Brain size scales as different functions of its number of neurons across mammalian orders such as rodents, primates, and insectivores. In rodents, we have previously shown that, across a sample of 6 species, from mouse to capybara, the cerebral cortex, cerebellum and the remaining brain structures increase in size faster than they gain neurons, with an accompanying decrease in neuronal density in these structures [Herculano-Houzel et al.: Proc Natl Acad Sci USA 2006;103:12138–12143]. Important remaining questions are whether such neuronal scaling rules within an order apply equally to all pertaining species, and whether they extend to closely related taxa. Here, we examine whether 4 other species of Rodentia, as well as the closely related rabbit (Lagomorpha), conform to the scaling rules identified previously for rodents. We report the updated neuronal scaling rules obtained for the average values of each species in a way that is directly comparable to the scaling rules that apply to primates [Gabi et al.: Brain Behav Evol 2010;76:32–44], and examine whether the scaling relationships are affected when phylogenetic relatedness in the dataset is accounted for. We have found that the brains of the spiny rat, squirrel, prairie dog and rabbit conform to the neuronal scaling rules that apply to the previous sample of rodents. The conformity to the previous rules of the new set of species, which includes the rabbit, suggests that the cellular scaling rules we have identified apply to rodents in general, and probably to Glires as a whole (rodents/lagomorphs), with one notable exception: the naked mole-rat brain is apparently an outlier, with only about half of the neurons expected from its brain size in its cerebral cortex and cerebellum.
Rodents; Brain size; Evolution; Neurons; Glia; Glires
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 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.
brain scaling; number of neurons; human; encephalization
What are the rules relating the size of the brain and its structures to the number of cells that compose them and their average sizes? We have shown previously that the cerebral cortex, cerebellum and the remaining brain structures increase in size as a linear function of their numbers of neurons and non-neuronal cells across 6 species of primates. Here we describe that the cellular composition of the same brain structures of 5 other primate species, as well as humans, conform to the scaling rules identified previously, and that the updated power functions for the extended sample are similar to those determined earlier. Accounting for phylogenetic relatedness in the combined dataset does not affect the scaling slopes that apply to the cerebral cortex and cerebellum, but alters the slope for the remaining brain structures to a value that is similar to that observed in rodents, which raises the possibility that the neuronal scaling rules for these structures are shared among rodents and primates. The conformity of the new set of primate species to the previous rules strongly suggests that the cellular scaling rules we have identified apply to primates in general, including humans, and not only to particular subgroups of primate species. In contrast, the allometric rules relating body and brain size are highly sensitive to the particular species sampled, suggesting that brain size is neither determined by body size nor together with it, but is rather only loosely correlated with body size.
Allometry; Brain size; Evolution; Glia, number; Neurons, number; Primates
The Gray-faced Sengi (Rhynchocyon udzungwensis) is a newly-discovered species of sengi (elephant-shrew) and is the largest known extant representative of the order Macroscelidea. The discovery of R. udzungwensis provides an opportunity to investigate the scaling relationship between brain size and body size within Macroscelidea, and to compare this allometry among insectivorous species of Afrotheria and other eutherian insectivores. We performed a spin-echo magnetic resonance imaging (MRI) scan on a preserved adult specimen of R. udzungwensis using a 7-Tesla high-field MR imaging system. The brain was manually segmented and its volume was compiled into a dataset containing previously-published allometric data on 56 other species of insectivore-grade mammals including representatives of Afrotheria, Soricomorpha and Erinaceomorpha. Results of log-linear regression indicate that R. udzungwensis exhibits a brain size that is consistent with the allometric trend described by other members of its order. Inter-specific comparisons indicate that macroscelideans as a group have relatively large brains when compared with similarly-sized terrestrial mammals that also share a similar diet. This high degree of encephalization within sengis remains robust whether sengis are compared with closely-related insectivorous afrotheres, or with more-distantly-related insectivorous laurasiatheres.
