NeuroImage 59 (2012) 1–3

Contents lists available at SciVerse ScienceDirect

NeuroImage

j ourna l homepage: www.e lsev ie r.com/ locate /yn img

Editorial

Neuroergonomics: The brain in action and at work

What is neuroergonomics?

Neuroimaging methods have steadily improved in their techni-cal sophistication and breadth of application over the past decade.Cognitive neuroscience studies using these methods have alsoincreased in their intricacy, and there has been growing interest intheir use to examine the neural circuits supporting complex tasksrepresentative of perception, cognition, and action as they occur innatural settings. At the same time, many fields in the biologicalsciences—including neuroscience—are being challenged to demon-strate their relevance to practical real-world problems. Much of thetranslational efforts in the area of neuroscience have been devotedto disease, namely the diagnosis and treatment of neurological,psychiatric, and other medical disorders (Editorial, 2002; Insel,2010; Matthews et al., 2006). Yet there are many opportunities fortranslational neuroscience outside of medicine or health proper.One example is the application of cognitive neuroscience researchto improve the design of automobiles and the safety of drivers invarious traffic conditions (Lees et al., 2010). More generally,translational neuroscience is relevant to the enhancement of humanperformance in domains such as aviation, education, security, and themilitary, aswell as inmany everyday settings. Collectively, such effortsare known as neuroergonomics (Parasuraman, 2011; Parasuramanand Rizzo, 2008).

Researchers and professionals in human factors and ergonomicsstudy human capabilities and limitations, both cognitive and physical,and use that knowledge to design technologies and work environ-ments to be safer and more usable, efficient, and enjoyable for peopleto interact with (Norman, 1990; Wickens and Holands, 2000). Thecentral premise of neuroergonomics is that human factors researchand practice can be enriched by consideration of theories and resultsfrom neuroscience. Some decades ago such a claim would have beenconsidered implausible because our knowledge of human (as opposedto animal) brain function was limited and restricted to only thesimplest aspects of human behavior. However, with the phenomenalgrowth of human cognitive, and more recently, social neuroscience, itis increasingly the case that theories of human performance can beconstrained or extended by consideration of findings from theneurosciences (Gazzaniga, 2009). The relevant neuroscience tech-niques include neuroimaging, non-invasive brain stimulation, molec-ular genetics, and related methods. This knowledge is amplified byever increasing improvements in modeling and decoding brainactivity with machine learning algorithms and related computationaltechniques (Mitchell et al., 2004). Integration across these differentmethods will be a necessary step in substantially advancing thescience of human performance and exploiting their potential foraddressing key questions concerning brain function. Neuroergo-

1053-8119/$ – see front matter © 2011 Elsevier Inc. All rights reserved.doi:10.1016/j.neuroimage.2011.08.011

nomics can therefore provide added value, beyond that availablefrom traditional neuroscience and conventional ergonomics, toenhance understanding of brain function and behavior as encoun-tered in work and in natural settings.

This emerging, inter-disciplinary area of research has experiencedextensive growth in recent years. A special issue on the topic firstappeared in an ergonomics journal (Parasuraman, 2003). This wasfollowed by a book (Parasuraman and Rizzo, 2008) and by a growingnumber of journal articles and conference proceedings. Much of thisresearch activity is being fueled by the emergence of substantialresearch and training grant funding provided by different federalagencies that have embraced this area. For these agencies, neuroer-gonomics provides an innovative approach to examining emergingissues in human performance—such as divided attention andmultitasking with large, information-saturated displays—as well asold problems surfacing in a new way such as vigilance in defendingcomputer networks.

Given these developments, we felt that the time was ripe for afocused survey of current and future trends in neuroergonomicsresearch. This special issue of NeuroImage consists of articles invitedfrom leaders in the field. All of the papers describe studies usingneuroimaging and related methods in the examination of differentfacets of perception, cognition, affect, and action. While there aremany cognitive neuroscience studies that have examined suchdomains of human behavior in basic laboratory tasks, many studiesoften fail to capture the complexity and dynamics of behavior as itoccurs naturally in everyday settings. In other cases, the tasks used inlaboratory studies may have little or no relation to those confrontingpeople in everyday life (Kingstone et al., 2003). Moreover, the resultsof such studies may have few direct applications to performance inthe real world. In contrast, the invitees for this special issue werechosen specifically because of their interest and expertise inexamining neural mechanisms of cognitive processes as related tohuman performance at work and other naturalistic environments.

We had two main goals for the special issue. The first was tohighlight recent research developments in neuroergonomics. Equallyimportant, our second goal was to illustrate for researchers outsidethe field that there exists another avenue for translational neurosci-ence than medical applications. Our hope is that these readers mayconsider neuroergonomics a field that they may wish to enter,particularly given the opportunities for scientific discovery as well asincreased funding for research in this area.

