Targeted cortical reorganization using optogenetics in non-human primates.

Brain stimulation modulates the excitability of neural circuits and drives neuroplasticity. While the local effects of stimulation have been an active area of investigation, the effects on large-scale networks remain largely unexplored. We studied stimulation-induced changes in network dynamics in two macaques. A large-scale optogenetic interface enabled simultaneous stimulation of excitatory neurons and electrocorticographic recording across primary somatosensory (S1) and motor (M1) cortex (Yazdan-Shahmorad et al., 2016). We tracked two measures of network connectivity, the network response to focal stimulation and the baseline coherence between pairs of electrodes; these were strongly correlated before stimulation. Within minutes, stimulation in S1 or M1 significantly strengthened the gross functional connectivity between these areas. At a finer scale, stimulation led to heterogeneous connectivity changes across the network. These changes reflected the correlations introduced by stimulation-evoked activity, consistent with Hebbian plasticity models. This work extends Hebbian plasticity models to large-scale circuits, with significant implications for stimulation-based neurorehabilitation

What effect does network size have on NRTK positioning?

The Network Real Time Kinematic (NRTK) positioning is nowadays a very common practice not only in academia but also in the professional world. To support the users several networks of Continuous Operating Reference Stations (CORSs) were born. These networks offer real-time services for NRTK positioning, providing a centimetric positioning accuracy with an average distance of 25-35 kms between the reference stations. But what is the effective distance between reference stations that allows to achieve the precision required for real-time positioning, using both geodetic and GIS receivers? How the positional accuracy changes with increasing distances between CORS? Can a service of geostationary satellites, such as the European EGNOS, be an alternative to the network positioning for medium-low cost receivers? These are only some of the questions that the Authors try to answer in this articl

Online Monitoring of the Osiris Reactor with the Nucifer Neutrino Detector

Originally designed as a new nuclear reactor monitoring device, the Nucifer detector has successfully detected its first neutrinos. We provide the second shortest baseline measurement of the reactor neutrino flux. The detection of electron antineutrinos emitted in the decay chains of the fission products, combined with reactor core simulations, provides an new tool to assess both the thermal power and the fissile content of the whole nuclear core and could be used by the Inter- national Agency for Atomic Energy (IAEA) to enhance the Safeguards of civil nuclear reactors. Deployed at only 7.2m away from the compact Osiris research reactor core (70MW) operating at the Saclay research centre of the French Alternative Energies and Atomic Energy Commission (CEA), the experiment also exhibits a well-suited configuration to search for a new short baseline oscillation. We report the first results of the Nucifer experiment, describing the performances of the 0.85m3 detector remotely operating at a shallow depth equivalent to 12m of water and under intense background radiation conditions. Based on 145 (106) days of data with reactor ON (OFF), leading to the detection of an estimated 40760 electron antineutrinos, the mean number of detected antineutrinos is 281 +- 7(stat) +- 18(syst) electron antineutrinos/day, in agreement with the prediction 277(23) electron antineutrinos/day. Due the the large background no conclusive results on the existence of light sterile neutrinos could be derived, however. As a first societal application we quantify how antineutrinos could be used for the Plutonium Management and Disposition Agreement.Comment: 22 pages, 16 figures - Version

Evidence against the Detectability of a Hippocampal Place Code Using Functional Magnetic Resonance Imaging

Individual hippocampal neurons selectively increase their firing rates in specific spatial locations. As a population, these neurons provide a decodable representation of space that is robust against changes to sensory- and path-related cues. This neural code is sparse and distributed, theoretically rendering it undetectable with population recording methods such as functional magnetic resonance imaging (fMRI). Existing studies nonetheless report decoding spatial codes in the human hippocampus using such techniques. Here we present results from a virtual navigation experiment in humans in which we eliminated visual- and path-related confounds and statistical limitations present in existing studies, ensuring that any positive decoding results would represent a voxel-place code. Consistent with theoretical arguments derived from electrophysiological data and contrary to existing fMRI studies, our results show that although participants were fully oriented during the navigation task, there was no statistical evidence for a place code

dCas9-based epigenome editing suggests acquisition of histone methylation is not sufficient for target gene repression.

Distinct epigenomic profiles of histone marks have been associated with gene expression, but questions regarding the causal relationship remain. Here we investigated the activity of a broad collection of genomically targeted epigenetic regulators that could write epigenetic marks associated with a repressed chromatin state (G9A, SUV39H1, Krüppel-associated box (KRAB), DNMT3A as well as the first targetable versions of Ezh2 and Friend of GATA-1 (FOG1)). dCas9 fusions produced target gene repression over a range of 0- to 10-fold that varied by locus and cell type. dCpf1 fusions were unable to repress gene expression. The most persistent gene repression required the action of several effector domains; however, KRAB-dCas9 did not contribute to persistence in contrast to previous reports. A 'direct tethering' strategy attaching the Ezh2 methyltransferase enzyme to dCas9, as well as a 'recruitment' strategy attaching the N-terminal 45 residues of FOG1 to dCas9 to recruit the endogenous nucleosome remodeling and deacetylase complex, were both successful in targeted deposition of H3K27me3. Surprisingly, however, repression was not correlated with deposition of either H3K9me3 or H3K27me3. Our results suggest that so-called repressive histone modifications are not sufficient for gene repression. The easily programmable dCas9 toolkit allowed precise control of epigenetic information and dissection of the relationship between the epigenome and gene regulation

Robots that can adapt like animals

As robots leave the controlled environments of factories to autonomously function in more complex, natural environments, they will have to respond to the inevitable fact that they will become damaged. However, while animals can quickly adapt to a wide variety of injuries, current robots cannot "think outside the box" to find a compensatory behavior when damaged: they are limited to their pre-specified self-sensing abilities, can diagnose only anticipated failure modes, and require a pre-programmed contingency plan for every type of potential damage, an impracticality for complex robots. Here we introduce an intelligent trial and error algorithm that allows robots to adapt to damage in less than two minutes, without requiring self-diagnosis or pre-specified contingency plans. Before deployment, a robot exploits a novel algorithm to create a detailed map of the space of high-performing behaviors: This map represents the robot's intuitions about what behaviors it can perform and their value. If the robot is damaged, it uses these intuitions to guide a trial-and-error learning algorithm that conducts intelligent experiments to rapidly discover a compensatory behavior that works in spite of the damage. Experiments reveal successful adaptations for a legged robot injured in five different ways, including damaged, broken, and missing legs, and for a robotic arm with joints broken in 14 different ways. This new technique will enable more robust, effective, autonomous robots, and suggests principles that animals may use to adapt to injury