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Aims The aim of this study is to investigate differences in gray matter volume and cortical complexity between Parkinson's disease with depression (PDD) patients and Parkinson's disease without depression (PDND) patients. Methods A total of 41 PDND patients, 36 PDD patients, and 38 healthy controls (HC) were recruited and analyzed by Voxel‐based morphometry (VBM) and surface‐based morphometry (SBM). Differences in gray matter volume and cortical complexity were compared using the one‐way analysis of variance (ANOVA) and correlated with the Hamilton Depression Scale‐17 (HAMD‐17) scores. Results PDD patients exhibited significant cortical atrophy in various regions, including bilateral medial parietal–occipital–temporal lobes, right dorsolateral temporal lobes, bilateral parahippocampal gyrus, and bilateral hippocampus, compared to HC and PDND groups. A negative correlation between the GMV of left precuneus and HAMD‐17 scores in the PDD group tended to be significant (r = −0.318, p = 0.059). Decreased gyrification index was observed in the bilateral insular and dorsolateral temporal cortex. However, there were no significant differences found in fractal dimension and sulcal depth. Conclusion Our research shows extensive cortical structural changes in the insular cortex, parietal–occipital–temporal lobes, and hippocampal regions in PDD. This provides a morphological perspective for understanding the pathophysiological mechanism underlying depression in Parkinson's disease. The first row of pictures shows extensive cortical volume loss in Parkinson's disease with depression patients, primarily concentrated in the parietal–occipital–temporal lobes, parahippocampal gyrus, and hippocampus. The second row of pictures shows decreased gyrification index in the insula.

PurposeAmyotrophic lateral sclerosis (ALS) presents with varying degrees of brain degeneration that can extend beyond the corticospinal tract (CST). Furthermore, the clinical course and progression of ALS varies widely. Brain degeneration detected using structural MRI could reflect disease progression.Subjects and methodsOn study registration, 3-Tesla volumetric MRI and diffusion tensor imaging scans were obtained at baseline in 38 healthy controls and 67 patients with sporadic ALS. Patients had Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised (ALSFRS-R) scores of ≥36 and did not have the chromosome 9, open reading frame 72 repeat expansion. Six months later, changes in ALSFRS-R (ΔALSFRS-R) scores were calculated and patients were grouped into three categories, namely, patients with slow progression with ΔALSFRS-R scores ≤3 (n=19), intermediate progression with ΔALSFRS-R scores =4, 5 and 6 (n=36) and rapid progression with ΔALSFRS-R scores ≥7 (n=12). We analysed voxel-based morphometry and tract-based spatial statistics among these subgroups and controls.ResultsIn comparison with controls, patients with ALS showed grey matter atrophy and decreased fractional anisotropy beyond the motor cortex and CST, especially in the frontotemporal lobes and basal ganglia. Moreover, the degree of change was highly proportional to ΔALSFRS-R at the 6-month assessment.ConclusionA more rapid disease progression and poorer functional decline were associated with greater involvement of the extra-motor cortex and basal ganglia, suggesting that the spatial extent of brain involvement can be an indicator of the progression in ALS.

Objective In major depressive disorder (MDD) patients, higher morning cortisol levels due to a hyperactive hypothalamic–pituitary–adrenal (HPA) axis have been reported. The aim of the present study was to evaluate the relationship between cortical thinning and the serum cortisol levels during the first depressive episode in drug‐naïve MDD patients using an automated surface‐based morphometry (SBM) method. Methods The institutional review board approved this prospective study. MR imaging data were obtained using a 3T scanner by a three‐dimensional fast‐spoiled gradient recalled acquisition with steady state (3D‐FSPGR). Thirty drug‐naïve patients with MDD and 41 age‐ and gender‐matched healthy subjects (controls) were enrolled. We then used the SBM method (Freesurfer) to generate cortical thickness maps, and measured the cortical thickness in each subject. Morning blood samples were drawn from all participants for cortisol measurements. Results We found the serum cortisol levels were significantly higher in the MDD patients than in the controls. The MDD patients manifested significant thinning of the left lateral orbitofrontal cortex compared with the controls. There was a significant negative linear correlation between the thickness of the left lateral orbitofrontal cortex and the serum cortisol levels in the MDD patients. Conclusions In the early stage of MDD, the thickness of the lateral orbitofrontal cortex was significantly reduced, and also showed a significant inverse correlation with the serum cortisol levels. Since the lateral orbitofrontal cortex contains a high concentration of glucocorticoid receptor, glucocorticoid receptor‐mediated signaling transductions could contribute to neurotoxicity, which might occur when there are high cortisol levels in patients with MDD.

