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      Modular structure facilitates mosaic evolution of the brain in chimpanzees and humans

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          Abstract

          Different brain components can evolve in a coordinated fashion or they can show divergent evolutionary trajectories according to a mosaic pattern of variation. Understanding the relationship between these brain evolutionary patterns, which are not mutually exclusive, can be informed by the examination of intraspecific variation. Our study evaluates patterns of brain anatomical covariation in chimpanzees and humans to infer their influence on brain evolution in the hominin clade. We show that chimpanzee and human brains have a modular structure that may have facilitated mosaic evolution from their last common ancestor. Spatially adjacent regions covary with one another to the strongest degree and separated regions are more independent from each other, which might be related to a predominance of local association connectivity. Despite the undoubted importance of developmental and functional factors in determining brain morphology, we find that these constraints are subordinate to the primary effect of local spatial interactions.

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          Most cited references63

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          A tension-based theory of morphogenesis and compact wiring in the central nervous system.

          Many structural features of the mammalian central nervous system can be explained by a morphogenetic mechanism that involves mechanical tension along axons, dendrites and glial processes. In the cerebral cortex, for example, tension along axons in the white matter can explain how and why the cortex folds in a characteristic species-specific pattern. In the cerebellum, tension along parallel fibres can explain why the cortex is highly elongated but folded like an accordion. By keeping the aggregate length of axonal and dendritic wiring low, tension should contribute to the compactness of neural circuitry throughout the adult brain.
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            Individual variability in functional connectivity architecture of the human brain.

            The fact that people think or behave differently from one another is rooted in individual differences in brain anatomy and connectivity. Here, we used repeated-measurement resting-state functional MRI to explore intersubject variability in connectivity. Individual differences in functional connectivity were heterogeneous across the cortex, with significantly higher variability in heteromodal association cortex and lower variability in unimodal cortices. Intersubject variability in connectivity was significantly correlated with the degree of evolutionary cortical expansion, suggesting a potential evolutionary root of functional variability. The connectivity variability was also related to variability in sulcal depth but not cortical thickness, positively correlated with the degree of long-range connectivity but negatively correlated with local connectivity. A meta-analysis further revealed that regions predicting individual differences in cognitive domains are predominantly located in regions of high connectivity variability. Our findings have potential implications for understanding brain evolution and development, guiding intervention, and interpreting statistical maps in neuroimaging. Copyright © 2013 Elsevier Inc. All rights reserved.
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              Open Access Series of Imaging Studies (OASIS): cross-sectional MRI data in young, middle aged, nondemented, and demented older adults.

              The Open Access Series of Imaging Studies is a series of magnetic resonance imaging data sets that is publicly available for study and analysis. The initial data set consists of a cross-sectional collection of 416 subjects aged 18 to 96 years. One hundred of the included subjects older than 60 years have been clinically diagnosed with very mild to moderate Alzheimer's disease. The subjects are all right-handed and include both men and women. For each subject, three or four individual T1-weighted magnetic resonance imaging scans obtained in single imaging sessions are included. Multiple within-session acquisitions provide extremely high contrast-to-noise ratio, making the data amenable to a wide range of analytic approaches including automated computational analysis. Additionally, a reliability data set is included containing 20 subjects without dementia imaged on a subsequent visit within 90 days of their initial session. Automated calculation of whole-brain volume and estimated total intracranial volume are presented to demonstrate use of the data for measuring differences associated with normal aging and Alzheimer's disease.
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                Author and article information

                Journal
                101528555
                37539
                Nat Commun
                Nat Commun
                Nature communications
                2041-1723
                25 June 2014
                22 July 2014
                2014
                22 January 2015
                : 5
                : 4469
                Affiliations
                [1 ]Department of Anthropology, The George Washington University, Washington, DC 20052
                [2 ]Neuroscience Institute, Georgia State University, Atlanta, GA 30302
                [3 ]Division of Developmental and Cognitive Neuroscience, Yerkes National Primate Research Center, Atlanta, GA 30322
                Author notes
                [* ]Corresponding author: Aida Gómez-Robles, aidagomezr@ 123456yahoo.es
                Article
                NIHMS607089
                10.1038/ncomms5469
                4144426
                25047085
                ef52d512-8275-404b-84ed-ca8dc924d79a
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