But that is different from being at the pinnacle of evolution in a number of very important ways. As Mark Twain pointed out in , to presume that evolution has been a long path leading to humans as its crowning achievement is just as preposterous as presuming that the whole purpose of building the Eiffel Tower was to put that final coat of paint on its tip.
Moreover, evolution is not synonymous with progress, but simply change over time. For example, more than new species of cichlid fish in Lake Victoria, the youngest of the great African lakes, have appeared since it filled with water some 14, years ago. Still, there is something unique about our brain that makes it cognitively able to ponder even its own constitution and the reasons for its own presumption that it reigns over all other brains.
If we are the ones putting other animals under the microscope, and not the other way around, 1 then the human brain must have something that no other brain has. Sheer mass would be the obvious candidate: If the brain is what generates conscious cognition, having more brain should only mean more cognitive abilities.
But here the elephant in the room is, well, the elephant—a species that is larger-brained than humans, but not equipped with behaviors as complex and flexible as ours. Besides, equating larger brain size with greater cognitive capabilities presupposes that all brains are made the same way, starting with a similar relationship between brain size and number of neurons.
But my colleagues and I already knew that all brains were not made the same. Primates have a clear advantage over other mammals, which lies in an evolutionary turn of events that resulted in the economical way in which neurons are added to their brain, without the massive increases in average cell size seen in other mammals.
Sheer number of neurons would be the obvious candidate, regardless of brain size, because if neurons are what generates conscious cognition, then having more neurons should mean more cognitive capabilities. Indeed, even though cognitive differences among species were once thought to be qualitative, with a number of cognitive capabilities once believed to be exclusive to humans, it is now recognized that the cognitive differences between humans and other animals are a matter of degree.
That is, they are quantitative, not qualitative, differences. Did the African elephant brain, more than three times as heavy as ours, really have more neurons than our brain? By Lauren R. Lauren R. Weinstein is a cartoonist based in New Jersey. She is currently working on a graphic novel tentatively entitled How to Draw a Nose. Her previous books include Girl Stories and The Goddess Our tool use is impressively complex, and we even design tools to make other tools—but chimpanzees use twigs as tools to dig for termites, monkeys learn to use rakes to reach for food that is out of sight, and crows not only shape wires to use as tools to get food, but also keep them safe for later reuse.
Alex, the African gray parrot owned by psychologist Irene Pepperberg, learned to produce words that symbolize objects, and chimpanzees and gorillas, though they cannot vocalize for anatomical reasons, learn to communicate with sign language. Chimpanzees can learn hierarchical sequences: They play games where they must touch squares in the ascending order of the numbers previously shown, and they do it as well and as fast as highly trained humans.
Chimpanzees and gorillas, elephants, dolphins, and also magpies appear to recognize themselves in the mirror, using it to inspect a visible mark placed on their heads. These are fundamental discoveries that attest to the cognitive capacities of nonhuman species—but such one-of-a-kind observations do not serve the types of cross-species comparisons we need to make if we are to find out what it is about the brain that allows some species to achieve cognitive feats that are outside the reach of others.
And here we run into another problem, the biggest one at this point: how to measure cognitive capabilities in a large number of species and in a way that generates measurements that are comparable across all those species.
A study tested for self-control, a cognitive ability that relies on the prefrontal, associative part of the cerebral cortex, among a number of animal species—mostly primates, but also small rodents, doglike carnivores, the Asian elephant, and a variety of bird species. They found that the best correlate with correct performance in the test of self-control was absolute brain volume—except for the Asian elephant, which, despite being the largest-brained in the set, failed miserably at the task.
Gimme something more challenging to do! Gimme videogames! Narration: What made you question that number? Herculano-Houzel: What made me realize that we didn't know the first thing about what brains are made of was a survey that I ran at a science museum in Brazil where I started working after I got my PhD.
I ran a survey with people who visited the museum on a number of things about the brain like Great right? I still don't know where that myth came from, but I started looking around and one of the possibilities was that you open textbooks and there it was. Do you know whoever actually counted and found that there are billion neurons in the brain, in the human brain, and 10 times as many glial cells?
