Brain network mapping of structural and functional alterations associated with alexithymia

Although numerous neuroimaging studies have reported structural and functional brain alterations in alexithymia, the findings have remained heterogeneous. Given the growing recognition that neuropsychiatric symptoms are better characterized by distributed brain networks rather than isolated regions, limited studies have examined alexithymia at the network level. We integrated findings from 43 neuroimaging publications and extracted reported locations showing structural and functional abnormalities related to alexithymia. Using a functional connectivity network mapping (FCNM) approach, these affected brain regions were mapped onto large-scale resting-state functional magnetic resonance imaging datasets (n = 872) to identify structural and functional alteration networks associated with alexithymia. Cross-sample spatial correlations were performed between the identified networks and 19 neurotransmitter distribution maps from over 1200 healthy participants. The gray matter volume alteration network was primarily involved in the subcortical network (65.06%), somatomotor network (23.52%), limbic network (19.02%), and ventral attention network (14.13%). The task-induced activation alteration network was mainly involved in the ventral attention network (26.91%), subcortical network (18.06%), and somatomotor network (6.36%). These findings were robust across different methodological parameters and test-retest analyses. In the cross-sample spatial correlation analyses, both alteration networks were associated with serotonin and vesicular acetylcholine transporters. These findings elucidate the network-level neurobiological mechanisms of alexithymia, indicating that individuals with alexithymia may exhibit dysfunction at lower levels of emotional awareness. The observed brain alterations may be linked to serotonergic and vesicular acetylcholine transporter dysfunction. The identified networks may serve as potential targets for therapeutic interventions and biomarkers for predicting treatment response or disease progression.