Corticostriatal dynamics encode the refinement of specific behavioral variability during skill learning.

Area of Science:

• Neuroscience
• Motor Learning
• Computational Neuroscience

Background:

• Complex motor task performance necessitates optimizing behavioral features under task constraints.
• Understanding how the brain refines motor skills is crucial for neuroscience and rehabilitation.

Purpose of the Study:

• To investigate how mice differentially refine specific behavioral features during novel motor learning.
• To examine the role of corticostriatal neural activity and plasticity in motor skill acquisition.

Main Methods:

• Mice were trained on a novel motor task involving progressively faster lever press sequences for reinforcement.
• Behavioral features (sequence frequency, duration) and neural activity (motor cortex, striatum) variability were analyzed.
• Corticostriatal plasticity was assessed using targeted interventions.

Main Results:

• Mice reduced variability in sequence frequency but increased variability in sequence duration.
• Trial-to-trial neural variability in motor cortex and striatum decreased with learning, correlating with frequency variability.
• Corticostriatal plasticity was essential for refining frequency variability but not duration variability.

Conclusions:

• Motor learning involves the selective refinement of distinct behavioral features.
• Corticostriatal dynamics encode and support the optimization of specific motor control strategies.
• Neural plasticity in corticostriatal circuits is critical for adapting motor behavior to achieve desired outcomes.