Fig 1 - uploaded by Roberto Toro
Content may be subject to copyright.
Diversity of the mammalian brain shape. Lateral aspect of various mammalian brains, drawn at the same scale. Based on images from http://brainmuseum.org
Source publication
The human brain is unique among primates in its complexity and variability. Here I argue that this variability is, however, strongly constrained by developmental processes common to all mammals. Comparative analyses of grey and white matter volume, cortical surface area and cortical folding show that the rostro–caudal axis of the central nervous sy...
Contexts in source publication
Context 1
... the most rostral part of the mammalian brain, the neocortex, is the one that displays the largest diversity. Figure 1 illustrates the shape of the brain (mostly neocortex) of several mammalian species. In general, the neocortex of small mammals, such as shrews, mice or squirrels, is smooth (lissencephalic), whereas that of large mammals, such as humans, dolphins or elephants, is pro- fusely folded (gyrencephalic). ...
Context 2
... where the perimeter of the cortical layer follows linearly the total area of the model (Fig. 4d), similar to the almost linear increase of cortical surface with brain volume across mammalian species (Fig. 2b). But large brains are not always gyrencephalic and small brains are not always lis- sencephalic. As we saw previously, the manatee brain (Fig. 1) is a well-known example of the former case. Interestingly, the manatee cortex is also particularly thick: 4 mm on average, whereas the human cortex is 2.5 mm thick on average. This should make the manatee brain especially difficult to bend. Our simulations showed indeed that the width of folds-their wavelength-depends directly on ...
Similar publications
The evolutionary expansion of the brain is among the most distinctive morphological features of mammals. During the past decades, considerable progress has been made in explaining brain evolution in terms of physical and adaptive principles. The objective of this chapter is to present current perspectives on primate brain evolution, especially in h...
Citations
... Brain folding may play an important role in facilitating and inducing a variety of anatomical and 35 functional organisation patterns (Welker 1990, Toro 2012). Among the many folded structures of the 36 mammalian brain, the cortices of the cerebrum and the cerebellum are the two largest ones. ...
The process of brain folding is thought to play an important role in the development and organisation of the cerebrum and the cerebellum. The study of cerebellar folding is challenging due to the small size and abundance of its folia. In consequence, little is known about its anatomical diversity and evolution. We constituted an open collection of histological data from 56 mammalian species and manually segmented the cerebrum and the cerebellum. We developed methods to measure the geometry of cerebellar folia and to estimate the thickness of the molecular layer. We used phylogenetic comparative methods to study the diversity and evolution of cerebellar folding and its relationship with the anatomy of the cerebrum. Our results show that the evolution of cerebellar and cerebral anatomy follows a stabilising selection process. We observed 2 groups of phenotypes changing concertedly through evolution: a group of 'diverse' phenotypes - varying over several orders of magnitude together with body size, and a group of 'stable' phenotypes varying over less than 1 order of magnitude across species. Our analyses confirmed the strong correlation between cerebral and cerebellar volumes across species, and showed in addition that large cerebella are disproportionately more folded than smaller ones. Compared with the extreme variations in cerebellar surface area, folial anatomy and molecular layer thickness varied only slightly, showing a much smaller increase in the larger cerebella. We discuss how these findings could provide new insights into the diversity and evolution of cerebellar folding, the mechanisms of cerebellar and cerebral folding, and their potential influence on the organisation of the brain across species.
... Understanding the functional relevance of cerebral sulci and gyri is thus crucial for deriving as much information as possible from endocasts. It has been shown that the number of cortical areas increases with brain size across mammals [72][73][74][75] as does the complexity of sulcal morphology across species 76,77 and among humans 78 . The number of distinct cortical areas, however, does not appear to vary substantially with brain size among anthropoid primates. ...
... In macaques, thalamic inputs to the primary visual cortex have been found to be involved in the development of primary visual cortex histology as well as the positioning of the lunate sulcus 82 . Computer simulations have found that convolutions may occur at cortical area borders as a mechanical consequence of cortical growth 77 . This notion of mechanical stress is congruent with research relating the development of gyri to growth factors that increase neurogenesis 83 as well as the finding that fold wavelengththe width of a foldis conserved among primates 26 given the relatively stable cortical thickness. ...