Everybody was like, "Um. I actually don't, but those are the numbers, aren't they? It's just hearsay. I went digging through the literature and that's when I realized that everybody thought that everybody else had already figured this out but nobody actually had.
Narration: Herculano-Houzel came up with an ingenious way to test how many neurons were actually in the human brain. The number she came up with? Herculano-Houzel: The average that we have so far is a total of 86 billion neurons and just as many non neuronal cells which includes not just glial, but also the endothelial cells.
That's something that we're working on now. That still leaves less than one glial cell per neuron in the brain as a whole. The thing is that this ratio between how many glial cells and how many neurons you have, that's highly variable across different parts of the brain. You can have two or maybe even three glial cells per neuron in some parts of the cortex, and less than 0. Getting those numbers for the first time was really exhilarating. Before that we had mice and rats, which you know, they're just mice and rats.
I remember thinking I know something that nobody else does. The next thought is, well I need to get the word out now because this is useless if I know this but nobody else does.
It was about the same thing with the humans with the bonus that once we had those numbers, we could actually start comparing them to other species and that's where you realize that compared to other primates we're just that generic primate with a 1. To me, that's the most important part about having the numbers. It's not just the numbers per say; it's what you can do with them. Narration: Why do you think people held on to the billion neurons myth for so long? The lion and striped hyena have only as many cortical neurons as the average dog, which is only slightly more neurons than the raccoon, and the brown bear has even fewer cortical neurons, about as many as found in the cat.
E The mass of the cerebellum scales as a power function of body mass with exponent 0. F The number of neurons in the cerebellum scales as a power function of body mass with exponent 0. G The mass of the rest of brain of carnivoran species scales as a power function of body mass with exponent 0. H The number of neurons in the rest of brain of carnivoran species scales as a power function of body mass with exponent 0.
Within the brain, carnivorans have cerebella of comparable mass and numbers of neurons to other non-primate mammals of similar body mass, artiodactyls in particular Figures 3E,F. Interestingly, the rest of brain is somewhat smaller in mass in carnivorans compared to artiodactyls of similar body mass Figure 3G , and also has significantly fewer neurons in carnivorans compared to artiodactyls and actually several other non-primate mammalian species of similar body mass Figure 3H. The raccoon, however, appears to have more neurons in the rest of brain than predicted for its body mass; indeed, removing the raccoon from the analysis improves the fit of the function that describes how the number of neurons in the RoB scales with body mass across carnivoran species Figure 3H.
As found in other mammalian clades, larger carnivoran species have larger cerebral cortices, whose mass is comparable to that of artiodactyls and several other non-primate mammalian species of similar body mass Figure 3C. Strikingly, however, larger carnivorans do not have increasingly more neurons in the cerebral cortex. While ferret, mongoose and cat have increasingly larger cortices 3. Even more strikingly, the brown bear has fewer neurons in the cerebral cortex than these two species, million neurons, which is only about as many as the house cat, even though the brown bear cortex had a nearly fold larger mass of The raccoon also stands out in its number of cortical neurons, but in a different direction: although the mass of the cerebral cortex in both raccoon and cat is a similar 24 g, the raccoon cerebral cortex has an average million neurons compared to million neurons in the cat Table 1.
Remarkably, of all the individuals we analyzed, the one with the most neurons in the cerebral cortex was a golden retriever dog million neurons , followed by the lion million neurons , one of the raccoons million neurons , the striped hyena million neurons , a smaller dog of unspecified breed million neurons and a second raccoon individual million neurons. As a result, the relationship between numbers of cerebral cortical neurons and body mass in carnivorans seems to saturate around — million neurons, and possibly adopt the shape of an inverted U with only half as many neurons in the brown bear cerebral cortex Figure 3D , a pattern that has not been observed in any other mammalian clade so far, where simple power laws apply Herculano-Houzel et al.
