Toto-Cell: A new software to analyze cellular events during video-microscopy.

Video-microscopy is a technology widely used to follow, in a single cell manner, cell behavior. A number of new studies are searching a way to track these behaviors by artificial intelligence; unfortunately some real-time events still have to be track manually. For that reason, we developed a software that helps the experimenter to analyze collected data. Toto-cell is very simple to use and it can be adapted at different type of analyses or treatments. It allows a wide new range of parameters that were nearly impossible to calculate only by hand. We thus developed this new software using HEC-1-A endometrial cell line to track different cellular parameters such as: the number of normal/abnormal mitosis, the ratio per day of death, mitosis, cell fusions or finally the length between two mitosis cycles. We treated our cells with cisplatin, doxorubicin or AZD5363 (an Akt inhibitor) to obtain different cellular events. What emerged is a huge heterogeneity for these analyzed parameters between the cells in a single treatment which is clearly demonstrated by the results provided by Toto-Cell. In conclusion, our software is an important tool to facilitate the analysis of video-microscopy, in a quantifying and qualifying manner. It enables a higher accuracy when compared to manual calculations.

Congruent action context releases Mu rhythm desynchronization when visual objects activate competing action representations.

Recent findings demonstrated that object perception is affected by the competition between action representations. Simultaneous activation of distinct structural ("grasp-to-move") and functional ("grasp-to-use") action representations slows down perceptual judgements on objects. At the brain level, competition reduces motor resonance effects during manipulable object perception, reflected by an extinction of µ rhythm desynchronization. However, how this competition is solved in the absence of object-directed action remains unclear. The present study investigates the role of context in the resolution of the competition between conflicting action representations during mere object perception. To this aim, thirty-eight volunteers were instructed to perform a reachability judgment task on 3D objects presented at different distances in a virtual environment. Objects were conflictual objects associated with distinct structural and functional action representations. Verbs were used to provide a neutral or congruent action context prior or after object presentation. Neurophysiological correlates of the competition between action representation were recorded using EEG. The main result showed a release of µ rhythm desynchronization when reachable conflictual objects were presented with a congruent action context. Context influenced µ rhythm desynchronization when the action context was provided prior or after object presentation in a time-window compatible with object-context integration (around 1000 ms after the presentation of the first stimulus). These findings revealed that action context biases competition between co-activated action representations during mere object perception and demonstrated that µ rhythm desynchronization may be an index of activation but also competition between action representations in perception.

Reconstructing Image Composition: Computation of Leading Lines.

The composition of an image is a critical element chosen by the author to construct an image that conveys a narrative and related emotions. Other key elements include framing, lighting, and colors. Assessing classical and simple composition rules in an image, such as the well-known "rule of thirds", has proven effective in evaluating the aesthetic quality of an image. It is widely acknowledged that composition is emphasized by the presence of leading lines. While these leading lines may not be explicitly visible in the image, they connect key points within the image and can also serve as boundaries between different areas of the image. For instance, the boundary between the sky and the ground can be considered a leading line in the image. Making the image's composition explicit through a set of leading lines is valuable when analyzing an image or assisting in photography. To the best of our knowledge, no computational method has been proposed to trace image leading lines. We conducted user studies to assess the agreement among image experts when requesting them to draw leading lines on images. According to these studies, which demonstrate that experts concur in identifying leading lines, this paper introduces a fully automatic computational method for recovering the leading lines that underlie the image's composition. Our method consists of two steps: firstly, based on feature detection, potential weighted leading lines are established; secondly, these weighted leading lines are grouped to generate the leading lines of the image. We evaluate our method through both subjective and objective studies, and we propose an objective metric to compare two sets of leading lines.

Stopping Criterion during Rendering of Computer-Generated Images Based on SVD-Entropy.

The estimation of image quality and noise perception still remains an important issue in various image processing applications. It has also become a hot topic in the field of photo-realistic computer graphics where noise is inherent in the calculation process. Unlike natural-scene images, however, a reference image is not available for computer-generated images. Thus, classic methods to assess noise quantity and stopping criterion during the rendering process are not usable. This is particularly important in the case of global illumination methods based on stochastic techniques: They provide photo-realistic images which are, however, corrupted by stochastic noise. This noise can be reduced by increasing the number of paths, as proved by Monte Carlo theory, but the problem of finding the right number of paths that are required in order to ensure that human observers cannot perceive any noise is still open. Until now, the features taking part in the human evaluation of image quality and the remaining perceived noise are not precisely known. Synthetic image generation tends to be very expensive and the produced datasets are high-dimensional datasets. In that case, finding a stopping criterion using a learning framework is a challenging task. In this paper, a new method for characterizing computational noise for computer generated images is presented. The noise is represented by the entropy of the singular value decomposition of each block composing an image. These Singular Value Decomposition (SVD)-entropy values are then used as input to a recurrent neural network architecture model in order to extract image noise and in predicting a visual convergence threshold of different parts of any image. Thus a new no-reference image quality assessment is proposed using the relation between SVD-Entropy and perceptual quality, based on a sequence of distorted images. Experiments show that the proposed method, compared with experimental psycho-visual scores, demonstrates a good consistency between these scores and stopping criterion measures that we obtain.

Contribution of the motor system to the perception of reachable space: an fMRI study.

The present functional magnetic resonance imaging (fMRI) study investigates the neural correlates of reachability judgements. In a block design experiment, 14 healthy participants judged whether a visual target presented at different distances in a virtual environment display was reachable or not with the right hand. In two control tasks, they judged the colour or the relative position of the visual target according to flankers. Contrasting the activations registered in the reachability judgement task and in the control tasks, we found activations in the frontal structures, and in the bilateral inferior and superior parietal lobe, including the precuneus, and the bilateral cerebellum. This fronto-parietal network including the cerebellum overlaps with the brain network usually activated during actual motor production and motor imagery. In a following event-related design experiment, we contrasted brain activations when targets were rated as 'reachable' with those when they were rated as 'unreachable'. We found activations in the left premotor cortex, the bilateral frontal structures, and the left middle temporal gyrus. At a lower threshold, we also found activations in the left motor cortex, and in the bilateral cerebellum. Given that reaction time increased with target distance in reachable space, we performed a subsequent parametric analysis that revealed a related increase of activity in the fronto-parietal network including the cerebellum. Unreachable targets did not show similar activation, and particularly in regions associated to motor production and motor imagery. Taken together, these results suggest that dynamical motor representations used to determine what is reachable are also part of the perceptual process leading to the distinct representation of peripersonal and extrapersonal spaces.