Meta-analysis Of Voxel-based Morphometry Studies Research Articles

Impact of Apolipoprotein E ε4 in Alzheimer's Disease: A Meta-Analysis of Voxel-Based Morphometry Studies.

Alzheimer's disease (AD) is the most-prevalent form of dementia and imposes substantial burdens at the personal and societal levels. The apolipoprotein E (APOE) ε4 allele is a genetic factor known to increase AD risk and exacerbate brain atrophy and its symptoms. We aimed to provide a comprehensive review of the impacts of APOE ε4 on brain atrophy in AD as well as in mild cognitive impairment (MCI) as a transitional stage of AD. We performed a coordinate-based meta-analysis of voxel-based morphometry studies to compare gray-matter atrophy patterns between carriers and noncarriers of APOE ε4. We obtained coordinate-based structural magnetic resonance imaging data from 1,135 individuals who met our inclusion criteria among 12 studies reported in PubMed and Google Scholar. We found that atrophy of the hippocampus and parahippocampus was significantly greater in APOE ε4 carriers than in noncarriers, especially among those with AD and MCI, while there was no significant atrophy in these regions in healthy controls who were also carriers. The present meta-analysis has highlighted the significant link between the APOE ε4 allele and hippocampal atrophy in both AD and MCI, which emphasizes the critical influence of the allele on neurodegeneration, especially in the hippocampus. These findings improve the understanding of AD pathology, potentially facilitating progress in early detection, targeted interventions, and personalized care strategies for individuals at risk of AD who carry the APOE ε4 allele.

Grey matter alterations in generalized anxiety disorder: A voxel-wise meta-analysis of voxel-based morphometry studies.

Grey matter, a crucial component of the brain, has been found altered in generalized anxiety disorder (GAD) of several voxel-based morphometry studies. The conclusive and consistent grey matter alterations in GAD have not been confirmed. Eleven voxel-based morphometry studies of GAD patients were included in the current systematic review and meta-analysis. The linear model of anxiety severity scores was applied to explore the relationship of grey matter alterations and anxiety severity. The subgroup analysis of adult GAD and adolescent GAD was also performed. Significantly modest grey matter alterations in the left superior temporal gyrus of patients with GAD were found. The anxiety severity score was significantly correlated with grey matter alterations in the right insula, lenticular nucleus, putamen and striatum. The subgroup analysis of adult GAD and adolescent GAD all failed to show significant grey matter alterations. However, in the adult GAD subgroup, anxiety severity score was significantly correlated with grey matter alterations in the right insula. GAD might have the modest grey matter alterations in the left superior temporal gyrus. Anxiety severity might be related to the grey matter alterations in the limbic regions, such as the right insula, lenticular nucleus, putamen and striatum. This kind of correlation might be related to the effects of adult GAD. Future studies with adequate sample sizes and sophisticated GAD categories will be needed.

Seeking Overlapping Neuroanatomical Alterations between Dyslexia and Attention-Deficit/Hyperactivity Disorder: A Meta-Analytic Replication Study.

The present work is a replication article based on the paper “Are there shared neural correlates between dyslexia and ADHD? A meta-analysis of voxel-based morphometry studies” by McGrath and Stoodley (2019). In the original research, the authors used activation likelihood estimation (ALE), a technique to perform coordinate-based meta-analysis (CBMA), to investigate the existence of brain regions undergoing gray matter alteration in association with both attention-deficit/hyper-activity disorder (ADHD) and dyslexia. Here, the same voxel-based morphometry dataset was analyzed, while using the permutation-subject images version of signed differential mapping (PSI-SDM) in place of ALE. Overall, the replication converged with the original paper in showing a limited overlap between the two conditions. In particular, no significant effect was found for dyslexia, therefore precluding any form of comparison between the two disorders. The possible influences of biological sex, age, and medication status were also ruled out. Our findings are in line with literature about gray matter alteration associated with ADHD and dyslexia, often showing conflicting results. Therefore, although neuropsychological and clinical evidence suggest some convergence between ADHD and dyslexia, more future research is sorely needed to reach a consensus on the neuroimaging domain in terms of patterns of gray matter alteration.

Gray Matter Abnormalities in Patients with Complex Regional Pain Syndrome: A Systematic Review and Meta-Analysis of Voxel-Based Morphometry Studies.

