Predicting treatment outcomes in major depressive disorder using brain magnetic resonance imaging: a meta-analysis.

Recent studies have provided promising evidence that neuroimaging data can predict treatment outcomes for patients with major depressive disorder (MDD). As most of these studies had small sample sizes, a meta-analysis is warranted to identify the most robust findings and imaging modalities, and to compare predictive outcomes obtained in magnetic resonance imaging (MRI) and studies using clinical and demographic features. We conducted a literature search from database inception to July 22, 2023, to identify studies using pretreatment clinical or brain MRI features to predict treatment outcomes in patients with MDD. Two meta-analyses were conducted on clinical and MRI studies, respectively. The meta-regression was employed to explore the effects of covariates and compare the predictive performance between clinical and MRI groups, as well as across MRI modalities and intervention subgroups. Meta-analysis of 13 clinical studies yielded an area under the curve (AUC) of 0.73, while in 44 MRI studies, the AUC was 0.89. MRI studies showed a higher sensitivity than clinical studies (0.78 vs. 0.62, Z = 3.42, P = 0.001). In MRI studies, resting-state functional MRI (rsfMRI) exhibited a higher specificity than task-based fMRI (tbfMRI) (0.79 vs. 0.69, Z = -2.86, P = 0.004). No significant differences in predictive performance were found between structural and functional MRI, nor between different interventions. Of note, predictive MRI features for treatment outcomes in studies using antidepressants were predominantly located in the limbic and default mode networks, while studies of electroconvulsive therapy (ECT) were restricted mainly to the limbic network. Our findings suggest a promise for pretreatment brain MRI features to predict MDD treatment outcomes, outperforming clinical features. While tasks in tbfMRI studies differed, those studies overall had less predictive utility than rsfMRI data. Overlapping but distinct network-level measures predicted antidepressants and ECT outcomes. Future studies are needed to predict outcomes using multiple MRI features, and to clarify whether imaging features predict outcomes generally or differ depending on treatments.

Impaired visual-motor functional connectivity in first-episode medication-naïve patients with major depressive disorder.

The perceptual dysfunctions have been fundamental causes of cognitive and emotional problems in patients with major depressive disorder. However, visual system impairment in depression has been underexplored. Here, we explored functional connectivity in a large cohort of first-episode medication-naïve patients with major depressive disorder (n = 190) and compared it with age- and sex-matched healthy controls (n = 190). A recently developed individual-oriented approach was applied to parcellate the cerebral cortex into 92 regions of interest using resting-state functional magnetic resonance imaging data. Significant reductions in functional connectivities were observed between the right lateral occipitotemporal junction within the visual network and 2 regions of interest within the sensorimotor network in patients. The volume of right lateral occipitotemporal junction was also significantly reduced in major depressive disorder patients, indicating that this visual region is anatomically and functionally impaired. Behavioral correlation analysis showed that the reduced functional connectivities were significantly associated with inhibition control in visual-motor processing in patients. Taken together, our data suggest that functional connectivity between visual network and sensorimotor network already shows a significant reduction in the first episode of major depressive disorder, which may interfere with the inhibition control in visual-motor processing. The lateral occipitotemporal junction may be a hub of disconnection and may play a role in the pathophysiology of major depressive disorder.

Altered controllability of white matter networks and related brain function changes in first-episode drug-naive schizophrenia.

Understanding how structural connectivity alterations affect aberrant dynamic function using network control theory will provide new mechanistic insights into the pathophysiology of schizophrenia. The study included 140 drug-naive schizophrenia patients and 119 healthy controls (HCs). The average controllability (AC) quantifying capacity of brain regions/networks to shift the system into easy-to-reach states was calculated based on white matter connectivity and was compared between patients and HCs as well as functional network topological and dynamic properties. The correlation analysis between AC and duration of untreated psychosis (DUP) were conducted to characterize the controllability progression pattern without treatment effects. Relative to HCs, patients exhibited reduced AC in multiple nodes, mainly distributed in default mode network (DMN), visual network (VN), and subcortical regions, and increased AC in somatomotor network. These networks also had impaired functional topology and increased temporal variability in dynamic functional connectivity analysis. Longer DUP was related to greater reductions of AC in VN and DMN. The current study highlighted potential structural substrates underlying altered functional dynamics in schizophrenia, providing a novel understanding of the relationship of anatomic and functional network alterations.

Novel MRI signs of the atlantodental space in patients with atlantoaxial dislocation.

OBJECTIVES: The type of atlantodental space tissue in patients with atlantoaxial dislocation (AAD) can help doctors understand the possibility of reduction before surgery. However, relevant research on this topic is lacking. In this study, we aimed to summarise the atlantodental space classification of patients with AAD using magnetic resonance imaging (MRI) and explore their clinical characteristics. MATERIALS AND METHODS: Preoperative 3T cervical MR images of patients who underwent posterior reduction and fixation surgery for non-traumatic AAD between 1 September 2012 and 31 July 2023 were collected. Two radiologists read and recorded the MRI results based on the standard protocol. The kappa value was used to evaluate intra- and inter-observer agreements. The patient's age, sex, body mass index, clinical symptoms, Japanese Orthopaedic Association (JOA) score, and visual analogue scale information were obtained from medical records. RESULTS: A total of 135 patients with AAD (mean age, 51.3 ± 14.0 years, 52 men) were included in the analysis. The inter-observer agreement between the two readers was 0.818 (P < 0.0001). The intra-observer consistencies were 0.882 (P < 0.0001) and 0.896 (P < 0.0001). Patients with inflexible tissue signs exhibit more irreducible in hyperextension position, and their range of motion of ADI is smaller. These patients were older and had a higher incidence of abnormal spinal cord signals and JOA scores. CONCLUSIONS: Novel MRI signs exhibited high inter- and intra-observer consistency and were associated with patient age, abnormal spinal cord signals, reducibility, range of motion of ADI, and symptoms.

[Anatomic Abnormalities of Hippocampal Subfields in First-Episode Drug-Naïve Schizophrenia and Major Depressive Disorder: A Structural MRI Comparative Study].

Objective: To compare the structural changes along the longitudinal axis of hippocampus subfields between schizophrenia (SCZ) patients and major depressive disorder (MDD) patients in the early stage of their SCZ and MDD. Methods: Seventy-nine first-episode drug-naïve patients with SCZ, 48 first-episode drug-naïve patients with MDD, and 79 healthy controls (HC) were recruited and underwent assessment of clinical symptoms and magnetic resonance imaging (MRI) of the head. Following the calculation of hippocampal and subfield volumes with FreeSurfer, the volume of longitudinal subfields were summed up. Inter-group comparison of these indicators was made with the data of different groups and the correlation between clinical symptoms and the volumes of longitudinal subfields was analyzed. Results: Compared with HC, SCZ patients had smaller bilateral posterior hippocampus (left: t=－2.69, P=0.01; right: t=－2.90, P=0.004), while MDD patients exhibited no changes along the longitudinal axis of hippocampal subfields. In SCZ patients, the volume of bilateral posterior hippocampus was negatively correlated with the negative symptom scores of Positive and Negative Syndrome Scale (left: r=－0.29, P=0.01; right: r=－0.23, P=0.04). Conclusion: The smaller posterior hippocampus may be an imaging feature for distinguishing SCZ from MDD and may have contributed to the neuropathophysiological mechanism of SCZ in the early stage of the onset of the disease.

Characteristics of Intrinsic Brain Functional Connectivity Alterations in Major Depressive Disorder Patients With Suicide Behavior.

