The field of motor control is sometimes referred to as "movement science". That very wording underlines a general state of affairs: when one asks how does the brain controls the body? what one often really asks is how does the brain make the body move? In reality, there are many situations where the brain decides to control the body not by initiating movement, but by controlling the biomechanical properties of the body. In fact, biomechanical properties can sometimes be controlled in complete independence from trajectory itself (e.g. this study). I am currently working on untangling how control of body stiffness, or rigidity, relates to control of movement, and how stiffness is centrally regulated to enable stable, yet flexible control of the body.

Providing rewarding feedback (money, food, etc..) is a reliable mean of improving someone's motor performance. In fact, there is nothing particularly surprising about the idea that rewarding (for instance, paying) someone to do well will actually make that person do well. However, how exactly does the motor control system allow for this rather mundane phenomenon to happen is not particularly clear. In a series of studies, I systematically dissect the motor system to outline which functional components show modulation by rewarding feedback and which do not.

Reward-based improvements in motor control are driven by multiple error-reducing mechanisms
Reward-driven enhancements in motor control are robust to TMS manipulation
Sensorimotor feedback loops are selectively sensitive to reward

While rewarding feedback can improve motor control, it can also improve acquisition of new motor memories, a process often referred to as motor learning. But like for motor control, motor learning relies on different contributing mechanisms to produce the behavioural improvements we observe and quantify. While initially it was hypothesised that reinforcement could improve motor adaptation, a subset of motor learning that recalibrates sensorimotor mapping, colleagues and I show in a series of studies that reinforcement acts instead at another level, often called "explicit control". That is, reinforcement biases participants' voluntary strategy toward more rewarded actions, which is reminiscent of decision-making. We also show that participants' capacity to capitalize on such reinforcement feedback to improve their performance is tied to their working memory capacity rather than their dopaminergic genetic profile directly.

A reccurent hope about motor learning through reinforcement has been to enhance sports coaching and motor rehabilitation procedures for clinical populations. The real potential for these applications is directly tied to how exactly reinforcement acts on the motor learning system, as different answers beset different prospects regarding their viability and means of achievement. You can find some points on this topic in chapter six of my Ph.D. thesis.

The relationship between reinforcement and explicit control during visuomotor adaptation
The contribution of explicit processes to reinforcement-based motor learning
Domain-specific working memory, but not dopamine-related genetic variability, shapes reward-based motor learning