Brain structural alterations are consistently reported in depressive disorders, yet it remains unclear whether these alterations exist prior to disorder onset and thus may reflect a preexisting vulnerability. The authors investigated prospective adolescent neurodevelopmental risk markers for depressive disorder onset, using data from a 15-year longitudinal study.

A community sample of 161 adolescents participated in neuroimaging assessments conducted during early (age 12), mid (age 16), and late (age 19) adolescence. Onsets of depressive disorders were assessed for the period spanning early adolescence through emerging adulthood (ages 12-27). Forty-six participants (28 female) experienced a first episode of a depressive disorder during the follow-up period; 83 participants (36 female) received no mental disorder diagnosis. Joint modeling was used to investigate whether brain structure (subcortical volume, cortical thickness, and surface area) or age-related changes in brain structure were associated with the risk of depressive disorder onset.

Age-related increases in amygdala volume (hazard ratio=3.01), and more positive age-related changes (i.e., greater thickening or attenuated thinning) of temporal (parahippocampal gyrus, hazard ratio=3.73; fusiform gyrus, hazard ratio=4.14), insula (hazard ratio=4.49), and occipital (lingual gyrus, hazard ratio=4.19) regions were statistically significantly associated with the onset of depressive disorder.

Relative increases in amygdala volume and temporal, insula, and occipital cortical thickness across adolescence may reflect disturbances in brain development, contributing to depression onset. This raises the possibility that prior findings of reduced gray matter in clinically depressed individuals instead reflect alterations that are caused by disorder-related factors after onset.

Background and Objectives: Human immunodeficiency virus (HIV) has a profound impact on the central nervous system (CNS), contributing to cognitive impairment and depressive symptoms even in individuals receiving combination antiretroviral therapy (cART). This study aimed to investigate the associations between brain parenchymal volumes and neuropsychological outcomes, specifically focusing on cognitive function and depressive symptoms in HIV-positive males. Materials and Methods: A total of 48 male participants underwent cognitive assessment using the Mini-Mental State Examination (MMSE), while depressive symptoms were evaluated in 35 participants using the Beck Depression Inventory (BDI). Volumetric brain analysis was conducted through automated imaging software, volBrain (Version 1.0, published on 23 November 2021), ensuring high consistency and accuracy. Statistical analyses included Pearson correlation to identify relationships between brain volumes and neuropsychological outcomes, emphasizing key regions like the basal forebrain and cingulate gyrus. Results: Significant trends were observed between basal forebrain volume and MMSE scores, emphasizing the role of this region in cognitive regulation. Additional correlations were found with the anterior and middle cingulate gyri, which are crucial for executive functioning and attentional control. Notably, smaller right basal forebrain volumes were associated with greater depressive symptom severity, suggesting the region's specific involvement in mood regulation. These findings highlight the dual impact of HIV on cognitive and emotional health, with structural vulnerabilities in key brain regions playing a central role. Conclusions: This study underscores the selective vulnerability of certain brain regions, such as the basal forebrain and cingulate gyrus, to HIV-associated neurodegeneration. The results highlight the importance of integrating neuroimaging and neuropsychological assessments in routine clinical care for HIV-positive individuals. The study emphasizes the importance of early detection and targeted interventions to address neuropsychological challenges in this population, with a call for further research in larger and more diverse cohorts.

Major depressive disorder (MDD) is a common, relapse-prone psychiatric disorder with unknown pathogenesis. Previous studies on resting-state functional magnetic resonance imaging of MDD have mostly focused on the spontaneous activity of blood oxygen level-dependent (BOLD) signals; however, a few studies have investigated BOLD signal stability.

We conducted a resting-state functional study in 42 patients with MDD and 42 healthy controls (HC) matched for age and sex. This included the BOLD signal stability, resting-state functional connectivity (RSFC) analysis, correlation analysis, and support vector machine (SVM) analysis.

The BOLD signal stability of the left fusiform gyrus, right inferior temporal gyrus, right temporal pole superior temporal gyrus, and left thalamus was significantly lower in the MDD group compared to the HC group. Further RSFC analysis revealed that the connectivity between right inferior temporal gyrus and both left inferior temporal gyrus and left supramarginal gyrus was significantly reduced in the MDD group. Additionally, the RSFC levels of left thalamus and right thalamus were decreased. Combining BOLD signal stability and RSFC, the SVM-based classification model achieved an accuracy of 80.95% (sensitivity: 78.57%; specificity: 83.33%; receiver-operating characteristic area under the curve: 0.8793).

The integration of the BOLD signal stability index and RSFC index demonstrates a robust capability to differentiate between individuals with MDD and HC subjects. We tentatively believe that a combination of the BOLD signal stability index and RSFC can be used to diagnose MDD.

