Predicting Depression Symptoms in Families at Risk for Depression: Interrelations of Posterior EEG Alpha and Religion/Spirituality.

BACKGROUND: Posterior EEG alpha has been identified as a putative biomarker of clinical outcomes in major depression (MDD). Separately, personal importance of religion and spirituality (R/S) has been shown to provide protective benefits for individuals at high familial risk for MDD. This study directly explored the joint value of posterior alpha and R/S on predicting clinical health outcomes of depression. METHODS: Using a mixed-effects model approach, we obtained virtual estimates of R/S at age 21 using longitudinal data collected at 5 timepoints spanning 25 years. Current source density and frequency principal component analysis was used to quantify posterior alpha in 72-channel resting EEG (eyes open/closed). Depression severity was measured between 5 and 10 years after EEG collection using PHQ-9 and IDAS-GD scales. RESULTS: Greater R/S (p = .008, η2p = 0.076) and higher alpha (p = .02, η2p = 0.056) were separately associated with fewer symptoms across scales. However, an interaction between alpha and R/S (p = .02, η2p = 0.062) was observed, where greater R/S predicted fewer symptoms with low alpha but high alpha predicted fewer symptoms with lower R/S. LIMITATIONS: Small-to-medium effect sizes and homogeneity of sample demographics caution overall interpretation and generalizability. CONCLUSIONS: Findings revealed a complementary role of R/S and alpha in that either variable exerted protective effects only if the other was present at low levels. These findings confirm the relevance of R/S importance and alpha oscillations as predictors of depression symptom severity. More research is needed on the neurobiological mechanism underlying the protective effects of R/S importance for MDD.

Frontal theta and posterior alpha in resting EEG: A critical examination of convergent and discriminant validity.

Prior research has identified two resting EEG biomarkers with potential for predicting functional outcomes in depression: theta current density in frontal brain regions (especially rostral anterior cingulate cortex) and alpha power over posterior scalp regions. As little is known about the discriminant and convergent validity of these putative biomarkers, a thorough evaluation of these psychometric properties was conducted toward the goal of improving clinical utility of these markers. Resting 71-channel EEG recorded from 35 healthy adults at two sessions (1-week retest) were used to systematically compare different quantification techniques for theta and alpha sources at scalp (surface Laplacian or current source density [CSD]) and brain (distributed inverse; exact low resolution electromagnetic tomography [eLORETA]) level. Signal quality was evaluated with signal-to-noise ratio, participant-level spectra, and frequency PCA covariance decomposition. Convergent and discriminant validity were assessed within a multitrait-multimethod framework. Posterior alpha was reliably identified as two spectral components, each with unique spatial patterns and condition effects (eyes open/closed), high signal quality, and good convergent and discriminant validity. In contrast, frontal theta was characterized by one low-variance component, low signal quality, lack of a distinct spectral peak, and mixed validity. Correlations between candidate biomarkers suggest that posterior alpha components constitute reliable, convergent, and discriminant biometrics in healthy adults. Component-based identification of spectral activity (CSD/eLORETA-fPCA) was superior to fixed, a priori frequency bands. Improved quantification and conceptualization of frontal theta is necessary to determine clinical utility.

Current Understanding of Religion, Spirituality, and Their Neurobiological Correlates.

Religion and spirituality (R/S) have been prominent aspects of most human cultures through the ages; however, scientific inquiry into this phenomenon has been limited. We conducted a systematic literature review of research on the neurobiological correlates of R/S, which resulted in 25 reports studying primarily R/S with electroencephalography, structural neuroimaging (MRI), and functional neuroimaging (fMRI, PET). These studies investigated a wide range of religions (e.g., Christianity, Buddhism, Islam) and R/S states and behaviors (e.g., resting state, prayer, judgments) and employed a wide range of methodologies, some of which (e.g., no control group, varying measures of religiosity, small sample sizes) raise concerns about the validity of the results. Despite these limitations, the findings of these studies collectively suggest that the experience of R/S has specific neurobiological correlates and that these correlates are distinct from non-R/S counterparts. The findings implicate several brain regions potentially associated with R/S development and behavior, including the medial frontal cortex, orbitofrontal cortex, precuneus, posterior cingulate cortex, default mode network, and caudate. This research may suggest future clinical applications and interventions related to R/S and various disorders, including mood, anxiety, psychotic, pain, and vertiginous disorders. Further studies with more rigorous study designs are warranted to elucidate the neurobiological mechanisms of R/S and their potential clinical applications.

