Mr-Nom: Multi-Scale Resolution of Neuronal Cells in Nissl-Stained Histological Slices Via Deliberate over-Segmentation and Merging

In comparative neuroanatomy, the characterization of brain cytoarchitecture is critical to a better understanding of brain structure and function, as it helps to distill information on the development, evolution, and distinctive features of different populations. The automatic segmentation of individual brain cells is a primary prerequisite and yet remains challenging. A new method (MR-NOM) was developed for the instance segmentation of cells in Nissl-stained histological images of the brain. MR-NOM exploits a multi-scale approach to deliberately over-segment the cells into superpixels and subsequently merge them via a classifier based on shape, structure, and intensity features. The method was tested on images of the cerebral cortex, proving successful in dealing with cells of varying characteristics that partially touch or overlap, showing better performance than two state-of-the-art methods

Multi-aspect testing and ranking inference to quantify dimorphism in the cytoarchitecture of cerebellum of male, female and intersex individuals: a model applied to bovine brains.

The dimorphism among male, female and freemartin intersex bovines, focusing on the vermal lobules VIII and IX, was analyzed using a novel data analytics approach to quantify morphometric differences in the cytoarchitecture of digitalized sections of the cerebellum. This methodology consists of multivariate and multi-aspect testing for cytoarchitecture-ranking, based on neuronal cell complexity among populations defined by factors, such as sex, age or pathology. In this context, we computed a set of shape descriptors of the neural cell morphology, categorized them into three domains named size, regularity and density, respectively. The output and results of our methodology are multivariate in nature, allowing an in-depth analysis of the cytoarchitectonic organization and morphology of cells. Interestingly, the Purkinje neurons and the underlying granule cells revealed the same morphological pattern: female possessed larger, denser and more irregular neurons than males. In the Freemartin, Purkinje neurons showed an intermediate setting between males and females, while the granule cells were the largest, most regular and dense. This methodology could be a powerful instrument to carry out morphometric analysis providing robust bases for objective tissue screening, especially in the field of neurodegenerative pathologies

Multi-aspect testing and ranking inference to quantify dimorphism in the cytoarchitecture of cerebellum of male, female and intersex individuals: a model applied to bovine brains

The dimorphism among male, female and freemartin intersex bovines, focusing on the vermal lobules VIII and IX, was analyzed using a novel data analytics approach to quantify morphometric differences in the cytoarchitecture of digitalized sections of the cerebellum. This methodology consists of multivariate and multi-aspect testing for cytoarchitecture-ranking, based on neuronal cell complexity among populations defined by factors, such as sex, age or pathology. In this context, we computed a set of shape descriptors of the neural cell morphology, categorized them into three domains named size, regularity and density, respectively. The output and results of our methodology are multivariate in nature, allowing an in-depth analysis of the cytoarchitectonic organization and morphology of cells. Interestingly, the Purkinje neurons and the underlying granule cells revealed the same morphological pattern: female possessed larger, denser and more irregular neurons than males. In the Freemartin, Purkinje neurons showed an intermediate setting between males and females, while the granule cells were the largest, most regular and dense. This methodology could be a powerful instrument to carry out morphometric analysis providing robust bases for objective tissue screening, especially in the field of neurodegenerative pathologies

Age-related changes in the primary auditory cortex of newborn, adults and aging bottlenose dolphins (Tursiops truncatus) are located in the upper cortical layers

Introduction: The auditory system of dolphins and whales allows them to dive in dark waters, hunt for prey well below the limit of solar light absorption, and to communicate with their conspecific. These complex behaviors require specific and sufficient functional circuitry in the neocortex, and vicarious learning capacities. Dolphins are also precocious animals that can hold their breath and swim within minutes after birth. However, diving and hunting behaviors are likely not innate and need to be learned. Our hypothesis is that the organization of the auditory cortex of dolphins grows and mature not only in the early phases of life, but also in adults and aging individuals. These changes may be subtle and involve sub-populations of cells specificall linked to some circuits. Methods: In the primary auditory cortex of 11 bottlenose dolphins belonging to three age groups (calves, adults, and old animals), neuronal cell shapes were analyzed separately and by cortical layer using custom computer vision and multivariate statistical analysis, to determine potential minute morphological differences across these age groups. Results: The results show definite changes in interneurons, characterized by round and ellipsoid shapes predominantly located in upper cortical layers. Notably, neonates interneurons exhibited a pattern of being closer together and smaller, developing into a more dispersed and diverse set of shapes in adulthood. Discussion: This trend persisted in older animals, suggesting a continuous development of connections throughout the life of these marine animals. Our findings further support the proposition that thalamic input reach upper layers in cetaceans, at least within a cortical area critical for their survival. Moreover, our results indicate the likelihood of changes in cell populations occurring in adult animals, prompting the need for characterization

