Scaling of Brain Metabolism with a Fixed Energy Budget per Neuron: Implications for Neuronal Activity, Plasticity and Evolution
Open accessAbstract
It is usually considered that larger brains have larger neurons, which consume more energy individually, and are therefore accompanied by a larger number of glial cells per neuron. These notions, however, have never been tested. Based on glucose and oxygen metabolic rates in awake animals and their recently determined numbers of neurons, here I show that, contrary to the expected, the estimated glucose use per neuron is remarkably constant, varying only by 40% across the six species of rodents and primates (including humans). The estimated average glucose use per neuron does not correlate with neuronal density in any structure. This suggests that the energy budget of the whole brain per neuron is fixed across species and brain sizes, such that total glucose use by the brain as a whole, by the cerebral cortex and also by the cerebellum alone are linear functions of the number of neurons in the structures across the species (although the average glucose consumption per neuron is at least 10× higher in the cerebral cortex than in the cerebellum). These results indicate that the apparently remarkable use in humans of 20% of the whole body energy budget by a brain that represents only 2% of body mass is explained simply by its large number of neurons. Because synaptic activity is considered the major determinant of metabolic cost, a conserved energy budget per neuron has several profound implications for synaptic homeostasis and the regulation of firing rates, synaptic plasticity, brain imaging, pathologies, and for brain scaling in evolution.
AI snapshot
Written from the paper’s full text.
TL;DR
Across six rodents and primates, estimated glucose use per neuron is remarkably constant, varying only about 40%, and total brain glucose use is best described as a linear function of neuron number rather than brain mass. This fixed energy budget per neuron implies that human brain energy demand is explained by its large number of neurons, with consequences for activity, plasticity, imaging, pathology, and evolution.
Key findings
- Estimated glucose use per neuron varied only 1.4-fold (40%) across mouse, rat, squirrel, macaque, baboon, and human, despite a 1213-fold variation in total brain neurons and a 3627-fold variation in brain mass.
- Total glucose use by the whole brain, cerebral cortex, and cerebellum scaled linearly with the number of neurons in each structure: whole brain power exponent 0.988, p<0.0001; linear fit r²=1.0, p<0.0001; cerebral cortex power exponent 0.944, p=0.0002; cerebellum power exponent 0.880, p=0.0001.
- Average glucose consumption per neuron was much higher in cerebral cortex (1.50×10⁻⁸ ± 0.49×10⁻⁸ µmol/neuron·min) than in cerebellum (0.87×10⁻⁹ ± 0.36×10⁻⁹ µmol/neuron·min), while whole-brain average was 5.79×10⁻⁹ ± 0.76×10⁻⁹ µmol/neuron·min.
- The human brain’s use of about 20% of the body energy budget at 2% of body mass is attributed to its large number of neurons; a brain with 86 billion neurons is estimated to use 497.9 µmol glucose/min, or 516 kCal/day.
Methods
- The study analyzed previously published in vivo glucose (CMRglc) and oxygen (CMRO2) metabolic rates from unanesthetized, resting adult animals, obtained from Karbowski (2007), for six species: mouse, rat, squirrel, macaque monkey, baboon, and human.
- Neuron numbers for whole brain, cerebral cortex, and cerebellum came from prior isotropic fractionator studies using DAPI-stained nuclei and NeuN immunoreactivity.
- Total glucose and oxygen use were calculated as the product of published specific rates and structure mass, then compared with neuron numbers using power fits, linear fits, and Spearman correlations.
Limitations
- The paper does not include a formal limitations section; it states that the study is entirely based on analysis of previously published data on brain metabolism and numbers of neurons.
- Evident from the text: the main glucose analysis includes only six species, and the oxygen analysis includes only four species (rat, monkey, baboon, human), limiting cross-species generalization.
- Evident from the text: the cerebral cortex glucose table omits squirrel, and the conclusions rely on indirect estimates and assumptions about neuron–astrocyte metabolic coupling rather than direct per-neuron energy measurements.
Model-written summary. Check it against the paper before relying on it.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
0 of 67 cited sources checked · 0 supported · 0 flagged
- Findingown data
The estimated glucose use per neuron is remarkably constant, varying only by 40% across the six species of rodents and primates including humans.
“Based on glucose and oxygen metabolic rates in awake animals and their recently determined numbers of neurons, here I show that, contrary to the expected, the estimated glucose use per neuron is remarkably constant, varying only by 40% across the six species of rodents and primates (including humans).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [20] J Karbowski, 2007, Global and regional brain metabolic scaling and its functional consequences., BMC Biol source
Not checked in the free run.
- Findingnone given
Average glucose consumption per neuron is at least 10 times higher in the cerebral cortex than in the cerebellum.
“although the average glucose consumption per neuron is at least 10× higher in the cerebral cortex than in the cerebellum”
Quote in the paperNot a substantial claim - Findingown data
The estimated average glucose use per neuron does not correlate with neuronal density in any structure.
“The estimated average glucose use per neuron does not correlate with neuronal density in any structure.”
Quote in the paperSubstantial claim - Findingown data
Small variations in estimated average glucose use per neuron are not correlated with the ratio between non-neuronal and neuronal cells (glia/neuron ratio) (Spearman p values).
“nor with the ratio between non-neuronal and neuronal cells (which approximates the glia/neuron ratio in the tissue; Spearman correlation, cerebral cortex, p = 0.2301; cerebellum, p = 0.5485; whole brain, p = 0.8480).”
Quote in the paperNot a substantial claim - Findingown data
Small variations in estimated average glucose use per neuron are not correlated with variations in neuronal density across species in any structure (Spearman p values).
“The small variations in the estimated average glucose use per neuron are not correlated with variations in neuronal density across species in any structure (Spearman correlation: cerebral cortex, p = 0.3173; cerebellum, p = 0.6892; whole brain, p = 0.5653)”
Quote in the paperSubstantial claim
- Findingown data
The total glucose use per minute estimated by the linear method is a very good approximation of the actual measurements made in the available species.
