This work was supported by NIGMS award GM127872 ACK, NINDS award 105072 to ERD and ACK, and NSF award 1656574 to ACK.

NOTE: Set up systems for behavioral tracking in larvae and adults.
1. Constructing a Sleep System for Larvae
NOTE: The monitoring system for tracking larval through juvenile fish aged 4 days post fertilization (dpf) through 30 dpf A. mexicanus requires multiple pieces of equipment including infrared (IR) lighting, acrylic IR light diffusers, automated light controls (timers), computers, cameras, and secondary materials such as wiring and power controllers (Figure 1A). The following instructions will inform how to build a system to accurately track locomotor behavior to study sleep and circadian rhythms in larval A. mexicanus. 
<ol>
	<li>Construct a lighting system consisting of IR and white light emitting diodes (LED): Place three IR lights in a triangle approximately 7.62 cm from each other on a 30.5 cm x 30.5 cm thin metal platform heatsink. Wire lights in series with electrical wire and connect to a power source.</li>
	<li>Place a single white light LED in the center of the three IR lights and attach them to the power source.</li>
	<li>Connect the power source for the LED to a light timer set to a standard circadian time.</li>
	<li>Construct a platform for larval tracking system. Use 0.33 cm thick white sign acrylic for all of the components of the platform.</li>
	<li>Place the recording platform on top of the lighted square heatsink on which arenas containing fish will reside during behavioral tracking.</li>
	<li>Place a second acrylic inside the box between the lights and the animals to diffuse the IR for optimal lighting and contrast. 
	NOTE: The dimensions for the larval light box is as follows: Two 18 cm x 8.5 cm and two 17 cm x 8.5 cm LEDs that are chemically bonded together to form an 18 cm x 18 cm square that is 8.5 cm tall. Additionally, acrylic may be easily cut or drilled using the proper tools for customized sizing.
	<ol>
		<li>Place the entire larval tracking stage and lighting setup within an enclosed plastic tube, and then position the camera on top of the tube. 
		NOTE: It is important to keep lighting reflections from appearing on the tracking video, as this will impair tracking accuracy. The placement of cameras on top of a tube that surrounds platform improves lighting and sharpness for the cameras that are used for these experiments.</li>
	</ol>
	</li>
	<li>Manipulate a webcam (see Table of Materials) for IR-based recording. Remove the manufacturer lens using a rotary tool (see Table of Materials).</li>
	<li>Remove the small silver screws on the back sides of the camera to remove the inner housing.</li>
	<li>Remove the small black screws inside the body of the camera to loosen the remainder of the lens. Use a small screwdriver to remove any portions of the lens housing that is left after cutting the lens.</li>
	<li>Remove the blue LED on the top part of the charged coupled device (CCD) housing.</li>
	<li>Put the camera back together by placing the inner housing back to its original orientation and screwing the two silver screws back to their original position.</li>
	<li>Route the inside of the camera using a small saw to fit with a rounded plastic routing bit. Smooth down the extra plastic until it can fit a lens adapter.</li>
	<li>Install an IR-pass filter inside the camera as close to the CCD as possible without making direct contact with the camera. 
	NOTE: Take care not to damage the CCD chip within the housing of the camera. Be sure to keep the cut as level as possible. Seal any open space between the outside of the IR filter and the body of the camera to keep light from reaching the CCD without being filtered.</li>
	<li>Attach the camera to a 35 mm fixed lens (see Table of Materials) by screwing the adaptor in the front of the camera into the back of the lens.</li>
	<li>Place the camera and lens in the hole drilled into the lid on top of the tube that houses the stage and lights and attach the USB to the computer the animals will be recorded from. 
	NOTE: Place fish in a behavior room that is separate from where stock fish are housed to ensure minimal disruptions during behavioral recordings. Take care to minimize fluctuations in temperature and ventilation which can confound behavioral experiments.</li>
</ol>
2. Sleep System for Adults
<ol>
