Anatomical Networks Research Articles

An ALE meta-analytic review of musical expertise

Through long-term training, music experts acquire complex and specialized sensorimotor skills, which are paralleled by continuous neuro-anatomical and -functional adaptations. The underlying neuroplasticity mechanisms have been extensively explored in decades of research in music, cognitive, and translational neuroscience. However, the absence of a comprehensive review and quantitative meta-analysis prevents the plethora of variegated findings to ultimately converge into a unified picture of the neuroanatomy of musical expertise. Here, we performed a comprehensive neuroimaging meta-analysis of publications investigating neuro-anatomical and -functional differences between musicians (M) and non-musicians (NM). Eighty-four studies were included in the qualitative synthesis. From these, 58 publications were included in coordinate-based meta-analyses using the anatomic/activation likelihood estimation (ALE) method. This comprehensive approach delivers a coherent cortico-subcortical network encompassing sensorimotor and limbic regions bilaterally. Particularly, M exhibited higher volume/activity in auditory, sensorimotor, interoceptive, and limbic brain areas and lower volume/activity in parietal areas as opposed to NM. Notably, we reveal topographical (dis-)similarities between the identified functional and anatomical networks and characterize their link to various cognitive functions by means of meta-analytic connectivity modelling. Overall, we effectively synthesized decades of research in the field and provide a consistent and controversies-free picture of the neuroanatomy of musical expertise.

Networks behind the morphology and structural design of living systems.

Technological advances in imaging techniques and biometric data acquisition have enabled us to apply methods of network science to study the morphology and structural design of organelles, organs, and tissues, as well as the coordinated interactions among them that yield a healthy physiology at the level of whole organisms. We here review research dedicated to these advances, in particular focusing on networks between cells, the topology of multicellular structures, neural interactions, fluid transportation networks, and anatomical networks. The percolation of blood vessels, structural connectivity within the brain, the porous structure of bones, and relations between different anatomical parts of the human body are just some of the examples that we explore in detail. We argue and show that the models, methods, and algorithms developed in the realm of network science are ushering in a new era of network-based inquiry into the morphology and structural design of living systems in the broadest possible terms. We also emphasize that the need and applicability of this research is likely to increase significantly in the years to come due to the rapid progress made in the development of bioartificial substitutes and tissue engineering.

The structural brain network topology of episodic memory.

Episodic memory is supported by a distributed network of brain regions, and this complex network of regions does not operate in isolation. To date, neuroscience research in this area has typically focused on the activation levels in specific regions or pairwise connectivity between such regions. However, research has yet to investigate how the complex interactions of structural brain networks influence episodic memory abilities. We applied graph theory methods to diffusion-based anatomical networks in order to examine the structural architecture of the medial temporal lobe needed to support effective episodic memory functioning. We examined the relationship between performance on tests of verbal and non-verbal episodic memory with node strength, which indexes how well connected a brain region is in the network. Findings mapped onto the Posterior Medial memory system, subserved by the parahippocampal cortex and overlapped with findings of previous studies of episodic memory employing different methodologies. This expands our current understanding by providing independent evidence for the importance of identified regions and suggesting the particular manner in which these regions support episodic memory.

Intrinsic Functional Connectivity in the Default Mode Network Differentiates the Combined and Inattentive Attention Deficit Hyperactivity Disorder Types.

Neuroimaging studies have revealed neurobiological differences in ADHD, particularly studies examining connectivity disruption and anatomical network organization. However, the underlying pathophysiology of ADHD types remains elusive as it is unclear whether dysfunctional network connections characterize the underlying clinical symptoms distinguishing ADHD types. Here, we investigated intrinsic functional network connectivity to identify neural signatures that differentiate the combined (ADHD-C) and inattentive (ADHD-I) presentation types. Applying network-based statistical (NBS) and graph theoretical analysis to task-derived intrinsic connectivity data from completed fMRI scans, we evaluated default mode network (DMN) and whole-brain functional network topology in a cohort of 34 ADHD participants (aged 8–17 years) defined using DSM-IV criteria as predominantly inattentive (ADHD-I) type (n = 15) or combined (ADHD-C) type (n = 19), and 39 age and gender-matched typically developing controls. ADHD-C were characterized from ADHD-I by reduced network connectivity differences within the DMN. Additionally, reduced connectivity within the DMN was negatively associated with ADHD-RS hyperactivity-impulsivity subscale score. Compared with controls, ADHD-C but not ADHD-I differed by reduced connectivity within the DMN; inter-network connectivity between the DMN and somatomotor networks; the DMN and limbic networks; and between the somatomotor and cingulo-frontoparietal, with ventral attention and dorsal attention networks. However, graph-theoretical measures did not significantly differ between groups. These findings provide insight into the intrinsic networks underlying phenotypic differences between ADHD types. Furthermore, these intrinsic functional connectomic signatures support neurobiological differences underlying clinical variations in ADHD presentations, specifically reduced within and between functional connectivity of the DMN in the ADHD-C type.