“Notice that the total glucose use per minute estimated by this method (Table 4) is a very good approximation of the actual measurements made in the available species (Table 1).”
Quote in the paperSubstantial claim - Findingown data
In the cerebral cortex and cerebellum, total glucose use scales with structure mass raised to powers of 0.850 and 0.844, respectively (p<0.0001, 95% CI 0.824-0.876 and 0.768-0.919).
“In the cerebral cortex and cerebellum, total glucose use also scales with structure mass raised to similar powers of 0.850 and 0.844, respectively (p<0.0001, 95% CI 0.824–0.876 and 0.768–0.919; Figure 1a).”
Quote in the paperSubstantial claim - Findingreasoning
Because about 80% of all brain neurons are in the cerebellum, average glucose use per neuron for the whole brain (5.79×10−9±0.76×10−9) is lower than average glucose use by cortical neurons.
“Because about 80% of all brain neurons are in the cerebellum, the average glucose use per neuron for the whole brain (5.79×10−9±0.76×10−9) is lower than the average glucose use by cortical neurons.”
Quote in the paperSubstantial claim - Findingown data
Average glucose consumption per neuron is nearly 20 times higher in the cerebral cortex (1.50×10−8±0.49×10−8 μmol glucose/neuron.min) than in the cerebellum (0.87×10−9±0.36×10−9 μmol glucose/neuron.min).
“the average glucose consumption per neuron is nearly 20× higher in the cerebral cortex (1.50×10−8±0.49×10−8 µmol glucose/neuron.min) than in the cerebellum (0.87×10−9±0.36×10−9 µmol glucose/neuron.min; see Table 1 for a comparison within species).”
Quote in the paperSubstantial claim - Findingown data
Total glucose use by the whole brain, cerebral cortex, and cerebellum varies with the number of neurons in those structures in a manner best described as a linear function across the six species (all p<0.0001).
“total glucose use by the brain as a whole, by the cerebral cortex and also by the cerebellum alone vary with the number of neurons in the structures in a manner that is best described as a linear function across the 6 species (all p<0.0001; Figure 1b)”
Quote in the paperSubstantial claim - Findingreasoning
Whole brain glucose use per gram of tissue decreases with brain mass raised to the power of −0.127.
“which means that glucose use per gram of tissue decreases with brain mass raised to the power of −0.127”
Quote in the paperSubstantial claim - Findingown data
The cross-species comparison of average energy cost per neuron indicates that this cost does not scale significantly with brain size, neuronal size, or number of neurons.
“Most importantly, the cross-species comparison of the average energy cost per neuron thus defined indicates that this cost does not scale significantly with brain size, neuronal size, or number of neurons.”
Quote in the paperSubstantial claim - Findingown data
Glucose use per gram of brain tissue increases linearly with neuronal density in the brain (r2 = 0.906, p = 0.0034; power exponent 0.986, p = 0.0041).
“glucose use per gram of brain tissue increases linearly with neuronal density in the brain (r2 = 0.906, p = 0.0034; power exponent, 0.986, p = 0.0041; Figure 2a).”
Quote in the paperSubstantial claim - Findingown data
Whole brain use of oxygen increases with brain mass raised to the power of 0.862 (p = 0.0037, 95% CI 0.635-1.088).
“Similarly, whole brain use of oxygen increases with brain mass raised to the power of 0.862 (p = 0.0037, 95% CI 0.635–1.088).”
Quote in the paperSubstantial claim - Findingown data
Across the six species, whole brain total glucose use increases with brain mass raised to the power of 0.873 (p<0.0001, 95% CI 0.830-0.915), significantly below linearity.
“Across the six species, whole brain total glucose use increases with brain mass raised to the power of 0.873 (p<0.0001, 95% CI 0.830–0.915), significantly below linearity”
Quote in the paperSubstantial claim - Findingreasoning
The metabolic cost per gram of brain tissue increases directly with the number of neurons per gram of tissue.
“the metabolic cost per gram of tissue, as shown here, increases directly with the number of neurons per gram of tissue.”
Quote in the paperSubstantial claim - Premisecitation
Primate brain structures increase in size through the addition of larger numbers of neurons whose average size remains constant.
“primate brain structures increase in size through the addition of larger numbers of neurons whose average size remains constant [24]–[26].”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [24]–[26]
Not checked in the free run.
- Premisecitation
The declining specific rate of brain metabolism in larger mammalian species varies with brain mass raised to an exponent of around −0.14.
“The declining specific rate of brain metabolism (that is, metabolic rates per gram of tissue) in larger mammalian species, which varies with brain mass raised to an exponent of around −0.14 [2], [20]”
Quote in the paperSubstantial claim0 of 2 sources checked - Premisecitation
The human brain, at 2% of body mass, consumes about 20% of the whole body energy budget.
“In contrast, the human brain, at 2% of body mass, consumes about 20% of the whole body energy budget [5]–[8]”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [5]–[8]
Not checked in the free run.
- Interpretationreasoning
It is not correct to assume that the declining specific rates of brain metabolism in larger brains result from larger metabolic needs of larger neurons.
“It is therefore not correct to assume that the declining specific rates of brain metabolism in larger brains result from larger metabolic needs of larger neurons.”
Quote in the paperSubstantial claim - Premisecitation
Rodent brain structures increase in size by gaining neurons whose average size increases.
“while rodent brain structures increase in size gaining neurons whose average size does increase”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [24]–[26]
Not checked in the free run.
- Interpretationown data
The energy budget of the whole brain per neuron is fixed across species and brain sizes.
“This suggests that the energy budget of the whole brain per neuron is fixed across species and brain sizes”
Quote in the paperSubstantial claim - Premisecitation
An increase in average neuronal size in larger brains is not the norm across mammalian species.
