Abstract

The weighted Phase Lag Index (wPLI) and the weighted Symbolic Mutual Information (wSMI) represent two robust and widely used methods for MEG/EEG functional connectivity estimation. Interestingly, both methods have been shown to detect relative alterations of brain functional connectivity in conditions associated with changes in the level of consciousness, such as following severe brain injury or under anaesthesia. Despite these promising findings, it was unclear whether wPLI and wSMI may account for distinct or similar types of functional interactions. Using simulated high-density (hd-)EEG data, we demonstrate that, while wPLI has high sensitivity for couplings presenting a mixture of linear and nonlinear interdependencies, only wSMI can detect purely nonlinear interaction dynamics. Moreover, we evaluated the potential impact of these differences on real experimental data by computing wPLI and wSMI connectivity in hd-EEG recordings of 12 healthy adults during wakefulness and deep (N3-)sleep, characterised by different levels of consciousness. In line with the simulation-based findings, this analysis revealed that both methods have different sensitivity for changes in brain connectivity across the two vigilance states. Our results indicate that the conjoint use of wPLI and wSMI may represent a powerful tool to study the functional bases of consciousness in physiological and pathological conditions.

Details

Title
EEG functional connectivity metrics wPLI and wSMI account for distinct types of brain functional interactions
Author
Imperatori, Laura Sophie 1   VIAFID ORCID Logo  ; Betta, Monica 1 ; Cecchetti, Luca 1   VIAFID ORCID Logo  ; Canales-Johnson, Andrés 2 ; Ricciardi, Emiliano 1 ; Siclari, Francesca 3   VIAFID ORCID Logo  ; Pietrini, Pietro 1 ; Chennu, Srivas 4 ; Bernardi, Giulio 5 

 MoMiLab Research Unit, IMT School for Advanced Studies Lucca, Lucca, Italy 
 Department of Psychology, University of Cambridge, Cambridge, United Kingdom; Center for Social and Cognitive Neuroscience (CSCN), School of Psychology, Universidad Adolfo Ibáñez, Santiago, Chile; The Neuropsychology and Cognitive Neurosciences Research Center (CINPSI Neurocog), Universidad Católica del Maule, Talca, Chile 
 Center for Investigation and Research on Sleep, Lausanne University Hospital, Lausanne, Switzerland 
 School of Computing, University of Kent, Chatham Maritime, United Kingdom; Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom 
 MoMiLab Research Unit, IMT School for Advanced Studies Lucca, Lucca, Italy; Center for Investigation and Research on Sleep, Lausanne University Hospital, Lausanne, Switzerland; University Hospital of Pisa, Pisa, Italy 
Pages
1-15
Publication year
2019
Publication date
Jun 2019
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2244136055
Copyright
© 2019. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.