Neuroergonomics Also by Addie Johnson TRAINING FOR A RAPIDLY CHANGING WORKPLACE: Applications of psychological research (ed. with Quiñones, M.).

Also by Robert W. Proctor CONTEXTUALISM IN PSYCHOLOGICAL RESEARCH? A critical review (with Capaldi, E. J.) EXPERIMENTAL (ed. with Healy, A. F.) (1st and 2nd editions). PSYCHOLOGY OF SCIENCE: Implicit and explicit processes (ed. with Capaldi, E. J.). WHY SCIENCE MATTERS: Understanding the methods of psychological research (with Capaldi, E. J.). CULTURAL FACTORS IN SYSTEMS DESIGN: Decision making and action (ed. with Nof, S. & Yih, Y.). (ed. with Read, L. E.). STIMULUS- RESPONSE COMPATIBILITY: An integrated perspective (ed. with Reeve, T. G.). HUMAN FACTORS IN SIMPLE AND COMPLEX SYSTEMS (ed. with Van Zandt, T.). STIMULUS- RESPONSE COMPATIBILITY PRINCIPLES: Data, theory, and application (with Vu, K.-P. L.). HANDBOOK OF HUMAN FACTORS IN WEB DESIGN (ed. with Vu, K.-P. L.) (1st and 2nd editions).

Also by Addie Johnson and Robert W. Proctor Theory and practice. SKILL ACQUISITION AND HUMAN PERFORMANCE. Neuroergonomics A Cognitive Approach to Human Factors and Ergonomics

Edited by Addie Johnson Psychology Department, University of Groningen, the Netherlands and Robert W. Proctor Department of Psychological Sciences, Purdue University, USA Addie Johnson and Robert W. Proctor © 2013 Individual Chapters © Contributors 2013 Softcover reprint of the hardcover 1st edition 2013 ISBN 978-0-230-29972-6 All rights reserved. No reproduction, copy or transmission of this publication may be made without written permission. No portion of this publication may be reproduced, copied or transmitted save with written permission or in accordance with the provisions of the Copyright, Designs and Patents Act 1988, or under the terms of any licence permitting limited copying issued by the Copyright Licensing Agency, Saffron House, 6–10 Kirby Street, London EC1N 8TS. Any person who does any unauthorized act in relation to this publication may be liable to criminal prosecution and civil claims for damages. The authors have asserted their rights to be identified as the authors of this work in accordance with the Copyright, Designs and Patents Act 1988. First published 2013 by PALGRAVE MACMILLAN Palgrave Macmillan in the UK is an imprint of Macmillan Publishers Limited, registered in England, company number 785998, of Houndmills, Basingstoke, Hampshire RG21 6XS. Palgrave Macmillan in the US is a division of St Martin’s Press LLC, 175 Fifth Avenue, New York, NY 10010. Palgrave Macmillan is the global academic imprint of the above companies and has companies and representatives throughout the world. Palgrave® and Macmillan® are registered trademarks in the United States, the United Kingdom, Europe and other countries. ISBN 978-1-349-33530-5 ISBN 978-1-137-31652-3 (eBook) DOI 10.1057/9781137316523

This book is printed on paper suitable for recycling and made from fully managed and sustained forest sources. Logging, pulping and manufacturing processes are expected to conform to the environmental regulations of the country of origin. A catalogue record for this book is available from the British Library. A catalog record for this book is available from the Library of Congress. 10 9 8 7 6 5 4 3 2 1 22 21 20 19 18 17 16 15 14 13 Contents

List of Tables and Figures ix Preface xiii Acknowledgements xiv Notes on Contributors xv List of Abbreviations xviii Prologue xxi

