: Cellular scaling rules for rodent brains.
Open accessAbstract
How do cell number and size determine brain size? Here, we show that, in the order Rodentia, increased size of the cerebral cortex, cerebellum, and remaining areas across six species is achieved through greater numbers of neurons of larger size, and much greater numbers of nonneuronal cells of roughly invariant size, such that the ratio between total neuronal and nonneuronal mass remains constant across species. Although relative cerebellar size remains stable among rodents, the number of cerebellar neurons increases with brain size more rapidly than in the cortex, such that the cerebellar fraction of total brain neurons increases with brain size. In contrast, although the relative cortical size increases with total brain size, the cortical fraction of total brain neurons remains constant. We propose that the faster increase in average neuronal size in the cerebral cortex than in the cerebellum as these structures gain neurons and the rapidly increasing glial numbers that generate glial mass to match total neuronal mass at a fixed glia/neuron total mass ratio are fundamental cellular constraints that lead to the relative expansion of cerebral cortical volume across species.
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
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.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cerebral cortex varies in relative size from 42% in the mouse to 82% in the human, but contains between 13 and 28% of all brain neurons in 15 of 18 species studied, ranging from 13% in moles to 41% in the squirrel monkey.
“the cerebral cortex, despite varying in relative size from 42% (in the mouse) to 82% of brain mass (in the human), contains between 13 and 28% of all brain neurons in 15 of 18 species studied, ranging between 13% (in moles) and 41% (in the squirrel monkey; Herculano-Houzel et al., 2006, 2007; Sarko et al., 2009).”
From The human brain in numbers: a linearly scaled-up primate brain (2009) · cites this paper as Herculano-Houzel et al., 2006
The Results (page not provided) report that cortical mass increases with brain size while the cortex contains a relatively stable 17.8 ± 3.4% of brain neurons across six rodent species. This supports the general pattern, but the paper does not establish the quoted 42%–82% mass range or the neuron percentages across 18 species, including humans, moles, and squirrel monkeys. (LLM, conf=0.88)
Experimental — accuracy not yet measuredIn mammals, the pallium accounts for most of total brain volume, but the cerebellum houses a large majority of brain neurons.
“This markedly contrasts with the situation found in mammals, in which the pallium accounts for most of total brain volume, but the cerebellum houses a large majority of brain neurons (32–39)”
From Birds have primate-like numbers of neurons in the forebrain (2016) · cites this paper as [32]
The Results report that the cerebellum contains 59.0%–72.4% of brain neurons in the six rodent species studied, while the cerebral cortex becomes the dominant structure by volume as brain size increases. The source does not establish that the pallium occupies most brain volume across mammals generally, or even across all six rodents. The indexed passages have section labels but no page numbers. (LLM, conf=0.86)
Experimental — accuracy not yet measuredLike in mammals, the proportion of nonneuronal cells is very small in the cerebellum, varying between 12% and 19% in songbirds and between 14% and 19% in parrots, but, in contrast to mammals, nonneuronal cells also constitute a minor cellular fraction in the telencephalon, representing 21-40% of cells in songbirds and 31-43% of cells in parrots.
“Like in mammals (32–39, 46), the proportion of nonneuronal cells is very small in the cerebellum, varying between 12% and 19% in songbirds and between 14% and 19% in parrots, but, in contrast to mammals, nonneuronal cells also constitute a minor cellular fraction in the telencephalon, representing 21–40% of cells in songbirds and 31–43% of cells in parrots”
From Birds have primate-like numbers of neurons in the forebrain (2016) · cites this paper as [32]
Split into 2 atoms — 0 confirmed, 2 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.
Experimental — accuracy not yet measuredIn Rodentia, brain size increases faster than neuron number, with neuronal density decreasing; with constant non-neuronal density, this implies average neuronal size increases rapidly as neurons become more numerous.
“In the order Rodentia, we find that the brain increases in size faster than it gains neurons, with a decrease in neuronal densities which, in the presence of constant non-neuronal cell densities, implies that average neuronal size increases rapidly as neurons become more numerous (Herculano-Houzel et al., 2006).”
From The human brain in numbers: a linearly scaled-up primate brain (2009) · cites this paper as Herculano-Houzel et al., 2006
The HiAER-Spike system capacity is roughly twice the neurons of a mouse brain and runs at faster than real time.
“In this work, we present HiAER-Spike, a modular, recon fi gurable, event-driven neuromorphic computing platform designed to execute large spiking neural networks with up to 160 million neurons and 40 billion synapses - roughly twice the neurons of a mouse brain at faster than real time.”
From HiAER-spike software-hardware reconfigurable platform for event-driven neuromorphic computing at scale (2026) · cites this paper as [9]
Non-neuronal cell density is remarkably constant across these species.
“Given that non-neuronal cell density is remarkably constant across these species [24], [25]”
From Scaling of Brain Metabolism with a Fixed Energy Budget per Neuron: Implications for Neuronal Activity, Plasticity and Evolution (2011) · cites this paper as [24]
There is no uniform scaling of neuronal density with brain size.
“However, it has now been demonstrated that there is no uniform scaling of neuronal density with brain size [24], [25], [41], which invalidates the previous estimate”
From Scaling of Brain Metabolism with a Fixed Energy Budget per Neuron: Implications for Neuronal Activity, Plasticity and Evolution (2011) · cites this paper as [24]
Brain metabolism is not necessarily related to whole body metabolism in any determining way; any apparent relationship might be coincidental and dependent on the rate with which brain size scales as a function of its number of neurons.
“the scaling of brain metabolism as a function of total numbers of neurons opens the possibility that brain metabolism is not necessarily related to whole body metabolism in any determining way; any apparent relationship might be coincidental, and dependent on the rate with which brain size scales as a function of its number of neurons, which we have shown to vary across mammalian orders [24], [25]”
From Scaling of Brain Metabolism with a Fixed Energy Budget per Neuron: Implications for Neuronal Activity, Plasticity and Evolution (2011) · cites this paper as [24]
Mammals whose brain scales with economical neuronal scaling rules, such as primates, have a large number of brain neurons for a given body size and would be expected to have a larger relative brain metabolic rate than other mammals, such as rodents, which have a smaller number of brain neurons for a same body or brain size.
“In this way, mammals whose brain scales with economical neuronal scaling rules, such as primates, have a large number of brain neurons for a given body size, and would accordingly be expected to have a larger relative brain metabolic rate than other mammals, such as rodents, which have a smaller number of brain neurons for a same body or brain size [24], [25].”
From Scaling of Brain Metabolism with a Fixed Energy Budget per Neuron: Implications for Neuronal Activity, Plasticity and Evolution (2011) · cites this paper as [24]
The previous estimate that average energy use per neuron increases with brain size is invalidated.
“However, it has now been demonstrated that there is no uniform scaling of neuronal density with brain size [24], [25], [41], which invalidates the previous estimate”
From Scaling of Brain Metabolism with a Fixed Energy Budget per Neuron: Implications for Neuronal Activity, Plasticity and Evolution (2011) · cites this paper as [24]
The human brain's use of 20% of the whole body energy budget while representing only 2% of body mass can be explained by the large number of neurons in the human brain, about 10× larger than would be expected of a rodent brain of its size.
“According to the scaling of brain metabolism with its total number of neurons proposed above, the apparently remarkable use in humans of 20% of the whole body energy budget by a brain that represents only 2% of this mass can be explained quite simply by the large number of neurons in the human brain, about 10× larger than would be expected of a rodent brain of its size [44], given the different”
From Scaling of Brain Metabolism with a Fixed Energy Budget per Neuron: Implications for Neuronal Activity, Plasticity and Evolution (2011) · cites this paper as [24]
The glia/neuron ratio may be determined simply by the addition of glial cells of a relatively constant size to neuronal parenchyma consisting of small or large neurons during brain development.
“the glia/neuron ratio may be determined simply by the addition of glial cells of a relatively constant size to neuronal parenchyma consisting of small or large neurons during brain development [24], [43].”
