The DOI matches its Crossref record; 75 of the 93 references it cites were found in a registry or an index; 11 of the 76 sources its claims cite were checked for support.
The human brain in numbers: a linearly scaled-up primate brain
Open accessAbstract
The human brain has often been viewed as outstanding among mammalian brains: the most cognitively able, the largest-than-expected from body size, endowed with an overdeveloped cerebral cortex that represents over 80% of brain mass, and purportedly containing 100 billion neurons and 10x more glial cells. Such uniqueness was seemingly necessary to justify the superior cognitive abilities of humans over larger-brained mammals such as elephants and whales. However, our recent studies using a novel method to determine the cellular composition of the brain of humans and other primates as well as of rodents and insectivores show that, since different cellular scaling rules apply to the brains within these orders, brain size can no longer be considered a proxy for the number of neurons in the brain. These studies also showed that the human brain is not exceptional in its cellular composition, as it was found to contain as many neuronal and non-neuronal cells as would be expected of a primate brain of its size. Additionally, the so-called overdeveloped human cerebral cortex holds only 19% of all brain neurons, a fraction that is similar to that found in other mammals. In what regards absolute numbers of neurons, however, the human brain does have two advantages compared to other mammalian brains: compared to rodents, and probably to whales and elephants as well, it is built according to the very economical, space-saving scaling rules that apply to other primates; and, among economically built primate brains, it is the largest, hence containing the most neurons. These findings argue in favor of a view of cognitive abilities that is centered on absolute numbers of neurons, rather than on body size or encephalization, and call for a re-examination of several concepts related to the exceptionality of the human brain.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
39 Own interpretation · 28 No full text of the sources · 13 Own result · 12 Not checked yet · 8 No basis given · 5 Partly supported · 5 Sources not found · 4 Supported · 1 Supported so far · accuracy not yet measured
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“In the gray matter of the cerebral cortex, glial cells outnumber neurons by a factor of <2 (Sherwood et al., 2006; Pelvig et al., 2008).”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > Introduction > The human brain in numbers
What the sources say
- Partly supportedcites Sherwood et al., 2006 sourceExperimental — accuracy not yet measured
Table 2 (Results; page unavailable) reports glia–neuron ratios below 2 in several sampled frontal-cortex areas, including 1.65 in human area 9L. But the ratio is 2.19 in human area 4, and some sampled ratios are below 1, so the paper does not establish that glia outnumber neurons by a factor of less than 2 throughout cerebral cortical gray matter. (LLM, conf=0.90)
- Not checked — no full text of the sourcecites Pelvig et al., 2008 source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Partly supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“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).”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > A New View: Scaling of Neuronal Numbers > Cellular scaling rules for rodent, insectivore, and primate brains
What the sources say
- Supportedcites Herculano-Houzel et al., 2006 source
The Abstract reports that, across six rodent species, all three brain divisions gain neurons and much greater numbers of nonneuronal cells as they grow. The Discussion states that the glia/neuron index increases with brain mass. Our copy does not provide page numbers for these passages. (LLM, conf=0.88)
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“there is no significant correlation between brain size and general cognitive ability within families (Schoenemann et al., 2000)”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > The Human Brain is a Linearly Scaled-Up Primate Brain in its Number of Neurons. What Now? > Intraspecific variability in size, numbers and abilities
What the sources say
- Supportedcites Schoenemann et al., 2000 source
The Abstract reports that within-family correlations between neuroanatomy and general cognitive ability were essentially zero in 36 sibling pairs. The Discussion likewise says that the positive association seen in the general population was not found among sisters in the same families. (LLM, conf=0.93)
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Supported
In the paper
“Instead, the number of neurons in the cerebral cortex increases coordinately with the number of neurons in the cerebellum (Herculano-Houzel, submitted).”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > Brain and Body Scaling: The Traditional View > Assumption 3: proportions and relative size matter
What the sources say
- Not matchedcites Herculano-Houzel, submitted
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
correlational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Not matched
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“the human brain is not exceptional in its cellular composition, as it was found to contain as many neuronal and non-neuronal cells as would be expected of a primate brain of its size.”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > Abstract
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“this fractional number of neurons in the cerebral cortex relative to the whole brain is not correlated with the relative size of the cerebral cortex (Figure 2).”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > Brain and Body Scaling: The Traditional View > Assumption 3: proportions and relative size matter
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“with 1468 million neurons, owl monkeys have almost twice as many neurons in the brain as agoutis (which hold 857 million)”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > A New View: Scaling of Neuronal Numbers > Not all brains are created equal: cognitive abilities and numbers of neurons
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“a similar 10-fold increase in the number of neurons in a primate brain results in an increase in brain size of only 11-fold”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > A New View: Scaling of Neuronal Numbers > Cellular scaling rules for rodent, insectivore, and primate brains
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“the capuchin monkey brain has more than twice the number of neurons of the larger-brained capybara (3.7 billion against 1.6 billion)”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > A New View: Scaling of Neuronal Numbers > Not all brains are created equal: cognitive abilities and numbers of neurons
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“a 10-fold increase in the number of neurons in a rodent brain results in a 35-fold larger brain”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > A New View: Scaling of Neuronal Numbers > Cellular scaling rules for rodent, insectivore, and primate brains
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Probably not a substantial claim. 20
- It may state two separate claims as one. 48
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Among birds, those that are larger-brained (corvids, parrots and owls) are also considered the most intelligent (Lefebvre et al., 2004).”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > Introduction > Why bother with cell numbers?
What the sources say
- Partly supportedcites Lefebvre et al., 2004 sourceExperimental — accuracy not yet measured
The “Neural and Cognitive Correlates of Innovation in Birds” section identifies corvids, parrots, and owls among larger-brained birds and reports a general association between brain size and cognitive measures. It does not establish that these three groups are considered the most intelligent; in particular, the passage listing owls does not link them to superior cognition. Page numbers are unavailable in our copy. (LLM, conf=0.84)
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Partly supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Absolute brain mass and number of neurons, left out of the encephalization equation, must clearly be taken into consideration, since the “exceeding number of neurons” in a large brain should necessarily be larger than that in a smaller brain of same EQ (Herculano-Houzel, 2007).”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > Brain and Body Scaling: The Traditional View > Assumption 1: body size matters
What the sources say
- Partly supportedcites Herculano-Houzel, 2007 sourceExperimental — accuracy not yet measured
The ‘Implications for Volume Comparisons Across Orders’ section says that comparisons of brain size should consider neuronal counts directly, not just brain volume. The paper also relates larger primate brain structures to greater numbers of neurons. It does not address encephalization quotient (EQ) or establish that a larger brain has more ‘exceeding’ neurons than a smaller brain with the same EQ; no page numbers are available in our copy. (LLM, conf=0.86)
boosteddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
- Rests on an assumption: Cognitive abilities can be meaningfully compared across species.
- Partly supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“we have suggested that, rather than humans having a larger brain than expected, it is the great apes such as orangutans and, more notably, gorillas that have bodies that are much larger than expected for primates of their brain size (Herculano-Houzel et al., 2007).”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > Brain and Body Scaling: The Traditional View > Assumption 1: body size matters
What the sources say
- Partly supportedcites Herculano-Houzel et al., 2007 sourceExperimental — accuracy not yet measured
Split into 2 atoms — 0 confirmed, 2 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Partly supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“primate brain size increases approximately isometrically as a function of neuron number, with no systematic change in neuronal density or in the non-neuronal/neuronal ratio with increasing brain size”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > A New View: Scaling of Neuronal Numbers > Cellular scaling rules for rodent, insectivore, and primate brains
What the sources say
- Supportedcites Herculano-Houzel et al., 2007 source
The Discussion states that primate brain size increases linearly with neuron number, neuronal densities remain stable, and the nonneuronal-to-neuronal cell ratio does not correlate with brain mass. These findings support all three parts of the paraphrase. (LLM, conf=0.94)
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“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).”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > A New View: Scaling of Neuronal Numbers > Cellular scaling rules for rodent, insectivore, and primate brains
What the sources say
- Supportedcites Herculano-Houzel et al., 2006 source
The Results report that brain mass increases faster than neuron number across the six rodent species, while neuronal density decreases and nonneuronal cell density varies very little with structure size. The Discussion says neurons increase in average size as their numbers increase; the paper treats that size change as an estimate rather than a direct measurement. (LLM, conf=0.93)
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Supported
The sources with a verdict support this claim; the rest weren’t checked yet, have no full text we could read, or their verdicts aren’t rated yet.