“we have recently shown an increase in average neuronal size in larger brains is not the norm across mammalian species”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [24]–[26]
Not checked in the free run.
- Premisecitation
The metabolic cost per neuron has never been examined in humans or across species of different brain sizes.
“the metabolic cost per neuron has never been examined, neither in humans nor across species of different brain sizes”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [20] J Karbowski, 2007, Global and regional brain metabolic scaling and its functional consequences., BMC Biol source
Not checked in the free run.
- Premisecitation
The specific metabolic rate of the human brain is predictably low given its large size.
“even though the specific metabolic rate of the human brain is predictably low, given its large size [2].”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [2] MA Hofman, 1983, Energy metabolism, brain size and longevity in mammals., Quarterly Rev Biol source
Not checked in the free run.
- Interpretationown data
The human brain's use of 20% of the whole body energy budget while representing only 2% of body mass is explained simply by its large number of neurons.
“These results indicate that the apparently remarkable use in humans of 20% of the whole body energy budget by a brain that represents only 2% of body mass is explained simply by its large number of neurons.”
Quote in the paperSubstantial claim - Interpretationreasoning
The apparent scaling of glucose use per gram of brain tissue with brain size raised to exponent −0.127 can be explained by a similar apparent scaling of neuronal density in the whole brain with brain size raised to exponent −0.116.
“The apparent scaling of glucose use per gram of brain tissue with brain size raised to an exponent of −0.127 in the present sample can therefore be explained by a similar apparent scaling of neuronal density in the whole brain with brain size raised to an exponent of −0.116 (Figure 2b).”
Quote in the paperSubstantial claim - Interpretationown data
The relatively stable average energy requirement per neuron, whether in the cerebral cortex or cerebellum, allows estimation of the energy requirement of these structures as a simple linear function of their numbers of neurons.
“The relatively stable average energy requirement per neuron, whether in the cerebral cortex or cerebellum, allows one to estimate the energy requirement of these structures as a simple linear function of their numbers of neurons (Table 3).”
Quote in the paperSubstantial claim - Interpretationreasoning
The overall metabolic cost of a brain can be inferred from its number of neurons.
“the overall metabolic cost of a brain can be inferred from its number of neurons.”
Quote in the paperSubstantial claim - Interpretationown data
The similarity between predicted and measured values validates the calculation of the total energy requirement of a mammalian brain as a linear function of its total number of neurons.
“The similarity between the predicted and measured values validates the calculation of the total energy requirement of a mammalian brain as a linear function of its total number of neurons.”
Quote in the paperSubstantial claim - Interpretationown data
The scaling of brain metabolism is best described as a function of the total number of neurons in the brain, regardless of how that relates to brain mass or neuronal density across species.
“The scaling of brain metabolism, therefore, is best described as a function of the total number of neurons in the brain, regardless of how that relates to brain mass or neuronal density across species.”
Quote in the paperSubstantial claim - Interpretationreasoning
The inverse of neuronal density can be considered to provide a direct estimate of how average neuronal size varies in the structures.
“the inverse of neuronal density can be considered to provide a direct estimate of how average neuronal size varies in the structures.”
Quote in the paperSubstantial claim - Premisecitation
The calculation of average metabolic cost per neuron as total metabolic cost of a structure divided by its number of neurons is justified by the finding that neurons and astrocytes are metabolically coupled.
“the calculation of the average metabolic cost per neuron defined here as the total metabolic cost of a structure divided by its number of neurons is justified by the finding that neurons and astrocytes are metabolically coupled [30].”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [30] L Pellerin, 1994, Glutamate uptake into astrocytes stimulates aerobic glycolysis: a mechanism coupling neuronal activity to glucose utilization., PNAS source
Not checked in the free run.
- Interpretationown data
The total metabolic cost of a brain is a simple, direct function of its number of neurons, each constrained to a fixed energy budget per neuron, regardless of brain size.
“As a result, the total metabolic cost of a brain seems to be a simple, direct function of its number of neurons, each of them constrained to a fixed energy budget per neuron, regardless of brain size.”
Quote in the paperSubstantial claim - Premisecitation
Non-neuronal cell density is remarkably constant across these species.
“Given that non-neuronal cell density is remarkably constant across these species [24], [25]”
Quote in the paperSubstantial claim0 of 2 sources checked - Premisecitation
The ratio between numbers of cortical and cerebellar neurons remains fairly constant across mammalian species.
“the coordinate scaling of the numbers of neurons in the cerebral cortex and cerebellum, such that the ratio between numbers of cortical and cerebellar neurons remains fairly constant across mammalian species [29]”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [29] S Herculano-Houzel, 2010, Coordinated scaling of cortical and cerebellar numbers of neurons., Front Neuroanat
Not checked in the free run.
- Interpretationreasoning
The finding that variations in estimated average glucose use per neuron are not correlated with variations in neuronal density across species suggests that average energy use per neuron does not scale with average neuronal size, including the soma and all arborizations.
“Therefore, the finding that variations in the estimated average glucose use per neuron are not correlated with variations in neuronal density across species suggests that the average energy use per neuron does not scale with average neuronal size (including the soma and all arborizations).”
Quote in the paperSubstantial claim - Interpretationown data
The average energy use per neuron does not scale with number of neurons or brain size.
“This indicates that the average energy use per neuron does not scale with number of neurons or brain size.”
Quote in the paperSubstantial claim - Premisecitation
The same stoichiometric coupling applies to rat and human cerebral cortex in vivo.
“Remarkably, these studies have shown that the same stoichiometric coupling applies to rat [32] and human [33] cerebral cortex in vivo.”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [32] NR Sibson, 1998, Stoichiometric coupling of brain glucose metabolism and glutamatergic neuronal activity., PNAS source
Not checked in the free run.
