Literature DB >> 18715725

A definition of drowsiness: one purpose for sleep?

Jeremy D Slater1.   

Abstract

While significant research has been done into the physiological mechanisms that underlie sleep and the sleep/wake cycle, the available data regarding the nature of drowsiness is far more limited. An objective measurement of drowsiness would have clinical utility, and a precise definition of the drowsy state could offer insights into the nature and purpose of sleep. Studies utilizing fMRI have demonstrated increased area of central nervous system involvement with tasks of increasing complexity. Preliminary data from studies of magnetoencephalography (MEG) with a receptive language task have demonstrated a progressive increase in global coherence of activity between MEG sensors with increasing drowsiness. The relationship between global coherence and the level of drowsiness suggests that the former may serve as an objective measurement of the latter. If true, the relationship suggests the hypothesis that drowsiness may be defined as a progressive loss of cortical network processing efficiency, requiring the recruitment of greater amounts of cortical tissue to perform the same task.

Mesh:

Year:  2008        PMID: 18715725     DOI: 10.1016/j.mehy.2008.05.035

Source DB:  PubMed          Journal:  Med Hypotheses        ISSN: 0306-9877            Impact factor:   1.538


  3 in total

1.  Electroencephalographic Measurement on Post-stroke Sensory Deficiency in Response to Non-painful Cold Stimulation.

Authors:  Yanhuan Huang; Jiao Jiao; Junyan Hu; Chihchia Hsing; Zhangqi Lai; Yang Yang; Zengyong Li; Xiaoling Hu
Journal:  Front Aging Neurosci       Date:  2022-05-11       Impact factor: 5.702

2.  EEG-Based Index for Timely Detecting User's Drowsiness Occurrence in Automotive Applications.

Authors:  Gianluca Di Flumeri; Vincenzo Ronca; Andrea Giorgi; Alessia Vozzi; Pietro Aricò; Nicolina Sciaraffa; Hong Zeng; Guojun Dai; Wanzeng Kong; Fabio Babiloni; Gianluca Borghini
Journal:  Front Hum Neurosci       Date:  2022-05-20       Impact factor: 3.473

3.  A Hybrid Approach to Detect Driver Drowsiness Utilizing Physiological Signals to Improve System Performance and Wearability.

Authors:  Muhammad Awais; Nasreen Badruddin; Micheal Drieberg
Journal:  Sensors (Basel)       Date:  2017-08-31       Impact factor: 3.576

  3 in total

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