Name: investigating motor skill learning processes with a robotic manipulandum
Uploaded: 2017-02-12T15:00:00
Description: Watch this Scientific Journal Video about Investigating Motor Skill Learning Processes with a Robotic Manipulandum at JoVE.com

This research was supported by the Swiss National Science Foundation, the Betty and David Koetser Foundation for Brain Research and the ETH Foundation.

The experiments presented here were approved by the Veterinary Office of the Canton of Zurich, Switzerland and were carried out according to national and institutional regulations.
1. Feeding Conditions
NOTE: All training sessions are performed under a scheduled feeding protocol.
<ol>
	<li>Feed the rats 50 g/kg of standard chow once per day, after training is completed. This amount of food is sufficient to prevent major weight loss (body weight is &#62;90% of free...

<ol>
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Skilled reaching tasks are commonly used to study motor skill acquisition as well as impairment of motor function under pathological conditions6. Reliable and unambiguous analysis of reaching behavior is essential for the study of cellular mechanisms underlying motor skill acquisition, as well as neurophysiological processes involved in loss and subsequent recovery of function in animal models of neurological disease. The results presented here show how spatial and temporal aspects of the pulling ...

Motor tasks are widely used to assess behavioral and neural changes related to motor learning or to alterations in motor function in neurological or pharmacological animal models. Fine motor function can be difficult to quantify in rodents, however. Tasks requiring manual dexterity, such as manipulation of cereal1, pasta2, or sunflower seeds3 are sensitive and do not require extensive training of the animal. Their main drawback is that these tasks yield mostly qualitative results and can be difficult to score unambiguously.
Skilled reaching tasks, such as variations of the single pellet reaching task are more straightforward to quantify4,5. However, kinematic factors that underlie successful execution of these tasks can only be inferred to a limited extent and require labor-intensive frame-by-frame video analysis.
Robotic devices have gained popularity as means of quantifying aspects of forelimb function and motor skill. Several automated reaching tasks are available. The majority focus on a single aspect of a forelimb movement, such as pulling of a handle along a linear guide6,7, simple distal limb movements8, or pronation and supination of the paw9. While these devices show promise for the analysis of motor function in, they only reflect the complex motor actions executed during single pellet reaching to a limited extend.
Here, we demonstrate the use of a three-degree-of-freedom robotic device, ETH Pattus, developed for training and assessment of various motor tasks in rats10,11. It records planar and rotational movement of rat forelimb movements in reach, grasp, and pulling tasks carried out in the horizontal plane. Rats interact with the robot via a 6 mm-diameter spherical handle that can be reached through a window in the testing cage (width: 15 cm, length: 40 cm, height: 45 cm) and moved in the horizontal plane (pushing and pulling movements) and rotated (pronation-supination movements). Thus, it enables the rat to carry out movements that approximate those executed during conventional single pellet reaching tasks. The window is 10 mm wide and located 50 mm above the cage floor. The handle is located 55 mm above the floor. A sliding door blocks access to the handle between reaching trials and opens when the robot reaches its start position and closes after a trial is completed. After a correctly executed movement, rats receive a food reward on the opposite side of the testing cage.
The robot is controlled via software and records output from 3 rotary encoders at 1000 Hz, resulting in information about the position of the handle in the horizontal plane, as well as its rotation angle (for details, see reference11). The conditions required for successful task execution are defined in the software prior to each training session (e.g. minimum required pulling distance and maximum deviation from midline in a reach-and-pull task). An initial standardized reference position of the handle is recorded with a fixed holder at the start of each training session. This reference is used for all trials within a session, assuring a constant start position of the handle for each trial. Constant positioning of the handle relative to the cage window is assured by alignment of marks on the cage and robot (Figure 1).
Video recordings of the reaching movements are recorded using a small high speed camera (120 frames/s, 640 x 480 resolution). A small display in the camera&#39;s view shows the rat&#39;s identification number, training session, trial number and trial result (success or failed). These videos are used to verify recorded results and to assess the effects of reaching movements that precede the touching, pulling or rotation of the handle.
Here, we demonstrate the use of this robotic platform in variations of a reach-and-pull task. This task can be trained within a period of time that is comparable to other skilled reaching paradigms and yields reproducible results. We describe a typical training protocol, as well as some of the main output parameters. Moreover, we show how minor changes in the used training protocol can result in altered time courses of behavioral outcomes that may represent independent subprocesses within the motor skill learning process.

