  A two dimensional time-dependent Duffing oscillator model of macroscopic
neocortex exhibits chaos for some ranges of parameters. We embed this model in
moderate noise, typical of the context presented in real neocortex, using
PATHINT, a non-Monte-Carlo path-integral algorithm that is particularly adept
in handling nonlinear Fokker-Planck systems. This approach shows promise to
investigate whether chaos in neocortex, as predicted by such models, can
survive in noisy contexts.
