Graph analysis of the guilt network highlights associations with subclinical anxiety and self-blame

Abstract

AbstractMaladaptive forms of guilt, such as excessive self-blame, are common characteristics of anxiety disorders. The associated network includes the superior anterior temporal lobe (sATL), underlying the conceptual representations of social meaning, and fronto-subcortical areas involved in the affective dimension of guilt. Nevertheless, despite understanding the anatomy of the guilt processing circuitry, network-level changes related to subclinical anxiety and self-blaming behaviour have not been depicted. To fill this gap, we used graph theory analyses on a resting-state functional and diffusion-weighted magnetic resonance imaging dataset of 78 healthy adults. Within the guilt network, we found increased functional contributions (higher clustering coefficient, local efficiency and strength) of the left sATL for individuals with higher self-blaming and trait-anxiety, while functional isolation (lower clustering coefficient and local efficiency) of the left pars opercularis and insula was related to higher trait-anxiety. Trait-anxiety was also linked to the structural network’s global parameters (mean clustering coefficient), with the circuitry’s architecture favouring increased local information processing in individuals with increased anxiety levels. Previous research suggests that aberrant interactions between conceptual (sATL) and affective (fronto-limbic) regions underlie maladaptive guilt and the current results align and expand on this theory by detailing network changes associated with self-blame and trait-anxiety.