Gorillas and orangutans are primates at least as large as humans, but their brains amount to about one third of the size of the human brain. This discrepancy has been used as evidence that the human brain is about 3 times larger than it should be for a primate species of its body size. In contrast to the view that the human brain is special in its size, we have suggested that it is the great apes that might have evolved bodies that are unusually large, on the basis of our recent finding that the cellular composition of the human brain matches that expected for a primate brain of its size, making the human brain a linearly scaled-up primate brain in its number of cells. To investigate whether the brain of great apes also conforms to the primate cellular scaling rules identified previously, we determine the numbers of neuronal and other cells that compose the orangutan and gorilla cerebella, use these numbers to calculate the size of the brain and of the cerebral cortex expected for these species, and show that these match the sizes described in the literature. Our results suggest that the brains of great apes also scale linearly in their numbers of neurons like other primate brains, including humans. The conformity of great apes and humans to the linear cellular scaling rules that apply to other primates that diverged earlier in primate evolution indicates that prehistoric Homo species as well as other hominins must have had brains that conformed to the same scaling rules, irrespective of their body size. We then used those scaling rules and published estimated brain volumes for various hominin species to predict the numbers of neurons that composed their brains. We predict that Homo heidelbergensis and Homo neanderthalensis had brains with approximately 80 billion neurons, within the range of variation found in modern Homo sapiens. We propose that while the cellular scaling rules that apply to the primate brain have remained stable in hominin evolution (since they apply to simians, great apes and modern humans alike), the Colobinae and Pongidae lineages favored marked increases in body size rather than brain size from the common ancestor with the Homo lineage, while the Homo lineage seems to have favored a large brain instead of a large body, possibly due to the metabolic limitations to having both.
Allometry; Brain size; Great apes; Human; Evolution, human; Neurons, number
Expansion of the cortical gray matter in evolution has been accompanied by an even faster expansion of the subcortical white matter volume and by folding of the gray matter surface, events traditionally considered to occur homogeneously across mammalian species. Here we investigate how white matter expansion and cortical folding scale across species of rodents and primates as the gray matter gains neurons. We find very different scaling rules of white matter expansion across the two orders, favoring volume conservation and smaller propagation times in primates. For a similar number of cortical neurons, primates have a smaller connectivity fraction and less white matter volume than rodents; moreover, as the cortex gains neurons, there is a much faster increase in white matter volume and in its ratio to gray matter volume in rodents than in primates. Order-specific scaling of the white matter can be attributed to different scaling of average fiber caliber and neuronal connectivity in rodents and primates. Finally, cortical folding increases as different functions of the number of cortical neurons in rodents and primates, scaling faster in the latter than in the former. While the neuronal rules that govern gray and white matter scaling are different across rodents and primates, we find that they can be explained by the same unifying model, with order-specific exponents. The different scaling of the white matter has implications for the scaling of propagation time and computational capacity in evolution, and calls for a reappraisal of developmental models of cortical expansion in evolution.
white matter; number of neurons; allometry; brain size; cortical expansion; gyrification
Deterministic filters such as competition and prey defences should have a strong influence on the community structure of animals such as insectivorous bats that have life histories characterized by low fecundity, low predation risk, long life expectancy, and stable populations. We investigated the relative influence of these two deterministic filters on the phenotypic structure of insectivorous bat ensembles in southern Africa. We used null models to simulate the random phenotypic patterns expected in the absence of competition or prey defences and analysed the deviations of the observed phenotypic pattern from these expected random patterns. The phenotypic structure at local scales exhibited non-random patterns consistent with both competition and prey defense hypotheses. There was evidence that competition influenced body size distribution across ensembles. Competition also influenced wing and echolocation patterns in ensembles and in functional foraging groups with high species richness or abundance. At the same time, prey defense filters influenced echolocation patterns in two species-poor ensembles. Non-random patterns remained evident even after we removed the influence of body size from wing morphology and echolocation parameters taking phylogeny into account. However, abiotic filters such as geographic distribution ranges of small and large-bodied species, extinction risk, and the physics of flight and sound probably also interacted with biotic filters at local and/or regional scales to influence the community structure of sympatric bats in southern Africa. Future studies should investigate alternative parameters that define bat community structure such as diet and abundance to better determine the influence of competition and prey defences on the structure of insectivorous bat ensembles in southern Africa.
The spinal cord can be considered a major sensorimotor interface between the body and the brain. How does the spinal cord scale with body and brain mass, and how are its numbers of neurons related to the number of neurons in the brain across species of different body and brain sizes? Here we determine the cellular composition of the spinal cord in eight primate species and find that its number of neurons varies as a linear function of cord length, and accompanies body mass raised to an exponent close to 1/3. This relationship suggests that the extension, mass and number of neurons that compose the spinal cord are related to body length, rather than to body mass or surface. Moreover, we show that although brain mass increases linearly with cord mass, the number of neurons in the brain increases with the number of neurons in the spinal cord raised to the power of 1.7. This faster addition of neurons to the brain than to the spinal cord is consistent with current views on how larger brains add complexity to the processing of environmental and somatic information.
