jsl-pathfinder 1.0.1

Morris Water Maze Search Strategy Analysis

Pathfinder

Jason Snyder Lab Watermaze Search strategy and entropy analysis. Created by Matthew Cooke at The University of British Columbia, Jason Snyder Lab

Synopsis

The Pathfinder package is a animal search strategy analysis tool for the Morris Water Maze. The program analyses X-Y coordinate data exported from tracking software (currently supports Ethovision, Anymazy, WaterMaze, and ezTrack). We then calculate the best-fit search strategy for the trial. We analyse the data and fit it into one of 9 search strategies: Direct Swim, Directed Search, Focal Search, Spatial indirect, Chaining, Scanning, Thigmotaxis, and Random Search.

Usage Example

1. The program can be opened by calling pathfinder if installed through PyPi or by navigating to your install location and calling python __main__.py in a terminal window. See Installation for install instructions.

2. This will open up the GUI window.

3. You can then select an inividual file or a directory containing files from the File dropdown menu. These files must be Excel files if you are using Ethovision tracking software, and CSV files if you are using Anymaze or Watermaze software. Note: For directory selection, you must enter into the directory and not just highlight it for it to be selected

4. From here you can choose to either (A) generate heatmaps for the chosen trials, or to (B) calculate search strategies.

(A) Generating Heatmaps

The Pathfinder package allows for the efficient generation of heatmaps. To do so, follow these steps.

1. Click on File -> Generate Heatmaps

2. A parameters panel will appear:

3. The parameters panel lets you tailor the output to your needs:

   1. Grid size. This roughly translates into how many bins to put the data in. For more information on grid size see matplotlib documentation: http://matplotlib.org/devdocs/api/_as_gen/matplotlib.axes.Axes.hexbin.html

   2. Maximum Value. This will allow you to change at which value the points in the heatmap will become their most saturated (dark red). Setting 'Auto' will dynamically assign the maximum value to be equal to the value of the maximum grid.

4. You can then click generate, and our software will plot a heatmap of your trial data.

(B) Search Strategy Analysis

1. For search strategy analysis we have multiple options. To use predefined values from either Snyder et el., 2017, Ruediger et al., 2012, or Gathe et al., 2009 click their respecive buttons. To set your own strategy parameters, click custom.

2. (Custom) The custom button will spawn a parameters panel

3. In the custom parameters pane, you can select and deselect any of the search strategies. Deselecting Strategies will remove them from consideration. You can also define the cutoff values for each strategy. For definitions of these values see Snyder et al., 2017.

4. Once you have chosen your parameters, be sure to select your tracking software. Ethovision, Anymaze, and Watermaze are currently supported. (Note: Anymaze and Watermaze are currently in beta -- not all features are available)

5. You may then alter the main values to suit your data. Platform position, pool centre, and pool diameter can be automatically calculated for groups of non-probe trials tracked in Ethovision. For all other data you must manually define these values (Example: Platform Position (x,y) | 6.53,-17.3). Old platform position is only used when Perseverance is chosen in the Custom parameters pane. For more in-depth explanations of these values, see Snyder et al., 2017.

6. There are 3 checkboxes above the Calculate button. The first, Scale Values is used to automatically scale the default values in an attempt to better match your data. This uses the Pixels/cm and the pool diameter to determine a constant C with which to multiply some parameters. (Note: If you are using custom values, it is best to disable scaling) The two other checkboxes enable manual categorization. Manual categorization can be used for trials in which our algorithm was unable to make a determination (Manual categorization for uncategorized trials) or for all trials (Manual categorization for all trials).

7. Once you are satisfied with your parameters, click calculate. This will begin the process of determining search strategies for the trials. Once calculation is complete you will be shown a display of the results.

8. Your results will be saved as a .csv file with whatever name was chosen in the Output File field. You will also receive a log file of the excecution, and any generated paths saved in your present working directory. The CSV file will automatically open with whatever default CSV software you use.

Motivation

This program was developed in order to simplify as well as remove inconsistencies in Morris Water Maze search strategy analysis.

Installation

Installing the program is easy for both macOS and Windows users.

Pathfinder requires you to have Python 3.6 or later. We highly recommend installing Conda for python via the Anaconda 🐍 package https://www.anaconda.com/distribution/. Once installed, the installation of Pathfinder is easy.

For the most recent stable version, cloning the GitHub repository or installing via PyPi is possible. For the most recent beta version of the software, the develop branch of the GitHub repository will host version currently being worked on.

Installation Instructions:

Windows:

Installing from the Python Package Index: Launch a CMD window by launching run from the start menu, and typing CMD in Run.

Once the CMD shell has opened, type pip install jsl-pathfinder

Press enter

Installing from GitHub

Download and install Git here: https://git-scm.com

Open Git Bash.

Change the current working directory to the location where you want the cloned directory to be made.

Type git clone https://github.com/MatthewBCooke/Pathfinder

Press enter

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Mac:

Installing from the Python Package Index:

Open a terminal window (located in your utilities folder under the Applications directory.

Type pip install jsl-pathfinder

Press return

Installing from GitHub

Open a terminal window Navigate to the folder you wish to install Pathfinder into

Type git clone https://github.com/MatthewBCooke/Pathfinder/

press return

References

Ruediger S, Spirig D, Donato F, Caroni P. Goal-oriented searching mediated by ventral hippocampus early in trial-and-error learning. Nat Neurosci. 2012 Nov;15(11):1563-71. doi: 10.1038/nn.3224. Epub 2012 Sep 23. PubMed PMID: 23001061.

Adult-Generated Hippocampal Neurons Allow the Flexible Use of Spatially Precise Learning Strategies Garthe A, Behr J, Kempermann G (2009) Adult-Generated Hippocampal Neurons Allow the Flexible Use of Spatially Precise Learning Strategies. PLOS ONE 4(5): e5464. https://doi.org/10.1371/journal.pone.0005464

Garthe A, Huang Z, Kaczmarek L, Filipkowski RK, Kempermann G. Not all water mazes are created equal: cyclin D2 knockout mice with constitutively suppressed adult hippocampal neurogenesis do show specific spatial learning deficits. Genes, Brain, and Behavior. 2014;13(4):357-364. doi:10.1111/gbb.12130.

Graziano A, Petrosini L, Bartoletti A. Automatic recognition of explorative strategies in the Morris water maze. J Neurosci Methods. 2003 Nov 30;130(1):33-44. PubMed PMID: 14583402.

License

GNU GENERAL PUBLIC LICENSE Version 3, 29 June 2007

Copyright (C) 2007 Free Software Foundation, Inc. http://fsf.org/ Everyone is permitted to copy and distribute verbatim copies of this license document, but changing it is not allowed.