Such technological advances are affecting not only civilian life, but the military as well. For example, the United States Air Force Chief Scientist recently released a report that details the expanding mismatch between human ‘warfighters’ and the technology available to them (Chief Scientist Air Force, 2010). The report attempts to make the case that as technological capacity continues to increase it will become increasingly important to examine the role of the human as a link in security and other systems. It is evident that now, more than ever, the military needs ergonomics research to enhance human–machine systems. The Air Force Chief Scientist report goes on to identify ‘augmentation of human performance’ as one of two key areas where substantial growth is possible in the coming decade (p. vii) and calls specifically for ‘direct augmentation of humans via drugs or implants to improve memory, alertness, cognition, or visual/aural acuity’ (p. viii), as well as ‘direct brainwave coupling between humans and machines, and screening of individual capacities for key specialty codes via brainwave patterns and genetic correlators’ (p. 58). In other words, cognitive science and cognitive neuroscience must be combined with traditional ergonomics to create new neuroergonomic applications.

Although much of the interest in, and funding for, neuroergonomic research has come from the military, key areas of neuroergonomics, such as operator– state-based adaptive automation and brain–computer interfaces, have applications in a range of work, transportation and leisure environments. The development of neuroergonomic applications requires an understanding of the tasks to be performed, the cognitive processing involved in their performance, and the existence of a set of techniques to measure or influence cognitive processing. Many books and articles have been devoted to task analysis and cognitive work analysis (e.g. Diaper & Stanton, 2004; Vicente, 1999). It can be argued that neuroergonomics, in seeking to apply neuroscience to system design, starts where cognitive task analysis leaves off. Instead of describing cognitive processing activities as, for example, ‘memory’ or ‘decision making’, an understanding of functional neuronal networks underlying those activities is applied to assess the quality of information processing and to intervene to improve system performance.

Much of what we know or hypothesize about neuronal networks comes from single-cell studies with animal subjects (e.g. Buzsáki, 2006; Kandel et al., 2013). Developments in neuroimaging are, however, making it increasingly possible to test hypotheses about how information is processed in the brain in healthy humans. Neuroimaging methods allow us to infer neuronal activity in terms of localized changes in blood flow or metabolism [positron emission tomography (PET)] or in terms of changes in blood oxygenation level dependent (BOLD) responses [functional magnetic resonance imaging (fMRI)]. Tracers that bind to different receptors have been used in combination with PET to examine transmitter density; pathways of activation can now be imaged using diffusion tensor imaging (DTI), in which MRI is used to trace white matter tracts. Lesion studies have played an important role in mapping brain regions to function and, in addition to the study of naturally-occurring lesions, transcranial magnetic stimulation (TMS) is being used to induce, on a short timescale, disruptions in normal brain processing to test conclusions about causal relations between brain activity and behaviour. Finally, measurement of electric [electroencephalogram (EEG)] or magnetic [magnetoencephalogram (MEG)] signals at the scalp can be used to provide detailed information about the time-course of information processing and, increasingly, its locus. Used separately or together, these methods and others (e.g. transcranial Doppler sonography, near-infrared spectroscopy, deep brain stimulation) form the toolkit of the neuroscientist studying the physiology of human brain networks.

These various neuroimaging techniques have been used extensively in cognitive neuroscience studies in which naïve participants, typically college undergraduates, are tested while performing simple laboratory tasks of perception and cognition (Gazzaniga, 2009). In contrast to cognitive neuroscience, one of the goals of neuroergonomics is to examine brain function in the more complex and dynamic tasks representative of everyday, naturalistic environments at work, in the home or in transportation, and—where possible—in expert populations, such as pilots, physicians or military personnel. From small beginnings, following the initial call for such research (Parasuraman, 2003), a growing number of studies have examined human brain function in work-relevant tasks. Examples include fMRI studies of frontal and parietal cortical networks involved in simulated driving (Just et al., 2008) and how they are altered in intoxicated drivers (Calhoun & Pearlson, 2012); EEG investigations of pilot mental workload during actual and simulated flight (Wilson, 2001) and the usability of hypermedia systems (Schultheis & Jameson, 2004); and functional near infrared spectroscopy (fNIRS) studies of frontal lobe activation in experts performing simulated minimally-invasive surgery (James et al., 2011).