Ischemic stroke is a vascular disease that may cause cognitive and behavioral abnormalities. This study aims to assess abnormal brain function in ischemic stroke patients using the percent amplitude of fluctuation (PerAF) method and further explore the feasibility of PerAF as an imaging biomarker for investigating ischemic stroke pathophysiology mechanisms. Sixteen ischemic stroke patients and 22 healthy controls (HCs) underwent resting state functional magnetic resonance imaging (rs-fMRI) scanning, and the resulting data were analyzed using PerAF. Then a correlation analysis was conducted between PerAF values and Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) scores. Finally, the abnormal PerAF values were extracted and defined as features for support vector machine (SVM) analysis. Compared with HCs, ischemic stroke patients showed decreased PerAF in the bilateral cuneus, left middle frontal gyrus, precuneus and right inferior temporal gyrus, and increased PerAF in the bilateral orbital part of middle frontal gyrus and right orbital part of superior frontal gyrus. Correlation analyses revealed that PerAF values in the left orbital part of middle frontal gyrus was negatively correlated with the MoCA scores. The SVM classification of the PerAF values achieved an area under the curve (AUC) of 0.98 and an accuracy of 94.74%. Abnormal brain function has been found among ischemic stroke patients, which may be correlated with visual impairment, attention deficits, and dysregulation of negative emotions following a stroke. Our findings may support the potential of PerAF as a sensitive biomarker for investigating the underlying mechanisms of ischemic stroke.

Rumination is a common symptom in major depressive disorder (MDD). Previous work has connected individual differences in rumination to structural properties in various brain regions. Some of these, such as the dorsolateral prefrontal cortex (dlPFC), have also been highlighted as being altered in MDD, suggesting a connection between structural changes and ruminative symptoms. Although informative, such localised relations have limitations in the context of a network view of the brain. To further investigate rumination-related structural changes in depression, and to situate these within potential functional networks, we acquired T1-weighted structural MRI data from patients with MDD (n = 32) and controls (n = 69). Rumination was measured with the Rumination Response Scale. Surface-based, whole-brain analysis of cortical grey-matter identified group differences in the dlPFC that were, however, not related to rumination. Instead, rumination was correlated with grey-matter properties in the right precuneus. Using normative functional connectivity analysis on an independent sample (n = 100), we show these two regions to be interconnected. Further developing a network-based perspective, it was shown that the rumination-related precuneus region is connected with networks associated with processes such as executive function, autobiographical memory, and visual perception. Notably, these processes have been connected to rumination. These results suggest that rumination in depression may be linked to focal structural changes. The effects of these focal changes on rumination may then be connected to their influence on distributed functional networks.

Treatment-resistant depression (TRD) is defined as patients diagnosed with depression having a history of failure with different antidepressants with an adequate dosage and treatment duration. The NMDA receptor antagonist ketamine rapidly reduces depressive symptoms in TRD. We examined neural correlates of treatment response to ketamine in TRD through a systematic review of brain magnetic resonance imaging (MRI) studies. A comprehensive search in PubMed was performed using "ketamine AND depression AND magnetic resonance." The time span for the database queries was "Start date: 2018/01/01; End date: 2024/05/31." Total 41 original articles comprising 1,396 TRD and 587 healthy controls (HC) were included. Diagnosis of depression was made using the Structured Clinical Interview for DSM Disorders (SCID), the Mini-International Neuropsychiatric Interview (MINI), and/or the clinical assessment by psychiatrists. Patients with affective psychotic disorders were excluded. Most studies applied ketamine [0.5mg/kg racemic ketamine and/or 0.25mg/kg S-ketamine] diluted in 60cc of normal saline via intravenous infusion over 40 min one time, four times, or six times spaced 2-3 days apart over 2 weeks. Clinical outcome was defined as either remission, response, and/or percentage changes of depressive symptoms. Brain MRI of the T2*-weighted imaging (resting-state or task performance), arterial spin labeling, diffusion weighted imaging, and T1-weighted imaging were acquired at baseline and mainly 1-3days after the ketamine administration. Only the study results replicated by ≥ 2 studies and were included in the default-mode, salience, fronto-parietal, subcortical, and limbic networks were regarded as meaningful. Putative brain-based markers of treatment response to ketamine in TRD were found in the structural/functional features of limbic (subgenual ACC, hippocampus, cingulum bundle-hippocampal portion; anhedonia/suicidal ideation), salience (dorsal ACC, insula, cingulum bundle-cingulate gyrus portion; thought rumination/suicidal ideation), fronto-parietal (dorsolateral prefrontal cortex, superior longitudinal fasciculus; anhedonia/suicidal ideation), default-mode (posterior cingulate cortex; thought rumination), and subcortical (striatum; anhedonia/thought rumination) networks. Brain features of limbic, salience, and fronto-parietal networks could be useful in predicting the TRD with better response to ketamine in relief of anhedonia, thought rumination, and suicidal ideation.

Previous studies in small samples have identified inconsistent cortical abnormalities in major depressive disorder (MDD). Despite genetic influences on MDD and the brain, it is unclear how genetic risk for MDD is translated into spatially patterned cortical vulnerability. Here, we initially examined voxel-wise differences in cortical function and structure using the largest multi-modal MRI data from 1660 MDD patients and 1341 controls. Combined with the Allen Human Brain Atlas, we then adopted transcription-neuroimaging spatial correlation and the newly developed ensemble-based gene category enrichment analysis to identify gene categories with expression related to cortical changes in MDD. Results showed that patients had relatively circumscribed impairments in local functional properties and broadly distributed disruptions in global functional connectivity, consistently characterized by hyper-function in associative areas and hypo-function in primary regions. Moreover, the local functional alterations were correlated with genes enriched for biological functions related to MDD in general (e.g., endoplasmic reticulum stress, mitogen-activated protein kinase, histone acetylation, and DNA methylation); and the global functional connectivity changes were associated with not only MDD-general, but also brain-relevant genes (e.g., neuron, synapse, axon, glial cell, and neurotransmitters). Our findings may provide important insights into the transcriptomic signatures of regional cortical vulnerability to MDD.

