Statistical methods for dissecting interactions between brain areas

João D. Semedo, Evren Gokcen, Christian K. Machens, Adam Kohn, Byron M. Yu

Research output: Contribution to journalReview articlepeer-review

1 Scopus citations

Abstract

The brain is composed of many functionally distinct areas. This organization supports distributed processing in the brain, and requires the coordination of signals across areas. Our understanding of how populations of neurons in different areas interact with each other is still in its infancy. As the availability of recordings from large populations of neurons across multiple brain areas increases, so does the need for statistical methods that are well suited for dissecting and interrogating these recordings. Here we review multivariate statistical methods that have been, or could be, applied to this class of recordings. By leveraging population responses, these methods can provide a rich description of inter-areal interactions. At the same time, these methods can introduce interpretational challenges. We thus conclude by discussing how to interpret the outputs of these methods to further our understanding of inter-areal interactions.

Original languageEnglish (US)
Pages (from-to)59-69
Number of pages11
JournalCurrent Opinion in Neurobiology
Volume65
DOIs
StatePublished - Dec 2020

ASJC Scopus subject areas

  • Neuroscience(all)

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