Over reliance on prior expectations in relapsing remitting multiple sclerosis

Cognitive impairment is a common and disabling feature of multiple sclerosis (MS). Bayesian models of perception and action offer a powerful framework for understanding how cognitive processes are altered in MS. In this case-control study, we used a time reproduction paradigm within a Bayesian framework to probe cognitive dysfunction in patients with relapsing-remitting MS, applying a modified Bayesian observer model that partitions timing into sensory measurement, estimation, and motor stages. Both MS and control groups overestimated short intervals and underestimated long ones, but this central tendency bias was significantly larger in MS, reflecting an over-reliance on prior expectations relative to sensory-motor information. Modeling attributed this to greater measurement noise at the sensory stage. In healthy participants, bias increased with age; interestingly, this age-related effect was absent in MS, where younger and older patients were equally biased and resembled older healthy participants.