	<li>Construct an IR lighting system for tracking adult fish by cutting IR strips to approximately 46 cm intervals. One 46 cm strip is sufficient for each 10 L behavior tank.</li>
	<li>Wire each strip together in a series, soldering each strip to DC electrical wire and attach to a 9 V power source.</li>
	<li>Attach each IR strip to a 51 cm x 5.1 cm piece of aluminum that will act as a heat sink.</li>
	<li>Place a 46 cm x 5 cm, 0.32 cm thick 9% light-pass white sign acrylic sheet directly in front of each IR light strip to diffuse the IR light.</li>
	<li>Place all tanks on a rack that supports rear-mounted IR lighting.</li>
	<li>Use opaque plastic dividers in 10 L glass tanks to create individual arenas. 
	NOTE: The arena size can be varied based on the number of dividers used and the size of the tank. Arena size impacts locomotor activity and sleep in both cave and surface fish23.</li>
	<li>Mount cameras approximately 4-6 m away from tanks. Each camera can typically record from 3 tanks at a time to provide sufficient resolution for tracking. 
	NOTE: Adult behavioral recordings generally do not require a separate white lighting system to control day-night changes. Simply utilizing standard overhead lights in a behavioral room connected to a timer is likely to be sufficient.</li>
</ol>
3. Recording Locomotor Activity
NOTE: All behavioral recordings are made using a standard laptop computer or desktop with a backup battery source. Due to the large file size of a 24 h recording (60-100 GB), save all recordings on external hard drives.
<ol>
	<li>Acclimate fish ages 4-30 dpf for 18-24 h prior to initiating recordings. Feed larval fish with live brine shrimp when first placed in the recording chamber, and 1 h prior to beginning the recording. Acclimate adult fish 4-5 days before recording behavior and feed once daily with flake food or with live blackworms. 
	NOTE: Be sure to place larval fish in fresh water prior to recording, as leftover brine shrimp will cause tracking issues during later analysis. Co-culturing with rotifers provides an alternative option, as their small size does not interfere with tracking.</li>
	<li>Place fish aged 4-6 dpf in 24-well tissue culture plates. House fish aged 20-30 dpf in 12-well tissue culture plates for recording.</li>
	<li>Record adults in 10 L tanks fit with dividers to accommodate five individually housed fish, or without dividers to record sleep and activity in a social setting. 
	NOTE: Take care to focus the camera prior to initiating the recording in order to maximize tracking accuracy. Do not open the iris of the camera lens too far, as this will drastically reduce sharpness of the image. There is a balance, however; if the iris is closed too far, the frame rate of the video will fall below 15.00 fps. It is essential for later analysis that the frame rate remains 15.00 frames per s for use with some custom-written sleep script23,24.</li>
	<li>Set lighting/brightness background illuminations.</li>
	<li>Optimize lighting prior to the start of recording. Always keep the contrast at the highest level possible and use the Brightness and Background Illumination to adjust the brightness till the animals are most clear.</li>
	<li>Record fish for 24 or 48 h. 
	NOTE: Emergency backup battery packs that power all the lighting, computers, and cameras should be purchased in case of power outages. All battery packs should also be plugged into emergency power outlets, if possible. Battery packs will generally not power the equipment for more than a few minutes to an hour at most and serve to bridge between losing main power and transferring to the emergency power system.</li>
</ol>
4. Analysis of Locomotor Activity in Individually Housed Fish Using Automated tracking Software
<ol>
	<li>To begin analysis of behavior, open tracking software, select New Experiment from Template, then select Apply a Pre-Defined Template.</li>
	<li>As the program will now ask what species to track, select Fish. Use the dropdown box to select either Zebrafish Larvae of Zebrafish Adult depending the experimental paradigm.</li>
	<li>Set up the arenas in which each animal will be tracked. For larvae, select Well Plate, Round Well and No Zone Template. For adults, use Open Field, Square with No Zone Template. Then determine the proper number of arenas, one for each animal being tracked in the video.</li>