- cites [33] J Shen, 1999, Determination of the rate of the glutamate/glutamine cycle in the human brain by in vivo 13C NRM., PNAS source
Not checked in the free run.
- Interpretationreasoning
Metabolic cost is an ever more limiting factor to brain expansion than previously suspected, given the steep, linear increase in brain metabolic cost with increasing numbers of neurons.
“The present evidence suggests that metabolic cost is actually an ever more limiting factor to brain expansion that previously suspected, given the steep, linear increase in brain metabolic cost with increasing numbers of neurons.”
Quote in the paperSubstantial claim - Premisecitation
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”
Quote in the paperSubstantial claim0 of 3 sources checked- cites [24] S Herculano-Houzel, 2006, : Cellular scaling rules for rodent brains., Proc Natl Acad Sci U S A source
Not checked in the free run.
- cites [25] S Herculano-Houzel, 2007, Cellular scaling rules for primate brains., Proc Natl Acad Sci USA source
Not checked in the free run.
- cites [41] DK Sarko, 2009, Cellular scaling rules of insectivore brains., Front Neuroanat source
Not checked in the free run.
- Interpretationcitation
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].”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [24] S Herculano-Houzel, 2006, : Cellular scaling rules for rodent brains., Proc Natl Acad Sci U S A source
Not checked in the free run.
- cites [43] S Herculano-Houzel, 2011, Not all brains are made the same: new views on brain scaling in evolution., Brain Behav Evol
Not checked in the free run.
- Interpretationreasoning
The linear scaling of brain metabolism with number of neurons can be reconciled with the experimental observation that specific glucose use in the brain decreases with increasing brain mass, given that average neuronal density in the whole brain appears to decrease with increasing brain size at the same rate.
“This latter finding can be reconciled with the experimental observation that specific glucose use in the brain decreases with increasing brain mass [20] given the present observation that average neuronal density in the whole brain may, depending on the species analyzed, appears to decrease with increasing brain size at the same rate.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [20] J Karbowski, 2007, Global and regional brain metabolic scaling and its functional consequences., BMC Biol source
Not checked in the free run.
- Interpretationcitation
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”
Quote in the paperSubstantial claim0 of 3 sources checked- cites [24] S Herculano-Houzel, 2006, : Cellular scaling rules for rodent brains., Proc Natl Acad Sci U S A source
Not checked in the free run.
- cites [25] S Herculano-Houzel, 2007, Cellular scaling rules for primate brains., Proc Natl Acad Sci USA source
Not checked in the free run.
- cites [41] DK Sarko, 2009, Cellular scaling rules of insectivore brains., Front Neuroanat source
Not checked in the free run.
- Interpretationown data
Within structures such as the cerebral cortex and cerebellum, neurons are allotted a fixed energy budget, regardless of their size, across species.
“Rather, it suggests that, within structures such as the cerebral cortex and cerebellum, neurons are allotted a fixed energy budget, regardless of their size, across species.”
Quote in the paperSubstantial claim - Interpretationcitation
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”
Quote in the paperSubstantial claim0 of 3 sources checked- cites [44] S Herculano-Houzel, 2009, The human brain in numbers: a linearly scaled-up primate brain., Front Human Neurosci source
Not checked in the free run.
- cites [24] S Herculano-Houzel, 2006, : Cellular scaling rules for rodent brains., Proc Natl Acad Sci U S A source
Not checked in the free run.
- cites [25] S Herculano-Houzel, 2007, Cellular scaling rules for primate brains., Proc Natl Acad Sci USA source
Not checked in the free run.
- Rests on an assumption: The human brain uses 20% of the whole body energy budget while representing only 2% of body mass.
- Interpretationreasoning
In primates, total brain metabolism scales linearly with brain volume, with an exponent of 1.
“The finding that total brain metabolism scales linearly with the number of brain neurons implies that in primates, whose brain mass scales linearly with its number of neurons, total brain metabolism scales linearly with brain volume, that is, with an exponent of 1, which is much greater than the much-cited Kleiber's 3/4 exponent that relates body metabolism to body mass [38].”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [38] M Kleiber, 1932, Body size and metabolism., Hilgardia source
Not checked in the free run.
- Interpretationcitation
The fixed energy budget per neuron across brain sizes disputes the traditional view that the ratio between numbers of glial and neuronal cells is related to increased metabolic needs of larger neurons.
“Moreover, the fixed energy budget per neuron across brain sizes disputes the traditional view that the ratio between numbers of glial and neuronal cells is related to increased metabolic needs of larger neurons [42]; instead, 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”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [42] A Reichenbach, 1989, Glia:Neuron index: Review and hypothesis to account for different values in various mammals., Glia source
Not checked in the free run.
- Premisecitation
The human brain conforms to the neuronal scaling rules that apply to other primates.
“We have shown previously that the human brain conforms to the neuronal scaling rules that apply to other primates [27], [44].”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [27] FAC Azevedo, 2009, Equal numbers of neuronal and nonneuronal cells make the human brain an isometrically scaled-up primate brain., J Comp Neurol source
Not checked in the free run.
- cites [44] S Herculano-Houzel, 2009, The human brain in numbers: a linearly scaled-up primate brain., Front Human Neurosci source
Not checked in the free run.
- Premisecitation
Increases in neuronal activity are expected to cost more energy.
“Increases in neuronal activity, with the associated depolarization and repolarization of cell membranes and cycling of transmitters, are expected to cost more energy [23], [49].”
Quote in the paperSubstantial claim0 of 2 sources checked - Interpretationreasoning
A doubling in the number of brain neurons from an orangutan-sized hominin ancestor would have required an additional 180 kCal/day.
“a doubling in the number of brain neurons from an orangutan-sized hominin ancestor would have required an additional 180 kCal/day that might not be readily available.”
