyrus                                                 0.000078   \n",
       "Cingulate Gyrus, anterior division                                  0.000079   \n",
       "Cingulate Gyrus, posterior division                                 0.000050   \n",
       "Precuneous Cortex                                                   0.000114   \n",
       "Cuneal Cortex                                                       0.000084   \n",
       "Frontal Orbital Cortex                                              0.001726   \n",
       "Parahippocampal Gyrus, anterior division                            0.000095   \n",
       "Parahippocampal Gyrus, posterior division                           0.000083   \n",
       "Lingual Gyrus                                                       0.000032   \n",
       "Temporal Fusiform Cortex, anterior division                         0.000135   \n",
       "Temporal Fusiform Cortex, posterior division                        0.000022   \n",
       "Temporal Occipital Fusiform Cortex                                  0.000007   \n",
       "Occipital Fusiform Gyrus                                            0.000053   \n",
       "Frontal Operculum Cortex                                            0.072283   \n",
       "Central Opercular Cortex                                            0.011661   \n",
       "Parietal Operculum Cortex                                           0.004927   \n",
       "Planum Polare                                                       0.005503   \n",
       "Heschl's Gyrus (includes H1 and H2)                                 0.003175   \n",
       "Planum Temporale                                                    0.002729   \n",
       "Supracalcarine Cortex                                               0.000045   \n",
       "Occipital Pole                                                      0.000419   \n",
       "\n",
       "                                                    Central Opercular Cortex  \\\n",
       "Frontal Pole                                                        0.000368   \n",
       "Insular Cortex                                                      0.021130   \n",
       "Superior Frontal Gyrus                                              0.000834   \n",
       "Middle Frontal Gyrus                                                0.001173   \n",
       "Inferior Frontal Gyrus, pars triangularis                           0.002615   \n",
       "Inferior Frontal Gyrus, pars opercularis                            0.002707   \n",
       "Precentral Gyrus                                                    0.001925   \n",
       "Temporal Pole                                                       0.001766   \n",
       "Superior Temporal Gyrus, anterior division                          0.003418   \n",
       "Superior Temporal Gyrus, posterior division                         0.001991   \n",
       "Middle Temporal Gyrus, anterior division                            0.000335   \n",
       "Middle Temporal Gyrus, posterior division                           0.000766   \n",
       "Middle Temporal Gyrus, temporooccipital part                        0.000830   \n",
       "Inferior Temporal Gyrus, anterior division                          0.000143   \n",
       "Inferior Temporal Gyrus, posterior division                         0.000190   \n",
       "Inferior Temporal Gyrus, temporooccipital part                      0.000455   \n",
       "Postcentral Gyrus                                                   0.004484   \n",
       "Superior Parietal Lobule                                            0.001390   \n",
       "Supramarginal Gyrus, anterior division                              0.005892   \n",
       "Supramarginal Gyrus, posterior division                             0.003590   \n",
       "Angular Gyrus                                                       0.001397   \n",
       "Lateral Occipital Cortex, superior division                         0.002214   \n",
       "Lateral Occipital Cortex, inferior division                         0.000737   \n",
       "Intracalcarine Cortex                                               0.000078   \n",
       "Frontal Medial Cortex                                               0.000065   \n",
       "Juxtapositional Lobule Cortex (formerly Supplem...                  0.000376   \n",
       "Subcallosal Cortex                                                  0.000111   \n",
       "Paracingulate Gyrus                                                 0.000132   \n",
       "Cingulate Gyrus, anterior division                                  0.000129   \n",
       "Cingulate Gyrus, posterior division                                 0.000220   \n",
       "Precuneous Cortex                                                   0.000715   \n",
       "Cuneal Cortex                                                       0.000292   \n",
