Michael Thompson & Larisa-Emilia Cheran 
Sensor Technology in Neuroscience [PDF ebook] 

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Biosensor technology has rapidly expanded into a wide variety of applications in the last few years. Such fields include clinical diagnostics, environmental chemistry, drug discovery and pathogen detection, to name but a few. The structure of these sensors is based on the intimate combination of a biological entity with a transducer capable of generating an electrical signal to provide information on the biological system being studied. Until now there has been a limited treatment of the study of whole cells (as a biological component) due to the difficulty in connecting transducers to cell populations. This book focuses on several aspects of neural behaviour both in vitro and in vivo, and for the first time, the detection of populations of neurons (rather than single cells) will be presented. The fundamental behaviour and characterization of neurons on various substrates, using a variety of electronic devices such as transistors and microelectrode arrays will be discussed. Future perspectives discussed in the book include artificial intelligence using biological neural networks and nanoneuromedicine. The authors have considerable experience in biosensor technology, and have pioneered the study of neural populations using biosensors in collaboration with neurophysiologists and neuroendrocrinologists. This book will be invaluable to university neuroscience and analytical chemistry departments and students, academics and physicians will benefit from its accessible style and format.

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Table of Content

Introduction; Surface Chemistry of Neurons on Substrates; Detection using Microelectronic Devices; Microelectrode Arrays and Light Addressable Potentiometric; Vibrational Fields – Acoustic Physics, Scanning Kelvin Nanoprobe; The Interface Between Brain and Artificial Implants; Future Perspectives

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Language English ● Format PDF ● Pages 250 ● ISBN 9781849735414 ● File size 8.3 MB ● Publisher Royal Society of Chemistry ● Published 2013 ● Edition 1 ● Downloadable 24 months ● Currency EUR ● ID 5496497 ● Copy protection Adobe DRM
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