In the paper
“Different mammalian orders have traditionally been pooled together in studies of brain allometry, as if their brains were built according to the same scaling rules (for example, Haug, 1987; Zhang and Sejnowski, 2000).”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > Brain and Body Scaling: The Traditional View > Assumption 2: brain size matters
What the sources say
- Not checked — no full text of the sourcecites Haug, 1987 source
- Supportedcites Zhang and Sejnowski, 2000 source
Section 2 (Empirical Scaling Law; page not provided) analyzes 59 mammalian species together under a single gray–white matter power law. The Introduction also describes earlier scaling studies using data from different species. This paper therefore serves as an example of pooling mammalian species under a shared scaling rule, though it does not explicitly classify them by order. (LLM, conf=0.88)
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“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).”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > Brain and Body Scaling: The Traditional View > Assumption 3: proportions and relative size matter
What the sources say
- Partly supportedcites Herculano-Houzel et al., 2006 sourceExperimental — accuracy not yet measured
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)
- Partly supportedcites Herculano-Houzel et al., 2007 sourceExperimental — accuracy not yet measured
In “Fractional Distribution of MBR and Neurons” (page unavailable), the paper reports that the cerebral cortex contains 18.9–41.8% of brain neurons in the primates examined, with 41.8% in the squirrel monkey (Saimiri). It does not establish the claimed 15-of-18-species distribution or the figures for moles, mice, and humans; its reported cortical mass range is 66.8–79.9% for the examined primates. (LLM, conf=0.88)
- Not matchedcites Sarko et al., 2009
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Partly supported
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“an informal survey with senior neuroscientists that we ran in 2007 showed that most believed that the number of cells in the human brain was indeed already known: that we have about 100 billion neurons, outnumbered by about 10 times more glial cells – but none of the consulted scientists could cite an original reference for these numbers”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > Introduction > The human brain in numbers
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“the so-called overdeveloped human cerebral cortex holds only 19% of all brain neurons, a fraction that is similar to that found in other mammals.”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > Abstract
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“the human cerebral cortex, which represents 82% of brain mass, holds only 19% of all neurons in the human brain”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > A New View: Scaling of Neuronal Numbers > The cellular composition of the human brain
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“An examination of the cellular composition of the cerebellum of orangutans and one gorilla shows that the sizes of the cerebellum and cerebral cortex predicted for these species from the number of cells in the cerebellum match their actual sizes, which suggests that the brain of these animals indeed is built according to the same scaling rules that apply to humans and other primates (Herculano-Hou”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > A New View: Scaling of Neuronal Numbers > Predictions for great apes
What the sources say
- Not matchedcites Herculano-Houzel and Kaas, in preparation
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Not matched
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“the absolute number of neurons in the rodent and primate cerebral cortex does increase much faster in larger brains compared to the number of neurons in the combined brainstem, diencephalon and basal ganglia, and is accompanied by a similarly fast increase in the number of neurons in the cerebellum (Figure 5).”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > A New View: Scaling of Neuronal Numbers > The cellular composition of the human brain
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“compared to rodents, and probably to whales and elephants as well, it is built according to the very economical, space-saving scaling rules that apply to other primates”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > Abstract
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“led two authors to conclude that the “factors that correlate better with intelligence (across species) are the number of cortical neurons and conduction velocity, as the basis for information processing” (Roth and Dicke, 2005).”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > Introduction > Why bother with cell numbers?
What the sources say
- Not checked — no full text of the sourcecites Roth and Dicke, 2005 source
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
None of the sources cited for this claim have been checked yet.
In the paper
“Many original articles, reviews and textbooks affirm that we have 100 billion neurons and 10 times more glial cells (Kandel et al., 2000; Ullian et al., 2001; Doetsch, 2003; Nishiyama et al., 2005; Noctor et al., 2007; Allen and Barres, 2009), usually with no references cited.”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > Introduction > The human brain in numbers
What the sources say
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A claim is checked only against the cited paper’s full text, never its abstract, and none is available for its sources.
In the paper
“These authors estimated the number of neurons in the human brain at about 85 billion: 12–15 billion in the telencephalon (Shariff, 1953), 70 billion in the cerebellum, as granule cells (based on Lange, 1975), and fewer than 1 billion in the brainstem.”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > Introduction > The human brain in numbers
What the sources say
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“among economically built primate brains, it is the largest, hence containing the most neurons.”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > Abstract
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“since different cellular scaling rules apply to the brains within these orders, brain size can no longer be considered a proxy for the number of neurons in the brain.”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > Abstract
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“the only possible explanation for the ubiquitous quote of 10 times more glial than neuronal cells in the entire human brain would be the presence of nearly one trillion glial cells in the remaining structures alone – an unlikely scenario, since these structures represent <10% of total brain mass.”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > Introduction > The human brain in numbers
What the sources say
- Not checked — no full text of the sourcecites Andersen et al., 1992 source
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Monkeys, for instance, possess brains that are much smaller than those of ungulates, but the higher cognitive and behavioral flexibility of monkeys over ungulates is anecdotally evident to any observer who compares the ingenious and complex abilities of macaques to those of cows or horses, even though the latter have 4–5× larger brains than macaques.”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > Introduction > Why bother with cell numbers?
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds. It may state two separate claims as one.
- Rests on an assumption: Cognitive abilities can be meaningfully compared across species.
In the paper
“Across species, the number of neurons and their relative abundance in different parts of the brain is widely considered to be a determinant of neural function and, consequently, of behavior (Williams and Herrup, 1988).”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > Introduction > Why bother with cell numbers?
What the sources say
- Not checked — no full text of the sourcecites Williams and Herrup, 1988 source
boosteddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This is evidence that the cellular scaling rules considered here from a set of primate species also extend to primates as a whole, and can be used to infer the expected cellular composition of the human brain”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > A New View: Scaling of Neuronal Numbers > Cellular scaling rules for rodent, insectivore, and primate brains
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“Across insectivore species, on the other hand, the cerebellum increases linearly in size as a function of its number of neurons (as in primates), while the cerebral cortex increases in size hypermetrically as it gains neurons (as in rodents; Sarko et al., 2009).”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > A New View: Scaling of Neuronal Numbers > Cellular scaling rules for rodent, insectivore, and primate brains
What the sources say
- Not matchedcites Sarko et al., 2009
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Not matched
None of the sources cited for this claim have been checked yet.
In the paper
“These findings corroborated previous studies describing neuronal density decreasing and the glia-to-neuron ratio increasing with increasing brain size across mammalian taxa (Tower and Elliot, 1952; Shariff, 1953; Friede, 1954; Tower, 1954; Hawking and Olszewski, 1957; Haug, 1987; Reichenbach, 1989; Stolzenburg et al., 1989).”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > A New View: Scaling of Neuronal Numbers > Cellular scaling rules for rodent, insectivore, and primate brains
What the sources say
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“our quantitative studies on the cellular scaling rules that apply to different mammalian orders have shown that this assumption is invalid and therefore should no longer be applied”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > Brain and Body Scaling: The Traditional View > Assumption 2: brain size matters
boosted- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“With a brain of only 52 g, the behavioral, social and cognitive repertoire of the capuchin monkey is outstanding compared to the capybara, a giant Amazonian rodent (MacDonald, 1981), even though the latter has a larger brain of 75 g.”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > Introduction > Why bother with cell numbers?
What the sources say
- Not checked — no full text of the sourcecites MacDonald, 1981 source
plaincorrelationalSingle case- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: Cognitive abilities can be meaningfully compared across species.
A claim is checked only against the cited paper’s full text, never its abstract, and none is available for its sources.
In the paper
“Capuchin monkeys, for instance, have much larger EQs than gorillas (Marino, 1998), but are outranked by these in cognitive performance (Deaner et al., 2007).”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > Brain and Body Scaling: The Traditional View > Assumption 1: body size matters
What the sources say
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: Cognitive abilities can be meaningfully compared across species.
