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

(A) Concurrent 7T fMRI and eye tracking were collected during resting state and naturalistic movie watching. (B) tvFC was computed over sliding windows for each pair of brain regions. (C) Pupil diameter was preprocessed to obtain a continuous arousal time series. Arousal–tvFC 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–tvFC 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-tvFC coupling.

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

(A) Unsupervised clustering of edgewise arousal–tvFC 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 (F(2,88)=12.24, p = 4.38×10-6), 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-modulated communities architecture 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.

Characterizing the spatial distribution, entropy, and hemispheric divergence of regional community affiliation.

(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–tvFC 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–D) Region-level community affiliation entropy revealed a systematic network gradient, in which heteromodal systems displayed more selective participation, whereas unimodal network showed broader, more distributed engagement across communities (t(798) = -23.81, p = 4.24×10–95) (E) No integration bias was detected in any community. (F) Significant leftward segregation biases were identified within specific communities (communities 3, 5, 6, and 7). These asymmetries were primarily localized in regions belonging to the DMN, FPN, LIMB, and VAN. 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-modulated 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 ≈ 0.72, p = 2.35×10-26), 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 ≈ 0.79, p = 1.35×10-11; segregation: rho ≈ 0.64, p = 5.82×10-7), 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–tvFC coupling are preserved across resting state and movie watching.

(A) Communities derived from rest and movie data were aligned using Hungarian algorithm, revealing robust correspondence between paradigms (average dice ≈ 0.46). (B) Network-pair composition profiles for each community were strongly correlated across paradigms (mean rho ≈ 0.58), indicating that the modular organization of arousal–tvFC coupling is stable across cognitive contexts.