Neural-like oscillatory network models allow to elucidate the possibilities of dynamical, synchronization-based types of image processing exploited by the brain. The oscillatory network capabilities, studied by means of computer modeling and qualitative analysis, are presented and discussed in this book, as well as several other problems of parallel distributed information processing.
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
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.
Dendrites form the major receiving part of neurons. This text presents a survey of knowledge on dendrites, from their morphology and development, through to their electrical chemical, and computational properties.
Devoted to local and global analysis of weakly connected systems with applications to neurosciences, this book uses bifurcation theory and canonical models as the major tools of analysis. It presents a systematic and well motivated development of both weakly connected system theory and mathematical neuroscience, addressing bifurcations in neuron and brain dynamics, synaptic organisations of the brain, and the nature of neural codes. The authors present classical results together with the most recent developments in the field, making this a useful reference for researchers and graduate students in various branches of mathematical neuroscience.
The purpose of this work is to review recent findings highlighting the mechanisms and functions of the neuronal oscillations that structure brain activity across the sleep-wake cycle. An increasing number of studies conducted in humans and animals, and using a variety of techniques ranging from intracellular recording to functional neuroimaging, has provided important insight into the mechanisms and functional properties of these brain rhythms. Studies of these rhythms are fundamental not only for basic neuroscience, but also for clinical neuroscience. At the basic science level, neuronal oscillations shape the interactions between different areas of the brain and profoundly impact neural responses to the environment, thereby mediating the processing of information in the brain. At the clinical level, brain oscillations are affected in numerous neurological conditions and might provide useful biomarkers that inform about patients’ evolution and vulnerability. During sleep, these brain rhythms could provide functional support to internal states that govern the basic maintenance of local circuit and systemic interactions. During wake, the rhythmicity of cortical and subcortical circuits have been linked with sensory processing, cognitive operations, and preparation for action. This book will attempt to link together these sleep and wake functional roles at the level of neuroimaging and electroencephalographic measures, local field potentials, and even at the cellular level. ​
"Applications of Pulse-Coupled Neural Networks" explores the fields of image processing, including image filtering, image segmentation, image fusion, image coding, image retrieval, and biometric recognition, and the role of pulse-coupled neural networks in these fields. This book is intended for researchers and graduate students in artificial intelligence, pattern recognition, electronic engineering, and computer science. Prof. Yide Ma conducts research on intelligent information processing, biomedical image processing, and embedded system development at the School of Information Science and Engineering, Lanzhou University, China.
Neural Network Dynamics is the latest volume in the Perspectives in Neural Computing series. It contains papers presented at the 1991 Workshop on Complex Dynamics in Neural Networks, held at IIASS in Vietri, Italy. The workshop encompassed a wide range of topics in which neural networks play a fundamental role, and aimed to bridge the gap between neural computation and computational neuroscience. The papers - which have been updated where necessary to include new results - are divided into four sections, covering the foundations of neural network dynamics, oscillatory neural networks, as well as scientific and biological applications of neural networks. Among the topics discussed are: A general analysis of neural network activity; Descriptions of various network architectures and nodes; Correlated neuronal firing; A theoretical framework for analyzing the behaviour of real and simulated neuronal networks; The structural properties of proteins; Nuclear phenomenology; Resonance searches in high energy physics; The investigation of information storage; Visual cortical architecture; Visual processing. Neural Network Dynamics is the first volume to cover neural networks and computational neuroscience in such detail. Although it is primarily aimed at researchers and postgraduate students in the above disciplines, it will also be of interest to researchers in electrical engineering, medicine, psychology and philosophy.
This edited volume provides an overview the state-of-the-art in the field of cognitive neuroscience of memory consolidation. In a number of sections, the editors collect contributions of leading researchers . The topical focus lies on current issues of interest such as memory consolidation including working and long-term memory. In particular, the role of sleep in relation to memory consolidation will be addressed. The target audience primarily comprises research experts in the field of cognitive neuroscience but the book may also be beneficial for graduate students.
