Biorealistic Hippocampal Modeling

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CARLsim is currently being used to simulate Izhikevich neuron models with electrophysiological characteristics emulating recorded cell types (see also SfN16 Presentation Number 639.27).

Summary

Poster Title: Biologically realistic spiking model of hippocampal circuitry for enhanced machine learning
Authors: David J. Hamilton, Diek W. Wheeler, Siva Venkadesh, Keivan Moradi, Christopher L. Rees, Giorgio A. Ascoli

The field of machine learning, which historically has utilized multilayered artificial neural networks and, more recently, “Deep Learning” to characterize large datasets, will benefit from exploiting specific organizational and functional principles garnered from hippocampal circuitry. Using knowledge available in Hippocampome.org, it is now possible to construct spiking neural network (SNN) models of the rodent hippocampus.

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