scholarly journals Robust estimation of sulcal morphology

2018 ◽  
Author(s):  
Christopher R. Madan
Keyword(s):  
Robust Estimation ◽  
Computational Approach ◽  
Brain Morphology ◽  
Individual Factors ◽  
Cortical Surface ◽  
Surface Reconstructions ◽  
Fourth Sample ◽  
Sulcal Morphology ◽  
Cortical Morphology ◽  
Test Retest Reliability

AbstractWhile it is well established that cortical morphology differs in relation to a variety of inter-individual factors, it is often characterized using estimates of volume, thickness, surface area, or gyrification. Here we developed a computational approach for estimating sulcal width and depth that relies on cortical surface reconstructions output by FreeSurfer. While other approaches for estimating sulcal morphology exist, studies often require the use of multiple brain morphology programs that have been shown to differ in their approaches to localize sulcal landmarks, yielding morphological estimates based on inconsistent boundaries. To demonstrate the approach, sulcal morphology was estimated in three large sample of adults across the lifespan, in relation to aging. A fourth sample is additionally used to estimate test-retest reliability of the approach. This toolbox is now made freely available as supplemental to this paper: https://cmadan.github.io/calcSulc/.

scholarly journals Quantitative comparison of cortical surface reconstructions from MP2RAGE and multi-echo MPRAGE data at 3 and 7T

NeuroImage ◽  
2014 ◽  
Vol 90 ◽  
pp. 60-73 ◽  
Author(s):  
Kyoko Fujimoto ◽  
Jonathan R. Polimeni ◽  
André J.W. van der Kouwe ◽  
Martin Reuter ◽  
Tobias Kober ◽  
...  
Keyword(s):  
Quantitative Comparison ◽  
Cortical Surface ◽  
Surface Reconstructions

scholarly journals Automated Video Interview Personality Assessments: Reliability, Validity, and Generalizability Investigations

2021 ◽  
Author(s):  
Louis Hickman ◽  
Nigel Bosch ◽  
Vincent Ng ◽  
Rachel Saef ◽  
Louis Tay ◽  
...  
Keyword(s):  
Job Applicants ◽  
The Other ◽  
Big Five Personality ◽  
Nonverbal Behaviors ◽  
Personality Assessments ◽  
Total N ◽  
Self Reports ◽  
Fourth Sample ◽  
Test Retest Reliability ◽  
Future Work

Organizations are increasingly adopting automated video interviews (AVIs) to screen job applicants despite a paucity of research on their reliability, validity, and generalizability. In this study, we address this gap by developing AVIs that use verbal, paraverbal, and nonverbal behaviors extracted from video interviews to assess Big Five personality traits. We developed and validated machine learning models within (using nested cross-validation) and across three separate samples of mock video interviews (total N = 1,073). Also, we examined their test–retest reliability in a fourth sample (N = 99). In general, we found that the AVI personality assessments exhibited stronger evidence of validity when they were trained on interviewer-reports rather than self-reports. When cross-validated in the other samples, AVI personality assessments trained on interviewer-reports had mixed evidence of reliability, exhibited consistent convergent and discriminant relations, used predictors that appear to be conceptually relevant to the focal traits, and predicted academic outcomes. On the other hand, there was little evidence of reliability or validity for the AVIs trained on self-reports. We discuss the implications for future work on AVIs and personality theory, and provide practical recommendations for the vendors marketing such approaches and organizations considering adopting them.

scholarly journals The subcortical morphology correlates of autistic traits in school-age children: a population-based neuroimaging study

2021 ◽  
Author(s):  
Tamsin Sharp ◽  
Mayada Elsabbagh ◽  
Andrew Pickles ◽  
Rachael Bedford
Keyword(s):  
Cognitive Development ◽  
Brain Size ◽  
Autistic Traits ◽  
Brain Morphology ◽  
School Age Children ◽  
Social Responsiveness ◽  
Imaging Data ◽  
Subcortical Structures ◽  
Development Study ◽  
Cortical Morphology

Background There is emerging evidence that the neuroanatomy of autism forms a spectrum which extends into the general population. However, whilst several studies have identified cortical morphology correlates of autistic traits, it is not established whether morphological differences are present in the subcortical structures of the brain. Additionally, it is not clear to what extent previously reported structural associations may be confounded by co-occurring psychopathology. To address these questions, we utilised neuroimaging data from the Adolescent Brain Cognitive Development Study to assess whether a measure of autistic traits was associated with differences in child subcortical morphology, and if any observed differences persisted after adjustment for child internalising and externalising symptoms. Methods Our analyses included data from 7,005 children aged 9-10 years (female: 47.19%) participating in the Adolescent Brain Cognitive Development Study. Autistic traits were assessed using scores from the Social Responsiveness Scale. Volumes of subcortical regions-of-interest were derived from structural magnetic resonance imaging data. Results Overall, we did not find strong evidence for an association of autistic traits with differences in subcortical morphology in this sample of school-aged children. Whilst lower absolute volumes of the nucleus accumbens and putamen were associated with higher scores of autistic traits, these differences did not persist once a global measure of brain size was accounted for. Conclusions These findings from our well-powered study suggest that other metrics of brain morphology, such as cortical morphology or shape-based phenotypes, may be stronger candidates to prioritise when attempting to identify robust neuromarkers of autistic traits.

scholarly journals Cerebral Sulcal Asymmetry in Macaque Monkeys

Symmetry ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 1509
Author(s):  
Kazuhiko Sawada
Keyword(s):  
Surface Area ◽  
Population Level ◽  
Primate Species ◽  
Evolutionary Significance ◽  
Macaque Monkeys ◽  
Left Handedness ◽  
Cynomolgus Macaques ◽  
Sulcal Morphology ◽  
And Function ◽  
Cortical Morphology

The asymmetry of the cerebral sulcal morphology is particularly obvious in higher primates. The sulcal asymmetry in macaque monkeys, a genus of the Old World monkeys, in our previous studies and others is summarized, and its evolutionary significance is speculated. Cynomolgus macaques displayed fetal sulcation and gyration symmetrically, and the sulcal asymmetry appeared after adolescence. Population-level rightward asymmetry was revealed in the length of arcuate sulcus (ars) and the surface area of superior temporal sulcus (sts) in adult macaques. When compared to other nonhuman primates, the superior postcentral sulcus (spcs) was left-lateralized in chimpanzees, opposite of the direction of asymmetry in the ars, anatomically-identical to the spcs, in macaques. This may be associated with handedness: either right-handedness in chimpanzees or left-handedness/ambidexterity in macaques. The rightward asymmetry in the sts surface area was seen in macaques, and it was similar to humans. However, no left/right side differences were identified in the sts morphology among great apes, which suggests the evolutionary discontinuity of the sts asymmetry. The diversity of the cortical lateralization among primate species suggests that the sulcal asymmetry reflects the species-related specialization of the cortical morphology and function, which is facilitated by evolutionary expansion in higher primates.

scholarly journals Mother-child similarity in brain morphology: A comparison of structural characteristics of the brain’s reading network

2021 ◽  
Author(s):  
Lynn V. Fehlbaum ◽  
Lien Peters ◽  
Plamina Dimanova ◽  
Margot ROELL ◽  
Réka Borbás ◽  
...  
Keyword(s):  
Brain Development ◽  
Brain Structure ◽  
Goodness Of Fit ◽  
Parietal Lobe ◽  
Structural Characteristics ◽  
Inferior Frontal Gyrus ◽  
Brain Morphology ◽  
Transfer Effects ◽  
Sulcal Morphology ◽  
Structural Brain

Background: Substantial evidence acknowledges the complex gene-environment interplay impacting brain development and learning. Intergenerational neuroimaging allows the assessment of familial transfer effects on brain structure, function and behavior by investigating neural similarity in caregiver-child dyads. Methods: Neural similarity in the human reading network was assessed through well-used measures of brain structure (i.e., surface area (SA), gyrification (lG), sulcal morphology, gray matter volume (GMV) and cortical thickness (CT)) in 69 mother-child dyads (children’s age~11y). Regions of interest for the reading network included left-hemispheric inferior frontal gyrus, inferior parietal lobe and fusiform gyrus. Mother-child similarity was quantified by correlation coefficients and familial specificity was tested by comparison to random adult-child dyads. Sulcal morphology analyses focused on occipitotemporal sulcus interruptions and similarity was assessed by chi-square goodness of fit. Results: Significant structural brain similarity was observed for mother-child dyads in the reading network for lG, SA and GMV (r=0.349/0.534/0.542, respectively), but not CT. Sulcal morphology associations were non-significant. Structural brain similarity in lG, SA and GMV were specific to parent- child pairs. Furthermore, structural brain similarity for SA and GMV was higher compared to CT. Conclusion: Intergenerational neuroimaging techniques promise to enhance our knowledge of familial transfer effects on brain development and disorders.

scholarly journals Structural Differences Across Multiple Visual Cortical Regions in the Absence of Cone Function in Congenital Achromatopsia

2021 ◽  
Vol 15 ◽  
Author(s):  
Rebecca Lowndes ◽  
Barbara Molz ◽  
Lucy Warriner ◽  
Anne Herbik ◽  
Pieter B. de Best ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Surface Area ◽  
Grey Matter Volume ◽  
Cortical Surface ◽  
Colour Perception ◽  
Cortical Surface Area ◽  
Visual Areas ◽  
Cortical Regions ◽  
Visual Cortical ◽  
Cortical Morphology

