This study investigates structural abnormalities in hippocampal subfield volumes and shapes, and their association with plasma CC chemokines in individuals with major depressive disorder (MDD).

A total of 61 patients with MDD and 65 healthy controls (HC) were recruited. All participants underwent high-resolution T1-weighted imaging and provided blood samples for the detection of CC chemokines (CCL2, CCL7, and CCL11). Comparisons of hippocampal subregion volumes, surface shapes, and plasma CC chemokine concentrations were conducted between the MDD and HC groups. Furthermore, partial correlation analysis was performed to assess the relationship between structural abnormalities (hippocampal subfield volume and shape) and plasma CC chemokine levels.

The MDD group exhibited a significant reduction in the volume of the left hippocampal tail compared to the HC group (F = 9.750, Bonferroni-corrected p = 0.026). No significant outward or inward deformation of the hippocampus was detected in MDD patients relative to the HC group (all FWE-corrected p > 0.05). Additionally, plasma CCL11 levels were elevated in the MDD group compared to the HC group (F = 9.982, p = 0.002), with these levels showing a positive correlation with the duration of the illness (r = 0.279, p = 0.029). Partial correlation analysis further revealed a negative correlation between the smaller left hippocampal tail volume and plasma CCL11 levels in MDD patients (r = −0.416, p = 0.001).

Abnormally elevated plasma CCL11 in MDD patients may mediate damage to specific hippocampal substructures.

Identifying key areas of brain dysfunction in mental illness is critical for developing precision diagnosis and treatment. This study aimed to develop region-specific brain aging trajectory prediction models using multimodal magnetic resonance imaging (MRI) to identify similarities and differences in abnormal aging between bipolar disorder (BD) and major depressive disorder (MDD) and pinpoint key brain regions of structural and functional change specific to each disorder.

Neuroimaging data from 340 healthy controls, 110 BD participants, and 68 MDD participants were included from the Taiwan Aging and Mental Illness cohort. We constructed 228 models using T1-weighted MRI, resting-state functional MRI, and diffusion tensor imaging data. Gaussian process regression was used to train models for estimating brain aging trajectories using structural and functional maps across various brain regions.

Our models demonstrated robust performance, revealing accelerated aging in 66 gray matter regions in BD and 67 in MDD, with 13 regions common to both disorders. The BD group showed accelerated aging in 17 regions on functional maps, whereas no such regions were found in MDD. Fractional anisotropy analysis identified 43 aging white matter tracts in BD and 39 in MDD, with 16 tracts common to both disorders. Importantly, there were also unique brain regions with accelerated aging specific to each disorder.

These findings highlight the potential of brain aging trajectories as biomarkers for BD and MDD, offering insights into distinct and overlapping neuroanatomical changes. Incorporating region-specific changes in brain structure and function over time could enhance the understanding and treatment of mental illness.

Methadone maintenance treatment (MMT) and protracted abstinence (PA) effectively reduce the craving for heroin among individuals with heroin use disorder (HUD). However, the difference in their effects on brain function, especially the coupling among the large-scale brain networks (default mode [DMN], salience [SN], and executive control [ECN] networks), remains unclear. This study analyzed the effects of the MMT and PA on these networks and the predictive value of the bilateral resource allocation index (RAI) for craving for heroin.

Twenty-five individuals undergoing the MMT, 22 undergoing the PA, and 51 healthy controls underwent resting-state functional magnetic resonance imaging (rs-fMRI). Independent component analysis identified the ECN, DMN, and SN. The SN-ECN and SN-DMN connectivity and the bilateral RAI were evaluated. The relationships between network coupling and clinical and psychological characteristics were analyzed. The multiple linear regression model identified significant variables for predicting craving scores.

The MMT group showed significantly stronger SN-left ECN (lECN) coupling and left RAI than the PA group. In the MMT group, SN-lECN connectivity and bilateral RAI were positively correlated with the total methadone dose. In both treatment groups, SN-right ECN (rECN) connectivity and right RAI were negatively correlated with craving. The models revealed that the bilateral RAI and the MMT and PA were associated with the craving.

The MMT enhances SN-lECN coupling and the left RAI more than the PA, possibly due to higher control modulation. The RAI could help predict heroin craving in individuals with HUD undergoing either treatment program.

Obstetric complications (OCs) are associated with cognitive and brain abnormalities observed in patients with schizophrenia. Gyrification, a measure of cortical integrity sensitive to events occurring during the prenatal and perinatal periods, is also altered in first-episode psychosis (FEP). We examined the relationship between OCs and gyrification in FEP, as well as whether gyrification mediates the relationship between OCs and cognition.

