Statistical methods for dissecting interactions between brain areas. (December 2020)

• Record Type: Journal Article
• Authors: Semedo, João D; Gokcen, Evren; Machens, Christian K; Kohn, Adam; Yu, Byron M
• Is Part Of: Current opinion in neurobiology. Volume 65(2020)
• Page Start: 59
• Page End: 69
• Publication Date: 2020-12
• Subjects: Neurobiology -- Periodicals; 573.8
• DOI: 10.1016/j.conb.2020.09.009
• Languages: English
• ISSNs: 0959-4388

Abstract

Highlights: A fundamental question in neuroscience is how neuronal populations in different brain areas communicate. Multi-area neuronal population recordings are increasingly common. Multivariate methods are needed to interrogate these recordings and characterize how neuronal population activity is related across areas. We discuss interpretational challenges and considerations for these methods, and suggest directions for future work. Abstract : The brain is composed of many functionally distinct areas. This organization supports distributed processing, 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.