Rhythmic Oscillations in Quantitative EEG Measured During a Continuous Performance Task

Abstract

The objective of the present investigation was to determine if cyclic variations in human performance recorded during a 30 min continuous performance task would parallel cyclic variations in right-hemisphere beta-wave activity. A fast fourier transformation was performed on the quantitative electroencephalogram (qEEG) and the performance record of each participant (N = 62), producing an individual periodogram for each outcome measure. An average periodogram was then produced for both qEEG and performance by combining (averaging) the amplitudes associated with each periodicity in the 62 original periodograms. Periodicities ranging from 1.00 to 2.00 min and from 4.70 to 5.70 min with amplitudes greater than would be expected due to chance were retained (Smith et al. 2003). The results of the present investigation validate the existence of cyclic variations in human performance that have been identified previously (Smith et al. 2003) and extend those findings by implicating right-hemisphere mediated arousal in the process (Arruda et al. 1996, 1999, 2007). Significant cyclic variations in left-hemisphere beta-wave activity were not observed. Taken together, the findings of the present investigation support a model of sustained attention that predicts cyclic changes in human performance that are the result of cyclic changes in right-hemisphere arousal.

Sleep loss and driver performance: Quantitative predictions with zero free parameters

“…It is well established that extended time on task leads to degradations in performance (e.g., Davies & Parasuraman, 1982;Van der Hulst, Meijman, & Rothengatter, 2001). There is also evidence for systematic oscillations in alertness over relatively short periods of a couple of minutes (Arruda, Zhang, Amoss, Coburn, & Aue, 2009). In addition, when people note that they have drifted well off the road, it is likely that they experience a transient spike in alertness, which would allow them to reestablish control.…”

Trial-by-Trial Variations in Subjective Attentional State are Reflected in Ongoing Prestimulus EEG Alpha Oscillations

“…Hence, our finding that attentional state ratings and prestimulus alpha power co-vary strongly when smoothed with a sliding window size of several minutes’ worth of trials is in agreement with this literature. In addition, many studies investigating periodicities in reaction times and error rates in detection tasks have reported cycle times in the range of 2–10 min (e.g., Wertheimer, 1953; Elliott, 1960; Makeig and Inlow, 1993; Conte et al, 1995; Smith et al, 2003; Arruda et al, 2009; Aue et al, 2009). In particular, Monto et al (2008) have demonstrated that somatosensory detection performance and power in all frequency bands are correlated with the phase of infraslow fluctuations (0.1–0.01 Hz, i.e., 10–100 s cycles) of EEG, a finding that could be interpreted as reflecting slow variations in attentional state.…”

Resting-State Neuronal Oscillatory Correlates of Working Memory Performance

“…More specifically, some investigators reported that resting-state activation in the parietal region is consistently linked to an attention network and n-back performance [19], [33]–[35]. Activation in the right frontal and parietal regions have previously been linked to the engagement of visuospatial processing and selective attention [19], [33]–[39]. Additionally, neurophysiological measures of selective attention and cortical arousal (e.g.…”

“…Additionally, neurophysiological measures of selective attention and cortical arousal (e.g. larger delta/theta and beta power) are associated with WM performance and WM capacity [2], [13], [15], [39]–[43].…”