ABSTRACT
The dynamical behavior of individual neurons and of neural circuits emerges from the interactions among multiple nonlinear processes at the molecular, cellular, synaptic and network levels. Thus, characterizing the dynamical performance of a complex system of nonlinear elements is fundamental to an understanding of neural function. This chapter illustrates how some of the concepts and analytical techniques of nonlinear dynamical systems were applied to computational and experimental analyses of single cell and multicellular neuronal oscillators. The results of these studies provided additional insights into how neurons and neural circuits might exploit nonlinear dynamics at the cellular level to generate and control oscillatory patterns of electrical activity and to process and store information.
