Comparisons between Brains of a Large and a Small Hystricomorph Rodent: Capybara, &lt;i&gt;Hydrochoerus &lt;/i&gt;and Guinea Pig, &lt;i&gt;Cavia&lt;/i&gt;;Neocortical Projection Regions and Measurements of Brain Subdivisions

It is known that the white matter of neocortex increases disproportionately with brain size. However, relatively few measurements have been made of white matter/gray matter scaling in the cerebellum. We present data on the volumes of white and gray matter in both structures, taken from 45 species of mammals. We find a scaling exponent of 1.13 for cerebellum and 1.28 for neocortex. The 95% confidence intervals for our estimates of these two exponents do not overlap. This difference likely reflects differences in the connectivity and/or micro-structure of white matter in the two regions.

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“…All were embedded in celloidin, sectioned exhaustively, and stained with thionin. For more details see for example Campos and Welker [1976].…”

Section: Methodsmentioning

confidence: 99%

The Scaling of White Matter to Gray Matter in Cerebellum and Neocortex

Bush

Allman²

2003

Brain Behav Evol

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“…The interspersed organization found in Glires constitutes a distinct design type also insensitive to V1 size. Orientation columns so far have only been found in large visual areas and may not exist in very (3,4,10,14,15)] (E) Mesozoic and cenozoic macroevolution of extant mammals showing divergence into six major clades: Monotremes, Marsupials, Afrotheria, Xenarthra, Laurasiatheria, and Euarchontoglires, which split into Euarchonta and Glires (11). Eutherian size expansion after the K-T extinction event is indicated on top.…”

mentioning

confidence: 99%

Response to Comment on “Universality in the Evolution of Orientation Columns in the Visual Cortex“

Keil

Kaschube

Schnabel

et al. 2012

Science

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Meng et al. conjecture that pinwheel density scales with body and brain size. Our data, spanning a 40-fold range of body sizes in Laurasiatheria and Euarchonta, do not support this conclusion. The noncolumnar layout in Glires also appears size-insensitive. Thus, body and brain size may be understood as a constraint on the evolution of visual cortical circuitry, but not as a determining factor. W e presented a comparative study of visual cortical orientation columns and pinwheels in three mammalian species whose evolutionary paths separated more than 65 million years ago (1). For this purpose, we introduced methods to measure pinwheel density objectively-i.e., insensitive of image data preprocessing [(1) and supporting online material (SOM) of (1), pp. 3-12 and 29-41]. We found that statistical measures characterizing the spatial layout of pinwheels from the scale of individual hypercolumns to the entire primary visual cortex (V1) were virtually identical, agreeing with an accuracy of a few percent. To understand how distinct evolutionary lineages can independently evolve this common design, we examined a broad set of mathematical models for the developmental self-organization of orientation columns [(1) and SOM of (1), pp. 13-62]. We found that models from a symmetry-defined class, exhibiting a universal (i.e., model-independent) solution set, robustly predict every aspect of the common design when suppressive long-range interactions are dominant [(1) and SOM of (1), pp. 13-41)]. This suggests that developmental network self-organization has canalized the evolution of neuronal circuitry underlying orientation maps in these species into the common design. A predicted signature of this mechanism is a pinwheel density close to the mathematical constant p. Confirming this prediction, we found that mean pinwheel density was indeed statistically indistinguishable from p (T2%).Meng et al. claim that pinwheel density is not an invariant but a function of V1 size (2). They conjecture a pinwheel density scaling law that can be approximated by , and 450 mm 2 V1 size, respectively (3, 4), pinwheel density in cats (galagos) should be 53% (28%) larger than in ferrets/tupaias. Our methods to accurately estimate pinwheel density are well suited to test this prediction. Figure 1A presents measured pinwheel densities for the four species graphed against body weight. Pinwheel densities appear invariant with respect to body weight. The hypothesis that mean pinwheel density in cat (galago) is more than 50% (20%) larger than in ferrets can be rejected with virtual certainty [P < 0.0001(0.0001), bootstrap test]. Meng et al. suggest greater variation in pinwheel density across species; however, those data were derived from studies with small sample sizes using first-generation optical imaging methods that are subject to various systematic errors described in detail in [SOM of (1),. Our analysis unambiguously indicates that pinwheel density is a genuine invariant feature of orientation column layout over a wide range of V1 sizes and th...

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“…Kawamura [1971] has re cently published an analysis of the fissural patterns of the neocortices of 89 domestic cats, which should be of use to investigators of feline neocortical functioning. Variations in the fissural patterns of the capybara [Campos and Welker, 1976], llama , and rock hyrax [Welker and Carlson, 1976] have also been depicted. The present study has revealed a wide variability in the fissural patterns of primate brain specimens and a correlation, at least in some instances, between atypical fissural patterns and functional subdivisions of the cortex.…”

Section: Discussionmentioning

confidence: 90%

Variations in the Fissural Pattern of the Cerebral Neocortex of the Spider Monkey <i>(Ateles)</i>

Pubols¹,

Pubols²

1979

Brain Behav Evol

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Data are reported on the range and variety of fissural patterning in 40 cerebral hemispheres from 22 specimens of spider monkeys (Ateles). The hemispheres are categorized according to a number of criteria, including proximity of the central sulcus to neighboring sulci, whether certain other sulci are joined or separated from each other, and the presence and location of idiosyncratic fissures. Interhemispheric variability was found to be as pronounced within as between specimens. The study revealed a wide variability in fissural patterns of primate brain specimens and a topological significance of many sulci in that they demarcate functional subdivisions of either somatosensory or somatomotor cortex.

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Comparisons between Brains of a Large and a Small Hystricomorph Rodent: Capybara, <i>Hydrochoerus </i>and Guinea Pig, <i>Cavia</i>;Neocortical Projection Regions and Measurements of Brain Subdivisions

Cited by 69 publications

References 7 publications

The Scaling of White Matter to Gray Matter in Cerebellum and Neocortex

The Scaling of White Matter to Gray Matter in Cerebellum and Neocortex

Response to Comment on “Universality in the Evolution of Orientation Columns in the Visual Cortex“

Variations in the Fissural Pattern of the Cerebral Neocortex of the Spider Monkey <i>(Ateles)</i>

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