Family Risk for Depression and Prioritization of Religion or Spirituality: Early Neurophysiological Modulations of Motivated Attention.

The personal importance of religion or spirituality (R/S) has been associated with a lower risk for major depression (MDD), suicidal behavior, reduced cortical thinning and increased posterior EEG alpha, which has also been linked to antidepressant treatment response in MDD. Building on prior event-related potential (ERP) findings using an emotional hemifield paradigm, this study examined whether abnormal early (preconscious) responsivity to negative arousing stimuli, which is indicative of right parietotemporal dysfunction in both MDD patients and individuals at clinical high risk for MDD, is likewise moderated by R/S. We reanalyzed 72-channel ERP data from 127 individuals at high or low family risk for MDD (Kayser et al., 2017, NeuroImage Clin. 14, 692-707) after R/S stratification (low R/S importance, low/high risk, n = 38/61; high R/S importance, n = 15/13). ERPs were transformed to reference-free current source density (CSD) and quantified by temporal principal components analysis (tPCA). This report focused on N2 sink (peak latency 212 ms), the earliest prominent CSD-tPCA component previously found to be sensitive to emotional content. While overall N2 sink reflected activation of occipitotemporal cortex (prestriate/cuneus), as estimated via a distributed inverse solution, affective significance was marked by a relative (i.e., superimposed) positivity. Statistical analyses employed both non-parametric permutation tests and repeated measures ANOVA for mixed factorial designs with unstructured covariance matrix, including sex, age, and clinical covariates. Participants with low R/S importance, independent of risk status, showed greater ERP responsivity to negative than neutral stimuli, particularly over the right hemisphere. In contrast, early emotional ERP responsivity and asymmetry was substantially reduced for high risk individuals with high R/S importance, however, enhanced for low risk individuals with high R/S importance. Hemifield modulations of these effects (i.e., emotional ERP enhancements with left visual field/right hemisphere stimulus presentations) further corroborated these observations. Results suggest down-regulation of a right-lateralized network for salience detection at an early processing stage in high risk and high R/S importance individuals, presumably to prevent overactivation of ventral brain regions further downstream. These findings may point to a neurophysiological mechanism underlying resilience of families at risk for depression with high R/S prioritization.

Resting EEG Measures of Brain Arousal in a Multisite Study of Major Depression.

Several studies have found upregulated brain arousal during 15-minute EEG recordings at rest in depressed patients. However, studies based on shorter EEG recording intervals are lacking. Here we aimed to compare measures of brain arousal obtained from 2-minute EEGs at rest under eyes-closed condition in depressed patients and healthy controls in a multisite project-Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care (EMBARC). We expected that depressed patients would show stable and elevated brain arousal relative to controls. Eighty-seven depressed patients and 36 healthy controls from four research sites in the United States were included in the analyses. The Vigilance Algorithm Leipzig (VIGALL) was used for the fully automatic classification of EEG-vigilance stages (indicating arousal states) of 1-second EEG segments; VIGALL-derived measures of brain arousal were calculated. We found that depressed patients scored higher on arousal stability ( Z = -2.163, P = .015) and A stages (dominant alpha activity; P = .027) but lower on B1 stages (low-voltage non-alpha activity, P = .008) compared with healthy controls. No significant group differences were observed in Stage B2/3. In summary, we were able to demonstrate stable and elevated brain arousal during brief 2-minute recordings at rest in depressed patients. Results set the stage for examining the value of these measures for predicting clinical response to antidepressants in the entire EMBARC sample and evaluating whether an upregulated brain arousal is particularly characteristic for responders to antidepressants.

Temporal stability of posterior EEG alpha over twelve years.

