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Methods for analyzing large neuroimaging datasets /
4.4 Studying the connectome at a large scale
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Category: Procedure
Description: https://osf.io/ay95f This chapter outlines a flexible connectome-based predictive modeling method that is optimised for large neuroimaging datasets via the use of parallel computing and by adding the capability to account for possible site- and scanner-related heterogeneity in multi-site neuroimaging datasets. We present the decision points that need to be made when conducting a connectome-based predictive modeling analysis and we provide full code to conduct an analysis on public data. To date, connectome-based predictive modeling has been applied to predict different cognitive and behavioural phenotypes with many studies reporting accurate predictions that generalized to external datasets.
Studying the connectome at a large scale preprint
The code used in this chapter is freely available here: https://github.com/rorytboyle/flexible_cpm
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OHBM 2022: Studying the connectome at a large scale
Yihe Weng (& Rory Boyle) 1:20-2:00
https://youtu.be/Opgmipo2XAg
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