alexa A rodent model of the human psychomotor vigilance test: Performance comparisons.
Bioinformatics & Systems Biology

Bioinformatics & Systems Biology

Journal of Data Mining in Genomics & Proteomics

Author(s): Davis CM, Roma PG, Hienz RD

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Abstract BACKGROUND: The human Psychomotor Vigilance Test (PVT) is commonly utilized as an objective risk assessment tool to quantify fatigue and sustained attention in laboratory, clinical, and operational settings. NEW METHOD: Recent studies have employed a rodent version of the PVT (rPVT) to measure various aspects of attention (lapses in attention, reaction times) under varying experimental conditions. RESULTS: Data are presented here to evaluate the short- and long-term utility of the rPVT adapted for laboratory rats designed to track the same types of performance variables as the human PVT-i.e., motor speed, inhibitory control ("impulsivity"), and attention/inattention. Results indicate that the rPVT is readily learned by rats and requires less than two weeks of training to acquire the basic procedure. Additional data are also presented on the effects of radiation exposure on these performance measures that indicate the utility of the procedure for assessing changes in neurobehavioral function in rodents across their lifespans. COMPARISON WITH EXISTING METHOD(S): Once stable performances are obtained, rats evidence a high degree of similarity to human performance measures, and include similarities in terms of lapses and reaction times, in addition to percent correct and premature responding. Similar to humans, rats display both a vigilance decrement across time on task and a response-stimulus interval effect. CONCLUSIONS: The rPVT is a useful tool in the investigation of the effects of a wide range of variables on vigilance performance that compares favorably to the human PVT and for developing potential prophylactics, countermeasures, and treatments for neurobehavioral dysfunctions. Copyright © 2015 Elsevier B.V. All rights reserved. This article was published in J Neurosci Methods and referenced in Journal of Data Mining in Genomics & Proteomics

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