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BehaviorCloud

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Description

BEHAVIOUR CLOUD

MAZEENGINEERS

The Behavior Cloud Camera

  • Onboard storage: 8Gb
  • Connectivity: Ethernet and Wifi
  • Power: 5v 1.0 a via USB C (included)
  • Mounting: Standard camera mount
  • IR compatible: Capable with illuminator (not included)

Multiple Integrations

With remote, home, and hybrid work becoming increasingly prevalent, the demand for streamlined and secure data sharing remains paramount across various sectors, including academia, clinical research, Biopharma, and CROs. BehaviorCloud emerges as an indispensable solution, simplifying good laboratory practices by facilitating efficient data collection, analysis, and sharing on a unified cloud platform. Unlike conventional methods restricted to single devices or systems, BehaviorCloud enables remote access to experiments and data, enhancing research productivity and efficiency.

Whether leveraging existing data or conducting real-time collection via live streaming, BehaviorCloud offers high-throughput capabilities to harness multiple data streams simultaneously. Utilizing a secure cloud-based system, researchers can seamlessly collect, collaborate on, and share data from any location without compromising security. Moreover, BehaviorCloud’s compatibility with Android and iOS mobile devices allows for flexible usage across desktops, tablets, and smartphones, bolstering accessibility and convenience. Leveraging cloud data streaming and storage capabilities, the platform empowers researchers to maximize data utilization and connectivity.

In addition to live experiment streaming, BehaviorCloud facilitates automated tracking of animal and insect behaviors, offering invaluable insights for tasks utilizing various apparatus such as the Elevated Plus Maze, Open-Field Test, Morris Water Maze, and Y-Maze. The platform’s robust feature set includes automated data generation for metrics like average velocity, visit counts, and latencies, complemented by an augmented manual scoring capability for complex behaviors such as nesting and walking. With minimal equipment requirements, researchers can swiftly commence using BehaviorCloud from either home or laboratory settings.

Trusted by prestigious academic institutions like Harvard University, Stanford University, Okayama University, and Ohio State University, as well as renowned research entities such as NASA, The Salk Institute for Biological Studies, SRI International, and Zafgen, BehaviorCloud stands as a proven solution for managing data across diverse research domains.

Sign up for BehaviorCloud to establish a secure cloud-based account tailored to your research requirements, whether you’re working remotely or on-site. BehaviorCloud seamlessly operates across multiple devices, including desktops, mobile phones, and tablets. To initiate BehaviorCloud’s live streaming functionality within your facility, simply activate your BehaviorCloud camera and link it to your account via either an ethernet connection or your wireless network. Once configured, this camera, equipped with 8GB of storage capacity, stands ready to commence video capture of short- or long-term behavioral tasks autonomously. All recorded footage is promptly streamed directly to your BehaviorCloud account.

Notably, the BehaviorCloud camera features night vision capabilities, ensuring compatibility with standard IR illuminators for experiments conducted in low-light or no-light conditions. Available for individual purchase, as part of a camera equipment bundle, or included within the BehaviorCloud starter package, the BehaviorCloud camera offers versatility and adaptability to suit diverse research needs.

To optimize your experience with BehaviorCloud, consider the following best practices:

  1. Adequate Lighting: Ensure that your experimental setup is well-lit and within the camera’s focal range to facilitate clear recording.
  2. Low-Light Conditions: For experiments requiring dim or dark environments, consider using a red light or infrared-light source (depending on device specifications) to capture high-quality videos.
  3. Minimal Interference: Conduct experiments in low-traffic areas to minimize shadows or other disturbances that may interfere with subject tracking or behaviors.
  4. Secure Camera Mounting: Safeguard against camera movement by securely mounting or fixing all cameras to prevent shifts during recordings.
  5. Stable Apparatus: Maintain the stability of your experimental apparatus to prevent inconsistencies in data collection.
  6. Reliable Connectivity: Ensure all connected devices have access to a stable internet connection and a reliable power source to prevent disruptions during recordings.
  7. Optimal Field of View: Consider using a wide-angle lens for close-up videos to achieve the desired field of view and enhance tracking accuracy.