From Scaling of Brain Metabolism with a Fixed Energy Budget per Neuron: Implications for Neuronal Activity, Plasticity and Evolution (2011) · cites this paper as [24]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
(1982) · Trends in Neurosciences · doi:10.1016/0166-2236(82)90076-5 · Cited by 9,148 · see citing works
Henry, M. A. (1995) · The Journal of the American Dental Association · doi:10.14219/jada.archive.1995.0108 · Cited by 3,454 · see citing works
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 · see citing works
NEURONAL CIRCUITS OF THE NEOCORTEX
Douglas, R. J., & Martin, K. A. C. (2004) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.27.070203.144152 · Cited by 1,886 · see citing works
Astrocytes, from brain glue to communication elements: the revolution continues
Volterra, A., & Meldolesi, J. (2005) · Nature reviews. Neuroscience · doi:10.1038/nrn1722 · Cited by 1,763 · see citing works
New roles for astrocytes: redefining the functional architecture of the brain.
Nedergaard, M., Ransom, B., & Goldman, S. A. (2003) · Trends in Neurosciences · doi:10.1016/j.tins.2003.08.008 · Cited by 1,334 · see citing works
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 · see citing works
Rakic, P. (1995) · Trends in Neurosciences · doi:10.1016/0166-2236(95)93934-p · Cited by 1,047 · see citing works
Big brains, enhanced cognition, and response of birds to novel environments
Sol, D., Duncan, R. P., Blackburn, T. M., Cassey, P., & Lefebvre, L. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0408145102 · Cited by 917 · see citing works
THE BASIC UNIFORMITY IN STRUCTURE OF THE NEOCORTEX
Röckel, A., Hiorns, R. W., & Powell, T. P. S. (1980) · Brain · doi:10.1093/brain/103.2.221 · Cited by 902 · see citing works
New and Revised Data on Volumes of Brain Structures in Insectivores and Primates
Stephan, H., Frahm, H. D., & Baron, G. (1981) · Folia Primatologica · doi:10.1159/000155963 · Cited by 877 · see citing works
The glial identity of neural stem cells
Doetsch, F. (2003) · Nature Neuroscience · doi:10.1038/nn1144 · Cited by 724 · see citing works
Relative brain size and basal metabolic rate in terrestrial vertebrates
Martin, R. D. (1981) · Nature · doi:10.1038/293057a0 · Cited by 711 · see citing works
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 · see citing works
Williams, R. W., & Herrup, K. (1988) · Annual Review of Neuroscience · doi:10.1146/annurev.ne.11.030188.002231 · Cited by 585 · see citing works
Herculano-Houzel, S., & Lent, R. (2005) · The Journal of Neuroscience · doi:10.1523/jneurosci.4526-04.2005 · Cited by 551 · see citing works
Self-citationThe human cerebro-cerebellar system: its computing, cognitive, and language skills
Leiner, H. C., Leiner, A. L., & Dow, R. S. (1991) · Behavioural Brain Research · doi:10.1016/s0166-4328(05)80016-6 · Cited by 495 · see citing works
Haug, H. (1987) · American Journal of Anatomy · doi:10.1002/aja.1001800203 · Cited by 481 · see citing works
Molecular mechanisms controlling cortical gliogenesis.
Sauvageot, C., & Stiles, C. (2002) · Current Opinion in Neurobiology · doi:10.1016/s0959-4388(02)00322-7 · Cited by 373 · see citing works
Signaling between glia and neurons: focus on synaptic plasticity
Allen, N. J., & Barres, B. A. (2005) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2005.08.006 · Cited by 321 · see citing works
Scalable architecture in mammalian brains
Clark, D. A., Mitra, P. P., & Wang, S. S.-H. (2001) · Nature · doi:10.1038/35075564 · Cited by 276 · see citing works
A 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 · see citing works
Animal intelligence as encephalization
Jerison, H. J. (1985) · Philosophical Transactions of the Royal Society of London. B, Biological Sciences · doi:10.1098/rstb.1985.0007 · Cited by 234 · see citing works
Tower, D. B. (1954) · Journal of Comparative Neurology · doi:10.1002/cne.901010103 · Cited by 203 · see citing works
Tower, D. B., & Young, O. M. (1973) · Journal of Neurochemistry · doi:10.1111/j.1471-4159.1973.tb12126.x · Cited by 189 · see citing works
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 · see citing works
Cell counts in the primate cerebral cortex
Shariff, G. A. (1953) · Journal of Comparative Neurology · doi:10.1002/cne.900980302 · Cited by 163 · see citing works
Comparison of brain structure volumes in Insectivora and Primates. I. Neocortex.
