Projecting the sulcal pattern of human brains onto a 2D plane — a new approach using potential theory and MRI

Haidekker, Mark A.; Evertsz, Carl J. G.; Fitzek, Clemens; Boor, Stephan; Andresen, Reimer; Falkai, Peter; Stoeter, P.; Peitgen, Heinz‐Otto

doi:10.1016/s0925-4927(98)00029-8

Cited by 4 publications

(4 citation statements)

References 30 publications

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“…Lohmann also found an effect of genes on sulcal patterns in 19 pairs of MZ twins, with stronger pairwise correlations for deeper (and ontogenetically older) sulci (Lohmann et al, 1999). Other groups have replicated these findings using different metrics of cortical shape and gyral complexity (Haidekker et al, 1998;Mohr et al, 2004). Similar conclusions are found when examining the morphology of the central sulcus (Bonan et al, 1998;Le Goualher et al, 2000), the planum temporale (Eckert et al, 2002), or the corpus callosum (Styner et al, 2005;Terriberry et al, 2005) specifically, rather than global sulcal patterns.…”

Section: Morphometric Measuresmentioning

confidence: 80%

“…The role of the genome on differences in brain shape appears to be significant, but more modest than its influence on volume. Though less well studied, twin findings on shape differences have been fairly consistent (Bartley et al, 1997;Biondi et al, 1998;Bonan et al, 1998;Eckert et al, 2002;Haidekker et al, 1998;Lohmann et al,1999;Mohr et al, 2004;Steinmetz et al, 1994;White et al, 2002). In general, brain morphology appears to be significantly heritable, but to a lesser extent than volume.…”

Section: Morphometric Measuresmentioning

confidence: 81%

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Review of Twin and Family Studies on Neuroanatomic Phenotypes and Typical Neurodevelopment

Schmitt¹,

Eyler

Giedd

et al. 2007

Twin Res Hum Genet

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This article reviews the extant twin studies employing magnetic resonance imaging data (MRI), with an emphasis on studies of populationbased samples. There have been approximately 75 twin reports using MRI, with somewhat under half focusing on typical brain structure. Of these, most are samples of adults. For large brain regions such as lobar volumes, the heritabilities of large brain volumes are consistently high, with genetic factors accounting for at least half of the phenotypic variance. The role of genetics in generating individual differences in the volumes of small brain regions is less clear, mostly due to a dearth of information, but rarely because of disagreement between studies. Multivariate analyses show strong genetic relationships between brain regions. Cortical regions involved in language, executive function, and emotional regulation appear to be more heritable than other areas. Studies of brain shape also show significant, albeit lower, genetic effects on population variance. Finally, there is evidence of significant genetically mediated relationships between intelligence and brain structure. At present, the majority of twin imaging studies are limited by sample sizes small by the standards of behavioral genetics; nevertheless the literature at present represents a pioneering effort in the pursuit of answers to many challenging neurobiological questions.

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Section: Morphometric Measuresmentioning

confidence: 80%

Section: Morphometric Measuresmentioning

confidence: 81%

Review of Twin and Family Studies on Neuroanatomic Phenotypes and Typical Neurodevelopment

Schmitt¹,

Eyler

Giedd

et al. 2007

Twin Res Hum Genet

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“…Indeed, heritability estimates for the length of several sulci in primate brains varied and were on average lower (0.44%) than that for cranial capacity (0.75%) (Cheverud et al, 1990). Studies in small samples of MZ (Bonan et al, 1998;Lohmann et al, 1999) and MZ and DZ twins (Bartley et al, 1997;Haidekker et al, 1998;Le Goualher et al, 2000) also suggest regional differences in the genetic and environmental inf luences on gyral and sulcal shape, size and patterns. Future detailed study of regional features of the brain will allow for quantification of genetic and environmental contributions to the anatomy of the neural networks underlying the different aspects of cognition and behavior (Gazzaniga, 1989(Gazzaniga, , 2000Mesulam, 1990Mesulam, , 1998Fuster, 2000).…”

Section: Discussionmentioning

confidence: 99%

Quantitative Genetic Modeling of Variation in Human Brain Morphology

Pol²,

et al. 2001

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The degree to which individual variation in brain structure in humans is genetically or environmentally determined is as yet not well understood. We studied the brains of 54 monozygotic (33 male, 21 female) and 58 dizygotic (17 male, 20 female, 21 opposite sex) pairs of twins and 34 of their full siblings (19 male, 15 female) by means of high resolution magnetic resonance imaging scans. Structural equation modeling was used to quantify the genetic and environmental contributions to phenotypic (co)variance in whole brain, gray and white matter volume of the cerebrum, lateral ventricle volume and associated variables such as intracranial volume and height. Because the cerebral cortex makes up more that two-thirds of the brain mass and almost three-quarters of its synapses, our data predominantly concerns the telencephalon. Genetic factors accounted for most of the individual differences in whole brain (90%), gray (82%) and white (88%) matter volume. Individual differences in lateral ventricle volume were best explained by a model containing common (58%) and unique (42%) environmental factors, indicating genes to be of no or minor influence. In our sample, genetic or environmental influences were not different for males and females. The same genes influenced brain volumes and intracranial volume and almost completely explained their high phenotypic correlation. Genes influencing gray and white matter overlapped to a large extent and completely determined their phenotypic correlation. The high heritability estimates that were found indicate that brain volumes may be useful as intermediate phenotypes in behavioral genetic research.

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“…The length minimization algorithm (s) used an intertraverse distance of 0.75 pixels. The accompanying difference derivatives are listed in Tables 2 and 3. modeling methods (outline-based (Levinthal and Ware, 1972;Christian and Sederberg, 1978) and/or volumetric-based (Lorenson and Cline, 1987)) followed by the analysis of flat maps (Griffen, 1994;Haidekker et al, 1998;Jouandet et al, 1989;Schwartz and Merker, 1986;Van Essen and Maunsell, 1980) of the surface of the human brain. It would be a great advantage to use these nonlinear transformation techniques to produce flat cytoarchitectonic maps of the human cerebral cortex, which would offer new perspectives in statistical evaluation and comparative inter-and intraindividual studies.…”

Section: Discussionmentioning

confidence: 99%

A Robust Transcortical Profile Scanner for Generating 2-D Traverses in Histological Sections of Richly Curved Cortical Courses

Schmitt

Böhme

2002

NeuroImage

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Projecting the sulcal pattern of human brains onto a 2D plane — a new approach using potential theory and MRI

Cited by 4 publications

References 30 publications

Review of Twin and Family Studies on Neuroanatomic Phenotypes and Typical Neurodevelopment

Review of Twin and Family Studies on Neuroanatomic Phenotypes and Typical Neurodevelopment

Quantitative Genetic Modeling of Variation in Human Brain Morphology

A Robust Transcortical Profile Scanner for Generating 2-D Traverses in Histological Sections of Richly Curved Cortical Courses

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