In the paper
“if primates have big brains merely because they have small bodies, we cannot presume that this represents an evolutionary trend driven by cognitive demands”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > Brain and Body Scaling: The Traditional View > Assumption 1: body size matters
What the sources say
- Not checked — no full text of the sourcecites Deacon, 1997 source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A claim is checked only against the cited paper’s full text, never its abstract, and none is available for its sources.
In the paper
“Brain size varies across mammals by a factor of approximately 100,000 (Tower, 1954; Stolzenburg et al., 1989).”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > Brain and Body Scaling: The Traditional View > Assumption 2: brain size matters
What the sources say
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“compared to other mammalian orders, primate encephalization is the result of a shift in postcranial growth processes, not a modification of brain growth (Deacon, 1997).”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > Brain and Body Scaling: The Traditional View > Assumption 1: body size matters
What the sources say
- Not checked — no full text of the sourcecites Deacon, 1997 source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Compared to mammals as a whole, humans have the largest EQ found for any mammal, of between 7 and 8 (Jerison, 1973)”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > Brain and Body Scaling: The Traditional View > Assumption 1: body size matters
What the sources say
- Not checked — no full text of the sourcecites Jerison, 1973
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“like in other non-anthropoid primates, the human brain mass represents about 2% of body mass.”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > Brain and Body Scaling: The Traditional View > Assumption 1: body size matters
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“a generic rodent brain of human-sized proportions, weighing 1.5 kg: such a brain would have only 12 billion neurons, and a much larger number of 46 billion non-neuronal cells”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > A New View: Scaling of Neuronal Numbers > Not all brains are created equal: cognitive abilities and numbers of neurons
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“the distribution of cortical mass in humans may differ from that in other primates, endowing particularly relevant regions such as area 10 with relatively more neurons in the human cortex (Semendeferi et al., 2001).”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > Brain and Body Scaling: The Traditional View > Assumption 3: proportions and relative size matter
What the sources say
- Not checked — no full text of the sourcecites Semendeferi et al., 2001 source
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“although gorillas and orangutans overlap or exceed humans in body size, their brains amount to only about one-third of the size of the human brain.”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > Brain and Body Scaling: The Traditional View > Assumption 1: body size matters
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds. It may state two separate claims as one.
In the paper
“even if compared to anthropoid primates only, humans still have an EQ of over 3, a value that is larger than that obtained for any other primate or cetacean (Marino, 1998).”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > Brain and Body Scaling: The Traditional View > Assumption 1: body size matters
What the sources say
- Not checked — no full text of the sourcecites Marino, 1998 source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The very concept of encephalization presupposes that not only the brain scales as a function of body size, but that all brains scale the same way, such that the only informative (and sufficient) variable is brain size and its deviation from the expected.”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > Brain and Body Scaling: The Traditional View > Assumption 2: brain size matters
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds. It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“its relatively large cerebral cortex, which accounts for 82% of brain mass.”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > Brain and Body Scaling: The Traditional View > Assumption 3: proportions and relative size matter
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“according to this notion, small-brained animals with very large EQs should be expected to have more cognitive abilities than large-brained animals with smaller EQs.”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > Brain and Body Scaling: The Traditional View > Assumption 1: body size matters
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
- Rests on an assumption: Cognitive abilities can be meaningfully compared across species.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“By maintaining the average neuronal size (including all arborizations) invariant as brain size changes, primate brains scale in size in a much more space-saving, economical manner compared to the inflationary growth that occurs in rodents, in which larger numbers of neurons are accompanied by larger neurons.”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > A New View: Scaling of Neuronal Numbers > Not all brains are created equal: cognitive abilities and numbers of neurons
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A claim is checked only against the cited paper’s full text, never its abstract, and none is available for its sources.
In the paper
“This assumption, which was justifiable by the lack of direct estimates of the neuronal composition of the brain of different species, is so widespread that it implicitly or explicitly underlies most comparative studies to date (for example, Haug, 1987; Finlay and Darlington, 1995; Barton and Harvey, 2000; Clark et al., 2001).”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > Brain and Body Scaling: The Traditional View > Assumption 2: brain size matters
What the sources say
boostedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
In the paper
“the human brain exhibits a further modification in that it continues to grow as though in a larger body (Deacon, 1997).”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > Brain and Body Scaling: The Traditional View > Assumption 1: body size matters
What the sources say
- Not checked — no full text of the sourcecites Deacon, 1997 source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“sheer size alone, or in relation to body size, is not an adequate parameter to qualify, or disqualify, the human brain as “special””
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > A New View: Scaling of Neuronal Numbers > Do we have the most neurons? predictions for other large-brained mammals
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“our standing among primates as the proud owners of the largest living brain assures that, at least among primates, we enjoy the largest number of neurons from which to derive cognition and behavior as a whole”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > The Human Brain is a Linearly Scaled-Up Primate Brain in its Number of Neurons. What Now? > Concluding remarks: our place in nature
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“the enlargement of the cerebral cortex is not, in principle, an exclusive feature of the human brain: a similar expansion of the mass of the cerebral cortex, relative to the whole brain, is predicted by both the rodent and primate cellular scaling rules, irrespective of the number of neurons contained in the cortex (Table 2).”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > A New View: Scaling of Neuronal Numbers > The cellular composition of the human brain
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“if the same linear scaling rules are considered to apply to great apes as to other primates, then similar three-fold differences in brain size and in brain neurons alike apply to humans compared to gorillas, and to gorillas compared to baboons”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > The Human Brain is a Linearly Scaled-Up Primate Brain in its Number of Neurons. What Now? > Cognitive abilities, brain size and number of neurons
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds. It may state two separate claims as one.
In the paper
“Azevedo et al. (2009), who found that the adult male human brain, at an average of 1.5 kg, has 86 billion neurons and 85 billion non-neuronal cells – numbers that deviate from the expected by 7 and 24% only.”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > A New View: Scaling of Neuronal Numbers > The cellular composition of the human brain
What the sources say
- Not checked — no full text of the sourcecites Azevedo et al. (2009) source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“the human brain scales as a primate brain: this economical property of scaling alone, compared to rodents, assures that the human brain has many more neurons than would fit into a rodent brain of similar size, and possibly into any other similar-sized brain”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > The Human Brain is a Linearly Scaled-Up Primate Brain in its Number of Neurons. What Now? > Concluding remarks: our place in nature
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This generic primate brain should have a cerebral cortex of about 1.4 kg, containing 25 billion neurons, and a cerebellum weighing 120 g, with 70 billion neurons (Table 2).”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > A New View: Scaling of Neuronal Numbers > The cellular composition of the human brain
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“a hypothetical rodent brain with 86 billion neurons, like the human brain, would be predicted to weigh overwhelming 35 kg – a value that is way beyond the largest known brain mass of 9 kg for the blue whale, and probably physiologically unattainable”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > A New View: Scaling of Neuronal Numbers > Do we have the most neurons? predictions for other large-brained mammals
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“it becomes increasingly likely that humans do not have truly unique cognitive abilities, and hence must differ from these animals not qualitatively, but rather in the combination and extent of abilities such as theory of mind, imitation and social cognition (Marino et al., 2009).”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > The Human Brain is a Linearly Scaled-Up Primate Brain in its Number of Neurons. What Now? > Cognitive abilities, brain size and number of neurons
What the sources say
- Not matchedcites Marino et al., 2009
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Not matched
None of the sources cited for this claim have been checked yet.
