Name: an open-source virtual reality system for the measurement of spatial learning in head-restrained mice
Uploaded: 2023-03-03T13:33:00
Description: Watch this Scientific Journal Video about An Open-Source Virtual Reality System for the Measurement of Spatial Learning in Head-Restrained Mice at JoVE.com

We would like to thank Noah Pettit from the Harvey lab for the discussion and suggestions while developing the protocol in this manuscript. This work was supported by a BBRF Young Investigator Award and NIMH 1R21MH122965 (G.F.T.), in addition to NINDS R56NS128177 (R.H., C.L.) and NIMH R01MH068542 (R.H.).

All procedures in this protocol were approved by the Institutional Animal Care and Use Committee of the New York State Psychiatric Institute.
NOTE: A single-board computer is used to display a VR visual environment coordinated with the running of a head-restrained mouse on a wheel. Movement information is received as serial input from an ESP32 microcontroller reading a rotary encoder coupled to the wheel axle. The VR environment is rendered using OpenGL hardware acceleration on the Raspberry P...

<ol>
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This open-source VR system for mice will only function if the serial connections are made properly between the rotary and behavior ESP32 microcontrollers and the single-board computer (step 2), which can be confirmed using the IDE serial monitor (step 2.4.5). For successful behavioral results from this protocol (step 4), the mice must be habituated to the apparatus and be comfortable running on the wheel for liquid rewards (steps 4.3-4.5). This requires sufficient (but not excessive) water restriction, as mice given ...

