Introducing Membrane Charge and Membrane Potential to T Cell Signaling

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Yuanqing Ma

2017-11-01

Full Text Available While membrane models now include the heterogeneous distribution of lipids, the impact of membrane charges on regulating the association of proteins with the plasma membrane is often overlooked. Charged lipids are asymmetrically distributed between the two leaflets of the plasma membrane, resulting in the inner leaflet being negatively charged and a surface potential that attracts and binds positively charged ions, proteins, and peptide motifs. These interactions not only create a transmembrane potential but they can also facilitate the formation of charged membrane domains. Here, we reference fields outside of immunology in which consequences of membrane charge are better characterized to highlight important mechanisms. We then focus on T cell receptor (TCR signaling, reviewing the evidence that membrane charges and membrane-associated calcium regulate phosphorylation of the TCR–CD3 complex and discuss how the immunological synapse exhibits distinct patterns of membrane charge distribution. We propose that charged lipids, ions in solution, and transient protein interactions form a dynamic equilibrium during T cell activation.

Application of neural networks to signal prediction in nuclear power plant

International Nuclear Information System (INIS)

Wan Joo Kim; Soon Heung Chang; Byung Ho Lee

1993-01-01

This paper describes the feasibility study of an artificial neural network for signal prediction. The purpose of signal prediction is to estimate the value of undetected next time step signal. As the prediction method, based on the idea of auto regression, a few previous signals are inputs to the artificial neural network and the signal value of next time step is estimated with the outputs of the network. The artificial neural network can be applied to the nonlinear system and answers in short time. The training algorithm is a modified backpropagation model, which can effectively reduce the training time. The target signal of the simulation is the steam generator water level, which is one of the important parameters in nuclear power plants. The simulation result shows that the predicted value follows the real trend well

The Application and Research of the GA-BP Neural Network Algorithm in the MBR Membrane Fouling

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Chunqing Li

2014-01-01

Full Text Available It is one of the important issues in the field of today's sewage treatment of researching the MBR membrane flux prediction for membrane fouling. Firstly this paper used the principal component analysis method to achieve dimensionality and correlation of input variables and obtained the three major factors affecting membrane fouling most obvious: MLSS, total resistance, and operating pressure. Then it used the BP neural network to establish the system model of the MBR intelligent simulation, the relationship between three parameters, and membrane flux characterization of the degree of membrane fouling, because the BP neural network has slow training speed, is sensitive to the initial weights and the threshold, is easy to fall into local minimum points, and so on. So this paper used genetic algorithm to optimize the initial weights and the threshold of BP neural network and established the membrane fouling prediction model based on GA-BP network. As this research had shown, under the same conditions, the BP network model optimized by GA of MBR membrane fouling is better than that not optimized for prediction effect of membrane flux. It demonstrates that the GA-BP network model of MBR membrane fouling is more suitable for simulation of MBR membrane fouling process, comparing with the BP network.

Automatic Speech Recognition from Neural Signals: A Focused Review

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Christian Herff

2016-09-01

Full Text Available Speech interfaces have become widely accepted and are nowadays integrated in various real-life applications and devices. They have become a part of our daily life. However, speech interfaces presume the ability to produce intelligible speech, which might be impossible due to either loud environments, bothering bystanders or incapabilities to produce speech (i.e.~patients suffering from locked-in syndrome. For these reasons it would be highly desirable to not speak but to simply envision oneself to say words or sentences. Interfaces based on imagined speech would enable fast and natural communication without the need for audible speech and would give a voice to otherwise mute people.This focused review analyzes the potential of different brain imaging techniques to recognize speech from neural signals by applying Automatic Speech Recognition technology. We argue that modalities based on metabolic processes, such as functional Near Infrared Spectroscopy and functional Magnetic Resonance Imaging, are less suited for Automatic Speech Recognition from neural signals due to low temporal resolution but are very useful for the investigation of the underlying neural mechanisms involved in speech processes. In contrast, electrophysiologic activity is fast enough to capture speech processes and is therefor better suited for ASR. Our experimental results indicate the potential of these signals for speech recognition from neural data with a focus on invasively measured brain activity (electrocorticography. As a first example of Automatic Speech Recognition techniques used from neural signals, we discuss the emph{Brain-to-text} system.

Electrocardiogram (ECG Signal Modeling and Noise Reduction Using Hopfield Neural Networks

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F. Bagheri

2013-02-01

Full Text Available The Electrocardiogram (ECG signal is one of the diagnosing approaches to detect heart disease. In this study the Hopfield Neural Network (HNN is applied and proposed for ECG signal modeling and noise reduction. The Hopfield Neural Network (HNN is a recurrent neural network that stores the information in a dynamic stable pattern. This algorithm retrieves a pattern stored in memory in response to the presentation of an incomplete or noisy version of that pattern. Computer simulation results show that this method can successfully model the ECG signal and remove high-frequency noise.

Biglycan and decorin differentially regulate signaling in the fetal membranes

Science.gov (United States)

Wu, Zhiping; Horgan, Casie E.; Carr, Olivia; Owens, Rick T.; Iozzo, Renato V.; Lechner, Beatrice E.

2014-01-01

Preterm birth is the leading cause of newborn mortality in the United States and about one third of cases are caused by preterm premature rupture of fetal membranes, a complication that is frequently observed in patients with Ehlers-Danlos Syndrome. Notably, a subtype of Ehlers-Danlos Syndrome is caused by expression of abnormal biglycan and decorin proteoglycans. As compound deficiency of these two small leucine-rich proteoglycans is a model of preterm birth, we investigated the fetal membranes of Bgn−/−;Dcn−/− double-null and single-null mice. Our results showed that biglycan signaling supported fetal membrane remodeling during early gestation in the absence of concomitant changes in TGFβ levels. In late gestation, biglycan signaling acted in a TGFβ–dependent manner to aid in membrane stabilization. In contrast, decorin signaling supported fetal membrane remodeling at early stages of gestation in a TGFβ–dependent manner, and fetal membrane stabilization at later stages of gestation without changes in TGFβ levels. Furthermore, exogenous soluble decorin was capable of rescuing the TGFβ signaling pathway in fetal membrane mesenchymal cells. Collectively, these findings provide novel targets for manipulation of fetal membrane extracellular matrix stability and could represent novel targets for research on preventive strategies for preterm premature rupture of fetal membranes. PMID:24373743

Cell membrane disruption stimulates cAMP and Ca2+ signaling to potentiate cell membrane resealing in neighboring cells

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Tatsuru Togo

2017-12-01

Full Text Available Disruption of cellular plasma membranes is a common event in many animal tissues, and the membranes are usually rapidly resealed. Moreover, repeated membrane disruptions within a single cell reseal faster than the initial wound in a protein kinase A (PKA- and protein kinase C (PKC-dependent manner. In addition to wounded cells, recent studies have demonstrated that wounding of Madin-Darby canine kidney (MDCK cells potentiates membrane resealing in neighboring cells in the short-term by purinergic signaling, and in the long-term by nitric oxide/protein kinase G signaling. In the present study, real-time imaging showed that cell membrane disruption stimulated cAMP synthesis and Ca2+ mobilization from intracellular stores by purinergic signaling in neighboring MDCK cells. Furthermore, inhibition of PKA and PKC suppressed the ATP-mediated short-term potentiation of membrane resealing in neighboring cells. These results suggest that cell membrane disruption stimulates PKA and PKC via purinergic signaling to potentiate cell membrane resealing in neighboring MDCK cells.

Hybrid digital signal processing and neural networks applications in PWRs

International Nuclear Information System (INIS)

Eryurek, E.; Upadhyaya, B.R.; Kavaklioglu, K.

1991-01-01

Signal validation and plant subsystem tracking in power and process industries require the prediction of one or more state variables. Both heteroassociative and auotassociative neural networks were applied for characterizing relationships among sets of signals. A multi-layer neural network paradigm was applied for sensor and process monitoring in a Pressurized Water Reactor (PWR). This nonlinear interpolation technique was found to be very effective for these applications

Towards a magnetoresistive platform for neural signal recording

Science.gov (United States)

Sharma, P. P.; Gervasoni, G.; Albisetti, E.; D'Ercoli, F.; Monticelli, M.; Moretti, D.; Forte, N.; Rocchi, A.; Ferrari, G.; Baldelli, P.; Sampietro, M.; Benfenati, F.; Bertacco, R.; Petti, D.

2017-05-01

A promising strategy to get deeper insight on brain functionalities relies on the investigation of neural activities at the cellular and sub-cellular level. In this framework, methods for recording neuron electrical activity have gained interest over the years. Main technological challenges are associated to finding highly sensitive detection schemes, providing considerable spatial and temporal resolution. Moreover, the possibility to perform non-invasive assays would constitute a noteworthy benefit. In this work, we present a magnetoresistive platform for the detection of the action potential propagation in neural cells. Such platform allows, in perspective, the in vitro recording of neural signals arising from single neurons, neural networks and brain slices.

The response of early neural genes to FGF signaling or inhibition of BMP indicate the absence of a conserved neural induction module

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Rogers Crystal D

2011-12-01

Full Text Available Abstract Background The molecular mechanism that initiates the formation of the vertebrate central nervous system has long been debated. Studies in Xenopus and mouse demonstrate that inhibition of BMP signaling is sufficient to induce neural tissue in explants or ES cells respectively, whereas studies in chick argue that instructive FGF signaling is also required for the expression of neural genes. Although additional signals may be involved in neural induction and patterning, here we focus on the roles of BMP inhibition and FGF8a. Results To address the question of necessity and sufficiency of BMP inhibition and FGF signaling, we compared the temporal expression of the five earliest genes expressed in the neuroectoderm and determined their requirements for induction at the onset of neural plate formation in Xenopus. Our results demonstrate that the onset and peak of expression of the genes vary and that they have different regulatory requirements and are therefore unlikely to share a conserved neural induction regulatory module. Even though all require inhibition of BMP for expression, some also require FGF signaling; expression of the early-onset pan-neural genes sox2 and foxd5α requires FGF signaling while other early genes, sox3, geminin and zicr1 are induced by BMP inhibition alone. Conclusions We demonstrate that BMP inhibition and FGF signaling induce neural genes independently of each other. Together our data indicate that although the spatiotemporal expression patterns of early neural genes are similar, the mechanisms involved in their expression are distinct and there are different signaling requirements for the expression of each gene.

Erythropoietin Receptor Signaling Is Membrane Raft Dependent

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McGraw, Kathy L.; Fuhler, Gwenny M.; Johnson, Joseph O.; Clark, Justine A.; Caceres, Gisela C.; Sokol, Lubomir; List, Alan F.

2012-01-01

Upon erythropoietin (Epo) engagement, Epo-receptor (R) homodimerizes to activate JAK2 and Lyn, which phosphorylate STAT5. Although recent investigations have identified key negative regulators of Epo-R signaling, little is known about the role of membrane localization in controlling receptor signal fidelity. Here we show a critical role for membrane raft (MR) microdomains in creation of discrete signaling platforms essential for Epo-R signaling. Treatment of UT7 cells with Epo induced MR assembly and coalescence. Confocal microscopy showed that raft aggregates significantly increased after Epo stimulation (mean, 4.3±1.4(SE) vs. 25.6±3.2 aggregates/cell; p≤0.001), accompanied by a >3-fold increase in cluster size (p≤0.001). Raft fraction immunoblotting showed Epo-R translocation to MR after Epo stimulation and was confirmed by fluorescence microscopy in Epo stimulated UT7 cells and primary erythroid bursts. Receptor recruitment into MR was accompanied by incorporation of JAK2, Lyn, and STAT5 and their activated forms. Raft disruption by cholesterol depletion extinguished Epo induced Jak2, STAT5, Akt and MAPK phosphorylation in UT7 cells and erythroid progenitors. Furthermore, inhibition of the Rho GTPases Rac1 or RhoA blocked receptor recruitment into raft fractions, indicating a role for these GTPases in receptor trafficking. These data establish a critical role for MR in recruitment and assembly of Epo-R and signal intermediates into discrete membrane signaling units. PMID:22509308

Slit/Robo1 signaling regulates neural tube development by balancing neuroepithelial cell proliferation and differentiation

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Wang, Guang; Li, Yan; Wang, Xiao-yu [Key Laboratory for Regenerative Medicine of The Ministry of Education, Department of Histology and Embryology, School of Medicine, Jinan University, Guangzhou 510632 (China); Han, Zhe [Institute of Vascular Biological Sciences, Guangdong Pharmaceutical University, Guangzhou 510224 (China); Chuai, Manli [College of Life Sciences Biocentre, University of Dundee, Dundee DD1 5EH (United Kingdom); Wang, Li-jing [Institute of Vascular Biological Sciences, Guangdong Pharmaceutical University, Guangzhou 510224 (China); Ho Lee, Kenneth Ka [Stem Cell and Regeneration Thematic Research Programme, School of Biomedical Sciences, Chinese University of Hong Kong, Shatin (Hong Kong); Geng, Jian-guo, E-mail: jgeng@umich.edu [Institute of Vascular Biological Sciences, Guangdong Pharmaceutical University, Guangzhou 510224 (China); Department of Biologic and Materials Sciences, University of Michigan School of Dentistry, Ann Arbor, MI 48109 (United States); Yang, Xuesong, E-mail: yang_xuesong@126.com [Key Laboratory for Regenerative Medicine of The Ministry of Education, Department of Histology and Embryology, School of Medicine, Jinan University, Guangzhou 510632 (China)

2013-05-01

Formation of the neural tube is the morphological hallmark for development of the embryonic central nervous system (CNS). Therefore, neural tube development is a crucial step in the neurulation process. Slit/Robo signaling was initially identified as a chemo-repellent that regulated axon growth cone elongation, but its role in controlling neural tube development is currently unknown. To address this issue, we investigated Slit/Robo1 signaling in the development of chick neCollege of Life Sciences Biocentre, University of Dundee, Dundee DD1 5EH, UKural tube and transgenic mice over-expressing Slit2. We disrupted Slit/Robo1 signaling by injecting R5 monoclonal antibodies into HH10 neural tubes to block the Robo1 receptor. This inhibited the normal development of the ventral body curvature and caused the spinal cord to curl up into a S-shape. Next, Slit/Robo1 signaling on one half-side of the chick embryo neural tube was disturbed by electroporation in ovo. We found that the morphology of the neural tube was dramatically abnormal after we interfered with Slit/Robo1 signaling. Furthermore, we established that silencing Robo1 inhibited cell proliferation while over-expressing Robo1 enhanced cell proliferation. We also investigated the effects of altering Slit/Robo1 expression on Sonic Hedgehog (Shh) and Pax7 expression in the developing neural tube. We demonstrated that over-expressing Robo1 down-regulated Shh expression in the ventral neural tube and resulted in the production of fewer HNK-1{sup +} migrating neural crest cells (NCCs). In addition, Robo1 over-expression enhanced Pax7 expression in the dorsal neural tube and increased the number of Slug{sup +} pre-migratory NCCs. Conversely, silencing Robo1 expression resulted in an enhanced Shh expression and more HNK-1{sup +} migrating NCCs but reduced Pax7 expression and fewer Slug{sup +} pre-migratory NCCs were observed. In conclusion, we propose that Slit/Robo1 signaling is involved in regulating neural tube

The development of a PZT-based microdrive for neural signal recording

International Nuclear Information System (INIS)

Park, Sangkyu; Yoon, Euisung; Park, Sukho; Lee, Sukchan; Shin, Hee-sup; Park, Hyunjun; Kim, Byungkyu; Kim, Daesoo; Park, Jongoh

2008-01-01

A hand-controlled microdrive has been used to obtain neural signals from rodents such as rats and mice. However, it places severe physical stress on the rodents during its manipulation, and this stress leads to alertness in the mice and low efficiency in obtaining neural signals from the mice. To overcome this issue, we developed a novel microdrive, which allows one to adjust the electrodes by a piezoelectric device (PZT) with high precision. Its mass is light enough to install on the mouse's head. The proposed microdrive has three H-type PZT actuators and their guiding structure. The operation principle of the microdrive is based on the well known inchworm mechanism. When the three PZT actuators are synchronized, linear motion of the electrode is produced along the guiding structure. The electrodes used for the recording of the neural signals from neuron cells were fixed at one of the PZT actuators. Our proposed microdrive has an accuracy of about 400 nm and a long stroke of about 5 mm. In response to formalin-induced pain, single unit activities are robustly measured at the thalamus with electrodes whose vertical depth is adjusted by the microdrive under urethane anesthesia. In addition, the microdrive was efficient in detecting neural signals from mice that were moving freely. Thus, the present study suggests that the PZT-based microdrive could be an alternative for the efficient detection of neural signals from mice during behavioral states without any stress to the mice. (technical note)

Sensor signal analysis by neural networks for surveillance in nuclear reactors

International Nuclear Information System (INIS)

Keyvan, S.; Rabelo, L.C.

1992-01-01

The application of neural networks as a tool for reactor diagnostics is examined here. Reactor pump signals utilized in a wear-out monitoring system developed for early detection of the degradation of a pump shaft are analyzed as a semi-benchmark test to study the feasibility of neural networks for monitoring and surveillance in nuclear reactors. The Adaptive Resonance Theory (ART 2 and ART 2-A) paradigm of neural networks is applied in this study. The signals are collected signals as well as generated signals simulating the wear progress. The wear-out monitoring system applies noise analysis techniques, and is capable of distinguishing these signals apart and providing a measure of the progress of the degradation. This paper presents the results of the analysis of these data, and provides an evaluation on the performance of ART 2-A and ART 2 for reactor signal analysis. The selection of ART 2 is due to its desired design principles such as unsupervised learning, stability-plasticity, search-direct access, and the match-reset tradeoffs

Exclusive photorelease of signalling lipids at the plasma membrane.

Science.gov (United States)

Nadler, André; Yushchenko, Dmytro A; Müller, Rainer; Stein, Frank; Feng, Suihan; Mulle, Christophe; Carta, Mario; Schultz, Carsten

2015-12-21

Photoactivation of caged biomolecules has become a powerful approach to study cellular signalling events. Here we report a method for anchoring and uncaging biomolecules exclusively at the outer leaflet of the plasma membrane by employing a photocleavable, sulfonated coumarin derivative. The novel caging group allows quantifying the reaction progress and efficiency of uncaging reactions in a live-cell microscopy setup, thereby greatly improving the control of uncaging experiments. We synthesized arachidonic acid derivatives bearing the new negatively charged or a neutral, membrane-permeant coumarin caging group to locally induce signalling either at the plasma membrane or on internal membranes in β-cells and brain slices derived from C57B1/6 mice. Uncaging at the plasma membrane triggers a strong enhancement of calcium oscillations in β-cells and a pronounced potentiation of synaptic transmission while uncaging inside cells blocks calcium oscillations in β-cells and causes a more transient effect on neuronal transmission, respectively. The precise subcellular site of arachidonic acid release is therefore crucial for signalling outcome in two independent systems.

Weak correlations between hemodynamic signals and ongoing neural activity during the resting state

Science.gov (United States)

Winder, Aaron T.; Echagarruga, Christina; Zhang, Qingguang; Drew, Patrick J.

2017-01-01

Spontaneous fluctuations in hemodynamic signals in the absence of a task or overt stimulation are used to infer neural activity. We tested this coupling by simultaneously measuring neural activity and changes in cerebral blood volume (CBV) in the somatosensory cortex of awake, head-fixed mice during periods of true rest, and during whisker stimulation and volitional whisking. Here we show that neurovascular coupling was similar across states, and large spontaneous CBV changes in the absence of sensory input were driven by volitional whisker and body movements. Hemodynamic signals during periods of rest were weakly correlated with neural activity. Spontaneous fluctuations in CBV and vessel diameter persisted when local neural spiking and glutamatergic input was blocked, and during blockade of noradrenergic receptors, suggesting a non-neuronal origin for spontaneous CBV fluctuations. Spontaneous hemodynamic signals reflect a combination of behavior, local neural activity, and putatively non-neural processes. PMID:29184204

Neural processing of auditory signals and modular neural control for sound tropism of walking machines

DEFF Research Database (Denmark)

Manoonpong, Poramate; Pasemann, Frank; Fischer, Joern

2005-01-01

and a neural preprocessing system together with a modular neural controller are used to generate a sound tropism of a four-legged walking machine. The neural preprocessing network is acting as a low-pass filter and it is followed by a network which discerns between signals coming from the left or the right....... The parameters of these networks are optimized by an evolutionary algorithm. In addition, a simple modular neural controller then generates the desired different walking patterns such that the machine walks straight, then turns towards a switched-on sound source, and then stops near to it....

Seismic signal auto-detecing from different features by using Convolutional Neural Network

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Huang, Y.; Zhou, Y.; Yue, H.; Zhou, S.

2017-12-01

We try Convolutional Neural Network to detect some features of seismic data and compare their efficience. The features include whether a signal is seismic signal or noise and the arrival time of P and S phase and each feature correspond to a Convolutional Neural Network. We first use traditional STA/LTA to recongnize some events and then use templete matching to find more events as training set for the Neural Network. To make the training set more various, we add some noise to the seismic data and make some synthetic seismic data and noise. The 3-component raw signal and time-frequancy ananlyze are used as the input data for our neural network. Our Training is performed on GPUs to achieve efficient convergence. Our method improved the precision in comparison with STA/LTA and template matching. We will move to recurrent neural network to see if this kind network is better in detect P and S phase.

Sphingosine-1-Phosphate (S1P) Signaling in Neural Progenitors.

Science.gov (United States)

Callihan, Phillip; Alqinyah, Mohammed; Hooks, Shelley B

2018-01-01

Sphingosine-1-phosphate (S1P) and its receptors are important in nervous system development. Reliable in vitro human model systems are needed to further define specific roles for S1P signaling in neural development. We have described S1P-regulated signaling, survival, and differentiation in a human embryonic stem cell-derived neuroepithelial progenitor cell line (hNP1) that expresses functional S1P receptors. These cells can be further differentiated to a neuronal cell type and therefore represent a good model system to study the role of S1P signaling in human neural development. The following sections describe in detail the culture and differentiation of hNP1 cells and two assays to measure S1P signaling in these cells.

Nonlinear signal processing using neural networks: Prediction and system modelling

Energy Technology Data Exchange (ETDEWEB)

Lapedes, A.; Farber, R.

1987-06-01

The backpropagation learning algorithm for neural networks is developed into a formalism for nonlinear signal processing. We illustrate the method by selecting two common topics in signal processing, prediction and system modelling, and show that nonlinear applications can be handled extremely well by using neural networks. The formalism is a natural, nonlinear extension of the linear Least Mean Squares algorithm commonly used in adaptive signal processing. Simulations are presented that document the additional performance achieved by using nonlinear neural networks. First, we demonstrate that the formalism may be used to predict points in a highly chaotic time series with orders of magnitude increase in accuracy over conventional methods including the Linear Predictive Method and the Gabor-Volterra-Weiner Polynomial Method. Deterministic chaos is thought to be involved in many physical situations including the onset of turbulence in fluids, chemical reactions and plasma physics. Secondly, we demonstrate the use of the formalism in nonlinear system modelling by providing a graphic example in which it is clear that the neural network has accurately modelled the nonlinear transfer function. It is interesting to note that the formalism provides explicit, analytic, global, approximations to the nonlinear maps underlying the various time series. Furthermore, the neural net seems to be extremely parsimonious in its requirements for data points from the time series. We show that the neural net is able to perform well because it globally approximates the relevant maps by performing a kind of generalized mode decomposition of the maps. 24 refs., 13 figs.

Reconstruction of periodic signals using neural networks

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José Danilo Rairán Antolines

2014-01-01

Full Text Available In this paper, we reconstruct a periodic signal by using two neural networks. The first network is trained to approximate the period of a signal, and the second network estimates the corresponding coefficients of the signal's Fourier expansion. The reconstruction strategy consists in minimizing the mean-square error via backpro-pagation algorithms over a single neuron with a sine transfer function. Additionally, this paper presents mathematical proof about the quality of the approximation as well as a first modification of the algorithm, which requires less data to reach the same estimation; thus making the algorithm suitable for real-time implementations.

Neural responses to multimodal ostensive signals in 5-month-old infants.

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Eugenio Parise

Full Text Available Infants' sensitivity to ostensive signals, such as direct eye contact and infant-directed speech, is well documented in the literature. We investigated how infants interpret such signals by assessing common processing mechanisms devoted to them and by measuring neural responses to their compounds. In Experiment 1, we found that ostensive signals from different modalities display overlapping electrophysiological activity in 5-month-old infants, suggesting that these signals share neural processing mechanisms independently of their modality. In Experiment 2, we found that the activation to ostensive signals from different modalities is not additive to each other, but rather reflects the presence of ostension in either stimulus stream. These data support the thesis that ostensive signals obligatorily indicate to young infants that communication is directed to them.

Neural redundancy applied to the parity space for signal validation

International Nuclear Information System (INIS)

Mol, Antonio Carlos de Abreu; Pereira, Claudio Marcio Nascimento Abreu; Martinez, Aquilino Senra

2005-01-01

The objective of signal validation is to provide more reliable information from the plant sensor data The method presented in this work introduces the concept of neural redundancy and applies it to the space parity method [1] to overcome an inherent deficiency of this method - the determination of the best estimative of the redundant measures when they are inconsistent. The concept of neural redundancy consists on the calculation of a redundancy through neural networks based on the time series of the own state variable. Therefore, neural networks, dynamically trained with the time series, will estimate the current value of the own measure, which will be used as referee of the redundant measures in the parity space. For this purpose the neural network should have the capacity to supply the neural redundancy in real time and with maximum error corresponding to the group deviation. The historical series should be enough to allow the estimate of the next value, during transients and at the same time, it should be optimized to facilitate the retraining of the neural network to each acquisition. In order to have the capacity to reproduce the tendency of the time series even under accident condition, the dynamic training of the neural network privileges the recent points of the time series. The tests accomplished with simulated data of a nuclear plant, demonstrated that this method applied on the parity space method improves the signal validation process. (author)

Neural redundancy applied to the parity space for signal validation

Energy Technology Data Exchange (ETDEWEB)

Mol, Antonio Carlos de Abreu; Pereira, Claudio Marcio Nascimento Abreu [Instituto de Engenharia Nuclear (IEN), Rio de Janeiro, RJ (Brazil)]. E-mail: cmnap@ien.gov.br; Martinez, Aquilino Senra [Universidade Federal, Rio de Janeiro, RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia]. E-mail: aquilino@lmp.br

2005-07-01

The objective of signal validation is to provide more reliable information from the plant sensor data The method presented in this work introduces the concept of neural redundancy and applies it to the space parity method [1] to overcome an inherent deficiency of this method - the determination of the best estimative of the redundant measures when they are inconsistent. The concept of neural redundancy consists on the calculation of a redundancy through neural networks based on the time series of the own state variable. Therefore, neural networks, dynamically trained with the time series, will estimate the current value of the own measure, which will be used as referee of the redundant measures in the parity space. For this purpose the neural network should have the capacity to supply the neural redundancy in real time and with maximum error corresponding to the group deviation. The historical series should be enough to allow the estimate of the next value, during transients and at the same time, it should be optimized to facilitate the retraining of the neural network to each acquisition. In order to have the capacity to reproduce the tendency of the time series even under accident condition, the dynamic training of the neural network privileges the recent points of the time series. The tests accomplished with simulated data of a nuclear plant, demonstrated that this method applied on the parity space method improves the signal validation process. (author)

WNT Signaling Is Required for Peritoneal Membrane Angiogenesis.

Science.gov (United States)

Padwal, Manreet Kaur; Cheng, Genyang; Liu, Limin; Boivin, Felix J; Gangji, Azim; Brimble, Kenneth Scott; Bridgewater, Darren; Margetts, Peter J

2018-01-24

The WNT signaling pathway is involved in wound healing and fibrosis. We evaluated the WNT signaling pathway in peritoneal membrane injury. We assessed WNT1 protein expression in the peritoneal effluents of 54 stable peritoneal dialysis (PD) patients and WNT-related gene expression in ex vivo mesothelial cell cultures from 21 PD patients. In a transforming growth factor beta (TGFB) mediated animal model of peritoneal fibrosis, we evaluated regulation of the WNT pathway and the effect of WNT inhibition on peritoneal fibrosis and angiogenesis. WNT1 and WNT2 gene expression were positively correlated with peritoneal membrane solute transport in PD patients. In the mouse peritoneum, TGFΒ-induced peritoneal fibrosis was associated with increased expression of WNT2 and WNT4. Peritoneal b-catenin protein was significantly upregulated after infection with AdTGFB along with elements of the WNT signaling pathway. Treatment with a b-catenin inhibitor (ICG-001) in mice with AdTGFB-induced peritoneal fibrosis resulted in attenuation of peritoneal angiogenesis and reduced vascular endothelial growth factor. Similar results were also observed with the WNT antagonist Dickkopf related protein (DKK) 1. In addition to this, DKK-1 blocked epithelial to mesenchymal transition and increased levels of the cell adhesion protein E-cadherin. We provide evidence that WNT signaling is active in the setting of experimental peritoneal fibrosis and WNT1 correlates with patient peritoneal membrane solute transport in PD patients. Intervention in this pathway is a possible therapy for peritoneal membrane injury.

Neural network committees for finger joint angle estimation from surface EMG signals

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Reddy Narender P

2009-01-01

Full Text Available Abstract Background In virtual reality (VR systems, the user's finger and hand positions are sensed and used to control the virtual environments. Direct biocontrol of VR environments using surface electromyography (SEMG signals may be more synergistic and unconstraining to the user. The purpose of the present investigation was to develop a technique to predict the finger joint angle from the surface EMG measurements of the extensor muscle using neural network models. Methodology SEMG together with the actual joint angle measurements were obtained while the subject was performing flexion-extension rotation of the index finger at three speeds. Several neural networks were trained to predict the joint angle from the parameters extracted from the SEMG signals. The best networks were selected to form six committees. The neural network committees were evaluated using data from new subjects. Results There was hysteresis in the measured SMEG signals during the flexion-extension cycle. However, neural network committees were able to predict the joint angle with reasonable accuracy. RMS errors ranged from 0.085 ± 0.036 for fast speed finger-extension to 0.147 ± 0.026 for slow speed finger extension, and from 0.098 ± 0.023 for the fast speed finger flexion to 0.163 ± 0.054 for slow speed finger flexion. Conclusion Although hysteresis was observed in the measured SEMG signals, the committees of neural networks were able to predict the finger joint angle from SEMG signals.

Hepatocyte growth factor/scatter factor-MET signaling in neural crest-derived melanocyte development.

Science.gov (United States)

Kos, L; Aronzon, A; Takayama, H; Maina, F; Ponzetto, C; Merlino, G; Pavan, W

1999-02-01

The mechanisms governing development of neural crest-derived melanocytes, and how alterations in these pathways lead to hypopigmentation disorders, are not completely understood. Hepatocyte growth factor/scatter factor (HGF/SF) signaling through the tyrosine-kinase receptor, MET, is capable of promoting the proliferation, increasing the motility, and maintaining high tyrosinase activity and melanin synthesis of melanocytes in vitro. In addition, transgenic mice that ubiquitously overexpress HGF/SF demonstrate hyperpigmentation in the skin and leptomenigenes and develop melanomas. To investigate whether HGF/ SF-MET signaling is involved in the development of neural crest-derived melanocytes, transgenic embryos, ubiquitously overexpressing HGF/SF, were analyzed. In HGF/SF transgenic embryos, the distribution of melanoblasts along the characteristic migratory pathway was not affected. However, additional ectopically localized melanoblasts were also observed in the dorsal root ganglia and neural tube, as early as 11.5 days post coitus (p.c.). We utilized an in vitro neural crest culture assay to further explore the role of HGF/SF-MET signaling in neural crest development. HGF/SF added to neural crest cultures increased melanoblast number, permitted differentiation into pigmented melanocytes, promoted melanoblast survival, and could replace mast-cell growth factor/Steel factor (MGF) in explant cultures. To examine whether HGF/SF-MET signaling is required for the proper development of melanocytes, embryos with a targeted Met null mutation (Met-/-) were analysed. In Met-/- embryos, melanoblast number and location were not overtly affected up to 14 days p.c. These results demonstrate that HGF/SF-MET signaling influences, but is not required for, the initial development of neural crest-derived melanocytes in vivo and in vitro.

Human Age Recognition by Electrocardiogram Signal Based on Artificial Neural Network

Science.gov (United States)

Dasgupta, Hirak

2016-12-01

The objective of this work is to make a neural network function approximation model to detect human age from the electrocardiogram (ECG) signal. The input vectors of the neural network are the Katz fractal dimension of the ECG signal, frequencies in the QRS complex, male or female (represented by numeric constant) and the average of successive R-R peak distance of a particular ECG signal. The QRS complex has been detected by short time Fourier transform algorithm. The successive R peak has been detected by, first cutting the signal into periods by auto-correlation method and then finding the absolute of the highest point in each period. The neural network used in this problem consists of two layers, with Sigmoid neuron in the input and linear neuron in the output layer. The result shows the mean of errors as -0.49, 1.03, 0.79 years and the standard deviation of errors as 1.81, 1.77, 2.70 years during training, cross validation and testing with unknown data sets, respectively.

Interactions of Ras proteins with the plasma membrane and their roles in signaling.

Science.gov (United States)

Eisenberg, Sharon; Henis, Yoav I

2008-01-01

The complex dynamic structure of the plasma membrane plays critical roles in cellular signaling; interactions with the membrane lipid milieu, spatial segregation within and between cellular membranes and/or targeting to specific membrane-associated scaffolds are intimately involved in many signal transduction pathways. In this review, we focus on the membrane interactions of Ras proteins. These small GTPases play central roles in the regulation of cell growth and proliferation, and their excessive activation is commonly encountered in human tumors. Ras proteins associate with the membrane continuously via C-terminal lipidation and additional interactions in both their inactive and active forms; this association, as well as the targeting of specific Ras isoforms to plasma membrane microdomains and to intracellular organelles, have recently been implicated in Ras signaling and oncogenic potential. We discuss biochemical and biophysical evidence for the roles of specific domains of Ras proteins in mediating their association with the plasma membrane, and consider the potential effects of lateral segregation and interactions with membrane-associated protein assemblies on the signaling outcomes.

Canonical Wnt signaling transiently stimulates proliferation and enhances neurogenesis in neonatal neural progenitor cultures

International Nuclear Information System (INIS)

Hirsch, Cordula; Campano, Louise M.; Woehrle, Simon; Hecht, Andreas

2007-01-01

Canonical Wnt signaling triggers the formation of heterodimeric transcription factor complexes consisting of β-catenin and T cell factors, and thereby controls the execution of specific genetic programs. During the expansion and neurogenic phases of embryonic neural development canonical Wnt signaling initially controls proliferation of neural progenitor cells, and later neuronal differentiation. Whether Wnt growth factors affect neural progenitor cells postnatally is not known. Therefore, we have analyzed the impact of Wnt signaling on neural progenitors isolated from cerebral cortices of newborn mice. Expression profiling of pathway components revealed that these cells are fully equipped to respond to Wnt signals. However, Wnt pathway activation affected only a subset of neonatal progenitors and elicited a limited increase in proliferation and neuronal differentiation in distinct subsets of cells. Moreover, Wnt pathway activation only transiently stimulated S-phase entry but did not support long-term proliferation of progenitor cultures. The dampened nature of the Wnt response correlates with the predominant expression of inhibitory pathway components and the rapid actuation of negative feedback mechanisms. Interestingly, in differentiating cell cultures activation of canonical Wnt signaling reduced Hes1 and Hes5 expression suggesting that during postnatal neural development, Wnt/β-catenin signaling enhances neurogenesis from progenitor cells by interfering with Notch pathway activity

Cell biology symposium: Membrane trafficking and signal transduction

Science.gov (United States)

In general, membrane trafficking is a broad group of processes where proteins and other large molecules are distributed throughout the cell as well as adjacent extracellular spaces. Whereas signal transduction is a process where signals are transmitted through a series of chemical or molecular event...

Comprehensive quantitative comparison of the membrane proteome, phosphoproteome, and sialiome of human embryonic and neural stem cells

DEFF Research Database (Denmark)

Melo-Braga, Marcella Nunes; Schulz, Melanie; Liu, Qiuyue

2014-01-01

Human embryonic stem cells (hESCs) can differentiate into neural stem cells (NSCs), which can further be differentiated into neurons and glia cells. Therefore, these cells have huge potential as source for treatment of neurological diseases. Membrane-associated proteins are very important......ESCs and NSCs as well as to investigate potential new markers for these two cell stages, we performed large-scale quantitative membrane-proteomic of hESCs and NSCs. This approach employed membrane purification followed by peptide dimethyl labeling and peptide enrichment to study the membrane subproteome as well...... in which 78% of phosphopeptides were identified with ≥99% confidence in site assignment and 1810 unique formerly sialylated N-linked glycopeptides. Several proteins were identified as significantly regulated in hESCs and NSC, including proteins involved in the early embryonic and neural development...

Detecting modulated signals in modulated noise: (II) neural thresholds in the songbird forebrain.

Science.gov (United States)

Bee, Mark A; Buschermöhle, Michael; Klump, Georg M

2007-10-01

Sounds in the real world fluctuate in amplitude. The vertebrate auditory system exploits patterns of amplitude fluctuations to improve signal detection in noise. One experimental paradigm demonstrating these general effects has been used in psychophysical studies of 'comodulation detection difference' (CDD). The CDD effect refers to the fact that thresholds for detecting a modulated, narrowband noise signal are lower when the envelopes of flanking bands of modulated noise are comodulated with each other, but fluctuate independently of the signal compared with conditions in which the envelopes of the signal and flanking bands are all comodulated. Here, we report results from a study of the neural correlates of CDD in European starlings (Sturnus vulgaris). We manipulated: (i) the envelope correlations between a narrowband noise signal and a masker comprised of six flanking bands of noise; (ii) the signal onset delay relative to masker onset; (iii) signal duration; and (iv) masker spectrum level. Masked detection thresholds were determined from neural responses using signal detection theory. Across conditions, the magnitude of neural CDD ranged between 2 and 8 dB, which is similar to that reported in a companion psychophysical study of starlings [U. Langemann & G.M. Klump (2007) Eur. J. Neurosci., 26, 1969-1978]. We found little evidence to suggest that neural CDD resulted from the across-channel processing of auditory grouping cues related to common envelope fluctuations and synchronous onsets between the signal and flanking bands. We discuss a within-channel model of peripheral processing that explains many of our results.

A digitally assisted, signal folding neural recording amplifier.

Science.gov (United States)

Chen, Yi; Basu, Arindam; Liu, Lei; Zou, Xiaodan; Rajkumar, Ramamoorthy; Dawe, Gavin Stewart; Je, Minkyu

2014-08-01

A novel signal folding and reconstruction scheme for neural recording applications that exploits the 1/f(n) characteristics of neural signals is described in this paper. The amplified output is 'folded' into a predefined range of voltages by using comparison and reset circuits along with the core amplifier. After this output signal is digitized and transmitted, a reconstruction algorithm can be applied in the digital domain to recover the amplified signal from the folded waveform. This scheme enables the use of an analog-to-digital convertor with less number of bits for the same effective dynamic range. It also reduces the transmission data rate of the recording chip. Both of these features allow power and area savings at the system level. Other advantages of the proposed topology are increased reliability due to the removal of pseudo-resistors, lower harmonic distortion and low-voltage operation. An analysis of the reconstruction error introduced by this scheme is presented along with a behavioral model to provide a quick estimate of the post reconstruction dynamic range. Measurement results from two different core amplifier designs in 65 nm and 180 nm CMOS processes are presented to prove the generality of the proposed scheme in the neural recording applications. Operating from a 1 V power supply, the amplifier in 180 nm CMOS has a gain of 54.2 dB, bandwidth of 5.7 kHz, input referred noise of 3.8 μVrms and power dissipation of 2.52 μW leading to a NEF of 3.1 in spike band. It exhibits a dynamic range of 66 dB and maximum SNDR of 43 dB in LFP band. It also reduces system level power (by reducing the number of bits in the ADC by 2) as well as data rate to 80% of a conventional design. In vivo measurements validate the ability of this amplifier to simultaneously record spike and LFP signals.

Model for neural signaling leap statistics

International Nuclear Information System (INIS)

Chevrollier, Martine; Oria, Marcos

2011-01-01

We present a simple model for neural signaling leaps in the brain considering only the thermodynamic (Nernst) potential in neuron cells and brain temperature. We numerically simulated connections between arbitrarily localized neurons and analyzed the frequency distribution of the distances reached. We observed qualitative change between Normal statistics (with T 37.5 0 C, awaken regime) and Levy statistics (T = 35.5 0 C, sleeping period), characterized by rare events of long range connections.

Model for neural signaling leap statistics

Science.gov (United States)

Chevrollier, Martine; Oriá, Marcos

2011-03-01

We present a simple model for neural signaling leaps in the brain considering only the thermodynamic (Nernst) potential in neuron cells and brain temperature. We numerically simulated connections between arbitrarily localized neurons and analyzed the frequency distribution of the distances reached. We observed qualitative change between Normal statistics (with T = 37.5°C, awaken regime) and Lévy statistics (T = 35.5°C, sleeping period), characterized by rare events of long range connections.

Phosphatidylinositol 3-phosphates-at the interface between cell signalling and membrane traffic.

Science.gov (United States)

Marat, Andrea L; Haucke, Volker

2016-03-15

Phosphoinositides (PIs) form a minor class of phospholipids with crucial functions in cell physiology, ranging from cell signalling and motility to a role as signposts of compartmental membrane identity. Phosphatidylinositol 3-phosphates are present at the plasma membrane and within the endolysosomal system, where they serve as key regulators of both cell signalling and of intracellular membrane traffic. Here, we provide an overview of the metabolic pathways that regulate cellular synthesis of PI 3-phosphates at distinct intracellular sites and discuss the mechanisms by which these lipids regulate cell signalling and membrane traffic. Finally, we provide a framework for how PI 3-phosphate metabolism is integrated into the cellular network. © 2016 The Authors.

Spatio-temporal Model of Endogenous ROS and Raft-Dependent WNT/Beta-Catenin Signaling Driving Cell Fate Commitment in Human Neural Progenitor Cells

Science.gov (United States)

Haack, Fiete; Lemcke, Heiko; Ewald, Roland; Rharass, Tareck; Uhrmacher, Adelinde M.

2015-01-01

Canonical WNT/β-catenin signaling is a central pathway in embryonic development, but it is also connected to a number of cancers and developmental disorders. Here we apply a combined in-vitro and in-silico approach to investigate the spatio-temporal regulation of WNT/β-catenin signaling during the early neural differentiation process of human neural progenitors cells (hNPCs), which form a new prospect for replacement therapies in the context of neurodegenerative diseases. Experimental measurements indicate a second signal mechanism, in addition to canonical WNT signaling, being involved in the regulation of nuclear β-catenin levels during the cell fate commitment phase of neural differentiation. We find that the biphasic activation of β-catenin signaling observed experimentally can only be explained through a model that combines Reactive Oxygen Species (ROS) and raft dependent WNT/β-catenin signaling. Accordingly after initiation of differentiation endogenous ROS activates DVL in a redox-dependent manner leading to a transient activation of down-stream β-catenin signaling, followed by continuous auto/paracrine WNT signaling, which crucially depends on lipid rafts. Our simulation studies further illustrate the elaborate spatio-temporal regulation of DVL, which, depending on its concentration and localization, may either act as direct inducer of the transient ROS/β-catenin signal or as amplifier during continuous auto-/parcrine WNT/β-catenin signaling. In addition we provide the first stochastic computational model of WNT/β-catenin signaling that combines membrane-related and intracellular processes, including lipid rafts/receptor dynamics as well as WNT- and ROS-dependent β-catenin activation. The model’s predictive ability is demonstrated under a wide range of varying conditions for in-vitro and in-silico reference data sets. Our in-silico approach is realized in a multi-level rule-based language, that facilitates the extension and modification of the

Neural signal processing for identifying failed fuel rods in nuclear reactors

International Nuclear Information System (INIS)

Seixas, Jose M. de; Soares Filho, William; Pereira, Wagner C.A.; Teles, Claudio C.B.

2002-01-01

Ultrasonic pulses were used for automatic detection of failed nuclear fuel rods. For experimental tests of the proposed method, an assembly prototype of 16 x 16 rods was built by using genuine rods but without fuel inside (just air). Some rods were partially filled with water to simulate cracked rods. Using neural signal processing on the received echoes of the emitted ultrasonic pulses, a detection efficiency of 97% was obtained. Neural detection is shown to outperform other classical discriminating methods and can also reveal important features of the signal structure of the received echoes. (author)

Music Signal Processing Using Vector Product Neural Networks

Science.gov (United States)

Fan, Z. C.; Chan, T. S.; Yang, Y. H.; Jang, J. S. R.

2017-05-01

We propose a novel neural network model for music signal processing using vector product neurons and dimensionality transformations. Here, the inputs are first mapped from real values into three-dimensional vectors then fed into a three-dimensional vector product neural network where the inputs, outputs, and weights are all three-dimensional values. Next, the final outputs are mapped back to the reals. Two methods for dimensionality transformation are proposed, one via context windows and the other via spectral coloring. Experimental results on the iKala dataset for blind singing voice separation confirm the efficacy of our model.

SoxB1-driven transcriptional network underlies neural-specific interpretation of morphogen signals.

Science.gov (United States)

Oosterveen, Tony; Kurdija, Sanja; Ensterö, Mats; Uhde, Christopher W; Bergsland, Maria; Sandberg, Magnus; Sandberg, Rickard; Muhr, Jonas; Ericson, Johan

2013-04-30

The reiterative deployment of a small cadre of morphogen signals underlies patterning and growth of most tissues during embyogenesis, but how such inductive events result in tissue-specific responses remains poorly understood. By characterizing cis-regulatory modules (CRMs) associated with genes regulated by Sonic hedgehog (Shh), retinoids, or bone morphogenetic proteins in the CNS, we provide evidence that the neural-specific interpretation of morphogen signaling reflects a direct integration of these pathways with SoxB1 proteins at the CRM level. Moreover, expression of SoxB1 proteins in the limb bud confers on mesodermal cells the potential to activate neural-specific target genes upon Shh, retinoid, or bone morphogenetic protein signaling, and the collocation of binding sites for SoxB1 and morphogen-mediatory transcription factors in CRMs faithfully predicts neural-specific gene activity. Thus, an unexpectedly simple transcriptional paradigm appears to conceptually explain the neural-specific interpretation of pleiotropic signaling during vertebrate development. Importantly, genes induced in a SoxB1-dependent manner appear to constitute repressive gene regulatory networks that are directly interlinked at the CRM level to constrain the regional expression of patterning genes. Accordingly, not only does the topology of SoxB1-driven gene regulatory networks provide a tissue-specific mode of gene activation, but it also determines the spatial expression pattern of target genes within the developing neural tube.

ETOH inhibits embryonic neural stem/precursor cell proliferation via PLD signaling

International Nuclear Information System (INIS)

Fujita, Yuko; Hiroyama, Masami; Sanbe, Atsushi; Yamauchi, Junji; Murase, Shoko; Tanoue, Akito

2008-01-01

While a mother's excessive alcohol consumption during pregnancy is known to have adverse effects on fetal neural development, little is known about the underlying mechanism of these effects. In order to investigate these mechanisms, we investigated the toxic effect of ethanol (ETOH) on neural stem/precursor cell (NSC) proliferation. In cultures of NSCs, phospholipase D (PLD) is activated following stimulation with epidermal growth factor (EGF) and fibroblast growth factor 2 (FGF2). Exposure of NSCs to ETOH suppresses cell proliferation, while it has no effect on cell death. Phosphatidic acid (PA), which is a signaling messenger produced by PLD, reverses ETOH inhibition of NSC proliferation. Blocking the PLD signal by 1-butanol suppresses the proliferation. ETOH-induced suppression of NSC proliferation and the protective effect of PA for ETOH-induced suppression are mediated through extracellular signal-regulated kinase signaling. These results indicate that exposure to ETOH impairs NSC proliferation by altering the PLD signaling pathway

Applications of autoassociative neural networks for signal validation in accident management

International Nuclear Information System (INIS)

Fantoni, P.; Mazzola, A.

1994-01-01

The OECD Halden Reactor Project has been working for several years with computer based systems for determination on plant status including early fault detection and signal validation. The method here presented explores the possibility to use a neural network approach to validate important process signals during normal and abnormal plant conditions. In BWR plants, signal validation has two important applications: reliable thermal limits calculation and reliable inputs to other computerized systems that support the operator during accident scenarious. This work shows how a properly trained autoassociative neural network can promptly detect faulty process signal measurements and produce a best estimate of the actual process value. Noise has been artificially added to the input to evaluate the network ability to respond in a very low signal to noise ratio environment. Training and test datasets have been simulated by the real time transient simulator code APROS. Future development addresses the validation of the model through the use of real data from the plant. (author). 5 refs, 17 figs

Model for neural signaling leap statistics

Energy Technology Data Exchange (ETDEWEB)

Chevrollier, Martine; Oria, Marcos, E-mail: oria@otica.ufpb.br [Laboratorio de Fisica Atomica e Lasers Departamento de Fisica, Universidade Federal da ParaIba Caixa Postal 5086 58051-900 Joao Pessoa, Paraiba (Brazil)

2011-03-01

We present a simple model for neural signaling leaps in the brain considering only the thermodynamic (Nernst) potential in neuron cells and brain temperature. We numerically simulated connections between arbitrarily localized neurons and analyzed the frequency distribution of the distances reached. We observed qualitative change between Normal statistics (with T 37.5{sup 0}C, awaken regime) and Levy statistics (T = 35.5{sup 0}C, sleeping period), characterized by rare events of long range connections.

Distributed sensing signal analysis of deformable plate/membrane mirrors

Science.gov (United States)

Lu, Yifan; Yue, Honghao; Deng, Zongquan; Tzou, Hornsen

2017-11-01

Deformable optical mirrors usually play key roles in aerospace and optical structural systems applied to space telescopes, radars, solar collectors, communication antennas, etc. Limited by the payload capacity of current launch vehicles, the deformable mirrors should be lightweight and are generally made of ultra-thin plates or even membranes. These plate/membrane mirrors are susceptible to external excitations and this may lead to surface inaccuracy and jeopardize relevant working performance. In order to investigate the modal vibration characteristics of the mirror, a piezoelectric layer is fully laminated on its non-reflective side to serve as sensors. The piezoelectric layer is segmented into infinitesimal elements so that microscopic distributed sensing signals can be explored. In this paper, the deformable mirror is modeled as a pre-tensioned plate and membrane respectively and sensing signal distributions of the two models are compared. Different pre-tensioning forces are also applied to reveal the tension effects on the mode shape and sensing signals of the mirror. Analytical results in this study could be used as guideline of optimal sensor/actuator placement for deformable space mirrors.

Notch signaling patterns neurogenic ectoderm and regulates the asymmetric division of neural progenitors in sea urchin embryos.