We examined differences in the Local Gyrification Index (LGI) for the frontal, parietal, temporal, occipital, and cingulate cortices between 139 FEP patients and 125 healthy controls (HCs). Regression analyses explored whether OCs and diagnosis interact to explain LGI variation. Parametric mediation analyses were conducted to assess the effect of LGI on the relationship between OCs and cognition for FEP and HC.

Significant LGI differences were observed between FEP patients and HC in the left parietal and bilateral cingulate and occipital cortices. There was a significant interaction between OCs and diagnosis on the left cingulate cortex (LCC) that was specific to males (p = 0.04) and was driven by gestational rather than intrauterine OCs.

In HCs, OCs had a direct effect on working memory (WM) (p = 0.048) in the mediation analysis, whereas in FEP, we observed no significant effect of OCs on either verbal or WM.

OCs interact with diagnosis to predict LCC gyrification, such that males with FEP exposed to OCs exhibit the lowest LGI. OCs influence WM, and LCC gyrification may mediate this relation only in HC, suggesting a differential neurodevelopmental process in psychosis.

Stroke due to basilar artery occlusion (BAO) carries poor outcomes despite advancements in endovascular therapy (EVT). Predictors of recovery remain underexplored. This study evaluates clinical and imaging predictors of outcomes following EVT, including a Critical Area Diffusion Score (CADS), assessing infarct location and extent in critical brainstem regions on post-EVT MRI.

This retrospective study analyzed 48 BAO patients treated with EVT at a provincial stroke center (2015–2021). Patients were categorized by outcomes (favorable: modified Rankin Scale [mRS] 0–3; unfavorable: mRS 4–6). Clinical, demographic and imaging data – age, baseline National Institutes of Health Stroke Scale (NIHSS), reperfusion success (thrombolysis in cerebral infarction [TICI] 2b–3) and post-EVT CADS from diffusion-weighted MRI – were assessed using univariate and multivariate logistic regression.

Patients with favorable outcomes were younger (median 64.0 vs. 73.0 years, p = 0.031), had lower NIHSS scores at presentation (median 8 vs. 16, p = 0.018) and achieved higher successful reperfusion rates (81.0% vs. 48.1%, p = 0.020). CADS ≤ 3 was linked to better outcomes (median mRS 3 vs. 5, p = 0.026) and higher odds of recovery in univariate analysis (OR = 10.89, p = 0.038). However, in multivariate analysis, CADS was not an independent predictor, with successful reperfusion (OR = 18.8, p = 0.044) as the strongest factor.

Age, NIHSS scores and successful reperfusion predict recovery in BAO patients undergoing EVT. Although CADS ≤ 3 is linked to favorable outcomes, it is not independently predictive. CADS holds promise as a prognostic tool, but its utility should be considered alongside clinical markers to enhance outcome prediction in BAO.

The identification of early warning signs is of great importance for identifying individuals at risk for mental disorders. Especially in the case of bipolar disorder, these research endeavours are imperative considering that the frequently delayed diagnoses and longer illness duration are associated with symptom exacerbation and lower recovery rates.

To multimodally investigate associations between hypomanic personality traits and altered social affect and social cognition to probe their role as early warning signs of bipolar disorder.

In a community sample (n = 140; 50.71% female), we investigated associations between hypomanic personality traits and both behavioural and neural activity measures of empathy and theory of mind (ToM) based on data from a functional magnetic resonance imaging paradigm.

Although analyses revealed no significant associations between behavioural or neural correlates of empathy and hypomanic personality traits, these traits were significantly associated with elevated ToM-related neural activity in the anterior rostral medial prefrontal cortex and anterior cingulate cortex. These neural activation differences were not accompanied by differences in behavioural ToM performance, suggesting more intense recruitment of task-relevant brain regions but unaffected behavioural outcomes.

Our findings indicate hypomanic personality traits to be positively associated with ToM-related neural activity but not with behavioural ToM performance. Prospectively, our study contributes to driving towards a more comprehensive and potentially neurobiologically grounded phenotype of bipolar disorder risk that contributes to a more differential understanding of risk and resilience mechanisms.

Mild behavioural impairment (MBI) is a neurobehavioral prodrome to dementia with multiple phenotypic characteristics. To investigate the complex neurobiological substrate underlying MBI, we evaluated its association with a composite magnetic resonance imaging (MRI)-based measure of concomitant cerebrovascular disease (CeVD) and neurodegeneration; and the interaction effects of MBI and MRI scores on cognitive and clinical trajectory.