BACKGROUND: The intrinsic brain functional connectivity of suicide attempts in major depressive disorder (MDD) remains incompletely understood. PURPOSE: To investigate graph-theoretical based functional connectivity strength (FCS) alterations in MDD patients with suicidal behavior. STUDY TYPE: Prospective. SUBJECTS: Fifty medication-free MDD patients, with (suicide attempters, SA, N = 15) and without (non-attempters, nSA, N = 35) a history of a suicide attempt, and 37 healthy controls (HC). FIELD STRENGTH/SEQUENCE: Resting-state functional magnetic resonance imaging (fMRI) using a gradient-echo imaging sequence was acquired at 3.0 T. ASSESSMENT: For each individual, voxel-wise whole-brain functional network was constructed and graph-theoretical based FCS map was calculated. For each individual in two patient groups, the seed-based functional connectivity map was constructed. STATISTICAL TESTS: Non-parameter permutation tests, analysis of covariance, two-sample t-test, Chi-square test, and Pearson correlation analysis. A P value <0.05 was considered statistically significant. RESULTS: Relative to the HC group, two MDD patient groups showed significantly lower FCS in the left hippocampus, while nSA patients showed additionally lower FCS in more widespread regions (P < 0.05). Importantly, comparing to nSA patients, SA patients had significantly higher FCS in the right orbitofrontal cortex (OFC) and bilateral dorsomedial prefrontal cortex (dmPFC) (P < 0.05). Further seed-based functional connectivity analysis revealed that the right OFC exhibited significantly higher connectivity to right middle frontal gyrus and lower connectivity to the left anterior cingulate cortex and left calcarine sulcus, and the bilateral dmPFC had significantly higher connectivity to the left middle frontal gyrus and right inferior temporal gyrus in the SA patients than in the nSA patients (P < 0.05). DATA CONCLUSION: This study identified disconnections of the OFC and dmPFC which were putatively related to a higher risk of suicidal behavior in MDD patients, thus extended the understanding of suicidal behavior at a brain circuit level. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY STAGE: 3.

Decoupling of Gray and White Matter Functional Networks in Medication-Naïve Patients With Major Depressive Disorder.

BACKGROUND: Major depressive disorder (MDD) has been increasingly conceptualized as a disconnection syndrome. However, most studies have only focused on functional connectivity (FC) alterations in gray matter (GM), and the functional alterations in white matter (WM) remain largely unknown in MDD. PURPOSE: To investigate WM functional alterations and the functional interaction between GM and WM networks in medication-naïve MDD. STUDY TYPE: Prospective. SUBJECTS: Sixty-eight patients with MDD and 66 age- and sex-matched healthy controls (HCs). FIELD STRENGTH/SEQUENCE: Resting state-functional MRI (fMRI) using a gradient-echo imaging sequence and T1 -weighted images were acquired at 3.0T. ASSESSMENT: Functional GM and WM networks, based on resting-state blood oxygenation level-dependent (BOLD) signals, were identified by the K-means clustering algorithm, and FC matrices were obtained for each subject. STATISTICAL TESTS: Two-sample t-tests, Pearson chi-square test, and Pearson correlation analysis. RESULTS: Both the GM and WM of the visual network (GM1 and WM11) showed reduced FC with the sensorimotor network (WM5 and GM8), lateral temporal network (GM5 and WM6), cingulo-opercular network (GM9), and dorsal attention network (GM7) in MDD patients compared to controls (P < 0.05, false discovery rate [FDR]-corrected). Reduced FC between the anterior cingulum network (WM3) and the lateral temporal network (GM5 and WM6) and temporal pole network (GM13) and between GM13 and the medial temporal network (GM4) and medial prefrontal-subcortical network (GM10) were also observed in MDD patients (P < 0.05, FDR-corrected). In addition, the WM BOLD signal in the sensorimotor network was negatively correlated with illness duration (r = -0.286, P = 0.018). DATA CONCLUSION: Disconnectivity between the GM and WM networks in the perception-motor system may be the foundation of extensively disrupted connections in MDD. Furthermore, the observed decoupling between subsystems of the default mode network may help explain previous findings of persistent negative rumination and theory of mind deficits in depression. LEVEL OF EVIDENCE: 3. TECHNICAL EFFICACY: Stage 3.

Evaluating the Prognosis of Ischemic Stroke Using Low-Dose Multimodal Computed Tomography Parameters in Hyperacute Phase.