1 The Working Brain 1 Addie Johnson, Jacob Jolij, Raja Parasuraman and Paolo Toffanin Brain structures and networks 4 A default mode of brain function 5 Assessing and influencing brain function 6 TMS and tDCS 6 fNIRS 7 EEG 8 Information processing in the brain 12 12 13 Attention and arousal 15 Decision-making 19 Action and motor control 20 Emotion and social interaction 20 Prediction of prospective activity 22 Direct augmentation of human performance 23 Conclusion 25 2 Cognitive Neuroergonomics of Perception 26 Jacob Jolij, Addie Johnson and Robert W. Proctor Visual processing 29 Top- down and bottom- up processing in perception 32 Learning to see 35 Auditory perception and sonification 38 Touch and the display of haptic information 40 Multimodal perception 43

v vi Contents

Perception of space and self 46 Perceptual docking for robotic control 49 Conclusion 50 3 Visual Attention and Display Design 51 Jason S. McCarley and Kelly S. Steelman Modes of orienting 52 Why is mental processing selective? 55 Perceptual selection 56 Central selection 57 Applications to display design 58 Visual search 58 Grouping and object displays 61 Head- up and head- mounted displays 64 Large- scale attention 65 Conclusion 68 4 Attentional Resources and Control 69 Paolo Toffanin and Addie Johnson Quantifying and describing attention 70 Eye movements and pupil diameter 70 EEG 71 Brain networks and fMRI 76 fNIRS 77 Augmented interaction 78 Brain–computer interfaces 79 Adaptive interfaces 82 Augmenting attention and 85 Enhancing attention through training 86 Using drugs to enhance attention 89 Conclusion 90 5 Performance Monitoring and Error- related Brain Activity 91 Addie Johnson and Rasa Gulbinaite Performance monitoring 93 Neural correlates of performance monitoring 96 Error- and feedback- related processing 99 Error prediction 101 Applications based on error- and feedback- related neural signals 103 Maintaining attentional control 104 Contents vii

Learning from errors 106 Online classification of feedback processing 108 Conclusion 109 6 Neuroergonomics of Sleep and Alertness 110 Jon Tippin, Nazan Aksan, Jeffrey Dawson and Matthew Rizzo The neurobiology of sleep and alertness 111 Sleepiness, performance and sleepiness countermeasures 111 OSA and driving 114 Effects of disordered sleep on arousal and cognition 115 Self- awareness of sleep impairments 116 Impaired sleep in OSA and PAP treatment 117 Assessing naturalistic driving behaviour in the real world 119 Case study 122 Conclusion 127 7 Affective and Social Neuroergonomics 129 Jacob Jolij and Yana Heussen The neural basis of emotion 130 How emotion guides vision and cognition 133 Reading emotional states 135 The social brain 138 Social human–computer communication and interaction 139 Social robotics 141 Conclusion 143 8 Neuroergonomics of Individual Differences in Cognition: Molecular Genetic Studies 144 Raja Parasuraman Genomics 144 Why look at individual differences? 146 A theoretical framework for the molecular genetics of cognition 150 Visual attention 152 Working memory 154 Decision-making 155 Conclusion 160 9 Validating Models of Complex, Real- life Tasks Using fMRI 163 Jelmer P. Borst, Niels A. Taatgen and Hedderik van Rijn Standard fMRI analysis 164 Cognitive architectures 165 viii Contents

Cognitive architectures and fMRI 165 Task and model 167 The task 167 The model 169 ROI analysis 170 Model- based fMRI analysis 174 Applications to task design 176 Conclusion 179

References 181 Subject Index 233 Author Index 239 List of Tables and Figures

Tables

1.1 Components of the event- related potentials (ERP), their onset, topography and the functionality they reflect 9 2.1 Guidelines for the design of auditory icons 40 6.1 Substances that affect arousal and sleep, their mechanisms of action and side effects 113