Science.gov (United States)

Mellott, Dan O; Thisdelle, Jordan; Burke, Robert D

2017-10-01

We have examined regulation of neurogenesis by Delta/Notch signaling in sea urchin embryos. At gastrulation, neural progenitors enter S phase coincident with expression of Sp-SoxC. We used a BAC containing GFP knocked into the Sp-SoxC locus to label neural progenitors. Live imaging and immunolocalizations indicate that Sp-SoxC-expressing cells divide to produce pairs of adjacent cells expressing GFP. Over an interval of about 6 h, one cell fragments, undergoes apoptosis and expresses high levels of activated Caspase3. A Notch reporter indicates that Notch signaling is activated in cells adjacent to cells expressing Sp-SoxC. Inhibition of γ-secretase, injection of Sp-Delta morpholinos or CRISPR/Cas9-induced mutation of Sp-Delta results in supernumerary neural progenitors and neurons. Interfering with Notch signaling increases neural progenitor recruitment and pairs of neural progenitors. Thus, Notch signaling restricts the number of neural progenitors recruited and regulates the fate of progeny of the asymmetric division. We propose a model in which localized signaling converts ectodermal and ciliary band cells to neural progenitors that divide asymmetrically to produce a neural precursor and an apoptotic cell. © 2017. Published by The Company of Biologists Ltd.

Spatial modeling of the membrane-cytosolic interface in protein kinase signal transduction.

Directory of Open Access Journals (Sweden)

Wolfgang Giese

2018-04-01

Full Text Available The spatial architecture of signaling pathways and the interaction with cell size and morphology are complex, but little understood. With the advances of single cell imaging and single cell biology, it becomes crucial to understand intracellular processes in time and space. Activation of cell surface receptors often triggers a signaling cascade including the activation of membrane-attached and cytosolic signaling components, which eventually transmit the signal to the cell nucleus. Signaling proteins can form steep gradients in the cytosol, which cause strong cell size dependence. We show that the kinetics at the membrane-cytosolic interface and the ratio of cell membrane area to the enclosed cytosolic volume change the behavior of signaling cascades significantly. We suggest an estimate of average concentration for arbitrary cell shapes depending on the cell volume and cell surface area. The normalized variance, known from image analysis, is suggested as an alternative measure to quantify the deviation from the average concentration. A mathematical analysis of signal transduction in time and space is presented, providing analytical solutions for different spatial arrangements of linear signaling cascades. Quantification of signaling time scales reveals that signal propagation is faster at the membrane than at the nucleus, while this time difference decreases with the number of signaling components in the cytosol. Our investigations are complemented by numerical simulations of non-linear cascades with feedback and asymmetric cell shapes. We conclude that intracellular signal propagation is highly dependent on cell geometry and, thereby, conveys information on cell size and shape to the nucleus.

G-protein signaling leverages subunit-dependent membrane affinity to differentially control βγ translocation to intracellular membranes.

Science.gov (United States)

O'Neill, Patrick R; Karunarathne, W K Ajith; Kalyanaraman, Vani; Silvius, John R; Gautam, N

2012-12-18

Activation of G-protein heterotrimers by receptors at the plasma membrane stimulates βγ-complex dissociation from the α-subunit and translocation to internal membranes. This intermembrane movement of lipid-modified proteins is a fundamental but poorly understood feature of cell signaling. The differential translocation of G-protein βγ-subunit types provides a valuable experimental model to examine the movement of signaling proteins between membranes in a living cell. We used live cell imaging, mathematical modeling, and in vitro measurements of lipidated fluorescent peptide dissociation from vesicles to determine the mechanistic basis of the intermembrane movement and identify the interactions responsible for differential translocation kinetics in this family of evolutionarily conserved proteins. We found that the reversible translocation is mediated by the limited affinity of the βγ-subunits for membranes. The differential kinetics of the βγ-subunit types are determined by variations among a set of basic and hydrophobic residues in the γ-subunit types. G-protein signaling thus leverages the wide variation in membrane dissociation rates among different γ-subunit types to differentially control βγ-translocation kinetics in response to receptor activation. The conservation of primary structures of γ-subunits across mammalian species suggests that there can be evolutionary selection for primary structures that confer specific membrane-binding affinities and consequent rates of intermembrane movement.

Erythropoietin receptor signaling is membrane raft dependent

NARCIS (Netherlands)

K.L. McGraw (Kathy); G.M. Fuhler (Gwenny); J.O. Johnson (Joseph); J.A. Clark (Justine); G.C. Caceres (Gisela); L. Sokol (Lubomir); A.F. List (Alan)

2012-01-01

textabstractUpon erythropoietin (Epo) engagement, Epo-receptor (R) homodimerizes to activate JAK2 and Lyn, which phosphorylate STAT5. Although recent investigations have identified key negative regulators of Epo-R signaling, little is known about the role of membrane localization in controlling

Characterization of Radar Signals Using Neural Networks

Science.gov (United States)

1990-12-01

e***e*e*eeeeeeeeeeeesseeeeeese*eee*e*e************s /* Function Name: load.input.ptterns Number: 4.1 /* Description: This function determines wether ...XSE.last.layer Number: 8.5 */ /* Description: The function determines wether to backpropate the *f /* parameter by the sigmoidal or linear update...Sigmoidal Function," Mathematics of Control, Signals and Systems, 2:303-314 (March 1989). 6. Dayhoff, Judith E. Neural Network Architectures. New York: Van

A conserved signaling network monitors delivery of sphingolipids to the plasma membrane in budding yeast.

Science.gov (United States)

Clarke, Jesse; Dephoure, Noah; Horecka, Ira; Gygi, Steven; Kellogg, Douglas

2017-10-01

In budding yeast, cell cycle progression and ribosome biogenesis are dependent on plasma membrane growth, which ensures that events of cell growth are coordinated with each other and with the cell cycle. However, the signals that link the cell cycle and ribosome biogenesis to membrane growth are poorly understood. Here we used proteome-wide mass spectrometry to systematically discover signals associated with membrane growth. The results suggest that membrane trafficking events required for membrane growth generate sphingolipid-dependent signals. A conserved signaling network appears to play an essential role in signaling by responding to delivery of sphingolipids to the plasma membrane. In addition, sphingolipid-dependent signals control phosphorylation of protein kinase C (Pkc1), which plays an essential role in the pathways that link the cell cycle and ribosome biogenesis to membrane growth. Together these discoveries provide new clues as to how growth--dependent signals control cell growth and the cell cycle. © 2017 Clarke et al. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Bile acids modulate signaling by functional perturbation of plasma membrane domains.

Science.gov (United States)

Zhou, Yong; Maxwell, Kelsey N; Sezgin, Erdinc; Lu, Maryia; Liang, Hong; Hancock, John F; Dial, Elizabeth J; Lichtenberger, Lenard M; Levental, Ilya

2013-12-13

Eukaryotic cell membranes are organized into functional lipid and protein domains, the most widely studied being membrane rafts. Although rafts have been associated with numerous plasma membrane functions, the mechanisms by which these domains themselves are regulated remain undefined. Bile acids (BAs), whose primary function is the solubilization of dietary lipids for digestion and absorption, can affect cells by interacting directly with membranes. To investigate whether these interactions affected domain organization in biological membranes, we assayed the effects of BAs on biomimetic synthetic liposomes, isolated plasma membranes, and live cells. At cytotoxic concentrations, BAs dissolved synthetic and cell-derived membranes and disrupted live cell plasma membranes, implicating plasma membrane damage as the mechanism for BA cellular toxicity. At subtoxic concentrations, BAs dramatically stabilized domain separation in Giant Plasma Membrane Vesicles without affecting protein partitioning between coexisting domains. Domain stabilization was the result of BA binding to and disordering the nonraft domain, thus promoting separation by enhancing domain immiscibility. Consistent with the physical changes observed in synthetic and isolated biological membranes, BAs reorganized intact cell membranes, as evaluated by the spatial distribution of membrane-anchored Ras isoforms. Nanoclustering of K-Ras, related to nonraft membrane domains, was enhanced in intact plasma membranes, whereas the organization of H-Ras was unaffected. BA-induced changes in Ras lateral segregation potentiated EGF-induced signaling through MAPK, confirming the ability of BAs to influence cell signal transduction by altering the physical properties of the plasma membrane. These observations suggest general, membrane-mediated mechanisms by which biological amphiphiles can produce their cellular effects.

Lipid rafts generate digital-like signal transduction in cell plasma membranes.

Science.gov (United States)

Suzuki, Kenichi G N

2012-06-01

Lipid rafts are meso-scale (5-200 nm) cell membrane domains where signaling molecules assemble and function. However, due to their dynamic nature, it has been difficult to unravel the mechanism of signal transduction in lipid rafts. Recent advanced imaging techniques have revealed that signaling molecules are frequently, but transiently, recruited to rafts with the aid of protein-protein, protein-lipid, and/or lipid-lipid interactions. Individual signaling molecules within the raft are activated only for a short period of time. Immobilization of signaling molecules by cytoskeletal actin filaments and scaffold proteins may facilitate more efficient signal transmission from rafts. In this review, current opinions of how the transient nature of molecular interactions in rafts generates digital-like signal transduction in cell membranes, and the benefits this phenomenon provides, are discussed. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Application of neural computing paradigms for signal validation

International Nuclear Information System (INIS)

Upadhyaya, B.R.; Eryurek, E.; Mathai, G.

1989-01-01

Signal validation and process monitoring problems often require the prediction of one or more process variables in a system. The feasibility of applying neural network paradigms to relate one variable with a set of other related variables is studied. The backpropagation network (BPN) is applied to develop models of signals from both a commercial power plant and the EBR-II. Modification of the BPN algorithm is studied with emphasis on the speed of network training and the accuracy of prediction. The prediction of process variables in a Westinghouse PWR is presented in this paper

Using neural networks to enhance the Higgs boson signal at hadron colliders

International Nuclear Information System (INIS)

Field, R.D.; Kanev, Y.; Tayebnejad, M.; Griffin, P.A.

1995-01-01

Neural networks are used to help distinguish the ZZ → ell + ell - -jet-jet signal produced by the decay of a 400 GeV Higgs boson at a proton-proton collider energy of 15 TeV from the ''ordinary'' QCD Z + jets background. The ideal case where only one event at a time enters the detector (no pile-up) and the case of multiple interactions per beam crossing (pile-up) are examined. In both cases, when used in conjunction with the standard cuts, neural networks provide an additional signal to background enhancement

Analysing 21cm signal with artificial neural network

Science.gov (United States)

Shimabukuro, Hayato; a Semelin, Benoit

2018-05-01

The 21cm signal at epoch of reionization (EoR) should be observed within next decade. We expect that cosmic 21cm signal at the EoR provides us both cosmological and astrophysical information. In order to extract fruitful information from observation data, we need to develop inversion method. For such a method, we introduce artificial neural network (ANN) which is one of the machine learning techniques. We apply the ANN to inversion problem to constrain astrophysical parameters from 21cm power spectrum. We train the architecture of the neural network with 70 training datasets and apply it to 54 test datasets with different value of parameters. We find that the quality of the parameter reconstruction depends on the sensitivity of the power spectrum to the different parameter sets at a given redshift and also find that the accuracy of reconstruction is improved by increasing the number of given redshifts. We conclude that the ANN is viable inversion method whose main strength is that they require a sparse extrapolation of the parameter space and thus should be usable with full simulation.

Multiple-failure signal validation in nuclear power plants using artificial neural networks

International Nuclear Information System (INIS)

Fantoni, P.F.; Mazzola, A.

1996-01-01

The possibility of using a neural network to validate process signals during normal and abnormal plant conditions is explored. In boiling water reactor plants, signal validation is used to generate reliable thermal limits calculation and to supply reliable inputs to other computerized systems that support the operator during accident scenarios. The way that autoassociative neural networks can promptly detect faulty process signal measurements and produce a best estimate of the actual process values even in multifailure situations is shown. A method was developed to train the network for multiple sensor-failure detection, based on a random failure simulation algorithm. Noise was artificially added to the input to evaluate the network's ability to respond in a very low signal-to-noise ratio environment. Training and test data sets were simulated by the real-time transient simulator code APROS

Reconstruction of Micropattern Detector Signals using Convolutional Neural Networks

Science.gov (United States)

Flekova, L.; Schott, M.

2017-10-01

Micropattern gaseous detector (MPGD) technologies, such as GEMs or MicroMegas, are particularly suitable for precision tracking and triggering in high rate environments. Given their relatively low production costs, MPGDs are an exemplary candidate for the next generation of particle detectors. Having acknowledged these advantages, both the ATLAS and CMS collaborations at the LHC are exploiting these new technologies for their detector upgrade programs in the coming years. When MPGDs are utilized for triggering purposes, the measured signals need to be precisely reconstructed within less than 200 ns, which can be achieved by the usage of FPGAs. In this work, we present a novel approach to identify reconstructed signals, their timing and the corresponding spatial position on the detector. In particular, we study the effect of noise and dead readout strips on the reconstruction performance. Our approach leverages the potential of convolutional neural network (CNNs), which have recently manifested an outstanding performance in a range of modeling tasks. The proposed neural network architecture of our CNN is designed simply enough, so that it can be modeled directly by an FPGA and thus provide precise information on reconstructed signals already in trigger level.

Neural Crest-Derived Mesenchymal Cells Require Wnt Signaling for Their Development and Drive Invagination of the Telencephalic Midline

Science.gov (United States)

Choe, Youngshik; Zarbalis, Konstantinos S.; Pleasure, Samuel J.

2014-01-01

Embryonic neural crest cells contribute to the development of the craniofacial mesenchyme, forebrain meninges and perivascular cells. In this study, we investigated the function of ß-catenin signaling in neural crest cells abutting the dorsal forebrain during development. In the absence of ß-catenin signaling, neural crest cells failed to expand in the interhemispheric region and produced ectopic smooth muscle cells instead of generating dermal and calvarial mesenchyme. In contrast, constitutive expression of stabilized ß-catenin in neural crest cells increased the number of mesenchymal lineage precursors suggesting that ß-catenin signaling is necessary for the expansion of neural crest-derived mesenchymal cells. Interestingly, the loss of neural crest-derived mesenchymal stem cells (MSCs) leads to failure of telencephalic midline invagination and causes ventricular system defects. This study shows that ß-catenin signaling is required for the switch of neural crest cells to MSCs and mediates the expansion of MSCs to drive the formation of mesenchymal structures of the head. Furthermore, loss of these structures causes striking defects in forebrain morphogenesis. PMID:24516524

Neural crest-derived mesenchymal cells require Wnt signaling for their development and drive invagination of the telencephalic midline.

Directory of Open Access Journals (Sweden)

Youngshik Choe

Full Text Available Embryonic neural crest cells contribute to the development of the craniofacial mesenchyme, forebrain meninges and perivascular cells. In this study, we investigated the function of ß-catenin signaling in neural crest cells abutting the dorsal forebrain during development. In the absence of ß-catenin signaling, neural crest cells failed to expand in the interhemispheric region and produced ectopic smooth muscle cells instead of generating dermal and calvarial mesenchyme. In contrast, constitutive expression of stabilized ß-catenin in neural crest cells increased the number of mesenchymal lineage precursors suggesting that ß-catenin signaling is necessary for the expansion of neural crest-derived mesenchymal cells. Interestingly, the loss of neural crest-derived mesenchymal stem cells (MSCs leads to failure of telencephalic midline invagination and causes ventricular system defects. This study shows that ß-catenin signaling is required for the switch of neural crest cells to MSCs and mediates the expansion of MSCs to drive the formation of mesenchymal structures of the head. Furthermore, loss of these structures causes striking defects in forebrain morphogenesis.

VEGF signaling inside vascular endothelial cells and beyond.

Science.gov (United States)

Eichmann, Anne; Simons, Michael

2012-04-01

Vascular endothelial growth factor-A (VEGF-A) has long been recognized as the key regulator of vascular development and function in health and disease. VEGF is a secreted polypeptide that binds to transmembrane tyrosine kinase VEGF receptors on the plasma membrane, inducing their dimerization, activation and assembly of a membrane-proximal signaling complex. Recent studies have revealed that many key events of VEGFR signaling occur inside the endothelial cell and are regulated by endosomal receptor trafficking. Plasma membrane VEGFR interacting molecules, including vascular guidance receptors Neuropilins and Ephrins also regulate VEGFR endocytosis and trafficking. VEGF signaling is increasingly recognized for its roles outside of the vascular system, notably during neural development, and blood vessels regulate epithelial branching morphogenesis. We review here recent advances in our understanding of VEGF signaling and its biological roles. Copyright © 2012 Elsevier Ltd. All rights reserved.

Anomalous Signal Detection in ELF Band Electromagnetic Wave using Multi-layer Neural Network with Wavelet Decomposition

Science.gov (United States)

Itai, Akitoshi; Yasukawa, Hiroshi; Takumi, Ichi; Hata, Masayasu

It is well known that electromagnetic waves radiated from the earth's crust are useful for predicting earthquakes. We analyze the electromagnetic waves received at the extremely low frequency band of 223Hz. These observed signals contain the seismic radiation from the earth's crust, but also include several undesired signals. Our research focuses on the signal detection technique to identify an anomalous signal corresponding to the seismic radiation in the observed signal. Conventional anomalous signal detections lack a wide applicability due to their assumptions, e.g. the digital data have to be observed at the same time or the same sensor. In order to overcome the limitation related to the observed signal, we proposed the anomalous signals detection based on a multi-layer neural network which is trained by digital data observed during a span of a day. In the neural network approach, training data do not need to be recorded at the same place or the same time. However, some noises, which have a large amplitude, are detected as the anomalous signal. This paper develops a multi-layer neural network to decrease the false detection of the anomalous signal from the electromagnetic wave. The training data for the proposed network is the decomposed signal of the observed signal during several days, since the seismic radiations are often recorded from several days to a couple of weeks. Results show that the proposed neural network is useful to achieve the accurate detection of the anomalous signal that indicates seismic activity.

Non-genomic actions of aldosterone: From receptors and signals to membrane targets.

LENUS (Irish Health Repository)

2012-02-01

In tissues which express the mineralocorticoid receptor (MR), aldosterone modulates the expression of membrane targets such as the subunits of the epithelial Na(+) channel, in combination with important signalling intermediates such as serum and glucocorticoid-regulated kinase-1. In addition, the rapid \\'non-genomic\\' activation of protein kinases and secondary messenger signalling cascades has also been detected in aldosterone-sensitive tissues of the nephron, distal colon and cardiovascular system. These rapid actions are variously described as being coupled to MR or to an as yet unidentified, membrane-associated aldosterone receptor. The rapidly activated signalling cascades add a level of fine-tuning to the activity of aldosterone-responsive membrane transporters and also modulate the aldosterone-induced changes in gene expression through receptor and transcription factor phosphorylation.

Non-genomic actions of aldosterone: From receptors and signals to membrane targets.

LENUS (Irish Health Repository)

Dooley, Ruth

2011-07-26

In tissues which express the mineralocorticoid receptor (MR), aldosterone modulates the expression of membrane targets such as the subunits of the epithelial Na(+) channel, in combination with important signalling intermediates such as serum and glucocorticoid-regulated kinase-1. In addition, the rapid \\'non-genomic\\' activation of protein kinases and secondary messenger signalling cascades has also been detected in aldosterone-sensitive tissues of the nephron, distal colon and cardiovascular system. These rapid actions are variously described as being coupled to MR or to an as yet unidentified, membrane-associated aldosterone receptor. The rapidly activated signalling cascades add a level of fine-tuning to the activity of aldosterone-responsive membrane transporters and also modulate the aldosterone-induced changes in gene expression through receptor and transcription factor phosphorylation.

Training Deep Spiking Neural Networks Using Backpropagation.

Science.gov (United States)

Lee, Jun Haeng; Delbruck, Tobi; Pfeiffer, Michael

2016-01-01

Deep spiking neural networks (SNNs) hold the potential for improving the latency and energy efficiency of deep neural networks through data-driven event-based computation. However, training such networks is difficult due to the non-differentiable nature of spike events. In this paper, we introduce a novel technique, which treats the membrane potentials of spiking neurons as differentiable signals, where discontinuities at spike times are considered as noise. This enables an error backpropagation mechanism for deep SNNs that follows the same principles as in conventional deep networks, but works directly on spike signals and membrane potentials. Compared with previous methods relying on indirect training and conversion, our technique has the potential to capture the statistics of spikes more precisely. We evaluate the proposed framework on artificially generated events from the original MNIST handwritten digit benchmark, and also on the N-MNIST benchmark recorded with an event-based dynamic vision sensor, in which the proposed method reduces the error rate by a factor of more than three compared to the best previous SNN, and also achieves a higher accuracy than a conventional convolutional neural network (CNN) trained and tested on the same data. We demonstrate in the context of the MNIST task that thanks to their event-driven operation, deep SNNs (both fully connected and convolutional) trained with our method achieve accuracy equivalent with conventional neural networks. In the N-MNIST example, equivalent accuracy is achieved with about five times fewer computational operations.

Explaining neural signals in human visual cortex with an associative learning model.

Science.gov (United States)

Jiang, Jiefeng; Schmajuk, Nestor; Egner, Tobias

2012-08-01

"Predictive coding" models posit a key role for associative learning in visual cognition, viewing perceptual inference as a process of matching (learned) top-down predictions (or expectations) against bottom-up sensory evidence. At the neural level, these models propose that each region along the visual processing hierarchy entails one set of processing units encoding predictions of bottom-up input, and another set computing mismatches (prediction error or surprise) between predictions and evidence. This contrasts with traditional views of visual neurons operating purely as bottom-up feature detectors. In support of the predictive coding hypothesis, a recent human neuroimaging study (Egner, Monti, & Summerfield, 2010) showed that neural population responses to expected and unexpected face and house stimuli in the "fusiform face area" (FFA) could be well-described as a summation of hypothetical face-expectation and -surprise signals, but not by feature detector responses. Here, we used computer simulations to test whether these imaging data could be formally explained within the broader framework of a mathematical neural network model of associative learning (Schmajuk, Gray, & Lam, 1996). Results show that FFA responses could be fit very closely by model variables coding for conditional predictions (and their violations) of stimuli that unconditionally activate the FFA. These data document that neural population signals in the ventral visual stream that deviate from classic feature detection responses can formally be explained by associative prediction and surprise signals.

A preferential design approach for energy-efficient and robust implantable neural signal processing hardware.

Science.gov (United States)

Narasimhan, Seetharam; Chiel, Hillel J; Bhunia, Swarup

2009-01-01

For implantable neural interface applications, it is important to compress data and analyze spike patterns across multiple channels in real time. Such a computational task for online neural data processing requires an innovative circuit-architecture level design approach for low-power, robust and area-efficient hardware implementation. Conventional microprocessor or Digital Signal Processing (DSP) chips would dissipate too much power and are too large in size for an implantable system. In this paper, we propose a novel hardware design approach, referred to as "Preferential Design" that exploits the nature of the neural signal processing algorithm to achieve a low-voltage, robust and area-efficient implementation using nanoscale process technology. The basic idea is to isolate the critical components with respect to system performance and design them more conservatively compared to the noncritical ones. This allows aggressive voltage scaling for low power operation while ensuring robustness and area efficiency. We have applied the proposed approach to a neural signal processing algorithm using the Discrete Wavelet Transform (DWT) and observed significant improvement in power and robustness over conventional design.

Enhancing the top-quark signal at Fermilab Tevatron using neural nets

International Nuclear Information System (INIS)

Ametller, L.; Garrido, L.; Talavera, P.

1994-01-01

We show, in agreement with previous studies, that neural nets can be useful for top-quark analysis at the Fermilab Tevatron. The main features of t bar t and background events in a mixed sample are projected on a single output, which controls the efficiency, purity, and statistical significance of the t bar t signal. We consider a feed-forward multilayer neural net for the CDF reported top-quark mass, using six kinematical variables as inputs. Our main results are based on the exhaustive comparison of the neural net performances with those obtainable from the standard experimental analysis, by imposing different sets of linear cuts over the same variables, showing how the neural net approach improves the standard analysis results

Neural signal processing and closed-loop control algorithm design for an implanted neural recording and stimulation system.

Science.gov (United States)

Hamilton, Lei; McConley, Marc; Angermueller, Kai; Goldberg, David; Corba, Massimiliano; Kim, Louis; Moran, James; Parks, Philip D; Sang Chin; Widge, Alik S; Dougherty, Darin D; Eskandar, Emad N

2015-08-01

A fully autonomous intracranial device is built to continually record neural activities in different parts of the brain, process these sampled signals, decode features that correlate to behaviors and neuropsychiatric states, and use these features to deliver brain stimulation in a closed-loop fashion. In this paper, we describe the sampling and stimulation aspects of such a device. We first describe the signal processing algorithms of two unsupervised spike sorting methods. Next, we describe the LFP time-frequency analysis and feature derivation from the two spike sorting methods. Spike sorting includes a novel approach to constructing a dictionary learning algorithm in a Compressed Sensing (CS) framework. We present a joint prediction scheme to determine the class of neural spikes in the dictionary learning framework; and, the second approach is a modified OSort algorithm which is implemented in a distributed system optimized for power efficiency. Furthermore, sorted spikes and time-frequency analysis of LFP signals can be used to generate derived features (including cross-frequency coupling, spike-field coupling). We then show how these derived features can be used in the design and development of novel decode and closed-loop control algorithms that are optimized to apply deep brain stimulation based on a patient's neuropsychiatric state. For the control algorithm, we define the state vector as representative of a patient's impulsivity, avoidance, inhibition, etc. Controller parameters are optimized to apply stimulation based on the state vector's current state as well as its historical values. The overall algorithm and software design for our implantable neural recording and stimulation system uses an innovative, adaptable, and reprogrammable architecture that enables advancement of the state-of-the-art in closed-loop neural control while also meeting the challenges of system power constraints and concurrent development with ongoing scientific research designed

Differential subcellular membrane recruitment of Src may specify its downstream signalling

International Nuclear Information System (INIS)

Diesbach, Philippe de; Medts, Thierry; Carpentier, Sarah; D'Auria, Ludovic; Van Der Smissen, Patrick; Platek, Anna; Mettlen, Marcel; Caplanusi, Adrian; Hove, Marie-France van den; Tyteca, Donatienne; Courtoy, Pierre J.

2008-01-01

Most Src family members are diacylated and constitutively associate with membrane 'lipid rafts' that coordinate signalling. Whether the monoacylated Src, frequently hyperactive in carcinomas, also localizes at 'rafts' remains controversial. Using polarized MDCK cells expressing the thermosensitive v-Src/tsLA31 variant, we here addressed how Src tyrosine-kinase activation may impact on its (i) membrane recruitment, in particular to 'lipid rafts'; (ii) subcellular localization; and (iii) signalling. The kinetics of Src-kinase thermoactivation correlated with its recruitment from the cytosol to sedimentable membranes where Src largely resisted solubilisation by non-ionic detergents at 4 deg. C and floated into sucrose density gradients like caveolin-1 and flotillin-2, i.e. 'lipid rafts'. By immunofluorescence, activated Src showed a dual localization, at apical endosomes/macropinosomes and at the apical plasma membrane. The plasma membrane Src pool did not colocalize with caveolin-1 and flotillin-2, but extensively overlapped GM1 labelling by cholera toxin. Severe (∼ 70%) cholesterol extraction with methyl-β-cyclodextrin (MβCD) did not abolish 'rafts' floatation, but strongly decreased Src association with floating 'rafts' and abolished its localization at the apical plasma membrane. Src activation independently activated first the MAP-kinase - ERK1/2 pathway, then the PI3-kinase - Akt pathway. MAP-kinase - ERK1/2 activation was insensitive to MβCD, which suppressed Akt phosphorylation and apical endocytosis induced by Src, both depending on the PI3-kinase pathway. We therefore suggest that activated Src is recruited at two membrane compartments, allowing differential signalling, first via ERK1/2 at 'non-raft' domains on endosomes, then via PI3-kinase-Akt on a distinct set of 'rafts' at the apical plasma membrane. Whether this model is applicable to c-Src remains to be examined

Filtering and spectral processing of 1-D signals using cellular neural networks

NARCIS (Netherlands)

Moreira-Tamayo, O.; Pineda de Gyvez, J.

1996-01-01

This paper presents cellular neural networks (CNN) for one-dimensional discrete signal processing. Although CNN has been extensively used in image processing applications, little has been done for 1-dimensional signal processing. We propose a novel CNN architecture to carry out these tasks. This

Modulators of Stomatal Lineage Signal Transduction Alter Membrane Contact Sites and Reveal Specialization among ERECTA Kinases.

Science.gov (United States)

Ho, Chin-Min Kimmy; Paciorek, Tomasz; Abrash, Emily; Bergmann, Dominique C

2016-08-22

Signal transduction from a cell's surface to its interior requires dedicated signaling elements and a cellular environment conducive to signal propagation. Plant development, defense, and homeostasis rely on plasma membrane receptor-like kinases to perceive endogenous and environmental signals, but little is known about their immediate downstream targets and signaling modifiers. Using genetics, biochemistry, and live-cell imaging, we show that the VAP-RELATED SUPPRESSOR OF TMM (VST) family is required for ERECTA-mediated signaling in growth and cell-fate determination and reveal a role for ERECTA-LIKE2 in modulating signaling by its sister kinases. We show that VSTs are peripheral plasma membrane proteins that can form complexes with integral ER-membrane proteins, thereby potentially influencing the organization of the membrane milieu to promote efficient and differential signaling from the ERECTA-family members to their downstream intracellular targets. Copyright © 2016 Elsevier Inc. All rights reserved.

Transcriptional response of Hoxb genes to retinoid signalling is regionally restricted along the neural tube rostrocaudal axis.

Science.gov (United States)

Carucci, Nicoletta; Cacci, Emanuele; Nisi, Paola S; Licursi, Valerio; Paul, Yu-Lee; Biagioni, Stefano; Negri, Rodolfo; Rugg-Gunn, Peter J; Lupo, Giuseppe

2017-04-01

During vertebrate neural development, positional information is largely specified by extracellular morphogens. Their distribution, however, is very dynamic due to the multiple roles played by the same signals in the developing and adult neural tissue. This suggests that neural progenitors are able to modify their competence to respond to morphogen signalling and autonomously maintain positional identities after their initial specification. In this work, we take advantage of in vitro culture systems of mouse neural stem/progenitor cells (NSPCs) to show that NSPCs isolated from rostral or caudal regions of the mouse neural tube are differentially responsive to retinoic acid (RA), a pivotal morphogen for the specification of posterior neural fates. Hoxb genes are among the best known RA direct targets in the neural tissue, yet we found that RA could promote their transcription only in caudal but not in rostral NSPCs. Correlating with these effects, key RA-responsive regulatory regions in the Hoxb cluster displayed opposite enrichment of activating or repressing histone marks in rostral and caudal NSPCs. Finally, RA was able to strengthen Hoxb chromatin activation in caudal NSPCs, but was ineffective on the repressed Hoxb chromatin of rostral NSPCs. These results suggest that the response of NSPCs to morphogen signalling across the rostrocaudal axis of the neural tube may be gated by the epigenetic configuration of target patterning genes, allowing long-term maintenance of intrinsic positional values in spite of continuously changing extrinsic signals.

Irrational exuberance and neural crash warning signals during endogenous experimental market bubbles.

Science.gov (United States)

Smith, Alec; Lohrenz, Terry; King, Justin; Montague, P Read; Camerer, Colin F

2014-07-22

Groups of humans routinely misassign value to complex future events, especially in settings involving the exchange of resources. If properly structured, experimental markets can act as excellent probes of human group-level valuation mechanisms during pathological overvaluations--price bubbles. The connection between the behavioral and neural underpinnings of such phenomena has been absent, in part due to a lack of enabling technology. We used a multisubject functional MRI paradigm to measure neural activity in human subjects participating in experimental asset markets in which endogenous price bubbles formed and crashed. Although many ideas exist about how and why such bubbles may form and how to identify them, our experiment provided a window on the connection between neural responses and behavioral acts (buying and selling) that created the bubbles. We show that aggregate neural activity in the nucleus accumbens (NAcc) tracks the price bubble and that NAcc activity aggregated within a market predicts future price changes and crashes. Furthermore, the lowest-earning subjects express a stronger tendency to buy as a function of measured NAcc activity. Conversely, we report a signal in the anterior insular cortex in the highest earners that precedes the impending price peak, is associated with a higher propensity to sell in high earners, and that may represent a neural early warning signal in these subjects. Such markets could be a model system to understand neural and behavior mechanisms in other settings where emergent group-level activity exhibits mistaken belief or valuation.

Modeling of membrane bioreactor treating hypersaline oily wastewater by artificial neural network

International Nuclear Information System (INIS)

Pendashteh, Ali Reza; Fakhru'l-Razi, A.; Chaibakhsh, Naz; Abdullah, Luqman Chuah; Madaeni, Sayed Siavash; Abidin, Zurina Zainal

2011-01-01

Highlights: → Hypersaline oily wastewater was treated in a membrane bioreactor. → The effects of salinity and organic loading rate were evaluated. → The system was modeled by neural network and optimized by genetic algorithm. → The model prediction agrees well with experimental values. → The model can be used to obtain effluent characteristics less than discharge limits. - Abstract: A membrane sequencing batch reactor (MSBR) treating hypersaline oily wastewater was modeled by artificial neural network (ANN). The MSBR operated at different total dissolved solids (TDSs) (35,000; 50,000; 100,000; 150,000; 200,000; 250,000 mg/L), various organic loading rates (OLRs) (0.281, 0.563, 1.124, 2.248, and 3.372 kg COD/(m 3 day)) and cyclic time (12, 24, and 48 h). A feed-forward neural network trained by batch back propagation algorithm was employed to model the MSBR. A set of 193 operational data from the wastewater treatment with the MSBR was used to train the network. The training, validating and testing procedures for the effluent COD, total organic carbon (TOC) and oil and grease (O and G) concentrations were successful and a good correlation was observed between the measured and predicted values. The results showed that at OLR of 2.44 kg COD/(m 3 day), TDS of 78,000 mg/L and reaction time (RT) of 40 h, the average removal rate of COD was 98%. In these conditions, the average effluent COD concentration was less than 100 mg/L and met the discharge limits.

Modeling of membrane bioreactor treating hypersaline oily wastewater by artificial neural network

Energy Technology Data Exchange (ETDEWEB)

Pendashteh, Ali Reza [Department of Chemical and Environmental Engineering, Faculty of Engineering, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor D.E. (Malaysia); Environmental Research Institute, Iranian Academic Center for Education, Culture and Research (ACECR), Rasht (Iran, Islamic Republic of); Fakhru' l-Razi, A., E-mail: fakhrul@eng.upm.edu.my [Department of Chemical and Environmental Engineering, Faculty of Engineering, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor D.E. (Malaysia); Chaibakhsh, Naz [Department of Chemistry, Faculty of Science, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor D.E. (Malaysia); Abdullah, Luqman Chuah [Department of Chemical and Environmental Engineering, Faculty of Engineering, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor D.E. (Malaysia); Madaeni, Sayed Siavash [Chemical Engineering Department, Razi University, Kermanshah (Iran, Islamic Republic of); Abidin, Zurina Zainal [Department of Chemical and Environmental Engineering, Faculty of Engineering, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor D.E. (Malaysia)

2011-08-30

Highlights: {yields} Hypersaline oily wastewater was treated in a membrane bioreactor. {yields} The effects of salinity and organic loading rate were evaluated. {yields} The system was modeled by neural network and optimized by genetic algorithm. {yields} The model prediction agrees well with experimental values. {yields} The model can be used to obtain effluent characteristics less than discharge limits. - Abstract: A membrane sequencing batch reactor (MSBR) treating hypersaline oily wastewater was modeled by artificial neural network (ANN). The MSBR operated at different total dissolved solids (TDSs) (35,000; 50,000; 100,000; 150,000; 200,000; 250,000 mg/L), various organic loading rates (OLRs) (0.281, 0.563, 1.124, 2.248, and 3.372 kg COD/(m{sup 3} day)) and cyclic time (12, 24, and 48 h). A feed-forward neural network trained by batch back propagation algorithm was employed to model the MSBR. A set of 193 operational data from the wastewater treatment with the MSBR was used to train the network. The training, validating and testing procedures for the effluent COD, total organic carbon (TOC) and oil and grease (O and G) concentrations were successful and a good correlation was observed between the measured and predicted values. The results showed that at OLR of 2.44 kg COD/(m{sup 3} day), TDS of 78,000 mg/L and reaction time (RT) of 40 h, the average removal rate of COD was 98%. In these conditions, the average effluent COD concentration was less than 100 mg/L and met the discharge limits.

Signal-independent timescale analysis (SITA) and its application for neural coding during reaching and walking.

Science.gov (United States)

Zacksenhouse, Miriam; Lebedev, Mikhail A; Nicolelis, Miguel A L

2014-01-01

What are the relevant timescales of neural encoding in the brain? This question is commonly investigated with respect to well-defined stimuli or actions. However, neurons often encode multiple signals, including hidden or internal, which are not experimentally controlled, and thus excluded from such analysis. Here we consider all rate modulations as the signal, and define the rate-modulations signal-to-noise ratio (RM-SNR) as the ratio between the variance of the rate and the variance of the neuronal noise. As the bin-width increases, RM-SNR increases while the update rate decreases. This tradeoff is captured by the ratio of RM-SNR to bin-width, and its variations with the bin-width reveal the timescales of neural activity. Theoretical analysis and simulations elucidate how the interactions between the recovery properties of the unit and the spectral content of the encoded signals shape this ratio and determine the timescales of neural coding. The resulting signal-independent timescale analysis (SITA) is applied to investigate timescales of neural activity recorded from the motor cortex of monkeys during: (i) reaching experiments with Brain-Machine Interface (BMI), and (ii) locomotion experiments at different speeds. Interestingly, the timescales during BMI experiments did not change significantly with the control mode or training. During locomotion, the analysis identified units whose timescale varied consistently with the experimentally controlled speed of walking, though the specific timescale reflected also the recovery properties of the unit. Thus, the proposed method, SITA, characterizes the timescales of neural encoding and how they are affected by the motor task, while accounting for all rate modulations.

Dual roles for spike signaling in cortical neural populations

Directory of Open Access Journals (Sweden)

Dana eBallard

2011-06-01

Full Text Available A prominent feature of signaling in cortical neurons is that of randomness in the action potential. The output of a typical pyramidal cell can be well fit with a Poisson model, and variations in the Poisson rate repeatedly have been shown to be correlated with stimuli. However while the rate provides a very useful characterization of neural spike data, it may not be the most fundamental description of the signaling code. Recent data showing γ frequency range multi-cell action potential correlations, together with spike timing dependent plasticity, are spurring a re-examination of the classical model, since precise timing codes imply that the generation of spikes is essentially deterministic. Could the observed Poisson randomness and timing determinism reflect two separate modes of communication, or do they somehow derive from a single process? We investigate in a timing-based model whether the apparent incompatibility between these probabilistic and deterministic observations may be resolved by examining how spikes could be used in the underlying neural circuits. The crucial component of this model draws on dual roles for spike signaling. In learning receptive fields from ensembles of inputs, spikes need to behave probabilistically, whereas for fast signaling of individual stimuli, the spikes need to behave deterministically. Our simulations show that this combination is possible if deterministic signals using γ latency coding are probabilistically routed through different members of a cortical cell population at different times. This model exhibits standard features characteristic of Poisson models such as orientation tuning post-stimulus histograms and exponential interval histograms. In addition it makes testable predictions that follow from the γ latency coding.

Semantic Congruence Accelerates the Onset of the Neural Signals of Successful Memory Encoding.

Science.gov (United States)

Packard, Pau A; Rodríguez-Fornells, Antoni; Bunzeck, Nico; Nicolás, Berta; de Diego-Balaguer, Ruth; Fuentemilla, Lluís

2017-01-11

As the stream of experience unfolds, our memory system rapidly transforms current inputs into long-lasting meaningful memories. A putative neural mechanism that strongly influences how input elements are transformed into meaningful memory codes relies on the ability to integrate them with existing structures of knowledge or schemas. However, it is not yet clear whether schema-related integration neural mechanisms occur during online encoding. In the current investigation, we examined the encoding-dependent nature of this phenomenon in humans. We showed that actively integrating words with congruent semantic information provided by a category cue enhances memory for words and increases false recall. The memory effect of such active integration with congruent information was robust, even with an interference task occurring right after each encoding word list. In addition, via electroencephalography, we show in 2 separate studies that the onset of the neural signals of successful encoding appeared early (∼400 ms) during the encoding of congruent words. That the neural signals of successful encoding of congruent and incongruent information followed similarly ∼200 ms later suggests that this earlier neural response contributed to memory formation. We propose that the encoding of events that are congruent with readily available contextual semantics can trigger an accelerated onset of the neural mechanisms, supporting the integration of semantic information with the event input. This faster onset would result in a long-lasting and meaningful memory trace for the event but, at the same time, make it difficult to distinguish it from plausible but never encoded events (i.e., related false memories). Conceptual or schema congruence has a strong influence on long-term memory. However, the question of whether schema-related integration neural mechanisms occur during online encoding has yet to be clarified. We investigated the neural mechanisms reflecting how the active

New insights into the organization of plasma membrane and its role in signal transduction.

Science.gov (United States)

Suzuki, Kenichi G N

2015-01-01

Plasma membranes have heterogeneous structures for efficient signal transduction, required to perform cell functions. Recent evidence indicates that the heterogeneous structures are produced by (1) compartmentalization by actin-based membrane skeleton, (2) raft domains, (3) receptor-receptor interactions, and (4) the binding of receptors to cytoskeletal proteins. This chapter provides an overview of recent studies on diffusion, clustering, raft association, actin binding, and signal transduction of membrane receptors, especially glycosylphosphatidylinositol (GPI)-anchored receptors. Studies on diffusion of GPI-anchored receptors suggest that rafts may be small and/or short-lived in plasma membranes. In steady state conditions, GPI-anchored receptors form transient homodimers, which may represent the "standby state" for the stable homodimers and oligomers upon ligation. Furthermore, It is proposed that upon ligation, the binding of GPI-anchored receptor clusters to cytoskeletal actin filaments produces a platform for downstream signaling, and that the pulse-like signaling easily maintains the stability of the overall signaling activity. Copyright © 2015 Elsevier Inc. All rights reserved.

Calcium signaling mediates five types of cell morphological changes to form neural rosettes.

Science.gov (United States)

Hříbková, Hana; Grabiec, Marta; Klemová, Dobromila; Slaninová, Iva; Sun, Yuh-Man

2018-02-12

Neural rosette formation is a critical morphogenetic process during neural development, whereby neural stem cells are enclosed in rosette niches to equipoise proliferation and differentiation. How neural rosettes form and provide a regulatory micro-environment remains to be elucidated. We employed the human embryonic stem cell-based neural rosette system to investigate the structural development and function of neural rosettes. Our study shows that neural rosette formation consists of five types of morphological change: intercalation, constriction, polarization, elongation and lumen formation. Ca 2+ signaling plays a pivotal role in the five steps by regulating the actions of the cytoskeletal complexes, actin, myosin II and tubulin during intercalation, constriction and elongation. These, in turn, control the polarizing elements, ZO-1, PARD3 and β-catenin during polarization and lumen production for neural rosette formation. We further demonstrate that the dismantlement of neural rosettes, mediated by the destruction of cytoskeletal elements, promotes neurogenesis and astrogenesis prematurely, indicating that an intact rosette structure is essential for orderly neural development. © 2018. Published by The Company of Biologists Ltd.

Signal-Independent Timescale Analysis (SITA and its Application for Neural Coding during Reaching and Walking

Directory of Open Access Journals (Sweden)

Miriam eZacksenhouse

2014-08-01

Full Text Available What are the relevant timescales of neural encoding in the brain? This question is commonly investigated with respect to well-defined stimuli or actions. However, neurons often encode multiple signals, including hidden or internal, which are not experimentally controlled, and thus excluded from such analysis. Here we consider all rate modulations as the signal, and define the rate-modulations signal-to-noise ratio (RM-SNR as the ratio between the variance of the rate and the variance of the neuronal noise. As the bin-width increases, RM-SNR increases while the update rate decreases. This tradeoff is captured by the ratio of RM-SNR to bin-width, and its variations with the bin-width reveal the timescales of neural activity. Theoretical analysis and simulations elucidate how the interactions between the recovery properties of the unit and the spectral content of the encoded signals shape this ratio and determine the timescales of neural coding. The resulting signal-independent timescale analysis (SITA is applied to investigate timescales of neural activity recorded from the motor cortex of monkeys during: (i reaching experiments with Brain-Machine Interface (BMI, and (ii locomotion experiments at different speeds. Interestingly, the timescales during BMI experiments did not change significantly with the control mode or training. During locomotion, the analysis identified units whose timescale varied consistently with the experimentally controlled speed of walking, though the specific timescale reflected also the recovery properties of the unit. Thus, the proposed method, SITA, characterizes the timescales of neural encoding and how they are affected by the motor task, while accounting for all rate modulations.

CCR5 internalisation and signalling have different dependence on membrane lipid raft integrity.

Science.gov (United States)

Cardaba, Clara Moyano; Kerr, Jason S; Mueller, Anja

2008-09-01

The chemokine receptor, CCR5, acts as a co-receptor for human immunodeficiency virus entry into cells. CCR5 has been shown to be targeted to cholesterol- and sphingolipid-rich membrane microdomains termed lipid rafts or caveolae. Cholesterol is essential for CCL4 binding to CCR5 and for keeping the conformational integrity of the receptor. Filipin treatment leads to loss of caveolin-1 from the membrane and therefore to a collapse of the caveolae. We have found here that sequestration of membrane cholesterol with filipin did not affect receptor signalling, however a loss of ligand-induced internalisation of CCR5 was observed. Cholesterol extraction with methyl-beta-cyclodextrin (MCD) reduced signalling through CCR5 as measured by release of intracellular Ca(2+) and completely abolished the inhibition of forskolin-stimulated cAMP accumulation with no effect on internalisation. Pertussis toxin (PTX) treatment inhibited the intracellular release of calcium that is transduced via Galphai G-proteins. Depletion of cholesterol destroyed microdomains in the membrane and switched CCR5/G-protein coupling to a PTX-independent G-protein. We conclude that cholesterol in the membrane is essential for CCR5 signalling via the Galphai G-protein subunit, and that integrity of lipid rafts is not essential for effective CCR5 internalisation however it is crucial for proper CCR5 signal transduction via Galphai G-proteins.

Active voltammetric microsensors with neural signal processing.

Energy Technology Data Exchange (ETDEWEB)

Vogt, M. C.

1998-12-11

Many industrial and environmental processes, including bioremediation, would benefit from the feedback and control information provided by a local multi-analyte chemical sensor. For most processes, such a sensor would need to be rugged enough to be placed in situ for long-term remote monitoring, and inexpensive enough to be fielded in useful numbers. The multi-analyte capability is difficult to obtain from common passive sensors, but can be provided by an active device that produces a spectrum-type response. Such new active gas microsensor technology has been developed at Argonne National Laboratory. The technology couples an electrocatalytic ceramic-metallic (cermet) microsensor with a voltammetric measurement technique and advanced neural signal processing. It has been demonstrated to be flexible, rugged, and very economical to produce and deploy. Both narrow interest detectors and wide spectrum instruments have been developed around this technology. Much of this technology's strength lies in the active measurement technique employed. The technique involves applying voltammetry to a miniature electrocatalytic cell to produce unique chemical ''signatures'' from the analytes. These signatures are processed with neural pattern recognition algorithms to identify and quantify the components in the analyte. The neural signal processing allows for innovative sampling and analysis strategies to be employed with the microsensor. In most situations, the whole response signature from the voltammogram can be used to identify, classify, and quantify an analyte, without dissecting it into component parts. This allows an instrument to be calibrated once for a specific gas or mixture of gases by simple exposure to a multi-component standard rather than by a series of individual gases. The sampled unknown analytes can vary in composition or in concentration, the calibration, sensing, and processing methods of these active voltammetric microsensors can

Active voltammetric microsensors with neural signal processing

Science.gov (United States)

Vogt, Michael C.; Skubal, Laura R.

1999-02-01

Many industrial and environmental processes, including bioremediation, would benefit from the feedback and control information provided by a local multi-analyte chemical sensor. For most processes, such a sensor would need to be rugged enough to be placed in situ for long-term remote monitoring, and inexpensive enough to be fielded in useful numbers. The multi-analyte capability is difficult to obtain from common passive sensors, but can be provided by an active device that produces a spectrum-type response. Such new active gas microsensor technology has been developed at Argonne National Laboratory. The technology couples an electrocatalytic ceramic-metallic (cermet) microsensor with a voltammetric measurement technique and advanced neural signal processing. It has been demonstrated to be flexible, rugged, and very economical to produce and deploy. Both narrow interest detectors and wide spectrum instruments have been developed around this technology. Much of this technology's strength lies in the active measurement technique employed. The technique involves applying voltammetry to a miniature electrocatalytic cell to produce unique chemical 'signatures' from the analytes. These signatures are processed with neural pattern recognition algorithms to identify and quantify the components in the analyte. The neural signal processing allows for innovative sampling and analysis strategies to be employed with the microsensor. In most situations, the whole response signature from the voltammogram can be used to identify, classify, and quantify an analyte, without dissecting it into component parts. This allows an instrument to be calibrated once for a specific gas or mixture of gases by simple exposure to a multi-component standard rather than by a series of individual gases. The sampled unknown analytes can vary in composition or in concentration; the calibration, sensing, and processing methods of these active voltammetric microsensors can detect, recognize, and

Estradiol Membrane-Initiated Signaling in the Brain Mediates Reproduction.

Science.gov (United States)

Micevych, Paul E; Mermelstein, Paul G; Sinchak, Kevin

2017-11-01

Over the past few years our understanding of estrogen signaling in the brain has expanded rapidly. Estrogens are synthesized in the periphery and in the brain, acting on multiple receptors to regulate gene transcription, neural function, and behavior. Various estrogen-sensitive signaling pathways often operate in concert within the same cell, increasing the complexity of the system. In females, estrogen concentrations fluctuate over the estrous/menstrual cycle, dynamically modulating estrogen receptor (ER) expression, activity, and trafficking. These dynamic changes influence multiple behaviors but are particularly important for reproduction. Using the female rodent model, we review our current understanding of estradiol signaling in the regulation of sexual receptivity. Copyright © 2017 Elsevier Ltd. All rights reserved.

β-arrestin regulates estradiol membrane-initiated signaling in hypothalamic neurons.

