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Characterizing psychological dimensions in non-pathological subjects through autonomic nervous system dynamics

Overview of attention for article published in Frontiers in Computational Neuroscience, March 2015
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Title
Characterizing psychological dimensions in non-pathological subjects through autonomic nervous system dynamics
Published in
Frontiers in Computational Neuroscience, March 2015
DOI 10.3389/fncom.2015.00037
Pubmed ID
Authors

Mimma Nardelli, Gaetano Valenza, Ioana A. Cristea, Claudio Gentili, Carmen Cotet, Daniel David, Antonio Lanata, Enzo P. Scilingo

Abstract

The objective assessment of psychological traits of healthy subjects and psychiatric patients has been growing interest in clinical and bioengineering research fields during the last decade. Several experimental evidences strongly suggest that a link between Autonomic Nervous System (ANS) dynamics and specific dimensions such as anxiety, social phobia, stress, and emotional regulation might exist. Nevertheless, an extensive investigation on a wide range of psycho-cognitive scales and ANS non-invasive markers gathered from standard and non-linear analysis still needs to be addressed. In this study, we analyzed the discerning and correlation capabilities of a comprehensive set of ANS features and psycho-cognitive scales in 29 non-pathological subjects monitored during resting conditions. In particular, the state of the art of standard and non-linear analysis was performed on Heart Rate Variability, InterBreath Interval series, and InterBeat Respiration series, which were considered as monovariate and multivariate measurements. Experimental results show that each ANS feature is linked to specific psychological traits. Moreover, non-linear analysis outperforms the psychological assessment with respect to standard analysis. Considering that the current clinical practice relies only on subjective scores from interviews and questionnaires, this study provides objective tools for the assessment of psychological dimensions.

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Mendeley readers

The data shown below were compiled from readership statistics for 83 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 1%
Germany 1 1%
Unknown 81 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 17%
Researcher 14 17%
Other 6 7%
Student > Master 6 7%
Professor 5 6%
Other 18 22%
Unknown 20 24%
Readers by discipline Count As %
Psychology 21 25%
Medicine and Dentistry 9 11%
Engineering 8 10%
Neuroscience 5 6%
Computer Science 3 4%
Other 11 13%
Unknown 26 31%