Criticality and network structure drive emergent oscillations in a stochastic whole-brain model

Understanding the relation between the structure of brain networks and their functions is a fundamental open question. Simple models of neural activity based on real anatomical networks have proven to be effective in describing features of whole-brain spontaneous activity when tuned at their critical point. In this work, we show that structural networks are indeed a crucial ingredient in the emergence of collective oscillations in a whole-brain stochastic model at criticality. We study analytically a stochastic Greenberg–Hastings cellular automaton in the mean-field limit, showing that it undergoes an abrupt phase transition with a bistable region. In particular, no global oscillations emerge in this limit. Then, we show that by introducing a network structure in the homeostatic normalization regime, the bistability may be disrupted, and the transition may become smooth. Concomitantly, through an interplay between network topology and weights, a large peak in the power spectrum appears around the transition point, signaling the emergence of collective oscillations. Hence, both the structure of brain networks and criticality are fundamental in driving the collective responses of whole-brain stochastic models.

Progression Patterns in Non-Contrast-Enhancing Gliomas Support Brain Tumor Responsiveness to Surgical Lesions.

Purpose: The overall benefit of surgical treatments for patients with glioma is undisputed. We have shown preclinically that brain tumor cells form a network that is capable of detecting damage to the tumor, and repair itself. The aim of this study was to determine whether a similar mechanism might contribute to local recurrence in the clinical setting. Methods: We evaluated tumor progression patterns of 24 initially non-contrast-enhancing gliomas that were partially resected or biopsied. We measured the distance between the new contrast enhancement developing over time, and prior surgical lesioning, and evaluated tumor network changes in response to sequential resections by quantifying tumor cells and tumor networks with specific stainings against IDH1-R132H. Results: We found that new contrast enhancement appeared within the residual, non-enhancing tumor mass in 21/24 patients (87.5%). The location of new contrast enhancement within the residual tumor region was non-random; it occurred adjacent to the wall of the resection cavity in 12/21 patients (57.1%). Interestingly, the density of the glioma cell network increased in all patient tumors between initial resection or biopsy and recurrence. In line with the histological and radiological malignization, Ki67 expression increased from initial to final resections in 14/17 cases. Conclusion: The non-random distribution of glioma malignization in patients and unidirectional increase of anatomical tumor networks after surgical procedures provides evidence that surgical lesions, in the presence of residual tumor cells, can stimulate local tumor progression and tumor cell network formation. This argues for the development of intraoperative treatments increasing the benefits from surgical resection by specifically disrupting the mechanisms of local recurrence, particularly tumor cell network functionality.

Redefining the simplicity of the craniomandibular complex of nightjars: The case of Systellura longirostris (Aves: Caprimulgidae) by means of anatomical network analysis.

To study morphological evolution, itis necessary to combine information from multiple intersecting research fields. Here, we report on the structure of the bony and muscular elements of the craniomandibular complex of birds, highlighting its morphological architecture and complexity (or simplification) in the context of anatomical networks of the Band-winged Nightjar Systellura longirostris (Caprimulgiformes, Caprimulgidae). This species has skull osteology and jaw myology that departs from the general structural plan of the craniomandibular complex of Neornithes and is considered morphologically simple. Our goal is to test if its simplification is also reflected in its anatomical network, particularly in those parameters that measure complexity and to explore if the distribution of the networks in a phylomorphospace is conditioned by their evolutionary history or by convergence. Our results show that S. longirostris clusters with other Strisores and momotids and is segregated from the other bird species analyzed when plotted in the phylomorphospace, as a consequence of convergence in the network parameters. Systellura has a craniomandibular complex consisting of fewer muscles connecting more bones than the model species (e.g., the rock pigeon or the guira cuckoo). In this sense, Systellura is actually more complex regarding the number of integrative bony parts, while its craniomandibular complex is simpler. According to its anatomical network, Systellura also can be interpreted as less complex, particularly compared with other Strisores and taxa that reflect the general structure of the craniomandibular complex in Neornithes.

Simulated Attack Reveals How Lesions Affect Network Properties in Poststroke Aphasia.

Aphasia is a prevalent cognitive syndrome caused by stroke. The rarity of premorbid imaging and heterogeneity of lesion obscures the links between the local effects of the lesion, global anatomic network organization, and aphasia symptoms. We applied a simulated attack approach in humans to examine the effects of 39 stroke lesions (16 females) on anatomic network topology by simulating their effects in a control sample of 36 healthy (15 females) brain networks. We focused on measures of global network organization thought to support overall brain function and resilience in the whole brain and within the left hemisphere. After removing lesion volume from the network topology measures and behavioral scores [the Western Aphasia Battery Aphasia Quotient (WAB-AQ), four behavioral factor scores obtained from a neuropsychological battery, and a factor sum], we compared the behavioral variance accounted for by simulated poststroke connectomes to that observed in the randomly permuted data. Global measures of anatomic network topology in the whole brain and left hemisphere accounted for 10% variance or more of the WAB-AQ and the lexical factor score beyond lesion volume and null permutations. Streamline networks provided more reliable point estimates than FA networks. Edge weights and network efficiency were weighted most highly in predicting the WAB-AQ for FA networks. Overall, our results suggest that global network measures provide modest statistical value beyond lesion volume when predicting overall aphasia severity, but less value in predicting specific behaviors. Variability in estimates could be induced by premorbid ability, deafferentation and diaschisis, and neuroplasticity following stroke.SIGNIFICANCE STATEMENT Poststroke, the remaining neuroanatomy maintains cognition and supports recovery. However, studies often use small, cross-sectional samples that cannot fully model the interactions between lesions and other variables that affect networks in stroke. Alternate methods are required to account for these effects. "Simulated attack" models are computational approaches that apply virtual damage to the brain and measure their putative consequences. Using a simulated attack model, we estimated how simulated damage to anatomic networks could account for language performance. Overall, our results reveal that global network measures can provide modest statistical value predicting overall aphasia severity, but less value in predicting specific behaviors. These findings suggest that more theoretically precise network models could be necessary to robustly predict individual outcomes in aphasia.

Breaking the mold: telescoping drives the evolution of more integrated and heterogeneous skulls in cetaceans.

BackgroundAlong with the transition to the aquatic environment, cetaceans experienced profound changes in their skeletal anatomy, especially in the skull, including the posterodorsal migration of the external bony nares, the reorganization of skull bones (= telescoping) and the development of an extreme cranial asymmetry (in odontocetes). Telescoping represents an important anatomical shift in the topological organization of cranial bones and their sutural contacts; however, the impact of these changes in the connectivity pattern and integration of the skull has never been addressed.MethodsHere, we apply the novel framework provided by the Anatomical Network Analysis to quantify the organization and integration of cetacean skulls, and the impact of the telescoping process in the connectivity pattern of the skull. We built anatomical networks for 21 cetacean skulls (three stem cetaceans, three extinct and 10 extant mysticetes, and three extinct and two extant odontocetes) and estimated network parameters related to their anatomical integration, complexity, heterogeneity, and modularity. This dataset was analyzed in the context of a broader tetrapod skull sample as well (43 species of 13 taxonomic groups).ResultsThe skulls of crown cetaceans (Neoceti) occupy a new tetrapod skull morphospace, with better integrated, more heterogeneous and simpler skulls in comparison to other tetrapods. Telescoping adds connections and improves the integration of those bones involved in the telescoping process (e.g., maxilla, supraoccipital) as well as other ones (e.g., vomer) not directly affected by telescoping. Other underlying evolutionary processes (such as basicranial specializations linked with hearing/breathing adaptations) could also be responsible for the changes in the connectivity and integration of palatal bones. We also find prograde telescoped skulls of mysticetes distinct from odontocetes by an increased heterogeneity and modularity, whereas retrograde telescoped skulls of odontocetes are characterized by higher complexity. In mysticetes, as expected, the supraoccipital gains importance and centrality in comparison to odontocetes, increasing the heterogeneity of the skull network. In odontocetes, an increase in the number of connections and complexity is probably linked with the dominant movement of paired bones, such as the maxilla, in retrograde telescoping. Crown mysticetes (Eubalaena, Caperea, Piscobalaena, and Balaenoptera)are distinguished by having more integrated skulls in comparison to stem mysticetes (Aetiocetus and Yamatocetus), whereas crown odontocetes (Waipatia, Notocetus, Physeter, and Tursiops) have more complex skulls than stem forms (Albertocetus). Telescoping along with feeding, hearing and echolocation specializations could have driven the evolution of the different connectivity patterns of living lineages.

