Can functional connectivity data be used as a predictor for neuropsychiatric diagnosis? This project explores the usefulness of connectivity data in predicting ADHD, Bipolar Disorder, and Schizophrenia diagnoses using machine learning classification methods.
Can functional connectivity predict sensory deprivation? This project 1. explores neuroimaging data organization and preprocessing using open science tools and 2. uses a predictive model to classify whether a participant is hearing or not. For better visualization, the most contributing coefficients in the classifier are displayed on the brain.
This project aimed to understand how to pre-process fMRI data using fMRIPrep. Through this learning experience, a tutorial was created.
In this project I employed some of the tools we learned at the Brainhack school to generate interactive figures to display functional connectivity from MEG and fMRI resting state data from the Human Connectome Project.
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