Investigating the clinical pattern of motor relearning in people with multiple sclerosis

Understanding how people with multiple sclerosis (PwMS) acquire motor skills during rehabilitation is essential for optimizing treatment strategies. Motor learning theory suggests that skill acquisition follows predictable trajectories, but the time course and variability of learning during task-oriented rehabilitation remain poorly defined in PwMS. The aim was to investigate the learning trajectory and performance variability in PwMS undergoing task-oriented rehabilitation, using mathematical modeling of behavioral changes over time.

This longitudinal prospective study included 44 PwMS admitted to a rehabilitation unit. Participants received either balance-specific or non-specific motor impairment treatments. Balance performance was assessed with the Berg Balance Scale (BBS) after each session. Session-to-session changes were analyzed using linear and exponential models to characterize the learning pattern, and residuals were examined to quantify variability.

An exponential mixed model (Akaike information criterion (AIC) = 2514.1) best described learning trajectories and provided more accurate estimates of pre-to-post improvement compared to a linear model (AIC = 2672.1). Performance variability decreased across sessions, from 1.16 to 0.75 points. Participants receiving specific balance treatment reached the minimal clinically important difference after three sessions, while participants receiving non-specific treatments achieved MCID only after 7 sessions.

Motor performance changes in PwMS during rehabilitation resemble motor learning in healthy individuals: improvements follow an exponential function and are accompanied by reduced variability. Treatment specificity enhances the velocity and magnitude of learning, underscoring the importance of targeted interventions in neurorehabilitation.