The shifting role of the cerebellum in executive, emotional and social processing across the lifespan

The cerebellum’s anatomical and functional organization and network interactions between the cerebellum and the cerebral cortex and subcortical structures are dynamic across the lifespan. Executive, emotional and social (EES) functions have likewise evolved during human development from contributing to primitive behaviors during infancy and childhood to being able to modulate complex actions in adults. In this review, we address how the importance of the cerebellum in the processing of EES functions might change across development. This evolution is driven by the macroscopic and microscopic modifications of the cerebellum that are occurring during development including its increasing connectivity with distant supra-tentorial cortical and sub-cortical regions. As a result of anatomical and functional changes, neuroimaging and clinical data indicate that the importance of the role of the cerebellum in human EES-related networks shifts from being crucial in newborns and young children to being only supportive later in life. In early life, given the immaturity of cortically mediated EES functions, EES functions and motor control and perception are more closely interrelated. At that time, the cerebellum due to its important role in motor control and sequencing makes EES functions more reliant on these computational properties that compute spatial distance, motor intent, and assist in the execution of sequences of behavior related to their developing EES expression. As the cortical brain matures, EES functions and decisions become less dependent upon these aspects of motor behavior and more dependent upon high-order cognitive and social conceptual processes. At that time, the cerebellum assumes a supportive role in these EES-related behaviors by computing their motor and sequential features. We suspect that this evolving role of the cerebellum has complicated the interpretation of its contribution to EES computational demands.

Simulating Multi-Scale Pulmonary Vascular Function by Coupling Computational Fluid Dynamics With an Anatomic Network Model.

The function of the pulmonary circulation is truly multi-scale, with blood transported through vessels from centimeter to micron scale. There are scale-dependent mechanisms that govern the flow in the pulmonary vascular system. However, very few computational models of pulmonary hemodynamics capture the physics of pulmonary perfusion across the spatial scales of functional importance in the lung. Here we present a multi-scale model that incorporates the 3-dimensional (3D) complexities of pulmonary blood flow in the major vessels, coupled to an anatomically-based vascular network model incorporating the multiple contributing factors to capillary perfusion, including gravity. Using the model we demonstrate how we can predict the impact of vascular remodeling and occlusion on both macro-scale functional drivers (flow distribution between lungs, and wall shear stress) and micro-scale contributors to gas exchange. The model predicts interactions between 3D and 1D models that lead to a redistribution of blood between postures, both on a macro- and a micro-scale. This allows us to estimate the effect of posture on left and right pulmonary artery wall shear stress, with predictions varying by 0.75-1.35dyne/cm2 between postures.

Effect of environmental signals on growth and development in mosses.