	<li>Select the model for optimal tracking, click on track Center-point, and be sure that the animal color is selected to be darker than the background. Apply the frame rate at which the video was acquired. The tracking software should automatically detect this.</li>
	<li>Draw a scale to calibrate the real-world distance of an object to accurately determine the locomotor behavior of the fish using Arena Settings.</li>
	<li>Edit the arenas to make sure that the entire area that the fish are in will be tracked; otherwise samples will be lost during acquisition. 
	NOTE: Use care when setting up areas. Larval fish especially are sensitive to tracking errors if the arenas are either too big or small. Bad lighting in the experiment can also create shadows on the walls of well plates, which the program may think is an animal, creating a false positive.</li>
	<li>Click on Advanced. Under Method in Detection Setting, select Dynamic Subtraction, then click on Background and select Start Learning. Adjust the dark contrast signal/noise ratio till the animals are being tracked well, and the background is not causing the tracking to jump. 
	NOTE: Video quality can vary between experiments, so each trial may need to use different settings, accordingly. Using the Subject Contour and Subject Size features can significantly improve tracking results.</li>
	<li>Select Trial list and load the proper parameters before starting to record the data into the program.</li>
	<li>Click into the Acquisition tab, select Track All Planned Trials and click on the record button.</li>
	<li>Under Analysis Profile, make sure Distance and Time &#38; Movement are selected. 
	NOTE: In order for later sleep analysis, it is critical that these settings are correct, as the .perl file must read these data in the correct order to calculate sleep.</li>
	<li>Under Export, select Raw Data, export the data as Unicode text.</li>
</ol>
5. Tracking Socially Housed Fish
<ol>
	<li>Follow steps 4.1-4.4 to set up the experiment in the tracking software.</li>
	<li>In the dropdown menu, select how many animals to track for the experiment.</li>
	<li>In Arena settings, draw the correct scale to calibrate the real-world distance.</li>
	<li>In Detection settings, use Dynamic Subtraction, and adjust the dark contrast to best track the animal.</li>
	<li>Adjust the subject size under the detection settings, so that only a very small portion of the animal is tracked. 
	NOTE: By tracking only a small part of the animal, this will reduce the amount of switching between animals when they cross paths during acquisition.</li>
	<li>Once the tracks are acquired, use the Track Editor to manually fix times where fish may cross paths.</li>
</ol>
6. Extraction of Sleep Data from Locomotor Activity
NOTE: The behavioral definition of sleep in both larval and adult A. mexicanus is 1 min or more of quiescence. This definition was determined using arousal threshold experiments, where a greater sensory stimulus is required to initiate a behavioral response in a sleeping state (&#62;60 s) compared to waking14,17. To account for small movements and drifting common to fish species, there are velocity thresholds applied to segregate real movement from noise or drift. These thresholds are computationally-derived by comparing correlations between distance and sleep duration to find the highest R-squared values; thereby determining the most accurate velocity for movement and sleep. For larval fish, the upper and lower limits are both 12 mm/s as there is little to no drift. For adult fish the lower limit is 2 cm/s with an upper limit of 4 cm/s to account for drift.
<ol>
	<li>Install Cygwin to the analysis computer to carry out the execution of the custom-written scripts to extract locomotor and sleep behavior.</li>
	<li>Create a new experiment folder within the Cygwin home directory.</li>
	<li>Import the raw Unicode data from tracking software and execute the .sh file in Cygwin to convert the encoding from UTF-16 to UTF-8.</li>
	<li>Execute the .perl file in Cygwin to extract the sleep data.</li>
	<li>Open the macro file and follow the instructions within the spreadsheet to finalize the data analysis as desired. 
	NOTE: A basic level of command-line coding will be necessary to carry out this portion of analysis. General Linux commands will suffice. If there are issues with the programs reading the data properly, check the data from tracking software in any freely available text editor to be sure the encoding and order is correct for the executables to write properly.</li>
</ol>

