Schizophrenia (SCZ) and bipolar disorder (BD) are severe psychiatric conditions with overlapping clinical presentations, genetic risk factors, and brain network dysfunction. Whether alterations in large-scale intrinsic brain networks reflect shared or disorder-specific genetic influences remains poorly understood. Clarifying this distinction is essential for refining etiological models and improving diagnostic precision.

Genome-wide inferred statistics (GWIS) were applied to decompose the genetic architecture of SCZ and BD into shared and unique components. Using resting-state network (RSN) data from the UK Biobank, functional connectivity (FC) and structural connectivity (SC) were extracted as neuroimaging phenotypes. Causal inference approaches were subsequently employed to infer potential directional relationships between brain network connectivity and each disorder.

Analyses revealed both common and distinct patterns of brain network connectivity associated with SCZ and BD. Notably, SC within the default mode network (DMN) exhibited opposing effects across the two disorders, suggesting divergent structural underpinnings despite clinical overlap. Additionally, SC within the limbic network (LN) and frontotemporal control network demonstrated potential causal relationships with both conditions, implicating these circuits astransdiagnostic neural substrates.

These findings illuminate the shared and disorder-specific genetic and neural architecture underlying SCZ and BD. Integrating genome-wide genetic methods with large-scale neuroimaging data offers a powerful framework for disentangling psychiatric comorbidity and may inform more targeted diagnostic criteria and individualized treatment strategies.

Functional connectivity (FC) is consistently altered in patients with schizophrenia. The brain’s primary inhibitory neurotransmitter, gamma-aminobutyric acid (GABA), and its relationship to FC in psychosis spectrum disorders are under-investigated. The anterior cingulate cortex (ACC) has been implicated in many cognitive functions impaired in psychosis. We hypothesize that the relationships between ACC GABA and FC in key brain networks will be altered in first-episode psychosis (FEP) patients as compared to healthy controls (HC).

We used magnetic resonance spectroscopy (MRS) with a MEGA-PRESS sequence to quantify ACC GABA levels in 67 antipsychotic medication-naïve FEP patients and 110 HC. Resting state functional magnetic resonance imaging (fMRI) was used to assess positive and negative FC within the default mode (DMN), salience (SN), dorsal attention (DAN), and executive control (ECN) networks. We used linear regressions to test GABA–FC relationships in each network between groups.

FEP patients had significantly lower GABA levels compared to HC. We also found several clusters in the ECN, DAN, and DMN where FC differed between groups. Ultimately, we found significant GABA–FC group interactions in two ECN clusters and one SN cluster, where GABA and FC were positively correlated in HC but negatively correlated in FEP.

Our data add to the growing literature supporting GABA’s significant role in psychosis spectrum disorders, especially as it relates to FC in key brain networks. Our findings call for further investigation of the mechanisms underlying altered neurometabolic activity and connectivity in psychosis spectrum disorders.

The development of cognitive impairment (CI) is a frequent and debilitating consequence of COVID-19 and can persist for more than 1 year after the acute infection stage. Previous neuroimaging studies in COVID-19 survivors with CI have revealed widespread alterations in functional connectivity (FC), particularly within fronto-parietal circuits and subcortical nuclei such as the hippocampus, basal ganglia, and thalamus. This study focuses on neural correlates of CI in subjects who recovered from COVID-19 and the relationship between FC patterns and discrete cognitive domains.

Resting-state functional MRI data from 136 subjects were analyzed using a ROI-to-ROI approach across 246 brain regions derived from the Human Brainnetome Atlas. Group comparisons were performed based on the presence or absence of CI, and correlation analyses were conducted between FC and scores obtained from a comprehensive neuropsychological test battery.

Whole-brain FC showed no difference between patients with and without CI. In the whole study sample, hypoconnectivity between two basal ganglia regions and two frontal motor regions was associated with impaired performance in the cognitive domain “Reasoning and Problem-Solving,” while hyperconnectivity between the prefrontal thalamus and the postcentral gyrus was associated with impaired performance in the same cognitive domain.

Our findings indicate that FC alterations within the cortico-striatal and thalamo-cortical circuits may subtend deficits in higher-order executive functions in post-COVID-19 patients and highlight the importance of examining discrete cognitive domains in relation to brain connectivity.

Glymphatic functioning is implicated in cognitive and affective functioning. Given that rumination, a major risk factor for major depressive disorder (MDD), is a cognitive process regulating information processing, knowledge of the neurobiological mechanisms underpinning the relationship among glymphatic functioning, rumination, and depression would offer significant insight into the precipitating and maintenance mechanisms of MDD.

This study recruited 53 MDD patients and 47 matched healthy controls (HCs). Diffusion Tensor Image Analysis along the Perivascular Space (DTI-ALPS) index was computed as a proxy of the glymphatic functioning. Rumination and depressive severity were evaluated using Ruminative Response Scale (RRS) and Hamilton Depression Rating Scale (HAMD), respectively. Static and dynamic functional connectivity (FC/dFC) analyses were performed, and associations with neurotransmitter maps were explored.

MDD patients showed reduced glymphatic function compared to HCs, with lower glymphatic function correlating with more severe depression and rumination. Rumination mediated the glymphatic–depression relationship. Furthermore, overlapping static FC involving default mode and subcortical networks linked the glymphatic functioning and rumination. Edge-centric dynamic FC analysis showed reduced State 3 occurrence and heightened rumination, further mediating the glymphatic–rumination relationship in HCs. Both FC biomarkers spatially correlated with various neurotransmitter maps (e.g. dopamine).

Glymphatic dysfunction may exacerbate depression by disrupting brain networks and neurotransmitter balance, trapping individuals in maladaptive rumination. Enhancing glymphatic flow (e.g. via physical exercise) could restore neurobiological health, breaking the maladaptive cycles. This highlights glymphatic functioning as a potential therapeutic target bridging neurobiology, cognition, and depression severity.

Prior neuroimaging studies and meta-analyses investigating brain correlates of placebo analgesia (PA) have yielded neuroanatomically heterogeneous findings, which may be reconciled from a connectomics perspective. The objective of this study was to examine network localization of brain functional alterations related to PA.

We initially identified PA-induced brain activation alterations (hyper-activation and hypo-activation separately) during experimental pain from 29 published studies with 674 individuals. By combining these implicated dysfunctional brain regions with large-scale discovery (N = 1113) and validation (N = 1093) resting-state functional magnetic resonance imaging datasets, we then employed a novel functional connectivity network mapping approach to construct PA hyper-activation and hypo-activation networks, respectively.

The PA hyper-activation network manifested as a pattern of circumscribed brain regions mainly involving the limbic, default, and frontoparietal networks. By contrast, the PA hypo-activation network comprised a broadly distributed set of brain regions primarily implicating the ventral attention, somatomotor, and subcortical networks.

Our findings regarding the brain network representations of PA may contribute to a deeper understanding of its action mechanisms and provide a neural framework that may inform future clinical translation.

Subcortical nuclei – including the thalamus, basal ganglia, and hippocampus-amygdala complex – are key regions in schizophrenia (SZ), bipolar disorder (BD), and major depressive disorder (MDD). While cortical–subcortical connectivity is well studied, fine intra- and inter-subcortical patterns are less known. This study aimed to identify shared and distinct functional connectivity alterations across SZ, BD, and MDD using a high-resolution subcortical atlas.

Resting-state functional magnetic resonance imaging data from 800 participants (200 per group: SZ, BD, MDD, and healthy controls) in a single-site cohort were analyzed. Subcortical structures were parcellated into 27 regions per hemisphere – thalamus (8 regions), hippocampus (5 regions), amygdala (2 regions), and striatum (12 regions) – based on the a priori atlas. Pairwise functional connectivity among the 54 regions was computed for each participant, and group differences were assessed using general linear models.

