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.
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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
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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.
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- 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.
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- Supported
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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.
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- 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.
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- 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.
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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.
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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.
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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.
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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.
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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.
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- 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.
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- Load-bearing: fails — The paper’s conclusions may not depend on it.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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- Load-bearing: passes — The paper’s conclusions depend on it.
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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.
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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.
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- 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.
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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.
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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
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“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
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The primate cortico-cerebellar system: anatomy and function
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“…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 1,301–1,400 of 1,776
Telepathy, Using the Force, and Other Paranormal Abilities
Stratmann, H. G. (2015) · Science and fiction · doi:10.1007/978-3-319-16015-3_8
Cell type marker enrichment across brain regions and experimental conditions
Tan, P. P. C. (2013) · cIRcle (University of British Columbia) · doi:10.14288/1.0073463
“Differences in gene expression may be due to the increased number of cortical neurons in primates compared to rodents [20].”
BackgroundStudying the Cognitive Involvement of Glia Cells Using Stochastic Functional MicroscopyPreprint
Spadaro, S. (2016) · viXra
Ariansen, J. L. (2019) · Carolina Digital Repository (University of North Carolina at Chapel Hill) · doi:10.17615/zm1y-5g22
Emotion Regulation and Primate Sociality
de Waal, F. Β. Μ. (2015) · Cambridge University Press eBooks · doi:10.1017/cbo9781139565790.008
Malhotra, M., & Nair, T. R. G. (2016) · Biologically Inspired Cognitive Architectures · doi:10.1016/j.bica.2016.04.001
Iron and manganese accumulation potential in water distribution networks
Danso-Amoako, E. (2016) · University of Salford Institutional Repository (University of Salford)
An evaluation of the Integrated Information Theory against some central problems of consciousness
Olsson, H. (2015) · Diva portal (Dalarna University Library)
Jain, M. K., & Apitz-Castro, R. J. (2016) · Philosophy study · doi:10.17265/2159-5313/2016.02.003
Scaling law, Power relation, Evolution, Brain, Volume surface ratio, grey
de Lussanet, M. H. E. (2015)
Plebe, A., & Cruz, V. M. D. L. (2016) · Lecture notes in morphogenesis · doi:10.1007/978-3-319-29483-4_10
"Only connect!": creating connections when reading fiction and digital texts
Kokkola, L. (2015) · e_Buah
Ávila, E. (2016) · doi:10.20868/upm.thesis.43059
“The brain of an adult can contain approximately 120 thousand million of neurons which suppose around a 100 trillion of connections among them (Herculano-Houzel, 2009).”
BackgroundSparse coding and its application to modeling the zebra finch's auditory system
Blättler, F. (2013) · Repository for Publications and Research Data (ETH Zurich) · doi:10.3929/ethz-a-010006431
“Some animals like the jellyfish do not posses a brain, some like the sponge completely lack a nervous system, whereas higher vertebrates developed brains embodying up to dozens of billions of neurons (Herculano-Houzel, 2010).”
BackgroundA Thermodynamic Account of the Emergence of Organised Matter
Akkerhuis, G. A. J. M. J. O. (2016) · Springer eBooks · doi:10.1007/978-3-319-43802-3_14
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Andreeva, N., & Poskrobko, B. (2015)
Gene-Environment Interplay on Oviposition Site Selection in Drosophila melanogaster
Vesterberg, A. (2015) · TSpace (University of Toronto)
Toward the Whole Brain Simulation of Insect Brain
Kazawa, T., Miyamoto, D., Goto, A., Park, H., Fukuda, T., & Kanzaki, R. (2015) · The Brain & Neural Networks · doi:10.3902/jnns.22.89
Blom, J. (2016) · doi:10.3990/1.9789036542715
Diagnostic neuropathology of brain tumours using biophotonics and spectrometry
Mudariki, T. (2016) · CLOK (University of Central Lancashire)
Via, G. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1707.06038
“It is been estimated that the human brain is composed of about 1011 neurons[1].”
BackgroundSmart memory: A neuromorphic semiconductor memory
Lam, C. H. (2016) · IEEE International Conference on Solid-State and Integrated Circuit Technology · doi:10.1109/icsict.2016.7998994
“However, only about 20% of the 86 billion neurons in the human brain reside in the neocortex [14].”
BackgroundIsolating neural indices of continuous speech processing from multivariate neural data
Liberto, D., & de Marco, G. (2017) · Arrow@dit (Dublin Institute of Technology)
Mehrpour, V. (2017) · eDiss (Georg-August-Universität Göttingen) · doi:10.53846/goediss-6599
Insights into the Animal’s Mind
Predoi, G., Raus, I., Bărbuceanu, F., & Opriș, I. C. (2017) · Springer series in cognitive and neural systems · doi:10.1007/978-3-319-29674-6_31
Im Spannungsfeld von Humanen und Humanoiden
Küppers, E. W. U. (2017) · Springer eBooks · doi:10.1007/978-3-658-17920-5_2
Veneziano, A. (2017) · Liverpool John Moores University · doi:10.24377/ljmu.t.00007451
Muskiet, F. A. J. (2018) · Bijblijven · doi:10.1007/s12414-018-0318-2
“Ze zijn waarschijnlijk niet meer dan een opgeschaald primatenbrein [57, 58].”
BackgroundMagnetic Resonance Imaging of Brain Development in Fetal Alcohol Spectrum Disorders
Treit, S. (2015) · ERA: Education and Research Archive (University of Alberta) · doi:10.7939/r3bk1716f
Charakterisierung des Targetingverhaltens präsynaptischer Proteine
Riemann, D. (2018) · eDiss (Georg-August-Universität Göttingen) · doi:10.53846/goediss-6846
Allocentric effort decision making : a neuroeconomic investigation
FitzGerald, S. C. (2018) · DR-NTU (Nanyang Technological University) · doi:10.32657/10356/74800
Hudson, A. E. (2018) · Anesthesiology · doi:10.1097/aln.0000000000002388
画像の見方(脳血管障害):-脳卒中の損傷部位を把握しその影響を考える-
靖裕, 小. (2013) · 理学療法学 · doi:10.15063/rigaku.kj00008722978
A theory of general intelligence
Lui, H. W. (2018) · Medical Hypotheses · doi:10.1016/j.mehy.2018.12.001
“In a human, is estimated that there are around 16 billion neurons in the cortex, and 86 billion neurons in total [160].”
BackgroundAn Automated Framework for Brain Tumour Class Detection
Nandan, B., & Rao, K. N. (2018) · International Journal of Engineering & Technology · doi:10.14419/ijet.v7i4.17930
“Though study of the human brain is still considered to be a challenge due to the complex structure, the researchers like S. Herculano-Houzel et al. [2] have made significant progress in estimating the number of cells or like the report from Brain Facts and Answers [3] estimated the number of…”
BackgroundMaking the Invisible Visible: The Effects of Neuroscience on Mental Injury Claims
Ng, J. (2018) · TSpace (University of Toronto)
3D Tissue Modelling of the Central Nervous System
Bang, S., Lee, B., & Jeon, N. L. (2019) · Royal Society of Chemistry eBooks · doi:10.1039/9781788012683-00171
McDaniel-Gray, S., Boothe, D. L., Yu, A., et al. (2018) · IEEE International Conference on High Performance Computing and Communications; IEEE International Conference on Smart City; IEEE International Conference on Data Science and Systems (HPCC/SmartCity/DSS) · doi:10.1109/hpcc/smartcity/dss.2018.00145
Directional Thought and Evolution
Glikson, A. Y. (2019) · Springer eBooks · doi:10.1007/978-3-030-10603-4_5
Multiscale Modeling of Neurobiological Systems
Kaya, C. (2018) · D-Scholarship@Pitt (University of Pittsburgh)
Los múltiples significados de la «complejidad cerebral»
Blanco, C. (2019) · Pensamiento Revista de investigación e información filosófica · doi:10.14422/pen.v75.i283.y2019.005
Silva, Y. R. D. M. (2019) · Digital Library of Theses and Dissertations (Universidade de São Paulo) · doi:10.11606/d.41.2019.tde-10012019-111750
Mathematical Modeling of Extinction of Inhomogeneous PopulationsPreprint
Karev, G. P., & Kareva, I. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1604.00507
Gamoudi, B. K. (2019) · University of the Western Cape Electronic Theses and Dissertations Repository (University of the Western Cape)
LABEL FREE OPTICAL DETECTION OF ELECTRICAL ACTIVITY IN MAMMALIAN NEURONS
Satpathy, S. (2018) · UTA ResearchCommons (University of Texas Arlington)
Harms, R. (2019) · doi:10.26481/dis.20191025rh
Benigno, G. (2019) · Scholarship@Western (Western University)
Shaules, J. (2019) · Springer eBooks · doi:10.1007/978-981-15-0587-4_4
Making of The Dark Anim: Technical and Scientific Notes
Zoppè, M., Loni, T., Carlone, I., & Cianchetta, S. (2019) · International Conference on Cyberworlds (CW) · doi:10.1109/cw.2019.00016
Phylogenetic comparison on cognition: Advances in evolutionary psychology
Chen, T., & Su, Y. (2019) · Chinese Science Bulletin (Chinese Version) · doi:10.1360/tb-2019-0204
Corticospinal excitability of the soleus muscle during water immersion
Mujunen, T. (2019) · Jyväskylä University Digital Archive (University of Jyväskylä)
Super-Resolution Spike Event-based Polarimetric Dynamic Vision Sensor p(DVS) Cognitive Imaging
Beninati, A., Nowak, M., Douard, N., et al. (2019) · IEEE International Conference on Imaging Systems and Techniques (IST) · doi:10.1109/ist48021.2019.9010257
Brain organoids as a model system for human neurodevelopment in health and disease
Reiner, O., & Karzbrun, E. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-814405-3.00010-2
Morrison, D. M. (2020) · Springer eBooks · doi:10.1007/978-3-030-48543-6_4
Workload-Aware Systems and Interfaces for Cognitive Augmentation
Kosch, T. (2020) · Elektronische Hochschulschriften der LMU München (Ludwig-Maximilians-Universität München) · doi:10.48550/arxiv.2010.07703 · Cited by 3
“Thereby, approximately 100 billion neurons underlie human cognition [165].”
BackgroundCanozo, F. J. G., Zuo, Z. C., Martin, J. F., & Samee, M. A. H. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.09.09.290064
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Gerum, R. C., & Schilling, A. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2004.13532
“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.”
BackgroundGetachew, M. N., Priyadarshini, R., & Mehra, R. M. (2020) · Journal of Computational Electronics · doi:10.1007/s10825-020-01580-9
Molecular Biology of Nervous System
Unnikrishnan, M. K., Marathakam, A., & Mathew, V. (2020) · Springer eBooks · doi:10.1007/978-981-15-5167-3_1
Classification of hand-related real and imaginary motor activity with fNIRS
Hramov, A. E., Grubov, V., & Badarin, A. (2020) · Scientific School Dynamics of Complex Networks and their Applications (DCNA) · doi:10.1109/dcnair50402.2020.9216914
“It is well-known, that in nonlinear dynamics brain considered as a very complex dynamical system with huge number of elements — neurons [1].”
BackgroundQuantum Neural Networks and Quantum Intelligence
Altaĭsky, M. V., & Kaputkina, N. E. (2020) · Studies in Rhythm Engineering · doi:10.1007/978-981-15-7253-1_6
DeepFoldit -- A Deep Reinforcement Learning Neural Network Folding ProteinsPreprint
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“It is estimated that the human brain comprises of 86 billion neurons and approximately 10 to 10 synapses [29].”
