A neural field lattice system motivated by the Amari neural field model is studied. It is formulated as an infinite-dimensional ordinary differential inclusion on a weighted space of infinite sequences. The existence of solutions is proved via a sequence of finite-dimensional approximations and the solutions are shown to generate a nonautonomous set-valued dynamical system which possesses a nonautonomous pullback attractor. Forward omega limit sets for the set-valued dynamical system are also discussed.

Reference: Xiaoying Han and P.E. Kloeden, Asymptotic behaviour of a neural field lattice  model with a Heaviside operator, Physica D (to appear).
