Escitalopram but not placebo modulates brain rhythmic oscillatory activity in the first week of treatment of Major Depressive Disorder

Resting and TMS-EEG markers of treatment response in major depressive disorder: A systematic review

Electroencephalography (EEG) is a non-invasive method to identify markers of treatment response in major depressive disorder (MDD). In this review, existing literature was assessed to determine how EEG markers change with different modalities of MDD treatments, and to synthesize the breadth of EEG markers used in conjunction with MDD treatments. PubMed and EMBASE were searched from 2000 to 2021 for studies reporting resting EEG (rEEG) and transcranial magnetic stimulation combined with EEG (TMS-EEG) measures in patients undergoing MDD treatments. The search yielded 966 articles, 204 underwent full-text screening, and 51 studies were included for a narrative synthesis of findings along with confidence in the evidence. In rEEG studies, non-linear quantitative algorithms such as theta cordance and theta current density show higher predictive value than traditional linear metrics. Although less abundant, TMS-EEG measures show promise for predictive markers of brain stimulation treatment response. Future focus on TMS-EEG measures may prove fruitful, given its ability to target cortical regions of interest related to MDD.

Investigating the Effects of Auditory and Vibrotactile Rhythmic Sensory Stimulation on Depression: An EEG Pilot Study

Background

Major depressive disorder (MDD) is a persistent psychiatric condition and one of the leading causes of global disease burden. In a previous study, we investigated the effects of a five-week intervention consisting of rhythmic gamma frequency (30-70 Hz) vibroacoustic stimulation in 20 patients formally diagnosed with MDD. In that study, the findings suggested a significant clinical improvement in depression symptoms as measured using the Montgomery-Asberg Depression Rating Scale (MADRS), with 37% of participants meeting the criteria for clinical response. The goal of the present research was to examine possible changes from baseline to posttreatment in resting-state electroencephalography (EEG) recordings using the same treatment protocol and to characterize basic changes in EEG related to treatment response.

Materials and methods

The study sample consisted of 19 individuals aged 18-70 years with a clinical diagnosis of MDD. The participants were assessed before and after a five-week treatment period, which consisted of listening to an instrumental musical track on a vibroacoustic device, delivering auditory and vibrotactile stimulus in the gamma-band range (30-70 Hz, with particular emphasis on 40 Hz). The primary outcome measure was the change in Montgomery-Asberg Depression Rating Scale (MADRS) from baseline to posttreatment and resting-state EEG.

Results

Analysis comparing MADRS score at baseline and post-intervention indicated a significant change in the severity of depression symptoms after five weeks (t = 3.9923, df = 18, p = 0.0009). The clinical response rate was 36.85%. Resting-state EEG power analysis revealed a significant increase in occipital alpha power (t = -2.149, df = 18, p = 0.04548), as well as an increase in the prefrontal gamma power of the responders (t = 2.8079, df = 13.431, p = 0.01442).

Conclusions

The results indicate that improvements in MADRS scores after rhythmic sensory stimulation (RSS) were accompanied by an increase in alpha power in the occipital region and an increase in gamma in the prefrontal region, thus suggesting treatment effects on cortical activity in depression. The results of this pilot study will help inform subsequent controlled studies evaluating whether treatment response to vibroacoustic stimulation constitutes a real and replicable reduction of depressive symptoms and to characterize the underlying mechanisms.

Using prefrontal and midline right frontal EEG-derived theta cordance and depressive symptoms to predict the differential response or remission to antidepressant treatment in major depressive disorder

There is a growing need for optimizing treatment selection and response prediction in individuals with major depressive disorder (MDD). Prior investigations have shown that changes in electroencephalographic (EEG)-based measures precede symptom improvement and could serve as biomarkers of treatment outcome. One such method is cordance, a computation of regional brain activity based on a combination of absolute and relative resting EEG activity. Specifically, early reduction in prefrontal (PF) and midline right frontal (MRF) theta (4-8Hz) cordance has been shown to predict response to various antidepressants, though replication is required. Thus, this study examined early changes (baseline to week 1) in PF and MRF cordance in 47 MDD patients undergoing antidepressant treatment. Early changes in cordance and in Montgomery Åsberg Depression Rating Scale (MADRS) scores were assessed alone, and in combination, to predict eventual (by week 12) treatment response and remission. Models combining early changes in theta cordance (PF and MRF) and depressive symptoms were most predictive of response to treatment at week 12; remission models (cordance, MADRS, and their combination) were weaker, though provided modest prediction values. These results suggest that antidepressant response may be optimally predicted by combining both EEG and symptom-based measures after one week of treatment.

Prospective testing of a neurophysiologic biomarker for treatment decisions in major depressive disorder: The PRISE-MD trial

Management of Major Depressive Disorder (MDD) might be improved by a biomarker to predict whether a selected medication is likely to lead to remission. We previously reported on a quantitative electroencephalogram-based biomarker, the Antidepressant Treatment Response (ATR) index, that integrated recordings at baseline and after one week of treatment. The present study prospectively tested whether treatment directed by the biomarker increased the likelihood of remission; we hypothesized that continued treatment with a drug predicted to lead to remission (i.e., high ATR values) would be associated with better outcomes than if the drug was predicted not to lead to remission (i.e., low ATR values). We enrolled 180 adult outpatients with unipolar MDD from the community. After one week of escitalopram treatment to determine the biomarker, stratified randomization (high vs. low ATR) was used to assign subjects to either continued escitalopram or a switch to bupropion as a blinded control condition, for seven additional weeks. For the 73 evaluable subjects assigned to continued escitalopram treatment, the remission rate was significantly higher for those in whom ATR had predicted remission versus non-remission (60.4% vs. 30.0%, respectively, p = 0.01). Accuracy was enhanced by combining 1-week depressive symptom change with ATR (68.6% vs 28.9%). This prospective validation study supports further development of the ATR biomarker, alone or together with early symptom change, to improve care by identifying individuals unlikely to remit with their current treatment, and support the decision to change treatment after one week rather than after failing a full, prolonged course of medication.

Resting-state EEG beta band power predicts quality of life outcomes in patients with depressive disorders: A longitudinal investigation

BACKGROUND

Quality of life is severely impaired in patients with depressive disorders. Previous studies have focused on biomarkers predicting depressive symptomatology; however, studies investigating biomarkers predicting quality of life outcomes are limited. Improving quality of life is important because it is related not only to mental health but also to physical health. We need to develop a biomarker related to quality of life as a therapeutic target for patients with depressive disorders. Resting-state electroencephalography (EEG) is easy to record in clinical settings. The index of bandwidth spectral power predicts treatment response in depressive disorders and thus may be a candidate biomarker. However, no longitudinal studies have investigated whether EEG-recorded power could predict quality of life outcomes in patients with depressive disorders.

METHODS

The resting-state EEG-recorded bandwidth spectral power at baseline and the World Health Organization Quality of Life (QOL)-26 scores at 3-year follow-up were measured in 44 patients with depressive disorders.

RESULTS

The high beta band power (20-30 Hz) at baseline significantly predicted QOL at the 3-year follow-up after considering depressive symptoms and medication effects in a longitudinal investigation in patients with depressive disorders (β = 0.38, p = 0.01).

LIMITATIONS

We did not have healthy subjects as a comparison group in this study.

CONCLUSIONS

Our findings suggest that resting-state beta activity has the potential to be a useful biomarker for predicting future quality of life outcomes in patients with depressive disorders.

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.

Time Course of Changes in Peripheral Blood Gene Expression During Medication Treatment for Major Depressive Disorder

Changes in gene expression (GE) during antidepressant treatment may increase understanding of the action of antidepressant medications and serve as biomarkers of efficacy. GE changes in peripheral blood are desirable because they can be assessed easily on multiple occasions during treatment. We report here on GE changes in 68 individuals who were treated for 8 weeks with either escitalopram alone, or escitalopram followed by bupropion. GE changes were assessed after 1, 2, and 8 weeks of treatment, with significant changes observed in 156, 121, and 585 peripheral blood gene transcripts, respectively. Thirty-one transcript changes were shared between the 1- and 8-week time points (seven upregulated, 24 downregulated). Differences were detected between the escitalopram- and bupropion-treated subjects, although there was no significant association between GE changes and clinical outcome. A subset of 18 genes overlapped with those previously identified as differentially expressed in subjects with MDD compared with healthy control subjects. There was statistically significant overlap between genes differentially expressed in the current and previous studies, with 10 genes overlapping in at least two previous studies. There was no enrichment for genes overexpressed in nervous system cell types, but there was a trend toward enrichment for genes in the WNT/β-catenin pathway in the anterior thalamus; three genes in this pathway showed differential expression in the present and in three previous studies. Our dataset and other similar studies will provide an important source of information about potential biomarkers of recovery and for potential dysregulation of GE in MDD.

Estimating patient-specific treatment advantages in the 'Treatment for Adolescents with Depression Study'

The 'Treatment for Adolescents with Depression Study' (TADS, ClinicalTrials.gov, identifier: NCT00006286) was a cornerstone, randomized controlled trial evaluating the effectiveness of standard treatment options for major depression in adolescents. Whereas previous TADS analyses examined primarily effect modifications of treatment-placebo differences by various patient characteristics, less is known about the modification of inter-treatment differences, and hence, patient characteristics that might guide treatment selection. We sought to fill this gap by estimating patient-specific inter-treatment differences as a function of patients' baseline characteristics. We did so by applying the 'model-based random forest', a recently-introduced machine learning-based method for evaluating effect heterogeneity that allows for the estimation of patient-specific treatment effects as a function of arbitrary baseline characteristics. Treatment conditions were cognitive-behavioural therapy (CBT) alone, fluoxetine (FLX) alone, and the combination of CBT and fluoxetine (COMB). All inter-treatment differences (CBT vs. FLX; CBT vs. COMB; FLX vs. COMB) were evaluated across 23 potential effect modifiers extracted from previous studies. Overall, FLX was superior to CBT, while COMB was superior to both CBT and FLX. Evidence for effect heterogeneity was found for the CBT-FLX difference and the FLX-COMB difference, but not for the CBT-COMB difference. Baseline depression severity modified the CBT-FLX difference; whereas baseline depression severity, patients' treatment expectations, and childhood trauma modified the FLX-COMB difference. All modifications were quantitative rather than qualitative, however, meaning that the differences varied only in magnitude, but not direction. These findings imply that combining CBT with fluoxetine may be superior to either therapy used alone across a broad range of patients.

Aberrant resting-state oscillatory brain activity in Parkinson's disease patients with visual hallucinations: An MEG source-space study

To gain insight into possible underlying mechanism(s) of visual hallucinations (VH) in Parkinson's disease (PD), we explored changes in local oscillatory activity in different frequency bands with source-space magnetoencephalography (MEG). Eyes-closed resting-state MEG recordings were obtained from 20 PD patients with hallucinations (Hall+) and 20 PD patients without hallucinations (Hall-), matched for age, gender and disease severity. The Hall+ group was subdivided into 10 patients with VH only (unimodal Hall+) and 10 patients with multimodal hallucinations (multimodal Hall+). Subsequently, neuronal activity at source-level was reconstructed using an atlas-based beamforming approach resulting in source-space time series for 78 cortical and 12 subcortical regions of interest in the automated anatomical labeling (AAL) atlas. Peak frequency (PF) and relative power in six frequency bands (delta, theta, alpha1, alpha2, beta and gamma) were compared between Hall+ and Hall-, unimodal Hall+ and Hall-, multimodal Hall+ and Hall-, and unimodal Hall+ and multimodal Hall+ patients. PF and relative power per frequency band did not differ between Hall+ and Hall-, and multimodal Hall+ and Hall- patients. Compared to the Hall- group, unimodal Hall+ patients showed significantly higher relative power in the theta band (p = 0.005), and significantly lower relative power in the beta (p = 0.029) and gamma (p = 0.007) band, and lower PF (p = 0.011). Compared to the unimodal Hall+, multimodal Hall+ showed significantly higher PF (p = 0.007). In conclusion, a subset of PD patients with only VH showed slowing of MEG-based resting-state brain activity with an increase in theta activity, and a concomitant decrease in beta and gamma activity, which could indicate central cholinergic dysfunction as underlying mechanism of VH in PD. This signature was absent in PD patients with multimodal hallucinations.

Electrophysiology of obsessive compulsive disorder: A systematic review of the electroencephalographic literature

Obsessive-compulsive disorder (OCD) is a chronic disease that causes significant decline in the quality of life of those affected. Due to our limited understanding of the underlying pathophysiology of OCD, successful treatment remains elusive. Although many have studied the pathophysiology of OCD through electroencephalography (EEG), limited attempts have been made to synthesize and interpret their findings. To bridge this gap, we conducted a comprehensive literature review using Medline/PubMed and considered the 65 most relevant studies published before June 2018. The findings are categorised into quantitative EEG, sleep related EEG and event related potentials (ERPs). Increased frontal asymmetry, frontal slowing and an enhancement in the ERP known as error related negativity (ERN) were consistent findings in OCD. However, sleep EEG and other ERP (P3 and N2) findings were inconsistent. Additionally, we analysed the usefulness of ERN as a potential candidate endophenotype. We hypothesize that dysfunctional frontal circuitry and overactive performance monitoring are the major underlying impairments in OCD. Additionally, we conceptualized that defective fronto-striato-thalamic circuitry causing poor cerebral functional connectivity gives rise to the OCD behavioural manifestations. Finally, we have discussed transcranial magnetic stimulation and EEG (TMS-EEG) applications in future research to further our knowledge of the underlying pathophysiology of OCD.

Hormonal regulation of circuit function: sex, systems and depression

Major depressive disorder (MDD) is a debilitating chronic illness that is two times more prevalent in women than in men. The mechanisms associated with the increased female susceptibility to depression remain poorly characterized. Aberrant neuronal oscillatory activity within the putative depression network is an emerging mechanism underlying MDD. However, innate sex differences in network activity and its contribution to depression vulnerability have not been well described. In this review, current evidence of sex differences in neuronal oscillatory activity, including the influence of sex hormones and female cycling, will first be described followed by evidence of disrupted neuronal circuit function in MDD and the effects of antidepressant treatment. Lastly, current knowledge of sex differences in MDD-associated aberrant circuit function and oscillatory activity will be highlighted, with an emphasis on the role of sex steroids and female cycling. Collectively, it is clear that there are significant gaps in the literature regarding innate and pathologically associated sex differences in network activity and that the elucidation of these differences is invaluable to our understanding of sex-specific vulnerabilities and therapies for MDD.

Change in Quantitative EEG Theta Cordance as a Potential Predictor of Repetitive Transcranial Magnetic Stimulation Clinical Outcome in Major Depressive Disorder

Repetitive transcranial magnetic stimulation (rTMS) has demonstrated efficacy in major depressive disorder (MDD), although clinical outcome is variable. Change in the resting-state quantitative electroencephalogram (qEEG), particularly in theta cordance early in the course of treatment, has been linked to antidepressant medication outcomes but has not been examined extensively in clinical rTMS. This study examined change in theta cordance over the first week of clinical rTMS and sought to identify a biomarker that would predict outcome at the end of 6 weeks of treatment. Clinically stable outpatients (n = 18) received nonblinded rTMS treatment administered to the dorsolateral prefrontal cortex (DLPFC). Treatment parameters (site, intensity, number of pulses) were adjusted on an ongoing basis guided by changes in symptom severity rating scale scores. qEEGs were recorded at pretreatment baseline and after 1 week of left DLPFC (L-DLPFC) rTMS using a 21-channel dry-electrode headset. Analyses examined the association between week 1 regional changes in theta band (4-8 Hz) cordance, and week 6 patient- and physician-rated outcomes. Theta cordance change in the central brain region predicted percent change in Inventory of Depressive Symptomology-Self-Report (IDS-SR) score, and improvement versus nonimprovement on the Clinical Global Impression-Improvement Inventory (CGI-I) ( R² = .38, P = .007; and Nagelkerke R² = .78, P = .0001, respectively). The cordance biomarker remained significant when controlling for age, gender, and baseline severity. Treatment-emergent change in EEG theta cordance in the first week of rTMS may predict acute (6-week) treatment outcome in MDD. This oscillatory synchrony biomarker merits further study in independent samples.

The serotonin hallucinogen 5-MeO-DMT alters cortico-thalamic activity in freely moving mice: Regionally-selective involvement of 5-HT1A and 5-HT2A receptors

5-MeO-DMT is a natural hallucinogen acting as serotonin 5-HT_1A/5-HT_2A receptor agonist. Its ability to evoke hallucinations could be used to study the neurobiology of psychotic symptoms and to identify new treatment targets. Moreover, recent studies revealed the therapeutic potential of serotonin hallucinogens in treating mood and anxiety disorders. Our previous results in anesthetized animals show that 5-MeO-DMT alters cortical activity via 5-HT_1A and 5-HT_2A receptors. Here, we examined 5-MeO-DMT effects on oscillatory activity in prefrontal (PFC) and visual (V1) cortices, and in mediodorsal thalamus (MD) of freely-moving wild-type (WT) and 5-HT_2A-R knockout (KO2A) mice. We performed local field potential multi-recordings evaluating the power at different frequency bands and coherence between areas. We also examined the prevention of 5-MeO-DMT effects by the 5-HT_1A-R antagonist WAY-100635. 5-MeO-DMT affected oscillatory activity more in cortical than in thalamic areas. More marked effects were observed in delta power in V1 of KO2A mice. 5-MeO-DMT increased beta band coherence between all examined areas. In KO2A mice, WAY100635 prevented most of 5-MeO-DMT effects on oscillatory activity. The present results indicate that hallucinatory activity of 5-MeO-DMT is likely mediated by simultaneous alteration of prefrontal and visual activities. The prevention of these effects by WAY-100635 in KO2A mice supports the potential usefulness of 5-HT_1A receptor antagonists to treat visual hallucinations. 5-MeO-DMT effects on PFC theta activity and cortico-thalamic coherence may be related to its antidepressant activity. This article is part of the Special Issue entitled 'Psychedelics: New Doors, Altered Perceptions'.

Quantitative Electroencephalographic Biomarkers in Preclinical and Human Studies of Huntington's Disease: Are They Fit-for-Purpose for Treatment Development?

A major focus in development of novel therapies for Huntington's disease (HD) is identification of treatments that reduce the burden of mutant huntingtin (mHTT) protein in the brain. In order to identify and test the efficacy of such therapies, it is essential to have biomarkers that are sensitive to the effects of mHTT on brain function to determine whether the intervention has been effective at preventing toxicity in target brain systems before onset of clinical symptoms. Ideally, such biomarkers should have a plausible physiologic basis for detecting the effects of mHTT, be measureable both in preclinical models and human studies, be practical to measure serially in clinical trials, and be reliably measurable in HD gene expansion carriers (HDGECs), among other features. Quantitative electroencephalography (qEEG) fulfills many of these basic criteria of a "fit-for-purpose" biomarker. qEEG measures brain oscillatory activity that is regulated by the brain structures that are affected by mHTT in premanifest and early symptom individuals. The technology is practical to implement in the laboratory and is well tolerated by humans in clinical trials. The biomarkers are measureable across animal models and humans, with findings that appear to be detectable in HDGECs and translate across species. We review here the literature on recent developments in both preclinical and human studies of the use of qEEG biomarkers in HD, and the evidence for their usefulness as biomarkers to help guide development of novel mHTT lowering treatments.