Fluorescence Single Neuron and Network Analysis Package

We have developed a set of MATLAB routines and a graphical user interface to facilitate the analysis of fluorescent calcium imaging of neuronal networks. The Fluorescence Single Neuron and Network Analysis Package (FluoroSNNAP) allows users to

  • Interactively view an image stack
  • Perform image registration and remove motion artifact
  • Perform both automated (independent component analysis and active contour evolution) and manual image segmentation to identify neuronal cell bodies
  • Identify ROI-based changes in fluorescence
  • Automatically determine the onset of calcium transients and compute the kinetics of each transient
  • Perform synchronization cluster analysis to reveal groups of neurons that are phase-locked
  • Infer functional connectivity using cross-correlation, partial correlation, instantaneous phase, Granger causality or transfer entropy methods
  • Perform network controllability analysis to identify driver nodes
  • Identify network ensembles
  • The MATLAB source code can be downloaded below. Please read the User Guide and our accompanying publication in the Journal of Neuroscience Methods for more details. To get started, simply download the source code, extract the zip file, run MATLAB and change directory to FluoroSNNAP. Enter FluoroSNNAP at the command window to start the software.

    A sample experiment of the spontaneous activity of cultured primary rat cortical neurons is also made available to test the software. For this experiment, neurons were transduced with AAV2-GCaMP6 and the activity was measured at 10Hz for 2 minutes. Note: the sample experiment, titled "baseline.tif", is a large file (800MB) so be patient when downloading. Alternatively, use the baseline.csv file which contains fluorescence vs. frame data for each neuron in the field view as a comma-separated format (columns = neurons, rows = frames).

  • FluoroSNNAP source code (MATLAB files), version 15.04
  • User Guide
  • FluoroSNNAP stand-alone for MacOSX (64-bit). Please read the Instructions for installation.
  • FluoroSNNAP stand-alone for Windows (64-bit). Please read the Instructions for installation.
  • Sample experiment (.tif stack)
  • Sample experiment with motion artifact (.tif stack)
  • Sample experiment (.csv file)
  • Screencast showing the use of FluoroSNNAP on a Macbook Pro with MacOSX10.9, 2.5GHz core i7 processor and 16 GB RAM, running MATLAB 2014a

    If your computer does not have sufficient memory, the ICA based batch segmentation feature may fail and MATLAB may freeze. In this case, you may still continue to use the software by choosing semi-automated segmentation methods - thresholding, and active coutour evolution. The screencast below demonstrates these features. It was recorded on a Windows 7, i7 930 computer with 12GB RAM, running MATLAB 2013b.