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The number of scientists and laboratories involved with brain mapping is increasing exponentially; and the second edition of this comprehensive reference has also grown much larger than the first (published in 1996), including, for example, five chapters on structural and functional MRI where the fi
The ability to image brain processes non-invasively has created a flood of experiments that fall into two categories—aiming to localize brain performance of abstractions like love, memory or intention—or to identify neuronal activities in response to observable behavior.
The utility of artificial neural network models lies in the fact that they can be used to infer functions from observations making them especially useful in applications where the complexity of data or tasks makes the design of such functions by hand impractical.Exploring Neural Networks with C# presents the important properties of neural networks
This text bridges the gap between introductory physics and its application to the life sciences. It is intended for advanced undergraduates and beginning graduate students. The Fourth Edition is updated to include new findings, discussion of stochastic processes and expanded coverage of anatomy and biology. The text includes many problems to test the student's understanding, and chapters include useful bibliographies for further reading. Its minimal prerequisites and wide coverage make it ideal for self-study. The fourth edition is updated throughout to reflect new developments.
This book is unique in linking in vivo 13C NMR measurements of neuronal activity and energetics with applications to functional imaging and certain disease states It provides a fundamental neurochemical explanation of brain activity applicable to functional imaging, theories of neuronal activity and disease states, e.g. epilepsy, psychiatric diseases and developmental disorders. Novel and potentially controversial Will inspire future research directions
This book focuses on the modeling, processing and visualization of anisotropy, irrespective of the context in which it emerges, using state-of-the-art mathematical tools. As such, it differs substantially from conventional reference works, which are centered on a particular application. It covers the following topics: (i) the geometric structure of tensors, (ii) statistical methods for tensor field processing, (iii) challenges in mapping neural connectivity and structural mechanics, (iv) processing of uncertainty, and (v) visualizing higher-order representations. In addition to original research contributions, it provides insightful reviews. This multidisciplinary book is the sixth in a seri...
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