Frahm, H. D., Stephan, H., & Stephan, M. (1982) · PubMed · Cited by 157 · see citing works
Gittins, R., & Harrison, P. J. (2004) · Brain Research Bulletin · doi:10.1016/j.brainresbull.2004.02.005 · Cited by 155 · see citing works
Korbo, L., Andersen, B. B., Ladefoged, O., & Møller, A. (1993) · Brain Research · doi:10.1016/0006-8993(93)90881-m · Cited by 147 · see citing works
Astrocytes and NG2‐glia: what's in a name?
Nishiyama, A., Yang, Z., & Butt, A. M. (2005) · Journal of Anatomy · doi:10.1111/j.1469-7580.2005.00489.x · Cited by 126 · see citing works
Glia/Nerve Cell Index for Cortex of the Whale
Hawkins, A., & Olszewski, J. (1957) · Science · doi:10.1126/science.126.3263.76 · Cited by 104 · see citing works
Activity 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 · see citing works
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 · see citing works
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 · see citing works
Analysis of mammalian brain architecture
Sultan, F. R. (2002) · Nature · doi:10.1038/415133b · Cited by 77 · see citing works
Stolzenburg, J., Reichenbach, A., & Neumann, M. (1989) · Glia · doi:10.1002/glia.440020203 · Cited by 66 · see citing works
Allometry of Major CNS Divisions: Towards a Reevaluation of Somatic Brain-Body Scaling
Fox, J. H., & Wilczynski, W. (2008) · Brain Behavior and Evolution · doi:10.1159/000118700 · Cited by 64 · see citing works
Density-Dependent Feedback Inhibition of Oligodendrocyte Precursor Expansion
Zhang, H., & Miller, R. H. (1996) · Journal of Neuroscience · doi:10.1523/jneurosci.16-21-06886.1996 · Cited by 61 · see citing works
Korbo, L., & Andersen, B. B. (1995) · Neuroscience · doi:10.1016/0306-4522(95)00223-6 · Cited by 31 · see citing works
Barton, R. A. (2002) · Nature · doi:10.1038/415134a · Cited by 28 · see citing works
A novel splice mutation of HERG in a Chinese family with long QT syndrome
Shang, Y., Xie, X., Wang, X., et al. (2005) · Journal of Zhejiang University. Science A · doi:10.1631/jzus.2005.b0626 · Cited by 21 · see citing works
[Importance of standardization in the biological monitoring of anti-vitamin K therapy].
Forestier, F., Boneu, B., Potron, G., et al. (1986) · PubMed · Cited by 2 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- [9]Frahm H. D., Stephan H., Stephan M. J. Hirnforsch. 1982;23:375–389. [PubMed] [Google Scholar]
Cited by
Sorted by citations
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 · see citing works
Self-citationThe human brain in numbers: a linearly scaled-up primate brain
Herculano-Houzel, S. (2009) · Frontiers in Human Neuroscience · doi:10.3389/neuro.09.031.2009 · Cited by 1,778 · see citing works
“The increase in numbers of neurons in the cerebral cortex, cerebellum and remaining areas is concurrent with an even greater increase in numbers of non-neurons, yielding a maximal glia/neuron ratio that increases with brain size (Herculano-Houzel et al., 2006).”
InfluentialSelf-citationConserved 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 · see citing works
Herculano-Houzel, S. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1201895109 · Cited by 726 · see citing works
Self-citationMyelination and the trophic support of long axons
Nave, K.-A. (2010) · Nature Reviews Neuroscience · doi:10.1038/nrn2797 · Cited by 648 · see citing works
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 · see citing works
Self-citationThe Indispensable Roles of Microglia and Astrocytes during Brain Development
Reemst, K., Noctor, S. C., Lucassen, P. J., & Hol, E. M. (2016) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2016.00566 · Cited by 516 · see citing works
High-throughput mapping of single-neuron projections by sequencing of barcoded RNA
Kebschull, J. M., Garcia da Silva, P., Reid, A. P., Peikon, I. D., Albeanu, D. F., & Zador, A. M. (2016) · Neuron · doi:10.1016/j.neuron.2016.07.036 · Cited by 376 · see citing works
Cellular scaling rules for primate brains.
