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-feeding weight), but small enough to ensure reproducible behavioral conditioning. Weigh the rats daily to ensure their body weight remains stable. 
	NOTE:&#160;Additional overnight (10-12 h) food deprivation may be useful prior to the first reward-touch session (step 2.3).</li>
</ol>
2. Training Procedure for a Reach-and-pull Task
<ol>
	<li>Preparation: Allow the rats to habituate to their new home cages for at least a week after arrival in the animal facility. Handle the rats regularly during this time and give dustless precision pellets in the home cage to habituate the rats to the new food. These pellets will be used as rewards throughout the training protocol.</li>
	<li>Habituation: Place the rats in the testing cage for 30-45 min and provide 30-50 pellets in the feeding bowl, mixed with powdered chow. Open and close the cage window and run the pellet dispenser occasionally to habituate the rats to their sound.
	<ol>
		<li>Repeat this for 2-3 days.</li>
	</ol>
	</li>
	<li>Reward-touch: Train the rats to touch the spherical handle through the cage window and to then move to the opposite side of the cage to retrieve a food reward.
	<ol>
		<li>Adjust the software settings so that the handle is located just outside the testing cage window at the start of each trial and align the handle with the center of the cage window. When the trials are successful, i.e., as soon as a light touch on the handle (0.25 mm displacement in any direction) has been detected, a tone sounds and a reward is dispensed. Classify trials as failed when no touch has been detected for 180 s after the window opens.</li>
		<li>Put the rat in the training cage. Prompt the rat to reach out by letting it grab at a pellet held near the handle. Direct the rat&#39;s attention to the handle and food bowl by tapping on the cage.</li>
		<li>Stop prompting when the rat independently reaches through the cage window and retrieves the food pellet.</li>
		<li>Continue until 100 trials (touches) are completed or until 60 min have passed, whichever comes first.</li>
		<li>Continue training for 3-4 days and begin the next stage of training (step 2.4) when rats achieve 100 trials within 30 min on 2 consecutive days. 
		NOTE: Do not over-train this step. The goal of reward-touch is to achieve reliable interaction between the rat and robot, so that this behavior can be shaped in subsequent training.</li>
	</ol>
	</li>
	<li>Free pull (FP): Train the rats to reach out and pull the robot&#39;s handle.
	<ol>
		<li>Adjust the software settings so that the handle is located 18 mm from the window at the start of each trial, and must be pulled for at least 10 mm without interruption for a successful trial. There are no lateral restrictions on the pulling movement in this stage.
		<ol>
			<li>Classify a trial as failed when the handle has not been moved for 180 s after the window opens, when the handle is moved outside of the reachable workspace (more than 12 mm from midline), or when the rat has pulled less than 10 mm within 5 s after the first touch has been detected.</li>
		</ol>
		</li>
		<li>Take note of the number of times the left and right paw are used during the first 20 trials of the first FP session. The paw that is used in at least 80% of the trials is considered the preferred paw. 
		NOTE: Paw preference may already be clear in reward-touch sessions.</li>
		<li>Move the handle laterally until it is aligned with the edge of the window to facilitate pulling with the preferred paw (i.e. move the robot 5 mm to the left side of the window for right-handed rats and vice-versa). 
		NOTE: Place the handle in this exact same position relative to the cage for all following training sessions for this rat. Assure exact placement by marks on the cage wall and on the robot.</li>
		<li>Put the rat in the training cage and train until 100 trials are completed or until 60 min have passed, whichever comes first. 
		NOTE: If the rat does not reach out far enough, prompt it by letting it grab at a pellet held near the handle. Rats may stop trying to pull after repeated failed attempts. Tap on the cage, let them grab for pellets held with a pair of forceps or dispense a pellet to restore their motivation.</li>
		<li>For experiments involving only FP training, continue training as described in 2.4. 
		NOTE: Typically, 1-2 FP sessions are needed to help transition from reward touch to SP(Straight Pull) training. The goal of these FP sessions is to habituate rats to reach out, grab and pull the handle, rather than to only touch it. As with reward-touch training, it is important not to over-train if the goal is to transition to a next training step.</li>
	</ol>
	</li>
	<li>Straight pull (SP): Train the rats to pull the handle without deviating more than 2 mm from midline. 
	NOTE: The midline is defined relative to the start position of the robot, not to the midpoint of the cage window. Thus, a pulling attempt ending at the midpoint of the cage window will result in a pulling trajectory that deviates more than 2 mm from midline.
	<ol>
		<li>Adjust the software settings so that only trials where the pulling movement does not deviate more than 2 mm from midline on either side are rewarded by a tone and a pellet. Keep all other parameters as described in step 2.4.</li>
		<li>Put the rat in the training cage and train until 100 trials are completed or until 60 min have passed, whichever comes first. 
		NOTE: Rats may become extremely agitated and stop trying to pull after repeated failed attempts. Tap on the cage to redirect their attention to the reaching task, let them grab for pellets held with a pair of forceps or dispense a pellet to restore their motivation.</li>
		<li>Continue training until the rats reach plateau performance, or adapt the training period according to the goal of an experiment.</li>
	</ol>
	</li>
</ol>

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Q. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Compensation+aids+skilled+reaching+in+aging+and+in+recovery+from+forelimb+motor+cortex+stroke+in+the+rat.">Compensation aids skilled reaching in aging and in recovery from forelimb motor cortex stroke in the rat.</a> Neurosci. 167 (1), 21-30 (2010).</li><li>Molina-Luna, K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Dopamine+in+motor+cortex+is+necessary+for+skill+learning+and+synaptic+plasticity.">Dopamine in motor cortex is necessary for skill learning and synaptic plasticity.</a> PloS one. 4 (9), (2009).</li><li>VandenBerg, P. M., Hogg, T. M., Kleim, J. A., Whishaw, I. Q. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Long-Evans+rats+have+a+larger+cortical+topographic+representation+of+movement+than+Fischer-344+rats:+A+microstimulation+study+of+motor+cortex+in+na&#305;&#776;ve+and+skilled+reaching-trained+rats.">Long-Evans rats have a larger cortical topographic representation of movement than Fischer-344 rats: A microstimulation study of motor cortex in na&#305;&#776;ve and skilled reaching-trained rats.</a> Brain Res Bull. 59 (3), 197-203 (2002).</li><li>Whishaw, I. Q., Gorny, B., Foroud, A., Kleim, J. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Long-Evans+and+Sprague-Dawley+rats+have+similar+skilled+reaching+success+and+limb+representations+in+motor+cortex+but+different+movements:+some+cautionary+insights+into+the+selection+of+rat+strains+for+neurobiological+motor+research.">Long-Evans and Sprague-Dawley rats have similar skilled reaching success and limb representations in motor cortex but different movements: some cautionary insights into the selection of rat strains for neurobiological motor research.</a> Behav Brain Res. 145 (1-2), 221-232 (2003).</li><li>Harms, K. J., Rioult-Pedotti, M. S., Carter, D. 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The authors have nothing to disclose

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 movement show distinct profiles during motor skill training. These may reflect different subprocesses within the motor skill learning process7,12.
In the results presented here, we show that even a small change in training protocol, such as a different starting position of the handle (SP1 vs. SP2), results in altered movement parameter profiles. By adding two FP sessions prior to straight pull training to our previously published training protocol10, we were able to dissociate the effects of learning to pull from the skill to pull straight. In addition, the off-center placement of the robot&#39;s handle in this improved training protocol (SP2) results in a task with a shallower learning curve that is more advantageous for studying mechanisms of motor learning as it allows time for interventions before plateau performance levels are reached. Moreover, it is possible to distinguish factors related to task execution from factors related to task difficulty that are not immediately reflected in success rates, but may indicate further refinement of motor skill4. Smooth execution of the pulling movements, reflected in the number of submovements may be considered a measure of skilled, straight pulling. By contrast, spatial variability of the movement drops rapidly as the number of valid pulls increases in all three versions of the reach-and-pull task, but is not directly related to pulling success in straight pull tasks and may reflect general motor function or convergence on the correct movement required for a successful trial, rather than skilled task execution once the rules of the task have been learned.
Execution of our robotic reach-and-pull tasks is remarkably reliable and reproducible between animals. All trained animals acquire the free pull task, and a majority (90-95% of animals) is able to learn the straight pull task. Even animals that show consistently low success rates during straight pulling continue to execute a high number of valid pulling attempts. These failed, but valid attempts are fully recorded. Failed reaching attempts in a classical skilled reaching task typically results in an incomplete reaching movement. It is therefore not only possible to analyze aspects of the movement related to successful task acquisition, but also to assess which movement parameters result in failure.
While the measurements presented here give detailed information about pulling movements, not all aspects of the reach-and-pull forelimb movement are captured. Any changes in reaching behavior that occur prior to the first touch or after release of the handle at the end of a valid pulling attempt are not recorded and can therefore not be analyzed with equal precision. For example, the number of grabbing attempts prior to a pulling movement are not measured, even though they may be relevant in relation to functional recovery models. Analysis of high-speed video recordings provides this additional information. Previously described methods for movement tracking13,14 can be adapted for this purpose.
Moreover, our recordings do not provide information about the quality of the rat&#39;s grip of the handle. Rotation of the handle, indicating pronation or supination of the paw, could provide some insight in combination with high-speed video. Since rotation and grip are particularly affected in rat stroke models9,15,16, future experiments are needed to determine how effective the reach-and-pull tasks presented here are in capturing post-stroke motor deficits.
The tasks presented here were designed to mimic conventional single pellet reaching tasks: the required pulling distance is based on the typical distance between window and pellet in these tasks and the free movement of the handle within the horizontal plane enables measurement of the rat&#39;s natural paw trajectories over a 10 mm distance in valid trials.
Likewise, invalid trials where the handle is moved outside of the robot&#39;s workspace (e.g., the handle is swiped aside during pulling) or where the pulled distance is insufficient could be interpreted as being similar to dropped pellets in single pellet reaching tasks, even though the handle does not drop to the floor when released.
This design captures more aspects of the pulling movement than automated tasks aimed at measuring a single simple movement. However, it also enables interaction between pulling and rotational movements and gives animals the opportunity for compensation. Insight into compensatory movements during motor function recovery may be valuable, but also complicates interpretation of the results.
A critical step in acquisition of the reach-and-pull tasks is successful conditioning of the reward touch step of training. Without reliable interaction between rat and robot, any further training steps are difficult to carry out and quantify reliably. It is equally important to not overtrain the rats during transitional training steps, however. While animals may continue to show improvements in performance during reward-touch training sessions for more than 3-4 days, over-consolidation prevents effective shaping of behavior in subsequent reach-and-pull training.
Constant placement of the handle is essential for correct execution and reliable analysis of any data obtained using the robotic reach-and-pull task presented here. While the position of the handle relative to rest of the robot and to midline is software-defined, the handle&#39;s position relative to the cage window is easily varied by moving either sideways. Here, we have shown how alignment of the handle with either the edge or center of the window alters task acquisition and can be used to study processes underlying motor skill learning. Inconstant alignment of the handle within a training period, however, will introduce confounding effects and yields unreliable behavioral readouts.
In the protocol described here, rats are trained during daily sessions comprised of 100 trials, similar to our previous single pellet reaching experiments4,17. With automated training setups the number of trials per session can easily be increased, without requiring much more effort on the part of the researcher. While higher numbers of trials per session can result in lower intra-individual variability, the effects of increasing the number of trials per training session on the speed of learning and recovery has to be taken into account. Moreover, factors like satiety and fatigue will become more relevant and could interfere with performance in very long training sessions.
Although strain and sex differences in motor skill learning ability have been described in rats4,18,19, we have obtained reliable performance in both male Sprague-Dawley and Long-Evans rats. Older animals (4-5 months old) are generally slower than younger ones (8-10 weeks) and show longer intervals between trials. Moreover, we have observed poor performance in older animals when food pellets are replaced with a sucrose-water reward. Older animals that receive liquid rewards experience difficulties when transitioning from reward-touch to pulling.&#160;This may be caused by age-related reward-preferences, in which case using a more palatable liquid reward such as yoghurt or peanut oil may yield better results. Alternatively, the behavior of older animals might indicate difficulties in understanding a more abstract reaching task (compared to conventional pellet reaching), although we do observe reliable learning behavior in these animals when solid food rewards are used. Thus, the effect of the chosen reward should particularly be considered when designing experiments where the use of older animals is preferable (i.e. in models of stroke or neurodegenerative disease).
We have not yet studied sex differences in motor skill learning using ETH Pattus. It is unlikely that female rats will not be able to acquire the SP or FP tasks, although their learning strategies may differ from males. However, although the estrous cycle affects spine density in female rats, effects on learning curves and learning-related plasticity in primary motor cortex are limited20.
The robotic tasks can be varied in several ways: the required movement may be more or less precise (for example, a limited amount of deviation from a prescribed trajectory in a reach-and-pull task), or the robot may interfere with or assist the executed movement in any one or all of three dimensions (lengthwise or sideways movements in the horizontal plane and rotation angle of the handle). Other than variations on the reach-and-pull tasks presented in this paper, it is possible to design motor skill learning tasks where for example rotation angle of the handle, maximum movement velocity, or acceleration profile define the success of a trial.
Other than allowing easy variation of task parameters, the experimental setup presented here spatially separates the motor action from the given reward, which is dispensed on the opposite side of the cage. Adapting the reward size is not possible in classical reaching tasks without affecting task difficulty21&#160;(a smaller food pellet is more difficult to grasp than a larger one), nor is it possible to vary the chance of a reward independently of the animal&#39;s skill level. Using a robotic task, the reward obtained for a motor action may be varied based on skill, current performance, or may be varied to assess factors such as motivation.
In conclusion, automated training combined with kinematic movement analysis provides an automated, objective method for studying motor skill learning that closely mimics conventional skilled reaching tasks, but yields additional data of both successful and failed pulling attempts. This approach opens up new avenues of investigation in combination with electrophysiological, pharmacological or optogenetic interventions aimed at enhancement of or interference with reach-and-pull movements or resulting food rewards.

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">
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		<tr height="21">
			<td height="21" style="height:21px;width:247px;">ETH Pattus</td>
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			<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 animals, the handle was placed in the center of the cage window. These results were previously published in Lambercy et al.10Rats in the SP2 group (N = 7) received 2 FP-training sessions before transitioning to straight-pull training. The handle was aligned with the edge of the cage window for this group, resulting is a slightly more difficult task, as the handle would deviate more than 2 mm from the midline if pulled to the midpoint of the cage window.
All rats readily learn to interact with the robotic manipulandum (Figure 2A). The number of valid pulls (i.e. the number of pulling attempts where the handle is pulled at least 10 mm) increases rapidly and reaches stable plateau levels after 2-3 days in FP and SP1. The number of valid attempts increases at a comparable rate during the FP sessions of SP2, resulting in a stable number of valid pulls per session throughout SP training in SP2 rats. Plateau performance is high in all training paradigms and is independent of task parameters like handle position and limits on the permitted amount of deviation from midline.
SP1 rats reach plateau success rate (i.e. the percentage of valid pulls that remains within 2 mm of midline) after 5-4 training sessions (Figure 2B). SP2 rats show a slower progression and reach plateau success rate after 11 sessions, indicating that successful execution of this version of the straight pull task is more difficult to achieve. Final success rates are similar for SP1 and SP2.
During SP training, pulling trajectories become increasingly straighter, as evidenced by decreased deviation from midline (i.e. the area between the measured trajectory and midline) and resulting in an increased number of successful pulls in both SP1 and SP2 (Figure 3, Figure 5A). Interestingly, the average pulling trajectory of FP rats becomes straighter during the 22 day training period as well, although the amount of deviation from midline stabilizes at a higher level than in SP1 rats. This indicates that the natural pulling trajectory is relatively straight when the robot&#39;s handle is located in the center of the cage window. When the handle is aligned with the edge of the window, however, the puling trajectory is curved and deviation from midline remains stable during the SP2-FP sessions. Deviation from midline in the SP2 group remains higher than in the SP1 group, likely as a result of off-center handle placement.
Variability of the pulling trajectories (i.e. size of the 95% confidence interval) drops rapidly in FP and SP1, and reaches comparable levels in these groups after 3-4 training sessions (Figure 5B). Interestingly, SP2 animals do not show this decrease in variability and continuously pull with relatively low variability during SP sessions, but do show a rapid decline of trajectory variability during the SP2-FP sessions.
Similarly, both mean and peak pulling speed increase during initial training sessions (FP, SP1 and SP2-FP), but are stable during SP2-SP sessions (Figures 5C, 5D). Although average pulling speed does not change during SP2 sessions, pulling speed profiles become much less variable through training (Figure 4). This is reflected in both the number of submovements (i.e. number of accelerations and decelerations in the pulling movement, Figure 5E) and the number of trials with stops (i.e. trials where pulling velocity drops to zero, Figure 5F). After a strong decrease during the initial SP1 and SP2-FP sessions, both the number of submovements and the number of trials with stops continue to decrease in SP1 and SP2 throughout the 22-session training period. In FP rats, the number of submovements and trials with stops initially rapidly decrease as well, but stabilize at a higher level than both straight-pull groups and do not show a continued improvement. Interestingly, pulling speed does not seem to be closely related to the outcome of a trial (Figure 4).
The ~5% of rats that do not successfully learn to perform the straight-pull task generally do learn to pull the handle, but are unable to pull straight (Figure 6). These animals show a consistently high deviation from midline, resulting in low success rates. Performance during SP2-FP sessions the animal presented here during is otherwise comparable to that of SP2 animals that do acquire the task successfully.
<img alt="Figure 1" src="/files/ftp_upload/54970/54970fig1.jpg" /> 
Figure 1: Overview of Robotic Manipulandum and Handle Positioning. (A) Technical drawing showing the robotic manipulandum and marks for alignment with the training cage. (B) Handle held in constant reference position at the start of a training session. (C) Handle in free starting position at the start of a pulling trial. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54970/54970fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" src="/files/ftp_upload/54970/54970fig2.jpg" /> 
Figure 2: Typical Learning Curves of a Reach-and-pull Task. (A) Valid pulling attempts in a free pull task (FP, N = 6), straight pull task without introductory FP-sessions (SP1, N = 12) and a straight pull task (SP2, N = 7) with introductory FP-sessions (SP2-FP). Values are mean &#177; S.E.M. (B) Successful pulling attempts as percentage of valid attempts in the straight pulling task with (SP2) and without (SP1) introductory FP-sessions. Values are mean &#177; S.E.M. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54970/54970fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" src="/files/ftp_upload/54970/54970fig3.jpg" /> 
Figure 3: Pulling Trajectories become Progressively Straighter and Less Variable Throughout Training of the SP2 Task. Successful (black), failed (grey) and average (green) trajectories are shown for the first and final straight pull training session for a representative animal. Dotted lines show the 4 mm wide zone within which a successful trial is executed. The red dot denotes the starting position of the handle. The green dot shows the theoretical endpoint of a perfectly straight 10 mm pulling attempt. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54970/54970fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" src="/files/ftp_upload/54970/54970fig4.jpg" /> 
Figure 4: Mean Speed in the Pulling Direction of Valid Attempts Increases Slightly Throughout Training and Becomes Less Variable from the First (A) to the Last (B) Training Session. Average (green) and individual pulling speed profiles of successful (black) and failed (grey) pulling attempts are shown for a representative animal carrying out the SP2 task. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54970/54970fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" src="/files/ftp_upload/54970/54970fig5.jpg" /> 
Figure 5: An Overview of Parameters Measured in a Free Pulling (FP, N = 6) Task, Straight Pull Task Without Introductory FP-sessions (SP1, N = 12) and a Straight Pull Task (SP2, N = 7) with Introductory FP-sessions (SP2-FP). Values are Mean &#177; S.E.M of All Valid Pulling Attempts. (A) Deviation from midline (area between the measured valid trajectories and a perfectly straight pulling attempt along midline, mm2). (B) Variability of pulling trajectories (95% confidence interval of all valid attempts within a session). (C) Mean pulling speed of all valid attempts (mm/s). (D) Peak pulling speed of all valid attempts (mm/s). (E) Submovements as indicated by zero crossings in the acceleration profile of valid pulling attempts (F) Pulling attempts with stops (% of valid pulls) <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54970/54970fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 6" src="/files/ftp_upload/54970/54970fig6.jpg" /> 
Figure 6: Example of an Animal that Does not Successfully Learn to Perform the SP2 Task. (A) Pulling trajectories in the first and last training session. Successful (black), failed (grey) and average (green) trajectories are shown for the first and final straight pull training session for a representative animal. Dotted lines show the 4 mm wide zone within which a successful trial is executed. The red dot denotes the starting position of the handle. The green dot shows the theoretical endpoint of a perfectly straight 10 mm pulling attempt. (B) Learning curve showing valid and successful pulling attempts throughout the training period. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54970/54970fig6large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

