Influences of Brain Size, Sex, and Sex Chromosome Complement on the Architecture of Human Cortical Folding

Fish, Ari M.; Cachia, Arnaud; Fischer, Clara; Mankiw, Catherine; Reardon, Paul K.; Clasen, Liv S.; Blumenthal, Jonathan D.; Greenstein, Deanna; Giedd, Jay N.; Mangin, Jean‐François; Raznahan, Armin

doi:10.1093/cercor/bhw323

Cited by 39 publications

(42 citation statements)

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“…In terms of gyrification in adults, males showed greater cortical gyrification in most areas of the cortex; however, this pattern was attenuated and even reversed in some regions after controlling for cortical volume in a cross-sectional study [66]. In a cross-sectional sample of individuals ages 5 to 25 years, cortical gyrification was found to be significantly greater in typically developing males than females [67]. Furthermore, these sex differences in gyrification are apparent early in development.…”

Section: Cortical Surface Area and Gyrificationmentioning

confidence: 82%

Sex differences in the developing brain: insights from multimodal neuroimaging

Kaczkurkin

Raznahan

Satterthwaite

2018

Neuropsychopharmacol

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273

213

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Youth (including both childhood and adolescence) is a period when the brain undergoes dramatic remodeling and is also a time when neuropsychiatric conditions often emerge. Many of these illnesses have substantial sex differences in prevalence, suggesting that sex differences in brain development may underlie differential risk for psychiatric symptoms between males and females. Substantial evidence documents sex differences in brain structure and function in adults, and accumulating data suggests that these sex differences may be present or emerge during development. Here we review the evidence for sex differences in brain structure, white matter organization, and perfusion during development. We then use these normative differences as a framework to understand sex differences in brain development associated with psychopathology. In particular, we focus on sex differences in the brain as they relate to anxiety, depression, psychosis, and attention-deficit/hyperactivity symptoms. Finally, we highlight existing limitations, gaps in knowledge, and fertile avenues for future research.

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Section: Cortical Surface Area and Gyrificationmentioning

confidence: 82%

Sex differences in the developing brain: insights from multimodal neuroimaging

Kaczkurkin

Raznahan

Satterthwaite

2018

Neuropsychopharmacol

Self Cite

273

213

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“…National Institutes of Health -Bethesda, USA (NIH) Sex Chromosome Aneuploidies: This dataset has been described in detail previously [37][38][39] . Briefly, we included 297 patients with various supernumerary X-and/or Ychromosome counts and 165 healthy controls (79 females) ( Table S1).…”

Section: Cohorts Diagnostic Classification and Mri Acquisitionmentioning

confidence: 99%

Transcriptomic and Cellular Decoding of Regional Brain Vulnerability to Neurodevelopmental Disorders

Seidlitz¹,

Nadig²,

Liu³

et al. 2019

Preprint

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Neurodevelopmental disorders are highly heritable and associated with spatially-selective disruptions of brain anatomy. The logic that translates genetic risks into spatially patterned brain vulnerabilities remains unclear but is a fundamental question in disease pathogenesis. Here, we approach this question by integrating (i) in vivo neuroimaging data from patient subgroups with known causal genomic copy number variations (CNVs), and (ii) bulk and single-cell gene expression data from healthy cortex. First, for each of six different CNV disorders, we show that spatial patterns of cortical anatomy change in youth are correlated with spatial patterns of expression for CNV region genes in bulk cortical tissue from typically-developing adults. Next, by transforming normative bulk-tissue cortical expression data into cell-type expression maps, we further link each disorder's anatomical change map to specific cell classes and specific CNV-region genes that these cells express. Finally, we establish convergent validity of this "transcriptional vulnerability model" by inter-relating patient neuroimaging data with measures of altered gene expression in both brain and bloodderived patient tissue. Our work clarifies general biological principles that govern the mapping of genetic risks onto regional brain disruption in neurodevelopmental disorders. We present new methods that can harness these principles to screen for potential cellular and molecular determinants of disease from readily available patient neuroimaging data.

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“…There have been many approaches capturing various features of cortical folding, such as the gyrification index (GI), fractal dimension, curvature, sulcal depth, sulcal length, sulcal area, and sulcal fundus curves (Fish et al, 2016;Hill et al, 2010;Im et al, 2008;Im et al, 2006;Kao et al, 2007;Li et al, 2010;Lyu et al, 2010;Mangin et al, 2004;Pienaar et al, 2008;Shi et al, 2008;Shimony et al, 2016;Zilles et al, 1988). However, they do not investigate the spatial, geometric and topological patterns of sulcal folding.…”

Section: Sulcal Pattern Analysis Using a Sulcal Pit-based Graph Strucmentioning

confidence: 99%

Sulcal pits and patterns in developing human brains

Grant²

2019

NeuroImage

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Spatial distribution and specific geometric and topological patterning of early sulcal folds have been hypothesized to be under stronger genetic control and are more associated with optimal organization of cortical functional areas and their white matter connections, compared to later developing sulci. Several previous studies of sulcal pit (putative first sulcal fold) distribution and sulcal pattern analyses using graph structures have provided evidence of the importance of sulcal pits and patterns as remarkable anatomical features closely related to human brain function, suggesting additional insights concerning the anatomical and functional development of the human brain. Recently, early sulcal folding patterns have been observed in healthy fetuses and fetuses with brain abnormalities such as polymicrogyria and agenesis of corpus callosum. Graph-based quantitative sulcal pattern analysis has shown high sensitivity in detecting emerging subtle abnormalities in cerebral cortical growth in early fetal stages that are difficult to detect via qualitative visual assessment or using traditional cortical measures such as gyrification index and curvature. It has proven effective for characterizing genetically influenced early cortical folding development. Future studies will be aimed at better understanding a comprehensive map of spatio-temporal dynamics of fetal cortical folding in a large longitudinal cohort in order to examine individual clinical fetal MRIs and predict postnatal neurodevelopmental outcomes from early fetal life.

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Influences of Brain Size, Sex, and Sex Chromosome Complement on the Architecture of Human Cortical Folding

Cited by 39 publications

References 50 publications

Sex differences in the developing brain: insights from multimodal neuroimaging

Sex differences in the developing brain: insights from multimodal neuroimaging

Transcriptomic and Cellular Decoding of Regional Brain Vulnerability to Neurodevelopmental Disorders

Sulcal pits and patterns in developing human brains

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