Analysis Module

Getting Started with BehaviorDEPOT

Formatting Data

Pose Estimation Format (DLC Output)

Video Format

Using the BehaviorDEPOT GUI

Running an Analysis Session (single)

Analysis Module - (In Progress)

This section will demonstrate how to run a session in the Analysis Module:

1. After installation, launch BehaviorDEPOT from the App tab within Matlab.

2. Select which classifiers to use:

   • Certain classifiers have adjustable parameters. Click on ‘Edit Params’ to adjust those parameters.

3. Set distance calibration

   • Calibration can be calculated using ImageJ. Open a frame from a video and measure out the pixel distance of a known dimension (e.g. arena length). Use that to calculate the pixel-to-centimeter ratio.

4. Enter number of custom ROIs (in addition to classifier-based ROIs, e.g. Elevated Plus Maze, Open Field Test)

5. Choose whether or not to filter based on frame-locked events

   • Input for these is required to be a spreadsheet file (.csv, .xlsx), with each event as a row, the start frame in the first column and the end frame in the second column.

6. Select plotting preferences

   • ‘View Spatial Trajectory’ plots all the positions of the animal across the session.
   • ‘View spatiotemporal trajectory’ plots position across time, color coding the location points.
   • ‘View behavior location’ overlays a marker on the locations where behavior(s) of interest occurred.

7. Select single session or batch process

   • Single session for analyzing one paired DLC output and video file.
   • Batch process for analyzing multiple files with the same parameters. The required input structure for batch processing:
     • Grandparent folder, which is selected for analysis.
       • Parent folder 1 (Containing exclusively a single, matching pair of spreadsheet and video files) A single event file can also be included, and must be indicated with ‘cue’ in the filename (eg myevents_cue.csv)
       • Parent folder 2 (same as above)
       • Parent folder n (same as above)

8. Hit Start.

9. Follow the onscreen prompts to enter and customize your data. Depending on your settings:

   • If doing ‘single session’, you will be prompted to use the directory browser to select the spreadsheet and video files for analysis.
   • If doing ‘batch process’, you will be prompted to select the folder containing directories for analysis (see batch process instructions for data organization)
   • You may be prompted by the GUI to draw and name ROIs or parts of the arena, depending on your settings.
   • You will be prompted to select the body part corresponding to your custom named part.
   • You may be prompted to select timestamp files containing the start and stop frames of temporal events, and then name those events.

10. Results will be saved in a new folder in the same directory as the data.

Running Batch Analysis

Converting Human Annotations to hB Files (In Progress)

1. Save manual annotations as a 3 column table (1st: Start Frame, 2nd: Stop Frame, 3rd: Behavior Label)

   • Function is compatible with data tables in .mat or .csv files ** To import data from larger excel/csv files, select "import data" in Matlab and create 3 column tables for each video analyzed. After importing data as a table, save the table file as a .mat

2. Run convertHumanAnnotations function in Matlab

   • Inputs:
     • 1. table_filename: str/char pointing to MATLAB table file (requires path if not in current directory)
     • 2. total_frames: int, optional total number of frames in analyzed video
       • NOTE: if total_frames is empty, function will use the video file IF IN SAME FOLDER AS INPUT TABLE
     • 3. output_filename: str/char, optional; (default behavior = hB_[original filename])

3. Results will be saved as an hBehavior structure (similar in format to Behavior structures from Analysis Module)

   • File name will be 'hB_[original filename]' or named as [output_filename] if applicable