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  Optimized alpha band patterns correlated with trait anxiety

Vidaurre, C., Nikulin, V. V., & Herrojo Ruiz, M. (2021). Optimized alpha band patterns correlated with trait anxiety. In Proceedings of the IEEE 34th International Symposium on Computer-Based Medical Systems (CBMS). doi:10.1109/CBMS52027.2021.00051.

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 Creators:
Vidaurre, C.1, Author
Nikulin, Vadim V.2, Author           
Herrojo Ruiz, M.3, Author
Affiliations:
1Public University of Navarre, Spain, ou_persistent22              
2Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634549              
3Centre for Cognition and Decision Making, National Research University Higher School of Economics, Moscow, Russia, ou_persistent22              

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Free keywords: Neuroimaging; Brain; Correlation; Mental disorders; Sociology; Biomarkers; Spatial filters
 Abstract: Anxiety is one of the most prevalent mental disorders, affecting approximately 5-10% of the adult population worldwide. It can severely impact quality of life, but also place a large burden on the health systems. Despite its omnipresence and impact on mental and physical health, most of the individuals suffering from anxiety do not receive appropriate treatment. Furthermore, while neuroimaging research consistently implicated subcortical structures such as amygdala, hippocampus and prefrontal cortex in anxiety, there is still a lack of consensus on the underlying neurophysiological processes contributing to this condition. Thus, the objective neurophysiological markers for anxiety remain elusive. Methods allowing non-invasive recording and assessment of cortical processing provide an opportunity to help identify anxiety signatures that could be used as intervention targets. In this paper, we tackle this problem by applying a regression spatial filter called Source-Power Comodulation (SPoC) to trait anxiety data of 43 individuals. By maximizing the correlation of alpha band power and the level of trait anxiety in resting state electroencephalography (EEG) we are able to obtain neurophysiologically meaningful patterns that should be helpful in the search of biomarkers for mental disorders.

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Language(s): eng - English
 Dates: 2021-07-12
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1109/CBMS52027.2021.00051
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Title: Proceedings of the IEEE 34th International Symposium on Computer-Based Medical Systems (CBMS)
Source Genre: Proceedings
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