Functional but not structural subgenual prefrontal cortex abnormalities in melancholia

Highfield imaging of the subgenual anterior cingulate cortex in uni- and bipolar depression

Background

The subgenual Anterior Cingulate Cortex (sgACC), as a part of the Anterior Cingulate Cortex and the limbic system plays a crucial role in mood regulation. Previous structural and functional brain imaging studies of the sgACC have revealed alterations of Gray Matter (GM) volumes and Blood Oxygenation Level Dependent signals (BOLD) in patients with Major Depressive Disorder (MDD) and Bipolar Disorder (BD), suggesting potential biomarker traits for affective disorders.

Method

In this study we investigated the gray matter volume of the sgACC in 3 different patient groups: 40 MDD patients, of which 20 were medicated (MDDm) and 20 were unmedicated (MDDu), and 21 medicated BD patients, and compared them with 23 healthy volunteers. We examined GM volume alteration using high-resolution 7T Magnetic Resonance Imaging (MRI) which produced quantitative maps of the spin-lattice relaxation time (T1). T1 maps provide high contrast between gray and white matter, and at 7 Tesla voxels with submillimeter resolution can be acquired in a reasonable scan time. We developed a semi-automatic segmentation protocol based on refined landmarks derived from previous volumetric studies using quantitative T1 maps as raw input data for automatic tissue segmentation of GM, WM and CSF (cerebrospinal fluid) tissue. The sgACC ROI was then superimposed on these tissue probability maps and traced manually by two independent raters (F.B., M.M.) following our semi-automatic segmentation protocol. Interrater reliability was calculated on a subset of 10 brain scans for each hemisphere, showing an Intra-Class Correlation coefficient (ICC) r = 0.96 for left sgACC and r = 0.84 for right sgACC respectively. In summary, we have developed a reproducible and reliable semi-automatic segmentation protocol to measure gray matter volume in the sgACC. Based on previous findings from meta-analyses on morphometric studies of the sgACC, we hypothesized that patients with MDD would have lower gray matter sgACC volumes compared to healthy subjects.

Results

Post-hoc analysis revealed smaller subgenual volumes for the left hemisphere in both the medicated (MDDm) and non-medicated (MDDu) group versus healthy controls (p = .001, p = .008) respectively. For the right hemisphere, the (MDDu) and BD group exhibited significantly lower subgenual volumes than healthy controls (p < .001, p = .004) respectively.

Conclusion

To our knowledge, this is the first morphometric MRI study using T1 maps obtained in high-resolution 7 Tesla MRI to compare MDD and BD patients with healthy controls.

Restricted Cortical Activity Involving Parietal Lobe and Sublobar Region Leads to Generalized Spike-Wave Discharges of Juvenile Myoclonic Epilepsy: Evidence from an EEG Source Localization Study

BACKGROUND

Previous studies have localized the origin of "generalized" spike-wave discharges of idiopathic generalized epilepsies to specific brain regions. Although there are studies in juvenile myoclonic epilepsy (JME) which have investigated the origin of spike-wave discharges, reports on the propagation of discharges are sparse.

OBJECTIVE

The current study investigated the propagation of spike-wave discharges in JME, which was investigated by statistically comparing the electroencephalography (EEG)-derived cortical source activity during (a) various phases of spike-wave discharge versus background (eyes closed) activity, and (b) various phases of the first spike wave versus the corresponding phase of subsequent spike waves.

MATERIAL AND METHODS

Fourteen patients with JME who had generalized spike/polyspike and slow wave discharges in interictal EEG were included in the study. A total of 179 spike waves (first discernible spike wave - 55; subsequent spike waves - 124) were selected for source localization. Source analysis was carried out using exact low-resolution electromagnetic tomography (eLORETA). Statistical analyses to estimate the probability distribution of differences in cortical activity between (a) eight phases of epileptic discharge versus background (eyes closed) activity and (b) phases of the first spike wave versus the corresponding phases of subsequent spike waves were performed by paired t-tests and corrected for multiple testing using LORETA-KEY software.

RESULTS

Widespread activation of cortical voxels (more than 94%) was observed during all phases of epileptic discharge except the initial phase (pre-first spike) and terminal phase (post-peak of the subsequent wave). The parietal lobe, which was the most activated lobe during the pre-first spike, was found to be the least activated during the post-peak of first and subsequent waves. More than 93% of voxels in the sublobar region were consistently activated during all eight phases of discharge.

CONCLUSION

The study findings suggest that the activity generated from the restricted brain network involving parietal lobe could be propagated through sublobar structures to cause widespread cortical activation during the subsequent phases of the spike-wave cycle.

Differentiating melancholic and non-melancholic depression via biological markers: A review

OBJECTIVES

Melancholia is a severe form of depression that is typified by greater genetic and biological influence, distinct symptomatology, and preferential response to physical treatment. This paper sought to broadly overview potential biomarkers of melancholia to benefit differential diagnosis, clinical responses and treatment outcomes. Given nuances in distinguishing melancholia as its own condition from other depressive disorder, we emphasised studies directly comparing melancholic to non-melancholic depression.

METHODS

A comprehensive literature search was conducted. Key studies were identified and summarised qualitatively.

RESULTS

105 studies in total were identified. These studies covered a wide variety of biomarkers, and largely fell into three domains: endocrinological (especially cortisol levels, particularly in response to the dexamethasone suppression test), neurological, and immunological (particularly inflammatory markers). Less extensive evidence also exists for metabolic, genetic, and cardiovascular markers.

CONCLUSIONS

Definitive conclusions were predominantly limited due to substantial heterogeneity in how included studies defined melancholia. Furthermore, this heterogeneity could be responsible for the between- and within-group variability observed in the candidate biomarkers that were examined. Therefore, clarifying these definitional parameters may help identify underlying patterns in biomarker expression to improve diagnostic and therapeutic precision for the depressive disorders.

Rostral Anterior Cingulate Cortex Oscillatory Power Indexes Treatment-Resistance to Multiple Therapies in Major Depressive Disorder

INTRODUCTION

High rostral anterior cingulate cortex (rACC) activity is proposed as a nonspecific prognostic marker for treatment response in major depressive disorder, independent of treatment modality. However, other studies report a negative association between baseline high rACC activation and treatment response. Interestingly, these contradictory findings were also found when focusing on oscillatory markers, specifically rACC-theta power. An explanation could be that rACC-theta activity dynamically changes according to number of previous treatment attempts and thus is mediated by level of treatment-resistance.

METHODS

Primarily, we analyzed differences in rACC- and frontal-theta activity in large national cross-sectional samples representing various levels of treatment-resistance and resistance to multimodal treatments in depressed patients (psychotherapy [n = 175], antidepressant medication [AD; n = 106], repetitive transcranial magnetic stimulation [rTMS; n = 196], and electroconvulsive therapy [ECT; n = 41]), and the respective difference between remitters and non-remitters. For exploratory purposes, we also investigated other frequency bands (delta, alpha, beta, gamma).

RESULTS

rACC-theta activity was higher (p < 0.001) in the more resistant rTMS and ECT patients relative to the less resistant psychotherapy and AD patients (psychotherapy-rTMS: d = 0.315; AD-rTMS: d = 0.320; psychotherapy-ECT: d = 1.031; AD-ECT: d = 1.034), with no difference between psychotherapy and AD patients. This association was even more pronounced after controlling for frontal-theta. Post hoc analyses also yielded effects for delta, beta, and gamma bands.

CONCLUSION

Our findings suggest that by factoring in degree of treatment-resistance during interpretation of the rACC-theta biomarker, its usefulness in treatment selection and prognosis could potentially be improved substantially in future real-world practice. Future research should however also investigate specificity of the theta band.

Deep Learning in the Identification of Electroencephalogram Sources Associated with Sexual Orientation

INTRODUCTION

It is unclear if sexual orientation is a biological trait that has neurofunctional footprints. With deep learning, the power to classify biological datasets without an a priori selection of features has increased by magnitudes. The aim of this study was to correctly classify resting-state electroencephalogram (EEG) data from males with different sexual orientation using deep learning and to explore techniques to identify the learned distinguishing features.

METHODS

Three cohorts (homosexual men, heterosexual men, and a mixed sex cohort), one pretrained network on sex classification, and one newly trained network for sexual orientation classification were used to classify sex. Further, Grad-CAM methodology and source localization were used to identify the spatiotemporal patterns that were used for differentiation by the networks.

RESULTS

Using a pretrained network for classification of males and females, no differences existed between classification of homosexual and heterosexual males. The newly trained network was able, however, to correctly classify the cohorts with a total accuracy of 83%. The retrograde activation using Grad-CAM technology yielded distinctive functional EEG patterns in the Brodmann area 40 and 1 when combined with Fourier analysis and a source localization.

DISCUSSION

This study shows that electrophysiological trait markers of male sexual orientation can be identified using deep learning. These patterns are different from the differentiating signatures of males and females in a resting-state EEG.