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The authors declare they have no competing interests.

This protocol describes a custom system for quantifying sleep and locomotor activity in larval and adult cavefish. Cavefish have emerged as a leading model for studying the evolution of sleep that can be used to investigate the genetic and neural basis of sleep regulation1. The critical steps in this protocol include optimization of lighting and video quality in order to assure accurate tracking that is necessary to quantify sleep. The system for acquisition and analysis described here are fully f...

Sleep is highly conserved throughout the animal kingdom at the physiological, functional, and behavioral levels1,2,3. While sleep in mammalian laboratory animals is typically assessed using electroencephalograms, electrophysiological recordings are less practical in small genetically amenable model systems and thus sleep is typically measured based on behavior3,4. Behavioral characteristics associated with sleep are highly conserved throughout the animal kingdom and include increased arousal threshold, reversibility with stimulation, and prolonged behavioral quiescence5. These measures can be used to characterize sleep in animals ranging from the nematode worm, C. elegans, through humans6.
The use of behavioral quiescence to characterize sleep requires automated tracking software. With tracking software, periods of activity and immobility are determined over a number of days, and long periods of inactivity are classified as sleep7,8. In recent years, multiple tracking systems have been developed for acquiring activity data among a diversity of small genetically-amenable model systems; including worms, fruit flies and fish9,10,11. These programs are accompanied by software that allows for automated tracking of animal behavior, including both open source freeware and commercially available software7,12,13,14. These systems differ in their flexibility and allow for efficient screening and characterization of sleep phenotypes in numerous genetically amendable models.
Genetic investigation of sleep in the zebrafish, Danio rerio, has led to the identification of numerous genes and neural circuits that regulate sleep15,16. While this has provided a powerful system for investigating the neural basis of sleep in a vertebrate laboratory animal, much less is known about how sleep evolves and how natural variation contributes to sleep regulation. The Mexican cavefish, Astyanax mexicanus (A. mexicanus), have evolved dramatic differences in sleep, locomotor activity and circadian rhythms17,18. These fish exist as eyed surface fish that inhabit the rivers of Mexico and Southern Texas and at least 29 cave populations around the Sierra Del Abra region of Northeast Mexico19,20,21. Remarkably, many behavioral differences, including sleep loss, appear to have emerged independently in multiple cavefish populations14,22. Therefore, cavefish provide a model for investigating the convergent evolution of sleep, circadian, and social behaviors.
This protocol describes a system for measuring sleep and locomotor behavior in A. mexicanus larvae and adults. A custom-built infrared-based recording system allows for video recording of animals under light and dark conditions. Commercially available software can be used to measure activity and custom macros are used to quantify several aspects of inactivity and determine periods of sleep. This protocol also describes experimental modifications for tracking the activity of multiple animals within a tank, providing the ability to examine interactions between sleep and social behaviors. These systems can be applied to measure sleep, circadian behavior, and locomotor activity in additional fish species including zebrafish and sticklebacks.

<table>
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			<td>Laptop/computer</td>
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			<td>LED light</td>
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			<td>Use with Chanzon 25pcs 1W 3W 5W LED Heat Sink (2 pin Black) Aluminum Base Plate Panel</td>
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			<td>Century 24 Hour Plug-in Mechanical Timer Grounded</td>
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			<td>MOONLIGHT DRIVER (350MA)</td>
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			<td>Seagate 3TB backup</td>
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			<td>Microsoft LifeCam</td>
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			<td>LDR Industries 1/2&#34; Steel pipe</td>
			<td>307 12X36</td>
			<td>Mounted on wall with Flange and 90 degree pipe elbow. Could also use a tripod to hold camera.</td>
		</tr>
	</tbody>
</table>

automated measurements of sleep and locomotor activity in mexican cavefish

Across phyla, sleep is characterized by highly conserved behavioral characteristics that include elevated arousal threshold, rebound following sleep deprivation, and consolidated periods of behavioral immobility. The Mexican cavefish, Astyanax mexicanus (A. mexicanus), is a model for studying trait evolution in response to environmental perturbation. A. mexicanus exist as in eyed surface-dwelling forms and multiple blind cave-dwelling populations that have robust morphological and behavioral differences. Sleep loss has occurred in multiple, independently-evolved cavefish populations. This protocol describes a methodology for quantifying sleep and locomotor activity in A. mexicanus cave and surface fish. A cost-effective video monitoring system allows for behavioral imaging of individually-housed larval or adult fish for periods of a week or longer. The system can be applied to fish aged 4 days post fertilization through adulthood. The approach can also be adapted for measuring the effects of social interactions on sleep by recording multiple fish in a single arena. Following behavioral recordings, data is analyzed using automated tracking software and sleep analysis is processed using customized scripts that quantify multiple sleep variables including duration, bout length, and bout number. This system can be applied to measure sleep, circadian behavior, and locomotor activity in almost any fish species including zebrafish and sticklebacks.

Larvae ages 4-30 dpf can be reliably recorded in the custom-build closed system described in Figure 1. The system includes both IR and visible lighting to allow for recordings under light and dark conditions, under various visible light conditions (Figure 1A). The videos are then analyzed using tracking software (Figure 1B,C) and post-processed using a custom sleep macro (See <strong...

Watch this Scientific Journal Video about Automated Measurements of Sleep and Locomotor Activity in Mexican Cavefish at JoVE.com

Automated Measurements of Sleep and Locomotor Activity in Mexican Cavefish

This protocol details the methodology for quantifying locomotor behavior and sleep in the Mexican cavefish. Previous analyses are extended to measure these behaviors in socially-housed fish. This system can be widely applied to study sleep and activity in other fish species.

Across phyla, sleep is characterized by highly conserved behavioral characteristics that include elevated arousal threshold, rebound following sleep ...

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Research

JoVE Journal

Behavior

6.7K Views.  Florida Atlantic University. This protocol details the methodology for quantifying locomotor behavior and sleep in the Mexican cavefish. Previous analyses are extended to measure these behaviors in socially-housed fish. This system can be widely applied to study sleep and activity in other fish species.

Video: Automated Measurements of Sleep and Locomotor Activity in Mexican Cavefish

Mouse Short- and Long-term Locomotor Activity Analyzed by Video Tracking Software

Locomotor activity (LMA) is a simple and easily performed measurement of behavior in mice and other rodents. Improvements in video tracking software (VTS) have allowed it to be coupled to LMA testing, dramatically improving specificity and sensitivity when compared to the line crossings method with manual scoring. In addition, VTS enables high-throughput experimentation. While similar to automated video tracking used for the open field test (OFT), LMA testing is unique in that it allows mice to remain in their home cage and does not utilize the anxiogenic stimulus of bright lighting during the active phase of the light-dark cycle. Traditionally, LMA has been used for short periods of time (mins), while longer movement studies (hrs-days) have often used implanted transmitters and biotelemetry. With the option of real-time tracking, long-, like short-term LMA testing, can now be conducted using videography. Long-term LMA testing requires a specialized, but easily constructed, cage so that food and water (which is usually positioned on the cage top) does not obstruct videography. Importantly, videography and VTS allows for the quantification of parameters, such as path of mouse movement, that are difficult or unfeasible to measure with line crossing and/or biotelemetry. In sum, LMA testing coupled to VTS affords a more complete description of mouse movement and the ability to examine locomotion over an extended period of time.

Locomotor activity (LMA) is a simple and easily performed measurement of behavior in mice. Coupling of video tracking software (VTS) and LMA allows for the improvement of specificity and sensitivity, especially when compared with the manual, line crossing method of LMA analysis. Additionally VTS allows long-term tracking of mouse LMA.

Locomotor  activity (LMA) is a simple and easily performed measurement of behavior in mice  and other rodents. Improvements in video tracking software ...

Automated Visual Cognitive Tasks for Recording Neural Activity Using a Floor Projection Maze

Neuropsychological tasks used in primates to investigate mechanisms of learning and memory are typically visually guided cognitive tasks. We have developed visual cognitive tasks for rats using the Floor Projection Maze1,2&#160;that are optimized for visual abilities of rats permitting stronger comparisons of experimental findings with other species.
In order to investigate neural correlates of learning and memory, we have integrated electrophysiological recordings into fully automated cognitive tasks on the Floor Projection Maze1,2. Behavioral software interfaced with an animal tracking system allows monitoring of the animal's behavior with precise control of image presentation and reward contingencies for better trained animals. Integration with an in vivo electrophysiological recording system enables examination of behavioral correlates of neural activity at selected epochs of a given cognitive task.
We describe protocols for a model system that combines automated visual presentation of information to rodents and intracranial reward with electrophysiological approaches. Our model system offers a sophisticated set of tools as a framework for other cognitive tasks to better isolate and identify specific mechanisms contributing to particular cognitive processes.

We describe protocols for training rats for chronic electrophysiological recordings in fully automated cognitive tasks on a Floor Projection Maze.