Patients with SZ exhibited significantly reduced intra-thalamic connectivity and increased intra-striatal connectivity, as well as enhanced connectivity between the thalamus, striatum, and limbic regions. Patients with BD showed reduced intra-thalamic and intra-striatal connectivity, along with decreased thalamus–amygdala and thalamus–striatum connectivity. In MDD, the predominant finding was reduced intra-limbic connectivity, accompanied by mild reductions in intra-thalamic and striatum–limbic connectivity.

The results suggest that intra-thalamic hypoconnectivity appears common to SZ, BD, and MDD, with graded degrees of severity. In contrast, distinct alterations in intra-striatal and striatum–limbic connectivity may differentiate mood disorders from SZ. These shared and disorder-specific subcortical connectivity patterns enhance the understanding of psychiatric neurobiology and may guide the development of targeted, disorder-tailored interventions.

Subthreshold depression (StD) is considered a prodromal stage of major depressive disorder (MDD). This study aims to investigate the neurobiological mechanisms of StD by analyzing functional connectivity (FC) and cognitive function in comparison to MDD.

A total of 153 StD individuals, 188 MDD patients, and 110 healthy controls (HCs) were studied using resting-state functional magnetic resonance imaging (fMRI). Whole-brain FC was calculated using seeds from the default mode network (DMN), salience network (SN), executive control network, and affective network (AN). Cognitive function was assessed across seven domains.

StD showed only a deficit in social cognition, while MDD exhibited multidomain cognitive impairments compared to HCs. Both MDD and StD exhibited reduced FC between the right anterior insula (AI) and the left inferior frontal gyrus (IFG), and increased FC between the right subcallosal cingulate cortex and the left posterior cingulate cortex (PCC), key areas of the SN and AN, compared to HCs. MDD particularly showed decreased connectivity between the left PCC and the left middle temporal gyrus, and within the left PCC, while no abnormal FC of the DMN was found in StD. Altered AI-IFG FC was positively correlated with social cognition in StD.

Abnormal connectivity patterns of the SN and AN may contribute to the development of depressive symptoms in StD and MDD, while altered FC of the DMN may be involved in the onset of the disease. A social cognition deficit appeared first in StD, relating to the abnormal connectivity of the SN.

Alexithymia is a multifaceted, transdiagnostic trait characterized by challenges in emotion processing. Affecting up to 10% in the general population, it represents a risk factor for various mental and physical health conditions. Recent neuroimaging studies have elucidated the neural substrates of alexithymia, providing initial insight into altered functional connectivity within key emotional, attentional, and interoceptive networks, potentially impairing emotion processing and everyday functioning. However, no large-scale study has yet confirmed these network alterations.

Resting-state functional magnetic resonance imaging from 575 individuals (ages 29–60, 334 women) in the population-based SHIP-TREND cohort, using regions of interest covering major functional networks across the whole brain, was paired with the 20-item Toronto Alexithymia Scale (TAS-20) to investigate the signature of alexithymia. The analysis accounted for technical variables, sociodemographic factors, lifestyle, and current depressive symptoms.

Higher TAS-20 scores were associated with altered functional connectivity within the frontoparietal network and between the dorsal attention and salience networks. Specifically, the subscale “difficulties identifying feelings” was associated with functional alterations between and within attentional, salience, and sensorimotor networks, indicating a divergent pattern within the salience network.

These findings underscore the widespread impact of alexithymia on brain networks involved in emotional attention, interoception, and somatosensory processing. Controlling for lifestyle factors, current depressive symptoms, and other health indicators supports the specificity of these patterns. This supports the view of alexithymia as a personality trait that affects large-scale network functioning, potentially hampering emotional regulation and self-awareness processes, contributing to mental and physical health risks.

Considerable effort has been devoted to investigate the neuroimaging correlates and predictors of antidepressant response to ketamine, yet inconsistency in the location and nature of the regional brain effects makes it difficult to unify this research. Despite the revolutionary notion that psychiatric therapeutics show network-level brain representations, investigations into network localization of brain functional effects of ketamine treatment are still lacking.

