50 research outputs found

    Developmental excitatory-to-inhibitory GABA-polarity switch is disrupted in 22q11.2 deletion syndrome: a potential target for clinical therapeutics.

    Get PDF
    Individuals with 22q11.2 microdeletion syndrome (22q11.2 DS) show cognitive and behavioral dysfunctions, developmental delays in childhood and risk of developing schizophrenia and autism. Despite extensive previous studies in adult animal models, a possible embryonic root of this syndrome has not been determined. Here, in neurons from a 22q11.2 DS mouse model (Lgdel +/-), we found embryonic-premature alterations in the neuronal chloride cotransporters indicated by dysregulated NKCC1 and KCC2 protein expression levels. We demonstrate with large-scale spiking activity recordings a concurrent deregulation of the spontaneous network activity and homeostatic network plasticity. Additionally, Lgdel +/- networks at early development show abnormal neuritogenesis and void of synchronized spontaneous activity. Furthermore, parallel experiments on Dgcr8 +/- mouse cultures reveal a significant, yet not exclusive contribution of the dgcr8 gene to our phenotypes of Lgdel +/- networks. Finally, we show that application of bumetanide, an inhibitor of NKCC1, significantly decreases the hyper-excitable action of GABAA receptor signaling and restores network homeostatic plasticity in Lgdel +/- networks. Overall, by exploiting an on-a-chip 22q11.2 DS model, our results suggest a delayed GABA-switch in Lgdel +/- neurons, which may contribute to a delayed embryonic development. Prospectively, acting on the GABA-polarity switch offers a potential target for 22q11.2 DS therapeutic intervention

    Hinders of Cloud Computing Usage in Higher Education in Iraq: A Model Development

    Get PDF
    Cloud computing (CC) is a trendy technology that is being used in business and daily life. However, limited studies is found on higher education usage. The barriers and obstacles that confront the usage is not clear and in particular in developing countries. The purpose of this study is to examine the barriers and obstacle that confront the usage CC services in Barash University in Iraq. Using the technology organization environment framework and the internal external factor (IE-TOE), the study proposed the conceptual framework. The data was collected from academic, non-academic staff and students using convivence sampling technique. The data was analyzed using Smart PLS. The findings showed that organizational obstacle followed by technological, internal and external factors, and environmental factors are the most severe obstacles that confront the university in using CC services. Decision makers can benefit from the developed model to ease the implementation of CC

    Investigating the relationship between knowledge management practices and organizational learning practices in the universities’ environment

    Get PDF
    The concept of knowledge management (KM) and organizational learning (OL) has been embraced by organizations to complement each other. Higher education institutions have embraced KM and OL as a means to improve organizational efficiency. This research explores the link between KM and OL. The target population included all the 432 academicians and administrators from 35 public universities in Iraq. The sampling was selected using a stratified random sampling technique. The correlation among the components of KM and OL was tested as well as the effect of KM components on OL. The findings were derived using smart partial least square. The findings showed that there is significant correlation between components of KM and components of OL. The regression analysis showed also that the effect of KM and its components; knowledge creation, knowledge sharing, knowledge storage, knowledge application and knowledge acquisition on OL are significant. These findings provide insights to universities management on strategies to implement KM practices that can align with OL practices to assure dynamic lifelong mechanisms for the basic daily activities such as teaching, learning, researching, and supervision

    3d plasmonic nanoantennas integrated with mea biosensors

    Get PDF
    Plasmonic 3D nanoantennas are integrated on multielectrode arrays. These biosensors can record extracellular activity and enhance Raman signals from living neurons

    Performance enhancement of Absolute Polar Duty Cycle Division Multiplexing with Dual-Drive Mach–Zehnder-Modulator in 40 Gbit/s optical fiber communication systems

    Get PDF
    We modeled and analyzed a method to improve receiver sensitivity of the Absolute Polar Duty Cycle Division Multiplexing (AP-DCDM) transmission system by using Dual-Drive Mach–Zehnder-Modulator (DD-MZM). It is found that by optimizing the bias voltage in DD-MZM, the sensitivity of the AP-DCDM can be improved. The optimizations lead towards the larger eye opening. As opposed to the previous work, in terms of receiver sensitivity and dispersion tolerance, similar performance for all channels was achieved. In comparison to the previously reported AP-DCDM system, this work resulted in almost 3.6 dB improvement of the receiver sensitivity, came together with acceptable chromatic dispersion tolerance

    Sloppiness in spontaneously active neuronal networks

    Get PDF
    Various plasticity mechanisms, including experience-dependent, spontaneous, as well as homeostatic ones, continuously remodel neural circuits. Yet, despite fluctuations in the properties of single neurons and synapses, the behavior and function of neuronal assemblies are generally found to be very stable over time. This raises the important question of how plasticity is coordinated across the network. To address this, we investigated the stability of network activity in cultured rat hippocampal neurons recorded with high-density multielectrode arrays over several days. We used parametric models to characterize multineuron activity patterns and analyzed their sensitivity to changes. We found that the models exhibited sloppiness, a property where the model behavior is insensitive to changes in many parameter combinations, but very sensitive to a few. The activity of neurons with sloppy parameters showed faster and larger fluctuations than the activity of a small subset of neurons associated with sensitive parameters. Furthermore, parameter sensitivity was highly correlated with firing rates. Finally, we tested our observations from cell cultures on an in vivo recording from monkey visual cortex and we confirm that spontaneous cortical activity also shows hallmarks of sloppy behavior and firing rate dependence. Our findings suggest that a small subnetwork of highly active and stable neurons supports group stability, and that this endows neuronal networks with the flexibility to continuously remodel without compromising stability and function

    Evaluating assumptions of scales for subjective assessment of thermal environments – Do laypersons perceive them the way, we researchers believe?

    Get PDF
    International audienc

    Spike Detection for Large Neural Populations Using High Density Multielectrode Arrays

    Get PDF
    An emerging generation of high-density microelectrode arrays (MEAs) is now capable of recording spiking activity simultaneously from thousands of neurons with closely spaced electrodes. Reliable spike detection and analysis in such recordings is challenging due to the large amount of raw data, and the dense sampling of spikes with closely spaced electrodes.Here, we present a highly efficient, online capable spike detection algorithm, and an offline method with improved detection rates, which enables estimation of spatial event locations at a resolution higher than that provided by the array by combining information from multiple electrodes. Data acquired with a 4,096 channel MEA from neuronal cultures and the neonatal retina, as well as synthetic data was used to test and validate these methods.We demonstrate that these algorithms outperform conventional methods due to a better noise estimate and an improved signal-to-noise ratio through combining information from multiple electrodes. Finally, we present a new approach for analyzing population activity based on the characterization of the spatio-temporal event profile, which does not require the isolation of single units.Overall, we show how the improved spatial resolution provided by high density, large scale microelectrode arrays can be reliably exploited to characterize activity from large neural populations and brain circuits
    corecore