Phylogenetic comparison of neuron and glia densities in the primary visual cortex and hippocampus of carnivores and primates

Orientation Preference Maps in Microcebus murinus Reveal Size-Invariant Design Principles in Primate Visual Cortex

Orientation preference maps (OPMs) are a prominent feature of primary visual cortex (V1) organization in many primates and carnivores. In rodents, neurons are not organized in OPMs but are instead interspersed in a “salt and pepper” fashion, although clusters of orientation-selective neurons have been reported. Does this fundamental difference reflect the existence of a lower size limit for orientation columns (OCs) below which they cannot be scaled down with decreasing V1 size? To address this question, we examined V1 of one of the smallest living primates, the 60-g prosimian mouse lemur (Microcebus murinus). Using chronic intrinsic signal imaging, we found that mouse lemur V1 contains robust OCs, which are arranged in a pinwheel-like fashion. OC size in mouse lemurs was found to be only marginally smaller compared to the macaque, suggesting that these circuit elements are nearly incompressible. The spatial arrangement of pinwheels is well described by a common mathematical design of primate V1 circuit organization. In order to accommodate OPMs, we found that the mouse lemur V1 covers one-fifth of the cortical surface, which is one of the largest V1-to-cortex ratios found in primates. These results indicate that the primate-type visual cortical circuit organization is constrained by a size limitation and raises the possibility that its emergence might have evolved by disruptive innovation rather than gradual change.

Orientation preference maps are a hallmark of V1 organization in all primates studied thus far, yet they are absent in rodents. It is uncertain whether these structures scale with body or brain size. Using intrinsic signal imaging, Ho et al. reveal the presence of such maps in the V1 of the world’s smallest primate, the mouse lemur (Microcebus murinus).

Human-specific ARHGAP11B induces hallmarks of neocortical expansion in developing ferret neocortex

The evolutionary increase in size and complexity of the primate neocortex is thought to underlie the higher cognitive abilities of humans. ARHGAP11B is a human-specific gene that, based on its expression pattern in fetal human neocortex and progenitor effects in embryonic mouse neocortex, has been proposed to have a key function in the evolutionary expansion of the neocortex. Here, we study the effects of ARHGAP11B expression in the developing neocortex of the gyrencephalic ferret. In contrast to its effects in mouse, ARHGAP11B markedly increases proliferative basal radial glia, a progenitor cell type thought to be instrumental for neocortical expansion, and results in extension of the neurogenic period and an increase in upper-layer neurons. Consequently, the postnatal ferret neocortex exhibits increased neuron density in the upper cortical layers and expands in both the radial and tangential dimensions. Thus, human-specific ARHGAP11B can elicit hallmarks of neocortical expansion in the developing ferret neocortex.

Inferring Evolutionary Process From Neuroanatomical Data

Brain evolution has interested neuroanatomists for over a century. These interests often fall on how free the brain is to evolve independently of the body, how free brain regions are to evolve independently of each other, and how different environmental and ecological factors affect the brain over evolutionary time. But despite major advances in phylogenetic methods, comparative neuroanatomists have tended to limit their macroevolutionary toolbox to regression-based analyses and ignored the scope of evolutionary process-based models at their disposal. This Review summarizes the history of comparative neuroanatomy and highlights the pitfalls of the methodologies traditionally used. It provides an overview of evolutionary process-based modeling approaches for investigating univariate and multivariate data, as well as more sophisticated methods that incorporate hypotheses about biotic and abiotic pressures that may drive brain evolution. The benefits of evolutionary process-based models, and shortcomings of regression-based ones, are illustrated with widely used neuroanatomical data. Ultimately, the intent of this Review is to be a guide for subsuming macroevolutionary methods not typically used in comparative neuroanatomy, in order to improve our understanding of how the brain evolves.

