4.5 Article

Predicting vulnerability to sleep deprivation using diffusion model parameters

Journal

JOURNAL OF SLEEP RESEARCH
Volume 23, Issue 5, Pages 576-584

Publisher

WILEY-BLACKWELL
DOI: 10.1111/jsr.12166

Keywords

fatigue; human factors; inter-individual differences; predicting performance

Funding

  1. National Research Foundation/National Medical Research Council, Singapore [STaR 004/2008]

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We used diffusion modelling to predict vulnerability to decline in psychomotor vigilance task (PVT) performance following a night of total sleep deprivation (SD). A total of 135 healthy young adults (69 women, age = 21.9 +/- 1.7 years) participated in several within-subject cross-over design studies that incorporated the PVT. Participants were classified as vulnerable (lower tertile) or non-vulnerable (upper tertile) according to their change in lapse rate [lapse = reaction time (RT) >= 500 ms] between the evening before (ESD) and the morning after SD. RT data were fitted using Ratcliff's diffusion model. Although both groups showed significant change in RT during SD, there was no significant group difference in RT during the ESDsession. In contrast, during ESD, the mean diffusion drift of vulnerable subjects was significantly lower than for non-vulnerable subjects. Mean drift and non-decision times were both adversely affected by sleep deprivation. Both mean drift and non-decision time showed significant state x vulnerability interaction. Diffusion modelling appears to have promise in predicting vulnerability to vigilance decline induced by a night of total sleep deprivation.

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