Learning and executing goal-directed choices by internally generated sequences in spiking neural circuits

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• dc.contributor.author Palmer, John R. B.
• dc.contributor.author Keane, Adam
• dc.contributor.author Gong, Pulin
• dc.date.accessioned 2025-03-03T07:27:48Z
• dc.date.available 2025-03-03T07:27:48Z
• dc.date.issued 2017
• dc.description.abstract Recent neural ensemble recordings have established a link between goal-directed spatial decision making and internally generated neural sequences in the hippocampus of rats. To elucidate the synaptic mechanisms of these sequences underlying spatial decision making processes, we develop and investigate a spiking neural circuit model endowed with a combination of two synaptic plasticity mechanisms including spike-timing dependent plasticity (STDP) and synaptic scaling. In this model, the interplay of the combined synaptic plasticity mechanisms and network dynamics gives rise to neural sequences which propagate ahead of the animals’ decision point to reach goal locations. The dynamical properties of these forward-sweeping sequences and the rates of correct binary choices executed by these sequences are quantitatively consistent with experimental observations; this consistency, however, is lost in our model when only one of STDP or synaptic scaling is included. We further demonstrate that such sequence-based decision making in our network model can adaptively respond to time-varying and probabilistic associations of cues and goal locations, and that our model performs as well as an optimal Kalman filter model. Our results thus suggest that the combination of plasticity phenomena on different timescales provides a candidate mechanism for forming internally generated neural sequences and for implementing adaptive spatial decision making.en
• dc.format.mimetype application/pdf
• dc.identifier.citation Palmer J, Keane A, Gong P. Learning and executing goal-directed choices by internally generated sequences in spiking neural circuits. PLoS Comput Biol. 2017 Jul 31;13(7):e1005669. DOI: 10.1371/journal.pcbi.1005669
• dc.identifier.doi http://dx.doi.org/10.1371/journal.pcbi.1005669
• dc.identifier.issn 1553-734X
• dc.identifier.uri http://hdl.handle.net/10230/69775
• dc.language.iso eng
• dc.publisher Public Library of Science (PLoS)
• dc.relation.ispartof PLoS Computational Biology. 2017 Jul 31;13(7):e1005669
• dc.rights © 2017 Palmer et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri http://creativecommons.org/licenses/by/4.0/
• dc.subject.other Neuronesca
• dc.subject.other Xarxes neuronals (Neurobiologia)ca
• dc.subject.other Circuit neuronalca
• dc.title Learning and executing goal-directed choices by internally generated sequences in spiking neural circuitsen
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion