Name: design and use of an apparatus for presenting graspable objects in 3d workspace
Uploaded: 2019-08-08T14:45:00
Description: Watch this Scientific Journal Video about Design and Use of an Apparatus for Presenting Graspable Objects in 3D Workspace at JoVE.com

We thank Mr. Shijiang Shen for his advice on apparatus design and Ms. Guihua Wang for her assistance with animal care and training. This work was supported by National Key Research and Development Program of China (2017YFC1308501), the National Natural Science Foundation of China (31627802), the Public Projects of Zhejiang Province (2016C33059), and the Fundamental Research Funds for the Central Universities.

All behavioral and surgical procedures conformed to the Guide for the Care and Use of Laboratory Animals (China Ministry of Health) and were approved by the Animal Care Committee at Zhejiang University, China.
1.Assembling the 3D translational device
<ol>
	<li>Build a frame of size 920 mm x 690 mm x 530 mm with aluminum construction rails (cross section: 40 mm x 40 mm).</li>
	<li>Secure four pedestals to the two ends of the Y-rails with screws (M4) (Figure 1B).<...

<ol>
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The behavioral apparatus is described here enables a trial-wise combination of different reaching and grasping movements (i.e., the monkey can grasp differently shaped objects in any arbitrary 3D locations in each trial). This is accomplished through the combination of a custom turning table that switches different objects and a linear translational device that transports the turning table to multiple positions in 3D space. In addition, the neural signals from the monkey, trajectory of wrist, and hand shapes were able to...

Various apparatuses have been developed to study the neural principles underlying reaching and grasping movement in non-human primate. In reaching tasks, touch screen1,2, screen cursor controlled by a joystick3,4,5,6,7, and virtual reality technology8,9,10 have all been employed to present 2D and 3D targets, respectively. To introduce different grip types, differently shaped objects fixed in one position or rotating around an axis were widely used in the grasping tasks11,12,13. An alternative is to use visual cues to inform subjects to grasp the same object with different grip types14,15,16,17. More recently, reaching and grasping movements have been studied together (i.e., subjects reach multiple positions and grasp with different grip types in an experimental session)18,19,20,21,22,23,24,25,26,27,28,29. Early experiments have presented objects manually, which inevitably lead to low time and spatial precision20,21. To improve experimental precision and save manpower, automatic presentation devices controlled by programs have been widely used. To vary the target position and grip type, experimenters have exposed multiple objects simultaneously, but the relative (or absolute) position of targets and the grip types are bound together, which causes rigid firing patterns through long-term training22,27,28. Objects are usually presented in a 2D plane, which limits the diversity of reaching movement and neural activity19,25,26. Recently, virtual reality24 and robot arm23,29 have been introduced to present objects in 3D space.
Presented here are detailed protocols for building and using an automated apparatus30 that can achieve any combination of multiple target positions and grip types in 3D space. We designed a turning table to switch objects and 3D translational device to transport the turning table in 3D space. Both the turning table and translational device are driven by independent motors. Meanwhile, the 3D trajectory of subject&rsquo;s wrist and neural signals are recorded simultaneously throughout the experiment. The apparatus provides a valuable platform for the study of upper limb function in the rhesus monkey.

