Parcellation and Area-Area Connectivity as a Function of Neocortex Size

Changizi, Mark A.; Shimojo, Shinsuke

doi:10.1159/000085942

Cited by 79 publications

(76 citation statements)

References 130 publications

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“…This variation is in sharp contrast to the claim by Rockel et al that the cortex is a uniform structure across mammalian species, built with a constant number of neurons Ͻ1 mm 2 of cortical surface (10), a claim that is widely used to support models of cortical connectivity (15,16) and developmental theories of cortical evolution that assume that cortex increases or decreases in size by adding or subtracting columnar units of modules of a fixed number of neurons (7).…”

Section: Discussionmentioning

confidence: 77%

“…The notion of numerical uniformity, although supported by data obtained through light microscopy analysis in the mouse (11), has since been disputed by separate research studies within (12,13) and across mammalian orders (14). Despite the evidence to the contrary, most models of cortical evolution and connectivity still assume that cortical columns hold a constant number of neurons across species (7,8,15,16).…”

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confidence: 99%

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The basic nonuniformity of the cerebral cortex

Herculano‐Houzel

Collins²,

Wong³

et al. 2008

Proc. Natl. Acad. Sci. U.S.A.

149

129

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These results have since been either corroborated or disputed by different groups. Here, we show that the number of neurons underneath 1 mm 2 of the cerebral cortical surface of nine primate species and the closely related Tupaia sp. is not constant and varies by three times across species. We found that cortical thickness is not inversely proportional to neuronal density across species and that total cortical surface area increases more slowly than, rather than linearly with, the number of neurons underneath it. The number of neurons beneath a unit area of cortical surface varies linearly with neuronal density, a parameter that is neither related to cortical size nor total number of neurons. Our finding of a variable number of neurons underneath a unit area of the cerebral cortex across primate species indicates that models of cortical organization cannot assume that cortical columns in different primates consist of invariant numbers of neurons.allometry ͉ brain size ͉ primates ͉ number of neurons ͉ cortical surface

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Section: Discussionmentioning

confidence: 77%

mentioning

confidence: 99%

The basic nonuniformity of the cerebral cortex

Herculano‐Houzel

Collins²,

Wong³

et al. 2008

Proc. Natl. Acad. Sci. U.S.A.

149

129

View full text Add to dashboard Cite

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“…An explanation for neocortical scaling concerns the economical manner in which neocortex compartmentalizes as the brain enlarges, and has been successful in predicting the number of cortical areas, interarea connectivity, and intra-area connectivity scale with brain size [1,2,[18][19][20]. Cities compartmentalize as well.…”

Section: City ''Ring Region'' Compartments and Cortical Areasmentioning

confidence: 99%

“…Too few compartments in a city will tend to be uneconomical because within-compartment travel will become too costly, and too many compartments will tend to be uneconomical because (given that each compartment will tend to require a highway route to all the other areas) of unnecessarily high highway costs. For neocortex, this tradeoff leads to the compartments increasing approximately as the 3/8 power of total convoluted surface area [1,18]. For cities it is not yet clear to us how to measure compartmentalization.…”

Section: City ''Ring Region'' Compartments and Cortical Areasmentioning

confidence: 99%

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Common scaling laws for city highway systems and the mammalian neocortex

Changizi

Destefano

2009

Complexity

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A variety of scaling laws are known for the mammalian neocortex relating gray matter volume, total number of synapses [1,2], white matter volume [3][4][5][6][7][8][9], number of neurons [6,[10][11][12], surface area [4,5,[13][14][15][16], axon caliber [1,17], and number of cortical areas or compartments [18]. These neocortical scaling laws appear to be a consequence of selection pressure for a sheet-like structure (namely, gray matter) to economically maintain a high level of interconnectedness [1,2,19,20]. We might therefore expect to find similar scaling laws for any sheetlike structure under similar selection pressures, in which case the neocortex would be just an instance of a more general kind of structure.Here, we investigate city highway systems as a potential kind of network which may be driven by similar principles as the neocortex. In contrast to neurons, which are conduits for information-related signals on which brain computations rely, highways are conduits for physical materials and people. But from the perspective of the city as a whole, the materials and people that highways transport are crucial to the large-scale function carried out by the city, and are, in a sense, signals-that one signal is electric and the other physical may not matter in regards to the fundamental principles governing them. In addition to the prima facie analogy between city highway networks and the brain's neural connections, there are several other reasons we chose to examine city highway networks. First, the organization of city highway networks tends to be driven by political and economic forces over decades, rather than being planned in advanced following known principles of highway engineering [21]-i.e., city highways systems are a result of an evolution-like mechanism. Second, cities are under selection pressure to efficiently interconnect via highways and roads. Third, because cities lie on the land they are approximately a surface, or a sheet. Fourth, highway network data are readily available (and our data set consists of 60 U.S. cities varying in population from 10 4 to nearly 10 7 , see Table 2 for raw data). Finally, the organization of city highway systems is interesting in and of itself: nearly half of Earth's 6.6 billion people now live in cities, and cities are becoming ever larger and densely populated. The proper functioning of a city requires that people and materials be quickly moved throughout it. This is a very difficult design problem, one that is magnified by the fact that city population tends to grow much faster than city surface area, and cities tend to increase in population over time, so that the efficient highway network must constantly evolve from the pre-existing one. Identification of scaling laws governing how highway organization scales with city size could potentially lead to better highway systems, and more efficiently running cities.

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Social Learning, Intelligence, and Brain Evolution

Street¹,

Laland²

2016

The Wiley Handbook of Evolutionary Neuroscience

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Parcellation and Area-Area Connectivity as a Function of Neocortex Size

Cited by 79 publications

References 130 publications

The basic nonuniformity of the cerebral cortex

The basic nonuniformity of the cerebral cortex

Common scaling laws for city highway systems and the mammalian neocortex

Social Learning, Intelligence, and Brain Evolution

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