Directory of Open Access Journals (Sweden)

Angela M Wong

Full Text Available Estradiol (E2 action in the nervous system is the result of both direct nuclear and membrane-initiated signaling (EMS. E2 regulates membrane estrogen receptor-α (ERα levels through opposing mechanisms of EMS-mediated trafficking and internalization. While ß-arrestin-mediated mERα internalization has been described in the cortex, a role of ß-arrestin in EMS, which underlies multiple physiological processes, remains undefined. In the arcuate nucleus of the hypothalamus (ARH, membrane-initiated E2 signaling modulates lordosis behavior, a measure of female sexually receptivity. To better understand EMS and regulation of ERα membrane levels, we examined the role of ß-arrestin, a molecule associated with internalization following agonist stimulation. In the present study, we used an immortalized neuronal cell line derived from embryonic hypothalamic neurons, the N-38 line, to examine whether ß-arrestins mediate internalization of mERα. β-arrestin-1 (Arrb1 was found in the ARH and in N-38 neurons. In vitro, E2 increased trafficking and internalization of full-length ERα and ERαΔ4, an alternatively spliced isoform of ERα, which predominates in the membrane. Treatment with E2 also increased phosphorylation of extracellular-signal regulated kinases 1/2 (ERK1/2 in N-38 neurons. Arrb1 siRNA knockdown prevented E2-induced ERαΔ4 internalization and ERK1/2 phosphorylation. In vivo, microinfusions of Arrb1 antisense oligodeoxynucleotides (ODN into female rat ARH knocked down Arrb1 and prevented estradiol benzoate-induced lordosis behavior compared with nonsense scrambled ODN (lordosis quotient: 3 ± 2.1 vs. 85.0 ± 6.0; p < 0.0001. These results indicate a role for Arrb1 in both EMS and internalization of mERα, which are required for the E2-induction of female sexual receptivity.

Global and local missions of cAMP signaling in neural plasticity, learning and memory

Directory of Open Access Journals (Sweden)

Daewoo eLee

2015-08-01

Full Text Available The fruit fly Drosophila melanogaster has been a popular model to study cAMP signaling and resultant behaviors due to its powerful genetic approaches. All molecular components (AC, PDE, PKA, CREB, etc essential for cAMP signaling have been identified in the fly. Among them, adenylyl cyclase (AC gene rutabaga and phosphodiesterase (PDE gene dunce have been intensively studied to understand the role of cAMP signaling. Interestingly, these two mutant genes were originally identified on the basis of associative learning deficits. This commentary summarizes findings on the role of cAMP in Drosophila neuronal excitability, synaptic plasticity and memory. It mainly focuses on two distinct mechanisms (global versus local regulating excitatory and inhibitory synaptic plasticity related to cAMP homeostasis. This dual regulatory role of cAMP is to increase the strength of excitatory neural circuits on one hand, but to act locally on postsynaptic GABA receptors to decrease inhibitory synaptic plasticity on the other. Thus the action of cAMP could result in a global increase in the neural circuit excitability and memory. Implications of this cAMP signaling related to drug discovery for neural diseases are also described.

miR-342-5p Regulates Neural Stem Cell Proliferation and Differentiation Downstream to Notch Signaling in Mice

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Fang Gao

2017-04-01

Full Text Available Summary: Notch signaling is critically involved in neural development, but the downstream effectors remain incompletely understood. In this study, we cultured neurospheres from Nestin-Cre-mediated conditional Rbp-j knockout (Rbp-j cKO and control embryos and compared their miRNA expression profiles using microarray. Among differentially expressed miRNAs, miR-342-5p showed upregulated expression as Notch signaling was genetically or pharmaceutically interrupted. Consistently, the promoter of the miR-342-5p host gene, the Ena-vasodilator stimulated phosphoprotein-like (Evl, was negatively regulated by Notch signaling, probably through HES5. Transfection of miR-342-5p promoted the differentiation of neural stem cells (NSCs into intermediate neural progenitors (INPs in vitro and reduced the stemness of NSCs in vivo. Furthermore, miR-342-5p inhibited the differentiation of neural stem/intermediate progenitor cells into astrocytes, likely mediated by targeting GFAP directly. Our results indicated that miR-342-5p could function as a downstream effector of Notch signaling to regulate the differentiation of NSCs into INPs and astrocytes commitment. : In this article, Han and colleagues show that miR-342-5p acts as a downstream effector of Notch signaling in the mouse CNS. Notch signal inhibits miR-342-5p expression by regulating its host gene Evl. And with attenuated Notch signal in NSCs, miR-342-5p is upregulated to promote NSCs transition into INPs, and to inhibit astrocyte commitment by targeting GFAP. Keywords: neural stem cells, intermediate neural progenitors, Notch, RBP-J, neuron, glia, miR-342-5p

Membrane-Initiated Estradiol Signaling Regulating Sexual Receptivity

Science.gov (United States)

Micevych, Paul E.; Dewing, Phoebe

2011-01-01

Estradiol has profound actions on the structure and function of the nervous system. In addition to nuclear actions that directly modulate gene expression, the idea that estradiol can rapidly activate cell signaling by binding to membrane estrogen receptors (mERs) has emerged. Even the regulation of sexual receptivity, an action previously thought to be completely regulated by nuclear ERs, has been shown to have a membrane-initiated estradiol signaling (MIES) component. This highlighted the question of the nature of mERs. Several candidates have been proposed, ERα, ERβ, ER-X, GPR30 (G protein coupled estrogen receptor), and a receptor activated by a diphenylacrylamide compound, STX. Although each of these receptors has been shown to be active in specific assays, we present evidence for and against their participation in sexual receptivity by acting in the lordosis-regulating circuit. The initial MIES that activates the circuit is in the arcuate nucleus of the hypothalamus (ARH). Using both activation of μ-opioid receptors (MOR) in the medial preoptic nucleus and lordosis behavior, we document that both ERα and the STX-receptor participate in the required MIES. ERα and the STX-receptor activation of cell signaling are dependent on the transactivation of type 1 metabotropic glutamate receptors (mGluR1a) that augment progesterone synthesis in astrocytes and protein kinase C (PKC) in ARH neurons. While estradiol-induced sexual receptivity does not depend on neuroprogesterone, proceptive behaviors do. Moreover, the ERα and the STX-receptor activation of medial preoptic MORs and augmentation of lordosis were sensitive to mGluR1a blockade. These observations suggest a common mechanism through which mERs are coupled to intracellular signaling cascades, not just in regulating reproduction, but in actions throughout the neuraxis including the cortex, hippocampus, striatum, and dorsal root ganglias. PMID:22649369

Genetic deletion of Rnd3 in neural stem cells promotes proliferation via upregulation of Notch signaling.

Science.gov (United States)

Dong, Huimin; Lin, Xi; Li, Yuntao; Hu, Ronghua; Xu, Yang; Guo, Xiaojie; La, Qiong; Wang, Shun; Fang, Congcong; Guo, Junli; Li, Qi; Mao, Shanping; Liu, Baohui

2017-10-31

Rnd3, a Rho GTPase, is involved in the inhibition of actin cytoskeleton dynamics through the Rho kinase-dependent signaling pathway. We previously demonstrated that mice with genetic deletion of Rnd3 developed a markedly larger brain compared with wild-type mice. Here, we demonstrate that Rnd3 knockout mice developed an enlarged subventricular zone, and we identify a novel role for Rnd3 as an inhibitor of Notch signaling in neural stem cells. Rnd3 deficiency, both in vivo and in vitro , resulted in increased levels of Notch intracellular domain protein. This led to enhanced Notch signaling and promotion of aberrant neural stem cell growth, thereby resulting in a larger subventricular zone and a markedly larger brain. Inhibition of Notch activity abrogated this aberrant neural stem cell growth.

Mechanism underlying the inner membrane retention of Escherichia coli lipoproteins caused by Lol avoidance signals.

Science.gov (United States)

Hara, Takashi; Matsuyama, Shin-ichi; Tokuda, Hajime

2003-10-10

Escherichia coli lipoproteins are localized to either the inner or outer membrane depending on the residue at position 2. The inner membrane retention signal, Asp at position 2 in combination with certain residues at position 3, functions as a Lol avoidance signal, i.e. the signal inhibits the recognition of lipoproteins by LolCDE that releases lipoproteins from the inner membrane. To understand the role of the residue at position 2, outer membrane-specific lipoproteins with Cys at position 2 were subjected to chemical modification followed by the release reaction in reconstituted proteoliposomes. Sulfhydryl-specific introduction of nonprotein molecules or a negative charge to Cys did not inhibit the LolCDE-dependent release. In contrast, oxidation of Cys to cysteic acid resulted in generation of the Lol avoidance signal, indicating that the Lol avoidance signal requires a critical length of negative charge at the second residue. Furthermore, not only modification of the carboxylic acid of Asp at position 2 but also that of the amine of phosphatidylethanolamine abolished the Lol avoidance function. Based on these results, the Lol avoidance mechanism is discussed.

Spatio-temporal Remodeling of Functional Membrane Microdomains Organizes the Signaling Networks of a Bacterium

NARCIS (Netherlands)

Schneider, Johannes; Klein, Teresa; Mielich-Süss, Benjamin; Koch, Gudrun; Franke, Christian; Kuipers, Oscar P; Kovács, Ákos T; Sauer, Markus; Lopez, Daniel

Lipid rafts are membrane microdomains specialized in the regulation of numerous cellular processes related to membrane organization, as diverse as signal transduction, protein sorting, membrane trafficking or pathogen invasion. It has been proposed that this functional diversity would require a

Pannexin 1 channels mediate 'find-me' signal release and membrane permeability during apoptosis.

Science.gov (United States)

Chekeni, Faraaz B; Elliott, Michael R; Sandilos, Joanna K; Walk, Scott F; Kinchen, Jason M; Lazarowski, Eduardo R; Armstrong, Allison J; Penuela, Silvia; Laird, Dale W; Salvesen, Guy S; Isakson, Brant E; Bayliss, Douglas A; Ravichandran, Kodi S

2010-10-14

Apoptotic cells release 'find-me' signals at the earliest stages of death to recruit phagocytes. The nucleotides ATP and UTP represent one class of find-me signals, but their mechanism of release is not known. Here, we identify the plasma membrane channel pannexin 1 (PANX1) as a mediator of find-me signal/nucleotide release from apoptotic cells. Pharmacological inhibition and siRNA-mediated knockdown of PANX1 led to decreased nucleotide release and monocyte recruitment by apoptotic cells. Conversely, PANX1 overexpression enhanced nucleotide release from apoptotic cells and phagocyte recruitment. Patch-clamp recordings showed that PANX1 was basally inactive, and that induction of PANX1 currents occurred only during apoptosis. Mechanistically, PANX1 itself was a target of effector caspases (caspases 3 and 7), and a specific caspase-cleavage site within PANX1 was essential for PANX1 function during apoptosis. Expression of truncated PANX1 (at the putative caspase cleavage site) resulted in a constitutively open channel. PANX1 was also important for the 'selective' plasma membrane permeability of early apoptotic cells to specific dyes. Collectively, these data identify PANX1 as a plasma membrane channel mediating the regulated release of find-me signals and selective plasma membrane permeability during apoptosis, and a new mechanism of PANX1 activation by caspases.

The Role of Membrane Curvature in Nanoscale Topography-Induced Intracellular Signaling.

Science.gov (United States)

Lou, Hsin-Ya; Zhao, Wenting; Zeng, Yongpeng; Cui, Bianxiao

2018-05-15

Over the past decade, there has been growing interest in developing biosensors and devices with nanoscale and vertical topography. Vertical nanostructures induce spontaneous cell engulfment, which enhances the cell-probe coupling efficiency and the sensitivity of biosensors. Although local membranes in contact with the nanostructures are found to be fully fluidic for lipid and membrane protein diffusions, cells appear to actively sense and respond to the surface topography presented by vertical nanostructures. For future development of biodevices, it is important to understand how cells interact with these nanostructures and how their presence modulates cellular function and activities. How cells recognize nanoscale surface topography has been an area of active research for two decades before the recent biosensor works. Extensive studies show that surface topographies in the range of tens to hundreds of nanometers can significantly affect cell functions, behaviors, and ultimately the cell fate. For example, titanium implants having rough surfaces are better for osteoblast attachment and host-implant integration than those with smooth surfaces. At the cellular level, nanoscale surface topography has been shown by a large number of studies to modulate cell attachment, activity, and differentiation. However, a mechanistic understanding of how cells interact and respond to nanoscale topographic features is still lacking. In this Account, we focus on some recent studies that support a new mechanism that local membrane curvature induced by nanoscale topography directly acts as a biochemical signal to induce intracellular signaling, which we refer to as the curvature hypothesis. The curvature hypothesis proposes that some intracellular proteins can recognize membrane curvatures of a certain range at the cell-to-material interface. These proteins then recruit and activate downstream components to modulate cell signaling and behavior. We discuss current technologies

[A wavelet neural network algorithm of EEG signals data compression and spikes recognition].

Science.gov (United States)

Zhang, Y; Liu, A; Yu, K

1999-06-01

A novel method of EEG signals compression representation and epileptiform spikes recognition based on wavelet neural network and its algorithm is presented. The wavelet network not only can compress data effectively but also can recover original signal. In addition, the characters of the spikes and the spike-slow rhythm are auto-detected from the time-frequency isoline of EEG signal. This method is well worth using in the field of the electrophysiological signal processing and time-frequency analyzing.

An input feature selection method applied to fuzzy neural networks for signal esitmation

International Nuclear Information System (INIS)

Na, Man Gyun; Sim, Young Rok

2001-01-01

It is well known that the performance of a fuzzy neural networks strongly depends on the input features selected for its training. In its applications to sensor signal estimation, there are a large number of input variables related with an output. As the number of input variables increases, the training time of fuzzy neural networks required increases exponentially. Thus, it is essential to reduce the number of inputs to a fuzzy neural networks and to select the optimum number of mutually independent inputs that are able to clearly define the input-output mapping. In this work, principal component analysis (PAC), genetic algorithms (GA) and probability theory are combined to select new important input features. A proposed feature selection method is applied to the signal estimation of the steam generator water level, the hot-leg flowrate, the pressurizer water level and the pressurizer pressure sensors in pressurized water reactors and compared with other input feature selection methods

Spatio-temporal remodeling of functional membrane microdomains organizes the signaling networks of a bacterium.

Directory of Open Access Journals (Sweden)

Johannes Schneider

2015-04-01

Full Text Available Lipid rafts are membrane microdomains specialized in the regulation of numerous cellular processes related to membrane organization, as diverse as signal transduction, protein sorting, membrane trafficking or pathogen invasion. It has been proposed that this functional diversity would require a heterogeneous population of raft domains with varying compositions. However, a mechanism for such diversification is not known. We recently discovered that bacterial membranes organize their signal transduction pathways in functional membrane microdomains (FMMs that are structurally and functionally similar to the eukaryotic lipid rafts. In this report, we took advantage of the tractability of the prokaryotic model Bacillus subtilis to provide evidence for the coexistence of two distinct families of FMMs in bacterial membranes, displaying a distinctive distribution of proteins specialized in different biological processes. One family of microdomains harbors the scaffolding flotillin protein FloA that selectively tethers proteins specialized in regulating cell envelope turnover and primary metabolism. A second population of microdomains containing the two scaffolding flotillins, FloA and FloT, arises exclusively at later stages of cell growth and specializes in adaptation of cells to stationary phase. Importantly, the diversification of membrane microdomains does not occur arbitrarily. We discovered that bacterial cells control the spatio-temporal remodeling of microdomains by restricting the activation of FloT expression to stationary phase. This regulation ensures a sequential assembly of functionally specialized membrane microdomains to strategically organize signaling networks at the right time during the lifespan of a bacterium.

Accumulation of raft lipids in T-cell plasma membrane domains engaged in TCR signalling

DEFF Research Database (Denmark)

Zech, Tobias; Ejsing, Christer S.; Gaus, Katharina

2009-01-01

Activating stimuli for T lymphocytes are transmitted through plasma membrane domains that form at T-cell antigen receptor (TCR) signalling foci. Here, we determined the molecular lipid composition of immunoisolated TCR activation domains. We observed that they accumulate cholesterol, sphingomyelin...... and saturated phosphatidylcholine species as compared with control plasma membrane fragments. This provides, for the first time, direct evidence that TCR activation domains comprise a distinct molecular lipid composition reminiscent of liquid-ordered raft phases in model membranes. Interestingly, TCR activation...... domains were also enriched in plasmenyl phosphatidylethanolamine and phosphatidylserine. Modulating the T-cell lipidome with polyunsaturated fatty acids impaired the plasma membrane condensation at TCR signalling foci and resulted in a perturbed molecular lipid composition. These results correlate...

The role of membrane microdomains in transmembrane signaling through the epithelial glycoprotein Gp140/CDCP1

Science.gov (United States)

Alvares, Stacy M.; Dunn, Clarence A.; Brown, Tod A.; Wayner, Elizabeth E.; Carter, William G.

2008-01-01

Cell adhesion to the extracellular matrix (ECM) via integrin adhesion receptors initiates signaling cascades leading to changes in cell behavior. While integrin clustering is necessary to initiate cell attachment to the matrix, additional membrane components are necessary to mediate the transmembrane signals and the cell adhesion response that alter downstream cell behavior. Many of these signaling components reside in glycosphingolipid-rich and cholesterol-rich membrane domains such as Tetraspanin Enriched Microdomains (TEMs)/Glycosynapse 3 and Detergent-Resistant Microdomains (DRMs), also known as lipid rafts. In the following article, we will review examples of how components in these membrane microdomains modulate integrin adhesion after initial attachment to the ECM. Additionally, we will present data on a novel adhesion-responsive transmembrane glycoprotein Gp140/CUB Domain Containing Protein 1, which clusters in epithelial cell-cell contacts. Gp140 can then be phosphorylated by Src Family Kinases at tyrosine 734 in response to outside-in signals- possibly through interactions involving the extracellular CUB domains. Data presented here suggests that outside-in signals through Gp140 in cell-cell contacts assemble membrane clusters that associate with membrane microdomains to recruit and activate SFKs. Active SFKs then mediate phosphorylation of Gp140, SFK and PKCδ with Gp140 acting as a transmembrane scaffold for these kinases. We propose that the clustering of Gp140 and signaling components in membrane microdomains in cell-cell contacts contributes to changes in cell behavior. PMID:18269919

Application of artificial neural network to search for gravitational-wave signals associated with short gamma-ray bursts

International Nuclear Information System (INIS)

Kim, Kyungmin; Lee, Hyun Kyu; Harry, Ian W; Hodge, Kari A; Kim, Young-Min; Lee, Chang-Hwan; Oh, John J; Oh, Sang Hoon; Son, Edwin J

2015-01-01

We apply a machine learning algorithm, the artificial neural network, to the search for gravitational-wave signals associated with short gamma-ray bursts (GRBs). The multi-dimensional samples consisting of data corresponding to the statistical and physical quantities from the coherent search pipeline are fed into the artificial neural network to distinguish simulated gravitational-wave signals from background noise artifacts. Our result shows that the data classification efficiency at a fixed false alarm probability (FAP) is improved by the artificial neural network in comparison to the conventional detection statistic. Specifically, the distance at 50% detection probability at a fixed false positive rate is increased about 8%–14% for the considered waveform models. We also evaluate a few seconds of the gravitational-wave data segment using the trained networks and obtain the FAP. We suggest that the artificial neural network can be a complementary method to the conventional detection statistic for identifying gravitational-wave signals related to the short GRBs. (paper)

Can Neural Activity Propagate by Endogenous Electrical Field?

Science.gov (United States)

Qiu, Chen; Shivacharan, Rajat S.; Zhang, Mingming

2015-01-01

It is widely accepted that synaptic transmissions and gap junctions are the major governing mechanisms for signal traveling in the neural system. Yet, a group of neural waves, either physiological or pathological, share the same speed of ∼0.1 m/s without synaptic transmission or gap junctions, and this speed is not consistent with axonal conduction or ionic diffusion. The only explanation left is an electrical field effect. We tested the hypothesis that endogenous electric fields are sufficient to explain the propagation with in silico and in vitro experiments. Simulation results show that field effects alone can indeed mediate propagation across layers of neurons with speeds of 0.12 ± 0.09 m/s with pathological kinetics, and 0.11 ± 0.03 m/s with physiologic kinetics, both generating weak field amplitudes of ∼2–6 mV/mm. Further, the model predicted that propagation speed values are inversely proportional to the cell-to-cell distances, but do not significantly change with extracellular resistivity, membrane capacitance, or membrane resistance. In vitro recordings in mice hippocampi produced similar speeds (0.10 ± 0.03 m/s) and field amplitudes (2.5–5 mV/mm), and by applying a blocking field, the propagation speed was greatly reduced. Finally, osmolarity experiments confirmed the model's prediction that cell-to-cell distance inversely affects propagation speed. Together, these results show that despite their weak amplitude, electric fields can be solely responsible for spike propagation at ∼0.1 m/s. This phenomenon could be important to explain the slow propagation of epileptic activity and other normal propagations at similar speeds. SIGNIFICANCE STATEMENT Neural activity (waves or spikes) can propagate using well documented mechanisms such as synaptic transmission, gap junctions, or diffusion. However, the purpose of this paper is to provide an explanation for experimental data showing that neural signals can propagate by means other than synaptic

Recurrent neural network approach to quantum signal: coherent state restoration for continuous-variable quantum key distribution

Science.gov (United States)

Lu, Weizhao; Huang, Chunhui; Hou, Kun; Shi, Liting; Zhao, Huihui; Li, Zhengmei; Qiu, Jianfeng

2018-05-01

In continuous-variable quantum key distribution (CV-QKD), weak signal carrying information transmits from Alice to Bob; during this process it is easily influenced by unknown noise which reduces signal-to-noise ratio, and strongly impacts reliability and stability of the communication. Recurrent quantum neural network (RQNN) is an artificial neural network model which can perform stochastic filtering without any prior knowledge of the signal and noise. In this paper, a modified RQNN algorithm with expectation maximization algorithm is proposed to process the signal in CV-QKD, which follows the basic rule of quantum mechanics. After RQNN, noise power decreases about 15 dBm, coherent signal recognition rate of RQNN is 96%, quantum bit error rate (QBER) drops to 4%, which is 6.9% lower than original QBER, and channel capacity is notably enlarged.

FGF signalling regulates chromatin organisation during neural differentiation via mechanisms that can be uncoupled from transcription.

Directory of Open Access Journals (Sweden)

Nishal S Patel

Full Text Available Changes in higher order chromatin organisation have been linked to transcriptional regulation; however, little is known about how such organisation alters during embryonic development or how it is regulated by extrinsic signals. Here we analyse changes in chromatin organisation as neural differentiation progresses, exploiting the clear spatial separation of the temporal events of differentiation along the elongating body axis of the mouse embryo. Combining fluorescence in situ hybridisation with super-resolution structured illumination microscopy, we show that chromatin around key differentiation gene loci Pax6 and Irx3 undergoes both decompaction and displacement towards the nuclear centre coincident with transcriptional onset. Conversely, down-regulation of Fgf8 as neural differentiation commences correlates with a more peripheral nuclear position of this locus. During normal neural differentiation, fibroblast growth factor (FGF signalling is repressed by retinoic acid, and this vitamin A derivative is further required for transcription of neural genes. We show here that exposure to retinoic acid or inhibition of FGF signalling promotes precocious decompaction and central nuclear positioning of differentiation gene loci. Using the Raldh2 mutant as a model for retinoid deficiency, we further find that such changes in higher order chromatin organisation are dependent on retinoid signalling. In this retinoid deficient condition, FGF signalling persists ectopically in the elongating body, and importantly, we find that inhibiting FGF receptor (FGFR signalling in Raldh2-/- embryos does not rescue differentiation gene transcription, but does elicit both chromatin decompaction and nuclear position change. These findings demonstrate that regulation of higher order chromatin organisation during differentiation in the embryo can be uncoupled from the machinery that promotes transcription and, for the first time, identify FGF as an extrinsic signal that

EEG signal classification using PSO trained RBF neural network for epilepsy identification

Directory of Open Access Journals (Sweden)

Sandeep Kumar Satapathy

Full Text Available The electroencephalogram (EEG is a low amplitude signal generated in the brain, as a result of information flow during the communication of several neurons. Hence, careful analysis of these signals could be useful in understanding many human brain disorder diseases. One such disease topic is epileptic seizure identification, which can be identified via a classification process of the EEG signal after preprocessing with the discrete wavelet transform (DWT. To classify the EEG signal, we used a radial basis function neural network (RBFNN. As shown herein, the network can be trained to optimize the mean square error (MSE by using a modified particle swarm optimization (PSO algorithm. The key idea behind the modification of PSO is to introduce a method to overcome the problem of slow searching in and around the global optimum solution. The effectiveness of this procedure was verified by an experimental analysis on a benchmark dataset which is publicly available. The result of our experimental analysis revealed that the improvement in the algorithm is significant with respect to RBF trained by gradient descent and canonical PSO. Here, two classes of EEG signals were considered: the first being an epileptic and the other being non-epileptic. The proposed method produced a maximum accuracy of 99% as compared to the other techniques. Keywords: Electroencephalography, Radial basis function neural network, Particle swarm optimization, Discrete wavelet transform, Machine learning

Application of the minimum fuel neural network to music signals

DEFF Research Database (Denmark)

Harbo, Anders La-Cour

2004-01-01

) for finding sparse representations of music signals. This method is a set of two ordinary differential equations. We argue that the most important parameter for optimal use of this method is the discretization step size, and we demonstrate that this can be a priori determined. This significantly speeds up......Finding an optimal representation of a signal in an over-complete dictionary is often quite difficult. Since general results in this field are not very application friendly it truly helps to specify the framework as much as possible. We investigate the method Minimum Fuel Neural Network (MFNN...

Forecast of TEXT plasma disruptions using soft X rays as input signal in a neural network

International Nuclear Information System (INIS)

Vannucci, A.; Oliveira, K.A.; Tajima, T.

1999-01-01

A feedforward neural network with two hidden layers is used to forecast major and minor disruptive instabilities in TEXT tokamak discharges. Using the experimental data of soft X ray signals as input data, the neural network is trained with one disruptive plasma discharge, and a different disruptive discharge is used for validation. After being properly trained, the networks, with the same set of weights, are used to forecast disruptions in two other plasma discharges. It is observed that the neural network is able to predict the occurrence of a disruption more than 3 ms in advance. This time interval is almost 3 times longer than the one already obtained previously when a magnetic signal from a Mirnov coil was used to feed the neural networks. Visually no indication of an upcoming disruption is seen from the experimental data this far back from the time of disruption. Finally, by observing the predictive behaviour of the network for the disruptive discharges analysed and comparing the soft X ray data with the corresponding magnetic experimental signal, it is conjectured about where inside the plasma column the disruption first started. (author)

Protein sorting by lipid phase-like domains supports emergent signaling function in B lymphocyte plasma membranes.

Science.gov (United States)

Stone, Matthew B; Shelby, Sarah A; Núñez, Marcos F; Wisser, Kathleen; Veatch, Sarah L

2017-02-01

Diverse cellular signaling events, including B cell receptor (BCR) activation, are hypothesized to be facilitated by domains enriched in specific plasma membrane lipids and proteins that resemble liquid-ordered phase-separated domains in model membranes. This concept remains controversial and lacks direct experimental support in intact cells. Here, we visualize ordered and disordered domains in mouse B lymphoma cell membranes using super-resolution fluorescence localization microscopy, demonstrate that clustered BCR resides within ordered phase-like domains capable of sorting key regulators of BCR activation, and present a minimal, predictive model where clustering receptors leads to their collective activation by stabilizing an extended ordered domain. These results provide evidence for the role of membrane domains in BCR signaling and a plausible mechanism of BCR activation via receptor clustering that could be generalized to other signaling pathways. Overall, these studies demonstrate that lipid mediated forces can bias biochemical networks in ways that broadly impact signal transduction.

Insertion of Neurotransmitters into a Lipid Bilayer Membrane and Its Implication on Membrane Stability: A Molecular Dynamics Study.

Science.gov (United States)

Shen, Chun; Xue, Minmin; Qiu, Hu; Guo, Wanlin

2017-03-17

The signaling molecules in neurons, called neurotransmitters, play an essential role in the transportation of neural signals, during which the neurotransmitters interact with not only specific receptors, but also cytomembranes, such as synaptic vesicle membranes and postsynaptic membranes. Through extensive molecular dynamics simulations, the atomic-scale insertion dynamics of typical neurotransmitters, including methionine enkephalin (ME), leucine enkephalin (LE), dopamine (DA), acetylcholine (ACh), and aspartic acid (ASP), into lipid bilayers is investigated. The results show that the first three neurotransmitters (ME, LE, and DA) are able to diffuse freely into both 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) and 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoethanolamine (POPE) membranes, and are guided by the aromatic residues Tyr and Phe. Only a limited number of these neurotransmitters are allowed to penetrate into the membrane, which suggests an intrinsic mechanism by which the membrane is protected from being destroyed by excessive inserted neurotransmitters. After spontaneous insertion, the neurotransmitters disturb the surrounding phospholipids in the membrane, as indicated by the altered distribution of components in lipid leaflets and the disordered lipid tails. In contrast, the last two neurotransmitters (ACh and ASP) cannot enter the membrane, but instead always diffuse freely in solution. These findings provide an understanding at the atomic level of how neurotransmitters interact with the surrounding cytomembrane, as well as their impact on membrane behavior. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Detection of directional eye movements based on the electrooculogram signals through an artificial neural network

International Nuclear Information System (INIS)

Erkaymaz, Hande; Ozer, Mahmut; Orak, İlhami Muharrem

2015-01-01

The electrooculogram signals are very important at extracting information about detection of directional eye movements. Therefore, in this study, we propose a new intelligent detection model involving an artificial neural network for the eye movements based on the electrooculogram signals. In addition to conventional eye movements, our model also involves the detection of tic and blinking of an eye. We extract only two features from the electrooculogram signals, and use them as inputs for a feed-forwarded artificial neural network. We develop a new approach to compute these two features, which we call it as a movement range. The results suggest that the proposed model have a potential to become a new tool to determine the directional eye movements accurately

The COP9 signalosome converts temporal hormone signaling to spatial restriction on neural competence.

Directory of Open Access Journals (Sweden)

Yi-Chun Huang

2014-11-01

Full Text Available During development, neural competence is conferred and maintained by integrating spatial and temporal regulations. The Drosophila sensory bristles that detect mechanical and chemical stimulations are arranged in stereotypical positions. The anterior wing margin (AWM is arrayed with neuron-innervated sensory bristles, while posterior wing margin (PWM bristles are non-innervated. We found that the COP9 signalosome (CSN suppresses the neural competence of non-innervated bristles at the PWM. In CSN mutants, PWM bristles are transformed into neuron-innervated, which is attributed to sustained expression of the neural-determining factor Senseless (Sens. The CSN suppresses Sens through repression of the ecdysone signaling target gene broad (br that encodes the BR-Z1 transcription factor to activate sens expression. Strikingly, CSN suppression of BR-Z1 is initiated at the prepupa-to-pupa transition, leading to Sens downregulation, and termination of the neural competence of PWM bristles. The role of ecdysone signaling to repress br after the prepupa-to-pupa transition is distinct from its conventional role in activation, and requires CSN deneddylating activity and multiple cullins, the major substrates of deneddylation. Several CSN subunits physically associate with ecdysone receptors to represses br at the transcriptional level. We propose a model in which nuclear hormone receptors cooperate with the deneddylation machinery to temporally shutdown downstream target gene expression, conferring a spatial restriction on neural competence at the PWM.

Pulse-coupled neural nets: translation, rotation, scale, distortion, and intensity signal invariance for images.

Science.gov (United States)

Johnson, J L

1994-09-10

The linking-field neural network model of Eckhorn et al. [Neural Comput. 2, 293-307 (1990)] was introduced to explain the experimentally observed synchronous activity among neural assemblies in the cat cortex induced by feature-dependent visual activity. The model produces synchronous bursts of pulses from neurons with similar activity, effectively grouping them by phase and pulse frequency. It gives a basic new function: grouping by similarity. The synchronous bursts are obtained in the limit of strong linking strengths. The linking-field model in the limit of moderate-to-weak linking characterized by few if any multiple bursts is investigated. In this limit dynamic, locally periodic traveling waves exist whose time signal encodes the geometrical structure of a two-dimensional input image. The signal can be made insensitive to translation, scale, rotation, distortion, and intensity. The waves transmit information beyond the physical interconnect distance. The model is implemented in an optical hybrid demonstration system. Results of the simulations and the optical system are presented.

Artificial Neural Network-Based Early-Age Concrete Strength Monitoring Using Dynamic Response Signals.

Science.gov (United States)

Kim, Junkyeong; Lee, Chaggil; Park, Seunghee

2017-06-07

Concrete is one of the most common materials used to construct a variety of civil infrastructures. However, since concrete might be susceptible to brittle fracture, it is essential to confirm the strength of concrete at the early-age stage of the curing process to prevent unexpected collapse. To address this issue, this study proposes a novel method to estimate the early-age strength of concrete, by integrating an artificial neural network algorithm with a dynamic response measurement of the concrete material. The dynamic response signals of the concrete, including both electromechanical impedances and guided ultrasonic waves, are obtained from an embedded piezoelectric sensor module. The cross-correlation coefficient of the electromechanical impedance signals and the amplitude of the guided ultrasonic wave signals are selected to quantify the variation in dynamic responses according to the strength of the concrete. Furthermore, an artificial neural network algorithm is used to verify a relationship between the variation in dynamic response signals and concrete strength. The results of an experimental study confirm that the proposed approach can be effectively applied to estimate the strength of concrete material from the early-age stage of the curing process.

Binding of Signal Recognition Particle Gives Ribosome/Nascent Chain Complexes a Competitive Advantage in Endoplasmic Reticulum Membrane Interaction

Science.gov (United States)

Neuhof, Andrea; Rolls, Melissa M.; Jungnickel, Berit; Kalies, Kai-Uwe; Rapoport, Tom A.

1998-01-01

Most secretory and membrane proteins are sorted by signal sequences to the endoplasmic reticulum (ER) membrane early during their synthesis. Targeting of the ribosome-nascent chain complex (RNC) involves the binding of the signal sequence to the signal recognition particle (SRP), followed by an interaction of ribosome-bound SRP with the SRP receptor. However, ribosomes can also independently bind to the ER translocation channel formed by the Sec61p complex. To explain the specificity of membrane targeting, it has therefore been proposed that nascent polypeptide-associated complex functions as a cytosolic inhibitor of signal sequence- and SRP-independent ribosome binding to the ER membrane. We report here that SRP-independent binding of RNCs to the ER membrane can occur in the presence of all cytosolic factors, including nascent polypeptide-associated complex. Nontranslating ribosomes competitively inhibit SRP-independent membrane binding of RNCs but have no effect when SRP is bound to the RNCs. The protective effect of SRP against ribosome competition depends on a functional signal sequence in the nascent chain and is also observed with reconstituted proteoliposomes containing only the Sec61p complex and the SRP receptor. We conclude that cytosolic factors do not prevent the membrane binding of ribosomes. Instead, specific ribosome targeting to the Sec61p complex is provided by the binding of SRP to RNCs, followed by an interaction with the SRP receptor, which gives RNC–SRP complexes a selective advantage in membrane targeting over nontranslating ribosomes. PMID:9436994

Noise in Neural Networks: Thresholds, Hysteresis, and Neuromodulation of Signal-To-Noise

Science.gov (United States)

Keeler, James D.; Pichler, Elgar E.; Ross, John

1989-03-01

We study a neural-network model including Gaussian noise, higher-order neuronal interactions, and neuromodulation. For a first-order network, there is a threshold in the noise level (phase transition) above which the network displays only disorganized behavior and critical slowing down near the noise threshold. The network can tolerate more noise if it has higher-order feedback interactions, which also lead to hysteresis and multistability in the network dynamics. The signal-to-noise ratio can be adjusted in a biological neural network by neuromodulators such as norepinephrine. Comparisons are made to experimental results and further investigations are suggested to test the effects of hysteresis and neuromodulation in pattern recognition and learning. We propose that norepinephrine may ``quench'' the neural patterns of activity to enhance the ability to learn details.

A probablistic neural network classification system for signal and image processing

Energy Technology Data Exchange (ETDEWEB)

Bowman, B. [Lawrence Livermore National Lab., CA (United States)

1994-11-15

The Acoustical Heart Valve Analysis Package is a system for signal and image processing and classification. It is being developed in both Matlab and C, to provide an interactive, interpreted environment, and has been optimized for large scale matrix operations. It has been used successfully to classify acoustic signals from implanted prosthetic heart valves in human patients, and will be integrated into a commercial Heart Valve Screening Center. The system uses several standard signal processing algorithms, as well as supervised learning techniques using the probabilistic neural network (PNN). Although currently used for the acoustic heart valve application, the algorithms and modular design allow it to be used for other applications, as well. We will describe the signal classification system, and show results from a set of test valves.

Automated embolic signal detection using Deep Convolutional Neural Network.

Science.gov (United States)

Sombune, Praotasna; Phienphanich, Phongphan; Phuechpanpaisal, Sutanya; Muengtaweepongsa, Sombat; Ruamthanthong, Anuchit; Tantibundhit, Charturong

2017-07-01

This work investigated the potential of Deep Neural Network in detection of cerebral embolic signal (ES) from transcranial Doppler ultrasound (TCD). The resulting system is aimed to couple with TCD devices in diagnosing a risk of stroke in real-time with high accuracy. The Adaptive Gain Control (AGC) approach developed in our previous study is employed to capture suspected ESs in real-time. By using spectrograms of the same TCD signal dataset as that of our previous work as inputs and the same experimental setup, Deep Convolutional Neural Network (CNN), which can learn features while training, was investigated for its ability to bypass the traditional handcrafted feature extraction and selection process. Extracted feature vectors from the suspected ESs are later determined whether they are of an ES, artifact (AF) or normal (NR) interval. The effectiveness of the developed system was evaluated over 19 subjects going under procedures generating emboli. The CNN-based system could achieve in average of 83.0% sensitivity, 80.1% specificity, and 81.4% accuracy, with considerably much less time consumption in development. The certainly growing set of training samples and computational resources will contribute to high performance. Besides having potential use in various clinical ES monitoring settings, continuation of this promising study will benefit developments of wearable applications by leveraging learnable features to serve demographic differentials.

Predictable information in neural signals during resting state is reduced in autism spectrum disorder.

Science.gov (United States)

Brodski-Guerniero, Alla; Naumer, Marcus J; Moliadze, Vera; Chan, Jason; Althen, Heike; Ferreira-Santos, Fernando; Lizier, Joseph T; Schlitt, Sabine; Kitzerow, Janina; Schütz, Magdalena; Langer, Anne; Kaiser, Jochen; Freitag, Christine M; Wibral, Michael

2018-04-04

The neurophysiological underpinnings of the nonsocial symptoms of autism spectrum disorder (ASD) which include sensory and perceptual atypicalities remain poorly understood. Well-known accounts of less dominant top-down influences and more dominant bottom-up processes compete to explain these characteristics. These accounts have been recently embedded in the popular framework of predictive coding theory. To differentiate between competing accounts, we studied altered information dynamics in ASD by quantifying predictable information in neural signals. Predictable information in neural signals measures the amount of stored information that is used for the next time step of a neural process. Thus, predictable information limits the (prior) information which might be available for other brain areas, for example, to build predictions for upcoming sensory information. We studied predictable information in neural signals based on resting-state magnetoencephalography (MEG) recordings of 19 ASD patients and 19 neurotypical controls aged between 14 and 27 years. Using whole-brain beamformer source analysis, we found reduced predictable information in ASD patients across the whole brain, but in particular in posterior regions of the default mode network. In these regions, epoch-by-epoch predictable information was positively correlated with source power in the alpha and beta frequency range as well as autocorrelation decay time. Predictable information in precuneus and cerebellum was negatively associated with nonsocial symptom severity, indicating a relevance of the analysis of predictable information for clinical research in ASD. Our findings are compatible with the assumption that use or precision of prior knowledge is reduced in ASD patients. © 2018 Wiley Periodicals, Inc.

Membrane Trafficking of Death Receptors: Implications on Signalling

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Wulf Schneider-Brachert

2013-07-01

Full Text Available Death receptors were initially recognised as potent inducers of apoptotic cell death and soon ambitious attempts were made to exploit selective ignition of controlled cellular suicide as therapeutic strategy in malignant diseases. However, the complexity of death receptor signalling has increased substantially during recent years. Beyond activation of the apoptotic cascade, involvement in a variety of cellular processes including inflammation, proliferation and immune response was recognised. Mechanistically, these findings raised the question how multipurpose receptors can ensure selective activation of a particular pathway. A growing body of evidence points to an elegant spatiotemporal regulation of composition and assembly of the receptor-associated signalling complex. Upon ligand binding, receptor recruitment in specialized membrane compartments, formation of receptor-ligand clusters and internalisation processes constitute key regulatory elements. In this review, we will summarise the current concepts of death receptor trafficking and its implications on receptor-associated signalling events.

Quality-on-Demand Compression of EEG Signals for Telemedicine Applications Using Neural Network Predictors

Directory of Open Access Journals (Sweden)

N. Sriraam

2011-01-01

Full Text Available A telemedicine system using communication and information technology to deliver medical signals such as ECG, EEG for long distance medical services has become reality. In either the urgent treatment or ordinary healthcare, it is necessary to compress these signals for the efficient use of bandwidth. This paper discusses a quality on demand compression of EEG signals using neural network predictors for telemedicine applications. The objective is to obtain a greater compression gains at a low bit rate while preserving the clinical information content. A two-stage compression scheme with a predictor and an entropy encoder is used. The residue signals obtained after prediction is first thresholded using various levels of thresholds and are further quantized and then encoded using an arithmetic encoder. Three neural network models, single-layer and multi-layer perceptrons and Elman network are used and the results are compared with linear predictors such as FIR filters and AR modeling. The fidelity of the reconstructed EEG signal is assessed quantitatively using parameters such as PRD, SNR, cross correlation and power spectral density. It is found from the results that the quality of the reconstructed signal is preserved at a low PRD thereby yielding better compression results compared to results obtained using lossless scheme.

Social discounting involves modulation of neural value signals by temporoparietal junction

Science.gov (United States)

Strombach, Tina; Weber, Bernd; Hangebrauk, Zsofia; Kenning, Peter; Karipidis, Iliana I.; Tobler, Philippe N.; Kalenscher, Tobias

2015-01-01

Most people are generous, but not toward everyone alike: generosity usually declines with social distance between individuals, a phenomenon called social discounting. Despite the pervasiveness of social discounting, social distance between actors has been surprisingly neglected in economic theory and neuroscientific research. We used functional magnetic resonance imaging (fMRI) to study the neural basis of this process to understand the neural underpinnings of social decision making. Participants chose between selfish and generous alternatives, yielding either a large reward for the participant alone, or smaller rewards for the participant and another individual at a particular social distance. We found that generous choices engaged the temporoparietal junction (TPJ). In particular, the TPJ activity was scaled to the social-distance–dependent conflict between selfish and generous motives during prosocial choice, consistent with ideas that the TPJ promotes generosity by facilitating overcoming egoism bias. Based on functional coupling data, we propose and provide evidence for a biologically plausible neural model according to which the TPJ supports social discounting by modulating basic neural value signals in the ventromedial prefrontal cortex to incorporate social-distance–dependent other-regarding preferences into an otherwise exclusively own-reward value representation. PMID:25605887

ER-to-plasma membrane tethering proteins regulate cell signaling and ER morphology.

Science.gov (United States)

Manford, Andrew G; Stefan, Christopher J; Yuan, Helen L; Macgurn, Jason A; Emr, Scott D

2012-12-11

Endoplasmic reticulum-plasma membrane (ER-PM) junctions are conserved structures defined as regions of the ER that tightly associate with the plasma membrane. However, little is known about the mechanisms that tether these organelles together and why such connections are maintained. Using a quantitative proteomic approach, we identified three families of ER-PM tethering proteins in yeast: Ist2 (related to mammalian TMEM16 ion channels), the tricalbins (Tcb1/2/3, orthologs of the extended synaptotagmins), and Scs2 and Scs22 (vesicle-associated membrane protein-associated proteins). Loss of all six tethering proteins results in the separation of the ER from the PM and the accumulation of cytoplasmic ER. Importantly, we find that phosphoinositide signaling is misregulated at the PM, and the unfolded protein response is constitutively activated in the ER in cells lacking ER-PM tether proteins. These results reveal critical roles for ER-PM contacts in cell signaling, organelle morphology, and ER function. Copyright © 2012 Elsevier Inc. All rights reserved.

Plasma membrane lipid–protein interactions affect signaling processes in sterol-biosynthesis mutants in Arabidopsis thaliana

Science.gov (United States)

Zauber, Henrik; Burgos, Asdrubal; Garapati, Prashanth; Schulze, Waltraud X.

2014-01-01

The plasma membrane is an important organelle providing structure, signaling and transport as major biological functions. Being composed of lipids and proteins with different physicochemical properties, the biological functions of membranes depend on specific protein–protein and protein–lipid interactions. Interactions of proteins with their specific sterol and lipid environment were shown to be important factors for protein recruitment into sub-compartmental structures of the plasma membrane. System-wide implications of altered endogenous sterol levels for membrane functions in living cells were not studied in higher plant cells. In particular, little is known how alterations in membrane sterol composition affect protein and lipid organization and interaction within membranes. Here, we conducted a comparative analysis of the plasma membrane protein and lipid composition in Arabidopsis sterol-biosynthesis mutants smt1 and ugt80A2;B1. smt1 shows general alterations in sterol composition while ugt80A2;B1 is significantly impaired in sterol glycosylation. By systematically analyzing different cellular fractions and combining proteomic with lipidomic data we were able to reveal contrasting alterations in lipid–protein interactions in both mutants, with resulting differential changes in plasma membrane signaling status. PMID:24672530

Novel Mutation of LRP6 Identified in Chinese Han Population Links Canonical WNT Signaling to Neural Tube Defects.

Science.gov (United States)

Shi, Zhiwen; Yang, Xueyan; Li, Bin-Bin; Chen, Shuxia; Yang, Luming; Cheng, Liangping; Zhang, Ting; Wang, Hongyan; Zheng, Yufang

2018-01-15

Neural tube defects (NTDs), the second most frequent cause of human congenital abnormalities, are debilitating birth defects due to failure of neural tube closure. It has been shown that noncanonical WNT/planar cell polarity (PCP) signaling is required for convergent extension (CE), the initiation step of neural tube closure (NTC). But the effect of canonical WNT//β-catenin signaling during NTC is still elusive. LRP6 (low density lipoprotein receptor related proteins 6) was identified as a co-receptor for WNT/β-catenin signaling, but recent studies showed that it also can mediate WNT/PCP signaling. In this study, we screened mutations in the LRP6 gene in 343 NTDs and 215 ethnically matched normal controls of Chinese Han population. Three rare missense mutations (c.1514A>G, p.Y505C); c.2984A>G, p.D995G; and c.4280C>A, p.P1427Q) of the LRP6 gene were identified in Chinese NTD patients. The Y505C mutation is a loss-of-function mutation on both WNT/β-catenin and PCP signaling. The D995G mutation only partially lost inhibition on PCP signaling without affecting WNT/β-catenin signaling. The P1427Q mutation dramatically increased WNT/β-catenin signaling but only mildly loss of inhibition on PCP signaling. All three mutations failed to rescue CE defects caused by lrp6 morpholino oligos knockdown in zebrafish. Of interest, when overexpressed, D995G did not induce any defects, but Y505C and P1427Q caused more severe CE defects in zebrafish. Our results suggested that over-active canonical WNT signaling induced by gain-of-function mutation in LRP6 could also contribute to human NTDs, and a balanced WNT/β-catenin and PCP signaling is probably required for proper neural tube development. Birth Defects Research 110:63-71, 2018. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Genomic DISC1 Disruption in hiPSCs Alters Wnt Signaling and Neural Cell Fate

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Priya Srikanth

2015-09-01

Full Text Available Genetic and clinical association studies have identified disrupted in schizophrenia 1 (DISC1 as a candidate risk gene for major mental illness. DISC1 is interrupted by a balanced chr(1;11 translocation in a Scottish family in which the translocation predisposes to psychiatric disorders. We investigate the consequences of DISC1 interruption in human neural cells using TALENs or CRISPR-Cas9 to target the DISC1 locus. We show that disruption of DISC1 near the site of the translocation results in decreased DISC1 protein levels because of nonsense-mediated decay of long splice variants. This results in an increased level of canonical Wnt signaling in neural progenitor cells and altered expression of fate markers such as Foxg1 and Tbr2. These gene expression changes are rescued by antagonizing Wnt signaling in a critical developmental window, supporting the hypothesis that DISC1-dependent suppression of basal Wnt signaling influences the distribution of cell types generated during cortical development.

Dangerous mating systems: signal complexity, signal content and neural capacity in spiders.

Science.gov (United States)

Herberstein, M E; Wignall, A E; Hebets, E A; Schneider, J M

2014-10-01

Spiders are highly efficient predators in possession of exquisite sensory capacities for ambushing prey, combined with machinery for launching rapid and determined attacks. As a consequence, any sexually motivated approach carries a risk of ending up as prey rather than as a mate. Sexual selection has shaped courtship to effectively communicate the presence, identity, motivation and/or quality of potential mates, which help ameliorate these risks. Spiders communicate this information via several sensory channels, including mechanical (e.g. vibrational), visual and/or chemical, with examples of multimodal signalling beginning to emerge in the literature. The diverse environments that spiders inhabit have further shaped courtship content and form. While our understanding of spider neurobiology remains in its infancy, recent studies are highlighting the unique and considerable capacities of spiders to process and respond to complex sexual signals. As a result, the dangerous mating systems of spiders are providing important insights into how ecology shapes the evolution of communication systems, with future work offering the potential to link this complex communication with its neural processes. Copyright © 2014 Elsevier Ltd. All rights reserved.

Lunatic fringe-mediated Notch signaling regulates adult hippocampal neural stem cell maintenance.

Science.gov (United States)

Semerci, Fatih; Choi, William Tin-Shing; Bajic, Aleksandar; Thakkar, Aarohi; Encinas, Juan Manuel; Depreux, Frederic; Segil, Neil; Groves, Andrew K; Maletic-Savatic, Mirjana

2017-07-12

Hippocampal neural stem cells (NSCs) integrate inputs from multiple sources to balance quiescence and activation. Notch signaling plays a key role during this process. Here, we report that Lunatic fringe ( Lfng), a key modifier of the Notch receptor, is selectively expressed in NSCs. Further, Lfng in NSCs and Notch ligands Delta1 and Jagged1, expressed by their progeny, together influence NSC recruitment, cell cycle duration, and terminal fate. We propose a new model in which Lfng-mediated Notch signaling enables direct communication between a NSC and its descendants, so that progeny can send feedback signals to the 'mother' cell to modify its cell cycle status. Lfng-mediated Notch signaling appears to be a key factor governing NSC quiescence, division, and fate.

Altered neural reward and loss processing and prediction error signalling in depression

Science.gov (United States)

Ubl, Bettina; Kuehner, Christine; Kirsch, Peter; Ruttorf, Michaela

2015-01-01

Dysfunctional processing of reward and punishment may play an important role in depression. However, functional magnetic resonance imaging (fMRI) studies have shown heterogeneous results for reward processing in fronto-striatal regions. We examined neural responsivity associated with the processing of reward and loss during anticipation and receipt of incentives and related prediction error (PE) signalling in depressed individuals. Thirty medication-free depressed persons and 28 healthy controls performed an fMRI reward paradigm. Regions of interest analyses focused on neural responses during anticipation and receipt of gains and losses and related PE-signals. Additionally, we assessed the relationship between neural responsivity during gain/loss processing and hedonic capacity. When compared with healthy controls, depressed individuals showed reduced fronto-striatal activity during anticipation of gains and losses. The groups did not significantly differ in response to reward and loss outcomes. In depressed individuals, activity increases in the orbitofrontal cortex and nucleus accumbens during reward anticipation were associated with hedonic capacity. Depressed individuals showed an absence of reward-related PEs but encoded loss-related PEs in the ventral striatum. Depression seems to be linked to blunted responsivity in fronto-striatal regions associated with limited motivational responses for rewards and losses. Alterations in PE encoding might mirror blunted reward- and enhanced loss-related associative learning in depression. PMID:25567763

Receptor density balances signal stimulation and attenuation in membrane-assembled complexes of bacterial chemotaxis signaling proteins

Science.gov (United States)

Besschetnova, Tatiana Y.; Montefusco, David J.; Asinas, Abdalin E.; Shrout, Anthony L.; Antommattei, Frances M.; Weis, Robert M.

2008-01-01

All cells possess transmembrane signaling systems that function in the environment of the lipid bilayer. In the Escherichia coli chemotaxis pathway, the binding of attractants to a two-dimensional array of receptors and signaling proteins simultaneously inhibits an associated kinase and stimulates receptor methylation—a slower process that restores kinase activity. These two opposing effects lead to robust adaptation toward stimuli through a physical mechanism that is not understood. Here, we provide evidence of a counterbalancing influence exerted by receptor density on kinase stimulation and receptor methylation. Receptor signaling complexes were reconstituted over a range of defined surface concentrations by using a template-directed assembly method, and the kinase and receptor methylation activities were measured. Kinase activity and methylation rates were both found to vary significantly with surface concentration—yet in opposite ways: samples prepared at high surface densities stimulated kinase activity more effectively than low-density samples, whereas lower surface densities produced greater methylation rates than higher densities. FRET experiments demonstrated that the cooperative change in kinase activity coincided with a change in the arrangement of the membrane-associated receptor domains. The counterbalancing influence of density on receptor methylation and kinase stimulation leads naturally to a model for signal regulation that is compatible with the known logic of the E. coli pathway. Density-dependent mechanisms are likely to be general and may operate when two or more membrane-related processes are influenced differently by the two-dimensional concentration of pathway elements. PMID:18711126

Two projects in theoretical neuroscience: A convolution-based metric for neural membrane potentials and a combinatorial connectionist semantic network method

Science.gov (United States)

Evans, Garrett Nolan

In this work, I present two projects that both contribute to the aim of discovering how intelligence manifests in the brain. The first project is a method for analyzing recorded neural signals, which takes the form of a convolution-based metric on neural membrane potential recordings. Relying only on integral and algebraic operations, the metric compares the timing and number of spikes within recordings as well as the recordings' subthreshold features: summarizing differences in these with a single "distance" between the recordings. Like van Rossum's (2001) metric for spike trains, the metric is based on a convolution operation that it performs on the input data. The kernel used for the convolution is carefully chosen such that it produces a desirable frequency space response and, unlike van Rossum's kernel, causes the metric to be first order both in differences between nearby spike times and in differences between same-time membrane potential values: an important trait. The second project is a combinatorial syntax method for connectionist semantic network encoding. Combinatorial syntax has been a point on which those who support a symbol-processing view of intelligent processing and those who favor a connectionist view have had difficulty seeing eye-to-eye. Symbol-processing theorists have persuasively argued that combinatorial syntax is necessary for certain intelligent mental operations, such as reasoning by analogy. Connectionists have focused on the versatility and adaptability offered by self-organizing networks of simple processing units. With this project, I show that there is a way to reconcile the two perspectives and to ascribe a combinatorial syntax to a connectionist network. The critical principle is to interpret nodes, or units, in the connectionist network as bound integrations of the interpretations for nodes that they share links with. Nodes need not correspond exactly to neurons and may correspond instead to distributed sets, or assemblies, of

Fault Tolerant Neural Network for ECG Signal Classification Systems

Directory of Open Access Journals (Sweden)

MERAH, M.

2011-08-01

Full Text Available The aim of this paper is to apply a new robust hardware Artificial Neural Network (ANN for ECG classification systems. This ANN includes a penalization criterion which makes the performances in terms of robustness. Specifically, in this method, the ANN weights are normalized using the auto-prune method. Simulations performed on the MIT ? BIH ECG signals, have shown that significant robustness improvements are obtained regarding potential hardware artificial neuron failures. Moreover, we show that the proposed design achieves better generalization performances, compared to the standard back-propagation algorithm.

Deep convolutional neural network for the automated detection and diagnosis of seizure using EEG signals.

Science.gov (United States)

Acharya, U Rajendra; Oh, Shu Lih; Hagiwara, Yuki; Tan, Jen Hong; Adeli, Hojjat

2017-09-27

An encephalogram (EEG) is a commonly used ancillary test to aide in the diagnosis of epilepsy. The EEG signal contains information about the electrical activity of the brain. Traditionally, neurologists employ direct visual inspection to identify epileptiform abnormalities. This technique can be time-consuming, limited by technical artifact, provides variable results secondary to reader expertise level, and is limited in identifying abnormalities. Therefore, it is essential to develop a computer-aided diagnosis (CAD) system to automatically distinguish the class of these EEG signals using machine learning techniques. This is the first study to employ the convolutional neural network (CNN) for analysis of EEG signals. In this work, a 13-layer deep convolutional neural network (CNN) algorithm is implemented to detect normal, preictal, and seizure classes. The proposed technique achieved an accuracy, specificity, and sensitivity of 88.67%, 90.00% and 95.00%, respectively. Copyright © 2017 Elsevier Ltd. All rights reserved.

Discrimination of Cylinders with Different Wall Thicknesses using Neural Networks and Simulated Dolphin Sonar Signals

DEFF Research Database (Denmark)

Andersen, Lars Nonboe; Au, Whitlow; Larsen, Jan

1999-01-01

This paper describes a method integrating neural networks into a system for recognizing underwater objects. The system is based on a combination of simulated dolphin sonar signals, simulated auditory filters and artificial neural networks. The system is tested on a cylinder wall thickness...... difference experiment and demonstrates high accuracy for small wall thickness differences. Results from the experiment are compared with results obtained by a false killer whale (pseudorca crassidens)....

Active generation and propagation of Ca2+ signals within tunneling membrane nanotubes.

Science.gov (United States)

Smith, Ian F; Shuai, Jianwei; Parker, Ian

2011-04-20

A new mechanism of cell-cell communication was recently proposed after the discovery of tunneling nanotubes (TNTs) between cells. TNTs are membrane protrusions with lengths of tens of microns and diameters of a few hundred nanometers that permit the exchange of membrane and cytoplasmic constituents between neighboring cells. TNTs have been reported to mediate intercellular Ca(2+) signaling; however, our simulations indicate that passive diffusion of Ca(2+) ions alone would be inadequate for efficient transmission between cells. Instead, we observed spontaneous and inositol trisphosphate (IP(3))-evoked Ca(2+) signals within TNTs between cultured mammalian cells, which sometimes remained localized and in other instances propagated as saltatory waves to evoke Ca(2+) signals in a connected cell. Consistent with this, immunostaining showed the presence of both endoplasmic reticulum and IP(3) receptors along the TNT. We propose that IP(3) receptors may actively propagate intercellular Ca(2+) signals along TNTs via Ca(2+)-induced Ca(2+) release, acting as amplification sites to overcome the limitations of passive diffusion in a chemical analog of electrical transmission of action potentials. Copyright © 2011 Biophysical Society. Published by Elsevier Inc. All rights reserved.

A subsequent closed-form description of propagated signaling phenomena in the membrane of an axon

Energy Technology Data Exchange (ETDEWEB)

Melendy, Robert F., E-mail: rfmelendy@liberty.edu [School of Engineering and Computational Science, Liberty University, Lynchburg, Virginia, 24515 (United States)

2016-05-15

I recently introduced a closed-form description of propagated signaling phenomena in the membrane of an axon [R.F. Melendy, Journal of Applied Physics 118, 244701 (2015)]. Those results demonstrate how intracellular conductance, the thermodynamics of magnetization, and current modulation, function together in generating an action potential in a unified, closed-form description. At present, I report on a subsequent closed-form model that unifies intracellular conductance and the thermodynamics of magnetization, with the membrane electric field, E{sub m}. It’s anticipated this work will compel researchers in biophysics, physical biology, and the computational neurosciences, to probe deeper into the classical and quantum features of membrane magnetization and signaling, informed by the computational features of this subsequent model.

A subsequent closed-form description of propagated signaling phenomena in the membrane of an axon

Science.gov (United States)

Melendy, Robert. F.

2016-05-01

I recently introduced a closed-form description of propagated signaling phenomena in the membrane of an axon [R.F. Melendy, Journal of Applied Physics 118, 244701 (2015)]. Those results demonstrate how intracellular conductance, the thermodynamics of magnetization, and current modulation, function together in generating an action potential in a unified, closed-form description. At present, I report on a subsequent closed-form model that unifies intracellular conductance and the thermodynamics of magnetization, with the membrane electric field, Em. It's anticipated this work will compel researchers in biophysics, physical biology, and the computational neurosciences, to probe deeper into the classical and quantum features of membrane magnetization and signaling, informed by the computational features of this subsequent model.

A Decline in Response Variability Improves Neural Signal Detection during Auditory Task Performance.

Science.gov (United States)

von Trapp, Gardiner; Buran, Bradley N; Sen, Kamal; Semple, Malcolm N; Sanes, Dan H

2016-10-26

The detection of a sensory stimulus arises from a significant change in neural activity, but a sensory neuron's response is rarely identical to successive presentations of the same stimulus. Large trial-to-trial variability would limit the central nervous system's ability to reliably detect a stimulus, presumably affecting perceptual performance. However, if response variability were to decrease while firing rate remained constant, then neural sensitivity could improve. Here, we asked whether engagement in an auditory detection task can modulate response variability, thereby increasing neural sensitivity. We recorded telemetrically from the core auditory cortex of gerbils, both while they engaged in an amplitude-modulation detection task and while they sat quietly listening to the identical stimuli. Using a signal detection theory framework, we found that neural sensitivity was improved during task performance, and this improvement was closely associated with a decrease in response variability. Moreover, units with the greatest change in response variability had absolute neural thresholds most closely aligned with simultaneously measured perceptual thresholds. Our findings suggest that the limitations imposed by response variability diminish during task performance, thereby improving the sensitivity of neural encoding and potentially leading to better perceptual sensitivity. The detection of a sensory stimulus arises from a significant change in neural activity. However, trial-to-trial variability of the neural response may limit perceptual performance. If the neural response to a stimulus is quite variable, then the response on a given trial could be confused with the pattern of neural activity generated when the stimulus is absent. Therefore, a neural mechanism that served to reduce response variability would allow for better stimulus detection. By recording from the cortex of freely moving animals engaged in an auditory detection task, we found that variability

The Crossroads of Synaptic Growth Signaling, Membrane Traffic and Neurological Disease: Insights from Drosophila.

Science.gov (United States)

Deshpande, Mugdha; Rodal, Avital A

2016-02-01

Neurons require target-derived autocrine and paracrine growth factors to maintain proper identity, innervation, homeostasis and survival. Neuronal growth factor signaling is highly dependent on membrane traffic, both for the packaging and release of the growth factors themselves, and for regulation of intracellular signaling by their transmembrane receptors. Here, we review recent findings from the Drosophila larval neuromuscular junction (NMJ) that illustrate how specific steps of intracellular traffic and inter-organelle interactions impinge on signaling, particularly in the bone morphogenic protein, Wingless and c-Jun-activated kinase pathways, regulating elaboration and stability of NMJ arbors, construction of synapses and synaptic transmission and homeostasis. These membrane trafficking and signaling pathways have been implicated in human motor neuron diseases including amyotrophic lateral sclerosis and hereditary spastic paraplegia, highlighting their importance for neuronal health and survival. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Neural network-based sensor signal accelerator.

Energy Technology Data Exchange (ETDEWEB)

Vogt, M. C.

2000-10-16

A strategy has been developed to computationally accelerate the response time of a generic electronic sensor. The strategy can be deployed as an algorithm in a control system or as a physical interface (on an embedded microcontroller) between a slower responding external sensor and a higher-speed control system. Optional code implementations are available to adjust algorithm performance when computational capability is limited. In one option, the actual sensor signal can be sampled at the slower rate with adaptive linear neural networks predicting the sensor's future output and interpolating intermediate synthetic output values. In another option, a synchronized collection of predictors sequentially controls the corresponding synthetic output voltage. Error is adaptively corrected in both options. The core strategy has been demonstrated with automotive oxygen sensor data. A prototype interface device is under construction. The response speed increase afforded by this strategy could greatly offset the cost of developing a replacement sensor with a faster physical response time.

Small leucine rich proteoglycan family regulates multiple signalling pathways in neural development and maintenance.

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Dellett, Margaret; Hu, Wanzhou; Papadaki, Vasiliki; Ohnuma, Shin-ichi

2012-04-01

The small leucine-rich repeat proteoglycan (SLRPs) family of proteins currently consists of five classes, based on their structural composition and chromosomal location. As biologically active components of the extracellular matrix (ECM), SLRPs were known to bind to various collagens, having a role in regulating fibril assembly, organization and degradation. More recently, as a function of their diverse proteins cores and glycosaminoglycan side chains, SLRPs have been shown to be able to bind various cell surface receptors, growth factors, cytokines and other ECM components resulting in the ability to influence various cellular functions. Their involvement in several signaling pathways such as Wnt, transforming growth factor-β and epidermal growth factor receptor also highlights their role as matricellular proteins. SLRP family members are expressed during neural development and in adult neural tissues, including ocular tissues. This review focuses on describing SLRP family members involvement in neural development with a brief summary of their role in non-neural ocular tissues and in response to neural injury. © 2012 The Authors Development, Growth & Differentiation © 2012 Japanese Society of Developmental Biologists.

Neural Network Based Recognition of Signal Patterns in Application to Automatic Testing of Rails

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Tomasz Ciszewski

2006-01-01

Full Text Available The paper describes the application of neural network for recognition of signal patterns in measuring data gathered by the railroad ultrasound testing car. Digital conversion of the measuring signal allows to store and process large quantities of data. The elaboration of smart, effective and automatic procedures recognizing the obtained patterns on the basisof measured signal amplitude has been presented. The test shows only two classes of pattern recognition. In authors’ opinion if we deliver big enough quantity of training data, presented method is applicable to a system that recognizes many classes.

A PtdIns(4)P-driven electrostatic field controls cell membrane identity and signalling in plants.

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Simon, Mathilde Laetitia Audrey; Platre, Matthieu Pierre; Marquès-Bueno, Maria Mar; Armengot, Laia; Stanislas, Thomas; Bayle, Vincent; Caillaud, Marie-Cécile; Jaillais, Yvon

2016-06-20

Many signalling proteins permanently or transiently localize to specific organelles. It is well established that certain lipids act as biochemical landmarks to specify compartment identity. However, they also influence membrane biophysical properties, which emerge as important features in specifying cellular territories. Such parameters include the membrane inner surface potential, which varies according to the lipid composition of each organelle. Here, we found that the plant plasma membrane (PM) and the cell plate of dividing cells have a unique electrostatic signature controlled by phosphatidylinositol-4-phosphate (PtdIns(4)P). Our results further reveal that, contrarily to other eukaryotes, PtdIns(4)P massively accumulates at the PM, establishing it as a critical hallmark of this membrane in plants. Membrane surface charges control the PM localization and function of the polar auxin transport regulator PINOID as well as proteins from the BRI1 KINASE INHIBITOR1 (BKI1)/MEMBRANE ASSOCIATED KINASE REGULATOR (MAKR) family, which are involved in brassinosteroid and receptor-like kinase signalling. We anticipate that this PtdIns(4)P-driven physical membrane property will control the localization and function of many proteins involved in development, reproduction, immunity and nutrition.

Orphan nuclear receptor TLX activates Wnt/β-catenin signalling to stimulate neural stem cell proliferation and self-renewal

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Qu, Qiuhao; Sun, Guoqiang; Li, Wenwu; Yang, Su; Ye, Peng; Zhao, Chunnian; Yu, Ruth T.; Gage, Fred H.; Evans, Ronald M.; Shi, Yanhong

2010-01-01

The nuclear receptor TLX (also known as NR2E1) is essential for adult neural stem cell self-renewal; however, the molecular mechanisms involved remain elusive. Here we show that TLX activates the canonical Wnt/β-catenin pathway in adult mouse neural stem cells. Furthermore, we demonstrate that Wnt/β-catenin signalling is important in the proliferation and self-renewal of adult neural stem cells in the presence of epidermal growth factor and fibroblast growth factor. Wnt7a and active β-catenin promote neural stem cell self-renewal, whereas the deletion of Wnt7a or the lentiviral transduction of axin, a β-catenin inhibitor, led to decreased cell proliferation in adult neurogenic areas. Lentiviral transduction of active β-catenin led to increased numbers of type B neural stem cells in the subventricular zone of adult brains, whereas deletion of Wnt7a or TLX resulted in decreased numbers of neural stem cells retaining bromodeoxyuridine label in the adult brain. Both Wnt7a and active β-catenin significantly rescued a TLX (also known as Nr2e1) short interfering RNA-induced deficiency in neural stem cell proliferation. Lentiviral transduction of an active β-catenin increased cell proliferation in neurogenic areas of TLX-null adult brains markedly. These results strongly support the hypothesis that TLX acts through the Wnt/β-catenin pathway to regulate neural stem cell proliferation and self-renewal. Moreover, this study suggests that neural stem cells can promote their own self-renewal by secreting signalling molecules that act in an autocrine/paracrine mode. PMID:20010817

Orphan nuclear receptor TLX activates Wnt/beta-catenin signalling to stimulate neural stem cell proliferation and self-renewal.

Science.gov (United States)

Qu, Qiuhao; Sun, Guoqiang; Li, Wenwu; Yang, Su; Ye, Peng; Zhao, Chunnian; Yu, Ruth T; Gage, Fred H; Evans, Ronald M; Shi, Yanhong

2010-01-01

The nuclear receptor TLX (also known as NR2E1) is essential for adult neural stem cell self-renewal; however, the molecular mechanisms involved remain elusive. Here we show that TLX activates the canonical Wnt/beta-catenin pathway in adult mouse neural stem cells. Furthermore, we demonstrate that Wnt/beta-catenin signalling is important in the proliferation and self-renewal of adult neural stem cells in the presence of epidermal growth factor and fibroblast growth factor. Wnt7a and active beta-catenin promote neural stem cell self-renewal, whereas the deletion of Wnt7a or the lentiviral transduction of axin, a beta-catenin inhibitor, led to decreased cell proliferation in adult neurogenic areas. Lentiviral transduction of active beta-catenin led to increased numbers of type B neural stem cells in the subventricular zone of adult brains, whereas deletion of Wnt7a or TLX resulted in decreased numbers of neural stem cells retaining bromodeoxyuridine label in the adult brain. Both Wnt7a and active beta-catenin significantly rescued a TLX (also known as Nr2e1) short interfering RNA-induced deficiency in neural stem cell proliferation. Lentiviral transduction of an active beta-catenin increased cell proliferation in neurogenic areas of TLX-null adult brains markedly. These results strongly support the hypothesis that TLX acts through the Wnt/beta-catenin pathway to regulate neural stem cell proliferation and self-renewal. Moreover, this study suggests that neural stem cells can promote their own self-renewal by secreting signalling molecules that act in an autocrine/paracrine mode.

Enhancement of signal sensitivity in a heterogeneous neural network refined from synaptic plasticity

Energy Technology Data Exchange (ETDEWEB)

Li Xiumin; Small, Michael, E-mail: ensmall@polyu.edu.h, E-mail: 07901216r@eie.polyu.edu.h [Department of Electronic and Information Engineering, Hong Kong Polytechnic University, Hung Hom, Kowloon (Hong Kong)

2010-08-15

Long-term synaptic plasticity induced by neural activity is of great importance in informing the formation of neural connectivity and the development of the nervous system. It is reasonable to consider self-organized neural networks instead of prior imposition of a specific topology. In this paper, we propose a novel network evolved from two stages of the learning process, which are respectively guided by two experimentally observed synaptic plasticity rules, i.e. the spike-timing-dependent plasticity (STDP) mechanism and the burst-timing-dependent plasticity (BTDP) mechanism. Due to the existence of heterogeneity in neurons that exhibit different degrees of excitability, a two-level hierarchical structure is obtained after the synaptic refinement. This self-organized network shows higher sensitivity to afferent current injection compared with alternative archetypal networks with different neural connectivity. Statistical analysis also demonstrates that it has the small-world properties of small shortest path length and high clustering coefficients. Thus the selectively refined connectivity enhances the ability of neuronal communications and improves the efficiency of signal transmission in the network.

Enhancement of signal sensitivity in a heterogeneous neural network refined from synaptic plasticity

International Nuclear Information System (INIS)

Li Xiumin; Small, Michael

2010-01-01

Long-term synaptic plasticity induced by neural activity is of great importance in informing the formation of neural connectivity and the development of the nervous system. It is reasonable to consider self-organized neural networks instead of prior imposition of a specific topology. In this paper, we propose a novel network evolved from two stages of the learning process, which are respectively guided by two experimentally observed synaptic plasticity rules, i.e. the spike-timing-dependent plasticity (STDP) mechanism and the burst-timing-dependent plasticity (BTDP) mechanism. Due to the existence of heterogeneity in neurons that exhibit different degrees of excitability, a two-level hierarchical structure is obtained after the synaptic refinement. This self-organized network shows higher sensitivity to afferent current injection compared with alternative archetypal networks with different neural connectivity. Statistical analysis also demonstrates that it has the small-world properties of small shortest path length and high clustering coefficients. Thus the selectively refined connectivity enhances the ability of neuronal communications and improves the efficiency of signal transmission in the network.

An N-Terminal ER Export Signal Facilitates the Plasma Membrane Targeting of HCN1 Channels in Photoreceptors.

Science.gov (United States)

Pan, Yuan; Laird, Joseph G; Yamaguchi, David M; Baker, Sheila A

2015-06-01

Hyperpolarization-activated cyclic nucleotide-gated 1 (HCN1) channels are widely expressed in the retina. In photoreceptors, the hyperpolarization-activated current (Ih) carried by HCN1 is important for shaping the light response. It has been shown in multiple systems that trafficking HCN1 channels to specific compartments is key to their function. The localization of HCN1 in photoreceptors is concentrated in the plasma membrane of the inner segment (IS). The mechanisms controlling this localization are not understood. We previously identified a di-arginine endoplasmic reticulum (ER) retention motif that negatively regulates the surface targeting of HCN1. In this study, we sought to identify a forward trafficking signal that could counter the function of the ER retention signal. We studied trafficking of HCN1 and several mutants by imaging their subcellular localization in transgenic X. laevis photoreceptors. Velocity sedimentation was used to assay the assembly state of HCN1 channels. We found the HCN1 N-terminus can redirect a membrane reporter from outer segments (OS) to the plasma membrane of the IS. The sequence necessary for this behavior was mapped to a 20 amino acid region containing a leucine-based ER export motif. The ER export signal is necessary for forward trafficking but not channel oligomerization. Moreover, this ER export signal alone counteracted the di-arginine ER retention signal. We identified an ER export signal in HCN1 that functions with the ER retention signal to maintain equilibrium of HCN1 between the endomembrane system and the plasma membrane.

Effect of signal noise on the learning capability of an artificial neural network

International Nuclear Information System (INIS)

Vega, J.J.; Reynoso, R.; Calvet, H. Carrillo

2009-01-01

Digital Pulse Shape Analysis (DPSA) by artificial neural networks (ANN) is becoming an important tool to extract relevant information from digitized signals in different areas. In this paper, we present a systematic evidence of how the concomitant noise that distorts the signals or patterns to be identified by an ANN set limits to its learning capability. Also, we present evidence that explains overtraining as a competition between the relevant pattern features, on the one side, against the signal noise, on the other side, as the main cause defining the shape of the error surface in weight space and, consequently, determining the steepest descent path that controls the ANN adaptation process.

Detecting and Predicting Muscle Fatigue during Typing By SEMG Signal Processing and Artificial Neural Networks

Directory of Open Access Journals (Sweden)

Elham Ghoochani

2011-03-01

Full Text Available Introduction: Repetitive strain injuries are one of the most prevalent problems in occupational diseases. Repetition, vibration and bad postures of the extremities are physical risk factors related to work that can cause chronic musculoskeletal disorders. Repetitive work on a computer with low level contraction requires the posture to be maintained for a long time, which can cause muscle fatigue. Muscle fatigue in shoulders and neck is one of the most prevalent problems reported with computer users especially during typing. Surface electromyography (SEMG signals are used for detecting muscle fatigue as a non-invasive method. Material and Methods: Nine healthy females volunteered for signal recoding during typing. EMG signals were recorded from the trapezius muscle, which is subjected to muscle fatigue during typing.  After signal analysis and feature extraction, detecting and predicting muscle fatigue was performed by using the MLP artificial neural network. Results: Recorded signals were analyzed in time and frequency domains for feature extraction. Results of classification showed that the MLP neural network can detect and predict muscle fatigue during typing with 80.79 % ± 1.04% accuracy. Conclusion: Intelligent classification and prediction of muscle fatigue can have many applications in human factors engineering (ergonomics, rehabilitation engineering and biofeedback equipment for mitigating the injuries of repetitive works.

An artificial neural network ensemble method for fault diagnosis of proton exchange membrane fuel cell system

International Nuclear Information System (INIS)

Shao, Meng; Zhu, Xin-Jian; Cao, Hong-Fei; Shen, Hai-Feng

2014-01-01

The commercial viability of PEMFC (proton exchange membrane fuel cell) systems depends on using effective fault diagnosis technologies in PEMFC systems. However, many researchers have experimentally studied PEMFC (proton exchange membrane fuel cell) systems without considering certain fault conditions. In this paper, an ANN (artificial neural network) ensemble method is presented that improves the stability and reliability of the PEMFC systems. In the first part, a transient model giving it flexibility in application to some exceptional conditions is built. The PEMFC dynamic model is built and simulated using MATLAB. In the second, using this model and experiments, the mechanisms of four different faults in PEMFC systems are analyzed in detail. Third, the ANN ensemble for the fault diagnosis is built and modeled. This model is trained and tested by the data. The test result shows that, compared with the previous method for fault diagnosis of PEMFC systems, the proposed fault diagnosis method has higher diagnostic rate and generalization ability. Moreover, the partial structure of this method can be altered easily, along with the change of the PEMFC systems. In general, this method for diagnosis of PEMFC has value for certain applications. - Highlights: • We analyze the principles and mechanisms of the four faults in PEMFC (proton exchange membrane fuel cell) system. • We design and model an ANN (artificial neural network) ensemble method for the fault diagnosis of PEMFC system. • This method has high diagnostic rate and strong generalization ability

Programmed Fetal Membrane Senescence and Exosome-Mediated Signaling: A Mechanism Associated With Timing of Human Parturition

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Ramkumar Menon

2017-08-01

Full Text Available Human parturition is an inflammatory process that involves both fetal and maternal compartments. The precise immune cell interactions have not been well delineated in human uterine tissues during parturition, but insights into human labor initiation have been informed by studies in animal models. Unfortunately, the timing of parturition relative to fetal maturation varies among viviparous species—indicative of different phylogenetic clocks and alarms—but what is clear is that important common pathways must converge to control the birth process. Herein, we hypothesize a novel signaling mechanism initiated by human fetal membrane aging and senescence-associated inflammation. Programmed events of fetal membrane aging coincide with fetal growth and organ maturation. Mechanistically, senescence involves in telomere shortening and activation of p38 mitogen-activated signaling kinase resulting in aging-associated phenotypic transition. Senescent tissues release inflammatory signals that are propagated via exosomes to cause functional changes in maternal uterine tissues. In vitro, oxidative stress causes increased release of inflammatory mediators (senescence-associated secretory phenotype and damage-associated molecular pattern markers that can be packaged inside the exosomes. These exosomes traverse through tissues layers, reach maternal tissues to increase overall inflammatory load transitioning them from a quiescent to active state. Animal model studies have shown that fetal exosomes can travel from fetal to the maternal side. Thus, aging fetal membranes and membrane-derived exosomes cargo fetal signals to the uterus and cervix and may trigger parturition. This review highlights a novel hypothesis in human parturition research based on data from ongoing research using human fetal membrane model system.

How membranes shape plant symbioses: signaling and transport in nodulation and arbuscular mycorrhiza

Science.gov (United States)

Bapaume, Laure; Reinhardt, Didier

2012-01-01

As sessile organisms that cannot evade adverse environmental conditions, plants have evolved various adaptive strategies to cope with environmental stresses. One of the most successful adaptations is the formation of symbiotic associations with beneficial microbes. In these mutualistic interactions the partners exchange essential nutrients and improve their resistance to biotic and abiotic stresses. In arbuscular mycorrhiza (AM) and in root nodule symbiosis (RNS), AM fungi and rhizobia, respectively, penetrate roots and accommodate within the cells of the plant host. In these endosymbiotic associations, both partners keep their plasma membranes intact and use them to control the bidirectional exchange of signaling molecules and nutrients. Intracellular accommodation requires the exchange of symbiotic signals and the reprogramming of both interacting partners. This involves fundamental changes at the level of gene expression and of the cytoskeleton, as well as of organelles such as plastids, endoplasmic reticulum (ER), and the central vacuole. Symbiotic cells are highly compartmentalized and have a complex membrane system specialized for the diverse functions in molecular communication and nutrient exchange. Here, we discuss the roles of the different cellular membrane systems and their symbiosis-related proteins in AM and RNS, and we review recent progress in the analysis of membrane proteins involved in endosymbiosis. PMID:23060892

Neural induction in Xenopus: requirement for ectodermal and endomesodermal signals via Chordin, Noggin, beta-Catenin, and Cerberus.

Directory of Open Access Journals (Sweden)

Hiroki Kuroda

2004-05-01

Full Text Available The origin of the signals that induce the differentiation of the central nervous system (CNS is a long-standing question in vertebrate embryology. Here we show that Xenopus neural induction starts earlier than previously thought, at the blastula stage, and requires the combined activity of two distinct signaling centers. One is the well-known Nieuwkoop center, located in dorsal-vegetal cells, which expresses Nodal-related endomesodermal inducers. The other is a blastula Chordin- and Noggin-expressing (BCNE center located in dorsal animal cells that contains both prospective neuroectoderm and Spemann organizer precursor cells. Both centers are downstream of the early beta-Catenin signal. Molecular analyses demonstrated that the BCNE center was distinct from the Nieuwkoop center, and that the Nieuwkoop center expressed the secreted protein Cerberus (Cer. We found that explanted blastula dorsal animal cap cells that have not yet contacted a mesodermal substratum can, when cultured in saline solution, express definitive neural markers and differentiate histologically into CNS tissue. Transplantation experiments showed that the BCNE region was required for brain formation, even though it lacked CNS-inducing activity when transplanted ventrally. Cell-lineage studies demonstrated that BCNE cells give rise to a large part of the brain and retina and, in more posterior regions of the embryo, to floor plate and notochord. Loss-of-function experiments with antisense morpholino oligos (MO showed that the CNS that forms in mesoderm-less Xenopus embryos (generated by injection with Cerberus-Short [CerS] mRNA required Chordin (Chd, Noggin (Nog, and their upstream regulator beta-Catenin. When mesoderm involution was prevented in dorsal marginal-zone explants, the anterior neural tissue formed in ectoderm was derived from BCNE cells and had a complete requirement for Chd. By injecting Chd morpholino oligos (Chd-MO into prospective neuroectoderm and Cerberus

Classifying the molecular functions of Rab GTPases in membrane trafficking using deep convolutional neural networks.

Science.gov (United States)

Le, Nguyen-Quoc-Khanh; Ho, Quang-Thai; Ou, Yu-Yen

2018-06-13

Deep learning has been increasingly used to solve a number of problems with state-of-the-art performance in a wide variety of fields. In biology, deep learning can be applied to reduce feature extraction time and achieve high levels of performance. In our present work, we apply deep learning via two-dimensional convolutional neural networks and position-specific scoring matrices to classify Rab protein molecules, which are main regulators in membrane trafficking for transferring proteins and other macromolecules throughout the cell. The functional loss of specific Rab molecular functions has been implicated in a variety of human diseases, e.g., choroideremia, intellectual disabilities, cancer. Therefore, creating a precise model for classifying Rabs is crucial in helping biologists understand the molecular functions of Rabs and design drug targets according to such specific human disease information. We constructed a robust deep neural network for classifying Rabs that achieved an accuracy of 99%, 99.5%, 96.3%, and 97.6% for each of four specific molecular functions. Our approach demonstrates superior performance to traditional artificial neural networks. Therefore, from our proposed study, we provide both an effective tool for classifying Rab proteins and a basis for further research that can improve the performance of biological modeling using deep neural networks. Copyright © 2018 Elsevier Inc. All rights reserved.

Larger Neural Responses Produce BOLD Signals That Begin Earlier in Time

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Serena eThompson

2014-06-01

Full Text Available Functional MRI analyses commonly rely on the assumption that the temporal dynamics of hemodynamic response functions (HRFs are independent of the amplitude of the neural signals that give rise to them. The validity of this assumption is particularly important for techniques that use fMRI to resolve sub-second timing distinctions between responses, in order to make inferences about the ordering of neural processes. Whether or not the detailed shape of the HRF is independent of neural response amplitude remains an open question, however. We performed experiments in which we measured responses in primary visual cortex (V1 to large, contrast-reversing checkerboards at a range of contrast levels, which should produce varying amounts of neural activity. Ten subjects (ages 22-52 were studied in each of two experiments using 3 Tesla scanners. We used rapid, 250 msec, temporal sampling (repetition time, or TR and both short and long inter-stimulus interval (ISI stimulus presentations. We tested for a systematic relationship between the onset of the HRF and its amplitude across conditions, and found a strong negative correlation between the two measures when stimuli were separated in time (long- and medium-ISI experiments, but not the short-ISI experiment. Thus, stimuli that produce larger neural responses, as indexed by HRF amplitude, also produced HRFs with shorter onsets. The relationship between amplitude and latency was strongest in voxels with lowest mean-normalized variance (i.e., parenchymal voxels. The onset differences observed in the longer-ISI experiments are likely attributable to mechanisms of neurovascular coupling, since they are substantially larger than reported differences in the onset of action potentials in V1 as a function of response amplitude.

Compartmentalized cAMP Signaling Associated With Lipid Raft and Non-raft Membrane Domains in Adult Ventricular Myocytes.

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Agarwal, Shailesh R; Gratwohl, Jackson; Cozad, Mia; Yang, Pei-Chi; Clancy, Colleen E; Harvey, Robert D

2018-01-01

Aim: Confining cAMP production to discrete subcellular locations makes it possible for this ubiquitous second messenger to elicit unique functional responses. Yet, factors that determine how and where the production of this diffusible signaling molecule occurs are incompletely understood. The fluid mosaic model originally proposed that signal transduction occurs through random interactions between proteins diffusing freely throughout the plasma membrane. However, it is now known that the movement of membrane proteins is restricted, suggesting that the plasma membrane is segregated into distinct microdomains where different signaling proteins can be concentrated. In this study, we examined what role lipid raft and non-raft membrane domains play in compartmentation of cAMP signaling in adult ventricular myocytes. Methods and Results: The freely diffusible fluorescence resonance energy transfer-based biosensor Epac2-camps was used to measure global cytosolic cAMP responses, while versions of the probe targeted to lipid raft (Epac2-MyrPalm) and non-raft (Epac2-CAAX) domains were used to monitor local cAMP production near the plasma membrane. We found that β-adrenergic receptors, which are expressed in lipid raft and non-raft domains, produce cAMP responses near the plasma membrane that are distinctly different from those produced by E-type prostaglandin receptors, which are expressed exclusively in non-raft domains. We also found that there are differences in basal cAMP levels associated with lipid raft and non-raft domains, and that this can be explained by differences in basal adenylyl cyclase activity associated with each of these membrane environments. In addition, we found evidence that phosphodiesterases 2, 3, and 4 work together in regulating cAMP activity associated with both lipid raft and non-raft domains, while phosphodiesterase 3 plays a more prominent role in the bulk cytoplasmic compartment. Conclusion: These results suggest that different membrane

EEG signal classification based on artificial neural networks and amplitude spectra features

Science.gov (United States)

Chojnowski, K.; FrÄ czek, J.

BCI (called Brain-Computer Interface) is an interface that allows direct communication between human brain and an external device. It bases on EEG signal collection, processing and classification. In this paper a complete BCI system is presented which classifies EEG signal using artificial neural networks. For this purpose we used a multi-layered perceptron architecture trained with the RProp algorithm. Furthermore a simple multi-threaded method for automatic network structure optimizing was shown. We presented the results of our system in the opening and closing eyes recognition task. We also showed how our system could be used for controlling devices basing on imaginary hand movements.

A model for the biosynthesis and transport of plasma membrane-associated signaling receptors to the cell surface

Directory of Open Access Journals (Sweden)

Sorina Claudia Popescu

2012-04-01

Full Text Available Intracellular protein transport is emerging as critical in determining the outcome of receptor-activated signal transduction pathways. In plants, relatively little is known about the nature of the molecular components and mechanisms involved in coordinating receptor synthesis and transport to the cell surface. Recent advances in this field indicate that signaling pathways and intracellular transport machinery converge and coordinate to render receptors competent for signaling at their plasma membrane activity sites. The biogenesis and transport to the cell surface of signaling receptors appears to require both general trafficking and receptor-specific factors. Several molecular determinants, residing or associated with compartments of the secretory pathway and known to influence aspects in receptor biogenesis, are discussed and integrated into a predictive cooperative model for the functional expression of signaling receptors at the plasma membrane.

Fatty acid-induced gut-brain signaling attenuates neural and behavioral effects of sad emotion in humans.

Science.gov (United States)

Van Oudenhove, Lukas; McKie, Shane; Lassman, Daniel; Uddin, Bilal; Paine, Peter; Coen, Steven; Gregory, Lloyd; Tack, Jan; Aziz, Qasim

2011-08-01

Although a relationship between emotional state and feeding behavior is known to exist, the interactions between signaling initiated by stimuli in the gut and exteroceptively generated emotions remain incompletely understood. Here, we investigated the interaction between nutrient-induced gut-brain signaling and sad emotion induced by musical and visual cues at the behavioral and neural level in healthy nonobese subjects undergoing functional magnetic resonance imaging. Subjects received an intragastric infusion of fatty acid solution or saline during neutral or sad emotion induction and rated sensations of hunger, fullness, and mood. We found an interaction between fatty acid infusion and emotion induction both in the behavioral readouts (hunger, mood) and at the level of neural activity in multiple pre-hypothesized regions of interest. Specifically, the behavioral and neural responses to sad emotion induction were attenuated by fatty acid infusion. These findings increase our understanding of the interplay among emotions, hunger, food intake, and meal-induced sensations in health, which may have important implications for a wide range of disorders, including obesity, eating disorders, and depression.

Neural Correlates of Success and Failure Signals During Neurofeedback Learning.

Science.gov (United States)

Radua, Joaquim; Stoica, Teodora; Scheinost, Dustin; Pittenger, Christopher; Hampson, Michelle

2018-05-15

Feedback-driven learning, observed across phylogeny and of clear adaptive value, is frequently operationalized in simple operant conditioning paradigms, but it can be much more complex, driven by abstract representations of success and failure. This study investigates the neural processes involved in processing success and failure during feedback learning, which are not well understood. Data analyzed were acquired during a multisession neurofeedback experiment in which ten participants were presented with, and instructed to modulate, the activity of their orbitofrontal cortex with the aim of decreasing their anxiety. We assessed the regional blood-oxygenation-level-dependent response to the individualized neurofeedback signals of success and failure across twelve functional runs acquired in two different magnetic resonance sessions in each of ten individuals. Neurofeedback signals of failure correlated early during learning with deactivation in the precuneus/posterior cingulate and neurofeedback signals of success correlated later during learning with deactivation in the medial prefrontal/anterior cingulate cortex. The intensity of the latter deactivations predicted the efficacy of the neurofeedback intervention in the reduction of anxiety. These findings indicate a role for regulation of the default mode network during feedback learning, and suggest a higher sensitivity to signals of failure during the early feedback learning and to signals of success subsequently. Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.

Neural network signal understanding for instrumentation

DEFF Research Database (Denmark)

Pau, L. F.; Johansen, F. S.

1990-01-01

understanding research is surveyed, and the selected implementation and its performance in terms of correct classification rates and robustness to noise are described. Formal results on neural net training time and sensitivity to weights are given. A theory for neural control using functional link nets is given...

Characterisation of eddy current signals using different types of artificial neural networks

International Nuclear Information System (INIS)

Shyamsunder, M.T.; Rajagopalan, C.; Jayakumar, T.; Kalyanasundaram, P.; Baldev Raj; Ray, K.K.

1996-01-01

Eddy current testing is one of the important techniques in nondestructive testing. Automated characterisation of eddy current signals (ECS), either in the form of lissajous patterns (figure-of-eight) or individual voltage vs. time signals is an area of growing interest. This is particularly relevant in environments where the signal-to-noise ratio (SNR) of ECS are very poor. Intelligent, timely and precise interpretation of resulting data, is the key for improving the efficiency of NDT and E. A comprehensive study has been undertaken by the authors for the characterisation of ECS having poor SNR, using three types of artificial neural networks (ANNs). The types of ANNs used in this study are [a] the error-back propagation model, [b] the binary Hopfield model and [c] the Kohonen's self-organising maps model. Eddy current signals, acquired from different types of defects such as holes and notches on stainless steel type 316 sheets were used in this study. (author)

Theta signal as the neural signature of social exclusion.

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Cristofori, Irene; Moretti, Laura; Harquel, Sylvain; Posada, Andres; Deiana, Gianluca; Isnard, Jean; Mauguière, François; Sirigu, Angela

2013-10-01

The feeling of being excluded from a social interaction triggers social pain, a sensation as intense as actual physical pain. Little is known about the neurophysiological underpinnings of social pain. We addressed this issue using intracranial electroencephalography in 15 patients performing a ball game where inclusion and exclusion blocks were alternated. Time-frequency analyses showed an increase in power of theta-band oscillations during exclusion in the anterior insula (AI) and posterior insula, the subgenual anterior cingulate cortex (sACC), and the fusiform "face area" (FFA). Interestingly, the AI showed an initial fast response to exclusion but the signal rapidly faded out. Activity in the sACC gradually increased and remained significant thereafter. This suggests that the AI may signal social pain by detecting emotional distress caused by the exclusion, whereas the sACC may be linked to the learning aspects of social pain. Theta activity in the FFA was time-locked to the observation of a player poised to exclude the participant, suggesting that the FFA encodes the social value of faces. Taken together, our findings suggest that theta activity represents the neural signature of social pain. The time course of this signal varies across regions important for processing emotional features linked to social information.

A low-power current-reuse dual-band analog front-end for multi-channel neural signal recording.

Science.gov (United States)

Sepehrian, H; Gosselin, B

2014-01-01

Thoroughly studying the brain activity of freely moving subjects requires miniature data acquisition systems to measure and wirelessly transmit neural signals in real time. In this application, it is mandatory to simultaneously record the bioelectrical activity of a large number of neurons to gain a better knowledge of brain functions. However, due to limitations in transferring the entire raw data to a remote base station, employing dedicated data reduction techniques to extract the relevant part of neural signals is critical to decrease the amount of data to transfer. In this work, we present a new dual-band neural amplifier to separate the neuronal spike signals (SPK) and the local field potential (LFP) simultaneously in the analog domain, immediately after the pre-amplification stage. By separating these two bands right after the pre-amplification stage, it is possible to process LFP and SPK separately. As a result, the required dynamic range of the entire channel, which is determined by the signal-to-noise ratio of the SPK signal of larger bandwidth, can be relaxed. In this design, a new current-reuse low-power low-noise amplifier and a new dual-band filter that separates SPK and LFP while saving capacitors and pseudo resistors. A four-channel dual-band (SPK, LFP) analog front-end capable of simultaneously separating SPK and LFP is implemented in a TSMC 0.18 μm technology. Simulation results present a total power consumption per channel of 3.1 μw for an input referred noise of 3.28 μV and a NEF for 2.07. The cutoff frequency of the LFP band is fc=280 Hz, and fL=725 Hz and fL=11.2 KHz for SPK, with 36 dB gain for LFP band 46 dB gain for SPK band.

RBF neural network prediction on weak electrical signals in Aloe vera var. chinensis

Science.gov (United States)

Wang, Lanzhou; Zhao, Jiayin; Wang, Miao

2008-10-01

A Gaussian radial base function (RBF) neural network forecast on signals in the Aloe vera var. chinensis by the wavelet soft-threshold denoised as the time series and using the delayed input window chosen at 50, is set up to forecast backward. There was the maximum amplitude at 310.45μV, minimum -75.15μV, average value -2.69μV and Aloe vera var. chinensis respectively. The electrical signal in Aloe vera var. chinensis is a sort of weak, unstable and low frequency signals. A result showed that it is feasible to forecast plant electrical signals for the timing by the RBF. The forecast data can be used as the preferences for the intelligent autocontrol system based on the adaptive characteristic of plants to achieve the energy saving on the agricultural production in the plastic lookum or greenhouse.

A potential neural substrate for processing functional classes of complex acoustic signals.

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Isabelle George

Full Text Available Categorization is essential to all cognitive processes, but identifying the neural substrates underlying categorization processes is a real challenge. Among animals that have been shown to be able of categorization, songbirds are particularly interesting because they provide researchers with clear examples of categories of acoustic signals allowing different levels of recognition, and they possess a system of specialized brain structures found only in birds that learn to sing: the song system. Moreover, an avian brain nucleus that is analogous to the mammalian secondary auditory cortex (the caudo-medial nidopallium, or NCM has recently emerged as a plausible site for sensory representation of birdsong, and appears as a well positioned brain region for categorization of songs. Hence, we tested responses in this non-primary, associative area to clear and distinct classes of songs with different functions and social values, and for a possible correspondence between these responses and the functional aspects of songs, in a highly social songbird species: the European starling. Our results clearly show differential neuronal responses to the ethologically defined classes of songs, both in the number of neurons responding, and in the response magnitude of these neurons. Most importantly, these differential responses corresponded to the functional classes of songs, with increasing activation from non-specific to species-specific and from species-specific to individual-specific sounds. These data therefore suggest a potential neural substrate for sorting natural communication signals into categories, and for individual vocal recognition of same-species members. Given the many parallels that exist between birdsong and speech, these results may contribute to a better understanding of the neural bases of speech.

Membrane proteins involved in transport, vesicle traffic and Ca(2+) signaling increase in beetroots grown in saline soils.

Science.gov (United States)

Lino, Bárbara; Chagolla, Alicia; E González de la Vara, Luis

2016-07-01

By separating plasma membrane proteins according to their hydropathy from beetroots grown in saline soils, several proteins probably involved in salt tolerance were identified by mass spectrometry. Beetroots, as a salt-tolerant crop, have developed mechanisms to cope with stresses associated with saline soils. To observe which plasma membrane (PM) proteins were more abundant in beet roots grown in saline soils, beet root plants were irrigated with water or 0.2 M NaCl. PM-enriched membrane preparations were obtained from these plants, and their proteins were separated according to their hydropathy by serial phase partitioning with Triton X-114. Some proteins whose abundance increased visibly in membranes from salt-grown beetroots were identified by mass spectrometry. Among them, there was a V-type H(+)-ATPase (probably from contaminating vacuolar membranes), which increased with salt at all stages of beetroots' development. Proteins involved in solute transport (an H(+)-transporting PPase and annexins), vesicle traffic (clathrin and synaptotagmins), signal perception and transduction (protein kinases and phospholipases, mostly involved in calcium signaling) and metabolism, appeared to increase in salt-grown beetroot PM-enriched membranes. These results suggest that PM and vacuolar proteins involved in transport, metabolism and signal transduction increase in beet roots adapted to saline soils. In addition, these results show that serial phase partitioning with Triton X-114 is a useful method to separate membrane proteins for their identification by mass spectrometry.

Distinct steps of neural induction revealed by Asterix, Obelix and TrkC, genes induced by different signals from the organizer.

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Sonia Pinho

2011-04-01

Full Text Available The amniote organizer (Hensen's node can induce a complete nervous system when grafted into a peripheral region of a host embryo. Although BMP inhibition has been implicated in neural induction, non-neural cells cannot respond to BMP antagonists unless previously exposed to a node graft for at least 5 hours before BMP inhibitors. To define signals and responses during the first 5 hours of node signals, a differential screen was conducted. Here we describe three early response genes: two of them, Asterix and Obelix, encode previously undescribed proteins of unknown function but Obelix appears to be a nuclear RNA-binding protein. The third is TrkC, a neurotrophin receptor. All three genes are induced by a node graft within 4-5 hours but they differ in the extent to which they are inducible by FGF: FGF is both necessary and sufficient to induce Asterix, sufficient but not necessary to induce Obelix and neither sufficient nor necessary for induction of TrkC. These genes are also not induced by retinoic acid, Noggin, Chordin, Dkk1, Cerberus, HGF/SF, Somatostatin or ionomycin-mediated Calcium entry. Comparison of the expression and regulation of these genes with other early neural markers reveals three distinct "epochs", or temporal waves, of gene expression accompanying neural induction by a grafted organizer, which are mirrored by specific stages of normal neural plate development. The results are consistent with neural induction being a cascade of responses elicited by different signals, culminating in the formation of a patterned nervous system.

Membrane fluidization by alcohols inhibits DesK-DesR signalling in Bacillus subtilis.