Neuropsychological tasks used in primates to investigate mechanisms of learning and memory are typically visually guided cognitive tasks. We have ...

Eye Tracking, Cortisol, and a Sleep vs. Wake Consolidation Delay: Combining Methods to Uncover an Interactive Effect of Sleep and Cortisol on Memory

Although rises in cortisol can benefit memory consolidation, as can sleep soon after encoding, there is currently a paucity of literature as to how these two factors may interact to influence consolidation. Here we present a protocol to examine the interactive influence of cortisol and sleep on memory consolidation, by combining three methods: eye tracking, salivary cortisol analysis, and behavioral memory testing across sleep and wake delays. To assess resting cortisol levels, participants gave a saliva sample before viewing negative and neutral objects within scenes. To measure overt attention, participants&#8217; eye gaze was tracked during encoding. To manipulate whether sleep occurred during the consolidation window, participants either encoded scenes in the evening, slept overnight, and took a recognition test the next morning, or encoded scenes in the morning and remained awake during a comparably long retention interval. Additional control groups were tested after a 20&#160;min&#160;delay in the morning or evening, to control for time-of-day effects. Together, results showed that there is a direct relation between resting cortisol at encoding and subsequent memory, only following a period of sleep. Through eye tracking, it was further determined that for negative stimuli, this beneficial effect of cortisol on subsequent memory may be due to cortisol strengthening the relation between where participants look during encoding and what they are later able to remember. Overall, results obtained by a combination of these methods uncovered an interactive effect of sleep and cortisol on memory consolidation.

We present a protocol used to discover an interactive effect between sleep and cortisol on memory consolidation, particularly for negative arousing images. Specifically, the experimental design utilizes eye tracking, salivary cortisol analysis, and behavioral memory testing &#8211; methods that can be used with both healthy and clinical participants.

Although rises in cortisol can benefit memory consolidation, as can sleep soon after encoding, there is currently a paucity of literature as to how these ...

Behavioral and Locomotor Measurements Using an Open Field Activity Monitoring System for Skeletal Muscle Diseases

The open field activity monitoring system comprehensively assesses locomotor and behavioral activity levels of mice. It is a useful tool for assessing locomotive impairment in animal models of neuromuscular disease and efficacy of therapeutic drugs that may improve locomotion and/or muscle function. The open field activity measurement provides a different measure than muscle strength, which is commonly assessed by grip strength measurements. It can also show how drugs may affect other body systems as well when used with additional outcome measures. In addition, measures such as total distance traveled mirror the 6 min walk test, a clinical trial outcome measure. However, open field activity monitoring is also associated with significant challenges: Open field activity measurements vary according to animal strain, age, sex, and circadian rhythm. In addition, room temperature, humidity, lighting, noise, and even odor can affect assessment outcomes. Overall, this manuscript provides a well-tested and standardized open field activity SOP for preclinical trials in animal models of neuromuscular diseases. We provide a discussion of important considerations, typical results, data analysis, and detail the strengths and weaknesses of open field testing. In addition, we provide recommendations for optimal study design when using open field activity in a preclinical trial.

Open field activity levels are used to assess locomotive and behavioral activity levels. This protocol provides a well-designed, standardized protocol to use in preclinical trials for neuromuscular disorders.

The open field activity monitoring system comprehensively assesses locomotor and behavioral activity levels of mice. It is a useful tool for assessing ...

fMRI Validation of fNIRS Measurements During a Naturalistic Task

We present a method to compare brain activity recorded with near-infrared spectroscopy (fNIRS) in a dance video game task to that recorded in a reduced version of the task using fMRI (functional magnetic resonance imaging). Recently, it has been shown that fNIRS can accurately record functional brain activities equivalent to those concurrently recorded with functional magnetic resonance imaging for classic psychophysical tasks and simple finger tapping paradigms. However, an often quoted benefit of fNIRS is that the technique allows for studying neural mechanisms of complex, naturalistic behaviors that are not possible using the constrained environment of fMRI. Our goal was to extend the findings of previous studies that have shown high correlation between concurrently recorded fNIRS and fMRI signals to compare neural recordings obtained in fMRI procedures to those separately obtained in naturalistic fNIRS experiments. Specifically, we developed a modified version of the dance video game Dance Dance Revolution (DDR) to be compatible with both fMRI and fNIRS imaging procedures. In this methodology we explain the modifications to the software and hardware for compatibility with each technique as well as the scanning and calibration procedures used to obtain representative results. The results of the study show a task-related increase in oxyhemoglobin in both modalities and demonstrate that it is possible to replicate the findings of fMRI using fNIRS in a naturalistic task. This technique represents a methodology to compare fMRI imaging paradigms which utilize a reduced-world environment to fNIRS in closer approximation to naturalistic, full-body activities and behaviors. Further development of this technique may apply to neurodegenerative diseases, such as Parkinson&#8217;s disease, late states of dementia, or those with magnetic susceptibility which are contraindicated for fMRI scanning.

