OHBM2022 Educational Course: Parcellating the white matter with neuropsychological symptoms скачать в хорошем качестве

OHBM2022 Educational Course: Parcellating the white matter with neuropsychological symptoms

Stroke significantly impacts the quality of life. However, the long-term cognitive evolution in stroke is poorly predictable at the individual level. There is an urgent need for a better prediction of long-term symptoms based on acute clinical neuroimaging data. Previous works have demonstrated a relationship between the location of white matter disconnections and clinical symptoms. However, rendering the entire space of possible lesion-deficit associations optimally surveyable will allow for a systematic association between brain disconnections and cognitive-behavioural measures at the individual level. Here we exploit nonlinear dimensionality reduction to report the characteristics of disconnection patterns of more than 1000 stroke lesions in a two-dimensional summary morphospace. Acute disconnectomes drawn from an independent distribution were projected into the morphospace to predict neuropsychological scores 1 year after stroke. Linking the latent disconnectome morphospace to neuropsychological outcomes yields a comprehensive atlas of disconnectome-deficit relations across 86 neuropsychological scores. Out-of-sample prediction derived from this atlas achieved average accuracy of over 80%. Our novel predictive framework is available as an interactive web application, the disconnectome symptoms discoverer (DSD), to provide the foundations for a new approach to modelling cognition in stroke. Article discussed Talozzi et al., 2021 DOI: 10.13140/RG.2.2.17963.36641 Software http://www.bcblab.com/BCB/Software.html http://disconnectomestudio.bcblab.com