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extrapolating Misophonia status from existing data

In a 2026 study reanalyzing open-source fMRI data, Hansen demonstrated that it is possible to extrapolate misophonia status from existing data indirectly. They did this by training a regression model in an independent sample to predict Misophonia Questionnaire scores from sensory profile items, validating the model, and then applying it to a large neuroimaging dataset that did not directly assess misophonia. The predicted scores were then used as a continuous proxy for misophonia severity in resting-state connectivity analyses. In the future, I should look into implementing a similar procedure with EEG, using existing trait or sensory measures to derive symptom proxies and then examining how these predicted scores relate to neural oscillatory or connectivity patterns (Hansen et al., 2026).