Fossil endocasts record features of brains from the past: size, shape, vasculature, and gyrification. These data, alongside experimental and comparative evidence, are needed to resolve questions about brain energetics, cognitive specializations, and developmental plasticity. Through the application of interdisciplinary techniques to the fossil record, paleoneurology has been leading major innovations. Neuroimaging is shedding light on fossil brain organization and behaviors. Inferences about the development and physiology of the brains of extinct species can be experimentally investigated through brain organoids and transgenic models based on ancient DNA. Phylogenetic comparative methods integrate data across species and associate genotypes to phenotypes, and brains to behaviors. Meanwhile, fossil and archeological discoveries continuously contribute new knowledge. Through cooperation, the scientific community can accelerate knowledge acquisition. Sharing digitized museum collections improves the availability of rare fossils and artifacts. Comparative neuroanatomical data are available through online databases, along with tools for their measurement and analysis. In the context of these advances, the paleoneurological record provides ample opportunity for future research. Biomedical and ecological sciences can benefit from paleoneurology’s approach to understanding the mind as well as its novel research pipelines that establish connections between neuroanatomy, genes and behavior.
... Brain folding may play an important role in facilitating and inducing a variety of anatomical and functional organisation patterns (Welker 1990, Toro 2012. Among the many folded structures of the mammalian brain, the cortices of the cerebrum and the cerebellum are the two largest ones. ...
The process of brain folding is thought to play an important role in the development and organisation of the cerebrum and the cerebellum. The study of cerebellar folding is challenging due to the small size and abundance of its folia. In consequence, little is known about its anatomical diversity and evolution. We constituted an open collection of histological data from 56 mammalian species and manually segmented the cerebrum and the cerebellum. We developed methods to measure the geometry of cerebellar folia and to estimate the thickness of the molecular layer. We used phylogenetic comparative methods to study the diversity and evolution of cerebellar folding and its relationship with the anatomy of the cerebrum. Our results show that the evolution of cerebellar and cerebral anatomy follows a stabilising selection process. Ancestral estimations indicate that size and folding of the cerebrum and cerebellum increase and decrease concertedly through evolution. Our analyses confirm the strong correlation between cerebral and cerebellar volumes across species, and show that large cerebella are disproportionately more folded than smaller ones. Compared with the extreme variations in cerebellar surface area, folial wavelength and molecular layer thickness varied only slightly, showing a much smaller increase in the larger cerebella. These findings provide new insight into the diversity and evolution of cerebellar folding and its potential influence on brain organisation across species.
... At the level of neuronal wiring, the mammalian brain is likely subject to internal tensions that give it a basic shape (Koser et al. 2016). However, brains are probably very flexible in their shape development: during the growth of an individual, the brain appears to mold itself to the endocranial space it "finds" (Toro 2012;Budday et al. 2015). Brain shape is also not always static during an individual's lifetime: different parts of the brain appear to grow and shrink seasonally in shrews and mustelids (Dechmann et al. 2017). ...
The metatherians (crown-clade marsupial mammals and their fossil relatives) originated in the Late Jurassic or Early Cretaceous of Laurasia, and have since spread worldwide with diversification in South America and Australasia during the Cenozoic. Despite this long evolutionary history, paleoneurology is known for a few taxa from the Americas and Australia, with most work being published in the last 40+ years. Here, we contextualise research on metatherian paleoneurology with traditional tenets that marsupials are developmentally constrained in their brain size and advanced cognitive and sensorimotor capabilities. We summarize recent research on marsupial neuromorphology with a perspective on how these insights apply to extinct species. We describe a digital cranial endocast of the didelphid Caluromys philander to compare with endocasts of crown and stem marsupials. Although endocasts of basal metatherians morphologically resemble those of didelphids, there is significant variation in brain shape and cerebrum gyrification among marsupials, possibly due to differences in how neural tissue is distributed within limited braincase space. Lastly, we examined existing endocranial volume and body mass estimates for crown and stem marsupials. The earliest metatherians have substantially smaller relative brain sizes than recent species, although this may relate to errors in estimating metatherian mass and endocast volumes.
... As the neural network grows in the number of units, the surface of the case size exhibits folding. During this process, the fold wavelength [47,48] decreases towards a small number, representing a highly convoluted surface. In a layered representational system, these folds introduce distortions that affect both the shortest distance between units and the alignment of processing columns. ...