       "Frontal Orbital Cortex                                              0.000958   \n",
       "Parahippocampal Gyrus, anterior division                            0.000228   \n",
       "Parahippocampal Gyrus, posterior division                           0.000634   \n",
       "Lingual Gyrus                                                       0.000018   \n",
       "Temporal Fusiform Cortex, anterior division                         0.000231   \n",
       "Temporal Fusiform Cortex, posterior division                        0.000113   \n",
       "Temporal Occipital Fusiform Cortex                                  0.000034   \n",
       "Occipital Fusiform Gyrus                                            0.000017   \n",
       "Frontal Operculum Cortex                                            0.028706   \n",
       "Central Opercular Cortex                                            0.096859   \n",
       "Parietal Operculum Cortex                                           0.049979   \n",
       "Planum Polare                                                       0.009588   \n",
       "Heschl's Gyrus (includes H1 and H2)                                 0.063332   \n",
       "Planum Temporale                                                    0.019686   \n",
       "Supracalcarine Cortex                                               0.000093   \n",
       "Occipital Pole                                                      0.000145   \n",
       "\n",
       "                                                    Parietal Operculum Cortex  \\\n",
       "Frontal Pole                                                         0.000443   \n",
       "Insular Cortex                                                       0.008273   \n",
       "Superior Frontal Gyrus                                               0.000114   \n",
       "Middle Frontal Gyrus                                                 0.000162   \n",
       "Inferior Frontal Gyrus, pars triangularis                            0.001650   \n",
       "Inferior Frontal Gyrus, pars opercularis                             0.000496   \n",
       "Precentral Gyrus                                                     0.000345   \n",
       "Temporal Pole                                                        0.001098   \n",
       "Superior Temporal Gyrus, anterior division                           0.000848   \n",
       "Superior Temporal Gyrus, posterior division                          0.001641   \n",
       "Middle Temporal Gyrus, anterior division                             0.000174   \n",
       "Middle Temporal Gyrus, posterior division                            0.000535   \n",
       "Middle Temporal Gyrus, temporooccipital part                         0.000522   \n",
       "Inferior Temporal Gyrus, anterior division                           0.000080   \n",
       "Inferior Temporal Gyrus, posterior division                          0.000070   \n",
       "Inferior Temporal Gyrus, temporooccipital part                       0.000098   \n",
       "Postcentral Gyrus                                                    0.002527   \n",
       "Superior Parietal Lobule                                             0.001924   \n",
       "Supramarginal Gyrus, anterior division                               0.005972   \n",
       "Supramarginal Gyrus, posterior division                              0.002512   \n",
       "Angular Gyrus                                                        0.000456   \n",
       "Lateral Occipital Cortex, superior division                          0.000524   \n",
       "Lateral Occipital Cortex, inferior division                          0.000179   \n",
       "Intracalcarine Cortex                                                0.000030   \n",
       "Frontal Medial Cortex                                                0.000055   \n",
       "Juxtapositional Lobule Cortex (formerly Supplem...                   0.000076   \n",
       "Subcallosal Cortex                                                   0.000034   \n",
       "Paracingulate Gyrus                                                  0.000044   \n",
       "Cingulate Gyrus, anterior division                                   0.000055   \n",
       "Cingulate Gyrus, posterior division                                  0.000149   \n",
       "Precuneous Cortex                                                    0.001133   \n",
       "Cuneal Cortex                                                        0.000079   \n",
       "Frontal Orbital Cortex                                               0.000445   \n",
       "Parahippocampal Gyrus, anterior division                             0.000084   \n",
       "Parahippocampal Gyrus, posterior division                            0.000074   \n",
       "Lingual Gyrus                                                        0.000007   \n",
       "Temporal Fusiform Cortex, anterior division                          0.000085   \n",