Quote in the paperSubstantial claim - Interpretationreasoning
It is not brain size, but rather absolute number of neurons, that imposes a metabolic constraint upon brain scaling in evolution.
“In our view, it is not brain size, but rather absolute number of neurons, that imposes a metabolic constraint upon brain scaling in evolution, as individuals with increasing numbers of neurons must be able to sustain their proportionately larger metabolic requirements to keep their brain functional.”
Quote in the paperSubstantial claim - Interpretationcitation
This scenario reconciles human brain metabolism with comparative genetic analyses showing that genes related to cell metabolism are among those with larger changes in human evolution and evidence of evolutionary pressure for high rates of aerobic energy consumption.
“This scenario reconciles human brain metabolism with comparative genetic analyses that show that genes related to cell metabolism are among those that exhibit the larger changes in human evolution [9], [10], with evidence of evolutionary pressure for high rates of aerobic energy consumption [52].”
Quote in the paperSubstantial claim0 of 3 sources checked- cites [9] M Cáceres, 2003, Elevated gene expression levels distinguish human from non-human primate brains., Proc Natl Acad Sci USA source
Not checked in the free run.
- cites [10] M Uddin, 2004, Sister grouping of chimpanzees and humans as revealed by genome-wide phylogenetic analysis of brain gene expression profiles., Proc Natl Acad Sci USA source
Not checked in the free run.
- cites [52] LI Grossman, 2001, Molecular evolution of aerobic energy metabolism in primates., Mol Phylogenet Evol source
Not checked in the free run.
- Interpretationcitation
The approximately 45% reduction in glucose or oxygen consumption with anesthesia-induced loss of consciousness is compatible with the idea that the neuronal energy budget is limiting in the conscious state.
“Moreover, the approximately 45% reduction in glucose or oxygen consumption with anesthesia-induced loss of consciousness is compatible with the idea that the neuronal energy budget is limiting in the conscious state, such that decreases may compromise function, leading to blackened vision, fainting, and ultimately causing unconsciousness [56].”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [56] RG Shulman, 2009, Baseline brain energy supports the state of consciousness., Proc Natl Acad Sci USA source
Not checked in the free run.
- Premisecitation
In other body organs, such as the liver, the intrinsic metabolic activity of the cells decreases with increasing body size.
“In contrast, in other body organs, such as the liver, the intrinsic metabolic activity of the cells actually decreases with increasing body size [50], [51].”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [50] RK Porter, 1995, Causes of differences in respiration rate of hepatocytes from mammals of different body mass., Am J Physiol
Not checked in the free run.
- cites [51] RK Porter, 1995, Cellular oxygen consumption depends on body mass., Am J Physiol
Not checked in the free run.
- Interpretationreasoning
Per gram, the cost of primate brain tissue scales faster than the cost of non-neuronal bodily tissues.
“The discrepancy suggests that, per gram, the cost of primate brain tissue scales faster than the cost of non-neuronal bodily tissues, which calls for a modification of the “expensive tissue hypothesis” of brain evolution [11], according to which brain size is a limiting factor.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [11] LC Aiello, 1995, The expensive tissue hypothesis: the brain and the digestive system in human and primate evolution., Curr Anthropol source
Not checked in the free run.
- Premisecitation
Larger energetic requirements necessitate more time spent foraging.
“Larger energetic requirements therefore necessitate more time spent foraging [45], and energy intake is further dependent on the availability and quality of foods: orangutans, for instance, spend 4–5 hours per day feeding, but during the months of low fruit availability that is still not enough to provide all the calories required, and the animals lose weight [46].”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [45] NR Owen-Smith, 1988, Megaherbivores. source
Not checked in the free run.
- Interpretationreasoning
During months of low fruit availability, the orangutan brain is estimated to require about 10% of the total caloric intake.
“During the months of low fruit availability, when total caloric intake by females is estimated at about 1800 kCal/day (at best, assuming 100% caloric efficiency of the foods ingested), the orangutan brain is estimated to require about 10% of the total caloric intake, which is less than sufficient to support the body (see above).”
Quote in the paperSubstantial claim- The authors state this as an assumption: The foods ingested by orangutans are 100% calorically efficient.
- Study design and conductreasoning
The measurements of glucose utilization in all species are directly comparable.
“In those studies, the measurements of glucose utilization in all species were performed by [14C]2-deoxyglucose uptake [4] in mouse, rat, squirrel and macaque monkey, or by the similar method of [18F]fluoro-2-deoxy-D-glucose uptake [66] in baboon, human, and one case of macaque, and are thus directly comparable.”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [4] L Sokoloff, 1977, Relation between physiological function and energy metabolism in the central nervous system., J Neurochem source
Not checked in the free run.
- cites [66] ME Phelps, 1975, Application of annihilation coincidence detection to transaxial reconstruction tomography., J Nuc Med
Not checked in the free run.
- May combine two claims. 27
- Classified as probably not a substantial claim. 1
May combine two claims.
FindingreasoningTotal glucose use by the whole brain, by the cerebral cortex, and by the cerebellum alone are linear functions of the number of neurons in those structures across the six species.
“total glucose use by the brain as a whole, by the cerebral cortex and also by the cerebellum alone are linear functions of the number of neurons in the structures across the species”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataVariation in total glucose use by the whole brain or cerebral cortex matches closely variation in numbers of neurons across species, although not as closely in the cerebellum.
“Indeed, the variation in total glucose use by the whole brain or cerebral cortex matches closely the variation in numbers of neurons in these structures across species (Table 1), although not as closely in the cerebellum.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataSmall variations in average energy use per neuron do not correlate with structure mass nor with number of neurons in the structure (Spearman p values).
