Time Intervals Comparing Neural Network.
The proposed neuronal network model consisting of several tens of neuron-like elements with graded responses performs a continual analysis of differences (> 25 ms) in time intervals between successive input signals. The network comprises the following building blocks: clock, pattern developing modules, dynamic memory units, coincidence detectors, identifiers. Two types of network organization were developed: one with a loop of modules and another one with a cascade of modules. The activity of the proposed "neuronal" assembly can be channeled to different outputs-depending on whether the stimulus presentation is regular or random. The described computation mechanism can be involved in various time-dependent brain functions. Copyright 1996 Elsevier Science Ltd