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Stress Assessment by Prefrontal Relative Gamma

Overview of attention for article published in Frontiers in Computational Neuroscience, September 2016
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Title
Stress Assessment by Prefrontal Relative Gamma
Published in
Frontiers in Computational Neuroscience, September 2016
DOI 10.3389/fncom.2016.00101
Pubmed ID
Authors

Jesus Minguillon, Miguel A. Lopez-Gordo, Francisco Pelayo

Abstract

Stress assessment has been under study in the last years. Both biochemical and physiological markers have been used to measure stress level. In neuroscience, several studies have related modification of stress level to brain activity changes in limbic system and frontal regions, by using non-invasive techniques such as functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). In particular, previous studies suggested that the exhibition or inhibition of certain brain rhythms in frontal cortical areas indicates stress. However, there is no established marker to measure stress level by EEG. In this work, we aimed to prove the usefulness of the prefrontal relative gamma power (RG) for stress assessment. We conducted a study based on stress and relaxation periods. Six healthy subjects performed the Montreal Imaging Stress Task (MIST) followed by a stay within a relaxation room while EEG and electrocardiographic signals were recorded. Our results showed that the prefrontal RG correlated with the expected stress level and with the heart rate (HR; 0.8). In addition, the difference in prefrontal RG between time periods of different stress level was statistically significant (p < 0.01). Moreover, the RG was more discriminative between stress levels than alpha asymmetry, theta, alpha, beta, and gamma power in prefrontal cortex. We propose the prefrontal RG as a marker for stress assessment. Compared with other established markers such as the HR or the cortisol, it has higher temporal resolution. Additionally, it needs few electrodes located at non-hairy head positions, thus facilitating the use of non-invasive dry wearable real-time devices for ubiquitous assessment of stress.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 136 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 136 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 26 19%
Student > Master 19 14%
Researcher 15 11%
Student > Bachelor 13 10%
Student > Doctoral Student 5 4%
Other 18 13%
Unknown 40 29%
Readers by discipline Count As %
Engineering 26 19%
Psychology 23 17%
Neuroscience 12 9%
Computer Science 9 7%
Medicine and Dentistry 6 4%
Other 21 15%
Unknown 39 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 22 September 2016.
All research outputs
#20,342,896
of 22,889,074 outputs
Outputs from Frontiers in Computational Neuroscience
#1,162
of 1,347 outputs
Outputs of similar age
#278,644
of 321,010 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#24
of 33 outputs
Altmetric has tracked 22,889,074 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
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