Current findings on brain structural alterations in complex regional pain syndrome (CRPS) are heterogenous and controversial. This study aimed to perform a systematic review and meta-analysis to explore the significant gray matter volume (GMV) abnormalities between patients with CRPS and healthy controls (HCs). A systematic search of the PubMed, Web of Science, and MEDLINE databases was performed, updated through 27 January 2022. A total of five studies (93 CRPS patients and 106 HCs) were included. Peak coordinates and effect sizes were extracted and meta-analyzed by anisotropic effect size–signed differential mapping (AES-SDM). Heterogeneity, sensitivity, and publication bias of the main results were checked by the Q test, jackknife analysis, and the Egger test, respectively. Meta-regression analysis was performed to explore the potential impact of risk factors on GMV alterations in patients with CRPS. The main analysis exhibited that patients with CRPS had increased GMV in the left medial superior frontal gyrus (SFGmedial.L), left striatum, and an undefined area (2, 0, −8) that may be in hypothalamus, as well as decreased GMV in the corpus callosum (CC) (extending to right supplementary motor area (SMA.R), right median cingulate/paracingulate gyri (MCC.R)), and an undefined area (extending to the right caudate nucleus (CAU.R), and right thalamus (THA.R)). Meta-regression analysis showed a negative relationship between increased GMV in the SFGmedial.L and disease duration, and the percentage of female patients with CRPS. Brain structure abnormalities in the sensorimotor regions (e.g., SFGmedial.L, SMA.R, CAU.R, MCC.R, and THA.R) may be susceptible in patients with CRPS. Additionally, sex differences and disease duration may have a negative effect on the increased GMV in SFGmedial.L.

Structural gray matter differences in Problematic Usage of the Internet: a systematic review and meta-analysis

Problematic Usage of the Internet (PUI) has been linked to diverse structural gray matter changes in individual data studies. However, no quantitative synthesis across studies has been conducted. We aimed to identify gray matter regions showing significant spatial convergence across neuroimaging studies in PUI. We searched PubMed and PsycINFO up to 10/03/2021 and included original, cross-sectional comparative studies that examined structural gray matter imaging in PUI versus control groups; reported a whole-brain analysis; and provided peak coordinates for gray matter differences. From a total of 624 potentially relevant studies, 15 (including 355 individuals with PUI and 363 controls) were included in a meta-analysis of voxel-based morphometry studies. Anatomical likelihood estimation (ALE) meta-analysis was performed using extracted coordinates and identified significant spatial convergence in the medial/superior frontal gyri, the left anterior cingulate cortex/cingulate gyrus, and the left middle frontal/precentral gyri. Datasets contributing to these findings all indicated reduced gray matter in cases compared to controls. In conclusion, voxel-based morphometric studies indicate replicable gray matter reductions in the dorsolateral prefrontal cortex and anterior cingulate cortex in PUI, regions implicated in reward processing and top-down inhibitory control. Further studies are required to understand the nature of gray matter differences across PUI behaviors, as well as the contribution of particular mental health disorders, and the influence of variation in study and sample characteristics.

Optical Coherence Tomography and Pattern Electroretinography Changes in Egyptian Patients with Major Depressive Disorder

Abstract Background Major depressive disorder (MDD) is a common psychiatric disorder that affects nearly 11.1-14.6 % of the population in their lifetime. Pathophysiology and brain imaging findings show that degenerative and inflammatory processes may play a role. Meta-analysis of voxel-based morphometry studies in MDD demonstrated significant gray matter loss. From anatomical and embryological perspectives, the retina can be considered a unique extension of the brain and is able to reflect axonal histopathology. Being unmyelinated, it can provide insight into the pathophysiological processes of diseases with a neurodegenerative element. Aim to compare retinal optical coherence tomography (OCT) parameters in a group of MDD patients with a healthy control group and to correlate OCT parameters with pattern electroretinography (PERG) parameters. Method a controlled cross sectional study was conducted on 30 MDD patients and 28 age and sex matched controls. Both groups had a full ophthalmological examination, OCT imaging and 7 patients and 11 controls have PERG recorded. Results Thinning of the superior retinal nerve fiber layer, thinning of most of the ganglion cell inner plexiform (GCIP) layer, thinning of most of the macular thickness and thinning of macular volume in both eyes were detected. There was a statistically significant positive correlation between the left GCIP layer and the amplitude of the N95 wave. Also a statistically significant negative correlation existed between MDD duration in years with the left eye's average volume of the outer ring of the macula. Conclusion Significant retinal changes were detected by OCT in MDD patients supporting the theory of neurodegeneration as a pathophysiology of MDD.

