Psychoradiology最新文献

Background: Late-life depression (LLD) and odor identification (OI) dysfunction are risk factors for dementia, but the underlying neural mechanisms remain unclear. This study investigated dynamic functional connectivity (dFC) in olfactory brain regions of LLD patients with and without OI dysfunction and examined how dFC moderates the OI-cognition link.

Methods: Resting-state functional magnetic resonance imaging data were acquired from 51 LLD patients with OI deficits (LLD-OID), 59 LLD patients without deficits (LLD-noOID), and 51 healthy controls (HC). A sliding-window approach (50 TR width, 1 TR step) was used to estimate dFC variability between the orbitofrontal cortex (OFC) and the whole brain. Bayesian regression and moderation analyses assessed associations among OFC dFC, OI scores, and cognitive measures. Results were robust across window sizes.

Results: Compared to LLD-noOID and HC, LLD-OID showed decreased OFC-left inferior frontal gyrus dFC variability (P < 0.01) and increased OFC-right middle frontal gyrus (MFG) variability (P < 0.001). Higher OFC-MFG variability was associated with worse OI and cognitive performance and significantly moderated the OI-global cognition relationship (β = 1.06, P = 0.027, 95% CI [0.12, 2.0]). No group differences were found in primary olfactory regions.

Conclusion: LLD patients with OI dysfunction exhibited more disrupted dFC in secondary olfactory regions compared with those without OI dysfunction. Dynamic OFC-MFG disconnectivity may index vulnerability to cognitive decline and dementia risk in LLD patients.

Background: Previous studies have reported accelerated brain aging in individuals with major depressive disorder (MDD) compared to healthy controls. However, these findings are based primarily on cross-sectional data, limiting dynamic association between brain aging and MDD. Here, we examined the relationship between brain aging and MDD progression by focusing on subthreshold depression, a prodromal stage of MDD, and aimed to determine whether quantitative markers of brain aging exhibit a stable association with disease progression.

Methods: Using neuroimaging data from the UK Biobank and a support vector regression (SVR) model, we predicted brain age in individuals who exhibited subthreshold depressive symptoms at baseline but showed divergent mental status at follow-up, and then conducted between-group comparisons. Logistic regression was then applied to assess whether brain-predicted age difference (Brain-PAD) stably associates with the progression of subthreshold depression after adjusting for covariates.

Results: Individuals with subthreshold depression showed a higher risk of progression to MDD compared to healthy controls. Those whose condition worsened from subthreshold depression to MDD exhibited greater brain aging than those who remained subthreshold or recovered. Importantly, Brain-PAD remained significantly and stably associated with this progression after controlling for sex, ethnicity, lifestyle, and socioeconomic factors.

Conclusions: This study supports an association between brain aging and MDD progression and demonstrates a robust association between an increased Brain-PAD and the conversion from subthreshold depression to MDD. These findings enhance our understanding of MDD's developmental trajectory and suggest that Brain-PAD may facilitate early detection and intervention targeting brain aging.

Background: Although language is traditionally regarded as unique to humans and predominantly left-lateralized in the brain, the dynamic interplay between cerebral hemispheres during language processing remains poorly understood.

Methods: Using 400 functional magnetic resonance imaging scans acquired with a 7T scanner under diverse narrative stimuli, this study examined whole-brain functional dynamic lateralization patterns during Chinese language processing and explored potential sex differences.

Results: We identified two distinct dynamic lateralization states. While core language regions consistently showed left-lateralization, other brain regions displayed reversed lateralization. These two states-characterized by higher-level functional regions lateralizing either left or right-corresponded to the processing of rational and emotional content, respectively. Notably, males showed a stronger tendency toward the former state, whereas females inclined toward the latter, particularly during the processing of rational content. Genetic analyses further suggested that sex differences in these lateralization states may be influenced by sex hormones.

Conclusion: This study offers novel insights into the dynamic organization of cerebral lateralization during Chinese language processing.

