Predictive regression modeling with MEG/EEG: from source power to signals and cognitive states

Sabbagh, David; Ablin, Pierre; Varoquaux, Gaël; Gramfort, Alexandre; Engemann, Denis A.

doi:10.1016/j.neuroimage.2020.116893

Cited by 67 publications

(97 citation statements)

References 88 publications

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“…• The creation of age-dependent normative equations, not of isolated element of the Cross-spectral matrices, but rather considering them in their totality as elements of the Riemannian manifold of Hermitian positive definite matrices (Sabbagh et al, 2020). • To calibrate and test new methods for source localization of activation and connectivity as in He et al (2019).…”

Section: Projected Uses Of This Normative Datasetmentioning

confidence: 99%

Resting State Healthy EEG: The First Wave of the Cuban Normative Database

et al. 2020

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Section: Projected Uses Of This Normative Datasetmentioning

confidence: 99%

Resting State Healthy EEG: The First Wave of the Cuban Normative Database

et al. 2020

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“…Recent studies suggest that brain age prediction can be enhanced by combining several neuroimaging modalities and found that electrophysiology adds unique information on aging (Liem et al, 2017;Engemann et al, 2020). First studies have demonstrated robust estimation of brain age from high-density EEG data (Sabbagh et al, 2020) and sleep EEG (Sun et al, 2019). However, this framework has been rarely applied outside of the laboratory.…”

Section: Introductionmentioning

confidence: 99%

Propofol Requirement and EEG Alpha Band Power During General Anesthesia Provide Complementary Views on Preoperative Cognitive Decline

Touchard¹,

Cartailler

Levé³

et al. 2020

Front. Aging Neurosci.

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Background: Although cognitive decline (CD) is associated with increased post-operative morbidity and mortality, routinely screening patients remains difficult. The main objective of this prospective study is to use the EEG response to a Propofol-based general anesthesia (GA) to reveal CD.Methods: 42 patients with collected EEG and Propofol target concentration infusion (TCI) during GA had a preoperative cognitive assessment using MoCA. We evaluated the performance of three variables to detect CD (MoCA < 25 points): age, Propofol requirement to induce unconsciousness (TCI at SEF95: 8–13 Hz) and the frontal alpha band power (AP at SEF95: 8–13 Hz).Results: The 17 patients (40%) with CD were significantly older (p < 0.001), had lower TCI (p < 0.001), and AP (p < 0.001). We found using logistic models that TCI and AP were the best set of variables associated with CD (AUC: 0.89) and performed better than age (p < 0.05). Propofol TCI had a greater impact on CD probability compared to AP, although both were complementary in detecting CD.Conclusion: TCI and AP contribute additively to reveal patient with preoperative cognitive decline. Further research on post-operative cognitive trajectory are necessary to confirm the interest of intra operative variables in addition or as a substitute to cognitive evaluation.

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“…SPoC is a supervised regression approach, in which a target variable (here: subjective emotional arousal) guides the extraction of relevant M/EEG oscillatory components (here: alpha power). SPoC has been used to predict single-trial reaction times from alpha power in a hand motor task (Meinel et al, 2016), muscular contraction from beta power (Sabbagh et al, 2020), and difficulty levels of a video game from theta and alpha power (Naumann et al, 2016). CSP is used to decompose a multivariate signal into components that maximize the difference in variance between distinct classes (here: periods of high and low emotional arousal).…”

Section: Methodological Challenges Of Naturalistic Experimentsmentioning

confidence: 99%

Decoding subjective emotional arousal from EEG during an immersive Virtual Reality experience

Hofmann

Klotzsche

Mariola

et al. 2020

Preprint

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Immersive virtual reality (VR) enables naturalistic neuroscientific studies while maintaining experimental control, but dynamic and interactive stimuli pose methodological challenges. We here probed the link between emotional arousal, a fundamental property of affective experience, and parieto-occipital alpha power under naturalistic stimulation: 37 young healthy adults completed an immersive VR experience, which included rollercoaster rides, while their EEG was recorded. They then continuously rated their subjective emotional arousal while viewing a replay of their experience. The association between emotional arousal and parieto-occipital alpha power was tested and confirmed by (1) decomposing the continu- ous EEG signal while maximizing the comodulation between alpha power and arousal ratings and by (2) decoding periods of high and low arousal with discriminative common spatial pat- terns and a Long Short-Term Memory recurrent neural network. We successfully combine EEG and a naturalistic immersive VR experience to extend previous findings on the neurophysiology of emotional arousal towards real-world neuroscience.

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Predictive regression modeling with MEG/EEG: from source power to signals and cognitive states

Cited by 67 publications

References 88 publications

Resting State Healthy EEG: The First Wave of the Cuban Normative Database

Resting State Healthy EEG: The First Wave of the Cuban Normative Database

Propofol Requirement and EEG Alpha Band Power During General Anesthesia Provide Complementary Views on Preoperative Cognitive Decline

Decoding subjective emotional arousal from EEG during an immersive Virtual Reality experience

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