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REVIEW ARTICLE
published: 09 November 2009
doi: 10.3389/neuro.09.031.2009
HUMAN NEUROSCIENCE
The human brain in numbers: a linearly scaled-up primate brain
Suzana Herculano-Houzel*
Instituto de Ciências Biomédicas, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brasil
Edited by:
Andreas Jeromin,
Allen Institute for Brain Science, USA
Reviewed by:
Karl Herrup,
Case Western University, USA
Robert Barton,
University of Durham, UK
*Correspondence:
Suzana Herculano-Houzel, Laboratório
de Neuroanatomia Comparada,
Instituto de Ciências Biomédicas,
Universidade Federal do Rio de
Janeiro, Rua Carlos Chagas Filho 373,
21950-902 Rio de Janeiro,
Rio de Janeiro, Brazil.
e-mail: suzanahh@gmail.com
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 10
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
fi ndings 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.
Keywords: brain scaling, number of neurons, human, encephalization
×
INTRODUCTION
THE HUMAN BRAIN AS A SPECIAL BRAIN
What makes us human? Is our brain, the only one known to study
other brains, special in any way? According to a recent popular
account of what makes us unique, “we have brains that are bigger than
expected for an ape, we have a neocortex that is three times bigger
than predicted for our body size, we have some areas of the neocortex
and the cerebellum that are larger than expected, we have more white
matter” – and the list goes on (
Gazzaniga, 2008
). Most specialists
seem to agree (for example,
Marino, 1998; Rilling, 2006; Sherwood
et al., 2006
). Since ours is obviously not the largest brain on Earth, our
superior cognitive abilities cannot be accounted for by something as
simple as brain size, the most readily measurable parameter regarding
the brain. Emphasis is thus placed on an exceptionality that is, curi-
ously, not brain-centered, but rather body-centered: With a smaller
body but a larger brain than great apes, the human species deviates
from the relationship between body and brain size that applies to
other primates, great apes included, boasting a brain that is 5–7
to such great lengths to affi rm, and teach, that evolution is the
origin of diversity in life, and to fi nd trends and laws that apply to
kingdoms, phyla and orders as a whole, why then insist that what-
ever scaling rules apply to other primates must not apply to us?
In view of the vexing size inferiority in brain size and of the lack
of information about what our brains are actually made of – and
how that compares to other brains, particularly those of whales and
elephants – resorting to a quest for uniqueness may have seemed
as a necessary, natural step to justify the cognitive superiority of
the human brain.
Recently, a novel quantitative tool developed in our lab
(
Herculano-Houzel and Lent, 2005
) has fi nally made the num-
bers of neurons and non-neuronal cells that compose the brains
of various mammals, humans included, available for comparative
analysis. This review will focus on such a quantitative, compara-
tive analysis, with emphasis on the numbers that characterize the
human brain: what they are, how they have been viewed in the past,
and how they change our view of where the human brain fi ts into
the diversity of the mammalian nervous system.
too
large for its body size (
Jerison, 1973; Marino, 1998
). Recent efforts
to support this uniqueness have focused on fi nding genetic differ-
ences 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., 2009; Hakeem et al., 2009
).
To regard the human brain as unique requires considering it
to be an outlier: an exception to the rule, whatever that rule is.
This makes little sense, however, in light of evolution. If we go
×
THE HUMAN BRAIN IN NUMBERS
How many neurons does the human brain have, and how does
that compare to other species? Many original articles, reviews and
textbooks affi rm 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. This leaves the reader with
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Herculano-Houzel
The human brain in numbers
the impression that the cellular composition of the human brain has
long been determined. Indeed, an informal survey with senior neu-
roscientists 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 (Herculano-Houzel and Lent,
unpublished observations). Curiously, the widespread concept that
neurons represent about 10% of all cells in the human brain might
be one of the arguments behind the popular, but mistaken, notion
that we only use 10% of our brain (
Herculano-Houzel, 2002
).
The reason for such lack of references is that indeed there was,
to our knowledge, no actual, direct estimate of numbers of cells
or of neurons in the entire human brain to be cited until 2009.
A reasonable approximation was provided by
Williams and Herrup
(1988)
, from the compilation of partial numbers in the literature.
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. With more recent
estimates of 21–26 billion neurons in the cerebral cortex (
Pelvig
et al., 2008
) and 101 billion neurons in the cerebellum (
Andersen
et al., 1992
), however, the total number of neurons in the human
brain would increase to over 120 billion neurons.
