Machine Learning and Interpretation in Neuroimaging Internationa
Brain imaging brings together the technology, methodology, research questions and approaches of a wide range of scientific fields including physics, statistics, computer science, neuroscience, biology, and engineering. Thus, methodological and technologic
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LNAI Founding Series Editor Joerg Siekmann DFKI and Saarland University, Saarbrücken, Germany
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Georg Langs Irina Rish Moritz Grosse-Wentrup Brian Murphy (Eds.)
Machine Learning and Interpretation in Neuroimaging International Workshop, MLINI 2011 Held at NIPS 2011 Sierra Nevada, Spain, December 16-17, 2011 Revised Selected and Invited Contributions
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Series Editors Randy Goebel, University of Alberta, Edmonton, Canada Jörg Siekmann, University of Saarland, Saarbrücken, Germany Wolfgang Wahlster, DFKI and University of Saarland, Saarbrücken, Germany Volume Editors Georg Langs Medical University of Vienna, Department of Radiology, CIR Lab Währinger Gürtel 18-20, 1090 Wien, Austria E-mail: [email protected] Irina Rish IBM T.J. Watson Research Center, Computational Biology Center 1101 Kitchawan Road, Yorktown Heights, NY 10598, USA E-mail: [email protected] Moritz Grosse-Wentrup Max Planck Institute for Intelligent Systems Spemannstraße 38, 72076 Tübingen, Germany E-mail: [email protected] Brian Murphy Carnegie Mellon University, Machine Learning Department 5000 Forbes Avenue, Pittsburgh, PA 15213-3891, USA E-mail: [email protected] ISSN 0302-9743 e-ISSN 1611-3349 ISBN 978-3-642-34712-2 e-ISBN 978-3-642-34713-9 DOI 10.1007/978-3-642-34713-9 Springer Heidelberg Dordrecht London New York Library of Congress Control Number: 2012951409 CR Subject Classification (1998): I.5.1-4, I.2.6, H.2.8, G.3, I.4.6-7, I.4.9, J.3, I.2.1, F.2.2 LNCS Sublibrary: SL 7 – Artificial Intelligence © Springer-Verlag Berlin Heidelberg 2012 This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, re-use of illustrations, recitation, broadcasting, reproduction on microfilms or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer. Violations are liable to prosecution under the German Copyright Law. The use of general descriptive names, registered names, trademarks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. Typesetting: Camera-ready by author, data conversion by Scientific Publishing Services, Chennai, India Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)
Preface
Brain imaging brings together the technology, methodology, research questions, and approaches of a wide range of scientific fields including physics, statistics, computer science, neuroscience, biology, and engineering. Thus, methodological and technological advances that enable us to obtain measurements, examine relationships across observations, and link these data to neuroscientific hypotheses happen in a highly interdisciplinary envir
