Adult Body Weight Is Programmed by a Redox-Regulated and Energy-Dependent Process during the Pronuclear Stage in Mouse

In mammals fertilization triggers a series of Ca2+ oscillations that not only are essential for events of egg activation but also stimulate oxidative phosphorylation. Little is known, however, about the relationship between quantitative changes in egg metabolism and specific long-term effects in offspring. This study assessed whether post-natal growth is modulated by early transient changes in NAD(P)H and FAD2+ in zygotes. We report that experimentally manipulating the redox potential of fertilized eggs during the pronuclear (PN) stage affects post-natal body weight. Exogenous pyruvate induces NAD(P)H oxidation and stimulates mitochondrial activity with resulting offspring that are persistently and significantly smaller than controls. Exogenous lactate stimulates NAD+ reduction and impairs mitochondrial activity, and produces offspring that are smaller than controls at weaning but catch up after weaning. Cytosolic alkalization increases NAD(P)+ reduction and offspring of normal birth-weight become significantly and persistently larger than controls. These results constitute the first report that post-natal growth rate is ultimately linked to modulation of NAD(P)H and FAD2+ concentration as early as the PN stage

A theory of how active behavior stabilises neural activity: neural gain modulation by closed-loop environmental feedback

During active behaviours like running, swimming, whisking or sniffing, motor actions shape sensory input and sensory percepts guide future motor commands. Ongoing cycles of sensory and motor processing constitute a closed-loop feedback system which is central to motor control and, it has been argued, for perceptual processes. This closed-loop feedback is mediated by brainwide neural circuits but how the presence of feedback signals impacts on the dynamics and function of neurons is not well understood. Here we present a simple theory suggesting that closed-loop feedback between the brain/body/environment can modulate neural gain and, consequently, change endogenous neural fluctuations and responses to sensory input. We support this theory with modeling and data analysis in two vertebrate systems. First, in a model of rodent whisking we show that negative feedback mediated by whisking vibrissa can suppress coherent neural fluctuations and neural responses to sensory input in the barrel cortex. We argue this suppression provides an appealing account of a brain state transition (a marked change in global brain activity) coincident with the onset of whisking in rodents. Moreover, this mechanism suggests a novel signal detection mechanism that selectively accentuates active, rather than passive, whisker touch signals. This mechanism is consistent with a predictive coding strategy that is sensitive to the consequences of motor actions rather than the difference between the predicted and actual sensory input. We further support the theory by re-analysing previously published two-photon data recorded in zebrafish larvae performing closed-loop optomotor behaviour in a virtual swim simulator. We show, as predicted by this theory, that the degree to which each cell contributes in linking sensory and motor signals well explains how much its neural fluctuations are suppressed by closed-loop optomotor behaviour. More generally we argue that our results demonstrate the dependence of neural fluctuations, across the brain, on closed-loop brain/body/environment interactions strongly supporting the idea that brain function cannot be fully understood through open-loop approaches alone

Current Status and Future Challenges of Sleep Monitoring Systems: Systematic Review

International audienceBackground:Sleep is essential for human health. Considerable effort has been made into academic and industrial research and development on wireless body area networks for sleep monitoring in terms of non-intrusiveness, portability and autonomy. Thanks to rapid advances in smart sensing and communication technologies, various sleep monitoring systems (SMS) have been developed with advantages such as low-cost, accessible, discreet, contactless, unmanned and suitable for long-term monitoring.Objective:The objective of this paper is to review current research in sleep monitoring to serve as a reference for researchers and to provide insights for future work. Specific selection criteria were chosen to include articles in which sleep monitoring systems or devices are covered.Methods:This review investigates the use of various common sensors in the hardware implementation of current SMS, as well as the types of parameters collected, the positions they are on the body, the possible description of sleep phases, and the advantages and drawbacks. In addition, the data processing algorithms and software used in different works about SMS and their results are presented. This review is not limited to the study of laboratory research, but also investigated the various popular commercial products available for sleep monitoring, presenting their characteristics, advantages and disadvantages. In particular, we categorized existing research on SMS based on how the sensor is used, including the number and type of sensors, and the preferred positions on the body. In addition to focusing on a specific system, issues concerning SMS such as privacy, economic and social impact are also included. Finally, we present an original SMS solution developed in our laboratory.Results:Through retrieving large number of articles and abstracts, we found that hotspot techniques such as big data, machine learning, artificial intelligence and data mining have not been widely applied to the sleep monitoring research area. Accelerometer is the most commonly used sensor in SMS. Most of commercial sleep monitoring products can’t provide performance evaluation based on gold standard PSG.Conclusions:The combination of hotspot techniques such as big data, machine learning, artificial intelligence and data mining with sleep monitoring may be a promising research direction and attracts more and more researchers in the future. How to balance user acceptance and monitoring performance is the biggest challenge in SMS research

Experimental validation of the influence of white matter anisotropy on the intracranial EEG forward solution

Forward solutions with different levels of complexity are employed for localization of current generators, which are responsible for the electric and magnetic fields measured from the human brain. The influence of brain anisotropy on the forward solution is poorly understood. The goal of this study is to validate an anisotropic model for the intracranial electric forward solution by comparing with the directly measured 'gold standard'. Dipolar sources are created at known locations in the brain and intracranial electroencephalogram (EEG) is recorded simultaneously. Isotropic models with increasing level of complexity are generated along with anisotropic models based on Diffusion tensor imaging (DTI). A Finite Element Method based forward solution is calculated and validated using the measured data. Major findings are (1) An anisotropic model with a linear scaling between the eigenvalues of the electrical conductivity tensor and water self-diffusion tensor in brain tissue is validated. The greatest improvement was obtained when the stimulation site is close to a region of high anisotropy. The model with a global anisotropic ratio of 10:1 between the eigenvalues (parallel: tangential to the fiber direction) has the worst performance of all the anisotropic models. (2) Inclusion of cerebrospinal fluid as well as brain anisotropy in the forward model is necessary for an accurate description of the electric field inside the skull. The results indicate that an anisotropic model based on the DTI can be constructed non-invasively and shows an improved performance when compared to the isotropic models for the calculation of the intracranial EEG forward solution. © The Author(s) 2009