scholarly journals Global elongation and high shape flexibility as an evolutionary hypothesis of accommodating mammalian brains into skulls

2020 ◽  
Author(s):  
Vera Weisbecker ◽  
Timothy Rowe ◽  
Stephen Wroe ◽  
Thomas E. Macrini ◽  
Kathleen L. S. Garland ◽  
...  
Keyword(s):  
Brain Size ◽  
Relative Volume ◽  
Shape Variation ◽  
Closely Related Species ◽  
Fossil Species ◽  
Mechanical Constraints ◽  
Statistical Shape ◽  
Mammalian Skull ◽  
And Function ◽  
Brain Shape

AbstractLittle is known about how the large brains of mammals are accommodated into the dazzling diversity of their skulls. It has been suggested that brain shape is influenced by relative brain size, that it evolves or develops according to extrinsic or intrinsic mechanical constraints, and that its shape can provide insights into its proportions and function. Here, we characterise the shape variation among 84 marsupial cranial endocasts of 57 species including fossils, using 3D geometric morphometrics and virtual dissections. Statistical shape analysis revealed four main patterns: over half of endocast shape variation ranges between elongate and straight to globular and inclined; little allometric variation with respect to centroid size, and none for relative volume; no association between locomotion and endocast shape; limited association between endocast shape and previously published histological cortex volumes. Fossil species tend to have smaller cerebral hemispheres. We find divergent endocast shapes in closely related species and within species, and diverse morphologies superimposed over the main variation. An evolutionarily and individually malleable brain with a fundamental tendency to arrange into a spectrum of elongate-to-globular shapes – possibly mostly independent of brain function - may explain the accommodation of brains within the enormous diversity of mammalian skull form.

scholarly journals How Can Satellite DNA Divergence Cause Reproductive Isolation? Let Us Count the Chromosomal Ways

2012 ◽  
Vol 2012 ◽  
pp. 1-11 ◽  
Author(s):  
Patrick M. Ferree ◽  
Satyaki Prasad
Keyword(s):  
Reproductive Isolation ◽  
Developmental Stages ◽  
Rapid Evolution ◽  
Model Organisms ◽  
Cellular Mechanisms ◽  
Closely Related Species ◽  
Heterochromatin Formation ◽  
Interspecies Hybrids ◽  
Postzygotic Reproductive Isolation ◽  
And Function

Satellites are one of the most enigmatic parts of the eukaryotic genome. These highly repetitive, noncoding sequences make up as much as half or more of the genomic content and are known to play essential roles in chromosome segregation during meiosis and mitosis, yet they evolve rapidly between closely related species. Research over the last several decades has revealed that satellite divergence can serve as a formidable reproductive barrier between sibling species. Here we highlight several key studies on Drosophila and other model organisms demonstrating deleterious effects of satellites and their rapid evolution on the structure and function of chromosomes in interspecies hybrids. These studies demonstrate that satellites can impact chromosomes at a number of different developmental stages and through distinct cellular mechanisms, including heterochromatin formation. These findings have important implications for how loci that cause postzygotic reproductive isolation are viewed.

scholarly journals Mammalian skull heterochrony reveals modular evolution and a link between cranial development and brain size

2014 ◽  
Vol 5 (1) ◽  
Author(s):  
Daisuke Koyabu ◽  
Ingmar Werneburg ◽  
Naoki Morimoto ◽  
Christoph P. E. Zollikofer ◽  
Analia M. Forasiepi ◽  
...  
Keyword(s):  
Brain Size ◽  
Cranial Development ◽  
Modular Evolution ◽  
Mammalian Skull

scholarly journals Inter-species comparison of the orientation algorithm directing larval chemotaxis in the genus Drosophila

2021 ◽  
Author(s):  
Elie Fink ◽  
Matthieu Louis
Keyword(s):  
Neural Circuits ◽  
Rapid Evolution ◽  
Structure And Function ◽  
Olfactory Behavior ◽  
Species Comparison ◽  
Closely Related Species ◽  
Genetic Studies ◽  
Phenotypic Differences ◽  
Peripheral Olfactory System ◽  
And Function

Animals differ in their appearances and behaviors. While many genetic studies have addressed the origins of phenotypic differences between fly species, we are still lacking a quantitative assessment of the variability in the way different fly species behave. We tackled this question in one of the most robust behaviors displayed by Drosophila: chemotaxis. At the larval stage, Drosophila melanogaster navigate odor gradients by combining four sensorimotor routines in a multilayered algorithm: a modulation of the overall locomotor speed and turn rate; a bias in turning during down-gradient motion; a bias in turning toward the gradient; the local curl of trajectories toward the gradient ("weathervaning"). Using high-resolution tracking and behavioral quantification, we characterized the olfactory behavior of eight closely related species of the Drosophila group in response to 19 ecologically-relevant odors. Significant changes are observed in the receptive field of each species, which is consistent with the rapid evolution of the peripheral olfactory system. Our results reveal substantial inter-species variability in the algorithms directing larval chemotaxis. While the basic sensorimotor routines are shared, their parametric arrangements can vary dramatically across species. The present analysis sets the stage for deciphering the evolutionary relationships between the structure and function of neural circuits directing orientation behaviors in Drosophila.

