Structural analysis of network models in tetrapod skulls : evolutionary trends and structural constraints in morphological complexity, integration and modularity

Background Ever since classic anatomists like George Cuvier, Geoffroy St. Hilaire, or Richard Owen laid down the fundamental principles of comparative anatomy in the 19th century, connections among anatomical parts have been essential for the recognition of biological homologies. However, few studies have addressed the possibility of implementing an adequate methodological tool to use connections among parts to unveil problems in morphology; although Woodger, Rashevsky, Riedl, and, more recently, Rasskin-Gutman pointed in this direction. In the last decades Network Theory has been developed as a novel conceptual and methodological framework to deal with the relational properties that emerge due to connections between parts in any organized system (e.g., robustness, self-organization, and modularity). Network analysis was readily applied to a wide range of complex biological systems, such as gene regulatory pathways, brain neuronal systems, or ecological communities. However, a seemingly natural arena to use this mathematical tool such as comparative anatomy has never been systematically studied using current network analysis tools. Aims The aim of my thesis is to carry out a comparative analysis of connectivity patterns in tetrapod skulls to assess problems on the evolution and ontogeny of morphological complexity, integration, and modularity. This kind of analysis can reveal key morphological properties of the skull that most common studies, based solely on shape and size, would keep unravel. Empirical and theoretical outcomes of this comparative analysis of skull networks have been used to assess how connectivity patterns affect the formation and evolution of the skull morphology in tetrapods. Methods I formalize the structure of connections in the skull (i.e., connectivity pattern) using network models, in which nodes and links represent bones and suture contacts, respectively. Thereby, skull networks were built for extant and extinct species, including some human newborn skulls with different craniosynostosis conditions. These skull networks were analyzed using current network analysis methods and null models to reveal the properties of their morphological organization related to complexity, integration, and modularity. To this end, I also developed a complete framework of anatomical interpretations for the most common parameters used in networks analysis (e.g., density, clustering coefficient, and path length), which, in general, have been never applied in a morphological context. Finally, the results of skull networks analysis have been discussed in an evolutionary and developmental context. Conclusions 1. Morphological complexity increases during evolution in tetrapod skulls, due to the random loss of poorly connected bones and the selective fusion of highly connected ones. 2. The organization of connectivity modules decreases in disparity during skull evolution, due to an increase in morphological integration of connectivity patterns. 3. Bones within the same connectivity module share the same allometric growth pattern in humans; as a consequence, connectivity modules resemble units of allometric growth. 4. The analysis of network models in human skulls with craniosynostosis indicates that modifications of connectivity patterns due to premature fusion of bones have similar effects than those observed during the evolution of the tetrapod skull (e.g., changes in complexity, variations in modular organization). This further suggests a strong relation between bone fusion during development and skull evolution. 5. Tetrapod skulls have occupied the space of possible forms following a directional pattern during their evolution; from forms with more bones and higher variability available, to forms with fewer bones and lower variability. 6. The null model that better explains this directional pattern is based on structural constraints imposed by the bilateral symmetry of the skull and a growth rule to establish connections between bones based on geometric proximity (Gabriel rule)

Anatomical Network Comparison of Human Upper and Lower, Newborn and Adult, and Normal and Abnormal Limbs, with Notes on Development, Pathology and Limb Serial Homology vs. Homoplasy

How do the various anatomical parts (modules) of the animal body evolve into very different integrated forms (integration) yet still function properly without decreasing the individual's survival? This long-standing question remains unanswered for multiple reasons, including lack of consensus about conceptual definitions and approaches, as well as a reasonable bias toward the study of hard tissues over soft tissues. A major difficulty concerns the non-trivial technical hurdles of addressing this problem, specifically the lack of quantitative tools to quantify and compare variation across multiple disparate anatomical parts and tissue types. In this paper we apply for the first time a powerful new quantitative tool, Anatomical Network Analysis (AnNA), to examine and compare in detail the musculoskeletal modularity and integration of normal and abnormal human upper and lower limbs. In contrast to other morphological methods, the strength of AnNA is that it allows efficient and direct empirical comparisons among body parts with even vastly different architectures (e.g. upper and lower limbs) and diverse or complex tissue composition (e.g. bones, cartilages and muscles), by quantifying the spatial organization of these parts-their topological patterns relative to each other-using tools borrowed from network theory. Our results reveal similarities between the skeletal networks of the normal newborn/adult upper limb vs. lower limb, with exception to the shoulder vs. pelvis. However, when muscles are included, the overall musculoskeletal network organization of the upper limb is strikingly different from that of the lower limb, particularly that of the more proximal structures of each limb. Importantly, the obtained data provide further evidence to be added to the vast amount of paleontological, gross anatomical, developmental, molecular and embryological data recently obtained that contradicts the long-standing dogma that the upper and lower limbs are serial homologues. In addition, the AnNA of the limbs of a trisomy 18 human fetus strongly supports Pere Alberch's ill-named "logic of monsters" hypothesis, and contradicts the commonly accepted idea that birth defects often lead to lower integration (i.e. more parcellation) of anatomical structures