In the paper
“although men have been reported to have more neurons in the cerebral cortex than women (Pakkenberg and Gundersen, 1997; Pelvig et al., 2008)”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > The Human Brain is a Linearly Scaled-Up Primate Brain in its Number of Neurons. What Now? > Intraspecific variability in size, numbers and abilities
What the sources say
- Not matchedcites Pakkenberg and Gundersen, 1997
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not checked — no full text of the sourcecites Pelvig et al., 2008 source
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Because of the diverging power laws that relate brain size and number of neurons across rodents and primates, the latter can hold more neurons in the same brain volume, with larger neuronal densities than found in rodents.”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > A New View: Scaling of Neuronal Numbers > The cellular composition of the human brain
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“the increase in cognitive abilities afforded by increasing the number of neurons in the brain can be expected to increase exponentially with absolute number of neurons, and might even be subject to a thresholding effect once critical points of information processing are reached”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > The Human Brain is a Linearly Scaled-Up Primate Brain in its Number of Neurons. What Now? > Cognitive abilities, brain size and number of neurons
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Since neuronal density does not scale with brain size in primates, but decreases with increasing brain size in rodents, the larger the brain size, the larger is the difference in number of neurons across similar-sized rodent and primate brains.”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > A New View: Scaling of Neuronal Numbers > The cellular composition of the human brain
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“The human cerebral cortex, with an average 1233 g and 16 billion neurons, is slightly below expectations for a primate brain of 1.5 kg”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > A New View: Scaling of Neuronal Numbers > The cellular composition of the human brain
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“glial cells in the human brain are at most 50% of all brain cells, which is an important finding since it is one more brain characteristic that we share with other primates (Azevedo et al., 2009)”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > The Human Brain is a Linearly Scaled-Up Primate Brain in its Number of Neurons. What Now? > Concluding remarks: our place in nature
What the sources say
- Not checked — no full text of the sourcecites Azevedo et al., 2009 source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A claim is checked only against the cited paper’s full text, never its abstract, and none is available for its sources.
In the paper
“Not only the extent of intraspecific variation is much smaller (on the order of 10–50%) than interspecific variation (which spans five orders of magnitude within mammals; Tower, 1954; Stolzenburg et al., 1989)”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > The Human Brain is a Linearly Scaled-Up Primate Brain in its Number of Neurons. What Now? > Intraspecific variability in size, numbers and abilities
What the sources say
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“while the human cerebellum, at 154 g and 69 billion neurons, matches or even slightly exceeds the expected (Table 2)”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > A New View: Scaling of Neuronal Numbers > The cellular composition of the human brain
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“According to one estimate, the false killer whale and the African elephant would have about 11 billion neurons in the cerebral cortex, despite their large size – and fewer neurons than the 11.5 billion estimated by the same method for the human cerebral cortex, though only marginally so (Roth and Dicke, 2005).”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > A New View: Scaling of Neuronal Numbers > Do we have the most neurons? predictions for other large-brained mammals
What the sources say
- Not checked — no full text of the sourcecites Roth and Dicke, 2005 source
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“According to these rules, a generic primate brain of 1.5 kg should have 93 billion neurons, and 112 billion non-neuronal cells: glial cells, thus, should constitute at most half of all brain cells.”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > A New View: Scaling of Neuronal Numbers > The cellular composition of the human brain
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper relies on this without support.
Humans are more cognitively capable than larger-brained mammals such as elephants and whales.
“Such uniqueness was seemingly necessary to justify the superior cognitive abilities of humans over larger-brained mammals such as elephants and whales.”
The paper relies on this without support.
Cognitive abilities can be meaningfully compared across species.
“the higher cognitive and behavioral flexibility of monkeys over ungulates is anecdotally evident to any observer who compares the ingenious and complex abilities of macaques to those of cows or horses”
The paper relies on this without support.
Non-neuronal cell densities are similar across species.
“In view of the similar non-neuronal cell densities across species”
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 source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Our neural network parameters represent a computational analog to biological neural capacity, directly reflecting the studies showing strong correlations between brain volume and total neuron count across species, humans, and mice brains (68–70).”
From What if eye...? Computationally recreating vision evolution (2025) · cites this paper as [68]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“The average number of glial cells in the human brain is estimated to be 84.61 ± 9.83 × 109 (Herculano-Houzel, 2009), with the population of glial cells in the neocortex estimated at from 18.2 to 38.6 × 109”
From Human Brain/Cloud Interface (2019) · cites this paper as Herculano-Houzel, 2009
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“We suggest that corvid brains are scaled-up songbird brains, just as humans brains are to brains of nonhuman primates (38, 47)”
From Birds have primate-like numbers of neurons in the forebrain (2016) · cites this paper as [47]
In the citing paper
“the relative homogeneity of the two largest neuronal structures, with ~69 billion (cerebellar cortex) and ~16 billion (cortex) neurons out of the 86 billion neurons in the human brain33, is striking and suggests an evolutionary expansion of a canonical cortical blueprint34.”
From An anatomically comprehensive atlas of the adult human brain transcriptome (2012) · cites this paper as [33]
In the citing paper
“The neocortex alone contains approximately 16.34 billion neurons (Herculano-Houzel, 2009) and 164 trillion synapses, points of communication between neurons (Tang et al., 2001).”
From The Cellular and Molecular Landscapes of the Developing Human Central Nervous System (2016) · cites this paper as Herculano-Houzel, 2009
In the citing paper
“The human CNS is possibly the most complex biological tissue, comprising on average 86.1 billion neurons in the brain and spinal cord in males, along with a roughly equal number of glial cells (Herculano-Houzel, 2009; Herculano-Houzel et al., 2015).”
From The Cellular and Molecular Landscapes of the Developing Human Central Nervous System (2016) · cites this paper as Herculano-Houzel, 2009
In the citing paper
“which is an order of magnitude more than the total number of cells in the brain of mouse, rat, and many other mammals (Herculano-Houzel, 2009).”
From The Cellular and Molecular Landscapes of the Developing Human Central Nervous System (2016) · cites this paper as Herculano-Houzel, 2009
In the citing paper
“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 [44]
In the citing paper
“We have shown previously that the human brain conforms to the neuronal scaling rules that apply to other primates [27], [44].”
From Scaling of Brain Metabolism with a Fixed Energy Budget per Neuron: Implications for Neuronal Activity, Plasticity and Evolution (2011) · cites this paper as [44]
In the citing paper
“The cortical reorganization hypothesis suggests that selection for absolutely larger brains-and concomitant cortical reorganization-was the predominant mechanism supporting cognitive evolution (77, 91, 100-106, 120).”
From The evolution of self-control. (2014) · cites this paper as [106]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > The Human Brain is a Linearly Scaled-Up Primate Brain in its Number of Neurons. What Now? > Concluding remarks: our place in nature
“a cerebral cortex that is exactly as large as expected for a primate brain of 1.5 kg”
§ The Human Brain in Numbers: A Linearly Scaled-up Primate Brain > A New View: Scaling of Neuronal Numbers > The cellular composition of the human brain
“The human cerebral cortex, with an average 1233 g and 16 billion neurons, is slightly below expectations for a primate brain of 1.5 kg”
Citations
Cites
Two new Later Stone Age sites from the Final Pleistocene in the Falémé Valley, eastern Senegal
Ndiaye, M., Lespez, L., Tribolo, C., Rassé, M., Hadjas, I., Davidoux, S., Huysecom, É., & Douze, K. (2024) · Monash University Research Portal (Monash University) · doi:10.3929/ethz-b-000667478 · Cited by 24,214
(1982) · Trends in Neurosciences · doi:10.1016/0166-2236(82)90076-5 · Cited by 9,150
Henry, M. A. (1995) · The Journal of the American Dental Association · doi:10.14219/jada.archive.1995.0108 · Cited by 3,454
Changes in grey matter induced by training
Draganski, B., Gaser, C., Busch, V., Schuierer, G., Bogdahn, U., & May, A. (2004) · Nature · doi:10.1038/427311a · Cited by 2,373
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-citationEVOLUTION OF THE BRAIN AND INTELLIGENCE
Radinsky, L., & Jerison, H. J. (1975) · Evolution · doi:10.2307/2407154 · Cited by 1,982
Control of Synapse Number by Glia
Ullian, E. M., Sapperstein, S. K., Christopherson, K. S., & Barres, B. A. (2001) · Science · doi:10.1126/science.291.5504.657 · Cited by 1,380 · cited 1×
“Recent efforts to support this uniqueness have focused on fi nding genetic differences between humans and other primates (reviewed in Vallender, 2008), as well as cellular particularities such as the presence and distribution of Von Economo neurons (Nimchinsky et al., 1999; but see Butti et al.,…”
Linked Regularities in the Development and Evolution of Mammalian Brains
Finlay, B. L., & Darlington, R. B. (1995) · Science · doi:10.1126/science.7777856 · Cited by 1,217 · cited 2×
“This assumption, which was justifi able by the lack of direct estimates of the neuronal composition of the brain of different species, is so widespread that it implicitly or explicitly underlies most comparative studies to date (for example, Haug, 1987; Finlay and Darlington, 1995; Barton and Harvey, 2000; Clark et al…”
Black, J. E., Isaacs, K. R., Anderson, B. J., Alcantara, A. A., & Greenough, W. T. (1990) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.87.14.5568 · Cited by 1,161
The primate cortico-cerebellar system: anatomy and function
Ramnani, N. (2006) · Nature Reviews Neuroscience · doi:10.1038/nrn1953 · Cited by 1,011 · cited 2×
“…as changes in the relative size of functional cortical areas (for instance, Semendeferi et al., 2001; Rilling and Seligman, 2002), in the volume of prefrontal white matter (Schoenemann et al., 2005) or in the size of specifi c portions of the cerebellum (Ramnani, 2006) may play in human cognition.”