In this paper, we review and discuss brain imaging studies which have used the source-based morphometry (SBM) approach over the past decade. SBM is a data-driven linear multivariate approach for decomposing structural brain imaging data into commonly covarying imaging components and subject-specific loading parameters. It is a well-established technique which has predominantly been used to study neuroanatomic differences between healthy controls and patients with neuropsychiatric diseases. We start by discussing the advantages of this technique over univariate analysis for imaging studies, followed by a discussion of results from recent studies which have successfully applied this methodology. We also present recent extensions of this framework including nonlinear SBM, biclustered independent component analysis (B-ICA) and conclude with the possible directions of work for future.

•First to measure MRI-based GM volume in the control and perinatally-deafened cat.•ROI analysis reveals whole-brain GM preservation following deafness.•ROI and TBM results generally aligned, but each approach provided distinct insights.•Specific auditory loci decreased in volume while visual and somatosensory increased.•GM volume changes suggest functional optimization and cortical reorganization. In response to sensory deprivation, the brain adapts according to contemporary demands to efficiently navigate a modified perceptual environment. This reorganization may result in improved processing of the remaining senses–a phenomenon referred to as compensatory crossmodal plasticity. One approach to explore this neuroplasticity is to consider the macrostructural changes in neural tissue that mirror this functional optimization. The current study is the first of its kind to measure MRI-derived gray matter (GM) volumes of control felines (n=30), while additionally identifying volumetric differences in response to perinatal deafness (30 ototoxically-deafened cats). To accomplish this purpose, regional and morphometric methods were performed in parallel. The regional analysis evaluated volumetric alterations of global GM, as well as the volumes of 146 regions of interest (ROIs) and 12 functional subgroupings of these ROIs. Results revealed whole-brain GM preservation; however, somatosensory and visual cortices exhibited an overall increase in volume. On a smaller scale, this analysis uncovered two auditory ROIs (second auditory cortex, A2, and ventral auditory field, VAF) that decreased in volume alongside two visual regions (anteromedial lateral suprasylvian area, AMLS and splenial visual area, SVA) that increased–all localized within the right hemisphere. Comparatively, the findings of tensor-based morphometry (TBM) generally aligned with those of the ROI-based method, as this voxel-wise approach demonstrated clusters of expansion coincident with visual- and somatosensory-related loci; although, it failed to detect any GM reductions following deafness. As distinct differences were identified in each analysis, the current study highlights the importance of employing multiple methods when exploring MRI volumetry. Overall, this study proposes that volumetric alterations within sensory loci allude to a redistribution of cortical space arising from modified perceptual demands following auditory deprivation.