PURPOSE: The aim of this study was to evaluate the potential value of low-dose multimodal computed tomography (CT) in predicting prognosis of acute ischemic stroke (AIS) within 6 hours. METHODS: The admission "one-stop-shop" multimodal CT examination, including noncontrast CT (NCCT), low-dose CT perfusion, and CT angiography (CTA), was performed in patients with symptoms of stroke within 6 hours. Noncontrast CT, CTA source image (CTA-SI), cerebral blood flow (CBF), cerebral blood volume (CBV), time to peak (TTP), and mean transit time (MTT) maps were studied using Alberta Stroke Program Early CT Score (ASPECTS). The regional leptomeningeal collateral (rLMC) score (0-20) was dichotomized into 2 groups: good (11-20) and poor (0-10) rLMC. Poor functional outcomes were defined by a modified Rankin scale score of 3 to 6. RESULTS: One hundred forty-four patients were ultimately selected; 43.8% of them showed poor functional outcomes. They had lower ASPECTSs on NCCT, CTA-SI, CBV, CBF, TTP, and MTT, and poor rLMC was more frequently associated with poor functional outcomes (all P < 0.001). In the multivariate analysis for AIS patients with conservative treatment, CTA-SI-ASPECTS 6 or less (odds ratio [OR], 5.9; 95% confidence interval [95% CI], 1.9-18.4; P = 0.002) and poor collaterals (OR, 5.0; 95% CI, 1.3-15.4; P = 0.017), CBV-ASPECTS 6 or less (OR, 8.0; 95% CI, 2.7-24.0; P < 0.001), CBF-ASPECTS 4 or less (OR, 8.0; 95% CI, 2.0-31.5; P = 0.003), MTT-ASPECTS≤3 (OR, 5.8; 95% CI, 1.8-18.1; P = 0.003), TTP-ASPECTS 4 or less (OR, 5.0; 95% CI, 1.6-15.1; P = 0.005), and NCCT-ASPECTS 8 or less (OR, 5.9; 95% CI, 1.7-20.4; P = 0.005) were significantly associated with poor functional outcome. In the multivariate analysis for AIS patients with thrombolysis, CTA-SI-ASPECTS 6 or less (OR, 27.5; 95% CI, 2.9-262.3; P = 0.004), poor collaterals (OR, 28.0; 95% CI, 2.8-283.0; P < 0.028), and CBV-ASPECTS 6 or less (OR, 18.0; 95% CI, 3.0-107.7; P = 0.002) were associated with poor functional outcomes. Furthermore, the area under the curve (AUC) of the combination of CTA-SI-ASPECTS 6 or less, poor collaterals, and CBV-ASPECTS 6 or less (AUC, 0.87) was greater than that for any single parameter alone: CTA-SI-ASPECTS 6 or less (AUC, 0.80; P < 0.001), poor collaterals (AUC, 0.76; P < 0.001), and CBV-ASPECTS 6 or less (AUC, 0.81; P = 0.002). CONCLUSIONS: The combination of CTA-SI-ASPECTS, collaterals, and CBV-ASPECTS may improve predictive power compared with a single parameter alone.

Microstructural brain abnormalities in medication-free patients with major depressive disorder: a systematic review and meta-analysis of diffusion tensor imaging.

BACKGROUND: Multiple meta-analyses of diffusion tensor imaging (DTI) studies have reported impaired white matter integrity in patients with major depressive disorder (MDD). However, owing to inclusion of medicated patients in these studies, it is difficult to conclude whether these reported alterations are associated with MDD or confounded by medication effects. A meta-analysis of DTI studies on medication-free (medication-naive and medication washout) patients with MDD would therefore be necessary to disentangle MDD-specific effects. METHODS: We analyzed white matter alterations between medication-free patients with MDD and healthy controls using anisotropic effect size-signed differential mapping (AES-SDM). We used DTI query software for fibre tracking. RESULTS: Both pooled and subgroup meta-analyses in medication washout patients showed robust fractional anisotropy (FA) reductions in white matter of the right cerebellum hemispheric lobule, body of the corpus callosum (CC) and bilateral superior longitudinal fasciculus III (SLF III), whereas FA reductions in the genu of the CC and right anterior thalamic projections were seen in only medication-naive patients. Fibre tracking showed that the main tracts with observed FA reductions included the right cerebellar tracts, body of the CC, bilateral SLF III and arcuate fascicle. LIMITATIONS: The analytic techniques, patient characteristics and clinical variables of the included studies were heterogeneous; we could not exclude the effects of nondrug therapies owing to a lack of data. CONCLUSION: By excluding the confounding influences of current medication status, findings from the present study may provide a better understanding of the underlying neuropathology of MDD.

Brain gray matter alterations and associated demographic profiles in adults with autism spectrum disorder: A meta-analysis of voxel-based morphometry studies.

BACKGROUND: There is increasing evidence that children with autism spectrum disorder are accompanied by specific anatomical alterations. However, the anatomical abnormalities in adults with autism spectrum disorder are poorly understood. This study was aimed to identify the neuroanatomical substrates underlying the pathophysiology of adults with autism spectrum disorder. We also investigated the relationship between neuroanatomical alterations and clinical and demographic characteristics. METHODS: A total of 13 datasets were enrolled, of which 12 studies compared whole-brain differences of 382 adult patients with autism and 393 healthy control subjects. We conducted a meta-analysis to quantitatively estimate regional gray matter volume abnormalities in individuals with autism using the effect-size signed differential mapping. RESULTS: The voxel-wise meta-analysis revealed that relative to controls, adults with autism spectrum disorder had significantly increased gray matter volume in the middle temporal gyrus, superior temporal gyrus, postcentral gyrus and parahippocampal gyrus, and reduced gray matter volume in the anterior cingulate cortex and cerebellum. Variations in gray matter volume were significantly associated with the mean age and mean total IQ score of the patients, as well as with the percentage of male patients with autism. CONCLUSION: These findings confirmed that the neuroanatomical alterations in the fronto-temporal cortices, limbic system and cerebellum in adult individuals with autism were different from the children and young adolescent's autism. The effects of demographic characteristics on the brain morphological changes allow us to further clarify the neurobiological mechanisms and developmental trajectory in adult population with autism spectrum disorder.

Voxel-wise meta-analyses of brain blood flow and local synchrony abnormalities in medication-free patients with major depressive disorder.

BACKGROUND: Published meta-analyses of resting-state regional cerebral blood flow (rCBF) studies of major depressive disorder (MDD) have included patients receiving antidepressants, which might affect brain activity and thus bias the results. To our knowledge, no meta-analysis has investigated regional homogeneity changes in medication-free patients with MDD. Moreover, an association between regional homogeneity and rCBF has been demonstrated in some brain regions in healthy controls. We sought to explore to what extent resting-state rCBF and regional homogeneity changes co-occur in the depressed brain without the potential confound of medication. METHODS: Using the effect-size signed differential mapping method, we conducted 2 meta-analyses of rCBF and regional homogeneity studies of medication-free patients with MDD. RESULTS: Our systematic search identified 14 rCBF studies and 9 regional homogeneity studies. We identified conjoint decreases in resting-state rCBF and regional homogeneity in the insula and superior temporal gyrus in medication-free patients with MDD compared with controls. Other changes included altered resting-state rCBF in the precuneus and in the frontal-limbic-thalamic-striatal neural circuit as well as altered regional homogeneity in the uncus and parahippocampal gyrus. Meta-regression revealed that the percentage of female patients with MDD was negatively associated with resting-state rCBF in the right anterior cingulate cortex and that the age of patients with MDD was negatively associated with rCBF in the left insula and with regional homogeneity in the left uncus. LIMITATIONS: The analysis techniques, patient characteristics and clinical variables of the included studies were heterogeneous. CONCLUSION: The conjoint alterations of rCBF and regional homogeneity in the insula and superior temporal gyrus may be core neuropathological changes in medication-free patients with MDD and serve as a specific region of interest for further studies on MDD.

Transdiagnostic white matter controllability deficits across patients with affective and anxiety spectrum disorders.

BACKGROUND: Affective and anxiety disorders including major depression disorder (MDD), post-traumatic stress disorder (PTSD), and social anxiety disorder (SAD) are characterized by network dysconnectivity. Network controllability quantifies the capability of specific brain regions to impact functional dynamics based on the underlying structural connectome. This study aimed to investigate transdiagnostic and illness-specific network controllability alterations across these three disorders. MATERIALS AND METHODS: The study enrolled 233 currently untreated and non-comorbid subjects, including 68 MDD patients, 51 PTSD patients, 46 SAD patients, and 68 healthy controls (HCs). White matter network controllability was compared among the four groups, and its associations with symptom severity and duration of untreated illness were evaluated. RESULTS: Compared with HCs, patients with PTSD, MDD and SAD exhibited reduced average controllability in the somatomotor, subcortical, and default mode network, notably in brain regions such as the superior frontal gyrus, postcentral gyrus, paracentral gyrus, pallidum, posterior cingulate, and putamen. MDD and SAD patients exhibited reduced average controllability in the left lateral occipital gyrus and bilateral accumbens. SAD patients showed reduced average controllability in the dorsal attention network. These controllability changes did not correlate with illness duration or symptom severity. LIMITATIONS: The cross-sectional design limits causal inference, and adjusting for age and sex differences may not completely eliminate their influence on the results. CONCLUSION: The present study revealed shared and specific alterations of network controllability in MDD, PTSD, and SAD, suggesting reduced ability of specific brain regions/networks in driving the brain system into different functional states across these disorders.

