Monthly
288 pp. per issue
6 x 9, illustrated
ISSN
0899-7667
E-ISSN
1530-888X
2014 Impact factor:
2.21

Neural Computation

Fall 1990, Vol. 2, No. 3, Pages 334-354
(doi: 10.1162/neco.1990.2.3.334)
© 1990 Massachusetts Institute of Technology
Spontaneous Development of Modularity in Simple Cortical Models
Article PDF (1.95 MB)
Abstract

The existence of modular structures in the organization of nervous systems (e.g., cortical columns, patches of neostriatum, and olfactory glomeruli) is well known. However, the detailed dynamic mechanisms by which such structures develop remain a mystery. We propose a mechanism for the formation of modular structures that utilizes a combination of intrinsic network dynamics and Hebbian learning. Specifically, we show that under certain conditions, layered networks can support spontaneous localized activity patterns, which we call collective excitations, even in the absence of localized or spatially correlated afferent stimulation. These collective excitations can then induce the formation of modular structures in both the afferent and lateral connections via a Hebbian learning mechanism. The networks we consider are spatially homogeneous before learning, but the spontaneous emergence of localized collective excitations and the consequent development of modules in the connection patterns break translational symmetry. The essential conditions required to support collective excitations include internal units with sufficiently high gains and certain patterns of lateral connectivity. Our proposed mechanism is likely to play a role in understanding more complex (and more biologically realistic) systems.