This repository contains the code and data used for the research titled "Interaction of network and rehabilitation therapy parameters in defining recovery after stroke in a Bilateral Neural Network" published in Journal of NeuroEngineering and Rehabilitation.
This project models stroke recovery using a bilateral neural network that simulates reaching movements in 3D space. The research explores the impact of lesion size, recovery stages (acute or chronic), and rehabilitation therapies on recovery outcomes. The bilateral network is designed to reflect the brain's hemispheric connections, allowing detailed exploration of rehabilitation strategies such as movement complexity, hand selection modes, and plasticity.
- Bilateral neural network model for simulating stroke recovery.
- Customizable lesion parameters and recovery stages.
- Evaluation of rehabilitation strategies like constrained-induced movement therapy (CIMT) and bilateral movement therapy (BMT).
- Explores the influence of plasticity (local vs. global) on recovery outcomes based on patient characteristics.
If you use this code, please cite the following paper:
- Elango, S., Francis, A.J.A., Chakravarthy, V.S. (2022). Interaction of network and rehabilitation therapy parameters in defining recovery after stroke in a Bilateral Neural Network. Journal of NeuroEngineering and Rehabilitation. DOI: 10.1186/s12984-022-01106-3
For questions or collaborations, feel free to contact:
- Your Name - sundarielango95@gmail.com