2413 lines
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<article data-history-node-id="136381" about="/labs-at-nibib/ideas-lab/projects/scorhe-system-continuous-observation-rodents-home-cage-environment" class="ideas-projects node--ideas-projects node--type-ideas-projects">
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<div class="field field--name-field-collaborator field--type-link field--label-hidden field__item"><span>Michael Gottesman, M.D.</span></div>
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<div class="field field--name-field-institution field--type-string field--label-hidden field__item">Laboratory of Cell Biology, Center for Cancer Research, NCI</div>
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<div class="field field--name-field-collaborator field--type-link field--label-hidden field__item"><span>Jean-Pierre Gillet, Ph.D.</span></div>
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<div class="field field--name-field-institution field--type-string field--label-hidden field__item">Laboratory of Cell Biology, Center for Cancer Research, NCI</div>
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<div class="field field--name-field-collaborator field--type-link field--label-hidden field__item"><span>Michael Bustin, Ph.D.</span></div>
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<div class="field field--name-field-institution field--type-string field--label-hidden field__item">Protein Section, Laboratory of Metabolism, Center for Cancer Research, NCI</div>
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<span class="grid-col flex-auto"> <div class="paragraph paragraph--type--collaborators paragraph--view-mode--default">
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<div class="field field--name-field-collaborator field--type-link field--label-hidden field__item"><span>Takashi Furusawa, Ph.D.</span></div>
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<div class="field field--name-field-institution field--type-string field--label-hidden field__item">Protein Section, Laboratory of Metabolism, Center for Cancer Research, NCI</div>
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<div class="field field--name-field-collaborator field--type-link field--label-hidden field__item"><span>Anastasia Sowers</span></div>
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<div class="field field--name-field-institution field--type-string field--label-hidden field__item">Radiation Biology Branch, Center for Cancer Research, NCI</div>
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<span class="grid-col flex-auto"> <div class="paragraph paragraph--type--collaborators paragraph--view-mode--default">
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<div class="field field--name-field-collaborator field--type-link field--label-hidden field__item"><span>James Mitchell, PhD</span></div>
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<div class="field field--name-field-institution field--type-string field--label-hidden field__item">Radiation Biology Branch, Center for Cancer Research, NCI</div>
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<span class="grid-col flex-auto"> <div class="paragraph paragraph--type--collaborators paragraph--view-mode--default">
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<div class="field field--name-field-collaborator field--type-link field--label-hidden field__item"><span>Lex Kravitz, Ph.D.</span></div>
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<div class="field field--name-field-institution field--type-string field--label-hidden field__item">Eating and Addiction Section, Diabetes Endocrinology and Obesity Branch, NIDDK</div>
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<span class="grid-col flex-auto"> <div class="paragraph paragraph--type--collaborators paragraph--view-mode--default">
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<div class="field field--name-field-collaborator field--type-link field--label-hidden field__item"><span>George Dold</span></div>
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<div class="field field--name-field-institution field--type-string field--label-hidden field__item">Section on Instrumentation, NIMH</div>
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<div class="field field--name-field-collaborator field--type-link field--label-hidden field__item"><span>Benes Trus, Ph.D.</span></div>
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<div class="field field--name-field-institution field--type-string field--label-hidden field__item">Mathematical and Statistical Computing Laboratory, Office of Intramural Research, CIT</div>
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<span class="grid-col flex-auto"> <div class="paragraph paragraph--type--collaborators paragraph--view-mode--default">
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<div class="field field--name-field-collaborator field--type-link field--label-hidden field__item"><span>Sinisa Pajevic, Ph.D.</span></div>
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<div class="field field--name-field-institution field--type-string field--label-hidden field__item">Mathematical and Statistical Computing Laboratory, Office of Intramural Research, CIT</div>
