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Temporal Coding in the Brain
Temporal coding in the brain documents a revolution now occurring in the neurosciences. How does parallel processing of information bind together the complex nature of the outer and our inner worlds? Do intrinsic oscillations and transient cooperative states of neurons represent the physiological basis of cognitive and motor functions of the brain? Some answers to these challenging issues are provided in this book by leading world experts of brain function. A common denominator of the works presented in this volume is the nature and mechanisms of neuronal cooperation in the temporal domain. The topics range from simple organisms to the human brain. The volume is intended for investigators and graduate students in neurophysiology, cognitive neuroscience, neural computation and neurology.
Models of Neural Networks
Since the appearance of Vol. 1 of Models of Neural Networks in 1991, the theory of neural nets has focused on two paradigms: information coding through coherent firing of the neurons and functional feedback. Information coding through coherent neuronal firing exploits time as a cardinal degree of freedom. This capacity of a neural network rests on the fact that the neuronal action potential is a short, say 1 ms, spike, localized in space and time. Spatial as well as temporal correlations of activity may represent different states of a network. In particular, temporal correlations of activity may express that neurons process the same "object" of, for example, a visual scene by spiking at the ...
Analysis of Parallel Spike Trains
Solid and transparent data analysis is the most important basis for reliable interpretation of experiments. The technique of parallel spike train recordings using multi-electrode arrangements has been available for many decades now, but only recently gained wide popularity among electro physiologists. Many traditional analysis methods are based on firing rates obtained by trial-averaging, and some of the assumptions for such procedures to work can be ignored without serious consequences. The situation is different for correlation analysis, the result of which may be considerably distorted if certain critical assumptions are violated. The focus of this book is on concepts and methods of correlation analysis (synchrony, patterns, rate covariance), combined with a solid introduction into approaches for single spike trains, which represent the basis of correlations analysis. The book also emphasizes pitfalls and potential wrong interpretations of data due to violations of critical assumptions.
Thin Film Growth Techniques for Low-Dimensional Structures
This work represents the account of a NATO Advanced Research Workshop on "Thin Film Growth Techniques for Low Dimensional Structures", held at the University of Sussex, Brighton, England from 15-19 Sept. 1986. The objective of the workshop was to review the problems of the growth and characterisation of thin semiconductor and metal layers. Recent advances in deposition techniques have made it possible to design new material which is based on ultra-thin layers and this is now posing challenges for scientists, technologists and engineers in the assessment and utilisation of such new material. Molecular beam epitaxy (MBE) has become well established as a method for growing thin single crystal l...
Neuronal Information Processing
Recent developments in the neurosciences have considerably modified our knowledge of both the operating modes of neurons and information processing in the cortex. Multi-unit recordings have enabled temporal correlations to be detected, within temporal windows of the order of 1ms. Oscillations corresponding to a quasi-periodic spike-giving, synchronized over several visual cortical areas, have been observed in anaesthesized cats and monkeys. Recent studies have also focused on the role played by the dendritic arborization. These developments have led to considerable interest in a coding scheme which relies on precise spatio-temporal patterns from both the theoretical and experimental points o...
Advances in Neural Information Processing Systems 12
The annual conference on Neural Information Processing Systems (NIPS) is the flagship conference on neural computation. It draws preeminent academic researchers from around the world and is widely considered to be a showcase conference for new developments in network algorithms and architectures. The broad range of interdisciplinary research areas represented includes computer science, neuroscience, statistics, physics, cognitive science, and many branches of engineering, including signal processing and control theory. Only about 30 percent of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. These proceedings contain all of the papers that were presented.
Advances in Neural Information Processing Systems 10
The annual conference on Neural Information Processing Systems (NIPS) is the flagship conference on neural computation. These proceedings contain all of the papers that were presented.
Seminar on Stochastic Analysis, Random Fields and Applications V
This volume contains refereed research or review papers presented at the 5th Seminar on Stochastic Processes, Random Fields and Applications, which took place at the Centro Stefano Franscini (Monte Verità) in Ascona, Switzerland, from May 29 to June 3, 2004. The seminar focused mainly on stochastic partial differential equations, stochastic models in mathematical physics, and financial engineering.
Sigmund Abeles
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