Herculano-Houzel, S., Collins, C. E., Wong, P., & Kaas, J. H. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0611396104 · Cited by 422 · see citing works
Self-citationHerculano-Houzel, S. (2011) · PLoS ONE · doi:10.1371/journal.pone.0017514 · Cited by 343 · see citing works
Self-citationThe effects of aerobic activity on brain structure.
Thomas, A. G., Dennis, A., Bandettini, P. A., & Johansen-Berg, H. (2012) · Frontiers in Psychology · doi:10.3389/fpsyg.2012.00086 · Cited by 303 · see citing works
Coordinated scaling of cortical and cerebellar numbers of neurons
Herculano-Houzel (2010) · Frontiers in Neuroanatomy · doi:10.3389/fnana.2010.00012 · Cited by 288 · see citing works
Hyder, F., Rothman, D. L., & Bennett, M. R. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1214912110 · Cited by 271 · see citing works
Evaluating the gray and white matter energy budgets of human brain function
Yu, Y., Herman, P., Rothman, D. L., Agarwal, D., & Hyder, F. (2018) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1177/0271678x17708691 · Cited by 211 · see citing works
Metabolic rate and body size are linked with perception of temporal information
Healy, K., McNally, L., Ruxton, G. D., Cooper, N., & Jackson, A. L. (2013) · Animal Behaviour · doi:10.1016/j.anbehav.2013.06.018 · Cited by 202 · see citing works
An atlas of gene regulatory elements in adult mouse cerebrum
Li, Y. E., Preissl, S., Hou, X., Zhang, Z., Zhang, K., Qiu, Y., Poirion, O. B., Li, B., Chiou, J., Liu, H., et al. (2021) · Nature · doi:10.1038/s41586-021-03604-1 · Cited by 185 · see citing works
Developmental mechanisms channeling cortical evolution
Finlay, B. L., & Uchiyama, R. (2015) · Trends in Neurosciences · doi:10.1016/j.tins.2014.11.004 · Cited by 163 · see citing works
Chronic Stress Weakens Connectivity in the Prefrontal Cortex: Architectural and Molecular Changes.
Woo, E., Sansing, L. H., Arnsten, A. F. T., & Datta, D. (2021) · Chronic Stress · doi:10.1177/24705470211029254 · Cited by 159 · see citing works
Global and regional brain metabolic scaling and its functional consequences.
Karbowski, J. (2007) · BMC Biology · doi:10.1186/1741-7007-5-18 · Cited by 161 · see citing works
Automated synaptic connectivity inference for volume electron microscopy
Dorkenwald, S., Schubert, P. J., Killinger, M. F., Urban, G., Mikula, S., Svara, F., & Kornfeld, J. (2017) · Nature Methods · doi:10.1038/nmeth.4206 · Cited by 132 · see citing works
Brains matter, bodies maybe not: the case for examining neuron numbers irrespective of body size
Herculano‐Houzel, S. (2011) · Annals of the New York Academy of Sciences · doi:10.1111/j.1749-6632.2011.05976.x · Cited by 137 · see citing works
Self-citationVentura-Antunes, L., Mota, B., & Herculano-Houzel, S. (2013) · Frontiers in Neuroanatomy · doi:10.3389/fnana.2013.00003 · Cited by 129 · see citing works
Self-citationDetecting Microglial Density With Quantitative Multi-Compartment Diffusion MRI
Yi, S. Y., Barnett, B. R., Torres-Velázquez, M., Zhang, Y., Hurley, S. A., Rowley, P. A., Hernando, D., & Yu, J.-P. J. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.00081 · Cited by 104 · see citing works
THE EVOLUTIONARY HISTORY OF CETACEAN BRAIN AND BODY SIZE: CETACEAN BRAIN EVOLUTION
Montgomery, S. H., Geisler, J. H., McGowen, M. R., Fox, C., Marino, L., & Gatesy, J. (2013) · Evolution · doi:10.1111/evo.12197 · Cited by 106 · see citing works
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 · see citing works
Self-citationCellular scaling rules of insectivore brains.
