Frontal and parietal EEG alpha asymmetry: A large-scale investigation of short-term reliability on distinct EEG systems

Abstract EEG resting state alpha asymmetry is one of the most widely investigated forms of functional hemispheric asymmetries in both basic and clinical neuroscience. However, studies yield very inconsistent results. One crucial prerequisite to obtain reproducible results is the reliability of the index of interest. There is a body of research suggesting a moderate to good reliability of EEG resting state alpha asymmetry, but unfortunately sample sizes in these studies are typically small. This study presents the first large scale short-term reliability study of frontal and parietal EEG resting state alpha asymmetry. We used the Dortmund Vital Study data set containing 541 participants. In each participant, EEG resting state was recorded eight times, twice with their eyes opened, twice with their eyes closed, each on two different EEG systems. We found good reliability of EEG alpha power and alpha asymmetry on both systems. Interestingly, we found no reliable alpha asymmetry in frontomedial brain regions, one of the most investigate brain regions in alpha asymmetry research. Furthermore, we investigated the link between EEG alpha asymmetry and handedness, since previous studies showed that right-handedness is associated with higher rightward alpha asymmetry. Our results only partly replicate this association. In conclusion, our results suggest that while EEG alpha asymmetry is an overall reliable measure, frontal alpha asymmetry should be assessed by using multiple electrode pairs. Furthermore, the question of EEG alpha asymmetry’s association with handedness remains unsettled and needs further investigation.

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Frontal and parietal EEG alpha asymmetry: a large-scale investigation of short-term reliability on distinct EEG systems

Brain Structure and Function ◽

10.1007/s00429-021-02399-1 ◽

2021 ◽

Author(s):

Dorothea Metzen ◽

Erhan Genç ◽

Stephan Getzmann ◽

Mauro F. Larra ◽

Edmund Wascher ◽

...

Keyword(s):

Resting State ◽

Large Scale ◽

Electrode Pair ◽

Alpha Power ◽

Short Term ◽

Good Reliability ◽

Data Set ◽

Alpha Asymmetry ◽

Eyes Closed ◽

Eeg Alpha

AbstractEEG resting-state alpha asymmetry is one of the most widely investigated forms of functional hemispheric asymmetries in both basic and clinical neuroscience. However, studies yield inconsistent results. One crucial prerequisite to obtain reproducible results is the reliability of the index of interest. There is a body of research suggesting a moderate-to-good reliability of EEG resting-state alpha asymmetry, but unfortunately sample sizes in these studies are typically small. This study presents the first large-scale short-term reliability study of frontal and parietal EEG resting-state alpha asymmetry. We used the Dortmund Vital Study data set containing 370 participants. In each participant, EEG resting state was recorded eight times, twice with their eyes opened, twice with their eyes-closed, each on two different EEG systems. We found good reliability of EEG alpha power and alpha asymmetry on both systems for electrode pairs. We also found that alpha power asymmetry reliability is higher in the eyes-closed condition than in the eyes-open condition. The frontomedial electrode pair showed weaker reliability than the frontolateral and parietal electrode pairs. Interestingly, we found no population-level alpha asymmetry in frontal electrodes, one of the most investigated electrode sites in alpha asymmetry research. In conclusion, our results suggest that while EEG alpha asymmetry is an overall reliable measure, frontal alpha asymmetry should be assessed using multiple electrode pairs.

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The effect of congenital blindness on resting-state functional connectivity revisited

Scientific Reports ◽

10.1038/s41598-021-91976-9 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Maria J. S. Guerreiro ◽

Madita Linke ◽

Sunitha Lingareddy ◽

Ramesh Kekunnaya ◽

Brigitte Röder

Keyword(s):