<table>
	<tbody>
		<tr>
			<td>Active X-rail</td>
			<td>CCM Automation technology Inc., China</td>
			<td>W50-25</td>
			<td>Effective travel, 600 mm; Load, 25 kg</td>
		</tr>
		<tr>
			<td>Active Y-rail</td>
			<td>CCM Automation technology Inc., China</td>
			<td>W60-35</td>
			<td>Effective travel, 300 mm, Load 35 kg</td>
		</tr>
		<tr>
			<td>Active Z-rail</td>
			<td>CCM Automation technology Inc., China</td>
			<td>W50-25</td>
			<td>Effective travel, 500 mm; Load 25 kg</td>
		</tr>
		<tr>
			<td>Bearing</td>
			<td>Taobao.com</td>
			<td>6004-2RSH</td>
			<td>Acrylic</td>
		</tr>
		<tr>
			<td>Case</td>
			<td>Custom mechanical processing</td>
			<td>TT-C</td>
			<td>Acrylic</td>
		</tr>
		<tr>
			<td>Connecting ring</td>
			<td>CCM Automation technology Inc., China</td>
			<td>57/60-W50</td>
			<td></td>
		</tr>
		<tr>
			<td>Connecting shaft</td>
			<td>CCM Automation technology Inc., China</td>
			<td>D12-700</td>
			<td>Diam., 12 mm;Length, 700 mm</td>
		</tr>
		<tr>
			<td>Diaphragm coupling</td>
			<td>CCM Automation technology Inc., China</td>
			<td>CCM 12-12</td>
			<td>Inner diam., 12-12mm</td>
		</tr>
		<tr>
			<td>Diaphragm coupling</td>
			<td>CCM Automation technology Inc., China</td>
			<td>CCM 12-14</td>
			<td>Inner diam., 14-12mm</td>
		</tr>
		<tr>
			<td>Electric slip ring</td>
			<td>Semring Inc., China</td>
			<td>SNH020a-12</td>
			<td>Acrylic</td>
		</tr>
		<tr>
			<td>Locating bar</td>
			<td>Custom mechanical processing</td>
			<td>TT-L</td>
			<td>Acrylic</td>
		</tr>
		<tr>
			<td>Motion capture system</td>
			<td>Motion Analysis Corp. US</td>
			<td>Eagle-2.36</td>
			<td></td>
		</tr>
		<tr>
			<td>Neural signal acquisition system</td>
			<td>Blackrock Microsystems Corp. US</td>
			<td>Cerebus</td>
			<td></td>
		</tr>
		<tr>
			<td>NI DAQ device</td>
			<td>National Instruments, US</td>
			<td>USB-6341</td>
			<td></td>
		</tr>
		<tr>
			<td>Object</td>
			<td>Custom mechanical processing</td>
			<td>TT-O</td>
			<td>Acrylic</td>
		</tr>
		<tr>
			<td>Passive Y-rail</td>
			<td>CCM Automation technology Inc., China</td>
			<td>W60-35</td>
			<td>Effective travel, 300 mm; Load 35 kg</td>
		</tr>
		<tr>
			<td>Passive Z-rail</td>
			<td>CCM Automation technology Inc., China</td>
			<td>W50-25</td>
			<td>Effective travel, 500 mm; Load 25 kg</td>
		</tr>
		<tr>
			<td>Pedestal</td>
			<td>CCM Automation technology Inc., China</td>
			<td>80-W60</td>
			<td></td>
		</tr>
		<tr>
			<td>Peristaltic pump</td>
			<td>Longer Inc., China</td>
			<td>BT100-1L</td>
			<td></td>
		</tr>
		<tr>
			<td>Planetary gearhead</td>
			<td>CCM Automation technology Inc., China</td>
			<td>PLF60-5</td>
			<td>Flange, 60&#215;60 mm; Reduction ratio, 1:5</td>
		</tr>
		<tr>
			<td>Right triangle frame</td>
			<td>CCM Automation technology Inc., China</td>
			<td>290-300</td>
			<td></td>
		</tr>
		<tr>
			<td>Rotator</td>
			<td>Custom mechanical processing</td>
			<td>TT-R</td>
			<td>Acrylic</td>
		</tr>
		<tr>
			<td>Servo motor</td>
			<td>Yifeng Inc., China</td>
			<td>60ST-M01930</td>
			<td>Flange, 60&#215;60 mm; Torque, 1.91 N&#183;m; for Y- and Z-rail</td>
		</tr>
		<tr>
			<td>Servo motor</td>
			<td>Yifeng Inc., China</td>
			<td>60ST-M01330</td>
			<td>Flange, 60&#215;60 mm; Torque, 1.27 N&#183;m; for X-rail</td>
		</tr>
		<tr>
			<td>Shaft</td>
			<td>Custom mechanical processing</td>
			<td>TT-S</td>
			<td>Acrylic</td>
		</tr>
		<tr>
			<td>Stepping motor</td>
			<td>Taobao.com</td>
			<td>86HBS120</td>
			<td>Flange, 86&#215;86 mm; Torque, 1.27 N&#183;m; Driving turning table</td>
		</tr>
		<tr>
			<td>Touch sensor</td>
			<td>Taobao.com</td>
			<td>CM-12X-5V</td>
			<td></td>
		</tr>
		<tr>
			<td>Tricolor LED</td>
			<td>Taobao.com</td>
			<td>CK017, RGB</td>
			<td></td>
		</tr>
		<tr>
			<td>T-shaped connecting board</td>
			<td>CCM Automation technology Inc., China</td>
			<td>110-120</td>
			<td></td>
		</tr>
	</tbody>
</table>

design and use of an apparatus for presenting graspable objects in 3d workspace

Reaching and grasping are highly-coupled movements, and their underlying neural dynamics have been widely studied in the last decade. To distinguish reaching and grasping encodings, it is essential to present different object identities independent of their positions. Presented here is the design of an automatic apparatus that is assembled with a turning table and three-dimensional (3D) translational device to achieve this goal. The turning table switches different objects corresponding to different grip types while the 3D translational device transports the turning table in 3D space. Both are driven independently by motors so that the target position and object are combined arbitrarily. Meanwhile, wrist trajectory and grip types are recorded via the motion capture system and touch sensors, respectively. Furthermore, representative results that demonstrate successfully trained monkey using this system are described. It is expected that this apparatus will facilitate researchers to study kinematics, neural principles, and brain-machine interfaces related to upper limb function.

The size of complete workspace of the apparatus is 600 mm, 300 mm, and 500&#8201;mm in x-, y-, and z-axes, respectively. The maximum load of the 3D translational device is 25 kg, while the turning table (including the stepping motor) is weighted 15&#8201;kg and can be transported at a speed of up to 500&#8201;mm/s. The kinematic precision of the 3D translational device is less than 0.1&#8201;mm and the noise of the apparatus is less than 60 dB.
To demonstrate the utility of the system, the mon...

Watch this Scientific Journal Video about Design and Use of an Apparatus for Presenting Graspable Objects in 3D Workspace at JoVE.com

Design and Use of an Apparatus for Presenting Graspable Objects in 3D Workspace

Presented here is a protocol to build an automatic apparatus that guides a monkey to perform the flexible reach-to-grasp task. The apparatus combines a 3D translational device and turning table to present multiple objects in an arbitrary position in 3D space.

Reaching and grasping are highly-coupled movements, and their underlying neural dynamics have been widely studied in the last decade. To distinguish ...