Predicting future learning from baseline network architecture

Human behavior and cognition result from a complex pattern of interactions between brain regions. The flexible reconfiguration of these patterns enables behavioral adaptation, such as the acquisition of a new motor skill. Yet, the degree to which these reconfigurations depend on the brain's baseline sensorimotor integration is far from understood. Here, we asked whether spontaneous fluctuations in sensorimotor networks at baseline were predictive of individual differences in future learning. We analyzed functional MRI data from 19 participants prior to six weeks of training on a new motor skill. We found that visual-motor connectivity was inversely related to learning rate: sensorimotor autonomy at baseline corresponded to faster learning in the future. Using three additional scans, we found that visual-motor connectivity at baseline is a relatively stable individual trait. These results suggest that individual differences in motor skill learning can be predicted from sensorimotor autonomy at baseline prior to task execution.

Brain evolution and development: adaptation, allometry and constraint

Phenotypic traits are products of two processes: evolution and development. But how do these processes combine to produce integrated phenotypes? Comparative studies identify consistent patterns of covariation, or allometries, between brain and body size, and between brain components, indicating the presence of significant constraints limiting independent evolution of separate parts. These constraints are poorly understood, but in principle could be either developmental or functional. The developmental constraints hypothesis suggests that individual components (brain and body size, or individual brain components) tend to evolve together because natural selection operates on relatively simple developmental mechanisms that affect the growth of all parts in a concerted manner. The functional constraints hypothesis suggests that correlated change reflects the action of selection on distributed functional systems connecting the different sub-components, predicting more complex patterns of mosaic change at the level of the functional systems and more complex genetic and developmental mechanisms. These hypotheses are not mutually exclusive but make different predictions. We review recent genetic and neurodevelopmental evidence, concluding that functional rather than developmental constraints are the main cause of the observed patterns.

Quantification of neuronal density across cortical depth using automated 3D analysis of confocal image stacks

A new framework for measuring densities of immunolabeled neurons across cortical layers was implemented that combines a confocal microscopy sampling strategy with automated analysis of 3D image stacks. Its utility was demonstrated by quantifying neuronal density in macaque cortical areas V1 and V2. A series of overlapping confocal image stacks were acquired, each spanning from the pial surface to the white matter. DAPI channel images were automatically thresholded, and contiguous regions that included multiple clumped nuclear profiles were split using k-means clustering of image pixels for a set of candidate k values determined based on the clump's area; the most likely candidate segmentation was selected based on criteria that capture expected nuclear profile shape and size. The centroids of putative nuclear profiles estimated from 2D images were then grouped across z planes in an image stack to identify the positions of nuclei in x-y-z. 3D centroids falling outside user-specified exclusion boundaries were deleted, nuclei were classified by the presence or absence of signal in a channel corresponding to an immunolabeled antigen (e.g., the pan-neuronal marker NeuN) at the nuclear centroid location, and the set of classified cells was combined across image stacks to estimate density across cortical depth. The method was validated by comparison with conventional stereological methods. The average neuronal density across cortical layers was 230 × 10³ neurons per mm³ in V1 and 130 × 10³ neurons per mm³ in V2. The method is accurate, flexible, and general enough to measure densities of neurons of various molecularly identified types.

Neocortex expansion is linked to size variations in gene families with chemotaxis, cell-cell signalling and immune response functions in mammals

Increased brain size is thought to have played an important role in the evolution of mammals and is a highly variable trait across lineages. Variations in brain size are closely linked to corresponding variations in the size of the neocortex, a distinct mammalian evolutionary innovation. The genomic features that explain and/or accompany variations in the relative size of the neocortex remain unknown. By comparing the genomes of 28 mammalian species, we show that neocortical expansion relative to the rest of the brain is associated with variations in gene family size (GFS) of gene families that are significantly enriched in biological functions associated with chemotaxis, cell-cell signalling and immune response. Importantly, we find that previously reported GFS variations associated with increased brain size are largely accounted for by the stronger link between neocortex expansion and variations in the size of gene families. Moreover, genes within these families are more prominently expressed in the human neocortex during early compared with adult development. These results suggest that changes in GFS underlie morphological adaptations during brain evolution in mammalian lineages.