253 dementia-free participants (mean age = 71.9, follow-up period = 49.89 months) from 2 memory clinics were included in this study. 37 (14.6%) participants met clinical diagnostic criteria for MBI, ascertained by repeated neuropsychiatric inventory assessments. MRI scores were computed using a validated weighted sum of white matter hyperintensities volume, presence of infarct, hippocampal volume, and cortical thickness of known Alzheimer’s disease-associated regions. Clinical and cognitive outcomes were evaluated annually using the Clinical Dementia Rating sum-of-boxes (CDR-SB) and standardised global cognitive scores of a comprehensive neuropsychological battery respectively.

Lower MRI scores, indicating greater burden of comorbid CeVD and neurodegeneration, yielded a 3.8-fold likelihood of MBI compared to 1.5-fold with larger WMH volume or lower cortical thickness individually. Interaction analyses showed that MBI participants with low MRI scores had greater increase in CDR-SB (B = 0.05, SE = 0.01, p < 0.001) over time. All models involving the composite MRI measure yielded a better fit compared to reduced models with either pathology alone.

MBI is associated with a composite MRI measure that reflects mixed pathologies of dementia and their co-evaluation may improve risk profiling and identification of memory clinic patients without dementia who are at the highest risk of experiencing clinical decline.

Suicidal ideation (SI) is very common in patients with major depressive disorder (MDD). However, its neural mechanisms remain unclear. The anterior cingulate cortex (ACC) region may be associated with SI in MDD patients. This study aimed to elucidate the neural mechanisms of SI in MDD patients by analyzing changes in gray matter volume (GMV) in brain structures in the ACC region, which has not been adequately studied to date.

According to the REST-meta-MDD project, this study subjects consisted of 235 healthy controls and 246 MDD patients, including 123 MDD patients with and 123 without SI, and their structural magnetic resonance imaging data were analyzed. The 17-item Hamilton Depression Rating Scale (HAMD) was used to assess depressive symptoms. Correlation analysis and logistic regression analysis were used to determine whether there was a correlation between GMV of ACC and SI in MDD patients.

MDD patients with SI had higher HAMD scores and greater GMV in bilateral ACC compared to MDD patients without SI (all p < 0.001). GMV of bilateral ACC was positively correlated with SI in MDD patients and entered the regression equation in the subsequent logistic regression analysis.

Our findings suggest that GMV of ACC may be associated with SI in patients with MDD and is a sensitive biomarker of SI.

This study aimed to utilise graph theory to explore the functional brain networks in individuals with tic disorders and to investigate resting-state functional connectivity changes in critical brain regions associated with tic disorders.

Participants comprised individuals with tic disorders and age-matched healthy controls, ranging from 6 to 18 years old, all recruited from Korea University Guro Hospital. We ensured a medication-naïve cohort by excluding participants exposed to psychotropic medications for at least three weeks prior to the study. Data included structural and resting-state functional MRI scans, analysed with the CONN-fMRI Functional Connectivity toolbox v20b. The analysis included 22 patients (18 males, 4 females) and 26 controls (14 males, 12 females).

Significantly increased global efficiency was observed in the left inferior frontal gyrus pars opercularis among tic disorder patients compared to controls. Furthermore, this region displayed enhanced resting-state functional connectivity with its right counterpart in patients versus controls.

The inferior frontal gyrus pars opercularis, known for its inhibitory role, may reflect adaptive functional adjustments in response to tic symptoms. Increased hubness of the inferior frontal gyrus pars opercularis possibly represents functional adjustments in response to tic symptoms. The identified brain region with increased efficiency and connectivity presents a promising avenue for further research into tic expression and control mechanisms.

Neuroimaging studies have documented brain structural changes in schizophrenia at different stages of the illness, including clinical high-risk (cHR), genetic high-risk (gHR), first-episode schizophrenia (FES), and chronic schizophrenia (ChS). There is growing awareness that neuropathological processes associated with a disease fail to map to a specific brain region but do map to a specific brain network. We sought to investigate brain structural damage networks across different stages of schizophrenia.

We initially identified gray matter alterations in 523 cHR, 855 gHR, 2162 FES, and 2640 ChS individuals relative to 6963 healthy controls. By applying novel functional connectivity network mapping to large-scale discovery and validation resting-state functional magnetic resonance imaging datasets, we mapped these affected brain locations to four specific networks.

