A microfluidic technique for generating monodisperse submicron-sized drops

International audienceWe present a route for producing monodisperse micro and nanodrops that is based on a liquid-gas phase transition occurring within a microfluidic device. A gas which is soluble in water is mixed with an insoluble one and injected into an aqueous surfactant solution, using a microfluidic device that produces monodisperse bubbles. As the soluble gas diffuses out of the bubbles, they shrink and the remaining insoluble gas condenses into drops. Their radius can be tuned over a wide range by changing the initial gas mixing ratio

Mechanical tuning of the evaporation rate of liquid on crossed fibers

We investigate experimentally the drying of a small volume of perfectly wetting liquid on two crossed fibers. We characterize the drying dynamics for the three liquid morphologies that are encountered in this geometry: drop, column and a mixed morphology, in which a drop and a column coexist. For each morphology, we rationalize our findings with theoretical models that capture the drying kinetics. We find that the evaporation rate depends significantly on the liquid morphology and that the drying of liquid column is faster than the evaporation of the drop and the mixed morphology for a given liquid volume. Finally, we illustrate that shearing a network of fibers reduces the angle between them, changes the morphology towards the column state, and so enhances the drying rate of a volatile liquid deposited on it

Preparation of Large Monodisperse Vesicles

Preparation of monodisperse vesicles is important both for research purposes and for practical applications. While the extrusion of vesicles through small pores (∼100 nm in diameter) results in relatively uniform populations of vesicles, extrusion to larger sizes results in very heterogeneous populations of vesicles. Here we report a simple method for preparing large monodisperse multilamellar vesicles through a combination of extrusion and large-pore dialysis. For example, extrusion of polydisperse vesicles through 5-µm-diameter pores eliminates vesicles larger than 5 µm in diameter. Dialysis of extruded vesicles against 3-µm-pore-size polycarbonate membranes eliminates vesicles smaller than 3 µm in diameter, leaving behind a population of monodisperse vesicles with a mean diameter of ∼4 µm. The simplicity of this method makes it an effective tool for laboratory vesicle preparation with potential applications in preparing large monodisperse liposomes for drug delivery

Bifurcation study of a neural field competition model with an application to perceptual switching in motion integration.

Perceptual multistability is a phenomenon in which alternate interpretations of a fixed stimulus are perceived intermittently. Although correlates between activity in specific cortical areas and perception have been found, the complex patterns of activity and the underlying mechanisms that gate multistable perception are little understood. Here, we present a neural field competition model in which competing states are represented in a continuous feature space. Bifurcation analysis is used to describe the different types of complex spatio-temporal dynamics produced by the model in terms of several parameters and for different inputs. The dynamics of the model was then compared to human perception investigated psychophysically during long presentations of an ambiguous, multistable motion pattern known as the barberpole illusion. In order to do this, the model is operated in a parameter range where known physiological response properties are reproduced whilst also working close to bifurcation. The model accounts for characteristic behaviour from the psychophysical experiments in terms of the type of switching observed and changes in the rate of switching with respect to contrast. In this way, the modelling study sheds light on the underlying mechanisms that drive perceptual switching in different contrast regimes. The general approach presented is applicable to a broad range of perceptual competition problems in which spatial interactions play a role

Combining Feature Selection and Integration—A Neural Model for MT Motion Selectivity

Background: The computation of pattern motion in visual area MT based on motion input from area V1 has been investigated in many experiments and models attempting to replicate the main mechanisms. Two different core conceptual approaches were developed to explain the findings. In integrationist models the key mechanism to achieve pattern selectivity is the nonlinear integration of V1 motion activity. In contrast, selectionist models focus on the motion computation at positions with 2D features. Methodology/Principal Findings: Recent experiments revealed that neither of the two concepts alone is sufficient to explain all experimental data and that most of the existing models cannot account for the complex behaviour found. MT pattern selectivity changes over time for stimuli like type II plaids from vector average to the direction computed with an intersection of constraint rule or by feature tracking. Also, the spatial arrangement of the stimulus within the receptive field of a MT cell plays a crucial role. We propose a recurrent neural model showing how feature integration and selection can be combined into one common architecture to explain these findings. The key features of the model are the computation of 1D and 2D motion in model area V1 subpopulations that are integrated in model MT cells using feedforward and feedback processing. Our results are also in line with findings concerning the solution of the aperture problem. Conclusions/Significance: We propose a new neural model for MT pattern computation and motion disambiguation that i