Depressive and anxiety symptoms are prevalent among patients with various clinical conditions, resulting in diminished emotional well-being and impaired daily functioning. The neural mechanisms underlying these symptoms, particularly across different disorders, remain unclear, limiting the effectiveness of conventional treatments. Therefore, it is crucial to elucidate the neural underpinnings of depressive and anxiety symptoms and investigate novel, effective treatments across clinical conditions. Transcranial direct current stimulation (tDCS) is a neuromodulatory technique that can help understand the neural underpinnings of symptoms and facilitate the development of interventions, addressing the two research gaps at both neural and clinical levels. Thus, this systematic review and meta-analysis aims to evaluate the existing evidence regarding the therapeutic efficacy of tDCS in reducing depressive and anxiety symptoms among individuals with diverse clinical diagnoses. This review evaluated evidence from fifty-six randomized, sham-controlled trials that administered repeated tDCS sessions with a parallel design, applying a three-level meta-analytic model. tDCS targeting the left dorsolateral prefrontal cortex (DLPFC) at 2-mA intensity demonstrates moderate efficacy in alleviating depressive symptoms, identifying the left DLPFC as a transdiagnostic neural mechanism of depressive symptoms across clinical conditions. In comparison, the findings on anxiety symptoms demonstrate greater heterogeneity. tDCS over the left DLPFC is effective in reducing depressive symptoms and shows promising effects in alleviating anxiety symptoms among individuals with diverse diagnoses. These findings enhance our understanding of the neuropsychological basis of depressive and anxiety symptoms, laying the groundwork for the development of more effective tDCS interventions applicable across clinical conditions.

Anhedonia is a critical diagnostic symptom of major depressive disorder (MDD), being associated with poor prognosis. Understanding the neural mechanisms underlying anhedonia is of great significance for individuals with MDD, and it encourages the search for objective indicators that can reliably identify anhedonia.

A predictive model used connectome-based predictive modeling (CPM) for anhedonia symptoms was developed by utilizing pre-treatment functional connectivity (FC) data from 59 patients with MDD. Node-based FC analysis was employed to compare differences in FC patterns between melancholic and non-melancholic MDD patients. The support vector machines (SVM) method was then applied for classifying these two subtypes of MDD patients.

CPM could successfully predict anhedonia symptoms in MDD patients (positive network: r = 0.4719, p < 0.0020, mean squared error = 23.5125, 5000 iterations). Compared to non-melancholic MDD patients, melancholic MDD patients showed decreased FC between the left cingulate gyrus and the right parahippocampus gyrus (p_bonferroni = 0.0303). This distinct FC pattern effectively discriminated between melancholic and non-melancholic MDD patients, achieving a sensitivity of 93.54%, specificity of 67.86%, and an overall accuracy of 81.36% using the SVM method.

This study successfully established a network model for predicting anhedonia symptoms in MDD based on FC, as well as a classification model to differentiate between melancholic and non-melancholic MDD patients. These findings provide guidance for clinical treatment.

The medial prefrontal cortex (mPFC) forms output pathways through projection neurons, inversely receiving adjacent and long-range inputs from other brain regions. However, how afferent neurons of mPFC are affected by chronic stress needs to be clarified. In this study, the effects of chronic restraint stress (CRS) on the distribution density of mPFC dendrites/dendritic spines and the projections from the cortex and subcortical brain regions to the mPFC were investigated.

In the present study, C57BL/6 J transgenic (Thy1-YFP-H) mice were subjected to CRS to establish an animal model of depression. The infralimbic (IL) of mPFC was selected as the injection site of retrograde AAV using stereotactic technique. The effects of CRS on dendrites/dendritic spines and afferent neurons of the mPFC IL were investigaed by quantitatively assessing the distribution density of green fluorescent (YFP) positive dendrites/dendritic spines and red fluorescent (retrograde AAV recombinant protein) positive neurons, respectively.

The results revealed that retrograde tracing virus labeled neurons were widely distributed in ipsilateral and contralateral cingulate cortex (Cg1), second cingulate cortex (Cg2), prelimbic cortex (PrL), infralimbic cortex, medial orbital cortex (MO), and dorsal peduncular cortex (DP). The effects of CRS on the distribution density of mPFC red fluorescence positive neurons exhibited regional differences, ranging from rostral to caudal or from top to bottom. Simultaneously, CRS resulted a decrease in the distribution density of basal, proximal and distal dendrites, as well as an increase in the loss of dendritic spines of the distal dendrites in the IL of mPFC. Furthermore, varying degrees of red retrograde tracing virus fluorescence signals were observed in other cortices, amygdala, hippocampus, septum/basal forebrain, hypothalamus, thalamus, mesencephalon, and brainstem in both ipsilateral and contralateral brain. CRS significantly reduced the distribution density of red fluorescence positive neurons in other cortices, hippocampus, septum/basal forebrain, hypothalamus, and thalamus. Conversely, CRS significantly increased the distribution density of red fluorescence positive neurons in amygdala.

