Nasal and oral breathing modes reconfigure brain network dynamics between stabilizing integration and promoting fragmentation.

Breathing rhythmically coordinates neural oscillations across the brain, yet how the breathing mode (nasal vs. oral) modulates large-scale functional networks over time remains unclear. Building on prior static connectivity findings, this study applied dynamic functional connectivity (dFC) analysis using a hidden Markov model (HMM) to resting-state fMRI data from 20 healthy adults during nasal and oral breathing, focusing on the 0.1-0.2 Hz frequency band. Three recurrent brain states were identified: (1) a weakly connected, segregated state; (2) a globally integrated state dominated by default mode, frontoparietal, salience, and limbic networks; and (3) a partially segregated intermediate state. Compared with oral breathing, nasal breathing stabilized the integrated state, increasing its lifetime (p-FDR = 0.03) and reducing switching rates (p-FDR = 0.002). Oral breathing showed greater fractional occupancy of the intermediate state (p-FDR = 0.03) and a higher probability of transitions from integration to fragmentation (p-FDR = 0.02). Graph-theoretic analysis also revealed that nasal breathing supported a configuration with higher efficiency and lower modularity. Taken together, this study provides the first respiration-entrained, HMM-based dFC analysis of resting-state fMRI, demonstrating that nasal breathing entrains a stable, globally coherent state, whereas oral breathing disrupts this stability and promotes fragmented network organization.