Measuring shared responses across subjects using intersubject correlation

Samuel A Nastase, Valeria Gazzola, Uri Hasson, Christian Keysers

Research output: Contribution to journal/periodicalArticleScientificpeer-review

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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.

Original languageEnglish
Pages (from-to)667-685
JournalSocial Cognitive and Affective Neuroscience
Publication statusPublished - 16 Mar 2019

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