Marco Capogrosso, PhD (3:00-4:00 pm): A computational framework for the design of spinal neuroprostheses

Severe Spinal Cord Injury (SCI) alters the communication between supra-spinal centers and the sensorimotor networks coordinating limb movements, leading to motor paralysis. Epidural electrical stimulation of lumbar segments has shown the ability to enable descending motor control of the lower limbs in rodents and humans with severe spinal cord injury. Using a combination of computational models and in-vivo experiments, I’ve found that EES facilitates motor control through the recruitment of muscle spindle feedback circuits. I’ve then used these models to design stimulation protocols targeting these circuits that allowed selective modulation of synergistic muscle groups, both in rodents and primates. This framework supported the design of brain controlled stimulation strategies that restored voluntary locomotion in primates with incomplete spinal cord injury. I am now expanding these models to design new technologies for the restoration of functional arm movements in people with cervical spinal cord injury.

Elvira Pirondini, PhD (4:00-5:00 pm): Robust imaging biomarkers for therapy personalization in neural disorders

Personalized neuro-rehabilitation approaches, such as robot-assisted therapies, have been suggested as a pivotal step to improve the clinical outcome in neural disorders. Indeed, in the past years, robotic systems have become increasingly popular for the use in both upper and lower limb rehabilitation. Nevertheless, clinical studies have so far not been able to confirm the superior efficacy of robotic therapy over conventional methods. The possibility to autonomously and continuously adapt the rehabilitation protocol to the patient’s status based on meaningful measures could improve the clinical relevance of such solutions. However, the identification of such informative and robust biomarkers has remained rather elusive. Here I will briefly discuss how neurophysiological relevant kinematic parameters capable of tracking changes in motor improvement could be identified and used for the personalization of the therapy in real-time. However, while kinematic measurements provide precise behavioral scores, they are unfit to describe the complex neural reorganization processes in neuro-motor disorders. I will therefore present advanced imaging tools to analyze brain activity able to provide novel and rich biomarkers to delineate responses to treatment. These methods will allow improving our understanding of the recovery mechanisms and the design of innovative personalized rehabilitative strategies.