Allometry; Number of neurons; Evolution; Connectivity
The exceptional diversity of neotropical bat communities is sustained by an intricate partitioning of available resources among the member species. Trophical specialization is considered an important evolutionary avenue towards niche partitioning in neotropical phyllostomid bats. From an ancestral insectivorous condition, phyllostomids evolved into highly specialized frugivorous, carnivorous, nectarivorous, piscivorous and even sanguivorous species. Previously, correlations between cranial morphology and trophic ecology within this group have been documented. Here, we examine the evolutionary relationships between bite force and head shape in over 20 species of bats from a single tropical savannah bat community. The results show that bite force increases exponentially with body size across all species examined. Despite the significant differences between large dietary groups using traditional analysis (i.e. non-phylogenetic) and the strong evolutionary correlations between body mass and bite force, phylogenetic analyses indicated no differences in bite performance between insectivorous, omnivorous and frugivorous bats. Comparisons of three species with highly specialized feeding habits (nectarivory, piscivory and sanguivory) with the rest of the species in the community indicate that specialization into these niches comes at the expense of bite performance and, hence, may result in a reduction of the trophic niche breadth.
The elemental composition of animals, or their organismal stoichiometry, is thought to constrain their contribution to nutrient recycling, their interactions with other animals, and their demographic rates. Factors that affect organismal stoichiometry are generally poorly understood, but likely reflect elemental investments in morphological features and life history traits, acting in concert with the environmental availability of elements. We assessed the relative contribution of organismal traits and environmental variability to the stoichiometry of an insectivorous Neotropical stream fish, Rivulus hartii. We characterized the influence of body size, life history phenotype, stage of maturity, and environmental variability on organismal stoichiometry in 6 streams that differ in a broad suite of environmental variables. The elemental composition of R. hartii was variable, and overlapped with the wide range of elemental composition documented across freshwater fish taxa. Average %P composition was ∼3.2%(±0.6), average %N∼10.7%(±0.9), and average %C∼41.7%(±3.1). Streams were the strongest predictor of organismal stoichiometry, and explained up to 18% of the overall variance. This effect appeared to be largely explained by variability in quality of basal resources such as epilithon N∶P and benthic organic matter C∶N, along with variability in invertebrate standing stocks, an important food source for R. hartii. Organismal traits were weak predictors of organismal stoichiometry in this species, explaining when combined up to 7% of the overall variance in stoichiometry. Body size was significantly and positively correlated with %P, and negatively with N∶P, and C∶P, and life history phenotype was significantly correlated with %C, %P, C∶P and C∶N. Our study suggests that spatial variability in elemental availability is more strongly correlated with organismal stoichiometry than organismal traits, and suggests that the stoichiometry of carnivores may not be completely buffered from environmental variability. We discuss the relevance of these findings to ecological stoichiometry theory.
Shade coffee plantations have received attention for their role in biodiversity conservation. Bats are among the most diverse mammalian taxa in these systems; however, previous studies of bats in coffee plantations have focused on the largely herbivorous leaf-nosed bats (Phyllostomidae). In contrast, we have virtually no information on how ensembles of aerial insectivorous bats – nearly half the Neotropical bat species – change in response to habitat modification. To evaluate the effects of agroecosystem management on insectivorous bats, we studied their diversity and activity in southern Chiapas, Mexico, a landscape dominated by coffee agroforestry. We used acoustic monitoring and live captures to characterize the insectivorous bat ensemble in forest fragments and coffee plantations differing in the structural and taxonomic complexity of shade trees. We captured bats of 12 non-phyllostomid species; acoustic monitoring revealed the presence of at least 12 more species of aerial insectivores. Richness of forest bats was the same across all land-use types; in contrast, species richness of open-space bats increased in low shade, intensively managed coffee plantations. Conversely, only forest bats demonstrated significant differences in ensemble structure (as measured by similarity indices) across land-use types. Both overall activity and feeding activity of forest bats declined significantly with increasing management intensity, while the overall activity, but not feeding activity, of open-space bats increased. We conclude that diverse shade coffee plantations in our study area serve as valuable foraging and commuting habitat for aerial insectivorous bats, and several species also commute through or forage in low shade coffee monocultures.
