Autistic spectrum disorder (ASD) is a neurodevelopmental disorder characterized by deficits in social interactions, communication and stereotyped behaviour. Recent evidence from neuroimaging supports ...the hypothesis that ASD deficits in adults may be related to abnormalities in a specific frontal–temporal network Autism‐specific Structural Network (ASN). To see whether these results extend to younger children and to better characterize these abnormalities, we applied three morphometric methods on brain grey matter (GM) of children with and without ASD. We selected 39 sMRI images of male children with ASD and 42 typically developing (TD) from the Autism Brain Imaging Data Exchange database. We used source‐based morphometry (SoBM), a whole‐brain multivariate approach to identify GM networks, voxel‐based morphometry (VBM), a voxel‐wise comparison of the local GM concentration and surface‐based morphometry (SuBM) for the estimation of the cortical parameters. SoBM showed a bilateral frontal–parietal–temporal network different between groups, including the inferior–middle temporal gyrus, the inferior parietal lobule and the postcentral gyrus; VBM returned differences only in the right temporal lobe; SuBM returned a thinning in the right inferior temporal lobe thinner in ASD, a higher gyrification in the right superior parietal lobule in TD and in the middle frontal gyrus in ASD. For the first time, we investigated the brain abnormalities in children with ASD using three morphometric techniques. The results were relatively consistent between methods, stressing the role of an Autism‐specific Structural Network in ASD individuals. We also make methodological speculations on the relevance of using multivariate and whole‐brain neuroimaging analysis to capture ASD complexity.
For the first time, three morphometric approaches were applied on MRI images of children with autistic spectrum disorder (ASD) and controls. Source‐based morphometry, an innovative method that extracts grey matter networks from the structural images, showed a temporal–frontal–parietal network specific for ASD children, seeming more powerful than other methods to detect the widespread abnormalities in the brain of ASD children. This circuit is similar to the ASN, a network found previously in adults with ASD.
The present study aimed to investigate poststroke morphological alterations contralesionally and correlations with functional outcomes. Structural magnetic resonance images were obtained from 27 ...poststroke patients (24 males, 50.21 ± 10.97 years) and 20 healthy controls (13 males, 46.63 ± 12.18 years). Voxel‐based and surface‐based morphometry analysis were conducted to detect alterations of contralesional grey matter volume (GMV), cortical thickness (CT), gyrification index (GI), sulcus depth (SD), and fractal dimension (FD) in poststroke patients. Partial correlation analysis was used to explore the relationship between regions with significant structural differences and scores of clinical assessments, including Modified Barthel Index (MBI), Berg Balance Scale (BBS), Fugl–Meyer Assessment of Upper Extremity (FMA‐UE), Mini‐Mental State Examination (MMSE), and Montreal Cognitive Assessment (MoCA). Correction for multiplicity was conducted within each parameter and for all tests. GMV significantly decreased in the contralesional motor‐related, occipital and temporal cortex, limbic system, and cerebellum lobe (P < 0.01, family‐wise error FWE correction). Lower CT was found in the contralesional precentral and lingual gyrus (P < 0.01, FWE correction), while lower GI found in the contralesional superior temporal gyrus and insula (P < 0.01, FWE correction). There were significant correlations between GMV of contralesional lingual gyrus and MBI (P = 0.031, r = 0.441), and BBS (P = 0.047, r = 0.409) scores, and GMV of contralesional hippocampus and FMA‐UE scores (P = 0.048, r = 0.408). In conclusion, stroke patients exhibited wide grey matter loss and cortical morphological changes in the contralesional hemisphere, which correlated with sensorimotor functions and the ability of daily living.
The present study aimed to investigate poststroke morphological alterations in the contralesional hemisphere and correlations with functional outcomes. Results suggested that poststroke patients exhibited wide grey matter loss and cortical morphological changes in the contralesional hemisphere, evidenced by decreased cortical thickness and gyrification index. Grey matter volume of brain regions contralesionally was correlated with sensorimotor functions and the ability of daily living.
