Name: a flexible platform for monitoring cerebellum-dependent sensory associative learning
Uploaded: 2022-01-19T13:00:00
Description: Watch this Scientific Journal Video about A Flexible Platform for Monitoring Cerebellum-Dependent Sensory Associative Learning at JoVE.com

This work is supported by grants from the National Institutes of Mental Health NRSA F32 MH120887-03 (to G.J.B.) and R01 NS045193 and R01 MH115750 (to S.S-H.W.). We thank Drs. Bas Koekkoek and Henk-Jan Boele for helpful discussions for optimizing the DEC setup and Drs. Yue Wang and Xiaoying Chen for helpful discussions for optimizing the DTSC setup.

The animal protocols described here have been approved by the Animal Care and Use Committees of Princeton University.
1. Setting up the SBC
<ol>
	<li>Connect the camera serial interface (CSI) cable to the Raspberry NoIR V2 camera and the camera port on the SBC.</li>
	<li>Download the operating system for the SBC onto the host computer. Write the operating system image to a micro secure digital (microSD) card. 
	NOTE: Detailed instructions for these procedures for a Rasp...

<ol>
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The platform with associated protocols outlined here can be used to reliably track animal behavior in two sensory associative learning tasks. Each task depends on intact communication through the climbing fiber pathway. In the design described here, we incorporate elements to facilitate learning and recording/perturbation of cerebellar response. These include a wheel to allow for free locomotion11,18 as well as head fixation. The wheel allows mouse subjects to lo...

Pavlovian conditioning of sub-second association between stimuli to elicit a conditioned response has long been used to probe cerebellar-dependent learning. For example, in classical delay eyeblink conditioning (DEC), animals learn to make a well-timed protective blink in response to a neutral conditional stimulus (CS; e.g., a flash of light or auditory tone) when it is paired repeatedly with an unconditional stimulus (US; e.g., a puff of air applied to the cornea) which always elicits a reflex blink, and which comes at or near the end of the CS. The learned response is referred to as a conditioned response (CR), while the reflex response is referred to as the unconditioned response (UR). In rabbits, cerebellum-specific lesions disrupt this form of learning1,2,3,4. Further, Purkinje cell complex spikes, driven by their climbing fiber inputs5, provide a necessary6,7 and sufficient8,9 signal for the acquisition of properly-timed CRs.
More recently, climbing fiber-dependent associative learning paradigms have been developed for head-fixed mice. DEC was the first associative learning paradigm to be adapted to this configuration10,11. DEC in head-fixed mice has been used to identify cerebellar regions11,12,13,14,15,16,17 and circuit elements11,12,13,14,15,18,19 that are required for task acquisition and extinction. This approach has also been used to demonstrate how the cellular-level physiological representation of task parameters evolves with learning13,15,16.
In addition to eyeblink, the delayed startle tactile conditioning (DTSC) paradigm was recently developed as a novel associative learning task for head-fixed mice20. Conceptually similar to DEC, DTSC involves the presentation of a neutral CS with a US, a tap to the face sufficient in intensity to engage a startle reflex21,22 as the UR. In the DTSC paradigm, both the UR and CR are read out as backward locomotion on a wheel. DTSC has now been used to uncover how associative learning alters cerebellar activity and patterns of gene expression20.
In this work, a method was developed for flexibly applying DEC or DTSC in a single platform. The stimulus and platform attributes are schematized in Figure 1. The design incorporates the capacity to track animal behavior with a camera as well as a rotary encoder to track mouse locomotion on a wheel. All aspects of data logging and trial structure are controlled by paired microcontrollers (Arduino) and a single-board computer (SBC; Raspberry Pi). These devices can be accessed through a provided graphical user interface. Here, we present a workflow for setup, experiment preparation and execution, and a customized analysis pipeline for data visualization.

