The Multi-Biophysical Nature of Computation in Brain Neural Networks

Comprehending the nature of nerve communication is fundamental to our understanding of the functioning of nervous systems in general. The ionic mechanisms underlying action potentials in the squid giant axon were first described by Hodgkin and Huxley in 1952, and their findings have formed our orthodox view of how the physiological action potential functions. However, substantial evidence has now accumulated to show that the action potential is accompanied by a synchronized coupled soliton pressure pulse in the cell membrane, the action potential pulse (APPulse), which we have recently shown to have an essential function in computation. Computational models of the action potential usually describe it as a binary event. Still, we have shown that it must be a quantum ternary event known as the computational action potential, whose temporal fixed point is the threshold of the soliton, rather than the plastic action potential peak used in other models to facilitate meaningful computation. Here we argue that for computation to occur in neurons, it must do so at the location of convergences of neurons by frequency modulated quantum interference. The timing of frequency changes indicates that the threshold must activate in less than 10-6 s, much faster than that of synapses. APPulse in a brain neural network collide according to the latencies of the neurons and the distinct frequency patterns. Here, we review the interactions between the soliton and the ionic mechanisms known to be associated with the action potential. Elsewhere, we have demonstrated this type of frequency computation for the retina, in detail, and also provided an extensive analysis for computation for other brain neural networks. However, while the physiological action potential is important for neural connectivity, it is irrelevant to computational processes as the soliton part of the APPulse always facilitates this for computational timing and effectiveness.