OBJECTIVE: We previously identified posterior EEG alpha as a potential biomarker for antidepressant treatment response. To meet the definition of a trait biomarker or endophenotype, it should be independent of the course of depression. Accordingly, this report evaluated the temporal stability of posterior EEG alpha at rest. METHODS: Resting EEG was recorded from 70 participants (29 male; 46 adults), during testing sessions separated by 12 ±â€¯1.1 years. EEG alpha was identified, separated and quantified using reference-free methods that combine current source density (CSD) with principal components analysis (PCA). Measures of overall (eyes closed-plus-open) and net (eyes closed-minus-open) posterior alpha amplitude and asymmetry were compared across testing sessions. RESULTS: Overall alpha was stable for the full sample (Spearman-Brown [rSB] = .834, Pearson's r = .718), and showed excellent reliability for adults (rSB = .918; r = 0.848). Net alpha showed acceptable reliability for adults (rSB = .750; r = .600). Hemispheric asymmetries (right-minus-left hemisphere) of posterior overall alpha showed significant correlations, but revealed acceptable reliability only for adults (rSB = .728; r = .573). Findings were highly comparable between 29 male and 41 female participants. CONCLUSIONS: Overall posterior EEG alpha amplitude is reliable over long time intervals in adults. SIGNIFICANCE: The temporal stability of posterior EEG alpha oscillations at rest over long time intervals is indicative of an individual trait.

Pretreatment Rostral Anterior Cingulate Cortex Theta Activity in Relation to Symptom Improvement in Depression: A Randomized Clinical Trial.

Importance: Major depressive disorder (MDD) remains challenging to treat. Although several clinical and demographic variables have been found to predict poor antidepressant response, these markers have not been robustly replicated to warrant implementation in clinical care. Increased pretreatment rostral anterior cingulate cortex (rACC) theta activity has been linked to better antidepressant outcomes. However, no prior study has evaluated whether this marker has incremental predictive validity over clinical and demographic measures. Objective: To determine whether increased pretreatment rACC theta activity would predict symptom improvement regardless of randomization arm. Design, Setting, and Participants: A multicenter randomized clinical trial enrolled outpatients without psychosis and with chronic or recurrent MDD between July 29, 2011, and December 15, 2015 (Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care [EMBARC]). Patients were consecutively recruited from 4 university hospitals: 634 patients were screened, 296 were randomized to receive sertraline hydrochloride or placebo, 266 had electroencephalographic (EEG) recordings, and 248 had usable EEG data. Resting EEG data were recorded at baseline and 1 week after trial onset, and rACC theta activity was extracted using source localization. Intent-to-treat analysis was conducted. Data analysis was performed from October 7, 2016, to January 19, 2018. Interventions: An 8-week course of sertraline or placebo. Main Outcomes and Measures: The 17-item Hamilton Rating Scale for Depression score (assessed at baseline and weeks 1, 2, 3, 4, 6, and 8). Results: The 248 participants (160 [64.5%] women, 88 [35.5%] men) with usable EEG data had a mean (SD) age of 36.75 (13.15) years. Higher rACC theta activity at both baseline (b = -1.05; 95% CI, -1.77 to -0.34; P = .004) and week 1 (b = -0.83; 95% CI, -1.60 to -0.06; P < .04) predicted greater depressive symptom improvement, even when controlling for clinical and demographic variables previously linked with treatment outcome. These effects were not moderated by treatment arm. The rACC theta marker, in combination with clinical and demographic variables, accounted for an estimated 39.6% of the variance in symptom change (with 8.5% of the variance uniquely attributable to the rACC theta marker). Conclusions and Relevance: Increased pretreatment rACC theta activity represents a nonspecific prognostic marker of treatment outcome. This is the first study to date to demonstrate that rACC theta activity has incremental predictive validity. Trial Registration: clinicaltrials.gov Identifier: NCT01407094.

Stability of Cortical Thinning in Persons at Increased Familial Risk for Major Depressive Disorder Across 8 Years.

BACKGROUND: A biological marker of vulnerability should precede onset of illness and be independent of disease course. We previously reported that cortical thinning may serve as a potential biomarker for risk for familial depression. We now test stability of the cortical thinning across 8 years, and whether thinning mediates associations between familial risk and depressive traits. METHOD: Participants were from a 3-generation family study of depression, where 2nd and 3rd generation offspring were characterized as being at high- or low-risk for depression based on the presence/absence of major depression in the 1st generation. The analysis includes 82 offspring with anatomical MRI scans across two assessment waves, 7.8 (S.D.1.3, range: 5.2-10.9) years apart. RESULTS: High-risk offspring had thinner bilateral superior and middle frontal gyri, and left inferior parietal lobule, at both time-points. High intra-subject correlation (0.60

Neuroanatomical correlates of familial risk-for-depression and religiosity/spirituality.

