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• W3001941051 abstract "Natural animal behavior displays rich lexical and temporal dynamics, even in a stable environment. This implies that behavioral variability arises from sources within the brain, but the origin and mechanics of these processes remain largely unknown. Here, we focus on the observation that the timing of self-initiated actions shows large variability even when they are executed in stable, well-learned sequences. Could this mix of reliability and stochasticity arise within the same circuit? We trained rats to perform a stereotyped sequence of self-initiated actions and recorded neural ensemble activity in secondary motor cortex (M2), which is known to reflect trial-by-trial action timing fluctuations. Using hidden Markov models we established a robust and accurate dictionary between ensemble activity patterns and actions. We then showed that metastable attractors, representing activity patterns with the requisite combination of reliable sequential structure and high transition timing variability, could be produced by reciprocally coupling a high dimensional recurrent network and a low dimensional feedforward one. Transitions between attractors were generated by correlated variability arising from the feedback loop between the two networks. This mechanism predicted a specific structure of low-dimensional noise correlations that were empirically verified in M2 ensemble dynamics. This work suggests a robust network motif as a novel mechanism to support critical aspects of animal behavior and establishes a framework for investigating its circuit origins via correlated variability." @default.
• W3001941051 created "2020-01-30" @default.
• W3001941051 creator A5012600410 @default.
• W3001941051 creator A5043975940 @default.
• W3001941051 creator A5056428592 @default.
• W3001941051 creator A5063189344 @default.
• W3001941051 creator A5069334616 @default.
• W3001941051 date "2020-01-27" @default.
• W3001941051 modified "2023-09-23" @default.
• W3001941051 title "Metastable attractors explain the variable timing of stable behavioral action sequences" @default.
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