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Mice make temporal inferences about novel locations based on previously learned spatiotemporal contingencies.
Gür, Ezgi; Duyan, Yalçin A; Balci, Fuat.
Afiliación
  • Gür E; Department of Biological Sciences, University of Manitoba, 50 Sifton Road, Room 222, Winnipeg, R3T 2M5, Canada.
  • Duyan YA; Department of Psychology, Koç University, Istanbul, Turkey.
  • Balci F; Department of Psychology, Koç University, Istanbul, Turkey.
Anim Cogn ; 26(3): 771-779, 2023 Jun.
Article en En | MEDLINE | ID: mdl-36394657
ABSTRACT
Animals learn multiple spatiotemporal contingencies and organize their anticipatory responses accordingly. The representational/computational capacity that underlies such spatiotemporally guided behaviors is not fully understood. To this end, we investigated whether mice make temporal inferences of novel locations based on previously learned spatiotemporal contingencies. We trained 18 C57BL/6J mice to anticipate reward after three different intervals at three different locations and tested their temporal expectations of a reward at five locations simultaneously, including two locations that were not previously associated with reward delivery but adjacent to the previously trained locations. If mice made spatiotemporal inferences, they were expected to interpolate between duration pairs associated with previously reinforced hoppers surrounding the novel hopper. We found that the maximal response rate at the novel locations indeed fell between the two intervals reinforced at the surrounding hoppers. We argue that this pattern of responding might be underlain by spatially constrained Bayesian computations.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Recompensa / Aprendizaje Límite: Animals Idioma: En Revista: Anim Cogn Asunto de la revista: MEDICINA VETERINARIA Año: 2023 Tipo del documento: Article País de afiliación: Canadá

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Recompensa / Aprendizaje Límite: Animals Idioma: En Revista: Anim Cogn Asunto de la revista: MEDICINA VETERINARIA Año: 2023 Tipo del documento: Article País de afiliación: Canadá