Neural Dynamics of Motion Perception: Direction Fields, Apertures, and Resonant Grouping

A neural network model of global motion segmentation by visual cortex is described. Called the Motion Boundary Contour System (BCS), the model clarifies how ambiguous local movements on a complex moving shape are actively reorganized into a coherent global motion signal. Unlike many previous researchers, we analyse how a coherent motion signal is imparted to all regions of a moving figure, not only to regions at which unambiguous motion signals exist. The model hereby suggests a solution to the global aperture problem. The Motion BCS describes how preprocessing of motion signals by a Motion Oriented Contrast Filter (MOC Filter) is joined to long-range cooperative grouping mechanisms in a Motion Cooperative-Competitive Loop (MOCC Loop) to control phenomena such as motion capture. The Motion BCS is computed in parallel with the Static BCS of Grossberg and Mingolla (1985a, 1985b, 1987). Homologous properties of the Motion BCS and the Static BCS, specialized to process movement directions and static orientations, respectively, support a unified explanation of many data about static form perception and motion form perception that have heretofore been unexplained or treated separately. Predictions about microscopic computational differences of the parallel cortical streams V1 --> MT and V1 --> V2 --> MT are made, notably the magnocellular thick stripe and parvocellular interstripe streams. It is shown how the Motion BCS can compute motion directions that may be synthesized from multiple orientations with opposite directions-of-contrast. Interactions of model simple cells, complex cells, hypercomplex cells, and bipole cells are described, with special emphasis given to new functional roles in direction disambiguation for endstopping at multiple processing stages and to the dynamic interplay of spatially short-range and long-range interactions.Air Force Office of Scientific Research (90-0175); Defense Advanced Research Projects Agency (90-0083); Office of Naval Research (N00014-91-J-4100

A Self-Organizing Neural System for Learning to Recognize Textured Scenes

A self-organizing ARTEX model is developed to categorize and classify textured image regions. ARTEX specializes the FACADE model of how the visual cortex sees, and the ART model of how temporal and prefrontal cortices interact with the hippocampal system to learn visual recognition categories and their names. FACADE processing generates a vector of boundary and surface properties, notably texture and brightness properties, by utilizing multi-scale filtering, competition, and diffusive filling-in. Its context-sensitive local measures of textured scenes can be used to recognize scenic properties that gradually change across space, as well a.s abrupt texture boundaries. ART incrementally learns recognition categories that classify FACADE output vectors, class names of these categories, and their probabilities. Top-down expectations within ART encode learned prototypes that pay attention to expected visual features. When novel visual information creates a poor match with the best existing category prototype, a memory search selects a new category with which classify the novel data. ARTEX is compared with psychophysical data, and is benchmarked on classification of natural textures and synthetic aperture radar images. It outperforms state-of-the-art systems that use rule-based, backpropagation, and K-nearest neighbor classifiers.Defense Advanced Research Projects Agency; Office of Naval Research (N00014-95-1-0409, N00014-95-1-0657

Contour Integration Across Polarities and Spatial Gaps: From Local Contrast Filtering to Global Grouping

This article introduces an experimental paradigm to selectively probe the multiple levels of visual processing that influence the formation of object contours, perceptual boundaries, and illusory contours. The experiments test the assumption that, to integrate contour information across space and contrast sign, a spatially short-range filtering process that is sensitive to contrast polarity inputs to a spatially long-range grouping process that pools signals from opposite contrast polarities. The stimuli consisted of thin subthreshold lines, flashed upon gaps between collinear inducers which potentially enable the formation of illusory contours. The subthreshold lines were composed of one or more segments with opposite contrast polarities. The polarity nearest to the inducers was varied to differentially excite the short-range filtering process. The experimental results are consistent with neurophysiological evidence for cortical mechanisms of contour processing and with the Boundary Contour System model, which identifies the short-range filtering process with cortical simple cells, and the long-range grouping process with cortical bipole cells.Office of Naval Research (N00014-95-1-0409, N00014-95-1-0657); Centre National de la Recherche Scientifique (France) URA (1939

Shear-stress controlled dynamics of nematic complex fluids

Based on a mesoscopic theory we investigate the non-equilibrium dynamics of a sheared nematic liquid, with the control parameter being the shear stress $\sigma_{\mathrm{xy}}$ (rather than the usual shear rate, $\dot\gamma$). To this end we supplement the equations of motion for the orientational order parameters by an equation for $\dot\gamma$, which then becomes time-dependent. Shearing the system from an isotropic state, the stress- controlled flow properties turn out to be essentially identical to those at fixed $\dot\gamma$. Pronounced differences when the equilibrium state is nematic. Here, shearing at controlled $\dot\gamma$ yields several non-equilibrium transitions between different dynamic states, including chaotic regimes. The corresponding stress-controlled system has only one transition from a regular periodic into a stationary (shear-aligned) state. The position of this transition in the $\sigma_{\mathrm{xy}}$-$\dot\gamma$ plane turns out to be tunable by the delay time entering our control scheme for $\sigma_{\mathrm{xy}}$. Moreover, a sudden change of the control method can {\it stabilize} the chaotic states appearing at fixed $\dot\gamma$.Comment: 10 pages, 11 figure

