OHBM2022 Connectome-based predictive modelling for large neuroimaging datasets
Автор: Clinical Neuroanatomy Seminars
Загружено: 2022-06-25
Просмотров: 1237
Connectome-based predictive modelling (CPM) is a data-driven approach which enables the prediction of behavioural and cognitive phenotypes from functional connectivity data. CPM has been applied to successfully predict individual differences in various cognitive and behavioural phenotypes. A previous protocol paper outlined the method (Shen et al., 2017). Here, we present a flexible CPM method that is optimised for large neuroimaging datasets via the use of parallel computing. This approach enables researchers to account for possible site and scanner-related heterogeneity in multi-site neuroimaging datasets by controlling for site and/or scanner type as a covariate or by using leave-site-out cross-validation.
Presenters: Yihe Weng & Robert Boyle
Доступные форматы для скачивания:
Скачать видео mp4
-
Информация по загрузке:
