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ABSTRACT Muscle loading is known to influence skeletal morphology. Therefore, modification of the biomechanical environment is expected to cause coordinated morphological changes to the bony and cartilaginous tissues. Understanding how this musculoskeletal coordination contributes to morphological variation has relevance to health sciences, developmental biology, and evolutionary biology. To investigate how muscle loading influences skeletal morphology, we replicate a classic in ovo embryology experiment in the domestic chick (Gallus gallus domesticus) while harnessing modern methodologies that allow us to quantify skeletal anatomy more precisely and in situ. We induced rigid muscle paralysis in developing chicks mid‐incubation, then compared the morphology of the cranium and mandible between immobilized and untreated embryos using microcomputed tomography and landmark‐based geometric morphometric methods. Like earlier studies, we found predictable differences in the size and shape of the cranium and mandible in paralyzed chicks. These differences were concentrated in areas known to experience high strains during feeding, including the jaw joint and jaw muscle attachment sites. These results highlight specific areas of the skull that appear to be mechanosensitive and suggest muscles that could produce the biomechanical stimuli necessary for normal hatchling morphology. Interestingly, these same areas correspond to areas that show the greatest disparity and fastest evolutionary rates across the avian diversity, which suggests that the musculoskeletal integration observed during development extends to macroevolutionary scales. Thus, selection and evolutionary changes to muscle physiology and architecture could generate large and predictable changes to skull morphology. Building upon previous work, the adoption of modern imaging and morphometric techniques allows richer characterization of musculoskeletal integration that empowers researchers to understand how tissue‐to‐tissue interactions contribute to overall phenotypic variation. 

Our ability to visualize and quantify the internal structures of objects via computed tomography (CT) has fundamentally transformed science. As tomographic tools have become more broadly accessible, researchers across diverse disciplines have embraced the ability to investigate the 3D structure-function relationships of an enormous array of items. Whether studying organismal biology, animal models for human health, iterative manufacturing techniques, experimental medical devices, engineering structures, geological and planetary samples, prehistoric artifacts, or fossilized organisms, computed tomography has led to extensive methodological and basic sciences advances and is now a core element in science, technology, engineering, and mathematics (STEM) research and outreach toolkits. Tomorrow's scientific progress is built upon today's innovations. In our data-rich world, this requires access not only to publications but also to supporting data. Reliance on proprietary technologies, combined with the varied objectives of diverse research groups, has resulted in a fragmented tomography-imaging landscape, one that is functional at the individual lab level yet lacks the standardization needed to support efficient and equitable exchange and reuse of data. Developing standards and pipelines for the creation of new and future data, which can also be applied to existing datasets is a challenge that becomes increasingly difficult as the amount and diversity of legacy data grows. Global networks of CT users have proved an effective approach to addressing this kind of multifaceted challenge across a range of fields. Here we describe ongoing efforts to address barriers to recently proposed FAIR (Findability, Accessibility, Interoperability, Reuse) and open science principles by assembling interested parties from research and education communities, industry, publishers, and data repositories to approach these issues jointly in a focused, efficient, and practical way. By outlining the benefits of networks, generally, and drawing on examples from efforts by the Non-Clinical Tomography Users Research Network (NoCTURN), specifically, we illustrate how standardization of data and metadata for reuse can foster interdisciplinary collaborations and create new opportunities for future-looking, large-scale data initiatives. 

Abstract The evolutionary history of vertebrates is replete with emergence of novel brain morphologies, including the origin of the human brain. Existing model organisms and toolkits for investigating drivers of neuroanatomical innovations have largely proceeded on mammals. As such, a compelling non‐mammalian model system would facilitate our understanding of how unique brain morphologies evolve across vertebrates. Here, we present the domestic chicken breed, white crested Polish chickens, as an avian model for investigating how novel brain morphologies originate. Most notably, these crested chickens exhibit cerebral herniation from anterodorsal displacement of the telencephalon, which results in a prominent protuberance on the dorsal aspect of the skull. We use a high‐density geometric morphometric approach on cephalic endocasts to characterize their brain morphology. Compared with standard white Leghorn chickens (WLCs) and modern avian diversity, the results demonstrate that crested chickens possess a highly variable and unique overall brain configuration. Proportional sizes of neuroanatomical regions are within the observed range of extant birds sampled in this study, but Polish chickens differ from WLCs in possessing a relatively larger cerebrum and smaller cerebellum and medulla. Given their accessibility, phylogenetic proximity, and unique neuroanatomy, we propose that crested breeds, combined with standard chickens, form a promising comparative system for investigating the emergence of novel brain morphologies. 

Abstract The field of comparative morphology has entered a new phase with the rapid generation of high-resolution three-dimensional (3D) data. With freely available 3D data of thousands of species, methods for quantifying morphology that harness this rich phenotypic information are quickly emerging. Among these techniques, high-density geometric morphometric approaches provide a powerful and versatile framework to robustly characterize shape and phenotypic integration, the covariances among morphological traits. These methods are particularly useful for analyses of complex structures and across disparate taxa, which may share few landmarks of unambiguous homology. However, high-density geometric morphometrics also brings challenges, for example, with statistical, but not biological, covariances imposed by placement and sliding of semilandmarks and registration methods such as Procrustes superimposition. Here, we present simulations and case studies of high-density datasets for squamates, birds, and caecilians that exemplify the promise and challenges of high-dimensional analyses of phenotypic integration and modularity. We assess: (1) the relative merits of “big” high-density geometric morphometrics data over traditional shape data; (2) the impact of Procrustes superimposition on analyses of integration and modularity; and (3) differences in patterns of integration between analyses using high-density geometric morphometrics and those using discrete landmarks. We demonstrate that for many skull regions, 20–30 landmarks and/or semilandmarks are needed to accurately characterize their shape variation, and landmark-only analyses do a particularly poor job of capturing shape variation in vault and rostrum bones. Procrustes superimposition can mask modularity, especially when landmarks covary in parallel directions, but this effect decreases with more biologically complex covariance patterns. The directional effect of landmark variation on the position of the centroid affects recovery of covariance patterns more than landmark number does. Landmark-only and landmark-plus-sliding-semilandmark analyses of integration are generally congruent in overall pattern of integration, but landmark-only analyses tend to show higher integration between adjacent bones, especially when landmarks placed on the sutures between bones introduces a boundary bias. Allometry may be a stronger influence on patterns of integration in landmark-only analyses, which show stronger integration prior to removal of allometric effects compared to analyses including semilandmarks. High-density geometric morphometrics has its challenges and drawbacks, but our analyses of simulated and empirical datasets demonstrate that these potential issues are unlikely to obscure genuine biological signal. Rather, high-density geometric morphometric data exceed traditional landmark-based methods in characterization of morphology and allow more nuanced comparisons across disparate taxa. Combined with the rapid increases in 3D data availability, high-density morphometric approaches have immense potential to propel a new class of studies of comparative morphology and phenotypic integration. 

Abstract The avian head is unique among living reptiles in its combination of relatively large brain and eyes, coupled with relatively small adductor jaw muscles. These derived proportions lend themselves to a trade‐off hypothesis, wherein adductor size was reduced over evolutionary time as a means (or as a consequence) of neurosensory expansion. In this study, we examine this evolutionary hypothesis through the lens of development by describing the jaw‐adductor anatomy of developing chickens,Gallus gallus, and comparing the volumetric expansion of these developing muscles with growth trajectories of the brain and eye. Under the trade‐off hypothesis, we predicted that the jaw muscles would grow with negative allometry relative to brain and eyes, and that osteological signatures of a relatively large adductor system, as found in most nonavian dinosaurs, would be differentially expressed in younger chicks. Results did not meet these expectations, at least not generally, with muscle growth exhibiting positive allometry relative to that of brain and eye. We propose three, nonmutually exclusive explanations: (1) these systems do not compete for space, (2) these systems competed for space in the evolutionary past, and growth of the jaw muscles was truncated early in development (paedomorphosis), and (3) trade‐offs in developmental investment in these systems are limited temporally to the perinatal period. These explanations are considered in light of the fossil record, and most notably the skull of the stem birdIchthyornis, which exhibits an interesting combination of plesiomorphically large adductor chamber and apomorphically large brain. 

Abstract Cranial endocasts, or the internal molds of the braincase, are a crucial correlate for investigating the neuroanatomy of extinct vertebrates and tracking brain evolution through deep time. Nevertheless, the validity of such studies pivots on the reliability of endocasts as a proxy for brain morphology. Here, we employ micro‐computed tomography imaging, including diffusible iodine‐based contrast‐enhancedCT, and a three‐dimensional geometric morphometric framework to examine both size and shape differences between brains and endocasts of two exemplar archosaur taxa – the American alligator (Alligator mississippiensis) and the domestic chicken (Gallus gallus). With ontogenetic sampling, we quantitatively evaluate how endocasts differ from brains and whether this deviation changes during development. We find strong size and shape correlations between brains and endocasts, divergent ontogenetic trends in the brain‐to‐endocast correspondence between alligators and chickens, and a comparable magnitude between brain–endocast shape differences and intraspecific neuroanatomical variation. The results have important implications for paleoneurological studies in archosaurs. Notably, we demonstrate that the pattern of endocranial shape variation closely reflects brain shape variation. Therefore, analyses of endocranial morphology are unlikely to generate spurious conclusions about large‐scale trends in brain size and shape. To mitigate any artifacts, however, paleoneurological studies should consider the lower brain–endocast correspondence in the hindbrain relative to the forebrain; higher size and shape correspondences in chickens than alligators throughout postnatal ontogeny; artificially ‘pedomorphic’ shape of endocasts relative to their corresponding brains; and potential biases in both size and shape data due to the lack of control for ontogenetic stages in endocranial sampling. 

Abstract Complex structures, like the vertebrate skull, are composed of numerous elements or traits that must develop and evolve in a coordinated manner to achieve multiple functions. The strength of association among phenotypic traits (i.e., integration), and their organization into highly-correlated, semi-independent subunits termed modules, is a result of the pleiotropic and genetic correlations that generate traits. As such, patterns of integration and modularity are thought to be key factors constraining or facilitating the evolution of phenotypic disparity by influencing the patterns of variation upon which selection can act. It is often hypothesized that selection can reshape patterns of integration, parceling single structures into multiple modules or merging ancestrally semi-independent traits into a strongly correlated unit. However, evolutionary shifts in patterns of trait integration are seldom assessed in a unified quantitative framework. Here, we quantify patterns of evolutionary integration among regions of the archosaur skull to investigate whether patterns of cranial integration are conserved or variable across this diverse group. Using high-dimensional geometric morphometric data from 3D surface scans and computed tomography scans of modern birds (n = 352), fossil non-avian dinosaurs (n = 27), and modern and fossil mesoeucrocodylians (n = 38), we demonstrate that some aspects of cranial integration are conserved across these taxonomic groups, despite their major differences in cranial form, function, and development. All three groups are highly modular and consistently exhibit high integration within the occipital region. However, there are also substantial divergences in correlation patterns. Birds uniquely exhibit high correlation between the pterygoid and quadrate, components of the cranial kinesis apparatus, whereas the non-avian dinosaur quadrate is more closely associated with the jugal and quadratojugal. Mesoeucrocodylians exhibit a slightly more integrated facial skeleton overall than the other grades. Overall, patterns of trait integration are shown to be stable among archosaurs, which is surprising given the cranial diversity exhibited by the clade. At the same time, evolutionary innovations such as cranial kinesis that reorganize the structure and function of complex traits can result in modifications of trait correlations and modularity.