Brain structural damage networks of cHR and gHR had limited and non-overlapping spatial distributions, with the former mainly involving the frontoparietal network and the latter principally implicating the subcortical network, indicative of distinct neuropathological mechanisms underlying cHR and gHR. By contrast, brain structural damage networks of FES and ChS manifested as similar patterns of widespread brain areas predominantly involving the somatomotor, ventral attention, and subcortical networks, suggesting an emergence of more prominent brain structural abnormalities with illness onset that have trait-like stability over time.

Our findings may not only provide a refined picture of schizophrenia neuropathology from a network perspective, but also potentially contribute to more targeted and effective intervention strategies for individuals at different schizophrenia stages.

Executive control over low-level information processing is impaired proximal to psychosis onset with evidence of recovery over the first year of illness. However, previous studies demonstrating diminished perceptual modulation via attention are complicated by simultaneously impaired perceptual responses. The present study examined the early auditory gamma-band response (EAGBR), a marker of early cortical processing that appears preserved in first-episode psychosis (FEP), and its modulation by attention in a longitudinal FEP sample.

Magnetoencephalography was recorded from 25 FEP and 32 healthy controls (HC) during active and passive listening conditions in an auditory oddball task at baseline and follow-up (4–12 months) sessions. EAGBR inter-trial phase coherence (ITPC) and evoked power were measured from responses to standard tones. Symptoms were assessed using the Positive and Negative Syndrome Scale (PANSS).

There was no group difference in EAGBR power or ITPC. While EAGBR ITPC increased with attention in HC, this modulation was impaired among FEP. Diminished EAGBR modulation in FEP persisted at longitudinal follow-up. However, among FEP, recovery of EAGBR modulation was associated with reduced PANSS negative scores.

FEP exhibit impaired executive control over the flow of information at the earliest stages of sensory processing within auditory cortex. In contrast to previous work, this deficit was observed despite an intact measure of sensory processing, mitigating potential confounds. Recovery of sensory gain modulation over time was associated with reductions in negative symptoms, highlighting a source of potential resiliency against some of the most debilitating and treatment refractory symptoms in early psychosis.

In contemporary neuroimaging studies, it has been observed that patients with major depressive disorder (MDD) exhibit aberrant spontaneous neural activity, commonly quantified through the amplitude of low-frequency fluctuations (ALFF). However, the substantial individual heterogeneity among patients poses a challenge to reaching a unified conclusion.

To address this variability, our study adopts a novel framework to parse individualized ALFF abnormalities. We hypothesize that individualized ALFF abnormalities can be portrayed as a unique linear combination of shared differential factors. Our study involved two large multi-center datasets, comprising 2424 patients with MDD and 2183 healthy controls. In patients, individualized ALFF abnormalities were derived through normative modeling and further deconstructed into differential factors using non-negative matrix factorization.

Two positive and two negative factors were identified. These factors were closely linked to clinical characteristics and explained group-level ALFF abnormalities in the two datasets. Moreover, these factors exhibited distinct associations with the distribution of neurotransmitter receptors/transporters, transcriptional profiles of inflammation-related genes, and connectome-informed epicenters, underscoring their neurobiological relevance. Additionally, factor compositions facilitated the identification of four distinct depressive subtypes, each characterized by unique abnormal ALFF patterns and clinical features. Importantly, these findings were successfully replicated in another dataset with different acquisition equipment, protocols, preprocessing strategies, and medication statuses, validating their robustness and generalizability.

This research identifies shared differential factors underlying individual spontaneous neural activity abnormalities in MDD and contributes novel insights into the heterogeneity of spontaneous neural activity abnormalities in MDD.

Bipolar disorder (BD) is a recurrent chronic disorder characterised by fluctuations in mood and energy disposition. Diseases could lead to degenerative alterations in brain structures such as corpus callosum (CC). Studies demonstrated that abnormalities in CC are associated with BD symptoms. The present study aims to analyse the CC of the patients with statistical shape analysis (SSA) and compare the findings with healthy controls.

Forty-one BD patients and 41 healthy individuals in similar age groups, which included 23 female and 18 male subjects, participated in the study. CC was marked with landmarks on the mid-sagittal images of each individual. The mean ‘Procrustes’ point was calculated, and shape deformations were analysed with thin-plate spline analysis.

Significant differences were observed in the shape of CC between the two groups, where maximum CC deformation was observed in posterior region marks in BD patients. There was no significant difference between the CC area of the BD patients and controls.

CC analysis conducted with SSA revealed significant differences between patients and healthy controls. The study findings emphasised the abnormal distribution of white matter in CC and the variable subregional nature of CC in BD patients. This study may enable the development of more targeted and effective treatment strategies by taking into account biological factors and understanding the differences in the brain regions of individuals with BD.