EEGNET: An Open Source Tool for Analyzing and Visualizing M/EEG Connectome

Hassan, Mahmoud; Shamas, Mohamad; Khalil, Mohamad; Falou, Wassim El; Wendling, Fabrice

doi:10.1371/journal.pone.0138297

Cited by 68 publications

(43 citation statements)

References 73 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The network measures and network visualization were performed using BCT (Rubinov and Sporns, 2010) and EEGNET (Hassan et al, 2015b) respectively. See Fig.…”

Section: Methodsmentioning

confidence: 99%

Functional connectivity disruptions correlate with cognitive phenotypes in Parkinson's disease

Hassan

Chaton

Benquet

et al. 2017

NeuroImage: Clinical

View full text Add to dashboard Cite

Cognitive deficits in Parkinson's disease are thought to be related to altered functional brain connectivity. To date, cognitive-related changes in Parkinson's disease have never been explored with dense-EEG with the aim of establishing a relationship between the degree of cognitive impairment, on the one hand, and alterations in the functional connectivity of brain networks, on the other hand.This study was aimed at identifying altered brain networks associated with cognitive phenotypes in Parkinson's disease using dense-EEG data recorded during rest with eyes closed. Three groups of Parkinson's disease patients (N = 124) with different cognitive phenotypes coming from a data-driven cluster analysis, were studied: G1) cognitively intact patients (63), G2) patients with mild cognitive deficits (46) and G3) patients with severe cognitive deficits (15). Functional brain networks were identified using a dense-EEG source connectivity method. Pairwise functional connectivity was computed for 68 brain regions in different EEG frequency bands. Network statistics were assessed at both global (network topology) and local (inter-regional connections) level.Results revealed progressive disruptions in functional connectivity between the three patient groups, typically in the alpha band. Differences between G1 and G2 (p < 0.001, corrected using permutation test) were mainly frontotemporal alterations. A statistically significant correlation (ρ = 0.49, p < 0.001) was also obtained between a proposed network-based index and the patients' cognitive score. Global properties of network topology in patients were relatively intact.These findings indicate that functional connectivity decreases with the worsening of cognitive performance and loss of frontotemporal connectivity may be a promising neuromarker of cognitive impairment in Parkinson's disease.

show abstract

“…The network measures and network visualization were performed using BCT (Rubinov and Sporns, 2010) and EEGNET (Hassan et al, 2015b) respectively. See Fig.…”

Section: Methodsmentioning

confidence: 99%

Functional connectivity disruptions correlate with cognitive phenotypes in Parkinson's disease

Hassan

Chaton

Benquet

et al. 2017

NeuroImage: Clinical

View full text Add to dashboard Cite

show abstract

“…The functional connectivity, network measures and network visualization were performed using BCT (Rubinov and Sporns, 2010), EEGNET (Hassan et al, 2015) and BrainNet viewer (Xia et al, 2013), respectively. The Network Community Toolbox (http://commdetect.weebly.com/) was used to compute the consensus matrices as well as the values provided by the flexibility metrics.…”

Section: Softwarementioning

confidence: 99%

Psychological resilience correlates with EEG source-space brain network flexibility

Paban

Modolo

Mheich

et al. 2018

Preprint

Self Cite

View full text Add to dashboard Cite

Objective:We aimed at identifying the potential relationship between the dynamical properties of the human functional network at rest and one of the most prominent traits of personality, namely resilience. Approach:To tackle this issue, we used resting-state EEG data recorded from 45 healthy subjects. Resilience was quantified using the 10-items Connor-Davidson Resilience Scale (CD-RISC). Using a sliding windows approach, brain networks in each EEG frequency band (delta, theta, alpha and beta) were constructed using the EEG source-space connectivity method. Brain networks dynamics were evaluated using the network flexibility, linked with the tendency of a given node to change its modular affiliation over time. Main Results:The results revealed a negative correlation between the psychological resilience and the brain network flexibility for a limited number of brain regions within the delta, alpha and beta bands. Significance:This study provides evidence that network flexibility, a metric of dynamic functional networks, is strongly correlated with psychological resilience as assessed from personality testing. Beyond this proof-of-principle that reliable EEG-based quantities representative of personality traits can be identified, this motivates further investigation regarding the full spectrum of personality aspects and their relationship with functional networks.

show abstract

“…Finally, Hassan et al . [HSK*15] introduce EEGNET to analyse and visualize functional brain networks from M/EEG recordings.…”

Section: Related Workmentioning

confidence: 99%

Visual Exploration of Dynamic Multichannel EEG Coherence Networks

Gronde

Maurits

et al. 2018

Computer Graphics Forum

View full text Add to dashboard Cite

Electroencephalography (EEG) coherence networks represent functional brain connectivity, and are constructed by calculating the coherence between pairs of electrode signals as a function of frequency. Visualization of such networks can provide insight into unexpected patterns of cognitive processing and help neuroscientists to understand brain mechanisms. However, visualizing dynamic EEG coherence networks is a challenge for the analysis of brain connectivity, especially when the spatial structure of the network needs to be taken into account. In this paper, we present a design and implementation of a visualization framework for such dynamic networks. First, requirements for supporting typical tasks in the context of dynamic functional connectivity network analysis were collected from neuroscience researchers. In our design, we consider groups of network nodes and their corresponding spatial location for visualizing the evolution of the dynamic coherence network. We introduce an augmented timeline‐based representation to provide an overview of the evolution of functional units (FUs) and their spatial location over time. This representation can help the viewer to identify relations between functional connectivity and brain regions, as well as to identify persistent or transient functional connectivity patterns across the whole time window. In addition, we introduce the time‐annotated FU map representation to facilitate comparison of the behaviour of nodes between consecutive FU maps. A colour coding is designed that helps to distinguish distinct dynamic FUs. Our implementation also supports interactive exploration. The usefulness of our visualization design was evaluated by an informal user study. The feedback we received shows that our design supports exploratory analysis tasks well. The method can serve as a first step before a complete analysis of dynamic EEG coherence networks.

show abstract

EEGNET: An Open Source Tool for Analyzing and Visualizing M/EEG Connectome

Cited by 68 publications

References 73 publications

Functional connectivity disruptions correlate with cognitive phenotypes in Parkinson's disease

Functional connectivity disruptions correlate with cognitive phenotypes in Parkinson's disease

Psychological resilience correlates with EEG source-space brain network flexibility

Visual Exploration of Dynamic Multichannel EEG Coherence Networks

Contact Info

Product

Resources

About