Individualized multi-modal MRI biomarkers predict 1-year clinical outcome in first-episode drug-naïve schizophrenia patients.

Background: Antipsychotic medications offer limited long-term benefit to about 30% of patients with schizophrenia. We aimed to explore the individual-specific imaging markers to predict 1-year treatment response of schizophrenia. Methods: Structural morphology and functional topological features related to treatment response were identified using an individualized parcellation analysis in conjunction with machine learning (ML). We performed dimensionality reductions using the Pearson correlation coefficient and three feature selection analyses and classifications using 10 ML classifiers. The results were assessed through a 5-fold cross-validation (training and validation cohorts, n = 51) and validated using the external test cohort (n = 17). Results: ML algorithms based on individual-specific brain network proved more effective than those based on group-level brain network in predicting outcomes. The most predictive features based on individual-specific parcellation involved the GMV of the default network and the degree of the control, limbic, and default networks. The AUCs for the training, validation, and test cohorts were 0.947, 0.939, and 0.883, respectively. Additionally, the prediction performance of the models constructed by the different feature selection methods and classifiers showed no significant differences. Conclusion: Our study highlighted the potential of individual-specific network parcellation in treatment resistant schizophrenia prediction and underscored the crucial role of feature attributes in predictive model accuracy.

Linked patterns of symptoms and cognitive covariation with functional brain controllability in major depressive disorder.

BACKGROUND: Controllability analysis is an approach developed for evaluating the ability of a brain region to modulate function in other regions, which has been found to be altered in major depressive disorder (MDD). Both depressive symptoms and cognitive impairments are prominent features of MDD, but the case-control differences of controllability between MDD and controls can not fully interpret the contribution of both clinical symptoms and cognition to brain controllability and linked patterns among them in MDD. METHODS: Sparse canonical correlation analysis was used to investigate the associations between resting-state functional brain controllability at the network level and clinical symptoms and cognition in 99 first-episode medication-naïve patients with MDD. FINDINGS: Average controllability was significantly correlated with clinical features. The average controllability of the dorsal attention network (DAN) and visual network had the highest correlations with clinical variables. Among clinical variables, depressed mood, suicidal ideation and behaviour, impaired work and activities, and gastrointestinal symptoms were significantly negatively associated with average controllability, and reduced cognitive flexibility was associated with reduced average controllability. INTERPRETATION: These findings highlight the importance of brain regions in modulating activity across brain networks in MDD, given their associations with symptoms and cognitive impairments observed in our study. Disrupted control of brain reconfiguration of DAN and visual network during their state transitions may represent a core brain mechanism for the behavioural impairments observed in MDD. FUNDING: National Natural Science Foundation of China (82001795 and 82027808), National Key R&D Program (2022YFC2009900), and Sichuan Science and Technology Program (2024NSFSC0653).

A voxel-based meta-analysis comparing medication-naive patients of major depression with treated longer-term ill cases.

Structural neuroimaging studies have identified brain areas implicated in the pathogenesis of major depressive disorder (MDD). However, findings have been inconsistent, potentially due to variable illness duration and effects of antidepressant treatment. Using a meta-analytic approach, we compared gray matter (GM) volumes in patients grouped by medication status (naïve and treated) and illness duration (early course and long-term ill) to identify potential treatment and illness duration effects on brain structure. A total of 70 studies were included, including 3682 patients and 3469 controls. The pooled analysis found frontal, temporal and limbic regions with decreased GM volume in MDD patients. Additional analyses indicated that larger GM volume in the right striatum and smaller GM volume in the right precuneus are likely to be associated with drug effects, while smaller GM volume in the right temporal gyrus may correlate with longer illness duration. Similar GM decreases in bilateral medial frontal cortex between patient subgroups suggest that this alteration may persist over the course of illness and drug treatment.

