Motor skill training without online visual feedback enhances feedforward control

Exploration biases forelimb reaching strategies

The brain can generate actions, such as reaching to a target, using different movement strategies. We investigate how such strategies are learned in a task where perched head-fixed mice learn to reach to an invisible target area from a set start position using a joystick. This can be achieved by learning to move in a specific direction or to a specific endpoint location. As mice learn to reach the target, they refine their variable joystick trajectories into controlled reaches, which depend on the sensorimotor cortex. We show that individual mice learned strategies biased to either direction- or endpoint-based movements. This endpoint/direction bias correlates with spatial directional variability with which the workspace was explored during training. Model-free reinforcement learning agents can generate both strategies with similar correlation between variability during training and learning bias. These results provide evidence that reinforcement of individual exploratory behavior during training biases the reaching strategies that mice learn.

Exploration biases how forelimb reaches to a spatial target are learned

The brain can learn to generate actions, such as reaching to a target, using different movement strategies. Understanding how different variables bias which strategies are learned to produce such a reach is important for our understanding of the neural bases of movement. Here we introduce a novel spatial forelimb target task in which perched head-fixed mice learn to reach to a circular target area from a set start position using a joystick. These reaches can be achieved by learning to move into a specific direction or to a specific endpoint location. We find that mice gradually learn to successfully reach the covert target. With time, they refine their initially exploratory complex joystick trajectories into controlled targeted reaches. The execution of these controlled reaches depends on the sensorimotor cortex. Using a probe test with shifting start positions, we show that individual mice learned to use strategies biased to either direction or endpoint-based movements. The degree of endpoint learning bias was correlated with the spatial directional variability with which the workspace was explored early in training. Furthermore, we demonstrate that reinforcement learning model agents exhibit a similar correlation between directional variability during training and learned strategy. These results provide evidence that individual exploratory behavior during training biases the control strategies that mice use to perform forelimb covert target reaches.

Asymmetrical transfer of adaptation between reaching and tracking: implications for feedforward and feedback processes

Reaching and manual tracking are two very common tasks for studying human sensorimotor processes. Although these motor tasks rely both on feedforward and feedback processes, emphasis is more on feedforward processes for reaching, and more on feedback processes for tracking. The extent to which feedforward and feedback processes are interrelated when being updated is not settled yet. Here, using reaching and tracking as proxies, we examined the bidirectional relationship between the update of feedforward and feedback processes. Forty right-handed participants were asked to move a joystick so as to either track a target moving rather unpredictably (pursuit tracking) or to make fast pointing movements toward a static target (center-out reaching task). Visuomotor adaptation was elicited by introducing a 45° rotation between the joystick motion and the cursor motion. Half of the participants adapted to rotation first via reaching movements, and then with pursuit tracking, while the other half performed both tasks in opposite order. Group comparisons revealed a strong asymmetrical transfer of adaptation between tasks. Namely, although nearly complete transfer of adaptation was observed from reaching to tracking, only modest transfer was found from tracking to reaching. A control experiment (N=10) revealed that making target motion fully predictable did not impact the latter finding. One possible interpretation is that the update of feedforward processes contributes directly to feedback processes, but the update of feedback processes engaged in tracking can be performed in isolation. These results suggest that reaching movements are supported by broader (i.e. more universal) mechanisms than tracking ones.