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Title: Brain markers of executive control in task management
Author: Roberts, Adam C.
ISNI:       0000 0004 2720 2673
Awarding Body: University of Sheffield
Current Institution: University of Sheffield
Date of Award: 2009
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The primary goal of the empirical research outlined in this thesis was to examine the role of the central executive in task management using EEG imaging methods. To achieve this goal, a series of experiments were conducted in order to determine decrements during complex task performance, and explore the relative contributions of executive fatigue and task load in the onset of compensatory control mechanisms which are said to manage goal directed activity. These experiments were based around a theoretical framework of neural correlates of Compensatory Control, drawing on evidence from imaging and psychophysiological studies. A laboratory-based complex process control task (aCAMS) was used to investigate the control of various life support systems, such as oxygen, pressure, carbon dioxide, humidity, and temperature in a simulated spaceship environment. The results of the automatic control experiment revealed no effect of fatigue, implicating a high level of goal protection. However, the results of the manual control experiment showed changes in many psychophysiological measures with load, with high inter-individual differences indicating the presence of different task strategies across operators. The results of more detailed analysis showed that, upon the examination of short-term changes, prefrontal theta response dropped in relation to task error reflecting a re-evaluation of task goals, and that this could be predicted based on the combination of prefrontal theta response and sub-optimal control strategies. The third and fourth experiments modified the task's primary operational criteria using adaptive automation, and found that it provided benefits in task performance, and automation interventions - changes in the level of automation, produced improved operator performance at individual levels of load. Taken together, these results demonstrate a number of ways that adaptive automation can be developed using psychophysiological markers of executive function.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available