On looking for neural networks and “cell assemblies” that underlie behavior: I. A mathematical model

Abstract

A list of important features of animal behavior related primarily to learning has suggested to many investigators that an important aspect of brain function is the establishment or modification of functional connections between neural elements. In this paper a considerably, more inclusive list of behavioral features suggests that another important aspect may be the utilization of patterns of activity constituting the resonant responses of linear networks in the brain. To account for the longer list on the basis of connections requires additional assumptions, while both lists follow immediately from the second mechanism. An input locus may become functionally connected to a particular response mode by firing at a frequency which comes to approach the resonant frequency of that mode. The information in a complicated “cell assembly” of the type considered could be transmitted through a nerve tract by a very simple frequency code. One neurological guess is that frequency-coded inputs excite the transients in dedritic networks. It the amplititude of the pattern becomes large, as it would near, resonance, the all-or-none axonal response would become excited. This axonal response would tend to augment resonant patterns and disrupt other patterns, for a reasonal inherent in any linear network. It is shown how the mechanism might be related to the list of important behavioral features, and a numerical illustration is provided. Since this mechanism is automatically present in any linear network, unless special processes suppress it, it must have led to overt hehavior in any animal, possessing such networks. Evolution either suppressed this feature or exploited it. Since its properties resemble those of animal behavior, the latter might be suspected.