Functional Connectivity ◽

Resting State ◽

Visual Experience ◽

Brain Regions ◽

State Condition ◽

Resting State Functional Connectivity ◽

Congenital Blindness ◽

Eyes Closed ◽

Congenitally Blind ◽

Eyes Open

AbstractLower resting-state functional connectivity (RSFC) between ‘visual’ and non-‘visual’ neural circuits has been reported as a hallmark of congenital blindness. In sighted individuals, RSFC between visual and non-visual brain regions has been shown to increase during rest with eyes closed relative to rest with eyes open. To determine the role of visual experience on the modulation of RSFC by resting state condition—as well as to evaluate the effect of resting state condition on group differences in RSFC—, we compared RSFC between visual and somatosensory/auditory regions in congenitally blind individuals (n = 9) and sighted participants (n = 9) during eyes open and eyes closed conditions. In the sighted group, we replicated the increase of RSFC between visual and non-visual areas during rest with eyes closed relative to rest with eyes open. This was not the case in the congenitally blind group, resulting in a lower RSFC between ‘visual’ and non-‘visual’ circuits relative to sighted controls only in the eyes closed condition. These results indicate that visual experience is necessary for the modulation of RSFC by resting state condition and highlight the importance of considering whether sighted controls should be tested with eyes open or closed in studies of functional brain reorganization as a consequence of blindness.

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Three times NO: no relationship between frontal alpha asymmetry and depressive disorders in a multiverse analysis of three studies

10.1101/2020.06.30.180760 ◽

2020 ◽

Author(s):

Aleksandra Kołodziej ◽

Mikołaj Magnuski ◽

Anastasia Ruban ◽

Aneta Brzezicka

Keyword(s):

Data Analysis ◽

Analytical Approach ◽

Depressive Disorders ◽

Alpha Power ◽

Alpha Oscillations ◽

Alpha Asymmetry ◽

Eeg Data ◽

Theoretical Assumptions ◽

Frontal Alpha Asymmetry ◽

Eeg Alpha

AbstractFor decades, the frontal alpha asymmetry (FAA) - a disproportion in EEG alpha oscillations power between right and left frontal channels - has been one of the most popular measures of depressive disorders (DD) in electrophysiology studies. Patients with DD often manifest a left-sided FAA: relatively higher alpha power in the left versus right frontal lobe. Recently, however, multiple studies failed to confirm this effect, questioning its reproducibility. Our purpose is to thoroughly test the validity of FAA in depression by conducting a multiverse analysis - running many related analyses and testing the sensitivity of the effect to changes in the analytical approach - on data from three independent studies. Only two of the 81 analyses revealed significant results. We conclude the paper by discussing theoretical assumptions underlying the FAA and suggest a list of guidelines for improving and expanding the EEG data analysis in future FAA studies.

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Organization of Propagated Intrinsic Brain Activity in Individual Humans

Cerebral Cortex ◽

10.1093/cercor/bhz198 ◽

2019 ◽

Vol 30 (3) ◽

pp. 1716-1734 ◽

Cited By ~ 10

Author(s):

Ryan V Raut ◽

Anish Mitra ◽

Scott Marek ◽

Mario Ortega ◽

Abraham Z Snyder ◽

...

Keyword(s):

Resting State ◽

Large Scale ◽

Cortical Excitability ◽

Brain Activity ◽

Resting State Fmri ◽

Brain Regions ◽

Brain Organization ◽

Individual Level ◽

Slow Activity ◽

Lag Structure

Abstract Spontaneous infra-slow (<0.1 Hz) fluctuations in functional magnetic resonance imaging (fMRI) signals are temporally correlated within large-scale functional brain networks, motivating their use for mapping systems-level brain organization. However, recent electrophysiological and hemodynamic evidence suggest state-dependent propagation of infra-slow fluctuations, implying a functional role for ongoing infra-slow activity. Crucially, the study of infra-slow temporal lag structure has thus far been limited to large groups, as analyzing propagation delays requires extensive data averaging to overcome sampling variability. Here, we use resting-state fMRI data from 11 extensively-sampled individuals to characterize lag structure at the individual level. In addition to stable individual-specific features, we find spatiotemporal topographies in each subject similar to the group average. Notably, we find a set of early regions that are common to all individuals, are preferentially positioned proximal to multiple functional networks, and overlap with brain regions known to respond to diverse behavioral tasks—altogether consistent with a hypothesized ability to broadly influence cortical excitability. Our findings suggest that, like correlation structure, temporal lag structure is a fundamental organizational property of resting-state infra-slow activity.