In contrast, the raccoon has more neurons in its cerebral cortex than expected for a non-primate mammal of its cortical mass, approaching the relationship expected for a primate Figure 4A , red circle and triangles. Indeed, while the banded mongoose, cat, dog and hyena have neuronal densities in the cerebral cortex that decrease predictably with increasing numbers of cortical neurons according to the scaling relationship that applies to other non-primates Figure 4B , the raccoon has an average neuronal density in the cerebral cortex that is about three times the expected for a non-primate mammal with its number of neurons in the cerebral cortex, approaching neuronal densities found in primate cortices.
On the other hand, neuronal densities are several times smaller than expected in the ferret, lion and especially the brown bear cerebral cortex for their numbers of cortical neurons, compared to non-primate mammals Figure 4B.
Scaling of mass of brain structures with numbers of neurons in carnivorans. A With the exception of the brown bear, ferret and raccoon, carnivoran species conform to the power function that describes how the mass of the cerebral cortex scales as a power function of the number of cortical neurons with exponent 1. The function calculated for carnivorans without the bear and raccoon has an exponent of 1.
B Again, with the exception of the brown bear, ferret and raccoon, the density of neurons in the cerebral cortex of carnivoran species conforms to the power function that describes the scaling of neuronal density with the number of cortical neurons of exponent —0. C With the exception of the raccoon, carnivoran species conform to the power function that describes how the mass of the cerebellum scales as a power function of the number of cerebellar neurons with exponent 1.
D With the exception of the raccoon, the density of neurons in the cerebellum of carnivoran species conforms to the power function that describes the scaling of neuronal density with the number of cerebellar neurons of exponent —0. E The power function that describes how the mass of the rest of brain scales with the number of rest of brain neurons across artiodactyls minus the giraffe , eulipotyphlans and marsupials exponent, 2.
F Carnivorans are aligned with the scaling of neuronal density in the rest of brain with the number of rest of brain neurons that applies to the ensemble of artiodactyls minus the giraffe , eulipotyphlans and marsupials, with exponent —1. In contrast to the cerebral cortex, the cerebellum of all carnivorans in the dataset conforms to the neuronal scaling rule that applies to the ensemble of afrotherians minus the elephant , glires, and artiodactyls — with the sole exception, again, of the raccoon Figure 4C.
The relationship between cerebellar mass and number of cerebellar neurons of carnivorans excluding the raccoon can be described by a power law of exponent 1.
In contrast, the raccoon cerebellum has nearly two times more neurons than predicted for a mammalian species belonging to those non-primate orders, conforming instead to the number of neurons found in the cerebellum of a primate of similar cerebellar mass. The mass of the carnivoran rest of brain scales with the number of neurons in the structure raised to an exponent of 1.
This exponent is not significantly different from the exponent of 2. Rodents, afrotherians and primates depart from this relationship Figure 4E. Carnivoran species conform to the relationship that describes how neuronal density in the RoB decreases with increasing number of neurons in the RoB across artiodactyls, eulipotyphlans and marsupials Figure 4F.
The discrepancies between expected and observed numbers of neurons in some carnivoran species, most notably the brown bear, could in principle be due to aberrant immunoreactivity to NeuN, which might fail to label all neurons in these species. Similarly, the aberrantly large numbers of neurons found in raccoon brain structures might in principle be due to non-specific labeling of non-neuronal cells with the anti-NeuN antibody.
In these scenarios, any unlabeled neurons in the bear cerebral cortex would be classified as non-neuronal cells and cause aberrantly high numbers of non-neuronal cells in brain structures for their mass; conversely, any labeled glial cells would be mistakenly classified as neurons and lead to aberrantly low numbers of non-neuronal cells in raccoon brain structures.
These aberrations would be particularly easy to spot since all major brain structures cerebral cortex, cerebellum and rest of brain of all mammalian species examined so far exhibit a relationship between structure mass and number of other non-neuronal cells that can be described by a single power function of near-linear exponent 1.
All carnivoran species and brain structures conform to the scaling of brain structure mass with numbers of other cells that applies universally across other mammalian species. Cerebral cortex is shown in circles, cerebellum in squares, rest of brain in triangles. A Brain structure mass scales universally as a power function of the number of non-neuronal other cells in the structures across non-carnivoran species plotted function; exponent 1.
