Bergström, F. | bioRxiv Science

bioRxiv2024

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

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.

neuroscience↗

bioRxiv2023

Neural and behavioral signatures of the multidimensionality of manipulable object processing.

Understanding how we recognize everyday objects requires unravelling the variables that govern the way we think about objects and the way in which our representations are organized neurally. A major hypothesis is that the organization of object knowledge follows key object-related dimensions, analogously to how sensory information is organized in the brain. Here, we explored, behaviorally and neurally, the multidimensionality of object processing. We focused on within-domain object information as a proxy for the kinds of object decision tasks we typically engage in our daily lives - e.g., identifying a knife from other types of manipulable objects such as spoons, axes or screwdrivers. To do so, we extracted object-related dimensions from subjective human judgments on a set of objects from a particular object domain - i.e., manipulable objects. We demonstrated that the extracted dimensions are cognitively interpretable - i.e., participants are able to label them; are cognitively relevant for manipulable object processing - i.e., categorization decisions are guided by these dimensions; and are important for the neural organization of knowledge - i.e., they are good predictors of the neural signals elicited by manipulable objects. This shows that multidimensionality is a hallmark of the organization of object knowledge in the brain.

neuroscience↗