Summary

Gathering Self-Initiated Rat Behavioral Data to Characterize Post-Stroke Deficits

Published: March 15, 2024
doi:

Summary

A system for acquiring data from self-initiated individual behavior sessions within a social colony cage setting is presented. The efficacy of this system is demonstrated using an automated skilled reach assessment, enabling the characterization of post-stroke motor impairments, potential behavioral alterations related to motivation, circadian variations, and other innovative dependent variables.

Abstract

Behavioral testing in rat models is frequently utilized for diverse purposes, including psychological, biomedical, and behavioral research. Many traditional approaches involve individual, one-on-one testing sessions between a single researcher and each animal in an experiment. This setup can be very time consuming for the researcher, and their presence may impact the behavioral data in unwanted ways. Additionally, traditional caging for rat research imposes a lack of enrichment, exercise, and socialization that would normally be typical for the species, and this context may also skew the results of behavioral data. Overcoming these limitations may be worthwhile for several research applications, including the study of acquired brain injury. Here, an example method is presented for automatically training and testing individual rat behavior in a colony cage without the presence of humans. Radio frequency identification can be utilized to tailor sessions to the individual rat. The validation of this system occurred in the example context of measuring skilled forelimb motor performance before and after stroke. Traditional characteristics of post-stroke behavioral impairments and novel measures enabled by the system are measured, including success rate, various aspects of pull force, bout analysis, initiation rate and patterns, session duration, and circadian patterns. These variables can be collected automatically with few limitations; though the apparatus removes experimental control of exposure, timing and practice, the validation produced reasonable consistency in these variables from animal to animal.

Introduction

Behavioral training and testing with rat models are important in countless research areas, from the exploration of cognitive processes to disease states and more1. Typically, this training and testing is conducted with single animals in one-on-one sessions, with a researcher manually removing the animal from their home caging and temporarily placing them in some kind of apparatus. Unfortunately, there are several difficulties and limitations with this approach. First, behavioral testing can take a great deal of time for researchers, and when training is necessary, that time requirement becomes even greater. Second, this approach automatically affects-or even potentially confounds-the acquired data, as has been established elsewhere2. These confounds are especially salient when considering enrichment-related variables. Specifically, laboratory rats are traditionally housed in small cages that are just big enough for one or two rats3, and if running wheels are not provided, they may go a lifetime without meaningful opportunities to exercise. Additionally, isolated housing can be a major source of stress in a social species such as the rat4. Some of these welfare-related drawbacks likely impact rat physiology5,6, which may preempt the development of species-typical behavioral expression4 and impact the quality of rodent models as applied to human contexts.

Researchers have pursued several types of solutions to these problems in recent years. The simplest type of solution has been to automate behavioral testing and training7,8,9,10, thus removing the requirement for a single researcher to attend to a single animal. An additional solution has been to automate animal transfer to experimental chambers11,12, further removing the need for human involvement. Last, several setups have been explored which allow animals to be housed in colony caging with other animals and with more room for exploration and enrichment13. Despite these advantages, such colony setups can limit or complicate the efforts to gather individually differentiated behavioral data (though see efforts to use computer vision)14,15. If individual behavioral data is required, it can be more difficult or complex to identify and retrieve animals from colony caging for behavioral sessions as well. At present, few systems exist for collecting individual behavioral data from (enriched) colony housing16,17,18.

These drawbacks may specifically impact research on the behavioral effects of acquired brain injury. First, it is clear that the presence and/or sex of humans as well as handling practices affect rodent behavior2,19, and these variables may differentially impact the behavior of rats before vs. after stroke. Second, human behavioral outcomes after stroke can be worsened by voluntarily decreased engagement with the recommended dosage of rehabilitation exercises20. Currently, rodent experiments tend to not model this sort of context, because rats are not free to choose to engage or abstain from behavioral sessions.