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<span class="grid-col flex-auto"> <div class="paragraph paragraph--type--collaborators paragraph--view-mode--default">
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<div class="field field--name-field-collaborator field--type-link field--label-hidden field__item"><span>James Malley, Ph.D.</span></div>
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<div class="field field--name-field-institution field--type-string field--label-hidden field__item">Mathematical and Statistical Computing Laboratory, Office of Intramural Research, CIT</div>
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<div class="field field--name-field-collaborator field--type-link field--label-hidden field__item"><span>John Dennis, DVM</span></div>
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<div class="field field--name-field-institution field--type-string field--label-hidden field__item">Division of Veterinary Services, Center for Biologics Evaluation and Research, Food and Drug Administration (FDA)</div>
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<h2>Project Brief</h2>
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<p>In collaboration with NCI, NIDDK, NIMH, and FDA, SCORHE is designed to meet the demands of NIH IRP researchers and animal care staff to automatically assess laboratory mice ethology in large-scale settings. SCORHE is comprised of custom video-acquisition and analysis tools developed to quantify mice activity and behavior for short and long (multi-day) durations while housed within a typical home-cage. The specialized hardware was designed to be space efficient, compatible with vivarium cage racks, and animal-facility user friendly. The advanced video analytics algorithms output ethology measures such as locomotion profiles and software-interpreted behaviors. SCORHE hardware targets the ‘natural’ home-cage setting in an effort to eliminate concerns, often associated with traditional mouse monitoring methods, such as circadian rhythm disruption, acclimation periods, lack of nighttime measurements, and short monitoring periods. With mice being the predominant mammalian model used in NIH IRP research, SCORHE is the most practical solution for large-scale use of vision systems in animal facilities, affording researchers and animal care staff accurate long-term activity and well-being measures. SCORHE developments will provide the scientific community an open-source platform for consistent and repeatable acquisition of home-cage ethology measures. More than a dozen SCORHE units being fabricated will provide access to this unique technology to additional IRP investigators. </p>
|
||
<h3>What is SCORHE?</h3>
|
||
<p>SCORHE (System for Continuous Observation of Rodents in Home-cage Environment) is comprised of custom video-acquisition and analysis tools developed to quantify mice activity and behavior for short and long (multi-day) durations while housed within a typical home-cage. The specialized hardware was designed to be space efficient, compatible with vivarium cage racks, and animal-facility user friendly. The advanced software algorithms output ethology measures such as locomotion profiles and software-interpreted behaviors. SCORHE hardware targets the ‘natural’ home-cage setting in an effort to eliminate concerns, often associated with traditional mouse monitoring methods, such as circadian rhythm disruption, acclimation periods, lack of nighttime measurements, and short monitoring periods. Overall, SCORHE developments will provide the scientific community an open-source platform for consistent and repeatable acquisition of home-cage ethology measures.</p>
|
||
<h3>Motivation</h3>
|
||
<p>Behavior assessment is an integral part in drug-efficacy, animal model development, and phenotyping studies. Video-based systems have emerged as a viable solution to quantify alterations in mouse locomotion and behavior profiles. Automated video analysis carries the promise of high-throughput, long-term, and fine-grained assessment of mouse activity and behavior. The results obtained through video analysis compliment other phenotypical measures to provide researchers more insight on deviations from baseline behavior. To enable wide-spread access to video-acquisition and analysis technology in animal facilities, the SCORHE units were designed to have a minimal footprint and integrate with existing colony racks. SCORHE units can also be used outside of the cage-racks. SCORHE space efficiency and automated video analysis makes SCORHE suitable for large-scale, long-term use with minimal user intervention.</p>
|
||
<h3>Collaboration</h3>
|
||
<p>SCORHE design, fabrication, evaluation, and deployment is a collaborative effort with NIH IRP researchers. Initial developments were focused on rather limited requirements (e.g., general mouse activity) associated with specific studies. More recently, advancements in algorithm development have led to obtaining detailed time-resolved behavior measures and accurate locomotor activity profiling. Ongoing collaborations will enable immediate innovative application of SCORHE to support IRP studies. New collaborations with will likely result in further SCORHE development to extend hardware and software analysis functionality. Overall, SCORHE developments will provide the scientific community an open-source platform for consistent and repeatable acquisition of home-cage ethology measures.</p>