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Assessing the Retest Reliability of Prefrontal EEG Markers of Brain Rhythm Slowing in the Eyes-Closed Resting State

Clinical EEG and Neuroscience ◽

10.1177/1550059420914832 ◽

2020 ◽

Vol 51 (5) ◽

pp. 348-356 ◽

Cited By ~ 1

Author(s):

Jungmi Choi ◽

Eunjo Lim ◽

Min-Goo Park ◽

Wonseok Cha

Keyword(s):

Resting State ◽

Brain Aging ◽

Low Cost ◽

Peak Frequency ◽

Brain Regions ◽

Median Frequency ◽

Brain Functions ◽

Eyes Closed ◽

Alpha Beta ◽

Prefrontal Lobe

Objective. We examined whether prefrontal lobe EEG markers of slower brain rhythms, which are correlated with functional brain aging, can reliably reflect those of other brain lobes, as measured by a multichannel device. Methods. EEG measurements were taken of 112 healthy individuals aged 20 to 69 years in the eyes-closed resting state. A 5-minute measurement was taken at 8 regions (Fp1, Fp2, F3, F4, T3, T4, O1, O2). Indices (median frequency [MDF], peak frequency [PF]) that quantitatively reflect the characteristics of EEG slowing, and traditional commonly used spectral indices (absolute powers as delta, theta, alpha, beta, and relative power as alpha-to-theta ratio [ATR]), were extracted from the EEG signals. For these indices, the differences between the prefrontal lobe and other areas were analyzed and the test-retest reproducibility was investigated. Results. The EEG slowing indicators showed high conformity over all brain lobes and stable reproducibility. On the other hand, the typical EEG spectral indicators delta, theta, alpha, beta, and ATR differed between brain regions. Conclusion. It was found that EEG slowing markers, which were used for assessing the aging or degeneration of brain functions, could be reliably extracted from a prefrontal EEG alone. Significance. These findings suggest that EEG prefrontal markers may reflect markers of other brain regions when a multi-channel device is used. Thus, this method may constitute a low-cost, wearable, wireless, easily accessible, and noninvasive tool for neurological assessment that could be used in the early detection of cognitive decline and in the prevention of dementia.

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Revisiting the deformation transients before the 2011 Tohoku-Oki Megathrust Earthquake with GPS

10.5194/egusphere-egu2020-21477 ◽

2020 ◽

Author(s):

Anne Socquet ◽

Lou Marill ◽

David Marsan ◽

Baptiste Rousset ◽

Mathilde Radiguet ◽

...

Keyword(s):

Time Series ◽

Large Scale ◽

Gravity Anomalies ◽

Seismogenic Zone ◽

Double Difference ◽

Ocean Bottom ◽

Slow Slip ◽

Short Term ◽

Data Set ◽

Systematic Analysis

<p>The precursory activity leading up to the Tohoku-Oki earthquake of 2011 has been suggested to feature both long- and short-term episodes of decoupling and suggests a particularly complex slow slip history. The analysis of the F3 solution of the Japanese GPS network suggested that an accelerated slip occurred in the deeper part of the seismogenic zone during the 10 years preceding the earthquake (Heki & Mitsui, EPSL 2013; Mavrommatis et al., GRL 2014; Yokota & Koketsu, Nat. Com. 2015). During the two months preceding the earthquake, no anomaly in the GPS position time series has been revealed so far, although several anomalous geophysical signals have been reported&#160;(an extended foreshock crisis near the future hypocenter (Kato et al., Science 2012), a synchronized increase of intermediate-depth background seismicity (Bouchon et al., Nat Geosc. 2016), a signal in ocean-bottom pressure gauges and on-land strainmeter time series (Ito et al., Tectonoph. 2013), and large scale gravity anomalies that suggest deep-seated slab deformation processes (Panet et al., Nat. Geosc. 2018&#160;; Wang & Burgmann, GRL 2019)).</p><p>We present novel results based on an independent analysis of the Japanese GPS data set. We perform a full reprocessing of the raw data with a double-difference approach, a systematic analysis of the obtained time-series, including noise characterization and network filtering, and make a robust assessment of long- and short-term tectonic aseismic transients preceding the Tohoku-Oki earthquake. An accelerated slip on the lower part of the seismogenic zone over the last decade is confirmed, not only below the epicenter of Tohoku-Oki earthquake but also further south, offshore Boso peninsula, which is a worrying sign of an on-going slow decoupling east of Tokyo. At shorter time-scale, first results seem compatible with a slow slip close to the epicenter initiating ~&#160;2 months before the mainshock.</p>

