Visual motion processing and human tracking behavior

The accurate visual tracking of a moving object is a human fundamental skill that allows to reduce the relative slip and instability of the object's image on the retina, thus granting a stable, high-quality vision. In order to optimize tracking performance across time, a quick estimate of the object's global motion properties needs to be fed to the oculomotor system and dynamically updated. Concurrently, performance can be greatly improved in terms of latency and accuracy by taking into account predictive cues, especially under variable conditions of visibility and in presence of ambiguous retinal information. Here, we review several recent studies focusing on the integration of retinal and extra-retinal information for the control of human smooth pursuit.By dynamically probing the tracking performance with well established paradigms in the visual perception and oculomotor literature we provide the basis to test theoretical hypotheses within the framework of dynamic probabilistic inference. We will in particular present the applications of these results in light of state-of-the-art computer vision algorithms

Biological model of motion integration and segmentation based on form cues

Active vision is an essential part of every biological organism possessing an eye system: posture, eye movements, visual research, ... All require a motion percept to operate. At the basis of active vision lays the ability to calculate movements of objects in the scene, at least on a sufficient level to react correctly. In this report we present a model of motion integration and segmentation in the first visual cortex areas. Specifically we modeled the first two cortex areas involved in motion processing in the primate: V1 and MT. To be able to process motion correctly a visual system also need to deal with form information. We investigate how form cues coming from the ventral pathway can be used by the V1/MT dorsal pathway to solve some perception problems. By using a recurrent dynamical system between the V1 and MT layers we are able to find out psychophysical results such as motion integration and center-surround effects due to the feedback connections, or end-of-line and 2D features detectors thanks to the shunting inhibition. We propose to modulate this system by a form information coming from the ventral stream and are thus able to explain asymmetric center-surround effects as well as motion segmentation and segregation between extrinsic and intrinsic junctions

Motion clouds: model-based stimulus synthesis of natural-like random textures for the study of motion perception

Choosing an appropriate set of stimuli is essential to characterize the response of a sensory system to a particular functional dimension, such as the eye movement following the motion of a visual scene. Here, we describe a framework to generate random texture movies with controlled information content, i.e., Motion Clouds. These stimuli are defined using a generative model that is based on controlled experimental parametrization. We show that Motion Clouds correspond to dense mixing of localized moving gratings with random positions. Their global envelope is similar to natural-like stimulation with an approximate full-field translation corresponding to a retinal slip. We describe the construction of these stimuli mathematically and propose an open-source Python-based implementation. Examples of the use of this framework are shown. We also propose extensions to other modalities such as color vision, touch, and audition

Motion integration modulated by form information

ISBN : 978-2-9532965-0-1We propose a model of motion integration modulated by form information, inspired by neurobiological data. Our dynamical system models several key features of the motion processing stream in primate visual cortex. Thanks to a multi-layer architecture incorporating both feedforward-feedback and inhibitive lateral connections, our model is able to solve local motion ambiguities. One important feature of our model is to propose an anitropic integration of motion based on the form information. Our model can be implemented efficiently on GPU and we show its properties on classical psychophysical examples. First, a simple read-out allows us to reproduce the dynamics of ocular following for a moving bar stimulus. Second, we show how our models able to discriminate between extrinsic and intrinsic junctions present in the chopstick illusion. Finally, we show some promising results on real videos

Modelling the dynamics of motion integration with a new luminance-gated diffusion mechanism

