Functional Near-Infrared Spectroscopy Reveals Delayed Hemodynamic Changes in the Primary Motor Cortex During Fine Motor Tasks and Decreased Interhemispheric Connectivity in Parkinson's Disease Patients

This code processes the dataset containing functional near-infrared spectroscopy (fNIRS) data from 20 patients with Parkinson’s disease and 20 age- and sex-matched healthy subjects without movement disorders. There are 3 folders, each corresponding to a different task: a 10-second finger-tapping task, a 2-minute walking task, and a 6-minute resting-state.

When using this code, please cite our work:

Guevara, E., Rivas-Ruvalcaba, F. J., Kolosovas-Machuca, E. S., Ramírez-Elías, M., Zapata, R. D. de L., Ramirez-GarciaLuna, J. L., & Rodríguez-Leyva, I. (2024). Parkinson’s disease patients show delayed hemodynamic changes in primary motor cortex in fine motor tasks and decreased resting-state interhemispheric functional connectivity: A functional near-infrared spectroscopy study. Neurophotonics, 11(2), 025004. https://doi.org/10.1117/1.NPh.11.2.025004

Guevara, E., Solana-Lavalle, G., & Rosas-Romero, R. (2024). Integrating fNIRS and machine learning: Shedding light on Parkinson’s disease detection. EXCLI Journal, 23, 763–771. https://doi.org/10.17179/excli2024-7151

Guevara, E., Kolosovas-Machuca, E. S., & Rodríguez-Leyva, I. (2024). Exploring motor cortex functional connectivity in Parkinson’s disease using fNIRS. Brain Organoid and Systems Neuroscience Journal, 2, 23–30. https://doi.org/10.1016/j.bosn.2024.04.001

fNIRS data of Parkinson's Disease Patients and matched controls are available in Guevara, E., et al. Zenodo. https://doi.org/10.5281/zenodo.7966830

Analysis of fNIRS signals with Machine learning source code: https://github.com/GabrielSolana29/rs_fNIRS_PD