motor rehabilitation

Brain-Machine Interfaces: Beyond Decoding

A brain-machine interface (BMI) is a system that enables users to interact with computers and robots through the voluntary modulation of their brain activity. Such a BMI is particularly relevant as an aid for patients with severe neuromuscular disabilities, although it also opens up new possibilities in human-machine interaction for able-bodied people. Real-time signal processing and decoding of brain signals are certainly at the heart of a BMI. Yet, this does not suffice for subjects to operate a brain-controlled device. In the first part of my talk I will review some of our recent studies, most involving participants with severe motor disabilities, that illustrate additional principles of a reliable BMI that enable users to operate different devices. In particular, I will show how an exclusive focus on machine learning is not necessarily the solution as it may not promote subject learning. This highlights the need for a comprehensive mutual learning methodology that foster learning at the three critical levels of the machine, subject and application. To further illustrate that BMI is more than just decoding, I will discuss how to enhance subject learning and BMI performance through appropriate feedback modalities. Finally, I will show how these principles translate to motor rehabilitation, where in a controlled trial chronic stroke patients achieved a significant functional recovery after the intervention, which was retained 6-12 months after the end of therapy.

Sensorimotor -independent brain representations in association cortices

How flexible are association cortices? I will present a series of fMRI experiments addressing this question by investigating individuals born without hands, who use their feet as effectors to perform everyday actions. These results suggest that computations in association cortices are abstracted from visuomotor features and experience, similarly to the visual -independence of the association networks in people born blind, highlighting these regions’ ability to compensate for experience in any specific modality. These findings also open new avenues to utilize effector-independence in the action system for motor rehabilitation.

Intensive sensorimotor rehabilitation restores gait disfunction and microstructure caused by experimental cerebral palsy in rats

Effectiveness of action observation treatment integrated with virtual reality in the motor rehabilitation of stroke patients: A randomized controlled clinical trial

FENS Forum 2024