Spatial navigation is an ethologically important behavior by which animals encode the features of new locations into a cognitive map, which is used for finding areas of possible reward and avoiding areas of potential danger. Inextricably linked with memory, the cognitive processes underlying spatial navigation share a neural substrate in the hippocampus1 and cortex, where neural circuits in these areas integrate incoming information and form cognitive maps of environments and events for later recall2. While the discovery of place cells in the hippocampus3,4 and grid cells in the entorhinal cortex5 has shed light on how the cognitive map within the hippocampus is formed, many questions remain about how specific neural subtypes, microcircuits, and individual subregions of the hippocampus (the dentate gyrus, and cornu ammonis areas, CA3-1) interact and participate in spatial memory formation and recall.
In vivo two-photon imaging has been a useful tool in uncovering cellular and population dynamics in sensory neurophysiology6,7; however, the typical necessity for head restraint limits the utility of this method for examining mammalian spatial behavior. The advent of virtual reality (VR)8 has addressed this shortcoming by presenting immersive and realistic visuospatial environments while head-restrained mice run on a ball or treadmill to study spatial and contextual encoding in the hippocampus8,9,10 and cortex11. Furthermore, the use of VR environments with behaving mice has allowed neuroscience researchers to dissect the components of spatial behavior by precisely controlling the elements of the VR environment12 (e.g., visual flow, contextual modulation) in ways not possible in real-world experiments of spatial learning, such as the Morris water maze, Barnes maze, or hole board tasks.
Visual VR environments are typically rendered on the graphical processing unit (GPU) of a computer, which handles the load of rapidly computing the thousands of polygons necessary to model a moving 3D environment on a screen in real time. The large processing requirements generally require the use of a separate PC with a GPU that renders the visual environment to a monitor, multiple screens13, or a projector14 as the movement is recorded from a treadmill, wheel, or foam ball under the animal. The resulting apparatus for controlling, rendering, and projecting the VR environment is, therefore, relatively expensive, bulky, and cumbersome. Furthermore, many such environments in the literature have been implemented using proprietary software that is both costly and can only be run on a dedicated PC.
For these reasons, we have designed an open-source VR system to study spatial learning behaviors in head-restrained mice using a Raspberry Pi single-board computer. This Linux computer is both small and inexpensive yet contains a GPU chip for 3D rendering, allowing the integration of VR environments with the display or behavioral apparatus in varied individual setups. Furthermore, we have developed a graphical software package written in Python, &#34;HallPassVR&#34;, which utilizes the single-board computer to render a simple visuospatial environment, a virtual linear track or hallway, by recombining custom visual features selected using a graphical user interface (GUI). This is combined with microcontroller subsystems (e.g., ESP32 or Arduino) to measure locomotion and coordinate behavior, such as by the delivery of other modalities of sensory stimuli or rewards to facilitate reinforcement learning. This system provides an inexpensive, flexible, and easy-to-use alternative method for delivering visuospatial VR environments to head-restrained mice during two-photon imaging (or other techniques requiring head fixation) for studying the neural circuits underlying spatial learning behavior.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>1/4 &#34; diam aluminum rod</td>
			<td>McMaster-Carr</td>
			<td>9062K26</td>
			<td>3&#34; in length for wheel axle</td>
		</tr>
		<tr>
			<td>1/4&#34;-20 cap screws, 3/4&#34; long (x2)</td>
			<td>Amazon.com</td>
			<td>B09ZNMR41V</td>
			<td>for affixing head post holders to optical posts</td>
		</tr>
		<tr>
			<td>2&#34;x7&#34; T-slotted aluminum bar (x2)</td>
			<td>8020.net</td>
			<td>1020</td>
			<td>wheel/animal mounting frame</td>
		</tr>
		<tr>
			<td>6&#34; diam, 3&#34; wide acrylic cylinder (1/8&#34; thick)</td>
			<td>Canal Plastics</td>
			<td>33210090702</td>
			<td>Running wheel (custom width cut at canalplastics.com)</td>
		</tr>
		<tr>
			<td>8-32 x 1/2&#34; socket head screws</td>
			<td>McMaster-Carr</td>
			<td>92196A194</td>
			<td>fastening head post holder to optical post&#160;</td>
		</tr>
		<tr>
			<td>Adjustable arm (14&#34;)</td>