Memory and processing speed impairments in first-episode drug-naïve patients with major depressive disorder.

BACKGROUND: Cognitive impairment, an intrinsic feature of major depressive disorder (MDD), affects daily and social functioning in depression patients. However, the cognitive impairment profile in MDD remains ambiguous because of the high heterogeneity of previous studies. METHODS: Four cognitive domains, including memory, processing speed, executive function (EF), and attention, were assessed in 184 first-episode drug-naïve (FEDN) MDD patients and matched 71 healthy controls (HCs). The effects of demographic and depressive factors on cognitive performance were analyzed using various statistical methods, including multi-factor analysis of variance, Mann-Whitney U test, and Spearman's rank correlation. In addition, the impact of depression severity on cognitive function was further assessed using subgroup analyses and partial correlation analyses. RESULTS: Age and education significantly impacted most cognitive performances, and depression severity appeared to influence processing speed. Moreover, cognitive scores in memory and processing speed, rather than in EF and attention, were significantly different between FEDN MDD patients and HCs after controlling for sex, age, educational attainment, household income, and body mass index. LIMITATIONS: The number of HCs was relatively small, which may have slightly reduced the study's statistical power. CONCLUSIONS: Age and educational attainment have confirmative confounding effects greater than those of depression in most cognitive functions. More importantly, memory and processing speed were impaired in MDD after strictly controlling for confounders. These findings provide new information for understanding the pattern of cognitive impairment and offer clues for further exploring the pathogenesis of cognitive abnormalities in MDD.

Individualized Functional Connectome Identified Replicable Biomarkers for Dysphoric Symptoms in First-Episode Medication-Naïve Patients With Major Depressive Disorder.

BACKGROUND: Major depressive disorder (MDD) is a heterogeneous syndrome and can be conceptualized as a mixture of dimensional abnormalities across several specific brain circuits. The neural underpinnings of different symptom dimensions in MDD are not well understood. We aimed to identify robust, generalizable, functional connectivity (FC)-based biomarkers for different symptom dimensions in MDD using individualized functional connectomes. METHODS: Patterns of FC associated with symptom severity were identified using a novel, individualized, functional network parcellation analysis in conjunction with hierarchical clustering. Dimension-specific prediction models were trained to estimate symptom severity in first-episode medication-naïve patients (discovery dataset, n = 95) and replicated in an independent validation dataset (n = 94). The correlation between FC changes and symptom changes was further explored in a treatment dataset (n = 55). RESULTS: Two distinct symptom clusters previously identified in patients with MDD, namely dysphoric and anxiosomatic clusters, were robustly replicated in our data. A connectivity biomarker associated with dysphoric symptoms was identified, which mainly involved the default, dorsal attention, and limbic networks. Critically, this brain-symptom association was confirmed in the validation dataset. Moreover, the marker also tracked dysphoric symptom improvement following a 2-week antidepressant treatment. For comparison, we repeated our analyses using a nonindividualized approach and failed to identify replicable brain-symptom biomarkers. Further quantitative analysis indicated that the generalizability of the connectivity-symptom association was hampered when functional regions were not localized in individuals. CONCLUSIONS: This work reveals robust, replicable FC biomarkers for dysphoric symptoms in MDD, demonstrates the advantage of individual-oriented approach, and emphasizes the importance of independent validation in psychiatric neuroimaging analysis.

Controllability of Functional Brain Networks and Its Clinical Significance in First-Episode Schizophrenia.