Cited by
Sorted by citations
Items 501–600 of 1,776
RGS5 augments astrocyte activation and facilitates neuroinflammation via TNF signaling
Yin, S., Ma, X., Sun, Y., Yin, Y., Long, Y., Zhao, C.-L., Ma, J.-W., Li, S., Yan, H., Li, M., et al. (2023) · Journal of Neuroinflammation · doi:10.1186/s12974-023-02884-w · Cited by 23
Multi-scale spiking network model of human cerebral cortex
Pronold, J., van Meegen, A., Shimoura, R. O., Vollenbröker, H., Senden, M., Hilgetag, C. C., Bakker, R., & van Albada, S. J. (2024) · Cerebral Cortex · doi:10.1093/cercor/bhae409 · Cited by 26
“With the number of gray matter neurons in human, N total neuron = 16 × 10 9 (Herculano-Houzel 2009),we arrive at the estimate N nonlocal neuron / N total neuron = 0.14 or N local neuron / N total neuron = 0.86 for human cortex.”
InfluentialNeural Dynamics Based Timing in the Subsecond to Seconds Range
Buonomano, D. V. (2014) · Advances in experimental medicine and biology · doi:10.1007/978-1-4939-1782-2_6 · Cited by 23
“The cerebellum has a class of neurons termed granule cells, and these are the most common type of neuron in your brain—more than half the neurons in the brain are granule neurons [10].”
BackgroundZainuddin, Z., Huong, L. K., & Ong, P. (2012) · Procedia Computer Science · doi:10.1016/j.procs.2012.09.016 · Cited by 23
“5 kg, and it is estimated that it contains as many as 93 billion neurons and 112 billion non-neuronal cells [1].”
BackgroundCommunicability distance reveals hidden patterns of Alzheimer’s disease
Lella, E., & Estrada, E. (2020) · Network Neuroscience · doi:10.1162/netn_a_00143 · Cited by 24
Cabrera, O. H., Dougherty, J. D., Singh, S., Swiney, B. S., Farber, N. B., & Noguchi, K. (2013) · Brain Research · doi:10.1016/j.brainres.2013.12.014 · Cited by 22
“The importance of the EGL in normal brain development and function is underscored by the fact that it produces 90% of the neurons in the cerebellum which represent over half the neurons in the brain (Andersen et al., 1992; Harvey and Napper, 1988; Herculano-Houzel, 2009).”
BackgroundNumber of Autonomous Cognitive Agents in a Neural Network
Kak, S. C. (2022) · Journal of Artificial Intelligence and Consciousness · doi:10.1142/s2705078522500023 · Cited by 22
Causes and Consequences of Genome Instability in Psychiatric and Neurodegenerative Diseases
Iourov, I. Y., Vorsanova, S. G., Куринная, О. С., Zelenova, M. A., Vasin, K. S., & Yurov, Y. B. (2021) · Molecular Biology · doi:10.1134/s0026893321010155 · Cited by 20
Using Organoids to Model Sex Differences in the Human Brain
Pavlinek, A., Adhya, D., Tsompanidis, A., Warrier, V., Baron‐Cohen, S., Allison, C. L., Warrier, V., Tsompanidis, A., Adhya, D., Holt, R., et al. (2024) · Biological Psychiatry Global Open Science · doi:10.1016/j.bpsgos.2024.100343 · Cited by 22
“The human cerebral cortex and cerebellum are signi fi cantly larger than those of other primates (38).”
Neurogenesis in the Adult Mammalian Brain: How Much Do We Need, How Much Do We Have?
Kazanis, I. (2012) · Current topics in behavioral neurosciences · doi:10.1007/7854_2012_227 · Cited by 20
“subsequently of gyrencephalia) and of connectivity, with the latter—among mammals—being correlated to the emergence of more complex patterns of behaviour (Herculano-Houzel 2009).”
BackgroundTakahata, T., Shukla, R., Yamamori, T., & Kaas, J. H. (2011) · Cerebral Cortex · doi:10.1093/cercor/bhr308 · Cited by 21
“A third possibility is that the amount of overexpression reflects the sizes of V1, which is small in rats and mice, larger in galagos, larger yet in marmosets, owl monkeys, and especially squirrel monkeys and much larger in macaques (Herculano-Houzel 2009).”
BackgroundMacroscopic Cerebral Tumor Growth Modeling From Medical Images: A Review
Elazab, A., AbdulAzeem, Y., Anter, A. M., Hu, Q., Wang, T., & Lei, B. (2018) · IEEE Access · doi:10.1109/access.2018.2839681 · Cited by 21
“Roughly estimated, human brain consists of 100 billion cells [2].”
BackgroundHuman exceptionalism, our ordinary cortex and our research futures
Finlay, B. L. (2019) · Developmental Psychobiology · doi:10.1002/dev.21838 · Cited by 22
Gustafsson, S. S., Sehlin, D., Lampa, E., Hammarlund‐Udenaes, M., & Loryan, I. (2019) · Scientific Reports · doi:10.1038/s41598-019-41828-4 · Cited by 23
Molecular drivers of human cerebral cortical evolution
Suzuki, I. (2019) · Neuroscience Research · doi:10.1016/j.neures.2019.05.007 · Cited by 22
The mitochondria as a potential therapeutic target in cerebral I/R injury
Fang, S., Huang, W., Qu, X.-H., & Chai, W. (2025) · Frontiers in Neuroscience · doi:10.3389/fnins.2024.1500647 · Cited by 26
Johnson, J. A. (2014) · Morgan Kaufmann Publishers Inc. eBooks · Cited by 21
Lambert, K. G., Hunter, R. G., Bartlett, A. A., Lapp, H. E., & Kent, M. (2019) · Frontiers in Neuroendocrinology · doi:10.1016/j.yfrne.2019.100802 · Cited by 23
Albumen based protein gated bioinspired neuromorphic transistors with learning abilities
Guo, L. Q., Li, Z. Y., Zhu, L. Q., Ren, Z. Y., Xiao, H., & Cai, J. C. (2020) · Organic Electronics · doi:10.1016/j.orgel.2020.105961 · Cited by 21
Cytoarchitectural characteristics associated with cognitive flexibility in raccoons
Jacob, J. C., Kent, M., Benson‐Amram, S., Herculano‐Houzel, S., Raghanti, M. A., Ploppert, E., Drake, J. H., Hindi, B., Natale, N. R., Daniels, S., et al. (2021) · The Journal of Comparative Neurology · doi:10.1002/cne.25197 · Cited by 22
Self-citationShin, S. S., Hefti, M. M., Mazandi, V. M., et al. (2022) · Journal of Neurotrauma · doi:10.1089/neu.2022.0070 · Cited by 21
“Pig brain has gyrencephalic complexity much closer to humans(24) and a large difference exists between the gray-white matter ratio as well as neuronal count between humans and rodents.(25) FIG.”
