Neural field models and reaction-diffusion framework
In the last decade attention to formalism describing self-organizing structures in spatially distributed systems with excitation and inhibition applied to neural networks increased. Here we consider integro-differential equations describing system of linear-non-linear rate neurons with distance dependent synaptic strength and appearing bump structures obtained with help of transition in activity level at bumps boarders. Then we make diffusive approximation and get reaction diffusive equations allowing Turing instability analysis and explaining Turing pattern formation in neural networks, also visual hallucination and salt and pepper model in binocular vision. Then we briefly consider several bump interactions including the case of plastic networks.
Mr. Dmytro Grytskyy