Journal of Computational Neuroscience 9, 171–185, 2000
c 2000 Kluwer Academic Publishers. Manufactured in The Netherlands.
The Autapse: A Simple Illustration of Short-Term Analog Memory
Storage by Tuned Synaptic Feedback
H. SEBASTIAN SEUNG
Brain and Cognitive Sciences Department, Massachusetts Institute of Technology, Cambridge, MA 02139;
Lucent Technologies, Bell Laboratories, Murray Hill, NJ 07974
[email protected]
DANIEL D. LEE, BEN Y. REIS AND DAVID W. TANK
Lucent Technologies, Bell Laboratories, Murray Hill, NJ 07974
Received May 20, 1999; Revised November 30, 1999; Accepted December 2, 1999
Action Editor: John Rinzel
Abstract.
According to a popular hypothesis, short-term memories are stored as persistent neural activity main-
tained by synaptic feedback loops. This hypothesis has been formulated mathematically in a number of recurrent
network models. Here we study an abstraction of these models, a single neuron with a synapse onto itself, or
autapse. This abstraction cannot simulate the way in which persistent activity patterns are distributed over neural
populations in the brain. However, with proper tuning of parameters, it does reproduce the continuously graded,
or analog, nature of many examples of persistent activity. The conditions for tuning are derived for the dynamics
of a conductance-based model neuron with a slow excitatory autapse. The derivation uses the method of averag-
ing to approximate the spiking model with a nonspiking, reduced model. Short-term analog memory storage is
possible if the reduced model is approximately linear and if its feedforward bias and autapse strength are precisely
tuned.
Keywords:
short-term memory, persistent neural activity, synaptic feedback, reverberating circuit
1.
Introduction
In parts of the central nervous system ranging from
the spinal cord (Prut and Fetz, 1999) to the neocortex
(Fuster, 1995), transient inputs have been observed to
cause persistent changes in the rate of action poten-
tial firing. By now, there is no doubt that this general
phenomenon is closely related to short-term memory,
but its physiological mechanisms remain unknown.
According to one long-standing hypothesis, persis-
tent neural activity is maintained by synaptic feed-
back loops (Lorente de No, 1933; Hebb, 1949; Amit,
1995). This hypothesis has found precise mathematical
formulation in a number of recurrent network mod-
els (Cannon et al., 1983; Seung, 1996; Georgopoulos
et al., 1993; Zipser et al., 1993; Griniasty et al., 1993;
Amit et al., 1994; Zhang, 1996; Camperi and Wang,
1998). Not only do these models maintain persistent
activity patterns, but they also reproduce the experi-
mentally observed ways in which neural firing rates
encode computational variables.
In this article we analyze an abstraction of these re-
current network models: a single neuron that makes
a synapse onto itself, or autapse. In this model, feed-
back is localized to a single loop, rather than distributed
over a complex web of connections. This simplification
This
preview
has intentionally blurred sections.
Sign up to view the full version.
172
Seung et al.

This is the end of the preview.
Sign up
to
access the rest of the document.
- Fall '09
- Autapse, analog memory storage
-
Click to edit the document details