Our results suggest a possible mechanism that CRS leads to disturbances in synaptic plasticity by affecting multiple inputs to the mPFC, which is characterized by a decrease in the distribution density of dendrites/dendritic spines in the IL of mPFC and a reduction in input neurons of multiple cortices to the IL of mPFC as well as an increase in input neurons of amygdala to the IL of mPFC, ultimately causing depression-like behaviors.

The efficacy of bright light therapy (BLT) in ameliorating depression has been validated. The present study is to investigate the changes of depressive symptoms, cognitive function and cerebellar functional connectivity (FC) following BLT in individuals with subthreshold depression (StD).

Participants were randomly assigned to BLT group (N = 47) or placebo (N = 41) in this randomized controlled trial between March 2020 and June 2022. Depression severity and cognitive function were assessed, as well as resting-state functional MRI scan was conducted before and after 8-weeks treatment. Seed-based whole-brain static FC (sFC) and dynamic FC (dFC) analyses of the bilateral cerebellar subfields were conducted. Besides, a multivariate regression model examined whether baseline brain FC was associated with changes of depression severity and cognitive function during BLT treatment.

After 8-week BLT treatment, individuals with StD showed improved depressive symptoms and attention/vigilance cognitive function. BLT also increased sFC between the right cerebellar lobule IX and left temporal pole, and decreased sFC within the cerebellum, and dFC between the right cerebellar lobule IX and left medial prefrontal cortex. Moreover, the fusion of sFC and dFC at baseline could predict the improvement of attention/vigilance in response to BLT.

The current study identified that BLT improved depressive symptoms and attention/vigilance, as well as changed cerebellum-DMN connectivity, especially in the cerebellar-frontotemporal and cerebellar internal FC. In addition, the fusion features of sFC and dFC at pre-treatment could serve as an imaging biomarker for the improvement of attention/vigilance cognitive function after BLT in StD.

Background: The treatment of depressive episodes is well established, with clearly demonstrated effectiveness of antidepressants and psychotherapies. However, more than one-third of depressed patients do not respond to treatment. Identifying the brain structural basis of treatment-resistant depression could prevent useless pharmacological prescriptions, adverse events, and lost therapeutic opportunities. Methods: Using diffusion magnetic resonance imaging, we performed structural connectivity analyses on a cohort of 154 patients with mood disorder (MD) and 77 sex- and age-matched healthy control (HC) participants. To assess illness improvement, the patients with MD went through two clinical interviews at baseline and at 6-month follow-up and were classified based on the Clinical Global Impression-Improvement score into improved or not-improved (NI). First, the threshold-free network-based statistics (NBS) was conducted to measure the differences in regional network architecture. Second, nonparametric permutations tests were performed on topological metrics based on graph theory to examine differences in connectome organization. Results: The threshold-free NBS revealed impaired connections involving regions of the basal ganglia in patients with MD compared with HC. Significant increase of local efficiency and clustering coefficient was found in the lingual gyrus, insula, and amygdala in the MD group. Compared with the NI, the improved displayed significantly reduced network integration and segregation, predominately in the default-mode regions, including the precuneus, middle temporal lobe, and rostral anterior cingulate. Conclusions: This study highlights the involvement of regions belonging to the basal ganglia, the fronto-limbic network, and the default mode network, leading to a better understanding of MD disease and its unfavorable outcome.

Depression is a serious public health problem, and adolescence is an 'age of risk' for the onset of Major Depressive Disorder. Recently, we and others have proposed neuroimmune network models that highlight bidirectional communication between the brain and the immune system in both mental and physical health, including depression. These models draw on research indicating that the cellular actors (particularly monocytes) and signaling molecules (particularly cytokines) that orchestrate inflammation in the periphery can directly modulate the structure and function of the brain. In the brain, inflammatory activity heightens sensitivity to threats in the cortico-amygdala circuit, lowers sensitivity to rewards in the cortico-striatal circuit, and alters executive control and emotion regulation in the prefrontal cortex. When dysregulated, and particularly under conditions of chronic stress, inflammation can generate feelings of dysphoria, distress, and anhedonia. This is proposed to initiate unhealthy, self-medicating behaviors (e.g. substance use, poor diet) to manage the dysphoria, which further heighten inflammation. Over time, dysregulation in these brain circuits and the inflammatory response may compound each other to form a positive feedback loop, whereby dysregulation in one organ system exacerbates the other. We and others suggest that this neuroimmune dysregulation is a dynamic joint vulnerability for depression, particularly during adolescence. We have three goals for the present paper. First, we extend neuroimmune network models of mental and physical health to generate a developmental framework of risk for the onset of depression during adolescence. Second, we examine how a neuroimmune network perspective can help explain the high rates of comorbidity between depression and other psychiatric disorders across development, and multimorbidity between depression and stress-related medical illnesses. Finally, we consider how identifying neuroimmune pathways to depression can facilitate a 'next generation' of behavioral and biological interventions that target neuroimmune signaling to treat, and ideally prevent, depression in youth and adolescents.

