Assessing Age-Related Gray Matter Differences in Young Adults with Voxel-Based Morphometry: The Effect of Field Strengths

Knowing the patterns of brain differences with age in the young population could lead to a better understanding of the causes of certain psychiatric disorders; however, relevant information is insufficient. Here, a pattern of regional gray matter (GM) that changed with age in a young cohort aged 20–30 years was provided. Extending from previous age studies, all participants were imaged at both 1.5 T and 3 T to address the question of how far the field strength influences results. Fifty-nine young participants aged 20–30 years were scanned at both 1.5 T and 3 T. Voxel-based morphometry (VBM) was used to estimate the GM volume. Some brain regions showed a significant field strength-dependent difference in GM volume. VBM uncovered a significantly age-related increase in the GM volume in the left visual-associated area at 3 T, which was not detected at 1.5 T. In addition, voxels at 1.5 T that revealed a significant age-related reduction in the GM volume were found in the right cerebellum. In conclusion, age-related differences in human brain morphology could even be detected in a young cohort aged 20–30 years; however, the results varied across field strengths. Thus, field strength should be considered an important factor when comparing age-specific brain differences across studies.

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Location, location, location– choice of Voxel-Based Morphometry processing pipeline drives variability in the location of neuroanatomical brain markers

10.1101/2021.03.09.434531 ◽

2021 ◽

Author(s):

Xinqi Zhou ◽

Renjing Wu ◽

Yixu Zeng ◽

Ziyu Qi ◽

Stefania Ferraro ◽

...

Keyword(s):

Gray Matter ◽

Brain Regions ◽

Voxel Based Morphometry ◽

Clinical Neuroscience ◽

Age Related ◽

Large Brain ◽

Magnetic Resonance Imaging Mri ◽

Computational Analyses ◽

Gray Matter Volumes

AbstractFundamental and clinical neuroscience has benefited from the development of automated computational analyses of Magnetic Resonance Imaging (MRI) data, such as Voxel-based Morphometry (VBM). VBM determines regional gray matter variations with high spatial resolution and results are commonly interpreted in a regional-specific manner, for instance with respect to which specific brain regions differ in volume between women and men. In excess of 600 papers using VBM are now published every year and a number of different automated VBM processing pipelines are frequently used in analyses although it remains to be fully and systematically assessed whether they come up with the same answers. Here we have therefore examined variability between four commonly used VBM pipelines in two large brain structural datasets. Spatial similarity, reproducibility and reliability of the processed gray matter brain maps was generally low between pipelines. Examination of sex-differences and age-related changes in gray matter volumes revealed considerable differences between the pipelines in terms of the specific regions identified as well as meta-analytic characterization of their function. In contrast, applying machine learning-based multivariate analyses allowed an accurate prediction of sex or age based on the gray matter maps across pipelines, although prediction accuracy differed strongly between them. Together the findings suggest that the choice of pipeline alone leads to considerable variability in brain structural analyses which poses a serious challenge for reproducibility as well as interpretation.

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Attentional bias to threat and gray mater volume morphology in high anxious individuals

10.1101/2020.10.20.346981 ◽

2020 ◽

Author(s):

Joshua M. Carlson ◽

Lin Fang

Keyword(s):

Attentional Bias ◽

Parietal Cortex ◽

Gray Matter ◽

Posterior Parietal Cortex ◽

Gray Matter Volume ◽

Anterior Cingulate ◽

Brain Morphology ◽

Matter Volume ◽

Posterior Parietal ◽

The Right

AbstractIn a sample of highly anxious individuals, the relationship between gray matter volume brain morphology and attentional bias to threat was assessed. Participants performed a dot-probe task of attentional bias to threat and gray matter volume was acquired from whole brain structural T1-weighted MRI scans. The results replicate previous findings in unselected samples that elevated attentional bias to threat is linked to greater gray matter volume in the anterior cingulate cortex, middle frontal gyrus, and striatum. In addition, we provide novel evidence that elevated attentional bias to threat is associated with greater gray matter volume in the right posterior parietal cortex, cerebellum, and other distributed regions. Lastly, exploratory analyses provide initial evidence that distinct sub-regions of the right posterior parietal cortex may contribute to attentional bias in a sex-specific manner. Our results illuminate how differences in gray matter volume morphology relate to attentional bias to threat in anxious individuals. This knowledge could inform neurocognitive models of anxiety-related attentional bias to threat and targets of neuroplasticity in anxiety interventions such as attention bias modification.

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Sleep spindles: a physiological marker of age-related changes in gray matter in brain regions supporting motor skill memory consolidation

Neurobiology of Aging ◽

10.1016/j.neurobiolaging.2016.10.009 ◽

2017 ◽

Vol 49 ◽

pp. 154-164 ◽

Cited By ~ 45

Author(s):

Stuart Fogel ◽

Catherine Vien ◽

Avi Karni ◽

Habib Benali ◽

Julie Carrier ◽

...

Keyword(s):

Gray Matter ◽

Memory Consolidation ◽

Motor Skill ◽

Brain Regions ◽

Sleep Spindles ◽

Age Related ◽

Age Related Changes

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Correlation between voxel based morphometry and manual volumetry in magnetic resonance images of the human brain

Anais da Academia Brasileira de Ciências ◽

10.1590/s0001-37652008000100010 ◽

2008 ◽

Vol 80 (1) ◽

pp. 149-156 ◽

Cited By ~ 16

Author(s):

Ricardo R. Uchida ◽

Cristina M. Del-Ben ◽

David Araújo ◽

Geraldo Busatto-Filho ◽

Fábio L.S. Duran ◽

...

Keyword(s):

Magnetic Resonance ◽

Gray Matter ◽

Brain Structures ◽

Magnetic Resonance Images ◽

Healthy Controls ◽

Gaussian Filter ◽

Voxel Based Morphometry ◽

The Right ◽

Correlation Procedure ◽

Structural Volume

This is a comparative study between manual volumetry (MV) and voxel based morphometry (VBM) as methods of evaluating the volume of brain structures in magnetic resonance images. The volumes of the hippocampus and the amygdala of 16 panic disorder patients and 16 healthy controls measured through MV were correlated with the volumes of gray matter estimated by optimized modulated VBM. The chosen structures are composed almost exclusively of gray matter. Using a 4 mm Gaussian filter, statistically significant clusters were found bilaterally in the hippocampus and in the right amygdala in the statistical parametric map correlating with the respective manual volume. With the conventional 12 mm filter,a significant correlation was found only for the right hippocampus. Therefore,narrowfilters increase the sensitivity of the correlation procedure, especially when small brain structures are analyzed. The two techniques seem to consistently measure structural volume.

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Right Lateralized Brain Reserve Offsets Age-Related Deficits in Ignoring Distraction

Cerebral Cortex Communications ◽

10.1093/texcom/tgaa049 ◽

2020 ◽

Vol 1 (1) ◽

Author(s):

Nir Shalev ◽

Méadhbh B Brosnan ◽

Magdalena Chechlacz

Keyword(s):

Cognitive Reserve ◽

Life Experiences ◽

Gray Matter Volume ◽

Leisure Activities ◽

Relevant Information ◽

Brain Regions ◽

Neural Basis ◽

Age Related ◽

The Face ◽

Efficient Selection

Abstract Age-related deterioration of attention decreases the ability to stay focused on the task at hand due to less efficient selection of relevant information and increased distractibility in the face of irrelevant, but salient stimuli. While older (compared with younger) adults may have difficulty suppressing salient distractors, the extent of these challenges differs vastly across individuals. Cognitive reserve measured by proxies of cognitively enriching life experiences, such as education, occupation, and leisure activities, is thought to mitigate the effects of the aging process and account for variability in trajectories of cognitive decline. Based on combined behavioral and neuroimaging (voxel-based morphometry) analyses of demographic, cognitive, and neural markers of aging and cognitive reserve proxy measures, we examine here predictors of variability in the age-related changes in attention function, indexed by ability to suppress salient distraction. Our findings indicate that in healthy (neurotypical), aging gray matter volume within several right lateralized fronto-parietal brain regions varies according to both levels of cognitive reserve (education) and the capacity to effectively select visual stimuli amid salient distraction. Thus, we provide here novel experimental evidence supporting Robertson’s theory of a right lateralized neural basis for cognitive reserve.

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Emotional Awareness in Schizophrenia Is Associated With Gray Matter Volume of Right Precuneus

Frontiers in Psychiatry ◽

10.3389/fpsyt.2021.601742 ◽

2021 ◽

Vol 12 ◽

Author(s):

Martin Jáni ◽

Zora Kikinis ◽

Jan Lošák ◽

Ofer Pasternak ◽

Filip Szczepankiewicz ◽

...