It is usually considered that larger brains have larger neurons, which consume more energy individually, and are therefore accompanied by a larger number of glial cells per neuron. These notions, however, have never been tested. Based on glucose and oxygen metabolic rates in awake animals and their recently determined numbers of neurons, here I show that, contrary to the expected, the estimated glucose use per neuron is remarkably constant, varying only by 40% across the six species of rodents and primates (including humans). The estimated average glucose use per neuron does not correlate with neuronal density in any structure. This suggests that the energy budget of the whole brain per neuron is fixed across species and brain sizes, such that total glucose use by the brain as a whole, by the cerebral cortex and also by the cerebellum alone are linear functions of the number of neurons in the structures across the species (although the average glucose consumption per neuron is at least 10× higher in the cerebral cortex than in the cerebellum). These results indicate that the apparently remarkable use in humans of 20% of the whole body energy budget by a brain that represents only 2% of body mass is explained simply by its large number of neurons. Because synaptic activity is considered the major determinant of metabolic cost, a conserved energy budget per neuron has several profound implications for synaptic homeostasis and the regulation of firing rates, synaptic plasticity, brain imaging, pathologies, and for brain scaling in evolution.
Most animal species display Sexual Size Dimorphism (SSD): males and females consistently attain different sizes, most frequently with females being larger than males. However the selective mechanisms driving patterns of SSD remain controversial. ‘Rensch's rule’ proposes a general scaling phenomenon for all taxa, whereby SSD increases with average body size when males are larger than females, and decreases with body size when females are larger than males. Rensch's rule appears to be general in the former case, but there is little evidence for the rule when females are larger then males.
Using comprehensive data for 1291 species of birds across 30 families, we find strong support for Rensch's rule in families where males are typically larger than females, but no overall support for the rule in families with female-biased SSD. Reviewing previous studies of a broad range of taxa (arthropods, reptiles, fish and birds) showing predominantly female-biased SSD, we conclude that Rensch's conjecture is the exception rather than the rule in such species.
The absence of consistent scaling of SSD in taxa with female-biased SSD, the most prevalent direction of dimorphism, calls into question previous general evolutionary explanations for Rensch's rule. We propose that, unlike several other ecological scaling relationships, Rensch's rule does not exist as an independent scaling phenomenon.
With the rising number of patients with human immunodeficiency virus (HIV)/AIDS in developing countries, the control of mycobacteria is of growing importance. Previous studies have shown that rodents and insectivores are carriers of mycobacteria. However, it is not clear how widespread mycobacteria are in these animals and what their role is in spreading them. Therefore, the prevalence of mycobacteria in rodents and insectivores was studied in and around Morogoro, Tanzania. Live rodents were trapped, with three types of live traps, in three habitats. Pieces of organs were pooled per habitat, species, and organ type (stratified pooling); these sample pools were examined for the presence of mycobacteria by PCR, microscopy, and culture methods. The mycobacterial isolates were identified using phenotypic techniques and sequencing. In total, 708 small mammals were collected, 31 of which were shrews. By pool prevalence estimation, 2.65% of the animals were carriers of mycobacteria, with a higher prevalence in the urban areas and in Cricetomys gambianus and the insectivore Crocidura hirta. Nontuberculous mycobacteria (Mycobacterium chimaera, M. intracellulare, M. arupense, M. parascrofulaceum, and Mycobacterium spp.) were isolated from C. gambianus, Mastomys natalensis, and C. hirta. This study is the first to report findings of mycobacteria in African rodents and insectivores and the first in mycobacterial ecology to estimate the prevalence of mycobacteria after stratified pool screening. The fact that small mammals in urban areas carry more mycobacteria than those in the fields and that potentially pathogenic mycobacteria were isolated identifies a risk for other animals and humans, especially HIV/AIDS patients, that have a weakened immune system.