Cranial anatomical integration and disparity among bones discriminate between primates and non-primate mammals

Data de publicació electrònica: 10-11-2021The primate skull hosts a unique combination of anatomical features among mammals, such as a short face, wide orbits, and big braincase. Together with a trend to fuse bones in late development, these features define the anatomical organization of the skull of primates—which bones articulate to each other and the pattern this creates. Here, I quantified the anatomical organization of the skull of 17 primates and 15 non-primate mammals using anatomical network analysis to assess how the skulls of primates have diverged from those of other mammals, and whether their anatomical differences coevolved with brain size. Results show that primates have a greater anatomical integration of their skulls and a greater disparity among bones than other non-primate mammals. Brain size seems to contribute in part to this difference, but its true effect could not be conclusively proven. This supports the hypothesis that primates have a distinct anatomical organization of the skull, but whether this is related to their larger brains remains an open question

A node-based informed modularity strategy to identify organizational modules in anatomical networks

The study of morphological modularity using anatomical networks is growing in recent years. A common strategy to find the best network partition uses community detection algorithms that optimize the modularity Q function. Because anatomical networks and their modules tend to be small, this strategy often produces two problems. One is that some algorithms find inexplicable different modules when one inputs slightly different networks. The other is that algorithms find asymmetric modules in otherwise symmetric networks. These problems have discouraged researchers to use anatomical network analysis and boost criticisms to this methodology. Here, I propose a node-based informed modularity strategy (NIMS) to identify modules in anatomical networks that bypass resolution and sensitivity limitations by using a bottom-up approach. Starting with the local modularity around every individual node, NIMS returns the modular organization of the network by merging non-redundant modules and assessing their intersection statistically using combinatorial theory. Instead of acting as a black box, NIMS allows researchers to make informed decisions about whether to merge non-redundant modules. NIMS returns network modules that are robust to minor variation and does not require optimization of a global modularity function. NIMS may prove useful to identify modules also in small ecological and social networks.B.E.-A. has received financial support through the Postdoctoral Junior Leader Fellowship Programme from ‘la Caixa’ Banking Foundation [LCF/BQ/LI18/ 11630002

Newborn Skull Networks JASs 2015

<p>Published in Esteve-Altava B, Rasskin-Gutman D. 2015. Evo-Devo Insights from Pathological Networks: Exploring Craniosynostosis as a Developmental Mechanism for Modularity and Complexity in the Human Skull. Journal of Anthropological Sciences 93: 1-15 DOI 10.4436/JASS.9300.</p> <p> </p

Primates Phylogeny

<p>- Item: calibrated phylogeny of 18 primate genera, with 2 outgroups.</p> <p>- Format: Phylip in txt.</p> <p>- Source: Perelman P, Johnson WE, Roos C, Seuánez HN, Horvath JE, et al. (2011) A Molecular Phylogeny of Living Primates. PLoS Genet 7(3): e1001342.<br>doi:10.1371/journal.pgen.1001342</p

Network Models in Morphology. Congreso Naciona de Herpetología. Tucuman, Argentina

<p>Plenary talk at the Argentinian National Meeting of Herpetology in Tucuman, Argentina.</p

Structural analysis of network models in tetrapod skulls

<p>Content: PhD dissertation presented in Dec 2013.</p> <p>Distinction: summa cum laude (with highest honor).</p> <p>Format: pdf</p> <p>Citation: Esteve-Altava B (2013) Structural analysis of network models in tetrapod skulls: Evolutionary trends and structural constraints in morphological complexity, integration, and modularity. University of Valencia.</p

Adjacency Matrices of Primate Skulls

<p>Adjacency matrices of the skull of 18 primates and 2 outgroup primatomorphs analyzed in the article:</p> <p>REF.</p

Adult and newborn head and limbs networks - Copy.xls

Network models of the musculoskeletal system of the head, upper and lower limb in an adult and a newborn human