Matches in SemOpenAlex for { <https://semopenalex.org/work/W2109203825> ?p ?o ?g. }
- W2109203825 endingPage "657" @default.
- W2109203825 startingPage "647" @default.
- W2109203825 abstract "•Several brain areas display sequences of neural activity generated on the basis of internal dynamics. •These sequences occur in brain areas implicated in memory and goal-directed behavior. •Such sequences can contribute to internal simulation and recombination of information. •Data as well as computational models suggest these sequences are instrumental for on-line choice and learning. •These models use sequences to infer future events and plan actions from previously acquired knowledge. A network of brain structures including hippocampus (HC), prefrontal cortex, and striatum controls goal-directed behavior and decision making. However, the neural mechanisms underlying these functions are unknown. Here, we review the role of ‘internally generated sequences’: structured, multi-neuron firing patterns in the network that are not confined to signaling the current state or location of an agent, but are generated on the basis of internal brain dynamics. Neurophysiological studies suggest that such sequences fulfill functions in memory consolidation, augmentation of representations, internal simulation, and recombination of acquired information. Using computational modeling, we propose that internally generated sequences may be productively considered a component of goal-directed decision systems, implementing a sampling-based inference engine that optimizes goal acquisition at multiple timescales of on-line choice, action control, and learning. A network of brain structures including hippocampus (HC), prefrontal cortex, and striatum controls goal-directed behavior and decision making. However, the neural mechanisms underlying these functions are unknown. Here, we review the role of ‘internally generated sequences’: structured, multi-neuron firing patterns in the network that are not confined to signaling the current state or location of an agent, but are generated on the basis of internal brain dynamics. Neurophysiological studies suggest that such sequences fulfill functions in memory consolidation, augmentation of representations, internal simulation, and recombination of acquired information. Using computational modeling, we propose that internally generated sequences may be productively considered a component of goal-directed decision systems, implementing a sampling-based inference engine that optimizes goal acquisition at multiple timescales of on-line choice, action control, and learning." @default.
- W2109203825 created "2016-06-24" @default.
- W2109203825 creator A5051130900 @default.
- W2109203825 creator A5053290697 @default.
- W2109203825 creator A5080548625 @default.
- W2109203825 creator A5082482795 @default.
- W2109203825 date "2014-12-01" @default.
- W2109203825 modified "2023-10-16" @default.
- W2109203825 title "Internally generated sequences in learning and executing goal-directed behavior" @default.
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