This article introduces a protocol designed to facilitate individual behavioral testing within the framework of enriched colony caging. This approach not only addresses the constraints of current practices but also opens avenues for the exploration of innovative measures. A one-rat turnstile (ORT) has been developed and can be affixed to a colony cage, enabling animals to enter behavioral chambers independently and initiate their own training and testing sessions. The system is affordable; each ORT can be assembled at low cost (given access to a 3D printer). In the past, validation of this system was carried out using a basic operant chamber, showing that animals could be consistently trained to perform a simple operant lever press without the presence of an experimenter16. Nevertheless, the question of whether this configuration is applicable to other scenarios remains unresolved. The aim is to validate the effectiveness of the ORT-colony caging setup, which was previously established, for training and quantifying skilled reach behavior relevant to motor impairment following a stroke. The configuration was utilized to generate novel variables that are typically not explored in stroke research. These variables include performance metrics for the skilled reach task and measurements of self-initiation, which could be pertinent to motivation and decision-making. Furthermore, stroke-induced changes in the circadian patterns of daily self-initiation across the entire 24 h period were effectively detected.

Protocol

All procedures and animal care were approved by the University of North Texas institutional animal care and use committee (IACUC) and adhered to National Institutes of Health guide for the care and use of Laboratory animals. Adult male and female Long-Evans rats (400-800 g, 1.5 years old), used in the present study, were housed in colony caging. 1. Equipment preparation Obtain or assemble the one-rat turnstile (ORT) according to the design files and instructions fo…

Representative Results

The animals were trained and tested with four female rats in one colony cage and four male rats in a separate colony cage. All rats learned to pass through the ORTs in four days or less. The four female rats reached >85% successful bouts at the 120 g force requirement in approximately 6 weeks of training and the male rats reached the same criterion in 10 weeks (compared to roughly 3 weeks with standard training with deprived rats)7. This training duration was greatly lengthened due to several …

Discussion

This protocol has multiple uses. First, and most broadly, the ORT was developed for the purpose of enabling automated single-subject behavioral training and data collection in the context of social, enriched housing. While this study tested the idea of collecting typical behavioral measures and elaborating upon them in the context of stroke, the same can be done for other applications and behavioral tasks. Even the measures gathered in this validation can also be adjusted as needed to include alternative reinforcement sc…

Divulgations

The authors have nothing to disclose.

Acknowledgements

This work was funded in part by the Beatrice H. Barrett endowment for research on neuro-operant relations to the University of North Texas (UNT). We are grateful for the input and assistance of all members of the Neuroplasticity and Repair Laboratory, especially Valerie Rojas, Mary Kate Moore, Cameron Scallon, and Hannah McGee.

Materials

3D printer  Consult with local makerspace
bolt Boltdepot 1346 6-32 or 8-32 by  0.5"
bolt Boltdepot 1348 6-32 or 8-32 by  0.75"
door hinge XJS (Amazon) 43398-16234 1" cabinet stainless steel door hinge set; Optional (if "perfect hinge" is not printed)
drill Any electric drill works
extension spring Nieko (Amazon) 50456A Choose and adjust spring based on ORT sized and desired tension
granulated sugar
lock nuts Boltdepot 2551 6-32 or 8-32
measuring tape
microcontroller Arduino A000066 Arduino Uno
microswitch Sparkfun KW4-Z5F mini microswitch (SPDT-roller lever)
One Rat Turnstile (ORT) Vulintus Contact company to request quote if not self-assembling
Operant Chambers as desired for behavioral assessment: For this experiment we used automated isometric pull chambers from Vulintus  Vulintus No cat #: contact Vulintus Contact Vulintus for quote
PLA filament  OVERTURE (Amazon) UK-MATTEPLA17511
plexiglass Lesnlok (Amazon) B09P74K7BR clear, 1/8" thickness, Cut to size
plexiglass cutter
python program Python Software Foundation software available on request
RFID reader Priority 1 Design RFIDRW-E-USB With antenna
RFID tag Unified Information Devices UC-1485-10
rod Boltdepot 23632 cut to > 3.5"
Rotary tool Used to bore hole in apparatus and colony caging for ORT; any hardware usable
sand paper HSYMQ (Amazon) TOMPOL-1118-1915-11
socket wrench set Any socket wrench set works
soldering iron
super glue 234790
wire Plusivo (Amazon) EAN0721248989789

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Armshaw, J., Butcher, G., Becker, A. Gathering Self-Initiated Rat Behavioral Data to Characterize Post-Stroke Deficits. J. Vis. Exp. (205), e64967, doi:10.3791/64967 (2024).

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