Adolescent major depressive disorder (MDD) is a significant mental health concern that often leads to recurrent depression in adulthood. Resting-state functional magnetic resonance imaging (rs-fMRI) offers unique insights into the neural mechanisms underlying this condition. However, despite previous research, the specific vulnerable brain regions affected in adolescent MDD patients have not been fully elucidated.

To identify consistent vulnerable brain regions in adolescent MDD patients using rs-fMRI and activation likelihood estimation (ALE) meta-analysis.

We performed a comprehensive literature search through July 12, 2023, for studies investigating brain functional changes in adolescent MDD patients. We utilized regional homogeneity (ReHo), amplitude of low-frequency fluctuations (ALFF) and fractional ALFF (fALFF) analyses. We compared the regions of aberrant spontaneous neural activity in adolescents with MDD vs healthy controls (HCs) using ALE.

Ten studies (369 adolescent MDD patients and 313 HCs) were included. Combining the ReHo and ALFF/fALFF data, the results revealed that the activity in the right cuneus and left precuneus was lower in the adolescent MDD patients than in the HCs (voxel size: 648 mm3, P < 0.05), and no brain region exhibited increased activity. Based on the ALFF data, we found decreased activity in the right cuneus and left precuneus in adolescent MDD patients (voxel size: 736 mm3, P < 0.05), with no regions exhibiting increased activity.

Through ALE meta-analysis, we consistently identified the right cuneus and left precuneus as vulnerable brain regions in adolescent MDD patients, increasing our understanding of the neuropathology of affected adolescents.

Major Depressive Disorder (MDD) is marked by abnormal brain function and elevated plasma oxidative stress markers. The specific relationship between these factors in MDD remains unclear. In this study, we conducted resting-state fMRI scans on fifty-seven first-episode, drug-naive MDD patients and sixty healthy controls. Plasma levels of oxidative stress markers (superoxide dismutase (SOD) and glutathione reductase (GSR)) were assessed using ELISA. Our results revealed a positive correlation between plasma SOD and GSR levels in MDD patients and the amplitude of low-frequency fluctuation (ALFF) values in key brain regions-thalamus, anterior cingulate gyrus, and superior frontal gyrus. Further analysis indicated positive correlations between plasma SOD and GSR levels and specific ALFF values in MDD patients without suicidal ideation, with these correlations not significant in MDD patients with suicidal ideation. Additionally, seed-based whole-brain functional connectivity analysis demonstrated a negative correlation between plasma GSR levels and connectivity between the thalamus and insula, while plasma SOD levels showed a positive correlation with connectivity between the thalamus and precuneus. These findings contribute to our understanding of MDD's pathophysiology and heterogeneity, highlighting the association between plasma oxidative stress markers and functional abnormalities in diverse brain regions.

Anxiety and depression co-occur; the neural substrates of shared and unique components of these symptoms are not understood. Given emotional alterations in internalizing disorders, we hypothesized that function of regions associated with emotion processing/regulation, including the anterior cingulate cortex (ACC), amygdala and fusiform gyrus (FG), would differentiate these symptoms. Forty-three adults with depression completed an emotional functional magnetic resonance imaging task and the Hamilton Depression and Anxiety Scales. We transformed these scales to examine two orthogonal components, one representing internalizing symptom severity and the other the type of internalizing symptoms (anxiety vs depression). We extracted blood oxygen level dependent signal from FG subregions, ACC, and amygdala and performed generalized psychophysiological interaction analyses to assess relationships between symptoms and brain function. Type of internalizing symptoms was associated with FG3-FG1 coupling (F = 8.14, P = 0.007). More coupling was associated with a higher concentration of depression, demonstrating that intra-fusiform coupling is differentially associated with internalizing symptom type (anxiety vs depression). We found an interaction between task condition and internalizing symptoms and dorsal (F = 4.51, P = 0.014) and rostral ACC activity (F = 4.27, P = 0.012). Post hoc comparisons revealed that less activity was associated with greater symptom severity during emotional regulation. Functional coupling differences during emotional processing are associated with depressive relative to anxiety symptoms and internalizing symptom severity. These findings could inform future treatments for depression.

Major depressive disorder is a common psychiatric condition often resistant to medication. The Wistar-Kyoto (WKY) rat has been suggested as an animal model of depression; however, it is still challenging to translate results from animal models into humans. Solitary housing is a mild stress paradigm that can simulate the environment of depressive patients with limited social activity due to symptoms. We used voxel-based morphometry to associate the solitary-housed WKY (sWKY) rat model with data from previous human studies and validated our results with behavioural studies. As a result, atrophy in sWKY rats was detected in the ventral hippocampus, caudate putamen, lateral septum, cerebellar vermis, and cerebellar nuclei (p < 0.05, corrected for family-wise error rate). Locomotor behaviour was negatively correlated with habenula volume and positively correlated with atrophy of the cerebellar vermis. In addition, sWKY rats showed depletion of sucrose consumption not after reward habituation but without reward habituation. Although the application of sWKY rats in a study of anhedonia might be limited, we observed some similarities between the regions of brain atrophy in sWKY rats and humans with depression, supporting the translation of sWKY rat studies to humans.