OBJECTIVE: To examine potential neural substrates that underlie the interplay between religiosity/spirituality and risk-for-depression. A new wave of data from a longitudinal, three generation study of individuals at high risk for depression is presented. In addition to providing new longitudinal data, we extend previous findings by employing additional (surface-based) methods for examining cortical volume. MEASURES PARTICIPANTS AND METHODS: Magnetic resonance imaging (MRI) scans were collected on 106 second and third generation family members at high or low risk for major depression defined by the presence or absence of depression in the first generation. Religiosity/spirituality measures were collected at the same time as the MRI scans and comprised self-report ratings of personal religious/spiritual (R/S) importance and frequency of religious attendance. Analyses were carried out with Freesurfer. Interactive effects of religiosity/spirituality and risk-for-depression were examined on measures of cortical thickness and cortical surface area. RESULTS: A high degree of belief in the importance of religion/spirituality was associated with both a thicker cortex and a larger pial surface area in persons at high risk for familial depression. No significant association was found between cortical regions and religious attendance in either risk group. CONCLUSIONS AND RELEVANCE: The results support previous findings of an association between R/S importance and cortical thickness in individuals at high risk for depression, and extend the findings to include an association between R/S importance and greater pial surface area. Moreover, the findings suggest these cortical changes may confer protective benefits to religious/spiritual individuals at high risk for depression.

Motivated attention and family risk for depression: Neuronal generator patterns at scalp elicited by lateralized aversive pictures reveal blunted emotional responsivity.

Behavioral and electrophysiologic evidence suggests that major depression (MDD) involves right parietotemporal dysfunction, a region activated by arousing affective stimuli. Building on prior event-related potential (ERP) findings (Kayser et al. 2016 NeuroImage 142:337-350), this study examined whether these abnormalities also characterize individuals at clinical high risk for MDD. We systematically explored the impact of family risk status and personal history of depression and anxiety on three distinct stages of emotional processing comprising the late positive potential (LPP). ERPs (72 channels) were recorded from 74 high and 53 low risk individuals (age 13-59 years, 58 male) during a visual half-field paradigm using highly-controlled pictures of cosmetic surgery patients showing disordered (negative) or healed (neutral) facial areas before or after treatment. Reference-free current source density (CSD) transformations of ERP waveforms were quantified by temporal principal components analysis (tPCA). Component scores of prominent CSD-tPCA factors sensitive to emotional content were analyzed via permutation tests and repeated measures ANOVA for mixed factorial designs with unstructured covariance matrix, including gender, age and clinical covariates. Factor-based distributed inverse solutions provided descriptive estimates of emotional brain activations at group level corresponding to hierarchical activations along ventral visual processing stream. Risk status affected emotional responsivity (increased positivity to negative-than-neutral stimuli) overlapping early N2 sink (peak latency 212 ms), P3 source (385 ms), and a late centroparietal source (630 ms). High risk individuals had reduced right-greater-than-left emotional lateralization involving occipitotemporal cortex (N2 sink) and bilaterally reduced emotional effects involving posterior cingulate (P3 source) and inferior temporal cortex (630 ms) when compared to those at low risk. While the early emotional effects were enhanced for left hemifield (right hemisphere) presentations, hemifield modulations did not differ between risk groups, suggesting top-down rather than bottom-up effects of risk. Groups did not differ in their stimulus valence or arousal ratings. Similar effects were seen for individuals with a lifetime history of depression or anxiety disorder in comparison to those without. However, there was no evidence that risk status and history of MDD or anxiety disorder interacted in their impact on emotional responsivity, suggesting largely independent attenuation of attentional resource allocation to enhance perceptual processing of motivationally salient stimuli. These findings further suggest that a deficit in motivated attention preceding conscious awareness may be a marker of risk for depression.

Association of posterior EEG alpha with prioritization of religion or spirituality: A replication and extension at 20-year follow-up.

A prior report (Tenke et al., 2013 Biol. Psychol. 94:426-432) found that participants who rated religion or spirituality (R/S) highly important had greater posterior alpha after 10 years compared to those who did not. Participants who subsequently lowered their rating also had prominent alpha, while those who increased their rating did not. Here we report EEG findings 20 years after initial assessment. Clinical evaluations and R/S ratings were obtained from 73 (52 new) participants in a longitudinal study of family risk for depression. Frequency PCA of current source density transformed EEG concisely quantified posterior alpha. Those who initially rated R/S as highly important had greater alpha compared to those who did not, even if their R/S rating later increased. Furthermore, changes in religious denomination were associated with decreased alpha. Results suggest the possibility of a critical stage in the ontogenesis of R/S that is linked to posterior resting alpha.

