Dynamics of interconnection development within visual cortex

Abstract

Two kinds of dynamic processes take place in neural networks. One involves the change with time of the activity of each neuron. The other involves the change in the strength of the connections (synapses) between neurons. When a neural network is learning or developing, both processes take place, and their dynamics interact. A theoretical framework is developed to help understand the combined activity and synapse dynamics for a class of adaptive networks. The methods are illustrated by using them to describe the development of orientation-selective cells in the cat primary visual cortex. Within this model, the column structure of different orientation-selective neurons originates from feedback pathways within an area of the cortex, rather than feedforward pathways between areas.<>