Multi-scale statistics of turbulence motorized by active matter

A number of micro-scale biological flows are characterized by spatio-temporal chaos. These include dense suspensions of swimming bacteria, microtubule bundles driven by motor proteins, and dividing and migrating confluent layers of cells. A characteristic common to all of these systems is that they are laden with active matter, which transforms free energy in the fluid into kinetic energy. Because of collective effects, the active matter induces multi-scale flow motions that bear strong visual resemblance to turbulence. In this study, multi-scale statistical tools are employed to analyze direct numerical simulations (DNS) of periodic two- (2D) and three-dimensional (3D) active flows and compare them to classic turbulent flows. Statistical descriptions of the flows and their variations with activity levels are provided in physical and spectral spaces. A scale-dependent intermittency analysis is performed using wavelets. The results demonstrate fundamental differences between active and high-Reynolds number turbulence; for instance, the intermittency is smaller and less energetic in active flows, and the work of the active stress is spectrally exerted near the integral scales and dissipated mostly locally by viscosity, with convection playing a minor role in momentum transport across scales.Comment: Accepted in Journal of Fluid Mechanics (2017

Direct observation of micron-scale ordered structure in a two-dimensional electron system

We have applied a novel scanned probe method to directly resolve the interior structure of a GaAs/AlGaAs two-dimensional electron system in a tunneling geometry. We find that the application of a perpendicular magnetic field can induce surprising density modulations that are not static as a function of the field. Near six and four filled Landau levels, stripe-like structures emerge with a characteristic wave length ~2 microns. Present theories do not account for ordered density modulations on this length scale.Comment: 5 pages, 4 figures. To appear in Phys. Rev.

Tuning the structure of non-equilibrium soft materials by varying the thermodynamic driving force for crystal ordering

The official published version of the Article can be accessed from the link below - Copyright @ 2010 Royal Society of ChemistryThe present work explores the ubiquitous morphological changes in crystallizing systems with increasing thermodynamic driving force based on a novel dynamic density functional theory. A colloidal ‘soft’ material is chosen as a model system for our investigation since there are careful colloidal crystallization observations at a particle scale resolution for comparison, which allows for a direct verification of our simulation predictions. We particularly focus on a theoretically unanticipated, and generic, morphological transition leading to progressively irregular-shaped single crystals in both colloidal and polymeric materials with an increasing thermodynamic driving force. Our simulation method significantly extends previous ‘phase field’ simulations by incorporating a minimal description of the ‘atomic’ structure of the material, while allowing simultaneously for a description of large scale crystal growth. We discover a ‘fast’ mode of crystal growth at high driving force, suggested before in experimental colloidal crystallization studies, and find that the coupling of this crystal mode to the well-understood ‘diffusive’ or ‘slow’ crystal growth mode (giving rise to symmetric crystal growth mode and dendritic crystallization as in snowflakes by the Mullins–Sekerka instability) can greatly affect the crystal morphology at high thermodynamic driving force. In particular, an understanding of this interplay between these fast and slow crystal growth modes allows us to describe basic crystallization morphologies seen in both colloidal suspensions with increasing particle concentration and crystallizing polymer films with decreasing temperature: compact symmetric crystals, dendritic crystals, fractal-like structures, and then a return to compact symmetric single crystal growth again.This work has been supported by the EU FP7 Collaborative Project ENSEMBLE under Grant Agreement NMP4-SL-2008-213669 and by the Hungarian Academy of Sciences under contract OTKA-K-62588

Correlation between crystalline order and vitrification in colloidal monolayers

We investigate experimentally the relationship between local structure and dynamical arrest in a quasi-2d colloidal model system which approximates hard discs. We introduce polydispersity to the system to suppress crystallisation. Upon compression, the increase in structural relaxation time is accompanied by the emergence of local hexagonal symmetry. Examining the dynamical heterogeneity of the system, we identify three types of motion : "zero-dimensional" corresponding to beta-relaxation, "one-dimensional" or stringlike motion and "two-dimensional" motion. The dynamic heterogeneity is correlated with the local order, that is to say locally hexagonal regions are more likely to be dynamically slow. However we find that lengthscales corresponding to dynamic heterogeneity and local structure do not appear to scale together approaching the glass transition.Comment: 13 papes, to appear in J. Phys.: Condens. Matte