Concurrent parallel-sequential processing in gamma controlled cortical-type networks of spiking neurones
In sensory recognition, rapid activation of an initial hypothesis based on few but reliably detected features, and the discrimination of the object by refined analysis of the sensory input are two conflicting requirements. We show that these two aspects of sensory recognition can be optimally served by a neocortical firmware model, the stereotypically structured columnar architecture, and that the resulting ensemble temporal encoding performed by such a modular unit enables both rapid and robust recognition by utilisation of the dimension of time to encode the reliability of a decision. The model suggests a novel functional interpretation of gamma oscillations in cortical processing.
KeywordsInitial Hypothesis Partial Match Gamma Oscillation Columnar Module Spike Sequence
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