|
||
<h3>Hardware</h3>
|
||
|
||
<figure role="group" class="align-center">
|
||
<img alt="SCORHE 3D-CAD model and prototype" data-entity-type="file" data-entity-uuid="c5a204d6-deba-4f4b-bd61-b9dc6bf5a167" height="302" src="/sites/default/files/inline-images/SCORHE%203D-CAD%20model.png" width="905" loading="lazy">
|
||
<figcaption>SCORHE 3D-CAD model and prototype fabricated at the NIH</figcaption>
|
||
</figure>
|
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<p> </p>
|
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<h3>Video Acquisition</h3>
|
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<div class="align-left">
|
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<div class="blazy blazy--nojs blazy--field blazy--field-media-oembed-video blazy--field-media-oembed-video--default field field--name-field-media-oembed-video field--type-string field--label-hidden field__item" data-blazy> <div data-b-token="b-cffda322804" class="media media--blazy media--youtube media--bundle--remote-video media--video media--ratio media--ratio--169"> <iframe allowfullscreen src="/media/oembed?url=https%3A//www.youtube.com/watch%3Fv%3DxwFsabGUdbE&max_width=0&max_height=0&hash=s1ojfoEKEIN8aEcPYlTiy9Dp5P0ch6Kv4OLd_r9qiJk&blazy=1" class="media__element" loading="lazy"></iframe>
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<p>The SCORHE hardware is comprised of two to four time-synchronized cameras giving complete view of the home-cage volume. Fisheye lenses allow capture of a full cage-view with the cameras positioned in very close proximity to the cage; resulting in a compact and space-efficient unit design. The side-panels of the SCORHE unit are equipped with near-infrared emitters to provide spatially and temporally uniform illumination during video acquisition without disrupting the light/dark cycle for the mice.</p>
|
||
<p> </p>
|
||
<h3><br> </h3>
|
||
<h3>In-Rack Operation</h3>
|
||
<p>The SCORHE unit was designed to achieve seamless integration with vivarium cage-racks, which includes maintaining full rack cage capacity and providing easy access to the cage via the windowed door. The current prototypes were engineered for compatibility with the Maxi-Miser racks (Thoren Caging Systems, Hazelton, PA) predominantly found in the National Cancer Institute (NCI) animal facilities.</p>
|
||
|
||
<figure role="group" class="align-center">
|
||
<img alt="SCORHE installed in the cage rack" data-entity-type="file" data-entity-uuid="e4acb794-55fa-4038-b792-b146efc7766a" height="290" src="/sites/default/files/inline-images/SCORHE%20installed.jpg" width="830" loading="lazy">
|
||
<figcaption>SCORHE installed in the cage rack</figcaption>
|
||
</figure>
|
||
<p>While the current SCORHE unit hardware is tailored to Thoren’s racks and Model 5 cage, the design could be modified to achieve compatibility with other racks and cage combinations. Alternatively, SCORHE units could be used as bench-top systems (i.e., outside a cage rack).</p>
|
||
<div>
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||
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||
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<div class="blazy blazy--nojs blazy--field blazy--field-media-oembed-video blazy--field-media-oembed-video--default field field--name-field-media-oembed-video field--type-string field--label-hidden field__item" data-blazy> <div data-b-token="b-e249886ed7c" class="media media--blazy media--youtube media--bundle--remote-video media--video media--ratio media--ratio--169"> <iframe allowfullscreen src="/media/oembed?url=https%3A//www.youtube.com/watch%3Fv%3DKHO9Lrvsq6w&max_width=0&max_height=0&hash=lLwOXpI-Tr7Ota6NHOMF4VaYR6FKqeVreysrF7Hl8QM&blazy=1" class="media__element" loading="lazy"></iframe>
|
||
</div>
|
||
</div>
|
||
|
||
</div>
|
||
<h3>Out-of-Rack Operation</h3>
|
||
<p>For researchers interested in using the system immediately in vivaria or laboratories not equipped with the Thoren racks, a bench-top rack solution has been designed to house four SCORHE units. The compact, open-frame system provides easy access to the units, and eliminates clutter by consolidating cables.</p>
|
||
|
||
<figure role="group" class="align-center">
|
||
<img alt="Computer diagram of the SCORHE bench-top rack" data-entity-type="file" data-entity-uuid="db4d1c6b-b418-4675-80d0-134ab226fa2d" height="312" src="/sites/default/files/inline-images/SW_4unit_enclosure%20v2.png" width="433" loading="lazy">
|
||
<figcaption>SCORHE bench-top rack</figcaption>
|
||
</figure>
|
||
<h3>Software</h3>
|
||