Brain stimulation techniques, such as TMS and transcranial direct current stimulation (tDCS), can supplement the use of neuroimaging techniques in neuroergonomics. Such techniques are of interest because of their potential for showing that brain networks that have been identified in neuroimaging studies are not only active, but are necessary for performance of a given task. This is typically achieved by showing that task performance is impaired when the associated brain region is momentarily inhibited using TMS (Walsh & Pascual-Leone, 2005) or tDCS (Jacobson et al., 2012). Of the two techniques, tDCS has some advantages over TMS for neuroergonomic studies because of its relative non-invasiveness, greater portability and lower cost. These methods also allow for the possibility of enhancement of human performance through electrical or magnetic stimulation of the brain. Again, whereas these techniques have been used primarily in studies of basic perception and cognition, they are making their way into neuroergonomic research. Examples include TMS investigations of reasoning and complex decision-making, (McKinley et al., 2012) and tDCS studies of detection of military threats in naturalistic scenes (Clark et al., 2012).

Imaging tells us much more about the brain than simply ‘where things are happening’ (but see, e.g., Uttal, 2011, for a dissenting view). For example, measurements of brain activity before a stimulus is presented can tell us how well subjects will remember a stimulus (Otten et al., 2002; Turk-Browne et al., 2006) or are prepared for a task (Leber et al., 2008; Toffanin et al., 2009). Posner and Rothbart (2007) argue that imaging is just beginning to realize its potential in elucidating (a) different brain networks, (b) neural computation in real time, (c) how assemblies develop over the lifespan and (d) neural plasticity following brain insult or training. As discussed in Chapter 8, a new development, the mapping of the human genome (Venter et al., 2001), offers great potential for understanding the physical basis for individual differences. Molecular genetics provides a set of methodological tools that can inform many issues concerning human brain function. Methods such as candidate-gene analysis and genome-wide association (GWAS) are being used to relate genetic differences to individual performance in tasks involving the network influenced by particular types of genes.

Assigning cognitive functions to brain areas has heuristic value, but most information processing involves multiple areas of the brain and depends on dynamic changes in the brain. Perhaps the most important dynamic process in the brain (other than neural transmission itself) is long-term potentiation, a long-lasting enhancement in signal transmission between two neurons that results from synchronous firing of the neurons. Long-term potentiation enhances synaptic transmission, improving the ability of pre- and postsynaptic neurons to communicate with one another across a synapse, and thus contributes to synaptic plasticity, such as that underlying learning and memory. Another aspect of brain dynamics is synchronization of brain areas. Many recent hypotheses of how information is transmitted between brain areas (e.g. Donner & Siegel, 2011) suggest that it occurs via synchronization of oscillations in different frequency bands.

How does one characterize activity in a passive or resting condition? Raichle et al. (2001) answer this question with regard to activity observed during task processing. They argue that the regional decreases seen during the performance of a task represent the presence of functionality that is ongoing in the resting state and attenuated only when resources are temporarily reallocated during goal-directed behaviour. Default activity can thus be defined only in reference to task activity. The fact that the spatially coherent, spontaneous BOLD activity that is the hallmark of intrinsic activity is also present under anaesthesia (Vincent et al., 2007) suggests that the activity is not associated with conscious mental activity, but rather may reflect a fundamental property of the functional organization of the brain. An intriguing idea is that the default network reveals the maintenance of information for interpreting, responding to or even predicting environmental changes. In this sense, understanding the default network may help us to understand much more about how we adapt to, and learn from, the environment.

Most cognitive research has used single-pulse TMS, in which only one magnetic pulse is delivered. Clinical work, however, has focused on the possibility of using repetitive-pulse TMS (rTMS). Just a single pulse of TMS can interfere momentarily with the functioning of a region or enhance excitability in a region for a short amount of time [less than 500 ms—although these stimulations may have longer-lasting effects on more distant cortical regions (Pascual-Leone et al., 2000)]. rTMS often has longer-lasting effects (Walsh & Cowey, 2000). Unfortunately, the possibilities of rTMS with respect to enhancing cognitive function (or ameliorating the effects of a disorder) are offset by questions about the safety of the technique and the risk of unpleasant side-effects. A related technique, tDCS, involves passing a mild direct electrical current between electrodes on the scalp to modify neuronal membrane resting potential. This is done in a polarity-dependent manner, such that neuron excitability in a given region is either elevated or lowered (Wagner et al., 2007). Both TMS and tDCS might be used to enhance perceptual and cognitive performance (see Chapter 3 and, for a review, Thut et al., 2011).

A number of components of the ERP have been identified and linked to information processing (Handy, 2004; Luck, 2005; Regan, 1989; see Table 1.1). ERP components can be divided roughly into early, exogenous components, which reflect the processing of stimuli, and late-onset, endogenous components related to cognitive processing. For e...