Workflow of resting state connectivity from a raw dataset to longitudinal visualization

To aim of this project was to provide a full neuroimaging workflow from preprocessing of raw data to visualisation of results, to explore longitudinal analysis between two treatments in this dataset and to visualise resting-state networks linked to the default mode network and attention. In my github repository you will find scripts and documentation about the the BIDS to NiFTY conversion, fMRI prep as well as resting-state visualisation of a single participant. There is also a powerpoint presentation slide to guide you through the work.

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Classifying Neuropsychiatric Disorder Diagnoses Using Resting State BOLD fMRI Connectivity Data

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.

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