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.

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.

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).

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.

Major depressive disorder (MDD) is a heterogeneous clinical syndrome with widespread subtle neuroanatomical correlates. Our objective was to identify the neuroanatomical dimensions that characterize MDD and predict treatment response to selective serotonin reuptake inhibitor (SSRI) antidepressants or placebo. In the COORDINATE-MDD consortium, raw MRI data were shared from international samples (N = 1,384) of medication-free individuals with first-episode and recurrent MDD (N = 685) in a current depressive episode of at least moderate severity, but not treatment-resistant depression, as well as healthy controls (N = 699). Prospective longitudinal data on treatment response were available for a subset of MDD individuals (N = 359). Treatments were either SSRI antidepressant medication (escitalopram, citalopram, sertraline) or placebo. Multi-center MRI data were harmonized, and HYDRA, a semi-supervised machine-learning clustering algorithm, was utilized to identify patterns in regional brain volumes that are associated with disease. MDD was optimally characterized by two neuroanatomical dimensions that exhibited distinct treatment responses to placebo and SSRI antidepressant medications. Dimension 1 was characterized by preserved gray and white matter (N = 290 MDD), whereas Dimension 2 was characterized by widespread subtle reductions in gray and white matter (N = 395 MDD) relative to healthy controls. Although there were no significant differences in age of onset, years of illness, number of episodes, or duration of current episode between dimensions, there was a significant interaction effect between dimensions and treatment response. Dimension 1 showed a significant improvement in depressive symptoms following treatment with SSRI medication (51.1%) but limited changes following placebo (28.6%). By contrast, Dimension 2 showed comparable improvements to either SSRI (46.9%) or placebo (42.2%) (β = -18.3, 95% CI (-34.3 to -2.3), P = 0.03). Findings from this case-control study indicate that neuroimaging-based markers can help identify the disease-based dimensions that constitute MDD and predict treatment response.

This study investigated the impact of intolerance of uncertainty (IU) on structural changes in the brain and symptom severity in patients with panic disorder.

This study included 90 participants diagnosed with panic disorder. The IU Scale, Panic Disorder Severity Scale (PDSS), Beck Depression Inventory-II (BDI-II), Penn State Worry Questionnaire (PSWQ), Self-Forgiveness Scale (SFS), and Short Form 36 Health Survey (SF) were used. A voxel-wise correlation analysis was conducted to investigate the structural differences in the gray matter.

As IU increased, the cortical thickness of the right lingual gyrus decreased significantly, while the gray matter volume of the right pars triangularis increased. The cortical thickness of the right lingual gyrus showed a significant negative correlation with the BDI-II score and a positive correlation with the SFS. Additionally, the gray matter volume of the right pars triangularis was positively correlated with the PDSS, PSWQ, and BDI-II scores and negatively correlated with the mental health domain of the SF.

According to our findings, elevated IU in participants with panic disorder was associated with cortical thinning in the lingual gyrus and increased gray matter volume in the pars triangularis. These structural alterations may also have an impact on perceived quality of life, as well as high levels of depression and anxiety.

Although tooth loss and periodontitis have been considered risk factors of Alzheimer disease, recent longitudinal researches have not found a significant association with hippocampal atrophy. Therefore, this study aimed to clarify a longitudinal association between the number of teeth present (NTP) and hippocampal atrophy dependent on the severity of periodontitis in a late middle-aged and older adult population.

This study included community-dwelling individuals aged 55 years or older who had no cognitive decline and had undergone brain MRI and oral and systemic data collection twice at 4-year intervals. Hippocampal volumes were obtained from MRIs by automated region-of-interest analysis. The mean periodontal probing depth (PD) was used as a measure of periodontitis. Multiple regression analysis was performed with the annual symmetric percentage change (SPC) of the hippocampal volume as the dependent variable and including an interaction term between NTP and mean PD as the independent variable. The interaction details were examined using the Johnson-Neyman technique and simple slope analysis. The 3-way interaction of NTP, mean PD, and time on hippocampal volume was analyzed using a linear mixed-effects model, and the interaction of NTP and time was examined in subgroups divided by the median mean PD. In all models, dropout bias was adjusted by inverse probability weighting.

Data of 172 participants were analyzed. The qualitative interaction between NTP and the mean PD was significant for the annual SPC in the left hippocampus. The regression coefficient of the NTP on the annual SPC in the left hippocampus was positive (B = 0.038, p = 0.026) at the low-level mean PD (mean -1 SD) and negative (B = -0.054, p = 0.001) at the high-level mean PD (mean +1 SD). Similar results were obtained in the linear mixed-effects model; the interaction of NTP and time was significant in the higher mean PD group.

In a late middle-aged and older cohort, fewer teeth were associated with a faster rate of left hippocampal atrophy in patients with mild periodontitis, whereas having more teeth was associated with a faster rate of atrophy in those with severe periodontitis. The importance of keeping teeth healthy is suggested.

