EFFECTS OF FEATURES OF GK+(A) ON RETRIEVAL IN AUTOASSOCIATIVE NETWORKS

Features of a voltage- and time-dependent potassium conductance, gK + (A), were incorporated into the neuronal response function of auto-associative, attractor neural networks. Simulations showed that an increase in the magnitude of gK + (A) decreased the rate of convergence to equilibria and could markedly change the probability that the final equilibrium state of the network would most highly correlate with a stationary stimulus embedded in noise. These results may provide a framework for evaluating the functional roles of the many agents which modulate gK + (A).