A computer algorithm for spatio-temporal patterns in interactive neuron populations.
A computer algorithm has been developed which enables numerical computations to be performed for interactive neuron populations whose spatio-temporal behaviors are represented by a set of certain integro-differential equations. The computation is based on the fact that the eigenfunctions of a symmetric Hilbert-Schmidt operator form a set of complete orthonormal functions in L2 space. This algorithm differs from the ones which computes the value of the solution at each (x,t) point in that it computes the coefficients corresponding to the eigenfunctions. Therefore it is shown that the error in the coefficient of one eigenfunction does not propagate to that of another eigenfunction from one sampling time to the next one. This enables us to analyze the temporal behavior of one spatial frequency which is not affected by that of the other spatial frequencies.
D000818:Animals; D003201:Computers; D008433:Mathematics; D008959:Models, Neurological; D009474:Neurons / Q000502:physiology*; D011817:Rabbits