We initially identified the locations of longitudinal brain functional alterations (increase and decrease separately) induced by ketamine treatment from 16 published studies with 508 depressed patients. By integrating these affected brain locations with large-scale functional MRI datasets from 1113 healthy and 255 depressed individuals, we then leveraged a novel functional connectivity network mapping approach to construct ketamine-induced hyper-functional and hypo-functional networks respectively.

The hyper-functional network mainly involved the subcortical (caudate nucleus and thalamus) and default (medial prefrontal cortex) networks, while its hypo-functional counterpart predominantly implicated the limbic (temporal pole), subcortical (hippocampus and amygdala), and default (lateral temporal cortex) networks.

Our findings may shed light on the neurobiological effects of ketamine from a network perspective, which might represent a crucial step toward fostering the clinical application of ketamine in antidepressant treatment.

This study investigated functional connectivity in the default mode, central executive, dorsal attention, and salience networks (SN) and its relation to executive function in youth with traumatic brain injury.

Twenty-three youth with traumatic brain injury (11 with moderate-to-severe injury (6 male, mage = 11.78 ± 2.68 years, mtimesinceinjury = 3.71 ± 2.43 years) and 12 with complicated-mild injury (9 male, mage = 12.59 ± 1.99 years, mtimesinceinjury = 4.55 ± 1.59 years) and 17 youth with orthopedic injury (11 male, mage = 11.75 ± 2.12 years, mtimesinceinjury = 3.95 ± 1.79 years)) completed resting-state functional magnetic resonance imaging and a parent rated their child’s executive function.

We found group differences in the strength of connectivity among four regions in the default mode network (DMN) and two regions of the SN, ps < .05, Eta2 = .151–.229. The orthopedic injury group demonstrated significant negative between-network connectivity, while brain injury groups had negligible negative or, in some cases, positive between-network associations. Groups did not differ on parent ratings of executive function, as all groups fell above the normative mean, reflecting poorer than expected everyday executive behavior. Attenuation of typical negative between-network association between the posterior cingulate in the DMN and two regions of the salience network was associated with worse parent-rated executive behavior (rs = .291–.317, ps < .05).

Findings illustrate the implications of disrupted downregulation of the default mode network by the SN following pediatric brain injury. They also demonstrate how disruption in functional connectivity may underlie poor executive function after childhood traumatic brain injury.

Adult major depression (MDD) studies implicate reward- and control-network dysconnectivity in suicidality, but it is unclear whether analogous alterations characterize adolescents, whose neural systems are still maturing.

Resting-state fMRI was obtained from 102 adolescents (12–17 years): 21 MDD with suicidal ideation (SI), 33 MDD without SI, and 48 matched healthy controls. Seed-based analyses targeted bilateral nucleus accumbens (NAc), ventral tegmental area (VTA), and bilateral dorsolateral prefrontal cortex (DLPFC).

Between-group effects were specific to NAc circuitry. Adolescents with SI showed reduced coupling of the left NAc with the left superior parietal lobule (BA7) versus controls, and diminished connectivity between the right NAc and right frontal pole (BA47) versus depressed peers without SI. No significant differences emerged for DLPFC- or VTA-seeded connectivity.

The identified functional dysconnectivities in reward-related circuits, particularly the FCs between the NAc and both the frontal pole and superior parietal lobule, may be implicated in the manifestation of suicidality among adolescents with MD. However, the lack of significant associations for DLPFC- and VTA-seeded FC in adolescent MDSI requires further elucidation.

Growing studies have reported an elevated risk of violence in patients with depression, yet the neurobiological underpinnings remain poorly understood. The present study explored the resting-state electroencephalogram (EEG) features in major depressive disorder (MDD) patients with violent offenses to identify potential neurological markers for violence prediction and intervention.

Twenty-nine MDD patients who committed violent offenses (violent depression [VD] group), 27 MDD patients without violent behaviors (nonviolent depression [NVD] group), and 25 healthy controls (HCs) were included. Resting-state EEGs were recorded for at least 5 min. EEG microstates, functional connectivity (FC), and graph theory metrics were analyzed and compared between groups.

