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Methods for analyzing large neuroimaging datasets  /

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Description: https://osf.io/8zyg9/ The Brain Predictability toolbox (BPt) is a Python-based library with a unified framework of machine learning (ML) tools designed to work with both tabulated data (e.g., brain-derived, psychiatric, behavioral and physiological variables) and neuroimaging specific data (e.g., brain volumes and surfaces). The toolbox is designed primarily for ‘population’ based predictive neuroimaging; that is to say, machine learning performed across data from multiple participants rather than many data points from a single or small set of participants. The BPt package is suitable for investigating a wide range of neuroimaging-based ML questions. This chapter is a brief introduction to general principles of the toolbox followed by a specific example of usage.

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OHBM 2022: A Brief Introduction to the Brain Predictability toolbox (BPt)

Sage Hahn 11:30-12:10 https://youtu.be/IyGXvsPn9t0

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