Cortical expansion, both in absolute terms and in relation to subcortical structures, is considered a major trend in mammalian brain evolution with important functional implications, given that cortical computations should add complexity and flexibility to information processing. Here, we investigate the numbers of neurons that compose 4 structures in the visual pathway across 11 non-human primate species to determine the scaling relationships that apply to these structures and among them. We find that primary visual cortex, area V1, as well as the superior colliculus (SC) and lateral geniculate nucleus scale in mass faster than they gain neurons. Areas V1 and MT gain neurons proportionately to the entire cerebral cortex, and represent fairly constant proportions of all cortical neurons (36 and 3 %, respectively), while V1 gains neurons much faster than both subcortical structures examined. Larger primate brains therefore have increased ratios of cortical to subcortical neurons involved in processing visual information, as observed in the auditory pathway, but have a constant proportion of cortical neurons dedicated to the primary visual representation, and a fairly constant ratio of about 45 times more neurons in primary visual than in primary auditory cortical areas.
Superior colliculus; Visual cortex; Lateral geniculate nucleus; V1; Area MT; Thalamus; Allometry; Brain size; Evolution
Trade-offs have long been a major theme in life-history theory, but they have been hard to document. We introduce a new method that reveals patterns of divergent trade-offs after adjusting for the pervasive variation in rate of resource allocation to offspring as a function of body size and lifestyle. Results suggest that preweaning vulnerability to predation has been the major factor determining how female placental mammals allocate production between a few large and many small offspring within a litter and between a few large litters and many small ones within a reproductive season. Artiodactyls, perissodactyls, cetaceans, and pinnipeds, which give birth in the open on land or in the sea, produce a few large offspring, at infrequent intervals, because this increases their chances of escaping predation. Insectivores, fissiped carnivores, lagomorphs, and rodents, whose offspring are protected in burrows or nests, produce large litters of small newborns. Primates, bats, sloths, and anteaters, which carry their young from birth until weaning, produce litters of one or a few offspring because of the need to transport and care for them.
life-history theory; trade-off; litter size; offspring size; litter frequency; litter mass
Gamma-aminobutyric-acidergic (GABAergic) cells form a very heterogeneous population of neurons that play a crucial role in the coordination and integration of cortical functions. Their number and diversity increase through mammalian brain evolution. Does evolution use the same or different developmental rules to provide the increased population of cortical GABAergic neurons? In rodents, these neurons are not generated in the pallial proliferative zones as glutamatergic principal neurons. They are produced almost exclusively by the subpallial proliferative zones, the ganglionic eminence (GE) and migrate tangentially to reach their target cortical layers. The GE is organized in molecularly different subdomains that produce different subpopulations of cortical GABAergic neurons. In humans and non-human primates, in addition to the GE, cortical GABAergic neurons are also abundantly generated by the proliferative zones of the dorsal telencephalon. Neurogenesis in ventral and dorsal telencephalon occurs with distinct temporal profiles. These dorsal and ventral lineages give rise to different populations of GABAergic neurons. Early-generated GABAergic neurons originate from the GE and mostly migrate to the marginal zone and the subplate. Later-generated GABAergic neurons, originating from both proliferative sites, populate the cortical plate. Interestingly, the pool of GABAergic progenitors in dorsal telencephalon produces mainly calretinin neurons, a population known to be significantly increased and to display specific features in primates. We conclude that the development of cortical GABAergic neurons have exclusive features in primates that need to be considered in order to understand pathological mechanisms leading to some neurological and psychiatric diseases.
interneurons; neurogenesis; tangential migration; ganglionic eminence; ventricular zone; glutamic acid decarboxylase
Nervous systems are information processing networks that evolved by natural selection, whereas very large scale integrated (VLSI) computer circuits have evolved by commercially driven technology development. Here we follow historic intuition that all physical information processing systems will share key organizational properties, such as modularity, that generally confer adaptivity of function. It has long been observed that modular VLSI circuits demonstrate an isometric scaling relationship between the number of processing elements and the number of connections, known as Rent's rule, which is related to the dimensionality of the circuit's interconnect topology and its logical capacity. We show that human brain structural networks, and the nervous system of the nematode C. elegans, also obey Rent's rule, and exhibit some degree of hierarchical modularity. We further show that the estimated Rent exponent of human brain networks, derived from MRI data, can explain the allometric scaling relations between gray and white matter volumes across a wide range of mammalian species, again suggesting that these principles of nervous system design are highly conserved. For each of these fractal modular networks, the dimensionality of the interconnect topology was greater than the 2 or 3 Euclidean dimensions of the space in which it was embedded. This relatively high complexity entailed extra cost in physical wiring: although all networks were economically or cost-efficiently wired they did not strictly minimize wiring costs. Artificial and biological information processing systems both may evolve to optimize a trade-off between physical cost and topological complexity, resulting in the emergence of homologous principles of economical, fractal and modular design across many different kinds of nervous and computational networks.