“Moreover, the small variations in average energy use per neuron do not correlate with structure mass nor with number of neurons in the structure (Spearman correlation, glucose: cerebral cortex, p = 0.2301; cerebellum, p = 0.1615; whole brain, p = 0.8480. Spearman correlation, oxygen: whole brain, p = 0.2987).”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataAcross the mammals examined so far, the apparent exponent for neuronal density scaling with brain mass for the whole sample is −0.172, close to the exponent of −0.15 for brain metabolism, but there is no universal scaling of neuronal density in the brain with brain mass across all species.
“Across the mammals that we have examined so far, the apparent exponent for the whole sample is −0.172, close to the exponent of −0.15 for brain metabolism, but notice that there is no universal scaling of neuronal density in the brain with brain mass across all species (Figure 2c).”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataThe average metabolic cost per neuron is relatively stable across species, with small variations that are not correlated with neuronal density nor with brain size.
“The results of this analysis, shown here, suggest that, contrary to expectations, the average metabolic cost per neuron is relatively stable across species, with small variations that are not correlated with neuronal density (and therefore not correlated with neuronal size) nor with brain size.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataThe average brain neuron is estimated to cost 5.79×10−9 μmol glucose/min, with no significant difference between rodents and primates.
“As the average brain neuron is estimated to cost 5.79×10−9 µmol glucose/min, with no significant difference between rodents and primates”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataAverage energy use per neuron is fixed (relatively invariant) across species and orders, such that total brain metabolism is a simple, linear function of the number of neurons that compose the brain.
“the direct scaling of total brain metabolic cost as a function of the number of brain neurons shown here indicates that the average energy use per neuron is fixed (that is, relatively invariant) across species and orders, such that total brain metabolism is a simple, linear function of the number of neurons that compose that brain.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataThe precise exponent that describes the scaling of average neuronal density with brain mass varies across mammalian orders and, for cross-order comparisons of metabolic scaling, is strongly dependent on the choice of species analyzed.
“as shown here, the precise exponent that describes the scaling of average neuronal density with brain mass varies across mammalian orders, and, for cross-order comparisons of metabolic scaling such as in [20], is strongly dependent on the choice of species analyzed.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [20] J Karbowski, 2007, Global and regional brain metabolic scaling and its functional consequences., BMC Biol source
Not checked in the free run.
May combine two claims.
InterpretationreasoningNeuronal density decreases with increasing brain size in rodents, but does not vary consistently with brain size in primates.
“As a result, neuronal density decreases with increasing brain size in rodents, but it does not vary consistently with brain size in primates.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationKarbowski estimated that cerebral energy per neuron increases with brain size based on the supposed scaling of neuronal density with brain size.
“although Karbowski [20], based on the supposed scaling of neuronal density with brain size, estimated that cerebral energy per neuron increases with brain size.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [20] J Karbowski, 2007, Global and regional brain metabolic scaling and its functional consequences., BMC Biol source
Not checked in the free run.
May combine two claims.
PremisecitationNearly 80% of a neuron's energy budget goes toward glutamate-related neurotransmission, and 13% is used to maintain the resting potential of the cell membrane.
“an estimate of the distribution of the energy budget among the several energy-consuming processes within a neuron which predicted that, while nearly 80% of a neuron's energy budget go toward glutamate-related neurotransmission, 13% are used to maintain the resting potential of the cell membrane [23].”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [23] D Attwell, 2001, An energy budget for signaling in the grey matter of the brain., J Cereb Blood FLow Metab source
Not checked in the free run.
May combine two claims.
PremisecitationThe majority of glucose used by the brain is taken up by astrocytes and used in anaerobic glycolysis that generates lactate, while the remainder is used by neurons in oxidative glycolysis.
“the majority of the glucose used by the brain is taken up by astrocytes and used in anaerobic glycolysis that generates lactate, while the remainder is used by neurons in oxidative glycolysis [31].”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [31] F Hyder, 2006, Neuronal-glial glucose oxidation and glutamatergic-GABAergic function., J Cereb Blood Flow Metab source
Not checked in the free run.
May combine two claims.
InterpretationreasoningA mammalian brain with 100 million neurons is predicted to consume 0.579 μmol glucose/min, requiring 0.6 kCal/day; with 1 billion neurons, 5.79 μmol/min or 6 kCal/day; and with 100 billion neurons, 579 μmol/min or 600 kCal/day, regardless of brain volume.
“Thus, a mammalian brain with 100 million neurons would be predicted to consume 0.579 µmol glucose/min, requiring 0.6 kCal/day; a brain with 1 billion neurons would use 5.79 µmol glucose/min, or 6 kCal/day; and a brain with 100 billion neurons would use 579 µmol glucose/min, or 600 kCal/day, regardless of the volume of these brains (Table 4).”
Quote in the paperSubstantial claim- Rests on an assumption: The six species examined are representative of mammals generally for the scaling of brain metabolism with neuron number.
May combine two claims.
PremisecitationTotal glucose use by neurons and astrocytes together is coupled directly to glutamate-mediated synaptic transmission, which accounts for 80-90% of total glucose use in the cerebral cortex.
“As a consequence, the total glucose use by neurons and astrocytes together is coupled directly to glutamate-mediated synaptic transmission [32], [34], [36], which accounts for 80–90% of total glucose use in the cerebral cortex [32].”
Quote in the paperSubstantial claim0 of 3 sources checked- cites [32] NR Sibson, 1998, Stoichiometric coupling of brain glucose metabolism and glutamatergic neuronal activity., PNAS source
Not checked in the free run.
- cites [34] PJ Magistretti, 1999, Energy on demand., Science source
Not checked in the free run.
- cites [36] A Loaiza, 2003, Glutamate triggers rapid glucose transport stimulation in astrocytes as evidenced by real-time confocal microscopy., J Neurosci source
Not checked in the free run.
May combine two claims.
PremisecitationGlucose taken up by astrocytes is related to neuronal energetics through stoichiometric coupling to uptake of glutamate released by synaptic activity and its conversion to glutamine, while lactate produced by anaerobic glycolysis is shuttled to neurons and used as fuel.