Science.gov (United States)

Vaňousová, Kateřina; Beranová, Jana; Fišer, Radovan; Jemioła-Rzemińska, Malgorzata; Matyska Lišková, Petra; Cybulski, Larisa; Strzałka, Kazimierz; Konopásek, Ivo

2018-03-01

After cold shock, the Bacillus subtilis desaturase Des introduces double bonds into the fatty acids of existing membrane phospholipids. The synthesis of Des is regulated exclusively by the two-component system DesK/DesR; DesK serves as a sensor of the state of the membrane and triggers Des synthesis after a decrease in membrane fluidity. The aim of our work is to investigate the biophysical changes in the membrane that are able to affect the DesK signalling state. Using linear alcohols (ethanol, propanol, butanol, hexanol, octanol) and benzyl alcohol, we were able to suppress Des synthesis after a temperature downshift. The changes in the biophysical properties of the membrane caused by alcohol addition were followed using membrane fluorescent probes and differential scanning calorimetry. We found that the membrane fluidization induced by alcohols was reflected in an increased hydration at the lipid-water interface. This is associated with a decrease in DesK activity. The addition of alcohol mimics a temperature increase, which can be measured isothermically by fluorescence anisotropy. The effect of alcohols on the membrane periphery is in line with the concept of the mechanism by which two hydrophilic motifs located at opposite ends of the transmembrane region of DesK, which work as a molecular caliper, sense temperature-dependent variations in membrane properties. Copyright © 2017 Elsevier B.V. All rights reserved.

Patterns of cortical oscillations organize neural activity into whole-brain functional networks evident in the fMRI BOLD signal

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Jennifer C Whitman

2013-03-01

Full Text Available Recent findings from electrophysiology and multimodal neuroimaging have elucidated the relationship between patterns of cortical oscillations evident in EEG / MEG and the functional brain networks evident in the BOLD signal. Much of the existing literature emphasized how high-frequency cortical oscillations are thought to coordinate neural activity locally, while low-frequency oscillations play a role in coordinating activity between more distant brain regions. However, the assignment of different frequencies to different spatial scales is an oversimplification. A more informative approach is to explore the arrangements by which these low- and high-frequency oscillations work in concert, coordinating neural activity into whole-brain functional networks. When relating such networks to the BOLD signal, we must consider how the patterns of cortical oscillations change at the same speed as cognitive states, which often last less than a second. Consequently, the slower BOLD signal may often reflect the summed neural activity of several transient network configurations. This temporal mismatch can be circumvented if we use spatial maps to assess correspondence between oscillatory networks and BOLD networks.

Calcineurin signaling and membrane lipid homeostasis regulates iron mediated multidrug resistance mechanisms in Candida albicans.

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Saif Hameed

2011-04-01

Full Text Available We previously demonstrated that iron deprivation enhances drug susceptibility of Candida albicans by increasing membrane fluidity which correlated with the lower expression of ERG11 transcript and ergosterol levels. The iron restriction dependent membrane perturbations led to an increase in passive diffusion and drug susceptibility. The mechanisms underlying iron homeostasis and multidrug resistance (MDR, however, are not yet resolved. To evaluate the potential mechanisms, we used whole genome transcriptome and electrospray ionization tandem mass spectrometry (ESI-MS/MS based lipidome analyses of iron deprived Candida cells to examine the new cellular circuitry of the MDR of this pathogen. Our transcriptome data revealed a link between calcineurin signaling and iron homeostasis. Among the several categories of iron deprivation responsive genes, the down regulation of calcineurin signaling genes including HSP90, CMP1 and CRZ1 was noteworthy. Interestingly, iron deprived Candida cells as well as iron acquisition defective mutants phenocopied molecular chaperone HSP90 and calcineurin mutants and thus were sensitive to alkaline pH, salinity and membrane perturbations. In contrast, sensitivity to above stresses did not change in iron deprived DSY2146 strain with a hyperactive allele of calcineurin. Although, iron deprivation phenocopied compromised HSP90 and calcineurin, it was independent of protein kinase C signaling cascade. Notably, the phenotypes associated with iron deprivation in genetically impaired calcineurin and HSP90 could be reversed with iron supplementation. The observed down regulation of ergosterol (ERG1, ERG2, ERG11 and ERG25 and sphingolipid biosynthesis (AUR1 and SCS7 genes followed by lipidome analysis confirmed that iron deprivation not only disrupted ergosterol biosynthesis, but it also affected sphingolipid homeostasis in Candida cells. These lipid compositional changes suggested extensive remodeling of the membranes in iron

Serotonin 2A Receptor Signaling Underlies LSD-induced Alteration of the Neural Response to Dynamic Changes in Music.

Science.gov (United States)

Barrett, Frederick S; Preller, Katrin H; Herdener, Marcus; Janata, Petr; Vollenweider, Franz X

2017-09-28

Classic psychedelic drugs (serotonin 2A, or 5HT2A, receptor agonists) have notable effects on music listening. In the current report, blood oxygen level-dependent (BOLD) signal was collected during music listening in 25 healthy adults after administration of placebo, lysergic acid diethylamide (LSD), and LSD pretreated with the 5HT2A antagonist ketanserin, to investigate the role of 5HT2A receptor signaling in the neural response to the time-varying tonal structure of music. Tonality-tracking analysis of BOLD data revealed that 5HT2A receptor signaling alters the neural response to music in brain regions supporting basic and higher-level musical and auditory processing, and areas involved in memory, emotion, and self-referential processing. This suggests a critical role of 5HT2A receptor signaling in supporting the neural tracking of dynamic tonal structure in music, as well as in supporting the associated increases in emotionality, connectedness, and meaningfulness in response to music that are commonly observed after the administration of LSD and other psychedelics. Together, these findings inform the neuropsychopharmacology of music perception and cognition, meaningful music listening experiences, and altered perception of music during psychedelic experiences. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Investigations of Escherichia coli promoter sequences with artificial neural networks: new signals discovered upstream of the transcriptional startpoint

DEFF Research Database (Denmark)

Pedersen, Anders Gorm; Engelbrecht, Jacob

1995-01-01

We present a novel method for using the learning ability of a neural network as a measure of information in local regions of input data. Using the method to analyze Escherichia coli promoters, we discover all previously described signals, and furthermore find new signals that are regularly spaced...

Oxidative stress damage-associated molecular signaling pathways differentiate spontaneous preterm birth and preterm premature rupture of the membranes.

Science.gov (United States)

Dutta, Eryn H; Behnia, Faranak; Boldogh, Istvan; Saade, George R; Taylor, Brandie D; Kacerovský, Marian; Menon, Ramkumar

2016-02-01

In women with preterm premature rupture of the membranes (PPROM), increased oxidative stress may accelerate premature cellular senescence, senescence-associated inflammation and proteolysis, which may predispose them to rupture. We demonstrate mechanistic differences between preterm birth (PTB) and PPROM by revealing differences in fetal membrane redox status, oxidative stress-induced damage, distinct signaling pathways and senescence activation. Oxidative stress-associated fetal membrane damage and cell cycle arrest determine adverse pregnancy outcomes, such as spontaneous PTB and PPROM. Fetal membranes and amniotic fluid samples were collected from women with PTB and PPROM. Molecular, biochemical and histologic markers were used to document differences in oxidative stress and antioxidant enzyme status, DNA damage, secondary signaling activation by Ras-GTPase and mitogen-activated protein kinases, and activation of senescence between membranes from the two groups. Oxidative stress was higher and antioxidant enzymes were lower in PPROM compared with PTB. PTB membranes had minimal DNA damage and showed activation of Ras-GTPase and ERK/JNK signaling pathway with minimal signs of senescence. PPROM had higher numbers of cells with DNA damage, prosenescence stress kinase (p38 MAPK) activation and signs of senescence. Samples were obtained retrospectively after delivery. The markers of senescence that we tested are specific but are not sufficient to confirm senescence as the pathology in PPROM. Oxidative stress-induced DNA damage and senescence are characteristics of fetal membranes from PPROM, compared with PTB with intact membranes. PTB and PPROM arise from distinct pathophysiologic pathways. Oxidative stress and oxidative stress-induced cellular damages are likely determinants of the mechanistic signaling pathways and phenotypic outcome. This study is supported by developmental funds to Dr R. Menon from the Department of Obstetrics and Gynecology at The University of

Fenspiride and membrane transduction signals in rat alveolar macrophages.

Science.gov (United States)

Féray, J C; Mohammadi, K; Taouil, K; Brunet, J; Garay, R P; Hannaert, P

1997-07-15

Fenspiride inhibits the calcium signal evoked by the inflammatory peptide formyl-Met-Leu-Phe (fMLP) in peritoneal macrophages, but at concentrations (approximately 1 mM) far above the therapeutic range (approximately 1 microM). Here, in rat alveolar macrophages, high fenspiride concentrations (1 mM) were required to inhibit the calcium signals evoked by the calcium agonist Bay K8644 or by ionomycin. Moreover, fenspiride (1 mM) was a poor inhibitor of the cell membrane depolarization induced by gramicidine D. By contrast, fenspiride blocked Na+-H+ antiport activation by (i) fMLP with an IC50 = 3.1 +/- 1.9 nM and (ii) PMA (phorbol 12-myristate 13-acetate) with an IC50 = 9.2 +/- 3.1 nM. Finally, protein kinase C (PKC) activity of macrophage homogenate was not significantly modified by 10 or 100 microM fenspiride (at 100 microM: 2.57 +/- 1.60 vs. 2.80 +/- 1.71 pmol/10(6) cells/min). In conclusion, fenspiride inhibits fMLP- and PMA-induced pH signals in rat alveolar macrophages, probably by acting distally on the PKC transduction signal. This pH antagonistic action may be relevant for the antiinflammatory mechanism of fenspiride and requires further investigation.

Development of a signal-analysis algorithm for the ZEUS transition-radiation detector under application of a neural network

International Nuclear Information System (INIS)

Wollschlaeger, U.

1992-07-01

The aim of this thesis consisted in the development of a procedure for the analysis of the data of the transition-radiation detector at ZEUS. For this a neural network was applied and first studied, which results concerning the separation power between electron an pions can be reached by this procedure. It was shown that neural nets yield within the error limits as well results as standard algorithms (total charge, cluster analysis). At an electron efficiency of 90% pion contaminations in the range 1%-2% were reached. Furthermore it could be confirmed that neural networks can be considered for the here present application field as robust in relatively insensitive against external perturbations. For the application in the experiment beside the separation power also the time-behaviour is of importance. The requirement to keep dead-times small didn't allow the application of standard method. By a simulation the time availabel for the signal analysis was estimated. For the testing of the processing time in a neural network subsequently the corresponding algorithm was implemented into an assembler code for the digital signal processor DSP56001. (orig./HSI) [de

Deep Learning Neural Networks and Bayesian Neural Networks in Data Analysis

Directory of Open Access Journals (Sweden)

Chernoded Andrey

2017-01-01

Full Text Available Most of the modern analyses in high energy physics use signal-versus-background classification techniques of machine learning methods and neural networks in particular. Deep learning neural network is the most promising modern technique to separate signal and background and now days can be widely and successfully implemented as a part of physical analysis. In this article we compare Deep learning and Bayesian neural networks application as a classifiers in an instance of top quark analysis.

Effect of spatial inhomogeneities on the membrane surface on receptor dimerization and signal initiation

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Romica Kerketta

2016-08-01

Full Text Available Important signal transduction pathways originate on the plasma membrane, where microdomains may transiently entrap diffusing receptors. This results in a non-random distribution of receptors even in the resting state, which can be visualized as clusters by high resolution imaging methods. Here, we explore how spatial in-homogeneities in the plasma membrane might influence the dimerization and phosphorylation status of ErbB2 and ErbB3, two receptor tyrosine kinases that preferentially heterodimerize and are often co-expressed in cancer. This theoretical study is based upon spatial stochastic simulations of the two-dimensional membrane landscape, where variables include differential distributions and overlap of transient confinement zones (domains for the two receptor species. The in silico model is parameterized and validated using data from single particle tracking experiments. We report key differences in signaling output based on the degree of overlap between domains and the relative retention of receptors in such domains, expressed as escape probability. Results predict that a high overlap of domains, which favors transient co-confinement of both receptor species, will enhance the rate of hetero-interactions. Where domains do not overlap, simulations confirm expectations that homo-interactions are favored. Since ErbB3 is uniquely dependent on ErbB2 interactions for activation of its catalytic activity, variations in domain overlap or escape probability markedly alter the predicted patterns and time course of ErbB3 and ErbB2 phosphorylation. Taken together, these results implicate membrane domain organization as an important modulator of signal initiation, motivating the design of novel experimental approaches to measure these important parameters across a wider range of receptor systems.

A membrane protein / signaling protein interaction network for Arabidopsis version AMPv2

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Sylvie Lalonde

2010-09-01

Full Text Available Interactions between membrane proteins and the soluble fraction are essential for signal transduction and for regulating nutrient transport. To gain insights into the membrane-based interactome, 3,852 open reading frames (ORFs out of a target list of 8,383 representing membrane and signaling proteins from Arabidopsis thaliana were cloned into a Gateway compatible vector. The mating-based split-ubiquitin system was used to screen for potential protein-protein interactions (pPPIs among 490 Arabidopsis ORFs. A binary robotic screen between 142 receptor-like kinases, 72 transporters, 57 soluble protein kinases and phosphatases, 40 glycosyltransferases, 95 proteins of various functions and 89 proteins with unknown function detected 387 out of 90,370 possible PPIs. A secondary screen confirmed 343 (of 387 pPPIs between 179 proteins, yielding a scale-free network (r2=0.863. Eighty of 142 transmembrane receptor-like kinases (RLK tested positive, identifying three homomers, 63 heteromers and 80 pPPIs with other proteins. Thirty-one out of 142 RLK interactors (including RLKs had previously been found to be phosphorylated; thus interactors may be substrates for respective RLKs. None of the pPPIs described here had been reported in the major interactome databases, including potential interactors of G protein-coupled receptors, phospholipase C, and AMT ammonium transporters. Two RLKs found as putative interactors of AMT1;1 were independently confirmed using a split luciferase assay in Arabidopsis protoplasts. These RLKs may be involved in ammonium-dependent phosphorylation of the C-terminus and regulation of ammonium uptake activity. The robotic screening method established here will enable a systematic analysis of membrane protein interactions in fungi, plants and metazoa.

Real-time classification of signals from three-component seismic sensors using neural nets

Science.gov (United States)

Bowman, B. C.; Dowla, F.

1992-05-01

Adaptive seismic data acquisition systems with capabilities of signal discrimination and event classification are important in treaty monitoring, proliferation, and earthquake early detection systems. Potential applications include monitoring underground chemical explosions, as well as other military, cultural, and natural activities where characteristics of signals change rapidly and without warning. In these applications, the ability to detect and interpret events rapidly without falling behind the influx of the data is critical. We developed a system for real-time data acquisition, analysis, learning, and classification of recorded events employing some of the latest technology in computer hardware, software, and artificial neural networks methods. The system is able to train dynamically, and updates its knowledge based on new data. The software is modular and hardware-independent; i.e., the front-end instrumentation is transparent to the analysis system. The software is designed to take advantage of the multiprocessing environment of the Unix operating system. The Unix System V shared memory and static RAM protocols for data access and the semaphore mechanism for interprocess communications were used. As the three-component sensor detects a seismic signal, it is displayed graphically on a color monitor using X11/Xlib graphics with interactive screening capabilities. For interesting events, the triaxial signal polarization is computed, a fast Fourier Transform (FFT) algorithm is applied, and the normalized power spectrum is transmitted to a backpropagation neural network for event classification. The system is currently capable of handling three data channels with a sampling rate of 500 Hz, which covers the bandwidth of most seismic events. The system has been tested in laboratory setting with artificial events generated in the vicinity of a three-component sensor.

Regulation of adult neural progenitor cell functions by purinergic signaling.

Science.gov (United States)

Tang, Yong; Illes, Peter

2017-02-01

Extracellular purines are signaling molecules in the neurogenic niches of the brain and spinal cord, where they activate cell surface purinoceptors at embryonic neural stem cells (NSCs) and adult neural progenitor cells (NPCs). Although mRNA and protein are expressed at NSCs/NPCs for almost all subtypes of the nucleotide-sensitive P2X/P2Y, and the nucleoside-sensitive adenosine receptors, only a few of those have acquired functional significance. ATP is sequentially degraded by ecto-nucleotidases to ADP, AMP, and adenosine with agonistic properties for distinct receptor-classes. Nucleotides/nucleosides facilitate or inhibit NSC/NPC proliferation, migration and differentiation. The most ubiquitous effect of all agonists (especially of ATP and ADP) appears to be the facilitation of cell proliferation, usually through P2Y1Rs and sometimes through P2X7Rs. However, usually P2X7R activation causes necrosis/apoptosis of NPCs. Differentiation can be initiated by P2Y2R-activation or P2X7R-blockade. A key element in the transduction mechanism of either receptor is the increase of the intracellular free Ca 2+ concentration, which may arise due to its release from intracellular storage sites (G protein-coupling; P2Y) or due to its passage through the receptor-channel itself from the extracellular space (ATP-gated ion channel; P2X). Further research is needed to clarify how purinergic signaling controls NSC/NPC fate and how the balance between the quiescent and activated states is established with fine and dynamic regulation. GLIA 2017;65:213-230. © 2016 Wiley Periodicals, Inc.

Acquiring neural signals for developing a perception and cognition model

Science.gov (United States)

Li, Wei; Li, Yunyi; Chen, Genshe; Shen, Dan; Blasch, Erik; Pham, Khanh; Lynch, Robert

2012-06-01

The understanding of how humans process information, determine salience, and combine seemingly unrelated information is essential to automated processing of large amounts of information that is partially relevant, or of unknown relevance. Recent neurological science research in human perception, and in information science regarding contextbased modeling, provides us with a theoretical basis for using a bottom-up approach for automating the management of large amounts of information in ways directly useful for human operators. However, integration of human intelligence into a game theoretic framework for dynamic and adaptive decision support needs a perception and cognition model. For the purpose of cognitive modeling, we present a brain-computer-interface (BCI) based humanoid robot system to acquire brainwaves during human mental activities of imagining a humanoid robot-walking behavior. We use the neural signals to investigate relationships between complex humanoid robot behaviors and human mental activities for developing the perception and cognition model. The BCI system consists of a data acquisition unit with an electroencephalograph (EEG), a humanoid robot, and a charge couple CCD camera. An EEG electrode cup acquires brainwaves from the skin surface on scalp. The humanoid robot has 20 degrees of freedom (DOFs); 12 DOFs located on hips, knees, and ankles for humanoid robot walking, 6 DOFs on shoulders and arms for arms motion, and 2 DOFs for head yaw and pitch motion. The CCD camera takes video clips of the human subject's hand postures to identify mental activities that are correlated to the robot-walking behaviors. We use the neural signals to investigate relationships between complex humanoid robot behaviors and human mental activities for developing the perception and cognition model.

Predominant membrane localization is an essential feature of the bacterial signal recognition particle receptor

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Graumann Peter

2009-11-01

Full Text Available Abstract Background The signal recognition particle (SRP receptor plays a vital role in co-translational protein targeting, because it connects the soluble SRP-ribosome-nascent chain complex (SRP-RNCs to the membrane bound Sec translocon. The eukaryotic SRP receptor (SR is a heterodimeric protein complex, consisting of two unrelated GTPases. The SRβ subunit is an integral membrane protein, which tethers the SRP-interacting SRα subunit permanently to the endoplasmic reticulum membrane. The prokaryotic SR lacks the SRβ subunit and consists of only the SRα homologue FtsY. Strikingly, although FtsY requires membrane contact for functionality, cell fractionation studies have localized FtsY predominantly to the cytosolic fraction of Escherichia coli. So far, the exact function of the soluble SR in E. coli is unknown, but it has been suggested that, in contrast to eukaryotes, the prokaryotic SR might bind SRP-RNCs already in the cytosol and only then initiates membrane targeting. Results In the current study we have determined the contribution of soluble FtsY to co-translational targeting in vitro and have re-analysed the localization of FtsY in vivo by fluorescence microscopy. Our data show that FtsY can bind to SRP-ribosome nascent chains (RNCs in the absence of membranes. However, these soluble FtsY-SRP-RNC complexes are not efficiently targeted to the membrane. In contrast, we observed effective targeting of SRP-RNCs to membrane-bond FtsY. These data show that soluble FtsY does not contribute significantly to cotranslational targeting in E. coli. In agreement with this observation, our in vivo analyses of FtsY localization in bacterial cells by fluorescence microscopy revealed that the vast majority of FtsY was localized to the inner membrane and that soluble FtsY constituted only a negligible species in vivo. Conclusion The exact function of the SRP receptor (SR in bacteria has so far been enigmatic. Our data show that the bacterial SR is

Forcast of TEXT plasma disruptions using soft X-rays as input signal in a neural network

International Nuclear Information System (INIS)

Vannucci, A.; Oliveira, K.A.; Tajima, T.

1998-02-01

A feed-forward neural network with two hidden layers is used in this work to forecast major and minor disruptive instabilities in TEXT discharges. Using soft X-ray signals as input data, the neural net is trained with one disruptive plasma pulse, and a different disruptive discharge is used for validation. After being properly trained the networks, with the same set of weights. is then used to forecast disruptions in two others different plasma pulses. It is observed that the neural net is able to predict the incoming of a disruption more than 3 ms in advance. This time interval is almost three times longer than the one already obtained previously when magnetic signal from a Mirnov coil was used to feed the neural networks with. To our own eye we fail to see any indication of an upcoming disruption from the experimental data this far back from the time of disruption. Finally, from what we observe in the predictive behavior of our network, speculations are made whether the disruption triggering mechanism would be associated to an increase of the m = 2 magnetic island, that disturbs the central part of the plasma column afterwards or, in face of the results from this work, the initial perturbation would have occurred first in the central part of the plasma column, within the q = 1 magnetic surface, and then the m = 2 MHD mode would be destabilized afterwards

Induced mitochondrial membrane potential for modeling solitonic conduction of electrotonic signals.

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R R Poznanski

Full Text Available A cable model that includes polarization-induced capacitive current is derived for modeling the solitonic conduction of electrotonic potentials in neuronal branchlets with microstructure containing endoplasmic membranes. A solution of the nonlinear cable equation modified for fissured intracellular medium with a source term representing charge 'soakage' is used to show how intracellular capacitive effects of bound electrical charges within mitochondrial membranes can influence electrotonic signals expressed as solitary waves. The elastic collision resulting from a head-on collision of two solitary waves results in localized and non-dispersing electrical solitons created by the nonlinearity of the source term. It has been shown that solitons in neurons with mitochondrial membrane and quasi-electrostatic interactions of charges held by the microstructure (i.e., charge 'soakage' have a slower velocity of propagation compared with solitons in neurons with microstructure, but without endoplasmic membranes. When the equilibrium potential is a small deviation from rest, the nonohmic conductance acts as a leaky channel and the solitons are small compared when the equilibrium potential is large and the outer mitochondrial membrane acts as an amplifier, boosting the amplitude of the endogenously generated solitons. These findings demonstrate a functional role of quasi-electrostatic interactions of bound electrical charges held by microstructure for sustaining solitons with robust self-regulation in their amplitude through changes in the mitochondrial membrane equilibrium potential. The implication of our results indicate that a phenomenological description of ionic current can be successfully modeled with displacement current in Maxwell's equations as a conduction process involving quasi-electrostatic interactions without the inclusion of diffusive current. This is the first study in which solitonic conduction of electrotonic potentials are generated by

Introduction to Artificial Neural Networks

DEFF Research Database (Denmark)

Larsen, Jan

1999-01-01

The note addresses introduction to signal analysis and classification based on artificial feed-forward neural networks.......The note addresses introduction to signal analysis and classification based on artificial feed-forward neural networks....

SOX1 links the function of neural patterning and Notch signalling in the ventral spinal cord during the neuron-glial fate switch

Energy Technology Data Exchange (ETDEWEB)

Genethliou, Nicholas; Panayiotou, Elena [The Cyprus Institute of Neurology and Genetics, Airport Avenue, No. 6, Agios Dometios, 2370 Nicosia (Cyprus); Department of Biological Sciences, University of Cyprus, P.O. Box 20537, 1678 Nicosia (Cyprus); Panayi, Helen; Orford, Michael; Mean, Richard; Lapathitis, George; Gill, Herman; Raoof, Sahir [The Cyprus Institute of Neurology and Genetics, Airport Avenue, No. 6, Agios Dometios, 2370 Nicosia (Cyprus); Gasperi, Rita De; Elder, Gregory [James J. Peters VA Medical Center, Research and Development (3F22), 130 West Kingsbridge Road, Bronx, NY 10468 (United States); Kessaris, Nicoletta; Richardson, William D. [Wolfson Institute for Biomedical Research and Research Department of Cell and Developmental Biology, University College London, Gower Street, London WC1E 6BT (United Kingdom); Malas, Stavros, E-mail: smalas@cing.ac.cy [The Cyprus Institute of Neurology and Genetics, Airport Avenue, No. 6, Agios Dometios, 2370 Nicosia (Cyprus); Department of Biological Sciences, University of Cyprus, P.O. Box 20537, 1678 Nicosia (Cyprus)

2009-12-25

During neural development the transition from neurogenesis to gliogenesis, known as the neuron-glial ({Nu}/G) fate switch, requires the coordinated function of patterning factors, pro-glial factors and Notch signalling. How this process is coordinated in the embryonic spinal cord is poorly understood. Here, we demonstrate that during the N/G fate switch in the ventral spinal cord (vSC) SOX1 links the function of neural patterning and Notch signalling. We show that, SOX1 expression in the vSC is regulated by PAX6, NKX2.2 and Notch signalling in a domain-specific manner. We further show that SOX1 regulates the expression of Hes1 and that loss of Sox1 leads to enhanced production of oligodendrocyte precursors from the pMN. Finally, we show that Notch signalling functions upstream of SOX1 during this fate switch and is independently required for the acquisition of the glial fate perse by regulating Nuclear Factor I A expression in a PAX6/SOX1/HES1/HES5-independent manner. These data integrate functional roles of neural patterning factors, Notch signalling and SOX1 during gliogenesis.

Combinatory annotation of cell membrane receptors and signalling pathways of Bombyx mori prothoracic glands

Science.gov (United States)

Moulos, Panagiotis; Samiotaki, Martina; Panayotou, George; Dedos, Skarlatos G.

2016-01-01

The cells of prothoracic glands (PG) are the main site of synthesis and secretion of ecdysteroids, the biochemical products of cholesterol conversion to steroids that shape the morphogenic development of insects. Despite the availability of genome sequences from several insect species and the extensive knowledge of certain signalling pathways that underpin ecdysteroidogenesis, the spectrum of signalling molecules and ecdysteroidogenic cascades is still not fully comprehensive. To fill this gap and obtain the complete list of cell membrane receptors expressed in PG cells, we used combinatory bioinformatic, proteomic and transcriptomic analysis and quantitative PCR to annotate and determine the expression profiles of genes identified as putative cell membrane receptors of the model insect species, Bombyx mori, and subsequently enrich the repertoire of signalling pathways that are present in its PG cells. The genome annotation dataset we report here highlights modules and pathways that may be directly involved in ecdysteroidogenesis and aims to disseminate data and assist other researchers in the discovery of the role of such receptors and their ligands. PMID:27576083

Phenothiourea sensitizes zebrafish cranial neural crest and extraocular muscle development to changes in retinoic acid and IGF signaling.

Directory of Open Access Journals (Sweden)

Brenda L Bohnsack

Full Text Available 1-Phenyl 2-thiourea (PTU is a tyrosinase inhibitor commonly used to block pigmentation and aid visualization of zebrafish development. At the standard concentration of 0.003% (200 µM, PTU inhibits melanogenesis and reportedly has minimal other effects on zebrafish embryogenesis. We found that 0.003% PTU altered retinoic acid and insulin-like growth factor (IGF regulation of neural crest and mesodermal components of craniofacial development. Reduction of retinoic acid synthesis by the pan-aldehyde dehydrogenase inhibitor diethylbenzaldehyde, only when combined with 0.003% PTU, resulted in extraocular muscle disorganization. PTU also decreased retinoic acid-induced teratogenic effects on pharyngeal arch and jaw cartilage despite morphologically normal appearing PTU-treated controls. Furthermore, 0.003% PTU in combination with inhibition of IGF signaling through either morpholino knockdown or pharmacologic inhibition of tyrosine kinase receptor phosphorylation, disrupted jaw development and extraocular muscle organization. PTU in and of itself inhibited neural crest development at higher concentrations (0.03% and had the greatest inhibitory effect when added prior to 22 hours post fertilization (hpf. Addition of 0.003% PTU between 4 and 20 hpf decreased thyroxine (T4 in thyroid follicles in the nasopharynx of 96 hpf embryos. Treatment with exogenous triiodothyronine (T3 and T4 improved, but did not completely rescue, PTU-induced neural crest defects. Thus, PTU should be used with caution when studying zebrafish embryogenesis as it alters the threshold of different signaling pathways important during craniofacial development. The effects of PTU on neural crest development are partially caused by thyroid hormone signaling.

Modulation Classification of Satellite Communication Signals Using Cumulants and Neural Networks

Science.gov (United States)

Smith, Aaron; Evans, Michael; Downey, Joseph

2017-01-01

National Aeronautics and Space Administration (NASA)'s future communication architecture is evaluating cognitive technologies and increased system intelligence. These technologies are expected to reduce the operational complexity of the network, increase science data return, and reduce interference to self and others. In order to increase situational awareness, signal classification algorithms could be applied to identify users and distinguish sources of interference. A significant amount of previous work has been done in the area of automatic signal classification for military and commercial applications. As a preliminary step, we seek to develop a system with the ability to discern signals typically encountered in satellite communication. Proposed is an automatic modulation classifier which utilizes higher order statistics (cumulants) and an estimate of the signal-to-noise ratio. These features are extracted from baseband symbols and then processed by a neural network for classification. The modulation types considered are phase-shift keying (PSK), amplitude and phase-shift keying (APSK),and quadrature amplitude modulation (QAM). Physical layer properties specific to the Digital Video Broadcasting - Satellite- Second Generation (DVB-S2) standard, such as pilots and variable ring ratios, are also considered. This paper will provide simulation results of a candidate modulation classifier, and performance will be evaluated over a range of signal-to-noise ratios, frequency offsets, and nonlinear amplifier distortions.

Investigating the effect of traditional Persian music on ECG signals in young women using wavelet transform and neural networks.

Science.gov (United States)

Abedi, Behzad; Abbasi, Ataollah; Goshvarpour, Atefeh

2017-05-01

In the past few decades, several studies have reported the physiological effects of listening to music. The physiological effects of different music types on different people are different. In the present study, we aimed to examine the effects of listening to traditional Persian music on electrocardiogram (ECG) signals in young women. Twenty-two healthy females participated in this study. ECG signals were recorded under two conditions: rest and music. For each ECG signal, 20 morphological and wavelet-based features were selected. Artificial neural network (ANN) and probabilistic neural network (PNN) classifiers were used for the classification of ECG signals during and before listening to music. Collected data were separated into two data sets: train and test. Classification accuracies of 88% and 97% were achieved in train data sets using ANN and PNN, respectively. In addition, the test data set was employed for evaluating the classifiers, and classification rates of 84% and 93% were obtained using ANN and PNN, respectively. The present study investigated the effect of music on ECG signals based on wavelet transform and morphological features. The results obtained here can provide a good understanding on the effects of music on ECG signals to researchers.

Mediator Med23 deficiency enhances neural differentiation of murine embryonic stem cells through modulating BMP signaling.

Science.gov (United States)

Zhu, Wanqu; Yao, Xiao; Liang, Yan; Liang, Dan; Song, Lu; Jing, Naihe; Li, Jinsong; Wang, Gang

2015-02-01

Unraveling the mechanisms underlying early neural differentiation of embryonic stem cells (ESCs) is crucial to developing cell-based therapies of neurodegenerative diseases. Neural fate acquisition is proposed to be controlled by a 'default' mechanism, for which the molecular regulation is not well understood. In this study, we investigated the functional roles of Mediator Med23 in pluripotency and lineage commitment of murine ESCs. Unexpectedly, we found that, despite the largely unchanged pluripotency and self-renewal of ESCs, Med23 depletion rendered the cells prone to neural differentiation in different differentiation assays. Knockdown of two other Mediator subunits, Med1 and Med15, did not alter the neural differentiation of ESCs. Med15 knockdown selectively inhibited endoderm differentiation, suggesting the specificity of cell fate control by distinctive Mediator subunits. Gene profiling revealed that Med23 depletion attenuated BMP signaling in ESCs. Mechanistically, MED23 modulated Bmp4 expression by controlling the activity of ETS1, which is involved in Bmp4 promoter-enhancer communication. Interestingly, med23 knockdown in zebrafish embryos also enhanced neural development at early embryogenesis, which could be reversed by co-injection of bmp4 mRNA. Taken together, our study reveals an intrinsic, restrictive role of MED23 in early neural development, thus providing new molecular insights for neural fate determination. © 2015. Published by The Company of Biologists Ltd.

Development of Filtered Bispectrum for EEG Signal Feature Extraction in Automatic Emotion Recognition Using Artificial Neural Networks

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Prima Dewi Purnamasari

2017-05-01

Full Text Available The development of automatic emotion detection systems has recently gained significant attention due to the growing possibility of their implementation in several applications, including affective computing and various fields within biomedical engineering. Use of the electroencephalograph (EEG signal is preferred over facial expression, as people cannot control the EEG signal generated by their brain; the EEG ensures a stronger reliability in the psychological signal. However, because of its uniqueness between individuals and its vulnerability to noise, use of EEG signals can be rather complicated. In this paper, we propose a methodology to conduct EEG-based emotion recognition by using a filtered bispectrum as the feature extraction subsystem and an artificial neural network (ANN as the classifier. The bispectrum is theoretically superior to the power spectrum because it can identify phase coupling between the nonlinear process components of the EEG signal. In the feature extraction process, to extract the information contained in the bispectrum matrices, a 3D pyramid filter is used for sampling and quantifying the bispectrum value. Experiment results show that the mean percentage of the bispectrum value from 5 × 5 non-overlapped 3D pyramid filters produces the highest recognition rate. We found that reducing the number of EEG channels down to only eight in the frontal area of the brain does not significantly affect the recognition rate, and the number of data samples used in the training process is then increased to improve the recognition rate of the system. We have also utilized a probabilistic neural network (PNN as another classifier and compared its recognition rate with that of the back-propagation neural network (BPNN, and the results show that the PNN produces a comparable recognition rate and lower computational costs. Our research shows that the extracted bispectrum values of an EEG signal using 3D filtering as a feature extraction

Using Pulse Width Modulation for Wireless Transmission of Neural Signals in Multichannel Neural Recording Systems

Science.gov (United States)

Yin, Ming; Ghovanloo, Maysam

2013-01-01

We have used a well-known technique in wireless communication, pulse width modulation (PWM) of time division multiplexed (TDM) signals, within the architecture of a novel wireless integrated neural recording (WINeR) system. We have evaluated the performance of the PWM-based architecture and indicated its accuracy and potential sources of error through detailed theoretical analysis, simulations, and measurements on a setup consisting of a 15-channel WINeR prototype as the transmitter and two types of receivers; an Agilent 89600 vector signal analyzer and a custom wideband receiver, with 36 and 75 MHz of maximum bandwidth, respectively. Furthermore, we present simulation results from a realistic MATLAB-Simulink model of the entire WINeR system to observe the system behavior in response to changes in various parameters. We have concluded that the 15-ch WINeR prototype, which is fabricated in a 0.5-μm standard CMOS process and consumes 4.5 mW from ±1.5 V supplies, can acquire and wirelessly transmit up to 320 k-samples/s to a 75-MHz receiver with 8.4 bits of resolution, which is equivalent to a wireless data rate of ~ 2.26 Mb/s. PMID:19497823

Single-molecule tracking of small GTPase Rac1 uncovers spatial regulation of membrane translocation and mechanism for polarized signaling

Science.gov (United States)

Das, Sulagna; Yin, Taofei; Yang, Qingfen; Zhang, Jingqiao; Wu, Yi I.; Yu, Ji

2015-01-01

Polarized Rac1 signaling is a hallmark of many cellular functions, including cell adhesion, motility, and cell division. The two steps of Rac1 activation are its translocation to the plasma membrane and the exchange of nucleotide from GDP to GTP. It is, however, unclear whether these two processes are regulated independent of each other and what their respective roles are in polarization of Rac1 signaling. We designed a single-particle tracking (SPT) method to quantitatively analyze the kinetics of Rac1 membrane translocation in living cells. We found that the rate of Rac1 translocation was significantly elevated in protrusions during cell spreading on collagen. Furthermore, combining FRET sensor imaging with SPT measurements in the same cell, the recruitment of Rac1 was found to be polarized to an extent similar to that of the nucleotide exchange process. Statistical analysis of single-molecule trajectories and optogenetic manipulation of membrane lipids revealed that Rac1 membrane translocation precedes nucleotide exchange, and is governed primarily by interactions with phospholipids, particularly PI(3,4,5)P3, instead of protein factors. Overall, the study highlights the significance of membrane translocation in spatial Rac1 signaling, which is in addition to the traditional view focusing primarily on GEF distribution and exchange reaction. PMID:25561548

A CMOS power-efficient low-noise current-mode front-end amplifier for neural signal recording.

Science.gov (United States)

Wu, Chung-Yu; Chen, Wei-Ming; Kuo, Liang-Ting

2013-04-01

In this paper, a new current-mode front-end amplifier (CMFEA) for neural signal recording systems is proposed. In the proposed CMFEA, a current-mode preamplifier with an active feedback loop operated at very low frequency is designed as the first gain stage to bypass any dc offset current generated by the electrode-tissue interface and to achieve a low high-pass cutoff frequency below 0.5 Hz. No reset signal or ultra-large pseudo resistor is required. The current-mode preamplifier has low dc operation current to enhance low-noise performance and decrease power consumption. A programmable current gain stage is adopted to provide adjustable gain for adaptive signal scaling. A following current-mode filter is designed to adjust the low-pass cutoff frequency for different neural signals. The proposed CMFEA is designed and fabricated in 0.18-μm CMOS technology and the area of the core circuit is 0.076 mm(2). The measured high-pass cutoff frequency is as low as 0.3 Hz and the low-pass cutoff frequency is adjustable from 1 kHz to 10 kHz. The measured maximum current gain is 55.9 dB. The measured input-referred current noise density is 153 fA /√Hz , and the power consumption is 13 μW at 1-V power supply. The fabricated CMFEA has been successfully applied to the animal test for recording the seizure ECoG of Long-Evan rats.

Acute inhibition of selected membrane-proximal mouse T cell receptor signaling by mitochondrial antagonists.

Directory of Open Access Journals (Sweden)

Kwangmi Kim

2009-11-01

Full Text Available T cells absorb nanometric membrane vesicles, prepared from plasma membrane of antigen presenting cells, via dual receptor/ligand interactions of T cell receptor (TCR with cognate peptide/major histocompatibility complex (MHC plus lymphocyte function-associated antigen 1 (LFA-1 with intercellular adhesion molecule 1. TCR-mediated signaling for LFA-1 activation is also required for the vesicle absorption. Exploiting those findings, we had established a high throughput screening (HTS platform and screened a library for isolation of small molecules inhibiting the vesicle absorption. Follow-up studies confirmed that treatments (1 hour with various mitochondrial antagonists, including a class of anti-diabetic drugs (i.e., Metformin and Phenformin, resulted in ubiquitous inhibition of the vesicle absorption without compromising viability of T cells. Further studies revealed that the mitochondrial drug treatments caused impairment of specific membrane-proximal TCR signaling event(s. Thus, activation of Akt and PLC-gamma1 and entry of extracellular Ca(2+ following TCR stimulation were attenuated while polymerization of monomeric actins upon TCR triggering progressed normally after the treatments. Dynamic F-actin rearrangement concurring with the vesicle absorption was also found to be impaired by the drug treatments, implying that the inhibition by the drug treatments of downstream signaling events (and the vesicle absorption could result from lack of directional relocation of signaling and cell surface molecules. We also assessed the potential application of mitochondrial antagonists as immune modulators by probing effects of the long-term drug treatments (24 hours on viability of resting primary T cells and cell cycle progression of antigen-stimulated T cells. This study unveils a novel regulatory mechanism for T cell immunity in response to environmental factors having effects on mitochondrial function.

Application of complex discrete wavelet transform in classification of Doppler signals using complex-valued artificial neural network.

Science.gov (United States)

Ceylan, Murat; Ceylan, Rahime; Ozbay, Yüksel; Kara, Sadik

2008-09-01

In biomedical signal classification, due to the huge amount of data, to compress the biomedical waveform data is vital. This paper presents two different structures formed using feature extraction algorithms to decrease size of feature set in training and test data. The proposed structures, named as wavelet transform-complex-valued artificial neural network (WT-CVANN) and complex wavelet transform-complex-valued artificial neural network (CWT-CVANN), use real and complex discrete wavelet transform for feature extraction. The aim of using wavelet transform is to compress data and to reduce training time of network without decreasing accuracy rate. In this study, the presented structures were applied to the problem of classification in carotid arterial Doppler ultrasound signals. Carotid arterial Doppler ultrasound signals were acquired from left carotid arteries of 38 patients and 40 healthy volunteers. The patient group included 22 males and 16 females with an established diagnosis of the early phase of atherosclerosis through coronary or aortofemoropopliteal (lower extremity) angiographies (mean age, 59 years; range, 48-72 years). Healthy volunteers were young non-smokers who seem to not bear any risk of atherosclerosis, including 28 males and 12 females (mean age, 23 years; range, 19-27 years). Sensitivity, specificity and average detection rate were calculated for comparison, after training and test phases of all structures finished. These parameters have demonstrated that training times of CVANN and real-valued artificial neural network (RVANN) were reduced using feature extraction algorithms without decreasing accuracy rate in accordance to our aim.

Transmission of wireless neural signals through a 0.18 µm CMOS low-power amplifier.

Science.gov (United States)

Gazziro, M; Braga, C F R; Moreira, D A; Carvalho, A C P L F; Rodrigues, J F; Navarro, J S; Ardila, J C M; Mioni, D P; Pessatti, M; Fabbro, P; Freewin, C; Saddow, S E

2015-01-01

In the field of Brain Machine Interfaces (BMI) researchers still are not able to produce clinically viable solutions that meet the requirements of long-term operation without the use of wires or batteries. Another problem is neural compatibility with the electrode probes. One of the possible ways of approaching these problems is the use of semiconductor biocompatible materials (silicon carbide) combined with an integrated circuit designed to operate with low power consumption. This paper describes a low-power neural signal amplifier chip, named Cortex, fabricated using 0.18 μm CMOS process technology with all electronics integrated in an area of 0.40 mm(2). The chip has 4 channels, total power consumption of only 144 μW, and is impedance matched to silicon carbide biocompatible electrodes.

Modulation of Hippocampal Neural Plasticity by Glucose-Related Signaling

Directory of Open Access Journals (Sweden)

Marco Mainardi

2015-01-01

Full Text Available Hormones and peptides involved in glucose homeostasis are emerging as important modulators of neural plasticity. In this regard, increasing evidence shows that molecules such as insulin, insulin-like growth factor-I, glucagon-like peptide-1, and ghrelin impact on the function of the hippocampus, which is a key area for learning and memory. Indeed, all these factors affect fundamental hippocampal properties including synaptic plasticity (i.e., synapse potentiation and depression, structural plasticity (i.e., dynamics of dendritic spines, and adult neurogenesis, thus leading to modifications in cognitive performance. Here, we review the main mechanisms underlying the effects of glucose metabolism on hippocampal physiology. In particular, we discuss the role of these signals in the modulation of cognitive functions and their potential implications in dysmetabolism-related cognitive decline.

Prediction of the rejection of organic compounds (neutral and ionic) by nanofiltration and reverse osmosis membranes using neural networks

Energy Technology Data Exchange (ETDEWEB)

Ammi, Yamina; Khaouane, Latifa; Hanini, Salah [University of Medea, Medea (Algeria)

2015-11-15

This work investigates the use of neural networks in modeling the rejection processes of organic compounds (neutral and ionic) by nanofiltration and reverse osmosis membranes. Three feed-forward neural network (NN) models, characterized by a similar structure (eleven neurons for NN1 and NN2 and twelve neurons for NN3 in the input layer, one hidden layer and one neuron in the output layer), are constructed with the aim of predicting the rejection of organic compounds (neutral and ionic). A set of 956 data points for NN1 and 701 data points for NN2 and NN3 were used to test the neural networks. 80%, 10%, and 10% of the total data were used, respectively, for the training, the validation, and the test of the three models. For the most promising neural network models, the predicted rejection values of the test dataset were compared to measured rejections values; good correlations were found (R= 0.9128 for NN1, R=0.9419 for NN2, and R=0.9527 for NN3). The root mean squared errors for the total dataset were 11.2430% for NN1, 9.0742% for NN2, and 8.2047% for NN3. Furthermore, the comparison between the predicted results and QSAR models shows that the neural network models gave far better.

Prediction of the rejection of organic compounds (neutral and ionic) by nanofiltration and reverse osmosis membranes using neural networks

International Nuclear Information System (INIS)

Ammi, Yamina; Khaouane, Latifa; Hanini, Salah

2015-01-01

This work investigates the use of neural networks in modeling the rejection processes of organic compounds (neutral and ionic) by nanofiltration and reverse osmosis membranes. Three feed-forward neural network (NN) models, characterized by a similar structure (eleven neurons for NN1 and NN2 and twelve neurons for NN3 in the input layer, one hidden layer and one neuron in the output layer), are constructed with the aim of predicting the rejection of organic compounds (neutral and ionic). A set of 956 data points for NN1 and 701 data points for NN2 and NN3 were used to test the neural networks. 80%, 10%, and 10% of the total data were used, respectively, for the training, the validation, and the test of the three models. For the most promising neural network models, the predicted rejection values of the test dataset were compared to measured rejections values; good correlations were found (R= 0.9128 for NN1, R=0.9419 for NN2, and R=0.9527 for NN3). The root mean squared errors for the total dataset were 11.2430% for NN1, 9.0742% for NN2, and 8.2047% for NN3. Furthermore, the comparison between the predicted results and QSAR models shows that the neural network models gave far better.

Beta1 integrins activate a MAPK signalling pathway in neural stem cells that contributes to their maintenance

DEFF Research Database (Denmark)

Campos, Lia S; Leone, Dino P; Relvas, Joao B

2004-01-01

, signalling is required for neural stem cell maintenance, as assessed by neurosphere formation, and inhibition or genetic ablation of beta1 integrin using cre/lox technology reduces the level of MAPK activity. We conclude that integrins are therefore an important part of the signalling mechanisms that control......The emerging evidence that stem cells develop in specialised niches highlights the potential role of environmental factors in their regulation. Here we examine the role of beta1 integrin/extracellular matrix interactions in neural stem cells. We find high levels of beta1 integrin expression...... in the stem-cell containing regions of the embryonic CNS, with associated expression of the laminin alpha2 chain. Expression levels of laminin alpha2 are reduced in the postnatal CNS, but a population of cells expressing high levels of beta1 remains. Using neurospheres - aggregate cultures, derived from...

A Fully Integrated Wireless Compressed Sensing Neural Signal Acquisition System for Chronic Recording and Brain Machine Interface.

Science.gov (United States)

Liu, Xilin; Zhang, Milin; Xiong, Tao; Richardson, Andrew G; Lucas, Timothy H; Chin, Peter S; Etienne-Cummings, Ralph; Tran, Trac D; Van der Spiegel, Jan

2016-07-18

Reliable, multi-channel neural recording is critical to the neuroscience research and clinical treatment. However, most hardware development of fully integrated, multi-channel wireless neural recorders to-date, is still in the proof-of-concept stage. To be ready for practical use, the trade-offs between performance, power consumption, device size, robustness, and compatibility need to be carefully taken into account. This paper presents an optimized wireless compressed sensing neural signal recording system. The system takes advantages of both custom integrated circuits and universal compatible wireless solutions. The proposed system includes an implantable wireless system-on-chip (SoC) and an external wireless relay. The SoC integrates 16-channel low-noise neural amplifiers, programmable filters and gain stages, a SAR ADC, a real-time compressed sensing module, and a near field wireless power and data transmission link. The external relay integrates a 32 bit low-power microcontroller with Bluetooth 4.0 wireless module, a programming interface, and an inductive charging unit. The SoC achieves high signal recording quality with minimized power consumption, while reducing the risk of infection from through-skin connectors. The external relay maximizes the compatibility and programmability. The proposed compressed sensing module is highly configurable, featuring a SNDR of 9.78 dB with a compression ratio of 8×. The SoC has been fabricated in a 180 nm standard CMOS technology, occupying 2.1 mm × 0.6 mm silicon area. A pre-implantable system has been assembled to demonstrate the proposed paradigm. The developed system has been successfully used for long-term wireless neural recording in freely behaving rhesus monkey.

Regulation of developmental and environmental signaling by interaction between microtubules and membranes in plant cells

Directory of Open Access Journals (Sweden)

Qun Zhang

2015-12-01

Full Text Available ABSTRACT Cell division and expansion require the ordered arrangement of microtubules, which are subject to spatial and temporal modifications by developmental and environmental factors. Understanding how signals translate to changes in cortical microtubule organization is of fundamental importance. A defining feature of the cortical microtubule array is its association with the plasma membrane; modules of the plasma membrane are thought to play important roles in the mediation of microtubule organization. In this review, we highlight advances in research on the regulation of cortical microtubule organization by membrane-associated and membrane-tethered proteins and lipids in response to phytohormones and stress. The transmembrane kinase receptor Rho-like guanosine triphosphatase, phospholipase D, phosphatidic acid, and phosphoinositides are discussed with a focus on their roles in microtubule organization.

Hydrolytic Degradation and Mechanical Stability of Poly(ε-Caprolactone)/Reduced Graphene Oxide Membranes as Scaffolds for In Vitro Neural Tissue Regeneration.

Science.gov (United States)

Sánchez-González, Sandra; Diban, Nazely; Urtiaga, Ane

2018-03-05

The present work studies the functional behavior of novel poly(ε-caprolactone) (PCL) membranes functionalized with reduced graphene oxide (rGO) nanoplatelets under simulated in vitro culture conditions (phosphate buffer solution (PBS) at 37 °C) during 1 year, in order to elucidate their applicability as scaffolds for in vitro neural regeneration. The morphological, chemical, and DSC results demonstrated that high internal porosity of the membranes facilitated water permeation and procured an accelerated hydrolytic degradation throughout the bulk pathway. Therefore, similar molecular weight reduction, from 80 kDa to 33 kDa for the control PCL, and to 27 kDa for PCL/rGO membranes, at the end of the study, was observed. After 1 year of hydrolytic degradation, though monomers coming from the hydrolytic cleavage of PCL diffused towards the PBS medium, the pH was barely affected, and the rGO nanoplatelets mainly remained in the membranes which envisaged low cytotoxic effect. On the other hand, the presence of rGO nanomaterials accelerated the loss of mechanical stability of the membranes. However, it is envisioned that the gradual degradation of the PCL/rGO membranes could facilitate cells infiltration, interconnectivity, and tissue formation.

Modeling and Optimization of NLDH/PVDF Ultrafiltration Nanocomposite Membrane Using Artificial Neural Network-Genetic Algorithm Hybrid.

