Cortical spike multiplexing using gamma frequency latencies

The Poisson statistics of cortical action potentials has been seen as a basic model of signal representation and proposed as a method of communicating Bayesian statistics. However these views are increasingly difficult to integrate with spike timing signals in the gamma frequency spectrum. Dana Ballard and Ruahan Zhang showed in simulation that the two sets of observations can be reconciled if gamma frequency action potentials can be seen as a general purpose method of modulating fast communication in cortical networks that use phase delays as the communicated signal. Such a representation allows faster computation and much more compact representations than traditional Poisson spiking models. Poisson spike distributions can be understood as a correlate of the more basic gamma phase coding model that can mix several independent computations.