NSF workshop report: discovering general principles of nervous system organization by comparing brain maps across species

Efforts to understand nervous system structure and function have received new impetus from the federal Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative. Comparative analyses can contribute to this effort by leading to the discovery of general principles of neural circuit design, information processing, and gene-structure-function relationships that are not apparent from studies on single species. We here propose to extend the comparative approach to nervous system 'maps' comprising molecular, anatomical, and physiological data. This research will identify which neural features are likely to generalize across species, and which are unlikely to be broadly conserved. It will also suggest causal relationships between genes, development, adult anatomy, physiology, and, ultimately, behavior. These causal hypotheses can then be tested experimentally. Finally, insights from comparative research can inspire and guide technological development. To promote this research agenda, we recommend that teams of investigators coalesce around specific research questions and select a set of 'reference species' to anchor their comparative analyses. These reference species should be chosen not just for practical advantages, but also with regard for their phylogenetic position, behavioral repertoire, well-annotated genome, or other strategic reasons. We envision that the nervous systems of these reference species will be mapped in more detail than those of other species. The collected data may range from the molecular to the behavioral, depending on the research question. To integrate across levels of analysis and across species, standards for data collection, annotation, archiving, and distribution must be developed and respected. To that end, it will help to form networks or consortia of researchers and centers for science, technology, and education that focus on organized data collection, distribution, and training. These activities could be supported, at least in part, through existing mechanisms at NSF, NIH, and other agencies. It will also be important to develop new integrated software and database systems for cross-species data analyses. Multidisciplinary efforts to develop such analytical tools should be supported financially. Finally, training opportunities should be created to stimulate multidisciplinary, integrative research into brain structure, function, and evolution.

What can volumes reveal about human brain evolution? A framework for bridging behavioral, histometric, and volumetric perspectives

An overall relationship between brain size and cognitive ability exists across primates. Can more specific information about neural function be gleaned from cortical area volumes? Numerous studies have found significant relationships between brain structures and behaviors. However, few studies have speculated about brain structure-function relationships from the microanatomical to the macroanatomical level. Here we address this problem in comparative neuroanatomy, where the functional relevance of overall brain size and the sizes of cortical regions have been poorly understood, by considering comparative psychology, with measures of visual acuity and the perception of visual illusions. We outline a model where the macroscopic size (volume or surface area) of a cortical region (such as the primary visual cortex, V1) is related to the microstructure of discrete brain regions. The hypothesis developed here is that an absolutely larger V1 can process more information with greater fidelity due to having more neurons to represent a field of space. This is the first time that the necessary comparative neuroanatomical research at the microstructural level has been brought to bear on the issue. The evidence suggests that as the size of V1 increases: the number of neurons increases, the neuron density decreases, and the density of neuronal connections increases. Thus, we describe how information about gross neuromorphology, using V1 as a model for the study of other cortical areas, may permit interpretations of cortical function.

The Cajal school and the physiological role of astrocytes: a way of thinking

Cajal is widely recognized by the scientific community for his important contributions to our knowledge of the neuronal organization of the nervous system. His studies on neuroglial cells are less recognized, yet they are no less relevant to our current understanding of the cellular bases of brain structure. Two pioneering studies published a century ago –“Something about the physiological significance of neuroglia” (Ramón y Cajal, 1897) and “A contribution to the understanding of neuroglia in the human brain” (Ramón y Cajal, 1913)—focused on glial cells and their role in brain physiology. Novel findings obtained using state-of-the-art and sophisticated technologies largely confirm many of the groundbreaking hypotheses proposed by Cajal related to the structural-functional properties of neuroglia. Here we propose to the reader a journey guided by the ideas of Cajal through the recent findings on the functional significance of astrocytes, the most abundant neuroglial cell type in the nervous system. Astrocyte–neuron interaction, which represents an emerging field in current neuroscience with important implications for our understanding of the cellular processes underlying brain function, has its roots in many of the original concepts proposed by Cajal.