BACKGROUND AND HYPOTHESIS: Disrupted control of brain state transitions may contribute to the diverse dysfunctions of cognition, emotion, and behavior that are fundamental to schizophrenia. Control theory provides the rationale for evaluating brain state transitions from a controllability perspective, which may help reveal the brain mechanism for clinical features such as cognitive control deficits associated with schizophrenia. We hypothesized that brain controllability would be altered in patients with schizophrenia, and that controllability of brain networks would be related to clinical symptomatology. STUDY DESIGN: Controllability measurements of functional brain networks, including average controllability and modal controllability, were calculated and compared between 125 first-episode never-treated patients with schizophrenia and 133 healthy controls (HCs). Associations between controllability metrics and clinical symptoms were evaluated using sparse canonical correlation analysis. STUDY RESULTS: Compared to HCs, patients showed significantly increased average controllability (PFDR = .023) and decreased modal controllability (PFDR = .023) in dorsal anterior cingulate cortex (dACC). General psychopathology symptoms and positive symptoms were positively correlated with average controllability in regions of default mode network and negatively associated with average controllability in regions of sensorimotor, dorsal attention, and frontoparietal networks. CONCLUSIONS: Our findings suggest that altered controllability of functional activity in dACC may play a critical role in the pathophysiology of schizophrenia, consistent with the importance of this region in cognitive and brain state control operations. The demonstration of associations of functional controllability with psychosis symptoms suggests that the identified alterations in average controllability of brain function may contribute to the severity of acute psychotic illness in schizophrenia.

Shared and Disorder-Specific Alterations of Brain Temporal Dynamics in Obsessive-Compulsive Disorder and Schizophrenia.

BACKGROUND: Obsessive-compulsive disorder (OCD) and schizophrenia have distinct but also overlapping symptoms. Few studies have examined the shared and disorder-specific disturbances in dynamic brain function in the 2 disorders. STUDY DESIGN: Resting-state functional magnetic resonance imaging data of 31 patients with OCD and 49 patients with schizophrenia, all untreated, and 45 healthy controls (HCs) were analyzed using spatial group independent component (IC) analysis. Time-varying degree centrality patterns across the whole brain were clustered into 3 reoccurring states, and state transition metrics were obtained. We further explored regional temporal variability of degree centrality for each IC across all time windows. STUDY RESULTS: Patients with OCD and patients with schizophrenia both showed decreased occurrence of a state having the highest centrality in the sensorimotor and auditory networks. Additionally, patients with OCD and patients with schizophrenia both exhibited reduced dynamics of degree centrality in the superior frontal gyrus than controls, while dynamic degree centrality of the cerebellum was lower in patients with schizophrenia than with OCD and HCs. Altered dynamics of degree centrality nominally correlated with symptom severity in both patient groups. CONCLUSIONS: Our study provides evidence of transdiagnostic and clinically relevant functional brain abnormalities across OCD and schizophrenia in neocortex, as well as functional dynamic alterations in the cerebellum specific to schizophrenia. These findings add to the recognition of overlap in neocortical alterations in the 2 disorders, and indicate that cerebellar alterations in schizophrenia may be specifically important in schizophrenia pathophysiology via impact on cerebellar thalamocortical circuitry.

The acute effects of repetitive transcranial magnetic stimulation on laminar diffusion anisotropy of neocortical gray matter.

Repetitive transcranial magnetic stimulation (rTMS) is increasingly used to treat neuropsychiatric disorders. Inhibitory and excitatory regimens have been both adopted but the exact mechanism of action remains unclear, and investigating their differential effects on laminar diffusion profiles of neocortex may add important evidence. Twenty healthy participants were randomly assigned to receive a low-frequency/inhibitory or high-frequency/excitatory rTMS targeting the left dorsolateral prefrontal cortex (DLPFC). With the brand-new submillimeter diffusion tensor imaging of whole brain and specialized surface-based laminar analysis, fractional anisotropy (FA) and mean diffusion (MD) profiles of cortical layers at different cortical depths were characterized before/after rTMS. Inhibitory and excitatory rTMS both showed impacts on diffusion metrics of somatosensory, limbic, and sensory regions, but different patterns of changes were observed-increased FA with inhibitory rTMS, whereas decreased FA with excitatory rTMS. More importantly, laminar analysis indicated laminar specificity of changes in somatosensory regions during different rTMS patterns-inhibitory rTMS affected the superficial layers contralateral to the DLPFC, while excitatory rTMS led to changes in the intermediate/deep layers bilateral to the DLPFC. These findings provide novel insights into acute neurobiological effects on diffusion profiles of rTMS that may add critical evidence relevant to different protocols of rTMS on neocortex.