B The density of other cells in the different structures of carnivoran brains overlaps with densities in the same structures in other mammalian species, which scales very slowly as a power function of structure mass of exponent C The ratio between numbers of other cells which approximates the number of glial cells and numbers of neurons in each structure is not a universal function of structure mass across mammalian species and structures.
D The ratio between numbers of other cells and neurons in each structure does vary universally with average neuronal density in the structure across non-carnivoran species plotted function, exponent Instead, we find that all carnivoran species and brain structures analyzed conform to the relationship that applies to all other mammalian species, including all raccoon brain structures and the brown bear cerebral cortex Figures 5A,B , colored points.
The conformity of carnivoran data to the relationship that applies to all other mammalian species and brain structures confirms the universality of the non-neuronal scaling rules Herculano-Houzel, ; Mota and Herculano-Houzel, This conformity also makes it highly unlikely that the unexpectedly small or large numbers of neurons in the brown bear cerebral cortex or raccoon brain structures are due to misclassification of cells as neurons.
As shown before Herculano-Houzel, , the ratio between numbers of other cells and neurons is not a universal function of structure mass across mammalian species, including carnivorans Figure 5C.
However, this ratio does scale universally with neuronal density in the structure across all mammalian species analyzed so far, and all carnivorans studied here, including the raccoon and brown bear, conform to that same relationship Figure 5D.
The dogs and cat individuals analyzed in this study were domesticated animals, raised by families who donated the brains after the animals died of natural causes, in contrast to other animals that were either wild-caught raccoon, hyena or kept in captivity which might lead to larger body mass, but are expected to be representative of wild species.
Notably, we find that these domesticated animals do not deviate from the relationship between brain mass or number of neurons and body mass that applies to carnivorans or to non-primates as a whole Figure 3. Additionally, cat and dog data points conform to the relationships between brain structure mass and number of neurons in the structure that apply to other carnivoran as well as various non-primate clades see Figure 4.
Both dog individuals examined a 7. The same applies to the cerebral cortex of the dogs, at Thus, the two most common species of domesticated carnivorans do not deviate from the relationship between cortical mass and number of neurons that applies both to wild carnivorans and other non-primate species of similar body, brain or cerebral cortical mass. The apparently decreased number of neurons in the cerebral cortex of large carnivorans for their cortical and body mass, notably in the brown bear, could in principle be the result of altered development that led to the generation of smaller numbers of much larger neurons, resulting in the observed lower neuronal densities but expected non-neuronal densities.
In that case, we might expect the cortical volume to still be distributed into surface area and thickness following the same scaling relationship that applies to other carnivorans, with larger surface areas accompanied by slowly increasing cortical thickness. Alternatively, if the unexpectedly small number of neurons in the cerebral cortex of large carnivorans is due to regressive phenomena after the cortex develops, such as pronounced neuronal loss after cortical expansion, we should find evidence of atrophy in the cerebral cortex of these species, with cortical thinning for their surface area, and possibly also a thicker cortex for their numbers of cortical neurons in case the maximal attained thickness is not entirely lost , compared to the allometric scaling that applies to other carnivoran species but still the same expected non-neuronal densities.
We thus determined how the cortical volume was distributed into surface area and thickness across carnivoran species, and how that distribution related to numbers of cortical neurons.
We find that carnivoran cerebral cortices with larger surface areas are also thicker, although cortical thickness increases more slowly than surface area, as a power function of surface area with exponent 0. While the raccoon and lion have combinations of cortical surface area and thickness that match the prediction for carnivoran species, the brown bear is a clear outlier, with a cortical thickness that is too small for its surface area, suggestive of cortical atrophy thinning.
Scaling of cortical surface area and thickness with number of neurons in carnivorans. Each carnivoran species is shown in a different color according to the key in the graphs. All other mammals are depicted in gray light gray filled circles, glires; light gray unfilled circles, artiodactyls; dark gray filled circles, marsupials; dark gray unfilled circles, afrotherians; filled triangles, primates; white triangle, scandentia.
