Connectivity and Dynamics in Local Cortical Networks

Abstract

Recent experimental work has begun to characterize activity in local cortical networks containing thousands of neurons. There has also been an explosion of work on connectivity in networks of all types. It would seem natural then to explore the influence of connectivity on dynamics at the local network level. In this chapter, we will give an overview of this emerging area. After a brief introduction, we will first review early neural network models and show how they suggested attractor dynamics based on recurrent connectivity. Second, we will review physiological reports of repeating activity patterns that have been influenced by this initial concept of attractors. Third, we will introduce tools from dynamical systems theory that will allow us to precisely quantify neural network dynamics. Fourth, we will apply these tools to simple network models where connectivity can be tuned. We will conclude with a summary and a discussion of future prospects.