Sarko, D. (2009) · Frontiers in Neuroanatomy · doi:10.3389/neuro.05.008.2009 · Cited by 92 · see citing works
Cell-type-specific epigenetic effects of early life stress on the brain
Rahman, M. F., & McGowan, P. O. (2022) · Translational Psychiatry · doi:10.1038/s41398-022-02076-9 · Cited by 75 · see citing works
The fly connectome reveals a path to the effectome
Pospisil, D. A., Aragon, M. J., Dorkenwald, S., Matsliah, A., Sterling, A. R., Schlegel, P., Yu, S.-C., McKellar, C. E., Costa, M., Eichler, K., et al. (2024) · Nature · doi:10.1038/s41586-024-07982-0 · Cited by 36 · see citing works
Cortico-thalamo-cortical interactions modulate electrically evoked EEG responses in mice
Claar, L. D., Rembado, I., Kuyat, J. R., Russo, S., Marks, L. C., Olsen, S. R., & Koch, C. (2023) · eLife · doi:10.7554/elife.84630.3 · Cited by 36 · see citing works
Lefebvre, L. (2012) · Progress in Brain Research · doi:10.1016/b978-0-444-53860-4.00019-2 · Cited by 36 · see citing works
NeuroMechFly v2: simulating embodied sensorimotor control in adult Drosophila
Wang-Chen, S., Stimpfling, V. A., Lam, T. K. C., Özdil, P. G., Genoud, L., Hurtak, F., & Ramdya, P. (2024) · Nature Methods · doi:10.1038/s41592-024-02497-y · Cited by 43 · see citing works
Understanding the Evolution of Mammalian Brain Structures; the Need for a (New) Cerebrotype Approach
Willemet, R. (2012) · Brain Sciences · doi:10.3390/brainsci2020203 · Cited by 25 · see citing works
Birch, J. (2024) · The Edge of Sentience · doi:10.1093/9780191966729.003.0003 · Cited by 1 · see citing works
Frank, G., Hota, G., Wang, K., Deng, C., Arora, K., Vins, D., Uppal, A., Olajide, O., Yoshimoto, K., Wang, Q., et al. (2026) · npj Unconventional Computing · doi:10.1038/s44335-026-00062-8
“…aim for each FPGA to support up to four million neurons and one billion synapses, yielding a total capacity of up to 160 million neurons and 40 billion synapses for the entire system - more than twice the number of neurons of a typical mouse brain [9] and at faster-than real-time simulation speed.”
- Authors
- Herculano-Houzel, S., Mota, B., & Lent, R.
- Affiliations
- *Departamento de Anatomia, Instituto de Ciências Biomédicas, Universidade Federal do Rio de Janeiro, 21941-590, Rio de Janeiro, Brazil; and
- Centro Brasileiro de Pesquisas Físicas (BR)
- Universidade Federal do Rio de Janeiro (BR)
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2006-08-08
- Volume
- 103
- Issue
- 32
- Pages
- 12138-12143
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC1567708
- OpenAlex
- W2166670234
- Cited by
- 579
- References
- 43
- Citations by year
- 2026: 27 · 2025: 29 · 2024: 58 · 2023: 51 · 2022: 36 · 2021: 51 · 2020: 64 · 2019: 26 · 2018: 31 · 2017: 22 · 2016: 29 · 2015: 19 · 2014: 28 · 2013: 21 · 2012: 18
- FWCI
- 3.67
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Conselho Nacional de Desenvolvimento Científico e Tecnológico
- Universidade Federal do Rio de Janeiro
- Topics
- Life Sciences › Neuroscience › Developmental Neuroscience › Neurogenesis and neuroplasticity mechanisms
- Social Sciences › Psychology › Social Psychology › Primate Behavior and Ecology
- Physical Sciences › Earth and Planetary Sciences › Paleontology › Evolution and Paleontology Studies
- Keywords
- brain scaling, rodent brain, cerebral cortex, cerebellum, neuron size, non-neuronal cells, brain size evolution, cross-species comparison, cortical expansion
- MeSH terms
- Animals, Brain, Cerebellum, Cerebral Cortex, Guinea Pigs, Male, Models, Neurological, Neurons, Rodentia, Species Specificity, Rats, Wistar, Mice, Rats
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
