Spontaneously emerging internal models of visual sequences combine abstract and event-specific information in the prefrontal cortex

When exposed to sensory sequences, do macaque monkeys spontaneously form abstract internal models that generalize to novel experiences? Here, we show that neuronal populations in macaque ventrolateral prefrontal cortex jointly encode visual sequences by separate codes for the specific pictures prese...

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Veröffentlicht in:Cell reports (Cambridge) 2024-03, Vol.43 (3), p.113952-113952, Article 113952
Hauptverfasser: Bellet, Marie E., Gay, Marion, Bellet, Joachim, Jarraya, Bechir, Dehaene, Stanislas, van Kerkoerle, Timo, Panagiotaropoulos, Theofanis I.
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Sprache:eng
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Zusammenfassung:When exposed to sensory sequences, do macaque monkeys spontaneously form abstract internal models that generalize to novel experiences? Here, we show that neuronal populations in macaque ventrolateral prefrontal cortex jointly encode visual sequences by separate codes for the specific pictures presented and for their abstract sequential structure. We recorded prefrontal neurons while macaque monkeys passively viewed visual sequences and sequence mismatches in the local-global paradigm. Even without any overt task or response requirements, prefrontal populations spontaneously form representations of sequence structure, serial order, and image identity within distinct but superimposed neuronal subspaces. Representations of sequence structure rapidly update following single exposure to a mismatch sequence, while distinct populations represent mismatches for sequences of different complexity. Finally, those representations generalize across sequences following the same repetition structure but comprising different images. These results suggest that prefrontal populations spontaneously encode rich internal models of visual sequences reflecting both content-specific and abstract information. [Display omitted] •Prefrontal populations recorded during a no-report local-global paradigm of visual sequences•Structure, identity, and prediction errors decoded from superimposed population subspaces•Rapid update of sequence-structure representations following exposure to a mismatch sequence•Generalization of sequence structure and prediction error representations Bellet et al. show that neuronal populations in the prefrontal cortex spontaneously form rich internal models that represent abstract and identity-specific information of visual sequences with different complexity. These models, detected in superimposed population subspaces, rapidly update after presentation of mismatch sequences and generalize to sequences with identical structure.
ISSN:2211-1247
2211-1247
DOI:10.1016/j.celrep.2024.113952