Toward reanimating the laughter‐involved large‐scale brain networks to alleviate affective symptoms

Abstract

Abstract Introduction The practicality of the idea whether the laughter‐involved large‐scale brain networks can be stimulated to remediate affective symptoms, namely depression, has remained elusive. Methods In this study, 25 healthy individuals were tested through 21‐channel quantitative electroencephalography (qEEG) setup upon resting state and while submitted to standardized funny video clips (corated by two behavioral neuroscientists and a verified expert comedian, into neutral and mildly to highly funny). We evaluated the individuals’ facial expressions against the valence and intensity of each stimulus through the Nuldos face analysis software. The study also employed an eye‐tracking setup to examine fixations, gaze, and saccadic movements upon each task. In addition, changes in polygraphic parameters were monitored upon resting state and exposure to clips using the 4‐channel Nexus polygraphy setup. Results The happy facial expression analysis, as a function of rated funny clips, showed a significant difference against neutral videos (p < 0.001). In terms of the polygraphic changes, heart rate variability and the trapezius muscle surface electromyography measures were significantly higher upon exposure to funny vs. neutral videos (p < 0.5). The average pupil size and fixation drifts were significantly higher and lower, respectively, upon exposure to funny videos (p < 0.01). The qEEG data revealed the highest current source density (CSD) for the alpha frequency band localized in the left frontotemporal network (FTN) upon exposure to funny clips. Additionally, left FTN acquired the highest value for theta coherence z‐score, while the beta CSD predominantly fell upon the salience network (SN). Conclusions These preliminary data support the notion that left FTN may be targeted as a cortical hub for noninvasive neuromodulation as a single or adjunct therapy in remediating affective disorders in the clinical setting. Further studies are needed to test the hypotheses derived from the present report.

Keywords

• eye‐tracker
• face analysis
• laughter network
• polygraphy
• qEEG