Plants perceive a multitude of environmental signals and stresses, and integrate their response to them in ways that culminate in modified phenotypes, optimized for plant survival. This ability of plants, known as phenotypic plasticity, is found throughout evolution, in all plant lineages. For any given environment, the specifics of the response to a particular signal may vary depending on the plants' unique physiology and ecological niche. The bryophyte lineage, including mosses, which diverged from the vascular plants ~450-430 million years ago, represent a unique ecological and phylogenetic group in plant evolution. Several aspects of the moss life cycle, their morphology including the presence of specialized tissue types and distinct anatomical features, gene repertoires and networks, as well as the habitat differ significantly from those of vascular plants. To evaluate the outcomes of these differences, we explore the phenotypic responses of mosses to environmental signals such as light, temperature, CO2, water, nutrients, and gravity, and compare those with what is known in vascular plants. We also outline knowledge gaps and formulate testable hypotheses based on the contribution of anatomical and molecular factors to specific phenotypic responses.

Modeling Skull Network Integrity at the Dawn of Amniote Diversification With Considerations on Functional Morphology and Fossil Jaw Muscle Reconstructions

One of the major questions in evolutionary vertebrate morphology is the origin and meaning of temporal skull openings in land vertebrates. Partly or fully surrounded by bones, one, two, or even three openings may evolve behind the orbit, within the ancestrally fully roofed anapsid (scutal) skull. At least ten different morphotypes can be distinguished in tetrapods with many modifications and transitions in more crownward representatives. A number of potential factors driving the emergence and differentiation of temporal openings have been proposed in the literature, but only today are proper analytical tools available to conduct traceable tests for the functional morphology underlying temporal skull constructions. In the present study, we examined the anatomical network in the skull of one representative of early amniotes, †Captorhinus aguti, which ancestrally exhibits an anapsid skull. The resulting skull modularity revealed a complex partitioning of the temporal region indicating, in its intersections, the candidate positions for potential infratemporal openings. The framework of †C. agutiwas then taken as a template to model a series of potential temporal skull morphotypes in order to understand how skull openings might influence the modular composition of the amniote skull in general. We show that the original pattern of skull modularity (†C. aguti) experiences comprehensive changes by introducing one or two temporal openings in different combinations and in different places. The resulting modules in each skull model are interpreted in regard to the feeding behavior of amniotes that exhibit(ed) the respective skull morphotypes. An important finding is the alternative incorporation of the jugal and palate to different modules enforcing the importance of an integrated view on skull evolution: the temporal region cannot be understood without considering palatal anatomy. Finally, we discuss how to better reconstruct relative jaw muscle compositions in fossils by considering the modularity of the skull network. These considerations might be relevant for future biomechanical studies on skull evolution.

Examining the Effects of Normal Ageing on Cortical Connectivity of Older Adults.

With the recent advancement in computer technology, we can extract the picture of the brain as a network. The aim of this study is to constructs large scale individual anatomical brain networks using regional gray matter cortical thickness from individual subject's magnetic resonance imaging (MRI) data, as well as to investigate changes with normal aging in global network organization. The dataset includes 183 healthy subjects sMRI data with an age range from 50 to 80 plus. For all brain networks, we calculated the global network measures and nodal network measures by using network analysis toolkit GRETNA. From global network measurements we calculated small-world measurements and network efficiency measurements, from nodal measurements we calculated node clustering coefficient (CC) and node efficiency at a wide-range of threshold values. All small world measurements showed more clustering at all the given threshold values than random networks and a alike least path length, indicative of that they were "small world". To analyze the effect normal ageing on networks organization, the networks of subjects were categorized into three age groups (50s, 60s, and 70 over). The global and nodal network measurements of each group were statistically analyzed to investigate the significant difference in network organization with in age groups. Results shows that the age has no significance effect in global measurements of brain network. However, by analysis the nodal measures of brain network between age group, network nodes from brain frontal lobe and temporal lobe showed age related significant difference. The results obtained from the proposed study suggest that this network method can deliver a concise network-level picture of brain organization and be used from the outlook of composite networks to investigate inter-individual variability in brain morphology.

