Effects of sleep deprivation on auditory and visual memory tasks.

Department of Psychology, Stephen F. Austin State University, Nacogdoches, TX 75962, USA.
Perceptual and Motor Skills (Impact Factor: 0.66). 11/2005; 101(2):451-67. DOI: 10.2466/PMS.101.6.451-467
Source: PubMed

ABSTRACT Probe recognition tasks have shown the effects of sleep deprivation following a full night of sleep loss. The current study investigated shorter durations of deprivation by testing 11 subjects for accuracy and response time every 2 hr. from 10 p.m. through 8 a.m. We replicated Elkin and Murray's auditory single-probe recognition task using the number triplets and added two visual tasks with number and shape triplets. Series of six stimuli were each followed by a probe, which was presented after 2.5 sec. as a short delay or 20 sec. as a long delay. Accuracy performance showed a significant decrease for the long delay beginning after 4 a.m. for the two visual tasks. Response times were significantly slower for the visual shapes task using the short delay. Visual tasks, especially shapes, may be more prone to disruption by sleep deprivation, given the visual information load and the briefness of iconic memory.

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    ABSTRACT: Driver sleepiness due to sleep deprivation is a causative factor in 1% to 3% of all motor vehicle crashes. In recent studies, the importance of developing driver fatigue countermeasure devices has been stressed, in order to help prevent driving accidents and errors. Although numerous physiological indicators are available to describe an individual's level of alertness, the EEG signal has been shown to be one of the most predictive and reliable, since it is a direct measure of brain activity. In the present study, multichannel EEG data that were collected from 20 sleep-deprived subjects during real environmental conditions of driving are presented for the first time. EEG data's annotation made by two independent Medical Doctors revealed an increase of slowing activity and an acute increase of the alpha waves 5-10 seconds before driving events. From the EEG data that were collected, the Relative Band Ratio (RBR) of the EEG frequency bands, the Shannon Entropy, and the Kullback-Leibler (KL) Entropy were estimated for each one second segment. The mean values of these measurements were estimated for 5 minutes periods. Analysis revealed a significant increase of alpha waves relevant band ratios (RBR), a decrease of gamma waves RBR, and a significant decrease of KL entropy when the first and the last 5-min periods were compared. A rapid decrease of both Shannon and K-L entropies was observed just before the driving events. Conclusively, EEG can assess effectively the brain activity alterations that occur a few seconds before sleeping/drowsiness events in driving, and its quantitative measurements can be used as potential sleepiness indicators for future development of driver fatigue countermeasure devices.
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