Event-Related Brain Dynamics in Continuous Sustained-Attention Tasks

Event-related brain dynamics of electroencephalographic (EEG) activity in a continuous compensatory tracking task (CTT) and in a continuous driving simulation were analyzed by independent component analysis (ICA) and time-frequency techniques. We showed that changes in the level of subject performance are accompanied by distinct changes in EEG spectrum of a class of bilateral posterior independent EEG components. During periods of high-error (drowsy) performance, tonic alpha band EEG power was significantly elevated, compared to that during periods of low-error (alert) performance. In addition, characteristic transient (phasic) alpha and other band increases and decreases followed critical task events, depending on current performance level. These performance-related and event-related spectral changes were consistently observed across subjects and sessions, and were remarkably similar across the two continuous sustained-attention tasks.

[1]  R. Ogilvie.  The process of falling asleep. , 2001, Sleep medicine reviews.

[2]  T. Sejnowski,et al.  Estimating alertness from the EEG power spectrum , 1997, IEEE Transactions on Biomedical Engineering.

[3]  Tzyy-Ping Jung,et al.  Imaging brain dynamics using independent component analysis , 2001, Proc. IEEE.

[4]  T. Sejnowski,et al.  Removing electroencephalographic artifacts by blind source separation. , 2000, Psychophysiology.

[5]  S. Makeig.  Auditory event-related dynamics of the EEG spectrum and effects of exposure to tones. , 1993, Electroencephalography and clinical neurophysiology.

[6]  Terrence J. Sejnowski,et al.  Independent Component Analysis Using an Extended Infomax Algorithm for Mixed Subgaussian and Supergaussian Sources , 1999, Neural Computation.

[7]  Terrence J. Sejnowski,et al.  An Information-Maximization Approach to Blind Separation and Blind Deconvolution , 1995, Neural Computation.

[8]  S. Makeig,et al.  Lapses in alertness: coherence of fluctuations in performance and EEG spectrum. , 1993, Electroencephalography and clinical neurophysiology.

[9]  R. Oostenveld,et al.  Validating the boundary element method for forward and inverse EEG computations in the presence of a hole in the skull , 2002, Human brain mapping.

[10]  T. Sejnowski,et al.  Awareness during drowsiness: dynamics and electrophysiological correlates. , 2000, Canadian journal of experimental psychology = Revue canadienne de psychologie experimentale.

[11]  Scott Makeig,et al.  COMPTRACK: A Compensatory Tracking Task for Monitoring Alertness. , 1995 .

[12]  T. Jung,et al.  Changes in alertness are a principal component of variance in the EEG spectrum , 1995, Neuroreport.

[13]  Tzyy-Ping Jung,et al.  Analyzing Event-Related Brain Dynamics in Continuous Compensatory Tracking Tasks , 2005, 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference.

[14]  P. R. Davidson,et al.  Frequent lapses of responsiveness during an extended visuomotor tracking task in non‐sleep‐deprived subjects , 2006, Journal of sleep research.

[15]  Arnaud Delorme,et al.  EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis , 2004, Journal of Neuroscience Methods.

[16]  Ruey-Song Huang,et al.  Selection of valid and reliable EEG features for predicting auditory and visual alertness levels. , 2001, Proceedings of the National Science Council, Republic of China. Part B, Life sciences.

[17]  T. Jung,et al.  Tonic, phasic, and transient EEG correlates of auditory awareness in drowsiness. , 1996, Brain research. Cognitive brain research.