Response to commentary on "Grey matter abnormalities in first episode mania: A systematic review and meta-analysis of voxel-based morphometry studies".

We appreciate the comments by Sheng and colleagues1 on our manuscript titled "Grey matter abnormalities in first-episode mania: A systematic review and meta-analysis of voxel-based morphometry studies 2 " and would like to take this opportunity to clarify our methodology and share the findings of additional analyses we have performed.

Gray matter abnormalities in Tourette Syndrome: a meta-analysis of voxel-based morphometry studies

Tourette syndrome (TS) is a neurobehavioral disorder for which the neurological mechanism has not been elucidated. Voxel-based morphometry (VBM) studies have revealed abnormalities in gray matter volume (GMV) in patients with TS; however, consistent results have not been obtained. The current study attempted to provide a voxel wise meta-analysis of gray matter changes using seed-based d mapping (SDM). We identified ten relevant studies that investigated gray matter alterations in TS patients and performed a meta-analysis using the SDM method to quantitatively estimate regional gray matter abnormalities. Next, we examined the relationships between GMV abnormalities and demographic and clinical characteristics. Our results demonstrated that TS patients had smaller GMV in the bilateral inferior frontal gyri and greater GMV in the cerebellum, right striatum (putamen), and bilateral thalami (pulvinar nucleus) than healthy controls. A meta-regression analysis did not identify correlations between GMV changes and demographic or clinical variables. This meta-analysis confirmed significant and consistent GMV changes in several brain regions of TS patients, primarily in the cortico-striato-thalamo-cortical network.

Gray matter reduction in high-risk subjects, recently diagnosed and chronic patients with schizophrenia: A revised coordinate-based meta-analysis

IntroductionCharacterizing neuroanatomical markers of different stages of schizophrenia (SZ) to assess of how the disorder develops is extremely important for the clinical practice. It still remains uncertain how abnormalities are formed as SZ progresses.ObjectivesWe reviewed and analyzed 113 voxel based morphometry studies on people at risk of or with schizophrenia to assess GM alterations at different stages of the disorder and to functionally characterize these GM variations.MethodsWe performed a meta-analysis of voxel-based morphometry studies of genetic and clinical high-risk subjects (g-/c-HR), recently diagnosed (RDSZ) and chronic SZ patients (ChSZ). We quantified gray matter (GM) changes associated with these four conditions and compared them with contrast and conjunctional data. We performed the behavioral analysis and networks decomposition of alterations to obtain their functional characterization.ResultsCompared to previous investigations, results reveal a robust cortical-subcortical, left-to-right homotopic progression of GM loss. The right anterior cingulate is the only altered region in all conditions. Contrast analyses show left-lateralized insular, amygdalar and parahippocampal GM reduction in RDSZ, which appears bilateral in ChSZ. An overlap between RDSZ and ChSZ is observed in the left insula, amygdala, precentral and inferior frontal gyri. Functional decomposition shows involvement of the salience network, with an enlargement of the sensorimotor network in RDSZ and the thalamus-basal nuclei network in ChSZ.ConclusionsThese results can help the research on diagnostic and neuroimaging biomarkers of SZ staging, as well as on the identification of new therapeutics neuroanotomic targets that could be addressed with focused magnetic or non-invasive electric stimulation.DisclosureNo significant relationships.

Gray and white matter morphology in substance use disorders: a neuroimaging systematic review and meta-analysis

Substance use disorders (SUDs) are characterized by a compulsion to seek and consume one or more substances of abuse, with a perceived loss of control and a negative emotional state. Prolonged substance use seems to be associated with morphological changes of multiple neural circuits, in particular the frontal–striatal and limbic pathways. Such neuroadaptations are evident across several substance disorders, but may vary depending on the type of substance, consumption severity and/or other unknown factors. We therefore identified studies investigating the effects of SUDs using volumetric whole-brain voxel-based morphometry (VBM) in gray (GM) and white matter (WM). We performed a systematic review and meta-analysis of VBM studies using the anatomic likelihood estimation (ALE) method implemented in GingerALE (PROSPERO pre-registration CRD42017071222). Sixty studies met inclusion criteria and were included in the final quantitative meta-analysis, with a total of 614 foci, 94 experiments and 4938 participants. We found convergence and divergence in brain regions and volume effects (higher vs. lower volume) in GM and WM depending on the severity of the consumption pattern and type of substance used. Convergent pathology was evident across substances in GM of the insula, anterior cingulate cortex, putamen, and thalamus, and in WM of the thalamic radiation and internal capsule bundle. Divergent pathology between occasional use (cortical pathology) and addiction (cortical-subcortical pathology) provides evidence of a possible top-down neuroadaptation. Our findings indicate particular brain morphometry alterations in SUDs, which may inform our understanding of disease progression and ultimately therapeutic approaches.

