Associative memory models of hippocampal areas CA1 and CA3

Graham, Bruce P., Cutsuridis, Vassilis and Hunter, Russell (2010) Associative memory models of hippocampal areas CA1 and CA3. In: Hippocampal Microcircuits: A computational modeller's resource book. Springer Series in Computational Neuroscience (5). Springer, pp. 459-494. ISBN 9781441909954, 9781461425625


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The hippocampal regions CA3 and CA1 have long been proposed to be autoand
heteroassociative memories, respectively (Marr, 1971; McNaughton and Morris,
1987; Treves and Rolls, 1994), for the storage of declarative information. An
autoassociative memory is formed when a set of neurons are recurrently connected
by modifiable synapses, whereas a heteroassociative memory is formed
through modifiable connections from an input layer of neurons to an output layer.
Associative memory storage simply requires a Hebbian strengthening of connections
between neurons that are coactive (Amit, 1989; Hopfield, 1982; Willshaw
et al., 1969). Recall proceeds from a cue activity pattern across neurons that is
a partial or noisy version of a previously stored pattern. A suitable firing threshold
on each neuron that receives input from already active neurons ensures that
neural activity evolves towards the stored pattern. This may happen with only
one or two updates of each neuron’s activity. Accurate recall is obtainable provided
not too many patterns have been stored, otherwise recall is poor, or even
Network models of spiking neurons can be used to explore the dynamics of storage
and recall in such memory networks. Here we introduce a recurrent network
model based on hippocampal area CA3 and a feedforward network model for area
CA1. Cells are simplified compartmental models with complex ion channel dynamics.
In addition to pyramidal cells, one or more types of interneuron are present. We
investigate, in particular, the roles of these interneurons in setting the appropriate
threshold for memory recall.

Keywords:associative memory networks
Subjects:B Subjects allied to Medicine > B140 Neuroscience
Divisions:College of Science > School of Computer Science
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ID Code:28784
Deposited On:29 Sep 2017 09:04

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