Science.gov (United States)

Arefi-Oskoui, Samira; Khataee, Alireza; Vatanpour, Vahid

2017-07-10

In this research, MgAl-CO 3 2- nanolayered double hydroxide (NLDH) was synthesized through a facile coprecipitation method, followed by a hydrothermal treatment. The prepared NLDHs were used as a hydrophilic nanofiller for improving the performance of the PVDF-based ultrafiltration membranes. The main objective of this research was to obtain the optimized formula of NLDH/PVDF nanocomposite membrane presenting the best performance using computational techniques as a cost-effective method. For this aim, an artificial neural network (ANN) model was developed for modeling and expressing the relationship between the performance of the nanocomposite membrane (pure water flux, protein flux and flux recovery ratio) and the affecting parameters including the NLDH, PVP 29000 and polymer concentrations. The effects of the mentioned parameters and the interaction between the parameters were investigated using the contour plot predicted with the developed model. Scanning electron microscopy (SEM), atomic force microscopy (AFM), and water contact angle techniques were applied to characterize the nanocomposite membranes and to interpret the predictions of the ANN model. The developed ANN model was introduced to genetic algorithm (GA) as a bioinspired optimizer to determine the optimum values of input parameters leading to high pure water flux, protein flux, and flux recovery ratio. The optimum values for NLDH, PVP 29000 and the PVDF concentration were determined to be 0.54, 1, and 18 wt %, respectively. The performance of the nanocomposite membrane prepared using the optimum values proposed by GA was investigated experimentally, in which the results were in good agreement with the values predicted by ANN model with error lower than 6%. This good agreement confirmed that the nanocomposite membranes prformance could be successfully modeled and optimized by ANN-GA system.

Neural computation and the computational theory of cognition.

Science.gov (United States)

Piccinini, Gualtiero; Bahar, Sonya

2013-04-01

We begin by distinguishing computationalism from a number of other theses that are sometimes conflated with it. We also distinguish between several important kinds of computation: computation in a generic sense, digital computation, and analog computation. Then, we defend a weak version of computationalism-neural processes are computations in the generic sense. After that, we reject on empirical grounds the common assimilation of neural computation to either analog or digital computation, concluding that neural computation is sui generis. Analog computation requires continuous signals; digital computation requires strings of digits. But current neuroscientific evidence indicates that typical neural signals, such as spike trains, are graded like continuous signals but are constituted by discrete functional elements (spikes); thus, typical neural signals are neither continuous signals nor strings of digits. It follows that neural computation is sui generis. Finally, we highlight three important consequences of a proper understanding of neural computation for the theory of cognition. First, understanding neural computation requires a specially designed mathematical theory (or theories) rather than the mathematical theories of analog or digital computation. Second, several popular views about neural computation turn out to be incorrect. Third, computational theories of cognition that rely on non-neural notions of computation ought to be replaced or reinterpreted in terms of neural computation. Copyright © 2012 Cognitive Science Society, Inc.

Neural signal for counteracting pre-action bias in the centromedian thalamic nucleus

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Takafumi eMinamimoto

2014-01-01

Full Text Available Most of our daily actions are selected and executed involuntarily under familiar situations by the guidance of internal drives, such as motivation. The behavioral tendency or biasing towards one over others reflects the action-selection process in advance of action execution (i.e., pre-action bias. Facing unexpected situations, however, pre-action bias should be withdrawn and replaced by an alternative that is suitable for the situation (i.e., counteracting bias. To understand the neural mechanism for the counteracting process, we studied the neural activity of the thalamic centromedian (CM nucleus in monkeys performing GO-NOGO task with asymmetrical or symmetrical reward conditions. The monkeys reacted to GO signal faster in large-reward condition, indicating behavioral bias toward large reward. In contrast, they responded slowly in small-reward condition, suggesting a conflict between internal drive and external demand. We found that neurons in the CM nucleus exhibited phasic burst discharges after GO and NOGO instructions especially when they were associated with small reward. The small-reward preference was positively correlated with the strength of behavioral bias toward large reward. The small-reward preference disappeared when only NOGO action was requested. The timing of activation predicted the timing of action opposed to bias. These results suggest that CM signals the discrepancy between internal pre-action bias and external demand, and mediates the counteracting process — resetting behavioral bias and leading to execution of opposing action.

The Neural Border: Induction, Specification and Maturation of the territory that generates Neural Crest cells.

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Pla, Patrick; Monsoro-Burq, Anne H

2018-05-28

The neural crest is induced at the edge between the neural plate and the nonneural ectoderm, in an area called the neural (plate) border, during gastrulation and neurulation. In recent years, many studies have explored how this domain is patterned, and how the neural crest is induced within this territory, that also participates to the prospective dorsal neural tube, the dorsalmost nonneural ectoderm, as well as placode derivatives in the anterior area. This review highlights the tissue interactions, the cell-cell signaling and the molecular mechanisms involved in this dynamic spatiotemporal patterning, resulting in the induction of the premigratory neural crest. Collectively, these studies allow building a complex neural border and early neural crest gene regulatory network, mostly composed by transcriptional regulations but also, more recently, including novel signaling interactions. Copyright © 2018. Published by Elsevier Inc.

Intelligent Noise Removal from EMG Signal Using Focused Time-Lagged Recurrent Neural Network

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S. N. Kale

2009-01-01

Full Text Available Electromyography (EMG signals can be used for clinical/biomedical application and modern human computer interaction. EMG signals acquire noise while traveling through tissue, inherent noise in electronics equipment, ambient noise, and so forth. ANN approach is studied for reduction of noise in EMG signal. In this paper, it is shown that Focused Time-Lagged Recurrent Neural Network (FTLRNN can elegantly solve to reduce the noise from EMG signal. After rigorous computer simulations, authors developed an optimal FTLRNN model, which removes the noise from the EMG signal. Results show that the proposed optimal FTLRNN model has an MSE (Mean Square Error as low as 0.000067 and 0.000048, correlation coefficient as high as 0.99950 and 0.99939 for noise signal and EMG signal, respectively, when validated on the test dataset. It is also noticed that the output of the estimated FTLRNN model closely follows the real one. This network is indeed robust as EMG signal tolerates the noise variance from 0.1 to 0.4 for uniform noise and 0.30 for Gaussian noise. It is clear that the training of the network is independent of specific partitioning of dataset. It is seen that the performance of the proposed FTLRNN model clearly outperforms the best Multilayer perceptron (MLP and Radial Basis Function NN (RBF models. The simple NN model such as the FTLRNN with single-hidden layer can be employed to remove noise from EMG signal.

Neural cell adhesion molecule (NCAM) marks adult myogenic cells committed to differentiation

International Nuclear Information System (INIS)

Capkovic, Katie L.; Stevenson, Severin; Johnson, Marc C.; Thelen, Jay J.; Cornelison, D.D.W.

2008-01-01

Although recent advances in broad-scale gene expression analysis have dramatically increased our knowledge of the repertoire of mRNAs present in multiple cell types, it has become increasingly clear that examination of the expression, localization, and associations of the encoded proteins will be critical for determining their functional significance. In particular, many signaling receptors, transducers, and effectors have been proposed to act in higher-order complexes associated with physically distinct areas of the plasma membrane. Adult muscle stem cells (satellite cells) must, upon injury, respond appropriately to a wide range of extracellular stimuli: the role of such signaling scaffolds is therefore a potentially important area of inquiry. To address this question, we first isolated detergent-resistant membrane fractions from primary satellite cells, then analyzed their component proteins using liquid chromatography-tandem mass spectrometry. Transmembrane and juxtamembrane components of adhesion-mediated signaling pathways made up the largest group of identified proteins; in particular, neural cell adhesion molecule (NCAM), a multifunctional cell-surface protein that has previously been associated with muscle regeneration, was significant. Immunohistochemical analysis revealed that not only is NCAM localized to discrete areas of the plasma membrane, it is also a very early marker of commitment to terminal differentiation. Using flow cytometry, we have sorted physically homogeneous myogenic cultures into proliferating and differentiating fractions based solely upon NCAM expression

Neuroendocrine signaling modulates specific neural networks relevant to migraine.

Science.gov (United States)

Martins-Oliveira, Margarida; Akerman, Simon; Holland, Philip R; Hoffmann, Jan R; Tavares, Isaura; Goadsby, Peter J

2017-05-01

Migraine is a disabling brain disorder involving abnormal trigeminovascular activation and sensitization. Fasting or skipping meals is considered a migraine trigger and altered fasting glucose and insulin levels have been observed in migraineurs. Therefore peptides involved in appetite and glucose regulation including insulin, glucagon and leptin could potentially influence migraine neurobiology. We aimed to determine the effect of insulin (10U·kg -1 ), glucagon (100μg·200μl -1 ) and leptin (0.3, 1 and 3mg·kg -1 ) signaling on trigeminovascular nociceptive processing at the level of the trigeminocervical-complex and hypothalamus. Male rats were anesthetized and prepared for craniovascular stimulation. In vivo electrophysiology was used to determine changes in trigeminocervical neuronal responses to dural electrical stimulation, and phosphorylated extracellular signal-regulated kinases 1 and 2 (pERK1/2) immunohistochemistry to determine trigeminocervical and hypothalamic neural activity; both in response to intravenous administration of insulin, glucagon, leptin or vehicle control in combination with blood glucose analysis. Blood glucose levels were significantly decreased by insulin (pneuronal firing in the trigeminocervical-complex was significantly inhibited by insulin (pmetabolic homeostasis may occur through disturbed glucose regulation and a transient hypothalamic dysfunction. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

Andrographolide Promotes Neural Differentiation of Rat Adipose Tissue-Derived Stromal Cells through Wnt/β-Catenin Signaling Pathway

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Yan Liang

2017-01-01

Full Text Available Adipose tissue-derived stromal cells (ADSCs are a high-yield source of pluripotent stem cells for use in cell-based therapies. We explored the effect of andrographolide (ANDRO, one of the ingredients of the medicinal herb extract on the neural differentiation of rat ADSCs and associated molecular mechanisms. We observed that rat ADSCs were small and spindle-shaped and expressed multiple stem cell markers including nestin. They were multipotent as evidenced by adipogenic, osteogenic, chondrogenic, and neural differentiation under appropriate conditions. The proportion of cells exhibiting neural-like morphology was higher, and neurites developed faster in the ANDRO group than in the control group in the same neural differentiation medium. Expression levels of the neural lineage markers MAP2, tau, GFAP, and β-tubulin III were higher in the ANDRO group. ANDRO induced a concentration-dependent increase in Wnt/β-catenin signaling as evidenced by the enhanced expression of nuclear β-catenin and the inhibited form of GSK-3β (pSer9. Thus, this study shows for the first time how by enhancing the neural differentiation of ADSCs we expect that ANDRO pretreatment may increase the efficacy of adult stem cell transplantation in nervous system diseases, but more exploration is needed.

Modeling fMRI signals can provide insights into neural processing in the cerebral cortex.

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Vanni, Simo; Sharifian, Fariba; Heikkinen, Hanna; Vigário, Ricardo

2015-08-01

Every stimulus or task activates multiple areas in the mammalian cortex. These distributed activations can be measured with functional magnetic resonance imaging (fMRI), which has the best spatial resolution among the noninvasive brain imaging methods. Unfortunately, the relationship between the fMRI activations and distributed cortical processing has remained unclear, both because the coupling between neural and fMRI activations has remained poorly understood and because fMRI voxels are too large to directly sense the local neural events. To get an idea of the local processing given the macroscopic data, we need models to simulate the neural activity and to provide output that can be compared with fMRI data. Such models can describe neural mechanisms as mathematical functions between input and output in a specific system, with little correspondence to physiological mechanisms. Alternatively, models can be biomimetic, including biological details with straightforward correspondence to experimental data. After careful balancing between complexity, computational efficiency, and realism, a biomimetic simulation should be able to provide insight into how biological structures or functions contribute to actual data processing as well as to promote theory-driven neuroscience experiments. This review analyzes the requirements for validating system-level computational models with fMRI. In particular, we study mesoscopic biomimetic models, which include a limited set of details from real-life networks and enable system-level simulations of neural mass action. In addition, we discuss how recent developments in neurophysiology and biophysics may significantly advance the modelling of fMRI signals. Copyright © 2015 the American Physiological Society.

Strong Static Magnetic Fields Increase the Gel Signal in Partially Hydrated DPPC/DMPC Membranes

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Jennifer Tang

2015-09-01

Full Text Available NIt was recently reported that static magnetic fields increase lipid order in the hydrophobic membrane core of dehydrated native plant plasma membranes [Poinapen, Soft Matter 9:6804-6813, 2013]. As plasma membranes are multicomponent, highly complex structures, in order to elucidate the origin of this effect, we prepared model membranes consisting of a lipid species with low and high melting temperature. By controlling the temperature, bilayers coexisting of small gel and fluid domains were prepared as a basic model for the plasma membrane core. We studied molecular order in mixed lipid membranes made of dimyristoyl-sn-glycero-3-phosphocholine (DMPC and dipalmitoyl-sn-glycero-3-phosphocholine (DPPC using neutron diffraction in the presence of strong static magnetic fields up to 3.5 T. The contribution of the hydrophobic membrane core was highlighted through deuterium labeling the lipid acyl chains. There was no observable effect on lipid organization in fluid or gel domains at high hydration of the membranes. However, lipid order was found to be enhanced at a reduced relative humidity of 43%: a magnetic field of 3.5 T led to an increase of the gel signal in the diffraction patterns of 5%. While all biological materials have weak diamagnetic properties, the corresponding energy is too small to compete against thermal disorder or viscous effects in the case of lipid molecules. We tentatively propose that the interaction between the fatty acid chains’ electric moment and the external magnetic field is driving the lipid tails in the hydrophobic membrane core into a better ordered state.

Strong Static Magnetic Fields Increase the Gel Signal in Partially Hydrated DPPC/DMPC Membranes.

Science.gov (United States)

Tang, Jennifer; Alsop, Richard J; Schmalzl, Karin; Epand, Richard M; Rheinstädter, Maikel C

2015-09-29

NIt was recently reported that static magnetic fields increase lipid order in the hydrophobic membrane core of dehydrated native plant plasma membranes [Poinapen, Soft Matter 9:6804-6813, 2013]. As plasma membranes are multicomponent, highly complex structures, in order to elucidate the origin of this effect, we prepared model membranes consisting of a lipid species with low and high melting temperature. By controlling the temperature, bilayers coexisting of small gel and fluid domains were prepared as a basic model for the plasma membrane core. We studied molecular order in mixed lipid membranes made of dimyristoyl-sn-glycero-3-phosphocholine (DMPC) and dipalmitoyl-sn-glycero-3-phosphocholine (DPPC) using neutron diffraction in the presence of strong static magnetic fields up to 3.5 T. The contribution of the hydrophobic membrane core was highlighted through deuterium labeling the lipid acyl chains. There was no observable effect on lipid organization in fluid or gel domains at high hydration of the membranes. However, lipid order was found to be enhanced at a reduced relative humidity of 43%: a magnetic field of 3.5 T led to an increase of the gel signal in the diffraction patterns of 5%. While all biological materials have weak diamagnetic properties, the corresponding energy is too small to compete against thermal disorder or viscous effects in the case of lipid molecules. We tentatively propose that the interaction between the fatty acid chains' electric moment and the external magnetic field is driving the lipid tails in the hydrophobic membrane core into a better ordered state.

CXXC5 is a novel BMP4-regulated modulator of Wnt signaling in neural stem cells

Czech Academy of Sciences Publication Activity Database

Andersson, T.; Södersten, E.; Duckworth, J.K.; Cascante, A.; Fritz, N.; Sacchetti, P.; Červenka, I.; Bryja, Vítězslav; Hermanson, O.

2008-01-01

Roč. 284, č. 6 (2008), s. 3672-3681 ISSN 0021-9258 Grant - others:GA AV ČR(CZ) KJB501630801 Institutional research plan: CEZ:AV0Z50040507; CEZ:AV0Z50040702 Keywords : Wnt signaling * CXXC5 * neural stem cells Subject RIV: BO - Biophysics Impact factor: 5.520, year: 2008

The obtaining of statistical characteristics of informative features of signals in the Autonomous information systems using neural networks

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V. K. Hohlov

2014-01-01

Full Text Available The article studies a neural network approach to obtain the statistical characteristics of the input vector implementations of signal and noise at ill-conditioned matrices of correlation moments to solve the problems to select and reduce the vector dimensions of informative features at detection and recognition of signals and noise based on regression methods.A scientific novelty is determined by applying neural network algorithms for the efficient solution of problems to select the informative features and determine the parameters of regression algorithms in terms of the degeneracy or ill-conditioned data with unknown expectation and covariance matrices.The article proposes to use a single-layer neural network with no zero weights and activation functions to calculate the initial regression characteristics and the mean-square value error of multiple initial regression representations, which are necessary to justify the selection of informative features, reduce a dimension of sign vectors and implement the regression algorithms. It is shown that when excluding direct links between the inputs and their corresponding neurons, in the training network the weight coefficients of neuron inputs are the coefficients of initial multiple regression, the error meansquare value of multiple initial regression representations is calculated at the outputs of neurons. The article considers conditionality of the problem to calculate the matrix that is inverse one for matrix of correlation moments. It defines a condition number, which characterizes the relative error of stated task.The problem concerning the matrix condition of the correlation moment of informative signal features and noise arises when solving the problem to find the multiple coefficients of initial regression (MCIR and the residual mean-square values of the multiple regression representations. For obtaining the MCIR and finding the residual mean-square values the matrix of correlation moments of

Activin/Nodal Signaling Supports Retinal Progenitor Specification in a Narrow Time Window during Pluripotent Stem Cell Neuralization

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Michele Bertacchi

2015-10-01

Full Text Available Retinal progenitors are initially found in the anterior neural plate region known as the eye field, whereas neighboring areas undertake telencephalic or hypothalamic development. Eye field cells become specified by switching on a network of eye field transcription factors, but the extracellular cues activating this network remain unclear. In this study, we used chemically defined media to induce in vitro differentiation of mouse embryonic stem cells (ESCs toward eye field fates. Inhibition of Wnt/β-catenin signaling was sufficient to drive ESCs to telencephalic, but not retinal, fates. Instead, retinal progenitors could be generated from competent differentiating mouse ESCs by activation of Activin/Nodal signaling within a narrow temporal window corresponding to the emergence of primitive anterior neural progenitors. Activin also promoted eye field gene expression in differentiating human ESCs. Our results reveal insights into the mechanisms of eye field specification and open new avenues toward the generation of retinal progenitors for translational medicine.

A quantitative overview of biophysical forces impinging on neural function

International Nuclear Information System (INIS)

Mueller, Jerel K; Tyler, William J

2014-01-01

The fundamentals of neuronal membrane excitability are globally described using the Hodgkin-Huxley (HH) model. The HH model, however, does not account for a number of biophysical phenomena associated with action potentials or propagating nerve impulses. Physical mechanisms underlying these processes, such as reversible heat transfer and axonal swelling, have been compartmentalized and separately investigated to reveal neuronal activity is not solely influenced by electrical or biochemical factors. Instead, mechanical forces and thermodynamics also govern neuronal excitability and signaling. To advance our understanding of neuronal function and dysfunction, compartmentalized analyses of electrical, chemical, and mechanical processes need to be revaluated and integrated into more comprehensive theories. The present perspective is intended to provide a broad overview of biophysical forces that can influence neural function, but which have been traditionally underappreciated in neuroscience. Further, several examples where mechanical forces have been shown to exert their actions on nervous system development, signaling, and plasticity are highlighted to underscore their importance in sculpting neural function. By considering the collective actions of biophysical forces influencing neuronal activity, our working models can be expanded and new paradigms can be applied to the investigation and characterization of brain function and dysfunction. (topical review)

Lymphotropic Virions Affect Chemokine Receptor-Mediated Neural Signaling and Apoptosis: Implications for Human Immunodeficiency Virus Type 1-Associated Dementia

Science.gov (United States)

Zheng, Jialin; Ghorpade, Anuja; Niemann, Douglas; Cotter, Robin L.; Thylin, Michael R.; Epstein, Leon; Swartz, Jennifer M.; Shepard, Robin B.; Liu, Xiaojuan; Nukuna, Adeline; Gendelman, Howard E.

1999-01-01

Chemokine receptors pivotal for human immunodeficiency virus type 1 (HIV-1) infection in lymphocytes and macrophages (CCR3, CCR5, and CXCR4) are expressed on neural cells (microglia, astrocytes, and/or neurons). It is these cells which are damaged during progressive HIV-1 infection of the central nervous system. We theorize that viral coreceptors could effect neural cell damage during HIV-1-associated dementia (HAD) without simultaneously affecting viral replication. To these ends, we studied the ability of diverse viral strains to affect intracellular signaling and apoptosis of neurons, astrocytes, and monocyte-derived macrophages. Inhibition of cyclic AMP, activation of inositol 1,4,5-trisphosphate, and apoptosis were induced by diverse HIV-1 strains, principally in neurons. Virions from T-cell-tropic (T-tropic) strains (MN, IIIB, and Lai) produced the most significant alterations in signaling of neurons and astrocytes. The HIV-1 envelope glycoprotein, gp120, induced markedly less neural damage than purified virions. Macrophage-tropic (M-tropic) strains (ADA, JR-FL, Bal, MS-CSF, and DJV) produced the least neural damage, while 89.6, a dual-tropic HIV-1 strain, elicited intermediate neural cell damage. All T-tropic strain-mediated neuronal impairments were blocked by the CXCR4 antibody, 12G5. In contrast, the M-tropic strains were only partially blocked by 12G5. CXCR4-mediated neuronal apoptosis was confirmed in pure populations of rat cerebellar granule neurons and was blocked by HA1004, an inhibitor of calcium/calmodulin-dependent protein kinase II, protein kinase A, and protein kinase C. Taken together, these results suggest that progeny HIV-1 virions can influence neuronal signal transduction and apoptosis. This process occurs, in part, through CXCR4 and is independent of CD4 binding. T-tropic viruses that traffic in and out of the brain during progressive HIV-1 disease may play an important role in HAD neuropathogenesis. PMID:10482576

Membrane-initiated non-genomic signaling by estrogens in the hypothalamus: cross-talk with glucocorticoids with implications for behavior

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Jennifer eRainville

2015-02-01

Full Text Available The estrogen receptor (ER and glucocorticoid receptor (GR are members of the nuclear receptor superfamily that can signal using both non-genomic and genomic transcriptional modes. Though genomic modes of signaling have been well characterized and several behaviors attributed to this signaling mechanism, the physiological significance of non-genomic modes of signaling has not been well understood. This has partly been due to the controversy regarding the identity of the membrane ER (mER or membrane GR (mGR that may mediate rapid, non-genomic signaling and the downstream signaling cascades that may result as a consequence of steroid ligands binding the mER or the mGR. Both estrogens and glucocorticoids exert a number of actions on the hypothalamus, including feedback. This review focuses on the various candidates for the mER or mGR in the hypothalamus and the contribution of non-genomic signaling to classical hypothalamically-driven behaviors and changes in neuronal morphology. It also attempts to categorize some of the possible functions of non-genomic signaling at both the cellular level and at the organismal level that are relevant for behavior, including some behaviors that are regulated by both estrogens and glucocorticoids in a potentially synergistic manner. Lastly, it attempts to show that steroid signaling via non-genomic modes may provide the organism with rapid behavioral responses to stimuli.

Extruded Bread Classification on the Basis of Acoustic Emission Signal With Application of Artificial Neural Networks

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Świetlicka, Izabela; Muszyński, Siemowit; Marzec, Agata

2015-04-01

The presented work covers the problem of developing a method of extruded bread classification with the application of artificial neural networks. Extruded flat graham, corn, and rye breads differening in water activity were used. The breads were subjected to the compression test with simultaneous registration of acoustic signal. The amplitude-time records were analyzed both in time and frequency domains. Acoustic emission signal parameters: single energy, counts, amplitude, and duration acoustic emission were determined for the breads in four water activities: initial (0.362 for rye, 0.377 for corn, and 0.371 for graham bread), 0.432, 0.529, and 0.648. For classification and the clustering process, radial basis function, and self-organizing maps (Kohonen network) were used. Artificial neural networks were examined with respect to their ability to classify or to cluster samples according to the bread type, water activity value, and both of them. The best examination results were achieved by the radial basis function network in classification according to water activity (88%), while the self-organizing maps network yielded 81% during bread type clustering.

Voltage fluctuations in neurons: signal or noise?

DEFF Research Database (Denmark)

Yarom, Yosef; Hounsgaard, Jorn

2011-01-01

, we discuss noise-free neuronal signaling and detrimental and beneficial forms of noise in large-scale functional neural networks. Evidence that noise and variability in some cases go hand in hand with behavioral variability and increase behavioral choice, richness, and adaptability opens new avenues......Noise and variability are fundamental companions to ion channels and synapses and thus inescapable elements of brain function. The overriding unresolved issue is to what extent noise distorts and limits signaling on one hand and at the same time constitutes a crucial and fundamental enrichment...... that allows and facilitates complex adaptive behavior in an unpredictable world. Here we review the growing experimental evidence that functional network activity is associated with intense fluctuations in membrane potential and spike timing. We trace origins and consequences of noise and variability. Finally...

A hardware model of the auditory periphery to transduce acoustic signals into neural activity

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Takashi eTateno

2013-11-01

Full Text Available To improve the performance of cochlear implants, we have integrated a microdevice into a model of the auditory periphery with the goal of creating a microprocessor. We constructed an artificial peripheral auditory system using a hybrid model in which polyvinylidene difluoride was used as a piezoelectric sensor to convert mechanical stimuli into electric signals. To produce frequency selectivity, the slit on a stainless steel base plate was designed such that the local resonance frequency of the membrane over the slit reflected the transfer function. In the acoustic sensor, electric signals were generated based on the piezoelectric effect from local stress in the membrane. The electrodes on the resonating plate produced relatively large electric output signals. The signals were fed into a computer model that mimicked some functions of inner hair cells, inner hair cell–auditory nerve synapses, and auditory nerve fibers. In general, the responses of the model to pure-tone burst and complex stimuli accurately represented the discharge rates of high-spontaneous-rate auditory nerve fibers across a range of frequencies greater than 1 kHz and middle to high sound pressure levels. Thus, the model provides a tool to understand information processing in the peripheral auditory system and a basic design for connecting artificial acoustic sensors to the peripheral auditory nervous system. Finally, we discuss the need for stimulus control with an appropriate model of the auditory periphery based on auditory brainstem responses that were electrically evoked by different temporal pulse patterns with the same pulse number.

Neural Signaling of Food Healthiness Associated with Emotion Processing.

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Herwig, Uwe; Dhum, Matthias; Hittmeyer, Anna; Opialla, Sarah; Scherpiet, Sigrid; Keller, Carmen; Brühl, Annette B; Siegrist, Michael

2016-01-01

The ability to differentiate healthy from unhealthy foods is important in order to promote good health. Food, however, may have an emotional connotation, which could be inversely related to healthiness. The neurobiological background of differentiating healthy and unhealthy food and its relations to emotion processing are not yet well understood. We addressed the neural activations, particularly considering the single subject level, when one evaluates a food item to be of a higher, compared to a lower grade of healthiness with a particular view on emotion processing brain regions. Thirty-seven healthy subjects underwent functional magnetic resonance imaging while evaluating the healthiness of food presented as photographs with a subsequent rating on a visual analog scale. We compared individual evaluations of high and low healthiness of food items and also considered gender differences. We found increased activation when food was evaluated to be healthy in the left dorsolateral prefrontal cortex and precuneus in whole brain analyses. In ROI analyses, perceived and rated higher healthiness was associated with lower amygdala activity and higher ventral striatal and orbitofrontal cortex activity. Females exerted a higher activation in midbrain areas when rating food items as being healthy. Our results underline the close relationship between food and emotion processing, which makes sense considering evolutionary aspects. Actively evaluating and deciding whether food is healthy is accompanied by neural signaling associated with reward and self-relevance, which could promote salutary nutrition behavior. The involved brain regions may be amenable to mechanisms of emotion regulation in the context of psychotherapeutic regulation of food intake.

Forecast of TEXT plasma disruptions using soft X-rays as input signal in a neural network

International Nuclear Information System (INIS)

Vannucci, A.; Oliveira, K.A.; Tajima, T.; Tajima, Y.J.

2001-01-01

A feed-forward neural network is used to forecast major and minor disruptions in TEXT tokamak discharges. Using the experimental data of soft X-ray signals as input data, the neural net is trained with one disruptive plasma discharge, while a different disruptive discharge is used for validation. After proper training, the net works with the same set of weights, it is then used to forecast disruptions in two other different plasma discharges. It is observed that the neural net is capable of predicting the onset of a disruption up to 3.12 ms in advance. From what we observe in the predictive behavior of our network, speculations are made whether the disruption triggering mechanism is associated with an increase in the m=2 magnetic island, that disturbs the central part of the plasma column afterwards, or the initial perturbation has first occurred in the central part of the plasma column and then the m=2 MHD mode is destabilized. (author)

Implantable neurotechnologies: a review of integrated circuit neural amplifiers.

Science.gov (United States)

Ng, Kian Ann; Greenwald, Elliot; Xu, Yong Ping; Thakor, Nitish V

2016-01-01

Neural signal recording is critical in modern day neuroscience research and emerging neural prosthesis programs. Neural recording requires the use of precise, low-noise amplifier systems to acquire and condition the weak neural signals that are transduced through electrode interfaces. Neural amplifiers and amplifier-based systems are available commercially or can be designed in-house and fabricated using integrated circuit (IC) technologies, resulting in very large-scale integration or application-specific integrated circuit solutions. IC-based neural amplifiers are now used to acquire untethered/portable neural recordings, as they meet the requirements of a miniaturized form factor, light weight and low power consumption. Furthermore, such miniaturized and low-power IC neural amplifiers are now being used in emerging implantable neural prosthesis technologies. This review focuses on neural amplifier-based devices and is presented in two interrelated parts. First, neural signal recording is reviewed, and practical challenges are highlighted. Current amplifier designs with increased functionality and performance and without penalties in chip size and power are featured. Second, applications of IC-based neural amplifiers in basic science experiments (e.g., cortical studies using animal models), neural prostheses (e.g., brain/nerve machine interfaces) and treatment of neuronal diseases (e.g., DBS for treatment of epilepsy) are highlighted. The review concludes with future outlooks of this technology and important challenges with regard to neural signal amplification.

Planar polarization of Vangl2 in the vertebrate neural plate is controlled by Wnt and Myosin II signaling

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Olga Ossipova

2015-07-01

Full Text Available The vertebrate neural tube forms as a result of complex morphogenetic movements, which require the functions of several core planar cell polarity (PCP proteins, including Vangl2 and Prickle. Despite the importance of these proteins for neurulation, their subcellular localization and the mode of action have remained largely unknown. Here we describe the anteroposterior planar cell polarity (AP-PCP of the cells in the Xenopus neural plate. At the neural midline, the Vangl2 protein is enriched at anterior cell edges and that this localization is directed by Prickle, a Vangl2-interacting protein. Our further analysis is consistent with the model, in which Vangl2 AP-PCP is established in the neural plate as a consequence of Wnt-dependent phosphorylation. Additionally, we uncover feedback regulation of Vangl2 polarity by Myosin II, reiterating a role for mechanical forces in PCP. These observations indicate that both Wnt signaling and Myosin II activity regulate cell polarity and cell behaviors during vertebrate neurulation.

Dual small-molecule targeting of SMAD signaling stimulates human induced pluripotent stem cells toward neural lineages.

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Methichit Wattanapanitch

Full Text Available Incurable neurological disorders such as Parkinson's disease (PD, Huntington's disease (HD, and Alzheimer's disease (AD are very common and can be life-threatening because of their progressive disease symptoms with limited treatment options. To provide an alternative renewable cell source for cell-based transplantation and as study models for neurological diseases, we generated induced pluripotent stem cells (iPSCs from human dermal fibroblasts (HDFs and then differentiated them into neural progenitor cells (NPCs and mature neurons by dual SMAD signaling inhibitors. Reprogramming efficiency was improved by supplementing the histone deacethylase inhibitor, valproic acid (VPA, and inhibitor of p160-Rho associated coiled-coil kinase (ROCK, Y-27632, after retroviral transduction. We obtained a number of iPS colonies that shared similar characteristics with human embryonic stem cells in terms of their morphology, cell surface antigens, pluripotency-associated gene and protein expressions as well as their in vitro and in vivo differentiation potentials. After treatment with Noggin and SB431542, inhibitors of the SMAD signaling pathway, HDF-iPSCs demonstrated rapid and efficient differentiation into neural lineages. Six days after neural induction, neuroepithelial cells (NEPCs were observed in the adherent monolayer culture, which had the ability to differentiate further into NPCs and neurons, as characterized by their morphology and the expression of neuron-specific transcripts and proteins. We propose that our study may be applied to generate neurological disease patient-specific iPSCs allowing better understanding of disease pathogenesis and drug sensitivity assays.

Supervised Learning with Complex-valued Neural Networks

CERN Document Server

Suresh, Sundaram; Savitha, Ramasamy

2013-01-01

Recent advancements in the field of telecommunications, medical imaging and signal processing deal with signals that are inherently time varying, nonlinear and complex-valued. The time varying, nonlinear characteristics of these signals can be effectively analyzed using artificial neural networks.  Furthermore, to efficiently preserve the physical characteristics of these complex-valued signals, it is important to develop complex-valued neural networks and derive their learning algorithms to represent these signals at every step of the learning process. This monograph comprises a collection of new supervised learning algorithms along with novel architectures for complex-valued neural networks. The concepts of meta-cognition equipped with a self-regulated learning have been known to be the best human learning strategy. In this monograph, the principles of meta-cognition have been introduced for complex-valued neural networks in both the batch and sequential learning modes. For applications where the computati...

TRAIL death receptor 4 signaling via lysosome fusion and membrane raft clustering in coronary arterial endothelial cells: evidence from ASM knockout mice.

Science.gov (United States)

Li, Xiang; Han, Wei-Qing; Boini, Krishna M; Xia, Min; Zhang, Yang; Li, Pin-Lan

2013-01-01

Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) and its receptor, death receptor 4 (DR4), have been implicated in the development of endothelial dysfunction and atherosclerosis. However, the signaling mechanism mediating DR4 activation leading to endothelial injury remains unclear. We recently demonstrated that ceramide production via hydrolysis of membrane sphingomyelin by acid sphingomyelinase (ASM) results in membrane raft (MR) clustering and the formation of important redox signaling platforms, which play a crucial role in amplifying redox signaling in endothelial cells leading to endothelial dysfunction. The present study aims to investigate whether TRAIL triggers MR clustering via lysosome fusion and ASM activation, thereby conducting transmembrane redox signaling and changing endothelial function. Using confocal microscopy, we found that TRAIL induced MR clustering and co-localized with DR4 in coronary arterial endothelial cells (CAECs) isolated from wild-type (Smpd1 (+/+)) mice. Furthermore, TRAIL triggered ASM translocation, ceramide production, and NADPH oxidase aggregation in MR clusters in Smpd1 ( +/+ ) CAECs, whereas these observations were not found in Smpd1 (-/-) CAECs. Moreover, ASM deficiency reduced TRAIL-induced O(2) (-[Symbol: see text]) production in CAECs and abolished TRAIL-induced impairment on endothelium-dependent vasodilation in small resistance arteries. By measuring fluorescence resonance energy transfer, we found that Lamp-1 (lysosome membrane marker protein) and ganglioside G(M1) (MR marker) were trafficking together in Smpd1 (+/+) CAECs, which was absent in Smpd1 (-/-) CAECs. Consistently, fluorescence imaging of living cells with specific lysosome probes demonstrated that TRAIL-induced lysosome fusion with membrane was also absent in Smpd1 (-/-) CAECs. Taken together, these results suggest that ASM is essential for TRAIL-induced lysosomal trafficking, membrane fusion and formation of MR redox signaling platforms

Membrane-associated signaling in human B-lymphoma lines

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Tauzin, Sebastien; Ding, Heidrun; Burdevet, Dimitri [Department of Pathology and Immunology, Centre medical universitaire, 1, rue Michel-Servet, 1211 Geneva 11 (Switzerland); Borisch, Bettina [Department of Social and Preventive Medicine, Centre medical universitaire, 1, rue Michel-Servet, 1211 Geneva 11 (Switzerland); Hoessli, Daniel C., E-mail: danielhoessli@gmail.com [Department of Pathology and Immunology, Centre medical universitaire, 1, rue Michel-Servet, 1211 Geneva 11 (Switzerland)

2011-01-15

In B-non-Hodgkin lymphomas, Lyn and Cbp/PAG constitute the core of an oncogenic signalosome that captures the Phosphatidylinositol-3-kinase, the Spleen tyrosine kinase and the Signal transducer and activator of transcription-3 to generate pro-survival and proliferative signals. Lymphoma lines corresponding to follicular, mantle-cell and Burkitt-derived lymphomas display type-specific signalosome organizations that differentially activate PI3K, Syk and STAT3. In the follicular lymphoma line, PI3K, Syk and STAT3 were optimally activated upon association with the Lyn-Cbp/PAG signalosome, while in the Burkitt lymphoma-derived line, the association with Cbp/PAG and activation of PI3K were interfered with by the latent membrane proteins encoded by the Epstein-Barr virus. In the Jeko-1 mantle-cell line, a weak association of Syk with the Lyn-Cbp/PAG signalosome resulted in poor activation of Syk, but in those cells, as in the follicular and Burkitt-derived lines, efficient apoptosis induction by the Syk inhibitor R406 indicated that Syk is nonetheless an important prosurvival element and therefore a valuable therapeutic target. In all configurations described herein is the Lyn-Cbp/PAG signalosome independent of external signals and provides efficient means of activation for its associated lipid and protein kinases. In follicular and Burkitt-derived lines, Syk appears to be activated following binding to Cbp/PAG and no longer requires B-cell receptor-associated activation motifs for activation. Assessment of the different modalities of Lyn-Cbp/PAG signalosome organization could help in selecting the appropriate combination of kinase inhibitors to eliminate a particular type of lymphoma cells.

Electrostatics and N-glycan-mediated membrane tethering of SCUBE1 is critical for promoting bone morphogenetic protein signalling.

Science.gov (United States)

Liao, Wei-Ju; Tsao, Ku-Chi; Yang, Ruey-Bing

2016-03-01

SCUBE1 (S1), a secreted and membrane-bound glycoprotein, has a modular protein structure composed of an N-terminal signal peptide sequence followed by nine epidermal growth factor (EGF)-like repeats, a spacer region and three cysteine-rich (CR) motifs with multiple potential N-linked glycosylation sites, and one CUB domain at the C-terminus. Soluble S1 is a biomarker of platelet activation but an active participant of thrombosis via its adhesive EGF-like repeats, whereas its membrane-associated form acts as a bone morphogenetic protein (BMP) co-receptor in promoting BMP signal activity. However, the mechanism responsible for the membrane tethering and the biological importance of N-glycosylation of S1 remain largely unknown. In the present study, molecular mapping analysis identified a polycationic segment (amino acids 501-550) in the spacer region required for its membrane tethering via electrostatic interactions possibly with the anionic heparan sulfate proteoglycans. Furthermore, deglycosylation by peptide N-glycosidase F treatment revealed that N-glycans within the CR motif are essential for membrane recruitment through lectin-mediated surface retention. Injection of mRNA encoding zebrafish wild-type but not N-glycan-deficient scube1 restores the expression of haematopoietic and erythroid markers (scl and gata1) in scube1-knockdown embryos. We describe novel mechanisms in targeting S1 to the plasma membrane and demonstrate that N-glycans are required for S1 functions during primitive haematopoiesis in zebrafish. © 2016 Authors; published by Portland Press Limited.

Random/aligned electrospun PCL/PCL-collagen nanofibrous membranes: comparison of neural differentiation of rat AdMSCs and BMSCs

International Nuclear Information System (INIS)

Çapkın, Merve; Gümüşderelioğlu, Menemşe; Çakmak, Soner; Kurt, Feyzan Özdal; Şen, B Hakan; Türk, B Tuğba; Deliloğlu-Gürhan, S İsmet

2012-01-01

In this study, the aligned (A) and randomly oriented (R) polycaprolactone (PCL-A and PCL-R) and PCL/collagen (PCL/Col-A and PCL/Col-R) nanofibers were electrospun onto smooth PCL membranes (PCLMs) prepared by solvent casting. In order to investigate the effects of chemical composition and nanotopography of fibrous surfaces on proliferation and on neural differentiation of mesenchymal stem cells (MSCs), adipose and bone marrow-derived rat MSCs (AdMSCs and BMSCs) were cultivated in suitable media i.e. inducing medium containing basic fibroblast growth factor (bFGF) and epidermal growth factor (EGF), and cell maintenance medium (CMM). BMSCs adhered and proliferated on all nanofibrous membranes more efficiently than AdMSCs. PCL/Col-A was found as the most convenient surface supporting proliferation in both cell types. Immunofluorescence staining indicated that BMSCs and AdMSCs are prone for differentiation to oligodendrocytes more than they differentiate to other neuronal cell types. PCL-A nanofibrous membranes supported differentiation of MSCs to O4 + (an oligodendrocytes surface antigen) cells in both culture media. The intensity of immunoreactivity of O4 + cells differentiated from BMSCs on PCL-A was highest when compared with the other groups (p + cells. In conclusion, this study can be evaluated to establish the cell therapy strategies in neurodegenerative disorders, which are relevant to oligodendrocyte abstinence using BMSCs or AdMSCs on aligned nanofibrous membranes. (paper)

Imaging Posture Veils Neural Signals

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Robert T Thibault

2016-10-01

Full Text Available Whereas modern brain imaging often demands holding body positions incongruent with everyday life, posture governs both neural activity and cognitive performance. Humans commonly perform while upright; yet, many neuroimaging methodologies require participants to remain motionless and adhere to non-ecological comportments within a confined space. This inconsistency between ecological postures and imaging constraints undermines the transferability and generalizability of many a neuroimaging assay.Here we highlight the influence of posture on brain function and behavior. Specifically, we challenge the tacit assumption that brain processes and cognitive performance are comparable across a spectrum of positions. We provide an integrative synthesis regarding the increasingly prominent influence of imaging postures on autonomic function, mental capacity, sensory thresholds, and neural activity. Arguing that neuroimagers and cognitive scientists could benefit from considering the influence posture wields on both general functioning and brain activity, we examine existing imaging technologies and the potential of portable and versatile imaging devices (e.g., functional near infrared spectroscopy. Finally, we discuss ways that accounting for posture may help unveil the complex brain processes of everyday cognition.

A neural network method for identification of prokaryotic and eukaryotic signal peptides and prediction of their cleavage sites

DEFF Research Database (Denmark)

Nielsen, Henrik; Engelbrecht, Jacob; Brunak, Søren

1997-01-01

We have developed a new method for the identication of signal peptides and their cleavage sites based on neural networks trained on separate sets of prokaryotic and eukaryotic sequences. The method performs signicantly better than previous prediction schemes, and can easily be applied to genome...

Neural network approach to the prediction of seismic events based on low-frequency signal monitoring of the Kuril-Kamchatka and Japanese regions

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Irina Popova

2013-08-01

Full Text Available Very-low-frequency/ low-frequency (VLF/LF sub-ionospheric radiowave monitoring has been widely used in recent years to analyze earthquake preparatory processes. The connection between earthquakes with M ≥5.5 and nighttime disturbances of signal amplitude and phase has been established. Thus, it is possible to use nighttime anomalies of VLF/LF signals as earthquake precursors. Here, we propose a method for estimation of the VLF/LF signal sensitivity to seismic processes using a neural network approach. We apply the error back-propagation technique based on a three-level perceptron to predict a seismic event. The back-propagation technique involves two main stages to solve the problem; namely, network training, and recognition (the prediction itself. To train a neural network, we first create a so-called ‘training set’. The ‘teacher’ specifies the correspondence between the chosen input and the output data. In the present case, a representative database includes both the LF data received over three years of monitoring at the station in Petropavlovsk-Kamchatsky (2005-2007, and the seismicity parameters of the Kuril-Kamchatka and Japanese regions. At the first stage, the neural network established the relationship between the characteristic features of the LF signal (the mean and dispersion of a phase and an amplitude at nighttime for a few days before a seismic event and the corresponding level of correlation with a seismic event, or the absence of a seismic event. For the second stage, the trained neural network was applied to predict seismic events from the LF data using twelve time intervals in 2004, 2005, 2006 and 2007. The results of the prediction are discussed.

Vehicle Signal Analysis Using Artificial Neural Networks for a Bridge Weigh-in-Motion System

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Min-Seok Park

2009-10-01

Full Text Available This paper describes the procedures for development of signal analysis algorithms using artificial neural networks for Bridge Weigh-in-Motion (B-WIM systems. Through the analysis procedure, the extraction of information concerning heavy traffic vehicles such as weight, speed, and number of axles from the time domain strain data of the B-WIM system was attempted. As one of the several possible pattern recognition techniques, an Artificial Neural Network (ANN was employed since it could effectively include dynamic effects and bridge-vehicle interactions. A number of vehicle traveling experiments with sufficient load cases were executed on two different types of bridges, a simply supported pre-stressed concrete girder bridge and a cable-stayed bridge. Different types of WIM systems such as high-speed WIM or low-speed WIM were also utilized during the experiments for cross-checking and to validate the performance of the developed algorithms.

Vehicle Signal Analysis Using Artificial Neural Networks for a Bridge Weigh-in-Motion System.

Science.gov (United States)

Kim, Sungkon; Lee, Jungwhee; Park, Min-Seok; Jo, Byung-Wan

2009-01-01

This paper describes the procedures for development of signal analysis algorithms using artificial neural networks for Bridge Weigh-in-Motion (B-WIM) systems. Through the analysis procedure, the extraction of information concerning heavy traffic vehicles such as weight, speed, and number of axles from the time domain strain data of the B-WIM system was attempted. As one of the several possible pattern recognition techniques, an Artificial Neural Network (ANN) was employed since it could effectively include dynamic effects and bridge-vehicle interactions. A number of vehicle traveling experiments with sufficient load cases were executed on two different types of bridges, a simply supported pre-stressed concrete girder bridge and a cable-stayed bridge. Different types of WIM systems such as high-speed WIM or low-speed WIM were also utilized during the experiments for cross-checking and to validate the performance of the developed algorithms.

Feature reconstruction of LFP signals based on PLSR in the neural information decoding study.

Science.gov (United States)

Yonghui Dong; Zhigang Shang; Mengmeng Li; Xinyu Liu; Hong Wan

2017-07-01

To solve the problems of Signal-to-Noise Ratio (SNR) and multicollinearity when the Local Field Potential (LFP) signals is used for the decoding of animal motion intention, a feature reconstruction of LFP signals based on partial least squares regression (PLSR) in the neural information decoding study is proposed in this paper. Firstly, the feature information of LFP coding band is extracted based on wavelet transform. Then the PLSR model is constructed by the extracted LFP coding features. According to the multicollinearity characteristics among the coding features, several latent variables which contribute greatly to the steering behavior are obtained, and the new LFP coding features are reconstructed. Finally, the K-Nearest Neighbor (KNN) method is used to classify the reconstructed coding features to verify the decoding performance. The results show that the proposed method can achieve the highest accuracy compared to the other three methods and the decoding effect of the proposed method is robust.

The neural subjective frame: from bodily signals to perceptual consciousness.

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Park, Hyeong-Dong; Tallon-Baudry, Catherine

2014-05-05

The report 'I saw the stimulus' operationally defines visual consciousness, but where does the 'I' come from? To account for the subjective dimension of perceptual experience, we introduce the concept of the neural subjective frame. The neural subjective frame would be based on the constantly updated neural maps of the internal state of the body and constitute a neural referential from which first person experience can be created. We propose to root the neural subjective frame in the neural representation of visceral information which is transmitted through multiple anatomical pathways to a number of target sites, including posterior insula, ventral anterior cingulate cortex, amygdala and somatosensory cortex. We review existing experimental evidence showing that the processing of external stimuli can interact with visceral function. The neural subjective frame is a low-level building block of subjective experience which is not explicitly experienced by itself which is necessary but not sufficient for perceptual experience. It could also underlie other types of subjective experiences such as self-consciousness and emotional feelings. Because the neural subjective frame is tightly linked to homeostatic regulations involved in vigilance, it could also make a link between state and content consciousness.

Optical imaging of neuronal activity and visualization of fine neural structures in non-desheathed nervous systems.

Directory of Open Access Journals (Sweden)

Christopher John Goldsmith

Full Text Available Locating circuit neurons and recording from them with single-cell resolution is a prerequisite for studying neural circuits. Determining neuron location can be challenging even in small nervous systems because neurons are densely packed, found in different layers, and are often covered by ganglion and nerve sheaths that impede access for recording electrodes and neuronal markers. We revisited the voltage-sensitive dye RH795 for its ability to stain and record neurons through the ganglion sheath. Bath-application of RH795 stained neuronal membranes in cricket, earthworm and crab ganglia without removing the ganglion sheath, revealing neuron cell body locations in different ganglion layers. Using the pyloric and gastric mill central pattern generating neurons in the stomatogastric ganglion (STG of the crab, Cancer borealis, we found that RH795 permeated the ganglion without major residue in the sheath and brightly stained somatic, axonal and dendritic membranes. Visibility improved significantly in comparison to unstained ganglia, allowing the identification of somata location and number of most STG neurons. RH795 also stained axons and varicosities in non-desheathed nerves, and it revealed the location of sensory cell bodies in peripheral nerves. Importantly, the spike activity of the sensory neuron AGR, which influences the STG motor patterns, remained unaffected by RH795, while desheathing caused significant changes in AGR activity. With respect to recording neural activity, RH795 allowed us to optically record membrane potential changes of sub-sheath neuronal membranes without impairing sensory activity. The signal-to-noise ratio was comparable with that previously observed in desheathed preparations and sufficiently high to identify neurons in single-sweep recordings and synaptic events after spike-triggered averaging. In conclusion, RH795 enabled staining and optical recording of neurons through the ganglion sheath and is therefore both a

Ras-dva1 small GTPase regulates telencephalon development in Xenopus laevis embryos by controlling Fgf8 and Agr signaling at the anterior border of the neural plate

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Maria B. Tereshina

2014-07-01

Full Text Available We previously found that the small GTPase Ras-dva1 is essential for the telencephalic development in Xenopus laevis because Ras-dva1 controls the Fgf8-mediated induction of FoxG1 expression, a key telencephalic regulator. In this report, we show, however, that Ras-dva1 and FoxG1 are expressed in different groups of cells; whereas Ras-dva1 is expressed in the outer layer of the anterior neural fold, FoxG1 and Fgf8 are activated in the inner layer from which the telencephalon is derived. We resolve this paradox by demonstrating that Ras-dva1 is involved in the transduction of Fgf8 signal received by cells in the outer layer, which in turn send a feedback signal that stimulates FoxG1 expression in the inner layer. We show that this feedback signal is transmitted by secreted Agr proteins, the expression of which is activated in the outer layer by mediation of Ras-dva1 and the homeodomain transcription factor Otx2. In turn, Agrs are essential for maintaining Fgf8 and FoxG1 expression in cells at the anterior neural plate border. Our finding reveals a novel feedback loop mechanism based on the exchange of Fgf8 and Agr signaling between neural and non-neural compartments at the anterior margin of the neural plate and demonstrates a key role of Ras-dva1 in this mechanism.

