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Multiple Temporal and Object-Based Strategies Across Learning for a Selective Detection Task in Mice.
Marrero, Krista; Aruljothi, Krithiga; Zareian, Behzad; Zhang, Zhaoran; Zagha, Edward.
Afiliação
  • Marrero K; University of California, Riverside.
  • Aruljothi K; University of California, Riverside.
  • Zareian B; University of California Riverside.
  • Zhang Z; University of California, Riverside.
  • Zagha E; University of California Riverside.
bioRxiv ; 2023 Feb 14.
Article em En | MEDLINE | ID: mdl-36824924
Goal-directed behavior paradigms inevitably involve temporal processes, such as anticipation, expectation, timing, waiting, and withholding. And yet, amongst the vast use of object-based task paradigms, characterizations of temporal features are often neglected. Here, we longitudinally analyzed mice from naïve to expert performance in a somatosensory selective detection task. In addition to tracking standard measures from signal detection theory, we also characterized learning of temporal features. We find that mice transition from general sampling strategies to stimulus detection and stimulus discrimination. During these transitions, mice learn to wait as they anticipate an expected stimulus presentation and to time their response after a stimulus presentation. By establishing and implementing standardized measures, we show that the development of waiting and timing in the task overlaps with learning of stimulus detection and discrimination. We also investigated sex differences in temporal and object-based trajectories of learning, finding that males learn strategies idiosyncratically and that females learn strategies more sequentially and stereotypically. Overall, our findings emphasize multiple temporal strategies in learning for an object-based task and highlight the importance of considering diverse temporal and object-based features when characterizing behavioral and neuronal aspects of learning.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article