Investigating Motor Skill Learning Processes with a Robotic Manipulandum

A paradigm is presented for training and analysis of an automated skilled reaching task in rats. Analysis of pulling attempts reveals distinct subprocesses of motor learning.

Transcript

The overall goal of training rats on this reaching task involving a robotic manipulandum is to investigate the processes underlying motor skill learning and motor function recovery. This method can help answer key questions in the field of behavioral neuroscience, specifically related to the mechanisms underlying motor learning and memory formation as well as loss and recovery of function after brain damage or stroke. The main advantage of this technique are that the rats'training and that analysis is easy to perform and that it is more objective than other conventional single pellet reaching task.

Moreover, the robotic manipulandum allows for better analysis of kinematics. In preparation, always allow newly acquired rats to habituate to their new home cages for at least a week before training them. During this time, handle the rats regularly and feed them the reward pellets used for the training protocol.

To begin the training process, first spend two or three days habituating the rats to the test cage. The first task is to train the rats to simply touch the spherical handle through the cage window and to then move to the opposite side of the cage and retrieve a food reward. First, adjust the software settings so that the handle is located just outside the testing cage window.

Now, put the rat in the training cage and hold a pellet near the handle. Direct the rat's attention by tapping on the cage as needed. Continue prompting the rat to the handle this way until it independently reaches through the cage window and touches the handle or food pellet.

Then, run the session until 100 touches have been completed or until 60 minutes have elapsed, whichever comes first. Continue training the rat daily until it completes 100 touches within 30 minutes on two consecutive days. This usually occurs in the first two sessions.

Once this proficiency is obtained, proceed directly with the next training paradigm. Rats can perform much more quickly in this task than the defined criteria, but it is important to not overtrain them as this can result in overconsolidation of the behavior and stifle shaping of the behavior to the final goal. The next challenge is for the rats to learn the intermediate step of reaching out and pulling the handle.

As with reward touch training, it is important not to overtrain as the final goal is to transition to the next stage of training. First, adjust the software setting so that the robot positions the handle 18 millimeters from the window at the start of each trial. The handle must be pulled at least 10 millimeters without interruption for a successful trial.

There are no lateral restrictions on the pulling movement. Then perform the sessions as before with 100 trials or 60 minutes marking their ends. If a rat is not reaching far enough to perform the task, then shape the correct behavior by holding a pellet with forceps near the handle.

If a rat seems to lose interest in pulling the handle, then tap on the cage or dispense a pellet. Determine the rat's paw preference from its first 20 attempts to pull the handle. Simply choose the paw that is used more often as the dominant paw.

Most rats will show a strong preference and used one paw in at least 80%of the trials. Once a dominant paw is noted, adjust the position of the handle laterally to favor this paw. Align the handle to the edge of the window and keep it in this position for all future sessions with this rat.

Continue training the task until the rat reaches a plateau performance or performs the task 100 times within 30 minutes on two consecutive days. Only two sessions are typically needed before proceeding to straight pulling. The final stage of training is to teach the rats to pull the handle straightly for a reward.

Change the parameters in the software so that a pulling movement that deviates by more than two millimeters from the midline is considered a failure. As usual, each session should be run until either 100 trials are completed or 60 minutes have passed. Continue training the rats on this task until their skill level reaches a plateau or until the rats exceed a defined criteria.

Using 10 to 12 week old male Long-Evans rats, three different training techniques were compared over 22 days of training. Each group was given reward touch training. Then the parameters changed.

In one group, FP, rats were trained to pull the robot's handle without any lateral restrictions. In the next group, SP1, rats were trained to pull the handle without deviating more than two millimeters from the midline but were not given any free pull training sessions. In the final group, SP2, rats received exactly two free pull training sessions and then transitioned to straight pull training.

Importantly for SP2, the handle was kept aligned near one edge of the window resulting in a more challenging task. This condition could occur by accident if the robot isn't consistently aligned to the cage by the operator. Possibly due to this added challenge, the task success rate for SP1 rats plateaued sooner than it did for SP2 rats.

Over the sessions, handle movement improved from the first session to the last. The data shown is of one representative rat from the SP2 group. Similarly, the speed of pulling became more regular from the first to the last session indicating a more stable movement was learned.

This data is also from a representative SP2 rat. After watching this video, you should have a good understanding of how to perform an automated skilled reaching task and of the factors that may impact your results. As we have shown, minor alteration in the training pattern will affect the animal performance.

So when attempting this procedure, it's important to keep all the conditions consistent for each animal such as the handle location.

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Journal (Behavior)

Journal (Behavior)

Investigating Motor Skill Learning Processes with a Robotic Manipulandum

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