Continuous multiplexed population representations of task context in the mouse primary visual cortex

Márton Albert Hajnal, Duy Tran, Michael Einstein, Mauricio Vallejo Martelo, Karen Safaryan, Pierre-Olivier Polack, Peyman Golshani () and Gergő Orbán ()
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Márton Albert Hajnal: Wigner Research Center for Physics
Duy Tran: University of California, Los Angeles
Michael Einstein: University of California, Los Angeles
Mauricio Vallejo Martelo: University of California, Los Angeles
Karen Safaryan: University of California, Los Angeles
Pierre-Olivier Polack: Rutgers University
Peyman Golshani: University of California, Los Angeles
Gergő Orbán: Wigner Research Center for Physics

Nature Communications, 2023, vol. 14, issue 1, 1-20

Abstract: Abstract Effective task execution requires the representation of multiple task-related variables that determine how stimuli lead to correct responses. Even the primary visual cortex (V1) represents other task-related variables such as expectations, choice, and context. However, it is unclear how V1 can flexibly accommodate these variables without interfering with visual representations. We trained mice on a context-switching cross-modal decision task, where performance depends on inferring task context. We found that the context signal that emerged in V1 was behaviorally relevant as it strongly covaried with performance, independent from movement. Importantly, this signal was integrated into V1 representation by multiplexing visual and context signals into orthogonal subspaces. In addition, auditory and choice signals were also multiplexed as these signals were orthogonal to the context representation. Thus, multiplexing allows V1 to integrate visual inputs with other sensory modalities and cognitive variables to avoid interference with the visual representation while ensuring the maintenance of task-relevant variables.

Date: 2023
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DOI: 10.1038/s41467-023-42441-w

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