Researchers find it difficult to distinguish between depression with ASD (Depress-wASD) and without ASD (Depression) in adult patients. We aimed to clarify the differences in brain connectivity between patients with depression with ASD and without ASD.

From April 2017 to February 2019, 22 patients with suspected depression were admitted to the hospital for diagnosis or follow-up and met the inclusion criteria. The diagnosis was determined according to the Diagnostic and Statistical Manual of Mental Disorders-5 by skilled psychiatrists. The Hamilton Depression Rating Scale (HAM-D), Young Mania Raging Scale (YMRS), Mini-International Neuropsychiatric Interview, Parent-interview ASD Rating Scale-Text Revision (PARS-TR), and Autism-Spectrum Quotient-Japanese version (AQ-J) were used to assess the patients' background and help with diagnosis. Resting-state functional magnetic resonance imaging (rs-fMRI) was performed using the 3-T-MRI system. rs-fMRI was processed using the CONN functional connectivity toolbox. Voxel-based morphometry was performed using structural images.

No significant difference was observed between the Depress-wASD and Depression groups using the HAM-D, YMRS, AQ-J, Intelligence Quotient (IQ), and verbal IQ results. rs-fMRI for the Depress-wASD group indicated a positive connection between the salience network (SN) and right supramarginal gyrus (SMG) and a negative connection between the SN and hippocampus and para-hippocampus than that for the Depression group. No significant structural differences were observed between the groups.

We identified differences in the SN involving the SMG and hippocampal regions between the Depress-wASD and Depression groups.

Cognitive theories of depression contend that biased cognitive information processing plays a causal role in the development of depression. Extensive research shows that deeper processing of negative and/or shallower processing of positive self-descriptors (i.e., negative and positive self-schemas) predicts current and future depression in adults and children. However, the neural correlates of the development of self-referent encoding are poorly understood. We examined children's self-referential processing using the self-referent encoding task (SRET) collected from 74 children at ages 6, 9, and 12; around age 10, these children also contributed structural magnetic resonance imaging data. From age 6 to age 12, both positive and negative self-referential processing showed mean-level growth, with positive self-schemas increasing relatively faster than negative ones. Further, voxel-based morphometry showed that slower growth in positive self-schemas was associated with lower regional gray matter volume (GMV) in ventrolateral prefrontal cortex (vlPFC). Our results suggest that smaller regional GMV within vlPFC, a critical region for regulatory control in affective processing and emotion development, may have implications for the development of depressogenic self-referential processing in mid-to-late childhood.

Prior research has demonstrated that the brains of adolescents with depression exhibit distinct structural alterations. However, preliminary studies have documented the pathophysiological changes in certain brain regions, such as the cerebellum, highlighting a need for further research to support the current understanding of this disease.

To study brain changes in depressed adolescents.

This study enrolled 34 adolescents with depression and 34 age-, sex-, and education-level-matched healthy control (HC) individuals. Structural and functional alterations were identified when comparing the brains of these two participant groups through voxel-based morphometry and cerebral blood flow (CBF) analysis, respectively. Associations between identified brain alterations and the severity of depressive symptoms were explored through Pearson correlation analyses.

The cerebellum, superior frontal gyrus, cingulate gyrus, pallidum, middle frontal gyrus, angular gyrus, thalamus, precentral gyrus, inferior temporal gyrus, superior temporal gyrus, inferior frontal gyrus, and supplementary motor areas of adolescents with depression showed an increase in brain volume compared to HC individuals. These patients with depression further presented with a pronounced drop in CBF in the left pallidum (group = 98, and peak t = - 4.4324), together with increased CBF in the right percental gyrus (PerCG) (group = 90, and peak t = 4.5382). In addition, 17-item Hamilton Depression Rating Scale scores were significantly correlated with the increased volume in the opercular portion of the left inferior frontal gyrus (r = - 0.5231, P < 0.01).

The right PerCG showed structural and CBF changes, indicating that research on this part of the brain could offer insight into the pathophysiological causes of impaired cognition.

Electroconvulsive therapy (ECT) is an important treatment for depression. Although it is known as the most effective acute treatment for severe mood disorders, its therapeutic mechanism is still unclear. With the rapid development of neuroimaging technology, various neuroimaging techniques have been available to explore the alterations of the brain by ECT, such as structural magnetic resonance imaging, functional magnetic resonance imaging, magnetic resonance spectroscopy, positron emission tomography, single photon emission computed tomography, arterial spin labeling, etc. This article reviews studies in neuroimaging on ECT for depression. These findings suggest that the neurobiological mechanism of ECT may regulate the brain functional activity, and neural structural plasticity, as well as balance the brain's neurotransmitters, which finally achieves a therapeutic effect.

Elevations in pain catastrophizing (PC) are associated with more severe pain, emotional distress, and impairment within samples with chronic pain. However, brain structure correlates underlying individual differences in PC are not well understood and predict more severe pain and impairment within samples with chronic pain. This study assessed links between regional gray matter volume (GMV) and individual differences in PC within a large mixed chronic pain sample.