We present a method to compare functional brain activity recorded during a naturalistic task using fNIRS with activity recorded during fMRI.

We present a method to compare brain activity recorded with near-infrared spectroscopy (fNIRS) in a dance video game task to that recorded in a reduced ...

Use of the Open Field Maze to Measure Locomotor and Anxiety-like Behavior in Mice

Animal models have proven to be invaluable to researchers trying to answer questions regarding the mechanisms of behavior. The Open Field Maze is one of the most commonly used platforms to measure behaviors in animal models. It is a fast and relatively easy test that provides a variety of behavioral information ranging from general ambulatory ability to data regarding the emotionality of the subject animal. As it relates to rodent models, the procedure allows the study of different strains of mice or rats both laboratory bred and wild-captured. The technique also readily lends itself to the investigation of different pharmacological compounds for anxiolytic or anxiogenic effects. Here, a protocol for use of the open field maze to describe mouse behaviors is detailed and a simple analysis of general locomotor ability and anxiety-related emotional behaviors between two strains of C57BL/6 mice is performed. Briefly, using the described protocol we show Wild Type mice exhibited significantly less anxiety related behaviors than did age-matched Knock Out mice while both strains exhibited similar ambulatory ability.

A protocol is provided to use an Open Field Maze to access general locomotor activity, anxiety and emotionality in a laboratory mouse model.

Animal models have proven to be invaluable to researchers trying to answer questions regarding the mechanisms of behavior. The Open Field Maze is one of ...

Manipulation of Epileptiform Electrocorticograms (ECoGs) and Sleep in Rats and Mice by Acupuncture

Ancient Chinese literature has documented that acupuncture possesses efficient therapeutic effects on epilepsy and insomnia. There is, however, little research to reveal the possible mechanisms behind these effects. To investigate the effect of acupuncture on epilepsy and sleep, several issues need to be addressed. The first is to identify the acupoints, which correspond between humans, rats, and mice. Furthermore, the depth of insertion of the acupuncture needle, the degree of needle twist in manual needle acupuncture, and the stimulation parameters for electroacupuncture (EA) need to be determined. To evaluate the effects of acupuncture on epilepsy and sleep, a feasible model of epilepsy in rodents is required. We administer pilocarpine into the left central nucleus of the amygdala (CeA) to simulate focal temporal lobe epilepsy (TLE) in rats. Intraperitoneal (IP) injection of pilocarpine induces generalized epilepsy and status epilepticus (SE) in rats. Five IP injections of pentylenetetrazol (PTZ) with a one-day interval between each injection successfully induces spontaneous generalized epilepsy in mice. Recordings of electrocorticograms (ECoGs), electromyograms (EMGs), brain temperature, and locomotor activity are used for sleep analysis in rats, while ECoGs, EMGs, and locomotor activity are employed for sleep analysis in mice. ECoG electrodes are implanted into the frontal, parietal, and contralateral occipital cortices, and a thermistor is implanted above the cerebral cortex by stereotactic surgery. EMG electrodes are implanted into the neck muscles, and an infrared detector determines locomotor activity. The criteria for categorizing vigilance stages, including wakefulness, rapid eye movement (REM) sleep, and non-REM (NREM) sleep are based on information from ECoGs, EMGs, brain temperature, and locomotor activity. Detailed classification criteria are stated in the text.

