Subcortical electrophysiological activity is detectable with high-density EEG source imaging

Seeber, Martin; Cantonas, Lucia-Manuela; Hoevels, Mauritius; Sesia, Thibaut; Visser‐Vandewalle, Veerle; Michel, Christoph M.

doi:10.1038/s41467-019-08725-w

Cited by 220 publications

(190 citation statements)

References 34 publications

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“…Importantly, hdEEG (especially with 256 electrodes as in our study) can have sufficient accuracy in source localization (e.g. associating dreams containing faces with activation of the fusiform face area (Siclari F et al 2017), even for the detection of signal originating from deep cerebral structures (Seeber M et al 2019). However, combined EEG/fMRI studies are certainly needed to further elucidate the exact contribution of subcortical structures, such as the amygdala, especially during REM sleep (Maquet P et al 1996;De Gennaro L et al 2011;Corsi-Cabrera M et al 2016).…”

Section: Discussionmentioning

confidence: 73%

Fear in dreams and in wakefulness: evidence for day/night affective homeostasis

Sterpenich

Perogamvros

Tononi

et al. 2019

Preprint

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Recent neuroscientific theories have proposed that emotions experienced in dreams contribute to the resolution of emotional distress and preparation for future affective reactions. We addressed one emerging prediction, namely that experiencing fear in dreams is associated with more adapted responses to threatening signals during wakefulness. Using a stepwise approach across two studies, we identified brain regions activated when experiencing fear in dreams and showed that frightening dreams modulated the response of these same regions to threatening stimuli during wakefulness. Specifically, in Study 1, we performed serial awakenings in 18 participants recorded throughout the night with highdensity EEG and asked them whether they experienced any fear in their dreams. Insula and midcingulate cortex activity increased for dreams containing fear. In Study 2, we tested 89 participants and found that those reporting higher incidence of fear in their dreams showed reduced emotional arousal and fMRI response to fear-eliciting stimuli in the insula, amygdala and midcingulate cortex, while awake. Consistent with better emotion regulation processes, the same participants displayed increased medial prefrontal cortex activity. These findings support that emotions in dreams and wakefulness engage similar neural substrates, and substantiate a link between emotional processes occurring during sleep and emotional brain functions during wakefulness. SIGNIFICANT STATEMENTHighly debated while pivotal to current theoretical models of dreaming, the relationship between emotion processing during wakefulness and in dreams remains elusive. In a first study, we used high-density EEG recordings and observed that regions involved in fear processing (i.e. the insula and midcingulate cortex) were activated during fear-related dreams. This first finding demonstrates that emotions in dreams engage similar neural circuits as during wakefulness. In a second study, using fMRI, we show that higher incidence of fear in dreams was associated with reduced emotional arousal and brain responses indicative of better emotion regulation during wakefulness. Together, these results strongly support the idea that experiencing fear in a secure environment, as in dreams, relates to more adapted responses to threatening events in real life. 2000), others reported a balance of positive and negative emotions (Schredl M and E Doll 1998), or found that joy and emotions related to approach behaviors may prevail (Fosse R et al. 2001;Malcolm-Smith S et al. 2012). When performing a lexicostatistical analysis of large datasets of dream reports, a clear dissociation between dreams containing basic, mostly fear-related, emotions and those with other more social emotions (e.g. embarrassment, excitement, frustration) was found, highlighting distinct affective modes operating during dreaming, with fear in dreams representing a prevalent and biologically-relevant emotional category (Revonsuo A 2000;Schwartz S 2004). Thus, if fear-containing dreams serve an emotion regulation f...

