EEG alpha activity is associated with individual differences in post-break improvement
Introduction
Periods of extended mental workload are taxing on neural and cognitive systems, and often cause those systems to perform at increasingly suboptimal levels over time. The slope of this decline has been labeled the time-on-task (TOT) effect, and understanding its biological basis has been of interest to those seeking to optimize real-world human performance, especially in the nascent field of neuroergonomics (Parasuraman and Wilson, 2008). Under normal conditions, most individuals suffer from the effects of TOT, leaving them vulnerable to making potentially costly errors in field operations. An important question to address, therefore, is whether and how TOT deficits may be arrested or reversed through external intervention, and whether our growing understanding of the neurobiology of these declines may inform the strategies we use to do this.
Historically, fatigue and mental workload have been most commonly studied using electroencephalography (EEG), and these studies have thus far focused on changes associated with task-related activity. Broadly, it has been found that lengthening TOT leads to observable changes in both ongoing EEG activity and event-related potentials locked to task stimuli. Commonly, TOT induces increases in low-frequency theta power (Craig et al., 2012, Paus et al., 1997, Phipps-Nelson et al., 2011), particularly over frontal midline areas (Boksem et al., 2005), as well as increases in alpha power (Klimesch, 1999, Oken and Salinsky, 1992). Several studies also report a shift to greater high-frequency (beta) energy as task time increases (Craig et al., 2012, Foxe et al., 2012); this is thought to reflect compensatory efforts to maintain levels of performance as vigilance and arousal decrease. These EEG changes have been of significant interest to those hoping to find biomarkers of fatigue that may be useful in predicting on-the-job performance and preventing workplace error (Jap et al., 2009, Lal and Craig, 2001).
In comparison with the rich body of findings on the EEG correlates of TOT, changes associated with recovery from mental workload have not been extensively explored. The literature is particularly lacking in laboratory-controlled studies that test the effects of break periods in relieving fatigue and improving performance, with scattered examples showing small improvements with rest (Chen et al., 2010, Phipps-Nelson et al., 2011). It has been a matter of recent debate as to whether brief task switches may reduce TOT (Ariga and Lleras, 2011, Helton and Russell, 2012), indicating that there are aspects of the behavior itself that are still not well understood. Field studies in the ergonomics literature have also demonstrated some beneficial effects of rest breaks on productivity and safety, although the findings in these studies have also been mixed (Folkard and Tucker, 2003, Henning et al., 1997, Tucker et al., 2003). In sum, the relative paucity of data points to the need for more controlled studies relevant to this topic area.
The current work is also motivated by studies which have tested tonic EEG activity during reference or resting periods, and attempted to link this activity to behavior or cognitive function. For example, Klimesch et al. (2000) have found that greater upper alpha and lower theta power in a reference period was associated with better recall on a verbal memory task. To our knowledge, this approach has not been applied to paradigms studying sustained attention and TOT, or to intra-task periods when subjects are at rest. This is important as EEG activity shows different associations with different cognitive processes (Klimesch et al., 2007), necessitating work that elucidates the correlates of each of these functions individually.
In the current study, we administered a challenging sustained attention task to a group of young healthy participants, and investigated the effect of providing a rest opportunity on their performance and electrophysiological activity. We hypothesized that providing this rest would lead to significant improvements in performance (reaction time), and that EEG markers of attention (alpha) and fatigue (theta) would be associated with individual differences in improvement over this rest opportunity. The study was designed to augment our current knowledge of EEG and TOT by examining both decrements and improvements in performance, and to investigate the factors that contribute to effective brain recovery.