“the glucose taken up by astrocytes is related to neuronal energetics through the stoichiometric coupling to the uptake of glutamate released by synaptic activity and its subsequent conversion to glutamine, while the lactate produced by anaerobic glycolysis is shuttled to neurons and used by them as fuel [32]–[35].”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [32]–[35]
Not checked in the free run.
May combine two claims.
PremisecitationIncreasing size of a neuronal cell, including all arborizations, should impose a higher metabolic demand related to the cost of maintaining membrane polarization, and energy metabolism is coupled to synaptic activity.
“Given that the increasing size of a neuronal cell (including all of its arborizations) should impose a higher metabolic demand related to the cost of maintaining membrane polarization [23] and that energy metabolism is coupled to synaptic activity [34]”
Quote in the paperSubstantial claim0 of 2 sources checkedMay combine two claims.
InterpretationcitationMammals 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].”
Quote in the paperSubstantial claim0 of 2 sources checkedMay combine two claims.
InterpretationreasoningThe existence of a fixed energy budget per neuron suggests that neuronal metabolism imposes constraints upon brain structure, function, and evolution, with direct consequences for pathologies in which neuronal metabolism is disturbed.
“the existence of a fixed energy budget per neuron suggests that neuronal metabolism imposes a series of constraints upon brain structure, function, and evolution, with direct consequences for pathologies in which neuronal metabolism is disturbed”
Quote in the paperSubstantial claimMay combine two claims.
InterpretationreasoningBrain 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]”
Quote in the paperSubstantial claim0 of 3 sources checked- cites [24] S Herculano-Houzel, 2006, : Cellular scaling rules for rodent brains., Proc Natl Acad Sci U S A source
Not checked in the free run.
- cites [25] S Herculano-Houzel, 2007, Cellular scaling rules for primate brains., Proc Natl Acad Sci USA source
Not checked in the free run.
- cites [41] DK Sarko, 2009, Cellular scaling rules of insectivore brains., Front Neuroanat source
Not checked in the free run.
May combine two claims.
InterpretationreasoningMechanisms of synaptic homeostasis and plasticity to maintain the number of synapses in check, as well as sparse coding, may be direct consequences of a limiting and size-invariant, fixed energy budget per neuron.
“Thus, mechanisms of synaptic homeostasis [62] and plasticity to maintain the number of synapses in check (including the decrease of synaptic markers during sleep [63]), as well as sparse coding, with only a small proportion of neurons firing at high frequencies at any moment [49], [64], [65], may be direct consequences to brain function of a limiting and size-invariant, fixed energy budget per”
Quote in the paperSubstantial claim0 of 3 sources checked- cites [62] GG Turrigiano, 2008, The self-tuning neuron: synaptic scaling of excitatory synapses., Cell source
Not checked in the free run.
- cites [63] GF Gilestro, 2009, Widespread changes in synaptic markers as a function of sleep and wakefulness in Drosophila., Science source
Not checked in the free run.
- cites [49] P Lennie, 2003, The cost of cortical computation., Curr Biol source
Not checked in the free run.
May combine two claims.
PremisecitationLarger neurons with larger numbers of synapses in culture have sparser connectivity and reduced unitary synapse strength, such that firing rate is preserved across clusters of different sizes.
“Indeed, larger neurons with larger numbers of synapses in culture have recently been found to have sparser connectivity and reduced unitary synapse strength, such that firing rate was preserved across clusters of different sizes [61].”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [61] NR Wilson, 2007, Synaptic reorganization in scaled networks of controlled size., J Neurosci source
Not checked in the free run.
May combine two claims.
InterpretationreasoningMechanisms must be in place that adjust firing rate with increasing neuronal size and avoid excessive synaptic activity.
“An energy budget that is relatively invariant across neuronal sizes implies that mechanisms must be in place that adjust firing rate with increasing neuronal size and avoid excessive synaptic activity.”
Quote in the paperSubstantial claimMay combine two claims.
InterpretationreasoningThe orangutan brain can be estimated to have roughly 1/3 as many neurons as the human brain and to require 1/3 as many calories to support the brain alone, about 180 kCal.
“The orangutan brain is about a third the size of the human brain, and therefore, given the linear neuronal scaling rules that apply to primate brains, can be estimated to have roughly 1/3 as many neurons and to require 1/3 as many calories to support the brain alone, that is, about 180 kCal.”
Quote in the paperSubstantial claim- Rests on an assumption: The orangutan brain is about one third the size of the human brain.
May combine two claims.
InterpretationreasoningThe larger the number of neurons, the higher the total caloric cost of the brain, and therefore the more time required to be spent feeding in order to support the brain alone.
“As illustrated in Table 4, the larger the number of neurons, the higher the total caloric cost of the brain, and therefore the more time required to be spent feeding in order to support the brain alone.”
Quote in the paperSubstantial claimMay combine two claims.
PremisecitationNeuronal activation is associated with a small energy demand: an 8-12% increase in ATP production with visual stimulation in awake human visual cortex and a 5% increase in metabolic rate with somatosensory stimulation in awake somatosensory cortex.
“While fractional changes in neuronal firing frequency are directly proportional to changes in energy use [53], the energy demand associated with neuronal activation appears to be small: there is only a 8–12% increase in ATP production with visual stimulation in the awake human visual cortex [54], and a 5% increase in metabolic rate with somatosensory stimulation in the awake somatosensory cortex [”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [54] A-L Lin, 2010, Nonlinear coupling between cerebral blood flow, oxygen consumption, and ATP production in human visual cortex., PNAS source
Not checked in the free run.
- cites [55] PT Fox, 1986, Focal physiological uncoupling of cerebral blood flow and oxidative metabolism during somatosensory stimulation in human subjects., PNAS source
Not checked in the free run.
May combine two claims.