Figures

1.1 The location of some major areas of relevance for information processing in the brain and the areas proposed by Posner and Rothbart (2007) to be involved in alerting, attentional orienting and executive function 15 2.1 A spectrogram of a one- second sound generated by The vOICe. Reprinted with permission (http://www. seeingwithsound.com) 46 3.1 Low display proximity between vertical tape gauges (a) allows an operator to read the value of a single gauge easily, but increases the difficulty of comparing values across the two gauges. High display proximity between the gauges (b) allows for easier comparisons across the gauges but makes the task of isolating and reading a single gauge more difficult 62 4.1 A user interface such as that used by Müller et al. (2008). The image on the left shows the interface as it is displayed when the user ‘moves’ the arrow to selects the hexagon containing the letter ‘I’. The image on the right shows the interface as displayed once the original contents of the hexagons have been replaced by the items in the previously selected hexagon 81 5.1 Conditional accuracy functions in the Eriksen flanker task. As illustrated, reaction times for both fast compatible and incompatible trials are at chance level, which indicates that influence of the flankers is strongest early in the trial and

ix x List of Tables and Figures

is reduced gradually as attention is focused on the target. [Adapted from Gratton, G., Coles, M. G., Sirevaag, E. J., Eriksen, C. W., & Donchin, E. (1988). Pre- and poststimulus activation of response channels: A psychophysiological analysis. Journal of Experimental Psychology. Human Perception and Performance, 14, 331–344. Used with permission from the American Psychological Association.] 97 5.2 (EEG) components related to performance monitoring [upper panel: correct- related negativity (CRN) and error- related negativity (ERN); lower panel: feedback- related negativity (FRN)] 101 6.1 Video and electronic data from the black box event recorder. Cameras capture driver behaviour (upper left panel) and forward view of the road (lower left panel; in this case indicating that approach to an intersection where traffic is stopped at a traffic signal). GPS indicates the location of the driver in a geospatial map (dot, upper right panel). The graphs of the electronic data (lower right panels) show that the driver’s speed has decreased from almost 70 kph to approximately 15 kph over about 15 s on the x- axis (Time) 121 6.2 (a–c) Hours spent asleep and in bed as indicated by wrist- worn actigraphy in relation to PAP use for two PAP recipients (OSA002 and OSA004) and a control participant (CS) matched to OSA002. (d) Average number of awakenings per hour of sleep per participant. The first two weeks are prior to PAP use and the second two weeks post-PAP use 124 6.3 The number of high g events (top) and number of safety errors per high g event (bottom) in OSA patients before and after starting PAP relative to the control individual. 125 6.4 Measures of sleepiness (top) versus alertness (bottom) based on video clip reviews during high g events 126 8.1 Amplitudes of the P1 component (μV) of the event- related potential (ERP) at the Pz electrode site for attended and unattended stimuli for 16 individual participants in a visuospatial attention task (top panel). Group- averaged ERPs (for 16 participants) at three midline electrode sites for attended and unattended stimuli (bottom panel). Reprinted from Figure 3 in Fu et al. (2008), NeuroImage, 39, 1349. Reprinted with permission from Elsevier Inc. 149 List of Tables and Figures xi

8.2 Mean decision accuracy (in percent) in the command and control task when carried out manually, and on reliable and unreliable trials in the Automation 80% condition (bars show standard errors). 158 9.1 The interface of the experiment, with the subtraction task on the left and the text entry task on the right. For the subtraction task, only one column is shown at a time, but participants were trained to consider the problems as part of a ten- column subtraction problem. The task that is not currently performed is masked with hash marks (#): for the text entry task, the mask marks the spot where the next letter will appear. As soon as a participant enters a digit for the subtraction task, this mask changes into the next letter to be typed and the subtraction task is masked. Reprinted from Borst et al. (2010b). The neural correlates of problem states: Testing fMRI predictions of a computational model of multitasking. PLoS ONE, 5, e12966 168 9.2 Example of model activity for a complete trial in each condition of the experiment. On the y-axis the different resources of ACT- R are shown; the x-axis represents time. Each box indicates that a resource is active at that moment in time. Reprinted from Borst et al. (2010b). The neural correlates of problem states: Testing fMRI predictions of a computational model of multitasking. PLoS ONE, 5, e12966 170 9.3 (a) Haemodynamic response function (HRF). (b) Convolution example. (c) Model activity for the problem–state resource and the manual resource, raw and convolved with the HRF over the course of four trials 171 9.4 Results of the regions-of- interest analysis for (a) the problem–state resource and (b) the manual resource. Graphs on the left show model predictions; graphs on the right recorded BOLD data in the region indicated in the brain 172 9.5 Results of the model- based analysis for (a) the problem–state resource and (b) the manual resource. On the left the located brain regions, significance maps were thresholded with p<0.01 (family-wise error-corrected) and 100 contiguous voxels. Coordinates indicate the most significant voxel in the region. White squares show the predefined mapping of ACT- R. The graphs on the right show the average BOLD data in the 100 most significant voxels in the region on the left 175 This page intentionally left blank Preface

