Computational Models of Encoding and Replay of Sequences in the Hippocampus
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2019-08-01
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en
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Abstract
Place cells in the rodent hippocampus display various electrophysiological phenomena
such as non-local replay sequences and phase precession that are widely studied
for their role in navigation and spatial memory consolidation. Distinct patterns
of activation are observed during locomotion and during resting periods that give
rise to phase precession and replays respectively. To investigate the mechanisms
through which these two different phenomena could arise within the same network,
Romani and Tsodyks developed a computational firing rate model of place cells in
the rodent CA3 hippocampal subfield in their 2015 study. In this model, simple
internal dynamics combined with a pre-defined and fixed connectivity structure
resulted in both non-local sequences and phase precession. For this thesis I first
replicated and then elaborated on some of these findings by creating a flexible
toolbox, where a synaptic learning rule is implemented to obtain the connectivity
structure through an exploration trial instead. I found that during resting periods,
the network exhibited very structured and consistent non-local sequences throughout
the spontaneous activity, showing that replay-like events can indeed arise from
a simple dynamical model featuring a learned connectivity matrix.
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Faculteit der Sociale Wetenschappen