Chinese adult community dwellers with chronic pain of at least 3 months duration (101 women and 59 men) completed self-report measures of background characteristics, pain severity, depression, and a widely validated PC questionnaire as well as a structural magnetic resonance imagining scan featuring voxel-based morphology to assess regional GMV correlates of PC.

After controlling for demographic correlates of PC, pain severity, and depression, higher PC scores had a significant, unique association with lower GMV levels in the inferior temporal area of the right fusiform gyrus, a region previously implicated in emotion regulation.

GMV deficits, particularly in right temporal-occipital emotion regulation regions, correspond to high levels of PC among individuals with chronic pain.

A third of people suffering from major depressive disorder do not experience a significant improvement in their symptoms even after adequate treatment with two different antidepressant medications. This common condition, termed treatment-resistant depression (TRD), severely affects the quality of life of millions of people worldwide, causing long-lasting interpersonal problems and social costs. Given its epidemiological and clinical relevance and the little consensus on whether the neurobiological underpinnings of TRD differ from treatment-sensitive depression (TSD), we sought to highlight the convergent morphometric and functional neuroimaging correlates of TRD.

We systematically reviewed the published literature on structural and resting-state functional neuroimaging of TRD compared to TSD and healthy controls (HC) and performed exploratory coordinate-based meta-analyses (CBMA) of significant results separately for each modality and multimodally ("all-effects"). CBMAs were also performed for each direction and combining both directions of group contrasts.

Out of the initial 1929 studies, only eight involving 555 participants (189 patients with TRD, 156 with TSD, and 210 HC) were included. In all-effects CBMA, precentral/superior frontal gyrus showed a significant difference between TRD and HC. Functional and structural imaging meta-analyses did not yield statistically significant results. A marginally significant cluster of altered intrinsic activity was found between TRD and HC in the cerebellum/pons.

Frontal, cerebellar, and brainstem functions can be involved in the pathophysiology of TRD. However, the design and heterogeneity of the (scarce) published literature hinder the generalizability of the findings.

Anxious depression is one of the subtypes of major depressive disorder (MDD), usually defined as "patients with MDD and high levels of anxiety symptoms". Compared to non-anxious MDD (naMDD), patients with anxious MDD (aMDD) have more severe depressive symptoms and suicidal ideation, worse treatment outcomes and remission rates, and poorer prognosis. Current research suggests that the Papez circuit is an important brain structure closely related to emotion, memory, and cognition. This study applied DTI to explore the altered white matter integrity in Papez circuit of patients with aMDD.

DTI data were acquired from 30 medication-naive outpatients with naMDD and 55 with aMDD and 88 demographically similar healthy control (HC) subjects. Voxel-based analysis (VBM) and region of interest (ROI) analysis were conducted to explore the significant difference of fractional anisotropy (FA) values among 3 groups. Pearson's correlations were performed to analyze the correlation between FA values and the score of HAMA-14 and HAMD-17.

We found that aMDD patients had significantly higher FA values in left fornix (belong to Papez circuit) and left posterior thalamic radiation and right anterior corona radiata (belong to limbic-thalamo-cortical circuitry) compared with HC. And there was variability in the white matter integrity in right posterior thalamic radiation (belong to limbic-thalamo-cortical circuitry) and left fornix (belong to Papez circuit) between aMDD and naMDD patients.

The cross-sectional study and the population vary between aMDD group and naMDD group are limitations.

Abnormal white matter integrity in Papez circuit and Limbic-Thalamo-Cortical circuitry may play an important role in the neuropathology of aMDD and might help to identify aMDD.

Efforts to develop neuroimaging-based biomarkers in major depressive disorder (MDD), at the individual level, have been limited to date. As diagnostic criteria are currently symptom-based, MDD is conceptualized as a disorder rather than a disease with a known etiology; further, neural measures are often confounded by medication status and heterogeneous symptom states.

We describe a consortium to quantify neuroanatomical and neurofunctional heterogeneity via the dimensions of novel multivariate coordinate system (COORDINATE-MDD). Utilizing imaging harmonization and machine learning methods in a large cohort of medication-free, deeply phenotyped MDD participants, patterns of brain alteration are defined in replicable and neurobiologically-based dimensions and offer the potential to predict treatment response at the individual level. International datasets are being shared from multi-ethnic community populations, first episode and recurrent MDD, which are medication-free, in a current depressive episode with prospective longitudinal treatment outcomes and in remission. Neuroimaging data consist of de-identified, individual, structural MRI and resting-state functional MRI with additional positron emission tomography (PET) data at specific sites. State-of-the-art analytic methods include automated image processing for extraction of anatomical and functional imaging variables, statistical harmonization of imaging variables to account for site and scanner variations, and semi-supervised machine learning methods that identify dominant patterns associated with MDD from neural structure and function in healthy participants.

We are applying an iterative process by defining the neural dimensions that characterise deeply phenotyped samples and then testing the dimensions in novel samples to assess specificity and reliability. Crucially, we aim to use machine learning methods to identify novel predictors of treatment response based on prospective longitudinal treatment outcome data, and we can externally validate the dimensions in fully independent sites.

We describe the consortium, imaging protocols and analytics using preliminary results. Our findings thus far demonstrate how datasets across many sites can be harmonized and constructively pooled to enable execution of this large-scale project.