Neuroergonomics combines neuroscience techniques and discoveries with ergonomics to contribute to the design of products and systems that enhance performance and safety, broadly defined, and to place constraints on concepts used to describe human performance in com- plex environments. Since the coining of the term ‘neuroergonomics’ by Raja Parasuraman in 2003, special issues of journals and an edited book have been devoted to this topic, several review chapters have been published, major research laboratories have identified themselves as ‘neuroergonomic’ laboratories and neuroergonomics has been a featured topic at conferences. Clearly, neuroergonomics is becoming a leading approach to the study of work and behaviour, and there is every reason to think that its impact will continue to increase in the future as our knowledge of brain function related to performance of complex tasks becomes progressively more sophisticated. This book introduces the field of neuroergonomics and gives the background needed to understand research in neuroergonomics. Our goal was to produce a book that is enjoyable to read—thanks to many examples—while providing an in- depth examination of the possibilities (and limitations) of neuroergonomics. This book is intended for upper- level undergraduates, graduate students, practising ergonomists who wish to acquaint themselves with cognitive neuroscience and cognitive neuroscientists who wish to broaden their thinking about the range of application of their work. We hope that the book serves to increase interest in the exciting and growing field of neuroergonomics.

xiii Acknowledgements

Many thanks to our colleagues and students for their helpful comments, support, inspiration and patience while this work was being completed.

xiv Notes on Contributors

Nazan Aksan is a Research Scientist at the Department of , University of Iowa, USA. Jelmer Borst works in the laboratory of Professor John Anderson at Carnegie Mellon University, USA. His main research interest is the connection between computational models and data. Currently, he investigates how this connection can be advanced and how it can be used to learn more about human cognition. Jeffrey D. Dawson is a Professor of Biostatistics, as well as the Associate Dean for Faculty Affairs, in the College of Public Health at the University of Iowa, USA. He has more than 15 years of experience in applied and methodo logical research in driver performance and safety. Rasa Gulbinaite is a PhD student in experimental psychology at the University of Groningen, the Netherlands. She studies cognitive mecha- nisms underlying automatic and controlled behaviour and, in particular, the brain activity that precedes and follows behavioural errors and the role of individual differences in error perception on subsequent strategic adjustments. Yana Heussen is a PhD candidate in Social and at the University Hospital Schleswig- Holstein, Germany. She is inter- ested in the neural basis of social cognition, and the conscious and unconscious processing of facial expressions, which she studies using neuroimaging methods, such as functional magnetic resonance imaging and electroencephalography. Addie Johnson is Professor of Human Performance and Ergonomics at the University of Groningen. Her research focuses on the intersection of memory and attention. Jacob Jolij is an Assistant Professor at the Department of Experimental Psychology of the University of Groningen, the Netherlands, and asso- ciate editor of Frontiers in Emotion Science. His main research interest is conscious visual perception and, in particular, the role of top- down factors, such as memory, expectancy and emotion, in perception. Waldemar Karwowski is Professor and Chair of Industrial Engineering and Management Systems and Executive Director of the Institute for

