Autonomous dynamics in neural networks: the dHAN concept and associative thought processes

Abstract

The neural activity of the human brain is dominated by self‐sustained activities. External sensory stimuli influence this autonomous activity but they do not drive the brain directly. Most standard artificial neural network models are however input driven and do not show spontaneous activities.It constitutes a challenge to develop organizational principles for controlled, self‐sustained activity in artificial neural networks. Here we propose and examine the dHAN concept for autonomous associative thought processes in dense and homogeneous associative networks. An associative thought‐process is characterized, within this approach, by a time‐series of transient attractors. Each transient state corresponds to a stored information, a memory. The subsequent transient states are characterized by large associative overlaps, which are identical to acquired patterns. Memory states, the acquired patterns, have such a dual functionality.In this approach the self‐sustained neural activity has a central functional rol...