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 ...

investigating-motor-skill-learning-processes-with-robotic

Nanyang Technological University

Research

JoVE Journal

Behavior

8.6K Views.  University Hospital Zurich. 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.

Video: Investigating Motor Skill Learning Processes with a Robotic Manipulandum

Study Motor Skill Learning by Single-pellet Reaching Tasks in Mice

Reaching for and retrieving objects require precise and coordinated motor movements in the forelimb. When mice are repeatedly trained to grasp and retrieve food rewards positioned at a specific location, their motor performance (defined as accuracy and speed) improves progressively over time, and plateaus after persistent training. Once such reaching skill is mastered, its further maintenance does not require constant practice. Here we introduce a single-pellet reaching task to study the acquisition and maintenance of skilled forelimb movements in mice. In this video, we first describe the behaviors of mice that are commonly encountered in this learning and memory paradigm, and then discuss how to categorize these behaviors and quantify the observed results. Combined with mouse genetics, this paradigm can be utilized as a behavioral platform to explore the anatomical underpinnings, physiological properties, and molecular mechanisms of learning and memory.

Persistent practice improves the precision of coordinated movements.&#160;Here we introduce a single-pellet reaching task, which is designed to assess the learning and memory of forelimb skill in mice.&#160;

Reaching for and retrieving objects require precise and coordinated motor movements in the forelimb. When mice are repeatedly trained to grasp and ...