Brains are often compared to computers but, apart from the trivial fact that both process information using a complex physical pattern of connections, it has been unclear whether this is more than just a metaphor. In our work, we rigorously uncover novel quantitative organizational principles that underlie the network organization of the human brain, high performance computer circuits, and the nervous system of the nematode C. elegans. We show through a topological and physical analysis of connectivity data that each of these systems is cost-efficiently embedded in physical space; they are organized as economical modular networks, paying a modest premium in wiring cost for the functional advantages of high dimensional topology. We also show that the fractal properties of human brain network connectivity can be used to explain allometric scaling relations between grey and white matter volumes in the brains of a wide range of differently sized mammals—from mouse opossum to sea lion—further suggesting that these principles of nervous system design are highly conserved across species. We propose that market-driven human invention and natural selection have negotiated trade-offs between cost and complexity in design of information processing networks and convergently come to similar conclusions.
In this paper, we demonstrate that two characteristic properties of mammalian brains emerge when scaling-up modular, cortical structures. Firstly, the glia-to-neuron ratio is not constant across brains of different sizes: large mammalian brains have more glia per neuron than smaller brains. Our analyses suggest that if one assumes that glia number is proportional to wiring, a particular quantitative relationship emerges between brain size and glia-to-neuron ratio that fits the empirical data. Secondly, many authors have reported that the number of neurons underlying one mm2 of mammalian cortex is remarkably constant, across both areas and species. Here, we will show that such a constancy emerges when enlarging modular, cortical brain structures. Our analyses thus corroborate recent studies on the mammalian brain as a scalable architecture, providing a possible mechanism to explain some of the principles, constancies and rules that hold across brains of different size.
Comparative neuroanatomy; Glia-to-neuron index; Neuron number
A total of 1,496 rodents and insectivores were live-trapped at Yeoncheon-gun (n = 351), Paju-shi (804), and Pocheon-gun (343), Gyeonggi-do (Province), and examined for intestinal helminths, including Neodiplostomum seoulense, seasonally from December 2004 to September 2005. Six species of rodents, including Apodemus agrarius (1,366), Mus musculus (32), Micronytus fortis (28), Eothenomys regulus (9), Micronys minutus (6), and Cricetulus triton (3), and 1 species of insectivores Crocidura lasiura (54) were collected. A total of 321 adult N. seoulense were collected from 19 (1.4%) A. agrarius. The worm burden ranged from 1 to 101 per A. agrarius (mean; 16.9). No N. seoulense was observed in other rodent or insectivore species examined. The infection rate during autumn (4.5%) was higher than those during spring (0.8%), summer (0.8%), and winter (0.5%). The average number of N. seoulense in infected A. agrarius was the highest in spring (66.0 specimens), followed by autumn (15.2), winter (4.5), and summer (3.3). This study first confirms that A. agrarius is a natural definitive host for N. seoulense, and demonstrates that the infection rates and intensities vary seasonally and geographically.
Neodiplostomum seoulense; wild rodent; Apodemus agrarius; prevalence; worm burden; Gyeonggi-do
Despite great interest in the role of the amygdala in animal and human behaviour, its very existence as a structurally and functionally unified brain component has been questioned, on the grounds that cell groups within it display divergent pharmacological and connectional characteristics. We argue that the question of whether particular brain nuclei constitute a valid structural and functional unit is inherently an evolutionary question, and we present a method for answering it. The method involves phylogenetic analysis of comparative data to determine whether or not separate regions of the putative brain structure show statistically correlated evolution. We find that, in three separate groups of mammals (primates and two groups of insectivores), evolutionary changes in the volumes of amygdala components are strongly correlated, even after controlling for volumetric change in a wide range of limbic and other brain structures. This allows us to reject the strong claim that the amygdala is neither a structural nor a functional unit, and demonstrates the importance of evolutionary analysis in resolving such issues in systems neuroscience.