As to the 10 times more numerous glial cells in the human
brain, that seems to be the case only in subcortical nuclei such as
the thalamus (17 glial cells per neuron) and the ventral pallidum
(12 glial cells per neuron;
Pakkenberg and Gundersen, 1988
). In the
gray matter of the cerebral cortex, glial cells outnumber neurons
by a factor of
However, the correlation between absolute brain size and
cognitive abilities breaks down when species of similar brain size are
compared across orders. Monkeys, for instance, possess brains that
are much smaller than those of ungulates, but the higher cognitive
and behavioral fl exibility 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. For similar-sized
brains, rodents also perform more poorly than primates: 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. This is reminiscent of the most striking and
troubling discrepancy regarding brain size and cognitive abilities:
that between humans and larger-brained species such as whales and
elephants. If the latter have brains that are up to six times larger than
a human brain, why should we be more cognitively able? Answering
this question requires a direct examination of the numbers of neu-
rons that compose the brains of humans and other species.
×
BRAIN AND BODY SCALING: THE TRADITIONAL VIEW
ASSUMPTION 1: BODY SIZE MATTERS
If the smaller size of the human brain compared to elephant and
whale brains (
Figure 1
) translates into a smaller number of neu-
rons in the human brain than in the latter, then what makes the
human brain outstanding in its cognitive abilities? In the absence
of direct estimates of numbers of neurons in these and other spe-
cies, the search for a neural correlate for human capacities has
placed emphasis on the characteristic that most undisputedly places
humans above other mammals: the EQ (
Jerison, 1973
). This meas-
ure is based on the observation that, across species, brain size cor-
relates with body size in a way that can be described mathematically
with a power function, thus allowing the predicted brain mass to
be calculated for any species. EQ indicates how much the observed
brain mass of a species deviates from the expected for its body
mass: an EQ of 1 indicates that the observed brain mass matches
the expected value; an EQ
2 (
Sherwood et al., 2006; Pelvig et al., 2008
). Given
the relatively small number of glial cells reported for the human
cerebellum, where they are outnumbered by neurons by at least
25:1 (
Andersen et al., 1992
), 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.
1 means that brain size in that species
is larger than expected for its body mass.
Compared to mammals as a whole, humans have the largest EQ
found for any mammal, of between 7 and 8 (
Jerison, 1973
); 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
>
WHY BOTHER WITH CELL NUMBERS?
Across species, the number of neurons and their relative abundance
in different parts of the brain is widely considered to be a determi-
nant of neural function and, consequently, of behavior (
Williams
and Herrup, 1988
). Among mammals, those species with the largest
brains, such as cetaceans and primates, have a greater range and
versatility of behavior than those with the smallest brains, such as
insectivores (
Jerison, 1985; Marino, 2002
). Among birds, those that
are larger-brained (corvids, parrots and owls) are also considered
the most intelligent (
Lefebvre et al., 2004
). A recent comparison
of several parameters, including brain size, relative brain size,
encephalization, conduction velocity and estimated numbers of
neurons led two authors to conclude that the “factors that correlate
better with intelligence (across species) are the number of corti-
cal neurons and conduction velocity, as the basis for information
processing” (
Roth and Dicke, 2005
). Indeed, within non-human
primates, a recent meta-analysis concluded that the best predictor
of the cognitive abilities of a species is absolute brain size, not rela-
tive size nor encephalization quotient (EQ;
Deaner et al., 2007
).
FIGURE 1 | The human brain is not the largest.
Brains of a human and of
an African elephant are depicted here at the same scale. Drawings by
Lorena Kaz based on images freely available from the University of
Wisconsin and Michigan State Comparative Mammalian Brain Collections
(
).
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Herculano-Houzel
The human brain in numbers
primate or cetacean (
Marino, 1998
). The position of the human
species as an outlier in the body
of brain allometry, as if their brains were built according to
the same scaling rules (for example,
Haug, 1987; Zhang and
Sejnowski, 2000
).
Comparisons across orders that seem to invalidate the correla-
tion between numbers of neurons and cognitive ability, such as
between monkeys and ungulates, or rodents and primates, also bear
this hidden caveat: the assumption that brain size relates to number
of neurons in the brain in a similar fashion across orders. 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 compara-
tive studies to date (for example,
Haug, 1987; Finlay and Darlington,
1995; Barton and Harvey, 2000; Clark et al., 2001
). 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 suffi cient) variable is brain size and
its deviation from the expected. However, 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 (see below).
brain comparison is made clear
if one considers that 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.