			<td>Amazon.com</td>
			<td>B087BZGKSL</td>
			<td>to hold/adjust lick spout</td>
		</tr>
		<tr>
			<td>Analysis code (MATLAB)</td>
			<td></td>
			<td>custom written</td>
			<td>file at github.com/GergelyTuri/HallPassVR/software/Analysis code</td>
		</tr>
		<tr>
			<td>Axle mounting flange, 1/4&#34; ID</td>
			<td>Pololu</td>
			<td>1993</td>
			<td>for mounting wheel to axle</td>
		</tr>
		<tr>
			<td>Ball bearing (5/8&#34; OD, 1/4&#34; ID, x2)</td>
			<td>McMaster-Carr</td>
			<td>57155K324</td>
			<td>for mounting wheel axle to frame</td>
		</tr>
		<tr>
			<td>Behavior ESP32 code</td>
			<td></td>
			<td>custom written</td>
			<td>file at github.com/GergelyTuri/HallPassVR/software/Arduino code/Behavior board</td>
		</tr>
		<tr>
			<td>Black opaque matte acrylic sheets (1/4&#34; thick)</td>
			<td>Canal Plastics</td>
			<td>32918353422</td>
			<td>laser cut file at github.com/GergelyTuri/HallPassVR/hardware/VR screen assembly</td>
		</tr>
		<tr>
			<td>Clear acrylic sheet (1/4&#34; thick)</td>
			<td>Canal Plastics</td>
			<td>32920770574</td>
			<td>laser cut file at github.com/GergelyTuri/HallPassVR/hardware/VR wheel assembly</td>
		</tr>
		<tr>
			<td>ESP32 devKitC v4 (x2)</td>
			<td>Amazon.com</td>
			<td>B086YS4Z3F</td>
			<td>microcontroller for behavior and rotary encoder</td>
		</tr>
		<tr>
			<td>ESP32 shield</td>
			<td>OpenMaze.org</td>
			<td>OMwSmall</td>
			<td>description at www.openmaze.org (https://claylacefield.wixsite.com/openmazehome/copy-of-om2shield). ZIP gerber files at: https://github.com/claylacefield/OpenMaze/tree/master/OM_PCBs</td>
		</tr>
		<tr>
			<td>Fasteners and brackets&#160;</td>
			<td>8020.net</td>
			<td>4138, 3382,3280</td>
			<td>for wheel frame mounts</td>
		</tr>
		<tr>
			<td>goniometers</td>
			<td>Edmund Optics</td>
			<td>66-526, 66-527</td>
			<td>optional for behavior. Fine tuning head for imaging</td>
		</tr>
		<tr>
			<td>HallPassVR python code</td>
			<td></td>
			<td>custom written</td>
			<td>file at github.com/GergelyTuri/HallPassVR/software/HallPassVR</td>
		</tr>
		<tr>
			<td>Head post holder</td>
			<td></td>
			<td>custom design</td>
			<td>3D design file at github.com/GergelyTuri/HallPassVR/hardware/VR head mount/Headpost Clamp</td>
		</tr>
		<tr>
			<td>LED projector</td>
			<td>Texas Instruments</td>
			<td>DLPDLCR230NPEVM</td>
			<td>or other small LED projector</td>
		</tr>
		<tr>
			<td>Lick spout</td>
			<td>VWR</td>
			<td>20068-638</td>
			<td>(or ~16 G metal hypodermic tubing)</td>
		</tr>
		<tr>
			<td>M 2.5 x 6 set screws</td>
			<td>McMaster-Carr</td>
			<td>92015A097</td>
			<td>securing head post&#160;</td>
		</tr>
		<tr>
			<td>Matte white diffusion paper</td>
			<td>Amazon.com</td>
			<td></td>
			<td>screen material</td>
		</tr>
		<tr>
			<td>Metal headposts</td>
			<td></td>
			<td>custom design</td>
			<td>3D design file at github.com/GergelyTuri/HallPassVR/hardware/VR head mount/head post designs</td>
		</tr>
		<tr>
			<td>Miscellenous tubing and tubing adapters (1/16&#34; ID)</td>
			<td></td>
			<td></td>
			<td>for constructing the water line</td>
		</tr>
		<tr>
			<td>Optical breadboard</td>
			<td>Thorlabs</td>
			<td>as per user&#39;s requirements</td>
			<td></td>
		</tr>
		<tr>
			<td>Optical posts, 1/2&#34; diam (2x)</td>
			<td>Thorlabs</td>
			<td>TR4</td>
			<td>for head fixation setup</td>
		</tr>
		<tr>
			<td>Processing code</td>
			<td></td>
			<td>custom written</td>
			<td>file at github.com/GergelyTuri/HallPassVR/software/Processing code</td>
		</tr>
		<tr>
			<td>Raspberry Pi 4B</td>
			<td>raspberry.com, adafruit.com</td>
			<td></td>
			<td>Single-board computer for rendering of HallPassVR envir.</td>
		</tr>
		<tr>
			<td>Right angle clamp</td>
			<td>Thorlabs</td>
			<td>RA90</td>
			<td>for head fixation setup</td>
		</tr>
		<tr>
			<td>Rotary encoder (quadrature, 256 step)</td>
			<td>DigiKey</td>
			<td>ENS1J-B28-L00256L</td>
			<td>to measure wheel rotation</td>
		</tr>
		<tr>
			<td>Rotary encoder ESP32 code</td>
			<td></td>
			<td>custom written</td>
			<td>file at github.com/GergelyTuri/HallPassVR/software/Arduino code/Rotary encoder</td>
		</tr>
		<tr>
			<td>SCIGRIP 10315 acrylic cement</td>
			<td>Amazon.com</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Shaft coupler</td>
			<td>McMaster-Carr</td>
			<td>9861T426</td>
			<td>to couple rotary encoder shaft with axle</td>
		</tr>
		<tr>
			<td>Silver mirror acrylic sheets</td>
			<td>Canal Plastics</td>
			<td>32913817934</td>
			<td>laser cut file at github.com/GergelyTuri/HallPassVR/hardware/VR screen assembly</td>
		</tr>
		<tr>
			<td>Solenoid valve</td>
			<td>Parker</td>
			<td>003-0137-900</td>
			<td>to administer water rewards</td>
		</tr>
	</tbody>
</table>