<p>Software methods have been developed to automate analysis of video acquired by the SCORHE units. The SCORHE algorithms accomplish two main tasks. The first task is estimation of mouse head/tail position. The trajectory information derived from the position estimates is used in analyzing locomotion patterns. The second is identification and labeling of bouts of nine pre-defined behaviors: eating, drinking, grooming, foraging, unsupported rearing, supported rearing, climbing, walking, and resting. The time-resolved behavior labels are used in detection of abnormalities. The algorithms are based on statistical modeling in a supervised learning scheme. Namely, for 3D head/tail estimation, mouse head/tail positions were manually marked for a large set of SCORHE images. Synchronized with each image, the actual physical head/tail positions were obtained via a parallel validation system comprised of additional cameras and corresponding perspectives. The set of annotated SCORHE images and corresponding validated physical positions was used to train a non-parametric regression model. The resulting regression model calculates the physical position of the mouse head/tail in each frame of video. The behavior detection module is posed as a classification problem with a training set comprising hours of manually labeled video. The resulting classifier incorporates temporal context from trajectory and spatial features to assign to each frame one of the nine aforementioned behavior labels. Currently, the processing rate for the software methods is slower than required for real-time operation. Videos acquired by SCORHE are analyzed offline by the software in a post-processing fashion. Refer to the video at the top of the page for example output of the SCORHE processing methods.</p>
|
||
<h3>Results</h3>
|
||
<p><img alt="9 charts labeled Eating, Drinking, Walking, Rearing-unsupported, Rearing-supported, Climbing, Grooming, Foraging, Resting" data-entity-type="file" data-entity-uuid="0b274313-ab1e-410b-981a-26c1d9026033" height="720" src="/sites/default/files/inline-images/SCORHE%20Resuts.png" width="1026" class="align-center" loading="lazy"></p>
|
||
<h3>Future Development</h3>
|
||
<p>The initial development phase targeted solitary-housed black mice. With the major hardware and software challenges resolved and a clear course for algorithm design charted, three main SCHORE development goals are currently underway. The first goal is optimization of the code to achieve real-time processing. The second is to mirror the black mouse algorithm development for other coat-colors. And the third is to extend SCORHE functionality to cages housing multiple animals.</p>
|
||
<p>Please contact us if you are interested in developing new SCORHE functionality and applications specific to meeting your research requirements. The video link below includes clips of multiple animals per cage that might aid in evaluating which measures could be obtained with the current SCORHE design, and those which would require SCORHE modification or further development.</p>
|
||
|
||
<figure role="group" class="align-center">
|
||
<img alt="SCORHE 3D models and prototype units in vivarium rack" data-entity-type="file" data-entity-uuid="c3b713e9-19d2-4576-89fe-8caae558ab7b" src="/sites/default/files/inline-images/Fig1_1.png" width="828" height="662" loading="lazy">
|
||
<figcaption>SCORHE hardware is designed to deliver large-scale automated video-based monitoring of research mice housed in standard ventilated racks. (a) A 3D-design model addressing investigator and animal facility requirements and procedures. (b) A SCORHE prototype built in-house. (<strong>c</strong>) Two SCORHE units installed in a cage rack (second row from bottom). SCORHE offers seamless integration while maintaining full rack cage capacity.</figcaption>
|
||
</figure>
|
||
<p> </p>
|
||
|
||
<figure role="group" class="align-center">
|
||
<img alt="Screenshots of SCORHE video and classification example" data-entity-type="file" data-entity-uuid="cd9aca6b-987f-4b29-ba65-3c9de6289b0c" src="/sites/default/files/inline-images/Fig2.png" width="890" height="704" loading="lazy">
|
||
<figcaption>SCORHE software analyzes incoming video streams to produce detailed time-resolved activity measures for full circadian cycles. (a) A still image from the front-view camera (top) and the rear-view camera (bottom). (b) The first processing module segments the incoming images to identify mouse pixels and determine the view in which the mouse is visible. (c) An advanced estimation algorithm reconstructs the corrected 3D position of the mouse head/tail from the fisheye distorted image. (d) A classifier is trained to inspect a sequence of frames and automatically detect one of nine pre-defined behaviors. (e) Time-resolved profiles are generated for each of the pre-defined behaviors. Shown is the ‘walking’ behavior profile for a 24-hour cycle. The gray shading in the plot indicates the dark cycle, highlighting the nocturnal nature of the mouse.</figcaption>
|
||
</figure>
|
||
</div>
|
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<div class="field field--name-field-card-title field--type-string field--label-hidden field__item">Publications</div>
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<div class="field field--name-field-card-text field--type-text-long field--label-hidden field__item"><p><a href="/sites/default/files/2022-08/SCORHE_ACIVS2016.pdf">Scalable Vision System for Mouse Homecage Ethology</a></p>
|
||
<p><a href="/sites/default/files/2022-08/SCORHE_GlobalSIP2016.pdf">Cascaded Regression for 3D Pose Estimation for Mouse in Fisheye Lens Distorted Monocular Images</a></p>
|
||
<p><a href="https://pubmed.ncbi.nlm.nih.gov/30946667/">Three Dimensional Pose Estimation of Mouse from Monocular Images in Compact Systems</a></p>
|
||
<p><a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4570574/">SCORHE: a novel and practical approach to video monitoring of laboratory mice housed in vivarium cage racks</a></p>
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