Using computational cognitive modeling to predict dual-task performance with sleep deprivation.
OBJECTIVE
The effects of fatigue on multiple-task performance were explored through computational cognitive modeling.


BACKGROUND
Fatigue typically has a negative impact on human performance. Biomathematical models exist that characterize the dynamics of human alertness, but the link between alertness and in situ performance on specific tasks is tenuous. Cognitive architectures offer a principled means of establishing that link.


METHODS
We implemented mechanisms for fatigue, which produce microlapses in cognitive processing, into an existing model, adaptive control of thought-rational, and validated the performance predictions with Bratzke, Rolke, Ulrich, and Peters' data on fatigue and multiple-task performance.


RESULTS
The microlapse model replicated the human performance results very well with zero free parameters, although the fit was improved when we allowed two individual differences parameters to vary.


CONCLUSIONS
Increased frequency of microlapses as a result of fatigue provides a parsimonious explanation for the impact of fatigue on dual-task performance and is consistent with previous research.


CONCLUSIONS
Our results illustrate how using biomathematical models of fatigue in conjunction with a cognitive architecture can result in accurate predictions of the effects of fatigue on dual-task performance. Extending and generalizing this capability has potential utility in any safety-critical domain in which fatigue may affect performance.
Gunzelmann
Glenn
G
Air Force Research Laboratory, 711 HPW/RHAC, 6030 S. Kent St., Mesa, AZ 85212-6061, USA. glenn.gunzelmann@us.af.mil
Byrne
Michael D
MD
Gluck
Kevin A
KA
Moore
L Richard
LR
D001143:Arousal / Q000502:physiology; D003071:Cognition / Q000502:physiology; D003072:Cognition Disorders / Q000503:physiopathology; D005221:Fatigue / Q000503:physiopathology; D006801:Humans; D008954:Models, Biological; D012892:Sleep Deprivation / Q000503:physiopathology; D013647:Task Performance and Analysis; D014851:Wakefulness