Making memories last using the peripheral effect of direct current stimulation

Most memories that are formed are forgotten, while others are retained longer and are subject to memory stabilization. We show that non-invasive transcutaneous electrical stimulation of the greater occipital nerve (NITESGON) using direct current during learning elicited a long-term memory effect. However, it did not trigger an immediate effect on learning. A neurobiological model of long-term memory proposes a mechanism by which memories that are initially unstable can be strengthened through subsequent novel experiences. In a series of studies, we demonstrate NITESGON's capability to boost the retention of memories when applied shortly before, during, or shortly after the time of learning by enhancing memory consolidation via activation and communication in and between the locus coeruleus pathway and hippocampus by plausibly modulating dopaminergic input. These findings may have a significant impact for neurocognitive disorders that inhibit memory consolidation such as Alzheimer's disease.

Electrophysiological correlates and predictors of the antidepressant response to repeated ketamine infusions in treatment-resistant depression

BACKGROUND

Sub-anesthetic ketamine doses rapidly reduce depressive symptoms, although additional investigations of the underlying neural mechanisms and the prediction of response outcomes are needed. Electroencephalographic (EEG)-derived measures have shown promise in predicting antidepressant response to a variety of treatments, and are sensitive to ketamine administration. This study examined their utility in characterizing changes in depressive symptoms following single and repeated ketamine infusions.

METHODS

Recordings were obtained from patients with treatment-resistant major depressive disorder (MDD) (N = 24) enrolled in a multi-phase clinical ketamine trial. During the randomized, double-blind, crossover phase (Phase 1), patients received intravenous ketamine (0.5 mg/kg) and midazolam (30 μg/kg), at least 1 week apart. For each medication, three resting, eyes-closed recordings were obtained per session (pre-infusion, immediately post-infusion, 2 h post-infusion), and changes in power (delta, theta1/2/total, alpha1/2/total, beta, gamma), alpha asymmetry, theta cordance, and theta source-localized anterior cingulate cortex activity were quantified. The relationships between ketamine-induced changes with early (Phase 1) and sustained (Phases 2,3: open-label repeated infusions) decreases in depressive symptoms (Montgomery-Åsberg Depression Rating Score, MADRS) and suicidal ideation (MADRS item 10) were examined.

RESULTS

Both medications decreased alpha and theta immediately post-infusion, however, only midazolam increased delta (post-infusion), and only ketamine increased gamma (immediately post- and 2 h post-infusion). Regional- and frequency-specific ketamine-induced EEG changes were related to and predictive of decreases in depressive symptoms (theta, gamma) and suicidal ideation (alpha). Early and sustained treatment responders differed at baseline in surface-level and source-localized theta.

CONCLUSIONS

Ketamine exerts frequency-specific changes on EEG-derived measures, which are related to depressive symptom decreases in treatment-resistant MDD and provide information regarding early and sustained individual response to ketamine.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov: Action of Ketamine in Treatment-Resistant Depression, NCT01945047.

Anterior cingulate cortex in individuals with depressive symptoms: A structural MRI study

Several magnetic resonance imaging (MRI) studies have reported reduction in anterior cingulate cortex (ACC) volume in individuals with major depressive disorder (MDD). However, some MRI studies did not find significant ACC volumetric changes in MDD, and sample sizes were generally small. This cross-sectional structural MRI study examined the relationship between current depressive symptoms and ACC volume in a large community sample of 1803 adults. A series of multiple linear regression analyses were conducted to predict right and left ACC volumes using Quick Inventory of Depressive Symptomatology Self-Report (QIDS-SR) scores, intracranial volume, age, sex, race/ethnicity, alcohol use, tobacco use, and psychotropic medications as predictor variables. Right ACC volume was significantly negatively associated with QIDS-SR scores, while no significant association was found between left ACC volume and QIDS-SR scores. In addition, there was a significant negative association between QIDS-SR scores and right but not left ACC volumes in males, and no significant association between QIDS-SR scores and right or left ACC volumes in females. These findings suggest that right ACC volume is reduced in people with greater self-reported depressive symptom severity, and that this association is only significant in men.

Extraversion but not depression predicts reward sensitivity: Revisiting the measurement of anhedonic phenotypes

Recently, increasing efforts have been made to define and measure dimensional phenotypes associated with psychiatric disorders. One example is a probabilistic reward task developed by Pizzagalli, Jahn, and O'Shea (2005) to assess anhedonia, by measuring response to a differential reinforcement schedule. This task has been used in many studies, which have connected blunted reward response in the task to depressive symptoms, across clinical groups and in the general population. The current study attempted to replicate these findings in a large community sample and also investigated possible associations with Extraversion, a personality trait linked to reward sensitivity. Participants (N = 299) completed the probabilistic reward task, as well as the Beck Depression Inventory, Personality Inventory for the DSM-5, Big Five Inventory, and Big Five Aspect Scales. Our direct replication attempts used bivariate correlations and analysis of variance models. Follow-up and extension analyses used structural equation models to assess relations among reward sensitivity, depression, Extraversion, and Neuroticism. No significant associations were found between reward sensitivity and depression, thus failing to replicate previous findings. Reward sensitivity (both modeled as response bias aggregated across blocks and as response bias controlling for baseline) showed positive associations with Extraversion, but not Neuroticism. Findings suggest reward sensitivity as measured by this task may be related primarily to Extraversion and its pathological manifestations, rather than to depression per se, consistent with existing models that conceptualize depressive symptoms as combining features of Neuroticism and low Extraversion. Findings are discussed in broader contexts of dimensional psychopathology frameworks, replicable science, and behavioral task reliability. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Multimodal Investigations of Reward Circuitry and Anhedonia in Adolescent Depression

Depression is a highly prevalent condition with devastating personal and public health consequences that often first manifests during adolescence. Though extensively studied, the pathogenesis of depression remains poorly understood, and efforts to stratify risks and identify optimal interventions have proceeded slowly. A major impediment has been the reliance on an all-or-nothing categorical diagnostic scheme based solely on whether a patient endorses an arbitrary number of common symptoms for a sufficiently long period. This approach masks the well-documented heterogeneity of depression, a disorder that is highly variable in presentation, severity, and course between individuals and is frequently comorbid with other psychiatric conditions. In this targeted review, we outline the limitations of traditional diagnosis-based research and instead advocate an alternative approach centered around symptoms as unique dimensions of clinical dysfunction that span across disorders and more closely reflect underlying neurobiological abnormalities. In particular, we highlight anhedonia-the reduced ability to anticipate and experience pleasure-as a specific, quantifiable index of reward dysfunction and an ideal candidate for dimensional investigation. Anhedonia is a core symptom of depression but also a salient feature of numerous other conditions, and its severity varies widely within clinical and even healthy populations. Similarly, reward dysfunction is a hallmark of depression but is evident across many psychiatric conditions. Reward function is especially relevant in adolescence, a period characterized by exaggerated reward-seeking behaviors and rapid maturation of neural reward circuitry. We detail extensive work by our research group and others to investigate the neural and systemic factors contributing to reward dysfunction in youth, including our cumulative findings using multiple neuroimaging and immunological measures to study depressed adolescents but also trans-diagnostic cohorts with diverse psychiatric symptoms. We describe convergent evidence that reward dysfunction: (a) predicts worse clinical outcomes, (b) is associated with functional and chemical abnormalities within and beyond the neural reward circuitry, (c) is linked to elevated peripheral levels of inflammatory biomarkers, and (d) manifests early in the course of illness. Emphasis is placed on high-resolution neuroimaging techniques, comprehensive immunological assays, and data-driven analyses to fully capture and characterize the complex, interconnected nature of these systems and their contributions to adolescent reward dysfunction.

Human Sensory Cortex Contributes to the Long-Term Storage of Aversive Conditioning

Growing animal data evince a critical role of the sensory cortex in the long-term storage of aversive conditioning, following acquisition and consolidation in the amygdala. Whether and how this function is conserved in the human sensory cortex is nonetheless unclear. We interrogated this question in a human aversive conditioning study using multidimensional assessments of conditioning and long-term (15 d) retention. Conditioned stimuli (CSs; Gabor patches) were calibrated to differentially activate the parvocellular (P) and magnocellular (M) visual pathways, further elucidating cortical versus subcortical mechanisms. Full-blown conditioning and long-term retention emerged for M-biased CS (vs limited effects for P-biased CS), especially among anxious individuals, in all four dimensions assessed: threat appraisal (threat ratings), physiological arousal (skin conductance response), perceptual learning [discrimination sensitivity (d') and response speed], and cortical plasticity [visual evoked potentials (VEPs) and cortical current density]. Interestingly, while behavioral, physiological, and VEP effects were comparable at immediate and delayed assessments, the cortical substrates evolved markedly over time, transferring from high-order cortices [inferotemporal/fusiform cortex and orbitofrontal cortex (OFC)] immediately to the primary and secondary visual cortex after the delay. In sum, the contrast between P- and M-biased conditioning confirms privileged conditioning acquisition via the subcortical pathway while the immediate cortical plasticity lends credence to the triadic amygdala-OFC-fusiform network thought to underlie threat processing. Importantly, long-term retention of conditioning in the basic sensory cortices supports the conserved role of the human sensory cortex in the long-term storage of aversive conditioning.SIGNIFICANCE STATEMENT A growing network of neural substrates has been identified in threat learning and memory. The sensory cortex plays a key role in long-term threat memory in animals, but such a function in humans remains unclear. To explore this problem, we conducted multidimensional assessments of immediate and delayed (15 d) effects of human aversive conditioning. Behavioral, physiological, and scalp electrophysiological data demonstrated conditioning effects and long-term retention. High-density EEG intracranial source analysis further revealed the cortical underpinnings, implicating high-order cortices immediately and primary and secondary visual cortices after the long delay. Therefore, while high-order cortices support aversive conditioning acquisition (i.e., threat learning), the human sensory cortex (akin to the animal homolog) underpins long-term storage of conditioning (i.e., long-term threat memory).