Methods to Explore the Influence of Top-down Visual Processes on Motor Behavior

Kinesthetic awareness is important to successfully navigate the environment. When we interact with our daily surroundings, some aspects of movement are deliberately planned, while others spontaneously occur below conscious awareness. The deliberate component of this dichotomy has been studied extensively in several contexts, while the spontaneous component remains largely under-explored. Moreover, how perceptual processes modulate these movement classes is still unclear. In particular, a currently debated issue is whether the visuomotor system is governed by the spatial percept produced by a visual illusion or whether it is not affected by the illusion and is governed instead by the veridical percept. Bistable percepts such as 3D depth inversion illusions (DIIs) provide an excellent context to study such interactions and balance, particularly when used in combination with reach-to-grasp movements. In this study, a methodology is developed that uses a DII to clarify the role of top-down processes on motor action, particularly exploring how reaches toward a target on a DII are affected in both deliberate and spontaneous movement domains.

It is unclear how top-down signals from the ventral visual stream affect movement. We developed a paradigm to test motor behavior towards a target on a 3D depth inversion illusion. Significant differences are reported in both deliberate, goal-directed movements and automatic actions under illusory and veridical viewing conditions.

Kinesthetic awareness is important to successfully navigate the environment. When we interact with our daily surroundings, some aspects of movement are ...

Compensatory Limb Use and Behavioral Assessment of Motor Skill Learning Following Sensorimotor Cortex Injury in a Mouse Model of Ischemic Stroke

Mouse models have become increasingly popular in the field of behavioral neuroscience, and specifically in studies of experimental stroke. As models advance, it is important to develop sensitive behavioral measures specific to the mouse. The present protocol describes a skilled motor task for use in mouse models of stroke. The Pasta Matrix Reaching Task functions as a versatile and sensitive behavioral assay that permits experimenters to collect accurate outcome data and manipulate limb use to mimic human clinical phenomena including compensatory strategies (i.e., learned non-use) and focused rehabilitative training. When combined with neuroanatomical tools, this task also permits researchers to explore the mechanisms that support behavioral recovery of function (or lack thereof) following stroke. The task is both simple and affordable to set up and conduct, offering a variety of training and testing options for numerous research questions concerning functional outcome following injury. Though the task has been applied to mouse models of stroke, it may also be beneficial in studies of functional outcome in other upper extremity injury models.

Mouse models have become increasingly popular in studies of behavioral neuroscience. As models advance, it is important to develop sensitive behavioral measures specific to the mouse. This protocol describes the Pasta Matrix Reaching Task, which is a skilled motor task for use in mouse models of stroke.

Mouse models have become increasingly popular in the field of behavioral neuroscience, and specifically in studies of experimental stroke. As models ...

Stimulating the Lip Motor Cortex with Transcranial Magnetic Stimulation

Transcranial magnetic stimulation (TMS) has proven to be a useful tool in investigating the role of the articulatory motor cortex in speech perception. Researchers have used single-pulse and repetitive TMS to stimulate the lip representation in the motor cortex. The excitability of the lip motor representation can be investigated by applying single TMS pulses over this cortical area and recording TMS-induced motor evoked potentials (MEPs) via electrodes attached to the lip muscles (electromyography; EMG). Larger MEPs reflect increased cortical excitability. Studies have shown that excitability increases during listening to speech as well as during&#160;viewing speech-related movements. TMS can be used also to disrupt the lip motor representation. A 15-min train of low-frequency sub-threshold repetitive stimulation has been shown to suppress motor excitability for a further 15-20 min. This TMS-induced disruption of the motor lip representation impairs subsequent performance in demanding speech perception tasks and modulates auditory-cortex responses to speech sounds. These findings are consistent with the suggestion that the motor cortex contributes to speech perception. This article describes how to localize the lip representation in the motor cortex and how to define the appropriate stimulation intensity for carrying out both single-pulse and repetitive TMS experiments.

Transcranial magnetic stimulation (TMS) has proven to be a useful tool in investigating the role of the articulatory motor cortex in speech perception.&#160; This article describes how to record motor evoked potentials (MEPs) from the lip muscles and how to disrupt the motor lip representation using repetitive TMS.

Transcranial magnetic stimulation (TMS) has proven to be a useful tool in investigating the role of the articulatory motor cortex in speech perception. ...