A new fossil species of the genus Parasinalda Heiss & Golub (Hemiptera: Heteroptera: Tingidae) from Upper Eocene Rovno amber

Zootaxa ◽  
2021 ◽  
Vol 5027 (2) ◽  
pp. 290-296
Author(s):  
VIKTOR B. GOLUB ◽  
EVGENY E. PERKOVSKY ◽  
DMITRY V. VASILENKO
Keyword(s):  
Related Species ◽  
Rovno Amber ◽  
Upper Eocene ◽  
Closely Related Species ◽  
Fossil Species ◽  
Similarities And Differences ◽  
Eocene Amber

Parasinalda sukachevae sp. nov. (Hemiptera: Heteroptera: Tingidae: Tinginae: Phatnomini) is described based on one specimen from Eocene amber of the Rovno region (Ukraine). Similarities and differences to closely related species Parasinalda baltica (Drake, 1950), P. froeschneri (Golub & Popov, 1998), and P. groehni Heiss & Golub, 2013 are discussed, and a key to the four known species of the genus is provided.  

Abstract 12471: Optimal Prediction of Atrial Fibrillation Recurrence After Ablation: A Computational Anatomy Study

Circulation ◽  
2015 ◽  
Vol 132 (suppl_3) ◽  
Author(s):  
Marta Varela ◽  
Felipe Bisbal ◽  
Ernesto Zacur ◽  
Esther Guiu ◽  
Antonio Berruezo ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Left Atrial ◽  
Complete Characterization ◽  
Statistical Shape Model ◽  
Patient Specific ◽  
Shape Variation ◽  
Global Features ◽  
Linear Discriminant ◽  
Af Ablation ◽  
Statistical Shape

Background: Left atrial structural remodelling, assessed by left atrial (LA) sphericity or antero-posterior diameter, has been shown to predict recurrence after atrial fibrillation (AF) ablation. The study aimed to perform a computational shape analysis of the LA to quantitatively characterise the LA shape remodelling process and identify metrics that optimally predict recurrence. Methods: Pre-procedural bright-blood MRIs of the LA of patients undergoing AF ablation were segmented. Patient-specific smooth 3D meshes were fitted to the segmentations. A statistical shape model of the LA was created and the global features underpinning the observed shape variation extracted as principal components (PCs). PCs were optimally combined to create non-empirical atlas-based metrics using linear discriminant analysis. Meshes depicting mean and extreme recurrent and non-recurrent LA shapes were also synthetized. The capability of different metrics to predict recurrence was evaluated using the area under the ROC curve (AUC) of a leave 1 out cross validation test. Results: In total, 111 patients were included. At 12 months follow-up, LA sphericity was the best predictor of recurrence (AUC: 0.66) over novel atlas-based metrics (AUC: 0.65). At 24 months, atlas-based metrics were the best predictors of recurrence (AUC: 0.66), outperforming a combination of sphericity and volume (AUC: 0.64), sphericity alone (AUC: 0.63) and any other traditional metric. Conclusions: Novel atlas-based metrics improve the prediction of recurrence at 2 years post-AF ablation. They allow a more complete characterization of the LA shape remodelling process, for example by allowing the synthesis of recurrent and non-recurrent LA shapes, which may contribute to patient stratification for AF ablation.

scholarly journals Emerging Roles of Long Non-Coding RNAs as Drivers of Brain Evolution

Cells ◽  
2019 ◽  
Vol 8 (11) ◽  
pp. 1399 ◽  
Author(s):  
Geraldine Zimmer-Bensch
Keyword(s):  
Human Brain ◽  
Cognitive Abilities ◽  
Brain Size ◽  
Expression Patterns ◽  
Brain Evolution ◽  
Relative Volume ◽  
Structural Reorganization ◽  
Protein Coding ◽  
Human Brain Evolution ◽  
Transcriptional Regulatory

