Automated analysis of synaptic activity

Synaptic Activity in ImageJ (SynActJ) is an image and data analysis workflow that allows to analyze synaptic activity. It is based on a Fiji plugin and a R Shiny App that implement the automated image analysis of active synapses in time-lapse movies. We tested the workflow with movies of pHluorin or calcium sensors.

Citation

This work has been published: https://doi.org/10.3389/fcomp.2021.777837

Please cite:

Schmied C, Soykan T, Bolz S, Haucke V and Lehmann M (2021) SynActJ: Easy-to-Use Automated Analysis of Synaptic Activity. Front. Comput. Sci. 3:777837. doi: 10.3389/fcomp.2021.777837

Core features

• Java Swing based graphical user interface
• Interactive adjustment over entire dataset
• Batch processing executed from main interface
• Saving and loading of processing settings
• Shiny App for data processing

Link to SynActJ repository
Link to SynActJ Shiny repository

Methods overview

  1. Detection & Segmentation

• Maximum intensity projections are performed before and after the specified stimulation frame
• The projection after the stimulation is divided by the projection before the stimulation
• A Laplacian of Gaussian is performed to enhance Blob-like structures and a maximum detection is performed
• An intensity threshold is used to segment the blob area
• The detection and the segmentation is fed into a seeded watershed to compute regions of interest (ROI) per detection and separate touching objects

2. Background segmentation

• Maximum intensity projection over movie
• Intensity based threshold
• Invert mask

3. Image measurements

• Mean signal per ROI is extracted for each frame
• Other parameters such as area are measured per ROI

4. Data processing

• Average signal and background is computed
• Background is subtracted from average signal
• Signal is surface normalized
• Signal is peak normalized

Fiji methods used

Marker controlled watershed:
David Legland, Ignacio Arganda-Carreras, Philippe Andrey; MorphoLibJ: integrated library and plugins for mathematical morphology with ImageJ. Bioinformatics 2016; 32 (22): 3532-3534. doi: 10.1093/bioinformatics/btw413

LoG3D plugin:
D. Sage, F.R. Neumann, F. Hediger, S.M. Gasser, M. Unser, “Automatic Tracking of Individual Fluorescence Particles: Application to the Study of Chromosome Dynamics,” IEEE Transactions on Image Processing, vol. 14, no. 9, pp. 1372-1383, September 2005.

Accepted Datasets

Expected are 2D single channel .tif files containing multiple frames. At a specific frame the cultured neurons were stimulated and active boutons show an increase in intensity. The image calibration can be changed in the workflow. A settings file can be provided but can also be created later.

A small example file is provided here: Link to example data
The default segmentation parameters should work for this example file.

Installation

Fiji plugin

For the image analysis you need to download and install Fiji: https://fiji.sc/ The plugin is available via an update site. Add the Cellular Imaging site and the ImageScience update site:

1. Select Help › Update… from the menu bar.
2. Click on Manage update sites. Which opens the Manage update sites dialog.
3. Press Add update site a new line in the Manage update sites dialog appears
4. Select: Cellular Imaging
5. Select: ImageScience
6. Press Apply and Close
7. SynActJ and its dependencies should appear in Updater.
8. Press Apply Changes

Data analysis - Rshiny app

For the data analysis you need to download R and RStudio: R Version 4.1.0
Link to R
Select version 4.1.0

RStudio 1.4.1717
Link to RStudio

1. Download the contents of the repository: SynActJ Shiny
   Click on the green button: Code.
   Press Download ZIP to download the scripts.
2. Unzip the script to a location of your choice.
3. Open the app.R file in RStudio.
4. Start the application: press Run App - top right corner of RStudio.
5. RStudio may ask to install or load extra packages - Download will take some time.
6. Once these packages are installed and loaded the RShiny GUI should pop up.
7. Optional: Press Open in Browser for a better rendering of the GUI.

Documentation and tutorials

- SynActJ Plugin Overview

- SynActJ Plugin Tutorial

- SynActJ R Shiny App