Quantifying Learning in Young Infants: Tracking Leg Actions During a Discovery-learning Task

Task-specific actions emerge from spontaneous movement during infancy. It has been proposed that task-specific actions emerge through a discovery-learning process. Here a method is described in which 3-4 month old infants learn a task by discovery and their leg movements are captured to quantify the learning process. This discovery-learning task uses an infant activated mobile that rotates and plays music based on specified leg action of infants. Supine infants activate the mobile by moving their feet vertically across a virtual threshold. This paradigm is unique in that as infants independently discover that their leg actions activate the mobile, the infants&#8217; leg movements are tracked using a motion capture system allowing for the quantification of the learning process. Specifically, learning is quantified in terms of the duration of mobile activation, the position variance of the end effectors (feet) that activate the mobile, changes in hip-knee coordination patterns, and changes in hip and knee muscle torque. This information describes infant exploration and exploitation at the interplay of person and environmental constraints that support task-specific action. Subsequent research using this method can investigate how specific impairments of different populations of infants at risk for movement disorders influence the discovery-learning process for task-specific action.

A method is described in which 3-4 month old infants learn a task by discovery and their leg movements are captured to quantify the learning process.

Task-specific actions emerge from spontaneous movement during infancy. It has been proposed that task-specific actions emerge through a discovery-learning ...

Event-related Potentials During Target-response Tasks to Study Cognitive Processes of Upper Limb Use in Children with Unilateral Cerebral Palsy

Unilateral Cerebral Palsy (CP) is a neurodevelopmental disorder that is a very common cause of disability in childhood. It is characterized by unilateral motor impairments that are frequently dominated in the upper limb. In addition to a reduced movement capacity of the affected upper limb, several children with unilateral CP show a reduced awareness of the remaining movement capacity of that limb. This phenomenon of disregarding the preserved capacity of the affected upper limb is regularly referred to as Developmental Disregard (DD). Different theories have been postulated to explain DD, each suggesting slightly different guidelines for therapy. Still, cognitive processes that might additionally contribute to DD in children with unilateral CP have never been directly studied. The current protocol was developed to study cognitive aspects involved in upper limb control in children with unilateral CP with and without DD. This was done by recording event-related potentials (ERPs) extracted from the ongoing EEG during target-response tasks asking for a hand-movement response. ERPs consist of several components, each of them associated with a well-defined cognitive process (e.g., the N1 with early attention processes, the N2 with cognitive control and the P3 with cognitive load and mental effort). Due to its excellent temporal resolution, the ERP technique enables to study several covert cognitive processes preceding overt motor responses and thus allows insight into the cognitive processes that might contribute to the phenomenon of DD. Using this protocol adds a new level of explanation to existing behavioral studies and opens new avenues to the broader implementation of research on cognitive aspects of developmental movement restrictions in children.

Several children with unilateral Cerebral Palsy seem to disregard the preserved capacity of their affected upper limb. This Developmental Disregard is extensively described in the literature but the involved cognitive processes have not been studied. To study underlying cognitive factors of upper limb control, an event-related potential protocol was developed.

Unilateral Cerebral Palsy (CP) is a neurodevelopmental disorder that is a very common cause of disability in childhood. It is characterized by unilateral ...

Using a Split-belt Treadmill to Evaluate Generalization of Human Locomotor Adaptation

Understanding the mechanisms underlying locomotor learning helps researchers and clinicians optimize gait retraining as part of motor rehabilitation. However, studying human locomotor learning can be challenging. During infancy and childhood, the neuromuscular system is quite immature, and it is unlikely that locomotor learning during early stages of development is governed by the same mechanisms as in adulthood. By the time humans reach maturity, they are so proficient at walking that it is difficult to come up with a sufficiently novel task to study de novo locomotor learning. The split-belt treadmill, which has two belts that can drive each leg at a different speed, enables the study of both short- (i.e., immediate) and long-term (i.e., over minutes-days; a form of motor learning) gait modifications in response to a novel change in the walking environment. Individuals can easily be screened for previous exposure to the split-belt treadmill, thus ensuring that all experimental participants have no (or equivalent) prior experience. This paper describes a typical split-belt treadmill adaptation protocol that incorporates testing methods to quantify locomotor learning and generalization of this learning to other walking contexts. A discussion of important considerations for designing split-belt treadmill experiments follows, including factors like treadmill belt speeds, rest breaks, and distractors. Additionally, potential but understudied confounding variables (e.g., arm movements, prior experience) are considered in the discussion.

We describe a protocol for investigating human locomotor adaptation using the split-belt treadmill, which has two belts that can drive each leg at a different speed. We specifically focus on a paradigm designed to test the generalization of adapted locomotor patterns to different walking contexts (e.g., gait speeds, walking environments).

Understanding the mechanisms underlying locomotor learning helps researchers and clinicians optimize gait retraining as part of motor rehabilitation. ...