•A relatively inactive dynamic brain status occurred more often in SSNHL participants. Early-stage SSNHL participants showed decreased brain status transition number.•Disturbed neurovascular coupling restricted to the primary auditory cortex occurred in the intermediate- and late-stage SSNHL patients.•A significant shrinkage of the left medial superior frontal gyrus developed at the late stage.•Our study offered neuroimaging evidence for evolvement from functional to structural brain alterations of SSNHL patients with disease duration less than 1 month. A cortical plasticity after long-duration single side deafness (SSD) is advocated with neuroimaging evidence while little is known about the short-duration SSDs. In this case-cohort study, we recruited unilateral sudden sensorineural hearing loss (SSNHL) patients and age-, gender-matched health controls (HC), followed by comprehensive neuroimaging analyses. The primary outcome measures were temporal alterations of varied dynamic functional network connectivity (dFNC) states, neurovascular coupling (NVC) and brain region volume at different stages of SSNHL. The secondary outcome measures were pure-tone audiograms of SSNHL patients before and after treatment. A total of 38 SSNHL patients (21 [55%] male; mean [standard deviation] age, 45.05 [15.83] years) and 44 HC (28 [64%] male; mean [standard deviation] age, 43.55 [12.80] years) were enrolled. SSNHL patients were categorized into subgroups based on the time from disease onset to the initial magnetic resonance imaging scan: early- (n = 16; 1-6 days), intermediate- (n = 9; 7-13 days), and late- stage (n = 13; 14-30 days) groups. We first identified slow state transitions between varied dFNC states at early-stage SSNHL, then revealed the decreased NVC restricted to the auditory cortex at the intermediate- and late-stage SSNHL. Finally, a significantly decreased volume of the left medial superior frontal gyrus (SFGmed) was observed only in the late-stage SSNHL cohort. Furthermore, the volume of the left SFGmed is robustly correlated with both disease duration and patient prognosis. Our study offered neuroimaging evidence for the evolvement from functional to structural brain alterations of SSNHL patients with disease duration less than 1 month, which may explain, from a neuroimaging perspective, why early-stage SSNHL patients have better therapeutic responses and hearing recovery. [Display omitted]

Prenatal exposure to undernutrition is widespread in both developing and industrialized countries, causing irreversible damage to the developing brain, resulting in altered brain structure and decreased cognitive function during adulthood. The Dutch famine in 1944/45 was a humanitarian disaster, now enabling studies of the effects of prenatal undernutrition during gestation on brain aging in late adulthood. We hypothesized that study participants prenatally exposed to maternal nutrient restriction (MNR) would demonstrate altered brain structure resembling premature brain aging in late adulthood, expecting the effect being stronger in men. Utilizing the Dutch famine birth cohort (n = 118; mean age: 67.5 ± 0.9 years), this study implements an innovative biomarker for individual brain aging, using structural neuroimaging. BrainAGE was calculated using state-of-the-art pattern recognition methods, trained on an independent healthy reference sample, then applied to the Dutch famine MRI sample, to evaluate the effects of prenatal undernutrition during early gestation on individual brain aging in late adulthood. Exposure to famine in early gestation was associated with BrainAGE scores indicative of an older-appearing brain in the male sample (mean difference to subjects born before famine: 4.3 years, p < 0.05). Furthermore, in explaining the observed variance in individual BrainAGE scores in the male sample, maternal age at birth, head circumference at birth, medical treatment of hypertension, history of cerebral incidences, actual heart rate, and current alcohol intake emerged to be the most influential variables (adjusted R2 = 0.63, p < 0.01). The findings of our study on exposure to prenatal undernutrition being associated with a status of premature brain aging during late adulthood, as well as individual brain structure being shaped by birth- and late-life health characteristics, are strongly supporting the critical importance of sufficient nutrient supply during pregnancy. Interestingly, the status of premature brain aging in participants exposed to the Dutch famine during early gestation occurred in the absence of fetal growth restriction at birth as well as vascular pathology in late-life. Additionally, the neuroimaging brain aging biomarker presented in this study will further enable tracking effects of environmental influences or (preventive) treatments on individual brain maturation and aging in epidemiological and clinical studies. [Display omitted] •Prenatal malnutrition is linked to older-appearing brains in males by 4.3y.•Variance in BrainAGE in males is explained by birth & health characteristics.•Increased BrainAGE occurred in absence of fetal growth.•Increased BrainAGE occurred in absence of vascular pathology in late-life.•BrainAGE biomarker enables tracking various effects on individual brain aging.

