A Multiscale Spatiotemporal Causal Mapping Algorithm for Revealing Neural Network Mechanisms of Transcutaneous...

Area of Science:

• Neuroimaging
• Computational Neuroscience
• Systems Neuroscience

Background:

• Neural mechanisms of transcutaneous auricular vagus nerve stimulation (taVNS) remain unclear due to limitations in analyzing brain connectivity.
• Existing analytical methods struggle with multiscale functional connectivity and causal inference in fMRI signals.

Purpose of the Study:

• To develop a novel algorithm, Multiscale Spatiotemporal Causal Mapping (MSTCM), for robust multiscale functional connectivity and causal inference.
• To investigate the neural effects of taVNS on large-scale brain networks using the proposed MSTCM algorithm.

Main Methods:

• Developed and validated the Multiscale Spatiotemporal Causal Mapping (MSTCM) algorithm integrating community-aware multiscale functional connectivity and delay-compensated causal inference.
• Evaluated MSTCM performance against seven existing causal inference algorithms using simulated fMRI data.
• Applied MSTCM to resting-state fMRI data before and after taVNS in four predefined cortical networks.

Main Results:

• MSTCM significantly outperformed existing algorithms in precision, sensitivity, MCC, and AUC.
• taVNS modulated functional connectivity, reducing coupling between L-LSMC and R-IPS.
• taVNS enhanced global efficiency, salience network (SN) integration, and DAN to SN information flow, while weakening DAN connectivity.

Conclusions:

• taVNS may improve cognitive flexibility and emotional regulation by optimizing large-scale network efficiency and shifting information processing.
• The study provides a novel methodological approach (MSTCM) for brain connectivity analysis.
• New neuroimaging evidence supports the clinical potential of taVNS for cognitive and emotional enhancement.