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Section: Discussionmentioning

confidence: 73%

Fear in dreams and in wakefulness: evidence for day/night affective homeostasis

Sterpenich

Perogamvros

Tononi

et al. 2019

Preprint

View full text Add to dashboard Cite

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“…Another potential direction is to develop the inversion methodology: one might apply the HBM for sub-cortical areas (Seeber et al 2019), with nondiagonal prior covariance structures and/or with sampling-based posterior exploration techniques, e.g., the Gibbs sampler (Spitzer 1971;Murphy 2012).…”

Section: Discussionmentioning

confidence: 99%

Zeffiro User Interface for Electromagnetic Brain Imaging: a GPU Accelerated FEM Tool for Forward and Inverse Computations in Matlab

Rezaei

Pursiainen

2019

Neuroinform

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This article introduces the Zeffiro interface (ZI) version 2.2 for brain imaging. ZI aims to provide a simple, accessible and multimodal open source platform for finite element method (FEM) based and graphics processing unit (GPU) accelerated forward and inverse computations in the Matlab environment. It allows one to (1) generate a given multi-compartment head model, (2) to evaluate a lead field matrix as well as (3) to invert and analyze a given set of measurements. GPU acceleration is applied in each of the processing stages (1)-(3). In its current configuration, ZI includes forward solvers for electro-/magnetoencephalography (EEG) and linearized electrical impedance tomography (EIT) as well as a set of inverse solvers based on the hierarchical Bayesian model (HBM). We report the results of EEG and EIT inversion tests performed with real and synthetic data, respectively, and demonstrate numerically how the inversion parameters affect the EEG inversion outcome in HBM. The GPU acceleration was found to be essential in the generation of the FE mesh and the LF matrix in order to achieve a reasonable computing time. The code package can be extended in the future based on the directions given in this article.

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“…However, the broad (rather than more localized) dipole effect seen here would likely reflect a deep source (e.g., originating from thalamus rather than cortex). While alpha and surrounding frequencies can indeed originate in the thalamus (or involve thalamocortical circuitry) (Bollimunta et al, 2011;Seeber et al, 2019), higher-frequency activity such as gamma is typically thought to originate more locally (Buzsáki and Wang, 2012). Therefore, while a single deep source may determine or coordinate LFϕ across multiple regions, this source is unlikely to be generating the coupled HFamp portion of the signal.…”

Section: Discussionmentioning

confidence: 99%

Developmental Changes in EEG Phase Amplitude Coupling and Phase Preference over the First Three Years After Birth

Mariscal

Levin

Gabard-Durnam

et al. 2019

Preprint

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The coupling of the phase of slower electrophysiological oscillations with the amplitude of faster oscillations, termed phase-amplitude coupling (PAC), is thought to facilitate dynamic connectivity in the brain. Though the brain undergoes dramatic changes in connectivity during the first few years of life, how PAC changes through this developmental period has not been studied. Here, we examined PAC through electroencephalography (EEG) data collected longitudinally during an awake, eyes-open EEG collection paradigm in 98 children between the ages of 3 months and 3 years. We implement a novel technique developed for capturing both PAC strength and phase preference (i.e., where in the slower oscillation waveform the faster oscillation shows increased amplitude) simultaneously, and employed non-parametric clustering methods to evaluate our metrics across a range of frequency pairs and electrode locations. We found that frontal and occipital PAC, primarily between the alpha-beta and gamma frequencies, increased from early infancy to early childhood (p = 1.35 x 10 -5 ). Additionally, we found frontal gamma coupled with the trough of the alpha-beta waveform, while occipital gamma coupled with the peak of the alpha-beta waveform. This opposing trend may reflect each region's specialization towards feedback or feedforward processing, respectively. Significance StatementThe brain undergoes significant changes in functional connectivity during infancy and early childhood, enabling the emergence of higher-level cognition. Phase-amplitude coupling (PAC) is thought to support the functional connectivity of the brain. Here, we find PAC increases from 3 months to 3 years of age. We additionally report the frontal and occipital brain areas show opposing forms of PAC; this difference could facilitate each region's tendency towards bottomup or top-down processing.

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Subcortical electrophysiological activity is detectable with high-density EEG source imaging

Cited by 220 publications

References 34 publications

Fear in dreams and in wakefulness: evidence for day/night affective homeostasis

Fear in dreams and in wakefulness: evidence for day/night affective homeostasis

Zeffiro User Interface for Electromagnetic Brain Imaging: a GPU Accelerated FEM Tool for Forward and Inverse Computations in Matlab

Developmental Changes in EEG Phase Amplitude Coupling and Phase Preference over the First Three Years After Birth

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