Linked Regularities in the Development and Evolution of Mammalian Brains

Finlay, Barbara L.; Darlington, Richard B.

doi:10.1126/science.7777856

Cited by 1,074 publications

(1,127 citation statements)

References 71 publications

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“…99 Several studies have also shown that total brain volume is a significant predictor of subcortical volumes. 72,100,101 An important study by Bigler et al 102 revealed that hippocampal volumes corrected with whole brain volume rather than total intracranial volume provide greater specificity and sensitivity.…”

Section: Discussionmentioning

confidence: 99%

MR-based in vivo hippocampal volumetrics: 1. Review of methodologies currently employed

2004

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The advance of neuroimaging techniques has resulted in a burgeoning of studies reporting abnormalities in brain structure and function in a number of neuropsychiatric disorders. Measurement of hippocampal volume has developed as a useful tool in the study of neuropsychiatric disorders. We reviewed the literature and selected all English-language, human subject, data-driven papers on hippocampal volumetry, yielding a database of 423 records. From this database, the methodology of all original manual tracing protocols were studied. These protocols differed in a number of important factors for accurate hippocampal volume determination including magnetic field strength, the number of slices assessed and the thickness of slices, hippocampal orientation correction, volumetric correction, software used, inter-rater reliability, and anatomical boundaries of the hippocampus. The findings are discussed in relation to optimizing determination of hippocampal volume.

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Section: Discussionmentioning

confidence: 99%

MR-based in vivo hippocampal volumetrics: 1. Review of methodologies currently employed

2004

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“…According to Finlay and Darlington (1995), there is predictability, or linked regularities, between brain mass and the structures that make up that mass. For example, they demonstrate that several major subdivisions of the actual matter of the brain covary in specific proportions in relation to the overall mass of the brain.…”

Section: Order Specific Predictability Of Tvvs Across Mammalian Speciesmentioning

confidence: 99%

“…Although certain exceptions to this predictability have been noted (e.g., Kaas and Collins, 2001), as a general rule it is applicable across mammalian species as a whole. Finlay and Darlington (1995) and their subsequent studies (e.g., Finlay et al, 2001;Reep et al, 2007;Yopak et al, 2010) have not examined that part of the brain, the ventricles, which do not contribute to total brain mass. In this study, we found that the TVV, whereas strongly correlated with brain mass, showed this relationship far more strongly when a specific order was examined.…”

Section: Order Specific Predictability Of Tvvs Across Mammalian Speciesmentioning

confidence: 99%

“…Given the likelihood that there are significant correlations between brain mass and TVV (Finlay and Darlington, 1995), the current study aimed to analyse this previously published data in relation to newly calculated TVVs for African elephants. Although elephant ventricles are indeed absolutely large (Shoshani et al, 2006), the question of whether they are relatively large remains open.…”

Section: Introductionmentioning

confidence: 99%

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Volumetric Analysis of the African Elephant Ventricular System

Maskeo

Spocter

Haagensen

et al. 2011

The Anatomical Record

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This study used magnetic resonance imaging (MRI) to determine the volume of the ventricular system in the brain of three adult male African elephants (Loxodonta africana). The ventricular system of the elephant has a volume of $240 mL, an order of magnitude larger than that seen in the adult human. Despite this large size, allometric analysis indicates that the volume of the ventricles in the elephant is what one would expect for a mammal with an $5 kg brain. Interestingly, our comparison with other mammals revealed that primates appear to have small relative ventricular volumes, and that megachiropterans and microchiropterans follow different scaling rules when comparing ventricular volume to brain mass indicating separate phylogenetic histories. The current study provides context for one aspect of the elephant brain in the broader picture of mammalian brain evolution.

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“…Anatomical studies in rodents, nonhuman primates, and humans have established that genes are major determinants of overall brain size. [15][16][17][18] Most notable are studies on whole brain volume in monozygotic and dizygotic twin populations, showing that individual variation in brain structure is highly heritable (h 2 ¼ 0.9). 19,20 Furthermore, variation in dopaminergic candidate genes may be related to morphometric variation since dopaminergic function has been shown to influence brain structure and plasticity: For example, chronic exposure to antipsychotic medication is known to produce changes in neurotransmitter levels and receptor sensitivity in the cortex.…”

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confidence: 99%

Differential effects of DRD4 and DAT1 genotype on fronto-striatal gray matter volumes in a sample of subjects with attention deficit hyperactivity disorder, their unaffected siblings, and controls

et al. 2005

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Genetic influences on behavior are complex and, as such, the effect of any single gene is likely to be modest. Neuroimaging measures may serve as a biological intermediate phenotype to investigate the effect of genes on human behavior. In particular, it is possible to constrain investigations by prior knowledge of gene characteristics and by including samples of subjects where the distribution of phenotypic variance is both wide and under heritable influences. Here, we use this approach to show a dissociation between the effects of two dopamine genes that are differentially expressed in the brain. We show that the DAT1 gene, a gene expressed predominantly in the basal ganglia, preferentially influences caudate volume, whereas the DRD4 gene, a gene expressed predominantly in the prefrontal cortex, preferentially influences prefrontal gray matter volume in a sample of subjects including subjects with ADHD, their unaffected siblings, and healthy controls. This demonstrates that, by constraining our investigations by prior knowledge of gene expression, including samples in which the distribution of phenotypic variance is wide and under heritable influences, and by using intermediate phenotypes, such as neuroimaging, we may begin to map out the pathways by which genes influence behavior. Investigators interested in the effect of genes on behavior face a challenge in that behavior is complex, and is likely affected by multiple genes, as well as gene-gene and gene-environment interactions. As such, the effect of any single gene on behavior is probably only small. Indeed, studies investigating the effect of genotype on behavior have reported modest associations. For example, Fossella et al 1 described the influence of four genes related to dopamine function on measures of executive attention and report small effect sizes. Furthermore, their effects were subtle in that not all aspects of executive attention were affected and that genes had differential effects. 1

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Linked Regularities in the Development and Evolution of Mammalian Brains

Cited by 1,074 publications

References 71 publications

MR-based in vivo hippocampal volumetrics: 1. Review of methodologies currently employed

MR-based in vivo hippocampal volumetrics: 1. Review of methodologies currently employed

Volumetric Analysis of the African Elephant Ventricular System

Differential effects of DRD4 and DAT1 genotype on fronto-striatal gray matter volumes in a sample of subjects with attention deficit hyperactivity disorder, their unaffected siblings, and controls

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