Brain Structure, Learning, And Memory


Book Description

In science, a few areas particularly capture the imagination because of a combination of excitement, substantial technical progress, and implicit significance in affecting the nature and quality of life. Perhaps no area of science exhibits these characteristics more abundantly than that dealing with the brain. Once shrouded in the mystical, studies in modem brain science are dramatically enhancing our understanding of brain function and its impact on learning and memory. It is perhaps the union of pragmatic and mystical aspects that makes this such an exciting arena of science. The Office of Naval Research (ONR) began an intensive effort in 1983 on the topic of the neural basis for learning and memory. This effort was aimed at providing the scientific understanding of how learning takes place. It is the expectation that a neurological understanding of learning processes will lead to the formulation of learning strategies that will significantly enhance performance. This is important in a civilian and military population faced with serious manpower problems requiring a few individuals to be more expert with technologically intensive systems. With these motivations in mind, two of us (EJW and RN) formulated a full-day symposium at the AAAS annual meeting held in New York, May 1984.







Spike-timing dependent plasticity


Book Description

Hebb's postulate provided a crucial framework to understand synaptic alterations underlying learning and memory. Hebb's theory proposed that neurons that fire together, also wire together, which provided the logical framework for the strengthening of synapses. Weakening of synapses was however addressed by "not being strengthened", and it was only later that the active decrease of synaptic strength was introduced through the discovery of long-term depression caused by low frequency stimulation of the presynaptic neuron. In 1994, it was found that the precise relative timing of pre and postynaptic spikes determined not only the magnitude, but also the direction of synaptic alterations when two neurons are active together. Neurons that fire together may therefore not necessarily wire together if the precise timing of the spikes involved are not tighly correlated. In the subsequent 15 years, Spike Timing Dependent Plasticity (STDP) has been found in multiple brain brain regions and in many different species. The size and shape of the time windows in which positive and negative changes can be made vary for different brain regions, but the core principle of spike timing dependent changes remain. A large number of theoretical studies have also been conducted during this period that explore the computational function of this driving principle and STDP algorithms have become the main learning algorithm when modeling neural networks. This Research Topic will bring together all the key experimental and theoretical research on STDP.







The Noisy Brain


Book Description

The activity of neurons in the brain is noisy in that the neuronal firing times are random for a given mean rate. The Noisy Brain shows that this is fundamental to understanding many aspects of brain function, including probabilistic decision-making, perception, memory recall, short-term memory, attention, and even creativity. There are many applications too of this understanding, to for example memory and attentional disorders, aging, schizophrenia, and obsessive-compulsive disorder.







Sixth International Conference on Cognitive Modeling


Book Description

The International Conference on Cognitive Modeling brings together researchers who develop computational models to explain and predict cognitive data. The core theme of the 2004 conference was "Integrating Computational Models," encompassing an integration of diverse data through models of coherent phenomena; integration across modeling approaches; and integration of teaching and modeling. This text presents the proceedings of that conference. The International Conference on Cognitive Modeling 2004 sought to grow the discipline of computational cognitive modeling by providing a sophisticated modeling audience for cutting-edge researchers, in addition to offering a forum for integrating insights across alternative modeling approaches in both basic research and applied settings, and a venue for planning the future growth of the discipline. The meeting included a careful peer-review process of 6-page paper submissions; poster-abstracts to include late-breaking work in the area; prizes for best papers; a doctoral consortium; and competitive modeling symposia that compare and contrast different approaches to the same phenomena.




Sixth International Conference on Cognitive Modeling - ICCM - 2004


Book Description

The International Conference on Cognitive Modeling brings together researchers who develop computational models that explain and predict cognitive data. The 2004 conference encompassed an integration of diverse data through models of coherent phenomena;




Neural Networks


Book Description

Neural Networks presents concepts of neural-network models and techniques of parallel distributed processing in a three-step approach: - A brief overview of the neural structure of the brain and the history of neural-network modeling introduces to associative memory, preceptrons, feature-sensitive networks, learning strategies, and practical applications. - The second part covers subjects like statistical physics of spin glasses, the mean-field theory of the Hopfield model, and the "space of interactions" approach to the storage capacity of neural networks. - The final part discusses nine programs with practical demonstrations of neural-network models. The software and source code in C are on a 3 1/2" MS-DOS diskette can be run with Microsoft, Borland, Turbo-C, or compatible compilers.




Complex-Valued Neural Networks: Utilizing High-Dimensional Parameters


Book Description

"This book covers the current state-of-the-art theories and applications of neural networks with high-dimensional parameters"--Provided by publisher.