       "Temporal Fusiform Cortex, posterior division                         0.000025   \n",
       "Temporal Occipital Fusiform Cortex                                   0.000005   \n",
       "Occipital Fusiform Gyrus                                             0.000007   \n",
       "Frontal Operculum Cortex                                             0.004127   \n",
       "Central Opercular Cortex                                             0.022890   \n",
       "Parietal Operculum Cortex                                            0.076883   \n",
       "Planum Polare                                                        0.004983   \n",
       "Heschl's Gyrus (includes H1 and H2)                                  0.055714   \n",
       "Planum Temporale                                                     0.026142   \n",
       "Supracalcarine Cortex                                                0.000018   \n",
       "Occipital Pole                                                       0.000025   \n",
       "\n",
       "                                                    Planum Polare  \\\n",
       "Frontal Pole                                             0.003270   \n",
       "Insular Cortex                                           0.028629   \n",
       "Superior Frontal Gyrus                                   0.001279   \n",
       "Middle Frontal Gyrus                                     0.002343   \n",
       "Inferior Frontal Gyrus, pars triangularis                0.014933   \n",
       "Inferior Frontal Gyrus, pars opercularis                 0.003074   \n",
       "Precentral Gyrus                                         0.001350   \n",
       "Temporal Pole                                            0.031483   \n",
       "Superior Temporal Gyrus, anterior division               0.023738   \n",
       "Superior Temporal Gyrus, posterior division              0.004867   \n",
       "Middle Temporal Gyrus, anterior division                 0.014653   \n",
       "Middle Temporal Gyrus, posterior division                0.005309   \n",
       "Middle Temporal Gyrus, temporooccipital part             0.003106   \n",
       "Inferior Temporal Gyrus, anterior division               0.003722   \n",
       "Inferior Temporal Gyrus, posterior division              0.001797   \n",
       "Inferior Temporal Gyrus, temporooccipital part           0.001559   \n",
       "Postcentral Gyrus                                        0.002952   \n",
       "Superior Parietal Lobule                                 0.001790   \n",
       "Supramarginal Gyrus, anterior division                   0.004518   \n",
       "Supramarginal Gyrus, posterior division                  0.002371   \n",
       "Angular Gyrus                                            0.001464   \n",
       "Lateral Occipital Cortex, superior division              0.005924   \n",
       "Lateral Occipital Cortex, inferior division              0.006773   \n",
       "Intracalcarine Cortex                                    0.002762   \n",
       "Frontal Medial Cortex                                    0.001091   \n",
       "Juxtapositional Lobule Cortex (formerly Supplem...       0.000756   \n",
       "Subcallosal Cortex                                       0.000977   \n",
       "Paracingulate Gyrus                                      0.000259   \n",
       "Cingulate Gyrus, anterior division                       0.000285   \n",
       "Cingulate Gyrus, posterior division                      0.000716   \n",
       "Precuneous Cortex                                        0.002516   \n",
       "Cuneal Cortex                                            0.003995   \n",
       "Frontal Orbital Cortex                                   0.024050   \n",
       "Parahippocampal Gyrus, anterior division                 0.001126   \n",
       "Parahippocampal Gyrus, posterior division                0.000736   \n",
       "Lingual Gyrus                                            0.002685   \n",
       "Temporal Fusiform Cortex, anterior division              0.002032   \n",
       "Temporal Fusiform Cortex, posterior division             0.000548   \n",
       "Temporal Occipital Fusiform Cortex                       0.000280   \n",
       "Occipital Fusiform Gyrus                                 0.005377   \n",
       "Frontal Operculum Cortex                                 0.027955   \n",
       "Central Opercular Cortex                                 0.018910   \n",
       "Parietal Operculum Cortex                                0.012786   \n",
       "Planum Polare                                            0.039733   \n",
       "Heschl's Gyrus (includes H1 and H2)                      0.015340   \n",
       "Planum Temporale                                         0.008433   \n",
       "Supracalcarine Cortex                                    0.002357   \n",