For the sake of clarity, scaling relationships for non-carnivoran clades are not plotted. A Average cortical thickness scales as a power function of cortical surface area with exponent 0. The brown bear has a much thinner cortex for its surface area compared to other carnivoran species; the raccoon, in contrast, has the predicted combination of cortical surface area and thickness for a carnivoran.
B Average cortical thickness scales as a power function of the number of cortical neurons with exponent 0. C Cortical surface area scales as a power function of the number of cortical neurons with exponent 0. All values refer to a single cortical hemisphere. The distribution of cortical neurons into surface area and thickness also suggest that a regressive phenomenon is in place.
Both the brown bear and lion cortices are thicker than expected for the number of neurons in the cerebral cortex Figure 6B , black , consistent with cortices that had more neurons in early development, attained adult-like morphology, but then lost significant numbers of neurons and along with them, lost part of the width of the parenchyma, but not all of it.
Similarly, the surface area of the brown bear cerebral cortex is almost one order of magnitude larger than expected for its number of neurons Figure 6C , black. This pattern is consistent with a reduction in number of neurons in the cerebral cortex that occurred after cortical expansion in development, when the brain attained its adult density of non-neuronal cells, volume and surface area, leading to partial thinning of the cerebral cortex but very little loss of surface area.
In contrast to the bear, the raccoon has many more neurons than predicted for a carnivoran species with either its cortical thickness Figure 6B , red or its cortical surface area Figure 6C , red , even though its cortical thickness x surface area relationship conforms to the pattern that applies to other carnivoran species excluding the brown bear; Figure 6A.
The larger than expected number of cortical neurons in the presence of the clade-typical relationship between cortical thickness and surface area is consistent with the generation of larger numbers of smaller neurons and thus the observed increase in neuronal density in the raccoon cerebral cortex, and possibly in the raccoon brain as a whole Figure 4.
We have previously found that a single power function undistinguishable from linearity and with a slope of around 4. Most carnivorans analyzed conform to the same relationship that applies to other mammals, with the clear exception of the brown bear, which, like the elephant, has a much larger ratio between numbers of neurons in the cerebellum and in the cerebral cortex of Remarkably, the lion and hyena also have fewer neurons in the cerebral cortex than expected for their number of neurons in the cerebellum, with 7.
Scaling of numbers of neurons across brain structures in carnivorans. A Except for the brown bear, carnivorans conform to the relationship between numbers of neurons in the cerebellum and in the cerebral cortex that apply to all mammalian species examined so far, including primates, but excluding the African elephant exponent, 0. B Only the ferret and brown bear conform to the scaling relationship that describes how the number of neurons in the cerebral cortex varies as a power function of the number of neurons in the rest of brain across glires, eulipotyphlans, and small Afrotherians, with exponent 1.
All other carnivoran species, like primates, artiodactyls and Australasian marsupials, have more neurons in the cerebral cortex than predicted for the number of neurons in the rest of brain for glires, eulipotyphlans and small Afrotherians. C Only the banded mongoose among carnivoran species conforms to the scaling relationship that describes how the number of neurons in the cerebellum varies as a power function of the number of neurons in the rest of brain across glires, eulipotyphlans, and small Afrotherians, with exponent 1.
Whereas the cerebral cortex and cerebellum gain neurons proportionately across the vast majority of mammalian species, a similar concerted scaling on numbers of neurons in the cerebral cortex and rest of brain, with a constant ratio across structures, is true only across glires, eulipotyphlans, small afrotherians, and South American marsupials Herculano-Houzel, Across these species, a ratio of is maintained between neurons in the cerebral cortex:rest of brain, in what we have proposed to be the ancestral allocation of neurons across these structures Herculano-Houzel et al.
Artiodactyls, primates and Australasian marsupials deviate from this relationship, with larger ratios between numbers of neurons in the cerebral cortex and in the rest of brain that may also increase with brain size.