Three counting methods agree on cell and neuron number in chimpanzee primary visual cortex

Determining the cellular composition of specific brain regions is crucial to our understanding of the function of neurobiological systems. It is therefore useful to identify the extent to which different methods agree when estimating the same properties of brain circuitry. In this study, we estimated the number of neuronal and non-neuronal cells in the primary visual cortex (area 17 or V1) of both hemispheres from a single chimpanzee. Specifically, we processed samples distributed across V1 of the right hemisphere after cortex was flattened into a sheet using two variations of the isotropic fractionator cell and neuron counting method. We processed the left hemisphere as serial brain slices for stereological investigation. The goal of this study was to evaluate the agreement between these methods in the most direct manner possible by comparing estimates of cell density across one brain region of interest in a single individual. In our hands, these methods produced similar estimates of the total cellular population (approximately 1 billion) as well as the number of neurons (approximately 675 million) in chimpanzee V1, providing evidence that both techniques estimate the same parameters of interest. In addition, our results indicate the strengths of each distinct tissue preparation procedure, highlighting the importance of attention to anatomical detail. In summary, we found that the isotropic fractionator and the stereological optical fractionator produced concordant estimates of the cellular composition of V1, and that this result supports the conclusion that chimpanzees conform to the primate pattern of exceptionally high packing density in V1. Ultimately, our data suggest that investigators can optimize their experimental approach by using any of these counting methods to obtain reliable cell and neuron counts.

NSF workshop report: discovering general principles of nervous system organization by comparing brain maps across species

Efforts to understand nervous system structure and function have received new impetus from the federal Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative. Comparative analyses can contribute to this effort by leading to the discovery of general principles of neural circuit design, information processing, and gene-structure-function relationships that are not apparent from studies on single species. We here propose to extend the comparative approach to nervous system 'maps' comprising molecular, anatomical, and physiological data. This research will identify which neural features are likely to generalize across species, and which are unlikely to be broadly conserved. It will also suggest causal relationships between genes, development, adult anatomy, physiology, and, ultimately, behavior. These causal hypotheses can then be tested experimentally. Finally, insights from comparative research can inspire and guide technological development. To promote this research agenda, we recommend that teams of investigators coalesce around specific research questions and select a set of 'reference species' to anchor their comparative analyses. These reference species should be chosen not just for practical advantages, but also with regard for their phylogenetic position, behavioral repertoire, well-annotated genome, or other strategic reasons. We envision that the nervous systems of these reference species will be mapped in more detail than those of other species. The collected data may range from the molecular to the behavioral, depending on the research question. To integrate across levels of analysis and across species, standards for data collection, annotation, archiving, and distribution must be developed and respected. To that end, it will help to form networks or consortia of researchers and centers for science, technology, and education that focus on organized data collection, distribution, and training. These activities could be supported, at least in part, through existing mechanisms at NSF, NIH, and other agencies. It will also be important to develop new integrated software and database systems for cross-species data analyses. Multidisciplinary efforts to develop such analytical tools should be supported financially. Finally, training opportunities should be created to stimulate multidisciplinary, integrative research into brain structure, function, and evolution.

Systematic, cross-cortex variation in neuron numbers in rodents and primates

Uniformity, local variability, and systematic variation in neuron numbers per unit of cortical surface area across species and cortical areas have been claimed to characterize the isocortex. Resolving these claims has been difficult, because species, techniques, and cortical areas vary across studies. We present a stereological assessment of neuron numbers in layers II-IV and V-VI per unit of cortical surface area across the isocortex in rodents (hamster, Mesocricetus auratus; agouti, Dasyprocta azarae; paca, Cuniculus paca) and primates (owl monkey, Aotus trivigratus; tamarin, Saguinus midas; capuchin, Cebus apella); these chosen to vary systematically in cortical size. The contributions of species, cortical areas, and techniques (stereology, "isotropic fractionator") to neuron estimates were assessed. Neurons per unit of cortical surface area increase across the rostro-caudal (RC) axis in primates (varying by a factor of 1.64-2.13 across the rostral and caudal poles) but less in rodents (varying by a factor of 1.15-1.54). Layer II-IV neurons account for most of this variation. When integrated into the context of species variation, and this RC gradient in neuron numbers, conflicts between studies can be accounted for. The RC variation in isocortical neurons in adulthood mirrors the gradients in neurogenesis duration in development.

