Brain imaging correlates of depressive symptom severity and predictors of symptom improvement after antidepressant treatment

Baseline Striatal Functional Connectivity as a Predictor of Response to Antipsychotic Drug Treatment

OBJECTIVE

Clinical response to antipsychotic drug treatment is highly variable, yet prognostic biomarkers are lacking. The authors recently demonstrated that successful antipsychotic drug treatment alters resting-state functional connectivity of the striatum. The goal of the present study was to test whether intrinsic striatal connectivity patterns provide prognostic information and can serve as a potential biomarker of treatment response to antipsychotic drugs.

METHOD

The authors used resting-state functional MRI (fMRI) to develop a prognostic index in a discovery cohort of 41 first-episode schizophrenia patients, then tested this index in an independent cohort of 40 newly hospitalized chronic patients with acute psychosis. In the discovery cohort, patients underwent resting-state fMRI scanning at the initiation of randomized controlled treatment with a second-generation antipsychotic. Whole-brain functional connectivity maps were generated for each subject from striatal seed regions. A stringent measure of clinical response was calculated that required sustained improvement over two consecutive study visits. Clinical response was entered into a survival analysis, and Cox regression was applied to the functional connectivity data. A striatal connectivity index was created, comprising functional connections of the striatum that predicted treatment response. This striatal connectivity index was tested on a generalizability cohort of patients with psychotic disorders who were hospitalized for an acute psychotic episode.

RESULTS

A total of 91 regions functionally connected with the striatum provided significant prognostic information. Connectivity in these regions was used to create a baseline striatal connectivity index that predicted response to antipsychotic treatment with high sensitivity and specificity in both the discovery and generalizability cohorts.

CONCLUSIONS

These results provide evidence that individual differences in striatal functional connectivity predict response to antipsychotic drug treatment in acutely psychotic patients. With further development, this has the potential to serve as a prognostic biomarker with clinical utility and to reduce the overall burden associated with psychotic illnesses.

Imaging predictors of remission to anti-depressant medications in major depressive disorder

BACKGROUND

We review what is currently known about neuroimaging predictors of remission in major depressive disorder (MDD) after antidepressant medication (ADM) treatment.

METHODS

A systematic literature search found a total of twenty-seven studies comparing baseline neuroimaging findings in depressed patients who achieved remission with non-remitters following treatment with ADMs.

RESULTS

Eighteen of these studies utilised structural magnetic resonance imaging (MRI). These studies associated larger hippocampal (four studies) and cingulate volume (two studies) with remission. Two diffusion MRI studies identified a positive relationship between the fractional anisotropy of the cingulum bundle and remission. White matter signal hyperintensities were quantified in two papers - both observing decreased remission rates with increasing lesion burden. Nine studies on functional imaging met inclusion criteria - three using functional MRI, one with single photon emission computed tomography (SPECT), and five which evaluated patients with positron emission tomography (PET). These findings were not convergent, with different regions of interest interrogated.

LIMITATIONS

The studies were generally underpowered. Overall these data were heterogeneous with only a small number identifying concordant findings.

CONCLUSIONS

At present, the data remains inconsistent. The more promising biomarker of remission to ADMs appears to be hippocampal size, although this marker also has conflicting reports. Given remission should be the primary end-point of treatment, and that ADMs are the front-line treatment type for MDD, more focussed research is required to focus specifically on the imaging correlates of remission to ADMs.

Baseline brain perfusion and brain structure in patients with major depression: a multimodal magnetic resonance imaging study

BACKGROUND

Abnormal regional cerebral blood flow (rCBF) and grey matter volume have been frequently reported in patients with major depressive disorder (MDD). However, it is unclear to what extent structural and functional change co-occurs in patients with MDD and whether markers of neural activity, such as rCBF, can be predicted by structural change.

METHODS

Using MRI, we investigated resting-state rCBF and brain structure in patients with MDD and healthy controls between July 2008 and January 2013. We acquired perfusion images obtained with continuous arterial spin labelling, used voxel-based morphometry to assess grey matter volume and integrated biological parametric mapping analyses to investigate the impact of brain atrophy on rCBF.

RESULTS

We included 43 patients and 29 controls in our study. Frontotemporal grey matter volume was reduced in patients compared with controls. In patients, rCBF was reduced in the anterior cingulate and bilateral parahippocampal areas and increased in frontoparietal and striatal regions. These abnormalities were confirmed by analyses with brain volume as a covariate. In patients with MDD there were significant negative correlations between the extent of depressive symptoms and bilateral parahippocampal rCBF. We found a positive correlation between depressive symptoms and rCBF for right middle frontal cortical blood flow.

LIMITATIONS

Medication use in patients has to be considered as a limitation of our study.

CONCLUSION

Our data suggest that while changes of cerebral blood flow and brain volume co-occur in patients with MDD, structural change is not sufficient to explain altered neural activity in patients at rest. Abnormal brain structure and function in patients with MDD appear to reflect distinct levels of neuropathology.

A review of fMRI studies during visual emotive processing in major depressive disorder

OBJECTIVES

This review synthesized literature on brain activity, indexed by functional magnetic resonance imaging (fMRI), during visual affective information processing in major depressive disorder (MDD). Activation was examined in regions consistently implicated in emotive processing, including the anterior cingulate cortex (ACC), prefrontal cortex (PFC), amygdala, thalamus/basal ganglia and hippocampus. We also reviewed the effects of antidepressant interventions on brain activity during emotive processing.

METHODS

Sixty-four fMRI studies investigating neural activity during visual emotive information processing in MDD were included.

RESULTS

Evidence indicates increased ventro-rostral ACC activity to emotive stimuli and perhaps decreased dorsal ACC activity in MDD. Findings are inconsistent for the PFC, though medial PFC hyperactivity tends to emerge to emotive information processing in the disorder. Depressed patients display increased amygdala activation to negative and arousing stimuli. MDD may also be associated with increased activity to negative, and decreased activity to positive, stimuli in basal ganglia/thalamic structures. Finally, there may be increased hippocampus activation during negative information processing. Typically, antidepressant interventions normalize these activation patterns.

CONCLUSION

In general, depressed patients have increased activation to emotive, especially negative, visual stimuli in regions involved in affective processing, with the exception of certain PFC regions; this pattern tends to normalize with treatment.

Successful antidepressant chronotherapeutics enhance fronto-limbic neural responses and connectivity in bipolar depression

The identification of antidepressant response predictors in bipolar disorder (BD) may provide new potential enhancements in treatment selection. Repeated total sleep deprivation combined with light therapy (TSD+LT) can acutely reverse depressive symptoms and has been proposed as a model antidepressant treatment. This study aims at investigating the effect of TSD+LT on effective connectivity and neural response in cortico-limbic circuitries during implicit processing of fearful and angry faces in patients with BD. fMRI and Dynamic Causal Modeling (DCM) were combined to study the effect of chronotherapeutics on neural responses in healthy controls (HC, n = 35) and BD patients either responder (RBD, n = 26) or non responder (nRBD, n = 11) to 3 consecutive TSD+LT sessions. Twenty-four DCMs exploring connectivity between anterior cingulate cortex (ACC), dorsolateral prefrontal cortex (DLPFC), Amygdala (Amy), fusiform gyrus and visual cortex were constructed. After treatment, patients significantly increased their neural responses in DLPFC, ACC and insula. nRBD showed lower baseline and endpoint neural responses than RBD. The increased activity in ACC and in medial prefrontal cortex, associated with antidepressant treatment, was positively associated with the improvement of depressive symptomatology. Only RBD patients increased intrinsic connectivity from DLPFC to ACC and reduced the modulatory effect of the task on Amy-DLPFC connection. A successful antidepressant treatment was associated with an increased functional activity and connectivity within cortico-limbic networks, suggesting the possible role of these measures in providing possible biomarkers for treatment efficacy.

Ventromedial prefrontal cortex thinning in preschool-onset depression

BACKGROUND

The ventromedial prefrontal cortex (VMPFC) is a key center of affect regulation and processing, fundamental aspects of emotional competence which are disrupted in mood disorders. Structural alterations of VMPFC have consistently been observed in adult major depression and are associated with depression severity, yet it is unknown whether young children with depression demonstrate similar abnormalities. We investigated cortical thickness differences in the VMPFC of children with a history of preschool-onset depression (PO-MDD).

METHODS

Participants in a longitudinal study of PO-MDD underwent structural brain imaging between the ages of 7 and 12 years. Using local cortical distance metrics, cortical thickness of the VMPFC was compared in children with and without a history of PO-MDD.

RESULTS

Children previously diagnosed with PO-MDD (n=34) had significantly thinner right VMPFC vs. children without a history of PO-MDD [(n=95); F(1,126)=5.97, (p=.016)]. This effect was specific to children with a history of PO-MDD vs. other psychiatric conditions and was independent of comorbid anxiety or externalizing disorders. Decreases in right VMPFC thickness were predicted by preschool depressive symptoms independent of depressive symptoms in school age.

LIMITATIONS

Results are cross-sectional and cannot distinguish whether thinner right VMPFC represents a vulnerability marker of MDD, consequence of MDD, or marker of remitted MDD. Longitudinal imaging is needed to contextualize how this difference relates to normative VMPFC structural development.

CONCLUSIONS

Onset of depression at preschool age was associated with decreased cortical thickness of right VMPFC. This finding implicates the VMPFC in depression from very early stages of brain development.

A study on EEG-based brain electrical source of mild depressed subjects

BACKGROUND AND OBJECTIVE

Several abnormal brain regions are known to be linked to depression, including amygdala, orbitofrontal cortex (OFC), anterior cingulate cortex (ACC), and dorsolateral prefrontal cortex (DLPFC) etc. The aim of this study is to apply EEG (electroencephalogram) data analysis to investigate, with respect to mild depression, whether there exists dysregulation in these brain regions.

METHODS

EEG sources were assessed from 9 healthy and 9 mildly depressed subjects who were classified according to the Beck Depression Inventory (BDI) criteria. t-Test was used to calculate the eye movement data and standardized low resolution tomography (sLORETA) was used to correlate EEG activity.

RESULTS

A comparison of eye movement data between the healthy and mild depressed subjects exhibited that mildly depressed subjects spent more time viewing negative emotional faces. Comparison of the EEG from the two groups indicated higher theta activity in BA6 (Brodmann area) and higher alpha activity in BA38.

CONCLUSIONS

EEG source location results suggested that temporal pole activity to be dysregulated, and eye-movement data analysis exhibited mild depressed subjects paid much more attention to negative face expressions, which is also in accordance with the results of EEG source location.

Prefrontal thinning affects functional connectivity and regional homogeneity of the anterior cingulate cortex in depression

Major depressive disorder (MDD) is associated with structural and functional alterations in the prefrontal cortex (PFC) and anterior cingulate cortex (ACC). Enhanced ACC activity at rest (measured using various imaging methodologies) is found in treatment-responsive patients and is hypothesized to bolster treatment response by fostering adaptive rumination. However, whether structural changes influence functional coupling between fronto-cingulate regions and ACC regional homogeneity (ReHo) and whether these functional changes are related to levels of adaptive rumination and treatment response is still unclear. Cortical thickness and ReHo maps were calculated in 21 unmedicated depressed patients and 35 healthy controls. Regions with reduced cortical thickness defined the seeds for the subsequent functional connectivity (FC) analyses. Patients completed the Response Style Questionnaire, which provided a measure of adaptive rumination associated with better response to psychotherapy. Compared with controls, depressed patients showed thinning of the right anterior PFC, increased prefrontal connectivity with the supragenual ACC (suACC), and higher ReHo in the suACC. The suACC clusters of increased ReHo and FC spatially overlapped. In depressed patients, suACC ReHo scores positively correlated with PFC thickness and with FC strength. Moreover, stronger fronto-cingulate connectivity was related to higher levels of adaptive rumination. Greater suACC ReHo and connectivity with the right anterior PFC seem to foster adaptive forms of self-referential processing associated with better response to psychotherapy, whereas prefrontal thinning impairs the ability of depressed patients to engage the suACC during a major depressive episode. Bolstering the function of the suACC may represent a potential target for treatment.

Development and validation of a brain maturation index using longitudinal neuroanatomical scans

BACKGROUND

Major psychiatric disorders are increasingly being conceptualized as 'neurodevelopmental', because they are associated with aberrant brain maturation. Several studies have hypothesized that a brain maturation index integrating patterns of neuroanatomical measurements may reliably identify individual subjects deviating from a normative neurodevelopmental trajectory. However, while recent studies have shown great promise in developing accurate brain maturation indices using neuroimaging data and multivariate machine learning techniques, this approach has not been validated using a large sample of longitudinal data from children and adolescents.

METHODS

T1-weighted scans from 303 healthy subjects aged 4.88 to 18.35years were acquired from the National Institute of Health (NIH) pediatric repository (http://www.pediatricmri.nih.gov). Out of the 303 subjects, 115 subjects were re-scanned after 2years. The least absolute shrinkage and selection operator algorithm (LASSO) was 'trained' to integrate neuroanatomical changes across chronological age and predict each individual's brain maturity. The resulting brain maturation index was developed using first-visit scans only, and was validated using second-visit scans.

RESULTS

We report a high correlation between the first-visit chronological age and brain maturation index (r=0.82, mean absolute error or MAE=1.69years), and a high correlation between the second-visit chronological age and brain maturation index (r=0.83, MAE=1.71years). The brain maturation index captured neuroanatomical volume changes between the first and second visits with an MAE of 0.27years.

CONCLUSIONS

The brain maturation index developed in this study accurately predicted individual subjects' brain maturation longitudinally. Due to its strong clinical potentials in identifying individuals with an abnormal brain maturation trajectory, the brain maturation index may allow timely clinical interventions for individuals at risk for psychiatric disorders.

Autobiographical deficits correlate with gray matter volume in depressed and high risk participants

Autobiographical memory (AM) overgenerality is a consistent neuropsychological feature of major depressive disorder (MDD) and is present in individuals at high-familial risk (HR) of developing MDD. Structural changes have been found in brain regions implicated in AM recall in MDDs and HRs. However, the relationship between selective regional gray matter volume (GMV) differences and AM recall deficits has not been examined. We examined this relationship in 27 HR, 43 unmedicated MDD and 47 low-risk healthy control participants as they completed an AM task during functional magnetic resonance imaging. FreeSurfer was used for automated anatomical image processing and volumetric quantification. Anatomical regions of interest for GMV analysis were selected based on regions most commonly activated in controls as they recall specific AMs according to a recent meta-analysis. Pearson correlations were calculated among volumetric and AM recall data. In HRs and MDDs, left hippocampal volume correlated positively with specific (HRs r = 0.42; MDDs r = 0.60) and inversely with categorical AM recall (HRs r = -0.51; MDDs r = -0.35). In MDDs, left precuneus volume also correlated positively with specific (r = 0.49) and inversely with categorical (r = -0.35) AM recall. Our results suggest selective GMV alterations within the AM network may contribute to AM impairments observed in both HR and MDD individuals.

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.

Specificity of abnormal brain volume in major depressive disorder: a comparison with borderline personality disorder

BACKGROUND

Abnormal brain volume has been frequently demonstrated in major depressive disorder (MDD). It is unclear if these findings are specific for MDD since aberrant brain structure is also present in disorders with depressive comorbidity and affective dysregulation, such as borderline personality disorder (BPD). In this transdiagnostic study, we aimed to investigate if regional brain volume loss differentiates between MDD and BPD. Further, we tested for associations between brain volume and clinical variables within and between diagnostic groups.

METHODS

22 Females with a DSM-IV diagnosis of MDD, 17 females with a DSM-IV diagnosis of BPD and without comorbid posttraumatic stress disorder, and 22 age-matched female healthy controls (HC) were investigated using magnetic resonance imaging. High-resolution structural data were analyzed using voxel-based morphometry.

RESULTS

A significant (p<0.05, cluster-corrected) volume decrease of the anterior cingulate cortex (ACC) was found in MDD compared to HC, as opposed to volume decreases of the amygdala in BPD compared to both HC and MDD. Sensitivity and specificity of regional gray matter volume for a diagnosis of MDD were modest to fair. Amygdala volume was related to depressive symptoms across the entire patient sample.

LIMITATIONS

Potential limitations of this study include the modest sample size and the heterogeneous psychotropic drug treatment.

CONCLUSIONS

ACC volume reduction is more pronounced in MDD with an intermediate degree of volume loss in BPD compared to HC. In contrast, amygdala volume loss is more pronounced in BPD compared to MDD, yet amygdala volume is associated with affective symptom expression in both disorders.

Toward stratified treatments for bipolar disorders

In bipolar disorders, there are unclear diagnostic boundaries with unipolar depression and schizophrenia, inconsistency of treatment guidelines, relatively long trial-and-error phases of treatment optimization, and increasing use of complex combination therapies lacking empirical evidence. These suggest that the current definition of bipolar disorders based on clinical symptoms reflects a clinically and etiologically heterogeneous entity. Stratification of treatments for bipolar disorders based on biomarkers and improved clinical markers are greatly needed to increase the efficacy of currently available treatments and improve the chances of developing novel therapeutic approaches. This review provides a theoretical framework to identify biomarkers and summarizes the most promising markers for stratification regarding beneficial and adverse treatment effects. State and stage specifiers, neuropsychological tests, neuroimaging, and genetic and epigenetic biomarkers will be discussed with respect to their ability to predict the response to specific pharmacological and psychosocial psychotherapies for bipolar disorders. To date, the most reliable markers are derived from psychopathology and history-taking, while no biomarker has been found that reliably predicts individual treatment responses. This review underlines both the importance of clinical diagnostic skills and the need for biological research to identify markers that will allow the targeting of treatment specifically to sub-populations of bipolar patients who are more likely to benefit from a specific treatment and less likely to develop adverse reactions.

Identifying predictors, moderators, and mediators of antidepressant response in major depressive disorder: neuroimaging approaches

OBJECTIVE

Despite significant advances in neuroscience and treatment development, no widely accepted biomarkers are available to inform diagnostics or identify preferred treatments for individuals with major depressive disorder.

METHOD

In this critical review, the authors examine the extent to which multimodal neuroimaging techniques can identify biomarkers reflecting key pathophysiologic processes in depression and whether such biomarkers may act as predictors, moderators, and mediators of treatment response that might facilitate development of personalized treatments based on a better understanding of these processes.

RESULTS

The authors first highlight the most consistent findings from neuroimaging studies using different techniques in depression, including structural and functional abnormalities in two parallel neural circuits: serotonergically modulated implicit emotion regulation circuitry, centered on the amygdala and different regions in the medial prefrontal cortex; and dopaminergically modulated reward neural circuitry, centered on the ventral striatum and medial prefrontal cortex. They then describe key findings from the relatively small number of studies indicating that specific measures of regional function and, to a lesser extent, structure in these neural circuits predict treatment response in depression.

CONCLUSIONS

Limitations of existing studies include small sample sizes, use of only one neuroimaging modality, and a focus on identifying predictors rather than moderators and mediators of differential treatment response. By addressing these limitations and, most importantly, capitalizing on the benefits of multimodal neuroimaging, future studies can yield moderators and mediators of treatment response in depression to facilitate significant improvements in shorter- and longer-term clinical and functional outcomes.

Adolescents with current major depressive disorder show dissimilar patterns of age-related differences in ACC and thalamus

OBJECTIVE

There is little understanding of the neural system abnormalities subserving adolescent major depressive disorder (MDD). In a cross-sectional study we compare currently unipolar depressed with healthy adolescents to determine if group differences in grey matter volume (GMV) were influenced by age and illness severity.

METHOD

Structural neuroimaging was performed on 109 adolescents with current MDD and 36 healthy controls, matched for age, gender, and handedness. GMV differences were examined within the anterior cingulate cortex (ACC) and across the whole-brain. The effects of age and self-reported depressive symptoms were also examined in regions showing significant main or interaction effects.

RESULTS

Whole-brain voxel based morphometry revealed no significant group differences. At the whole-brain level, both groups showed a main effect of age on GMV, although this effect was more pronounced in controls. Significant group-by-age interactions were noted: A significant regional group-by-age interaction was observed in the ACC. GMV in the ACC showed patterns of age-related differences that were dissimilar between adolescents with MDD and healthy controls. GMV in the thalamus showed an opposite pattern of age-related differences in adolescent patients compared to healthy controls. In patients, GMV in the thalamus, but not the ACC, was inversely related with self-reported depressive symptoms.

CONCLUSIONS

The depressed adolescent brain shows dissimilar age-related and symptom-sensitive patterns of GMV differences compared with controls. The thalamus and ACC may comprise neural markers for detecting these effects in youth. Further investigations therefore need to take both age and level of current symptoms into account when disaggregating antecedent neural vulnerabilities for MDD from the effects of MDD on the developing brain.

Brain Structural Effects of Antidepressant Treatment in Major Depression

Depressive disorder is a very frequent and heterogeneous syndrome. Structural imaging techniques offer a useful tool in the comprehension of neurobiological alterations that concern depressive disorder. Altered brain structures in depressive disorder have been particularly located in the prefrontal cortex (medial prefrontal cortex and orbitofrontal cortex, OFC) and medial temporal cortex areas (hippocampus). These brain areas belong to a structural and functional network related to cognitive and emotional processes putatively implicated in depressive symptoms. These volumetric alterations may also represent biological predictors of response to pharmacological treatment. In this context, major findings of magnetic resonance (MR) imaging, in relation to treatment response in depressive disorder, will here be presented and discussed.

A Study of Long-Term fMRI Reproducibility Using Data-Driven Analysis Methods

The reproducibility of functional magnetic resonance imaging (fMRI) is important for fMRI-based neuroscience research and clinical applications. Previous studies show considerable variation in amplitude and spatial extent of fMRI activation across repeated sessions on individual subjects even using identical experimental paradigms and imaging conditions. Most existing fMRI reproducibility studies were typically limited by time duration and data analysis techniques. Particularly, the assessment of reproducibility is complicated by a fact that fMRI results may depend on data analysis techniques used in reproducibility studies. In this work, the long-term fMRI reproducibility was investigated with a focus on the data analysis methods. Two spatial smoothing techniques, including a wavelet-domain Bayesian method and the Gaussian smoothing, were evaluated in terms of their effects on the long-term reproducibility. A multivariate support vector machine (SVM)-based method was used to identify active voxels, and compared to a widely used general linear model (GLM)-based method at the group level. The reproducibility study was performed using multisession fMRI data acquired from eight healthy adults over 1.5 years' period of time. Three regions-of-interest (ROI) related to a motor task were defined based upon which the long-term reproducibility were examined. Experimental results indicate that different spatial smoothing techniques may lead to different reproducibility measures, and the wavelet-based spatial smoothing and SVM-based activation detection is a good combination for reproducibility studies. On the basis of the ROIs and multiple numerical criteria, we observed a moderate to substantial within-subject long-term reproducibility. A reasonable long-term reproducibility was also observed from the inter-subject study. It was found that the short-term reproducibility is usually higher than the long-term reproducibility. Furthermore, the results indicate that brain regions with high contrast-to-noise ratio do not necessarily exhibit high reproducibility. These findings may provide supportive information for optimal design/implementation of fMRI studies and data interpretation.

Impact of lingual gyrus volume on antidepressant response and neurocognitive functions in Major Depressive Disorder: a voxel-based morphometry study

BACKGROUND

Voxel-based morphometry (VBM) has demonstrated structural brain changes between patients with Major Depressive Disorder (MDD) and healthy individuals. The initial response to antidepressants is crucial to predict prognosis in the treatment of MDD. The aim of the present study was to investigate gray matter abnormalities predicting antidepressant responsiveness and the relationships between volumetric differences and clinical/cognitive traits in MDD patients.

METHODS

Fifty MDD patients who received 8 week period antidepressant treatment and 29 healthy controls participated in this study. VBM was applied to assess structural changes between MDD groups and control group. Neuropsychological tests were conducted on all participants.

RESULTS

Both treatment responsive and non-responsive patients showed a significant volume reduction of the left insular, but only non-responsive patients had decreased volume in the right superior frontal gyrus compared to healthy controls. The comparison between treatment responsive and non-responsive patient groups demonstrated a significant difference in gray matter volume in the lingual gyrus. The larger volume of lingual gryus predicted early antidepressant response, which was attributable to better performance in neuropsychological tests.

LIMITATION

This study included a small sample size and the patients received various antidepressants and benzodiazepines.

CONCLUSION

Our findings suggest that the patients who responded poorly to antidepressants were morphologically and cognitively impaired, whereas the treatment responsive patients showed less structural changes and relatively preserved cognitive functions. The lingual gyrus may be a possible candidate region to predict antidepressant responsiveness and maintained cognition in MDD.

Toward the application of functional neuroimaging to individualized treatment for anxiety and depression

Functional neuroimaging has led to significant gains in understanding the biological bases of anxiety and depressive disorders. However, the ability of functional neuroimaging to directly impact clinical practice is unclear. One important method by which neuroimaging could impact clinical care is to generate single patient level predictions that can guide clinical decision-making. The present review summarizes published functional neuroimaging studies of predictors of medication or psychotherapy outcome in major depressive disorder, obsessive-compulsive disorder (OCD), posttraumatic stress disorder, generalized anxiety disorder, panic disorder, and social anxiety disorder. In major depressive disorder and OCD, there is converging evidence of specific brain circuitry that has both been implicated in the disordered state itself, and where pretreatment activation levels have been predictive of treatment response. Specifically, in major depressive disorder, greater pretreatment ventral and pregenual anterior cingulate cortex (ACC) activation may predict better antidepressant medication outcome but poorer psychotherapy outcome. In OCD, activation in the ACC and orbitofrontal cortex has been inversely associated with pharmacological treatment response. In other anxiety disorders, research in this area is just beginning, with the ACC potentially implicated. However, the question of whether these results can directly translate to clinical practice remains open. In order to achieve the goal of single patient level prediction and individualized treatment, future research should strive to establish replicable models with good predictive performance and clear incremental validity.

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.

Unraveling the effects of plasticity and pain on personality

Chronic pain resulting from physical stressors is often accompanied by psychological disorders such as depression. Although depressive disorders are associated with changes in brain anatomy, it remains unknown if changes in brain anatomy associated with increased state depression levels also occur in patients with chronic pain. When individuals are experiencing physical stressors such as ongoing pain, depressive personality traits may predispose them to develop depressive states. The aim of this study was to use brain morphometry to determine the interaction among chronic pain, state and trait depression, and regional brain structure. We investigated regional gray matter volume in 42 chronic pain patients and 35 controls using voxel-based morphometry of T1-weighted anatomical images. Significant relationships between regional gray matter volume and state or trait depressive values were determined. In chronic pain patients, state depression scores were significantly correlated to subtle changes in the thalamus and the cingulate, dorsolateral prefrontal, and hippocampal cortices. These same brain regions were also significantly correlated to trait depressive scores. Unexpectedly, gray matter volumes in these regions were not correlated to trait depressive scores in healthy controls. Because trait depressive values were not correlated to gray matter in controls, but were so in chronic pain patients, these data strongly suggest that subtle changes in brain anatomy can evoke changes in individuals' trait depression values. If these regional gray matter changes are severe enough, changes in an individual's personality trait may result.

PERSPECTIVE

This study demonstrates anatomical brain alterations associated with both state and trait depression in chronic pain patients. Because our study reveals that trait depression is not correlated to the anatomy of these regions in healthy controls, ongoing pain itself may result in anatomical changes that in turn can alter an individual's personality.

Temporal-lobe morphology differs between healthy adolescents and those with early-onset of depression

Major depressive disorder (MDD) has previously been linked to structural changes in several brain regions, particularly in the medial temporal lobes (Bellani, Baiano, Brambilla, 2010; Bellani, Baiano, Brambilla, 2011). This has been determined using voxel-based morphometry, segmentation algorithms, and analysis of shape deformations (Bell-McGinty et al., 2002; Bergouignan et al., 2009; Posener et al., 2003; Vasic et al., 2008; Zhao et al., 2008): these are methods in which information related to the shape and the pose (the size, and anatomical position and orientation) of structures is lost. Here, we incorporate information about shape and pose to measure structural deformation in adolescents and young adults with and without depression (as measured using the Beck Depression Inventory and Diagnostic and Statistical Manual of Mental Disorders criteria). As a hypothesis-generating study, a significance level of p < 0.05, uncorrected for multiple comparisons, was used, so that subtle morphological differences in brain structures between adolescent depressed individuals and control participants could be identified. We focus on changes in cortical and subcortical temporal structures, and use a multi-object statistical pose and shape model to analyze imaging data from 16 females (aged 16-21) and 3 males (aged 18) with early-onset MDD, and 25 female and 1 male normal control participants, drawn from the same age range. The hippocampus, parahippocampal gyrus, putamen, and superior, inferior and middle temporal gyri in both hemispheres of the brain were automatically segmented using the LONI Probabilistic Brain Atlas (Shattuck et al., 2008) in MNI space. Points on the surface of each structure in the atlas were extracted and warped to each participant's structural MRI. These surface points were analyzed to extract the pose and shape features. Pose differences were detected between the two groups, particularly in the left and right putamina, right hippocampus, and left and right inferior temporal gyri. Shape differences were detected between the two groups, particularly in the left hippocampus and in the left and right parahippocampal gyri. Furthermore, pose measures were significantly correlated with BDI score across the whole (clinical and control) sample. Since the clinical participants were experiencing their very first episodes of MDD, morphological alteration in the medial temporal lobe appears to be an early sign of MDD, and is unlikely to result from treatment with antidepressants. Pose and shape measures of morphology, which are not usually analyzed in neuromorphometric studies, appear to be sensitive to depressive symptomatology.

Effects of antidepressant medication on emotion regulation in depressed patients: an iSPOT-D report

BACKGROUND

Antidepressant medication (ADM) is thought to reduce depressive symptoms by altering emotion-generative brain systems. However, it is unknown whether successful ADM treatment is associated with changes in psychobehavioral strategies used to regulate emotions. We examined depressive symptoms and emotion regulation strategies before and after ADM in the international Study to Predict Optimized Treatment in Depression (iSPOT-D).

METHODS

The study enrolled 1008 adult patients with MDD (18-65 years old) from 18 primary and psychiatric care sites worldwide. Patients were randomly assigned to an 8-week course of escitalopram, sertraline, or venlafaxine-extended-release. We examined whether ADM is associated with changes in suppression, usually associated with maladaptive outcomes, and reappraisal, usually associated with adaptive outcomes. We also tested whether changes in emotion regulation predict changes in depressive symptoms following ADM.

RESULTS

We observed more adaptive emotion regulation (decreased use of suppression and increased use of reappraisal) following ADM. Furthermore, the largest improvements in emotion regulation were associated with the best treatment outcomes.

LIMITATIONS

Because we assessed acute outcomes, it is not yet known if the effects of ADM on emotion regulation would persist over time.

CONCLUSIONS

ADMs are associated with acute, adaptive changes in the psychobehavioral strategies used to regulate emotions.

Magnetic resonance imaging predictors of treatment response in late-life depression

In older adults, depression not only results in more years lived with disability than any other disease but it also carries additional risks of suicide, medical comorbidities, and family caregiving burden. Because it can take many months to identify an effective treatment regimen, it is of utmost importance to shorten the window of time and identify early on what medications and dosages will work effectively for individuals having depression. Late-life depression (LLD) has been associated with greater burden of age-related changes (eg, atrophy, white matter ischemic changes, and functional connectivity). Depression in midlife has been shown to alter affective reactivity and regulation, and functional magnetic resonance imaging (fMRI) studies in LLD have replicated the same abnormalities. Effective treatment can normalize these alterations. This article provides a review of the current literature using structural and functional neuroimaging to identify MRI predictors of treatment response in LLD. The majority of the literature on structural MRI has focused on the vascular depression hypothesis, and studies support the view that loss of brain volume and white matter integrity was associated with poorer treatment outcomes. Studies using fMRI have reported that lower task-based activity in the prefrontal cortex and limbic regions was associated with poorer outcome. These imaging markers may be integrated into clinical decision making to attain better treatment outcomes in the future.

Brain regions related to fear extinction in obsessive-compulsive disorder and its relation to exposure therapy outcome: a morphometric study

BACKGROUND

The size of particular sub-regions within the ventromedial prefrontal cortex (vmPFC) has been associated with fear extinction in humans. Exposure therapy is a form of extinction learning widely used in the treatment of obsessive-compulsive disorder (OCD). Here we investigated the relationship between morphometric measurements of different sub-regions of the vmPFC and exposure therapy outcome in OCD.

METHOD

A total of 74 OCD patients and 86 healthy controls underwent magnetic resonance imaging (MRI). Cortical thickness and volumetric measurements were obtained for the rostral anterior cingulate cortex (rACC), the medial orbital frontal cortex and the subcallosal cortex. After MRI acquisition, patients were enrolled in an exposure therapy protocol, and we assessed the relationship between MRI-derived measurements and treatment outcome. Baseline between-group differences for such measurements were also assessed.

RESULTS

Compared with healthy controls, OCD patients showed a thinner left rACC (p = 0.008). Also, left rACC thickness was inversely associated with exposure therapy outcome (r - 0.32, p = 0.008), and this region was significantly thinner in OCD patients who responded to exposure therapy than in those who did not (p = 0.006). Analyses based on regional volumetry did not yield any significant results.

CONCLUSIONS

OCD patients showed cortical thickness reductions in the left rACC, and these alterations were related to exposure therapy outcome. The precise characterization of neuroimaging predictors of treatment response derived from the study of the brain areas involved in fear extinction may optimize exposure therapy planning in OCD and other anxiety disorders.

Are there meaningful biomarkers of treatment response for depression?

During the past decades, the prevalence of affective disorders has been on the rise globally, with only one out of three patients achieving remission in acute treatment with antidepressants. The identification of physiological markers that predict treatment course proves useful in increasing therapeutic success. On the basis of well-documented, recent findings in depression research, we highlight and discuss the most promising biomarkers for antidepressant therapy response. These include genetic variants and gene expression profiles, proteomic and metabolomic markers, neuroendocrine function tests, electrophysiology and imaging techniques. Ultimately, this review proposes an integrative use of biomarkers for antidepressant treatment outcome.

Diagnostic and therapeutic utility of neuroimaging in depression: an overview

A growing number of studies have used neuroimaging to further our understanding of how brain structure and function are altered in major depression. More recently, these techniques have begun to show promise for the diagnosis and treatment of depression, both as aids to conventional methods and as methods in their own right. In this review, we describe recent neuroimaging findings in the field that might aid diagnosis and improve treatment accuracy. Overall, major depression is associated with numerous structural and functional differences in neural systems involved in emotion processing and mood regulation. Furthermore, several studies have shown that the structure and function of these systems is changed by pharmacological and psychological treatments of the condition and that these changes in candidate brain regions might predict clinical response. More recently, "machine learning" methods have used neuroimaging data to categorize individual patients according to their diagnostic status and predict treatment response. Despite being mostly limited to group-level comparisons at present, with the introduction of new methods and more naturalistic studies, neuroimaging has the potential to become part of the clinical armamentarium and may improve diagnostic accuracy and inform treatment choice at the patient level.

No change in N-acetyl aspartate in first episode of moderate depression after antidepressant treatment: (1)H magnetic spectroscopy study of left amygdala and left dorsolateral prefrontal cortex

BACKGROUND

The role of brain metabolites as biological correlates of the intensity, symptoms, and course of major depression has not been determined. It has also been inconclusive whether the change in brain metabolites, measured with proton magnetic spectroscopy, could be correlated with the treatment outcome.

METHODS

Proton magnetic spectroscopy was performed in 29 participants with a first episode of moderate depression occurring in the left dorsolateral prefrontal cortex and left amygdala at baseline and after 8 weeks of antidepressant treatment with escitalopram. The Montgomery-Asberg Depression Rating Scale, the Hamilton Rating Scale for Depression, and the Beck Depression Inventory were used to assess the intensity of depression at baseline and at the endpoint of the study. At endpoint, the participants were identified as responders (n=17) or nonresponders (n=12) to the antidepressant therapy.

RESULTS

There was no significant change in the N-acetyl aspartate/creatine ratio (NAA/Cr) after treatment with antidepressant medication. The baseline and endpoint NAA/Cr ratios were not significantly different between the responder and nonresponder groups. The correlation between NAA/Cr and changes in the scores of clinical scales were not significant in either group.

CONCLUSION

This study could not confirm any significant changes in NAA after antidepressant treatment in the first episode of moderate depression, or in regard to therapy response in the left dorsolateral prefrontal cortex or left amygdala. Further research is necessary to conclude whether NAA alterations in the first episode of depression could possibly be different from chronic or late-onset depression, and whether NAA alterations in stress-induced (reactive) depression are different from endogenous depression. The potential role of NAA as a biomarker of a treatment effect has yet to be established.

Changes in cortical thickness across the lifespan in major depressive disorder

Neurobiological mechanisms underlying the development of major depressive disorder (MDD) may differ depending on age-of-onset. Our aim was to compare patients who differ in age-of-onset, while controlling for illness duration, and number of depressive episodes. By directly comparing early-(EOD) and late-onset (LOD) patients, we examined whether age-of-onset is associated with changes in the extent or spatial pattern of cortical thickness. Cross-sectional comparison of cortical thickness in EOD vs. LOD. Age-of-onset was determined based on self-report, with EOD defined as onset prior to age 25. Reduced cortical thickness in the dorsal-lateral prefrontal cortex (DLPFC), pre- and postcentral gyrus, and the lingual gyrus were found in EOD compared to healthy controls (p<0.001). In linear regression models controlling for number of episodes, illness duration, severity, and sex, differences (at p<0.001) were found between EOD and LOD in the bilateral posterior cingulate, parahippocampal gyri, right precuneus, lingual, and fusiform gyri, but not the DLPFC. EOD is associated with greater disturbances in cortical thickness than LOD, even when duration of illness and other factors are controlled. These results provide novel insights on how development of depression is differentiated by age.

fMRI response to negative words and SSRI treatment outcome in major depressive disorder: a preliminary study

Clinically useful predictors of treatment outcome in major depressive disorder (MDD) remain elusive. We examined associations between functional magnetic resonance imaging (fMRI) blood oxygen level dependent (BOLD) signal during active negative word processing and subsequent selective serotonin reuptake inhibitor (SSRI) treatment outcome in MDD. Unmedicated MDD subjects (n=17) performed an emotional word processing fMRI task, and then received eight weeks of standardized antidepressant treatment with escitalopram. Lower pre-treatment BOLD responses to negative words in midbrain, dorsolateral prefrontal cortex, paracingulate, anterior cingulate, thalamus and caudate nuclei correlated significantly with greater improvement following escitalopram treatment. Activation of these regions in response to negative words correlated significantly with reaction time for rating word relevance. Maximally predictive clusters of voxels identified using a cross-validation approach predicted 48% of the variance in response to treatment. This study provides preliminary evidence that SSRIs may be most beneficial in patients who are less able to engage cognitive control networks while processing negative stimuli. Differences between these findings and previous fMRI studies of SSRI treatment outcome may relate to differences in task design. Regional BOLD responses to negative words predictive of SSRI outcome in this study were both overlapping and distinct from those predictive of outcome with cognitive behavioral therapy (CBT) in previous studies using the same task. Future studies may examine prediction of differential outcome across treatments in the context of a randomized controlled trial.

State-dependent changes in hippocampal grey matter in depression

Reduced hippocampal volume has been reported in depression and may be involved in the aetiology of depressive symptoms and vulnerability to depressive relapse. Neuroplasticity following antidepressant drug treatment in the hippocampus has been demonstrated in animal models but adaptive changes after such treatment have not been shown in humans. In this study, we determined whether grey matter loss in the hippocampus in depression (1) is present in medication-free depressed (2) changes in response to antidepressant treatment and (3) is present as a stable trait in medication-free remitted patients. Sixty-four medication-free unipolar depressed patients: 39 currently depressed and 25 in remission, and 66 healthy controls (HC) underwent structural magnetic resonance imaging in a cross-sectional and longitudinal design. Thirty-two currently depressed participants were then treated with the antidepressant citalopram for 8 weeks. Adherence to treatment was evaluated by measuring plasma citalopram concentration. We measured regional variation in grey matter concentration by using voxel-based morphometry-Diffeomorphic Anatomical Registration Through Exponentiated Lie algebra. Patients with current depression had bilaterally reduced grey matter in the hippocampus compared with HC and untreated patients in stable remission with the latter groups not differing. An increase in grey matter was observed in the hippocampus following treatment with citalopram in currently depressed patients. Grey matter reduction in the hippocampus appears specific to the depressed state and is a potential biomarker for a depressive episode.

Temporal and spatial neural dynamics in the perception of basic emotions from complex scenes

The different temporal dynamics of emotions are critical to understand their evolutionary role in the regulation of interactions with the surrounding environment. Here, we investigated the temporal dynamics underlying the perception of four basic emotions from complex scenes varying in valence and arousal (fear, disgust, happiness and sadness) with the millisecond time resolution of Electroencephalography (EEG). Event-related potentials were computed and each emotion showed a specific temporal profile, as revealed by distinct time segments of significant differences from the neutral scenes. Fear perception elicited significant activity at the earliest time segments, followed by disgust, happiness and sadness. Moreover, fear, disgust and happiness were characterized by two time segments of significant activity, whereas sadness showed only one long-latency time segment of activity. Multidimensional scaling was used to assess the correspondence between neural temporal dynamics and the subjective experience elicited by the four emotions in a subsequent behavioral task. We found a high coherence between these two classes of data, indicating that psychological categories defining emotions have a close correspondence at the brain level in terms of neural temporal dynamics. Finally, we localized the brain regions of time-dependent activity for each emotion and time segment with the low-resolution brain electromagnetic tomography. Fear and disgust showed widely distributed activations, predominantly in the right hemisphere. Happiness activated a number of areas mostly in the left hemisphere, whereas sadness showed a limited number of active areas at late latency. The present findings indicate that the neural signature of basic emotions can emerge as the byproduct of dynamic spatiotemporal brain networks as investigated with millisecond-range resolution, rather than in time-independent areas involved uniquely in the processing one specific emotion.

Functional connectivity between the amygdala and prefrontal cortex in medication-naive individuals with major depressive disorder

BACKGROUND

Convergent evidence suggests dysfunction within the prefrontal cortex (PFC) and amygdala, important components of a neural system that subserves emotional processing, in individuals with major depressive disorder (MDD). Abnormalities in this system in the left hemisphere and during processing of negative emotional stimuli are especially implicated. In this study, we used functional magnetic resonance imaging (fMRI) to investigate amygdala-PFC functional connectivity during emotional face processing in medication-naive individuals with MDD.

METHODS

Individuals with MDD and healthy controls underwent fMRI scanning while processing 3 types of emotional face stimuli. We compared the strength of functional connectivity from the amygdala between the MDD and control groups.

RESULTS

Our study included 28 individuals with MDD and 30 controls. Decreased amygdala-left rostral PFC (rPFC) functional connectivity was observed in the MDD group compared with controls for the fear condition (p < 0.05, corrected). No significant differences were found in amygdala connectivity to any cerebral regions between the MDD and control groups for the happy or neutral conditions.

LIMITATIONS

All participants with MDD were experiencing acute episodes, therefore the findings could not be generalized to the entire MDD population.

CONCLUSION

Medication-naive individuals with MDD showed decreased amygdala-left rPFC functional connectivity in response to negative emotional stimuli, suggesting that abnormalities in amygdala-left rPFC neural circuitry responses to negative emotional stimuli might play an important role in the pathophysiology of MDD.

Prediction of antidepressant treatment response from gray matter volume across diagnostic categories

Dysfunctional limbic, paralimbic and prefrontal brain circuits represent neural substrates of major depression that are targeted by pharmacotherapy. In a high resolution structural magnetic resonance imaging (MRI) study we investigated the potential of variability of the cortex volume to predict the response to antidepressant treatment among patients with major depression. We enrolled 167 patients participating in the Munich Antidepressant Response Signature (MARS) study and employed voxel based morphometry to investigate covariation of gray matter (GM) maps with changes of depression severity over 5 weeks. Larger left hippocampal and bilateral posterior cingulate GM volumes and lower right temporolateral GM volumes were associated with beneficial treatment response. Subcallosal/orbitofrontal GM volumes were associated with treatment response mainly through gender-by-region interactions. A hippocampal/temporolateral composite marker proved robust in both first episode and recurrent unipolar patients and in bipolar patients. Compared with 92 healthy controls, abnormally low volumes were only detected in the left hippocampal area, particularly in recurrent unipolar patients. These findings indicate that variability of the cortex volume of specific brain areas is associated with different response to antidepressants. In addition, hippocampal findings recursively link together unfavorable treatment response and progressive hippocampal structural changes in recurrent depression.

Magnetic resonance imaging of a randomized controlled trial investigating predictors of recovery following psychological treatment in adolescents with moderate to severe unipolar depression: study protocol for Magnetic Resonance-Improving Mood with Psychoanalytic and Cognitive Therapies (MR-IMPACT)

BACKGROUND

Major depressive disorders (MDD) are a debilitating and pervasive group of mental illnesses afflicting many millions of people resulting in the loss of 110 million working days and more than 2,500 suicides per annum. Adolescent MDD patients attending NHS clinics show high rates of recurrence into adult life. A meta-analysis of recent research shows that psychological treatments are not as efficacious as previously thought. Modest treatment outcomes of approximately 65% of cases responding suggest that aetiological and clinical heterogeneity may hamper the better use of existing therapies and discovery of more effective treatments. Information with respect to optimal treatment choice for individuals is lacking, with no validated biomarkers to aid therapeutic decision-making.

METHODS/DESIGN

Magnetic resonance-Improving Mood with Psychoanalytic and Cognitive Therapies, the MR-IMPACT study, plans to identify brain regions implicated in the pathophysiology of depressions and examine whether there are specific behavioural or neural markers predicting remission and/or subsequent relapse in a subsample of depressed adolescents recruited to the IMPACT randomised controlled trial (Registration # ISRCTN83033550).

DISCUSSION

MR-IMPACT is an investigative biomarker component of the IMPACT pragmatic effectiveness trial. The aim of this investigation is to identify neural markers and regional indicators of the pathophysiology of and treatment response for MDD in adolescents. We anticipate that these data may enable more targeted treatment delivery by identifying those patients who may be optimal candidates for therapeutic response.

TRIAL REGISTRATION

Adjunctive study to IMPACT trial (Current Controlled Trials: ISRCTN83033550).

Widespread reductions in gray matter volume in depression

Abnormalities in functional limbic–anterior cingulate–prefrontal circuits associated with emotional reactivity, evaluation and regulation have been implicated in the pathophysiology of major depressive disorder (MDD). However, existing knowledge about structural alterations in depression is equivocal and based on cohorts of limited sample size. This study used voxel-based morphometry (VBM) and surface-based cortical thickness to investigate the structure of these circuits in a large and well-characterized patient cohort with MDD.

Non-geriatric MDD outpatients (n = 102) and age- and gender-matched healthy control participants (n = 34) provided T1-weighted magnetic resonance imaging data during their baseline visit as part of the International Study to Predict Optimized Treatment for Depression. Whole-brain VBM volumetric and surface-based cortical thickness assessments were performed voxel-wise and compared (at p < 0.05 corrected for multiple comparisons) between the MDD and control groups.

MDD participants had reduced gray matter volume in the anterior cingulate cortex, regions of the prefrontal circuits, including dorsolateral and dorsomedial prefrontal cortices, and lateral and medial orbitofrontal cortices, but not in limbic regions. Additional reductions were observed cortically in the posterior temporal and parieto-occipital cortices and, subcortically in the basal ganglia and cerebellum. Focal cortical thinning in the medial orbitofrontal cortex was also observed for the MDD group. These alterations in volume and cortical thickness were not associated with severity of depressive symptoms.

The findings demonstrate that widespread gray matter structural abnormalities are present in a well-powered study of patients with depression. The patterns of gray matter loss correspond to the same brain functional network regions that were previously established to be abnormal in MDD, which may support an underlying structural abnormality for these circuits.

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Focal gray matter volume decrease in depression exceeded loss via aging 11–50 years.

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Gray matter differences were found in regions with established roles in depression.

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Structural change findings support the idea of depression as a network abnormality.

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Hippocampal gray matter volume loss likely has no role in non-geriatric depression.

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Amygdala gray matter volume loss likely plays no role in depression pathophysiology.

Cortical shape and curvedness analysis of structural deficits in remitting and non-remitting depression

In morphometric neuroimaging studies, the relationship between brain structural changes and the antidepressant treatment response in patients with major depressive disorder has been explored to search depression-trait biomarkers. Although patients were treated with serotonin-related drugs, whether the same treatment resulted in remission and non-remission in depressed patients is currently under investigation. We recruited 25 depressed patients and 25 healthy controls and acquired volumetric magnetic resonance imaging of each participant. We used the shape index and curvedness to classify cortical shapes and quantify shape complexities, respectively, in studying the pharmacological effect on brain morphology. The results showed that different regions of structural abnormalities emerged between remitting and non-remitting patients when contrasted with healthy controls. In addition to comparing structural metrics in each cortical parcellation, similar to the traditional voxel-based morphometric method, we highlighted the importance of structural integrity along the serotonin pathway in response to medication treatment. We discovered that disrupted serotonin-related cortical regions might cause non-remission to antidepressant treatment from a pharmacological perspective. The anomalous areas manifested in non-remitting patients were mainly in the frontolimbic areas, which can be used to differentiate remitting from non-remitting participants before medication treatment. Because non-remission is the failure to respond to treatment with serotonin-related drugs, our method may help clinicians choose appropriate medications for non-remitting patients.

Neural responses to witnessing peer rejection after being socially excluded: fMRI as a window into adolescents' emotional processing

During adolescence, concerns about peer rejection and acceptance become increasingly common. Adolescents regularly experience peer rejection firsthand and witness these behaviors among their peers. In the current study, neuroimaging techniques were employed to conduct a preliminary investigation of the affective and cognitive processes involved in witnessing peer acceptance and rejection - specifically when these witnessed events occur in the immediate aftermath of a firsthand experience with rejection. During an fMRI scan, 23 adolescents underwent a simulated experience of firsthand peer rejection. Then, immediately following this experience they watched as another adolescent was ostensibly first accepted and then rejected. Findings indicated that in the immediate aftermath of being rejected by peers, adolescents displayed neural activity consistent with distress when they saw another peer being accepted, and neural activity consistent with emotion regulation and mentalizing (e.g. perspective-taking) processes when they saw another peer being rejected. Furthermore, individuals displaying a heightened sensitivity to firsthand rejection were more likely to show neural activity consistent with distress when observing a peer being accepted. Findings are discussed in terms of how witnessing others being accepted or rejected relates to adolescents' interpretations of both firsthand and observed experiences with peers. In addition, the potential impact that witnessed events might have on the broader perpetuation of bullying at this age is also considered.

Gray matter volume in major depressive disorder: a meta-analysis of voxel-based morphometry studies

We designed this study to perform a meta-analysis of gray matter (GM) findings in major depressive disorder (MDD) by using the signed differential mapping (SDM) toolbox. The Pubmed, ScienceDirect and Scopus databases were searched, and only studies published or published online before November 2010 have been included. Twenty voxel-based morphometry (VBM) studies of adult MDD patients were entered in the meta-analysis by SDM toolbox with threshold criteria set as error probability less than 0.00005 and cluster more than 50 voxels. Onset age, numbers of patients and controls, gender ratio of both groups, ratio of medicated patients, depression rating scores, illness duration, co-morbidity and existence of corrected p value were also meta-regressed as covariates to exclude confounding biases. Voxel-wise meta-analytic results of these 20 VBM studies in MDD patients revealed that GM deficits were observed in the right anterior cingulate cortex and left anterior cingulate cortex when patients were compared with controls. The findings remained mostly unchanged in jackknife sensitivity analyses. The potential confounding factors had little impact on the results. This meta-analysis suggested GM deficits of the anterior cingulate cortex might be important in the etiology of MDD.

Towards automated detection of depression from brain structural magnetic resonance images

INTRODUCTION

Depression is a major issue worldwide and is seen as a significant health problem. Stigma and patient denial, clinical experience, time limitations, and reliability of psychometrics are barriers to the clinical diagnoses of depression. Thus, the establishment of an automated system that could detect such abnormalities would assist medical experts in their decision-making process. This paper reviews existing methods for the automated detection of depression from brain structural magnetic resonance images (sMRI).

METHODS

Relevant sources were identified from various databases and online sites using a combination of keywords and terms including depression, major depressive disorder, detection, classification, and MRI databases. Reference lists of chosen articles were further reviewed for associated publications.

RESULTS

The paper introduces a generic structure for representing and describing the methods developed for the detection of depression from sMRI of the brain. It consists of a number of components including acquisition and preprocessing, feature extraction, feature selection, and classification.

CONCLUSION

Automated sMRI-based detection methods have the potential to provide an objective measure of depression, hence improving the confidence level in the diagnosis and prognosis of depression.

Post-stroke depression: mechanisms, translation and therapy

The interaction between depression and stroke is highly complex. Post-stroke depression (PSD) is among the most frequent neuropsychiatric consequences of stroke. Depression also negatively impacts stroke outcome with increased morbidity, mortality and poorer functional recovery. Antidepressants such as the commonly prescribed selective serotonin reuptake inhibitors improve stroke outcome, an effect that may extend far beyond depression, e.g., to motor recovery. The main biological theory of PSD is the amine hypothesis. Conceivably, ischaemic lesions interrupt the projections ascending from midbrain and brainstem, leading to a decreased bioavailability of the biogenic amines – serotonin (5HT), dopamine (DA) and norepinephrine (NE). Acetylcholine would also be involved. So far, preclinical and translational research on PSD is largely lacking. The implementation and characterization of suitable animal models is clearly a major prerequisite for deeper insights into the biological basis of post-stroke mood disturbances. Equally importantly, experimental models may also pave the way for the discovery of novel therapeutic targets. If we cannot prevent stroke, we shall try to limit its long-term consequences. This review therefore presents animal models of PSD and summarizes potential underlying mechanisms including genomic signatures, neurotransmitter and neurotrophin signalling, hippocampal neurogenesis, cellular plasticity in the ischaemic lesion, secondary degenerative changes, activation of the hypothalamo-pituitary-adrenal (HPA) axis and neuroinflammation. As stroke is a disease of the elderly, great clinical benefit may especially accrue from deciphering and targeting basic mechanisms underlying PSD in aged animals.

Quest for biomarkers of treatment-resistant depression: shifting the paradigm toward risk

The search for potential biomarkers of psychiatric disorders is a central topic in biological psychiatry. This review concerns published studies on potential biomarkers of treatment-resistant depression (TRD). The search for biomarkers of TRD in the bloodstream has focused on cytokines and steroids as well as brain-derived neurotropic factor. Additional approaches to identifying biomarkers of TRD have dealt with cerebrospinal fluid analysis, magnetic resonance imaging, and positron emission tomography. Some studies have also investigated potential genetic and epigenetic factors in TRD. Most studies have, however, used a post hoc experimental design that failed to determine the association between biomarkers and the initial risk of TRD. Particular attention in future studies should be on shifting the experimental paradigm toward procedures that can determine the risk for developing treatment resistance in untreated depressed individuals.

An algorithm for determination of rank and degree of contribution of sMRI volumetric features in depression detection

Brain volume changes at structural level appear to have utmost importance in depression biomarkers studies. However, these brain volumetric findings have very minimal utilization in depression detection studies at individual level. Thus, this paper presents an evaluation of volumetric features to identify the relevant/optimal features for the detection of depression. An algorithm is presented for determination of rank and degree of contribution (DoC) of structural magnetic resonance imaging (sMRI) volumetric features. The algorithm is based on the frequencies of each feature contribution toward the desired accuracy limit. Forty-four volumetric features from various brain regions were adopted for evaluation. From DoC analysis, the DoC of each volumetric feature for depression detection is calculated and the features that dominate the contribution are determined.