Characterizing Psychological Dimensions in Non-Pathological Subjects through Autonomic Nervous System Dynamics

• Main Authors: Mimma eNardelli, Gaetano eValenza, Ioana eCristea, Claudio eGentili, Carmen eCotet, Daniel eDavid, Antonio eLanatà, Enzo Pasquale eScilingo
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2015-03-01
• Series: Frontiers in Computational Neuroscience
• Subjects: Autonomic Nervous System; Heart rate variability; NonLinear Analysis; multiscale entropy; Psychological scales; Cognitive scales
• Online Access: http://journal.frontiersin.org/Journal/10.3389/fncom.2015.00037/full

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 nonlinear 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 nonlinear analysis was performed on Heart Rate Variability, InterBreath Interval series, and Inter-Beat Respiration series, which were considered as monovariate and multivariate measurements. Experimental results show that each ANS feature is linked to specific psychological traits. Moreover, nonlinear 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.