High pressure modulated transport and signaling functions of membrane proteins in models and in vivo

International Nuclear Information System (INIS)

Vogel, R F; Linke, K; Teichert, H; Ehrmann, M A

2008-01-01

Cellular membranes serve in the separation of compartments, recognition of the environment, selective transport and signal transduction. Membrane lipids and membrane proteins play distinct roles in these processes, which are affected by environmental chemical (e. g. pH) or physical (e. g. pressure and temperature) changes. High hydrostatic pressure (HHP) affects fluidity and integrity of bacterial membranes instantly during the ramp, resulting in a loss of membrane potential and vital membrane protein functions. We have used the multiple drug transporter LmrA from Lactococcus lactis and ToxR, a membrane protein sensor from Photobacterium profundum, a deep-sea bacterium, and Vibrio cholerae to study membrane protein interaction and functionality in proteolioposomes and by the use of in vivo reporter systems, respectively. Both proteins require dimerization in the phospholipid bilayer for their functionality, which was favoured in the liquid crystalline lipid phase with ToxR and LmrA. Whereas LmrA, which resides in liposomes consisting of DMPC, DMPC/cholesterol or natural lipids, lost its ATPase activity above 20 or 40 MPa, it maintained its active dimeric structure in DOPC/DPPC/cholesterol liposomes up to 120 MPa. By using a specific indicator strain in which the dimerisation of ToxR initiates the transcription of lacZ it was demonstrated, that the amino acid sequence of the transmembrane domain influences HHP stability of ToxR dimerization in vivo. Thus, both the lipid structure and the nature of the protein affect membrane protein interaction. It is suggested that the protein structure determines basic functionality, e.g. principle ability or kinetics to dimerize to a functional complex, while the lipid environment modulates this property

High pressure modulated transport and signaling functions of membrane proteins in models and in vivo

Energy Technology Data Exchange (ETDEWEB)

Vogel, R F; Linke, K; Teichert, H; Ehrmann, M A [Technische Universitaet Muenchen, Technische Mikrobiologie, Weihenstephaner Steig 16, 85350 Freising (Germany)], E-mail: rudi.vogel@wzw.tum.de

2008-07-15

Cellular membranes serve in the separation of compartments, recognition of the environment, selective transport and signal transduction. Membrane lipids and membrane proteins play distinct roles in these processes, which are affected by environmental chemical (e. g. pH) or physical (e. g. pressure and temperature) changes. High hydrostatic pressure (HHP) affects fluidity and integrity of bacterial membranes instantly during the ramp, resulting in a loss of membrane potential and vital membrane protein functions. We have used the multiple drug transporter LmrA from Lactococcus lactis and ToxR, a membrane protein sensor from Photobacterium profundum, a deep-sea bacterium, and Vibrio cholerae to study membrane protein interaction and functionality in proteolioposomes and by the use of in vivo reporter systems, respectively. Both proteins require dimerization in the phospholipid bilayer for their functionality, which was favoured in the liquid crystalline lipid phase with ToxR and LmrA. Whereas LmrA, which resides in liposomes consisting of DMPC, DMPC/cholesterol or natural lipids, lost its ATPase activity above 20 or 40 MPa, it maintained its active dimeric structure in DOPC/DPPC/cholesterol liposomes up to 120 MPa. By using a specific indicator strain in which the dimerisation of ToxR initiates the transcription of lacZ it was demonstrated, that the amino acid sequence of the transmembrane domain influences HHP stability of ToxR dimerization in vivo. Thus, both the lipid structure and the nature of the protein affect membrane protein interaction. It is suggested that the protein structure determines basic functionality, e.g. principle ability or kinetics to dimerize to a functional complex, while the lipid environment modulates this property.

High pressure modulated transport and signaling functions of membrane proteins in models and in vivo

Science.gov (United States)

Vogel, R. F.; Linke, K.; Teichert, H.; Ehrmann, M. A.

2008-07-01

Cellular membranes serve in the separation of compartments, recognition of the environment, selective transport and signal transduction. Membrane lipids and membrane proteins play distinct roles in these processes, which are affected by environmental chemical (e. g. pH) or physical (e. g. pressure and temperature) changes. High hydrostatic pressure (HHP) affects fluidity and integrity of bacterial membranes instantly during the ramp, resulting in a loss of membrane potential and vital membrane protein functions. We have used the multiple drug transporter LmrA from Lactococcus lactis and ToxR, a membrane protein sensor from Photobacterium profundum, a deep-sea bacterium, and Vibrio cholerae to study membrane protein interaction and functionality in proteolioposomes and by the use of in vivo reporter systems, respectively. Both proteins require dimerization in the phospholipid bilayer for their functionality, which was favoured in the liquid crystalline lipid phase with ToxR and LmrA. Whereas LmrA, which resides in liposomes consisting of DMPC, DMPC/cholesterol or natural lipids, lost its ATPase activity above 20 or 40 MPa, it maintained its active dimeric structure in DOPC/DPPC/cholesterol liposomes up to 120 MPa. By using a specific indicator strain in which the dimerisation of ToxR initiates the transcription of lacZ it was demonstrated, that the amino acid sequence of the transmembrane domain influences HHP stability of ToxR dimerization in vivo. Thus, both the lipid structure and the nature of the protein affect membrane protein interaction. It is suggested that the protein structure determines basic functionality, e.g. principle ability or kinetics to dimerize to a functional complex, while the lipid environment modulates this property.

Reconstruction of gastric slow wave from finger photoplethysmographic signal using radial basis function neural network.

Science.gov (United States)

Mohamed Yacin, S; Srinivasa Chakravarthy, V; Manivannan, M

2011-11-01

Extraction of extra-cardiac information from photoplethysmography (PPG) signal is a challenging research problem with significant clinical applications. In this study, radial basis function neural network (RBFNN) is used to reconstruct the gastric myoelectric activity (GMA) slow wave from finger PPG signal. Finger PPG and GMA (measured using Electrogastrogram, EGG) signals were acquired simultaneously at the sampling rate of 100 Hz from ten healthy subjects. Discrete wavelet transform (DWT) was used to extract slow wave (0-0.1953 Hz) component from the finger PPG signal; this slow wave PPG was used to reconstruct EGG. A RBFNN is trained on signals obtained from six subjects in both fasting and postprandial conditions. The trained network is tested on data obtained from the remaining four subjects. In the earlier study, we have shown the presence of GMA information in finger PPG signal using DWT and cross-correlation method. In this study, we explicitly reconstruct gastric slow wave from finger PPG signal by the proposed RBFNN-based method. It was found that the network-reconstructed slow wave provided significantly higher (P wave than the correlation obtained (≈0.7) between the PPG slow wave from DWT and the EEG slow wave. Our results showed that a simple finger PPG signal can be used to reconstruct gastric slow wave using RBFNN method.

Randomly organized lipids and marginally stable proteins: a coupling of weak interactions to optimize membrane signaling.

Science.gov (United States)

Rice, Anne M; Mahling, Ryan; Fealey, Michael E; Rannikko, Anika; Dunleavy, Katie; Hendrickson, Troy; Lohese, K Jean; Kruggel, Spencer; Heiling, Hillary; Harren, Daniel; Sutton, R Bryan; Pastor, John; Hinderliter, Anne

2014-09-01

Eukaryotic lipids in a bilayer are dominated by weak cooperative interactions. These interactions impart highly dynamic and pliable properties to the membrane. C2 domain-containing proteins in the membrane also interact weakly and cooperatively giving rise to a high degree of conformational plasticity. We propose that this feature of weak energetics and plasticity shared by lipids and C2 domain-containing proteins enhance a cell's ability to transduce information across the membrane. We explored this hypothesis using information theory to assess the information storage capacity of model and mast cell membranes, as well as differential scanning calorimetry, carboxyfluorescein release assays, and tryptophan fluorescence to assess protein and membrane stability. The distribution of lipids in mast cell membranes encoded 5.6-5.8bits of information. More information resided in the acyl chains than the head groups and in the inner leaflet of the plasma membrane than the outer leaflet. When the lipid composition and information content of model membranes were varied, the associated C2 domains underwent large changes in stability and denaturation profile. The C2 domain-containing proteins are therefore acutely sensitive to the composition and information content of their associated lipids. Together, these findings suggest that the maximum flow of signaling information through the membrane and into the cell is optimized by the cooperation of near-random distributions of membrane lipids and proteins. This article is part of a Special Issue entitled: Interfacially Active Peptides and Proteins. Guest Editors: William C. Wimley and Kalina Hristova. Copyright © 2014 Elsevier B.V. All rights reserved.

LDL receptor-related protein 1 regulates the abundance of diverse cell-signaling proteins in the plasma membrane proteome.

Science.gov (United States)

Gaultier, Alban; Simon, Gabriel; Niessen, Sherry; Dix, Melissa; Takimoto, Shinako; Cravatt, Benjamin F; Gonias, Steven L

2010-12-03

LDL receptor-related protein 1 (LRP1) is an endocytic receptor, reported to regulate the abundance of other receptors in the plasma membrane, including uPAR and tissue factor. The goal of this study was to identify novel plasma membrane proteins, involved in cell-signaling, that are regulated by LRP1. Membrane protein ectodomains were prepared from RAW 264.7 cells in which LRP1 was silenced and control cells using protease K. Peptides were identified by LC-MS/MS. By analysis of spectral counts, 31 transmembrane and secreted proteins were regulated in abundance at least 2-fold when LRP1 was silenced. Validation studies confirmed that semaphorin4D (Sema4D), plexin domain-containing protein-1 (Plxdc1), and neuropilin-1 were more abundant in the membranes of LRP1 gene-silenced cells. Regulation of Plxdc1 by LRP1 was confirmed in CHO cells, as a second model system. Plxdc1 coimmunoprecipitated with LRP1 from extracts of RAW 264.7 cells and mouse liver. Although Sema4D did not coimmunoprecipitate with LRP1, the cell-surface level of Sema4D was increased by RAP, which binds to LRP1 and inhibits binding of other ligands. These studies identify Plxdc1, Sema4D, and neuropilin-1 as novel LRP1-regulated cell-signaling proteins. Overall, LRP1 emerges as a generalized regulator of the plasma membrane proteome.

Plant immune and growth receptors share common signalling components but localise to distinct plasma membrane nanodomains.

Science.gov (United States)

Bücherl, Christoph A; Jarsch, Iris K; Schudoma, Christian; Segonzac, Cécile; Mbengue, Malick; Robatzek, Silke; MacLean, Daniel; Ott, Thomas; Zipfel, Cyril

2017-03-06

Cell surface receptors govern a multitude of signalling pathways in multicellular organisms. In plants, prominent examples are the receptor kinases FLS2 and BRI1, which activate immunity and steroid-mediated growth, respectively. Intriguingly, despite inducing distinct signalling outputs, both receptors employ common downstream signalling components, which exist in plasma membrane (PM)-localised protein complexes. An important question is thus how these receptor complexes maintain signalling specificity. Live-cell imaging revealed that FLS2 and BRI1 form PM nanoclusters. Using single-particle tracking we could discriminate both cluster populations and we observed spatiotemporal separation between immune and growth signalling platforms. This finding was confirmed by visualising FLS2 and BRI1 within distinct PM nanodomains marked by specific remorin proteins and differential co-localisation with the cytoskeleton. Our results thus suggest that signalling specificity between these pathways may be explained by the spatial separation of FLS2 and BRI1 with their associated signalling components within dedicated PM nanodomains.

Membrane Transfer from Mononuclear Cells to Polymorphonuclear Neutrophils Transduces Cell Survival and Activation Signals in the Recipient Cells via Anti-Extrinsic Apoptotic and MAP Kinase Signaling Pathways.

Science.gov (United States)

Li, Ko-Jen; Wu, Cheng-Han; Shen, Chieh-Yu; Kuo, Yu-Min; Yu, Chia-Li; Hsieh, Song-Chou

2016-01-01

The biological significance of membrane transfer (trogocytosis) between polymorphonuclear neutrophils (PMNs) and mononuclear cells (MNCs) remains unclear. We investigated the biological/immunological effects and molecular basis of trogocytosis among various immune cells in healthy individuals and patients with active systemic lupus erythematosus (SLE). By flow cytometry, we determined that molecules in the immunological synapse, including HLA class-I and-II, CD11b and LFA-1, along with CXCR1, are exchanged among autologous PMNs, CD4+ T cells, and U937 cells (monocytes) after cell-cell contact. Small interfering RNA knockdown of the integrin adhesion molecule CD11a in U937 unexpectedly enhanced the level of total membrane transfer from U937 to PMN cells. Functionally, phagocytosis and IL-8 production by PMNs were enhanced after co-culture with T cells. Total membrane transfer from CD4+ T to PMNs delayed PMN apoptosis by suppressing the extrinsic apoptotic molecules, BAX, MYC and caspase 8. This enhancement of activities of PMNs by T cells was found to be mediated via p38- and P44/42-Akt-MAP kinase pathways and inhibited by the actin-polymerization inhibitor, latrunculin B, the clathrin inhibitor, Pitstop-2, and human immunoglobulin G, but not by the caveolin inhibitor, methyl-β-cyclodextrin. In addition, membrane transfer from PMNs enhanced IL-2 production by recipient anti-CD3/anti-CD28 activated MNCs, and this was suppressed by inhibitors of mitogen-activated protein kinase (PD98059) and protein kinase C (Rottlerin). Of clinical significance, decreased total membrane transfer from PMNs to MNCs in patients with active SLE suppressed mononuclear IL-2 production. In conclusion, membrane transfer from MNCs to PMNs, mainly at the immunological synapse, transduces survival and activation signals to enhance PMN functions and is dependent on actin polymerization, clathrin activation, and Fcγ receptors, while membrane transfer from PMNs to MNCs depends on MAP kinase and

Membrane Transfer from Mononuclear Cells to Polymorphonuclear Neutrophils Transduces Cell Survival and Activation Signals in the Recipient Cells via Anti-Extrinsic Apoptotic and MAP Kinase Signaling Pathways.

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Ko-Jen Li

Full Text Available The biological significance of membrane transfer (trogocytosis between polymorphonuclear neutrophils (PMNs and mononuclear cells (MNCs remains unclear. We investigated the biological/immunological effects and molecular basis of trogocytosis among various immune cells in healthy individuals and patients with active systemic lupus erythematosus (SLE. By flow cytometry, we determined that molecules in the immunological synapse, including HLA class-I and-II, CD11b and LFA-1, along with CXCR1, are exchanged among autologous PMNs, CD4+ T cells, and U937 cells (monocytes after cell-cell contact. Small interfering RNA knockdown of the integrin adhesion molecule CD11a in U937 unexpectedly enhanced the level of total membrane transfer from U937 to PMN cells. Functionally, phagocytosis and IL-8 production by PMNs were enhanced after co-culture with T cells. Total membrane transfer from CD4+ T to PMNs delayed PMN apoptosis by suppressing the extrinsic apoptotic molecules, BAX, MYC and caspase 8. This enhancement of activities of PMNs by T cells was found to be mediated via p38- and P44/42-Akt-MAP kinase pathways and inhibited by the actin-polymerization inhibitor, latrunculin B, the clathrin inhibitor, Pitstop-2, and human immunoglobulin G, but not by the caveolin inhibitor, methyl-β-cyclodextrin. In addition, membrane transfer from PMNs enhanced IL-2 production by recipient anti-CD3/anti-CD28 activated MNCs, and this was suppressed by inhibitors of mitogen-activated protein kinase (PD98059 and protein kinase C (Rottlerin. Of clinical significance, decreased total membrane transfer from PMNs to MNCs in patients with active SLE suppressed mononuclear IL-2 production. In conclusion, membrane transfer from MNCs to PMNs, mainly at the immunological synapse, transduces survival and activation signals to enhance PMN functions and is dependent on actin polymerization, clathrin activation, and Fcγ receptors, while membrane transfer from PMNs to MNCs depends on

Two multichannel integrated circuits for neural recording and signal processing.

Science.gov (United States)

Obeid, Iyad; Morizio, James C; Moxon, Karen A; Nicolelis, Miguel A L; Wolf, Patrick D

2003-02-01

We have developed, manufactured, and tested two analog CMOS integrated circuit "neurochips" for recording from arrays of densely packed neural electrodes. Device A is a 16-channel buffer consisting of parallel noninverting amplifiers with a gain of 2 V/V. Device B is a 16-channel two-stage analog signal processor with differential amplification and high-pass filtering. It features selectable gains of 250 and 500 V/V as well as reference channel selection. The resulting amplifiers on Device A had a mean gain of 1.99 V/V with an equivalent input noise of 10 microV(rms). Those on Device B had mean gains of 53.4 and 47.4 dB with a high-pass filter pole at 211 Hz and an equivalent input noise of 4.4 microV(rms). Both devices were tested in vivo with electrode arrays implanted in the somatosensory cortex.

Bearings Fault Diagnosis Based on Convolutional Neural Networks with 2-D Representation of Vibration Signals as Input

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Zhang Wei

2017-01-01

Full Text Available Periodic vibration signals captured by the accelerometers carry rich information for bearing fault diagnosis. Existing methods mostly rely on hand-crafted time-consuming preprocessing of data to acquire suitable features. In this paper, we use an easy and effective method to transform the 1-D temporal vibration signal into a 2-D image. With the signal image, convolutional Neural Network (CNN is used to train the raw vibration data. As powerful feature extractor and classifier for image recognition, CNN can learn to acquire features most suitable for the classification task by being trained. With the image format of vibration signals, the neuron in fully-connected layer of CNN can see farther and capture the periodic feature of signals. According to the results of the experiments, when fed in enough training samples, the proposed method outperforms other common methods. The proposed method can also be applied to solve intelligent diagnosis problems of other machine systems.

Recent Advances in Neural Recording Microsystems

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Benoit Gosselin

2011-04-01

Full Text Available The accelerating pace of research in neuroscience has created a considerable demand for neural interfacing microsystems capable of monitoring the activity of large groups of neurons. These emerging tools have revealed a tremendous potential for the advancement of knowledge in brain research and for the development of useful clinical applications. They can extract the relevant control signals directly from the brain enabling individuals with severe disabilities to communicate their intentions to other devices, like computers or various prostheses. Such microsystems are self-contained devices composed of a neural probe attached with an integrated circuit for extracting neural signals from multiple channels, and transferring the data outside the body. The greatest challenge facing development of such emerging devices into viable clinical systems involves addressing their small form factor and low-power consumption constraints, while providing superior resolution. In this paper, we survey the recent progress in the design and the implementation of multi-channel neural recording Microsystems, with particular emphasis on the design of recording and telemetry electronics. An overview of the numerous neural signal modalities is given and the existing microsystem topologies are covered. We present energy-efficient sensory circuits to retrieve weak signals from neural probes and we compare them. We cover data management and smart power scheduling approaches, and we review advances in low-power telemetry. Finally, we conclude by summarizing the remaining challenges and by highlighting the emerging trends in the field.

Frequency-difference-dependent stochastic resonance in neural systems

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Guo, Daqing; Perc, Matjaž; Zhang, Yangsong; Xu, Peng; Yao, Dezhong

2017-08-01

Biological neurons receive multiple noisy oscillatory signals, and their dynamical response to the superposition of these signals is of fundamental importance for information processing in the brain. Here we study the response of neural systems to the weak envelope modulation signal, which is superimposed by two periodic signals with different frequencies. We show that stochastic resonance occurs at the beat frequency in neural systems at the single-neuron as well as the population level. The performance of this frequency-difference-dependent stochastic resonance is influenced by both the beat frequency and the two forcing frequencies. Compared to a single neuron, a population of neurons is more efficient in detecting the information carried by the weak envelope modulation signal at the beat frequency. Furthermore, an appropriate fine-tuning of the excitation-inhibition balance can further optimize the response of a neural ensemble to the superimposed signal. Our results thus introduce and provide insights into the generation and modulation mechanism of the frequency-difference-dependent stochastic resonance in neural systems.

AUTOMATIC SEGMENTATION OF BROADCAST AUDIO SIGNALS USING AUTO ASSOCIATIVE NEURAL NETWORKS

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P. Dhanalakshmi

2010-12-01

Full Text Available In this paper, we describe automatic segmentation methods for audio broadcast data. Today, digital audio applications are part of our everyday lives. Since there are more and more digital audio databases in place these days, the importance of effective management for audio databases have become prominent. Broadcast audio data is recorded from the Television which comprises of various categories of audio signals. Efficient algorithms for segmenting the audio broadcast data into predefined categories are proposed. Audio features namely Linear prediction coefficients (LPC, Linear prediction cepstral coefficients, and Mel frequency cepstral coefficients (MFCC are extracted to characterize the audio data. Auto Associative Neural Networks are used to segment the audio data into predefined categories using the extracted features. Experimental results indicate that the proposed algorithms can produce satisfactory results.

Bioelectric signal classification using a recurrent probabilistic neural network with time-series discriminant component analysis.

Science.gov (United States)

Hayashi, Hideaki; Shima, Keisuke; Shibanoki, Taro; Kurita, Yuichi; Tsuji, Toshio

2013-01-01

This paper outlines a probabilistic neural network developed on the basis of time-series discriminant component analysis (TSDCA) that can be used to classify high-dimensional time-series patterns. TSDCA involves the compression of high-dimensional time series into a lower-dimensional space using a set of orthogonal transformations and the calculation of posterior probabilities based on a continuous-density hidden Markov model that incorporates a Gaussian mixture model expressed in the reduced-dimensional space. The analysis can be incorporated into a neural network so that parameters can be obtained appropriately as network coefficients according to backpropagation-through-time-based training algorithm. The network is considered to enable high-accuracy classification of high-dimensional time-series patterns and to reduce the computation time taken for network training. In the experiments conducted during the study, the validity of the proposed network was demonstrated for EEG signals.

SU-F-E-09: Respiratory Signal Prediction Based On Multi-Layer Perceptron Neural Network Using Adjustable Training Samples

Energy Technology Data Exchange (ETDEWEB)

Sun, W; Jiang, M; Yin, F [Duke University Medical Center, Durham, NC (United States)

2016-06-15

Purpose: Dynamic tracking of moving organs, such as lung and liver tumors, under radiation therapy requires prediction of organ motions prior to delivery. The shift of moving organ may change a lot due to huge transform of respiration at different periods. This study aims to reduce the influence of that changes using adjustable training signals and multi-layer perceptron neural network (ASMLP). Methods: Respiratory signals obtained using a Real-time Position Management(RPM) device were used for this study. The ASMLP uses two multi-layer perceptron neural networks(MLPs) to infer respiration position alternately and the training sample will be updated with time. Firstly, a Savitzky-Golay finite impulse response smoothing filter was established to smooth the respiratory signal. Secondly, two same MLPs were developed to estimate respiratory position from its previous positions separately. Weights and thresholds were updated to minimize network errors according to Leverberg-Marquart optimization algorithm through backward propagation method. Finally, MLP 1 was used to predict 120∼150s respiration position using 0∼120s training signals. At the same time, MLP 2 was trained using 30∼150s training signals. Then MLP is used to predict 150∼180s training signals according to 30∼150s training signals. The respiration position is predicted as this way until it was finished. Results: In this experiment, the two methods were used to predict 2.5 minute respiratory signals. For predicting 1s ahead of response time, correlation coefficient was improved from 0.8250(MLP method) to 0.8856(ASMLP method). Besides, a 30% improvement of mean absolute error between MLP(0.1798 on average) and ASMLP(0.1267 on average) was achieved. For predicting 2s ahead of response time, correlation coefficient was improved from 0.61415 to 0.7098.Mean absolute error of MLP method(0.3111 on average) was reduced by 35% using ASMLP method(0.2020 on average). Conclusion: The preliminary results

Electroacupuncture in the repair of spinal cord injury: inhibiting the Notch signaling pathway and promoting neural stem cell proliferation

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Xin Geng

2015-01-01

Full Text Available Electroacupuncture for the treatment of spinal cord injury has a good clinical curative effect, but the underlying mechanism is unclear. In our experiments, the spinal cord of adult Sprague-Dawley rats was clamped for 60 seconds. Dazhui (GV14 and Mingmen (GV4 acupoints of rats were subjected to electroacupuncture. Enzyme-linked immunosorbent assay revealed that the expression of serum inflammatory factors was apparently downregulated in rat models of spinal cord injury after electroacupuncture. Hematoxylin-eosin staining and immunohistochemistry results demonstrated that electroacupuncture contributed to the proliferation of neural stem cells in rat injured spinal cord, and suppressed their differentiation into astrocytes. Real-time quantitative PCR and western blot assays showed that electroacupuncture inhibited activation of the Notch signaling pathway induced by spinal cord injury. These findings indicate that electroacupuncture repaired the injured spinal cord by suppressing the Notch signaling pathway and promoting the proliferation of endogenous neural stem cells.

Self-assembly of tissue spheroids on polymeric membranes.

Science.gov (United States)

Messina, Antonietta; Morelli, Sabrina; Forgacs, Gabor; Barbieri, Giuseppe; Drioli, Enrico; De Bartolo, Loredana

2017-07-01

In this study, multicellular tissue spheroids were fabricated on polymeric membranes in order to accelerate the fusion process and tissue formation. To this purpose, tissue spheroids composed of three different cell types, myoblasts, fibroblasts and neural cells, were formed and cultured on agarose and membranes of polycaprolactone (PCL) and chitosan (CHT). Membranes prepared by a phase-inversion technique display different physicochemical, mechanical and transport properties, which can affect the fusion process. The membranes accelerated the fusion process of a pair of spheroids with respect to the inert substrate. In this process, a critical role is played by the membrane properties, especially by their mechanical characteristics and oxygen and carbon dioxide mass transfer. The rate of fusion was quantified and found to be similar for fibroblast, myoblast and neural tissue spheroids on membranes, which completed the fusion within 3 days. These spheroids underwent faster fusion and maturation on PCL membrane than on agarose, the rate of fusion being proportional to the value of oxygen and carbon dioxide permeances and elastic characteristics. Consequently, tissue spheroids on the membranes expressed high biological activity in terms of oxygen uptake, making them more suitable as building blocks in the fabrication of tissues and organs. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

Membrane Recruitment of the Non-receptor Protein GIV/Girdin (Gα-interacting, Vesicle-associated Protein/Girdin) Is Sufficient for Activating Heterotrimeric G Protein Signaling.

Science.gov (United States)

Parag-Sharma, Kshitij; Leyme, Anthony; DiGiacomo, Vincent; Marivin, Arthur; Broselid, Stefan; Garcia-Marcos, Mikel

2016-12-30

GIV (aka Girdin) is a guanine nucleotide exchange factor that activates heterotrimeric G protein signaling downstream of RTKs and integrins, thereby serving as a platform for signaling cascade cross-talk. GIV is recruited to the cytoplasmic tail of receptors upon stimulation, but the mechanism of activation of its G protein regulatory function is not well understood. Here we used assays in humanized yeast models and G protein activity biosensors in mammalian cells to investigate the role of GIV subcellular compartmentalization in regulating its ability to promote G protein signaling. We found that in unstimulated cells GIV does not co-fractionate with its substrate G protein Gα i3 on cell membranes and that constitutive membrane anchoring of GIV in yeast cells or rapid membrane translocation in mammalian cells via chemically induced dimerization leads to robust G protein activation. We show that membrane recruitment of the GIV "Gα binding and activating" motif alone is sufficient for G protein activation and that it does not require phosphomodification. Furthermore, we engineered a synthetic protein to show that recruitment of the GIV "Gα binding and activating" motif to membranes via association with active RTKs, instead of via chemically induced dimerization, is also sufficient for G protein activation. These results reveal that recruitment of GIV to membranes in close proximity to its substrate G protein is a major mechanism responsible for the activation of its G protein regulatory function. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Human Neural Stem Cell Aging Is Counteracted by α-Glycerylphosphorylethanolamine.

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Daniele, Simona; Da Pozzo, Eleonora; Iofrida, Caterina; Martini, Claudia

2016-07-20

Neural stem cells (NSCs) represent a subpopulation of cells, located in specific regions of the adult mammalian brain, with the ability of self-renewing and generating neurons and glia. In aged NSCs, modifications in the amount and composition of membrane proteins/lipids, which lead to a reduction in membrane fluidity and cholinergic activities, have been reported. In this respect, molecules that are effective at normalizing the membrane composition and cholinergic signaling could counteract stem cell aging. α-Glycerylphosphorylethanolamine (GPE), a nootropic drug, plays a role in phospholipid biosynthesis and acetylcholine release. Herein, GPE was assayed on human NSC cultures and on hydroxyurea-aged cells. Using cell counting, colorimetric, and fluorimetric analyses, immunoenzymatic assays, and real time PCR experiments, NSC culture proliferation, senescence, reactive oxygen species, and ADP/ATP levels were assessed. Aged NSCs exhibited cellular senescence, decreased proliferation, and an impairment in mitochondrial metabolism. These changes included a substantial induction in the nuclear factor NF-κB, a key inflammatory mediator. GPE cell treatment significantly protected the redox state and functional integrity of mitochondria, and counteracted senescence and NF-κB activation. In conclusion, our data show the beneficial properties of GPE in this model of stem cell aging.

Optimization of neural network architecture for classification of radar jamming FM signals

Science.gov (United States)

Soto, Alberto; Mendoza, Ariadna; Flores, Benjamin C.

2017-05-01

The purpose of this study is to investigate several artificial Neural Network (NN) architectures in order to design a cognitive radar system capable of optimally distinguishing linear Frequency-Modulated (FM) signals from bandlimited Additive White Gaussian Noise (AWGN). The goal is to create a theoretical framework to determine an optimal NN architecture to achieve a Probability of Detection (PD) of 95% or higher and a Probability of False Alarm (PFA) of 1.5% or lower at 5 dB Signal to Noise Ratio (SNR). Literature research reveals that the frequency-domain power spectral densities characterize a signal more efficiently than its time-domain counterparts. Therefore, the input data is preprocessed by calculating the magnitude square of the Discrete Fourier Transform of the digitally sampled bandlimited AWGN and linear FM signals to populate a matrix containing N number of samples and M number of spectra. This matrix is used as input for the NN, and the spectra are divided as follows: 70% for training, 15% for validation, and 15% for testing. The study begins by experimentally deducing the optimal number of hidden neurons (1-40 neurons), then the optimal number of hidden layers (1-5 layers), and lastly, the most efficient learning algorithm. The training algorithms examined are: Resilient Backpropagation, Scaled Conjugate Gradient, Conjugate Gradient with Powell/Beale Restarts, Polak-Ribiére Conjugate Gradient, and Variable Learning Rate Backpropagation. We determine that an architecture with ten hidden neurons (or higher), one hidden layer, and a Scaled Conjugate Gradient for training algorithm encapsulates an optimal architecture for our application.

An artificial neural network model of energy expenditure using nonintegrated acceleration signals.

Science.gov (United States)

Rothney, Megan P; Neumann, Megan; Béziat, Ashley; Chen, Kong Y

2007-10-01

Accelerometers are a promising tool for characterizing physical activity patterns in free living. The major limitation in their widespread use to date has been a lack of precision in estimating energy expenditure (EE), which may be attributed to the oversimplified time-integrated acceleration signals and subsequent use of linear regression models for EE estimation. In this study, we collected biaxial raw (32 Hz) acceleration signals at the hip to develop a relationship between acceleration and minute-to-minute EE in 102 healthy adults using EE data collected for nearly 24 h in a room calorimeter as the reference standard. From each 1 min of acceleration data, we extracted 10 signal characteristics (features) that we felt had the potential to characterize EE intensity. Using these data, we developed a feed-forward/back-propagation artificial neural network (ANN) model with one hidden layer (12 x 20 x 1 nodes). Results of the ANN were compared with estimations using the ActiGraph monitor, a uniaxial accelerometer, and the IDEEA monitor, an array of five accelerometers. After training and validation (leave-one-subject out) were completed, the ANN showed significantly reduced mean absolute errors (0.29 +/- 0.10 kcal/min), mean squared errors (0.23 +/- 0.14 kcal(2)/min(2)), and difference in total EE (21 +/- 115 kcal/day), compared with both the IDEEA (P types under free-living conditions.

Towards an understanding of the evolution of the chorioallantoic placenta: steroid biosynthesis and steroid hormone signaling in the chorioallantoic membrane of an oviparous reptile.

Science.gov (United States)

Cruze, Lori; Kohno, Satomi; McCoy, Michael W; Guillette, Louis J

2012-09-01

Amniotes, mammals, reptiles, and birds form common extraembryonic membranes during development to perform essential functions, such as protection, nutrient transfer, gas exchange, and waste removal. Together with the maternal uterus, extraembryonic membranes of viviparous (live-bearing) amniotes develop as an endocrine placenta that synthesizes and responds to steroid hormones critical for development. The ability of these membranes to synthesize and respond to steroid hormone signaling has traditionally been considered an innovation of placental amniotes. However, our laboratory recently demonstrated that this ability extends to the chorioallantoic membrane (CAM) of an oviparous (egg-laying) amniote, the domestic chicken, and we hypothesized that steroidogenic extraembryonic membranes could be an evolutionarily conserved characteristic of all amniotes because of similarities in basic structure, function, and shared evolutionary ancestry. In this study, we examined steroid hormone synthesis and signaling in the CAM of another oviparous amniote, the American alligator (Alligator mississippiensis). We quantified mRNA expression of a steroidogenic factor involved in the regulation of steroidogenesis (NR5A1), the key steroidogenic enzymes involved in the synthesis of progestins (HSD3B1), androgens (CYP17A1), and estrogens (CYP19A1), and the receptors involved in the signaling of progestins (PR), androgens (AR), estrogens (ESR1 and ESR2), and glucocorticoids (GR). Furthermore, we performed protein immunolocalization for PR and ESR1. Collectively, our findings indicate that the alligator CAM has the capability to regulate, synthesize, and respond to steroid hormone signaling, thus, supporting our hypothesis that the extraembryonic membranes of Amniota share a unifying characteristic, that is, the ability to synthesize and respond to steroid hormones.

Aminoacylation of the N-terminal cysteine is essential for Lol-dependent release of lipoproteins from membranes but does not depend on lipoprotein sorting signals.

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Fukuda, Ayumu; Matsuyama, Shin-Ichi; Hara, Takashi; Nakayama, Jiro; Nagasawa, Hiromichi; Tokuda, Hajime

2002-11-08

Lipoproteins are present in a wide variety of bacteria and are anchored to membranes through lipids attached to the N-terminal cysteine. The Lol system of Escherichia coli mediates the membrane-specific localization of lipoproteins. Aspartate at position 2 functions as a Lol avoidance signal and causes the retention of lipoproteins in the inner membrane, whereas lipoproteins having residues other than aspartate at position 2 are released from the inner membrane and localized to the outer membrane by the Lol system. Phospholipid:apolipoprotein transacylase, Lnt, catalyzes the last step of lipoprotein modification, converting apolipoprotein into mature lipoprotein. To reveal the importance of this aminoacylation for the Lol-dependent membrane localization, apolipoproteins were prepared by inhibiting lipoprotein maturation. Lnt was also purified and used to convert apolipoprotein into mature lipoprotein in vitro. The release of these lipoproteins was examined in proteoliposomes. We show here that the aminoacylation is essential for the Lol-dependent release of lipoproteins from membranes. Furthermore, lipoproteins with aspartate at position 2 were found to be aminoacylated both in vivo and in vitro, indicating that the lipoprotein-sorting signal does not affect lipid modification.

Effects of social sustainability signals on neural valuation signals and taste-experience of food products

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Laura eEnax

2015-09-01

Full Text Available Value-based decision making occurs when individuals choose between different alternatives and place a value on each alternative and its attributes. Marketing actions frequently manipulate product attributes, by adding e.g., health claims on the packaging. A previous imaging study found that an emblem for organic products increased willingness to pay (WTP and activity in the ventral striatum (VS. The current study investigated neural and behavioral processes underlying the influence of Fair Trade (FT labeling on food valuation and choice. Sustainability is an important product attribute for many consumers, with FT signals being one way to highlight ethically sustainable production. Forty participants valuated products in combination with an FT emblem or no emblem and stated their WTP in a bidding task while in an MRI scanner. After that, participants tasted – objectively identical – chocolates, presented either as FT or as conventionally produced. In the fMRI task, WTP was significantly higher for FT products. FT labeling increased activity in regions important for reward-processing and salience, that is, in the VS, anterior and posterior cingulate, as well as superior frontal gyrus. Subjective value, that is, WTP was correlated with activity in the ventromedial prefrontal cortex (vmPFC. We find that the anterior cingulate, VS and superior frontal gyrus exhibit task-related increases in functional connectivity to the vmPFC when an FT product was evaluated, suggesting a network which alters valuation processes. We also found a significant taste-placebo effect, with higher experienced taste pleasantness and intensity for FT labeled chocolates. Our results reveal a possible neural mechanism underlying valuation processes of certified food products. The results are important in light of understanding current marketing trends as well as designing future interventions that aim at positively influencing food choice.

Membrane microdomains in immunoreceptor signaling

Czech Academy of Sciences Publication Activity Database

Hořejší, Václav; Hrdinka, Matouš

2014-01-01

Roč. 588, č. 15 (2014), s. 2392-2397 ISSN 0014-5793 R&D Projects: GA ČR(CZ) GBP302/12/G101 Institutional support: RVO:68378050 Keywords : membrane raft * microdomain * immunoreceptor Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 3.169, year: 2014

Serotonin, neural markers and memory

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Alfredo eMeneses

2015-07-01

Full Text Available Diverse neuropsychiatric disorders present dysfunctional memory and no effective treatment exits for them; likely as result of the absence of neural markers associated to memory. Neurotransmitter systems and signaling pathways have been implicated in memory and dysfunctional memory; however, their role is poorly understood. Hence, neural markers and cerebral functions and dysfunctions are revised. To our knowledge no previous systematic works have been published addressing these issues. The interactions among behavioral tasks, control groups and molecular changes and/or pharmacological effects are mentioned. Neurotransmitter receptors and signaling pathways, during normal and abnormally functioning memory with an emphasis on the behavioral aspects of memory are revised. With focus on serotonin, since as it is a well characterized neurotransmitter, with multiple pharmacological tools, and well characterized downstream signaling in mammals’ species. 5-HT1A, 5-HT4, 5-HT5, 5-HT6 and 5-HT7 receptors as well as SERT (serotonin transporter seem to be useful neural markers and/or therapeutic targets. Certainly, if the mentioned evidence is replicated, then the translatability from preclinical and clinical studies to neural changes might be confirmed. Hypothesis and theories might provide appropriate limits and perspectives of evidence

Cell-geometry-dependent changes in plasma membrane order direct stem cell signalling and fate

Science.gov (United States)

von Erlach, Thomas C.; Bertazzo, Sergio; Wozniak, Michele A.; Horejs, Christine-Maria; Maynard, Stephanie A.; Attwood, Simon; Robinson, Benjamin K.; Autefage, Hélène; Kallepitis, Charalambos; del Río Hernández, Armando; Chen, Christopher S.; Goldoni, Silvia; Stevens, Molly M.

2018-03-01

Cell size and shape affect cellular processes such as cell survival, growth and differentiation1-4, thus establishing cell geometry as a fundamental regulator of cell physiology. The contributions of the cytoskeleton, specifically actomyosin tension, to these effects have been described, but the exact biophysical mechanisms that translate changes in cell geometry to changes in cell behaviour remain mostly unresolved. Using a variety of innovative materials techniques, we demonstrate that the nanostructure and lipid assembly within the cell plasma membrane are regulated by cell geometry in a ligand-independent manner. These biophysical changes trigger signalling events involving the serine/threonine kinase Akt/protein kinase B (PKB) that direct cell-geometry-dependent mesenchymal stem cell differentiation. Our study defines a central regulatory role by plasma membrane ordered lipid raft microdomains in modulating stem cell differentiation with potential translational applications.

An Implantable Mixed Analog/Digital Neural Stimulator Circuit

DEFF Research Database (Denmark)

Gudnason, Gunnar; Bruun, Erik; Haugland, Morten

1999-01-01

This paper describes a chip for a multichannel neural stimulator for functional electrical stimulation. The chip performs all the signal processing required in an implanted neural stimulator. The power and signal transmission to the stimulator is carried out via an inductive link. From the signals...... electrical stimulation is to restore various bodily functions (e.g. motor functions) in patients who have lost them due to injury or disease....

Possible Roles of Neural Electron Spin Networks in Memory and Consciousness

CERN Document Server

Hu, H P

2004-01-01

Spin is the origin of quantum effects in both Bohm and Hestenes quantum formulism and a fundamental quantum process associated with the structure of space-time. Thus, we have recently theorized that spin is the mind-pixel and developed a qualitative model of consciousness based on nuclear spins inside neural membranes and proteins. In this paper, we explore the possibility of unpaired electron spins being the mind-pixels. Besides free O2 and NO, the main sources of unpaired electron spins in neural membranes and proteins are transition metal ions and O2 and NO bound/absorbed to large molecules, free radicals produced through biochemical reactions and excited molecular triplet states induced by fluctuating internal magnetic fields. We show that unpaired electron spin networks inside neural membranes and proteins are modulated by action potentials through exchange and dipolar coupling tensors and spin-orbital coupling and g-factor tensors and perturbed by microscopically strong and fluctuating internal magnetic...

A multi-channel low-power system-on-chip for single-unit recording and narrowband wireless transmission of neural signal.

Science.gov (United States)

Bonfanti, A; Ceravolo, M; Zambra, G; Gusmeroli, R; Spinelli, A S; Lacaita, A L; Angotzi, G N; Baranauskas, G; Fadiga, L

2010-01-01

This paper reports a multi-channel neural recording system-on-chip (SoC) with digital data compression and wireless telemetry. The circuit consists of a 16 amplifiers, an analog time division multiplexer, an 8-bit SAR AD converter, a digital signal processor (DSP) and a wireless narrowband 400-MHz binary FSK transmitter. Even though only 16 amplifiers are present in our current die version, the whole system is designed to work with 64 channels demonstrating the feasibility of a digital processing and narrowband wireless transmission of 64 neural recording channels. A digital data compression, based on the detection of action potentials and storage of correspondent waveforms, allows the use of a 1.25-Mbit/s binary FSK wireless transmission. This moderate bit-rate and a low frequency deviation, Manchester-coded modulation are crucial for exploiting a narrowband wireless link and an efficient embeddable antenna. The chip is realized in a 0.35- εm CMOS process with a power consumption of 105 εW per channel (269 εW per channel with an extended transmission range of 4 m) and an area of 3.1 × 2.7 mm(2). The transmitted signal is captured by a digital TV tuner and demodulated by a wideband phase-locked loop (PLL), and then sent to a PC via an FPGA module. The system has been tested for electrical specifications and its functionality verified in in-vivo neural recording experiments.

A role for chemokine signaling in neural crest cell migration and craniofacial development

Science.gov (United States)

Killian, Eugenia C. Olesnicky; Birkholz, Denise A.; Artinger, Kristin Bruk

2009-01-01

Neural crest cells (NCCs) are a unique population of multipotent cells that migrate along defined pathways throughout the embryo and give rise to many diverse cell types including pigment cells, craniofacial cartilage and the peripheral nervous system (PNS). Aberrant migration of NCCs results in a wide variety of congenital birth defects including craniofacial abnormalities. The chemokine Sdf1 and its receptors, Cxcr4 and Cxcr7, have been identified as key components in the regulation of cell migration in a variety of tissues. Here we describe a novel role for the zebrafish chemokine receptor Cxcr4a in the development and migration of cranial NCCs (CNCCs). We find that loss of Cxcr4a, but not Cxcr7b results in aberrant CNCC migration, defects in the neurocranium, as well as cranial ganglia dismorphogenesis. Moreover, overexpression of either Sdf1b or Cxcr4a causes aberrant CNCC migration and results in ectopic craniofacial cartilages. We propose a model in which Sdf1b signaling from the pharyngeal arch endoderm and optic stalk to Cxcr4a expressing CNCCs is important for both the proper condensation of the CNCCs into pharyngeal arches and the subsequent patterning and morphogenesis of the neural crest derived tissues. PMID:19576198

Binding of Neurotransmitters to Lipid Membranes

DEFF Research Database (Denmark)

Peters, Günther H.J.; Werge, Mikkel; Elf-Lind, Maria Northved

2014-01-01

/ acetylated g-aminobutyrate (GABAneu) with a dipalmitoylphosphatidylcholine (DPPC) bilayer. This study was motivated by recent research results that suggested that neural transmission may also be affected by nonspecific interactions of NTs with the lipid matrix of the synaptic membrane. Our results revealed...... backbone of the phospholipids. It is surprising that hydrophilic solutes can deeply penetrate into the membrane pointing to the fact that membrane affinity is governed by specific interactions. Our MD simulations identified the salt-bridge between the primary amine of NTs and the lipid phosphate group...

The TOPCONS web server for consensus prediction of membrane protein topology and signal peptides.

Science.gov (United States)

Tsirigos, Konstantinos D; Peters, Christoph; Shu, Nanjiang; Käll, Lukas; Elofsson, Arne

2015-07-01

TOPCONS (http://topcons.net/) is a widely used web server for consensus prediction of membrane protein topology. We hereby present a major update to the server, with some substantial improvements, including the following: (i) TOPCONS can now efficiently separate signal peptides from transmembrane regions. (ii) The server can now differentiate more successfully between globular and membrane proteins. (iii) The server now is even slightly faster, although a much larger database is used to generate the multiple sequence alignments. For most proteins, the final prediction is produced in a matter of seconds. (iv) The user-friendly interface is retained, with the additional feature of submitting batch files and accessing the server programmatically using standard interfaces, making it thus ideal for proteome-wide analyses. Indicatively, the user can now scan the entire human proteome in a few days. (v) For proteins with homology to a known 3D structure, the homology-inferred topology is also displayed. (vi) Finally, the combination of methods currently implemented achieves an overall increase in performance by 4% as compared to the currently available best-scoring methods and TOPCONS is the only method that can identify signal peptides and still maintain a state-of-the-art performance in topology predictions. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Transfer functions for protein signal transduction: application to a model of striatal neural plasticity.

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Gabriele Scheler

Full Text Available We present a novel formulation for biochemical reaction networks in the context of protein signal transduction. The model consists of input-output transfer functions, which are derived from differential equations, using stable equilibria. We select a set of "source" species, which are interpreted as input signals. Signals are transmitted to all other species in the system (the "target" species with a specific delay and with a specific transmission strength. The delay is computed as the maximal reaction time until a stable equilibrium for the target species is reached, in the context of all other reactions in the system. The transmission strength is the concentration change of the target species. The computed input-output transfer functions can be stored in a matrix, fitted with parameters, and even recalled to build dynamical models on the basis of state changes. By separating the temporal and the magnitudinal domain we can greatly simplify the computational model, circumventing typical problems of complex dynamical systems. The transfer function transformation of biochemical reaction systems can be applied to mass-action kinetic models of signal transduction. The paper shows that this approach yields significant novel insights while remaining a fully testable and executable dynamical model for signal transduction. In particular we can deconstruct the complex system into local transfer functions between individual species. As an example, we examine modularity and signal integration using a published model of striatal neural plasticity. The modularizations that emerge correspond to a known biological distinction between calcium-dependent and cAMP-dependent pathways. Remarkably, we found that overall interconnectedness depends on the magnitude of inputs, with higher connectivity at low input concentrations and significant modularization at moderate to high input concentrations. This general result, which directly follows from the properties of

Expression of p53/HGF/c-met/STAT3 signal in fetuses with neural tube defects.

Science.gov (United States)

Trovato, Maria; D'Armiento, Maria; Lavra, Luca; Ulivieri, Alessandra; Dominici, Roberto; Vitarelli, Enrica; Grosso, Maddalena; Vecchione, Raffaella; Barresi, Gaetano; Sciacchitano, Salvatore

2007-02-01

Neural tube defects (NTD) are morphogenetic alterations due to a defective closure of neural tube. Hepatocyte growth factor (HGF)/c-met system plays a role in morphogenesis of nervous system, lung, and kidney. HGF/c-met morphogenetic effects are mediated by signal transducers and activators of transcription (STAT)3 and both HGF and c-met genes are regulated from p53. The aim of our study was to analyze mRNA and protein expressions of p53, HGF, c-met, and STAT3 in fetuses with NTD. By reverse transcriptase-polymerase chain reaction and immunohistochemistry, we analyzed neural tissues from four NTD fetuses and the corresponding non-malformed lungs, kidneys and placentas. We found a reduced mRNA expression of HGF/c-met/STAT3 pathway, in the malformed nervous systems and placentas. The reduced expression of this pathway correlated with the absence of p53 in all these samples. On the contrary, detectable expression levels of p53, HGF, c-met, and STAT3 were observed in non-malformed lungs and kidneys obtained from the same fetuses. Comparable results were obtained by immunohistochemistry, with the exception of p53, which was undetected in all fetal tissues. In conclusion, in NTD fetuses, both the defective neural tube tissue and the placenta have a reduction in all components of the p53/HGF/c-met/STAT3 cascade. This raises the possibility of using the suppression of these genes for early diagnosis of NTD especially on chorionic villus sampling.

Ectopic cross-talk between thyroid and retinoic acid signaling: A possible etiology for spinal neural tube defects.

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Li, Huili; Bai, Baoling; Zhang, Qin; Bao, Yihua; Guo, Jin; Chen, Shuyuan; Miao, Chunyue; Liu, Xiaozhen; Zhang, Ting

2015-12-01

Previous studies have highlighted the connections between neural tube defects (NTDs) and both thyroid hormones (TH) and vitamin A. However, whether the two hormonal signaling pathways interact in NTDs has remained unclear. We measured the expression levels of TH signaling genes in human fetuses with spinal NTDs associated with maternal hyperthyroidism as well as levels of retinoic acid (RA) signaling genes in mouse fetuses exposed to an overdose of RA using NanoString or real-time PCR on spinal cord tissues. Interactions between the two signaling pathways were detected by ChIP assays. The data revealed attenuated DIO2/DIO3 switching in fetuses with NTDs born to hyperthyroid mothers. The promoters of the RA signaling genes CRABP1 and RARB were ectopically occupied by increased RXRG and RXRB but displayed decreased levels of inhibitory histone modifications, suggesting that elevated TH signaling abnormally stimulates RA signaling genes. Conversely, in the mouse model, the observed decrease in Dio3 expression could be explained by increased levels of inhibitory histone modifications in the Dio3 promoter region, suggesting that overactive RA signaling may ectopically derepress TH signaling. This study thus raises in vivo a possible abnormal cross-promotion between two different hormonal signals through their common RXRs and the subsequent recruitment of histone modifications, prompting further investigation into their involvement in the etiology of spinal NTDs. Copyright © 2015 Elsevier B.V. All rights reserved.

