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eConnectome (Electrophysiological Connectome) is an open-source MATLAB software package for imaging brain functional connectivity from electrophysiological signals. It provides interactive graphical interfaces for EEG/ECoG/MEG preprocessing, source estimation, connectivity analysis and visualization. Connectivity from EEG/ECoG/MEG can be mapped over sensor and source domains.
This package is designed for use by researchers in neuroscience, psychology, cognitive science, clinical neurophysiology, neurology and other disciplines. The graphical interface-based platform requires little programming knowledge or experience with MATLAB.
eConnectome is developed by the Biomedical Functional Imaging and Neuroengineering Laboratory at the University of Minnesota, directed by Dr. Bin He. The visualization module is jointly developed with Drs. Fabio Babiloni and Laura Astolfi at the University of Rome "La Sapienza".
eConnectome was developed with support from the National Institute of Biomedical Imaging and Bioengineering of the National Institutes of Health under grants RO1 EB006433 and RO1 EB007920 to Bin He.
eConnectome is listed in the Neuroimaging Informatics Tools and Resources Clearinghouse directory.
The eConnectome toolbox is developed for imaging brain functional connectivity from electrophysiological signals. The toolbox consists of the following modules:
- Graphical user interface
- EEG/ECoG/MEG preprocessing
- Filtering, artifact rejection, baseline correction, ERP/ERF analysis
- Power spectrum and time-frequency analysis
- Potential/Field and spectrum mapping
- Source estimation
- Forward modeling
- Three-layer BEM model based on the MNI brain (for EEG)
- Single spherical volume conduction model (for MEG)
- High-resolution cortex model
- Inverse calculation
- Cortical Current Density model
- Minimum norm estimate and lead field weighted MNE with regularization
- ROI analysis
- ROI definition according to Brodmann Areas
- Customized definition of ROIs based on source images
- Individual anatomic head model
- Cortical source imaging with individual BEM model
- ROI analysis on individual cortical surface
- Connectivity analysis
- Granger causality analysis
- Directed Transfer Function
- Adaptive Directed Transfer Function
- Surrogate assessment
- Connectivity visualization
- EEG connectivity among scalp electrodes
- ECoG connectivity among subdural electrodes
- MEG connectivity among magnetometers
- Source connectivity based on selected ROIs
- eConnectome Version 2.0 beta was released on 6/1/2011.
- eConnectome Version 1.0 was released on 8/19/2010.
- eConnectome Version 1.0 beta was released on 3/12/2010.
- MATLAB environment (2007 or higher)
- MATLAB toolboxes:
- Signal Processing Toolbox
- Spline Toolbox
- ARfit and Regularization third-party toolboxes as explained in the download instructions below.
- Click here to register. Once you receive the email with your password, you can download the package here.
- Install the package as follows:
- Unzip econnectome.zip
- Download the ARfit package developed by Drs. Tapio Schneider and Arnold Neumaier. Unzip arfit.zip and put the package into ‘\eConnectome\tools\’.
- Download the Regularization Tools package developed by Dr. Per Christian Hansen. Unzip Software.zip and put the package into ‘\eConnectome\tools\’.
- In MATLAB, add ‘\eConnectome’ to the search path: File
Set Path
- Start to use the eConnectome software by typing econnectome in the MATLAB command window.
Send any questions or comments about eConnectome to econnect@umn.edu.
