The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index.
Cellular Scaling Rules for the Brains of Marsupials: Not as “Primitive” as Expected
Abstract
In the effort to understand the evolution of mammalian brains, we have found that common relationships between brain structure mass and numbers of nonneuronal (glial and vascular) cells apply across eutherian mammals, but brain structure mass scales differently with numbers of neurons across structures and across primate and nonprimate clades. This suggests that the ancestral scaling rules for mammalian brains are those shared by extant nonprimate eutherians - but do these scaling relationships apply to marsupials, a sister group to eutherians that diverged early in mammalian evolution? Here we examine the cellular composition of the brains of 10 species of marsupials. We show that brain structure mass scales with numbers of nonneuronal cells, and numbers of cerebellar neurons scale with numbers of cerebral cortical neurons, comparable to what we have found in eutherians. These shared scaling relationships are therefore indicative of mechanisms that have been conserved since the first therians. In contrast, while marsupials share with nonprimate eutherians the scaling of cerebral cortex mass with number of neurons, their cerebella have more neurons than nonprimate eutherian cerebella of a similar mass, and their rest of brain has fewer neurons than eutherian structures of a similar mass. Moreover, Australasian marsupials exhibit ratios of neurons in the cerebral cortex and cerebellum over the rest of the brain, comparable to artiodactyls and primates. Our results suggest that Australasian marsupials have diverged from the ancestral Theria neuronal scaling rules, and support the suggestion that the scaling of average neuronal cell size with increasing numbers of neurons varies in evolution independently of the allocation of neurons across structures.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Specification of Cerebral Cortical Areas
Rakic, P. (1988) · Science · doi:10.1126/science.3291116 · Cited by 3,127
NeuN, a neuronal specific nuclear protein in vertebratesxs
Mullen, R. J., Buck, C. R., & Smith, A. M. (1992) · Development · doi:10.1242/dev.116.1.201 · Cited by 2,351
Azevedo, F. A. C., Carvalho, L. R. B., Grinberg, L. T., Farfel, J. M., Ferretti, R. E. L., Leite, R. E. P., Filho, W. J., Lent, R., & Herculano‐Houzel, S. (2009) · Journal of Comparative Neurology · doi:10.1002/cne.21974 · Cited by 2,337
Self-citationThe delayed rise of present-day mammals
Bininda-Emonds, O. R. P., Cardillo, M., Jones, K. E., MacPhee, R. D. E., Beck, R. M. D., Grenyer, R., Price, S. A., Vos, R. A., Gittleman, J. L., & Purvis, A. (2007) · Nature · doi:10.1038/nature05634 · Cited by 2,082
Social intelligence, innovation, and enhanced brain size in primates
Reader, S. M., & Laland, K. N. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.062041299 · Cited by 1,126
Herculano‐Houzel, S. (2014) · Glia · doi:10.1002/glia.22683 · Cited by 731
Self-citationThe glial identity of neural stem cells
Doetsch, F. (2003) · Nature Neuroscience · doi:10.1038/nn1144 · Cited by 724
Andreasen, N. C., O'Leary, D. S., Cizadlo, T., Arndt, S., Rezai, K., Ponto, L. L., Watkins, G. L., & Hichwa, R. D. (1996) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.93.18.9985 · Cited by 625
Birds have primate-like numbers of neurons in the forebrain
Olkowicz, S., Kocourek, M., Lučan, R. K., Porteš, M., Fitch, W. T., Herculano-Houzel, S., & Němec, P. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1517131113 · Cited by 564 · cited 1×
“…[Mullen et al., 1992; Gittins and Harrison, 2004] and evolutionarily conserved enough that the same polyclonal antibody stains all nuclei with anatomical characteristics of neurons, and only those, not only in mammals but also in crocodiles [Ngwenya et al., 2016] and birds [Olkowicz et al., 2016].”