First, the VD group had increased microstate A, more microstates A-B transition, but lower microstates B-D and C-D transition. Second, the VD group exhibited two enhanced functional brain networks compared to NVD and HCs, and three weakened functional brain networks compared to HCs, which were primarily distributed in the frontal and frontoparietal networks. Third, the VD group specifically exhibited reduced nodal efficiency (aNe) in the superior parietal lobe and increased aNe in the middle occipital gyrus.

MDD patients with violent offenses exhibited alterations in EEG microstates, FCs in the frontal lobe and frontoparietal network, and disrupted aNe in specific parietal and occipital lobes. These alternations are closely associated with deficits in emotional regulation, executive function, and inhibitory control, which may subserve as potential neurobiomarkers for violence risk assessment in patients with depression.

Parkinson’s disease (PD) is a neurodegenerative disorder whose diagnostic motor symptoms appear only after significant progression of neurodegeneration. Identification of preclinical markers is essential. Idiopathic rapid eye movement sleep behavior disorder (iRBD) has a high risk of conversion to PD. Olfactory impairment (hyposmia) is present in both PD and iRBD; hyposmia in iRBD may be an additional clue indicating the development of PD. The processes underlying hyposmia in iRBD are unknown. Using resting-state functional connectivity (rsFC), a “sensory olfactory subnetwork” (SOS) has been identified that is thought to represent the processing of basic sensory olfactory information. We investigated whether changes in the SOS are seen in both PD and iRBD and whether changes are associated with hyposmia in both conditions.

The University of Pennsylvania Smell Identification Test (UPSIT) and a seed-based approach to analyze SOS region rsFC in early PD, iRBD and healthy controls (HC) were employed. Our SOS regions included (right hemisphere) anterior piriform cortex, dorsal insula (INSd), ventral insula (INSv), posterior insula (INSp) and ventral posterior thalamus (THLvp).

Compared to HC, idiopathic iRBD and PD participants performed significantly worse on UPSIT and exhibited lower FC between INSd and INSv and higher FC between INSd and THLvp and INSv and THLvp. UPSIT scores were negatively correlated with FC between INSv and THLvp and INSp and THLvp.

Idiopathic iRBD may be associated with similar functional and perceptual olfactory alterations and potential compensatory changes as early PD, which may show promise as additional preclinical biomarkers of PD.

Major depressive disorder (MDD) is closely associated with suicide, which often begins with suicidal ideation (SI). However, the underlying neural mechanisms remain unclear.

We included 73 MDD patients with SI (MDD-SI), 44 MDD patients without SI (MDD-NSI) and 78 healthy controls (HCs), then compared the amplitude of low-frequency fluctuations (ALFF), functional connectivity (FC), and effective connectivity (EC) differences across groups and analyzed their relationship with SI severity. FC and EC analyses used brain regions with ALFF differences between MDD-SI and MDD-NSI as seed points. ALFF findings were validated using the REST-meta-MDD consortium dataset (N = 1 596, 24 sites). Additionally, we explored the trend of changes in abnormal activity and connectivity of SI and suicidal behavior (SB) in MDD-SI.

Compared to MDD-NSI, MDD-SI showed increased ALFF in the right anterior cingulate cortex (ACC), validated by the REST-meta-MDD consortium dataset. MDD-SI also exhibited reduced FC between the right ACC and the left inferior frontal gyrus and decreased EC from the right ACC to the right fusiform gyrus, which were negatively correlated with the Hamilton Depression Rating Scale (HAMD)-suicidality item scores. Increased EC was observed in MDD-SI from the right ACC to the right cerebellar tonsil and from the left inferior parietal lobule (IPL) to the right ACC, following a progressive increase pattern (HC < MDD-NSI < MDD-SI without SB < MDD-SI with SB).

Increased activity and aberrant connectivity of the ACC may be associated with SI in MDD patients and potentially serve as biomarkers for suicide risk.