Prediction of Reaction Time and Vigilance Variability From Spatio-Spectral Features of Resting-State EEG in a Long Sustained Attention Task (original) (raw)
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Electrophysiological Correlates of Vigilance During a Continuous Performance Test in Healthy Adults
Applied Psychophysiology and Biofeedback, 2004
The present study evaluated patterns of electrophysiological activity associated with sustained vigilance in healthy adults. Quantitative electroencephalographs (QEEG) were recorded during the performance of a Continuous Performance Test (CPT). Participants were divided into low and high vigilance groups based upon their reaction time changes between the early and late portions of the CPT. Coherence measures were calculated from the QEEG across the baseline, early CPT, and late CPT experimental conditions. Participants in the low vigilance group had higher baseline and CPT frontal to posterior coherence in the alpha and beta bands suggestive of a less vigilant state throughout the entire study. Additionally, the low vigilance group had a significantly greater beta 1 band coherence drop from baseline to the initial portion of the CPT than the high vigilance group. The combined groups had significantly lower amounts of right hemisphere frontal to posterior coherence across a number of frequency bands throughout all of the phases of the study when compared to the homologous left hemisphere sites. These interhemispheric coherence differences are consistent with vigilance network theories that implicate the right frontal and parietal lobes in the maintenance of sustained attention (M. I. Posner & M. E. Raichle, 1994).
International Journal of Human–Computer Interaction, 2017
This research investigated a brain-computer interface (BCI) for classifying vigilance states. We employed a BCI approach based on event-related potential (ERP) and spectral features of EEG data derived from an auditory oddball paradigm. A 128channel EEG system recorded potentials while participants simultaneously completed a prolonged visual match-to-sample task. We hypothesized that better classification rates would be found for a group of "bored" participants, as compared to the not-bored A c c e p t e d M a n u s c r i p t participants. The best classification rates were found by extracting EEG features from gamma frequencies at middle and late latencies (for the standard tones). Critically, the BCI paradigm was most effective for the bored participants (mean misclassification rate = 13%), as compared to the not-bored participants (mean misclassification rate = 21%). These findings extend our knowledge of reliable latencies and spectral features of ERP data most salient to the classification of vigilance states.
Electroencephalography (EEG)-derived markers to Measure Components of Attention Processing
2017
Although extensively studied for decades, attention system remains an interesting challenge in neuroscience field. The Attention Network Task (ANT) has been developed to provide a measure of the efficiency for the three attention components identified in the Posner’s theoretical model: alerting, orienting and executive control. Here we propose a study on 15 healthy subjects who performed the ANT. We combined advanced methods for connectivity estimation on electroencephalographic (EEG) signals and graph theory with the aim to identify neuro-physiological indices describing the most important features of the three networks correlated with behavioral performances. Our results provided a set of band-specific connectivity indices able to follow the behavioral task performances among subjects for each attention component as defined in the ANT paradigm. Extracted EEG-based indices could be employed in future clinical applications to support the behavioral assessment or to evaluate the infl...
We measured the influence of EEG vigilance regulation pattern on early visual perception continuously with steady state visual evoked potentials (SSVEP). We identified subjects with stable vs. unstable regulation pattern by means of the VIGALL algorithm applied to a 15-min resting EEG. We found an increase in SSVEP amplitudes in the unstable subjects over the time course of the experiment but not in the stable subjects. a b s t r a c t Objective: To investigate influences of EEG-vigilance regulation patterns on perceptual processing during sustained visual attention in early visual areas. Methods: We compared a subject group with stable vigilance regulation to a group with unstable EEG-vigilance regulation. A rapid serial visual presentation stream (RSVP) elicited a 7.5 Hz steady state visual evoked potential (SSVEP), a continuous sinusoidal brain response as a measure of attentional resource allocation during sustained attention in early visual cortex. Subjects performed a target discrimination task. 150 trials were divided into two parts (75 trials each, trial duration: 11 s). Results: A significant interaction vigilance group by experimental part provided significantly greater SSVEP amplitudes for the unstable group in the second compared to the first part of the experiment. Both groups showed training effects with increased hit rates and d 0-values in the second part of the experiment. Conclusions: The unexpected finding of SSVEP amplitude increase for the unstable group might be due to competitive interactions for neural resources between the alpha response and SSVEPs. Significance: Individual patterns of EEG-vigilance regulation have a moderate impact on early sensory processing during sustained visual attention that is not paralleled in task performance.
International Journal of Psychophysiology, 1999
w Arruda and colleagues Arruda, J.E., Weiler, M.D., . A guide for applying principalx component analysis and confirmatory factor analysis to qEEG data. Int. J. Psychophysiol. 23, 63᎐81. recently described seven neurophysiological measures that were previously derived and confirmed using factor analytic Ž . procedures and the quantitative electroencephalogram EEG sampled from 208 normal controls during an auditory Ž . continuous performance test CPT . The purpose of the present investigation was to further test the validity of these empirically derived measures by examining each measure's relationship with CPT-related declines in performance.
Estimating alertness from the EEG power spectrum
1997
In tasks requiring sustained attention, human alertness varies on a minute time scale. This can have serious consequences in occupations ranging from air tra c control to monitoring of nuclear power plants. Changes in the electroencephalographic (EEG) power spectrum accompany these uctuations in the level of alertness, as assessed by measuring simultaneous changes in EEG and performance on an auditory monitoring task. By combining power spectrum estimation, principal component analysis and arti cial neural networks, we show that continuous, accurate, noninvasive, and near real-time estimation of an operator's global level of alertness is feasible using EEG measures recorded from as few as two central scalp sites. This demonstration could lead to a practical system for noninvasive monitoring of the cognitive state of human operators in attention-critical settings.
Neural network analysis of event related potentials and electroencephalogram predicts vigilance
1993
Automated monitoring of vigilance in attention intensive tasks such as air traffic control or sonar operation is highly desirable. As the operator monitors the instrument, the instrument would monitor the operator, insuring against lapses. We have taken a first step toward this goal by using feedforward neural networks trained with backpropagation to interpret event related potentials (ERPs) and electroencephalogram (EEG) associated with periods of high and low vigilance. The accuracy of our system on an ERP data set averaged over 28 minutes was 96%, better than the 83% accuracy obtained using linear discriminant analysis. Practical vigilance monitoring will require prediction over shorter time periods. We were able to average the ERP over as little as 2 minutes and still get 90% correct prediction of a vigilance measure. Additionally, we achieved similarly good performance using segments of EEG power spectrum as short as 56 sec.
Comparison of QEEG and response accuracy in good vs poorer performers during a vigilance task
International Journal of Psychophysiology, 1993
Subjects performed an auditory continuous performance test requiring them to detect targets in a series of letters presented at a rate of 2/s. 2-min samples of EEG were obtained from eight bipolar sites during a resting condition and during early and late (7-10 min) test performance. EEG power spectra from 27 subjects whose performance accuracy decreased between these latter periods (LoVig group) were compared with those from 27 subjects who maintained a constant level of performance (HiVig group). In both groups EEG power changed significantly between resting and test conditions for all frequency bands: beta power increased, especially in fronto-temporal and temporal left-hemisphere sites; alpha and posterior theta decreased; anterior theta and delta increased. Significant changes also were found between early and late test performance: anterior theta and delta power decreased in both groups; temporal beta power decreased in the LoVig group only, and is thus considered the best indicator of performance changes. Other differences found between groups were across conditions. The HiVig group had more anterior beta and less posterior alpha and theta than the LoVig group. EEG results are discussed in relation to an explanation of vigilance errors based on signal detection theory.