ENGLISH
La vitrine de diffusion des publications et contributions des chercheurs de l'ÉTS
RECHERCHER

A time-frequency analysis of the dynamics of cortical networks of sleep spindles from MEG-EEG recordings

Téléchargements

Téléchargements par mois depuis la dernière année

Plus de statistiques...

Zerouali, Younes, Lina, Jean-Marc, Sekerovic, Zoran, Godbout, Jonthan, Dube, Jonathan, Jolicoeur, Pierre et Carrier, Julie. 2014. « A time-frequency analysis of the dynamics of cortical networks of sleep spindles from MEG-EEG recordings ». Frontiers in Neuroscience, vol. 8.
Compte des citations dans Scopus : 28.

[thumbnail of Lina J-M 2014 8756.pdf]
Prévisualisation
PDF
Lina J-M 2014 8756.pdf - Version publiée
Licence d'utilisation : Creative Commons CC BY.

Télécharger (3MB) | Prévisualisation

Résumé

Sleep spindles are a hallmark of NREM sleep. They result from a widespread thalamo-cortical loop and involve synchronous cortical networks that are still poorly understood. We investigated whether brain activity during spindles can be characterized by specific patterns of functional connectivity among cortical generators. For that purpose, we developed a wavelet-based approach aimed at imaging the synchronous oscillatory cortical networks from simultaneous MEG-EEG recordings. First, we detected spindles on the EEG and extracted the corresponding frequency-locked MEG activity under the form of an analytic ridge signal in the time-frequency plane (Zerouali et al., 2013). Secondly, we performed source reconstruction of the ridge signal within the Maximum Entropy on the Mean framework (Amblard et al., 2004), yielding a robust estimate of the cortical sources producing observed oscillations. Lastly, we quantified functional connectivity among cortical sources using phase-locking values. The main innovations of this methodology are (1) to reveal the dynamic behavior of functional networks resolved in the time-frequency plane and (2) to characterize functional connectivity among MEG sources through phase interactions. We showed, for the first time, that the switch from fast to slow oscillatory mode during sleep spindles is required for the emergence of specific patterns of connectivity. Moreover, we show that earlier synchrony during spindles was associated with mainly intra-hemispheric connectivity whereas later synchrony was associated with global long-range connectivity. We propose that our methodology can be a valuable tool for studying the connectivity underlying neural processes involving sleep spindles, such as memory, plasticity or aging.

Type de document: Article publié dans une revue, révisé par les pairs
Professeur:
Professeur
Lina, Jean-Marc
Affiliation: Génie électrique
Date de dépôt: 27 oct. 2014 15:36
Dernière modification: 29 nov. 2021 15:34
URI: https://espace2.etsmtl.ca/id/eprint/8756

Actions (Authentification requise)

Dernière vérification avant le dépôt Dernière vérification avant le dépôt