Predicting the connectivity of primate cortical networks from topological and spatial node properties

The organization of the connectivity between mammalian cortical areas has become a major subject of study, because of its important role in scaffolding the macroscopic aspects of animal behavior and intelligence. In this study we present a computational reconstruction approach to the problem of network organization, by considering the topological and spatial features of each area in the primate cerebral cortex as subsidy for the reconstruction of the global cortical network connectivity. Starting with all areas being disconnected, pairs of areas with similar sets of features are linked together, in an attempt to recover the original network structure. Inferring primate cortical connectivity from the properties of the nodes, remarkably good reconstructions of the global network organization could be obtained, with the topological features allowing slightly superior accuracy to the spatial ones. Analogous reconstruction attempts for the C. elegans neuronal network resulted in substantially poorer recovery, indicating that cortical area interconnections are relatively stronger related to the considered topological and spatial properties than neuronal projections in the nematode. The close relationship between area-based features and global connectivity may hint on developmental rules and constraints for cortical networks. Particularly, differences between the predictions from topological and spatial properties, together with the poorer recovery resulting from spatial properties, indicate that the organization of cortical networks is not entirely determined by spatial constraints

Two-pion exchange NN potential from Lorentz-invariant χ\chiEFT

We outline the progress made in the past five years by the S\~ao Paulo group in the development of a two-pion exchange nucleon-nucleon potential within a Lorentz-invariant framework of (baryon) chiral perturbation theory.Comment: 5 pages, Talk given at the 18th International IUPAP Conference on Few-Body Problems in Physics, August 21-26 2006, Santos, Sao Paulo, Brazi

João e Maria: realidade socioeconômica no conto tradicional e no reconto contemporâneo

Os contos de fadas são obras clássicas que permanecem vivas ao longo do tempo, seja por meio de versões ―originais‖, adaptações ou releituras. O presente artigo apresenta um estudo do conto clássico João e Maria e da releitura Joãozinho e Maria (2013), adaptação de Cristina Agostinho e Ronaldo Simões Coelho, ilustrações de Walter Lara. Buscar-se-á destacar um diálogo entre as obras e relacionar fatos narrados em contos tradicionais e contemporâneos com a realidade socioeconômica. Nesse sentido, pretende-se destacar o papel dos mediadores de leitura em relação à seleção de obras literárias infantis que privilegiem o segmento étnico e estabeleçam a aproximação das crianças ao imaginário cultural, com histórias ambientadas no cenário brasileiro. Para tanto, será utilizada, como base teórica, sobretudo Histórias que os camponeses contam: o significado de Mamãe Ganso de Robert Darnton (2011) e a obra Conto e Reconto: das fontes à invenção, organizado por Vera Teixeira de Aguiar e Alice Áurea Penteado Martha (2012).Los cuentos de fadas son obras clásicas que permanecen vivas al largo del tiempo, sea por medio de versiones ―originales‖, adaptaciones o relecturas. El presente artículo presenta un estudio del cuento clásico João y Maria y de la relectura Joãozinho e Maria (2013), adaptación de Cristina Agostinho y Ronaldo Simões Coelho, ilustraciones de Walter Lara. Buscar-se-á destacar un diálogo entre las obras y relacionar hechos narrados en cuentos tradicionales y contemporáneos con la realidad socioeconómica. En ese sentido, se pretende destacar el papel de los mediadores de lectura en relación a la selección de obras literarias infantiles que privilegien el segmento étnico y establezcan la aproximación de los niños al imaginario cultural, con historias ambientadas en el escenario brasileño. Para tanto, será utilizada, como base teórica, sobre todo Histórias que os camponeses contam: o significado de Mamãe Ganso de Robert Darnton (2011) e a obra Conto e Reconto: das fontes à invenção de Vera Teixeira de Aguiar e Alice Áurea Penteado Martha (2012)Universidade Federal da Integração Latino Americana (UNILA-PR) e Universidade Estadual do Oeste do Paraná (UNIOESTE-PR

