Download the README.txt file for a detailed description of this dataset's contentThis dataset accompanies the manuscript "Measuring shared responses across subjects using intersubject correlation" by Nastase, Gazzola, Hasson, and Keysers. In particular, these data is used in a tutorial notebook located at https://github.com/snastase/isc-tutorial.The dataset is a fully processed subset of http://arks.princeton.edu/ark:/88435/dsp015d86p269

Gazzola, Valeria

Hasson, Uri

Keysers, Christian

Nastase, Samuel

Our capacity to jointly represent information about the world underpins our social experience. By leveraging one individual's brain activity to model another's, we can measure shared information across brains-even in dynamic, naturalistic scenarios where an explicit response model may be unobtainable. Introducing experimental manipulations allows us to measure, for example, shared responses between speakers and listeners, or between perception and recall. In this tutorial, we develop the logic of intersubject correlation (ISC) analysis and discuss the family of neuroscientific questions that stem from this approach. We also extend this logic to spatially distributed response patterns and functional network estimation. We provide a thorough and accessible treatment of methodological considerations specific to ISC analysis, and outline best practices

Nastase, Samuel A

NARCIS 

Measuring shared responses across subjects using intersubject correlation

Our capacity to jointly represent information about the world underpins our social experience. By leveraging one individual's brain activity to model another's, we can measure shared information across brains-even in dynamic, naturalistic scenarios where an explicit response model may be unobtainable. Introducing experimental manipulations allows us to measure, for example, shared responses between speakers and listeners or between perception and recall. In this tutorial, we develop the logic of intersubject correlation (ISC) analysis and discuss the family of neuroscientific questions that stem from this approach. We also extend this logic to spatially distributed response patterns and functional network estimation. We provide a thorough and accessible treatment of methodological considerations specific to ISC analysis and outline best practices

Nastase, S.A.

Gazzola, V.

Hasson, U.

Keysers, C.

Our capacity to jointly represent information about the world underpins our social experience. By leveraging one individual's brain activity to model another's, we can measure shared information across brains-even in dynamic, naturalistic scenarios where an explicit response model may be unobtainable. Introducing experimental manipulations allows us to measure, for example, shared responses between speakers and listeners or between perception and recall. In this tutorial, we develop the logic of intersubject correlation (ISC) analysis and discuss the family of neuroscientific questions that stem from this approach. We also extend this logic to spatially distributed response patterns and functional network estimation. We provide a thorough and accessible treatment of methodological considerations specific to ISC analysis and outline best practices.</p

Measuring shared responses across subjects using intersubject correlation

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International Migration, Integration and Social Cohesion online publications

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International Migration, Integration and Social Cohesion online publications