Abstract
The brain is a large-scale complex network often referred to as the “connectome”. Exploring the dynamic behavior of the connectome is a challenging issue as both excellent time and space resolution is required. In this context Magneto/Electroencephalography (M/EEG) are effective neuroimaging techniques allowing for analysis of the dynamics of functional brain networks at scalp level and/or at reconstructed sources. However, a tool that can cover all the processing steps of identifying brain networks from M/EEG data is still missing. In this paper, we report a novel software package, called EEGNET, running under MATLAB (Math works, inc), and allowing for analysis and visualization of functional brain networks from M/EEG recordings. EEGNET is developed to analyze networks either at the level of scalp electrodes or at the level of reconstructed cortical sources. It includes i) Basic steps in preprocessing M/EEG signals, ii) the solution of the inverse problem to localize / reconstruct the cortical sources, iii) the computation of functional connectivity among signals collected at surface electrodes or/and time courses of reconstructed sources and iv) the computation of the network measures based on graph theory analysis. EEGNET is the unique tool that combines the M/EEG functional connectivity analysis and the computation of network measures derived from the graph theory. The first version of EEGNET is easy to use, flexible and user friendly. EEGNET is an open source tool and can be freely downloaded from this webpage: https://sites.google.com/site/eegnetworks/.
Highlights
Magneto/Electroencephalography (M/EEG) are key techniques to analyze functional connectivity from surface signals [1, 2] or/and from reconstructed brain sources [3, 4]
The main advantage of M/EEG is the excellent temporal resolution that offers the unique opportunity i) to track brain networks over very short duration which is the case in many cognitive tasks and ii) to analyze fast dynamical changes that can occur in brain disorders
We show the difference steps realized using EEGNET to identify networks involved during picture naming task for a given subject
Summary
Magneto/Electroencephalography (M/EEG) are key techniques to analyze functional connectivity from surface signals [1, 2] or/and from reconstructed brain sources [3, 4]. The main advantage of M/EEG is the excellent temporal resolution (sub-second) that offers the unique opportunity i) to track brain networks over very short duration which is the case in many cognitive tasks and ii) to analyze fast dynamical changes that can occur in brain disorders (like epileptic seizures for instance). Approaches based on graph theory have represented brain networks as sets of nodes interconnected by edges [5]. Once the nodes and edges are defined from the neuroimaging. PLOS ONE | DOI:10.1371/journal.pone.0138297 September 17, 2015
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