Neuroimaging studies aimed at ergonomic applications representa relatively small area of research when compared to other areas ofcognitive neuroscience. Nevertheless, the field is growing each day.Given the multiplicity of activities that people engage in at work andin their everyday pursuits, the sky is the limit as far as applications are

2 Editorial

concerned. The full range of applications of neuroergonomics is onlygradually becoming apparent and will likely increase exponentially inthe future. This special issue provides an overview of this exciting,expanding new field.

Overview of papers

The special issue consists of 14 papers covering a number of topicsin neuroergonomics. The first two papers examine how the humanbrain perceives and comprehends the activities of other people asthey move and act in the world—biological motion. The topic isimportant because communication and social interaction with otherpeople requires that we recognize and comprehend their movementsand intentions. Action recognition and understanding are alsoimportant in many work settings such as surveillance, search andrescue, and security operations. Thompson and Parasuraman review -behavioral, functional magnetic resonance imaging (fMRI), and event-related potential (ERP) evidence indicating that although actionrecognition can be rapid and efficient, it is dependent on attention,particularly when visual information about actions is degraded,ambiguous, or intermixed with competing stimuli. They provideevidence for effects of selective, divided, and sustained attention onbrain networks of biological motion. Grafton and Tipper describe theuse of electroencephalography (EEG) and fMRI in decoding intentionsfrom the perception of biological motion, e.g., those associated withbodymovements and hand-object interactions of others. They concludethatwhile nofield-ready neuroergonomicmethod is currently availablefor decoding unspoken intentions, present approaches to the problemare promising and merit further development.

The next two papers consider two important real-world workdomains—both involving transportation—that have been the object ofextensive study in previous ergonomics research and practice—driving (Lee, 2008) and aviation (Tsang and Vidulich, 2003). Calhounand Pearlson review fMRI studies examining the functional connec-tivity of brain networks involved in simulated driving. They alsodescribe the effects of alcohol on these networks. Ayaz and colleaguesdescribe the use of functional near infrared spectroscopy (fNIR) forevaluating the mental workload of air traffic controllers and ofoperators remotely piloting air vehicles, in realistic, complexsimulations of these work environments. These two papers are goodexamples of neuroergonomic studies of brain function in experiencedhuman operators engaged in high-fidelity simulations of complex,real-world work activities that go beyond the simple cognitive taskswith college students typically used in laboratory studies.

These papers are followed by a group of three papers concernedwith classifying operator cognitive states for future use in real-timeadaptive systems. All three studies chose to develop EEG-basedclassifiers, given the greater temporal resolution and greater potentialfor ambulatory monitoring of EEG (compared, for example, to fMRI).The papers address the problem of variability in the accuracy ofmachine learning-based pattern classification across tasks, time, andpeople. The three studies use different computational techniques toattack the problem. Baldwin and Penaranda describe the within- andcross-task accuracy of artificial neural network (ANN) classifiers ofcognitive workload-related EEG activity for use in adaptive learningsystems. Christensen and colleagues also describe the application ofANN and two other common pattern classification techniques to EEGdata obtained from participants performing a multitask battery acrossseveral days. They conclude that with proper methods, patternclassification is stable enough across days and weeks to be usefulfor adaptive systems. In these two studies, classifiers were developedand trained individually for each subject. In contrast, Wang andcolleagues describe the use of hierarchical Bayesian modeling todevelop a cross-subject cognitive workload classifier based on EEGdata obtained from the same multitask battery used by Christensenand colleagues. Collectively, this group of studies shows the potential

of neuroimaging to classify human cognitive states in real time, andthis work represents significant progress in the goal of usingphysiological signals in on-line adaptive systems (Byrne andParasuraman, 1996). At the same time, the results also point to themany challenges that must be overcome before such classificationtechniques could be fielded.

Some of the previously discussed papers have touched on the issueof inter-subject variability, but the next group of three papersspecifically addresses differences and communalities in brain functionbetween individuals. Parasuraman and Jiang describe the use ofbehavioral, neuroimaging (fMRI, ERP), and molecular genetic ap-proaches to characterizing inter-individual variability in cognitionand affect. They conclude that a broad neuroergonomic approach thatcombines examination of brain function with genetic data can beusefully applied to understanding individual differences in cognitionand affect, and that the results carry implications for understandinghuman performance issues at work such as training and selection.Miller and colleagues examine inter-subject variability in fMRIactivity in a memory retrieval task. They conclude that individualdifferences in cognitive style and encoding strategy must be takeninto account when using fMRI to make inferences about an individual.Finally, Eckstein and colleagues also examine brain function (EEG) indifferent individuals, but instead of focusing on differences, theyexamine how aggregation of neural activity across the manyindividuals in a group can lead to improvements in decision accuracyin a perceptual task. They conclude that the neural activity of a groupof individuals can be computationally combined and used to define“collective wisdom.”

This paper, as do many others in the special issue, uses differentcomputational techniques to analyze and classify neuroimaging data.The next paper, by Liu and colleagues, more broadly examines the useof computational modeling of human brain and cognitive function inthe context of neuroergonomics. Drawing on previous work incomputational neuroscience and ergonomics, the authors outline aqueuing network based computational neuroergonomic architectureand its applications to the solution of different problems in humanfactors and ergonomics.