Section snippets
Material and methods
31 undergraduates (17 male; mean age = 22.8(3.0)) from the National University of Singapore were recruited for this study via word-of mouth and online advertising. Volunteers were pre-screened via a telephone interview to ensure they were right-handed using the Edinburgh Handedness inventory (Oldfield, 1971), and had no history of chronic physical or mental illnesses. Hearing ability was assessed using the Quick Hearing Check (Koike et al., 1994), and subjects were excluded if their score on this
Behavioral results
Mean accuracy for the auditory oddball task was 90.70% (6.89) for the break condition and 91.03% (9.58) for the no-break condition. The overall false alarm rate was low (1.12 (1.34) for break condition, 1.15 (2.17) for no-break condition). Reaction-time (RT) and accuracy data were averaged into 10-minute bins (Fig. 1). We analyzed the effect of time-on-task on both accuracy and RT using repeated-measures ANOVA with time (six 10-minute bins) and condition (break vs. no-break) as within subject
Discussion
The current study represents one of the first looks at the neural basis of recovery from fatigue during a mid-task break opportunity. In line with previous work, we found relative increases in theta and lower alpha from the first to last five minutes of the task. Furthermore, we found three key points of interest surrounding the break opportunity, which may be summarized as follows: 1) At the group level, behavioral changes ensuing from the five-minute break were small and non-significant, 2)
Conclusion
The current study characterizes the behavioral and electrophysiological responses of healthy adults to a break opportunity in the middle of a sustained attention test. Even in the absence of a group behavioral effect, EEG power in theta and alpha bands provided interesting information about individual differences in the behavioral change following a period of rest. These results may have implications for real-world operators who must maximize the use of break opportunities. Promising avenues of
Acknowledgments
Funding for this research was provided by NEUROEN grant R3940000059232. We acknowledge the assistance of Ong How Hwee in EEG data collection, and Tania Kong and Tse Chun-Yu for assistance in analysis and helpful comments.
Conflict of interest
The authors have no conflict of interest to declare.
References (52)
- et al.
Electrophysiological correlates of anxious rumination
Int. J. Psychophysiol.
(2009) - et al.
Brief and rare mental “breaks” keep you focused: deactivation and reactivation of task goals preempt vigilance decrements
Cognition
(2011) - et al.
Effects of mental fatigue on attention: an ERP study
Cogn. Brain Res.
(2005) - et al.
Vigilance and intrinsic maintenance of alert state: an ERP study
Behav. Brain Res.
(2010) - et al.
Body posture affects electroencephalographic activity and psychomotor vigilance task performance in sleep-deprived subjects
Clin. Neurophysiol.
(2003) - et al.
Paradox lost? Exploring the role of alpha oscillations during externally vs. internally directed attention and the implications for idling and inhibition hypotheses
Int. J. Psychophysiol.
(2003) - et al.
EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis
J. Neurosci. Methods
(2004) - et al.
Alpha rhythm of the EEG modulates visual detection performance in humans
Cogn. Brain Res.
(2004) - et al.
Dual electroencephalogram markers of human sleep homeostasis: correlation between theta activity in waking and slow-wave activity in sleep
Neuroscience
(2000) - et al.
Assessing the effects of caffeine and theanine on the maintenance of vigilance during a sustained attention task
Neuropharmacology
(2012)
A new method for off-line removal of ocular artifact
Electroencephalogr. Clin. Neurophysiol.
Visual discrimination performance is related to decreased alpha amplitude but increased phase locking
Neurosci. Lett.
Signal salience and the mindlessness theory of vigilance
Acta Psychol. (Amst.)
Association of individual resting state EEG alpha frequency and cerebral blood flow
NeuroImage
Using EEG spectral components to assess algorithms for detecting fatigue
Expert Syst. Appl.
EEG alpha and theta oscillations reflect cognitive and memory performance: a review and analysis
Brain Res. Rev.
Induced alpha band power changes in the human EEG and attention
Neurosci. Lett.
Interindividual differences in alpha and theta power reflect memory performance
Intelligence
EEG alpha oscillations: the inhibition-timing hypothesis
Brain Res. Rev.
A critical review of the psychophysiology of driver fatigue
Biol. Psychol.
Imaging brain fatigue from sustained mental workload: an ASL perfusion study of the time-on-task effect
NeuroImage
Tonic, phasic, and transient EEG correlates of auditory awareness in drowsiness
Cogn. Brain Res.
The assessment and analysis of handedness: the Edinburgh inventory
Neuropsychologia
Psychophysiological investigation of vigilance decrement: boredom or cognitive fatigue?
Physiol. Behav.
Sleepiness on the job: continuously measured EEG changes in train drivers
Electroencephalogr. Clin. Neurophysiol.
Rest breaks and accident risk
Lancet
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