Mammalian genomes encode tens of thousands of long-noncoding RNAs (lncRNAs), which are capable of interactions with DNA, RNA and protein molecules, thereby enabling a variety of transcriptional and post-transcriptional regulatory activities. Strikingly, about 40% of lncRNAs are expressed specifically in the brain with precisely regulated temporal and spatial expression patterns. In stark contrast to the highly conserved repertoire of protein-coding genes, thousands of lncRNAs have newly appeared during primate nervous system evolution with hundreds of human-specific lncRNAs. Their evolvable nature and the myriad of potential functions make lncRNAs ideal candidates for drivers of human brain evolution. The human brain displays the largest relative volume of any animal species and the most remarkable cognitive abilities. In addition to brain size, structural reorganization and adaptive changes represent crucial hallmarks of human brain evolution. lncRNAs are increasingly reported to be involved in neurodevelopmental processes suggested to underlie human brain evolution, including proliferation, neurite outgrowth and synaptogenesis, as well as in neuroplasticity. Hence, evolutionary human brain adaptations are proposed to be essentially driven by lncRNAs, which will be discussed in this review.

Probabilistic Study of a Lumbar Motion Segment: Sensitivity of Kinematics to Material and Anatomical Variability

2011 ◽  
Author(s):  
Kelli S. Barnes ◽  
Jeffrey R. Armstrong ◽  
Amit Agarwala ◽  
Anthony J. Petrella
Keyword(s):  
Statistical Shape Model ◽  
Single Subject ◽  
Shape Variation ◽  
Shape Model ◽  
Probabilistic Simulation ◽  
Motion Segment ◽  
Biomechanical Simulation ◽  
Statistical Shape ◽  
Probabilistic Study ◽  
Lumbar Motion

Finite element modeling of the lumbar spine has advanced significantly in the last decade [1] and become a relatively well established method for examining fundamental biomechanics as well as new spinal implants and procedures. However, most of these models only represent a single subject and do not account for normal subject-to-subject variation. This limitation can be addressed using a probabilistic simulation in which virtual specimens are used to represent a broad population of subjects. The greatest challenge to implementing probabilistic techniques in biomechanical simulation is parameterization of anatomy to capture normal variation across subjects. In the present study, shape variation was captured using a statistical shape model (SSM) and implemented in a probabilistic framework to evaluate biomechanics of a single motion segment. The Monte Carlo (MC) method is a common probabilistic simulation technique that is robust even for non-monotonic or highly non-linear systems. The purpose of this study was to perform a probabilistic study of a lumbar motion segment using MC simulation to determine the sensitivity of spinal rotations to changes in geometry and soft tissue material properties.

scholarly journals Thinking outside the glenohumeral box: Hierarchical shape variation of the periarticular anatomy of the scapula using statistical shape modeling

2020 ◽  
Vol 38 (10) ◽  
pp. 2272-2279
Author(s):  
Matthijs Jacxsens ◽  
Shireen Y. Elhabian ◽  
Sarah E. Brady ◽  
Peter N. Chalmers ◽  
Andreas M. Mueller ◽  
...  
Keyword(s):  
Shape Modeling ◽  
Shape Variation ◽  
Statistical Shape ◽  
Statistical Shape Modeling

Expert Vision Systems in Archaeometry

MRS Bulletin ◽  
1989 ◽  
Vol 14 (3) ◽  
pp. 40-44 ◽  
Author(s):  
John C. Russ ◽  
Irwin Rovner
Keyword(s):  
Size Variation ◽  
Statistical Interpretation ◽  
Shape Variation ◽  
Art Object ◽  
Irregular Shapes ◽  
Structure Correlations ◽  
Production History ◽  
Length Width ◽  
Few Data ◽  
And Function

In the analysis of object or material form and structure, especially micro-structure, correlations of material properties with their microstructure, and of structures with their production history and function, are at the heart of much of artifact and fossil analysis in archaeometry. Presently, a great deal of such examination of archaeomaterials is either:∎ qualitative, descriptive and anecdotal, comparing “representative” specimens to illustrate the differences of mean, typical, or normative structures, and forms; or∎ limited to measurement of parameters which oversimplify the structure or are easily measured by hand, e.g., length, width, and thickness.These do not differentiate shape variation or describe irregular shapes effectively. Hand measurements, even simple ones, are often difficult to derive on microstructures or on irregular macroscopic-sized objects and normally involve too few data points for statistical interpretation. Images of tesselated mosaics and multiphase microstructures in materials such as metals or ceramics are often chaotic and irregular in form, size variation and distribution of elements, inclusions and phases. Because of this, they are difficult to quantify precisely or accurately. Moreover, analysis is often limited more by the need to minimize destruction to an irreplacable artifact or art object than by a method's ability to generate significant data. Sample size is often held at the minimum threshold of significance or adequacy. Thus, any method which enhances the quality and quantity of such data should be welcome in archaeometric research.

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