Elevated cortisol levels have been frequently reported in Alzheimer's disease (AD) and linked to brain atrophy, especially of the hippocampus. Besides, high cortisol levels have been shown to impair memory performance and increase the risk of developing AD in healthy individuals. We investigated the associations between serum cortisol levels, hippocampal volume, gray matter volume and memory performance in healthy aging and AD. In our cross-sectional study, we analyzed the relationships between morning serum cortisol levels, verbal memory performance, hippocampal volume, and whole-brain voxel-wise gray matter volume in an independent sample of 29 healthy seniors (HS) and 29 patients along the spectrum of biomarker-based AD. Cortisol levels were significantly elevated in patients with AD as compared to HS, and higher cortisol levels were correlated with worse memory performance in AD. Furthermore, higher cortisol levels were significantly associated with smaller left hippocampal volumes in HS and indirectly negatively correlated to memory function through hippocampal volume. Higher cortisol levels were further related to lower gray matter volume in the hippocampus and temporal and parietal areas in the left hemisphere in both groups. The strength of this association was similar in HS and AD. In AD, cortisol levels are elevated and associated with worse memory performance. Furthermore, in healthy seniors, higher cortisol levels show a detrimental relationship with brain regions typically affected by AD. Thus, increased cortisol levels seem to be indirectly linked to worse memory function even in otherwise healthy individuals. Cortisol may therefore not only serve as a biomarker of increased risk for AD, but maybe even more importantly, as an early target for preventive and therapeutic interventions.

A positive association between brain size and intelligence is firmly established, but whether region-specific anatomical differences contribute to general intelligence remains an open question. Results from voxel-based morphometry (VBM) - one of the most widely used morphometric methods - have remained inconclusive so far. Here, we applied cross-validated machine learning-based predictive modeling to test whether out-of-sample prediction of individual intelligence scores is possible on the basis of voxel-wise gray matter volume. Features were derived from structural magnetic resonance imaging data (N = 308) using (a) a purely data-driven method (principal component analysis) and (b) a domain knowledge-based approach (atlas parcellation). When using relative gray matter (corrected for total brain size), only the atlas-based approach provided significant prediction, while absolute gray matter (uncorrected) allowed for above-chance prediction with both approaches. Importantly, in all significant predictions, the absolute error was relatively high, i.e., greater than ten IQ points, and in the atlas-based models, the predicted IQ scores varied closely around the sample mean. This renders the practical value even of statistically significant prediction results questionable. Analyses based on the gray matter of functional brain networks yielded significant predictions for the fronto-parietal network and the cerebellum. However, the mean absolute errors were not reduced in contrast to the global models, suggesting that general intelligence may be related more to global than region-specific differences in gray matter volume. More generally, our study highlights the importance of predictive statistical analysis approaches for clarifying the neurobiological bases of intelligence and provides important suggestions for future research using predictive modeling.

Audiovisual working memory (WM) plays a critical role in multisensory cognitive processing, yet its structural neural correlates remain insufficiently understood. This study employed an audiovisual dual n-back task paradigm and voxel-based morphometry (VBM) to investigate gray matter volume (GMV) associations with behavioral performance in 60 healthy individuals. Behavioral results revealed a significant visual dominance effect under high cognitive load: visual performance remained stable across conditions, whereas auditory performance declined. Structural analyses showed modality-specific GMV correlations. Visual performance was positively associated with GMV in the insula, posterior cingulate, hippocampus, and inferior frontal regions, while auditory performance was negatively correlated with GMV in the angular and middle occipital gyri. Notably, the left cuneus exhibited a strong positive correlation with the Δd prime (visual–auditory) difference under high load, suggesting its potential role in cross-modal resource allocation. Furthermore, cognitive overload appeared to disrupt the structure–behavior associations observed under lower load, highlighting a load-dependent dissociation within executive control and sensory integration regions. These findings underscore the distinct anatomical substrates supporting audiovisual WM and the neural basis of visual dominance, offering structural markers for targeted cognitive training and clinical intervention.