an open-source virtual reality system for the measurement of spatial learning in head-restrained mice

Head-restrained behavioral experiments in mice allow neuroscientists to observe neural circuit activity with high-resolution electrophysiological and optical imaging tools while delivering precise sensory stimuli to a behaving animal. Recently, human and rodent studies using virtual reality (VR) environments have shown VR to be an important tool for uncovering the neural mechanisms underlying spatial learning in the hippocampus and cortex, due to the extremely precise control over parameters such as spatial and contextual cues. Setting up virtual environments for rodent spatial behaviors can, however, be costly and require an extensive background in engineering and computer programming. Here, we present a simple yet powerful system based upon inexpensive, modular, open-source hardware and software that enables researchers to study spatial learning in head-restrained mice using a VR environment. This system uses coupled microcontrollers to measure locomotion and deliver behavioral stimuli while head-restrained mice run on a wheel in concert with a virtual linear track environment rendered by a graphical software package running on a single-board computer. The emphasis on distributed processing allows researchers to design flexible, modular systems to elicit and measure complex spatial behaviors in mice in order to determine the connection between neural circuit activity and spatial learning in the mammalian brain.

This open-source virtual reality behavioral setup allowed us to quantify licking behavior as a read-out of spatial learning as head-restrained mice navigated a virtual linear track environment. Seven C57BL/6 mice of both sexes at 4 months of age were placed on a restricted water schedule and first trained to lick continuously at low levels while running on the wheel for random spatial rewards (&#34;random foraging&#34;) without VR. Although their performance was initially affected when moved to the VR projection screen s...

Watch this Scientific Journal Video about An Open-Source Virtual Reality System for the Measurement of Spatial Learning in Head-Restrained Mice at JoVE.com

An Open-Source Virtual Reality System for the Measurement of Spatial Learning in Head-Restrained Mice

Here, we present a simplified open-source hardware and software setup for investigating mouse spatial learning using virtual reality (VR). This system displays a virtual linear track to a head-restrained mouse running on a wheel by utilizing a network of microcontrollers and a single-board computer running an easy-to-use Python graphical software package.

Head-restrained behavioral experiments in mice allow neuroscientists to observe neural circuit activity with high-resolution electrophysiological and ...

Research

JoVE Journal

Neuroscience

Low-stress Route Learning Using the Lashley III Maze in Mice

Many behavior tests designed to assess learning and memory in rodents, particularly mice, rely on visual cues, food and/or water deprivation, or other ...

Human Fear Conditioning Conducted in Full Immersion 3-Dimensional Virtual Reality

Fear conditioning is a widely used paradigm in non-human animal research to investigate the neural mechanisms underlying fear and anxiety. A major ...

Optical Recording of Suprathreshold Neural Activity with Single-cell and Single-spike Resolution

Signaling of information in the vertebrate central nervous system is often carried by populations of neurons rather than individual neurons. Also ...

Building An Open-source Robotic Stereotaxic Instrument

This protocol includes the designs and software necessary to upgrade an existing stereotaxic instrument to a robotic (CNC) stereotaxic instrument for ...

In vivo Optogenetic Stimulation of the Rodent Central Nervous System

In vivo Optogenetic Stimulation of the Rodent Central Nervous System

The ability to probe defined neural circuits in awake, freely-moving animals with cell-type specificity, spatial precision, and high temporal resolution ...

Immunohistochemical Visualization of Hippocampal Neuron Activity After Spatial Learning in a Mouse Model of Neurodevelopmental Disorders

Induction of phosphorylated extracellular-regulated kinase (pERK) is a reliable molecular readout of learning-dependent neuronal activation. Here, we ...

Electrophysiological Method for Recording Intracellular Voltage Responses of Drosophila Photoreceptors and Interneurons to Light Stimuli In Vivo

Electrophysiological Method for Recording Intracellular Voltage Responses of Drosophila Photoreceptors and Interneurons to Light Stimuli In Vivo

Voltage responses of insect photoreceptors and visual interneurons can be accurately recorded with conventional sharp microelectrodes. The method ...

Assessing Spatial Learning and Memory in Small Squamate Reptiles

Clinical research has leveraged a variety of paradigms to assess cognitive decline, commonly targeting spatial learning and memory abilities. However, ...

An Objective and Reproducible Test of Olfactory Learning and Discrimination in Mice

Olfaction is the predominant sensory modality in mice and influences many important behaviors, including foraging, predator detection, mating, and ...

A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells

Serial sectioning and subsequent high-resolution imaging of biological tissue using electron microscopy (EM) allow for the segmentation and reconstruction ...