Trends in Augmentation of Human Performance. Series editor Vassilis Cutsuridis, Boston University, Boston, USA

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1 Trends in Augmentation of Human Performance Series editor Vassilis Cutsuridis, Boston University, Boston, USA

2 Human performance enhancement refers to the augmentation of human skills, attributes and competencies through the use of technology, medicine and therapy designed to replace or increase human performance capability. In the turn of the second decade of the 21st century the convergence of the neurosciences including neuroimaging, genetics and cognitive science, neurotechnology and informatics is creating powerful tools that have the potential to significantly enhance human performance. Three broad domains of human performance enhancement will be covered by the book series: (1) Enhancement of human performance to restore normal human capability from the disabled or dysfunctional, (2) enhancement of human performance to superhuman levels, and (3) Ethical consequences of the first two domains. Examples of the first domain will include but not limited to restoration of sight, hearing, memory, mobility, reversing aging effects, prosthesis of limbs, brain-machine interface and genetic manipulation. Examples of the second domain will include, but not limited to enhanced memory, augmentation of vision, hearing, strength, mobility, brain-machine and machine-brain interfaces. This series will publish works of the highest quality that advance the understanding and practical application of human performance enhancement. Research monographs, introductory and advanced level textbooks, volume editions and proceedings will be considered. Please contact the editors with your book ideas. Finally, an advisory board of distinguished scientists from the fields on neurotechnology, neurosciences, cybernetics, cognitive sciences, psychophysics, psychiatry, genetics, neuropharmacology, neuroimaging and ethics will assist the book series editor with the selection of future book proposals. The advisory board members will also serve as reviewers of future book proposals. More information about this series at

3 Seong-Whan Lee Heinrich H. Bülthoff Klaus-Robert Müller Editors Recent Progress in Brain and Cognitive Engineering 123

4 Editors Seong-Whan Lee Department of Brain and Cognitive Engineering Korea University Klaus-Robert Müller Machine Learning Group Berlin Institute of Technology Berlin, Germany Heinrich H. Bülthoff Department Human Perception, Cognition and Action Max Planck Institute for Biological Cybernetics Tübingen, Germany ISSN ISSN (electronic) Trends in Augmentation of Human Performance ISBN ISBN (ebook) DOI / Library of Congress Control Number: Springer Dordrecht Heidelberg New York London Springer Science+Business Media Dordrecht 2015 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, 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. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. Printed on acid-free paper Springer Science+Business Media B.V. Dordrecht is part of Springer Science+Business Media (www. springer.com)

5 Preface Brain and cognitive engineering is converging toward a better understanding of cognitive information processing in the human brain. There are first attempts to develop humanlike and neuromorphic artificial intelligent systems. Ultimately this could lead to better modeling, prediction and analysis of brain-related diseases. This book provides overviews and in-depth discussions of recent studies in brain and cognitive engineering. It starts from efforts toward the understanding of perceptual, structural, and functional principles behind the high-order information processing, then considers aspects on how the brain may implement these in artificial systems that can interact intelligently with the real world. Its contributions report recent progress in brain science and cognitive engineering made by scholars from around the world. The book covers four major topics: Noninvasive Brain-Computer Interface, Cognitive- and Neural-Rehabilitation Engineering, Big Data Neurocomputing,and Early Diagnosis and Prediction of Neural Diseases. We hope that the articles in the book will be a valuable resource for researchers in the field and also that the guiding introductory materials will be of use for the potential researchers who step into the field anew. Thank you. Tübingen, Germany Berlin, Germany Seong-Whan Lee Heinrich H. Bülthoff Klaus-Robert Müller v

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7 Contents Part I Non-invasive Brain-Computer Interface 1 Future Directions for Brain-Machine Interfacing Technology... 3 Kyuwan Choi and Byoung-Kyong Min 2 Brain-Computer Interface for Smart Vehicle: Detection of Braking Intention During Simulated Driving Jeong-Woo Kim, Il-Hwa Kim, Stefan Haufe, and Seong-Whan Lee 3 Benefits and Limits of Multimodal Neuroimaging for Brain Computer Interfaces Siamac Fazli, Min-Ho Lee, Seul-Ki Yeom, John Williamson, Isabella Schlattner, Yiyu Chen, and Seong-Whan Lee 4 Multifrequency Analysis of Brain-Computer Interfaces Siamac Fazli, Heung-Il Suk, Seong-Whan Lee, and Klaus-Robert Müller Part II Cognitive- and Neural-Rehabilitation Engineering 5 Current Trends in Memory Implantation and Rehabilitation Hyun Jae Jang, Sahn Woo Park, and Jeehyun Kwag 6 Moving Brain-Controlled Devices Outside the Lab: Principles and Applications Robert Leeb, Ricardo Chavarriaga, Serafeim Perdikis, Iñaki Iturrate, and José d.r. Millán vii

