Detecting phasic lapses in alertness using pupillometric measures

Small, nonreflexive pupillary changes are robust physiological indicators of cognitive activity. In the present paper, we examined whether measures of pupillary changes could be used to detect phasic lapses in alertness during a vigilance task. A polynomial curve-fitting method for quantifying parameters from single task-evoked pupillary responses (TEPRs) is described. The TEPR parameters associated with long latency responses (indicating low alertness) were compared to the TEPR parameters associated with normal latency responses (indicating an alert state) within a multilevel modeling framework. Three parameters, pupil diameter, linear pupil dilation rate and curvilinear pupil dilation rate, significantly differed between the long latency and normal latency response types. The results provide preliminary evidence that these parameters would be useful neurocognitive markers of operator state in a bio-behavioral alertness monitoring system.