Rostral anterior cingulate cortex activity and early symptom improvement during treatment for major depressive disorder

Impact of response shift effects in the assessment of self-reported depression during treatment: Insights from a rTMS versus Venlafaxine randomized controlled trial

PURPOSE

Patient-Reported Outcomes are essential to properly assess treatment effectiveness in randomized clinical trial (RCT) for Major Depressive Disorder (MDD). MDD self-assessment may vary over time depending on change in the meaning of patients' self-evaluation of depression, i.e. Response Shift (RS). Our aim was to investigate RS and its impact on different depression domains in a clinical trial comparing rTMS versus Venlafaxine.

METHODS

The occurrence and type of RS was determined using Structural Equation Modeling applied to change over time in 3 domains (Sad Mood, Performance Impairment, Negative Self-Reference) of the short-form Beck Depression Inventory (BDI-13) in a secondary analysis of a RCT on 170 patients with MDD treated by rTMS, venlafaxine or both.

RESULTS

RS was evidenced in the venlafaxine group in the Negative Self-Reference and Sad Mood domains.

CONCLUSION

RS effects differed between treatment arms in self-reported depression domains in patients with MDD. Ignoring RS would have led to a slight underestimation of depression improvement, depending on treatment group. Further investigations of RS and advancing new methods are needed to better inform decision making based on Patient-Reported Outcomes.

The update of self-identity: Importance of assessing autobiographical memory in major depressive disorder

Major depressive disorder is a leading global cause of disability. There is a growing interest for memory in mood disorders since it might constitute an original tool for prevention, diagnosis, and treatment. MDD is associated with impaired autobiographical memory characterized by a tendency to overgeneral memory, rather than vivid episodic self-defining memory, which is mandatory for problem-solving and projection in the future. This memory bias is maintained by three mechanisms: ruminations, avoidance, and impaired executive control. If we adopt a broader and comprehensive perspective, we can hypothesize that all those alterations have the potential to impair self-identity updating. We posit that this update requires a double referencing process: (1) to internalized self-representation and (2) to an externalized framework dealing with the representation of the consequence of actions. Diagnostic and therapeutic implications are discussed in the light of this model and the importance of assessing autobiographical memory in MDD is highlighted. This article is categorized under: Psychology > Memory Psychology > Brain Function and Dysfunction Neuroscience > Clinical.

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.

Rostral anterior cingulate network effective connectivity in depressed adolescents and associations with treatment response in a randomized controlled trial

The rostral anterior cingulate cortex (rACC) is consistently implicated in the neurobiology of depression. While the functional connectivity of the rACC has been previously associated with treatment response, there is a paucity of work investigating the specific directional interactions underpinning these associations. We compared the fMRI resting-state effective connectivity of 94 young people with major depressive disorder and 91 healthy controls. Following the fMRI scan, patients were randomized to receive cognitive behavioral therapy for 12 weeks, plus either fluoxetine or a placebo. Using spectral dynamic causal modelling, we examined the effective connectivity of the rACC with eight other regions implicated in depression: the left and right anterior insular cortex (AIC), amygdalae, and dorsolateral prefrontal cortex (dlPFC); and in the midline, the subgenual (sgACC) and dorsal anterior cingulate cortex (dACC). Parametric empirical Bayes was used to compare baseline differences between controls and patients and responders and non-responders to treatment. Depressed patients demonstrated greater inhibitory connectivity from the rACC to the dlPFC, AIC, dACC and left amygdala. Moreover, treatment responders illustrated greater inhibitory connectivity from the rACC to dACC, greater excitatory connectivity from the dACC to sgACC and reduced inhibitory connectivity from the sgACC to amygdalae at baseline. The inhibitory hyperconnectivity of the rACC in depressed patients aligns with hypotheses concerning the dominance of the default mode network over other intrinsic brain networks. Surprisingly, treatment responders did not demonstrate connectivity which was more similar to healthy controls, but rather distinct alterations that may have predicated their enhanced treatment response.

Suppressed activity of the rostral anterior cingulate cortex as a biomarker for depression remission

BACKGROUND

Suppression of the rostral anterior cingulate cortex (rACC) has shown promise as a prognostic biomarker for depression. We aimed to use machine learning to characterise its ability to predict depression remission.

METHODS

Data were obtained from 81 15- to 25-year-olds with a major depressive disorder who had participated in the YoDA-C trial, in which they had been randomised to receive cognitive behavioural therapy plus either fluoxetine or placebo. Prior to commencing treatment patients performed a functional magnetic resonance imaging (fMRI) task to assess rACC suppression. Support vector machines were trained on the fMRI data using nested cross-validation, and were similarly trained on clinical data. We further tested our fMRI model on data from the YoDA-A trial, in which participants had completed the same fMRI paradigm.

RESULTS

Thirty-six of 81 (44%) participants in the YoDA-C trial achieved remission. Our fMRI model was able to predict remission status (AUC = 0.777 [95% confidence interval (CI) 0.638-0.916], balanced accuracy = 67%, negative predictive value = 74%, p < 0.0001). Clinical models failed to predict remission status at better than chance levels. Testing the model on the alternative YoDA-A dataset confirmed its ability to predict remission (AUC = 0.776, balanced accuracy = 64%, negative predictive value = 70%, p < 0.0001).

CONCLUSIONS

We confirm that rACC activity acts as a prognostic biomarker for depression. The machine learning model can identify patients who are likely to have difficult-to-treat depression, which might direct the earlier provision of enhanced support and more intensive therapies.

Psychobiology of Stress and Adolescent Depression (PSY SAD) Study: Protocol overview for an fMRI-based multi-method investigation

Depression is a common, often recurrent disorder that causes substantial disease burden worldwide, and this is especially true for women following the pubertal transition. According to the Social Signal Transduction Theory of Depression, stressors involving social stress and rejection, which frequently precipitate major depressive episodes, induce depressive symptoms in vulnerable individuals in part by altering the activity and connectivity of stress-related neural pathways, and by upregulating components of the immune system involved in inflammation. To test this theory, we recruited adolescent females at high and low risk for depression and assessed their psychological, neural, inflammatory, and genomic responses to a brief (10 minute) social stress task, in addition to trait psychological and microbial factors affecting these responses. We then followed these adolescents longitudinally to investigate how their multi-level stress responses at baseline were related to their biological aging at baseline, and psychosocial and clinical functioning over one year. In this protocol paper, we describe the theoretical motivations for conducting this study as well as the sample, study design, procedures, and measures. Ultimately, our aim is to elucidate how social adversity influences the brain and immune system to cause depression, one of the most common and costly of all disorders.

Traces of culture: The feedback loop between behavior, brain, and disorder

Culture is part of an extensive series of feedback loops, which involve multiple organismic levels including social contexts, cognitive mediations, neural processes, and behavior. Recent studies in neuroscience show that culturally contingent social processes shape some neural pathways. Studying the influence of cultural context on neural processes may yield new insights into psychiatric disorders. New methodologies in the neurosciences offer innovative ways to assess the impact of culture on mental health and illness. However, implementing these methodologies raises important theoretical and ethical concerns, which must be resolved to address patient individuality and the complexity of cultural diversity. This article discusses cultural context as a major influence on (and consequence of) human neural plasticity and advocates a culture-brain-behavior (CBB) interaction model for conceptualizing the relationship between culture, brain, and psychiatric disorders. Recommendations are made for integrating neuroscientific techniques into transcultural psychiatric research by taking a systems approach to evaluating disorders.

Connectivity between the anterior insula and dorsolateral prefrontal cortex links early symptom improvement to treatment response

BACKGROUND

Early improvement (EI) following treatment with antidepressants is a widely reported predictor to the treatment response. This study aimed to identify the resting-state functional connectivity (rs-FC) and its related clinical features that link the treatment response at the time of EI.

METHODS

This study included 23 first-episode treatment-naive patients with MDD. After 2 weeks of antidepressant treatment, these patients received 3.0 Tesla resting-state functional magnetic resonance imaging scanning and were subgrouped into an EI group (N = 13) and a non-EI group (N = 10). Using the anterior insula (rAI) as a seed region, this study identified the rs-FC that were associated with both EI and the treatment response at week 12, and further tested the associations of the identified rs-FC with either the clinical features or the early symptom improvement.

RESULTS

Rs-FC between rAI and the left dorsolateral prefrontal cortex (dlPFC) was associated with EI (t₂₁ = -6.091, p = 0.022 after FDR correction for multiple comparisons). This rs-FC was also associated with an interaction between EI and the treatment response at the week 12 (t₂₁ = -5.361, p = 6.37e-5). Moreover, among the clinical features, this rs-FC was associated with the early symptom improvement in the insomnia, somatic symptoms, and anxiety symptoms, and these early symptom improvements were associated with the treatment response.

CONCLUSION

Rs-FC between the rAI and the left dlPFC played a crucial role in the early antidepressant effect, which linked the treatment response. The early treatment effect relating to rAI may represent an early symptom improvement in self-perceptual anxiety, somatic symptoms and insomnia.

Brainwaves Oscillations as a Potential Biomarker for Major Depression Disorder Risk

Major depressive disorder (MDD) is a multidimensional disorder that is characterized by the presence of alterations in mood, cognitive capacity, sensorimotor, and homeostatic functions. Given that about half of the patients diagnosed with MDD do not respond to the various current treatments, new techniques are being sought to predict not only the course of the disease but also the characteristics that differentiate responders from non-responders. Using the electroencephalogram, a noninvasive and inexpensive tool, most studies have proposed that patients with MDD have some lateralization in brain electrical activity, with alterations in alpha and theta rhythms being observed, which would be related to dysfunctions in emotional capacity such as the absence or presence of responses to the different existing treatments. These alterations help in the identification of subjects at high risk of suffering from depression, in the differentiation into responders and nonresponders to various therapies (pharmacological, electroconvulsive therapy, and so on), as well as to establish in which period of the disease the treatment will be more effective. Although the data are still inconclusive and more research is needed, these alpha and theta neurophysiological markers could support future clinical practice when it comes to establishing an early diagnosis and treating state disorders more successfully and accurately of mood disorders.

Pilot Study of An Intracranial Electroencephalography Biomarker of Depressive Symptoms in Epilepsy

OBJECTIVES

Adult patients with epilepsy have an increased prevalence of major depressive disorder (MDD). Intracranial EEG (iEEG) captured during extended inpatient monitoring of patients with treatment-resistant epilepsy offers a particularly promising method to study MDD networks in epilepsy.

METHODS

The authors used 24 hours of resting-state iEEG to examine the neural activity patterns within corticolimbic structures that reflected the presence of depressive symptoms in 13 adults with medication-refractory epilepsy. Principal component analysis was performed on the z-scored mean relative power in five standard frequency bands averaged across electrodes within a region.

RESULTS

Principal component 3 was a statistically significant predictor of the presence of depressive symptoms (R²=0.35, p=0.014). A balanced logistic classifier model using principal component 3 alone correctly classified 78% of patients as belonging to the group with a high burden of depressive symptoms or a control group with minimal depressive symptoms (sensitivity, 75%; specificity, 80%; area under the curve=0.8, leave-one-out cross validation). Classification was dependent on beta power throughout the corticolimbic network and low-frequency cingulate power.

CONCLUSIONS

These finding suggest, for the first time, that neural features across circuits involved in epilepsy may distinguish patients who have depressive symptoms from those who do not. Larger studies are required to validate these findings and to assess their diagnostic utility in MDD.

Pretreatment Rostral Anterior Cingulate Cortex Connectivity With Salience Network Predicts Depression Recovery: Findings From the EMBARC Randomized Clinical Trial

BACKGROUND

Baseline rostral anterior cingulate cortex (rACC) activity is a well-replicated nonspecific predictor of depression improvement. The rACC is a key hub of the default mode network, which prior studies indicate is hyperactive in major depressive disorder. Because default mode network downregulation is reliant on input from the salience network and frontoparietal network, an important question is whether rACC connectivity with these systems contributes to depression improvement.

METHODS

Our study evaluated this hypothesis in outpatients (N = 238; 151 female) enrolled in the Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care (EMBARC) 8-week randomized clinical trial of sertraline versus placebo for major depressive disorder. Depression severity was measured using the Hamilton Rating Scale for Depression, and electroencephalography was recorded at baseline and week 1. Exact low-resolution electromagnetic tomography was used to compute activity from the rACC, and key regions within the default mode network (posterior cingulate cortex), frontoparietal network (left dorsolateral prefrontal cortex), and salience network (right anterior insula [rAI]). Connectivity in the theta band (4.5-7 Hz) and beta band (12.5-21 Hz) was computed using lagged phase synchronization.

RESULTS

Stronger baseline theta-band rACC-rAI (salience network hub) connectivity predicted greater depression improvement across 8 weeks of treatment for both treatment arms (B = -0.57, 95% confidence interval = -1.07, -0.08, p = .03). Early increases in theta-band rACC-rAI connectivity predicted greater likelihood of achieving remission at week 8 (odds ratio = 2.90, p = .03).

CONCLUSIONS

Among patients undergoing treatment, theta-band rACC-rAI connectivity is a prognostic, albeit treatment-nonspecific, indicator of depression improvement, and early connectivity changes may predict clinically meaningful outcomes.

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.

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

IMPORTANCE

Major depressive disorder (MDD) remains challenging to treat. Although several clinical and demographic variables have been found to predict poor antidepressant response, these markers have not been robustly replicated to warrant implementation in clinical care. Increased pretreatment rostral anterior cingulate cortex (rACC) theta activity has been linked to better antidepressant outcomes. However, no prior study has evaluated whether this marker has incremental predictive validity over clinical and demographic measures.

OBJECTIVE

To determine whether increased pretreatment rACC theta activity would predict symptom improvement regardless of randomization arm.

DESIGN, SETTING, AND PARTICIPANTS

A multicenter randomized clinical trial enrolled outpatients without psychosis and with chronic or recurrent MDD between July 29, 2011, and December 15, 2015 (Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care [EMBARC]). Patients were consecutively recruited from 4 university hospitals: 634 patients were screened, 296 were randomized to receive sertraline hydrochloride or placebo, 266 had electroencephalographic (EEG) recordings, and 248 had usable EEG data. Resting EEG data were recorded at baseline and 1 week after trial onset, and rACC theta activity was extracted using source localization. Intent-to-treat analysis was conducted. Data analysis was performed from October 7, 2016, to January 19, 2018.

INTERVENTIONS

An 8-week course of sertraline or placebo.

MAIN OUTCOMES AND MEASURES

The 17-item Hamilton Rating Scale for Depression score (assessed at baseline and weeks 1, 2, 3, 4, 6, and 8).

RESULTS

The 248 participants (160 [64.5%] women, 88 [35.5%] men) with usable EEG data had a mean (SD) age of 36.75 (13.15) years. Higher rACC theta activity at both baseline (b = -1.05; 95% CI, -1.77 to -0.34; P = .004) and week 1 (b = -0.83; 95% CI, -1.60 to -0.06; P < .04) predicted greater depressive symptom improvement, even when controlling for clinical and demographic variables previously linked with treatment outcome. These effects were not moderated by treatment arm. The rACC theta marker, in combination with clinical and demographic variables, accounted for an estimated 39.6% of the variance in symptom change (with 8.5% of the variance uniquely attributable to the rACC theta marker).

CONCLUSIONS AND RELEVANCE

Increased pretreatment rACC theta activity represents a nonspecific prognostic marker of treatment outcome. This is the first study to date to demonstrate that rACC theta activity has incremental predictive validity.

TRIAL REGISTRATION

clinicaltrials.gov Identifier: NCT01407094.

Dissociative states in borderline personality disorder and their relationships to psychotropic medication

BACKGROUND

According to recent data, dissociation may play an important role in borderline personality disorder (BPD), nevertheless specific influences of psychotropic medication on dissociative symptoms in BPD and their therapeutic indications are largely unknown. The purpose of this study was to assess relationships of dissociative symptoms in BPD patients with levels of psychotropic medication and compare these results with a subgroup of patients with schizophrenia.

MATERIALS AND METHODS

In this study, we investigated 52 BPD patients and compared the results with a control group of 36 schizophrenia patients. In all participants, we assessed actual day doses of antipsychotic medication in chlorpromazine equivalents and antidepressant medication in fluoxetine equivalents. Dissociative symptoms were measured by Dissociative Experiences Scale (DES), and other psychopathological symptoms were measured using Health of the Nation Outcome Scales.

RESULTS

Results indicate that dissociative symptoms measured by DES were significantly correlated with antipsychotic medication (Spearman R=0.45, P<0.01) in chlorpromazine equivalents and antidepressant medication in fluoxetine equivalents (0.36, P<0.01). These relationships between medication and dissociative symptoms were not found in the control group of schizophrenia patients.

CONCLUSION

The results suggest that levels of antipsychotic medication and antidepressant medication are significantly associated with dissociative symptoms in BPD but not in schizophrenia.

A Novel Strategy to Identify Placebo Responders: Prediction Index of Clinical and Biological Markers in the EMBARC Trial

BACKGROUND

One in three clinical trial patients with major depressive disorder report symptomatic improvement with placebo. Strategies to mitigate the effect of placebo responses have focused on modifying study design with variable success. Identifying and excluding or controlling for individuals with a high likelihood of responding to placebo may improve clinical trial efficiency and avoid unnecessary medication trials.

METHODS

Participants included those assigned to the placebo arm (n = 141) of the Establishing Moderators and Biosignatures for Antidepressant Response in Clinical Care (EMBARC) trial. The elastic net was used to evaluate 283 baseline clinical, behavioral, imaging, and electrophysiological variables to identify the most robust yet parsimonious features that predicted depression severity at the end of the double-blind 8-week trial. Variables retained in at least 50% of the 100 imputed data sets were used in a Bayesian multiple linear regression model to simultaneously predict the probabilities of response and remission.

RESULTS

Lower baseline depression severity, younger age, absence of melancholic features or history of physical abuse, less anxious arousal, less anhedonia, less neuroticism, and higher average theta current density in the rostral anterior cingulate predicted a higher likelihood of improvement with placebo. The Bayesian model predicted remission and response with an actionable degree of accuracy (both AUC > 0.73). An interactive calculator was developed predicting the likelihood of placebo response at the individual level.

CONCLUSION

Easy-to-measure clinical, behavioral, and electrophysiological assessments can be used to identify placebo responders with a high degree of accuracy. Development of this calculator based on these findings can be used to identify potential placebo responders.

Recent advances in predicting responses to antidepressant treatment

Major depressive disorder is one of the leading causes of disability in the world since depression is highly frequent and causes a strong burden. In order to reduce the duration of depressive episodes, clinicians would need to choose the most effective therapy for each individual right away. A prerequisite for this would be to have biomarkers at hand that would predict which individual would benefit from which kind of therapy (for example, pharmacotherapy or psychotherapy) or even from which kind of antidepressant class. In the past, neuroimaging, electroencephalogram, genetic, proteomic, and inflammation markers have been under investigation for their utility to predict targeted therapies. The present overview demonstrates recent advances in all of these different methodological areas and concludes that these approaches are promising but also that the aim to have such a marker available has not yet been reached. For example, the integration of markers from different systems needs to be achieved. With ongoing advances in the accuracy of sensing techniques and improvement of modelling approaches, this challenge might be achievable.

Salience Network Functional Connectivity Predicts Placebo Effects in Major Depression

BACKGROUND

Recent neuroimaging studies have demonstrated resting-state functional connectivity (rsFC) abnormalities among intrinsic brain networks in Major Depressive Disorder (MDD); however, their role as predictors of treatment response has not yet been explored. Here, we investigate whether network-based rsFC predicts antidepressant and placebo effects in MDD.

METHODS

We performed a randomized controlled trial of two weeklong, identical placebos (described as having either "active" fast-acting, antidepressant effects or as "inactive") followed by a ten-week open-label antidepressant medication treatment. Twenty-nine participants underwent a rsFC fMRI scan at the completion of each placebo condition. Networks were isolated from resting-state blood-oxygen-level-dependent signal fluctuations using independent component analysis. Baseline and placebo-induced changes in rsFC within the default-mode, salience, and executive networks were examined for associations with placebo and antidepressant treatment response.

RESULTS

Increased baseline rsFC in the rostral anterior cingulate (rACC) within the salience network, a region classically implicated in the formation of placebo analgesia and the prediction of treatment response in MDD, was associated with greater response to one week of active placebo and ten weeks of antidepressant treatment. Machine learning further demonstrated that increased salience network rsFC, mainly within the rACC, significantly predicts individual responses to placebo administration.

CONCLUSIONS

These data demonstrate that baseline rsFC within the salience network is linked to clinical placebo responses. This information could be employed to identify patients who would benefit from lower doses of antidepressant medication or non-pharmacological approaches, or to develop biomarkers of placebo effects in clinical trials.

Current source density analysis of resting state EEG in depression: a review

Electroencephalography (EEG) has been widely used in the neurophysiological investigation of major depressive disorder (MDD) during past decades. An approach that has attracted particular interest over the past 20 years is current source density (CSD) that assesses current source in extracellular spaces, which are the local generators of the field potentials caused by the activation of neurones. Our aim was to review the current literature regarding resting state CSD analysis in MDD patients. To date, the most prominent aspects in such studies comprise the identification of clinical endophenotypes on the basis of resting state CSD, and the investigation of CSD with respect to treatment outcome prediction. Increased alpha band resting state CSD in frontal regions is typical for MDD, while increased theta band activity in the rostral anterior cingulate gyrus (rACC) has been found to be a good predictor of better antidepressant response. However, differences in the methods used in different studies could be responsible for some contradictions in reported findings. Further research is needed for better distinction of depressive patients from patients with other psychiatric disorders, as well as from healthy subjects.

Multimodal approaches to define network oscillations in depression

The renaissance in the use of encephalography-based research methods to probe the pathophysiology of neuropsychiatric disorders is well afoot and continues to advance. Building on the platform of neuroimaging evidence on brain circuit models, magnetoencephalography, scalp electroencephalography, and even invasive electroencephalography are now being used to characterize brain network dysfunctions that underlie major depressive disorder using brain oscillation measurements and associated treatment responses. Such multiple encephalography modalities provide avenues to study pathologic network dynamics with high temporal resolution and over long time courses, opportunities to complement neuroimaging methods and findings, and new approaches to identify quantitative biomarkers that indicate critical targets for brain therapy. Such goals have been facilitated by the ongoing testing of novel invasive neuromodulation therapies, notably, deep brain stimulation, where clinically relevant treatment effects can be monitored at multiple brain sites in a time-locked causal manner. We review key brain rhythms identified in major depressive disorder as foundation for development of putative biomarkers for objectively evaluating neuromodulation success and for guiding deep brain stimulation or other target-based neuromodulation strategies for treatment-resistant depression patients.

Persistent decrease in alpha current density in fully remitted subjects with major depressive disorder treated with fluoxetine: A prospective electric tomography study

Major depressive disorder (MDD) is recurrent, and its pathophysiology is not fully understood. Studies using electric tomography (ET) have identified abnormalities in the current density (CD) of MDD subjects in regions associated with the neurobiology of MDD, such as the anterior cingulate cortex (ACC) and medial orbitofrontal cortex (mOFC). However, little is known regarding the long-term CD changes in MDD subjects who respond to antidepressants. The aim of this study was to compare CD between healthy and MDD subjects who received 1-year open-label treatment with fluoxetine. Thirty-two-channel electroencephalograms (EEGs) were collected from 70 healthy controls and 74 MDD subjects at baseline (pre-treatment), 1 and 2weeks and 1, 2, 6, 9 and 12months. Variable-resolution ET (VARETA) was used to assess the CD between subject groups at each time point. The MDD group exhibited decreased alpha CD (αCD) in the occipital and parietal cortices, ACC, mOFC, thalamus and caudate nucleus at each time point. The αCD abnormalities persisted in the MDD subjects despite their achieving full remission. The low sub-alpha band was different between the healthy and MDD subjects. Differences in the amount of αCD between sexes and treatment outcomes were observed. Lack of a placebo arm and the loss of depressed patients to follow-up were significant limitations. The persistence of the decrease in αCD might suggest that the underlying pathophysiologic mechanisms of MDD are not corrected despite the asymptomatic state of MDD subjects, which could be significant in understanding the highly recurrent nature of MDD.

Brain functional changes in facial expression recognition in patients with major depressive disorder before and after antidepressant treatment: A functional magnetic resonance imaging study

Functional magnetic resonance imaging was used during emotion recognition to identify changes in functional brain activation in 21 first-episode, treatment-naive major depressive disorder patients before and after antidepressant treatment. Following escitalopram oxalate treatment, patients exhibited decreased activation in bilateral precentral gyrus, bilateral middle frontal gyrus, left middle temporal gyrus, bilateral postcentral gyrus, left cingulate and right parahippocampal gyrus, and increased activation in right superior frontal gyrus, bilateral superior parietal lobule and left occipital gyrus during sad facial expression recognition. After antidepressant treatment, patients also exhibited decreased activation in the bilateral middle frontal gyrus, bilateral cingulate and right parahippocampal gyrus, and increased activation in the right inferior frontal gyrus, left fusiform gyrus and right precuneus during happy facial expression recognition. Our experimental findings indicate that the limbic-cortical network might be a key target region for antidepressant treatment in major depressive disorder.

Resting-state functional connectivity in anterior cingulate cortex in normal aging

Growing evidence suggests that normal aging is associated with cognitive decline and well-maintained emotional well-being. The anterior cingulate cortex (ACC) is an important brain region involved in emotional and cognitive processing. We investigated resting-state functional connectivity (FC) of two ACC subregions in 30 healthy older adults vs. 33 healthy younger adults, by parcellating into rostral (rACC) and dorsal (dACC) ACC based on clustering of FC profiles. Compared with younger adults, older adults demonstrated greater connection between rACC and anterior insula, suggesting that older adults recruit more proximal dACC brain regions connected with insula to maintain a salient response. Older adults also demonstrated increased FC between rACC and superior temporal gyrus and inferior frontal gyrus, decreased integration between rACC and default mode, and decreased dACC-hippocampal and dACC-thalamic connectivity. These altered FCs reflected rACC and dACC reorganization, and might be related to well emotion regulation and cognitive decline in older adults. Our findings provide further insight into potential functional substrates of emotional and cognitive alterations in the aging brain.

The neuroscience of depression: implications for assessment and intervention

Major Depressive Disorder (MDD) is among the most prevalent of all psychiatric disorders and is the single most burdensome disease worldwide. In attempting to understand the profound deficits that characterize MDD across multiple domains of functioning, researchers have identified aberrations in brain structure and function in individuals diagnosed with this disorder. In this review we synthesize recent data from human neuroimaging studies in presenting an integrated neural network framework for understanding the impairments experienced by individuals with MDD. We discuss the implications of these findings for assessment of and intervention for MDD. We conclude by offering directions for future research that we believe will advance our understanding of neural factors that contribute to the etiology and course of depression, and to recovery from this debilitating disorder.

Amygdala-frontal couplings characterizing SSRI and placebo response in social anxiety disorder

In patients with social anxiety disorder (SAD) it has been reported that selective serotonin reuptake inhibitors (SSRIs) and placebo induce anxiolytic effects by attenuating neural activity in overlapping amygdala subregions, i.e. left basolateral and right ventrolateral amygdala. However, it is not known whether these treatments inhibit amygdala subregions via similar or distinct brain pathways. As anxiolytic treatments may alter amygdala-frontal couplings we investigated differences and similarities in amygdala-frontal functional co-activation patterns between responders and nonresponders to SSRIs and placebo in patients with SAD. Positron emission tomography (PET) with oxygen-15-labeled water was used to measure anxiety-related regional cerebral blood flow in 72 patients with SAD before and after 6-8 wk of treatment under double-blind conditions. Functional couplings were evaluated with a seed region approach using voxel values from the left basolateral and right ventrolateral amygdala. Responders and nonresponders to SSRIs and placebo showed different treatment-induced co-activations between the left amygdala and the dorsolateral prefrontal cortex (dlPFC) as well as the rostral anterior cingulate cortex (ACC). Conjunction analysis suggested shared anxiolysis-dependent inverse co-activations in SSRI and placebo responders between the left amygdala-dlPFC and left amygdala-rostral ACC, and a shared positive co-activation between left amygdala-dorsal ACC. We demonstrate that amygdala-frontal co-activation patterns differentiate effective from ineffective anxiolytic treatments and that SSRI and placebo responders share overlapping neuromodulatory paths that may underlie improved emotion regulation and reduced expression of anxiety.

TRIAL REGISTRATION

clinicaltrials.gov Identifier: NCT00343707.

Do prefrontal midline electrodes provide unique neurophysiologic information in Major Depressive Disorder?

Brain oscillatory activity from the midline prefrontal region has been shown to reflect brain dysfunction in subjects with Major Depressive Disorder (MDD). It is not known, however, whether electrodes from this area provide unique information about brain function in MDD. We examined a set of midline sites and two other prefrontal locations for detecting cerebral activity differences between subjects with MDD and healthy controls. Resting awake quantitative EEG (qEEG) data were recorded from 168 subjects: 47 never-depressed adults and 121 with a current major depressive episode. Individual midline electrodes (Fpz, Fz, Cz, Pz, and Oz) and prefrontal electrodes outside the hairline (Fp1, Fp2) were examined with absolute and relative power and cordance in the theta band. We found that MDD subjects exhibited higher values of cordance (p = 0.0066) at Fpz than controls; no significant differences were found at other locations, and power measures showed trend-level differences. Depressed adults showed higher midline cordance than did never-depressed subjects at the most-anterior midline channel. Salient abnormalities in MDD may be detectable by focusing on the prefrontal midline region, and EEG metrics from focused electrode arrays may offer clinical practicality for clinical monitoring.

Examining relations between alpha power as well as anterior cingulate cortex-localized theta activity and response to single or dual antidepressant pharmacotherapies

Electrocortical indices may be useful in predicting antidepressant response. Greater pretreatment alpha power and high rostral anterior cingulate cortex (rACC) theta activity tend to index a favorable outcome. The predictive utility of alpha power asymmetry has been under-explored. Baseline alpha2 (10.5-13.0 Hz) power/asymmetry, rACC theta2 (6.0-8.0 Hz) activity and early (one week) changes in these measures were assessed in relation to antidepressant response by week 12 to three treatment regimens (escitalopram (ESC) + bupropion (BUP), ESC or BUP) in patients with major depressive disorder (N=51). No treatment differences in response existed at week 12. Overall, treatment responders exhibited high, and non-responders low, frontal baseline alpha2 power. Frontal alpha2 power weakly discriminated responders/non-responders overall while posterior alpha2 power and BA25-localized theta2 activity strongly discriminated ESC responders/non-responders. No associations with alpha2 asymmetry and response emerged. BUP responders exhibited high, and BUP non-responders low, baseline rACC theta2 activity. Greater early decreases in rACC theta2 activity existed in ESC+BUP non-responders versus ESC+BUP responders. BUP responders exhibited greater rACC theta2 activity decreases than ESC responders. These preliminary results indicate that baseline and early changes in alpha2 and rACC theta2 activity associate with response and have implications for tailoring antidepressant treatments.

TMS by double-cone coil prefrontal stimulation for medication resistant chronic depression: a case report

A double-cone coil with large angled windings has been developed to modulate deeper brain areas such as the anterior cingulate cortex (ACC). Abnormal resting state activity in the pregenual ACC (pgACC), dorsal ACC (dACC) and subgenual ACC (sgACC) has been observed in depression. A patient with medication resistant chronic depression received ten sessions of transcranial magnetic stimulation (TMS) (10 Hz, 2000 stimuli/session) using a double-cone coil placed over the supplementary motor area, targeting the anterior cingulate. Source localized EEG recordings were conducted pre- and post-TMS. The Beck Depression Inventory (BDI-II) improved by 27%, and the two subscales of the Hospital Anxiety Depression Scale (HADS), namely depression (40%) and anxiety (33%) improved as well. Along with the clinical improvement eletrophysiological resting state activity changed in the dACC and sgACC in this patient in comparison to a normative group. The results of this case report further support the involvement of pgACC, dACC and sgACC activity in the pathophysiology of depression and indicate that modulation of neural activity in this area by high frequency TMS with a double-cone coil might represent a new promising approach in the treatment of medication resistant chronic depression.

Electrocortical features of depression and their clinical utility in assessing antidepressant treatment outcome

Major depressive disorder (MDD) is primarily characterized by decreased affect and accompanying behavioural consequences, but it is also associated with cognitive dysfunction. Assessment of electroencephalographic (EEG) activity and associated event-related potentials (ERPs; derived from averaged EEG activity in response to a stimulus) in the context of MDD has provided insights into the electrocortical abnormalities associated with the disorder. Importantly, EEG and ERPs also have emerged as candidates for predicting and optimizing antidepressant (AD) treatment outcome. This is critical in light of relatively low remission rates or a limited response to initial AD interventions. In contrast to other neuroimaging approaches, EEG and ERPs may be superior for predicting and monitoring AD response, as electrocortical measures are relatively inexpensive, easy to use, and have excellent temporal (that is, millisecond) resolution, enabling fine-grained assessment of basic cognitive and emotive processes. This review aims to highlight the most consistently noted EEG and ERP features in MDD, which may one day assist with diagnostic confirmation, as well as the potential clinical utility of specific electrocortical measures in aiding with response prediction.

Acute neural effects of selective serotonin reuptake inhibitors versus noradrenaline reuptake inhibitors on emotion processing: Implications for differential treatment efficacy

Clinical research has demonstrated differential efficacy of selective serotonin reuptake inhibitors (SSRIs) and norepinephrine reuptake inhibitors (NRIs), which may relate to differential acute effects these medications have on emotional brain processes. Here we present findings from a Multi-Level Kernel Density Analysis meta-analysis that integrates and contrasts activations from disparate fMRI studies in order to examine whether single dose SSRIs and NRIs have different effects on emotion processing tasks in healthy participants. Seven SSRI and four NRI studies were eligible for inclusion. SSRIs decreased amygdala responses, suggesting reduced emotional reactivity to emotional stimuli, whereas NRIs increased frontal and medial activation, suggesting increased emotion regulation. As hypothesised, an interaction of antidepressant and task type was found, such that SSRIs modulated amygdaloid-hippocampal, medial and frontal activity during both the presentation of faces and pictures, whereas NRIs only modulated the activation in medial and frontal regions during the presentation of pictures. Findings are interpreted within a novel model of the differential effects of SSRIs and NRIs on emotion processing.

α Power, α asymmetry and anterior cingulate cortex activity in depressed males and females

Left fronto-cortical hypoactivity, thought to reflect reduced activity in approach-related systems, and right parietal hypoactivity, associated with emotional under-arousal, have been noted in major depressive disorder (MDD). Altered theta activity in the anterior cingulate cortex (ACC) has also been associated with the disorder. We assessed resting frontal and parietal alpha asymmetry and power in non-medicated MDD (N = 53; 29 females) and control (N = 43; 23 females) individuals. Theta activity was examined using standardized low-resolution electromagnetic tomography (sLORETA) in the ACC [BA24ab and BA32 comprising the rostral ACC and BA25/subgenual (sg) ACC]. The MDD group, and particularly depressed males, displayed increased overall frontal and parietal alpha power and left midfrontal hypoactivity (alpha(2)-indexed). They also exhibited increased sgACC theta(2) activity. MDD females had increased right parietal activity, suggesting increased emotive arousal. Thus, unmedicated depressed adults were characterized by lower activity in regions implicated in approach/positive affective tendencies as well as diffuse cortical hypoarousal, though sex specific modulations emerged. Altered theta in the sgACC may reflect emotion regulation abnormalities in MDD.