<table border="0" cellpadding="0" cellspacing="0" width="679">
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:247px;">ETH Pattus</td>
			<td style="width:105px;"></td>
			<td style="width:136px;"></td>
			<td style="width:191px;">ETH Pattus was made by the Rehabilitation Engineering Laboratory of Prof. Gassert at ETH Zurich.&#160;</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:247px;">Training cage&#160;</td>
			<td style="width:105px;"></td>
			<td style="width:136px;"></td>
			<td>The plexiglass training cage was made in-house.&#160;</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:247px;">Pellet dispenser</td>
			<td style="width:105px;">Campden Instruments</td>
			<td align="right" style="width:136px;">80209</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:247px;">45-mg dustless precision pellets</td>
			<td style="width:105px;">Bio-Serv</td>
			<td style="width:136px;">F0021-J</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:247px;">GoPro Hero 3+ Silver Edition&#160;</td>
			<td style="width:105px;">digitec.ch</td>
			<td align="right">284528</td>
			<td>Small highspeed camera&#160;</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:247px;">Small display</td>
			<td style="width:105px;">Adafruit Industries</td>
			<td style="width:136px;">#50, #661</td>
			<td>128x32 SPI Oled display controlled via an Arduino Uno microcontroller and Labview software</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:247px;">Labview 2012</td>
			<td style="width:105px;">National Instruments</td>
			<td style="width:136px;">776678-3513</td>
			<td>ETH Pattus is compatible with more recent Labview versions.&#160;</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:247px;">Matlab 2014b</td>
			<td style="width:105px;">The Mathworks</td>
			<td style="width:136px;">MLALL</td>
			<td></td>
		</tr>
	</tbody>
</table>

investigating motor skill learning processes with a robotic manipulandum

Skilled reaching tasks are commonly used in studies of motor skill learning and motor function under healthy and pathological conditions, but can be time-intensive and ambiguous to quantify beyond simple success rates. Here, we describe the training procedure for reach-and-pull tasks with ETH Pattus, a robotic platform for automated forelimb reaching training that records pulling and hand rotation movements in rats. Kinematic quantification of the performed pulling attempts reveals the presence of distinct temporal profiles of movement parameters such as pulling velocity, spatial variability of the pulling trajectory, deviation from midline, as well as pulling success. We show how minor adjustments in the training paradigm result in alterations in these parameters, revealing their relation to task difficulty, general motor function or skilled task execution. Combined with electrophysiological, pharmacological and optogenetic techniques, this paradigm can be used to explore the mechanisms underlying motor learning and memory formation, as well as loss and recovery of function (e.g. after stroke).

Here, we show 3 variations of a reach-and pull task using male Long-Evans rats (10-12 weeks old). In the free-pull (FP) group (N = 6), rats were trained to pull the robot&#39;s handle for a 22 day period without lateral restrictions. Animals in the straight-pull 1 (SP1) group (N = 12) were trained to pull the handle without deviating more than 2 mm from midline. These animals transitioned directly from reward-touch (step 2.3) to straight-pull training (step 2.5). For both FP and SP1 anima...

Watch this Scientific Journal Video about Investigating Motor Skill Learning Processes with a Robotic Manipulandum at JoVE.com

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.

Skilled reaching tasks are commonly used in studies of motor skill learning and motor function under healthy and pathological conditions, but can be ...

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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