The dynamics of motion integration show striking similarities when observed at neuronal, psychophysical, and oculomotor levels. Based on the inter-relation and complementary insights given by those dynamics, our goal was to test how basic mechanisms of dynamical cortical processing can be incorporated in a dynamical model to solve several aspects of 2D motion integration and segmentation. Our model is inspired by the hierarchical processing stages of the primate visual cortex: we describe the interactions between several layers processing local motion and form information through feedforward, feedback, and inhibitive lateral connections. Also, following perceptual studies concerning contour integration and physiological studies of receptive fields, we postulate that motion estimation takes advantage of another low level cue, which is luminance smoothness along edges or surfaces, in order to gate recurrent motion diffusion. With such a model, we successfully reproduced the temporal dynamics of motion integration on a wide range of simple motion stimuli: line segments, rotating ellipses, plaids, and barber poles. Furthermore, we showed that the proposed computational rule of luminance-gated diffusion of motion information is sufficient to explain a large set of contextual modulations of motion integration and segmentation in more elaborated stimuli such as chopstick illusions, simulated aperture problems, or rotating diamonds. As a whole, in this paper we proposed a new basal luminance-driven motion integration mechanism as an alternative to less parsimonious models, we carefully investigated the dynamics of motion integration, and we established a distinction between simple and complex stimuli according to the kind of information required to solve their ambiguities

Лечение и реабилитация детей с аллергическими заболеваниями

аллергические заболеванияАСТМА БРОНХИАЛЬНАЯДЕТИциклоферонгипооксибаротерапияреабилитация дете

IdeaValuation : Favoriser les échanges lors d'un atelier de créativité par le vote qualitatif des idées à l'aide d'un outil numérique

International audienceIn the context of the emergence of collaborative innovation projects, the animation of creative sessions permits to identify new opportunities. The number of ideas generated is a lot more important than the number of collaborative projects implemented. To improve this ratio, we assume that group discussions could be facilitated by the cleavage of opinions about the quality of the ideas discussed during the meeting. We support our approach with a digital tool to promote information feedback throughout the session.Dans le cadre de l'émergence de projets collaboratifs d'innovation, l'animation de séance de créativité permet d'identifier de nouvelles opportunités. Généralement, le nombre d'idées générées est bien plus important que le nombre de suites données (e.g. étude, lancement et montage de projets associés). Afin d'améliorer ce ratio, nous faisons les hypothèses que d'une part les évaluations et discussions en groupe sur les idées proposées pourraient être facilitées, et d'autre part que la singularité d'opinions concernant la qualité des idées évoquées en séance peut être facilitateur d'échanges. Pour cela, nous appuyons notre démarche par un outil numérique pour réaliser le partage d'informations des évaluations tout au long de la séance de créativité

A bee in the corridor: centering and wall-following

International audienceIn an attempt to better understand the mechanism underlying lateral collision avoidance in 7 flying insects, we trained honeybees (Apis mellifera) to fly through a large (95cm-wide) flight 8 tunnel. We found that depending on the entrance and feeder positions, honeybees would 9 either center along the corridor midline or fly along one wall. Bees kept following one wall 10 even when a major (150cm-long) part of the opposite wall was removed. These findings 11 cannot be accounted for by the 'optic flow balance' hypothesis that has been put forward to 12 explain the typical bees' 'centering response' observed in narrower corridors. Both centering 13 and wall-following behaviours are well accounted for, however, by a mechanism called the 14 lateral optic flow regulator, i.e., a feedback system that strives to maintain the unilateral optic 15 flow constant. The power of this mechanism is that it would allow the bee to guide itself 16 visually in a corridor without having to measure its speed or distance from the walls

Functional properties of feed-forward inhibition

ISBN : 978-2-9532965-0-1Neurons receive a large number of excitatory and inhibitory synaptic inputs whose temporal interplay determines the spiking behavior. On average, excitation and inhibition balance each other, such that spikes are elicited by fluctuations. In addition, it has been shown in vivo that excitation and inhibition are correlated, with inhibition lagging excitation only by few milliseconds (~6 ms), creating a small temporal integration window. This correlation structure could be induced by feed-forward inhibition (FFI), which has been shown to be present at many sites in the central nervous system. To characterize the functional properties of feed-forward inhibition, we constructed a simple circuit using spiking neurons with conductance based synapses and applied spike pulse packets with defined strength and width. We found that the small temporal integration window, induced by the FFI, changes the integrative properties of the neuron. Only transient stimuli could produce a response when the FFI was active, whereas without FFI the neuron responded to both steady and transient stimuli. In addition, the FFI increased the trial-by-trial precision