BehaviorCloud empowers researchers and their teams with a unified cloud-based system tailored to their research requirements. This comprehensive platform offers ample data storage capacity, seamlessly integrated into the subscription, enabling high-throughput data collection across multiple streams while ensuring data security. Moreover, BehaviorCloud facilitates participation and collaboration from remote, on-site, and home locations, fostering easy sharing and collaboration of experimental data and records across laboratories via internet-enabled devices such as mobile phones, desktops, and tablets.

Setting up BehaviorCloud is a breeze, with the platform ready for use within minutes. Its user-friendly interface boasts intuitiveness and minimal learning curve, allowing seamless integration with all internet-enabled devices in the laboratory for remote control. Compatible with a wide range of camera devices, BehaviorCloud’s behavior tracking software enables tracking of behaviors in both live and pre-recorded videos, with options for manual data analysis as well.

Key Advantages:

  • Laboratory Notebook: BehaviorCloud’s lab notebook consolidates all data, from raw to completed datasets, with each version tagged and saved for accountability and repeatability. Good laboratory practices are simplified with BehaviorCloud.
  • Instrument Connectivity: Bridge technology facilitates connection of existing lab equipment to the cloud, enabling remote experiment control and real-time data streaming, streamlining multidimensional data collection for high-throughput studies.
  • Built-in Analysis Suite: The platform provides built-in analysis and visualization tools for all compatible data collection sources, including photobeam activity systems, video-based activity/behavior tracking, and manual behavioral coding.
  • Collaboration and Sharing: Researchers have full control over their data with permissions management, allowing for inviting collaborators to view, comment, and contribute to experiments. Project management is further streamlined with oversight of progress, assignment of responsibilities, and seamless project transfers between team members.
  • Secure Data Storage: BehaviorCloud ensures data security with all data and progress backed up on the cloud, adhering to the strictest industry security standards to safeguard researchers’ data.

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Considerations:

  • Camera Quality: Video tracking accuracy may be influenced by camera quality, necessitating appropriate lighting setup for clear recordings.
  • Recording Environment: To avoid interference, recordings should ideally be conducted in low-traffic areas, ensuring optimal performance from both the video recording and subjects.
  • Wide-angle Lens: Close-up videos may require a wide-angle lens to cover the desired recording area effectively.
  • Consistent Setup: To mitigate data discrepancies, maintain consistent positioning of cameras and apparatuses throughout recordings.

Stream & Upload

Use your mobile device to quickly start running live, video-based behavioral tracking or analyze existing videos you’ve captured

Track

BehaviorCloud offers automated video analysis capabilities, delivering accurate positional data for maze and cage-based experiments. Beyond basic tracking, the software generates a range of downstream variables including distance traveled, average velocity, zone entries, and additional metrics.

Zones

BehaviorCloud automates video analysis to provide dependable zone data, enabling precise scoring of geographical locations within MazeEngineers mazes.

Live Recording

  1. Start by logging into your BehaviorCloud account on all devices designated for the experiment.
  2. Ensure cameras are positioned and securely mounted to maintain a tight tracking boundary around the maze, eliminating extraneous movements from the footage.
  3. Using the designated control device, access your BehaviorCloud account in the browser and navigate to My Tests in the left-hand menu.
  4. Create a new experiment by clicking the ā€˜Ā­+ā€™ (plus sign) located at the bottom right-hand corner of the screen.
  5. Enter the Experiment Name and optionally provide a short description.
  6. From the drop-down menu, select the Automated Video Tracking option.
  7. Click Run a Live Test to proceed to the experiment page.
  8. Once on the experiment page, initiate distance calibration by clicking Calibration.
  9. Place the printed calibration pattern within full view of the maze.
  10. Select the camera device from the drop-down menu to start distance calibration.
  11. Click Next to save and apply the calibration to the entire experiment.
  12. After completing distance calibration, navigate to Experiment Video on the experiment page and click the ā€˜Ā­+ā€™ (plus sign) to add a new trial.
  13. Choose the desired recording device from the drop-down menu and enter the Subject ID and trial duration in seconds.
  14. Proceed to the next screen by clicking the arrow on the clear arena prompt, then place the subject and click the arrow on the insert subject prompt to initiate trial recording.
  15. Trials will conclude based on the specified duration, after which a prompt for the next subject will appear.