Psychiatric disorders are complex, disabling conditions that continue to rely on subjective diagnostic criteria due to the absence of objective biological markers. Neuroradiology has become a critical discipline for examining the structural, functional, and biochemical underpinnings of these disorders through advanced brain imaging. This review synthesizes findings from five major psychiatric conditions including major depressive disorder, schizophrenia, autism spectrum disorder, obsessive-compulsive disorder, and generalized anxiety disorder, and briefly discusses the behavioral variant of Alzheimer's disease, a variant with neuropsychological overlay, across multiple imaging modalities, including structural magnetic resonance imaging (MRI), diffusion tensor imaging, functional MRI, magnetic resonance spectroscopy, functional near-infrared spectroscopy, and positron emission tomography. We present a comparative overview of cross-condition and modality-specific findings, highlighting converging disruptions in frontolimbic and temporoparietal circuits, alongside unique neurobiological features in each disorder. We also acknowledge key confounds such as medication effects, comorbidities, and methodological variability that limit direct transdiagnostic inference. We further discuss methodological limitations, emerging trends such as multimodal integration and machine learning, and future directions for translating imaging data into clinically meaningful biomarkers.

Background: Chronic insomnia disorder (CID) is associated with disrupted functional brain networks, yet prior research has focused primarily on group-level analyses. This study employed personalized functional network mapping to identify connectivity abnormalities in CID.

Methods: Resting-state functional magentic resonance imaging (rs-fMRI) data were collected from 86 CID patients and 38 good sleeper controls (GSCs). Using non-negative matrix factorization (NMF), we derived individualized large-scale brain networks for each participant to uncover subject-specific connectivity changes in CID. We also constructed functional network connectivity (FNC) matrices using Pearson correlation coefficients and compared global and local graph-theory metrics across groups based on these individualized networks.

Results: FNC analysis revealed significant differences between CID patients and GSCs within the default mode network (DMN), ventral attention network, visual network (VIS), and other key brain regions. CID exhibited altered global network topology and significant differences in local topological properties. At the global level, CID demonstrated significantly higher small-worldness (Sigma) and normalized clustering coefficient (Gamma). At the nodal level, CID showed increased local efficiency and clustering coefficient, as well as decreased nodal efficiency in the DMN, along with increased degree centrality in the VIS.

Conclusion: By focusing on individualized functional connectivity, this approach reveals unique "fingerprint" alterations in CID. These findings provide novel insights into CID's neurobiological mechanisms and underscore the value of personalized network approaches for understanding and treating sleep disorders.

Emotion regulation (ER) research has, for decades, focused on mental health outcomes, such as emotional recovery and wellbeing reinstatement, in behavioral, physiological, and neural measures across different regulatory strategies. Although important, the practical significance of ER research should not only be limited to mental health, but also needs to consider aiding people's real-time adaptive behavior, to meet varying environmental demands or goals flexibly. In this paper, we propose an idea of ER adaptiveness that pays equal attention to both mental health outcomes, and how an ER strategy may be used to facilitate functional adaptiveness in meeting distinct goals. For instance, research of ER adaptiveness needs to highlight how to design regulatory strategies for the purpose of promoting cognitive, behavior, or social functions (nonaffective goal) in addition to that of affective wellbeing, and how to help a learned strategy work flexibly in changing contexts (affective goal). Lastly, taking application in sport psychology for example, we propose potential directions of how ER adaptiveness research may help participants to improve motor performance in competitive sports.

We aimed to evaluate how the AIR™ Recon DL algorithm influences magentic resonance imaging (MRI) quality and quantitative brain morphometry relative to conventional reconstruction (CR). Seventy-four healthy adults underwent 3D T1-weighted MRI reconstructed with CR and AIR™ Recon DL. Image quality was rated by two neuroradiologists (κ = 0.74-0.97). Voxel-based morphometry assessed total, gray matter (GM), white matter (WM), and cerebrospinal (CSF) volumes; surface-based morphometry analyzed cortical thickness, sulcal depth, fractal dimension, and gyrification across 148 regions. Hippocampal volumes were extracted using the Neuromorphometrics atlas. Reconstruction times were compared. AIR™ Recon DL significantly improved image quality (reduced noise and artifacts, P < 0.001) but introduced systematic morphometric shifts-smaller total and WM volumes, larger GM and CSF volumes, and widespread regional thickness increases (effect sizes d ≈ 0.3-0.5). Hippocampal volumes increased bilaterally (ΔL = +0.15 mL, +3.97%; ΔR = +0.15 mL, +3.88%; both P < 0.05). Mean reconstruction time was longer for deep learning-based reconstruction (11.6 ± 1.6 s) than CR (9.9 ± 1.4 s; Δ = +1.7 s, P < 0.001). AIR™ Recon DL enhances image quality but causes modest, systematic volumetric biases. Harmonizing reconstruction methods is essential for reliable morphometric comparisons in neuropsychiatric imaging.