Manipulation of Epileptiform Electrocorticograms ECoGs and Sleep in Rats and Mice by Acupuncture

This paper demonstrates the performance of acupuncture, epilepsy models, and the analysis of sleep in rodents. The acupuncture procedure and the identification of acupoints are described. Pilocarpine or pentylenetetrazol (PTZ) is used to induce epilepsy. Electrocorticogram (ECoG), electromyogram (EMG), brain temperature, and locomotor activity recordings are employed for sleep analysis.

Ancient Chinese literature has documented that acupuncture possesses efficient therapeutic effects on epilepsy and insomnia. There is, however, little ...

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. ...

Noninvasive, High-throughput Determination of Sleep Duration in Rodents

Traditionally, sleep is monitored by an electroencephalogram (EEG). EEG studies in rodents require surgical implantation of the electrodes followed by a long recovery period. To perform an EEG recording, the animal is connected to a receiver, creating an unnatural tether to the head-mount. EEG monitoring is time consuming, carries risk to the animal, and is not a completely natural setting for the measurement of sleep. Alternative methods to detect sleep, particularly in a high-throughput fashion, would greatly advance the field of sleep research. Here, we describe a validated method for detecting sleep via activity-based home-cage monitoring. Previous studies have shown that sleep assessed via this method has a high degree of agreement with sleep defined by traditional EEG-based measures. Whereas this method is validated for total sleep time, it is important to note that sleep bout duration should be assessed by an EEG which has better temporal resolution. The EEG can also differentiate rapid eye movement (REM) and non-REM sleep, giving more detail about the exact nature of sleep. Nevertheless, activity-based sleep determination can be used to analyze multiple days of undisturbed sleep and to assess sleep as a response to an acute event (like stress). Here, we show the power of this system to detect the response of mice to daily intraperitoneal injections.

We describe a high-throughput method of measuring sleep by means of activity-based home-cage monitoring. This method offers advantages over traditional EEG-based methods. It is well validated for the determination of total sleep duration and can be a powerful tool to monitor sleep in rodent models of human disease.

Traditionally, sleep is monitored by an electroencephalogram (EEG). EEG studies in rodents require surgical implantation of the electrodes followed by a ...

A High-performance Liquid Chromatography Measurement of Kynurenine and Kynurenic Acid: Relating Biochemistry to Cognition and Sleep in Rats

The kynurenine pathway (KP) of tryptophan degradation has been implicated in psychiatric disorders. Specifically, the astrocyte-derived metabolite kynurenic acid (KYNA), an antagonist at both N-methyl-d-aspartate (NMDA) and &#945;7 nicotinic acetylcholine (&#945;7nACh) receptors, has been implicated in cognitive processes in health and disease. As KYNA levels are elevated in the brains of patients with schizophrenia, a malfunction at the glutamatergic and cholinergic receptors is believed to be causally related to cognitive dysfunction, a core domain of the psychopathology of the illness. KYNA may play a pathophysiologically significant role in individuals with schizophrenia. It is possible to elevate endogenous KYNA in the rodent brain by treating animals with the direct bioprecursor kynurenine, and preclinical studies in rats have demonstrated that acute elevations in KYNA may impact their learning and memory processes. The current protocol describes this experimental approach in detail and combines a) a biochemical analysis of blood kynurenine levels and brain KYNA formation (using high-performance liquid chromatography), b) behavioral testing to probe the hippocampal-dependent contextual memory (passive avoidance paradigm), and c) an assessment of sleep-wake behavior [telemetric recordings combining electroencephalogram (EEG) and electromyogram (EMG) signals] in rats. Taken together, a relationship between elevated KYNA, sleep, and cognition is studied, and this protocol describes in detail an experimental approach to understanding function outcomes of kynurenine elevation and KYNA formation in vivo in rats. Results obtained through variations of this protocol will test the hypothesis that the KP and KYNA serve pivotal roles in modulating sleep and cognition in health and disease states.

Alterations in the kynurenine pathway (KP) neuroactive metabolites are implicated in psychiatric illnesses. Investigating the functional outcomes of an altered kynurenine pathway metabolism in vivo in rodents may help elucidate novel therapeutic approaches. The current protocol combines biochemical and behavioral approaches to investigate the impact of an acute kynurenine challenge in rats.