The neural principle underlying reach and grasp has been studied extensively in past decades, however, few devices has been developed to enable a flexible combination of both movements in one task. By coupling a custom turning table with a 3-dimensional translational device, our apparatus enable a trial-wise combination of multiple positions in 3-dimensional space, and differently shaped objects in each position. Our apparatus provides a valuable platform to study upper limb function and their underlying neural principles.It may also facilitate simultaneous reconstruction of reaching and grasping movements in brain-machine interface. Begin by fixing two Y rails onto the top surface of the frame in parallel, by securing the pedestals to the top surface with screws. Then, connect two Y rails with a connecting shaft and two diaphragm couplings.Tighten the lockscrews of the couplings to synchronize the shafts of the two rails. Put six nuts into the back grooves of the Z rail and attach one side of the right triangle frame to the back of the Z rail with screws. Pull the triangle frame to the end that is distal to the shaft and tighten the screws.Attach the other right triangle frame to the other Z rail in the same way. Fix the other right angled sides of the two triangle frames to the sliders of the two Y rails with screws. Next, connect the two Z rails with a connecting shaft and diaphragm couplings, and tighten the lockscrews of the coupling.Attach the two T shaped connecting boards to the back of the X rail with nuts and screws. Then, pull the two T shaped boards to the two ends of the X rail and tighten the screws. Fix the two T shaped connecting boards onto the sliders of the two Z rails with screws.Insert the stepping motor into the shaft hole of the gear reducer, and screw their flanges together. Finally, screw the connecting ring to the shaft end of the X rail. Insert the shaft of the gear reducer into the coupling, and screw the gear reducer to the connecting ring.Tighten the lockscrew of the coupling. Begin by placing the touch sensors into the groove of the object body and stick them onto the predefined touch areas with double sided tape. Pass the wires through the hole of the object backboard and fix the coverboard onto the object body with screws.Then, pass the wires through the holes on the sides of the rotator, and screw the objects onto the rotator. Solder the wire ends of the touch sensors to the rotating wire ends of the electric slip ring, and wrap the joints with electrical tape. Screw the case to the slider of the X rail.Place the bearing in the bottom hole of the box. Next, put the rotator into the case from the right and pass the wires of the electric slip ring through the top hole of the case. Then, insert the metal shaft into the bearing from the top hole of the case, and fit the shaft key to the keyway of the rotator.Set the electric slip ring around the metal shaft. Place the end of the locating bar into the notch of the electric slip ring to prevent the outer ring from rotating. Insert the stepping motor shaft into the metal shaft hole, and fix the motor on the top of the box with screws.Stick a tricolor LED onto the front side of the case with tape. Finally, screw the right sideboard onto the case. Insert the control wires of stepping motors, LED, and touch sensors into the digital ports of a data acquisition board.To initialize the 3-dimensional translational device and turning table, pull the sliders of all linear slide rails to the starting point, and turn the first object of the turning table to face the front side of the turning table. Next, enter the coordinates of all positions in a matrix into a text document. Ensure that each row includes the X, Y, and Z coordinates of one position separated with a space, and then save the document.Then, open the paradigm software, click Open File in the Pool panel, and select the text document to load the presentation positions into the paradigm software. Check the objects to presented in the experiment in the Object Pool of the paradigm software. Then, adjust the experimental parameters in the Time Parameters panel of the paradigm software.Set baseline at 400 milliseconds, Motor Run equals 2000 milliseconds, Planning equals 1000 milliseconds, max Reaction Time equals 500 milliseconds, max Reach Time equals 1000 milliseconds, min Hold Time equals 500 milliseconds, Reward equals 60 milliseconds, and Error Cue equals 1000 milliseconds. Next, fix the monkey chair to the aluminum construction frame. Attach three reflective markers at the end of the arm with double sided tape.Make sure that the three markers form a scalene triangle. Then, in the paradigm software, click Run to start the task. Click the RECORD button on the motion capture panel of the Cortex software to record the trajectories of the three markers for 60 seconds when the monkey is doing the task.Click the STOP button to end the experiment. Build a tracking template of the three markers on the software using the recorded trajectories and save the template. Then, connect the ground wire of the front end amplifier to the ground of the microelectrode array, which is implanted in the motor cortex of the monkey.Insert the head stages into the connector of the microelectrode array. Open the Central software of the neural signal acquisition system. Open the synchronization software.Click the three connect buttons in the Cerebus, Motion Capture, and Paradigm panels to connect the synchronization software with the neural signal acquisition system, motion capture system, and the paradigm software respectively. Finally, click the Run button of the paradigm software to start the task again, followed by the Record button on the File Storage panel of the central software to start recording the neural signals. Check the saved tracking template and click the RECORD button on the motion capture panel of the Cortex software to start recording the trajectory of the monkey's wrist.The trajectory of the wrist during the reaching phase in all successful trials was extracted and divided into eight groups based on target positions. The ends of eight groups of trajectory forms a cuboid, which has the same size as the predefined cuboid workspace. Here, the peristimulus time histogram shows two example neurons tuning both reaching position and objects is shown.The neuron on the top shows significant selectivity during the reaching and holding phases. While the neuron on the bottom starts to tune positions and objects from the middle of the motor run phase. As the paradigm software could not read the positions of motors, it's essential to initialize the turning table and the translational device before each session.To fully control when the subject could see the target object and its position, a switchable glass could be installed in front of the apparatus. By using our apparatus, it is now feasible to study the neural interaction between reaching and grasp movements, which may help to simultaneously decode the reach trajectory and the grip types.

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