Brain Connectivity Based Biomarkers of Cognitive-Motor Dysfunction and Recovery

Abstract

Restoring safe, efficient movement after neurological injury or disease remains a central challenge in rehabilitation and demands technologies that can sense, interpret, and ultimately influence how the brain controls movement. Dr. Saleh studies supraspinal control of movement during real-world, ecologically valid tasks such as dual-tasking, obstacle avoidance, and navigation in complex environments. By integrating neuroimaging with advanced connectivity analytics, she identifies connectivity signatures that (i) distinguish patients from controls, (ii) predict recovery and treatment response, and (iii) change with targeted interventions. Dr. Saleh’s seminar will discuss altered brain connectivity in people with multiple sclerosis (MS) versus healthy controls during walking and obstacle negotiation, revealing altered connectivity within premotor and prefrontal circuits. These distinct neural signatures differentiate people with MS from healthy controls and capture both dual-task costs and obstacle-avoidance demands, highlighting network-level biomarkers of gait dysfunction in everyday mobility contexts. Her talk will also address brain connectivity as a biomarker of post-stroke recovery, where altered connectivity of premotor cortices can predict functional gains. Dr. Saleh will discuss the use of connectivity-based biomarkers as a powerful framework for quantifying impairment, tracking recovery, and guiding targeted interventions.

Biography

Soha Saleh, PhD, is an Assistant Professor in the Department of Rehabilitation and Movement Sciences at Rutgers School of Health Professions and in the Department of Neurology at Rutgers Robert Wood Johnson Medical School. Her research integrates mobile neuroimaging, connectivity analytics, virtual reality, robotics, and neuromodulation to better understand and enhance supraspinal control of movement across neurological conditions. Her work spans functional and structural neuroimaging (EEG, fNIRS, fMRI, DTI), advanced network modeling (PLS, graph theory, DCM), and the development of connectivity-informed rehabilitation technologies. Dr. Saleh serves as MPI or PI on multiple federally and state-funded projects, including an NIH R01 on robot-assisted gait rehabilitation after stroke, a NIDILRR-funded clinical trial on cognitively integrated gait training, and New Jersey Commission–funded research on brain-based biomarkers and mobility recovery in spinal cord injury. Her publications cover mobile neuroimaging during gait and obstacle negotiation in multiple sclerosis, connectivity-driven mechanisms of VR-based motor learning in stroke, and neuromodulation approaches for enhancing motor performance. She serves on multiple editorial boards and technical committees in biomedical engineering and neuroengineering, including the IEEE EMBS Technical Committee on Biorobotics, where she is an elected Vice Chair.