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In this paper a theoretical model of functioning of a neural circuit during abehavioral response has been proposed. A neural circuit can be thought of as adirected multigraph whose each vertex is a neuron and each edge is a synapse.It has been assumed in this paper that the behavior of such circuits ismanifested through the collective behavior of neurons belonging to thatcircuit. Behavioral information of each neuron is contained in the coefficientsof the fast Fourier transform (FFT) over the output spike train. Thosecoefficients form a vector in a multidimensional vector space. Behavioraldynamics of a neuronal network in response to strong aversive stimuli has beenstudied in a vector space in which a suitable pseudometric has been defined.The neurodynamical model of network behavior has been formulated in terms ofexisting memory, synaptic plasticity and feelings. The model has an analogy inclassical electrostatics, by which the notion of force and potential energy hasbeen introduced. Since the model takes input from each neuron in a network andproduces a behavior as the output, it would be extremely difficult or may evenbe impossible to implement. But with the help of the model a possibleexplanation for an hitherto unexplained neurological observation in human brainhas been offered. The model is compatible with a recent model of sequentialbehavioral dynamics. The model is based on electrophysiology, but its relevanceto hemodynamics has been outlined.

Behavioral response to strong aversive stimuli: A neurodynamical model