BackgroundA Hierarchy of Decision-Making
Boraud, T. (2020) · Oxford University Press eBooks · doi:10.1093/oso/9780198824367.003.0009
The Grandmaster and the Playmates
Boraud, T. (2020) · Oxford University Press eBooks · doi:10.1093/oso/9780198824367.003.0015
Boraud, T. (2020) · Oxford University Press eBooks · doi:10.1093/oso/9780198824367.003.0010
Boraud, T. (2020) · Oxford University Press eBooks · doi:10.1093/oso/9780198824367.003.0011
Boraud, T. (2020) · Oxford University Press eBooks · doi:10.1093/oso/9780198824367.003.0008
Boraud, T. (2020) · Oxford University Press eBooks · doi:10.1093/oso/9780198824367.003.0002
Boraud, T. (2020) · Oxford University Press eBooks · doi:10.1093/oso/9780198824367.003.0017
Boraud, T. (2020) · Oxford University Press eBooks · doi:10.1093/oso/9780198824367.003.0014
Boraud, T. (2020) · Oxford University Press eBooks · doi:10.1093/oso/9780198824367.003.0005
Boraud, T. (2020) · Oxford University Press eBooks · doi:10.1093/oso/9780198824367.003.0006
Twenty-Five Centuries of Debate
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Pathologies of Decision-Making
Boraud, T. (2020) · Oxford University Press eBooks · doi:10.1093/oso/9780198824367.003.0019
Boraud, T. (2020) · Oxford University Press eBooks · doi:10.1093/oso/9780198824367.003.0004
Introduction to Information Transfer in the Nervous System
Boraud, T. (2020) · Oxford University Press eBooks · doi:10.1093/oso/9780198824367.003.0003
Küppers, E. W. U. (2020) · Springer eBooks · doi:10.1007/978-3-658-30690-8_5
Csf1r-GCaMP5 Reporter Mice Reveal Immune Cell Communication in Vitro and in VivoPreprint
Taghdiri, N., Calcagno, D. M., Fu, Z., Huang, K., Kohler, R., Weissleder, R., Coleman, T. P., & King, K. R. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.02.24.432710
“Methods for investigating cell communication are well-established in electrically excitable cells such as neurons and cardiomyocytes; however, these represent less than 1% of all cells in the human body(6, 7).”
BackgroundWhy does processing instruction work?
Leeser, M. J. (2020) · Studies in bilingualism · doi:10.1075/sibil.62.10lee
Wie ähnlich sind Tiere und Menschen?
Schleim, S. (2021) · Springer eBooks · doi:10.1007/978-3-662-62229-2_4
Using CNNs for AD classification based on spatial correlation of BOLD signals during the observationPreprint
Beheshti, N., & Johnsson, L. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2104.10596
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Hadjiivanov, A. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2104.10851 · Cited by 1
“The human brain contains close to 10(11) neurons, each of which communicates with an average of 10(4) other neurons, putting the total number of neuron-neuron connections at close to 10(15) [25, 31].”
BackgroundThe Role of Down Syndrome Cell Adhesion Molecule in Development and Diseases
Liu, H. (2020) · Deep Blue (University of Michigan)
Impacts of Drug (Ab)Use on the Development of the Human Central Nervous System
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Industrialisation and Technological History
van den Bergh, J. C. J. M. (2018) · Cambridge University Press eBooks · doi:10.1017/9781108564922.013
The Implications of Adolescent Neuroscience on Policy
Galván, A. (2018) · Cambridge University Press eBooks · doi:10.1017/9781316106143.009
Shared and Private VAEs with Generative Replay for Continual LearningPreprint
Ghosh, S. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2105.07627 · Cited by 1
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van den Bergh, J. C. J. M. (2018) · Cambridge University Press eBooks · doi:10.1017/9781108564922.004
Dendritic biophysics and evolution
Beaulieu-Laroche, L. (2020) · DSpace@MIT (Massachusetts Institute of Technology)
de Lima, F. F. (2020) · Digital Library of Theses and Dissertations (Universidade de São Paulo) · doi:10.11606/d.3.2020.tde-16032021-113848
Prehistory Until the Rise of Agriculture
van den Bergh, J. C. J. M. (2018) · Cambridge University Press eBooks · doi:10.1017/9781108564922.012
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 ›
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