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(Ebook) Methods for neural ensemble recordings by Miguel A. L. Nicolelis ISBN 9780849370465, 0849370469

  • SKU: EBN-1397634
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Authors:Miguel A. L. Nicolelis
Pages:286 pages.
Year:2008
Editon:2nd ed
Publisher:CRC Press
Language:english
File Size:14.98 MB
Format:pdf
ISBNS:9780849370465, 0849370469
Categories: Ebooks

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(Ebook) Methods for neural ensemble recordings by Miguel A. L. Nicolelis ISBN 9780849370465, 0849370469

In the last ten years neural ensemble recording grew into a well-respected and highly data-lucrative science. New experimental paradigms, including the fabrication of high-density microelectrodes, new surgical implantation techniques, multi-channel signal processing, and the establishment of direct real-time brain-machine interfaces, hold promise not just for neurophysiology research, but also for new-generation prosthetic devices aimed at restoring mobility and communication skills in severely disabled patients. Extensively updated and expanded, Methods for Neural Ensemble Recording, Second Edition distills the current state-of-the-science and provides the nuts and bolts foundation from which to advance the field for the next ten years. With contributions from pioneering researchers, this second edition begins with an overview of microwire array design for chronic neural recordings. Demonstrating the diversity now enjoyed in the field, the book reviews new surgical techniques for chronic implantation of microwire arrays in not just rodents, but primates as well. It explores microelectrode microstimulation of brain tissue, discusses multielectrode recordings in the somatosensory system and during learning, and analyzes neural ensemble recordings from the central gustatory-reward pathways in awake and behaving animals. An exploration of new strategies for neural ensemble data analysis for Brain-Machine Interface (BMI) applications foreshadows an investigation into employing BMI to restore neurological function. Using multielectrode field potential recordings, contributions define global brain states and propose conceptual and technical approaches to human neural ensemble recordings in the future.
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