An ecological approach to identify distinct neural correlates of disinhibition in frontotemporal dementia

Disinhibition is a core symptom of many neurodegenerative diseases, particularly frontotemporal dementia, and is a major cause of stress for caregivers. While a distinction between behavioural and cognitive disinhibition is common, an operational definition of behavioural disinhibition is still missing. Furthermore, conventional assessment of behavioural disinhibition, based on questionnaires completed by the caregivers, often lacks ecological validity. Therefore, their neuroanatomical correlates are non-univocal.In the present work, we used an original behavioural approach in a semi-ecological situation to assess two specific dimensions of behavioural disinhibition: compulsivity and social disinhibition. First, we investigated disinhibition profile in patients compared to controls. Then, to validate our approach, compulsivity and social disinhibition scores were correlated with classic cognitive tests measuring disinhibition (Hayling Test) and social cognition (mini-Social cognition & Emotional Assessment). Finally, we disentangled the anatomical networks underlying these two subtypes of behavioural disinhibition, taking in account the grey (voxel-based morphometry) and white matter (diffusion tensor imaging tractography). We included 17 behavioural variant frontotemporal dementia patients and 18 healthy controls.We identified patients as more compulsive and socially disinhibited than controls. We found that behavioural metrics in the semi-ecological task were related to cognitive performance: compulsivity correlated with the Hayling test and both compulsivity and social disinhibition were associated with the emotion recognition test. Based on voxel-based morphometry and tractography, compulsivity correlated with atrophy in the bilateral orbitofrontal cortex, the right temporal region and subcortical structures, as well as with alterations of the bilateral cingulum and uncinate fasciculus, the right inferior longitudinal fasciculus and the right arcuate fasciculus. Thus, the network of regions related to compulsivity matched the “semantic appraisal” network. Social disinhibition was associated with bilateral frontal atrophy and impairments in the forceps minor, the bilateral cingulum and the left uncinate fasciculus, regions corresponding to the frontal component of the “salience” network.Summarizing, this study validates our semi-ecological approach, through the identification of two subtypes of behavioural disinhibition, and highlights different neural networks underlying compulsivity and social disinhibition. Taken together, these findings are promising for clinical practice by providing a better characterisation of inhibition disorders, promoting their detection and consequently a more adapted management of patients.

Anatomical and functional visual network patterns in progressive multiple sclerosis.

The gradual accrual of disability over time in progressive multiple sclerosis is believed to be driven by widespread degeneration. Yet another facet of the problem may reside in the loss of the brain's ability to adapt to the damage incurred as the disease progresses. In this study, we attempted to examine whether changes associated with optic neuritis in the structural and functional visual networks can still be discerned in progressive patients even years after the acute insult. Forty‐eight progressive multiple sclerosis patients, 21 with and 27 without prior optic neuritis, underwent structural and functional MRI, including DTI and resting state fMRI. Anatomical and functional visual networks were analyzed using graph theory‐based methods. While no functional metrics were significantly different between the two groups, anatomical global efficiency and density were significantly lower in the optic neuritis group, despite no significant difference in lesion load between the groups. We conclude that long‐standing distal damage to the optic nerve causes trans‐synaptic effects and the early ability of the cortex to adapt may be altered, or possibly nullified. We suggest that this limited ability of the brain to compensate should be considered when attempting to explain the accumulation of disability in progressive multiple sclerosis patients.

The effect of microglial genes on network diffusion of pathology in mouse models of tauopathy

AbstractBackgroundMisfolded tau and amyloid, the hallmark pathologies of Alzheimer’s disease, undergo “prion‐like” trans‐synaptic transmission along the brain’s anatomic connectivity network (Frost, et al,2010). Our lab has previously shown that Alzheimer’s neuropathology progression is well‐approximated by a network diffusion model (NDM) (Raj, et al,2012). However, other processes in the brain may affect the neuropathology progression by mediating intraregional clearance/amplification and interregional spread. For instance, microglial activation is a common pathological feature of Alzheimer’s disease, with TREM2‐expressing microglia being integral to the inflammatory response. We show here that the NDM can be extended to include effects of microglial mediation of pathology.MethodWe modified the NDM to an extended NDM (eNDM) with additional model parameters related to microglia‐mediated spread/clearance and applied it to the 426×426 region mouse connectome. The eNDM included datasets of longitudinal spatiotemporal tau pathology in PS19 mice, expression levels of five microglial homeostatic signature genes (Cx3Cr1, C1qa, P2ry12, Fcrls, Olfml3) as well as TREM2 and CD33, microglial surface‐markers and phagocytosis regulators (Li, et al,2018). We compared the fits of the NDM to those of the eNDM using each gene individually as well as the first two principal components of spatial gene expression (Lein, et al,2007) after optimizing model parameters using a constrained nonlinear optimization algorithm.ResultsInclusion of microglial gene expression improved the predictive power of the model beyond that of the NDM (R2=0.46). Using the principal components of gene expression generally provided better model fits than individual genes. Notably, exclusion of TREM2 before performing PCA had a significant effect on model fit (p<0.001, R2=0.5) (Table 1, Figure 1), increasing the values of the optimal diffusion and spread parameters.ConclusionAlthough network spread models capture well the spread of pathology between brain regions, there are other factors that mediate this process. We demonstrated that an eNDM with microglial genes had an improved model fit even after accounting for differences in model parsimony. We also showed that exclusion of TREM2 from the model resulted in higher diffusivity parameter values, thus supporting the biological observation of TREM2‐knockout resulting in increased spread of pathology, putatively by affecting microglial phagocytic potential (Griciuc, et al, 2019).