What role does phenotypic complexity play in the systems-level function of an embodied agent? The organismal phenotype is a topologically complex structure that interacts with a genotype, developmental physics, and an informational environment. Using this observation as inspiration, we utilize a type of embodied agent that exhibits layered representational capacity: meta-brain models. Meta-brains are used to demonstrate how phenotypes process information
and exhibit self-regulation from development to maturity. We focus on two candidate structures that potentially explain this capacity: folding and layering. As layering and folding can be observed in a host of biological contexts, they form the basis for our representational
investigations. First, an innate starting point (genomic encoding) is described. The generative output of this encoding is a differentiation tree, which results in a layered phenotypic representation. Then we specify a formal meta-brain model of the gut, which exhibits folding and layering in development in addition to different degrees of representation of processed information. This organ topology is retained in maturity, with the potential for additional folding
and representational drift in response to inflammation. Next, we consider topological remapping using the developmental Braitenberg Vehicle (dBV) as a toy model. During topological remapping, it is shown that folding of a layered neural network can introduce a number of distortions to the original model, some with functional implications. The paper concludes with a discussion on how the meta-brains method can assist us in the investigation of enactivism,
holism, and cognitive processing in the context of biological simulation.
... As the neural network grows in the number of units, the surface of the case size exhibits folding. During this process, the fold wavelength [47,48] decreases towards a small number, representing a highly convoluted surface. In a layered representational system, these folds introduce distortions that affect both the shortest distance between units and the alignment of processing columns. ...
What role does phenotypic complexity play in the systems-level function of an embodied agent? The organismal phenotype is a topologically complex structure that interacts with a genotype, developmental physics, and an informational environment. Using this observation as inspiration, we utilize a type of embodied agent that exhibits layered representational capacity: meta-brain models. Meta-brains are used to demonstrate how phenotypes process information and exhibit self-regulation from development to maturity. We focus on two candidate structures that potentially explain this capacity: folding and layering. As layering and folding can be observed in a host of biological contexts, they form the basis for our representational investigations. First, an innate starting point (genomic encoding) is described. The generative output of this encoding is a differentiation tree, which results in a layered phenotypic representation. Then we specify a formal meta-brain model of the gut, which exhibits folding and layering in development in addition to different degrees of representation of processed information. This organ topology is retained in maturity, with the potential for additional folding and representational drift in response to inflammation. Next, we consider topological remapping using the developmental Braitenberg Vehicle (dBV) as a toy model. During topological remapping, it is shown that folding of a layered neural network can introduce a number of distortions to the original model, some with functional implications. The paper concludes with a discussion on how the meta-brains method can assist us in the investigation of enactivism, holism, and cognitive processing in the context of biological simulation.
... Although it has been suggested that confidence is linked to task-based networks fluctuations [22], to date this question has not been investigated experimentally using rs-networks. Importantly, even among non-clinical populations, large inter-individual variability has been observed in confidence ratings [23] and such heterogeneity has been hypothesized to originate from, or to be reflected in, Biology 2022, 11, 896 3 of 13 brain organization [24,25]. Moreover, psychological factors such as anxiety proneness are known to be linked not only to learning but also to inter-individual variability in confidence ratings [26] and may thereby influence confidence-related Rs brain networks [27,28]. ...
While resting-state networks are able to rapidly adapt to experiences and stimuli, it is currently unknown whether metacognitive processes such as confidence in learning and psychological temperament may influence this process. We explore the neural traces of confidence in learning and their variability by: (1) targeting rs-networks in which functional connectivity (FC) modifications induced by a learning task were associated either with the participant’s performance or confidence in learning; and (2) investigating the links between FC changes and psychological temperament. Thirty healthy individuals underwent neuropsychological and psychometric evaluations as well as rs-fMRI scans before and after a visuomotor associative learning task. Confidence in learning was positively associated with the degree of FC changes in 11 connections including the cerebellar, frontal, parietal, and subcortical areas. Variability in FC changes was linked to the individual’s level of anxiety sensitivity. The present findings indicate that reconfigurations of resting state networks linked to confidence in learning differ from those linked to learning accuracy. In addition, certain temperament characteristics appear to influence these reconfigurations.
... Larger brains therefore tend to have more convolutions and a greater volume of neocortical tissue relative to the total volume of the brain (e.g., Jerison, 1973;Finlay and Darlington, 1995). What determines the shape of the sulci is not fully understood, and there are several theories, including genetics (Bartley et al., 1997) and mechanical factors related to the shape and thickness of the cortex (Toro, 2012;Heuer and Toro, 2019). ...
