Joel L. Davis – författare

The distributed coding hypothesis --the view that complex cognitivefunctions such as visual perception or memory formation are thework of large networks of neurons in areas of the cerebral cortex--is widely accepted in contemporary neuroscience. Yet only inrecent years have tools emerged that can monitor theelectrophysiological activity of neuron ensembles in the corticalareas of awake, behaving animals. The use of these multichannelrecording techniques in biological network analysis is changing theway scientists view brain function. These methods also offer thepossibility of a direct test of the distributed codinghypothesis. Neuronal Ensembles: Strategies for Recording and Decoding presentsa comprehensive treatment of multichannel recording techniques--how to apply them and how to analyze the vast amounts of datathey generate. Composed of contributions by leading neuroscientistsat the forefront of this technology, the book covers groundbreakingwork in multichannel microelectrode technology, analyses of singleneuron spike trains, and ensemble analysis of cell populations. Theauthors outline established techniques, offer practical tips ondeveloping new methods, and share their ideas for further brainresearch. Topics covered include:* Extracellular recording and analysis of neural activity* The relationship between neuronal codes and cortical organization* Cell assemblies and cognitive function* Neuronal population coding* Motor cortical information processing* Detection and identification of ensemble codes in the motorcortex* Ensemble recordings and the nature of stimulus representation inhippocampal cognitive maps* Methods, results, and issues related to recording neuralensembles* Neuronal ensemble dynamics in the hippocampus and neocortexduring sleep and waking* Behavioral, electrophysiological, and genetic approaches to thestudy of synaptic plasticity and memory Neuronal Ensembles: Strategies for Recording and Decoding is animportant reference for researchers, graduate students, andpostdoctoral fellows in all areas of neuroscience, cognitiveneuroscience, and bioengineering.

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.