The final group of three papers examines an important appliedtopic—how best to train individuals to promote learning and enhanceperformance—but the respective authors approach the issue fromdifferent perspectives. Two of the papers examine the utility of non-invasive brain stimulation to enhance human perceptual andcognitive performance. First, Clark and colleagues describe the useof transcranial direct current stimulation (tDCS) guided by fMRI toaccelerate learning rate in a militarily-relevant task: threat detectionof objects concealed in a naturalistic virtual environment. The authorsconclude that tDCS may be useful to decrease the time required toattain expertise in a variety of work settings. In a second paper onbrain stimulation, McKinley and colleagues review studies using bothtranscranial magnetic stimulation (TMS) and tDCS and propose thatsuch techniques can complement other approaches to humanperformance optimization. The third paper by Voss and colleaguesexamines the use of different training strategies, specifically fixed orvariable priority training, on the functional connectivity of brainnetworks in acquiring skill in a complex videogame task. The authorsconclude that their approach can be used to explore mechanisms ofbrain plasticity involved in transfer of trained abilities to complextasks in the real world, including driving and sport.

A commentary by Michael Posner—a noted pioneer of cognitiveneuroscience—closes the special issue. Posner traces the history ofergonomics to the wartime work of Paul Fitts, with whom hecompleted an influential early volume on human performance (Fittsand Posner, 1967). He then describes the early history of cognitiveengineering and the emergence of cognitive neuroscience, leading tothe current interest in neuroergonomics. Posner names his commen-tary “Expanding horizons in ergonomics research.” The title is apt.

3Editorial

Neuroergonomics indeed represents a new horizon in the science andpractice of human factors and ergonomics.

Acknowledgments

Preparation of this special issue was supported in part by AFOSR/AFRL grant FA9550-10-1-0385 and the Center of Excellence inNeuroergonomics, Technology, and Cognition (CENTEC) to RP.

References

Byrne, E.A., Parasuraman, R., 1996. Psychophysiology and adaptive automation. Biol.Psychol. 42, 249–268.

Editorial, 2002. Taking neuroscience beyond the bench. Nat. Neurosci. 5, 1019 (Suppl.).Fitts, P.M., Posner, M.I., 1967. Human Performance. Brooks/Cole, Belmont, CA.Gazzaniga, M.S. (Ed.), 2009. The Cognitive Neurosciences, 4th Edition. MIT Press,

Cambridge, MA.Insel, T.R., 2010. The challenge of translation in social neuroscience: a review of

oxytocin, vasopressin, and affiliative behavior. Neuron 6, 768–779.Kingstone,A., Smilek, D., Ristic, J., Friesen, C.K., Eastwood, J.D., 2003.Attention, researchers!

It is time to take a look at the real world. Curr. Dir. Psychol. Sci. 12, 176–180.Lee, J.D., 2008. Fifty years of driving safety research. Hum. Factors 50, 521–528.Lees, M.N., Cosman, J.D., Fricke, N., Lee, J.D., Rizzo, M., 2010. Translating cognitive

neuroscience to the driver's operational environment: a neuroergonomicsapproach. Am. J. Psychol. 123, 391–411.

Matthews, P.M., Honey, G.D., Bullmore, E.T., 2006. Applications of fMRI in translationalmedicine and clinical practice. Nat. Rev. Neurosci. 7, 732–744.

Mitchell, T.M., Hutchinson, R., Niculescu, R.S., Pereira, F.,Wang, X., Just,M., Newman, S., 2004.Learning to decode cognitive states from brain images. Mach. Learn. 57, 145–175.

Norman, D.A., 1990. The Design of Everyday Things. Doubleday, New York, NY.Parasuraman, R., 2011. Neuroergonomics: brain, cognition, and performance at work.

Curr. Dir. Psychol. Sci. 20, 181–186.Parasuraman, R., Rizzo, M., 2008. Neuroergonomics: The Brain at Work. Oxford

University Press, New York, NY.Parasuraman, R., 2003. Neuroergonomics; research and practice. Theor. Iss. Ergon. Sci.

4, 5–20.Tsang, P., Vidulich, M., 2003. Principles of Aviation Psychology. Erlbaum, Mahwah, NJ.Wickens, C.D., Holands, J.G., 2000. Engineering Psychology and Human Performance,

3rd ed. Prentice-Hall, Upper Saddle River, NJ.

Raja ParasuramanArch Laboratory and Department of Psychology,

George Mason University, Fairfax, VA 22030, USACorresponding author. Fax: +1 703 993 1330.

E-mail address: rparasur@gmu.edu

James ChristensenAir Force Research Laboratory,

Wright-Patterson Air Force Base, Dayton, OH 45433, USA

Scott GraftonDepartment of Psychological and Brain Science,

University of California, Santa Barbara, CA 93106, USA