Logistic Patterning of Brain Activity

Abstract

Brain activity is a set of electrochemical events in the neural tissue during a specified period of time. Neural networks are the functionally connected and dynamically organized population of neurons and neuroglial cells, serving as a unified interface between environmental input and behavioral output at a specified time. They are patterned dynamically in neural space, time and intensity. It is proposed that 1. the electrophysiological patterning of brain activity follows the laws of logistic growth, decay and impulse response function and 2. that this process of logistic transform (LOGIT) of electrochemcial processes is itself the general code of information transfer in the brain. A mathematical model of logistic transformation and new electrophysiological data based on the topographic mapping of event-related potentials (ERP) during selective auditory attentional tasks from nine healthy adults is presented. The N100-P200 and the N200-P300 segments of ERP''s were analyzed at 20 ms intervals. Logarithmic latencies and voltages were highly correlated. Significant correlation was found between the mathematically estimated and actual values. The interpeak latencies also followed the logistic growth pattern and could be predicted by the model. A general equation of logistic transformation of brain activity, including variables of cortical voltage and frequency is proposed.