       "Occipital Pole                                           0.015674   \n",
       "\n",
       "                                                    Heschl's Gyrus (includes H1 and H2)  \\\n",
       "Frontal Pole                                                                   0.000389   \n",
       "Insular Cortex                                                                 0.010420   \n",
       "Superior Frontal Gyrus                                                         0.000387   \n",
       "Middle Frontal Gyrus                                                           0.000731   \n",
       "Inferior Frontal Gyrus, pars triangularis                                      0.001186   \n",
       "Inferior Frontal Gyrus, pars opercularis                                       0.001406   \n",
       "Precentral Gyrus                                                               0.000514   \n",
       "Temporal Pole                                                                  0.002168   \n",
       "Superior Temporal Gyrus, anterior division                                     0.005917   \n",
       "Superior Temporal Gyrus, posterior division                                    0.002281   \n",
       "Middle Temporal Gyrus, anterior division                                       0.000455   \n",
       "Middle Temporal Gyrus, posterior division                                      0.001489   \n",
       "Middle Temporal Gyrus, temporooccipital part                                   0.001844   \n",
       "Inferior Temporal Gyrus, anterior division                                     0.000184   \n",
       "Inferior Temporal Gyrus, posterior division                                    0.000455   \n",
       "Inferior Temporal Gyrus, temporooccipital part                                 0.001130   \n",
       "Postcentral Gyrus                                                              0.002385   \n",
       "Superior Parietal Lobule                                                       0.002010   \n",
       "Supramarginal Gyrus, anterior division                                         0.003240   \n",
       "Supramarginal Gyrus, posterior division                                        0.002890   \n",
       "Angular Gyrus                                                                  0.001493   \n",
       "Lateral Occipital Cortex, superior division                                    0.005081   \n",
       "Lateral Occipital Cortex, inferior division                                    0.001856   \n",
       "Intracalcarine Cortex                                                          0.000191   \n",
       "Frontal Medial Cortex                                                          0.000067   \n",
       "Juxtapositional Lobule Cortex (formerly Supplem...                             0.000438   \n",
       "Subcallosal Cortex                                                             0.000249   \n",
       "Paracingulate Gyrus                                                            0.000087   \n",
       "Cingulate Gyrus, anterior division                                             0.000095   \n",
       "Cingulate Gyrus, posterior division                                            0.000587   \n",
       "Precuneous Cortex                                                              0.001763   \n",
       "Cuneal Cortex                                                                  0.000974   \n",
       "Frontal Orbital Cortex                                                         0.000797   \n",
       "Parahippocampal Gyrus, anterior division                                       0.000323   \n",
       "Parahippocampal Gyrus, posterior division                                      0.000389   \n",
       "Lingual Gyrus                                                                  0.000037   \n",
       "Temporal Fusiform Cortex, anterior division                                    0.000504   \n",
       "Temporal Fusiform Cortex, posterior division                                   0.000294   \n",
       "Temporal Occipital Fusiform Cortex                                             0.000086   \n",
       "Occipital Fusiform Gyrus                                                       0.000027   \n",
       "Frontal Operculum Cortex                                                       0.003540   \n",
       "Central Opercular Cortex                                                       0.032331   \n",
       "Parietal Operculum Cortex                                                      0.043193   \n",
       "Planum Polare                                                                  0.011796   \n",
       "Heschl's Gyrus (includes H1 and H2)                                            0.085388   \n",
       "Planum Temporale                                                               0.015165   \n",