Frontotemporal dementia, music perception and social cognition share neurobiological circuits: A meta-analysis

Frontotemporal dementia (FTD) is a neurodegenerative disease that presents with profound changes in social cognition. Music might be a sensitive probe for social cognition abilities, but underlying neurobiological substrates are unclear. We performed a meta-analysis of voxel-based morphometry studies in FTD patients and functional MRI studies for music perception and social cognition tasks in cognitively normal controls to identify robust patterns of atrophy (FTD) or activation (music perception or social cognition). Conjunction analyses were performed to identify overlapping brain regions. In total 303 articles were included: 53 for FTD (n = 1153 patients, 42.5% female; 1337 controls, 53.8% female), 28 for music perception (n = 540, 51.8% female) and 222 for social cognition in controls (n = 5664, 50.2% female). We observed considerable overlap in atrophy patterns associated with FTD, and functional activation associated with music perception and social cognition, mostly encompassing the ventral language network. We further observed overlap across all three modalities in mesolimbic, basal forebrain and striatal regions. The results of our meta-analysis suggest that music perception and social cognition share neurobiological circuits that are affected in FTD. This supports the idea that music might be a sensitive probe for social cognition abilities with implications for diagnosis and monitoring.

Brain structural correlates of familial risk for mental illness: a meta-analysis of voxel-based morphometry studies in relatives of patients with psychotic or mood disorders.

Schizophrenia (SCZ), bipolar disorder (BD), and major depressive disorder (MDD) are heritable psychiatric disorders with partially overlapping genetic liability. Shared and disorder-specific neurobiological abnormalities associated with familial risk for developing mental illnesses are largely unknown. We performed a meta-analysis of structural brain imaging studies in relatives of patients with SCZ, BD, and MDD to identify overlapping and discrete brain structural correlates of familial risk for mental disorders. Search for voxel-based morphometry studies in relatives of patients with SCZ, BD, and MDD in PubMed and Embase identified 33 studies with 2292 relatives and 2052 healthy controls (HC). Seed-based d Mapping software was used to investigate global differences in gray matter volumes between relatives as a group versus HC, and between those of each psychiatric disorder and HC. As a group, relatives exhibited gray matter abnormalities in left supramarginal gyrus, right striatum, right inferior frontal gyrus, left thalamus, bilateral insula, right cerebellum, and right superior frontal gyrus, compared with HC. Decreased right cerebellar gray matter was the only abnormality common to relatives of all three conditions. Subgroup analyses showed disorder-specific gray matter abnormalities in left thalamus and bilateral insula associated with risk for SCZ, in left supramarginal gyrus and right frontal regions with risk for BD, and in right striatum with risk for MDD. While decreased gray matter in right cerebellum might be a common brain structural abnormality associated with shared risk for SCZ, BD, and MDD, regional gray matter abnormalities in neocortex, thalamus, and striatum appear to be disorder-specific.

Meta-analysis of Voxel-Based Neuroimaging Studies using Seed-based d Mapping with Permutation of Subject Images (SDM-PSI).

Most methods for conducting meta-analysis of voxel-based neuroimaging studies do not assess whether effects are not null, but whether there is a convergence of peaks of statistical significance, and reduce the assessment of the evidence to a binary classification exclusively based on p-values (i.e., voxels can only be "statistically significant" or "non-statistically significant"). Here, we detail how to conduct a meta-analysis using Seed-based d Mapping with Permutation of Subject Images (SDM-PSI), a novel method that uses a standard permutation test to assess whether effects are not null. We also show how to grade the strength of the evidence according to a set of criteria that considers a range of statistical significance levels (from more liberal to more conservative), the amount of data or the detection of potential biases (e.g., small-study effect and excess of significance). To exemplify the procedure, we detail the conduction of a meta-analysis of voxel-based morphometry studies in obsessive-compulsive disorder, and we provide all the data already extracted from the manuscripts to allow the reader to replicate the meta-analysis easily. SDM-PSI can also be used for meta-analyses of functional magnetic resonance imaging, diffusion tensor imaging, position emission tomography and surface-based morphometry studies.

Are there shared neural correlates between dyslexia and ADHD? A meta-analysis of voxel-based morphometry studies

BackgroundDyslexia and Attention-deficit/hyperactivity disorder (ADHD) are highly comorbid neurodevelopmental disorders (estimates of 25–40% bidirectional comorbidity). Previous work has identified strong genetic and cognitive overlap between the disorders, but neural overlap is relatively unexplored. This study is a systematic meta-analysis of existing voxel-based morphometry studies to determine whether there is any overlap in the gray matter correlates of both disorders.MethodsWe conducted anatomic likelihood estimate (ALE) meta-analyses of voxel-based morphometry studies in which individuals with dyslexia (15 studies; 417 cases, 416 controls) or ADHD (22 studies; 898 cases, 763 controls) were compared to typically developing controls. We generated ALE maps for dyslexia vs. controls and ADHD vs. controls using more conservative (p < .001, k = 50) and more lenient (p < .005, k = 50) thresholds. To determine the overlap of gray matter correlates of dyslexia and ADHD, we examined the statistical conjunction between the ALE maps for dyslexia vs. controls and ADHD vs. controls (false discovery rate [FDR] p < .05, k = 50, 5000 permutations).ResultsResults showed largely distinct gray matter differences associated with dyslexia and ADHD. There was no evidence of statistically significant gray matter overlap at our conservative threshold, and only one region of overlap in the right caudate at our more lenient threshold. Reduced gray matter in the right caudate may be relevant to shared cognitive correlates in executive functioning and/or procedural learning. The more general finding of largely distinct regional differences in gray matter between dyslexia and ADHD suggests that other neuroimaging modalities may be more sensitive to overlapping neural correlates, and that current neuroimaging recruitment approaches may be hindering progress toward uncovering neural systems associated with comorbidity.ConclusionsThe current study is the first to meta-analyze overlap between gray matter differences in dyslexia and ADHD, which is a critical step toward constructing a multi-level understanding of this comorbidity that spans the genetic, neural, and cognitive levels of analysis.

Brain gray matter correlates of extraversion: A systematic review and meta-analysis of voxel-based morphometry studies.

Extraversion is a fundamental personality dimension closely related to an individual's life outcomes and mental health. Although an increasing number of studies have attempted to identify the neurostructural markers of extraversion, the results have been highly inconsistent. The current study aimed to achieve a comprehensive understanding of brain gray matter (GM) correlates of extraversion with a systematic review and meta-analysis approach. Our review showed relatively high interstudy heterogeneity among previous findings. Our meta-analysis of whole-brain voxel-based morphometry studies revealed that extraversion was stably associated with six core brain regions. Additionally, meta-regression analyses identified brain regions where the associations of extraversion with GM volume were modulated by gender and age. The relationships between extraversion and GM structures were discussed based on three extraversion-related functional systems. Furthermore, we explained the gender and age effects. Overall, our study is the first to reveal a comprehensive picture of brain GM correlates of extraversion, and the findings may be useful for the selection of targeted brain areas for extraversion interventions.

Regional gray matter reductions associated with mild cognitive impairment in Parkinson’s disease: A meta-analysis of voxel-based morphometry studies

Mild cognitive impairment (MCI) is inconclusively associated with regional gray matter (GM) abnormalities in Parkinson’s disease (PD). We aimed to quantitatively evaluate whole-brain voxel-based morphometry (VBM) studies that have investigated brain GM changes in PD patients with MCI (PD-MCI). Seed-based d Mapping, a well-validated coordinate-based meta-analytic approach, was utilized. We included 20 VBM studies that reported 22 datasets containing 504 patients with PD-MCI and 554 PD patients without MCI (PD-NCI). The most reliable finding identified in this meta-analysis was that patients with PD-MCI exhibited greater GM atrophy in the left anterior insula than those with PD-NCI. Our findings further suggest that several moderators (age, gender, educational level, disease stage, severity of motor disability, and the severity of cognitive impairments) in PD-MCI individuals, as well as scanner field-strength, may drive heterogeneous GM changes across studies. GM abnormalities in the anterior insula, an important cognitive hub involved in switching between neural networks, contribute to understanding the neural substrates of MCI in PD, which may serve as a biomarker of PD-MCI.

