Brain-computer interfaces (BCIs) make it possible to restore lost functions by allowing individuals to control external devices through the modulation of their brain activity. The CEA has developed a BCI technology based on the WIMAGINE implant, which records brain activity using electrocorticography (ECoG), along with algorithms for decoding motor intentions. This technology was initially tested for controlling robotic effectors such as exoskeletons and spinal cord stimulation devices to compensate for severe motor impairments. While this initial paradigm of substitution and compensation is promising, a different application potential is now emerging: functional recovery through BCI-guided rehabilitation. Current literature suggests that BCIs, when used intensively and in a targeted manner, can promote neural plasticity and, in turn, improve residual motor abilities. In particular, ECoG-based implanted BCIs could offer significant therapeutic outcomes. The objective of this thesis is therefore to assess the potential of CEA's BCI technology to enhance patients' residual motor functions through neural plasticity.
This work will be approached through a rigorous and multidisciplinary scientific methodology, including a comprehensive review of the scientific literature, the setup and execution of experimentations with patients, the algorithmic development of tools for monitoring and analyzing patient progress, and the publication of significant results in high-level scientific journals.
This PhD is intended for a student specializing in biomedical engineering, with expertise in signal processing and the analysis of complex physiological data, as well as experience in Python or Matlab. A strong interest in clinical experimentation and neuroscience will also be required. The student will work within a multidisciplinary team at CLINATEC, contributing to cutting-edge research in the field of BCIs.