This repository contains the code and data used for the research titled "A lateralized motor network in order to understand adaptation to visuomotor rotation" published in Journal of Neural Engineering.
This project implements a computational model called the Bilateral Control Network to simulate motor learning and adaptation during visuomotor rotation tasks. The model is inspired by experiments demonstrating the shared control of motor learning between hemispheres. The repository includes a neural network framework that simulates arm movements in 2D space.
- Simulates visuomotor rotation and adaptation using a 2D arm model.
- Replicates experimental results showing motor learning transfer across arms.
- Includes implementations for direction and distance coding in different hemispheres.
The dataset used for this research is included in the dataset/ folder. If you are using your own data, ensure it follows the specified format as described in the documentation.
If you use this code, please cite the following paper:
- Elango, S., Chakravarthy, V. S., & Mutha, P. K. (2024). A lateralized motor network in order to understand adaptation to visuomotor rotation. Journal of Neural Engineering. DOI: 10.1088/1741-2552/ad4211
For questions or collaborations, feel free to contact:
- *Sundari Elango - [email protected] """