Mammalian sleep varies widely, ranging from frequent napping in rodents to consolidated blocks in primates and unihemispheric sleep in cetaceans. In humans, rats, mice and cats, sleep patterns are orchestrated by homeostatic and circadian drives to the sleep–wake switch, but it is not known whether this system is ubiquitous among mammals. Here, changes of just two parameters in a recent quantitative model of this switch are shown to reproduce typical sleep patterns for 17 species across 7 orders. Furthermore, the parameter variations are found to be consistent with the assumptions that homeostatic production and clearance scale as brain volume and surface area, respectively. Modeling an additional inhibitory connection between sleep-active neuronal populations on opposite sides of the brain generates unihemispheric sleep, providing a testable hypothetical mechanism for this poorly understood phenomenon. Neuromodulation of this connection alone is shown to account for the ability of fur seals to transition between bihemispheric sleep on land and unihemispheric sleep in water. Determining what aspects of mammalian sleep patterns can be explained within a single framework, and are thus universal, is essential to understanding the evolution and function of mammalian sleep. This is the first demonstration of a single model reproducing sleep patterns for multiple different species. These wide-ranging findings suggest that the core physiological mechanisms controlling sleep are common to many mammalian orders, with slight evolutionary modifications accounting for interspecies differences.
The field of sleep physiology has made huge strides in recent years, uncovering the neurological structures which are critical to sleep regulation. However, given the small number of species studied in such detail in the laboratory, it remains to be seen how universal these mechanisms are across the whole mammalian order. Mammalian sleep is extremely diverse, and the unihemispheric sleep of dolphins is nothing like the rapidly cycling sleep of rodents, or the single daily block of humans. Here, we use a mathematical model to demonstrate that the established sleep physiology can indeed account for the sleep of a wide range of mammals. Furthermore, the model gives insight into why the sleep patterns of different species are so distinct: smaller animals burn energy more rapidly, resulting in more rapid sleep–wake cycling. We also show that mammals that sleep unihemispherically may have a single additional neuronal pathway which prevents sleep-promoting neurons on opposite sides of the hypothalamus from activating simultaneously. These findings suggest that the basic physiology controlling sleep evolved before mammals, and illustrate the functional flexibility of this simple system.
The presence of Salmonella and Campylobacter spp. in rodents and insectivores (n = 282) was investigated on organic farms. Infections were encountered in house mice (8 of 83 Campylobacter positive and 1 of 83 Salmonella sp. strain Livingstone positive) and brown rats (1 of 8 Campylobacter positive) but not in other species. No shared Campylobacter genotypes were found between rodent and pig manure isolates. Effective on-farm rodent management is recommended.
Bats are unusual among mammals in showing great ecological diversity even among closely related species and are thus well suited for studies of adaptation to the ecological background. Here we investigate whether behavioral flexibility and simple- and complex-rule learning performance can be predicted by foraging ecology. We predict faster learning and higher flexibility in animals hunting in more complex, variable environments than in animals hunting in more simple, stable environments. To test this hypothesis, we studied three closely related insectivorous European bat species of the genus Myotis that belong to three different functional groups based on foraging habitats: M. capaccinii, an open water forager, M. myotis, a passive listening gleaner, and M. emarginatus, a clutter specialist. We predicted that M. capaccinii would show the least flexibility and slowest learning reflecting its relatively unstructured foraging habitat and the stereotypy of its natural foraging behavior, while the other two species would show greater flexibility and more rapid learning reflecting the complexity of their natural foraging tasks. We used a purposefully unnatural and thus species-fair crawling maze to test simple- and complex-rule learning, flexibility and re-learning performance. We found that M. capaccinii learned a simple rule as fast as the other species, but was slower in complex rule learning and was less flexible in response to changes in reward location. We found no differences in re-learning ability among species. Our results corroborate the hypothesis that animals’ cognitive skills reflect the demands of their ecological niche.
Life-history theory posits a fundamental trade-off between number and size of offspring that structures the variability in parental investment across and within species. We investigate this ‘quantity–quality’ trade-off across primates and present evidence that a similar trade-off is also found across natural-fertility human societies. Restating the classic Smith–Fretwell model in terms of allometric scaling of resource supply and offspring investment predicts an inverse scaling relation between birth rate and offspring size and a −¼ power scaling between birth rate and body size. We show that these theoretically predicted relationships, in particular the inverse scaling between number and size of offspring, tend to hold across increasingly finer scales of analyses (i.e. from mammals to primates to apes to humans). The advantage of this approach is that the quantity–quality trade-off in humans is placed into a general framework of parental investment that follows directly from first principles of energetic allocation.
quantity–quality trade-off; Smith–Fretwell model; number and size of offspring; natural-fertility human societies; primate life histories; quarter-power scaling