We find that among carnivorans, only the ferret and the brown bear align themselves with the first group Figure 7B , with small ratios of 2. In line with the approximately ratio between numbers of neurons in the cerebellum and in the cerebral cortex across most species but not the elephant and brown bear, we find that the cerebellum and rest of brain also gain neurons proportionately across glires, eulipotyphlans, small afrotherians, and South American marsupials, maintaining a ratio of about Figure 7C.
In contrast, artiodactyls, primates and Australasian marsupials gain neurons in the cerebellum faster than in the rest of brain Figure 7C. Carnivorans again align with the latter mammalian species, with faster addition of neurons to the cerebellum than to the rest of brain, and thus larger ratios between numbers of neurons in the two structures, compared to glires, eulipotyphlans, and small afrotherians Figure 7C.
Here we find that all carnivoran species examined match the relationship between brain structure mass and number of non-neuronal cells that has been found to apply to all mammalian species examined so far Dos Santos et al. This relationship is a consequence of the lack of systematic variation in the density of non-neuronal cells across brain structures and species. Accordingly, none of the eight carnivoran species analyzed deviated significantly from the non-neuronal cell densities found previously in other mammalian species.
These findings are consistent with our proposition that the mechanisms that regulate addition of non-neuronal cells to brain tissue have been remarkably conserved in evolution, which indicates that average size of non-neuronal cells is tightly controlled in development and does not accept much variation across species or structures Mota and Herculano-Houzel, The addition of non-neuronal cells in development with relatively unchanging cell density across brain structures and species seems to also apply to the raccoon and the brown bear, regardless of the mechanisms that lead to their deviating neuronal densities.
Most of the carnivoran species analyzed also conformed to the relationship between numbers of neurons and neuronal density found to apply to other non-primate species, and thus also to the resulting relationship between numbers of neurons and structure mass Herculano-Houzel et al.
However, the smallest ferret and largest brown bear species had fewer neurons in the cerebral cortex than expected for the mass of this structure in a non-primate mammal, a trend followed also by the lion, which has a cortex with fewer neurons than the golden retriever despite being nearly twice larger.
As discussed below, in the context of metabolic cost and the relationships across cortical surface area, thickness and number of neurons, the lower than expected neuronal densities restricted to the cerebral cortex are suggestive of neuronal loss. Conversely, the raccoon had systematically larger neuronal densities than expected in all three structures examined — cerebral cortex, cerebellum and rest of brain.
In the context of a relationship between cortical surface area and thickness that still matched that found for most other carnivoran species, this finding suggests that the raccoon brain develops with a larger number of smaller neurons than expected for a carnivoran, resulting in larger numbers of neurons than expected for a non-primate, approaching the numbers found in primate species.
Indeed, given only the relationship between brain structure mass and numbers of neurons, one might inadvertently take the raccoon for a primate. Comparisons of the brain mass vs. One should keep in mind, however, that a lateral shift in the relationship is equally possible, with domestication inducing larger body masses rather than decreased brain mass which would be expected due to greater food availability in captivity. Indeed, recent evidence suggests that domestication of the chicken has led mostly to a larger body mass, and to a lesser extent, to larger not smaller absolute brain mass, mainly due to enlargement of the cerebellum Henriksen et al.
Untangling the two possibilities — increased body mass for the size of the brain or decreased brain mass for the size of the body — is not feasible when brain size and body size are the only variables available, and when only one species is considered in its wild and domesticated versions.
By bringing in other variables and examining other carnivoran as well as other non-primate species, here we show that laboratory-raised ferrets as well as the most common domesticated species, cat and dog, do not have smaller brains or fewer neurons than expected for their body mass.
Similarly, we have found that the pig shares a relationship between brain mass and number of neurons with other artiodactyl and non-primate species, although it is an outlier in its much larger body mass for its number of brain neurons Kazu et al. We thus have no reason to believe that domesticated animals have become any different from other carnivorans in the allometric scaling of their brains although the ferret, the smallest carnivoran species examined, might be affected by energetic constraints because of its size; see below.
