Neuronal Noise
Neuronal Noise combines experimental, theoretical and computational results to show how noise is inherent to neuronal activity, and how noise can be important for neuronal computations. The book covers many aspects of noise in neurons, with an empha
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Volume 8
Series Editors Alain Destexhe Unit´e de Neuroscience, Information et Complexit´e (UNIC) CNRS Gif-sur-Yvette France Romain Brette Equipe Audition (ENS/CNRS) ´ D´epartement d’Etudes Cognitives ´Ecole Normale Sup´erieure Paris France
For further volumes: http://www.springer.com/series/8164
Alain Destexhe • Michelle Rudolph-Lilith
Neuronal Noise
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Dr. Alain Destexhe CNRS, UPR-2191 Unit´e de Neuroscience, Information et Complexit´e av. de la Terrasse 1 91198 Gif-sur-Yvette Bat. 32-33 France [email protected]
Dr. Michelle Rudolph-Lilith CNRS, UPR-2191 Unit´e de Neuroscience, Information et Complexit´e av. de la Terrasse 1 91198 Gif-sur-Yvette Bat. 32-33 France [email protected]
ISBN 978-0-387-79019-0 e-ISBN 978-0-387-79020-6 DOI 10.1007/978-0-387-79020-6 Springer New York Dordrecht Heidelberg London Library of Congress Control Number: 2011944121 © Springer Science+Business Media, LLC 2012 All rights reserved. This work may not be translated or copied in whole or in part without the written permission of the publisher (Springer Science+Business Media, LLC, 233 Spring Street, New York, NY 10013, USA), except for brief excerpts in connection with reviews or scholarly analysis. Use in connection with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed is forbidden. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights. Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)
To Our Families
Foreword
Any student of the human condition or of animal behavior will be struck by its unpredictability, its randomness. While crowds of people, schools of fish, flocks of geese or clouds of gnats behave in predictable ways, the actions of individuals are often highly idiosyncratic. The roots of this unpredictability is apparent at every level of the brain, the organ responsible for behavior. Whether patch-clamping individual ionic channels, recording the electrical potential from inside or from outside neurons or measuring the local field potential (LFP) via EEG electrodes on the skull, one is struck by the ceaseless commotion, the feverish traces that move up and down irregularly, riding on top of slower fluctuations. The former are consequences of various noise sources. By far the biggest is synaptic noise. Single synapses are unreliable—the release of a puff of neurotransmitter molecules can occur as infrequently as one out of every ten times that an action potential (AP) invades the presynaptic terminal. This should be contrasted with the reliability of transistors in integrated silicon circuits, whose switching probability is very, very close to unity. Is this a bug—an unavoidable consequence of packing roughly one billion synapses into one cubic millimeter of cort
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