AbstractWe investigate the phase space dynamics of local systems of biological neurons in order to deduce the salient computational characteristics of such systems. In this rst report, we develop an abstract physical system that models local systems of spiking biological neurons. The system is based on a limited set of realistic assumptions and in consequence accommodates a wide range of neuronal models. Simulations of the model demonstrate that the dynamical behavior of the system is akin to that observed in neurophysiological experiments. In an upcoming report, we shall demonstrate that the dynamics of the model exhibits the classic characteristics of a chaotic system, namely, contraction, expansion, and folding. We view this research as a rst step towards understanding the basis for symbolic computation in the brain.
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