Differentiating Melancholic and Non-melancholic Major Depressive Disorder Using Fractional Amplitude of Low-Frequency Fluctuations

BACKGROUND

Melancholic major depressive disorder (MDD) is a network-based brain disorder. However, whether or not network-based changes can be applied to differentiate melancholic (MEL) from non-melancholic (NMEL) MDD remains unclear.

METHODS

Thirty-one MEL patients, 28 NMEL patients, and 32 matched healthy controls (HCs) were scanned using resting-state functional magnetic resonance imaging. Patients were assessed by the Chinese version of Snaith-Hamilton Pleasure Scale (SHAPS-C) and Temporal Experience of Pleasure Scale (TEPS). Fractional amplitude of low-frequency fluctuations (fALFF) and correlation analysis were used to analyze the data.

RESULTS

Compared with HCs, the MEL group had significantly higher fALFF values in the bilateral inferior frontal gyrus and right supplementary motor area (SMA) and significantly lower fALFF values in the right inferior occipital gyrus (IOG), right middle temporal gyrus (MTG)/left IOG, and bilateral superior occipital gyrus (SOG)/MTG. On the other hand, the NMEL group showed significantly higher fALFF values in the bilateral SMA and significantly lower fALFF values in the bilateral posterior cingulate cortex/precuneus relative to HCs. Compared with the NMEL group, the MEL group showed significantly lower fALFF values in the left anterior cingulate cortex (ACC). A correlation was found between the fALFF values of the right SMA and the SHAPS-C in the MEL group. In addition, correlations were observed between the fALFF values of the left ACC and the TEPS contextual consummatory and total scores in all patients.

CONCLUSION

Our study uncovered that MDD exhibited altered brain activity in extensive brain networks, including the default-mode network, frontal-striatal network, reward system, and frontal-limbic network. Decreased fALFF in the left ACC might be applied to differentiate the two subtypes of MDD.

Effects of Transcranial Direct Current Stimulation on Brain Networks Related to Creative Thinking

Human creative thinking is unique and capable of generating novel and valuable ideas. Recent research has clarified the contribution of different brain networks (default mode network, DN; executive control network; salience network) to creative thinking. However, the effects of brain stimulation on brain networks during creative thinking and on creative performance have not been clarified. The present study was designed to examine the changes in functional connectivity (FC) and effective connectivity (EC) of the large-scale brain network, and the ensuing changes in creative performance, induced by transcranial direct current stimulation (tDCS). Fourteen healthy male students underwent two tDCS sessions, one with actual stimulation and one with sham stimulation, on two separate days. Participants underwent tDCS (anode over the left dorsolateral prefrontal cortex, DLPFC; cathode over the right inferior parietal lobule, IPL) for 20 min. Before and after the tDCS session, electroencephalography signals were acquired from 32 electrodes over the whole head during the creative thinking task. On FC analysis, the delta band FC between the posterior cingulate cortex and IPL significantly increased only after real stimulation. We also found that the change of flexibility score was significantly correlated with the change in: (i) delta band FC between mPFC and left lateral temporal cortex (LTC) and (ii) alpha band FC between IPL and right LTC. On EC analysis, decreased flow within the DN (from left LTC to right IPL) was observed. Our results reveal that tDCS could affect brain networks, particularly the DN, during creative thinking and modulate key FC in the generation of flexible creative ideas.

Multilayer MEG functional connectivity as a potential marker for suicidal thoughts in major depressive disorder

Major depressive disorder (MDD) is highly heterogeneous in its clinical presentation. The present exploratory study used magnetoencephalography (MEG) to investigate electrophysiological intrinsic connectivity differences between healthy volunteers and unmedicated participants with treatment-resistant MDD. The study examined canonical frequency bands from delta through gamma. In addition to group comparisons, correlational studies were conducted to determine whether connectivity was related to five symptom factors: depressed mood, tension, negative cognition, suicidal thoughts, and amotivation. The MDD and healthy volunteer groups did not differ significantly at baseline when corrected across all frequencies and clusters, although evidence of generalized slowing in MDD was observed. Notably, however, electrophysiological connectivity was strongly related to suicidal thoughts, particularly as coupling of low frequency power fluctuations (delta and theta) with alpha and beta power. This analysis revealed hub areas underlying this symptom cluster, including left hippocampus, left anterior insula, and bilateral dorsolateral prefrontal cortex. No other symptom cluster demonstrated a relationship with neurophysiological connectivity, suggesting a specificity to these results as markers of suicidal ideation.

Efficacy of Buspirone Augmentation of Escitalopram in Patients with Major Depressive Disorder with and without Atypical Features: A Randomized, 8 Week, Multicenter, Open-Label Clinical Trial

OBJECTIVE

This study investigated the treatment response and cognitive enhancement effects of buspirone augmentation of escitalopram in patients with major depressive disorder (MDD), according to atypical feature subtypes of MDD.

METHODS

An 8 week, randomized, parallel-controlled, open-label study was conducted. The Columbia Atypical Depression Diagnostic Scale was administered to evaluate atypical features. Patients were assigned randomly to the buspirone augmentation or non-buspirone groups. Symptom severity and cognitive function were evaluated using the 17-item Hamilton Depression Rating Scale, Hamilton Anxiety Rating Scale, Beck Depression Inventory, Beck Anxiety Inventory, digit span test, word fluency test, and Trail Making Tests A and B.

RESULTS

A total of 89 patients were recruited. There were no significant differences in the measures between the groups; however, among the MDD patients without atypical features, the digit span and word fluency tests were improved by treatment. In the MDD patients without atypical features, the buspirone augmentation group showed a significant improvement on the digit span test compared to the non-buspirone group.

CONCLUSION

Buspirone augmentation did not demonstrate significant benefits in MDD patients; however, buspirone augmentation showed greater efficacy for the improvement of cognitive function in MDD patients without atypical features. Our study suggests that atypical features are an important factor for cognitive enhancement in buspirone augmentation treatment in patients with MDD.

Posttraumatic Stress Disorder Is Associated with α Dysrhythmia across the Visual Cortex and the Default Mode Network

Anomalies in default mode network (DMN) activity and α (8–12 Hz) oscillations have been independently observed in posttraumatic stress disorder (PTSD). Recent spatiotemporal analyses suggest that α oscillations support DMN functioning via interregional synchronization and sensory cortical inhibition. Therefore, we examined a unifying pathology of α deficits in the visual-cortex-DMN system in PTSD. Human patients with PTSD (N = 25) and two control groups, patients with generalized anxiety disorder (GAD; N = 24) and healthy controls (HCs; N = 20), underwent a standard eyes-open resting state (S-RS) and a modified resting state (M-RS) of passively viewing salient images (known to deactivate the DMN). High-density electroencephalogram (hdEEG) were recorded, from which intracortical α activity (power and connectivity/Granger causality) was extracted using the exact low-resolution electromagnetic tomography (eLORETA). Patients with PTSD (vs GAD/HC) demonstrated attenuated α power in the visual cortex (VC) and key hubs of the DMN [posterior cingulate cortex (PCC) and medial prefrontal cortex (mPFC)] at both states, the severity of which further correlated with hypervigilance symptoms. With increased visual input (at M-RS vs S-RS), patients with PTSD further demonstrated reduced α-frequency directed connectivity within the DMN (PCC→mPFC) and, importantly, from the VC to both DMN hubs (VC→PCC and VC→mPFC), linking α deficits in the two systems. These interrelated α deficits align with DMN hypoactivity/hypoconnectivity, sensory disinhibition, and hypervigilance in PTSD, representing a unifying neural underpinning of these anomalies. The identification of visual-cortex-DMN α dysrhythmia in PTSD further presents a novel therapeutic target, promoting network-based intervention of neural oscillations.

Processing Facial Expressions That Conflict With Their Meanings to an Observer: An Event Related Potential Study

As social signals, identical facial expressions can be perceived differently, even oppositely, depending on the circumstances. Fast and accurate understanding of the information conveyed by others’ facial expressions is crucial for successful social interaction. In the current study, we used electroencephalographic analysis of several event-related potentials (ERPs) to investigate how the brain processes the facial expressions of others when they indicate different self-outcomes. In half of the trial blocks, a happy face indicated “Win” and an angry face indicated “Lose.” In the other half of the blocks, the rule was reversed. The results showed that the N170 could distinguish expression valence and the N300 could distinguish outcome valence. The valence of the expression (happy or angry) and the valence of the outcome (Win or Loss) interacted with each other in the early, automatic perceptual processing stage (N1) as well as in the later, cognitive evaluation stage (P300). Standardized Low-Resolution Electromagnetic Tomography (sLORETA) results indicated that the N1 modulation only occurred for happy faces, which may relate to automatic emotion regulation, while the interaction on P300 was significant only for angry faces, which might be associated with the regulation of negative emotions.

Prediction of Antidepressant Treatment Outcome Using Event-Related Potential in Patients with Major Depressive Disorder

(1) Background: Prediction of treatment outcome has been one of the core objectives in clinical research of patients with major depressive disorder (MDD). This study explored the possibility of event-related potential (ERP) markers to predict antidepressant treatment outcomes among MDD patients; (2) Methods: Fifty-two patients with MDD were recruited and evaluated through Hamilton depression (HAM-D), Hamilton anxiety rating scale (HAM-A), and CORE. Patients underwent a battery of ERP measures including frontal alpha symmetry (FAA) in the low alpha band (8–10 Hz), mismatch negativity (MMN), and loudness-dependent auditory evoked potentials (LDAEP); (3) Results: During the eight weeks of study, 61% of patients achieved remission, and 77% showed successful treatment responsiveness. Patients with low FAA in F5/F6 demonstrated a significantly higher remission/response ratio and better treatment responsiveness (F (2.560, 117.755) = 3.84, p = 0.016) compared to patients with high FAA. In addition, greater FAA in F7/F8 EEG channels was significantly associated with greater melancholia scores (r = 0.34, p = 0.018). Other ERP markers lacked any significant effect; (4) Conclusions: Our results suggested low FAA (i.e., greater left frontal activity) could reflect a good treatment response in MDD patients. These findings support that FAA could be a promising index in understanding both MDD and melancholic subtype.

Random Forest Classification of Alcohol Use Disorder Using EEG Source Functional Connectivity, Neuropsychological Functioning, and Impulsivity Measures

: Individuals with alcohol use disorder (AUD) manifest a variety of impairments that can be attributed to alterations in specific brain networks. The current study aims to identify features of EEG-based functional connectivity, neuropsychological performance, and impulsivity that can classify individuals with AUD (N = 30) from unaffected controls (CTL, N = 30) using random forest classification. The features included were: (i) EEG source functional connectivity (FC) of the default mode network (DMN) derived using eLORETA algorithm, (ii) neuropsychological scores from the Tower of London test (TOLT) and the visual span test (VST), and (iii) impulsivity factors from the Barratt impulsiveness scale (BIS). The random forest model achieved a classification accuracy of 80% and identified 29 FC connections (among 66 connections per frequency band), 3 neuropsychological variables from VST (total number of correctly performed trials in forward and backward sequences and average time for correct trials in forward sequence) and all four impulsivity scores (motor, non-planning, attentional, and total) as significantly contributing to classifying individuals as either AUD or CTL. Although there was a significant age difference between the groups, most of the top variables that contributed to the classification were not significantly correlated with age. The AUD group showed a predominant pattern of hyperconnectivity among 25 of 29 significant connections, indicating aberrant network functioning during resting state suggestive of neural hyperexcitability and impulsivity. Further, parahippocampal hyperconnectivity with other DMN regions was identified as a major hub region dysregulated in AUD (13 connections overall), possibly due to neural damage from chronic drinking, which may give rise to cognitive impairments, including memory deficits and blackouts. Furthermore, hypoconnectivity observed in four connections (prefrontal nodes connecting posterior right-hemispheric regions) may indicate a weaker or fractured prefrontal connectivity with other regions, which may be related to impaired higher cognitive functions. The AUD group also showed poorer memory performance on the VST task and increased impulsivity in all factors compared to controls. Features from all three domains had significant associations with one another. These results indicate that dysregulated neural connectivity across the DMN regions, especially relating to hyperconnected parahippocampal hub as well as hypoconnected prefrontal hub, may potentially represent neurophysiological biomarkers of AUD, while poor visual memory performance and heightened impulsivity may serve as cognitive-behavioral indices of AUD.

Increased Resting State Triple Network Functional Connectivity in Undergraduate Problematic Cannabis Users: A Preliminary EEG Coherence Study

An increasing body of experimental data have suggested that aberrant functional interactions between large-scale networks may be the most plausible explanation of psychopathology across multiple mental disorders, including substance-related and addictive disorders. In the current research, we have investigated the association between problematic cannabis use (PCU) and triple-network electroencephalographic (EEG) functional connectivity. Twelve participants with PCU and 24 non-PCU participants were included in the study. EEG recordings were performed during resting state (RS). The exact Low-Resolution Electromagnetic Tomography software (eLORETA) was used for all EEG analyses. Compared to non-PCU, PCU participants showed an increased delta connectivity between the salience network (SN) and central executive network (CEN), specifically, between the dorsal anterior cingulate cortex and right posterior parietal cortex. The strength of delta connectivity between the SN and CEN was positively and significantly correlated with higher problematic patterns of cannabis use after controlling for age, sex, educational level, tobacco use, problematic alcohol use, and general psychopathology (r_p = 0.40, p = 0.030). Taken together, our results show that individuals with PCU could be characterized by a specific dysfunctional interaction between the SN and CEN during RS, which might reflect the neurophysiological underpinnings of attentional and emotional processes of cannabis-related thoughts, memories, and craving.

Baseline Difference in Quantitative Electroencephalography Variables Between Responders and Non-Responders to Low-Frequency Repetitive Transcranial Magnetic Stimulation in Depression

Repetitive transcranial magnetic stimulation (rTMS) is an effective treatment for depressive disorder, with outcomes approaching 45-55% response and 30-40% remission. Eligible predictors of treatment outcome, however, are still lacking. Few studies have investigated quantitative electroencephalography (QEEG) parameters as predictors of rTMS treatment outcome and none of them have addressed the source localization techniques to predict the response to low-frequency rTMS (LF rTMS). We investigated electrophysiological differences based on scalp EEG data and inverse solution method, exact low-resolution brain electromagnetic tomography (eLORETA), between responders and non-responders to LF rTMS in resting brain activity recorded prior to the treatment. Twenty-five unmedicated depressive patients (mean age of 45.7 years, 20 females) received a 4-week treatment of LF rTMS (1 Hz; 20 sessions per 600 pulses; 100% of the motor threshold) over the right dorsolateral prefrontal cortex. Comparisons between responders (≥50% reduction in Montgomery-Åsberg Depression Rating Scale score) and non-responders were made at baseline for measures of eLORETA current density, spectral absolute power, and inter-hemispheric and intra-hemispheric EEG asymmetry. Responders were found to have lower current source densities in the alpha-2 and beta-1 frequency bands bilaterally (with predominance on the left side) in the inferior, medial, and middle frontal gyrus, precentral gyrus, cingulate gyrus, anterior cingulate, and insula. The most pronounced difference was found in the left middle frontal gyrus for alpha-2 and beta-1 bands (p < 0.05). Using a spectral absolute power analysis, we found a negative correlation between the absolute power in beta and theta frequency bands on the left frontal electrode F7 and the change in depressive symptomatology. None of the selected asymmetries significantly differentiated responders from non-responders in any frequency band. Pre-treatment reduction of alpha-2 and beta-1 sources, but not QEEG asymmetry, was found in patients with major depressive disorder who responded to LF rTMS treatment. Prospective trials with larger groups of subjects are needed to further validate these findings.

Pineal Gland Volume in Major Depressive and Bipolar Disorders

Abnormal melatonin secretion has been demonstrated in patients with affective disorders such as major depressive disorder (MDD) and bipolar disorder (BD). However, magnetic resonance imaging (MRI) studies that previously investigated the volume of the pineal gland, which regulates circadian rhythms by secreting melatonin, in these patients reported inconsistent findings. The present study employed MRI to examine pineal gland volumes and pineal cyst prevalence in 56 MDD patients (29 currently depressed and 27 remitted patients), 26 BD patients, and matched controls (33 for MDD and 24 for BD). Pineal volumes and cyst prevalence in the current MDD, remitted MDD, and BD groups did not significantly differ from those of the healthy controls. However, pineal gland volumes were significantly smaller in the current MDD subgroup of non-melancholic depression than in the melancholic MDD subgroup. Interestingly, pineal volumes correlated negatively with the severity of loss of interest in the current MDD group. Medication and the number of affective episodes were not associated with pineal volumes in the MDD or BD group. While these results do not suggest that pineal volumes reflect abnormal melatonin secretion in affective disorders, they do point to the possibility that pineal abnormalities are associated with clinical subtypes of MDD and its symptomatology.

The Effect of Lexical Cohort Size Is Independent of Semantic Context Effects in a Picture-Word Interference Task: A Combined ERP and sLORETA Study

Lexical cohort size is known to play an important role in the magnitude of semantic interference during picture naming in continuous and blocking naming tasks. Nevertheless, whether and how lexical cohort size influences semantic context effects in a picture-word interference (PWI) task remains unclear. To address this issue, participants were required to name pictures, which were paired with both semantically related and unrelated distractors, from both large and small lexical cohorts while electroencephalogram (EEG) signals were recorded. Behavior results showed a semantic interference effect but no interaction between semantic relatedness and lexical cohort size in naming latencies. ERPs and correlation analyses revealed that semantic interference effects occurred at the lexical level in the time windows of 200-400 and 400-600 ms, and lexical cohort size effects occurred at the conceptual level in the time window of 100-200 ms and at the lexical level in the time windows of 200-400 ms. Critically, no interaction between two variables was found, reflecting that lexical cohort size is independent of semantic interference for categorical relations in the PWI. sLORETA results found stronger brain activations for large lexical cohorts at the left superior temporal gyrus and inferior frontal gyrus in the time interval of 250-300 ms, which may relate to lexical selection and self-monitoring. Our findings provide evidence for the swinging lexical network rather than the response exclusion hypothesis in spoken production.

Computational modelling in source space from scalp EEG to inform presurgical evaluation of epilepsy

OBJECTIVE

The effectiveness of intracranial electroencephalography (iEEG) to inform epilepsy surgery depends on where iEEG electrodes are implanted. This decision is informed by noninvasive recording modalities such as scalp EEG. Herein we propose a framework to interrogate scalp EEG and determine epilepsy lateralization to aid in electrode implantation.

METHODS

We use eLORETA to map source activities from seizure epochs recorded from scalp EEG and consider 15 regions of interest (ROIs). Functional networks are then constructed using the phase-locking value and studied using a mathematical model. By removing different ROIs from the network and simulating their impact on the network's ability to generate seizures in silico, the framework provides predictions of epilepsy lateralization. We consider 15 individuals from the EPILEPSIAE database and study a total of 62 seizures. Results were assessed by taking into account actual intracranial implantations and surgical outcome.

RESULTS

The framework provided potentially useful information regarding epilepsy lateralization in 12 out of the 15 individuals (p=0.02, binomial test).

CONCLUSIONS

Our results show promise for the use of this framework to better interrogate scalp EEG to determine epilepsy lateralization.

SIGNIFICANCE

The framework may aid clinicians in the decision process to define where to implant electrodes for intracranial monitoring.

An Electrophysiological Biomarker That May Predict Treatment Response to ECT

OBJECTIVE

Electroconvulsive therapy (ECT) is the most effective treatment for major depression but also carries risk of cognitive side effects. The ability to predict whether treatment will be effective before initiation of treatment could significantly improve quality of care, reduce suffering, and diminish costs. We sought to carry out a comprehensive and definitive study of the relationship between the background electroencephalography (EEG) and therapeutic response to ECT.

METHODS

Twenty-one channel resting EEG was collected pre-ECT and 2 to 3 days after ECT course from 2 separate data sets, one to develop an EEG model of therapeutic response (n = 30) and a second to test this model (n = 40). A 3-way principal components analysis was applied and coherence and spectral amplitude across 6 frequency bands were examined. The primary outcome measure was the Montgomery-Asberg Rating Scale (MADRS).

RESULTS

Four patterns of amplitude and coherence along with baseline MADRS score accounted for 85% of the variance in posttreatment course MADRS score in study 1 (R = 0.85, F = 11.7, P < 0.0002) and 53% of the variance in MADRS score in study 2 (R = 0.53, F = 5.5, P < 0.003). Greater pre-ECT course anterior delta coherence accounted for the majority of variance in therapeutic response (study 1: R = 0.44, P = 0.01; study 2: R = 0.16, P = 0.008).

CONCLUSIONS

These results suggest a putative electrophysiological biomarker that can predict therapeutic response before a course of ECT. Greater baseline anterior delta coherence is significantly associated with a better subsequent therapeutic response and could be indicative of intact circuitry allowing for improved seizure propagation.

Phantom Perception of Sound and the Abnormal Cortical Inhibition System: An Electroencephalography (EEG) Study

Objectives:

Despite no observable external sound present, a perceived feeling of a recurrent unpleasant sound is a main complaint in the patients with chronic tinnitus. This phantom perception of sound is considered as the auditory equivalent of phantom limb pain, and altered excitability may be involved in its underlying pathology. Tinnitus-related hyper-excitation is suppressed by inhibitory repetitive transcranial magnetic stimulation (rTMS). However, the neural mechanism underlying the treatment is not fully understood, and quantifying the suppression induced by rTMS has yet to be considered.

Methods:

We evaluated the effect of rTMS on the cortical inhibition status following single-site stimulation over the auditory temporal cortex (T group) or dual-site stimulation over the auditory temporal and the frontal regions (TF group). These effects were also compared with outcomes following sham stimulation (S group). Subjective response was recorded using tinnitus-related handicap index (THI), and changes in the cortical inhibition status were assessed using an auditory paired-pulse suppression index (PPSI).

Results:

TF group showed the greatest benefit from the treatment evidenced in the reduced PPSI and THI scores. T and S groups did not benefit much. TF group overlapped mostly with the responder group, indicating improvement in both subjective THI and objective PPSI measurements.

Conclusion:

Our results suggest that rTMS is a beneficial therapeutic treatment for chronic tinnitus patients and the dual-site treatment was the most effective in terms of both tinnitus complaint and quantitative indices. Thus, subjective reports and electrophysiological signatures may be complementary for the diagnosis/prognosis of tinnitus.

Electrophysiological correlates of top-down attentional modulation in olfaction

The capacity to pay attention is important for the cognitive ability, for example, evaluating an object for its qualities. Attention can selectively prioritize the neural processes that are relevant to a given task. Neuroimaging investigations on human attention are primarily focused on vision to the exclusion of other sensory systems, particularly olfaction. Neural underpinnings of human olfactory attention are still not clearly understood. Here, we combined electroencephalographic measurements of olfactory event related potential with electrical neuroimaging to investigate how the neural responses after inhaling the same odor differ between conditions with varying levels of attention, and, in which brain areas. We examined the neural responses when participants attended to a rose-like odor of phenylethyl alcohol for evaluating its pleasantness versus its passive inhalation. Our results gathered significant evidence for attentional modulation of the olfactory neural response. The most prominent effect was found for the late positive component, P3, of olfactory event related potential within a second from the odor onset. The source reconstruction of this data revealed activations in a distributed network of brain regions predominantly in inferior frontal cortex, insula, and  inferior temporal gyrus. These results suggest that the neuronal modulations from attention to olfactory pleasantness may be subserved by this network.

Frequency of helping friends and helping strangers is explained by different neural signatures

Acts of helping friends and strangers are part of everyday life. However, people vary significantly with respect to how often they help others and with respect to whom they actually help on a day-to-day basis. Despite everyday helping being so pervasive, these individual differences are poorly understood. Here, we used source-localized resting electroencephalography to measure objective and stable individual differences in neural baseline activation in combination with an ecologically valid method that allows assessment of helping behavior in the field. Results revealed that neural baseline activation in the right dorsolateral prefrontal cortex (DLPFC) - a brain region associated with self-control and strategic social behavior - predicts the daily frequency of helping friends, whereas the daily frequency of helping strangers was predicted by neural baseline activation in the dorsomedial prefrontal cortex (DMPFC) - a brain region associated with social cognition processes. These findings offer evidence that distinct neural signatures and associated psychological and cognitive processes may underlie the propensity to help friends and strangers in daily life.

Electroconvulsive Therapy Modulates Resting-State EEG Oscillatory Pattern and Phase Synchronization in Nodes of the Default Mode Network in Patients With Depressive Disorder

Introduction: Electroconvulsive therapy (ECT) has antidepressant effects, but it also has possible cognitive side effects. The effects of ECT on neuronal oscillatory pattern and phase synchronization, and the relationship between clinical response or cognitive change and electroencephalogram (EEG) measurements remain elusive. Methods: Individuals with unipolar depressive disorder receiving bilateral ECT were recruited. Five minutes of resting, eyes-closed, 19-lead EEG recordings were obtained before and after a course of ECT. Non-overlapping 60 artifact-free epocs of 2-s duration were used for the analyses. We used exact low resolution electromagnetic tomography (eLORETA) to compute the whole-brain three-dimensional intracortical distribution of current source density (CSD) and phase synchronization among 28 regions-of-interest (ROIs). Paired t-tests were used to identify cortical voxels and connectivities showing changes after ECT. Montgomery Asberg Depression Rating Scale (MADRS) and Mini-Mental State Examination (MMSE) were used to evaluate the severity of depression and the global cognitive function. Correlation analyses were conducted to identify the relationship between changes in the EEG measurements and changes in MADRS or MMSE. Results: Thirteen depressed patients (five females, mean age: 58.4 years old) were included. ECT increased theta CSD in the anterior cingulate cortex (ACC), and decreased beta CSD in the frontal pole (FP), and gamma CSD in the inferior parietal lobule (IPL). ECT increased theta phase synchronization between the posterior cingulate cortex (PCC) and the anterior frontal cortex, and decreased beta phase synchronization between the PCC and temporal regions. A decline in beta synchronization in the left hemisphere was associated with cognitive changes after ECT. Conclusion: ECT modulated resting-state EEG oscillatory patterns and phase synchronization in central nodes of the default mode network (DMN). Changes in beta synchronization in the left hemisphere might explain the ECT-related cognitive side effects.

Frequency of everyday pro-environmental behaviour is explained by baseline activation in lateral prefrontal cortex

Humankind faces a plethora of environmental problems, many of which are directly influenced by individual human behaviour. To better understand pro-environmental behaviour, we here try to identify interindividual markers that explain variance in the frequency of every-day pro-environmental behaviour. So far, research on this topic has mainly relied on subjective self-report measures and has yielded mixed results. In this study, we applied a neural trait approach to assess stable, objective individual differences. Using source-localised electroencephalography, we measured cortical activation at rest and combined our neural task-independent data with an ecologically valid assessment of everyday pro-environmental behaviour. We find whole-brain-corrected evidence that task-independent baseline activation in the right lateral prefrontal cortex, a brain area known to be involved in cognitive control and self-control processes, explains individual differences in pro-environmental behaviour. The higher the cortical baseline activation in this area, the higher the frequency of everyday pro-environmental behaviour. Implications for the promotion of pro-environmental behaviour are discussed.

Striatal Functional Connectivity Alterations After Two-Week Antidepressant Treatment Associated to Enduring Clinical Improvement in Major Depressive Disorder

Background: Only less than 40% of patients with Major depressive disorder (MDD) can achieve remission after several weeks of initial antidepressant treatment. Predicting whether the prescribed treatment is effective in the following course may help clinicians modify the treatment regimen in time, and reduce the staggering burden for patients and society. However, there are not yet reliable markers based on neurobiological change after a treatment regimen steadily applied, for predicting clinical treatment outcome. The striatal circuits often exhibit abnormality for MDD patients, and are implicated in antidepressant treatments. Methods: Nineteen first-episode drug-naive MDD patients (nine females, mean age was 30 years old) were recruited to undergo clinical symptom assessment and resting state fMRI scanning at baseline, after 2 and 8 weeks of treatment with duloxetine. A seed-based analysis was used to obtain functional connectivity (FC) maps of six sub-regions of the stratum, then we explored the relationship of 2-week changes of striatal FC with clinical symptom improvement after 8-week duloxetine treatment. Results: The results revealed that 2-week FC changes of the striatal cognitive and affective subdivisions with the frontoparietal regions positively correlated with 8-week symptom improvement. We also found that early FC changes between the striatal motor subdivision and the motor-related cortical regions negatively correlated with later symptom improvement. Conclusions: These findings suggest that change of the FC of the cortical-striatal circuits at the early stage of treatment is critical for later remission of MDD. Furthermore, the association between the FC change and symptom improvement may have significant implication for clinical practice to regard neural changes as reference for evaluating how antidepressant treatment works.

EEG spectral powers and source localization in depressing, sad, and fun music videos focusing on gender differences

Previously, gender-specific affective responses have been shown using neurophysiological signals. The present study intended to compare the differences in electroencephalographic (EEG) power spectra and EEG brain sources between men and women during the exposure of affective music video stimuli. The multi-channel EEG signals of 15 males and 15 females available in the database for emotion analysis using physiological signals were studied, while subjects were watching sad, depressing, and fun music videos. Seven EEG frequency bands were computed using average Fourier cross-spectral matrices. Then, standardized low-resolution electromagnetic tomography (sLORETA) was used to localize regions involved specifically in these emotional responses. To evaluate gender differences, independent sample t test was calculated for the sLORETA source powers. Our results showed that (1) the mean EEG power for all frequency bands in the women's group was significantly higher than that of the men's group; (2) spatial distribution differentiation between men and women was detected in all EEG frequency bands. (3) This difference has been related to the emotional stimuli, which was more evident for negative emotions. Taken together, our results showed that men and women recruited dissimilar brain networks for processing sad, depressing, and fun audio-visual stimuli.

Neural signatures of different behavioral types in fairness norm compliance

Fairness norm compliance is critical in any society. However, norm compliant behavior is very heterogeneous. Some people are reliably fair (voluntary compliers). Some are fair to avoid sanctions (sanction-based compliers), and some are reliably unfair (non-compliers). These types play divergent roles in society. However, they remain poorly understood. Here, we combined neural measures (resting electroencephalography and event-related potentials) and economic paradigms to better understand these types. We found that voluntary compliers are characterized by higher baseline activation in the right temporo-parietal junction, suggesting better social cognition capacity compared to sanction-based compliers and non-compliers. The latter two types are differentiated by (a) baseline activation in the dorso-lateral prefrontal cortex, a brain area known to be involved in self-control processes, and (b) event-related potentials in a classic self-control task. Both results suggest that sanction-based compliers have better self-control capacity than non-compliers. These findings improve our understanding of fairness norm compliance. Broadly, our findings suggest that established training techniques that boost self-control might help non-compliers adhere to fairness norms.

Initial Unilateral Exposure to Deep Brain Stimulation in Treatment-Resistant Depression Patients Alters Spectral Power in the Subcallosal Cingulate

Background: High-frequency Deep Brain Stimulation (DBS) of the subcallosal cingulate (SCC) region is an emerging strategy for treatment-resistant depression (TRD). This study examined changes in SCC local field potentials (LFPs). The LFPs were recorded from the DBS leads following transient, unilateral stimulation at the neuroimaging-defined optimal electrode contact. The goal was identifying a putative electrophysiological measure of target engagement during implantation. Methods: Fourteen consecutive patients underwent bilateral SCC DBS lead implantation. LFP recordings were collected from all electrodes during randomized testing of stimulation on each DBS contact (eight total). Analyses evaluated changes in spectral power before and after 3 min of unilateral stimulation at the contacts that later facilitated antidepressant response, as a potential biomarker of optimal contact selection in each hemisphere. Results: Lateralized and asymmetric power spectral density changes were detected in the SCC with acute unilateral SCC stimulation at those contacts subsequently selected for chronic, therapeutic stimulation. Left stimulation induced broadband ipsilateral decreases in theta, alpha, beta and gamma bands. Right stimulation effects were restricted to ipsilateral beta and gamma decreases. These asymmetric effects contrasted with identical white matter stimulation maps used in each hemisphere. More variable ipsilateral decreases were seen with stimulation at the adjacent "suboptimal" contacts, but changes were not statistically different from the "optimal" contact in either hemisphere despite obvious differences in impacted white matter bundles. Change in theta power was, however, most robust and specific with left-sided optimal stimulation, which suggested a putative functional biomarker on the left with no such specificity inferred on the right. Conclusion: Hemisphere-specific oscillatory changes can be detected from the DBS lead with acute intraoperative testing at contacts that later engender antidepressant effects. Our approach defined potential target engagement signals for further investigation, particularly left-sided theta decreases following initial exposure to stimulation. More refined models combining tractography, bilateral SCC LFP, and cortical recordings may further improve the precision and specificity of these putative biomarkers. It may also optimize and standardize the lead implantation procedure and provide input signals for next generation closed-loop therapy and/or monitoring technologies for TRD.

Cortical hypoactivation during resting EEG suggests central nervous system pathology in patients with chronic fatigue syndrome

We investigated central fatigue in 50 patients with chronic fatigue syndrome (CFS) and 50 matched healthy controls (HC). Resting state EEG was collected from 19 scalp locations during a 3 min, eyes-closed condition. Current densities were localized using exact low-resolution electromagnetic tomography (eLORETA). The Multidimensional Fatigue Inventory (MFI-20) and the Fatigue Severity Scale (FSS) were administered to all participants. Independent t-tests and linear regression analyses were used to evaluate group differences in current densities, followed by statistical non-parametric mapping (SnPM) correction procedures. Significant differences were found in the delta (1-3 Hz) and beta-2 (19-21 Hz) frequency bands. Delta sources were found predominately in the frontal lobe, while beta-2 sources were found in the medial and superior parietal lobe. Left-lateralized, frontal delta sources were associated with a clinical reduction in motivation. The implications of abnormal cortical sources in patients with CFS are discussed.

Post-error Brain Activity Correlates With Incidental Memory for Negative Words

The present study had three main objectives. First, we aimed to evaluate whether short-duration affective states induced by negative and positive words can lead to increased error-monitoring activity relative to a neutral task condition. Second, we intended to determine whether such an enhancement is limited to words of specific valence or is a general response to arousing material. Third, we wanted to assess whether post-error brain activity is associated with incidental memory for negative and/or positive words. Participants performed an emotional stop-signal task that required response inhibition to negative, positive or neutral nouns while EEG was recorded. Immediately after the completion of the task, they were instructed to recall as many of the presented words as they could in an unexpected free recall test. We observed significantly greater brain activity in the error-positivity (Pe) time window in both negative and positive trials. The error-related negativity amplitudes were comparable in both the neutral and emotional arousing trials, regardless of their valence. Regarding behavior, increased processing of emotional words was reflected in better incidental recall. Importantly, the memory performance for negative words was positively correlated with the Pe amplitude, particularly in the negative condition. The source localization analysis revealed that the subsequent memory recall for negative words was associated with widespread bilateral brain activity in the dorsal anterior cingulate cortex and in the medial frontal gyrus, which was registered in the Pe time window during negative trials. The present study has several important conclusions. First, it indicates that the emotional enhancement of error monitoring, as reflected by the Pe amplitude, may be induced by stimuli with symbolic, ontogenetically learned emotional significance. Second, it indicates that the emotion-related enhancement of the Pe occurs across both negative and positive conditions, thus it is preferentially driven by the arousal content of an affective stimuli. Third, our findings suggest that enhanced error monitoring and facilitated recall of negative words may both reflect responsivity to negative events. More speculatively, they can also indicate that post-error activity of the medial prefrontal cortex may selectively support encoding for negative stimuli and contribute to their privileged access to memory.

Thalamocortical dysrhythmia detected by machine learning

Thalamocortical dysrhythmia (TCD) is a model proposed to explain divergent neurological disorders. It is characterized by a common oscillatory pattern in which resting-state alpha activity is replaced by cross-frequency coupling of low- and high-frequency oscillations. We undertook a data-driven approach using support vector machine learning for analyzing resting-state electroencephalography oscillatory patterns in patients with Parkinson’s disease, neuropathic pain, tinnitus, and depression. We show a spectrally equivalent but spatially distinct form of TCD that depends on the specific disorder. However, we also identify brain areas that are common to the pathology of Parkinson’s disease, pain, tinnitus, and depression. This study therefore supports the validity of TCD as an oscillatory mechanism underlying diverse neurological disorders.

Thalamocortical dysrhythmia has been proposed to occur in a number of neurological and psychiatric disorders. Here, the authors use a data-driven approach to demonstrate thalamocortical dysrhythmia occurs in individuals with Parkinson’s disease, neuropathic pain, tinnitus, and depression.

Exploring the effects of anodal and cathodal high definition transcranial direct current stimulation targeting the dorsal anterior cingulate cortex

The dorsal anterior cingulate cortex (dACC) has been identified as a core region affected by many disorders, representing a promising target for neuromodulation. High Definition-transcranial Direct Current Stimulation (HD-tDCS) is a non-invasive neuromodulation technique that has already shown promising outcomes and has been tested to engage deeper structures. This study investigates whether it is possible to modulate dACC activity using anodal and cathodal HD-tDCS. Furthermore, it examines what effects anodal and cathodal HD-tDCS targeting dACC have on cognitive and emotional processing. Forty-five healthy subjects were randomly assigned to 1 of 3 groups: anodal, cathodal, and sham. Resting-state electroencephalography (rsEEG) and a cognitive and emotional Counting Stroop task were administered before and after HD-tDCS. RsEEG showed changes: anodal HD-tDCS showed significant increase in beta frequency band activity in dACC, while cathodal HD-tDCS led to significant increase in activity at dorsal and rostral ACC in the theta frequency band. Behavioral changes were also found after anodal HD-tDCS in the cognitive Counting Stroop for incongruent trials and after cathodal HD-tDCS in the emotional Counting Stroop for emotional trials. This study demonstrated that HD-tDCS is able to modulate dACC activity, suggesting that it has the potential to be used as a treatment tool.

Subtypes of depression and their overlap in a naturalistic inpatient sample of major depressive disorder

Subtyping depression is important in order to further delineate biological causes of depressive syndromes. The aim of this study was to evaluate clinical and outcome characteristics of distinct subtypes of depression and to assess proportion and features of patients fulfilling criteria for more than one subtype. Melancholic, atypical and anxious subtypes of depression were assessed in a naturalistic sample of 833 inpatients using DSM-IV specifiers based on operationalized criteria. Baseline characteristics and outcome criteria at discharge were compared between distinct subtypes and their overlap. A substantial proportion of patients (16%) were classified with more than one subtype of depression, 28% were of the distinct anxious, 7% of the distinct atypical and 5% of the distinct melancholic subtype. Distinct melancholic patients had shortest duration of episode, highest baseline depression severity, but were more often early improvers; distinct anxious patients had higher NEO-Five Factor Inventory (NEO-FFI) neuroticism scores compared with patients with unspecific subtype. Melancholic patients with overlap of anxious features had worse treatment outcome compared to distinct melancholic and distinct anxious subtype. Distinct subtypes differed in only few variables and patients with overlap of depression subtypes may have independent clinical and outcome characteristics. Studies investigating biological causes of subtypes of depression should take influence of features of other subtypes into account.

Leveraging Machine Learning Approaches for Predicting Antidepressant Treatment Response Using Electroencephalography (EEG) and Clinical Data

Background: Individuals with major depressive disorder (MDD) vary in their response to antidepressants. However, identifying objective biomarkers, prior to or early in the course of treatment that can predict antidepressant efficacy, remains a challenge. Methods: Individuals with MDD participated in a 12-week antidepressant pharmacotherapy trial. Electroencephalographic (EEG) data was collected before and 1 week post-treatment initiation in 51 patients. Response status at week 12 was established with the Montgomery-Asberg Depression Scale (MADRS), with a ≥50% decrease characterizing responders (N = 27/24 responders/non-responders). We used a machine learning (ML)-approach for predicting response status. We focused on Random Forests, though other ML methods were compared. First, we used a tree-based estimator to select a relatively small number of significant features from: (a) demographic/clinical data (age, sex, individual item/total MADRS scores at baseline, week 1, change scores); (b) scalp-level EEG power; (c) source-localized current density (via exact low-resolution electromagnetic tomography [eLORETA] software). Second, we applied kernel principal component analysis to reduce and map important features. Third, a set of ML models were constructed to classify response outcome based on mapped features. For each dataset, predictive features were extracted, followed by a model of all predictive features, and finally by a model of the most predictive features. Results: Fifty eLORETA features were predictive of response (across bands, both time-points); alpha₁/theta eLORETA features showed the highest predictive value. Eighty-eight scalp EEG features were predictive of response (across bands, both time-points), with theta/alpha₂ being most predictive. Clinical/demographic data consisted of 31 features, with the most important being week 1 "concentration difficulty" scores. When all features were included into one model, its predictive utility was high (88% accuracy). When the most important features were extracted in the final model, 12 predictive features emerged (78% accuracy), including baseline scalp-EEG frontopolar theta, parietal alpha₂ and frontopolar alpha₁. Conclusions: These findings suggest that ML models of pre- and early treatment-emergent EEG profiles and clinical features can serve as tools for predicting antidepressant response. While this must be replicated using large independent samples, it lays the groundwork for research on personalized, "biomarker"-based treatment approaches.

Risk for affective disorders is associated with greater prefrontal gray matter volumes: A prospective longitudinal study

Background

Major depression and bipolar disorders aggregates in families and are linked with a wide range of neurobiological abnormalities including cortical gray matter (GM) alterations. Prospective studies of individuals at familial risk may expose the neural mechanisms underlying risk transmission.

Methods

We used voxel based morphometry to investigate changes in regional GM brain volume, over a seven-year period, in 37 initially healthy individuals having a mono- or di-zygotic twin diagnosed with major depression or bipolar disorder (high-risk group; mean age 41.6 yrs.) as compared to 36 individuals with no history of affective disorders in the index twin and first-degree relatives (low-risk group; mean age 38.5 yrs.).

Results

Groups did not differ in regional GM volume changes over time. However, independent of time, high-risk twins had significantly greater GM volumes in bilateral dorsal anterior cingulate, inferior frontal gyrus and temporoparietal regions as compared to low-risk twins. Further, individuals who developed an affective disorder at follow-up (n = 12), had relatively the largest GM volumes, both at baseline and follow-up, in the right dorsal anterior cingulate cortex and right inferior frontal cortex compared to high- and low-risk twins who remained well at follow-up.

Conclusion

This pattern of apparently stable grater regional GM volume may constitute a neural marker of an increased risk for developing an affective disorder in individuals at familial risk.

Electroencephalography Source Functional Connectivity Reveals Abnormal High-Frequency Communication Among Large-Scale Functional Networks in Depression

BACKGROUND

Functional magnetic resonance imaging studies of resting-state functional connectivity have shown that major depressive disorder (MDD) is characterized by increased connectivity within the default mode network (DMN) and between the DMN and the frontoparietal network (FPN). However, much remains unknown about abnormalities in higher frequency (>1 Hz) synchronization. Findings of abnormal synchronization in specific frequencies would contribute to a better understanding of the potential neurophysiological origins of disrupted functional connectivity in MDD.

METHODS

We used the high temporal resolution of electroencephalography to compare the spectral properties of resting-state functional connectivity in individuals with MDD (n = 65) with healthy control subjects (n = 79) and examined the extent to which connectivity disturbances were evident in a third sample of individuals in remission from depression (n = 30). Exact low resolution electromagnetic tomography was used to compute intracortical activity from regions within the DMN and FPN, and functional connectivity was computed using lagged phase synchronization.

RESULTS

Compared to control subjects, the MDD group showed greater within-DMN beta 2 band (18.5-21 Hz) connectivity and greater beta 1 band (12.5-18 Hz) connectivity between the DMN and FPN. This hyperconnectivity was not observed in the remitted MDD group. However, greater beta 1 band DMN-FPN connectivity was associated with more frequent depressive episodes since first depression onset, even after controlling for current symptom severity.

CONCLUSIONS

These findings extend our understanding of the neurophysiological basis of abnormal resting-state functional connectivity in MDD and indicate that elevations in high-frequency DMN-FPN connectivity may be a neural marker linked to a more recurrent illness course.

Resting state electrical brain activity and connectivity in fibromyalgia

The exact mechanism underlying fibromyalgia is unknown, but increased facilitatory modulation and/or dysfunctional descending inhibitory pathway activity are posited as possible mechanisms contributing to sensitization of the central nervous system. The primary goal of this study is to identify a fibromyalgia neural circuit that can account for these abnormalities in central pain. The second goal is to gain a better understanding of the functional connectivity between the default and the executive attention network (salience network plus dorsal lateral prefrontal cortex) in fibromyalgia. We examine neural activity associated with fibromyalgia (N = 44) and compare these with healthy controls (N = 44) using resting state source localized EEG. Our data support an important role of the pregenual anterior cingulate cortex but also suggest that the degree of activation and the degree of integration between different brain areas is important. The inhibition of the connectivity between the dorsal lateral prefrontal cortex and the posterior cingulate cortex on the pain inhibitory pathway seems to be limited by decreased functional connectivity with the pregenual anterior cingulate cortex. Our data highlight the functional dynamics of brain regions integrated in brain networks in fibromyalgia patients.

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.

Changes in brain activation during sedation induced by dexmedetomidine

Objective

Dexmedetomidine (DEX) has been widely used as a sedative, acting as an α2-adrenergic agonist on autoreceptors, presynaptic receptors and postsynaptic receptors without risk of respiratory depression. Although consciousness impairment is closely related to disturbances of brain function in different frequency bands, the time-varying DEX effects on cortical activity in specific frequency bands has not yet been studied.

Methods

We used electroencephalography (EEG) to analyse differences in cerebral cortex activity between the awake and sedated states, using electromagnetic tomography (standardized low resolution electromagnetic tomography (sLORETA)) to localize multiple channel scalp recordings of cerebral electric activity to specific brain regions.

Results

The results revealed increased activity in the cuneus at delta-band frequencies, and in the posterior cingulate cortex at theta frequencies, during awake and sedated states induced by DEX at specific frequency bands. Differences in standardized low resolution cingulate gyrus were found in beta1 frequencies (13–18 Hz), and in the cuneus at gamma frequencies.

Conclusion

Cerebral cortical activity was significantly altered in various brain areas during DEX sedation, including parts of the default mode network and common midline core in different frequency ranges. These alterations may elucidate the mechanisms underlying DEX sedation.

Occipital Nerve Field Transcranial Direct Current Stimulation Normalizes Imbalance Between Pain Detecting and Pain Inhibitory Pathways in Fibromyalgia

Occipital nerve field (OCF) stimulation with subcutaneously implanted electrodes is used to treat headaches, more generalized pain, and even failed back surgery syndrome via unknown mechanisms. Transcranial direct current stimulation (tDCS) can predict the efficacy of implanted electrodes. The purpose of this study is to unravel the neural mechanisms involved in global pain suppression, mediated by occipital nerve field stimulation, within the realm of fibromyalgia. Nineteen patients with fibromyalgia underwent a placebo-controlled OCF tDCS. Electroencephalograms were recorded at baseline after active and sham stimulation. In comparison with healthy controls, patients with fibromyalgia demonstrate increased dorsal anterior cingulate cortex, increased premotor/dorsolateral prefrontal cortex activity, and an imbalance between pain-detecting dorsal anterior cingulate cortex and pain-suppressing pregenual anterior cingulate cortex activity, which is normalized after active tDCS but not sham stimulation associated with increased pregenual anterior cingulate cortex activation. The imbalance improvement between the pregenual anterior cingulate cortex and the dorsal anterior cingulate cortex is related to clinical changes. An imbalance assumes these areas communicate and, indeed, abnormal functional connectivity between the dorsal anterior cingulate cortex and pregenual anterior cingulate cortex is noted to be caused by a dysfunctional effective connectivity from the pregenual anterior cingulate cortex to the dorsal anterior cingulate cortex, which improves and normalizes after real tDCS but not sham tDCS. In conclusion, OCF tDCS exerts its effect via activation of the descending pain inhibitory pathway and de-activation of the salience network, both of which are abnormal in fibromyalgia.

Influencing connectivity and cross-frequency coupling by real-time source localized neurofeedback of the posterior cingulate cortex reduces tinnitus related distress

Background

In this study we are using source localized neurofeedback to moderate tinnitus related distress by influencing neural activity of the target region as well as the connectivity within the default network.

Hypothesis

We hypothesize that up-training alpha and down-training beta and gamma activity in the posterior cingulate cortex has a moderating effect on tinnitus related distress by influencing neural activity of the target region as well as the connectivity within the default network and other functionally connected brain areas.

Methods

Fifty-eight patients with chronic tinnitus were included in the study. Twenty-three tinnitus patients received neurofeedback training of the posterior cingulate cortex with the aim of up-training alpha and down-training beta and gamma activity, while 17 patients underwent training of the lingual gyrus as a control situation. A second control group consisted of 18 tinnitus patients on a waiting list for future tinnitus treatment.

Results

This study revealed that neurofeedback training of the posterior cingulate cortex results in a significant decrease of tinnitus related distress. No significant effect on neural activity of the target region could be obtained. However, functional and effectivity connectivity changes were demonstrated between remote brain regions or functional networks as well as by altering cross frequency coupling of the posterior cingulate cortex.

Conclusion

This suggests that neurofeedback could remove the information, processed in beta and gamma, from the carrier wave, alpha, which transports the high frequency information and influences the salience attributed to the tinnitus sound. Based on the observation that much pathology is the result of an abnormal functional connectivity within and between neural networks various pathologies should be considered eligible candidates for the application of source localized EEG based neurofeedback training.

Allostasis in health and food addiction

Homeostasis is the basis of modern medicine and allostasis, a further elaboration of homeostasis, has been defined as stability through change, which was later modified to predictive reference resetting. It has been suggested that pleasure is related to salience (behavioral relevance), and withdrawal has been linked to allostasis in addictive types. The question arises how the clinical and neural signatures of pleasure, salience, allostasis and withdrawal relate, both in a non-addicted and addicted state. Resting state EEGs were performed in 66 people, involving a food-addicted obese group, a non-food addicted obese group and a lean control group. Correlation analyses were performed on behavioral data, and correlation, comparative and conjunction analyses were performed to extract electrophysiological relationships between pleasure, salience, allostasis and withdrawal. Pleasure/liking seems to be the phenomenological expression that enough salient stimuli are obtained, and withdrawal can be seen as a motivational incentive because due to allostatic reference resetting, more stimuli are required. In addition, in contrast to non-addiction, a pathological, non-adaptive salience attached to food results in withdrawal mediated through persistent allostatic reference resetting.

The brain, obesity and addiction: an EEG neuroimaging study

Obesity is among the greatest challenges facing healthcare systems with 20% of the world’s population afflicted. Great controversy exists whether obesity can be regarded as an addictive disorder or not. Recently the Yale Food Addiction Scale questionnaire has been developed as a tool to identify individuals with traits of addiction towards food. Using clinical and source localized EEG data we dichotomize obesity. Brain activity in food-addicted and non-food-addicted obese people is compared to alcohol-addicted and non-addicted lean controls. We show that food addiction shares common neural brain activity with alcohol addiction. This ‘addiction neural brain activity’ consists of the dorsal and pregenual anterior cingulate cortex, parahippocampal area and precuneus. Furthermore, common neural obesity neural brain activity exists as well. The ‘obesity neural brain activity’ consists of dorsal and pregenual anterior cingulate cortex, posterior cingulate extending into the precuneus/cuneus as well as the parahippocampal and inferior parietal area. However food-addicted differ from non-food-addicted obese people by opposite activity in the anterior cingulate gyrus. This food addiction and non-food-addiction obesity dichotomy demonstrates there is at least 2 different kinds of obesity with overlapping network activity, but different in anterior cingulate cortex activity.