This project aims to push neurofeedback one step forward by creating a control system that differentially regulates the subject's brain activity to a desired value.
In a first approach, this project aims to investigate the primary motor cortex (M1) and create a multi-parametric model of the M1 activation in regards to force and complexity of finger movements. This first experiment will give important insights into the differential sensorimotor response of the brain to multiple input parameter combinations. In a second approach, this project attempts to exploit the discovered multi-parametric model by creating a non-invasive neurofeedback control algorithm that adjusts its inputs to the subject according to their online measured M1 activity. Such a virtual therapist could improve current therapeutic methods as it is autonomously and in real-time adapting finger movement instructions of the subject to achieve a desired M1 activation. This project will take neurofeedback one step forward as it externalizes the controller and avoids unpredictable or difficult reproducible outcomes of self-regulation made with the subject's own thoughts.