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Relation Between Frontal Alpha Asymmetry and Anxiety in Young Patients with Generalized Anxiety Disorder

PRILOZI ◽

10.1515/prilozi-2015-0064 ◽

2015 ◽

Vol 36 (2) ◽

pp. 157-177 ◽

Cited By ~ 2

Author(s):

Aneta Demerdzieva ◽

Nada Pop-Jordanova

Keyword(s):

Anxiety Disorder ◽

Generalized Anxiety Disorder ◽

Frontal Region ◽

Generalized Anxiety ◽

Alpha Power ◽

Alpha Asymmetry ◽

Eyes Closed ◽

Frontal Alpha Asymmetry ◽

Eyes Open ◽

The Right

Abstract Frontal alpha asymmetry (the relative difference in power between two signals in different hemispheres) has been suggested as biomarker for anxiety. The goal of this study was to evaluate alpha asymmetry in the frontal region for young people (7-18 years) with generalized anxiety disorder, diagnosed according to two statistic manuals (DMS-IV-R and ICD-10), the medical history and the neuropsychological assessment. The QEEG recording and analysis of the obtained results from alpha spectra power and log of alpha spectra power are made in four conditions (eyes open, eyes closed, VCPT and ACPT). The obtained results for alpha power in general showed higher cortical activity in the right hemisphere, associated with negative emotions. The calculated alpha asymmetry separate for eyes open, eyes closed, VCPT and ACPT conditions showed the right activation in all four conditions. In addition, the right frontal asymmetry was specific for the Fp1-Fp2 region, while a greater left frontal activation was recorded for the F7-F8 region. The log of alpha power in general was additionally analyzed. The calculated asymmetry score in general (in a way that the left log transformed score was subtracted from the right) confirmed a greater right activation. Testing the power of the whole alpha band (μV2) in general, for all four conditions and for frontal region confirmed the right alpha asymmetries in all participants. The right alpha asymmetry in the frontal region was specific only for the Fp1-Fp2 region (frontopolar region). The only greater left frontal activation was registered between the F7-F8 region. Our findings are supported by many other studies using specific localization methods like fMRI or LORETA source localization.

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Effects of familiarity with musical style on music-evoked emotions: An EEG study

10.31234/osf.io/vzny2 ◽

2021 ◽

Author(s):

Gladys Jiamin Heng ◽

Quek Hiok Chai ◽

SH Annabel Chen

Keyword(s):

Brain Activity ◽

Treatment Plan ◽

Brain Regions ◽

Alpha Power ◽

Musical Style ◽

Learning Mechanisms ◽

Behavioral Ratings ◽

Eyes Closed ◽

Beta Power ◽

Musical Excerpts

Learning mechanisms have been postulated to be one of the primary reasons why different individuals have similar or different emotional responses to music. While existing studies have largely examined mechanisms related to learning in terms of cultural familiarity or recognition, few studies have conceptualized it in terms of an individual’s level of familiarity with musical style, which could be a better reflection of an individual’s composite musical experiences. Therefore, the current study aimed to bridge this research gap by investigating the electrophysiological correlates of the effects of familiarity with musical style on music-evoked emotions. 49 non-musicians listened to 12 musical excerpts of a familiar musical style (Japanese animation soundtracks) and eight musical excerpts of an unfamiliar musical style (Greek Laïkó music) with their eyes closed as electroencephalography is being recorded. Participants rated their felt emotions after each musical excerpt is played. Behavioral ratings showed that music of the familiar musical style was felt as significantly more pleasant as compared to the unfamiliar musical style while no significant differences in arousal were observed. In terms of brain activity, music of the unfamiliar musical style elicited higher (1) theta power in all brain regions (including frontal midline), (2) alpha power in frontal region, and (3) beta power in fronto-temporo-occipital regions as compared to the familiar musical style. This is interpreted to reflect the need for greater attentional resources when listening to music of an unfamiliar style, where listeners are less familiar with the syntax and structure of the music as compared to music of a familiar style. In addition, classification analysis showed that unfamiliar and familiar musical styles can be distinguished with 67.86% accuracy, Thus, clinicians should consider the musical profile of the client when choosing an appropriate selection of music in the treatment plan, so as to achieve better efficacy.

