Neural network model of forward shift of CA1 place fields towards reward location

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Abstract

In a recent experimental paper I. Lee et al. [1] showed that the firing patterns of CA1 complex-spike neurons gradually shifted forward across trials toward prospective goal locations within a recording session over multiple trials. Here we propose a simple model of this result based on the phenomenon of awake sequence reverse replay [2] which occurs when the animal pauses at the reward location. The model is based on the CA3-CA1 anatomy with modulation of CA3-CA1 synaptic plasticity by feedback from CA3 projecting CA1 interneurons. Sequence replays, which are generated in CA3 by removal of septal inhibition on CA1 interneurons, are recoded into the synaptic weights of individual CA1 cells. This produces spatially extended CA1 firing fields, whose response provides a value function on experienced paths towards goal locations. Simulations show that the CA1 firing fields show positive movement in center of mass towards reward locations over many trials with negative shift in first few trials, and development of positive skew. © 2008 Springer-Verlag Berlin Heidelberg.

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APA

Ponzi, A. (2008). Neural network model of forward shift of CA1 place fields towards reward location. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4984 LNCS, pp. 309–316). https://doi.org/10.1007/978-3-540-69158-7_33

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