Supplementary file 2_Network-based mapping and neurotransmitter architecture of brain gray matter correlates of extraversion.docx

ObjectiveTo identify common functional brain networks underlying heterogeneous gray matter (GM) correlates of extraversion and to characterize the neurotransmitter receptor and transporter architecture associated with these networks.
MethodsA systematic literature search identified 13 voxel-based morphometry (VBM) studies reporting GM correlates of extraversion in healthy individuals (N = 1,478). Functional connectivity network mapping (FCNM) approach using normative resting-state functional MRI data from the Human Connectome Project (HCP, N = 1,093) mapped divergent GM correlates extraversion onto common networks. Robustness was assessed via replication using an independent Southwest University Adult Lifespan Dataset (SALD, N = 329) and sensitivity analyses varying seed radii. Spatial relationships between the identified brain networks and the distribution of major neurotransmitter receptors/transporters were subsequently characterized using the JuSpace toolbox.
ResultsFCNM analysis revealed that reported GM correlates of extraversion converge onto specific functional networks. Spatial overlap analysis showed the highest association with the frontoparietal network (FPN) (37.32%) and the default mode network (DMN) (32.99%). Furthermore, JuSpace analysis indicated that these extraversion-linked networks exhibited significant positive spatial correlations with 5-hydroxytryptamine receptor 2A (5HT2a; p = 0.021, r = 0.215), cannabinoid receptor type-1 (CB1; p = 0.005, r = 0.392), and metabotropic glutamate receptor 5 (mGluR5; p = 0.01, r = 0.330), and negative correlations with the norepinephrine transporter (NAT; p = 0.018, r = −0.221) and serotonin transporter (SERT; p = 0.023, r = −0.201).
ConclusionDespite regional heterogeneity in prior VBM studies, structural GM correlates of extraversion consistently map onto the DMN and FPN. This network-based approach reconciles previous inconsistencies and highlights the importance of these large-scale networks as a plausible functional substrate underlying structural variations associated with extraversion. These findings advance a systems-level understanding of the neural basis of this core personality dimension and suggest a distinct neurochemical architecture within these networks.