Demonstrating test-retest reliability of electrophysiological measures for healthy adults in a multisite study of biomarkers of antidepressant treatment response.

Growing evidence suggests that loudness dependency of auditory evoked potentials (LDAEP) and resting EEG alpha and theta may be biological markers for predicting response to antidepressants. In spite of this promise, little is known about the joint reliability of these markers, and thus their clinical applicability. New standardized procedures were developed to improve the compatibility of data acquired with different EEG platforms, and used to examine test-retest reliability for the three electrophysiological measures selected for a multisite project-Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care (EMBARC). Thirty-nine healthy controls across four clinical research sites were tested in two sessions separated by about 1 week. Resting EEG (eyes-open and eyes-closed conditions) was recorded and LDAEP measured using binaural tones (1000 Hz, 40 ms) at five intensities (60-100 dB SPL). Principal components analysis of current source density waveforms reduced volume conduction and provided reference-free measures of resting EEG alpha and N1 dipole activity to tones from auditory cortex. Low-resolution electromagnetic tomography (LORETA) extracted resting theta current density measures corresponding to rostral anterior cingulate (rACC), which has been implicated in treatment response. There were no significant differences in posterior alpha, N1 dipole, or rACC theta across sessions. Test-retest reliability was .84 for alpha, .87 for N1 dipole, and .70 for theta rACC current density. The demonstration of good-to-excellent reliability for these measures provides a template for future EEG/ERP studies from multiple testing sites, and an important step for evaluating them as biomarkers for predicting treatment response.

Neuronal generator patterns at scalp elicited by lateralized aversive pictures reveal consecutive stages of motivated attention.

Event-related potential (ERP) studies have provided evidence for an allocation of attentional resources to enhance perceptual processing of motivationally salient stimuli. Emotional modulation affects several consecutive components associated with stages of affective-cognitive processing, beginning as early as 100-200ms after stimulus onset. In agreement with the notion that the right parietotemporal region is critically involved during the perception of arousing affective stimuli, some ERP studies have reported asymmetric emotional ERP effects. However, it is difficult to separate emotional from non-emotional effects because differences in stimulus content unrelated to affective salience or task demands may also be associated with lateralized function or promote cognitive processing. Other concerns pertain to the operational definition and statistical independence of ERP component measures, their dependence on an EEG reference, and spatial smearing due to volume conduction, all of which impede the identification of distinct scalp activation patterns associated with affective processing. Building on prior research using a visual half-field paradigm with highly controlled emotional stimuli (pictures of cosmetic surgery patients showing disordered [negative] or healed [neutral] facial areas before or after treatment), 72-channel ERPs recorded from 152 individuals (ages 13-68years; 81 female) were transformed into reference-free current source density (CSD) waveforms and submitted to temporal principal components analysis (PCA) to identify their underlying neuronal generator patterns. Using both nonparametric randomization tests and repeated measures ANOVA, robust effects of emotional content were found over parietooccipital regions for CSD factors corresponding to N2 sink (212ms peak latency), P3 source (385ms) and a late centroparietal source (630ms), all indicative of greater positivity for negative than neutral stimuli. For the N2 sink, emotional effects were right-lateralized and modulated by hemifield, with larger amplitude and asymmetry for left hemifield (right hemisphere) presentations. For all three factors, more positive amplitudes at parietooccipital sites were associated with increased ratings of negative valence and greater arousal. Distributed inverse solutions of the CSD-PCA-based emotional effects implicated a sequence of maximal activations in right occipitotemporal cortex, bilateral posterior cingulate cortex, and bilateral inferior temporal cortex. These findings are consistent with hierarchical activations of the ventral visual pathway reflecting subsequent processing stages in response to motivationally salient stimuli.

Neural Correlates of Three Promising Endophenotypes of Depression: Evidence from the EMBARC Study.