This study aimed to explore the alterations in gray matter volume (GMV) based on high‐resolution structural data and the temporal precedence of structural alterations in patients with sleep‐related ...hypermotor epilepsy (SHE). After preprocessing of T1 structural images, the voxel‐based morphometry and source‐based morphometry (SBM) methods were applied in 60 SHE patients and 56 healthy controls to analyze the gray matter volumetric alterations. Furthermore, a causal network of structural covariance (CaSCN) was constructed using Granger causality analysis based on structural data of illness duration ordering to assess the causal impact of structural changes in abnormal gray matter regions. The GMVs of SHE patients were widely reduced, mainly in the bilateral cerebellums, fusiform gyri, the right angular gyrus, the right postcentral gyrus, and the left parahippocampal gyrus. In addition to those regions, the results of the SBM analysis also found decreased GMV in the bilateral frontal lobes, precuneus, and supramarginal gyri. The analysis of CaSCN showed that along with disease progression, the cerebellum was the prominent node that tended to affect other brain regions in SHE patients, while the frontal lobe was the transition node and the supramarginal gyrus was the prominent node that may be easily affected by other brain regions. Our study found widely affected regions of decreased GMVs in SHE patients; these regions underlie the morphological basis of epileptic networks, and there is a temporal precedence relationship between them.
This study estimated the causal influence between regions of structural alterations as epilepsy progresses in sleep‐related hypermobility epilepsy.
Thyroid hormones play a critical role in brain development, but paradoxically, patients with hyperthyroidism often exhibit cognitive decline and irritability. This study aims to explore the pattern ...of atrophy in hyperthyroid patients, changes in specific areas of the brain, including hypothalamic subfields and limbic structures, and their relationships with hormonal levels and psychometric tests. This prospective cross‐sectional study involves 19 newly diagnosed, untreated hyperthyroid patients, and 15 age and gender‐matched control subjects. The participants underwent psychometric and cognitive tests and volumetric MRI. The hypothalamic subfield (anterior‐inferior, anterior‐superior, superior‐tubular, inferior‐tubular, and posterior hypothalamus) and limbic structures (fornix, basal forebrain, nucleus accumbens, and septal nucleus) were segmented using voxel‐based morphometry, surface‐based morphometry, and deep learning algorithms. The groups were compared using the t‐test, and correlation analyses were performed between clinical parameters and volumetric measurements. The correlation between hormonal parameters and volumetric measurements in patient and control groups was assessed with the Meng test. Hyperthyroid patients displayed widespread grey matter loss and sulcal shallowing in the left hemisphere. However, no local gyrification index changes or cortical thickness variations were detected. The limbic structures and hypothalamic subunits did not show any volume discrepancies. Free thyroxine in the patient group negatively correlated with bilateral anterior‐inferior and right septal nucleus, but positively correlated with left anterior‐inferior in the control group. Thyroid stimulating hormone in the patient group showed a positive correlation with bilateral fornix volume, a correlation absent in the control group. Disease duration negatively correlated with right anterior‐inferior, right tubular inferior, and right septal nucleus. Changes in cognitive and psychometric test scores in the patient group correlated with the bilateral septal nucleus volume. Hyperthyroidism primarily leads to a reduction in grey matter volume and sulcal shallowing. Thyroid hormones have differing volumetric effects in limbic structures and hypothalamic subunits under physiological and hyperthyroid conditions.
Trait impulsivity is a multifaceted personality characteristic that contributes to maladaptive life outcomes. Although a growing body of neuroimaging studies have investigated the structural ...correlates of trait impulsivity, the findings remain highly inconsistent and heterogeneous. Herein, we performed a systematic review to depict an integrated delineation of gray matter (GM) substrates of trait impulsivity and a meta‐analysis to examine concurrence across previous whole‐brain voxel‐based morphometry studies. The systematic review summarized the diverse findings in GM morphometry in the past literature, and the quantitative meta‐analysis revealed impulsivity‐related volumetric GM alterations in prefrontal, temporal, and parietal cortices. In addition, we identified the modulatory effects of age and gender in impulsivity‐GM volume associations. The present study advances understanding of brain GM morphometry features underlying trait impulsivity. The findings may have practical implications in the clinical diagnosis of and intervention for impulsivity‐related disorders.
To depict an integrated delineation of grey matter substrates underlying trait impulsivity, we performed a systematic review and voxel‐based meta‐analysis to uncover volumetrically correlated regions in prefrontal, temporal, and parietal cortices. The findings may have practical implications in the clinical diagnosis of and intervention for impulsivity‐related disorders.
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.
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