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 defined brain regions (Herculano-Houzel and Lent, 2005
). Through the estimation 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 scaling 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 .
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 (more ...)
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 commonalities 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 reflects 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 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 five primate species (Gabi et al., submitted), and found that the same cellular scaling relationships apply to the original 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 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 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 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
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 hypermetrically as it gains neurons (as in rodents; Sarko et al., 2009
). In view of the similar non-neuronal cell densities across species, hypermetric 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 definition, 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 , 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.
Power law exponents that apply to the scaling of brain mass, or structure mass, as a function of the number of neurons they contain in rodents, insectivores and primates.
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 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 cognitive consequences of this difference, which allows primate brains to enjoy the benefits of a large increase in numbers of neurons without the otherwise associated cost of a much larger increase in overall brain volume, can be glimpsed by returning to the comparison between rodents and primates of similar brain size. Now that absolute numbers of neurons can be compared across the similar-sized brains of agoutis and owl monkeys, and of capybaras and capuchin monkeys (Figure ), the expected correlation between cognitive ability and numbers of neurons is actually found to hold: with 1468 million neurons, owl monkeys have almost twice as many neurons in the brain as agoutis (which hold 857 million), and about four times more neurons in the cerebral cortex than the agouti (442 million versus 113 million). Likewise, the capuchin monkey brain has more than twice the number of neurons of the larger-brained capybara (3.7 billion against 1.6 billion), and also about four times more neurons in the cerebral cortex (1.1 billion against 0.3).
Figure 4 Brain size is not a reliable indicator of number of neurons across orders. Because of the different cellular scaling rules that apply to rodent and primate brains, primates always concentrate larger numbers of neurons in the brain than rodents of a similar, (more ...)
The significance of the difference in scaling rules for building brains with large numbers of neurons becomes even more obvious if one considers the expected number of neurons for 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. This number of neurons is smaller than the number of neurons estimated to exist in the human cerebral cortex alone (Pakkenberg and Gundersen, 1997
; Pelvig et al., 2008
), and about seven times smaller than the number of neurons predicted for a 1.5-kg brain built with the scaling rules that apply to primates (see below).
The cellular composition of the human brain
The determination of the cellular scaling rules that apply to primate brains (Herculano-Houzel et al., 2007
) enabled us to predict the cellular composition of the human brain. 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. 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 ).
Table 2 Expected values for a generic rodent and primate brains of 1.5kg, and values observed for the human brain (Azevedo et al., 2009).
Establishing whether the human brain indeed conforms to the scaling rules that apply to other primates, however, required determining its cellular composition using the same method. This was accomplished by 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 cerebral cortex, with an average 1233
g and 16 billion neurons, is slightly below expectations for a primate brain of 1.5
kg, while the human cerebellum, at 154
g and 69 billion neurons, matches or even slightly exceeds the expected (Table ).
Although not observed in the comparatively small rodent species analyzed, 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 ). Remarkably, the human cerebral cortex, which represents 82% of brain mass, holds only 19% of all neurons in the human brain – a fraction that is similar to the fraction that we observed in several other primates, rodents, and even insectivores (Figure ). The relatively large human cerebral cortex, therefore, is not different from the cerebral cortex of other animals in its relative number of neurons.
It should be noted that the unchanging proportional number of neurons in the cerebral cortex relative to the whole brain does not contradict an expansion in volume, function and number of neurons of the cerebral cortex in evolution: 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 ).
Figure 5 Numbers of neurons increase faster in the cerebral cortex and cerebellum than in the remaining brain areas (the combined brainstem, diencephalon and basal ganglia). Data points indicate average values for individual species of rodents (Herculano-Houzel (more ...)
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. 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.
Predictions for great apes
The finding that the same cellular scaling rules apply to humans and non-anthropoid primate brains alike, irrespective of body size, indicates that the brains of the great apes, which diverged from the hominin lineage before humans, should also conform to the same cellular scaling rules. 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-Houzel and Kaas, in preparation). In view of the discrepant relationship between body and brain size in humans, great apes, and non-anthropoid primates, these findings suggest that the rules that apply to scaling primate brains are much more conserved than those that apply to scaling the body. This raises the possibility that brain mass and body mass across species are only correlated, rather than brain mass being determined by body mass, as presumed in studies that focus on the variation of residuals after regression onto body size. Supportive evidence comes from the dissociation between brain and body growth in development, in which the former actually precedes the latter (reviewed in Deacon, 1997
), and from our observation that body mass seems more free to vary across species than brain mass as a function of its number of neurons. In this view, it will be interesting to consider the alternative hypothesis that body size is not a determining variable for brain size in comparative studies of brain neuroanatomy, and particularly not an (independent) parameter for assessing quantitative aspects of the human brain.
Do we have the most neurons? predictions for other large-brained mammals
The different cellular scaling rules that apply to rodents and primates strongly indicate that it is not valid to use brain size as a proxy for number of neurons across humans, whales, elephants
and other large-brained species belonging to different mammalian orders. One consequence of this realization is that sheer size alone, or in relation to body size, is not an adequate parameter to qualify, or disqualify, the human brain as “special”.
A comparison of expected numbers can nevertheless be very illuminating. For instance, given the cellular scaling rules that we have observed for rodents (Herculano-Houzel et al., 2006
), 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. As mentioned above, a generic rodent brain of human-sized proportions, weighing 1.5
kg, would have only 12 billion neurons: in this sense, therefore, being a primate endows us with seven times more neurons than would be expected if we were rodents. Notice that this remarkable difference does not rely on assumptions about how brain size or cellular composition relate to body size in the species.
A burning question is now whether cetaceans and elephants, endowed with much larger brains than humans, also have much larger numbers of neurons than humans. 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
). These estimates, however, were obtained by simply multiplying cerebral cortical volume and the neuronal densities determined for a few cortical areas, which probably do not reflect average neuronal density in the entire cortex.
Although direct measurements of cellular composition are not yet available from whole elephant and whale brains, it is illuminating to consider how their cellular compositions would differ depending on whether predicted from the scaling rules that apply to rodent or to primate brains. As shown in Table , the difference in numbers of neurons predicted to compose the brains of the false killer whale and of the African elephant is 10-fold depending on the scaling rules employed. Speculatively, the estimate of neuronal density in the gray matter of the cerebral cortex of the whale and the elephant at a low figure of about 7000
) suggests that these brains conform to scaling rules that are much closer to those that apply to rodents than to the primate scaling rules. It may turn out, therefore, these very large brains are composed of remarkably fewer neurons than the human brain, despite their size, thanks to the distinct, economical scaling rules that apply to primates in general (and not to humans in particular).
Predicted cellular composition of whale and elephant brains if they scaled according to rodent or primate cellular scaling rules.