Conical expansion of the outer subventricular zone and the role of neocortical folding in evolution and development

THERE IS A BASIC RULE TO MAMMALIAN NEOCORTICAL EXPANSION

as it expands, so does it fold. The degree to which it folds, however, cannot strictly be attributed to its expansion. Across species, cortical volume does not keep pace with cortical surface area, but rather folds appear more rapidly than expected. As a result, larger brains quickly become disproportionately more convoluted than smaller brains. Both the absence (lissencephaly) and presence (gyrencephaly) of cortical folds is observed in all mammalian orders and, while there is likely some phylogenetic signature to the evolutionary appearance of gyri and sulci, there are undoubtedly universal trends to the acquisition of folds in an expanding neocortex. Whether these trends are governed by conical expansion of neocortical germinal zones, the distribution of cortical connectivity, or a combination of growth- and connectivity-driven forces remains an open question. But the importance of cortical folding for evolution of the uniquely mammalian neocortex, as well as for the incidence of neuropathologies in humans, is undisputed. In this hypothesis and theory article, we will summarize the development of cortical folds in the neocortex, consider the relative influence of growth- vs. connectivity-driven forces for the acquisition of cortical folds between and within species, assess the genetic, cell-biological, and mechanistic implications for neocortical expansion, and discuss the significance of these implications for human evolution, development, and disease. We will argue that evolutionary increases in the density of neuron production, achieved via maintenance of a basal proliferative niche in the neocortical germinal zones, drive the conical migration of neurons toward the cortical surface and ultimately lead to the establishment of cortical folds in large-brained mammal species.

Neocortical development as an evolutionary platform for intragenomic conflict

Embryonic development in mammals has evolved a platform for genomic conflict between mothers and embryos and, by extension, between maternal and paternal genomes. The evolutionary interests of the mother and embryo may be maximized through the promotion of sex-chromosome genes and imprinted alleles, resulting in the rapid evolution of postzygotic phenotypes preferential to either the maternal or paternal genome. In eutherian mammals, extraordinary in utero maternal investment in the brain, and neocortex especially, suggests that convergent evolution of an expanded mammalian neocortex along divergent lineages may be explained, in part, by parent-of-origin-linked gene expression arising from parent-offspring conflict. The influence of this conflict on neocortical development and evolution, however, has not been investigated at the genomic level. In this hypothesis and theory article, we provide preliminary evidence for positive selection in humans in the regions of two platforms of intragenomic conflict—chromosomes 15q11-q13 and X—and explore the potential relevance of cis-regulated imprinted domains to neocortical expansion in mammalian evolution. We present the hypothesis that maternal- and paternal-specific pressures on the developing neocortex compete intragenomically to influence neocortical expansion in mammalian evolution.

Understanding the evolution of Mammalian brain structures; the need for a (new) cerebrotype approach

The mammalian brain varies in size by a factor of 100,000 and is composed of anatomically and functionally distinct structures. Theoretically, the manner in which brain composition can evolve is limited, ranging from highly modular ("mosaic evolution") to coordinated changes in brain structure size ("concerted evolution") or anything between these two extremes. There is a debate about the relative importance of these distinct evolutionary trends. It is shown here that the presence of taxa-specific allometric relationships between brain structures makes a taxa-specific approach obligatory. In some taxa, the evolution of the size of brain structures follows a unique, coordinated pattern, which, in addition to other characteristics at different anatomical levels, defines what has been called here a "taxon cerebrotype". In other taxa, no clear pattern is found, reflecting heterogeneity of the species' lifestyles. These results suggest that the evolution of brain size and composition depends on the complex interplay between selection pressures and constraints that have changed constantly during mammalian evolution. Therefore the variability in brain composition between species should not be considered as deviations from the normal, concerted mammalian trend, but in taxa and species-specific versions of the mammalian brain. Because it forms homogenous groups of species within this complex "space" of constraints and selection pressures, the cerebrotype approach developed here could constitute an adequate level of analysis for evo-devo studies, and by extension, for a wide range of disciplines related to brain evolution.