Messner, W. (2022) · International Journal of Information Management Data Insights · doi:10.1016/j.jjimei.2022.100118 · Cited by 27
Porcine spinal cord injury model for translational research across multiple functional systems
Ahmed, R. U., Knibbe, C. A., Wilkins, F., Sherwood, L. C., Howland, D. R., & Boakye, M. (2022) · Experimental Neurology · doi:10.1016/j.expneurol.2022.114267 · Cited by 22
An artificial optoelectronic synapse based on MoO x film
Zhao, J., Zheng, S., Zhou, L., Mi, W., Ding, Y., & Wang, M. (2023) · Nanotechnology · doi:10.1088/1361-6528/acb217 · Cited by 21
Zarzor, M. S., Blümcke, I., & Budday, S. (2023) · eLife · doi:10.7554/elife.82925 · Cited by 26
Monetizing Animal Welfare Impacts for Benefit–Cost Analysis
Budolfson, M., Espinosa, R., Fischer, B., & Treich, N. (2024) · Journal of Benefit-Cost Analysis · doi:10.1017/bca.2024.19 · Cited by 16
“…potential metrics – cortical neuron counts – where the ratio of the average number of forebrain neurons in a chicken brain to the average number of forebrain neurons in a human brain is taken to represent chickens ’ welfare potential (i.e., ~61M/~21B; Olkowicz et al., 2016; Herculano-Houzel, 2009).”
Noguchi, K. (2014) · Cells · doi:10.3390/cells3010036 · Cited by 20
“As the cerebellum actually contains more neurons than the cerebrum, the EGL produces over half (with some estimating over 80%) the neurons in the entire brain [25–27].”
BackgroundReal-time simulation of a cat-scale artificial cerebellum on PEZY-SC processors
Yamazaki, T., Igarashi, J., Makino, J., & Ebisuzaki, T. (2017) · The International Journal of High Performance Computing Applications · doi:10.1177/1094342017710705 · Cited by 21
Geometry processing of conventionally produced mouse brain slice images
Agarwal, N., Xu, X., & Gopi, M. (2018) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2018.04.008 · Cited by 21
“Second, such models play a vital role in studying the connectome or the wiring diagram of the mouse brain [29], computing the density and distribution of neurons [16] and analyzing the common gene expression patterns [33, 9].”
BackgroundCeravolo, S. A., Hammond, B. R., Oliver, W., Clementz, B. A., Miller, L. S., & Renzi‐Hammond, L. M. (2019) · Molecular Nutrition & Food Research · doi:10.1002/mnfr.201801051 · Cited by 21
Expansion coding and computation in the cerebellum: 50 years after the Marr–Albus codon theory
Sanger, T. D., Yamashita, O., & Kawato, M. (2019) · The Journal of Physiology · doi:10.1113/jp278745 · Cited by 24
“Thestriking expansion of representation in humans from approximately 250 million mossy fibres to more than 50 billion granule cells (Herculano-Houzel, 2009), followed by compression through 15 million Purkinje cells (Eccles et al. 1967) was the basis for the original codon theory.”
BackgroundInfluentialLu, W., Zeng, L., Wang, J., Xiang, S., Qi, Y., Zheng, Q., Xu, N., & Feng, J. (2024) · National Science Review · doi:10.1093/nsr/nwae080 · Cited by 23
“First, the scale of the human brain, with up to 86 billion neurons and 100 tri l lion synapses [5 ,6 ], including long-distance and irregular connections, creates great challenges for both high-performance computing systems [7 –11 ] and brain-inspired chips [12 – 16 ] to simulate a brain model of…”
BackgroundAdvancing Neural Networks: Innovations and Impacts on Energy Consumption
Fedorova, A., Jovišić, N., Vallverdú, J., Battistoni, S., Jovičić, M., Medojević, M., Toschev, A. S., Alshanskaia, E., Talanov, M. O., & Erokhin, V. V. (2024) · Advanced Electronic Materials · doi:10.1002/aelm.202400258 · Cited by 20
Gerum, R. C., & Schilling, A. (2021) · Neural Computation · doi:10.1162/neco_a_01424 · Cited by 21
“Thus, we do not need huge hardware components but are limited to approximately 10 11 neurons (Herculano-Houzel, 2009), which perform these tasks in a very efficient way.”
BackgroundDREADDs in Epilepsy Research: Network-Based Review
Mueller, J.-S., Tescarollo, F. C., & Sun, H. (2022) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2022.863003 · Cited by 21
“The required light stimulation when using optogenetics has posed challenges for its implementation in larger brains such as nonhuman primates due to the skull’s thickness (Herculano-Houzel, 2009; Watanabe et al., 2020).”
BackgroundRosin, J. M., McAllister, B. B., Dyck, R. H., Percival, C. J., Kurrasch, D. M., & Cobb, J. A. (2014) · Developmental Biology · doi:10.1016/j.ydbio.2014.12.013 · Cited by 20
Brain composition and scaling in social bee species differing in body size
Gowda, V., & Gronenberg, W. (2019) · Apidologie · doi:10.1007/s13592-019-00685-w · Cited by 20
“It is the number of neurons that contributes to the computational capacities of brains more than the overall volume of a brain or neuropil (Herculano-Houzel 2009), and one might therefore potentially expect to find increases in cognitive abilities in bumblebees compared with honeybees.”
BackgroundAssari, S. (2020) · Brain Sciences · doi:10.3390/brainsci10120956 · Cited by 20
Design and demonstration in vitro of a mouse-specific Transcranial Magnetic Stimulation coil
Khokhar, F., Voss, L., Steyn-Ross, D. A., & Wilson, M. T. (2020) · bioRxiv · doi:10.1109/tmag.2021.3077976 · Cited by 19
“Broadly, the mouse brain is smaller than the human brain by a factor of approximately ten in linear dimensions [40].”
BackgroundCo-operative Populations of Neurons: Mean Field Models of Mesoscopic Brain Activity
Liley, D. T. J., Foster, B. L., & Bojak, I. (2012) · Springer eBooks · doi:10.1007/978-94-007-3858-4_11 · Cited by 21
Yamamoto, M., Abe, H., Hirouchi, H., et al. (2021) · PLoS ONE · doi:10.1371/journal.pone.0251068 · Cited by 20
Connectomics to Semantomics: Addressing the Brain's Big Data Challenge1
Arsiwalla, X. D., Dalmazzo, D., Zucca, R., Betella, A., Brandi, S., Martinez, E., Omedas, P., & Verschure, P. F. M. J. (2015) · Procedia Computer Science · doi:10.1016/j.procs.2015.07.278 · Cited by 19
Governing sporting brains: concussion, neuroscience, and the biopolitical regulation of sport
Hardes, J. J. (2017) · Sport Ethics and Philosophy · doi:10.1080/17511321.2017.1281344 · Cited by 20
“Approximately 100 billion neurons in the brain that interact through the trillion synaptic connections have come to be regarded as the key to unlocking humanity and providing the answer to every element of human behavior (Herculano-Houzel 2009; Mahfoud 2014).”
BackgroundHaynes, E. M., Ulland, T. K., & Eliceiri, K. W. (2022) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2022.867010 · Cited by 24
“Human and non-human primates have large and complex brains, ranging in size from the ∼86 billion neurons of humans to the 634 million neurons of the marmoset (Herculano-Houzel, 2009).”
BackgroundCerebro-Cerebellar Networks in Migraine Symptoms and Headache
Noseda, R. (2022) · Frontiers in Pain Research · doi:10.3389/fpain.2022.940923 · Cited by 21
“Its computational power is involved in virtually all brain functions, and, despite being overshadowed in mass by the cerebral cortex (10%), particularly in humans, its energy demand is thought to be around 75% of the whole brain, which would be necessary to maintain the 2/3 of total brain cells that are exclusively co…”
BackgroundNeurobiology and Spirituality in Addiction Recovery.
Roy, A. K., Bowirrat, A., Smith, D. E., Braverman, E. R., Jalali, R., Badgaiyan, R. D., Baron, D. A., Llanos-Gomez, L., Barh, D., & Blum, K. (2021) · PubMed · Cited by 19
Developing guinea pig brain as a model for cortical folding
Hatakeyama, J., Sato, H., & Shimamura, K. (2017) · Development Growth & Differentiation · doi:10.1111/dgd.12371 · Cited by 18
“Many mammalian species including humans possess gyrencephalic cerebral cortices in which numerous convoluted folds and fissures are present (Welker 1990; Herculano-Houzel 2009; Defelipe 2011; Zilles et al. 2013).”
