Researchers at McGill University, led by Kathleen Cullen, Department of Physiology have revealed that when learning new motor skills, nerve cells within the cerebellum virtually perform intricate mathematical computations to efficiently compare the actual and expected sensory feedback. After appropriate readjustment – changes in the strength of associations between neural pathways – they accomplish the task.

Learning A New Motor Skill

When acquiring a new motor skill, the brain first estimates the expected sensory input it should receive from the sensory system. The cerebellum then uses this assessment to calculate the difference between what is intended and what is actually done. Professional athletes, other than having superior coordination skills, are also better at evaluating these predictions and adjustments efficiently.

“A gymnast doing a back flip on a balance beam depends on this ability – precisely compute the mismatch between where they expect to land and where they actually find themselves”, explained Cullen. “But the research is equally relevant to stroke and multiple sclerosis patients, as well as the clinicians who treat them”.

The New Discovery

Cullen stated that researchers had already discovered the involvement of the cerebellum in assessing sensory information, and determining appropriate movements or reactions. What they did not know was that single nerve cells in the brain were able to dynamically perform this comparison; what is expected by the brain from the sensory input and what is actually received during motor learning.

Researchers performed a trial-by-trial analysis of single cerebellar neural responses in macaque monkey subjects while they performed certain movement learning tasks. The study demonstrates the use of calculated differences – ‘sensory prediction error’ signals – in rapidly modifying the pathways between nerve cells, assisting in acquiring new motor skills. The findings were recently published in the journal Nature Neuroscience.