Local adaptations of two naturally occurring neuronal conductances, gK + (A) and gK + (Ca), allow for associative conditioning and contiguity judgements in artificial neural networks.

Features of two potassium conductances implicated in the acquisition of conditioned reflexes, the slow calcium dependent conductance (gK + (Ca] and the fast transient conductance (gK + (A], were incorporated into a 6 x 6 element artificial neural network. Adaptive algorithms derived from observations of cortical neurons during associative learning changed gK + (A) in proportion to the product of this current and an EPSP-induced second messenger concentration, and changed gK + (Ca) as a function of a spike-induced second messenger concentration. This network concurrently acquired two distinct representations in response to presentation of stimuli: one resembled associative conditioning (defined in terms of its sensitivity to forward pairing vs. simultaneous or backward pairing); the other reflected contiguous pairings of stimuli. The acquisition of one representation did not markedly interfere with acquisition of the other. This network may accordingly serve as an example of a self-organizing system which minimizes the postulated inherent cross talk between functionally dissiminar representations (Minsky and Papert 1988).