Computational
Neuroscience: Trends in Research, 1998. New York: Plenum Press, pp. 465-470.
Attractor
Dynamics in Realistic Hippocampal Networks
Elliot
D. Menschik1,2, Shih-Cheng Yen3, and Leif H. Finkel2,3
1Medical
Scientist Training Program
2Institute of Neurological Sciences
3Department of Bioengineering
3320 Smith Walk, 301 Hayden Hall
University of Pennsylvania
Philadelphia, PA 19104, U. S. A.
menschik@neuroengineering.upenn.edu
syen@neuroengineering.upenn.edu
leif@neuroengineering.upenn.edu
Abstract
Attractor-based
networks offer a powerful paradigm for the storage and recall of memory. However,
as traditionally formulated (Hopfield, 1982; Amit, 1989) with abstracted neurons,
these networks bear only an indirect relation to actual hippocampal and neocortical
networks. Here we present an attractor network instantiated in a detailed biophysical-level
model of the CA3 region of the hippocampus, simulated using GENESIS. The network
is comprised of the 66-compartment pyramidal cells and 51-compartment interneurons
of Traub and colleagues (Traub et al., 1994; Traub and Miles, 1995) and takes
advantage of the mechanism of pyramidal cell synchrony imposed by networks of
interneurons oscillating in the gamma range (Traub et al., 1996b; Wang and Buzsaki,
1996; Bush and Sejnowski, 1996). We demonstrate that such a network rapidly
converges to stored memory states (metastable attractors) and has interesting
temporal dynamics that arise from the interplay of AMPA, NMDA, and GABAA
synapses (particularly as influenced by neuromodulators) and our studies suggest
that a cellular-level model of CA3 can exhibit functional-level properties.