Modeling in the Neurosciences

Introduction to modelling in the neurosciences; statistical analysis of ionic channel current fluctuations; physiological and statistical approaches to modelling of synaptic responses; natural variability in the geometry of dendritic branching patterns; mathematical analysis of a multiple equivalent cylinder model; methods in modelling passive dendritic trees with tapering dendrites; the Lanczos procedure for generating equivalent cables; parameter estimation algorithms for the Shunt cable model; estimation of cable parameters for neurons with dendro-dendritic gap junctions; information processing by electrotonic networks of the outer retina; ionic current modelling of neurons in the outer retina; ephaptic interaction between neurons; the example of the hippocampus; numerical modelling of neocortical pyramid cells; some problems arising in models of conduction in excitable dendrites; model analysis of bistable dendrites with wind-up; nonlinear dynamics of a simplified neuron model; modelling the dynamics of associative neural networks; perspective on the analysis and synthesis of morphologically realistic neural.