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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

A model for the peak-interval task based on neural oscillation-delimited states

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Autor(es):
Varella, Thiago T. [1, 2] ; Reyes, Marcelo Bussotti [3] ; Caetano, Marcelo S. [3, 4] ; de Camargo, Raphael Y. [3]
Número total de Autores: 4
Afiliação do(s) autor(es):
[1] Princeton Univ, Dept Psychol, Princeton, NJ 08544 - USA
[2] Univ Sao Paulo, Mol Sci Program, Sao Paulo, SP - Brazil
[3] Univ Fed ABC, Ctr Math Comp & Cognit, Sao Bernardo Do Campo, SP - Brazil
[4] Inst Nacl Ciencia & Tecnol Comportamento Cognicao, Sao Carlos - Brazil
Número total de Afiliações: 4
Tipo de documento: Artigo Científico
Fonte: Behavioural Processes; v. 168, NOV 2019.
Citações Web of Science: 0
Resumo

Specific mechanisms underlying how the brain keeps track of time are largely unknown. Several existing computational models of timing reproduce behavioral results obtained with experimental psychophysical tasks, but only a few tackle the underlying biological mechanisms, such as the synchronized neural activity that occurs throughout brain areas. In this paper, we introduce a model for the peak-interval task based on neuronal network properties. We consider that Local Field Potential (LFP) oscillation cycles specify a sequence of states, represented as neuronal ensembles. Repeated presentation of time intervals during training reinforces the connections of specific ensembles to downstream networks - sets of neurons connected to the sequence of states. Later, during the peak-interval procedure, these downstream networks are reactivated by previously experienced neuronal ensembles, triggering behavioral responses at the learned time intervals. The model reproduces experimental response patterns from individual rats in the peak-interval procedure, satisfying relevant properties such as the Weber law. Finally, we provide a biological interpretation of the parameters of the model. (AU)

Processo FAPESP: 16/19691-1 - Adequação de um modelo de dinâmica neural às propriedades neurofisiológicas da percepção temporal
Beneficiário:Thiago Tarraf Varella
Modalidade de apoio: Bolsas no Brasil - Iniciação Científica