BackgroundNeural networks through stock market data prediction
Verma, R., Choure, P., & Singh, U. (2017) · International Conference on Electronics, Communication and Aerospace Technology (ICECA) · doi:10.1109/iceca.2017.8212717 · Cited by 19
“” – Nigrin (1993)[3,4,5]”
Applications of stable isotopes in MALDI imaging: current approaches and an eye on the future
Grey, A. C., Tang, M., Zahraei, A., et al. (2021) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-021-03189-8 · Cited by 19
Bertocchi, C., Goh, W. I., Zhang, Z., & Kanchanawong, P. (2013) · Critical Reviews in Biomedical Engineering · doi:10.1615/critrevbiomedeng.2014010448 · Cited by 20
Neuron Model with Simplified Memristive Ionic Channels
Hegab, A. M., Salem, N. M., Radwan, A. G., & Chua, L. O. (2015) · International Journal of Bifurcation and Chaos · doi:10.1142/s0218127415300177 · Cited by 19
Imaging microstructure in the living human brain: A viewpoint
Paus, T. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.10.013 · Cited by 19
“With cortical grey andwhite matter combined, the mass of cerebral cortex constitutes 82% of the total brain mass in humans (Herculano-Houzel, 2009).”
BackgroundMichelucci, P. E. (2013) · Springer eBooks · doi:10.1007/978-1-4614-8806-4_36 · Cited by 18
Biomimic and bioinspired soft neuromorphic tactile sensory system
Kang, K., Kim, K., Baek, J. H., Lee, D. J., & Yu, K. J. (2024) · Applied Physics Reviews · doi:10.1063/5.0204104 · Cited by 19
Biological Polymers: Evolution, Function, and Significance
Matange, K., Marland, E., Frenkel‐Pinter, M., & Williams, L. D. (2025) · Accounts of Chemical Research · doi:10.1021/acs.accounts.4c00546 · Cited by 20
Generation of Neural Organoids and Their Application in Disease Modeling and Regenerative Medicine
Huang, R., Gao, F., Yu, L., Chen, H., & Zhu, R. (2025) · Advanced Science · doi:10.1002/advs.202501198 · Cited by 20
The AI trilemma: Saving the planet without ruining our jobs
Ernst, E. (2022) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2022.886561 · Cited by 23
“Source: https://support.apple.com/en-am/HT213100 Herculano-Houzel (2009),Luo(2015).”
Song, J. Y., Patton, C. D., Friedman, R., Mahajan, L. S., Nordlicht, R., Sayed, R., & Lipton, M. L. (2022) · Frontiers in Neuroendocrinology · doi:10.1016/j.yfrne.2022.101051 · Cited by 23
Role of cerebellum in sleep-dependent memory processes
Jackson, A., & Xu, W. (2023) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2023.1154489 · Cited by 21
“Despite the fact that the cerebellum contains over 80% of the brain’s neurons (Herculano-Houzel, 2009), this brain structure has until recently been an “uncharted land in sleep research” (Canto et al.”
BackgroundCerebellar transcranial magnetic stimulation improves motor function in Parkinson's disease
Grobe‐Einsler, M., Baljasnikowa, V., Faikus, A., Schaprian, T., & Kaut, O. (2024) · Annals of Clinical and Translational Neurology · doi:10.1002/acn3.52183 · Cited by 20
“50,51 55 The role of the cerebellum in PD is still incompletely understood, but we are constantly gaining new insights into the complex interactions through which the cerebellum may influence PD symptoms.”
BackgroundAn adaptive filter model of cerebellar zone C3 as a basis for safe limb control?
Dean, P., Anderson, S., Porrill, J., & Jörntell, H. (2013) · The Journal of Physiology · doi:10.1113/jphysiol.2013.261545 · Cited by 18
“One is the enormous proliferation of granule cells, which are estimated to constitute ∼80% of all neurons in the human brain (Herculano-Houzel, 2009).”
BackgroundHuman astrocytic grid networks patterned in parylene-C inlayed SiO2 trenches
Jordan, M. D., Raos, B. J., Bunting, A. S., Murray, A. F., Graham, E. S., & Unsworth, C. P. (2016) · Biomaterials · doi:10.1016/j.biomaterials.2016.08.006 · Cited by 18
“1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 2 consists of a similar number of non-neuronal cells [1] and in the last 10 years, research has revealed”
Sur, C. (2019) · Multimedia Tools and Applications · doi:10.1007/s11042-019-08021-1 · Cited by 18
Rahman, S. M. A., Nassef, A. M., Al‐Dhaifallah, M., et al. (2020) · Foods · doi:10.3390/foods9030308 · Cited by 18
NeuralScale: Efficient Scaling of Neurons for Resource-Constrained Deep Neural Networks
Lee, E., & Lee, C. (2020) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr42600.2020.00155 · Cited by 18
Brain Organoids: Tiny Mirrors of Human Neurodevelopment and Neurological Disorders
Yadav, A., Seth, B., & Chaturvedi, R. K. (2020) · The Neuroscientist · doi:10.1177/1073858420943192 · Cited by 19
“The brain is the most complex and mysterious organ of the body that harbors billions of neurons and glial cells working precisely in a coordinated manner to carry out higher cognitive and sensorimotor functions (Herculano-Houzel 2009, 2012).”
BackgroundOrchestrated neuronal migration and cortical folding: A computational and experimental study
Wang, S., Saito, K., Kawasaki, H., & Holland, M. A. (2022) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1010190 · Cited by 21
“It is a hallmark of advanced brain function and intelligence [1, 2], offering gyrencephalic mammals superior information processing capabilities than other species with smooth or lissencephalic brains [3].”
Background(2023) · Advances in magnetic resonance technology and applications · doi:10.1016/b978-0-323-91771-1.00016-2 · Cited by 19
Seizure development in the acute intrahippocampal epileptic focus
Li, L., Kriukova, K. K., Engel, J., et al. (2018) · Scientific Reports · doi:10.1038/s41598-018-19675-6 · Cited by 18
Introduction to the special issue on neuro‐information science
Jacek Gwizdka, A., Moshfeghi, Y., & Wilson, M. L. (2019) · Journal of the Association for Information Science and Technology · doi:10.1002/asi.24263 · Cited by 18
A bio-inspired asynchronous skin system for crack detection applications
Sharp, N. D., Kuntz, A., Brubaker, C. D., et al. (2014) · Smart Materials and Structures · doi:10.1088/0964-1726/23/5/055020 · Cited by 17
The Relevance of Ecological Transitions to Intelligence in Marine Mammals
Bauer, G. B., Cook, P. F., & Harley, H. E. (2020) · Frontiers in Psychology · doi:10.3389/fpsyg.2020.02053 · Cited by 20
“It must be emphasized that, from the perspective of modern neuroscience, while size does matter, this is mostly as it relates to the number of neuron units (Herculano-Houzel, 2009).”
BackgroundEffect of remote signal propagation in an empirical brain network
Wang, Z., & Liu, Z. (2021) · Chaos An Interdisciplinary Journal of Nonlinear Science · doi:10.1063/5.0054296 · Cited by 17
The Brains of Reptiles and Birds
Güntürkün, O., Stacho, M., & Ströckens, F. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-820584-6.00008-8 · Cited by 18
Somatic mosaicism in the diseased brain
Iourov, I. Y., Vorsanova, S. G., Куринная, О. С., Kutsev, S. I., & Yurov, Y. B. (2022) · Molecular Cytogenetics · doi:10.1186/s13039-022-00624-y · Cited by 18
“Taking into account these astronomical amounts, neuronal and glial cells are unlikely to possess identical genomes [1, 2].”
BackgroundCorrelative light and volume electron microscopy to study brain development
Hayashi, S., Ohno, N., Knott, G. W., & Molnár, Z. (2023) · Microscopy · doi:10.1093/jmicro/dfad002 · Cited by 18
Ismail, L., Karwowski, W., Hancock, P., Taiar, R., & Fernandez-Sumano, R. (2023) · Journal of Integrative Neuroscience · doi:10.31083/j.jin2203062 · Cited by 16
“The human brain is composed of over 100 billion neurons that communicate via electrical signals generating an electrical current, which subsequently creates wave patterns termed as brain signals [12].”
