This project aims to investigate the functional connectivity patterns in individuals with Parkinson’s disease and neuropsychiatric symptoms (PD+NPS) compared to those without the NPS. The study utilizes resting-state fMRI data to analyze the connectivity matrix and identify alterations in functional brain networks associated with PD+NPS. The project also involves familiarizing with data science packages, interpreting neuroimaging data, and advanced visualization techniques. The findings may contribute to understanding the neural mechanisms underlying PD+NPS and inform future research and interventions. The project involves BIDS validation, fMRI preprocessing, functional connectivity analysis, group comparisons, and prediction modeling for mild cognitive impairment.
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 aim to combine data from different modalities (fMRI, EEG, and behavioral) to understand more about sound and music processing. My main focus in this project was to try to reproduce some of the results from a published paper starting form raw data.