Browsing by Author "Laxminarayan, Srinivas"
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- ItemCan a mathematical model predict an individual's trait-like response to both total and partial sleep loss?(2015-01-12) Ramakrishnan, Sridhar; Lu, Wei; Laxminarayan, Srinivas; Wesensten, Nancy J; Rupp, Tracy L; Balkin, Thomas J; Reifman, JaquesHumans display a trait like response to sleep loss However it is not known whether this trait like response can be captured by a mathematical model from only one sleep loss condition to facilitate neurobehavioural performance prediction of the same individual during a different sleep loss condition In this paper we investigated the extent to which the recently developed unified mathematical model of performance UMP captured such trait like features for different sleep loss conditions We used the UMP to develop two sets of individual specific models for 15 healthy adults who underwent two different sleep loss challenges order counterbalanced separated by 2 4 weeks i 64 h of total sleep deprivation TSD and ii chronic sleep restriction CSR of 7 days of 3 h nightly time in bed We then quantified the extent to which models developed using psychomotor vigilance task data under TSD predicted performance data under CSR and vice versa The results showed that the models customized to an individual under one sleep loss condition accurately predicted performance of the same individual under the other condition yielding on average up to 50 improvement over non individualized group average model predictions This finding supports the notion that the UMP captures an individual s trait like response to different sleep loss conditions
- ItemDose-dependent model of caffeine effects on human vigilance during total sleep deprivation.(2014-08-05) Ramakrishnan, Sridhar; Laxminarayan, Srinivas; Wesensten, Nancy J; Kamimori, Gary H; Balkin, Thomas J; Reifman, JaquesCaffeine is the most widely consumed stimulant to counter sleep loss effects While the pharmacokinetics of caffeine in the body is well understood its alertness restoring effects are still not well characterized In fact mathematical models capable of predicting the effects of varying doses of caffeine on objective measures of vigilance are not available In this paper we describe a phenomenological model of the dose dependent effects of caffeine on psychomotor vigilance task PVT performance of sleep deprived subjects We used the two process model of sleep regulation to quantify performance during sleep loss in the absence of caffeine and a dose dependent multiplier factor derived from the Hill equation to model the effects of single and repeated caffeine doses We developed and validated the model fits and predictions on PVT lapse number of reaction times exceeding 500 ms data from two separate laboratory studies At the population average level the model captured the effects of a range of caffeine doses 50 300 mg yielding up to a 90 improvement over the two process model Individual specific caffeine models on average predicted the effects up to 23 better than population average caffeine models The proposed model serves as a useful tool for predicting the dose dependent effects of caffeine on the PVT performance of sleep deprived subjects and therefore can be used for determining caffeine doses that optimize the timing and duration of peak performance