# Citation

Han, B. (Biao), Pim Mostert, Lange, F.P. de (Floris) (2019).
Predictable tones elicit stimulus-specific suppression of evoked activity in auditory cortex [Data set].
http://hdl.handle.net/11633/aacfytwf.

# Abstract

The auditory cortex is sensitive to many forms of acoustic regularity, resulting in suppressed neural activity for expected auditory events. It is unclear whether this activity reduction for expected events is the result of suppression of neurons that are tuned to the expected stimulus (i.e., dampening), or alternatively suppression of neurons that are tuned away from the expected stimulus (i.e., sharpening). In the present study, we adjudicated between these models by characterizing the effect of expectation on the ability to classify the identity of auditory stimuli from auditory neural activity patterns, using magnetoencephalography (MEG) in healthy human observers. Participants listened to pure tone pairs, in which the identity of the second tone was either expected or unexpected. The task of the participants was to detect a target tone, which deviated strongly from both the expected and unexpected tones. We found a strong suppression of the overall neural response in the expected condition compared to the unexpected condition. Linear classifiers showed a reduced ability to decode stimulus identity from event-related auditory fields in the expected condition compared to the unexpected condition. This suggests that stimulus-specific event-related activity is dampened for expected tones in auditory cortex. 

# Background information

You can find more information, including relevant publications pertaining to this dataset on the collection overview page at http://hdl.handle.net/11633/aacfytwf.

A complete list of files that are part of this dataset can be found in the file MANIFEST.txt, including a SHA256 hash for each file to allow verification of correct data transfer.

# Restrictions on data access and reuse 

The access to and use of this dataset is only allowed under the conditions listed in the data use agreement, as detailed in the file LICENSE.txt. 

Neither the Donders Institute or Radboud University, nor the researchers that provide this dataset should be included as an author of publications or presentations if this authorship would be based solely on the use of this data. 

However, we ask you to acknowledge the use of the data and data derived from the data when publicly presenting any results or algorithms that benefitted from their use:

    1) Papers, book chapters, books, posters, oral presentations, and all other presentations of results derived from the data should acknowledge the origin of the data as follows: "Data were provided (in part) by the Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen".
    2) Authors of publications or presentations using the data should cite relevant publications describing the methods developed and used by the Donders Institute to acquire and process the data. The specific publications that are appropriate to cite in any given study will depend on what the data were used for and for what purposes. When applicable, a list of publications will be specified on the collection overview page.