BackgroundSelf-citationEvolution of increased glia–neuron ratios in the human frontal cortex
Sherwood, C. C., Stimpson, C. D., Raghanti, M. A., Wildman, D. E., Uddin, M., Grossman, L. I., Goodman, M., Redmond, J. C., Bonar, C. J., Erwin, J. M., et al. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0605843103 · Cited by 342
Self-citationA quantitative study of the human cerebellum with unbiased stereological techniques
Andersen, B. B., Korbo, L., & Pakkenberg, B. (1992) · Journal of Comparative Neurology · doi:10.1002/cne.903260405 · Cited by 276
Cell number and cell density in the cerebellar cortex of man and some other mammals
Lange, W. (1975) · Cell and Tissue Research · doi:10.1007/bf00223234 · Cited by 171
Specializations of the granular prefrontal cortex of primates: Implications for cognitive processing
Elston, G. N., Benavides‐Piccione, R., Elston, A., Zietsch, B., Defelipe, J., Manger, P., Casagrande, V., & Kaas, J. H. (2006) · The Anatomical Record Part A: Discoveries in Molecular, Cellular, and Evolutionary Biology · doi:10.1002/ar.a.20278 · Cited by 167
Self-citationCell counts in the primate cerebral cortex
Shariff, G. A. (1953) · Journal of Comparative Neurology · doi:10.1002/cne.900980302 · Cited by 163
Cellular Scaling Rules for the Brains of an Extended Number of Primate Species
Gabi, M., Collins, C. E., Wong, P., Torres, L. B., Kaas, J. H., & Herculano-Houzel, S. (2010) · Brain, Behavior and Evolution · doi:10.1159/000319872 · Cited by 102
Self-citationActivity of Acetylcholine System in Cerebral Cortex of Various Unanesthetized Mammals
Tower, D. B., & Elliott, K. A. C. (1952) · American Journal of Physiology-Legacy Content · doi:10.1152/ajplegacy.1952.168.3.747 · Cited by 100
Glia:Neuron index: Review and hypothesis to account for different values in various mammals.
Reichenbach, A. (1989) · Glia · doi:10.1002/glia.440020202 · Cited by 97
Cellular scaling rules of insectivore brains.
Sarko, D. (2009) · Frontiers in Neuroanatomy · doi:10.3389/neuro.05.008.2009 · Cited by 92
Scaling laws in the mammalian neocortex: Does form provide clues to function?
Harrison, K. H., Hof, P. R., & Wang, S. S.-H. (2002) · Journal of Neurocytology · doi:10.1023/a:1024178127195 · Cited by 78
Stolzenburg, J., Reichenbach, A., & Neumann, M. (1989) · Glia · doi:10.1002/glia.440020203 · Cited by 66
Neocortex in early mammals and its subsequent variations
Kaas, J. H. (2011) · Annals of the New York Academy of Sciences · doi:10.1111/j.1749-6632.2011.05981.x · Cited by 64 · cited 1×
“…argued that the Cx of American marsupial species may reflect the size, gross anatomy, and connectivity of the early mammalian cortex [Kemp, 2004; Kaas, 2011a, b], Ashwell [2008] showed that encephalization levels of Australasian species are comparable to those of eutherian mammals and even…”
Background
Cited by
The WU-Minn Human Connectome Project: An overview
Van Essen, D. C., Smith, S. M., Barch, D. M., Behrens, T. E. J., Yacoub, E., & Ugurbil, K. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.05.041 · Cited by 5,651
Revised Estimates for the Number of Human and Bacteria Cells in the Body
Sender, R., Fuchs, S., & Milo, R. (2016) · PLOS Biology · doi:10.1371/journal.pbio.1002533 · Cited by 5,425
23andMe Research Team, Lee, J. J., COGENT (Cognitive Genomics Consortium), Social Science Genetic Association Consortium, Wedow, R., Okbay, A., Kong, E., Maghzian, O., Zacher, M., Nguyen-Viet, T. A., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0147-3 · Cited by 2,470
The Human Connectome Project: A data acquisition perspective
Van Essen, D. C., Ugurbil, K., Auerbach, E., Barch, D., Behrens, T. E. J., Bucholz, R., Chang, A., Chen, L., Corbetta, M., Curtiss, S. W., et al. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.02.018 · Cited by 2,680
Conserved cell types with divergent features in human versus mouse cortex
Hodge, R. D., Bakken, T. E., Miller, J. A., Smith, K. A., Barkan, E. R., Graybuck, L. T., Close, J. L., Long, B., Johansen, N., Penn, O., et al. (2019) · Nature · doi:10.1038/s41586-019-1506-7 · Cited by 1,775
Metadata
- Authors
- Dos Santos, S. E., Porfirio, J., da Cunha, F. B., Manger, P. R., Tavares, W., Pessoa, L., Raghanti, M. A., Sherwood, C. C., & Herculano-Houzel, S.
- Venue
- Brain, Behavior and Evolution
- Publisher
- S. Karger AG
- Published
- 2017
- Volume
- 89
- Issue
- 1
- Pages
- 48-63
- ISSN
- 0006-8977 (ISSN-L)
- 1421-9743
- OpenAlex
- W2581259096
- Cited by
- 2,642
- References
- 21
- FWCI
- 144.48
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.