Cranial Anatomical Integration and Disparity Among Bones Discriminate Between Primates and Non-primate Mammals

The 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.

Construction of Anatomical Structure-specific Developmental Dynamic Networks for Human Brain on Multiple Omics Levels

Background: Human brain development is a series of complex processes exhibiting profound changes from gestation to adulthood. Objective: We aimed to construct dynamic developmental networks for each anatomical structure of the human brain based on omics’ levels in order to gain a new systematical brain map on the molecular level. Methods: We performed the brain development analyses by constructing dynamical networks between adjacent time points on different grouping levels of anatomical structures. The gene-time networks were first built to obtain the developing brain dynamical maps on transcriptome level. Then miRNA-mRNA networks and protein-protein networks were constructed by integrating the information from miRNomics and proteomics. The time and structure-specific biomarkers were filtered based on analyses of topological characters. Results: The most dramatic developmental time and structure were fetal-infancy and telencephalon, respectively. Cortex was the key developmental region in ‘late fetal and neonatal’ and ‘early infancy’. The development of the temporal lobe was different from other lobes since the significant changes of molecules were found only in the comparison pair ‘early fetal-early mid-fetal’ and ‘adolescence-young adulthood’. Interestingly, the changes among different brain structures inside adolescence and adulthood were bigger than other time points. hsa-miR-548c-3p and H3C2 may be new brain development indicators considering their key roles in networks. Conclusion: To our knowledge, this study is the first report of dynamical brain development maps for different anatomical structures on multiple omics. The results provide a new sight of brain development in a systematical way which may provide a more accurate understanding of the human brain.

Geometric morphometrics and anatomical network analyses reveal ecospace partitioning among geoemydid turtles from the Uinta Formation, Utah.

We present new fossil records of the geoemydid turtle Bridgeremys pusilla from the Uinta Formation of Utah. Turtles are abundant throughout the unit, and known taxa are similar to those from the older strata in the Upper Green River Basin in Wyoming from the Bridger and Washakie Formations. B. pusilla is known from Bridgerian deposits but was not previously known from after the Turtle Bluff Member of the Bridger Formation. The taxon was coveal with two species of the geoemydid Echmatemys (E. callopyge and E. wyomingensis), a common genus of extinct pond turtles known primarily from lacustrine and fluvial deposits in western North America, including the Uinta Basin. In addition to previously documented morphological differences, our geometric morphometric analyses revealed significant differences in epiplastral morphology between B. pusilla and the two coeval Echmatemys species. Bridgeremys pusilla shared several morphological characters with Testudinidae. However, our anatomical network analysis suggests that the carapace of B. pusilla distributed stress forces in a manner more similar to emydids (basal and derived) than to derived testudinoids (Testudinidae and Emydidae), including Echmatemys species. This finding changes our understanding of the ecology of the species and sheds light onto how geoemydid turtles of the Uinta Formation may have partitioned the available ecospace. These new Uintan records extend the geographic range of B. pusilla into the Uinta Basin and stratigraphically through the top of the Uinta Formation, extending the temporal range of the taxon by more than 4 million years through the Uintan North American Land Mammal Age to the base of the Duchesne River Formation.