Most individuals with congenital achromatopsia (ACHM) carry mutations that affect the retinal phototransduction pathway of cone photoreceptors, fundamental to both high acuity vision and colour perception. As the central fovea is occupied solely by cones, achromats have an absence of retinal input to the visual cortex and a small central area of blindness. Additionally, those with complete ACHM have no colour perception, and colour processing regions of the ventral cortex also lack typical chromatic signals from the cones. This study examined the cortical morphology (grey matter volume, cortical thickness, and cortical surface area) of multiple visual cortical regions in ACHM (n = 15) compared to normally sighted controls (n = 42) to determine the cortical changes that are associated with the retinal characteristics of ACHM. Surface-based morphometry was applied to T1-weighted MRI in atlas-defined early, ventral and dorsal visual regions of interest. Reduced grey matter volume in V1, V2, V3, and V4 was found in ACHM compared to controls, driven by a reduction in cortical surface area as there was no significant reduction in cortical thickness. Cortical surface area (but not thickness) was reduced in a wide range of areas (V1, V2, V3, TO1, V4, and LO1). Reduction in early visual areas with large foveal representations (V1, V2, and V3) suggests that the lack of foveal input to the visual cortex was a major driving factor in morphological changes in ACHM. However, the significant reduction in ventral area V4 coupled with the lack of difference in dorsal areas V3a and V3b suggest that deprivation of chromatic signals to visual cortex in ACHM may also contribute to changes in cortical morphology. This research shows that the congenital lack of cone input to the visual cortex can lead to widespread structural changes across multiple visual areas.

scholarly journals Test–retest reliability of brain morphology estimates

2017 ◽  
Vol 4 (2) ◽  
pp. 107-121 ◽  
Author(s):  
Christopher R. Madan ◽  
Elizabeth A. Kensinger
Keyword(s):  
Brain Morphology ◽  
Retest Reliability ◽  
Test Retest Reliability

scholarly journals Predicting age from cortical structure across the lifespan

2018 ◽  
Author(s):  
Christopher R. Madan ◽  
Elizabeth A. Kensinger
Keyword(s):  
Fractal Dimensionality ◽  
Brain Morphology ◽  
Training Dataset ◽  
Anatomical Landmarks ◽  
Cortical Structure ◽  
Age Related ◽  
Median Error ◽  
Structural Measures ◽  
Cortical Morphology ◽  
Age Prediction

AbstractDespite inter-individual differences in cortical structure, cross-sectional and longitudinal studies have demonstrated a large degree of population-level consistency in age-related differences in brain morphology. The present study assessed how accurately an individual’s age could be predicted by estimates of cortical morphology, comparing a variety of structural measures, including thickness, gyrification, and fractal dimensionality. Structural measures were calculated across up to seven different parcellation approaches, ranging from 1 region to 1000 regions. The age-prediction framework was trained using morphological measures obtained from T1-weighted MRI volumes collected from multiple sites, yielding a training dataset of 1056 healthy adults, aged 18-97. Age predictions were calculated using a machine-learning approach that incorporated non-linear differences over the lifespan. In two independent, held-out test samples, age predictions had a median error of 6-7 years. Age predictions were best when using a combination of cortical metrics, both thickness and fractal dimensionality. Overall, the results reveal that age-related differences in brain structure are systematic enough to enable reliable age prediction based on metrics of cortical morphology.Graphical AbstractSeveral measures of cortical structure differ in relation to age. We examined the cortical granularity of these differences across seven parcellation approaches, from a 1 region (unparcellated cortical ribbon) to 1000 regions (patches with boundaries informed by anatomical landmarks), and three measures: thickness, gyrification, and fractal dimensionality. Rather than merely examining age-related relationships, we examined how these parcellations and measures can be used topredictage.

scholarly journals The MIR137 VNTR rs58335419 Is Associated With Cognitive Impairment in Schizophrenia and Altered Cortical Morphology

2020 ◽  
Author(s):  
Ebrahim Mahmoudi ◽  
Joshua R Atkins ◽  
Yann Quidé ◽  
William R Reay ◽  
Heath M Cairns ◽  
...  
Keyword(s):  
Association Studies ◽  
Variable Number Tandem Repeat ◽  
Variable Number ◽  
Brain Morphology ◽  
Whole Genome Sequencing Data ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Sequencing Data ◽  
Genome Wide ◽  
Cortical Morphology

Abstract Genome-wide association studies (GWAS) of schizophrenia have strongly implicated a risk locus in close proximity to the gene for miR-137. While there are candidate single-nucleotide polymorphisms (SNPs) with functional implications for the microRNA’s expression encompassed by the common haplotype tagged by rs1625579, there are likely to be others, such as the variable number tandem repeat (VNTR) variant rs58335419, that have no proxy on the SNP genotyping platforms used in GWAS to date. Using whole-genome sequencing data from schizophrenia patients (n = 299) and healthy controls (n = 131), we observed that the MIR137 4-repeats VNTR (VNTR4) variant was enriched in a cognitive deficit subtype of schizophrenia and associated with altered brain morphology, including thicker left inferior temporal gyrus and deeper right postcentral sulcus. These findings suggest that the MIR137 VNTR4 may impact neuroanatomical development that may, in turn, influence the expression of more severe cognitive symptoms in patients with schizophrenia.

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