xv xvi Notes on Contributors

Advanced Systems Engineering at the University of Central Florida, USA. He is past president of the International Ergonomics Association and the Human Factors and Ergonomics Society, and served on the Committee on Human Factors/Human Systems Integration of the National Research Council, USA. Jason McCarley is currently a Professor in the School of Psychology at Flinders University, South Australia. Raja Parasuraman is Professor of Psychology and Director of the Center of Excellence in Neuroergonomics, Technology, and Cognition (CENTEC) at George Mason University, USA. His research covers human– machine systems, particularly the role of human attention, memory and vigilance in automated and robotic systems, and the cognitive neu- roscience of attention. He is Fellow of the American Association for the Advancement of Science, the American Psychological Association, the American Psychological Society, the Human Factors and Ergonomics Society, the International Ergonomics Association and a National Associate of the National Academy of Sciences. Robert W. Proctor is Distinguished Professor of Psychological Sciences, with a courtesy appointment in Industrial Engineering, at Purdue University. His research focuses on basic and applied aspects of human performance, with an emphasis on stimulus–response compatibility. Niels Taatgen is the Head of the Cognitive Modeling group within the department of Artificial Intelligence of the University of Groningen, the Netherlands. He has a background in both computer science and psychology, with computational models of human cognition as his main research focus. More specifically, he studies human multitasking, skill acquisition and transfer, and time perception. In addition to cognitive simulation and behavioural experiments, he pursues the goal of using cognitive models to analyse neuroimaging data. Jon Tippin is Clinical Professor of Neurology at the University of Iowa Hospitals and Clinics and is director of the Sleep Disorders/EEG Laboratory at the Iowa City Veterans Affairs Medical Center, USA. He is a fellow of the American Academy of Neurology, the American Academy of Sleep Medicine and the American Clinical Society. Paolo Toffanin gained his PhD in neuroscience from the University of Groningen, the Netherlands. His research focuses on basic aspects of attention using both electroencephalography and eye movement recording. His interests include the neural basis of individual differences Notes on Contributors xvii in intelligence, working memory and perfectionism, and optimizing human–machine interaction through adaptive support/automation and brain–computer interfaces. Hedderik van Rijn is Associate Professor in the Psychology Department at the University of Groningen. His work focuses on the refinement of psychological theories by means of formal modelling and behav- ioural and neuroimaging- based experimentation. Current projects include extending and refining formal models of the neurobiological foundations of interval timing, and examining how working memory constrains and influences strategy selection and language processing. Matthew Rizzo is Professor of Neurology and Director of the University of Iowa (UI) Aging Mind and Brain Initiative, USA. He is Vice- Chair for Translational and Clinical Research, Director of the Division of Neuroergonomics and its laboratories, a senior member of the Division of and Cognitive Neuroscience, and a senior attending physician in the Memory Disorders Clinic. He has partici- pated in the National Academy of Sciences Board on Human–Systems Integration. Kelly S. Steelman completed a PhD in Psychology at the University of Illinois at Urbana–Champaign in 2011. She is currently a post doctoral researcher at Flinders University in South Australia. Her research focuses on the attentional control mechanisms that drive performance in technological environments. List of Abbreviations

ANT attention network task ACC anterior cingulate cortex ADHD attention deficit/hyperactivity disorder BCI brain–computer interface BAS behavioural activation system BIS behavioural inhibition system BMI brain–machine interface BOLD blood oxygenation level dependent CNV contingent negative variation CRN correct- related negativity DA dopamine DBH dopamine beta hydroxylase DTI diffusion tensor imaging EDR electrodermal response EDS excessive daytime sleepiness EEG electroencephalogram or electroencephalography EPP error- preceding positivity ERN error- related negativity ERP event- related potential ERP components P1, N1, C1, N1-a, ELAN, N1-v, N170, IIN, P2, MMN/N2a, N2b, N2c, N2pc, LDAP, EDAN, ADAN, P3/P300/P3b, P3a, P4pc, RON, P600, CNV, LRP, ERN/Ne FACS facial action coding system fMRI functional magnetic resonance imaging fNIRS functional near infrared spectroscopy FRN feedback- related negativity GWAS genome- wide association

