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TEMPO processing pipeline

Introduction

This is a pipeline for converting dual-channel TEMPO microscopy recordings to dF/F movies with physiological and recording artifacts removed via convolution unmixing procedure.

Installation

This pipeline was tested in MATLAB 2019b, 2021b, and 2023a.

Add all folders (except pipelines) to MATLAB path. Add all dependencies to MATLAB path.

Dependencies

internal matlab utils

see dependencies_utils.txt

external dependencies

Inpaint_nans\inpaint_nans.m
NoRMCorre\dftregistration_min_max.m

For .dcimg to .h5 conversion, binary files dcimgmex.mexw64 / dcimgmatlab.mexw64, dct_readtimestamps.exe, and drives from Hamamatsu are required

Getting Started

movie processing pipeline

Browse the example pipelines in pipelines folder.

Preprocessing

pipelines\pipeline_preprocessing_2xmoco.m
Data preprocessing that includes independent motion correction of both channels and registration of the reference channel to the signal channel.

Unmixing

convolutional unmixing - data model convolutional unmixing - algorithm

pipelines\pipeline_unmixing.m
Unmixing of physiological and recording artifacts. Decrosstalking, high-pass filtering, convolutional unmixing, and F0 normalization.

Citations

This processing pipeline is described in upcoming biorxiv link Haziza et al., 2024. The convolutional unmixing procedure was first introduced in a talk Kruzhilin et al., 2023. Please cite us if you use this pipeline in your own work.

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