The motor cortex of the sheep: laminar organization, projections and diffusion tensor imaging of the intracranial pyramidal and extrapyramidal tracts

The laminar organization of the motor cortex of the sheep and other large domestic herbivores received scarce attention and is generally considered homologous to that of rodents and primates. Thickness of the cortex, subdivision into layers and organization are scarcely known. In the present study, we applied different modern morphological, mathematical and image-analyses techniques to the study of the motor area that controls movements of the forelimb in the sheep. The thickness of the cortex resulted comparable to that of other terrestrial Cetartiodactyls (but thicker than in marine Cetartiodactyls of similar body mass). The laminar organization showed marked development of layer 1, virtual absence of layer 4, and image analysis suggested prevalence of large irregular neural cells in the deeper layers. Diffusion tensor imaging revealed robust projections from the motor cortex to the pyramids in the brainstem, and well evident tracts descending to the tegmentum of the mesencephalon and dorsal pons. Our data contrast the general representation of the motor system of this species, considered to be predominantly based on extra-pyramidal tracts that originate from central pattern generators in the brainstem. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature

The laminar organization of the motor cortex in monodactylous mammals: a comparative assessment based on horse, chimpanzee, and macaque

The architecture of the neocortex classically consists of six layers, based on cytological criteria and on the layout of intra/interlaminar connections. Yet, the comparison of cortical cytoarchitectonic features across different species proves overwhelmingly difficult, due to the lack of a reliable model to analyze the connection patterns of neuronal ensembles forming the different layers. We first defined a set of suitable morphometric cell features, obtained in digitized Nissl-stained sections of the motor cortex of the horse, chimpanzee, and crab-eating macaque. We then modeled them using a quite general non-parametric data representation model, showing that the assessment of neuronal cell complexity (i.e., how a given cell differs from its neighbors) can be performed using a suitable measure of statistical dispersion such as the mean absolute deviation\u2014mean absolute deviation (MAD). Along with the non-parametric combination and permutation methodology, application of MAD allowed not only to estimate, but also to compare and rank the motor cortical complexity across different species. As to the instances presented in this paper, we show that the pyramidal layers of the motor cortex of the horse are far more irregular than those of primates. This feature could be related to the different organizations of the motor system in monodactylous mammals

A Non-parametric Method for Defining a Global Preference Ranking of Industrial Products

Although experimentation is a crucial stage in the process of research and development of industrial products, no satisfactory procedure is available to deal with the common but rather important industrial problem of defining a preference ranking among all the studied product prototypes on the basis of performances. In this paper we propose a two-stage non-parametric procedure in which we firstly perform a set of C-sample testing procedures, followed by multiple comparisons, in this way evaluating a set of partial preference rankings, and secondly synthesise the partial rankings by combining them into a global ranking that provides a general product preference rule. The proposed method is particularly useful in the context of industrial experimentation and offers several advantages such as effectiveness, high flexibility and practical adherence to real problems where preference ranking is a natural goal.Dependent rankings, industrial products, non-parametric combination, permutation tests, research and development,

AN EMPIRICAL STUDY ON NEW PRODUCT DEVELOPMENT PROCESS BY NONPARAMETRIC COMBINATION (NPC) TESTING METHODOLOGY AND POST-STRATIFICATION

In many scientific disciplines and industrial fields researchers and practitioners are often faced with complex problems when dealing with comparisons between two or more groups using classical parametric methods although real problems rarely agree with the stringent assumptions required by such methods. The NPC methodology (Pesarin, 2001) offers an innovative but well tested approach that frees the researcher from stringent assumptions of parametric method

Sample size determination for multivariate performance analysis with complex designs

In this paper three methods to produce a performance ranking of C treatments are taken into account. By means of a simulation study, it is possible to calculate the percentages of correct classifications of the compared methods and study their performances. This study also allows us to determine the minimum sample size useful for detecting performance differences among treatments