A General Hippocampal Computational Model Combining Episodic and Spatial Memory in a Spiking Model
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Date
06/2006Author
Aguiar, Paulo de Castro
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Abstract
The hippocampus, in humans and rats, plays crucial roles in spatial tasks and nonspatial
tasks involving episodic-type memory. This thesis presents a novel computational
model of the hippocampus (CA1, CA3 and dentate gyrus) which creates a framework
where spatial memory and episodic memory are explained together. This general
model follows the approach where the memory function of the rodent hippocampus is
seen as a “memory space” instead of a “spatial memory”.
The innovations of this novel model are centred around the fact that it follows detailed
hippocampal architecture constraints and uses spiking networks to represent all
hippocampal subfields. This hippocampal model does not require stable attractor states
to produce a robust memory system capable of pattern separation and pattern completion.
In this hippocampal theory, information is represented and processed in the form
of activity patterns. That is, instead of assuming firing-rate coding, this model assumes
that information is coded in the activation of specific constellations of neurons. This
coding mechanism, associated with the use of spiking neurons, raises many problems
on how information is transferred, processed and stored in the different hippocampal
subfields. This thesis explores which mechanisms are available in the hippocampus
to achieve such control, and produces a detailed model which is biologically realistic
and capable of explaining how several computational components can work together to
produce the emergent functional properties of the hippocampus. In this hippocampal
theory, precise explanations are given to why mossy fibres are important for storage
but not recall, what is the functional role of the mossy cells (excitatory interneurons)
in the dentate gyrus, why firing fields can be asymmetric with the firing peak closer to
the end of the field, which features are used to produce “place fields”, among others.
An important property of this hippocampal model is that the memory system provided
by the CA3 is a palimpsest memory: after saturation, the number of patterns that can
be recalled is independent of the number of patterns engraved in the recurrent network.
In parallel with the development of the hippocampal computational model, a simulation
environment was created. This simulation environment was tailored for the
needs and assumptions of the hippocampal model and represents an important component
of this thesis.