| | |
Summary: DECODING NEURONAL FIRING
AND
MODELING NEURAL NETWORKS
L.F. Abbott
Center for Complex Systems
Brandeis University
Waltham, MA 02254
Published in Quart. Rev. Biophys. 27:291-331 (1994).
1. Introduction
Biological neural networks are large systems of complex elements interacting through
a complex array of connections. Individual neurons express a large number of active con-
ductances (Connors et al., 1982; Adams & Gavin, 1986; LlinŽas, 1988; McCormick, 1990;
Hille, 1992) and exhibit a wide variety of dynamic behaviors on time scales ranging from
milliseconds to many minutes (LlinŽas, 1988; Harris-Warrick & Marder, 1991; Churchland &
Sejnowski, 1992; Turrigiano et al., 1994). Neurons in cortical circuits are typically coupled
to thousands of other neurons (Stevens, 1989) and very little is known about the strengths
of these synapses (although see Rosenmund et al., 1993; Hessler et al., 1993; Smetters &
Nelson, 1993). The complex firing patterns of large neuronal populations are difficult to
describe let alone understand. There is little point in accurately modeling each membrane
potential in a large neural circuit unless we have an effective method for interpreting (or
|
