ePoster

CENTRAL AUTONOMIC NETWORK (CAN) INVOLVEMENT IN CARDIAC ELECTROPHYSIOLOGICAL REGULATION

Liping Lanand 1 co-author

Max Planck Institute for Human Cognitive and Brain Sciences

FENS Forum 2026 (2026)
Barcelona, Spain
Board PS07-10AM-647

Presentation

Date TBA

Board: PS07-10AM-647

Poster preview

CENTRAL AUTONOMIC NETWORK (CAN) INVOLVEMENT IN CARDIAC ELECTROPHYSIOLOGICAL REGULATION poster preview

Event Information

Poster Board

PS07-10AM-647

Abstract

Cardiac responses to central autonomic network (CAN) regions may be reflected in every heartbeat, but the co-occurrence of heart-specific autonomic dynamics in the brain remains unclear. In this study, we combine fMRI with ECG to explore the role of the CAN in the dynamics of heart-brain interaction. We analyzed participates with both ECG and fMRI scanning in the LIFE dataset. Subjects were without neurologic disease (N = 1100, 507 F; M=69.79; SD=4.63). Modularity is used to quantify the within-module connection densities. Degree centrality (DC) is used to evaluate the significance of CAN regions for the network integrity. CAN components are selected based on a meta-analysis of autonomic correlates. We used the modularity of the CAN to discriminate two groups with a median cutoff and performed permutation-based t-tests to detect the ECG clusters that show significant differences. Multiple regression analyses were conducted to associate averaged P wave duration, PR intervals, QRS duration and QT intervals with DC and FC of CAN regions, controlled for age, sex and head motion. As a result, the elevation of PQ and ST segments in the inferior direction is linked to lower modularity of CAN. QT intervals are significantly positively correlated with the DC of the pregenual anterior cingulate cortex (pgACC) (r=0.082, p=0.007). pgACC connections with the right frontal pole are positively correlated with QT intervals (r=0.14, p < 0.05 FWE-corrected). The findings indicate that CAN regions involved in autonomic processing play roles in cardiac activity, providing a novel insight into cardiac autonomic processing.

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