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

Cerebral blood flow recorded at high sensitivity in two dimensions using high resolution optical imaging

Knowledge about sensory-evoked blood-flow changes is essential for constraining hemodynamic response models used to interpret functional brain imaging signals, such as fMRI. Here, we extracted 2-dimensional blood-flow and its temporal modulations from high-resolution optical imaging data in the awake monkey. Optical imaging allows to track moving erythrocytes (or small clusters thereof), thus providing, albeit noisy, information about their velocity in individual blood vessels, across the whole imaged area. Here, we illustrate the algorithms that allowed us to extract, at the single micro-vessel level, red blood cell (RBC) motion information from the noisy optical signals. For this purpose, we developed an algorithm that is both robust and computationally efficient, using the structure tensor, known to detect an average direction of image intensity gradient. This structure tensor tool is applied to detect trajectory directions in the spatio-temporal data. Since blood-flow modulation by the cardiac pulsation was clearly detected, our method should be applicable also to study blood-flow modulations by neuronal activity, and their spatio-temporal patterns

Approche variationnelle pour la déconvolution rapide de données 3D en microscopie biphotonique

National audienceBetter understanding of biological processes requires new, improved, high resolution imagery techniques. The present work concerns the restoration of data acquired with two-photon microscopy in biological tissue, in-vivo in particular. Two main challenges to tackle are: the large dimensionality of the acquired data and the incomplete knowledge of the impulse response of the system. We propose here an experimental setting to estimate it based on the observation of fluorescent micro-beads. The non-blind formulation of the related inverse problem of image restoration is then solved by minimizing a penalized criterion using an efficient convex optimization strategy based on the Majoration-Minimization approach. The effectiveness of the proposed approach is not only shown on simulated data but also on real data.Les technologies d'imagerie permettant d'obtenir des images à l'échelle cellulaire sont devenues incontournables pour mieux comprendre les processus biologiques. Nous nous intéressons ici à l'imagerie biphotonique et plus particulièrement, à la reconstruction des images acquises par un tel système dans un contexte in-vivo. Deux difficultés majeures sont : les gros volumes de données que représentent les acquisitions et la mauvaise connaissance de la réponse impulsionnelle de l'instrument. Nous proposons dans ce travail d'estimer cette dernière à l'aide d'un montage expérimental basé sur l'observation de micro-billes fluorescentes. Le problème inverse de restauration d'image est ensuite résolu dans un cadre non aveugle, en le formulant sous la forme d'un critère pénalisé minimisé à l'aide d'une méthode d'optimisation convexe efficace fondée sur la technique de Majoration-Minimisation. L'efficacité de l'approche proposée est démontrée sur données simulées et réelles

Behavioral Receptive Field for Ocular Following in Humans: Dynamics of Spatial Summation and Center-Surround Interactions

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Elliptically Polarized Light for Depth Resolved Optical Imaging

International audienceUsing elliptically polarized light allows performing a selection of a well defined subsurface volume in a turbid medium. This offers the possibility to probe biological tissues in depth. The method and preliminary results are presented