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Spatiotemporal empirical mode decomposition of resting-state fMRI signals: application to global signal regression

10.1101/556555 ◽

2019 ◽

Cited By ~ 2

Author(s):

Narges Moradi ◽

Mehdy Dousty ◽

Roberto C. Sotero

Keyword(s):

Functional Connectivity ◽

Empirical Mode Decomposition ◽

Resting State ◽

Large Scale ◽

Pearson Correlation ◽

Brain Regions ◽

Connectivity Matrix ◽

Correlation Pattern ◽

Mode Decomposition ◽

Global Signal

AbstractResting-state functional connectivity MRI (rs-fcMRI) is a common method for mapping functional brain networks. However, estimation of these networks is affected by the presence of a common global systemic noise, or global signal (GS). Previous studies have shown that the common preprocessing steps of removing the GS may create spurious correlations between brain regions. In this paper, we decompose fMRI signals into 5 spatial and 3 temporal intrinsic mode functions (SIMF and TIMF, respectively) by means of the empirical mode decomposition (EMD), which is an adaptive data-driven method widely used to analyze nonlinear and nonstationary phenomena. For each SIMF, brain connectivity matrices were computed by means of the Pearson correlation between TIMFs of different brain areas. Thus, instead of a single connectivity matrix, we obtained 5 × 3 = 15 functional connectivity matrices. Given the high value obtained for large-scale topological measures such as transitivity, in the low spatial maps (SIMF3, SIMF4, and SIMF5), our results suggest that these maps can be considered as spatial global signal masks. Thus, the spatiotemporal EMD of fMRI signals automatically regressed out the GS, although, interestingly, the removed noisy component was voxel-specific. We compared the performance of our method with the conventional GS regression and to the results when the GS was not removed. While the correlation pattern identified by the other methods suffers from a low level of precision, our approach demonstrated a high level of accuracy in extracting the correct correlation between different brain regions.

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Heterogeneity of EEG resting-state brain networks in absolute pitch

10.1101/2020.05.03.063206 ◽

2020 ◽

Author(s):

Marielle Greber ◽

Carina Klein ◽

Simon Leipold ◽

Silvano Sele ◽

Lutz Jäncke

Keyword(s):

Functional Connectivity ◽

Auditory Cortex ◽

Resting State ◽

Large Scale ◽

Absolute Pitch ◽

Brain Regions ◽

Brain Network ◽

Higher Order ◽

Neural Basis ◽

Whole Brain

AbstractThe neural basis of absolute pitch (AP), the ability to effortlessly identify a musical tone without an external reference, is poorly understood. One of the key questions is whether perceptual or cognitive processes underlie the phenomenon as both sensory and higher-order brain regions have been associated with AP. One approach to elucidate the neural underpinnings of a specific expertise is the examination of resting-state networks.Thus, in this paper, we report a comprehensive functional network analysis of intracranial resting-state EEG data in a large sample of AP musicians (n = 54) and non-AP musicians (n = 51). We adopted two analysis approaches: First, we applied an ROI-based analysis to examine the connectivity between the auditory cortex and the dorsolateral prefrontal cortex (DLPFC) using several established functional connectivity measures. This analysis is a replication of a previous study which reported increased connectivity between these two regions in AP musicians. Second, we performed a whole-brain network-based analysis on the same functional connectivity measures to gain a more complete picture of the brain regions involved in a possibly large-scale network supporting AP ability.In our sample, the ROI-based analysis did not provide evidence for an AP-specific connectivity increase between the auditory cortex and the DLPFC. In contrast, the whole-brain analysis revealed three networks with increased connectivity in AP musicians comprising nodes in frontal, temporal, subcortical, and occipital areas. Commonalities of the networks were found in both sensory and higher-order brain regions of the perisylvian area. Further research will be needed to confirm these exploratory results.

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