Graph analysis of guilt processing network highlights links with subclinical anxiety and self-blame

Abstract Maladaptive forms of guilt, such as excessive self-blame, are common characteristics of anxiety and depressive disorders. The underlying network consists of multiple associative areas, including 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 circuitry’s anatomy, 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 (20 females, 20–35 years old). Within the guilt network, we found increased functional contributions of the left sATL for individuals with higher self-blaming, while functional isolation of the left pars opercularis and insula was related to higher trait anxiety. Trait anxiety was also linked to the structural network’s mean clustering coefficient, with the circuitry’s architecture favouring increased local information processing in individuals with increased anxiety levels, however, only when a highly specific subset of connections was considered. 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.