Shifts in attention drive context-dependent subspace encoding in anterior cingulate cortex in mice during decision making

Autor: Márton Albert Hajnal, Duy Tran, Zsombor Szabó, Andrea Albert, Karen Safaryan, Michael Einstein, Mauricio Vallejo Martelo, Pierre-Olivier Polack, Peyman Golshani, Gergő Orbán
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Nature Communications, Vol 15, Iss 1, Pp 1-17 (2024)
Druh dokumentu: article
ISSN: 2041-1723
DOI: 10.1038/s41467-024-49845-2
Popis: Abstract Attention supports decision making by selecting the features that are relevant for decisions. Selective enhancement of the relevant features and inhibition of distractors has been proposed as potential neural mechanisms driving this selection process. Yet, how attention operates when relevance cannot be directly determined, and the attention signal needs to be internally constructed is less understood. Here we recorded from populations of neurons in the anterior cingulate cortex (ACC) of mice in an attention-shifting task where relevance of stimulus modalities changed across blocks of trials. In contrast with V1 recordings, decoding of the irrelevant modality gradually declined in ACC after an initial transient. Our analytical proof and a recurrent neural network model of the task revealed mutually inhibiting connections that produced context-gated suppression as observed in mice. Using this RNN model we predicted a correlation between contextual modulation of individual neurons and their stimulus drive, which we confirmed in ACC but not in V1.
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