There are, however, several problems with the notion that
the explanation for the superior cognitive abilities of the human
species lies in its large EQ. For one, it is not obvious how larger-
than-expected brain mass would confer a cognitive advantage. In
principle, this advantage would rely on the availability for cognitive
functions of whatever brain mass exceeds what is necessary to proc-
ess body-related information. However, 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. Capuchin monkeys, for instance, have much larger
EQs than gorillas (
Marino, 1998
), but are outranked by these in cog-
nitive performance (
Deaner et al., 2007
). 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
).
Another problem with the utility of the EQ is that the body–
brain mass relationship from which expected brain mass is derived
depends on the precise combination of species computed (
Barton,
2006; Herculano-Houzel et al., 2007
). We have recently found that,
compared to the linear brain
×
ASSUMPTION 3: PROPORTIONS AND RELATIVE SIZE MATTER
An often cited argument in favor of the uniqueness of the human
brain is its relatively large cerebral cortex, which accounts for 82%
of brain mass. Within this large cerebral cortex, a relative enlarge-
ment of the prefrontal cortex was once considered a hallmark of
the human brain, but this view has however been overthrown by
modern measurements (
Semendeferi et al., 2002
). Still, the distri-
bution 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
).
Relative size is supposed to be a meaningful indicator of relative
functional importance of a brain structure based on the assumption
that it is a proxy for relative number of neurons. For instance, the
increase in relative size of the cerebral cortex with increasing brain
size simultaneously with no systematic change in the relative size of
the cerebellum has been used as evidence that these structures are
functionally independent and have been evolving separately (
Clark
et al., 2001
). Such discrepancy would support the popular notion
that brain evolution equates with development of the cerebral cor-
tex, which comes to predominate over the other brain structures.
However, analysis of absolute, rather than relative, cerebral cortical
and cerebellar volumes in the same dataset leads to the opposite
conclusion: the coordinated scaling of these volumes, as well as of
the surface areas of these structures, would be evidence that the
cerebral cortex and cerebellum are functionally related and have
been evolving coordinately (
Barton, 2002; Sultan, 2002
).
As it turns out, however, the underlying assumption that the
relative size of a brain structure refl ects the relative number of
brain neurons that it contains is fl awed.
Now that numbers of neurons are available across rodents, pri-
mates and insectivores, we fi nd that 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.,
body relationship that applies to
the primate species in our sample (which consisted of simian and
prosimian primates;
Herculano-Houzel et al., 2007
), the human
brain deviates by only 10% from its expected size (
Azevedo et al.,
2009
). This conformity to the body
×
brain relationship that applies
to non-anthropoid primates is consistent with the observation that,
like in other non-anthropoid primates, the human brain mass rep-
resents about 2% of body mass. Given the sensitivity of EQ to the
species included and our fi nding that the human brain conforms
to the scaling rules that apply to other primates (see below), 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
).
This latter possibility of a dissociation between brain and body
development in evolution (which might be only circumstantially,
and not causally, related) constitutes a fi nal criticism to the useful-
ness of the EQ as an index of “brain” evolution in comparative
studies: indeed, the emphasis on the body-centered EQ overlooks
the observation that, compared to other mammalian orders, primate
encephalization is the result of a shift in postcranial growth proc-
esses, not a modifi cation of brain growth (
Deacon, 1997
). In the
words of Deacon, “if primates have big brains merely because they
have small bodies, we cannot presume that this represents an evolu-
tionary trend driven by cognitive demands”(p. 343). In this scenario,
however, the human brain exhibits a further modifi cation in that it
continues to grow as though in a larger body (
Deacon, 1997
).
×
ASSUMPTION 2: BRAIN SIZE MATTERS
Brain size varies across mammals by a factor of approximately
100,000 (
Tower, 1954; Stolzenburg et al., 1989
). Different mam-
malian orders have traditionally been pooled together in studies
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Herculano-Houzel
The human brain in numbers
2006, 2007; Sarko et al., 2009
). Most importantly, 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
). Instead, the number of neurons in the cerebral cortex
increases coordinately with the number of neurons in the cerebel-
lum (Herculano-Houzel, submitted).
orders, considers solely how brain size changes as a function of
its number of neurons within a given order, irrespective of body
size, and without any concerns regarding phylogenenetic effects
within that order, or even whether evolution of the extant species
has involved an expansion of brain size, a reduction, or both. In the
particular case of primates, we have recently extended our analysis
to another set of fi ve primate species (Gabi et al., submitted), and
found that the same cellular scaling relationships apply to the origi-
nal dataset (
Herculano-Houzel et al., 2007
), to the second dataset,
and to the combined, extended dataset. 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 – even though
small variations may occur across species that might, indeed, be
due to phylogenetic interdependencies.