       "Supracalcarine Cortex                                                          0.000317   \n",
       "Occipital Pole                                                                 0.000181   \n",
       "\n",
       "                                                    Planum Temporale  \\\n",
       "Frontal Pole                                                0.004162   \n",
       "Insular Cortex                                              0.028026   \n",
       "Superior Frontal Gyrus                                      0.001929   \n",
       "Middle Frontal Gyrus                                        0.002721   \n",
       "Inferior Frontal Gyrus, pars triangularis                   0.011893   \n",
       "Inferior Frontal Gyrus, pars opercularis                    0.006857   \n",
       "Precentral Gyrus                                            0.005688   \n",
       "Temporal Pole                                               0.007347   \n",
       "Superior Temporal Gyrus, anterior division                  0.017928   \n",
       "Superior Temporal Gyrus, posterior division                 0.023731   \n",
       "Middle Temporal Gyrus, anterior division                    0.004468   \n",
       "Middle Temporal Gyrus, posterior division                   0.006380   \n",
       "Middle Temporal Gyrus, temporooccipital part                0.006207   \n",
       "Inferior Temporal Gyrus, anterior division                  0.000846   \n",
       "Inferior Temporal Gyrus, posterior division                 0.001333   \n",
       "Inferior Temporal Gyrus, temporooccipital part              0.001796   \n",
       "Postcentral Gyrus                                           0.014898   \n",
       "Superior Parietal Lobule                                    0.014510   \n",
       "Supramarginal Gyrus, anterior division                      0.029199   \n",
       "Supramarginal Gyrus, posterior division                     0.025294   \n",
       "Angular Gyrus                                               0.009932   \n",
       "Lateral Occipital Cortex, superior division                 0.012053   \n",
       "Lateral Occipital Cortex, inferior division                 0.003408   \n",
       "Intracalcarine Cortex                                       0.000546   \n",
       "Frontal Medial Cortex                                       0.000728   \n",
       "Juxtapositional Lobule Cortex (formerly Supplem...          0.002165   \n",
       "Subcallosal Cortex                                          0.000854   \n",
       "Paracingulate Gyrus                                         0.000359   \n",
       "Cingulate Gyrus, anterior division                          0.000440   \n",
       "Cingulate Gyrus, posterior division                         0.001857   \n",
       "Precuneous Cortex                                           0.008652   \n",
       "Cuneal Cortex                                               0.002019   \n",
       "Frontal Orbital Cortex                                      0.003388   \n",
       "Parahippocampal Gyrus, anterior division                    0.001064   \n",
       "Parahippocampal Gyrus, posterior division                   0.001190   \n",
       "Lingual Gyrus                                               0.000115   \n",
       "Temporal Fusiform Cortex, anterior division                 0.001275   \n",
       "Temporal Fusiform Cortex, posterior division                0.000865   \n",
       "Temporal Occipital Fusiform Cortex                          0.000188   \n",
       "Occipital Fusiform Gyrus                                    0.000062   \n",
       "Frontal Operculum Cortex                                    0.024076   \n",
       "Central Opercular Cortex                                    0.064287   \n",
       "Parietal Operculum Cortex                                   0.109177   \n",
       "Planum Polare                                               0.027306   \n",
       "Heschl's Gyrus (includes H1 and H2)                         0.069378   \n",
       "Planum Temporale                                            0.122353   \n",
       "Supracalcarine Cortex                                       0.000518   \n",
       "Occipital Pole                                              0.000933   \n",
       "\n",
       "                                                    Supracalcarine Cortex  \\\n",
       "Frontal Pole                                                     0.000488   \n",
       "Insular Cortex                                                   0.000302   \n",
       "Superior Frontal Gyrus                                           0.000035   \n",
       "Middle Frontal Gyrus                                             0.000014   \n",
       "Inferior Frontal Gyrus, pars triangularis                        0.000156   \n",
       "Inferior Frontal Gyrus, pars opercularis                         0.000020   \n",
       "Precentral Gyrus                                                 0.000020   \n",