Keyword(s):

Gray Matter ◽

Gray Matter Volume ◽

Emotional Awareness ◽

Brain Regions ◽

Magnetic Resonance Images ◽

Healthy Controls ◽

Emotional States ◽

Brain Volumes ◽

Matter Volume ◽

The Right

Objectives: We assessed the relationship between emotional awareness (e.g., the ability to identify and differentiate our own feelings and feelings of others) and regional brain volumes in healthy and in schizophrenia groups.Methods: Magnetic resonance images of 29 subjects with schizophrenia and 33 matched healthy controls were acquired. Brain gray matter was parcellated using FreeSurfer and 28 regions of interest associated with emotional awareness were analyzed. All participants were assessed using the Levels of Emotional Awareness Scale (LEAS) of Self and of Other. LEAS scores were correlated with gray matter volume for each hemisphere on the 14 brain regions of the emotional awareness network.Results: Individuals with schizophrenia showed decreased emotional awareness on both LEAS Self and LEAS Other compared to healthy controls. There were no statistically significant between-group differences in gray matter volumes of the emotional awareness network. The performance on LEAS Other correlated negatively with right precuneus gray matter volume only in the schizophrenia group.Conclusion: Our findings suggest a relationship between gray matter volume of the right precuneus and deficits in understanding of emotional states of others in schizophrenia.

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In-scanner head motion and structural covariance networks

10.1101/2021.04.28.441807 ◽

2021 ◽

Author(s):

Heath R. Pardoe ◽

Samantha P. Martin

Keyword(s):

Gray Matter ◽

Brain Mri ◽

Brain Regions ◽

Head Motion ◽

Voxel Based Morphometry ◽

Structural Covariance ◽

Graph Theoretic ◽

Network Analyses ◽

Gray Matter Volumes ◽

Source Of Error

AbstractIn-scanner head motion systematically reduces estimated regional gray matter volumes obtained from structural brain MRI. Here, we investigate how head motion affects structural covariance networks that are derived from regional gray matter volumetric estimates. We acquired motion-affected and motion-free whole brain T1-weighted MRI in 29 healthy adult subjects and estimated relative regional gray matter volumes using a voxel-based morphometry approach. Structural covariance network analyses were undertaken while systematically increasing the number of motion-affected scans included in the analysis. We demonstrate that the standard deviation in regional gray matter estimates increases as the number of motion-affected scans increases. This subsequently increases pair-wise correlations between regions, a key determinant for construction of structural covariance networks. We further demonstrate that head motion systematically alters graph theoretic metrics derived from these networks. Our findings suggest that in-scanner head motion is a source of error that violates the assumption that structural covariance networks reflect neuroanatomical connectivity between brain regions. Results of structural covariance studies should be interpreted with caution, particularly when subject groups are likely to move their heads in the scanner.

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Developmental brain structural atypicalities in autism: A voxel-based morphometry analysis

10.21203/rs.3.rs-1066676/v1 ◽

2021 ◽

Author(s):

Hui Wang ◽

Zeng-Hui Ma ◽

Ling-Zi Xu ◽

Liu Yang ◽

Zhao-Zheng Ji ◽

...

Keyword(s):

Gray Matter ◽

Gray Matter Volume ◽

Age Groups ◽

Brain Regions ◽

Inferior Parietal Lobule ◽

Voxel Based Morphometry ◽

Whole Brain ◽

Autism Group ◽

Significant Difference ◽

Parietal Lobule

Abstract Background Accumulating structural Magnetic Resonance Imaging (sMRI) studies have showed atypicalities in developmental changes of structural regional brain in autism, with largely inconsistent results. Methods The current study investigated the brain structural abnormal features of autistic individuals aged 6~30 years. We included 52 autism individuals and 50 age, gender, and IQ matched typically developing individuals (TD), who were divided into three groups: childhood (6-12 years old), adolescent (13-18 years old) and adulthood (19-30 years old). Whole brain volume and Voxel-Based Morphometry (VBM) analyses were employed on the sMRI data collected from our participants. Results We found no significant difference in the volume of whole brain, gray matter and white matter between autism and TD groups of the three age groups. For VBM analyses, the volumes of gray matter in right superior temporal gyrus and right inferior parietal lobule in children autism group were smaller than those in TD group; the volume of gray matter in left inferior parietal lobule in adolescent autism group was larger than that in TD group; the volume of gray matter in right middle occipital gyrus in adult autism group was larger than that in TD group, and the gray matter in left posterior cingulate gyrus was smaller than that in TD group. Conclusions Findings suggest autism individuals showed different atypical brain regions of gray matter volume in childhood, adolescent, and adulthood relative to their normal peers respectively, indiciating that it is essential to take developmental perspectives into consideration when exploring brain structural abnormalities in autism.

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