Pipeline for estimating arousal–FC coupling from fMRI and pupillometry.

(A) Concurrent 7T fMRI and eye tracking were collected during resting state and naturalistic movie watching. (B) Functional connectivity (FC) was computed over sliding windows to obtain time-resolved FC for each pair of brain regions. (C) Pupil diameter was preprocessed to obtain a continuous arousal time series. Arousal–FC coupling for each connection was then defined as the Pearson correlation between its windowed FC time course and the corresponding arousal fluctuations. (D) These edgewise coupling values yielded a dense arousal–FC coupling matrix per run, which served as the input for analyses of community structure, hemispheric asymmetry, and cross-paradigm consistency. (E) The connections were categorized based on the hemispheres of the connected regions: Left-Left (LL) and Right-Right (RR) represent intra-hemispheric connections; Left-Right (LR) and Right-Left (RL) represent inter-hemispheric connections. This classification enabled hemisphere-specific analyses of arousal-FC coupling.

Arousal–FC coupling partitions the connectome into seven distinct connectivity communities.

(A) Unsupervised clustering of edgewise arousal–FC coupling identified seven stable communities, demonstrating that arousal-linked modulation is organized into low-dimensional structure rather than uniformly distributed across connections. (B) Mapping communities onto network-pair space revealed distinct and reproducible composition profiles (upper panel), with some communities dominated by heteromodal interactions and others enriched in H–U or U–U network pairs (bottom panel). (C) Community participation entropy varied systematically across connection modal types: U–U network pairs showed lower entropy, indicating concentrated engagement in a small subset of communities, whereas H-H and H–U network pairs exhibited significantly higher entropy (p = 0.002), reflecting broader distribution across communities. (D) Dominant-community assignments confirmed this organization, showing that heteromodal interactions load onto multiple arousal-sensitive communities, whereas U–U network pairs show more restricted community involvement.

Arousal-related connectivity communities exhibit community-specific hemispheric asymmetry.

(A) Integration indices for each network pair revealed significant leftward or rightward deviations from a spatial permutation null, indicating that arousal differentially modulates between- and within-hemisphere interactions for specific network pairs. (B) Segregation indices identified network pairs showing hemisphere-specific strengthening of within-hemisphere connectivity, further demonstrating that lateralization is localized rather than global. (C–D) Community-averaged integration and segregation values showed that hemispheric biases vary across communities and are not determined solely by connection modal type, underscoring the community-specific nature of the asymmetry. (E) Aggregating all significantly lateralized network pairs, each community exhibited a distinct integration–segregation profile, revealing unique hemispheric signatures across communities. (F) Low similarity among communities’ integration and segregation patterns confirmed that arousal imposes multiple, community-specific forms of hemispheric asymmetry, rather than a single unified left- or right-dominant pattern.

Regional affiliation patterns reveal a lateralized division of labor within the ventral attention network (VAN).

(A–B) Nodal-level community affiliation matrices, computed separately for LL, LR, RL, and RR edges, showed substantial heterogeneity in how nodes distribute their arousal–FC coupling across the seven communities, with distinct patterns emerging across canonical networks. For visualization purposes, Figure A is restricted to displaying values where the proportion exceeds 0.2. (C) Nodal-level community affiliation entropy revealed a systematic network gradient, in which heteromodal systems displayed more selective participation, whereas unimodal and dorsal attention regions showed broader, more distributed engagement across communities (p < 10⁻¹⁰). (D) The VAN exhibited a pronounced hemispheric dissociation: the left VAN showed significantly higher entropy than the right VAN (p < 10⁻¹⁰), indicating greater flexibility and broader multi-community participation. (E) Within the community most strongly recruiting the right VAN (community 7), we observed a significant rightward segregation bias (p_FDR < 0.001). (F) No corresponding integration bias was detected, suggesting that arousal selectively strengthens right intra-hemispheric cohesion without increasing cross-hemispheric coupling. The color of each box corresponds to the community identity. Statistical significance: * p_FDR < 0.01; ** p_FDR < 0.001.

Spatial heterogeneity—not mean shifts—drives arousal-related hemispheric asymmetry.

(A) Mean integration and segregation values showed no consistent hemispheric bias across individual communities or at the whole-brain (WB) level, indicating minimal imbalance in overall modulation strength. (B) Spatial heterogeneity, quantified as the slope of integration or segregation values ranked along a lateralization axis, was significantly steeper in every community compared with the whole-brain baseline (all p_FDR < 0.0001). These effects demonstrate that hemispheric asymmetry arises from spatially patterned variation, not from uniform shifts in mean modulation. (C) Leave-one-out analyses revealed that this heterogeneity reflects distributed contributions from many network pairs, rather than being driven by a few extreme edges. (D) Contribution patterns for integration and segregation were strongly correlated (rho ≈ 0.73), indicating coordinated spatial organization across metrics. (E–F) Similarity in contribution patterns between communities was positively associated with similarity in communities’ intrinsic structure (integration: rho ≈ 0.33; segregation: rho ≈ 0.36), showing that spatial heterogeneity is constrained by each community’s underlying connectivity architecture. Statistical note: * p_FDR < 0.01; ** p_FDR < 0.001; *** p_FDR < 0.0001.

Community structure and hemispheric asymmetry of arousal–FC coupling are preserved across resting state and movie watching.

(A) Communities derived from rest and movie data were aligned using Jaccard similarity–based optimal matching, revealing robust correspondence between paradigms (rho ≈ 0.63). (B) Network-pair composition profiles for each community were strongly correlated across paradigms (mean rho ≈ 0.72), indicating that the modular organization of arousal–FC coupling is highly stable across cognitive contexts. The heteromodal-dominated community (Community 7), which shows pronounced right-hemisphere segregation, exhibited exceptionally high cross-paradigm similarity (rho ≈ 0.95), suggesting context-independent expression of its arousal-linked lateralization pattern. Together, these findings demonstrate that arousal imposes a modular and lateralized connectivity architecture that remains highly consistent across resting and naturalistic movie-watching states.