A neural network with multiple hysteresis capabilities for short-term visual memory (STVM)

A dynamic neural network, called the positive-negative (PN) neural processor, with individual neural computing units that exhibit multiple hysteresis phenomena is proposed as a plausible mechanism for the replication of certain aspects of short-term visual memory. The basic premise of the neural network model is that the cortical nervous tissue is fundamentally two-dimensional in structure. Short-term visual memory results from the immense feedback amongst the radially and laterally distributed subpopulations in the two-dimensional layer. The basic computing unit for describing the computational operations is, therefore, the neural activity generated by a particular positive or negative influencing subpopulation. STVM is defined as states of activity that persist following the removal of a visual stimulus. Once stabilized, the PN neural processor response remains unperturbed by a weak or familiar stimulus