BAYESIAN ANALYSIS OF TWO STELLAR POPULATIONS IN GALACTIC GLOBULAR CLUSTERS I: STATISTICAL AND COMPUTATIONAL METHODS

We develop a Bayesian model for globular clusters composed of multiple stellar populations, extending earlier statistical models for open clusters composed of simple (single) stellar populations (e.g., van Dyk et al. 2009; Stein et al. 2013). Specifically, we model globular clusters with two populations that differ in helium abundance. Our model assumes a hierarchical structuring of the parameters in which physical properties—age, metallicity, helium abundance, distance, absorption, and initial mass—are common to (i) the cluster as a whole or to (ii) individual populations within a cluster, or are unique to (iii) individual stars. An adaptive Markov chain Monte Carlo (MCMC) algorithm is devised for model fitting that greatly improves convergence relative to its precursor non-adaptive MCMC algorithm. Our model and computational tools are incorporated into an open-source software suite known as BASE-9. We use numerical studies to demonstrate that our method can recover parameters of two-population clusters, and also show model misspecification can potentially be identified. As a proof of concept, we analyze the two stellar populations of globular cluster NGC 5272 using our model and methods. (BASE-9 is available from GitHub: https://github.com/argiopetech/base/releases)

What are the Best Hierarchical Descriptors for Complex Networks?

This work reviews several hierarchical measurements of the topology of complex networks and then applies feature selection concepts and methods in order to quantify the relative importance of each measurement with respect to the discrimination between four representative theoretical network models, namely Erd\"{o}s-R\'enyi, Barab\'asi-Albert, Watts-Strogatz as well as a geographical type of network. The obtained results confirmed that the four models can be well-separated by using a combination of measurements. In addition, the relative contribution of each considered feature for the overall discrimination of the models was quantified in terms of the respective weights in the canonical projection into two dimensions, with the traditional clustering coefficient, hierarchical clustering coefficient and neighborhood clustering coefficient resulting particularly effective. Interestingly, the average shortest path length and hierarchical node degrees contributed little for the separation of the four network models.Comment: 9 pages, 4 figure

A Higher-Order Calculation of npnp Scattering in Cut-Off Effective Field Theory

We report a next-to-leading-order (NLO) chiral perturbation theory calculation of the neutron-proton scattering cross section in the ${}^1S_0$ channel using a cut-off regularization. The inclusion of two-pion exchanges in the irreducible diagrams -- or potential -- figuring at NLO is found to be important in enlarging the domain of validity of the effective field theory. We are able to reproduce the {\it empirical} scattering phase shift up to p=300 MeV -- which is comparable to the cutoff scale involved -- with an agreement which is superior to results of other effective field theory approaches. We also discuss the role of the cutoff as a renormalization prescription and the importance of the explicit pion degree of freedom in scattering process.Comment: Substantial changes made in texts and Fig.2. To appear in Phys. Lett.

Neural development features: Spatio-temporal development of the Caenorhabditis elegans neuronal network

The nematode Caenorhabditis elegans, with information on neural connectivity, three-dimensional position and cell linage provides a unique system for understanding the development of neural networks. Although C. elegans has been widely studied in the past, we present the first statistical study from a developmental perspective, with findings that raise interesting suggestions on the establishment of long-distance connections and network hubs. Here, we analyze the neuro-development for temporal and spatial features, using birth times of neurons and their three-dimensional positions. Comparisons of growth in C. elegans with random spatial network growth highlight two findings relevant to neural network development. First, most neurons which are linked by long-distance connections are born around the same time and early on, suggesting the possibility of early contact or interaction between connected neurons during development. Second, early-born neurons are more highly connected (tendency to form hubs) than later born neurons. This indicates that the longer time frame available to them might underlie high connectivity. Both outcomes are not observed for random connection formation. The study finds that around one-third of electrically coupled long-range connections are late forming, raising the question of what mechanisms are involved in ensuring their accuracy, particularly in light of the extremely invariant connectivity observed in C. elegans. In conclusion, the sequence of neural network development highlights the possibility of early contact or interaction in securing long-distance and high-degree connectivity