Inferring neural information flow from spiking data.

ABSTRACT: The brain can be regarded as an information processing system in which neurons store and propagate information about external stimuli and internal processes. Therefore, estimating interactions between neural activity at the cellular scale has significant implications in understanding how neuronal circuits encode and communicate information across brain areas to generate behavior. While the number of simultaneously recorded neurons is growing exponentially, current methods relying only on pairwise statistical dependencies still suffer from a number of conceptual and technical challenges that preclude experimental breakthroughs describing neural information flows. In this review, we examine the evolution of the field over the years, starting from descriptive statistics to model-based and mod

SUBMITTER: Tauste Campo A 

PROVIDER: S-EPMC7548302 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature