Medial Prefrontal Aberrations in Major Depressive Disorder Revealed by Cytoarchitectonically Informed Voxel-Based Morphometry

Depression, brain structure and socioeconomic status: A UK Biobank study

BACKGROUND

Depression results from interactions between biological, social, and psychological factors. Literature shows that depression is associated with abnormal brain structure, and that socioeconomic status (SES) is associated with depression and brain structure. However, limited research considers the interaction between each of these factors.

METHODS

Multivariate regression analysis was conducted using UK Biobank data on 39,995 participants to examine the relationship between depression and brain volume in 23 cortical regions for the whole sample and then separated by sex. It then examined whether SES affected this relationship.

RESULTS

Eight out of 23 brain areas had significant negative associations with depression in the whole population. However, these relationships were abolished in seven areas when SES was included in the analysis. For females, three regions had significant negative associations with depression when SES was not included, but only one when it was. For males, lower volume in six regions was significantly associated with higher depression without SES, but this relationship was abolished in four regions when SES was included. The precentral gyrus was robustly associated with depression across all analyses.

LIMITATIONS

Participants with conditions that could affect the brain were not excluded. UK Biobank is not representative of the general population which may limit generalisability. SES was made up of education and income which were not considered separately.

CONCLUSIONS

SES affects the relationship between depression and cortical brain volume. Health practitioners and researchers should consider this when working with imaging data in these populations.

Longitudinal development of resting-state functional connectivity in adolescents with and without internalizing disorders

Longitudinal studies using resting-state functional magnetic resonance imaging (rs-fMRI) focused on adolescent internalizing psychopathology are scarce and have mostly investigated standardized treatment effects on functional connectivity (FC) of the full amygdala. The role of amygdala subregions and large resting-state networks had yet to be elucidated, and treatment is in practice often personalized. Here, longitudinal FC development of amygdala subregions and whole-brain networks are investigated in a clinically representative sample. Treatment-naïve adolescents with clinical depression and comorbid anxiety who started care-as-usual (n = 23; INT) and healthy controls (n = 24; HC) participated in rs-fMRI scans and questionnaires at baseline (before treatment) and after three months. Changes between and within groups over time in FC of the laterobasal amygdala (LBA), centromedial amygdala (CMA) and whole-brain networks derived from independent component analysis (ICA) were investigated. Groups differed significantly in FC development of the right LBA to the postcentral gyrus and the left LBA to the frontal pole. Within INT, FC to the frontal pole and postcentral gyrus changed over time while changes in FC of the right LBA were also linked to symptom change. No significant interactions were observed when considering FC from CMA bilateral seeds or within ICA-derived networks. Results in this cohort suggest divergent longitudinal development of FC from bilateral LBA subregions in adolescents with internalizing disorders compared to healthy peers, possibly reflecting nonspecific treatment effects. Moreover, associations were found with symptom change. These results highlight the importance of differentiation of amygdala subregions in neuroimaging research in adolescents.

Efficacy of transcranial photobiomodulation in the treatment for major depressive disorder: A TMS-EEG and pilot study

BACKGROUND

Major depressive disorder (MDD) was a prevalent mental condition that may be accompanied by decreased excitability of left frontal pole (FP) and abnormal brain connections. An 820 nm tPBM can induce an increase in stimulated cortical excitability. The purpose of our study was to establish how clinical symptoms and time-varying brain network connectivity of MDD were affected by transcranial photobiomodulation (tPBM).

METHODS

A total of 11 patients with MDD received 820 nm tPBM targeting the left FP for 14 consecutive days. The severity of symptoms was evaluated by neuropsychological assessments at baseline, after treatment, 4-week and 8-week follow-up; 8-min transcranial magnetic stimulation combined electroencephalography (TMS-EEG) was performed for five healthy controls and five patients with MDD before and after treatment, and time-varying EEG network was analyzed using the adaptive-directed transfer function.

RESULTS

All of scales scores in the 11 patients decreased significantly after 14-day tPBM (p < .01) and remained at 8-week follow-up. The time-varying brain network analysis suggested that the brain regions with enhanced connection information outflow in MDD became gradually more similar to healthy controls after treatment.

CONCLUSIONS

This study showed that tPBM of the left FP could improve symptoms of patients with MDD and normalize the abnormal network connections.

Development and validation of a multimodal neuroimaging biomarker for electroconvulsive therapy outcome in depression: a multicenter machine learning analysis

BACKGROUND

Electroconvulsive therapy (ECT) is the most effective intervention for patients with treatment resistant depression. A clinical decision support tool could guide patient selection to improve the overall response rate and avoid ineffective treatments with adverse effects. Initial small-scale, monocenter studies indicate that both structural magnetic resonance imaging (sMRI) and functional MRI (fMRI) biomarkers may predict ECT outcome, but it is not known whether those results can generalize to data from other centers. The objective of this study was to develop and validate neuroimaging biomarkers for ECT outcome in a multicenter setting.

METHODS

Multimodal data (i.e. clinical, sMRI and resting-state fMRI) were collected from seven centers of the Global ECT-MRI Research Collaboration (GEMRIC). We used data from 189 depressed patients to evaluate which data modalities or combinations thereof could provide the best predictions for treatment remission (HAM-D score ⩽7) using a support vector machine classifier.

RESULTS

Remission classification using a combination of gray matter volume and functional connectivity led to good performing models with average 0.82-0.83 area under the curve (AUC) when trained and tested on samples coming from the three largest centers (N = 109), and remained acceptable when validated using leave-one-site-out cross-validation (0.70-0.73 AUC).

CONCLUSIONS

These results show that multimodal neuroimaging data can be used to predict remission with ECT for individual patients across different treatment centers, despite significant variability in clinical characteristics across centers. Future development of a clinical decision support tool applying these biomarkers may be feasible.

Choroid plexus volume is increased in mood disorders and associates with circulating inflammatory cytokines

Depressed patients exhibit altered levels of immune-inflammatory markers both in the peripheral blood and in the cerebrospinal fluid (CSF) and inflammatory processes have been widely implicated in the pathophysiology of mood disorders. The Choroid Plexus (ChP), located at the base of each of the four brain ventricles, regulates the exchange of substances between the blood and CSF and several evidence supported a key role for ChP as a neuro-immunological interface between the brain and circulating immune cells. Given the role of ChP as a regulatory gate between periphery, CSF spaces and the brain, we compared ChP volumes in patients with bipolar disorder (BP) or major depressive disorder (MDD) and healthy controls, exploring their association with history of illness and levels of circulating cytokines. Plasma levels of inflammatory markers and MRI scans were acquired for 73 MDD, 79 BD and 72 age- and sex-matched healthy controls (HC). Patients with either BD or MDD had higher ChP volumes than HC. With increasing age, the bilateral ChP volume was larger in patients, an effect driven by the duration of illness; while only minor effects were observed in HC. Right ChP volumes were proportional to higher levels of circulating cytokines in the clinical groups, including IFN-γ, IL-13 and IL-17. Specific effects in the two diagnostic groups were observed when considering the left ChP, with positive association with IL-1ra, IL-13, IL-17, and CCL3 in BD, and negative associations with IL-2, IL-4, IL-1ra, and IFN-γ in MDD. These results suggest that ChP could represent a reliable and easy-to-assess biomarker to evaluate the brain effects of inflammatory status in mood disorders, contributing to personalized diagnosis and tailored treatment strategies.

Depressive Disorder Recognition Based on Frontal EEG Signals and Deep Learning

Depressive disorder (DD) has become one of the most common mental diseases, seriously endangering both the affected person's psychological and physical health. Nowadays, a DD diagnosis mainly relies on the experience of clinical psychiatrists and subjective scales, lacking objective, accurate, practical, and automatic diagnosis technologies. Recently, electroencephalogram (EEG) signals have been widely applied for DD diagnosis, but mainly with high-density EEG, which can severely limit the efficiency of the EEG data acquisition and reduce the practicability of diagnostic techniques. The current study attempts to achieve accurate and practical DD diagnoses based on combining frontal six-channel electroencephalogram (EEG) signals and deep learning models. To this end, 10 min clinical resting-state EEG signals were collected from 41 DD patients and 34 healthy controls (HCs). Two deep learning models, multi-resolution convolutional neural network (MRCNN) combined with long short-term memory (LSTM) (named MRCNN-LSTM) and MRCNN combined with residual squeeze and excitation (RSE) (named MRCNN-RSE), were proposed for DD recognition. The results of this study showed that the higher EEG frequency band obtained the better classification performance for DD diagnosis. The MRCNN-RSE model achieved the highest classification accuracy of 98.48 ± 0.22% with 8-30 Hz EEG signals. These findings indicated that the proposed analytical framework can provide an accurate and practical strategy for DD diagnosis, as well as essential theoretical and technical support for the treatment and efficacy evaluation of DD.

Identification of structural brain alterations in adolescents with depressive symptomatology

INTRODUCTION

Depressive symptoms can emerge as early as childhood and may lead to adverse situations in adulthood. Studies have examined structural brain alternations in individuals with depressive symptoms, but findings remain inconclusive. Furthermore, previous studies have focused on adults or used a categorical approach to assess depression. The current study looks to identify grey matter volumes (GMV) that predict depressive symptomatology across a clinically concerning sample of adolescents.

METHODS

Structural MRI data were collected from 338 clinically concerning adolescents (mean age = 15.30 SD=2.07; mean IQ = 101.01 SD=12.43; 132 F). Depression symptoms were indexed via the Mood and Feelings Questionnaire (MFQ). Freesurfer was used to parcellate the brain into 68 cortical regions and 14 subcortical regions. GMV was extracted from all 82 brain areas. Multiple linear regression was used to look at the relationship between MFQ scores and region-specific GMV parameter. Follow up regressions were conducted to look at potential effects of psychiatric diagnoses and medication intake.

RESULTS

Our regression analysis produced a significant model (R2 = 0.446, F(86, 251) = 2.348, p < 0.001). Specifically, there was a negative association between GMV of the left parahippocampal (B = -0.203, p = 0.005), right rostral anterior cingulate (B = -0.162, p = 0.049), and right frontal pole (B = -0.147, p = 0.039) and a positive association between GMV of the left bank of the superior temporal sulcus (B = 0.173, p = 0.029). Follow up analyses produced results proximal to the main analysis.

CONCLUSIONS

Altered regional brain volumes may serve as biomarkers for the development of depressive symptoms during adolescence. These findings suggest a homogeneity of altered cortical structures in adolescents with depressive symptoms.

Smaller cornu ammonis (CA3) as a potential risk factor for suicidal behavior in mood disorders

Mood disorders and suicidal behavior have moderate heritability and familial transmission, and are associated with smaller hippocampal volumes. However, it is unclear whether hippocampal alterations reflect heritable risk or epigenetic effects of childhood adversity, compensatory mechanisms, illness-related changes, or treatment effects. We sought to separate the relationships of hippocampal substructure volumes to mood disorder, suicidal behavior, and risk and resilience to both by examining high familial risk individuals (HR) who have passed the age of greatest risk for psychopathology onset. Structural brain imaging and hippocampal substructure segmentation quantified Cornu Ammonis (CA1-4), dentate gyrus, and subiculum gray matter volumes in healthy volunteers (HV, N = 25) and three groups with one or more relatives reporting early-onset mood disorder and suicide attempt: 1. Unaffected HR (N = 20); 2. HR with lifetime mood disorder and no suicide attempt (HR-MOOD, N = 25); and 3. HR with lifetime mood disorder and a previous suicide attempt (HR-MOOD + SA, N = 18). Findings were tested in an independent cohort not selected for family history (HV, N = 47; MOOD, N = 44; and MOOD + SA, N = 21). Lower CA3 volume was found in HR (vs. HV), consistent with the direction of previously published findings in MOOD+SA (vs. HV and MOOD), suggesting the finding reflects a familial biological risk marker, not illness or treatment-related sequelae, of suicidal behavior and mood disorder. Familial suicide risk may be mediated in part by smaller CA3 volume. The structure may serve as a risk indicator and therapeutic target for suicide prevention strategies in high-risk families.

Progressive brain structural abnormality in depression assessed with MR imaging by using causal network analysis

BACKGROUND

As a neuroprogressive illness, depression is accompanied by brain structural abnormality that extends to many brain regions. However, the progressive structural alteration pattern remains unknown.

METHODS

To elaborate the progressive structural alteration of depression according to illness duration, we recruited 195 never-treated first-episode patients with depression and 130 healthy controls (HCs) undergoing T1-weighted MRI scans. Voxel-based morphometry method was adopted to measure gray matter volume (GMV) for each participant. Patients were first divided into three stages according to the length of illness duration, then we explored stage-specific GMV alterations and the causal effect relationship between them using causal structural covariance network (CaSCN) analysis.

RESULTS

Overall, patients with depression presented stage-specific GMV alterations compared with HCs. Regions including the hippocampus, the thalamus and the ventral medial prefrontal cortex (vmPFC) presented GMV alteration at onset of illness. Then as the illness advanced, others regions began to present GMV alterations. These results suggested that GMV alteration originated from the hippocampus, the thalamus and vmPFC then expanded to other brain regions. The results of CaSCN analysis revealed that the hippocampus and the vmPFC corporately exerted causal effect on regions such as nucleus accumbens, the precuneus and the cerebellum. In addition, GMV alteration in the hippocampus was also potentially causally related to that in the dorsolateral frontal gyrus.

CONCLUSIONS

Consistent with the neuroprogressive hypothesis, our results reveal progressive morphological alteration originating from the vmPFC and the hippocampus and further elucidate possible details about disease progression of depression.

Mapping Cytoarchitectonics and Receptor Architectonics to Understand Brain Function and Connectivity

This review focuses on cytoarchitectonics and receptor architectonics as biological correlates of function and connectivity. It introduces the 3-dimensional cytoarchitectonic probabilistic maps of cortical areas and nuclei of the Julich-Brain Atlas, available at EBRAINS, to study structure-function relationships. The maps are linked to the BigBrain as microanatomical reference model and template space. The siibra software tool suite enables programmatic access to the maps and to receptor architectonic data that are anchored to brain areas. Such cellular and molecular data are tools for studying magnetic resonance connectivity including modeling and simulation. At the end, we highlight perspectives of the Julich-Brain as well as methodological considerations. Thus, microstructural maps as part of a multimodal atlas help elucidate the biological correlates of large-scale networks and brain function with a high level of anatomical detail, which provides a basis to study brains of patients with psychiatric disorders.

Neural responses to monetary incentives in postpartum women affected by baby blues

Up to 50% of new mothers experience baby blues (BB) within a week of delivery, with affective disturbances being the central symptoms. Because reward processing is known to be affected in depression, this study sought to investigate whether incentive processing during the experience of BB can be altered through the monetary incentive delay (MID) task. The MID task allows reward processing to be investigated based on responses to 'anticipation' and 'feedback of reward or loss'. 60 women participated in the fMRI-based MID task within 1-6 days of delivery, and 50% of them developed BB within the first few postpartum weeks. Over a 12-week observation period, a greater number of women in the BB group (52% vs. 13%) developed psychiatric conditions, with 24% of women with BB developing postpartum depression compared to only 3% of those without BB. During the feedback trials of the MID task, women with BB, compared to those without, showed increased activation in both the winning and losing trials (the temporal areas, the insula, the midbrain, and the inferior frontal gyrus). During the anticipation trials, however, subjects affected by BB showed reduced activation in the pregenual and the subgenual anterior cingulate cortices (pg/sg ACC). Our results demonstrate, for the first time, that the BB-related time window overlaps with alterations in the brain networks associated with incentive processing. Given the involvement of pg/sgACC in the development of depressive mood, the weaker involvement of these brain regions during anticipation in participants affected by BB is of particular interest.

Significant age by childhood trauma interactions on grey matter volumes: A whole brain VBM analysis

BACKGROUND

Childhood trauma is deleterious to long term brain development. The changes are variable, and depend on gender, age and the nature of the trauma. In this exploratory analysis, we investigated the effects of exposure to emotional trauma on grey matter (GM) volumes in adolescent females.

METHODS

We explored GM volumes in non-clinical females aged 12-17 years who had been exposed to either higher (HET; N = 75) or minimal (MET; N = 127) emotional trauma. High-resolution T1-weighted structural images were analysed with an optimised FSL-VBM protocol. The General Linear Model was run on HET versus MET with continuous age as an interaction. Mean GM volumes were extracted from significant corrected age interaction statistical maps and scrutinised with SPSS®.

RESULTS

We observed greater HET*age than MET*age interactions (corrected p-value = 0.0002), in 4 separate bilateral cortical regions associated with mood disorders. Scrutiny of these regions showed significant GM volume enlargements in the early adolescent HET group (p = 0.017) and reductions in the late adolescent HET group (p < 0.0001). Notably, there were no differences in middle adolescence (p > 0.05).

LIMITATIONS

Causality cannot be inferred from this cross-sectional study and the onset of trauma cannot be determined using retrospective measures.

CONCLUSIONS

Whilst GM volumes diminish from early adolescence onwards, our results show that HET impacts this brain development, perhaps first via unstable adaptative mechanisms, followed by maladaptive processes in late adolescence. This suggests that compromises of emotional and cognitive self-regulation in mood disorders may underpin the structural abnormalities observed across multiple brain regions in these teenage girls.

Hippocampal morphological atrophy and distinct patterns of structural covariance network in Alzheimer's disease and mild cognitive impairment

Elucidating distinct morphological atrophy patterns of Alzheimer's disease (AD) and its prodromal stage, namely, mild cognitive impairment (MCI) helps to improve early diagnosis and medical intervention of AD. On that account, we aimed to obtain distinct patterns of voxel-wise morphological atrophy and its further perturbation on structural covariance network in AD and MCI compared with healthy controls (HCs). T1-weighted anatomical images of matched AD, MCI, and HCs were included in this study. Gray matter volume was obtained using voxel-based morphometry and compared among three groups. In addition, structural covariance network of identified brain regions exhibiting morphological difference was constructed and compared between pairs of three groups. Thus, patients with AD have a reduced hippocampal volume and an increased rate of atrophy compared with MCI and HCs. MCI exhibited a decreased trend in bilateral hippocampal volume compared with HCs and the accelerated right hippocampal atrophy rate than HCs. In AD, the hippocampus further exhibited increased structural covariance connected to reward related brain regions, including the anterior cingulate cortex, the putamen, the caudate, and the insula compared with HCs. In addition, the patients with AD exhibited increased structural covariance of left hippocampus with the bilateral insula, the inferior frontal gyrus, the superior temporal gyrus, and the cerebellum than MCI. These results reveal distinct patterns of morphological atrophy in AD and MCI, providing new insights into pathology of AD.

The expectant brain-pregnancy leads to changes in brain morphology in the early postpartum period

There is growing evidence that pregnancy may have a significant impact on the maternal brain, causing changes in its structure. To investigate the patterns of these changes, we compared nulliparous women (n = 40) with a group of primiparous women (n = 40) and multiparous mothers (n = 37) within 1-4 days postpartum, using voxel-based and surface-based morphometry (SBM). Compared with the nulliparous women, the young mothers showed decreases in gray matter volume in the bilateral hippocampus/amygdala, the orbitofrontal/subgenual prefrontal area, the right superior temporal gyrus and insula, and the cerebellum. These pregnancy-related changes in brain structure did not predict the quality of mother-infant attachment at either 3 or 12 weeks postpartum nor were they more pronounced among the multiparous women. SBM analyses showed significant cortical thinning especially in the frontal and parietal cortices, with the parietal cortical thinning likely potentiated by multiple pregnancies. We conclude that, compared with the brain of nulliparous women, the maternal brain shows widespread morphological changes shortly after childbirth. Also, the experience of pregnancy alone may not be the underlying cause of the adaptations for mothering. As regards the exact biological function of the changes in brain morphology, longitudinal research will be needed to draw any definitive conclusions.

An ecological animal model of subthreshold depression in adolescence: behavioral and resting state 18F-FDG PET imaging characterization

The different depressive disorders that exist can take root at adolescence. For instance, some functional and structural changes in several brain regions have been observed from adolescence in subjects that display either high vulnerability to depressive symptoms or subthreshold depression. For instance, adolescents with depressive disorder have been shown to exhibit hyperactivity in hippocampus, amygdala and prefrontal cortex as well as volume reductions in hippocampus and amygdala (prefrontal cortex showing more variable results). However, no animal model of adolescent subthreshold depression has been developed so far. Our objective was to design an animal model of adolescent subthreshold depression and to characterize the neural changes associated to this phenotype. For this purpose, we used adolescent Swiss mice that were evaluated on 4 tests assessing cognitive abilities (Morris water maze), anhedonia (sucrose preference), anxiety (open-field) and stress-coping strategies (forced swim test) at postnatal day (PND) 28-35. In order to identify neural alterations associated to behavioral profiles, we assessed brain resting state metabolic activity in vivo using ¹⁸F-FDG PET imaging at PND 37. We selected three profiles of mice distinguished in a composite Z-score computed from performances in the behavioral tests: High, Intermediate and Low Depressive Risk (HDR, IDR and LDR). Compared to both IDR and LDR, HDR mice were characterized by passive stress-coping behaviors, low cognition and high anhedonia and anxiety and were associated with significant changes of ¹⁸F-FDG uptakes in several cortical and subcortical areas including prelimbic cortex, infralimbic cortex, nucleus accumbens, amygdala, periaqueductal gray and superior colliculus, all displaying higher metabolic activity, while only the thalamus was associated with lower metabolic activity (compared to IDR). LDR displayed an opposing behavioral phenotype and were associated with significant changes of ¹⁸F-FDG uptakes in the dorsal striatum and thalamus that both exhibited markedly lower metabolic activity in LDR. In conclusion, our study revealed changes in metabolic activities that can represent neural signatures for behavioral profiles predicting subthreshold depression at adolescence in a mouse model.

A single injection of pregabalin induces short- and long-term beneficial effects on fear memory and anxiety-like behavior in rats with experimental type-1 diabetes mellitus

Anxiety Disorders and Posttraumatic Stress Disorders (PTSD) associated with type-1 diabetes mellitus (T1DM) are increasingly common comorbidities and the treatment is quite challenging. In that sense, evidence indicates that the anticonvulsant pregabalin is highly effective in treating severe cases of anxiety, as well as PTSD and diabetic neuropathic pain which is also very prevalent in T1DM. Herein, the short- and long-term effects of a single injection of pregabalin on the acquisition of a fear extinction memory and parameters of anxiety in induced-T1DM animals were investigated. For that, we used the contextual fear conditioning (CFC) and elevated plus maze paradigms, respectively. A putative antioxidant activity was also evaluated. Our findings demonstrated that induced-T1DM animals presented greater expression of fear memory, difficulty in extinguishing this fear memory, associated with a more pronounced anxiety-like response. Pregabalin was able to induce a short and long-lasting effect by facilitating the acquisition of the fear extinction memory and inducing a later anxiolytic-like effect. Also, the increased lipid peroxidation levels in the hippocampus and prefrontal cortex of induced-T1DM rats were reduced after pregabalin injection, while the decreased levels of reduced glutathione were increased in the hippocampus. Despite the need for more studies to understand the mechanism of action of pregabalin under these conditions, our data demonstrate for the first time that a single injection of pregabalin in a specific time window was able to improve behavioral parameters in addition to inducing neuroprotective effect. Thus, pregabalin has potential worth exploring for the treatment of PTSD and/or Anxiety associated with T1DM.

Alcohol Use and Prefrontal Cortex Volume Trajectories in Young Adults with Mood Disorders and Associated Clinical Outcomes

(1) Background: Alcohol use in the course of mood disorders is associated with worse clinical outcomes. The mechanisms by which alcohol use alters the course of illness are unclear but may relate to prefrontal cortical (PFC) sensitivity to alcohol. We investigated associations between alcohol use and PFC structural trajectories in young adults with a mood disorder compared to typically developing peers. (2) Methods: 41 young adults (24 with a mood disorder, agemean = 21 ± 2 years) completed clinical evaluations, assessment of alcohol use, and two structural MRI scans approximately one year apart. Freesurfer was used to segment PFC regions of interest (ROIs) (anterior cingulate, orbitofrontal cortex, and frontal pole). Effects of group, alcohol use, time, and interactions among these variables on PFC ROIs at baseline and follow-up were modeled. Associations were examined between alcohol use and longitudinal changes in PFC ROIs with prospective mood. (3) Results: Greater alcohol use was prospectively associated with decreased frontal pole volume in participants with a mood disorder, but not typically developing comparison participants (time-by-group-by-alcohol interaction; p = 0.007); however, this interaction became a statistical trend in a sensitivity analysis excluding one outlier in terms of alcohol use. Greater alcohol use and a decrease in frontal pole volume related to longer duration of major depression during follow-up (p’s < 0.05). (4) Conclusion: Preliminary findings support more research on alcohol use, PFC trajectories, and depression recurrence in young adults with a mood disorder including individuals with heavier drinking patterns.

Alterations of dynamic redundancy of functional brain subnetworks in Alzheimer's disease and major depression disorders

The human brain is not only efficiently but also "redundantly" connected. The redundancy design could help the brain maintain resilience to disease attacks. This paper explores subnetwork-level redundancy dynamics and the potential of such metrics in disease studies. As such, we looked into specific functional subnetworks, including those associated with high-level functions. We investigated how the subnetwork redundancy dynamics change along with Alzheimer's disease (AD) progression and with major depressive disorder (MDD), two major disorders that could share similar subnetwork alterations. We found an increased dynamic redundancy of the subcortical-cerebellum subnetwork and its connections to other high-order subnetworks in the mild cognitive impairment (MCI) and AD compared to the normal control (NC). With gained spatial specificity, we found such a redundancy index was sensitive to disease symptoms and could act as a protective mechanism to prevent the collapse of the brain network and functions. The dynamic redundancy of the medial frontal subnetwork and its connections to the frontoparietal subnetwork was also found decreased in MDD compared to NC. The spatial specificity of the redundancy dynamics changes may provide essential knowledge for a better understanding of shared neural substrates in AD and MDD.

Structuro-functional surrogates of response to subcallosal cingulate deep brain stimulation for depression

Subcallosal cingulate deep brain stimulation (SCC-DBS) produces long-term clinical improvement in approximately half of patients with severe treatment-resistant depression (TRD). We hypothesized that both structural and functional brain attributes may be important in determining responsiveness to this therapy. In a TRD SCC-DBS cohort, we retrospectively examined baseline and longitudinal differences in MRI-derived brain volume (n = 65) and 18F-fluorodeoxyglucose-PET glucose metabolism (n = 21) between responders and non-responders. Support-vector machines (SVMs) were subsequently trained to classify patients' response status based on extracted baseline imaging features. A machine learning model incorporating pre-operative frontopolar, precentral/frontal opercular, and orbitofrontal local volume values classified binary response status (12 months) with 83% accuracy (leave-one-out cross-validation (LOOCV): 80% accuracy) and explained 32% of the variance in continuous clinical improvement. It was also predictive in an out-of-sample SCC-DBS cohort (n = 21) with differing primary indications (bipolar disorder/anorexia nervosa) (76% accuracy). Adding pre-operative glucose metabolism information from rostral anterior cingulate cortex and temporal pole improved model performance, enabling it to predict response status in the TRD cohort with 86% accuracy (LOOCV: 81% accuracy) and explain 67% of clinical variance. Response-related patterns of metabolic and structural post-DBS change were also observed, especially in anterior cingulate cortex and neighbouring white matter. Areas where responders differed from non-responders - both at baseline and longitudinally - largely overlapped with depression-implicated white matter tracts, namely uncinate fasciculus, cingulum bundle, and forceps minor/rostrum of corpus callosum. The extent of patient-specific engagement of these same tracts (according to electrode location and stimulation parameters) also served as a predictor of TRD response status (72% accuracy; LOOCV: 70% accuracy) and augmented performance of the volume-based (88% accuracy; LOOCV: 82% accuracy) and combined volume/metabolism-based SVMs (100% accuracy; LOOCV: 94% accuracy). Taken together, these results indicate that responders and non-responders to SCC-DBS exhibit differences in brain volume and metabolism, both pre- and post-surgery. Baseline imaging features moreover predict response to treatment (particularly when combined with information about local tract engagement) and could inform future patient selection and other clinical decisions.

Macro- and Microscale Stress-Associated Alterations in Brain Structure: Translational Link With Depression

Major depressive disorder (MDD) is a stress-related disorder associated with many cytoarchitectural and neurochemical changes. However, the majority of these changes cannot be reliably detected in the living brain. The examination of animal stress models and postmortem human brain tissue has significantly contributed to our understanding of the pathophysiology of MDD. Ronald Duman's work in humans and in rodent models was critical to the investigation of the contribution of synaptic deficits to MDD and chronic stress pathology, their role in the development and expression of depressive-like behavior, and reversal by novel drugs. Here, we review evidence from magnetic resonance imaging in humans and animals that suggests that corticolimbic alterations are associated with depression symptomatology. We also discuss evidence of cytoarchitectural alterations affecting neurons, astroglia, and synapses in MDD and highlight how similar changes are described in rodent chronic stress models and are linked to the emotion-related behavioral deficits. Finally, we report on the latest approaches developed to measure the synaptic and astroglial alterations in vivo, using positron emission tomography, and how it can inform on the contribution of MDD-associated cytoarchitectural alterations to the symptomatology and the treatment of stress-related disorders.

Transcranial photobiomodulation changes topology, synchronizability, and complexity of resting state brain networks

Objective. Transcranial photobiomodulation (tPBM) is a recently proposed non-invasive brain stimulation approach with various effects on the nervous system from the cells to the whole brain networks. Specially in the neural network level, tPBM can alter the topology and synchronizability of functional brain networks. However, the functional properties of the neural networks after tPBM are still poorly clarified.Approach. Here, we employed electroencephalography and different methods (conventional and spectral) in the graph theory analysis to track the significant effects of tPBM on the resting state brain networks. The non-parametric statistical analysis showed that just one short-term tPBM session over right medial frontal pole can significantly change both topological (i.e. clustering coefficient, global efficiency, local efficiency, eigenvector centrality) and dynamical (i.e. energy, largest eigenvalue, and entropy) features of resting state brain networks.Main results. The topological results revealed that tPBM can reduce local processing, centrality, and laterality. Furthermore, the increased centrality of central electrode was observed.Significance. These results suggested that tPBM can alter topology of resting state brain network to facilitate the neural information processing. On the other hand, the dynamical results showed that tPBM reduced stability of synchronizability and increased complexity in the resting state brain networks. These effects can be considered in association with the increased complexity of connectivity patterns among brain regions and the enhanced information propagation in the resting state brain networks. Overall, both topological and dynamical features of brain networks suggest that although tPBM decreases local processing (especially in the right hemisphere) and disrupts synchronizability of network, but it can increase the level of information transferring and processing in the brain network.

Hippocampal subregion volume in high-risk offspring is associated with increases in depressive symptoms across the transition to adolescence

BACKGROUND

The hippocampus has been implicated in the pathophysiology of depression. This study examined whether youth hippocampal subregion volumes were differentially associated with maternal depression history and youth's depressive symptoms across the transition to adolescence.

METHODS

74 preadolescent offspring (M_age=10.74+/-0.84 years) of mothers with (n = 33) and without a lifetime depression history (n = 41) completed a structural brain scan. Youth depressive symptoms were assessed with clinical interviews and mother- and youth-reports prior to the neuroimaging assessment at age 9 (M_age=9.08+/-0.29 years), at the neuroimaging assessment, and in early adolescence (M_age=12.56+/-0.40 years).

RESULTS

Maternal depression was associated with preadolescent offspring's reduced bilateral hippocampal head volumes and increased left hippocampal body volume. Reduced bilateral head volumes were associated with offspring's increased concurrent depressive symptoms. Furthermore, reduced right hippocampal head volume mediated associations between maternal depression and increases in offspring depressive symptoms from age 9 to age 12.

LIMITATIONS

This study included a modest-sized sample that was oversampled for early temperamental characteristics, one neuroimaging assessment, and no correction for multiple comparisons.

CONCLUSIONS

Findings implicate reductions in hippocampal head volume in the intergenerational transmission of risk from parents to offspring.

Neurofilament Light Chain Is a Promising Biomarker in Alcohol Dependence

Background: Alcohol dependence, a global public health problem, leads to structural and functional damage in the brain. Alcohol dependence patients present complex and varied clinical manifestations and live with general complaints existing in contemporary society, making most people with alcohol dependence hard to identify. Therefore, it is important to find potential biomarkers for the diagnosis and evaluation of alcohol dependence. In the study, we explored potential biomarkers for the diagnosis and monitoring of diseases and evaluated brain structural changes in alcohol dependence patients. Methods: Enzyme-linked immunosorbent assay (ELSA) was employed to detect the expression of serum nucleotide-binding oligomerization domain containing 3 (NLRP3) and single-molecule array (Simoa) assay was used to detect the expression of serum neurofilament light (NfL) in 50 alcohol dependence patients and 50 controls with no drinking history. Alcohol consumption was measured by standard drinks. Neuropsychological assessments, including the Montreal cognitive assessment (MoCA), Pittsburgh sleep quality index (PSQI), generalized anxiety disorder (GAD-7), and patient health questionnaire-9 (PHQ-9), were conducted to evaluate cognitive function and psychological state. The degree of white matter lesions (WMLs) was rated using the Fazekas scale based on magnetic resonance imaging analysis. White matter structure was quantified using the voxel-based morphometry method. The correlations between NLRP3 levels, NfL levels, neuropsychological dysfunction, the degree of WMLs, and white matter volume (WMV) were analyzed in alcohol dependence patients. Results: Serum NLRP3 and NfL levels were higher in the alcohol dependence group. NLRP3 levels were irrelevant to monthly alcohol assumption as well as to the MoCA, PSQI, GAD-7, PHQ-9, and Fazekas scale scores and WMV. NfL levels were positively correlated with the PSQI and PHQ-9 scores as well as the degree of WMLs and negatively correlated with the MoCA scores and WMV. No associations were evident between NfL and monthly alcohol assumption and GAD-7 scores in the alcohol dependence group. Conclusion: This study supports the potential value of serum NfL as a non-invasive biomarker in alcohol dependence. The association with neuropsychological dysfunction and degree of WMLs has implications to use NfL as a promising biomarker to assess the severity of brain damage as well as the progression and prognosis of alcohol dependence.

The Gut-Brain-Axis on the Manifestation of Depressive Symptoms in Epilepsy: An Evidence-Driven Hypothesis

Epilepsy is a severe neurological disorder involving 70 million people around the globe. Epilepsy-related neuropsychiatric comorbidities such as depression, which is the most common, is an additional factor that negatively impacts the living quality of epilepsy patients. There are many theories and complexities associated with both epilepsy and associated comorbidities, one of which is the gut-brain-axis influence. The gut microbiome is hypothesized to be linked with many neurological disorders; however, little conclusive evidence is available in this area. Thus, highlighting the role will create interest in researchers to conduct detailed research in comprehending the influence of gut-brain-axis in the manifestation of depressive symptoms in epilepsy. The hypothesis which is explored in this review is that the gut-brain-axis do play an important role in the genesis of epilepsy and associated depression. The correction of this dysbiosis might be beneficial in treating both epilepsy and related depression. This hypothesis is illustrated through extensive literature discussion, proposed experimental models, and its applicability in the field. There is indirect evidence which revealed some specific bacterial strains that might cause depression in epilepsy.

Brain structural and functional changes in patients with major depressive disorder: a literature review

Depression is a mental disorder characterized by low mood and anhedonia that involves abnormalities in multiple brain regions and networks. Epidemiological studies demonstrated that depression has become one of the most important diseases affecting human health and longevity. The pathogenesis of the disease has not been fully elucidated. The clinical effect of treatment is not satisfactory in many cases. Neuroimaging studies have provided rich and valuable evidence that psychological symptoms and behavioral deficits in patients with depression are closely related to structural and functional abnormalities in specific areas of the brain. There were morphological differences in several brain regions, including the frontal lobe, temporal lobe, and limbic system, in people with depression compared to healthy people. In addition, people with depression also had abnormal functional connectivity to the default mode network, the central executive network, and the salience network. These findings provide an opportunity to re-understand the biological mechanisms of depression. In the future, magnetic resonance imaging (MRI) may serve as an important auxiliary tool for psychiatrists in the process of early and accurate diagnosis of depression and finding the appropriate treatment target for each patient to optimize clinical response.

Increased Global Interaction Across Functional Brain Modules During Cognitive Emotion Regulation

Cognitive emotion regulation (CER) enables humans to flexibly modulate their emotions. While local theories of CER neurobiology suggest interactions between specialized local brain circuits underlying CER, e.g., in subparts of amygdala and medial prefrontal cortices (mPFC), global theories hypothesize global interaction increases among larger functional brain modules comprising local circuits. We tested the global CER hypothesis using graph-based whole-brain network analysis of functional MRI data during aversive emotional processing with and without CER. During CER, global between-module interaction across stable functional network modules increased. Global interaction increase was particularly driven by subregions of amygdala and cuneus-nodes of highest nodal participation-that overlapped with CER-specific local activations, and by mPFC and posterior cingulate as relevant connector hubs. Results provide evidence for the global nature of human CER, complementing functional specialization of embedded local brain circuits during successful CER.

Large-scale Meta-analysis Suggests Low Regional Modularity in Lateral Frontal Cortex

Extensive fMRI study of human lateral frontal cortex (LFC) has yet to yield a consensus mapping between discrete anatomy and psychological states, partly due to the difficulty of inferring mental states from brain activity. Despite this, there have been few large-scale efforts to map the full range of psychological states across the entirety of LFC. Here, we used a data-driven approach to generate a comprehensive functional-anatomical mapping of LFC from 11 406 neuroimaging studies. We identified putatively separable LFC regions on the basis of whole-brain co-activation, revealing 14 clusters organized into 3 whole-brain networks. Next, we generated functional preference profiles by using multivariate classification to identify the psychological states that best predicted activity within each cluster. We observed large functional differences between networks, suggesting brain networks support distinct modes of processing. Within each network, however, we observed relatively low functional specificity, suggesting discrete psychological states are not strongly localized to individual regions; instead, our results are consistent with the view that individual LFC regions work as part of distributed networks to give rise to flexible behavior. Collectively, our results provide a comprehensive synthesis of a diverse neuroimaging literature using relatively unbiased data-driven methods.

Frontal white matter architecture predicts efficacy of deep brain stimulation in major depression

Major depression is a frequent and severe disorder, with a combination of psycho- and pharmacotherapy most patients can be treated. However, ~20% of all patients suffering from major depressive disorder remain treatment resistant; a subgroup might be treated with deep brain stimulation (DBS). We present two trials of DBS to the superolateral medial forebrain bundle (slMFB DBS; FORESEE I and II). The goal was to identify informed features that allow to predict treatment response. Data from N = 24 patients were analyzed. Preoperative imaging including anatomical sequences (T1 and T2) and diffusion tensor imaging (DTI) magnetic resonance imaging sequences were used together with postoperative helical CT scans (for DBS electrode position). Pathway activation modeling (PAM) as well as preoperative structural imaging and morphometry was used to understand the response behavior of patients (MADRS). A left fronto-polar and partly orbitofrontal region was identified that showed increased volume in preoperative anatomical scans. Further statistical analysis shows that the volume of this "HUB-region" is predictive for later MADRS response from DBS. The HUB region connects to typical fiber pathways that have been addressed before in therapeutic DBS in major depression. Left frontal volume growth might indicate intrinsic activity upon disconnection form the main emotional network. The results are significant since for the first time we found an informed feature that might allow to identify and phenotype future responders for slMFB DBS. This is a clear step into the direction of personalized treatments.

Associations between subclinical depressive symptoms and reduced brain volume in middle-aged to older adults

OBJECTIVES

The associations between subclinical depressive symptoms, as well specific symptom subscales, on brain structure in aging are not completely elucidated. This study investigated the extent to which depressive symptoms were related to brain volumes in fronto-limbic structures in a sample of middle-aged to older adults.

METHOD

Eighty participants underwent structural neuroimaging and completed the Beck Depression Inventory, 2nd Edition (BDI-II), which comprises separate affective, cognitive, and somatic subscales. Gray matter volumes were extracted from the caudal and rostral anterior cingulate, posterior cingulate, hippocampus, and amygdala. Hierarchical regression models examined the relationship between brain volumes and (i) total depressive symptoms and (ii) BDI-II subscales were conducted.

RESULTS

After adjusting for total intracranial volume, race, and age, higher total depressive symptoms were associated with smaller hippocampal volume (p = 0.005). For the symptom subscales, after controlling for the abovementioned covariates and the influence of the other symptom subscales, more somatic symptoms were related to smaller posterior cingulate (p = 0.025) and hippocampal (p < 0.001) volumes. In contrast, the affective and cognitive subscales were not associated with brain volumes in any regions of interest.

CONCLUSION

Our data showed that greater symptomatology was associated with smaller volume in limbic brain regions. These findings provide evidence for preclinical biological markers of major depression and specifically advance knowledge of the relationship between subclinical depressive symptoms and brain volume. Importantly, we observed variations by specific depressive symptom subscales, suggesting a symptom-differential relationship between subclinical depression and brain volume alterations in middle-aged and older individuals.

Moving pharmacoepigenetics tools for depression toward clinical use

BACKGROUND

Major depressive disorder (MDD) is a leading cause of disability worldwide, and over half of patients do not achieve symptom remission following an initial antidepressant course. Despite evidence implicating a strong genetic basis for the pathophysiology of MDD, there are no adequately validated biomarkers of treatment response routinely used in clinical practice. Pharmacoepigenetics is an emerging field that has the potential to combine both genetic and environmental information into treatment selection and further the goal of precision psychiatry. However, this field is in its infancy compared to the more established pharmacogenetics approaches.

METHODS

We prepared a narrative review using literature searches of studies in English pertaining to pharmacoepigenetics and treatment of depressive disorders conducted in PubMed, Google Scholar, PsychINFO, and Ovid Medicine from inception through January 2019. We reviewed studies of DNA methylation and histone modifications in both humans and animal models of depression.

RESULTS

Emerging evidence from human and animal work suggests a key role for epigenetic marks, including DNA methylation and histone modifications, in the prediction of antidepressant response. The challenges of heterogeneity of patient characteristics and loci studied as well as lack of replication that have impacted the field of pharmacogenetics also pose challenges to the development of pharmacoepigenetic tools. Additionally, given the tissue specific nature of epigenetic marks as well as their susceptibility to change in response to environmental factors and aging, pharmacoepigenetic tools face additional challenges to their development.

LIMITATIONS

This is a narrative and not systematic review of the literature on the pharmacoepigenetics of antidepressant response. We highlight key studies pertaining to pharmacoepigenetics and treatment of depressive disorders in humans and depressive-like behaviors in animal models, regardless of sample size or methodology. While we discuss DNA methylation and histone modifications, we do not cover microRNAs, which have been reviewed elsewhere recently.

CONCLUSIONS

Utilization of genome-wide approaches and reproducible epigenetic assays, careful selection of the tissue assessed, and integration of genetic and clinical information into pharmacoepigenetic tools will improve the likelihood of developing clinically useful tests.

The Impact of Stress and Major Depressive Disorder on Hippocampal and Medial Prefrontal Cortex Morphology

Volumetric reductions in the hippocampus and medial prefrontal cortex (mPFC) are among the most well-documented neural abnormalities in major depressive disorder (MDD). Hippocampal and mPFC structural reductions have been specifically tied to MDD illness progression markers, including greater number of major depressive episodes (MDEs), longer illness duration, and nonremission/treatment resistance. Chronic stress plays a critical role in the development of hippocampal and mPFC deficits, with some studies suggesting that these deficits occur irrespective of MDE occurrence. However, preclinical and human research also points to other stress-mediated neurotoxic processes, including enhanced inflammation and neurotransmitter disturbances, which may require the presence of an MDE and contribute to further brain structural decline as the illness advances. Specifically, hypothalamic-pituitary-adrenal axis dysfunction, enhanced inflammation and oxidative stress, and neurotransmitter abnormalities (e.g., serotonin, glutamate, gamma-aminobutyric acid) likely interact to facilitate illness progression in MDD. Congruent with stress sensitization models of MDD, with each consecutive MDE it may take lower levels of stress to trigger these neurotoxic pathways, leading to more pronounced brain volumetric reductions. Given that stress and MDD have overlapping and distinct influences on neurobiological pathways implicated in hippocampal and mPFC structural decline, further work is needed to clarify which precise mechanisms ultimately contribute to MDD development and maintenance.

Prenatal stress leads to chromatin and synaptic remodeling and excessive alcohol intake comorbid with anxiety-like behaviors in adult offspring

Epidemiologic evidence suggests that individuals during their prenatal development may be especially vulnerable to the effects of environmental factors such as stress that predisposes them to psychiatric disorders including alcohol use disorder (AUD) later in life. Currently, the epigenetic mechanisms of anxiety comorbid with AUD induced by prenatal stress (PRS) remain to be elucidated. Here, we examined anxiety-like and alcohol drinking behaviors in adult offspring of prenatally stressed dam (PRS-mice) using elevated plus maze, light/dark box and two-bottle free-choice paradigm. It was found that PRS-mice exhibit heightened anxiety-like behaviors and increased alcohol intake in adulthood and these behavioral deficits were associated with a significant decrease in dendritic spine density (DSD) in medial prefrontal cortex (mPFC) relative to non-stressed mice (NS mice). To determine the mechanisms by which PRS reduces DSD, we examined the expressions of key genes associated with synaptic plasticity, including activity regulated cytoskeleton associated protein (Arc), spinophilin (Spn), postsynaptic density 95 (Psd95), tropomyosin receptor kinase B (TrkB), protein kinase B (Akt), mammalian target of rapamycin (mTOR) and period 2 (Per2) in mPFC of PRS and NS mice. The mRNA levels of these genes were significantly decreased in PRS mice. Methylated DNA and chromatin immunoprecipitation studies revealed hyper DNA methylation or reduced histone H3K14 acetylation on promoters of above genes suggesting that epigenetic dysregulation may be responsible for the deficits in their expression. Findings from this study suggest that prenatal stress induced abnormal epigenetic mechanisms and synaptic plasticity-related events may be associated with anxiety-like and alcohol drinking behaviors in adulthood.

Action and object words are differentially anchored in the sensory motor system - A perspective on cognitive embodiment

Embodied and grounded cognition theories have assumed that the sensorimotor system is causally involved in processing motor-related language content. Although a causal proof on a single-cell basis is ethically not possible today, the present fMRI study provides confirmation of this longstanding speculation, as far as it is possible with recent methods, employing a new computational approach. More specifically, we were looking for common activation of nouns and objects, and actions and verbs, representing the canonical and mirror neuron system, respectively. Using multivariate pattern analysis, a resulting linear classifier indeed successfully generalized from distinguishing actions from objects in pictures to distinguishing the respective verbs from nouns in written words. Further, these action-related pattern responses were detailed by recently introduced predictive pattern decomposition into the constituent activity atoms and their relative contributions. The findings support the concept of canonical neurons and mirror neurons implementing embodied processes with separate roles in distinguishing objects from actions, and nouns from verbs, respectively. This example of neuronal recycling processing algorithms is consistent with a multimodal brain signature of human action and object concepts. Embodied language theory is thus merged with actual neurobiological implementation.

Integration of transcriptomic and cytoarchitectonic data implicates a role for MAOA and TAC1 in the limbic-cortical network

Decoding the chain from genes to cognition requires detailed insights how areas with specific gene activities and microanatomical architectures contribute to brain function and dysfunction. The Allen Human Brain Atlas contains regional gene expression data, while the JuBrain Atlas offers three-dimensional cytoarchitectonic maps reflecting interindividual variability. To date, an integrated framework that combines the analytical benefits of both scientific platforms towards a multi-level brain atlas of adult humans was not available. We have, therefore, developed JuGEx, a new method for integrating tissue transcriptome and cytoarchitectonic segregation. We investigated differential gene expression in two JuBrain areas of the frontal pole that we have structurally and functionally characterized in previous studies. Our results show a significant upregulation of MAOA and TAC1 in the medial area frontopolaris which is a node in the limbic-cortical network and known to be susceptible for gray matter loss and behavioral dysfunction in patients with depression. The MAOA gene encodes an enzyme which is involved in the catabolism of dopamine, norepinephrine, serotonin, and other monoaminergic neurotransmitters. The TAC1 locus generates hormones that play a role in neuron excitations and behavioral responses. Overall, JuGEx provides a new tool for the scientific community that empowers research from basic, cognitive and clinical neuroscience in brain regions and disease models with regard to gene expression.

Cortical Connections Position Primate Area 25 as a Keystone for Interoception, Emotion, and Memory

The structural and functional integrity of subgenual cingulate area 25 (A25) is crucial for emotional expression and equilibrium. A25 has a key role in affective networks, and its disruption has been linked to mood disorders, but its cortical connections have yet to be systematically or fully studied. Using neural tracers in rhesus monkeys, we found that A25 was densely connected with other ventromedial and posterior orbitofrontal areas associated with emotions and homeostasis. A moderate pathway linked A25 with frontopolar area 10, an area associated with complex cognition, which may regulate emotions and dampen negative affect. Beyond the frontal lobe, A25 was connected with auditory association areas and memory-related medial temporal cortices, and with the interoceptive-related anterior insula. A25 mostly targeted the superficial cortical layers of other areas, where broadly dispersed terminations comingled with modulatory inhibitory or disinhibitory microsystems, suggesting a dominant excitatory effect. The architecture and connections suggest that A25 is the consummate feedback system in the PFC. Conversely, in the entorhinal cortex, A25 pathways terminated in the middle-deep layers amid a strong local inhibitory microenvironment, suggesting gating of hippocampal output to other cortices and memory storage. The graded cortical architecture and associated laminar patterns of connections suggest how areas, layers, and functionally distinct classes of inhibitory neurons can be recruited dynamically to meet task demands. The complement of cortical connections of A25 with areas associated with memory, emotion, and somatic homeostasis provide the circuit basis to understand its vulnerability in psychiatric and neurologic disorders.SIGNIFICANCE STATEMENT Integrity of the prefrontal subgenual cingulate cortex is crucial for healthy emotional function. Subgenual area 25 (A25) is mostly linked with other prefrontal areas associated with emotion in a dense network positioned to recruit large fields of cortex. In healthy states, A25 is associated with internal states, autonomic function, and transient negative affect. Constant hyperactivity in A25 is a biomarker for depression in humans and may trigger extensive activation in its dominant connections with areas associated with emotions and internal balance. A pathway between A25 and frontopolar area 10 may provide a critical link to regulate emotions and dampen persistent negative affect, which may be explored for therapeutic intervention in depression.

Linking the biological underpinnings of depression: Role of mitochondria interactions with melatonin, inflammation, sirtuins, tryptophan catabolites, DNA repair and oxidative and nitrosative stress, with consequences for classification and cognition

The pathophysiological underpinnings of neuroprogressive processes in recurrent major depressive disorder (rMDD) are reviewed. A wide array of biochemical processes underlie MDD presentations and their shift to a recurrent, neuroprogressive course, including: increased immune-inflammation, tryptophan catabolites (TRYCATs), mitochondrial dysfunction, aryl hydrocarbonn receptor activation, and oxidative and nitrosative stress (O&NS), as well as decreased sirtuins and melatonergic pathway activity. These biochemical changes may have their roots in central, systemic and/or peripheral sites, including in the gut, as well as in developmental processes, such as prenatal stressors and breastfeeding consequences. Consequently, conceptualizations of MDD have dramatically moved from simple psychological and central biochemical models, such as lowered brain serotonin, to a conceptualization that incorporates whole body processes over a lifespan developmental timescale. However, important hubs are proposed, including the gut-brain axis, and mitochondrial functioning, which may provide achievable common treatment targets despite considerable inter-individual variability in biochemical changes. This provides a more realistic model of the complexity of MDD and the pathophysiological processes that underpin the shift to rMDD and consequent cognitive deficits. Such accumulating data on the pathophysiological processes underpinning MDD highlights the need in psychiatry to shift to a classification system that is based on biochemical processes, rather than subjective phenomenology.

Abnormal Functional Connectivity of Frontopolar Subregions in Treatment-Nonresponsive Major Depressive Disorder

BACKGROUND

Approximately 30% of patients with major depressive disorder develop treatment-nonresponsive depression (TNRD); novel interventions targeting the substrates of this illness population are desperately needed. Convergent evidence from lesion, stimulation, connectivity, and functional neuroimaging studies implicates the frontopolar cortex (FPC) as a particularly important region in TNRD pathophysiology; regions functionally connected to the FPC, once identified, could present favorable targets for novel brain stimulation treatments.

METHODS

We recently published a parcellation of the FPC based on diffusion tensor imaging data, identifying distinct medial and lateral subregions. Here, we applied this parcellation to resting-state functional magnetic resonance imaging scans obtained in 56 patients with TNRD and 56 matched healthy control subjects.

RESULTS

In patients, the medial FPC showed reduced connectivity to the anterior midcingulate cortex and insula. The left lateral FPC showed reduced connectivity to the right lateral orbitofrontal cortex and increased connectivity to the fusiform gyri. In addition, TNRD symptom severity correlated significantly with connectivity of the left lateral FPC subregion to a medial orbitofrontal cortex region of the classical reward network.

CONCLUSIONS

Taken together, these findings suggest that changes in FPC subregion connectivity may underlie several dimensions of TNRD pathology, including changes in reward/positive valence, nonreward/negative valence, and cognitive control domains. Nodes of functional networks showing abnormal connectivity to the FPC could be useful in generating novel candidates for therapeutic brain stimulation in TNRD.

Functional Connectivity of the Subcallosal Cingulate Cortex And Differential Outcomes to Treatment With Cognitive-Behavioral Therapy or Antidepressant Medication for Major Depressive Disorder

OBJECTIVE

The purpose of this article was to inform the first-line treatment choice between cognitive-behavioral therapy (CBT) or an antidepressant medication for treatment-naive adults with major depressive disorder by defining a neuroimaging biomarker that differentially identifies the outcomes of remission and treatment failure to these interventions.

METHOD

Functional MRI resting-state functional connectivity analyses using a bilateral subcallosal cingulate cortex (SCC) seed was applied to 122 patients from the Prediction of Remission to Individual and Combined Treatments (PReDICT) study who completed 12 weeks of randomized treatment with CBT or antidepressant medication. Of the 122 participants, 58 achieved remission (Hamilton Depression Rating Scale [HAM-D] score ≤7 at weeks 10 and 12), and 24 had treatment failure (<30% decrease from baseline in HAM-D score). A 2×2 analysis of variance using voxel-wise subsampling permutation tests compared the interaction of treatment and outcome. Receiver operating characteristic curves constructed using brain connectivity measures were used to determine possible classification rates for differential treatment outcomes.

RESULTS

The resting-state functional connectivity of the following three regions with the SCC was differentially associated with outcomes of remission and treatment failure to CBT and antidepressant medication and survived application of the subsample permutation tests: the left anterior ventrolateral prefrontal cortex/insula, the dorsal midbrain, and the left ventromedial prefrontal cortex. Using the summed SCC functional connectivity scores for these three regions, overall classification rates of 72%-78% for remission and 75%-89% for treatment failure was demonstrated. Positive summed functional connectivity was associated with remission with CBT and treatment failure with medication, whereas negative summed functional connectivity scores were associated with remission to medication and treatment failure with CBT.

CONCLUSIONS

Imaging-based depression subtypes defined using resting-state functional connectivity differentially identified an individual's probability of remission or treatment failure with first-line treatment options for major depression. This biomarker should be explored in future research through prospective testing and as a component of multivariate treatment prediction models.

Topographic organization of the cerebral cortex and brain cartography

One of the most specific but also challenging properties of the brain is its topographic organization into distinct modules or cortical areas. In this paper, we first review the concept of topographic organization and its historical development. Next, we provide a critical discussion of the current definition of what constitutes a cortical area, why the concept has been so central to the field of neuroimaging and the challenges that arise from this view. A key aspect in this discussion is the issue of spatial scale and hierarchy in the brain. Focusing on in-vivo brain parcellation as a rapidly expanding field of research, we highlight potential limitations of the classical concept of cortical areas in the context of multi-modal parcellation and propose a revised interpretation of cortical areas building on the concept of neurobiological atoms that may be aggregated into larger units within and across modalities. We conclude by presenting an outlook on the implication of this revised concept for future mapping studies and raise some open questions in the context of brain parcellation.

Local gyrification index in patients with major depressive disorder and its association with tryptophan hydroxylase-2 (TPH2) polymorphism

The tryptophan hydroxylase-2 (TPH2) gene is considered a promising genetic candidate regarding its association with a predisposition to major depressive disorder (MDD). Local gyrification reflects the early neural development of cortical connectivity, and is regarded as a potential neural endophenotype in psychiatric disorders. They aimed to investigate the alterations in the cortical gyrification of the prefrontal cortex and anterior cingulate cortex and their association with the TPH2 rs4570625 polymorphism in patients with MDD. One hundred and thirteen patients with MDD and eighty-six healthy controls underwent T1-weighted structural magnetic resonance imaging and genotyping for TPH2 rs4570625. The local gyrification index of 22 cortical regions in the prefrontal cortex and anterior cingulate cortex was analyzed using the FreeSurfer. The patients with MDD showed significant hypergyria in the right rostral anterior cingulate cortex (P = 0.001), medial orbitofrontal cortex (P = 0.003), and frontal pole (P = 0.001). There was a significant genotype-by-diagnosis interaction for the local gyrification index in the right rostral anterior cingulate cortex (P = 0.003). Their study revealed significant hypergyria of the anterior cingulate cortex and prefrontal cortex and an interactive effect between the diagnosis of MDD and the genotype in the anterior cingulate cortex. This might be associated with the dysfunction of neural circuits mediating emotion processing, which could contribute to pathophysiology of MDD. Hum Brain Mapp 38:1299-1310, 2017. © 2016 Wiley Periodicals, Inc.

Behavior, sensitivity, and power of activation likelihood estimation characterized by massive empirical simulation

Given the increasing number of neuroimaging publications, the automated knowledge extraction on brain-behavior associations by quantitative meta-analyses has become a highly important and rapidly growing field of research. Among several methods to perform coordinate-based neuroimaging meta-analyses, Activation Likelihood Estimation (ALE) has been widely adopted. In this paper, we addressed two pressing questions related to ALE meta-analysis: i) Which thresholding method is most appropriate to perform statistical inference? ii) Which sample size, i.e., number of experiments, is needed to perform robust meta-analyses? We provided quantitative answers to these questions by simulating more than 120,000 meta-analysis datasets using empirical parameters (i.e., number of subjects, number of reported foci, distribution of activation foci) derived from the BrainMap database. This allowed to characterize the behavior of ALE analyses, to derive first power estimates for neuroimaging meta-analyses, and to thus formulate recommendations for future ALE studies. We could show as a first consequence that cluster-level family-wise error (FWE) correction represents the most appropriate method for statistical inference, while voxel-level FWE correction is valid but more conservative. In contrast, uncorrected inference and false-discovery rate correction should be avoided. As a second consequence, researchers should aim to include at least 20 experiments into an ALE meta-analysis to achieve sufficient power for moderate effects. We would like to note, though, that these calculations and recommendations are specific to ALE and may not be extrapolated to other approaches for (neuroimaging) meta-analysis.