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			<td>&#34;B&#34; Quick Base For C&#38;B METABOND - 10 mL bottle</td>
			<td>Parkell</td>
			<td>S398</td>
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			<td>Parkell</td>
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			<td>&#8206;ED_YT05_U_100Pcs</td>
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			<td>SanDisk</td>
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			<td>B00ZC6B8VM</td>
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			<td>Servocity</td>
			<td>585444</td>
			<td>4.5&#34; aluminum channel</td>
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			<td>Towallmark</td>
			<td>SODIAL</td>
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			<td>4PCS Breadboards Kit Include 2PCS 830 Point 2PCS 400 Point Solderless Breadboards for Proto Shield Distribution Connecting Blocks</td>
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			<td>&#8206;TL-SG105</td>
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			<td>5 V 2.5 A Raspberry Pi 3 B+ Power Supply/Adapter</td>
			<td>Canakit</td>
			<td>&#8206;DCAR-RSP-2A5</td>
			<td>Power supply for Raspberry Pi 3B+</td>
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			<td>5-0 ETHILON BLACK 1 x 18&#34; C-3</td>
			<td>Ethicon</td>
			<td>668G</td>
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			<td>6 mm Shaft Encoder 2000 PPR Pushpull Line Driver Universal Output Line Driver Output 5-26 V dc Supply</td>
			<td>Calt</td>
			<td>&#160;B01EWER68I</td>
			<td>Rotary encoder</td>
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			<td>&#216;1/2&#34; Optical Post, SS, 8-32 Setscrew, 1/4&#34;-20 Tap, L = 1&#34;, 5 Pack</td>
			<td>Thorlabs</td>
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			<td>&#216;1/2&#34; Optical Post, SS, 8-32 Setscrew, 1/4&#34;-20 Tap, L = 2&#34;, 5 Pack</td>
			<td>Thorlabs</td>
			<td>TR2-P5</td>
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			<td>&#216;1/2&#34; Optical Post, SS, 8-32 Setscrew, 1/4&#34;-20 Tap, L = 4&#34;, 5 Pack</td>
			<td>Thorlabs</td>
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			<td>&#216;1/2&#34; Optical Post, SS, 8-32 Setscrew, 1/4&#34;-20 Tap, L = 6&#34;, 5 Pack</td>
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			<td>Arduino</td>
			<td>A000066</td>
			<td>Arduino Uno (microcontroller board)</td>
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		<tr>
			<td>Arduino Due</td>
			<td>Arduino</td>
			<td>&#8206;A000062</td>
			<td>Arduino Due (microcontroller board)</td>
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			<td>Bench Power Supply, Single, Adjustable, 3 Output, 0 V, 24 V, 0 A, 2 A</td>
			<td>Tenma</td>
			<td>72-8335A</td>
			<td>Power supply</td>
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			<td>McMaster Carr</td>
			<td>8560K257</td>
			<td>Acrylic sheet</td>
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			<td>Stepper Online</td>
			<td>B06Y5VPSFN</td>
			<td>Stepper motor driver</td>
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			<td>McMaster Carr</td>
			<td>6763K13</td>
			<td>Air source regulator</td>
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			<td>Puritan</td>
			<td>806-WC</td>
			<td>Cotton swab</td>
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		<tr>
			<td>Dell 1908FP 19&#34; Flat Panel Monitor - 1908FPC</td>
			<td>Dell</td>
			<td>1908FPC</td>
			<td>Computer monitor</td>
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			<td>Adafruit</td>
			<td>2144</td>
			<td>camera serial interface cable</td>
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			<td>Stepper Online</td>
			<td>17HS24-2104S</td>
			<td>Stepper motor</td>
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			<td>Isoflurane</td>
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			<td>VetOne</td>
			<td>510212</td>
			<td>Lidocaine</td>
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			<td>Low-Strength Steel Hex Nut, Grade 2, Zinc-Plated, 1/4&#34;-20 Thread Size</td>
			<td>McMaster Carr</td>
			<td>90473A029</td>
			<td>Nuts</td>
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			<td>Uxcell</td>
			<td>A16040100ux1380</td>
			<td>M3 bolt</td>
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			<td>ACTOBOTICS</td>
			<td>555152</td>
			<td>Stepper motor mount</td>
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			<td>Adafruit</td>
			<td>4298</td>
			<td>Power supply for Raspberry Pi 4B</td>
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			<td>Optixcare Dog &#38; Cat Eye Lube Lubricating Gel, 0.70-oz tube</td>
			<td>Optixcare</td>
			<td>142422</td>
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			<td>McMaster-Carr</td>
			<td>3759T57</td>
			<td>Bearing</td>
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			<td>Premium Female/Female Jumper Wires - 40 x 6&#34;</td>
			<td>Adafruit</td>
			<td>266</td>
			<td>Wires</td>
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			<td>Premium Female/Male &#39;Extension&#39; Jumper Wires - 40 x 6&#34; (150 mm)</td>
			<td>Adafruit</td>
			<td>826</td>
			<td>Wires</td>
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			<td>Premium Male/Male Jumper Wires - 40 x 6&#34;</td>
			<td>Adafruit</td>
			<td>758</td>
			<td>Wires</td>
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			<td>Parkell</td>
			<td>S396</td>
			<td>Dental cement powder</td>
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			<td>Raspberry Pi (3B+ or 4B)</td>
			<td>Adafruit</td>
			<td>3775 or 4295</td>
			<td>Raspberry Pi</td>
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			<td>Raspberry Pi NoIR Camera Module V2 - 8MP 1080P30</td>
			<td>Raspberry Pi Foundation</td>
			<td>RPI3-NOIR-V2</td>
			<td>Raspberry NoIR V2 camera</td>
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			<td>Right-Angle Bracket, 1/4&#34; (M6) Counterbored Slot, 8-32 Taps</td>
			<td>Thorlabs</td>
			<td>AB90E</td>
			<td>Right-angle bracket</td>
		</tr>
		<tr>
			<td>Right-Angle Clamp for &#216;1/2&#34; Posts, 3/16&#34; Hex</td>
			<td>Thorlabs</td>
			<td>RA90</td>
			<td>Right-angle optical post clamp</td>
		</tr>
		<tr>
			<td>Right-Angle End Clamp for &#216;1/2&#34; Posts, 1/4&#34;-20 Stud and 3/16&#34; Hex</td>
			<td>Thorlabs</td>
			<td>RA180</td>
			<td>Right-angle end clamp</td>
		</tr>
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			<td>RJ45 Cat-6 Ethernet Patch Internet Cable</td>
			<td>Amazon</td>
			<td>&#8206;CAT6-7FT-5P-BLUE</td>
			<td>Ethernet cable</td>
		</tr>
		<tr>
			<td>Rotating Clamp for &#216;1/2&#34; Posts, 360&#176; Continuously Adjustable, 3/16&#34; Hex</td>
			<td>Thorlabs</td>
			<td>SWC</td>
			<td>Rotating optical post clamps</td>
		</tr>
		<tr>
			<td>Spike &#38; Hold Driver-0.1 TO 5 MS</td>
			<td>The Lee Co.</td>
			<td>IECX0501350A</td>
			<td>Solenoid valve driver</td>
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			<td>Swivel Base Adapter</td>
			<td>Thorlabs</td>
			<td>UPHA</td>
			<td>Post holder adapter</td>
		</tr>
		<tr>
			<td>USB 2.0 A-Male to Micro B Cable, 6 feet</td>
			<td>Amazon</td>
			<td>&#8206;7T9MV4</td>
			<td>USB2 type A to USB2 micro cable</td>
		</tr>
		<tr>
			<td>USB 2.0 Printer Cable - A-Male to B-Male, 6 Feet (1.8 m)</td>
			<td>Amazon</td>
			<td>B072L34SZS</td>
			<td>USB2 type B to USB2 type A cable</td>
		</tr>
		<tr>
			<td>VHS-M/SP-12 V</td>
			<td>The Lee Co.</td>
			<td>INKX0514900A</td>
			<td>Solenoid valve</td>
		</tr>
		<tr>
			<td>Zinc-Plated Steel 1/4&#34; washer, OD 1.000&#34;</td>
			<td>McMaster Carr</td>
			<td>91090A108</td>
			<td>Washers</td>
		</tr>
	</tbody>
</table>

