Means to an end: Neotropical parrots manage to pull strings to meet their goals

Although parrots share with corvids and primates many of the traits believed to be associated with advanced cognitive processing, knowledge of parrot cognition is still limited to a few species, none of which are Neotropical. Here we examine the ability of three Neotropical parrot species (Blue-Fronted Amazons, Hyacinth and Lear`s macaws) to spontaneously solve a novel physical problem: the string-pulling test. The ability to pull up a string to obtain out-of-reach food has been often considered a cognitively complex task, as it requires the use of a sequence of actions never previously assembled, along with the ability to continuously monitor string, food and certain body movements. We presented subjects with pulling tasks where we varied the spatial relationship between the strings, the presence of a reward and the physical contact between the string and reward to determine whether (1) string-pulling is goal-oriented in these parrots, (2) whether the string is recognized as a means to obtain the reward and (3) whether subjects can visually determine the continuity between the string and the reward, selecting only those strings for which no physical gaps between string and reward were present. Our results show that some individuals of all species were able to use the string as a means to reach a specific goal, in this case, the retrieval of the food treat. Also, subjects from both macaw species were able to visually determine the presence of physical continuity between the string and reward, making their choices consistently with the recognition that no gaps should be present between the string and the reward. Our findings highlight the potential of this taxonomic group for the understanding of the underpinnings of cognition in evolutionarily distant groups such as birds and primates.

Combinatorial-topological framework for the analysis of global dynamics

We discuss an algorithmic framework based on efficient graph algorithms and algebraic-topological computational tools. The framework is aimed at automatic computation of a database of global dynamics of a given m-parameter semidynamical system with discrete time on a bounded subset of the n-dimensional phase space. We introduce the mathematical background, which is based upon Conley's topological approach to dynamics, describe the algorithms for the analysis of the dynamics using rectangular grids both in phase space and parameter space, and show two sample applications. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4767672]

Reproducing kernel Hilbert spaces associated with kernels on topological spaces

We analyze reproducing kernel Hilbert spaces of positive definite kernels on a topological space X being either first countable or locally compact. The results include versions of Mercer's theorem and theorems on the embedding of these spaces into spaces of continuous and square integrable functions.

QUASI-TOPOLOGICAL QUANTUM FIELD THEORIES AND Z(2) LATTICE GAUGE THEORIES

We consider a two-parameter family of Z(2) gauge theories on a lattice discretization T(M) of a three-manifold M and its relation to topological field theories. Familiar models such as the spin-gauge model are curves on a parameter space Gamma. We show that there is a region Gamma(0) subset of Gamma where the partition function and the expectation value h < W-R(gamma)> i of the Wilson loop can be exactly computed. Depending on the point of Gamma(0), the model behaves as topological or quasi-topological. The partition function is, up to a scaling factor, a topological number of M. The Wilson loop on the other hand, does not depend on the topology of gamma. However, for a subset of Gamma(0), < W-R(gamma)> depends on the size of gamma and follows a discrete version of an area law. At the zero temperature limit, the spin-gauge model approaches the topological and the quasi-topological regions depending on the sign of the coupling constant.

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

Abstract Background 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. Results 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. Conclusion 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.