Learning Behavioural Context

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Action Recognition with a Bio--Inspired Feedforward Motion Processing Model: The Richness of Center-Surround Interactions

International audienceHere we show that reproducing the functional properties of MT cells with various center--surround interactions enriches motion representation and improves the action recognition performance. To do so, we propose a simplified bio--inspired model of the motion pathway in primates: It is a feedforward model restricted to V1-MT cortical layers, cortical cells cover the visual space with a foveated structure, and more importantly, we reproduce some of the richness of center-surround interactions of MT cells. Interestingly, as observed in neurophysiology, our MT cells not only behave like simple velocity detectors, but also respond to several kinds of motion contrasts. Results show that this diversity of motion representation at the MT level is a major advantage for an action recognition task. Defining motion maps as our feature vectors, we used a standard classification method on the Weizmann database: We obtained an average recognition rate of 98.9%, which is superior to the recent results by Jhuang et al. (2007). These promising results encourage us to further develop bio--inspired models incorporating other brain mechanisms and cortical layers in order to deal with more complex videos

Continuation for thin film hydrodynamics and related scalar problems

This chapter illustrates how to apply continuation techniques in the analysis of a particular class of nonlinear kinetic equations that describe the time evolution through transport equations for a single scalar field like a densities or interface profiles of various types. We first systematically introduce these equations as gradient dynamics combining mass-conserving and nonmass-conserving fluxes followed by a discussion of nonvariational amendmends and a brief introduction to their analysis by numerical continuation. The approach is first applied to a number of common examples of variational equations, namely, Allen-Cahn- and Cahn-Hilliard-type equations including certain thin-film equations for partially wetting liquids on homogeneous and heterogeneous substrates as well as Swift-Hohenberg and Phase-Field-Crystal equations. Second we consider nonvariational examples as the Kuramoto-Sivashinsky equation, convective Allen-Cahn and Cahn-Hilliard equations and thin-film equations describing stationary sliding drops and a transversal front instability in a dip-coating. Through the different examples we illustrate how to employ the numerical tools provided by the packages auto07p and pde2path to determine steady, stationary and time-periodic solutions in one and two dimensions and the resulting bifurcation diagrams. The incorporation of boundary conditions and integral side conditions is also discussed as well as problem-specific implementation issues

Classification of mesic grasslands and their transitions of South Transdanubia (Hungary)

Relevés from meadows and pastures of South Transdanubia (Hungary) are evaluated by clustering and ordination methods. The relevé selection focused on the Arrhenatheretalia order but its transitions towards other types were also included. The groups of relevés are delimited and described according to differential, dominant and constant species. Ecological conditions of the groups were compared using indicator values. Nine groups were distinguished, four of them belonging strictly to the order Arrhenatheretalia. Each alliance of Arrhenatheretalia presented in the study area (Cynosurion, Arrhenatherion) was represented by two groups. Groups from these two alliances are separated along a light gradient, while groups of the same alliance differ in nutrient values. Within Cynosurion, the nutrient-poor group cannot be identified unambiguously as any syntaxa previously known from Hungary. The nutrient-rich Cynosurion meadows are similar to Lolio–Cynosuretum, however, they show a stronger relationship with wet meadows. Within Arrhenatherion, Pastinaco–Arrhenatheretum is recognised as a hay meadow of nutrient-rich soils. The other meadow type is similar to Filipendulo–Arrhenatheretum, thus raising syntaxonomical problems. There are transitional groups towards semi-dry and wet meadows, one dynamic phase and one outlier group among the other five clusters

De novo mutations in GRIN1 cause extensive bilateral polymicrogyria

Polymicrogyria is a malformation of cortical development. The aetiology of polymicrogyria remains poorly understood. Using whole-exome sequencing we found de novo heterozygous missense GRIN1 mutations in 2 of 57 parent-offspring trios with polymicrogyria. We found nine further de novo missense GRIN1 mutations in additional cortical malformation patients. Shared features in the patients were extensive bilateral polymicrogyria associated with severe developmental delay, postnatal microcephaly, cortical visual impairment and intractable epilepsy. GRIN1 encodes GluN1, the essential subunit of the N-methyl-d-aspartate receptor. The polymicrogyria-associated GRIN1 mutations tended to cluster in the S2 region (part of the ligand-binding domain of GluN1) or the adjacent M3 helix. These regions are rarely mutated in the normal population or in GRIN1 patients without polymicrogyria. Using two-electrode and whole-cell voltage-clamp analysis, we showed that the polymicrogyria-associated GRIN1 mutations significantly alter the in vitro activity of the receptor. Three of the mutations increased agonist potency while one reduced proton inhibition of the receptor. These results are striking because previous GRIN1 mutations have generally caused loss of function, and because N-methyl-d-aspartate receptor agonists have been used for many years to generate animal models of polymicrogyria. Overall, our results expand the phenotypic spectrum associated with GRIN1 mutations and highlight the important role of N-methyl-d-aspartate receptor signalling in the pathogenesis of polymicrogyria

Distribution of plant communities, ecological strategy types and diversity along a moisture gradient

The influence of water regime on the zonation of wetland communities, distribution patterns of plant species, ecological strategies and biodiversity, was studied in this work. Vegetation of the herbaceous wetland was sampled along a transect, in accordance with the standard central European method. Water level was also measured. The changes in plant species composition, plant functional types (ecological strategies, life forms) and diversity were studied. Classification of vegetation relevés enabled the definition of five grassland communities. The same pattern remained in DCA ordination also when the species matrix was replaced with a matrix of ecological strategies. Relevés were always segregated into distinct plant communities and distributed along the moisture gradient in the same way. Biodiversity is strongly negatively correlated with moisture-it is decreasing with decreasing ground level. Plant ecological strategy types (C-S-R) change significantly along the transect as well. In communities thriving on the driest sites ( Triseto-Centaureetum ), there are three times more C-than C-S-strategists, while in the wettest sites ( Caricetum elatae ) C-S-strategists predominate over C-strategists by almost two times. At the same time Rand C-R-strategists, as well as therophytes, which are present in drier sites almost disappear in the wettest sites. We show that the moisture gradient essentially influences the distribution pattern of plant communities, species diversity, and manifestation of certain ecological strategy types