a flexible platform for monitoring cerebellum-dependent sensory associative learning

Climbing fiber inputs to Purkinje cells provide instructive signals critical for cerebellum-dependent associative learning. Studying these signals in head-fixed mice facilitates the use of imaging, electrophysiological, and optogenetic methods. Here, a low-cost behavioral platform (~$1000) was developed that allows tracking of associative learning in head-fixed mice that locomote freely on a running wheel. The platform incorporates two common associative learning paradigms: eyeblink conditioning and delayed tactile startle conditioning. Behavior is tracked using a camera and the wheel movement by a detector. We describe the components and setup and provide a detailed protocol for training and data analysis. This platform allows the incorporation of optogenetic stimulation and fluorescence imaging. The design allows a single host computer to control multiple platforms for training multiple animals simultaneously.

Workflow for DEC experiments and analysis 
Proper experimental parameter selection is important for successful delay eyeblink conditioning (DEC) training. For the data presented here, the GUI was used to choose a CS duration of 350 ms and a US duration of 50 ms. This pairing results in an inter-stimulus interval of 300 ms: long enough to prevent low-amplitude CR production10 and short enough to avoid getting into the regime of poor learning or trace conditioning, a process th...

Watch this Scientific Journal Video about A Flexible Platform for Monitoring Cerebellum-Dependent Sensory Associative Learning at JoVE.com

A Flexible Platform for Monitoring Cerebellum-Dependent Sensory Associative Learning

We have developed a single platform to track animal behavior during two climbing fiber-dependent associative learning tasks. The low-cost design allows integration with optogenetic or imaging experiments directed towards climbing fiber-associated cerebellar activity.

Climbing fiber inputs to Purkinje cells provide instructive signals critical for cerebellum-dependent associative learning. Studying these signals in ...

Research

JoVE Journal

Neuroscience

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C. elegans Positive Butanone Learning, Short-term, and Long-term Associative Memory Assays

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