Cortical areas interact through a communication subspace

By João Dias Semedo, Amin Zandvakili, Christian K. Machens, Byron M. Yu, Adam Kohn. Neuron, 2019

387 citations recorded by the source corpus.

Summary Most brain functions involve interactions among multiple, distinct areas or nuclei. For instance, visual processing in primates requires the appropriate relaying of signals across many distinct cortical areas. Yet our understanding of how populations of neurons in interconnected brain areas communicate is in its infancy. Here we investigate how trial-to-trial fluctuations of population responses in primary visual cortex (V1) are related to simultaneously-recorded population responses in area V2. Using dimensionality reduction methods, we find that V1-V2 interactions occur through a communication subspace: V2 fluctuations are related to a small subset of V1 population activity patterns, distinct from the largest fluctuations shared among neurons within V1. In contrast, interactions between subpopulations within V1 are less selective. We propose that the communication subspace may be a general, population-level mechanism by which activity can be selectively routed across brain areas.

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/cb884984245983dafe92b977b39f39c71a6a46f4

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In Cellular and Molecular Neuroscience

In Cognitive Neuroscience

In Statistical and Nonlinear Physics

Citations in the corpus

Interpreting neural computations by examining intrinsic and embedding dimensionality of neural activity (2021, background): “Similar principles might govern interactions across cortical areas, by confining to orthogonal subspaces information that is private to an area and information that is communicated [57,58].”
Computation Through Neural Population Dynamics (2020, positive): “Sheahan et al. (2016) developed a two-sequence task where planning and execution could be separated.”
The representation of abstract goals in working memory is supported by task-congruent neural geometry (2024, unknown): “…geometry can remain stable when underlying single-neuron activities change [38], one benefit of forming task-con-gruent, low-dimensional geometry of task information could be that the stable geometry facilitates information relay between cortical regions through communication subspaces [28,29].”
Cognition is an emergent property (2024, unknown): “This has been interpreted to mean that only a restricted subspace of population activity in one area, a ‘communication sub-space’, drives activity in another [44,45].”