In the order Rodentia, we fi nd 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
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
). These
fi ndings 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
).
In contrast to rodent brains, which scale hypermetrically in
size with their numbers of neurons, 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 (
Herculano-Houzel et al.,
2007
). 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 hypermetri-
cally as it gains neurons (as in rodents;
Sarko et al., 2009
). In view
of the similar non-neuronal cell densities across species, hyper-
metric scaling of brain structure mass as a function of its number
of neurons implies a concurrent increase in the average neuronal
size (which, in the method’s defi nition, includes not only the cell
soma but also the entire dendritic and axonal arborizations as well
as synapses;
Herculano-Houzel et al., 2006
). As a consequence of
these different cellular scaling rules, shown in
Table 1
, a 10-fold
increase in the number of neurons in a rodent brain results in a
35-fold larger brain; in contrast, 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.
A NEW VIEW: SCALING OF NEURONAL NUMBERS
CELLULAR SCALING RULES FOR RODENT, INSECTIVORE,
AND PRIMATE BRAINS
Our group has been investigating the cellular scaling rules that
apply to brain allometry in different mammalian orders using the
novel method of isotropic fractionation, which produces cell counts
derived from tissue homogenates from anatomically defi ned brain
regions (
Herculano-Houzel and Lent, 2005
). Through the estima-
tion of absolute numbers of neuronal and non-neuronal cells in
the brains of different mammalian species and their comparison
within individual orders, we have been able to determine the scal-
ing rules that apply to the brains of species spanning a wide range
of body and brain masses in rodents (
Herculano-Houzel et al.,
2006
), primates (
Herculano-Houzel et al., 2007
) and more recently
in insectivores (
Sarko et al., 2009
). A comparative overview of brain
mass and total number of neurons for these species can be seen
in
Figure 3
.
A recent issue in comparative studies of brain scaling has been
the examination of how residual variation in different parameters
relate to phylogenetic relationships once shared evolutionary com-
monalities in body or brain size are accounted for (
Harvey and
Pagel, 1991; Nunn and Barton, 2000
). Although such analyses of
independent contrasts are instrumental for identifying evolutionary
correlations across taxa while taking into account this phylogenetic
nonindependence, they overlook the very issue at hand here: how
the size of the brain refl ects the number of neurons that it contains,
regardless of body size and of any other shared characteristics.
For this reason, the analysis reviewed here, referred to as unveiling
the “cellular scaling rules” for the brain of different mammalian
NOT ALL BRAINS ARE CREATED EQUAL: COGNITIVE ABILITIES AND
NUMBERS OF NEURONS
The different cellular scaling rules that apply to rodent, primate
and insectivore brains show very clearly that brain size cannot be
used indiscriminately as a proxy for numbers of neurons in the
brain, or even in a brain structure, across orders. By maintaining
the average neuronal size (including all arborizations) invariant
FIGURE 2 | Relative size of the cerebral cortex does not inform about the
relative number of neurons in the cortex compared to the whole brain.
Each point indicates, for a given species, the average relative cortical mass as
a percentage of total brain mass (X-axis) and the average relative number of
cortical neurons as a percentage of the total number of neurons in the brain
(Y-axis). Data from
Herculano-Houzel et al. (2006, 2007)
;
Azevedo et al. (2009)
;
and
Sarko et al. (2009)
.
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Herculano-Houzel
The human brain in numbers
FIGURE 3 | Brain mass and total number of neurons for the mammalian
species examined so far with the isotropic fractionator.
Brains are arranged
from left to right, top to bottom, in order of increasing number of neurons
according to average species values from
Herculano-Houzel et al., 2006
(rodents),
Herculano-Houzel et al., 2007
(non-human primates),
Sarko et al.,
2009
(insectivores) and
Azevedo et al., 2009
(human brain). Rodent brains face
right, primate brains face left, insectivore brains can be identifi ed in the fi gure by
their bluish hue (due to illumination conditions). All images shown to the same
scale. Primate images, except for the capuchin monkey and human brain, from
the University of Wisconsin and Michigan State Comparative Mammalian Brain
Collections (
. Insectivore images kindly provided by
Diana Sarko, and human brain image by Roberto Lent. Rodent images from the
author. Notice that some rodent brains, such as the agouti and the capybara,
contain fewer neurons than primate brains that are smaller than them.
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