BackgroundTemporal patterning of the vertebrate developing neural tube
Sagner, A. (2024) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2024.102179 · Cited by 17
Review of memristor based neuromorphic computation: opportunities, challenges and applications
Shekinah Archita, S., & Ravi, V. K. K. (2024) · Engineering Research Express · doi:10.1088/2631-8695/ad6662 · Cited by 19
Rajtmajer, S. M., Roy, A., Albert, R., Molenaar, P. C. M., & Hillary, F. G. (2015) · Frontiers in Neuroanatomy · doi:10.3389/fnana.2015.00097 · Cited by 17
Senk, J., Hagen, E., van Albada, S. J., & Diesmann, M. (2024) · Cerebral Cortex · doi:10.1093/cercor/bhae405 · Cited by 21
“Assuming a neuron density of 10(5) neurons/mm(2) across the cortical surface (Herculano-Houzel, 2009), the number of neurons covered by a Utah array is more than a million.”
BackgroundFukushima, M., Ichinohe, N., & Okano, H. (2018) · Elsevier eBooks · doi:10.1016/b978-0-12-811829-0.00003-0 · Cited by 17
Ailion, A. S., Roberts, S. R., Crosson, B., & King, T. Z. (2019) · NeuroImage Clinical · doi:10.1016/j.nicl.2019.101894 · Cited by 17
“Thus, researchers have called for a more integrated view of the brain that accounts for the structural and functional role of the cerebellum in coordination with the cortex (Herculano-Houzel, 2009; Whiting and Barton, 2003).”
Ordered arrangement of dendrites within a C. elegans sensory nerve bundle
Yip, Z. C., & Heiman, M. G. (2018) · eLife · doi:10.7554/elife.35825 · Cited by 18
“For example, the human brain consists of over 100 billion neurons and glial cells (Herculano-Houzel, 2009), all of which are precisely connected to form a functioning organ.”
BackgroundChromatin Remodeling in the Brain-a NuRDevelopmental Odyssey
Larrigan, S., Shah, S. J., Fernandes, J. A. L., & Mattar, P. A. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22094768 · Cited by 18
Principles of brain aging: Status and challenges of modeling human molecular changes in mice
Kluever, V., & Fornasiero, E. F. (2021) · Ageing Research Reviews · doi:10.1016/j.arr.2021.101465 · Cited by 18
Neural field theory of nonlinear wave-wave and wave-neuron processes
Robinson, P. A., & Roy, N. (2015) · Physical Review E · doi:10.1103/physreve.91.062719 · Cited by 18
Ilić, D., & Gignac, G. E. (2024) · Intelligence · doi:10.1016/j.intell.2024.101858 · Cited by 43
“…higher neuronal density compared to other mammals, it is also the intricate patterns of connectivity and the hierarchical organization of these densely packed neurons that enable advanced cognitive functions like language, reasoning, and problem-solving (Herculano-Houzel, 2009; Roth & Dicke, 2005).”
BackgroundExpansion of a conserved architecture drives the evolution of the primate visual cortex
Meyer, E. E., Martynek, M. P., Kästner, S., Livingstone, M. S., & Arcaro, M. J. (2025) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2421585122 · Cited by 21
Innovations in noninvasive sensory stimulation treatments to combat Alzheimer’s disease
Park, J. M., & Tsai, L. (2025) · PLoS Biology · doi:10.1371/journal.pbio.3003046 · Cited by 19
“The human brain is an incredibly complex organ composed of ~86 billion neurons and tril-lions of synapses [18].”
Co‐evolution of cerebral and cerebellar expansion in cetaceans
Muller, A. S., & Montgomery, S. H. (2019) · Journal of Evolutionary Biology · doi:10.1111/jeb.13539 · Cited by 15
“In contrast, the cerebellum has received much less attention, despite housing the majority of neurons in the brain (Barton, 2012; Herculano‐Houzel, 2009).”
BackgroundThe Dilemma of Human Brain Surrogates: Scientific Opportunities, Ethical Concerns
Greely, H. T. (2020) · Springer eBooks · doi:10.1007/978-3-030-38840-9_18 · Cited by 18
Constructing the rodent stereotaxic brain atlas: a survey
Feng, Z., Li, A., Gong, H., & Luo, Q. (2021) · Science China Life Sciences · doi:10.1007/s11427-020-1911-9 · Cited by 16
“The human brain consists of about 86 billion neurons and 100 billion glia cells (Azevedo et al., 2009; von Bartheld et al., 2016; Herculano-Houzel, 2009).”
BackgroundL’animal est-il une personne ?
Christen, Y. (2011) · Flammarion eBooks · doi:10.14375/np.9782081265950 · Cited by 16
“…n’en est rien : le cer-veau humain se situe (par le nombre de neurones qu’il contient) tr`es exactement sur la courbe correspondant aux primates, soit au-dessus de celle des rongeurs, mais d’une fa¸con qui ne le fait en rien ´echapper au champ de la normalit´e biologique (Herculano-Houzel, 2009).”
BackgroundRobust, Long-Term Video EEG Monitoring in a Porcine Model of Post-Traumatic Epilepsy
Martinez-Ramirez, L. F., Slate, A. R., Price, G., Duhaime, A., Staley, K. J., & Costine, B. A. (2022) · eNeuro · doi:10.1523/eneuro.0025-22.2022 · Cited by 16
“Differences in brain anatomy including location of the hippocampus (direct mechanical trauma in rodent impact models vs secondary cascades or diffuse TBI in humans), variability in the abundance of white matter and white matter injury, variation in the pathoanatomic character of the lesion developing from the injury (…”
BackgroundRoles of Epigenetics and Glial Cells in Drug-Induced Autism Spectrum Disorder
Csoka, A. B., Kouhen, N. E., Bennani, S., Getachew, B., Aschner, M., & Tizabi, Y. (2024) · Biomolecules · doi:10.3390/biom14040437 · Cited by 16
Exact Distribution of the Quantal Content in Synaptic Transmission
Rijal, K., Müller, N. I. C., Friauf, E., Singh, A., Prasad, A., & Das, D. (2024) · Physical Review Letters · doi:10.1103/physrevlett.132.228401 · Cited by 15
L’animal est-il une personne ?
Christen, Y. (2010) · Biologie Aujourd hui · doi:10.1051/jbio/2010012 · Cited by 16
Neural spiking dynamics in asynchronous digital circuits
Imam, N., Wecker, K., Tse, J., Karmazin, R., & Manohar, R. (2013) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn.2013.6706952 · Cited by 15
“The human brain consists of approximately 1010 neurons and 1013 synapses, all contained within a volume of 2 L, weighing less than 4 lbs, and running on a 20 W power budget [1].”
BackgroundThe Human Brain Online: An Open Resource for Advancing Brain Research
Ball, S., Gilbert, T. L., & Overly, C. C. (2012) · PLoS Biology · doi:10.1371/journal.pbio.1001453 · Cited by 16
“[1] and about a trillion synapses per cubic”
Background
Metadata
- Authors
- Herculano-Houzel, S.
- Venue
- Frontiers in Human Neuroscience
- Publisher
- Frontiers Media SA
- Published
- 2009
- Volume
- 3
- Pages
- 31-31
- ISSN
- 1662-5161 (ISSN-L)
- PMC
- PMC2776484
- OpenAlex
- W2005926822
- Cited by
- 1,778
- References
- 93
- Citations by year
- 2026: 89 · 2025: 159 · 2024: 192 · 2023: 145 · 2022: 133 · 2021: 172 · 2020: 176 · 2019: 144 · 2018: 140 · 2017: 91 · 2016: 77 · 2015: 71 · 2014: 61 · 2013: 50 · 2012: 45
- FWCI
- 33.51
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Frontiers in Human Neuroscience (publishedVersion, cc-by)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Conselho Nacional de Desenvolvimento Científico e Tecnológico
- Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro
- Topics
- Life Sciences › Agricultural and Biological Sciences › Ecology, Evolution, Behavior and Systematics › Primate Behavior and Ecology
- Life Sciences › Neuroscience › Developmental Neuroscience › Neurogenesis and neuroplasticity mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Keywords
- human brain, primate brain, brain size, neuron number, glial cells, cerebral cortex, encephalization, cognitive ability, rodents, elephants, whales
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.
A language model drew the claims from the paper on 2026-09-28, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-09-28 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Cited sources are checked with a language model’s help (gpt-6-sol).
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
