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People performing actions together have a natural tendency to synchronize their behavior. Consistently, people doing a task together build internal representations not only of their actions and goals, but also of the other people performing the task. However, little is known about which are the behavioral mechanisms and the psychological factors affecting the subjective sensation of synchrony, or "connecting" with someone else. In this work, we sought to find which factors induce the subjective sensation of synchrony, combining motion capture data and psychological measures. Our results show that the subjective sensation of synchrony is affected by performance quality together with task category, and time. Psychological factors such as empathy and negative subjective affects also correlate with the subjective sensation of synchrony. However, when people estimate synchrony as seen from a third person perspective, their psychological factors do not affect the accuracy of the estimation. We suggest that to feel this sensation it is necessary to, first, have a good joint performance and, second, to assume the existence of an attention monitoring mechanism that reports that the attention of both participants (self and other) is focused on the task.

We examined the expression of genes related to brain energy metabolism and particularly those encoding glia (astrocyte)-specific functions in the dorsal hippocampus subsequent to learning. Context-dependent avoidance behavior was tested in mice using the step-through Inhibitory Avoidance (IA) paradigm. Animals were sacrificed 3, 9, 24, or 72 hours after training or 3 hours after retention testing. The quantitative determination of mRNA levels revealed learning-induced changes in the expression of genes thought to be involved in astrocyte-neuron metabolic coupling in a time dependent manner. Twenty four hours following IA training, an enhanced gene expression was seen, particularly for genes encoding monocarboxylate transporters 1 and 4 (MCT1, MCT4), alpha2 subunit of the Na/K-ATPase and glucose transporter type 1. To assess the functional role for one of these genes in learning, we studied MCT1 deficient mice and found that they exhibit impaired memory in the inhibitory avoidance task. Together, these observations indicate that neuron-glia metabolic coupling undergoes metabolic adaptations following learning as indicated by the change in expression of key metabolic genes.

The monocarboxylate transporter 1 (MCT1 or SLC16A1) is a carrier of short-chain fatty acids, ketone bodies, and lactate in several tissues. Genetically modified C57BL/6J mice were produced by targeted disruption of the mct1 gene in order to understand the role of this transporter in energy homeostasis. Null mutation was embryonically lethal, but MCT1 (+/-) mice developed normally. However, when fed high fat diet (HFD), MCT1 (+/-) mice displayed resistance to development of diet-induced obesity (24.8% lower body weight after 16 weeks of HFD), as well as less insulin resistance and no hepatic steatosis as compared to littermate MCT1 (+/+) mice used as controls. Body composition analysis revealed that reduced weight gain in MCT1 (+/-) mice was due to decreased fat accumulation (50.0% less after 9 months of HFD) notably in liver and white adipose tissue. This phenotype was associated with reduced food intake under HFD (12.3% less over 10 weeks) and decreased intestinal energy absorption (9.6% higher stool energy content). Indirect calorimetry measurements showed ∼ 15% increase in O₂ consumption and CO₂ production during the resting phase, without any changes in physical activity. Determination of plasma concentrations for various metabolites and hormones did not reveal significant changes in lactate and ketone bodies levels between the two genotypes, but both insulin and leptin levels, which were elevated in MCT1 (+/+) mice when fed HFD, were reduced in MCT1 (+/-) mice under HFD. Interestingly, the enhancement in expression of several genes involved in lipid metabolism in the liver of MCT1 (+/+) mice under high fat diet was prevented in the liver of MCT1 (+/-) mice under the same diet, thus likely contributing to the observed phenotype. These findings uncover the critical role of MCT1 in the regulation of energy balance when animals are exposed to an obesogenic diet.

Red blood cells (RBCs) present unique reversible shape deformability, essential for both function and survival, resulting notably in cell membrane fluctuations (CMF). These CMF have been subject of many studies in order to obtain a better understanding of these remarkable biomechanical membrane properties altered in some pathological states including blood diseases. In particular the discussion over the thermal or metabolic origin of the CMF has led in the past to a large number of investigations and modeling. However, the origin of the CMF is still debated. In this article, we present an analysis of the CMF of RBCs by combining digital holographic microscopy (DHM) with an orthogonal subspace decomposition of the imaging data. These subspace components can be reliably identified and quantified as the eigenmode basis of CMF that minimizes the deformation energy of the RBC structure. By fitting the observed fluctuation modes with a theoretical dynamic model, we find that the CMF are mainly governed by the bending elasticity of the membrane and that shear and tension elasticities have only a marginal influence on the membrane fluctations of the discocyte RBC. Further, our experiments show that the role of ATP as a driving force of CMF is questionable. ATP, however, seems to be required to maintain the unique biomechanical properties of the RBC membrane that lead to thermally excited CMF.

Background: Digital holography provides a non-invasive measurement of the quantitative phase shifts induced by cells in culture, which can be related to cell volume changes. It has been shown previously that regulation of cell volume, in particular as it relates to ionic homeostasis, is crucially involved in the activation/inactivation of the cell death processes. We thus present here an application of digital holographic microscopy (DHM) dedicated to early and label-free detection of cell death., Methods and Findings: We provide quantitative measurements of phase signal obtained on mouse cortical neurons, and caused by early neuronal cell volume regulation triggered by excitotoxic concentrations of L-glutamate. We show that the efficiency of this early regulation of cell volume detected by DHM, is correlated with the occurrence of subsequent neuronal death assessed with the widely accepted trypan blue method for detection of cell viability., Conclusions: The determination of the phase signal by DHM provides a simple and rapid optical method for the early detection of cell death.

Chloride channels represent a group of targets for major clinical indications. However, molecular screening for chloride channel modulators has proven to be difficult and time-consuming as approaches essentially rely on the use of fluorescent dyes or invasive patch-clamp techniques which do not lend themselves to the screening of large sets of compounds. To address this problem, we have developed a non-invasive optical method, based on digital holographic microcopy (DHM), allowing monitoring of ion channel activity without using any electrode or fluorescent dye. To illustrate this approach, GABA(A) mediated chloride currents have been monitored with DHM. Practically, we show that DHM can non-invasively provide the quantitative determination of transmembrane chloride fluxes mediated by the activation of chloride channels associated with GABA(A) receptors. Indeed through an original algorithm, chloride currents elicited by application of appropriate agonists of the GABA(A) receptor can be derived from the quantitative phase signal recorded with DHM. Finally, chloride currents can be determined and pharmacologically characterized non-invasively simultaneously on a large cellular sampling by DHM.

In this article we introduce JULIDE, a software toolkit developed to perform the 3D reconstruction, intensity normalization, volume standardization by 3D image registration and voxel-wise statistical analysis of autoradiographs of mouse brain sections. This software tool has been developed in the open-source ITK software framework and is freely available under a GPL license. The article presents the complete image processing chain from raw data acquisition to 3D statistical group analysis. Results of the group comparison in the context of a study on spatial learning are shown as an illustration of the data that can be obtained with this tool.