Special Issue on IEEE Transactions on Neural Systems and Rehabilitation
Broadening the Impact of the DARE Conference: Transformative Opportunities for Modeling in Neurorehabilitation
Paper Submission Deadline: June 2025
Recent advancements in computational modeling have created new avenues for enhancing clinical diagnosis and treatment in the field of neurorehabilitation. Computational models, defined broadly here as relationship equations used to model neural mechanisms or behavioral observations in the context of neurorehabilitation, can be based on theories of nervous system function (e.g., Hebbian plasticity, motor learning, optimal control theory), leverage data-driven (i.e., model-free) approaches, or combine the two frameworks. Such models hold transformative potential for understanding, predicting, and optimizing recovery and rehabilitation of neurologic disorders. However, model development is an ongoing challenge due to the need to accurately represent complex human systems, devices, rehabilitation processes, and their interactions. Robust development and validation of these models are critical for translating data into functional and effective neurorehabilitation strategies