R. Ritz, W. Gerstner, U. Fuentes, and J. L. van Hemmen.
A biologically motivated and analytically soluble model of collective
oscillations in the cortex: II. Application to binding and pattern
segmentation.
Biol. Cybern., 71:349-358, 1994.
Abstract
Feature linking and pattern separation are shown to be performed as simultaneous processes by a highly connected auto-associative network of spiking neurons (Spike Response Model). In principle, many (e.g., with 9) patterns can be separated, but with a biological set of parameters the number is limited to four. The patterns have been learned by an asymmetric Hebbian rule that can handle a low activity which may vary from pattern to pattern (in a range between 4 and 7%). Spikes are generated by a threshold process and - with some delay - transmitted to postsynaptic neurons. Here they evoke an excitatory or inhibitory postsynaptic potential (EPSP or IPSP). Spike emission is followed by an absolute refractory period (1ms) and activates an inhibitory delay loop that prevents continuous firing. Three different network topologies are discussed, i.e., a structureless fully connected system, a network composed of two `hemispheres', and finally a hierarchical network with four subsystems that represent different `functions' and interact via feedforward and feedback connections. Functional feedback turns out to be essential for context-sensitive binding. The coherence between the two hemispheres is dependent on the inter-hemispheric delays. If these are on the average too large, the two hemispheres oscillate coherently by themselves but phase-shifted by half of the period with respect to each other.