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Disorder-Specific Salience-Network Insula Connectivity Supports a Spectrum Model of Misophonia

In a 2026 study, Hansen and colleagues sought to characterize the anterior insula connectivity profile of misophonia and determine whether it is distinct from anxiety, depression, and autism by analyzing resting-state fMRI data in a large open-access adult sample using seed-based connectivity methods. They estimated misophonia severity using a regression model trained in an independent dataset and applied it as a continuous predictor in connectivity analyses. They found that greater misophonia severity was associated with stronger anterior insula connectivity to clusters overlapping motor, somatosensory, and auditory regions, specifically within the salience network. From this, they concluded that misophonia is marked by a disorder-specific salience-network insular connectivity signature and is better conceptualized as a spectrum condition rather than a binary diagnosis (Hansen et al., 2026) .