Major depressive disorder (MDD) is clinically, and likely pathophysiologically, heterogeneous. A potentially fruitful approach to parsing this heterogeneity is to focus on promising endophenotypes. Guided by the NIMH Research Domain Criteria initiative, we used source localization of scalp-recorded EEG resting data to examine the neural correlates of three emerging endophenotypes of depression: neuroticism, blunted reward learning, and cognitive control deficits. Data were drawn from the ongoing multi-site EMBARC study. We estimated intracranial current density for standard EEG frequency bands in 82 unmedicated adults with MDD, using Low-Resolution Brain Electromagnetic Tomography. Region-of-interest and whole-brain analyses tested associations between resting state EEG current density and endophenotypes of interest. Neuroticism was associated with increased resting gamma (36.5-44 Hz) current density in the ventral (subgenual) anterior cingulate cortex (ACC) and orbitofrontal cortex (OFC). In contrast, reduced cognitive control correlated with decreased gamma activity in the left dorsolateral prefrontal cortex (dlPFC), decreased theta (6.5-8 Hz) and alpha2 (10.5-12 Hz) activity in the dorsal ACC, and increased alpha2 activity in the right dlPFC. Finally, blunted reward learning correlated with lower OFC and left dlPFC gamma activity. Computational modeling of trial-by-trial reinforcement learning further indicated that lower OFC gamma activity was linked to reduced reward sensitivity. Three putative endophenotypes of depression were found to have partially dissociable resting intracranial EEG correlates, reflecting different underlying neural dysfunctions. Overall, these findings highlight the need to parse the heterogeneity of MDD by focusing on promising endophenotypes linked to specific pathophysiological abnormalities.

Posterior EEG alpha at rest and during task performance: Comparison of current source density and field potential measures.

Resting and task-related EEG alpha are used in studies of cognition and psychopathology. Although Laplacian methods have been applied, apprehensions about loss of global activity dissuade researchers from greater use except as a supplement to reference-dependent measures. The unfortunate result has been continued reliance on reference strategies that differ across labs, and a systemic preference for a montage-dependent average reference over true reference-free measures. We addressed these concerns by comparing resting- and task-related EEG alpha using three EEG transformations: nose- (NR) and average-referenced (AR) EEG, and the corresponding CSD. Amplitude spectra of resting and prestimulus task-related EEG (novelty oddball) and event-related spectral perturbations were scaled to equate each transformation. Alpha measures quantified for 8-12 Hz bands were: 1) net amplitude (eyes-closed minus eyes-open) and 2) overall amplitude (eyes-closed plus eyes-open); 3) task amplitude (prestimulus baseline) and 4) task event-related desynchronization (ERD). Mean topographies unambiguously represented posterior alpha for overall, net and task, as well as poststimulus alpha ERD. Topographies were similar for the three transformations, but differed in dispersion, CSD being sharpest and NR most broadly distributed. Transformations also differed in scale, AR showing less attenuation or spurious secondary maxima at anterior sites, consistent with simulations of distributed posterior generators. Posterior task alpha and alpha ERD were positively correlated with overall alpha, but not with net alpha. CSD topographies consistently and appropriately represented posterior EEG alpha for all measures.

Surface Laplacians (SL) and phase properties of EEG rhythms: Simulated generators in a volume-conduction model.

Surface Laplacian (SL) methods offer advantages in spectral analysis owing to the well-known implications of volume conduction. Although recognition of the superiority of SL over reference-dependent measures is widespread, well-reasoned cautions have precluded their universal adoption. Notably, the expected selectivity of SL for superficial rather than deep generators has relegated SL to the role of an add-on to conventional analyses, rather than as an independent area of inquiry, despite empirical findings supporting the consistency and replicability of physiological effects of interest. It has also been reasoned that the contrast-enhancing effects of SL necessarily make it insensitive to broadly distributed generators, including those suspected for oscillatory rhythms such as EEG alpha. These concerns are further exacerbated for phase-sensitive measures (e.g., phase-locking, coherence), where key features of physiological generators have yet to be evaluated. While the neuronal generators of empirically-derived EEG measures cannot be precisely known due to the inverse problem, simple dipole generator configurations can be simulated using a 4-sphere head model and linearly combined. We simulated subdural and deep generators and distributed dipole layers using sine and cosine waveforms, quantified at 67-scalp sites corresponding to those used in previous research. Reference-dependent (nose, average, mastoids reference) EEG and corresponding SL topographies were used to probe signal fidelity in the topography of the measured amplitude spectra, phase and coherence of sinusoidal stimuli at and between "active" recording sites. SL consistently outperformed the conventional EEG measures, indicating that continued reluctance by the research community is unfounded.

