Oscillations In Neural Systems
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Oscillations in Neural Systems
This book is the fourth in a series based on conferences sponsored by the Metroplex Institute for Neural Dynamics (MIND), an interdisciplinary organization of Dallas-Fort Worth area neural network professionals in both academia and industry. This topic was chosen as the focus for this special issue because of the increasing interest by neuroscientists and psychologists in both rhythmic and chaotic activity patterns observed in the nervous system. Neither the mathematical structure of neural oscillations nor their functional significance is precisely understood. There are a great many open problems in both the structure and function of neural oscillations, whether rhythmic, chaotic, or a combination of the two, and many of these problems are dealt with in the chapters of this book.
Oscillations in Neural Systems
Written for those interested in designing machines to perform intelligent functions & those interested in studying how these functions are performed by living organisms,this bk dicusses the mathematical structure & functional significance of neural oscil
Oscillatory Neural Networks
Author: Margarita G. Kuzmina
language: en
Publisher: Walter de Gruyter
Release Date: 2013-11-27
Understanding of the human brain functioning currently represents a challenging problem. In contrast to usual serial computers and complicated hierarchically organized artificial man-made systems, decentralized, parallel and distributed information processing principles are inherent to the brain. Besides adaptation and learning, which play a crucial role in brain functioning, oscillatory neural activity, synchronization and resonance accompany the brain work. Neural-like oscillatory network models, designed by the authors for image processing, allow to elucidate the capabilities of dynamical, synchronization-based types of image processing, presumably exploited by the brain. The oscillatory network models, studied by means of computer modeling and qualitative analysis, are presented and discussed in the book. Some other problems of parallel distributed information processing are also considered, such as a recall process from network memory for large-scale recurrent associative memory neural networks, performance of oscillatory networks of associative memory, dynamical oscillatory network methods of image processing with synchronization-based performance, optical parallel information processing based on the nonlinear optical phenomenon of photon echo, and modeling random electric fields of quasi-monochromatic polarized light beams using systems of superposed stochastic oscillators. This makes the book highly interesting to researchers dealing with various aspects of parallel information processing.