Single Neuron Computation

This book contains twenty-two original contributions that provide a comprehensive overview of computational approaches to understanding a single neuron structure. The focus on cellular-level processes is twofold. From a computational neuroscience perspective, a thorough understanding of the information processing performed by single neurons leads to an understanding of circuit- and systems-level activity. From the standpoint of artificial neural networks (ANNs), a single real neuron is as complex an operational unit as an entire ANN, and formalizing the complex computations performed by real neurons is essential to the design of enhanced processor elements for use in the next generation of ANNs.The book covers computation in dendrites and spines, computational aspects of ion channels, synapses, patterned discharge and multistate neurons, and stochastic models of neuron dynamics. It is the most up-to-date presentation of biophysical and computational methods.

Computation in Dendrites and Spines: W. Holmes and W. Rall, Electronic Models of Neuronal Dendrites and Single Neuron Computation. G. Shepherd, Canonical Neurons and Their Computational Organization. B. Claiborne, A. Zador, Z.F. Mainen, and T. Brown, Computational Models of Hippocampal Neurons. T. Brown, A. Zador, Z.F. Meinen, and B. Claiborne, Hebbian Computations in Hippocampal Dendrites and Spines. T. Sejnowski and N. Qian, Synaptic Integration by Electro-Diffusion in Dendritic Spines. C. Wilson, Dendritic Morphology, Inward Rectification, and the Functional Properties of Neostriatal Neurons. I. Segev, M. Rapp, Y. Manor, and Y. Yarom, Analog and Digital Processing in Single Nerve Cells: Dendritic Integration and Axonal Propagation. Ion Channels, Synapses, and Patterned Discharge: P. Schwindt, Ionic Currents Governing Input-Output Relations of Betz Cells. R. Traub and R. Miles, Synchronized Multiple Bursts in the Hippocampus: A Neuronal Population Oscillation Uninterpretable without Accurate Cellular Membrane Kinetics. P. Anton, R. Granger, and G. Lynch, Physiological Models with Temporal Integration of Synaptic Inputs. C. Koch and T. Poggio, Multiplying with Synapses and Neurons. L. Borg-Graham and N. Grzywacz, A Model of the Direction Selectivity in Vertebrate Retina: Transformations by Neurons Singly and in Concert. R. Douglas and K. Martin, Exploring Cortical Microcircuits: A Combined Anatomical, Physiological, and Computational Approach. M. Mahowald, Evolving Analog VLSI Neurons. L. Cauller and B. Connors, Functions of Synapses on Very Distal Dendrites: Layer 1 Inputs to Layer 5 Pyramidal Cells in Neocortex. J. Bower, Relations between the Dynamical Properties of Single Cells and their Networks in Piriform (Olfactory) Cortex. Multistate Neurons and Stochastic Models of Neuron Dynamics: D. McCormick, J. Huguenard, and B. Stowbridge, Determination of State Dependent Processing in Thalamus by Single Neuron Properties and Neuromodulators. D. Tam, Signal Processing in Multi-Threshold Neurons. K. Selz and A. Mandell, Critical Coherence and Characteristic Times in Brain Stem Neuronal Discharge Patterns. C. Smith, Stochastic Neuron Models. M. Teich, Fractal Neuronal Firing Patterns. A. Bulsara, W. Schieve, and F. Moss, Cooperative Stochastic Effects in a Model of a Single Neuron. Index.