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Rapid learning of predictive maps with STDP and theta phase precession

George, Tom M; de Cothi, William; Stachenfeld, Kimberly L; Barry, Caswell; (2023) Rapid learning of predictive maps with STDP and theta phase precession. eLife , 12 , Article e80663. 10.7554/eLife.80663. Green open access

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Abstract

The predictive map hypothesis is a promising candidate principle for hippocampal function. A favoured formalisation of this hypothesis, called the successor representation, proposes that each place cell encodes the expected state occupancy of its target location in the near future. This predictive framework is supported by behavioural as well as electrophysiological evidence and has desirable consequences for both the generalisability and efficiency of reinforcement learning algorithms. However, it is unclear how the successor representation might be learnt in the brain. Error-driven temporal difference learning, commonly used to learn successor representations in artificial agents, is not known to be implemented in hippocampal networks. Instead, we demonstrate that spike-timing dependent plasticity (STDP), a form of Hebbian learning, acting on temporally compressed trajectories known as 'theta sweeps', is sufficient to rapidly learn a close approximation to the successor representation. The model is biologically plausible - it uses spiking neurons modulated by theta-band oscillations, diffuse and overlapping place cell-like state representations, and experimentally matched parameters. We show how this model maps onto known aspects of hippocampal circuitry and explains substantial variance in the temporal difference successor matrix, consequently giving rise to place cells that demonstrate experimentally observed successor representation-related phenomena including backwards expansion on a 1D track and elongation near walls in 2D. Finally, our model provides insight into the observed topographical ordering of place field sizes along the dorsal-ventral axis by showing this is necessary to prevent the detrimental mixing of larger place fields, which encode longer timescale successor representations, with more fine-grained predictions of spatial location.

Type: Article
Title: Rapid learning of predictive maps with STDP and theta phase precession
Location: England
Open access status: An open access version is available from UCL Discovery
DOI: 10.7554/eLife.80663
Publisher version: https://doi.org/10.7554/eLife.80663
Language: English
Additional information: © 2023, George, de Cothi et al. This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.
Keywords: STDP, hippocampus, neuroscience, none, phase precession, place cells, successor representations, theta, Neurons, Hippocampus, Reinforcement, Psychology, Behavior Therapy, Algorithms, Theta Rhythm, Models, Neurological, Action Potentials
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences > Cell and Developmental Biology
URI: https://discovery.ucl.ac.uk/id/eprint/10167004
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