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Biomarker extraction of sustained attention based on brain functional network / 生物医学工程学杂志
Journal of Biomedical Engineering ; (6): 176-181, 2018.
Article in Chinese | WPRIM | ID: wpr-687648
ABSTRACT
Although attention plays an important role in cognitive and perception, there is no simple way to measure one's attention abilities. We identified that the strength of brain functional network in sustained attention task can be used as the physiological indicator to predict behavioral performance. Behavioral and electroencephalogram (EEG) data from 14 subjects during three force control tasks were collected in this paper. The reciprocal of the product of force tolerance and variance were used to calculate the score of behavioral performance. EEG data were used to construct brain network connectivity by wavelet coherence method and then correlation analysis between each edge in connectivity matrices and behavioral score was performed. The linear regression model combined those with significantly correlated network connections into physiological indicator to predict participant's performance on three force control tasks, all of which had correlation coefficients greater than 0.7. These results indicate that brain functional network strength can provide a widely applicable biomarker for sustained attention tasks.

Full text: Available Index: WPRIM (Western Pacific) Type of study: Prognostic study Language: Chinese Journal: Journal of Biomedical Engineering Year: 2018 Type: Article

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Full text: Available Index: WPRIM (Western Pacific) Type of study: Prognostic study Language: Chinese Journal: Journal of Biomedical Engineering Year: 2018 Type: Article