xviii List of Abbreviations xix

HbO2 oxy-haemoglobin HbR deoxy-haemoglobin HCI human–computer interaction HMD head- mounted display HRF haemodynamic response function HUD head- up display IErrPs interaction error potentials IT inferotemporal cortex LED light emitting diode LGN lateral geniculate nucleus lPFC lateral PFC MEG magnetoencephalogram MFC medial frontal cortex mPFC medial PFC MRI magnetic resonance imaging MSLT multiple sleep latency test NE norepinephrine PAP positive airway pressure treatment PET positron emission tomography PFC prefrontal cortex PHC parahippocampal cortex PPA parahippocampal place area PPC posterior parietal cortex RA rapidly adapting (afferent) ROI region of interest rTMS repetitive- pulse TMS SA1 slowly adapting type 1 (afferent) SART Sustained Attention to Response Test SCN suprachiasmatic nucleus SNPs single nucleotide polymorphisms SSEP steady- state evoked potential xx List of Abbreviations

STS superior temporal sulcus tDCS transcranial direct current stimulation TMS transcranial magnetic stimulation UAV uninhabited air vehicle V1, A1, S1, V2, V4, MT sensory processing regions in the brain VWM visual working memory WIMP Windows- Icons-Mouse-Pointer Prologue Neuroergonomics: A Complex Systems Perspective Waldemar Karwowski

Contemporary human factors and ergonomics (HF/E) focuses on the discovery and understanding of the true nature of human–artefact interactions, viewed from the unified perspective of science, engineer- ing, design, technology and management. Human- compatible systems include a variety of natural and artificial consumer products, work processes and living environments to satisfy people’s demands and requirements (Karwowski, 2005). The discipline of HF/E promotes a human- centred approach to the design of work systems and technology that considers physical, cognitive, social, organizational, environmen- tal and other relevant factors of human–systems interactions, broadly defined, in order to make them compatible with the needs, abilities and limitations of people, with the ultimate goal of optimizing human wellbeing and overall system performance (IEA, 2004). The discipline of HF/E advocates the systematic use of knowledge of human characteristics in order to design interactive systems of people, machines, environments and devices of all kinds that ensure that system goals are met (HFES, 2012). Typically, such goals include improved system effectiveness, productivity, safety, ease of performance, and the contribution to overall human wellbeing and quality of life (Karwowski, 2005). Furthermore, HF/E discovers and applies information about human behaviour, abilities, limitations and other characteristics to the design and evaluation of work systems, consumer products and working environments in which human–machine interactions affect human performance and product usability, including tools, machines, systems, tasks, jobs and environments for productive, safe, comfortable and effective human use (Helander, 1997; Sanders & McCormick, 1993). Karwowski (2000) introduced the term human–compatible systems in order to focus on the need for comprehensive treatment of compatibility in HF/E. The science of HF/E aims to understand and model how people interact with their environments given the specific human characteristics, xxi xxii Prologue including human performance capabilities and limitations. It should be noted that contemporary ergonomics faces the problems of increased systems’ complexity (i.e., the scaling of human factors) and the related human- and system- based nonlinearity and fuzziness. Nonlinear dynamics and fuzziness characterize not only the states of the human mind resulting from neural information processing, but also the essence of human development and existence, and are neces- sary conditions for human learning, growth, and survival (Karwowski, 1992). According to Ashby’s (1956) law of requisite variety, a model system or controller can only model or control something to the extent that it has sufficient internal variety to represent it. In general, the larger the variety of actions available to a control system, the larger the variety of perturbations it is able to compensate. In this context, our ability to understand and model complex human–system interac- tions at work will depend on our understanding of the complexity of neural processes.