InterpretationreasoningThe energy budget per neuron, contrary to the energy budget for other cell types, has been stretched in evolution to remain constant, and therefore might operate close to its limit, imposing a constraint for neuronal activity.
“The relatively constant values of energy use per neuron across species of smaller neuronal densities (and hence larger neurons) thus suggests that the energy budget per neuron, contrary to the energy budget for other cell types, has been stretched in evolution to remain constant, and therefore might operate close to its limit, imposing a constraint for neuronal activity.”
Quote in the paperSubstantial claimMay combine two claims.
InterpretationreasoningThe energy budget of individual neurons is limited over time, as it does not accommodate large variations related to neuronal activity.
“Additionally, there is evidence that the energy budget of individual neurons is not only limited across species but also over time, given that it does not accommodate large variations related to neuronal activity.”
Quote in the paperSubstantial claimMay combine two claims.
InterpretationreasoningChronic impairments of neuronal metabolism would be expected to compromise brain function and contribute to brain pathology.
“For the same reason, chronic impairments of neuronal metabolism would be expected to compromise brain function and contribute to brain pathology, which may be the case in epilepsy (due to runaway excitatory activity or directly to metabolic disorders [57]), sepsis [58], mitochondrial disorders, which strongly affect the brain [59], and Alzheimer's disease [60].”
Quote in the paperSubstantial claim0 of 3 sources checked- cites [57] C la Fougère, 2009, PET and SPECT in epilepsy: a critical review., Epilepsy Behav source
Not checked in the free run.
- cites [58] JC d'Avila, 2008, Sepsis induces brain mitochondrial dysfunction., Crit Care Med source
Not checked in the free run.
- cites [59] J Finsterer, 2008, Cognitive decline as a manifestation of mitochondrial disorders (mitochondrial dementia)., J Neurol Sci source
Not checked in the free run.
The paper relies on this without support.
The six species examined are representative of mammals generally for the scaling of brain metabolism with neuron number.
“Thus, a mammalian brain with 100 million neurons would be predicted to consume 0.579 µmol glucose/min, requiring 0.6 kCal/day; a brain with 1 billion neurons would use 5.79 µmol glucose/min, or 6 kCal/day; and a brain with 100 billion neurons would use 579 µmol glucose/min, or 600 kCal/day, regardless of the volume of these brains (Table 4).”
The paper relies on this without support.
The orangutan brain is about one third the size of the human brain.
“The orangutan brain is about a third the size of the human brain”
The authors state this as an assumption.
The foods ingested by orangutans are 100% calorically efficient.
“assuming 100% caloric efficiency of the foods ingested”
The paper relies on this without support.
The human brain uses 20% of the whole body energy budget while representing only 2% of body mass.
“the apparently remarkable use in humans of 20% of the whole body energy budget by a brain that represents only 2% of this mass”
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 adult human brain makes up only 2% of body weight but consumes approximately 20% of the energy deriving from glucose, which provides the bioenergetic basis for neurotransmission.
“The adult human brain makes up only 2% of the body weight, but it consumes approximately 20% of the energy deriving from glucose, which provides the bioenergetic basis for neurotransmission.”
From Vitamins and Minerals for Energy, Fatigue and Cognition: A Narrative Review of the Biochemical and Clinical Evidence (2020) · cites this paper as [28]
The proportional energy need of the adult human brain is more than twice that of adult non-primate vertebrates, which allocate only 2% to 8% of their basal metabolism to their brain; this may be related to the higher development and larger neuronal number of the human brain.
“The proportional energy need of the adult human brain is more than twice that of adult non-primate vertebrates, which allocate only 2% to 8% of their basal metabolism to their brain; this may be related to the higher development and larger neuronal number of the human brain [28].”
From Vitamins and Minerals for Energy, Fatigue and Cognition: A Narrative Review of the Biochemical and Clinical Evidence (2020) · cites this paper as [28]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Cerebellar O/N variation is understated
MinorThe cerebellar O/N values range from 0.067 to 0.232, a 3.46-fold variation, not the reported 1.4-fold variation.
Reported 1.4 · recomputed 3.462687
“| variation | 2750× | 3.4× | 812× | 1635× | 2.3× | 1.4× | 1.7× |”
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“Although energy is recognized as a limiting factor for the human 277 cerebral cortex (Herculano-Houzel 2011; Niven and Laughlin 2008), the increase in lactate 278 concentration occurring upon sensory stimulation is not the result of limited oxygen availability 279 (Aalling et al.”
Background
- Authors
- Herculano-Houzel, S.
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2011-03-01
- Volume
- 6
- Issue
- 3
- Pages
- e17514
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC3046985
- OpenAlex
- W1997267143
- Semantic Scholar
- 5396f2be11c9bc4ff205011a5f4a6008b291c420
- Cited by
- 343
- References
- 71
- Citations by year
- 2026: 21 · 2025: 20 · 2024: 34 · 2023: 22 · 2022: 39 · 2021: 31 · 2020: 25 · 2019: 20 · 2018: 15 · 2017: 17 · 2016: 20 · 2015: 18 · 2014: 23 · 2013: 22 · 2012: 14
- FWCI
- 8.01
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS ONE (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- James S. McDonnell Foundation
- Conselho Nacional de Desenvolvimento Científico e Tecnológico
- Institute for Translational Neuroscience
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Physical Sciences › Environmental Science › Ecology › Physiological and biochemical adaptations
- Keywords
- brain scaling, neuronal density, cerebral cortex, cerebellum, synaptic homeostasis, synaptic plasticity, neuronal firing rate, brain evolution, rodents, primates, glial cells
- MeSH terms
- Animals, Brain, Cell Count, Cerebellum, Cerebral Cortex, Energy Metabolism, Biological Evolution, Glucose, Humans, Neuronal Plasticity, Neurons, Oxygen Consumption
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.
Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-09.
Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-09.
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 ›
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