A structural MRI marker predicts individual differences in impulsivity and classifies patients with behavioral-variant frontotemporal dementia from matched controls

Abstract

Impulsive decision-making is a symptom across many neuropsychiatric and neurological disorders. Yet, it is still unknown whether impulsivity can be predicted based on individual differences in brain structure. Here, we used machine-learning to develop a structural MRI signature of impulsivity, tested its validity in several independent samples, and assessed its diagnostic value in patients with behavioral variant frontotemporal dementia (bvFTD)--a neurodegenerative disease characterized by high impulsivity. The resulting whole-brain grey matter density pattern--the Structural Impulsivity Signature (SIS)--showed a good prediction-outcome correlation of r=0.35 (out-of-sample, p=0.0028) in the training sample of healthy adults (N=117) and significantly predicted individual differences in impulsivity in four other, independent studies (total N=626), including healthy and clinical participants with neuropsychiatric and neurological conditions. Further, the SIS separated bvFTD patients from controls with high accuracy (81% correct, p=0.002) and predicted impulsivity-related symptom severity among patients. The spatial distribution of weights in the SIS brain pattern highlights the key role of brain regions associated with affective processing in impulsivity. Together, these results provide evidence for a new structural neuromarker of individual differences in impulsivity that can be easily applied to new samples. Future studies can further assess its predictive value towards better prevention, diagnosis and treatment of mental disorders associated with impulsivity symptoms.