Neuroscience and neuroergonomics

Since the times of Hippocrates, scientists have continued their efforts to understand how the human brain works. Contemporary neuroscience applies various levels of analysis in investigating human brain activity, including , , systems neu- roscience, behavioural neuroscience and cognitive neuroscience (Bear et al., 2007). Of particular interest to understanding people at work are the last three neuroscience approaches. While explores the function of neural circuits and systems, behavioural neuroscience applies biological principles to the study of genetic, physiological and developmental mechanisms of behaviour. Finally, cognitive neuroscience studies the neural substrate of mental processes and how the activity of the brain creates what is known as the human mind (Bear et al., 2007). These three perspectives on human brain functioning, which are immediately relevant and necessary for advanc- ing the study and understanding of human–systems interactions at work, led to realization of the utility of the knowledge of neuroscience in HF/E and vice versa, which consequently led to the emergence of neuroergonomics. As stated by Parasuraman (2003), ‘Neuroergonomics focuses on investigations of the neural bases of mental functions and physical performance in relation to technology, work, leisure, transpor- tation, health care and other settings in the real world’ (p. 5). Prologue xxiii

A systems view of neuroergonomics

Neuroergonomics, as the study of brain and behaviour at work, aims to explore the premise of designing work to match the neural capacities and limitations of people (Parasuraman, 2003). As such, neuroergonomics focuses on the neural control and brain manifestations of the percep- tual, physical, cognitive and emotional inter-relationships of human work activities (Parasuraman & Rizzo, 2007). Experimental research in neuroergonomics has benefited in recent years from the emergence of many noninvasive techniques for human brain monitoring that can be used to study various aspects of neural activity and behaviour in relation to technology and work systems, including such domains as mental workload, visual attention, working memory, motor control, human–automation interaction and adaptive automation. The poten- tial benefits of this important new branch of HF/E are far- reaching, from advances in occupational health (Karwowski et al., 2003) and medical therapies, to development of neuroadaptive technologies (Fafrowicz et al., 2013), to applications of new human- centred design principles of complex technological, industrial or service ‘ systems- of-systems’. By extension of the original classification of the discipline of HF/E (Karwowski, 2005) one can distinguish three main paradigms of neuro- ergonomics, namely: (i) neuroergonomics theory, (ii) neuroergonomics abstraction and (iii) neuroergonomics design. In this context, neuro- ergonomics theory is concerned with the ability to identify, describe and evaluate human brain indicators and markers of human performance, and brain–system interactions in the context of work and technology. Neuroergonomics abstraction is concerned with the ability to use these brain indicators and interactions to make predictions that can be validated in the real world. Neuroergonomics design is concerned with the ability to implement knowledge about human brain indicators and relevant interactions, and to use them to develop systems that satisfy human compatibility requirements from the neural processing point of view. From the system- of- systems perspective, the focus of neuroergonomics is on the understanding and designing of complex, and often nonlinear, interactions between the human brain and the artefact systems. The neuroergonomics design process can be represented as mapping human brain capabilities and limitations to system–technology–environment requirements and affordances, and, ultimately, to human– brain compat- ibility requirements at work. Furthermore, as a unique new discipline that combines the scientific knowledge of ergonomics and neuroscience, xxiv Prologue neuroergonomics should allow the making of a significant leap forward in the near future in our understanding of the true nature of com- plex inter-relationships between human operators (human capacities and limitations), technology (products, machines, devices, processes) and broadly-defined work systems (business processes and organiza- tional structures). Without a doubt, the current book will contribute significantly to meeting the aforementioned challenges by bridging ergonomics and neuroscience for the benefit of these two respective fields of scientific endeavour, and, by doing so, will also positively affect the welfare of the global society.