Neural correlation via random connections.
A simple neural network is studied, which has sparse, random, plastic, excitatory connections and also feedback loops between sensory cells and correlator cells. Time is limited to several discrete instants, where firing is synchronous. For parameter values within biological ranges, the system exhibits a capacity for associative recall, with a controlled amount of extraneous firing, following Hebb-like synaptic changes.
Department of Mathematics, University of Wisconsin-Madison 53706, USA.
J
J
Chover
D000200:Action Potentials / Q000502:physiology; D000818:Animals; D003198:Computer Simulation; D003344:Cortical Synchronization; D005246:Feedback; D051379:Mice; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D009433:Neural Inhibition / Q000502:physiology; D009473:Neuronal Plasticity / Q000502:physiology*; D011336:Probability; D015203:Reproducibility of Results; D013269:Stochastic Processes