Zhang K, Sejnowski TJA universal scaling law between gray matter and white matter of cerebral cortex. Proc Natl Acad Sci USA 97:5621-5626

Howard Hughes Medical Institute, Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, 10010 North Torrey Pines Road, La Jolla, California 92037, USA.
Proceedings of the National Academy of Sciences (Impact Factor: 9.81). 06/2000; 97(10):5621-6. DOI: 10.1073/pnas.090504197
Source: PubMed

ABSTRACT Neocortex, a new and rapidly evolving brain structure in mammals, has a similar layered architecture in species over a wide range of brain sizes. Larger brains require longer fibers to communicate between distant cortical areas; the volume of the white matter that contains long axons increases disproportionally faster than the volume of the gray matter that contains cell bodies, dendrites, and axons for local information processing, according to a power law. The theoretical analysis presented here shows how this remarkable anatomical regularity might arise naturally as a consequence of the local uniformity of the cortex and the requirement for compact arrangement of long axonal fibers. The predicted power law with an exponent of 4/3 minus a small correction for the thickness of the cortex accurately accounts for empirical data spanning several orders of magnitude in brain sizes for various mammalian species, including human and nonhuman primates.

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Available from: Terrence Sejnowski, Jan 01, 2015
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    • ", 2014 ) . Morphological anomalies described in ASD infants have been proposed as a correlate of the atypical organization of brain con - nectivity ( Zhang and Sejnowski , 2000 ; Lewis and Elman , 2008 ) . Indeed , the first years of postnatal life represent a crucial time period of brain development characterized in typical develop - ment by both axonal pruning and synaptogenesis to build up and strengthen cortical networks . "
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    ABSTRACT: There is overwhelming evidence that autism spectrum disorder (ASD) is related to altered brain connectivity. While these alterations are starting to be well characterized in subjects where the clinical picture is fully expressed, less is known on their earlier developmental course. In the present study we systematically reviewed current knowledge on structural connectivity in ASD infants and toddlers. We searched PubMed and Medline databases for all English language papers, published from year 2000, exploring structural connectivity in populations of infants and toddlers whose mean age was below 30 months. Of the 264 papers extracted, four were found to be eligible and were reviewed. Three of the four selected studies reported higher fractional anisotropy values in subjects with ASD compared to controls within commissural fibers, projections fibers, and association fibers, suggesting brain hyper-connectivity in the earliest phases of the disorder. Similar conclusions emerged from the other diffusion parameters assessed. These findings are reversed to what is generally found in studies exploring older patient groups and suggest a developmental course characterized by a shift toward hypo-connectivity starting at a time between two and four years of age.
    Frontiers in Human Neuroscience 04/2015; 9. DOI:10.3389/fnhum.2015.00159 · 2.90 Impact Factor
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    • "cortical scaling across mammalian species (Zhang and Sejnowski, 2000) may not apply to cortical scaling within a species, e.g., within humans (Peters et al., 1998; Im et al., 2008). Therefore, in the context of the present study we aimed at revealing how the disproportionally increased WM is distributed within the cortex in larger compared with smaller human brains. "
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    ABSTRACT: Twenty years ago, Ringo and colleagues proposed that maintaining absolute connectivity in larger compared with smaller brains is computationally inefficient due to increased conduction delays in transcallosal information transfer and expensive with respect to the brain mass needed to establish these additional connections. Therefore, they postulated that larger brains are relatively stronger connected intrahemispherically and smaller brains interhemispherically, resulting in stronger functional lateralization in larger brains. We investigated neuronal interconnections in 138 large and small human brains using diffusion tensor imaging-based fiber tractography. We found a significant interaction between brain size and the type of connectivity. Structural intrahemispheric connectivity is stronger in larger brains, whereas interhemispheric connectivity is only marginally increased in larger compared with smaller brains. Although brain size and gender are confounded, this effect is gender-independent. Additionally, the ratio of interhemispheric to intrahemispheric connectivity correlates inversely with brain size. The hypothesis of neuronal interconnectivity as a function of brain size might account for shorter and more symmetrical interhemispheric transfer times in women and for empirical evidence that visual and auditory processing are stronger lateralized in men. The hypothesis additionally shows that differences in interhemispheric and intrahemispheric connectivity are driven by brain size and not by gender, a finding contradicting a recently published study. Our findings are also compatible with the idea that the more asymmetric a region is, the smaller the density of interhemispheric connections, but the larger the density of intrahemispheric connections. The hypothesis represents an organization principle of the human connectome that might be applied also to non-human animals as suggested by our cross-species comparison.
    Frontiers in Human Neuroscience 11/2014; 8. DOI:10.3389/fnhum.2014.00915 · 2.90 Impact Factor
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    • "In animal tracing studies, cortical structural characteristics including thickness, folding and neuronal density have predicted anatomical connections between cortical regions [Barbas and Rempel-Clower, 1997; Dombrowski et al., 2001]. Although the mechanism of this coordinated structural network is unknown, it has been attributed to mutually trophic [Pezawas et al., 2004], developmental [Bush and Allman, 2003; Zhang and Sejnowski, 2000] and experience-related plasticity [Draganski et al., 2004]. "
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    ABSTRACT: Recent neuroimaging and behavioral studies have revealed that children with new onset epilepsy already exhibit brain structural abnormalities and cognitive impairment. How the organization of large-scale brain structural networks is altered near the time of seizure onset and whether network changes are related to cognitive performances remain unclear. Recent studies also suggest that regional brain volume covariance reflects synchronized brain developmental changes. Here, we test the hypothesis that epilepsy during early-life is associated with abnormalities in brain network organization and cognition. We used graph theory to study structural brain networks based on regional volume covariance in 39 children with new-onset seizures and 28 healthy controls. Children with new-onset epilepsy showed a suboptimal topological structural organization with enhanced network segregation and reduced global integration compared with controls. At the regional level, structural reorganization was evident with redistributed nodes from the posterior to more anterior head regions. The epileptic brain network was more vulnerable to targeted but not random attacks. Finally, a subgroup of children with epilepsy, namely those with lower IQ and poorer executive function, had a reduced balance between network segregation and integration. Taken together, the findings suggest that the neurodevelopmental impact of new onset childhood epilepsies alters large-scale brain networks, resulting in greater vulnerability to network failure and cognitive impairment. Hum Brain Mapp, 2014. © 2014 Wiley Periodicals, Inc.
    Human Brain Mapping 08/2014; 35(8). DOI:10.1002/hbm.22428 · 6.92 Impact Factor
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