Intraspecific variation is an important issue to consider in this context. We know that it can be large even in species considered to be fairly homogeneous such as the laboratory mouse, in which body mass still varies across young adult animals of same sex and age by a factor of 2, and brain mass varies by a factor of 1.
Importantly, we found that larger mice do not have significantly larger brains than smaller mice, and those mouse individuals with larger brains or brain structures do not necessarily have more neurons than individuals with smaller brains or brain structures Herculano-Houzel et al. The lack of a strong correlation across individuals mirroring the power functions that apply across species can be attributed to the finding that across mouse individuals, those with more neurons in a brain structure also have smaller , not bigger, neurons.
This discrepancy suggests a fundamental difference between developmental and evolutionary patterns of brain variation Herculano-Houzel et al. Indeed, it is well established that allometric relationships that apply across species usually do not apply within species, at least not with the same exponents Armstrong, The lack of continuity between intra- and interspecific comparisons might still be simply due to the typically much smaller range of variation across individuals of a given species, precluding the calculation of accurate relationships — although that should be possible to compensate for with larger sample sizes.
Dogs, with their enormous variation in body and brain size at least fold and 2-fold, respectively; Wosinski et al. While we acknowledge that intraspecific variation not only is significant but also is a very interesting topic in its own right, we still expect it to be negligible when compared to the variation over 2 orders of magnitude in body mass across carnivoran species that we examine here.
Thus, while expanding the analysis to a larger number of individuals of each species would of course have been ideal, we believe it is reasonable to expect that individual variation in most species other than the dog is unlikely to affect the results we report here. We and others have suggested that the absolute number of neurons in the cerebral cortex are a major determinant of the cognitive capabilities of different species Roth and Dicke, ; Herculano-Houzel et al.
Testing that prediction requires data on cognitive performance that can be compared across species. It is only recently that data obtained with systematic comparative analyses have started to become available, although most studies continue to focus on particular clades, mostly primates Deaner et al.
Cognitive performance in carnivorans was recently addressed specifically by Benson-Amram et al. Across these species, even though brain size relative to body mass is a significant predictor of success in opening a puzzle box, species with larger absolute brain volumes also tended to be better than others at opening the puzzle box Benson-Amram et al. Other studies found that absolute brain size or absolute size of the cerebral cortex across primates is a much better correlate of task performance than encephalization quotient Deaner et al.
Given that larger primate brains are composed of increasing numbers of neurons Herculano-Houzel et al. Indeed, small-brained corvids show similar performance to much larger-brained primates Kabadayi et al. It is thus likely that the larger the number of neurons found in the cerebral cortex of a carnivoran, the more cognitively capable the species is.
The twice larger absolute number of neurons we find in the cerebral cortex of the dog compared to the domestic cat suggests that dogs have a cognitive advantage over cats — and raccoons, despite their smaller brain size compared to dogs, should have similar capabilities to dogs. Unfortunately, no dogs, cats or raccoons were examined in the comprehensive study of carnivorans by Benson-Amram et al. Any argument about their cognitive capabilities at this point will be largely a matter of opinion until direct, systematic comparisons of cognitive capacity are performed across these and other species.
Moreover, given that both cats and dogs seem to obey the same neuronal scaling rules for the cerebral cortex, any difference in cognitive capabilities between them due to differences in numbers of cortical neurons would be tied to differences in resulting brain size, suggesting that cat-sized dogs, if they have cat-sized brains, might have only as many cortical neurons as domestic cats. Still, our data allow us to predict that, with their larger numbers of neurons in the cerebral cortex, dogs of the sizes examined here should have more complex and flexible cognition than cats.
It was once believed that dogs had evolved special forms of cognition relative to their wild counterparts, wolves Frank, , but the same author later concluded that his thesis was incorrect and no such difference existed Frank, Although the domestic cat has been a favored non-primate model for neurophysiological studies of sensory systems and perception, not much has been done to examine its cognitive capabilities, especially in direct comparison to the domestic dog Shreve and Udell, These authors have called attention to how popular articles often present cat cognition with a negative spin, whereas research suggests that domestic cats, like dogs, have developed a range of behaviors that facilitate their interaction with humans.
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