Sympathovagal quotient and resting-state functional connectivity of control networks are related to gut Ruminococcaceae abundance in healthy men.

INTRODUCTION: Heart rate variability (HRV), brain resting-state functional connectivity (rsFC), and gut microbiota (GM) are three recognized indicators of health status, whose relationship has not been characterized. We aimed to identify the GM genera and families related to HRV and rsFC, the interaction effect of HRV and rsFC on GM taxa abundance, and the mediation effect of diet on these relationships. METHODS: Eighty-eight healthy, young Colombian men were included in this cross-sectional study. HRV metrics were extracted from 24-hour Holter monitoring data and the resting functional connectivity strength (FCS) of 15 networks were derived from functional magnetic resonance imaging. Gut microbiota composition was assessed using the sequences of the V3-V4 regions of the 16 S rRNA gene, and diet was evaluated using a food frequency questionnaire. Multivariate linear regression analyses were performed to evaluate the correlations between the independent variables (HRV metrics and FCS) and the dependent variables (GM taxa abundance or alpha diversity indexes). Mediation analyses were used to test the role of diet in the relationship between HRV and GM. RESULTS: The sympathovagal quotient (SQ) and the FCS of control networks were positively correlated with the abundance of the gut Ruminococcaceae family and an unclassified Ruminococcaceae genus (Ruminococcaceae_unc). Additionally, the interaction between the FCS of the control network and SQ reduced the individual main effects on the Ruminococcaceae_unc abundance. Finally, reduced habitual fiber intake partially mediated the relationship between SQ and this genus. CONCLUSION: Two indicators of self-regulation, HRV and the rsFC of control networks, are related to the abundance of gut microbiota taxa in healthy men. However, only HRV is related to habitual dietary intake; thus, HRV could serve as a marker of food choice and GM composition in the future.

Neurophysiological changes associated with training in laparoscopic surgery using EEG: a pilot study.

Laparoscopy is a minimally invasive technique that requires surgeons to acquire special motor skills derived from an extensive training. This work focuses on exploring the neurophysiological changes associated with motor learning. Electroencephalographic (EEG) signals were recorded from eight subjects while performing a bimanual coordination task in a laparoscopic simulator. Spectral power measurements in theta, alpha and beta bands during four training sessions were calculated. Power indices, task score and perception of mental workload were evaluated using analysis of variance to show the effect of training session. Results show improvements in task performance and changes in power measurements associated with the training process. This work opens the possibility to assess the training performance of surgical residents using electrophysiological recordings.