Using Virtual Reality to Transfer Motor Skill Knowledge from One Hand to Another

As far as acquiring motor skills is concerned, training by voluntary physical movement is superior to all other forms of training (e.g. training by observation or passive movement of trainee&#39;s hands by a robotic device). This obviously presents a major challenge in the rehabilitation of a paretic limb since voluntary control of physical movement is limited. Here, we describe a novel training scheme we have developed that has the potential to circumvent this major challenge. We exploited the voluntary control of one hand and provided real-time movement-based manipulated sensory feedback as if the other hand is moving. Visual manipulation through virtual reality (VR) was combined with a device that yokes left-hand fingers to passively follow right-hand voluntary finger movements. In healthy subjects, we demonstrate enhanced within-session performance gains of a limb in the absence of voluntary physical training. Results in healthy subjects suggest that training with the unique VR setup might also be beneficial for patients with upper limb hemiparesis by exploiting the voluntary control of their healthy hand to improve rehabilitation of their affected hand.

We describe a novel virtual-reality based setup which exploits voluntary control of one hand to improve motor-skill performance in the other (non-trained) hand. This is achieved by providing real-time movement-based sensory feedback as if the non-trained hand is moving. This new approach may be used to enhance rehabilitation of patients with unilateral hemiparesis.

As far as acquiring motor skills is concerned, training by voluntary physical movement is superior to all other forms of training (e.g. training by ...

The "Motor" in Implicit Motor Sequence Learning: A Foot-stepping Serial Reaction Time Task

This protocol describes a modified serial reaction time (SRT) task used to study implicit motor sequence learning. Unlike the classic SRT task that involves finger-pressing movements while sitting, the modified SRT task requires participants to step with both feet while maintaining a standing posture. This stepping task necessitates whole body actions that impose postural challenges. The foot-stepping task complements the classic SRT task in several ways. The foot-stepping SRT task is a better proxy for the daily activities that require ongoing postural control, and thus may help us better understand sequence learning in real-life situations. In addition, response time serves as an indicator of sequence learning in the classic SRT task, but it is unclear whether response time, reaction time (RT) representing mental process, or movement time (MT) reflecting the movement itself, is a key player in motor sequence learning. The foot-stepping SRT task allows researchers to disentangle response time into RT and MT, which may clarify how motor planning and movement execution are involved in sequence learning. Lastly, postural control and cognition are interactively related, but little is known about how postural control interacts with learning motor sequences. With a motion capture system, the movement of the whole body (e.g., the center of mass (COM)) can be recorded. Such measures allow us to reveal the dynamic processes underlying discrete responses measured by RT and MT, and may aid in elucidating the relationship between postural control and the explicit and implicit processes involved in sequence learning. Details of the experimental set-up, procedure, and data processing are described. The representative data are adopted from one of our previous studies. Results are related to response time, RT, and MT, as well as the relationship between the anticipatory postural response and the explicit processes involved in implicit motor sequence learning.

We introduce the foot-stepping serial reaction time (SRT) task. This modified SRT task, complementing the classic SRT task that involves only finger-pressing movement, better approximates daily sequenced activities and allows researchers to study the dynamic processes underlying discrete response measures and disentangle the explicit process operating in implicit sequence learning.

This protocol describes a modified serial reaction time (SRT) task used to study implicit motor sequence learning. Unlike the classic SRT task that ...

Modeling Verbal Behavior Deficits with the Stimulus Control Ratio Equation, SCoRE

Verbal operant analyses are the extension of functional analysis technology to the field of verbal behavior, of particular relevance to autism spectrum disorders and associated developmental disabilities. Similarly, a verbal operant analysis carefully controls specific environmental factors that influence language, and measures strength of responding across four verbal operant classes: tact, mand, echoic, and sequelic. The frequency of each independent verbal operant is then measured against one another using the stimulus control ratio equation (SCoRE) to summarize the relative strength of the speaker&#8217;s repertoire. The verbal behavior SCoRE yields a statistic that can be compared against itself (e.g., for the purposes of pre/post testing) or against others (e.g., for the purposes of randomized controlled trials). The results of this evaluation provide an individualized hierarchy for diverging stimulus control across the verbal operants, from which a treatment plan for errorless language learning may be prescribed.

This article describes the procedures for conducting a verbal operant analysis (VOA), calculating the stimulus control ratio equation (SCoRE), and developing individualized verbal behavior treatment plans, specifically significant to address the deficits characteristic of autism.

Verbal operant analyses are the extension of functional analysis technology to the field of verbal behavior, of particular relevance to autism spectrum ...