FROM BIOPHYSICS TO MODELS OF NETWORK FUNCTION

Abstract

▪ Abstract  Neurons and synapses display a rich range of time-dependent processes. Which of these are critical to understanding specific integrative functions in the brain? Computational methods of various kinds are used to understand how systems of neurons interact to produce behavior. However, these models often assume that neuronal dynamics and synaptic strengths are fixed. This review presents some recent models that illustrate that short-term synaptic plasticity mechanisms such as facilitation and depression can have important implications for network function. Other features of synaptic transmission such as multi-component synaptic potentials, cotransmission, and neuromodulation with obvious potential computational implications are presented. These examples illustrate that synaptic strength and intrinsic properties in networks are continuously varying on numerous time scales as a function of the temporal patterns of activity in the network. Thus, both firing frequency of the neurons in a circuit, and the modulatory environment determine the intrinsic and synaptic properties that produce behavior.