We report on a nearly complete cranium of Ekweeconfractus amorui gen. et sp. nov. (Hyaenodonta, Teratodontinae), from the early Miocene of Moruorot, Kenya. The cranium is dorsoventrally compressed, but sufficiently intact to allow for digital reconstruction of the neurocranium, resulting in a digital endocast that gives us a first glimpse into teratodontine brain morphology. The virtual endocast is one of the most well preserved of any hyaenodont known to date, with many of the cranial nerves and blood vessels identifiable. Endocasts are known from only a handful of hyaenodont species and little work has been done on hyaenodont brains in recent decades. To better understand the evolution of the brain in these animals, we place the endocast of E. amorui gen. et sp. nov., as well as several other previously described endocasts, in the latest phylogenetic framework. This analysis suggests that the expansion of the neocortex occurred convergently in several clades of Hyaenodonta. Our study provides a basis for future research on brain evolution in Hyaenodonta.
... The cortical folding patterns are influenced by various physical parameters, e.g., the initial cortical thickness [22,149,171,172], the initial geometry [17,174,175], the initial curvature of the surface [105] and the relative growth [13,14,22,65,176,191]. In addition to these recent observations, many questions are still open regarding the morphogenesis of folding patterns, including links between the physical parameters of simulation models and the folding patterns observed in in vivo MRI data. ...
... The pattern and location of folds can be influenced by initial geometry [17,174,175]. For example, in ellipsoid models, most folds run either parallel or orthogonal to the ellipsoid's long axis [174,175]. ...
... The pattern and location of folds can be influenced by initial geometry [17,174,175]. For example, in ellipsoid models, most folds run either parallel or orthogonal to the ellipsoid's long axis [174,175]. In order to understand the impact of the initial geometry more clearly, an affine transformation (elongated transformation) is applied to the initial geometry to determine whether the complexity of folding patterns and how the direction of folds will change. ...
Perinatal ischemic stroke constitutes the leading cause of unilateral cerebral palsy or epilepsy in term-born children. However, the causes of these observed disabilities remain unclear. In this context, computational modeling is a powerful tool to provide a better understanding of the early brain folding process. Recent studies based on biomechanical modeling have shown that mechanical forces play a crucial role in the formation of cortical convolutions. However, the effect of physical parameters in these models, and the correlation between simulation results and biological facts remain unclear. In this thesis, using a biomechanical brain folding model, we investigate the effect of the cortical growth, the initial geometry and the initial cortical thickness on cortical folding patterns. In addition, we improve the biomechanical model by adding a new brain longitudinal length growth model and a spatio-temporal differential cortical expansion mechanism to the model. Furthermore, in order to quantify the surfacemorphology of simulations, several descriptors of the folds are used such as curvaturebased measures, gyrification index and sulcal depth. Besides, we introduce a novel approach to measure the folding orientation through geometric tools.
... It has been shown that the cortical folding patterns are influenced by various physical parameters, e.g., the initial cortical thickness [5][6][7][8][9] , the initial geometry [10][11][12] and the relative growth 2,5,[13][14][15][16] . In addition to these recent observations, many questions are still open regarding the morphogenesis of folding patterns, including links between the physical parameters of simulation models and the folding patterns observed in in vivo MRI data. ...
... The pattern and location of folds can be influenced by initial geometry [10][11][12] . For example, in ellipsoid models, most folds run either parallel or orthogonal to the ellipsoid's long axis 10,11 . ...
... The pattern and location of folds can be influenced by initial geometry [10][11][12] . For example, in ellipsoid models, most folds run either parallel or orthogonal to the ellipsoid's long axis 10,11 . In order to understand more clearly, an affine transformation (elongated transformation) is applied to the initial geometry to determine whether the complexity of folding patterns and how the direction of folds will change. ...
Abnormal cortical folding patterns, such as lissencephaly, pachygyria and polymicrogyria malformations, may be related to neurodevelopmental disorders. In this context, computational modeling is a powerful tool to provide a better understanding of the early brain folding process. Recent studies based on biomechanical modeling have shown that mechanical forces play a crucial role in the formation of cortical convolutions. However, the effect of biophysical parameters in these models remain unclear. In this paper, we investigate the effect of the cortical growth, the initial geometry and the initial cortical thickness on folding patterns. In addition, we not only use several descriptors of the folds such as the dimensionless mean curvature, the surface-based three-dimensional gyrification index and the sulcal depth, but also propose a new metric to quantify the folds orientation. The results demonstrate that the cortical growth mode does almost not affect the complexity degree of surface morphology; the variation in the initial geometry changes the folds orientation and depth, and in particular, the slenderer the shape is, the more folds along its longest axis could be seen and the deeper the sulci become. Moreover, the thinner the initial cortical thickness is, the higher the spatial frequency of the folds is, but the shallower the sulci become, which is in agreement with the previously reported effects of cortical thickness.