8 viii Contents Part III Big Data Neurocomputing 7 Across Cultures: A Cognitive and Computational Analysis of Emotional and Conversational Facial Expressions in Germany and Korea Christian Wallraven, Dong-Cheol Hur, and Ahyoung Shin 8 Bottom-Up Processing in Complex Scenes: A Unifying Perspective on Segmentation, Fixation Saliency, Candidate Regions, Base-Detail Decomposition, and Image Enhancement Boyan Bonev and Alan L. Yuille 9 Perception-Based Motion Cueing: A Cybernetics Approach to Motion Simulation Paolo Pretto, Joost Venrooij, Alessandro Nesti, and Heinrich H. Bülthoff 10 The Other-Race Effect Revisited: No Effect for Faces Varying in Race Only Isabelle Bülthoff, Regine G.M. Armann, Ryo Kyung Lee, and Heinrich H. Bülthoff Part IV Early Diagnosis and Prediction of Neural Diseases 11 Functional Neuromonitoring in Acquired Head Injury Hakseung Kim, Young-Tak Kim, and Dong-Joo Kim 12 Diagnostic Optical Imaging Technology and Its Principles Jae-Ho Han 13 Detection of Brain Metastases Using Magnetic Resonance Imaging Jaeseok Park 14 Deep Learning in Diagnosis of Brain Disorders Heung-Il Suk, Dinggang Shen, and the Alzheimer s Disease Neuroimaging Initiative

9 Contributors Regine G.M. Armann Max Planck Institute for Biological Cybernetics, Tübingen, Germany Department of Brain and Cognitive Engineering, Korea University, Seoul, Republic of Korea Department of Psychology, University of York, York, UK Boyan Bonev Department of Statistics, University of California, Los Angeles, CA, USA Heinrich H. Bülthoff Max Planck Institute for Biological Cybernetics, Tübingen, Germany Department of Brain and Cognitive Engineering, Korea University, Seoul, Republic of Korea Isabelle Bülthoff Max Planck Institute for Biological Cybernetics, Tübingen, Germany Department of Brain and Cognitive Engineering, Korea University, Seoul, Republic of Korea Ricardo Chavarriaga Defitech Chair in Brain-Machine Interface, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland Yiyu Chen Department of Brain and Cognitive Engineering, Korea University, Kyuwan Choi BK21 Plus Global Leader Development Division in Brain Engineering, Korea University, Siamac Fazli Department of Brain and Cognitive Engineering, Korea University, Jae-Ho Han Department of Brain and Cognitive Engineering, Korea University, ix

10 x Contributors Stefan Haufe Neural Engineering Group, Department of Biomedical Engineering, The City College of New York, New York, NY, USA Machine Learning Group, Department of Computer Science, Berlin Institute of Technology, Berlin, Germany Bernstein Focus Neurotechnology, Berlin, Germany Dong-Cheol Hur Department of Computer Science and Engineering, Korea University, Iñaki Iturrate Defitech Chair in Brain-Machine Interface, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland Hyun Jae Jang Department of Brain and Cognitive Engineering, Korea University, Dong-Joo Kim Department of Brain and Cognitive Engineering, Korea University, Hakseung Kim Department of Brain and Cognitive Engineering, Korea University, Il-Hwa Kim Department of Brain and Cognitive Engineering, Korea University, Jeong-Woo Kim Department of Brain and Cognitive Engineering, Korea University, Young-Tak Kim Department of Brain and Cognitive Engineering, Korea University, Jeehyun Kwag Department of Brain and Cognitive Engineering, Korea University, Ryo Kyung Lee Department of Brain and Cognitive Engineering, Korea University, Min-Ho Lee Department of Brain and Cognitive Engineering, Korea University, Seong-Whan Lee Department of Brain and Cognitive Engineering, Korea University, Robert Leeb Center for Neuroprosthetics, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland José d.r. Millán Defitech Chair in Brain-Machine Interface, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland Byoung-Kyong Min Department of Brain and Cognitive Engineering, Korea University,

11 Contributors xi Klaus-Robert Müller Machine Learning Group, Berlin Institute of Technology, Berlin, Germany Alessandro Nesti Max Planck Institute for Biological Cybernetics, Tübingen, Germany Jaeseok Park Department of Brain and Cognitive Engineering, Korea University, Sahn Woo Park Department of Brain and Cognitive Engineering, Korea University, Serafeim Perdikis Defitech Chair in Brain-Machine Interface, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland Paolo Pretto Max Planck Institute for Biological Cybernetics, Tübingen, Germany Isabella Schlattner Department of Brain and Cognitive Engineering, Korea University, Dinggang Shen Department of Brain and Cognitive Engineering, Korea University, Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA Ahyoung Shin Department of Brain and Cognitive Engineering, Korea University, Heung-Il Suk Department of Brain and Cognitive Engineering, Korea University, Joost Venrooij Max Planck Institute for Biological Cybernetics, Tübingen, Germany Christian Wallraven Department of Brain and Cognitive Engineering, Korea University, John Williamson Department of Brain and Cognitive Engineering, Korea University, Seul-Ki Yeom Department of Brain and Cognitive Engineering, Korea University, Alan L. Yuille Department of Statistics, University of California, Los Angeles, CA, USA