       "Temporal Pole                                                    0.000764   \n",
       "Superior Temporal Gyrus, anterior division                       0.000068   \n",
       "Superior Temporal Gyrus, posterior division                      0.000036   \n",
       "Middle Temporal Gyrus, anterior division                         0.000613   \n",
       "Middle Temporal Gyrus, posterior division                        0.000445   \n",
       "Middle Temporal Gyrus, temporooccipital part                     0.000473   \n",
       "Inferior Temporal Gyrus, anterior division                       0.000595   \n",
       "Inferior Temporal Gyrus, posterior division                      0.000692   \n",
       "Inferior Temporal Gyrus, temporooccipital part                   0.001349   \n",
       "Postcentral Gyrus                                                0.000027   \n",
       "Superior Parietal Lobule                                         0.000015   \n",
       "Supramarginal Gyrus, anterior division                           0.000023   \n",
       "Supramarginal Gyrus, posterior division                          0.000015   \n",
       "Angular Gyrus                                                    0.000009   \n",
       "Lateral Occipital Cortex, superior division                      0.000121   \n",
       "Lateral Occipital Cortex, inferior division                      0.000132   \n",
       "Intracalcarine Cortex                                            0.007499   \n",
       "Frontal Medial Cortex                                            0.000200   \n",
       "Juxtapositional Lobule Cortex (formerly Supplem...               0.000047   \n",
       "Subcallosal Cortex                                               0.000323   \n",
       "Paracingulate Gyrus                                              0.000263   \n",
       "Cingulate Gyrus, anterior division                               0.000444   \n",
       "Cingulate Gyrus, posterior division                              0.000928   \n",
       "Precuneous Cortex                                                0.002258   \n",
       "Cuneal Cortex                                                    0.007322   \n",
       "Frontal Orbital Cortex                                           0.000662   \n",
       "Parahippocampal Gyrus, anterior division                         0.000475   \n",
       "Parahippocampal Gyrus, posterior division                        0.001010   \n",
       "Lingual Gyrus                                                    0.006158   \n",
       "Temporal Fusiform Cortex, anterior division                      0.001197   \n",
       "Temporal Fusiform Cortex, posterior division                     0.000750   \n",
       "Temporal Occipital Fusiform Cortex                               0.000378   \n",
       "Occipital Fusiform Gyrus                                         0.000939   \n",
       "Frontal Operculum Cortex                                         0.000181   \n",
       "Central Opercular Cortex                                         0.000040   \n",
       "Parietal Operculum Cortex                                        0.000024   \n",
       "Planum Polare                                                    0.000132   \n",
       "Heschl's Gyrus (includes H1 and H2)                              0.000026   \n",
       "Planum Temporale                                                 0.000029   \n",
       "Supracalcarine Cortex                                            0.018860   \n",
       "Occipital Pole                                                   0.000696   \n",
       "\n",
       "                                                    Occipital Pole  \n",
       "Frontal Pole                                              0.045025  \n",
       "Insular Cortex                                            0.064000  \n",
       "Superior Frontal Gyrus                                    0.002559  \n",
       "Middle Frontal Gyrus                                      0.003883  \n",
       "Inferior Frontal Gyrus, pars triangularis                 0.035948  \n",
       "Inferior Frontal Gyrus, pars opercularis                  0.007066  \n",
       "Precentral Gyrus                                          0.002513  \n",
       "Temporal Pole                                             0.102068  \n",
       "Superior Temporal Gyrus, anterior division                0.144851  \n",
       "Superior Temporal Gyrus, posterior division               0.043859  \n",
       "Middle Temporal Gyrus, anterior division                  0.145214  \n",
       "Middle Temporal Gyrus, posterior division                 0.076183  \n",
       "Middle Temporal Gyrus, temporooccipital part              0.043433  \n",
       "Inferior Temporal Gyrus, anterior division                0.083353  \n",
       "Inferior Temporal Gyrus, posterior division               0.043847  \n",
