Dr. Timothy H. Murphy
Software developed RFID tagging
of mice Python
Download zipped file here
Bolanos, F. and LeDue J., Murphy TH. (2017) Cost effective
raspberry pi-based radio frequency identification tagging of
mice suitable for automated in vivo imaging.
J. Neurosci. Meth.
Software developed and used in our lab
Source code written in Python for controlling automation
of mouse cage and 3D printer files.
Download Python code and 3D printer files (ZIP)
please cite Murphy et al.
Nat Commun. 2016 Jun
13;7:11611. doi: 10.1038/ncomms11611.
Neurophotonics tutorial on making connectivity diagrams
from Channelrhodopsin-2 stimulated data
This package of sample data and
matlab codes will process, filter, and average raw voltage
sensitive dye images, generate a comprehensive connectivity
matrix and a network diagram (as seen in Lim et al.,
(with Bioinformatics Toolbox and Brain Connectivity Toolbox)
Inputs: sample data; Matlab functions;
Mask.tif (as included in .zip file)
Outputs: dF/F0(%) VSD connectivity matrix;
Figure of network properties as a function of threshold
levels; Network diagram
Download source code (MATLAB
scripts and raw data)
Download user guide (txt)
Automated and quantitative analysis of blebbed dendrites
BlebQuant is developed for automated detection
and quantification of blebbing1.
The program is a MATLAB-based graphical user interface.
Download source code
Download user guide (PDF)
Download demo data:
Screenshot of BlebQuant
Images of YFP-labelled dendrites,
recorded with in vivo 2-photon microscopy in the mouse cortex,
in ZIP-archived TIFF files:
to interpolate pixels with value "NaN" and "Infinity" in
images or image stacks. This tool is supposedly useful to apply before Gaussian
or Mean filtering data because it avoids the subsequent formation of filtering artifacts.
Options of this plugin may be set to match the parameters of the filter applied thereafter.
Dispose ALL windows
- Updated 2013 -
plugin closes all image windows and non-image windows as selected by the user.
The code is based on the
plugin by Tony Collins and J. Anthony Parker.
In this updated version, multiple subsequent dialog screens are displayed in case
the available space on monitor won't be large enough for listing the titles of
all open image windows. If the plugin is started wwhile <Shift> or <Alt> key being pressed, all images and/or non-image windows can be selected at once.
If the Plugin is called from the Macro executer with options set, it will dispose
without confirmation any image and non-image windows as specified
(regardles it is locked or changes are not saved.)
Fixed and updated
Jan 5, 2013
- run("Dispose All Windows", "image_1.tif image_2.tif Exception");
- dispose the specified windows, (which could be either the title of images like in this example "image_1.tif" and "image_1.tif", and/or titles of non-image windows like, in this example, the title of the text window "Exeption".)
Note that spaces in window names have to be replaced by underscores. If there are two windows with the same (space to underscore replaced) title, add an underscore for referring the second one.
Window names that doesn't match with an existing window will be ignored. disposing the specified windows, (which could be either the title of images like in this example "image_1.tif", and/or titles of non-image windows like, in this example, the title of the text window "Exeption".) Note that spaces in window names have to be replaced by underscores. If there are two windows with the same (space to underscore replaced) title, add an underscore for referring the second one. Window names that doesn't match with an existing window will be ignored.
- run("Dispose All Windows", "/all image");
run("Dispose All Windows", "/all images");
- dispose all image windows (without confirmation!)
- run("Dispose All Windows", "/all non-image");
- automatically dispose all non-image windows
- run("Dispose All Windows", "/all image non-image");
- automatically dispose all image and non-image windows
- run("Dispose All Windows");
- show the user dialog (window disposing upon confirmation)
- Compiled plugin
- Source code
The main plugin features should work with all
The optional functionality of closing non-image windows requires
ImageJ version 1.40 or newer.
IO and VSD Signal Processor
- Updated Version: January 6, 2012 -
Plugin for ImageJ
for analysis of Intrinsic Optical signal (IOS) or voltage sensitive dye (VSD) fluorescence
signal in imaging data2.
Written by Albrecht Sigler.
Download Installation file
To install, copy the file into the plugin folder and restart ImageJ.
Detailed information about handling plugins can be found at the
of ImageJ. Requires ImageJ version 1.31v or later,
whereas updating to newer ImageJ versions is recommended for performance.
For further analysis of the resulting (ΔF/F0)
image stacks we suggest using the Dynamic Z Profiler plugin (former name "Intensity v Time Monitor"; source code: Z Profiler.java.)
Download Source Code
Open Source; feel free to modify and to distribute according to the rules of the
GNU General Public Licence.
PDF file with detailed program description and user guide.
Screenshot of the IO and VSD Signal Processor (Version 1.0.8)
You may use software of this site that is linked or described on this page for any personal, commercial or educational purpose, including installing it on as many different computers as you wish. You may also copy, distribute, modify, and/or sell it under the terms of the GNU General Public License (GPL) as published by the Free Software Foundation - either version 2 of the License, or (at your option) any later version. In granting you this right, the GPL requires that the source code you distribute is itself available under the GPL. If you have questions, please contact us.
1. Chen S, Tran S, Sigler A, Murphy TH (2011) Automated and quantitative image
analysis of ischemic dendritic blebbing using in vivo 2-photon microscopy data.
J Neurosci Methods 195, Issue 2, 15 February 2011, Pages 222-231;
2. Harrison TC, Sigler A, Murphy TH (2009) Simple and cost-effective hardware and software for functional brain mapping using intrinsic optical signal imaging. J Neurosci Methods 182, 211-218.