Background: There are notable sex differences in the symptoms and treatment response of late-life depression (LLD); however, the underlying static and dynamic abnormalities in brain function that may drive these disparities remain unclear. This study was to investigate sex-specific aberrant brain activity in LLD.

Methods: We recruited 75 LLD patients and 164 healthy controls (HCs). Static and dynamic metrics of amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), and functional connectivity (FC) were compared across four groups (LLD-female, LLD-male, HC-female, and HC-male). Correlation and moderation analyses were then used to examine whether sex moderated the associations between brain activity, cognitive impairment, and depressive symptoms.

Results: First, significant interaction effects between diagnosis (LLD vs. HCs) and sex were found for ALFF in the left paracentral lobule, ReHo in the right superior temporal gyrus, and static FC (sFC) between the right superior temporal gyrus and left middle frontal gyrus. Second, in LLD-female, ReHo (right superior temporal gyrus) and sFC (right superior temporal gyrus-left middle frontal gyrus) correlated with weight, and ALFF (left paracentral lobule) correlated with visuospatial skills. Third, sex significantly moderated the relationships between ReHo (right superior temporal gyrus) and cognition, ALFF (left paracentral lobule) and depressive symptoms, and sFC (right superior temporal gyrus-left middle frontal gyrus) and depressive symptoms in the LLD group.

Conclusion: Our study highlights sex differences in static brain activity related to cognitive impairment and depressive symptoms in LLD, indicating sex-specific neurobiological underpinnings for this disorder.

Background: Major depressive disorder (MDD) is associated with dysregulation of γ-aminobutyric acid (GABA) and glutamate(Glu) neurotransmission in the prefrontal cortex. Proton magnetic resonance spectroscopy (1H-MRS) enables non-invasive in vivo quantification of GABA and Glx(glutamate + glutamine) levels. This study investigated neurochemical characteristics of the bilateral dorsolateral prefrontal cortex (DLPFC) in first-episode adolescent MDD (FEA-MDD) and repetitive transcranial magnetic stimulation (rTMS)'s impact on these changes.

Methods: 42 drug-naïve FEA-MDD patients underwent bilateral DLPFC MRS scans before and after rTMS, with 42 healthy controls (HCs) as baseline. All participants were right-handed. The Mescher-Garwood point-resolved spectroscopy (MEGA-PRESS) protocol detected GABA+ (GABA plus macromolecules and high carnosine) and Glx levels, processed via Gannet software.

Results: FEA-MDD patients exhibited significantly lower GABA+ and higher Glx levels in the left DLPFC than HCs; in the right DLPFC, no significant difference in GABA+ levels was observed, though Glx levels were elevated. After rTMS treatment, GABA+ levels in the left DLPFC increased significantly, whereas Glx levels showed a non-significant decreasing trend. Additionally, HCs had no hemispheric differences, while in FEA-MDD, the left DLPFC showed lower GABA+ and Glx levels compared to the right. We also found that in the left DLPFC, baseline GABA+ levels were negatively correlated with Hamilton Depression Scale (HAMD) scores; Glx levels showed positive correlations with scores on the Ruminative Response Scale (RRS), Self-Rating Depression Scale (SDS), and Self-Esteem Scale (SES).

Conclusions: FEA-MDD involves prefrontal GABA+/Glx dysregulation, and rTMS may aid in restoring neurotransmitter balance within the DLPFC. This study adds to the expanding body of evidence supporting the application of targeted neurochemical modulation in the treatment of FEA-MDD, while also providing insights into potential intervention mechanisms.