       "Inferior Temporal Gyrus, temporooccipital part            0.040242  \n",
       "Postcentral Gyrus                                         0.002602  \n",
       "Superior Parietal Lobule                                  0.002209  \n",
       "Supramarginal Gyrus, anterior division                    0.002855  \n",
       "Supramarginal Gyrus, posterior division                   0.004407  \n",
       "Angular Gyrus                                             0.004125  \n",
       "Lateral Occipital Cortex, superior division               0.041263  \n",
       "Lateral Occipital Cortex, inferior division               0.083214  \n",
       "Intracalcarine Cortex                                     0.043894  \n",
       "Frontal Medial Cortex                                     0.065386  \n",
       "Juxtapositional Lobule Cortex (formerly Supplem...        0.001909  \n",
       "Subcallosal Cortex                                        0.042563  \n",
       "Paracingulate Gyrus                                       0.004916  \n",
       "Cingulate Gyrus, anterior division                        0.003589  \n",
       "Cingulate Gyrus, posterior division                       0.004638  \n",
       "Precuneous Cortex                                         0.016512  \n",
       "Cuneal Cortex                                             0.075233  \n",
       "Frontal Orbital Cortex                                    0.088306  \n",
       "Parahippocampal Gyrus, anterior division                  0.043790  \n",
       "Parahippocampal Gyrus, posterior division                 0.025329  \n",
       "Lingual Gyrus                                             0.029514  \n",
       "Temporal Fusiform Cortex, anterior division               0.057990  \n",
       "Temporal Fusiform Cortex, posterior division              0.025571  \n",
       "Temporal Occipital Fusiform Cortex                        0.009349  \n",
       "Occipital Fusiform Gyrus                                  0.017713  \n",
       "Frontal Operculum Cortex                                  0.038022  \n",
       "Central Opercular Cortex                                  0.011761  \n",
       "Parietal Operculum Cortex                                 0.003973  \n",
       "Planum Polare                                             0.103114  \n",
       "Heschl's Gyrus (includes H1 and H2)                       0.007853  \n",
       "Planum Temporale                                          0.010495  \n",
       "Supracalcarine Cortex                                     0.059660  \n",
       "Occipital Pole                                            0.187266  \n",
       "\n",
       "[48 rows x 48 columns]"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "normalized_network"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/anaconda2/envs/python3/lib/python3.6/importlib/_bootstrap.py:219: ImportWarning: can't resolve package from __spec__ or __package__, falling back on __name__ and __path__\n",
      "  return f(*args, **kwds)\n"
     ]
    }
   ],
   "source": [
    "import networkx as nx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [],
   "source": [
    "mform = np.matrix(normalized_network)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [],
   "source": [
    "mform[mform < 0.01] = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [],
   "source": [
    "cnetwork = nx.from_numpy_matrix(mform)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<networkx.classes.graph.Graph at 0x2c3b2d5630>"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cnetwork"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [],
   "source": [
    "shortest_path = nx.average_shortest_path_length(cnetwork)\n",
    "avg_clustering = nx.average_clustering(cnetwork)\n",
    "avg_degree = nx.average_degree_connectivity(cnetwork)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1.5186170212765957,\n",
       " 0.7252555362207577,\n",
       " {49: 24.122448979591837,\n",
       "  40: 25.425,\n",
       "  26: 26.423076923076923,\n",
       "  28: 25.178571428571427,\n",
       "  25: 26.92,\n",
       "  30: 26.166666666666668,\n",
       "  34: 25.080882352941178,\n",
       "  22: 27.560606060606062,\n",
       "  15: 29.2,\n",
       "  29: 27.775862068965516,\n",
       "  17: 27.91176470588235,\n",
       "  19: 27.333333333333332,\n",
       "  16: 25.875,\n",
       "  31: 26.403225806451612,\n",
       "  23: 26.159420289855074,\n",
       "  45: 24.644444444444446,\n",
       "  13: 24.576923076923077,\n",
       "  14: 27.357142857142858,\n",
       "  21: 23.833333333333332,\n",
       "  24: 27.4375,\n",
       "  12: 23.75,\n",
       "  20: 28.85,\n",
       "  18: 27.555555555555557})"
      ]
     },
     "execution_count": 96,
     "metadata": {},
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   "outputs": [],
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