Almira Kustubayeva

Use of EEG Workload Indices for Diagnostic Monitoring of Vigilance Decrement

Objective: A study was run to test which of five electroencephalographic (EEG) indices was most diagnostic of loss of vigilance at two levels of workload. Background: EEG indices of alertness include conventional spectral power measures as well as indices combining measures from multiple frequency bands, such as the Task Load Index (TLI) and the Engagement Index (EI). However, it is unclear which indices are optimal for early detection of loss of vigilance. Method: Ninety-two participants were assigned to one of two experimental conditions, cued (lower workload) and uncued (higher workload), and then performed a 40-min visual vigilance task. Performance on this task is believed to be limited by attentional resource availability. EEG was recorded continuously. Performance, subjective state, and workload were also assessed. Results: The task showed a vigilance decrement in performance; cuing improved performance and reduced subjective workload. Lower-frequency alpha (8 to 10.9 Hz) and TLI were most sensitive to the task parameters. The magnitude of temporal change was larger for lower-frequency alpha. Surprisingly, higher TLI was associated with superior performance. Frontal theta and EI were influenced by task workload only in the final period of work. Correlational data also suggested that the indices are distinct from one another. Conclusions: Lower-frequency alpha appears to be the optimal index for monitoring vigilance on the task used here, but further work is needed to test how diagnosticity of EEG indices varies with task demands. Application: Lower-frequency alpha may be used to diagnose loss of operator alertness on tasks requiring vigilance.

Diagnostic monitoring of vigilance decrement using EEG workload indices

The resource model of vigilance (Warm, Parasuraman, & Matthews, 2008) suggests that EEG-based indices of workload might be used to monitor the operator’s fitness to sustain signal detection. 92 participants performed a 40 minute vigilance task believed to be sensitive to resource availability. Half performed in a cued condition, half without cues. Findings confirmed that cueing reduces workload and enhances vigilance. EEG was recorded throughout performance. Of the various EEG indices analyzed, lower frequency alpha and the Task Load Index (TLI) corresponded most closely to changes in signal detection rates. Other indices, the Engagement Index (EI) and frontal theta, did not show systematic decrement but discriminated cued and uncued conditions towards the end of the task. Implications of the findings for using EEG to drive adaptive automation are discussed.

Emotional and cognitive Self-Regulation

A brief outline of four studies that investigated interrelations of cognitive and emotional regulation in collaboration between Departments of Psychology of the University of Cincinnati and Kazakh National University is presented in this article. The aim of the first research was to examine the role of EI in regulating the affective response to a potentially threatening video and relation to brain electrical activity. The second study, conducted at the University of Cincinnati, explored the role of emotion in the search for information relevant to decision-making. The third study was devoted to the evaluating the sensitivity of a range of EEG indexes of engagement to time-on-task effects and to workload manipulation (cueing) during vigilance task performance. The fourth research was based on Posner’s theory of executive control and Matthews’ theory of task engagement. Results of empirical studies has theoretical meaning in understanding selfregulation and practical value in different fields of applied psychology.

Individual Differences in Cognition from a Neurophysiological Perspective: The Commentaries

We think this is an open empirical question. A good analogy is the concept of general intelligence, which has been the focus of many recent neuroscience studies. It is ultimately an empirical question as to whether intelligence is best described as a single monolithic construct or in terms of narrower lower-order abilities (e.g., visuospatial ability, verbal intelligence, etc.). Some studies have found important brain structural and functional correlates of general intelligence, when treated as a monolithic construct (e.g., Thompson). However, other work has led potential to refinement or revision of the construct (e.g., placing focus on lower-level processes, such as interference control). The concept of arousal has received less attention in cognitive neuroscience research, but the situation may nevertheless be similar. Is there a monolithic arousal system in the brain? Perhaps not, just as few people would argue that there is a single “intelligence system”; on the other hand, we suspect that when arousal is operationalized in relatively general ways – e.g., in terms of individuals’ propensity to respond to emotional stimuli, their basal activity level, etc. – there will be identifiable neural correlates.