Developmental time windows for axon growth influence neuronal network topology

Early brain connectivity development consists of multiple stages: birth of neurons, their migration and the subsequent growth of axons and dendrites. Each stage occurs within a certain period of time depending on types of neurons and cortical layers. Forming synapses between neurons either by growing axons starting at similar times for all neurons (much-overlapped time windows) or at different time points (less-overlapped) may affect the topological and spatial properties of neuronal networks. Here, we explore the extreme cases of axon formation especially concerning short-distance connectivity during early development, either starting at the same time for all neurons (parallel, i.e. maximally-overlapped time windows) or occurring for each neuron separately one neuron after another (serial, i.e. no overlaps in time windows). For both cases, the number of potential and established synapses remained comparable. Topological and spatial properties, however, differed: neurons that started axon growth early on in serial growth achieved higher out-degrees, higher local efficiency, and longer axon lengths while neurons demonstrated more homogeneous connectivity patterns for parallel growth. Second, connection probability decreased more rapidly with distance between neurons for parallel growth than for serial growth. Third, bidirectional connections were more numerous for parallel growth. Finally, we tested our predictions with C. elegans data. Together, this indicates that time windows for axon growth influence the topological and spatial properties of neuronal networks opening the possibility to a posteriori estimate developmental mechanisms based on network properties of a developed network.Comment: Biol Cybern. 2015 Jan 30. [Epub ahead of print

Multidimensional Membership Mixture Models

We present the multidimensional membership mixture (M3) models where every dimension of the membership represents an independent mixture model and each data point is generated from the selected mixture components jointly. This is helpful when the data has a certain shared structure. For example, three unique means and three unique variances can effectively form a Gaussian mixture model with nine components, while requiring only six parameters to fully describe it. In this paper, we present three instantiations of M3 models (together with the learning and inference algorithms): infinite, finite, and hybrid, depending on whether the number of mixtures is fixed or not. They are built upon Dirichlet process mixture models, latent Dirichlet allocation, and a combination respectively. We then consider two applications: topic modeling and learning 3D object arrangements. Our experiments show that our M3 models achieve better performance using fewer topics than many classic topic models. We also observe that topics from the different dimensions of M3 models are meaningful and orthogonal to each other.Comment: 9 pages, 7 figure

Learning to Place New Objects

The ability to place objects in the environment is an important skill for a personal robot. An object should not only be placed stably, but should also be placed in its preferred location/orientation. For instance, a plate is preferred to be inserted vertically into the slot of a dish-rack as compared to be placed horizontally in it. Unstructured environments such as homes have a large variety of object types as well as of placing areas. Therefore our algorithms should be able to handle placing new object types and new placing areas. These reasons make placing a challenging manipulation task. In this work, we propose a supervised learning algorithm for finding good placements given the point-clouds of the object and the placing area. It learns to combine the features that capture support, stability and preferred placements using a shared sparsity structure in the parameters. Even when neither the object nor the placing area is seen previously in the training set, our algorithm predicts good placements. In extensive experiments, our method enables the robot to stably place several new objects in several new placing areas with 98% success-rate; and it placed the objects in their preferred placements in 92% of the cases

Integrating anticipative replenishment-allocation with reactive fulfillment for online retailing using robust optimization

Ministry of Education, Singapore under its Academic Research Funding Tier 1; Lee Kong Chian Fellowship; MPA Research Fellowshi

VISUAL-PERCEPTUAL-MOTOR SKILLS OF ELITE SILAT ATHLETES WHEN RESPONDING TO VARIOUS COMBAT SITUATIONS THROUGH AN INTEGRATED STEREOSCOPIC SYSTEM

Understanding the visual-perceptual-motor skill of an athlete can help optimize the periodization of a training plan. This study was designed to explore the visual-perceptual-motor skill of ten male elite Silat athlete when tasked to react to a set of projected video stimuli comprised of specific combat attack situations; side kicks, roundhouse kicks and crocodiles. A customized stereoscopic video system projected the stimuli in two- and three-dimensions with the latter being added with the aim of improving combat realism. This system synchronously recorded the gaze and movement behaviours of the participants when they responded to the combat situations. No differences in visual search behaviour, quiet eye and reaction time were found when tasked to respond between two- and three-dimensional videos, which may be due to the complexity of the stimulus. There was a significantly higher quantity and longer duration of fixations spent on the trunk of the opponent as compared to other areas of the body. Reaction time was also significantly different in the side kicks (slower responses) as compared to other attacks. Results from this study can pave way for future studies that seek to investigate how visual-perceptual-motor skill differs between expertise levels in the sport of Silat and serve as a basis for targeted coaching to enhance combat Silat performance

Effect of hydrogen bonding and complexation with metal ions on the fluorescence of luotonin A

Fluorescence characteristics of a biologically active natural alkaloid, luotonin A (LuA), were studied by steady-state and time-resolved spectroscopic methods. The rate constant of the radiationless deactivation from the singlet-excited state diminished by more than one order of magnitude when the solvent polarity was changed from toluene to water. Dual emission was found in polyfluorinated alcohols of large hydrogen bond donating ability due to photoinitiated proton displacement along the hydrogen bond. In CH 2Cl2, LuA produced both 1:1 and 1:2 hydrogen-bonded complexes with hexafluoro-2-propanol (HFIP) in the ground state. Photoexcitation of the 1:2 complex led to protonated LuA, whose fluorescence appeared at a long wavelength. LuA served as a bidentate ligand forming 1:1 complexes with metal ions in acetonitrile. The stability of the complexes diminished in the series of Cd2+ > Zn2+ > Ag+, and upon competitive binding of water to the metal cations. The effect of chelate formation on the fluorescent properties was revealed. © 2013 The Royal Society of Chemistry and Owner Societies