Brain gray and white matter abnormalities in preterm-born adolescents: A meta-analysis of voxel-based morphometry studies.

IntroductionStudies using voxel-based morphometry report variable and inconsistent abnormalities of gray matter volume (GMV) and white matter volume (WMV) in brains of preterm-born adolescents (PBA). In such circumstances a meta-analysis can help identify the most prominent and consistent abnormalities.MethodWe identified 9 eligible studies by systematic search of the literature up to October 2017. We used Seed-based d Mapping to analyze GMV and WMV alterations between PBA and healthy controls.ResultsIn the GMV meta-analysis, PBA compared to healthy controls showed: increased GMV in left cuneus cortex, left superior frontal gyrus, and right anterior cingulate cortex; decreased GMV in bilateral inferior temporal gyrus (ITG), left superior frontal gyrus, and right caudate nucleus. In the WMV meta-analysis, PBA showed: increased WMV in right fusiform gyrus and precuneus; decreased WMV in bilateral ITG, and right inferior frontal gyrus. In meta-regression analysis, the percentage of male PBA negatively correlated with decreased GMV of bilateral ITG.InterpretationPBA show widespread GMV and WMV alterations in the default mode network, visual recognition network, and salience network. These changes may be causally relevant to socialization difficulties and cognitive impairments. The meta-regression results perhaps reveal the structural underpinning of the cognition-related sex differences in PBA.

Meta-analysis of voxel-based morphometry studies of gray matter abnormalities in patients with mesial temporal lobe epilepsy and unilateral hippocampal sclerosis.

We aimed to perform a meta-analysis to systematically determine the most consistent regions of gray matter volume (GMV) abnormality in patients of unilateral mesial temporal lobe epilepsy with hippocampal sclerosis (MTLE-HS), and to reveal the difference of GMV abnormality between the patients with left-sided and right-sided MTLE-HS. A comprehensive and systematic search was performed in PubMed for voxel-based morphometry (VBM) studies of MTLE-HS. A total of 12 MTLE-HS studies, including 9 left-sided MTLE-HS (LMTLE-HS) and 8 right-sided MTLE-HS (RMTLE-HS) studies were included. The activation likelihood estimation (ALE) method was applied in our meta-analysis. Compared to the healthy controls, MTLE-HS patients showed significant GMV decrease in the parahippocampal gyrus, left pulvinar and right pyramis. For LMTLE-HS, the most consistent GMV decrease was detected in the left parahippocampal gyrus. For RMTLE-HS, the most consistent GMV decrease was found in the right parahippocampal gyrus. No shared regions of significant GMV reduction were found between LMTLE-HS and RMTLE-HS either. This meta-analysis revealed that MTLE-HS patients had significant GMV reduction even beyond the hippocampus, and the subtypes showed distinct reduction patterns. Our findings, if were further verified with larger samples, would have implications for the clinical diagnosis of MTLE-HS.

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

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. 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. 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. 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.

Computational meta-analysis of statistical parametric maps in major depression.

Several neuroimaging meta-analyses have summarized structural brain changes in major depression using coordinate-based methods. These methods might be biased toward brain regions where significant differences were found in the original studies. In this study, a novel voxel-based technique is implemented that estimates and meta-analyses between-group differences in grey matter from individual MRI studies, which are then applied to the study of major depression. A systematic review and meta-analysis of voxel-based morphometry studies were conducted comparing participants with major depression and healthy controls by using statistical parametric maps. Summary effect sizes were computed correcting for multiple comparisons at the voxel level. Publication bias and heterogeneity were also estimated and the excess of heterogeneity was investigated with metaregression analyses. Patients with major depression were characterized by diffuse bilateral grey matter loss in ventrolateral and ventromedial frontal systems extending into temporal gyri compared to healthy controls. Grey matter reduction was also detected in the right parahippocampal and fusiform gyri, hippocampus, and bilateral thalamus. Other areas included parietal lobes and cerebellum. There was no evidence of statistically significant publication bias or heterogeneity. The novel computational meta-analytic approach used in this study identified extensive grey matter loss in key brain regions implicated in emotion generation and regulation. Results are not biased toward the findings of the original studies because they include all available imaging data, irrespective of statistically significant regions, resulting in enhanced detection of additional areas of grey matter loss.