Uploading Videos

  1. Log-in to your BehaviorCloud account and clickĀ My TestĀ in the left-hand menu. Create a new experiment by clicking theĀ ā€˜Ā­+ā€™ (plus sign)Ā at the bottom right-hand corner of the screen.
  2. Enter theĀ Experiment NameĀ and short description (optional) and select theĀ Automated Video TrackingĀ option from the drop-down menu.
  3. Choose theĀ Upload Existing DataĀ to get directed to the experiment page and upload the videos. ClickĀ Experiment VideoĀ to upload files individually or in bulk by dragging and dropping.
  4. On the experiment page, clickĀ CalibrationĀ to initiate distance calibration. Using the tools provided draw a line of known length on the preview image. Enter the values for the lines in centimeters. Click
  5. Click on the uploaded video and a tool for specifying timestamps will appear. Using the top slider set the timestamp for the background image when the arena is clear. ClickĀ Set Cleared Timestamp. Next, using the bottom slider set the timestamp for when the animal is inserted, and tracking should begin. ClickĀ Set Inserted Timestamp. ClickĀ Save and Finalize.

Data Analysis

  1. Log-in to your BehaviorCloud account and clickĀ My TestĀ in the left-hand menu.
  2. On the experiment page, clickĀ Experiment VideoĀ to play back video or download raw video files as .mp4 files.
  3. On the experiment page, clickĀ Tracking BoundaryĀ to set area to be tracked. Using the shape tools provided cover the maze area and clickĀ Save. (Optional but recommended)
  4. Following setting of tracking boundary, on the experiment page selectĀ Raw Position DataĀ to generate raw tracked data for the experiment. Tracked video data and locomotion path of the animal can be viewed and/or downloaded by clicking on the individual subjects once the analysis is complete.
  5. On the experiment page, set the zones of the maze by selectingĀ Zone Maps. Enter the names for each zone and clickĀ Save. (Optional)
  6. For data analysis, on the experiment page select one of the following four options
    • Activity Analysis: Generates unzoned activity data.
    • Zoned Activity Analysis: Generates activity data broken into zones, according to the zones specified inĀ Zone Maps.
    • Zoned Sequence Analysis: Lists the zones entered in order of entry.
    • Spontaneous Alternation: Calculates percent spontaneous alternation in three-arm mazes like Y-maze or T-maze.

A prompt to segment the trial into time bins will appear before generation of analyzed data. Values can be entered in seconds, or the field can be left black.

  1. Analyzed data can be downloaded as a .csv file and imported directly into a data visualization program or statistical analysis software.

Activity Analysis

Ā Ā 

totaltime

:Total test time in seconds

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ambulatorytime

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:

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Total time the subject was moving, in seconds

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distancetraveled

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:

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Total distance traveled, in cm

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averagevelocity

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:

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Average velocity, in cm/s

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starttime

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:

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The start time of trial as an ISO8601 formatted date and time stamp

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restingtime

Ā 

:

Ā 

Total time the subject was resting, in seconds

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endtime

Ā 

:

Ā 

End time of trial as an ISO8601 formatted date and time stamp

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subject

Ā 

:

Ā 

Subject ID as provided by the user

Raw Position Data

Ā Ā 

time

:An ISO8601 formatted date and time stamp

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xcoordinate

Ā 

:

Ā 

X coordinate of the subject relative to the upper left corner of the video, in microns

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ycoordinate

Ā 

:

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Y coordinate of the subject relative to the upper left corner of the video, in microns

Zoned Sequence Analysis

Ā Ā 

time

:An ISO8601 formatted date and time stamp

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zone

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:

Ā 

Zone name as provided by the user

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subject

Ā 

:

Ā 

Subject ID as provided by the user

Spontaneous Alternation

Ā Ā 

Ā 

spontaneousalternation

Ā 

:

Ā 

Percent alternation (number of triads / (number of arm entries ā€“ 2)) x 100

Ā 

starttime

Ā 

:

Ā 

The start time of trial as an ISO8601 formatted date and time stamp

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endtime

Ā 

:

Ā 

End time of trial as an ISO8601 formatted date and time stamp

Ā 

subject

Ā 

:

Ā 

Subject ID as provided by the user

Zoned Activity Analysis

Ā 

Ā Ā 
totaltime:Total time spent in the zone, in seconds

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latency

Ā 

:

Ā 

Amount of time to first enter a zone, in seconds

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ambulatorytime

Ā 

Ā 

:

Ā 

Total time the subject was moving within the zone, in seconds

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zonename

Ā 

Ā 

:

Ā 

Name of the zone as provided by the user

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distancetraveled

Ā 

:

Ā 

Total distance traveled within the zone, in cm

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averagevelocity

Ā 

:

Ā 

Average velocity within a zone, in cm/s

Ā 

starttime

Ā 

Ā 

:

Ā 

The start time of trial as an ISO8601 formatted date and time stamp

Ā 

zoneentries

Ā 

:

Ā 

Number of entries into the zone

Ā 

restingtime

Ā 

Ā 

:

Ā 

Total time the subject was resting within a zone, in seconds

Ā 

endtime

Ā 

:

Ā 

End time of trial as an ISO8601 formatted date and time stamp

Ā 

subject

Ā 

:

Ā 

Subject ID as provided by the user

Manual Scoring

Manual scoring in the BehaviorCloud can be performed on live videos as well as uploaded videos. For performing manual scoring on live videos

  1. Follow step 1 to 4 of Live Recording Using BehaviorCloud. In the last step selectĀ Manual Video ScoringĀ in the drop-down menu for experiment type.
  2. On the experiment page, clickĀ Experiment Video. Set-up video recording by clicking the add icon at bottom right of the screen to record new subject.
  3. On prompt select the video streaming device and enter the subject ID and recording duration. Click the arrow to advance through the prompt screens to begin trial recording.
  4. Trials will terminate as per the values entered, and a new prompt for the next subject will appear.

Ā 

For manual scoring using uploaded videos, the procedure will be the same as the Uploading Video Files for Video Tracking with the exception, instead of selecting theĀ Automated Video TrackingĀ option, selectĀ Manual ScoringĀ option.

Following the video set-up follow the following steps to score the behaviors manually,

  1. On the experiment page, selectĀ Manual Scoring ConfigurationĀ to set up behaviors to be scored.
  2. Click the add icon at the bottom right to add behaviors and their corresponding labels. Also, select if the event is timed (behaviors such as walking) or instantaneous (behaviors such as counting fecal boli).
  3. Group mutually exclusive behaviors by clicking the menu icon to the right of the behavior and selectingĀ Group. Enter theĀ Group NameĀ and assign all relevant individual behaviors to their corresponding group. Follow the same process to ungroup behaviors.
  4. On the experiment page, selectĀ Manual ScoringĀ ClickĀ Import SubjectĀ to bring all videos into the workspace. Click on the subject to playback the video. Score behaviors either by clicking a behavior from the list or using keyboard shortcuts. Behaviors can be deleted or edited on the timeline that appears under the video.
  5. Following completion of scoring, return to the experiment page and clickĀ Manual Scoring Analysis. Initiate analysis by clickingĀ Generate Data.
  6. Individual subject data can be viewed in the browser or downloaded as a .csv file. Each behavior is also accompanied by the number of times the behavior occurred (count), the duration (total time), the beginning time of the first bout (latency), the beginning time of the last bout (last), and the behavior label and group ID.

Scoring

For behaviors and social interactions that pose challenges for automated quantification, BehaviorCloud offers tools to effortlessly define, observe, and score custom behaviors. This feature ensures researchers can apply the same robust analysis capabilities available for automated tracking to manual observations.

Collaborations

Sharing means caring, and BehaviorCloud allows multiple collaborators in your experimentation. No more thumb drives or email attachments

Additional information

BehaviorCloud Video Bundle

1-year Subscription, 2 years Subscription, 3+ years

Behaviour Cloud Subscription

1-year Basic Subscription, Commercial/Custom Lab Pricing, Multi-Year Basic Subscription

Behaviour Cloud

BehaviorCloud Subscription, BehaviorCloud Video Bundle

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