Issues and considerations for using the scalp surface Laplacian in EEG/ERP research: A tutorial review.

Despite the recognition that the surface Laplacian may counteract adverse effects of volume conduction and recording reference for surface potential data, electrophysiology as a discipline has been reluctant to embrace this approach for data analysis. The reasons for such hesitation are manifold but often involve unfamiliarity with the nature of the underlying transformation, as well as intimidation by a perceived mathematical complexity, and concerns of signal loss, dense electrode array requirements, or susceptibility to noise. We revisit the pitfalls arising from volume conduction and the mandated arbitrary choice of EEG reference, describe the basic principle of the surface Laplacian transform in an intuitive fashion, and exemplify the differences between common reference schemes (nose, linked mastoids, average) and the surface Laplacian for frequently-measured EEG spectra (theta, alpha) and standard event-related potential (ERP) components, such as N1 or P3. We specifically review common reservations against the universal use of the surface Laplacian, which can be effectively addressed by employing spherical spline interpolations with an appropriate selection of the spline flexibility parameter and regularization constant. We argue from a pragmatic perspective that not only are these reservations unfounded but that the continued predominant use of surface potentials poses a considerable impediment on the progress of EEG and ERP research.

Hemifield-dependent N1 and event-related theta/delta oscillations: An unbiased comparison of surface Laplacian and common EEG reference choices.

Surface Laplacian methodology has been used to reduce the impact of volume conduction and arbitrary choice of EEG recording reference for the analysis of surface potentials. However, the empirical implications of employing these different transformations to the same EEG data remain obscure. This study directly compared the statistical effects of four commonly-used (nose, linked mastoids, average) or recommended (reference electrode standardization technique [REST]) references and their spherical spline current source density (CSD) transformation for a large data set stemming from a well-understood experimental manipulation. ERPs (72 sites) recorded from 130 individuals during a visual half-field paradigm with highly-controlled emotional stimuli were characterized by mid-parietooccipital N1 (125 ms peak latency) and event-related synchronization (ERS) of theta/delta (160 ms), which were most robust over the contralateral hemisphere. All five data transformations were rescaled to the same covariance and submitted to a single temporal or time-frequency PCA (Varimax) to yield simplified estimates of N1 or theta/delta ERS. Unbiased nonparametric permutation tests revealed that these hemifield-dependent asymmetries were by far most focal and prominent for CSD data, despite all transformations showing maximum effects at mid-parietooccipital sites. Employing smaller subsamples (signal-to-noise) or window-based ERP/ERS amplitudes did not affect these comparisons. Furthermore, correlations between N1 and theta/delta ERS at these sites were strongest for CSD and weakest for nose-referenced data. Contrary to the common notion that the spatial high pass filter properties of a surface Laplacian reduce important contributions of neuronal generators to the EEG signal, the present findings demonstrate that instead volume conduction inherent in surface potentials weakens the representation of neuronal activation patterns at scalp that directly reflect regional brain activity.

Identifying electrode bridging from electrical distance distributions: a survey of publicly-available EEG data using a new method.

OBJECTIVE: EEG topographies may be distorted by electrode bridges, typically caused by electrolyte spreading between adjacent electrodes. We therefore sought to determine the prevalence of electrode bridging and its potential impact on the EEG literature. METHODS: Five publicly-available EEG datasets were evaluated for evidence of bridging using a new screening method that employs the temporal variance of pairwise difference waveforms (electrical distance). Distinctive characteristics of electrical distance frequency distributions were used to develop an algorithm to identify electrode bridges in datasets with different montages (22-64 channels) and noise properties. RESULTS: The extent of bridging varied substantially across datasets: 54% of EEG recording sessions contained an electrode bridge, and the mean percentage of bridged electrodes in a montage was as high as 18% in one of the datasets. Furthermore, over 40% of the recording channels were bridged in 9 of 203 sessions. These findings were independently validated by visual inspection. CONCLUSIONS: The new algorithm conveniently, efficiently, and reliably identified electrode bridges across different datasets and recording conditions. Electrode bridging may constitute a substantial problem for some datasets. SIGNIFICANCE: Given the extent of the electrode bridging across datasets, this problem may be more widespread than commonly thought. However, when used as an automatic screening routine, the new algorithm will prevent pitfalls stemming from unrecognized electrode bridges.