High speed digital interfacing for a neural data acquisition system

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Bahr Andreas

2016-09-01

Full Text Available Diseases like schizophrenia and genetic epilepsy are supposed to be caused by disorders in the early development of the brain. For the further investigation of these relationships a custom designed application specific integrated circuit (ASIC was developed that is optimized for the recording from neonatal mice [Bahr A, Abu-Saleh L, Schroeder D, Krautschneider W. 16 Channel Neural Recording Integrated Circuit with SPI Interface and Error Correction Coding. Proc. 9th BIOSTEC 2016. Biodevices: Rome, Italy, 2016; 1: 263; Bahr A, Abu-Saleh L, Schroeder D, Krautschneider W. Development of a neural recording mixed signal integrated circuit for biomedical signal acquisition. Biomed Eng Biomed Tech Abstracts 2015; 60(S1: 298–299; Bahr A, Abu-Saleh L, Schroeder D, Krautschneider WH. 16 Channel Neural Recording Mixed Signal ASIC. CDNLive EMEA 2015 Conference Proceedings, 2015.]. To enable the live display of the neural signals a multichannel neural data acquisition system with live display functionality is presented. It implements a high speed data transmission from the ASIC to a computer with a live display functionality. The system has been successfully implemented and was used in a neural recording of a head-fixed mouse.

DRAGON, a GPI-anchored membrane protein, inhibits BMP signaling in C2C12 myoblasts.

Science.gov (United States)

Kanomata, Kazuhiro; Kokabu, Shoichiro; Nojima, Junya; Fukuda, Toru; Katagiri, Takenobu

2009-06-01

Bone morphogenetic proteins (BMPs) induce osteoblastic differentiation of myoblasts via binding to cell surface receptors. Repulsive guidance molecules (RGMs) have been identified as BMP co-receptors. We report here that DRAGON/RGMb, a member of the RGM family, suppressed BMP signaling in C2C12 myoblasts via a novel mechanism. All RGMs were expressed in C2C12 cells that were differentiated into myocytes and osteoblastic cells, but RGMc was not detected in immature cells. In C2C12 cells, only DRAGON suppressed ALP and Id1 promoter activities induced by BMP-4 or by constitutively activated BMP type I receptors. This inhibition by DRAGON was dependent on the secretory form of the von Willbrand factor type D domain. DRAGON even suppressed BMP signaling induced by constitutively activated Smad1. Over-expression of neogenin did not alter the inhibitory capacity of DRAGON. Taken together, these findings indicate that DRAGON may be an inhibitor of BMP signaling in C2C12 myoblasts. We also suggest that a novel molecule(s) expressed on the cell membrane may mediate the signal transduction of DRAGON in order to suppress BMP signaling in C2C12 myoblasts.

Nuclear reactor pump diagnostics via noise analysis/artificial neural networks

International Nuclear Information System (INIS)

Keyvan, S.; Rabelo, L.C.

1991-01-01

A feasibility study is performed on the utilization of artificial neural networks as a tool for reactor diagnostics. Reactor pump signals utilized in a wear-out monitoring system developed for early detection of degradation of pump shaft are analyzed as a semi-benchmark test to study the feasibility of neural networks for pattern recognition. The Adaptive Resonance Theory (ART 2) paradigm of artificial neural networks is applied in this study. The signals are collected signals as well as generated signals simulating the wear progress. The wear-out monitoring system applies noise analysis techniques, and is capable of distinguishing between these signals and providing a measure of the progress of the degradation. This paper presents the results of the analysis of these data via the ART 2 paradigm

Tumor necrosis factor α triggers proliferation of adult neural stem cells via IKK/NF-κB signaling

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Kaltschmidt Christian

2006-09-01

Full Text Available Abstract Background Brain inflammation has been recognized as a complex phenomenon with numerous related aspects. In addition to the very well-described neurodegenerative effect of inflammation, several studies suggest that inflammatory signals exert a potentially positive influence on neural stem cell proliferation, migration and differentiation. Tumor necrosis factor alpha (TNF-α is one of the best-characterized mediators of inflammation. To date, conclusions about the action of TNF on neural stem or progenitor cells (NSCs, NPCs have been conflicting. TNF seems to activate NSC proliferation and to inhibit their differentiation into NPCs. The purpose of the present study was to analyze the molecular signal transduction mechanisms induced by TNF and resulting in NSC proliferation. Results Here we describe for the first time the TNF-mediated signal transduction cascade in neural stem cells (NSCs that results in increased proliferation. Moreover, we demonstrate IKK-α/β-dependent proliferation and markedly up-regulated cyclin D1 expression after TNF treatment. The significant increase in proliferation in TNF-treated cells was indicated by increased neurosphere volume, increased bromodeoxyuridin (BrdU incorporation and a higher total cell number. Furthermore, TNF strongly activated nuclear factor-kappa B (NF-κB as measured by reporter gene assays and by an activity-specific antibody. Proliferation of control and TNF-treated NSCs was strongly inhibited by expression of the NF-κB super-repressor IκB-AA1. Pharmacological blockade of IκB ubiquitin ligase activity led to comparable decreases in NF-κB activity and proliferation. In addition, IKK-β gene product knock-down via siRNA led to diminished NF-κB activity, attenuated cyclin D1 expression and finally decreased proliferation. In contrast, TGFβ-activated kinase 1 (TAK-1 is partially dispensable for TNF-mediated and endogenous proliferation. Understanding stem cell proliferation is crucial

In vitro evaluation of biocompatibility of uncoated thermally reduced graphene and carbon nanotube-loaded PVDF membranes with adult neural stem cell-derived neurons and glia

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Çagla Defterali

2016-12-01

Full Text Available Graphene, graphene-based nanomaterials (GBNs and carbon nanotubes (CNTs are being investigated as potential substrates for the growth of neural cells. However, in most in vitro studies the cells were seeded on these materials coated with various proteins implying that the observed effects on the cells could not solely be attributed to the GBN and CNT properties. Here we studied the biocompatibility of uncoated thermally reduced graphene (TRG and poly-vinylidene fluoride (PVDF membranes loaded with multi walled CNTs (MWCNTs using neural stem cells (NSCs isolated from the adult mouse olfactory bulb (termed aOBSCs. When aOBSCs were induced to differentiate on coverslips treated with TRG or control materials (polyethyleneimine-PEI and polyornithine plus fibronectin-PLO/F in a serum-free medium, neurons, astrocytes, and oligodendrocytes were generated in all conditions, indicating that TRG permits the multi-lineage differentiation of aOBSCs. However, the total number of cells was reduced on both PEI and TRG. In a serum-containing medium, aOBSC-derived neurons and oligodendrocytes grown on TRG were more numerous than in controls; the neurons developed synaptic boutons and oligodendrocytes were more branched. In contrast, neurons growing on PVDF membranes had reduced neurite branching and on MWCNTs-loaded membranes, oligodendrocytes were lower in numbers than in controls. Overall, these findings indicate that uncoated TRG may be biocompatible with the generation, differentiation, and maturation of aOBSC-derived neurons and glial cells, implying a potential use for TRG to study functional neuronal networks.

Classification Technique for Ultrasonic Weld Inspection Signals using a Neural Network based on 2-dimensional fourier Transform and Principle Component Analysis

International Nuclear Information System (INIS)

Kim, Jae Joon

2004-01-01

Neural network-based signal classification systems are increasingly used in the analysis of large volumes of data obtained in NDE applications. Ultrasonic inspection methods on the other hand are commonly used in the nondestructive evaluation of welds to detect flaws. An important characteristic of ultrasonic inspection is the ability to identify the type of discontinuity that gives rise to a peculiar signal. Standard techniques rely on differences in individual A-scans to classify the signals. This paper proposes an ultrasonic signal classification technique based on the information tying in the neighboring signals. The approach is based on a 2-dimensional Fourier transform and the principal component analysis to generate a reduced dimensional feature vector for classification. Results of applying the technique to data obtained from the inspection of actual steel welds are presented

Dlx proteins position the neural plate border and determine adjacent cell fates.

Science.gov (United States)

Woda, Juliana M; Pastagia, Julie; Mercola, Mark; Artinger, Kristin Bruk

2003-01-01

The lateral border of the neural plate is a major source of signals that induce primary neurons, neural crest cells and cranial placodes as well as provide patterning cues to mesodermal structures such as somites and heart. Whereas secreted BMP, FGF and Wnt proteins influence the differentiation of neural and non-neural ectoderm, we show here that members of the Dlx family of transcription factors position the border between neural and non-neural ectoderm and are required for the specification of adjacent cell fates. Inhibition of endogenous Dlx activity in Xenopus embryos with an EnR-Dlx homeodomain fusion protein expands the neural plate into non-neural ectoderm tissue whereas ectopic activation of Dlx target genes inhibits neural plate differentiation. Importantly, the stereotypic pattern of border cell fates in the adjacent ectoderm is re-established only under conditions where the expanded neural plate abuts Dlx-positive non-neural ectoderm. Experiments in which presumptive neural plate was grafted to ventral ectoderm reiterate induction of neural crest and placodal lineages and also demonstrate that Dlx activity is required in non-neural ectoderm for the production of signals needed for induction of these cells. We propose that Dlx proteins regulate intercellular signaling across the interface between neural and non-neural ectoderm that is critical for inducing and patterning adjacent cell fates.

Tcf3 represses Wnt-β-catenin signaling and maintains neural stem cell population during neocortical development.

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Atsushi Kuwahara

Full Text Available During mouse neocortical development, the Wnt-β-catenin signaling pathway plays essential roles in various phenomena including neuronal differentiation and proliferation of neural precursor cells (NPCs. Production of the appropriate number of neurons without depletion of the NPC population requires precise regulation of the balance between differentiation and maintenance of NPCs. However, the mechanism that suppresses Wnt signaling to prevent premature neuronal differentiation of NPCs is poorly understood. We now show that the HMG box transcription factor Tcf3 (also known as Tcf7l1 contributes to this mechanism. Tcf3 is highly expressed in undifferentiated NPCs in the mouse neocortex, and its expression is reduced in intermediate neuronal progenitors (INPs committed to the neuronal fate. We found Tcf3 to be a repressor of Wnt signaling in neocortical NPCs in a reporter gene assay. Tcf3 bound to the promoter of the proneural bHLH gene Neurogenin1 (Neurog1 and repressed its expression. Consistent with this, Tcf3 repressed neuronal differentiation and increased the self-renewal activity of NPCs. We also found that Wnt signal stimulation reduces the level of Tcf3, and increases those of Tcf1 (also known as Tcf7 and Lef1, positive mediators of Wnt signaling, in NPCs. Together, these results suggest that Tcf3 antagonizes Wnt signaling in NPCs, thereby maintaining their undifferentiated state in the neocortex and that Wnt signaling promotes the transition from Tcf3-mediated repression to Tcf1/Lef1-mediated enhancement of Wnt signaling, constituting a positive feedback loop that facilitates neuronal differentiation.

Analysis of acoustic emission signals at austempering of steels using neural networks

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Łazarska, Malgorzata; Wozniak, Tadeusz Z.; Ranachowski, Zbigniew; Trafarski, Andrzej; Domek, Grzegorz

2017-05-01

Bearing steel 100CrMnSi6-4 and tool steel C105U were used to carry out this research with the steels being austempered to obtain a martensitic-bainitic structure. During the process quite a large number of acoustic emissions (AE) were observed. These signals were then analysed using neural networks resulting in the identification of three groups of events of: high, medium and low energy and in addition their spectral characteristics were plotted. The results were presented in the form of diagrams of AE incidence as a function of time. It was demonstrated that complex transformations of austenite into martensite and bainite occurred when austempering bearing steel at 160 °C and tool steel at 130 °C respectively. The selected temperatures of isothermal quenching of the tested steels were within the area near to MS temperature, which affected the complex course of phase transition. The high activity of AE is a typical occurrence for martensitic transformation and this is the transformation mechanism that induces the generation of AE signals of higher energy in the first stage of transition. In the second stage of transformation, the initially nucleated martensite accelerates the occurrence of the next bainitic transformation.

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

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Christopher L Buckley

2018-01-01

Full Text Available 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

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

Science.gov (United States)

Buckley, Christopher L; Toyoizumi, Taro

2018-01-01

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

Noise Analysis studies with neural networks

International Nuclear Information System (INIS)

Seker, S.; Ciftcioglu, O.

1996-01-01

Noise analysis studies with neural network are aimed. Stochastic signals at the input of the network are used to obtain an algorithmic multivariate stochastic signal modeling. To this end, lattice modeling of a stochastic signal is performed to obtain backward residual noise sources which are uncorrelated among themselves. There are applied together with an additional input to the network to obtain an algorithmic model which is used for signal detection for early failure in plant monitoring. The additional input provides the information to the network to minimize the difference between the signal and the network's one-step-ahead prediction. A stochastic algorithm is used for training where the errors reflecting the measurement error during the training are also modelled so that fast and consistent convergence of network's weights is obtained. The lattice structure coupled to neural network investigated with measured signals from an actual power plant. (authors)

Functional microdomains in bacterial membranes.

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López, Daniel; Kolter, Roberto

2010-09-01

The membranes of eukaryotic cells harbor microdomains known as lipid rafts that contain a variety of signaling and transport proteins. Here we show that bacterial membranes contain microdomains functionally similar to those of eukaryotic cells. These membrane microdomains from diverse bacteria harbor homologs of Flotillin-1, a eukaryotic protein found exclusively in lipid rafts, along with proteins involved in signaling and transport. Inhibition of lipid raft formation through the action of zaragozic acid--a known inhibitor of squalene synthases--impaired biofilm formation and protein secretion but not cell viability. The orchestration of physiological processes in microdomains may be a more widespread feature of membranes than previously appreciated.

Improved prediction of signal peptides: SignalP 3.0

DEFF Research Database (Denmark)

Bendtsen, Jannick Dyrløv; Nielsen, Henrik; von Heijne, G.

2004-01-01

We describe improvements of the currently most popular method for prediction of classically secreted proteins, SignalP. SignalP consists of two different predictors based on neural network and hidden Markov model algorithms, where both components have been updated. Motivated by the idea that the ...

Neural Networks

International Nuclear Information System (INIS)

Smith, Patrick I.

2003-01-01

Physicists use large detectors to measure particles created in high-energy collisions at particle accelerators. These detectors typically produce signals indicating either where ionization occurs along the path of the particle, or where energy is deposited by the particle. The data produced by these signals is fed into pattern recognition programs to try to identify what particles were produced, and to measure the energy and direction of these particles. Ideally, there are many techniques used in this pattern recognition software. One technique, neural networks, is particularly suitable for identifying what type of particle caused by a set of energy deposits. Neural networks can derive meaning from complicated or imprecise data, extract patterns, and detect trends that are too complex to be noticed by either humans or other computer related processes. To assist in the advancement of this technology, Physicists use a tool kit to experiment with several neural network techniques. The goal of this research is interface a neural network tool kit into Java Analysis Studio (JAS3), an application that allows data to be analyzed from any experiment. As the final result, a physicist will have the ability to train, test, and implement a neural network with the desired output while using JAS3 to analyze the results or output. Before an implementation of a neural network can take place, a firm understanding of what a neural network is and how it works is beneficial. A neural network is an artificial representation of the human brain that tries to simulate the learning process [5]. It is also important to think of the word artificial in that definition as computer programs that use calculations during the learning process. In short, a neural network learns by representative examples. Perhaps the easiest way to describe the way neural networks learn is to explain how the human brain functions. The human brain contains billions of neural cells that are responsible for processing

Embryoid body attachment to reconstituted basement membrane induces a genetic program of epithelial differentiation via jun N-terminal kinase signaling.

Science.gov (United States)

Ho, Hoang-Yen; Moffat, Ryan C; Patel, Rupal V; Awah, Franklin N; Baloue, Kaitrin; Crowe, David L

2010-09-01

Embryonic stem (ES) cells are derived from early stage mammalian embryos and have broad developmental potential. These cells can be manipulated experimentally to generate cells of multiple tissue types which could be important in treating human diseases. The ability to produce relevant amounts of these differentiated cell populations creates the basis for clinical interventions in tissue regeneration and repair. Understanding how embryonic stem cells differentiate also can reveal important insights into cell biology. A previously reported mouse embryonic stem cell model demonstrated that differentiated epithelial cells migrated out of embryoid bodies attached to reconstituted basement membrane. We used genomic technology to profile ES cell populations in order to understand the molecular mechanisms leading to epithelial differentiation. Cells with characteristics of cultured epithelium migrated from embryoid bodies attached to reconstituted basement membrane. However, cells that comprised embryoid bodies also rapidly lost ES cell-specific gene expression and expressed proteins characteristic of stratified epithelia within hours of attachment to basement membrane. Gene expression profiling of sorted cell populations revealed upregulation of the BMP/TGFbeta signaling pathway, which was not sufficient for epithelial differentiation in the absence of basement membrane attachment. Activation of c-jun N-terminal kinase 1 (JNK1) and increased expression of Jun family transcription factors was observed during epithelial differentiation of ES cells. Inhibition of JNK signaling completely blocked epithelial differentiation in this model, revealing a key mechanism by which ES cells adopt epithelial characteristics via basement membrane attachment. Copyright (c) 2010 Elsevier B.V. All rights reserved.

Clustering on Membranes

DEFF Research Database (Denmark)

Johannes, Ludger; Pezeshkian, Weria; Ipsen, John H

2018-01-01

Clustering of extracellular ligands and proteins on the plasma membrane is required to perform specific cellular functions, such as signaling and endocytosis. Attractive forces that originate in perturbations of the membrane's physical properties contribute to this clustering, in addition to direct...... protein-protein interactions. However, these membrane-mediated forces have not all been equally considered, despite their importance. In this review, we describe how line tension, lipid depletion, and membrane curvature contribute to membrane-mediated clustering. Additional attractive forces that arise...... from protein-induced perturbation of a membrane's fluctuations are also described. This review aims to provide a survey of the current understanding of membrane-mediated clustering and how this supports precise biological functions....

Eddy Current Flaw Characterization Using Neural Networks

International Nuclear Information System (INIS)

Song, S. J.; Park, H. J.; Shin, Y. K.

1998-01-01

Determination of location, shape and size of a flaw from its eddy current testing signal is one of the fundamental issues in eddy current nondestructive evaluation of steam generator tubes. Here, we propose an approach to this problem; an inversion of eddy current flaw signal using neural networks trained by finite element model-based synthetic signatures. Total 216 eddy current signals from four different types of axisymmetric flaws in tubes are generated by finite element models of which the accuracy is experimentally validated. From each simulated signature, total 24 eddy current features are extracted and among them 13 features are finally selected for flaw characterization. Based on these features, probabilistic neural networks discriminate flaws into four different types according to the location and the shape, and successively back propagation neural networks determine the size parameters of the discriminated flaw

Recycling domains in plant cell morphogenesis: small GTPase effectors, plasma membrane signalling and the exocyst.

Science.gov (United States)

Zárský, Viktor; Potocký, Martin

2010-04-01

The Rho/Rop small GTPase regulatory module is central for initiating exocytotically ACDs (active cortical domains) in plant cell cortex, and a growing array of Rop regulators and effectors are being discovered in plants. Structural membrane phospholipids are important constituents of cells as well as signals, and phospholipid-modifying enzymes are well known effectors of small GTPases. We have shown that PLDs (phospholipases D) and their product, PA (phosphatidic acid), belong to the regulators of the secretory pathway in plants. We have also shown that specific NOXs (NADPH oxidases) producing ROS (reactive oxygen species) are involved in cell growth as exemplified by pollen tubes and root hairs. Most plant cells exhibit several distinct plasma membrane domains (ACDs), established and maintained by endocytosis/exocytosis-driven membrane protein recycling. We proposed recently the concept of a 'recycling domain' (RD), uniting the ACD and the connected endosomal recycling compartment (endosome), as a dynamic spatiotemporal entity. We have described a putative GTPase-effector complex exocyst involved in exocytic vesicle tethering in plants. Owing to the multiplicity of its Exo70 subunits, this complex, along with many RabA GTPases (putative recycling endosome organizers), may belong to core regulators of RD organization in plants.

Neural networks and applications tutorial

Science.gov (United States)

Guyon, I.

1991-09-01

The importance of neural networks has grown dramatically during this decade. While only a few years ago they were primarily of academic interest, now dozens of companies and many universities are investigating the potential use of these systems and products are beginning to appear. The idea of building a machine whose architecture is inspired by that of the brain has roots which go far back in history. Nowadays, technological advances of computers and the availability of custom integrated circuits, permit simulations of hundreds or even thousands of neurons. In conjunction, the growing interest in learning machines, non-linear dynamics and parallel computation spurred renewed attention in artificial neural networks. Many tentative applications have been proposed, including decision systems (associative memories, classifiers, data compressors and optimizers), or parametric models for signal processing purposes (system identification, automatic control, noise canceling, etc.). While they do not always outperform standard methods, neural network approaches are already used in some real world applications for pattern recognition and signal processing tasks. The tutorial is divided into six lectures, that where presented at the Third Graduate Summer Course on Computational Physics (September 3-7, 1990) on Parallel Architectures and Applications, organized by the European Physical Society: (1) Introduction: machine learning and biological computation. (2) Adaptive artificial neurons (perceptron, ADALINE, sigmoid units, etc.): learning rules and implementations. (3) Neural network systems: architectures, learning algorithms. (4) Applications: pattern recognition, signal processing, etc. (5) Elements of learning theory: how to build networks which generalize. (6) A case study: a neural network for on-line recognition of handwritten alphanumeric characters.

Membrane interaction of retroviral Gag proteins

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Robert Alfred Dick

2014-04-01

Full Text Available Assembly of an infectious retroviral particle relies on multimerization of the Gag polyprotein at the inner leaflet of the plasma membrane. The three domains of Gag common to all retroviruses-- MA, CA, and NC-- provide the signals for membrane binding, assembly, and viral RNA packaging, respectively. These signals do not function independently of one another. For example, Gag multimerization enhances membrane binding and is more efficient when NC is interacting with RNA. MA binding to the plasma membrane is governed by several principles, including electrostatics, recognition of specific lipid head groups, hydrophobic interactions, and membrane order. HIV-1 uses many of these principles while Rous sarcoma virus (RSV appears to use fewer. This review describes the principles that govern Gag interactions with membranes, focusing on RSV and HIV-1 Gag. The review also defines lipid and membrane behavior, and discusses the complexities in determining how lipid and membrane behavior impact Gag membrane binding.

Neural Global Pattern Similarity Underlies True and False Memories.

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Ye, Zhifang; Zhu, Bi; Zhuang, Liping; Lu, Zhonglin; Chen, Chuansheng; Xue, Gui

2016-06-22

The neural processes giving rise to human memory strength signals remain poorly understood. Inspired by formal computational models that posit a central role of global matching in memory strength, we tested a novel hypothesis that the strengths of both true and false memories arise from the global similarity of an item's neural activation pattern during retrieval to that of all the studied items during encoding (i.e., the encoding-retrieval neural global pattern similarity [ER-nGPS]). We revealed multiple ER-nGPS signals that carried distinct information and contributed differentially to true and false memories: Whereas the ER-nGPS in the parietal regions reflected semantic similarity and was scaled with the recognition strengths of both true and false memories, ER-nGPS in the visual cortex contributed solely to true memory. Moreover, ER-nGPS differences between the parietal and visual cortices were correlated with frontal monitoring processes. By combining computational and neuroimaging approaches, our results advance a mechanistic understanding of memory strength in recognition. What neural processes give rise to memory strength signals, and lead to our conscious feelings of familiarity? Using fMRI, we found that the memory strength of a given item depends not only on how it was encoded during learning, but also on the similarity of its neural representation with other studied items. The global neural matching signal, mainly in the parietal lobule, could account for the memory strengths of both studied and unstudied items. Interestingly, a different global matching signal, originated from the visual cortex, could distinguish true from false memories. The findings reveal multiple neural mechanisms underlying the memory strengths of events registered in the brain. Copyright © 2016 the authors 0270-6474/16/366792-11$15.00/0.

Polarity-specific high-level information propagation in neural networks.

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Lin, Yen-Nan; Chang, Po-Yen; Hsiao, Pao-Yueh; Lo, Chung-Chuan

2014-01-01

Analyzing the connectome of a nervous system provides valuable information about the functions of its subsystems. Although much has been learned about the architectures of neural networks in various organisms by applying analytical tools developed for general networks, two distinct and functionally important properties of neural networks are often overlooked. First, neural networks are endowed with polarity at the circuit level: Information enters a neural network at input neurons, propagates through interneurons, and leaves via output neurons. Second, many functions of nervous systems are implemented by signal propagation through high-level pathways involving multiple and often recurrent connections rather than by the shortest paths between nodes. In the present study, we analyzed two neural networks: the somatic nervous system of Caenorhabditis elegans (C. elegans) and the partial central complex network of Drosophila, in light of these properties. Specifically, we quantified high-level propagation in the vertical and horizontal directions: the former characterizes how signals propagate from specific input nodes to specific output nodes and the latter characterizes how a signal from a specific input node is shared by all output nodes. We found that the two neural networks are characterized by very efficient vertical and horizontal propagation. In comparison, classic small-world networks show a trade-off between vertical and horizontal propagation; increasing the rewiring probability improves the efficiency of horizontal propagation but worsens the efficiency of vertical propagation. Our result provides insights into how the complex functions of natural neural networks may arise from a design that allows them to efficiently transform and combine input signals.

Proposal of a model of mammalian neural induction

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Levine, Ariel J.; Brivanlou, Ali H.

2009-01-01

How does the vertebrate embryo make a nervous system? This complex question has been at the center of developmental biology for many years. The earliest step in this process – the induction of neural tissue – is intimately linked to patterning of the entire early embryo, and the molecular and embryological basis these processes are beginning to emerge. Here, we analyze classic and cutting-edge findings on neural induction in the mouse. We find that data from genetics, tissue explants, tissue grafting, and molecular marker expression support a coherent framework for mammalian neural induction. In this model, the gastrula organizer of the mouse embryo inhibits BMP signaling to allow neural tissue to form as a default fate – in the absence of instructive signals. The first neural tissue induced is anterior and subsequent neural tissue is posteriorized to form the midbrain, hindbrain, and spinal cord. The anterior visceral endoderm protects the pre-specified anterior neural fate from similar posteriorization, allowing formation of forebrain. This model is very similar to the default model of neural induction in the frog, thus bridging the evolutionary gap between amphibians and mammals. PMID:17585896

Isolation and Molecular Characterization of Biofouling Bacteria and Profiling of Quorum Sensing Signal Molecules from Membrane Bioreactor Activated Sludge

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Harshad Lade

2014-02-01

Full Text Available The formation of biofilm in a membrane bioreactor depends on the production of various signaling molecules like N-acyl homoserine lactones (AHLs. In the present study, a total of 200 bacterial strains were isolated from membrane bioreactor activated sludge and screened for AHLs production using two biosensor systems, Chromobacterium violaceum CV026 and Agrobacterium tumefaciens A136. A correlation between AHLs production and biofilm formation has been made among screened AHLs producing strains. The 16S rRNA gene sequence analysis revealed the dominance of Aeromonas and Enterobacter sp. in AHLs production; however few a species of Serratia, Leclercia, Pseudomonas, Klebsiella, Raoultella and Citrobacter were also identified. The chromatographic characterization of sludge extract showed the presence of a broad range of quorum sensing signal molecules. Further identification of sludge AHLs by thin layer chromatography bioassay and high performance liquid chromatography confirms the presence of C4-HSL, C6-HSL, C8-HSL, 3-oxo-C8-HSL, C10-HSL, C12-HSL, 3-oxo-C12-HSL and C14-HSL. The occurrence of AHLs in sludge extract and dominance of Aeromonas and Enterobacter sp. in activated sludge suggests the key role of these bacterial strains in AHLs production and thereby membrane fouling.

Isolation and molecular characterization of biofouling bacteria and profiling of quorum sensing signal molecules from membrane bioreactor activated sludge.

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Lade, Harshad; Paul, Diby; Kweon, Ji Hyang

2014-02-04

The formation of biofilm in a membrane bioreactor depends on the production of various signaling molecules like N-acyl homoserine lactones (AHLs). In the present study, a total of 200 bacterial strains were isolated from membrane bioreactor activated sludge and screened for AHLs production using two biosensor systems, Chromobacterium violaceum CV026 and Agrobacterium tumefaciens A136. A correlation between AHLs production and biofilm formation has been made among screened AHLs producing strains. The 16S rRNA gene sequence analysis revealed the dominance of Aeromonas and Enterobacter sp. in AHLs production; however few a species of Serratia, Leclercia, Pseudomonas, Klebsiella, Raoultella and Citrobacter were also identified. The chromatographic characterization of sludge extract showed the presence of a broad range of quorum sensing signal molecules. Further identification of sludge AHLs by thin layer chromatography bioassay and high performance liquid chromatography confirms the presence of C4-HSL, C6-HSL, C8-HSL, 3-oxo-C8-HSL, C10-HSL, C12-HSL, 3-oxo-C12-HSL and C14-HSL. The occurrence of AHLs in sludge extract and dominance of Aeromonas and Enterobacter sp. in activated sludge suggests the key role of these bacterial strains in AHLs production and thereby membrane fouling.

Membrane order in the plasma membrane and endocytic recycling compartment.

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Iaea, David B; Maxfield, Frederick R

2017-01-01

The cholesterol content of membranes plays an important role in organizing membranes for signal transduction and protein trafficking as well as in modulating the biophysical properties of membranes. While the properties of model or isolated membranes have been extensively studied, there has been little evaluation of internal membranes in living cells. Here, we use a Nile Red based probe, NR12S, and ratiometric live cell imaging, to analyze the membrane order of the plasma membrane and endocytic recycling compartment. We find that after a brief incubation to allow endocytosis, NR12S is distributed between the plasma membrane and the endocytic recycling compartment. The NR12S reports that the endocytic recycling compartment is more highly ordered than the plasma membrane. We also find that the plasma membrane and the endocytic recycling compartment are differentially affected by altering cellular cholesterol levels. The membrane order of the plasma membrane, but not the endocytic recycling compartment, is altered significantly when cellular cholesterol content is increased or decreased by 20%. These results demonstrate that changes in cellular cholesterol differentially alter membrane order within different organelles.

Signal sequence and keyword trap in silico for selection of full-length human cDNAs encoding secretion or membrane proteins from oligo-capped cDNA libraries.

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Otsuki, Tetsuji; Ota, Toshio; Nishikawa, Tetsuo; Hayashi, Koji; Suzuki, Yutaka; Yamamoto, Jun-ichi; Wakamatsu, Ai; Kimura, Kouichi; Sakamoto, Katsuhiko; Hatano, Naoto; Kawai, Yuri; Ishii, Shizuko; Saito, Kaoru; Kojima, Shin-ichi; Sugiyama, Tomoyasu; Ono, Tetsuyoshi; Okano, Kazunori; Yoshikawa, Yoko; Aotsuka, Satoshi; Sasaki, Naokazu; Hattori, Atsushi; Okumura, Koji; Nagai, Keiichi; Sugano, Sumio; Isogai, Takao

2005-01-01

We have developed an in silico method of selection of human full-length cDNAs encoding secretion or membrane proteins from oligo-capped cDNA libraries. Fullness rates were increased to about 80% by combination of the oligo-capping method and ATGpr, software for prediction of translation start point and the coding potential. Then, using 5'-end single-pass sequences, cDNAs having the signal sequence were selected by PSORT ('signal sequence trap'). We also applied 'secretion or membrane protein-related keyword trap' based on the result of BLAST search against the SWISS-PROT database for the cDNAs which could not be selected by PSORT. Using the above procedures, 789 cDNAs were primarily selected and subjected to full-length sequencing, and 334 of these cDNAs were finally selected as novel. Most of the cDNAs (295 cDNAs: 88.3%) were predicted to encode secretion or membrane proteins. In particular, 165(80.5%) of the 205 cDNAs selected by PSORT were predicted to have signal sequences, while 70 (54.2%) of the 129 cDNAs selected by 'keyword trap' preserved the secretion or membrane protein-related keywords. Many important cDNAs were obtained, including transporters, receptors, and ligands, involved in significant cellular functions. Thus, an efficient method of selecting secretion or membrane protein-encoding cDNAs was developed by combining the above four procedures.

A nontoxic, photostable and high signal-to-noise ratio mitochondrial probe with mitochondrial membrane potential and viscosity detectivity

Science.gov (United States)

Chen, Yanan; Qi, Jianguo; Huang, Jing; Zhou, Xiaomin; Niu, Linqiang; Yan, Zhijie; Wang, Jianhong

2018-01-01

Herein, we reported a yellow emission probe 1-methyl-4-(6-morpholino-1, 3-dioxo-1H-benzo[de]isoquinolin-2(3H)-yl) pyridin-1-ium iodide which could specifically stain mitochondria in living immortalized and normal cells. In comparison to the common mitochondria tracker (Mitotracker Deep Red, MTDR), this probe was nontoxic, photostable and ultrahigh signal-to-noise ratio, which could real-time monitor mitochondria for a long time. Moreover, this probe also showed high sensitivity towards mitochondrial membrane potential and intramitochondrial viscosity change. Consequently, this probe was used for imaging mitochondria, detecting changes in mitochondrial membrane potential and intramitochondrial viscosity in physiological and pathological processes.

Predicting membrane protein types by fusing composite protein sequence features into pseudo amino acid composition.

Science.gov (United States)

Hayat, Maqsood; Khan, Asifullah

2011-02-21

Membrane proteins are vital type of proteins that serve as channels, receptors, and energy transducers in a cell. Prediction of membrane protein types is an important research area in bioinformatics. Knowledge of membrane protein types provides some valuable information for predicting novel example of the membrane protein types. However, classification of membrane protein types can be both time consuming and susceptible to errors due to the inherent similarity of membrane protein types. In this paper, neural networks based membrane protein type prediction system is proposed. Composite protein sequence representation (CPSR) is used to extract the features of a protein sequence, which includes seven feature sets; amino acid composition, sequence length, 2 gram exchange group frequency, hydrophobic group, electronic group, sum of hydrophobicity, and R-group. Principal component analysis is then employed to reduce the dimensionality of the feature vector. The probabilistic neural network (PNN), generalized regression neural network, and support vector machine (SVM) are used as classifiers. A high success rate of 86.01% is obtained using SVM for the jackknife test. In case of independent dataset test, PNN yields the highest accuracy of 95.73%. These classifiers exhibit improved performance using other performance measures such as sensitivity, specificity, Mathew's correlation coefficient, and F-measure. The experimental results show that the prediction performance of the proposed scheme for classifying membrane protein types is the best reported, so far. This performance improvement may largely be credited to the learning capabilities of neural networks and the composite feature extraction strategy, which exploits seven different properties of protein sequences. The proposed Mem-Predictor can be accessed at http://111.68.99.218/Mem-Predictor. Copyright © 2010 Elsevier Ltd. All rights reserved.

Distribution network fault section identification and fault location using artificial neural network

DEFF Research Database (Denmark)

Dashtdar, Masoud; Dashti, Rahman; Shaker, Hamid Reza

2018-01-01

In this paper, a method for fault location in power distribution network is presented. The proposed method uses artificial neural network. In order to train the neural network, a series of specific characteristic are extracted from the recorded fault signals in relay. These characteristics...... components of the sequences as well as three-phase signals could be obtained using statistics to extract the hidden features inside them and present them separately to train the neural network. Also, since the obtained inputs for the training of the neural network strongly depend on the fault angle, fault...... resistance, and fault location, the training data should be selected such that these differences are properly presented so that the neural network does not face any issues for identification. Therefore, selecting the signal processing function, data spectrum and subsequently, statistical parameters...

Folic Acid supplementation stimulates notch signaling and cell proliferation in embryonic neural stem cells.

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Liu, Huan; Huang, Guo-Wei; Zhang, Xu-Mei; Ren, Da-Lin; X Wilson, John

2010-09-01

The present study investigated the effect of folic acid supplementation on the Notch signaling pathway and cell proliferation in rat embryonic neural stem cells (NSCs). The NSCs were isolated from E14-16 rat brain and grown as neurospheres in serum-free suspension culture. Individual cultures were assigned to one of 3 treatment groups that differed according to the concentration of folic acid in the medium: Control (baseline folic acid concentration of 4 mg/l), low folic acid supplementation (4 mg/l above baseline, Folate-L) and high folic acid supplementation (40 mg/l above baseline, Folate-H). NSCs were identified by their expression of immunoreactive nestin and proliferating cells by incorporation of 5'bromo-2'deoxyuridine. Cell proliferation was also assessed by methyl thiazolyl tetrazolium assay. Notch signaling was analyzed by real-time PCR and western blot analyses of the expression of Notch1 and hairy and enhancer of split 5 (Hes5). Supplementation of NSCs with folic acid increased the mRNA and protein expression levels of Notch1 and Hes5. Folic acid supplementation also stimulated NSC proliferation dose-dependently. Embryonic NSCs respond to folic acid supplementation with increased Notch signaling and cell proliferation. This mechanism may mediate the effects of folic acid supplementation on neurogenesis in the embryonic nervous system.

Study on Magneto-Hydro-Dynamics Disturbance Signal Feature Classification Using Improved S-Transform Algorithm and Radial Basis Function Neural Network

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Nan YU

2014-09-01

Full Text Available The interference signal in magneto-hydro-dynamics (MHD may be the disturbance from the power supply, the equipment itself, or the electromagnetic radiation. Interference signal mixed in normal signal, brings difficulties for signal analysis and processing. Recently proposed S-Transform algorithm combines advantages of short time Fourier transform and wavelet transform. It uses Fourier kernel and wavelet like Gauss window whose width is inversely proportional to the frequency. Therefore, S-Transform algorithm not only preserves the phase information of the signals but also has variable resolution like wavelet transform. This paper proposes a new method to establish a MHD signal classifier using S-transform algorithm and radial basis function neural network (RBFNN. Because RBFNN centers ascertained by k-means clustering algorithm probably are the local optimum, this paper analyzes the characteristics of k-means clustering algorithm and proposes an improved k-means clustering algorithm called GCW (Group-cluster-weight k-means clustering algorithm to improve the centers distribution. The experiment results show that the improvement greatly enhances the RBFNN performance.

High-Density Stretchable Electrode Grids for Chronic Neural Recording.

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Tybrandt, Klas; Khodagholy, Dion; Dielacher, Bernd; Stauffer, Flurin; Renz, Aline F; Buzsáki, György; Vörös, János

2018-04-01

Electrical interfacing with neural tissue is key to advancing diagnosis and therapies for neurological disorders, as well as providing detailed information about neural signals. A challenge for creating long-term stable interfaces between electronics and neural tissue is the huge mechanical mismatch between the systems. So far, materials and fabrication processes have restricted the development of soft electrode grids able to combine high performance, long-term stability, and high electrode density, aspects all essential for neural interfacing. Here, this challenge is addressed by developing a soft, high-density, stretchable electrode grid based on an inert, high-performance composite material comprising gold-coated titanium dioxide nanowires embedded in a silicone matrix. The developed grid can resolve high spatiotemporal neural signals from the surface of the cortex in freely moving rats with stable neural recording quality and preserved electrode signal coherence during 3 months of implantation. Due to its flexible and stretchable nature, it is possible to minimize the size of the craniotomy required for placement, further reducing the level of invasiveness. The material and device technology presented herein have potential for a wide range of emerging biomedical applications. © 2018 The Authors. Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Beneficial role of noise in artificial neural networks

International Nuclear Information System (INIS)

Monterola, Christopher; Saloma, Caesar; Zapotocky, Martin

2008-01-01

We demonstrate enhancement of neural networks efficacy to recognize frequency encoded signals and/or to categorize spatial patterns of neural activity as a result of noise addition. For temporal information recovery, noise directly added to the receiving neurons allow instantaneous improvement of signal-to-noise ratio [Monterola and Saloma, Phys. Rev. Lett. 2002]. For spatial patterns however, recurrence is necessary to extend and homogenize the operating range of a feed-forward neural network [Monterola and Zapotocky, Phys. Rev. E 2005]. Finally, using the size of the basin of attraction of the networks learned patterns (dynamical fixed points), a procedure for estimating the optimal noise is demonstrated

Reciprocal bystander effect between α-irradiated macrophage and hepatocyte is mediated by cAMP through a membrane signaling pathway

International Nuclear Information System (INIS)

He, Mingyuan; Dong, Chen; Xie, Yuexia; Li, Jitao; Yuan, Dexiao; Bai, Yang; Shao, Chunlin

2014-01-01

Highlights: • α-Irradiation induced reciprocal effects between macrophage and hepatocyte cells. • cAMP played a protective role in regulating the reverse bystander effect. • cAMP communication contributed to the reciprocal effects via membrane signaling. • p53 was required for cAMP-regulated bystander effect in the recipient cells. - Abstract: Irradiated cells can induce biological effects on vicinal non-irradiated bystander cells, meanwhile the bystander cells may rescue the irradiated cells through a feedback signal stress. To elucidate the nature of this reciprocal effect, we examined the interaction between α-irradiated human macrophage cells U937 and its bystander HL-7702 hepatocyte cells using a cell co-culture system. Results showed that after 6 h of cell co-culture, mitochondria depolarization corresponding to apoptosis was significantly induced in the HL-7702 cells, but the formation of micronuclei in the irradiated U937 cells was markedly decreased compared to that without cell co-culture treatment. This reciprocal effect was not observed when the cell membrane signaling pathway was blocked by filipin that inhibited cAMP transmission from bystander cells to irradiated cells. After treatment of cells with exogenous cAMP, forskolin (an activator of cAMP) or KH-7 (an inhibitor of cAMP), respectively, it was confirmed that cAMP communication from bystander cells to targeted cells could mitigate radiation damage in U739 cells, and this cAMP insufficiency in the bystander cells contributed to the enhancement of bystander apoptosis. Moreover, the bystander apoptosis in HL-7702 cells was aggravated by cAMP inhibition but it could not be evoked when p53 of HL-7702 cells was knocked down no matter of forskolin and KH-7 treatment. In conclusion, this study disclosed that cAMP could be released from bystander HL-7702 cells and compensated to α-irradiated U937 cells through a membrane signaling pathway and this cAMP communication played a profound role in

Reciprocal bystander effect between α-irradiated macrophage and hepatocyte is mediated by cAMP through a membrane signaling pathway

Energy Technology Data Exchange (ETDEWEB)

He, Mingyuan [Institute of Radiation Medicine, Fudan University, No. 2094 Xie-Tu Road, Shanghai 200032 (China); Department of Radiation Oncology, China–Japan Union Hospital of Jilin University, Changchun 130033 (China); Dong, Chen; Xie, Yuexia; Li, Jitao; Yuan, Dexiao; Bai, Yang [Institute of Radiation Medicine, Fudan University, No. 2094 Xie-Tu Road, Shanghai 200032 (China); Shao, Chunlin, E-mail: clshao@shmu.edu.cn [Institute of Radiation Medicine, Fudan University, No. 2094 Xie-Tu Road, Shanghai 200032 (China)

2014-05-15

Highlights: • α-Irradiation induced reciprocal effects between macrophage and hepatocyte cells. • cAMP played a protective role in regulating the reverse bystander effect. • cAMP communication contributed to the reciprocal effects via membrane signaling. • p53 was required for cAMP-regulated bystander effect in the recipient cells. - Abstract: Irradiated cells can induce biological effects on vicinal non-irradiated bystander cells, meanwhile the bystander cells may rescue the irradiated cells through a feedback signal stress. To elucidate the nature of this reciprocal effect, we examined the interaction between α-irradiated human macrophage cells U937 and its bystander HL-7702 hepatocyte cells using a cell co-culture system. Results showed that after 6 h of cell co-culture, mitochondria depolarization corresponding to apoptosis was significantly induced in the HL-7702 cells, but the formation of micronuclei in the irradiated U937 cells was markedly decreased compared to that without cell co-culture treatment. This reciprocal effect was not observed when the cell membrane signaling pathway was blocked by filipin that inhibited cAMP transmission from bystander cells to irradiated cells. After treatment of cells with exogenous cAMP, forskolin (an activator of cAMP) or KH-7 (an inhibitor of cAMP), respectively, it was confirmed that cAMP communication from bystander cells to targeted cells could mitigate radiation damage in U739 cells, and this cAMP insufficiency in the bystander cells contributed to the enhancement of bystander apoptosis. Moreover, the bystander apoptosis in HL-7702 cells was aggravated by cAMP inhibition but it could not be evoked when p53 of HL-7702 cells was knocked down no matter of forskolin and KH-7 treatment. In conclusion, this study disclosed that cAMP could be released from bystander HL-7702 cells and compensated to α-irradiated U937 cells through a membrane signaling pathway and this cAMP communication played a profound role in

Mapping and signaling of neural pathways involved in the regulation of hydromineral homeostasis

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J. Antunes-Rodrigues

2013-04-01

Full Text Available Several forebrain and brainstem neurochemical circuitries interact with peripheral neural and humoral signals to collaboratively maintain both the volume and osmolality of extracellular fluids. Although much progress has been made over the past decades in the understanding of complex mechanisms underlying neuroendocrine control of hydromineral homeostasis, several issues still remain to be clarified. The use of techniques such as molecular biology, neuronal tracing, electrophysiology, immunohistochemistry, and microinfusions has significantly improved our ability to identify neuronal phenotypes and their signals, including those related to neuron-glia interactions. Accordingly, neurons have been shown to produce and release a large number of chemical mediators (neurotransmitters, neurohormones and neuromodulators into the interstitial space, which include not only classic neurotransmitters, such as acetylcholine, amines (noradrenaline, serotonin and amino acids (glutamate, GABA, but also gaseous (nitric oxide, carbon monoxide and hydrogen sulfide and lipid-derived (endocannabinoids mediators. This efferent response, initiated within the neuronal environment, recruits several peripheral effectors, such as hormones (glucocorticoids, angiotensin II, estrogen, which in turn modulate central nervous system responsiveness to systemic challenges. Therefore, in this review, we shall evaluate in an integrated manner the physiological control of body fluid homeostasis from the molecular aspects to the systemic and integrated responses.

Automatic sleep stage classification based on EEG signals by using neural networks and wavelet packet coefficients.

Science.gov (United States)

Ebrahimi, Farideh; Mikaeili, Mohammad; Estrada, Edson; Nazeran, Homer

2008-01-01

Currently in the world there is an alarming number of people who suffer from sleep disorders. A number of biomedical signals, such as EEG, EMG, ECG and EOG are used in sleep labs among others for diagnosis and treatment of sleep related disorders. The usual method for sleep stage classification is visual inspection by a sleep specialist. This is a very time consuming and laborious exercise. Automatic sleep stage classification can facilitate this process. The definition of sleep stages and the sleep literature show that EEG signals are similar in Stage 1 of non-rapid eye movement (NREM) sleep and rapid eye movement (REM) sleep. Therefore, in this work an attempt was made to classify four sleep stages consisting of Awake, Stage 1 + REM, Stage 2 and Slow Wave Stage based on the EEG signal alone. Wavelet packet coefficients and artificial neural networks were deployed for this purpose. Seven all night recordings from Physionet database were used in the study. The results demonstrated that these four sleep stages could be automatically discriminated from each other with a specificity of 94.4 +/- 4.5%, a of sensitivity 84.2+3.9% and an accuracy of 93.0 +/- 4.0%.

An Improved Neural Network Training Algorithm for Wi-Fi Fingerprinting Positioning

Directory of Open Access Journals (Sweden)

Esmond Mok

2013-09-01

Full Text Available Ubiquitous positioning provides continuous positional information in both indoor and outdoor environments for a wide spectrum of location based service (LBS applications. With the rapid development of the low-cost and high speed data communication, Wi-Fi networks in many metropolitan cities, strength of signals propagated from the Wi-Fi access points (APs namely received signal strength (RSS have been cleverly adopted for indoor positioning. In this paper, a Wi-Fi positioning algorithm based on neural network modeling of Wi-Fi signal patterns is proposed. This algorithm is based on the correlation between the initial parameter setting for neural network training and output of the mean square error to obtain better modeling of the nonlinear highly complex Wi-Fi signal power propagation surface. The test results show that this neural network based data processing algorithm can significantly improve the neural network training surface to achieve the highest possible accuracy of the Wi-Fi fingerprinting positioning method.

A Chip for an Implantable Neural Stimulator

DEFF Research Database (Denmark)

Gudnason, Gunnar; Bruun, Erik; Haugland, Morten

2000-01-01

This paper describes a chip for a multichannel neural stimulator for functional electrical stimulation (FES). The purpose of FES is to restore muscular control in disabled patients. The chip performs all the signal processing required in an implanted neural stimulator. The power and digital data...

Proton detection for signal enhancement in solid-state NMR experiments on mobile species in membrane proteins

Energy Technology Data Exchange (ETDEWEB)

Ward, Meaghan E.; Ritz, Emily [University of Guelph, Department of Physics (Canada); Ahmed, Mumdooh A. M. [Suez University, The Department of Physics, Faculty of Science (Egypt); Bamm, Vladimir V.; Harauz, George [University of Guelph, Biophysics Interdepartmental Group (Canada); Brown, Leonid S.; Ladizhansky, Vladimir, E-mail: vladizha@uoguelph.ca [University of Guelph, Department of Physics (Canada)

2015-12-15

Direct proton detection is becoming an increasingly popular method for enhancing sensitivity in solid-state nuclear magnetic resonance spectroscopy. Generally, these experiments require extensive deuteration of the protein, fast magic angle spinning (MAS), or a combination of both. Here, we implement direct proton detection to selectively observe the mobile entities in fully-protonated membrane proteins at moderate MAS frequencies. We demonstrate this method on two proteins that exhibit different motional regimes. Myelin basic protein is an intrinsically-disordered, peripherally membrane-associated protein that is highly flexible, whereas Anabaena sensory rhodopsin is composed of seven rigid transmembrane α-helices connected by mobile loop regions. In both cases, we observe narrow proton linewidths and, on average, a 10× increase in sensitivity in 2D insensitive nuclear enhancement of polarization transfer-based HSQC experiments when proton detection is compared to carbon detection. We further show that our proton-detected experiments can be easily extended to three dimensions and used to build complete amino acid systems, including sidechain protons, and obtain inter-residue correlations. Additionally, we detect signals which do not correspond to amino acids, but rather to lipids and/or carbohydrates which interact strongly with membrane proteins.

Analysis of ultrasonic techniques for the characterization of microfiltration polymeric membranes

International Nuclear Information System (INIS)

Lucas, Carla S.; Baroni, Douglas B.; Costa, Antonio M.L.M.; Bittencourt, Marcelo S.Q.

2009-01-01

The use of polymeric membranes is extremely important in several industries such as nuclear, biotechnology, chemical and pharmaceutical. In the nuclear area, for instance, systems based on membrane separation technologies are currently being used in the treatment of radioactive liquid effluent, and new technologies using membranes are being developed at a great rate. The knowledge of the physical characteristics of these membranes, such as, pore size and the pore size distribution, is very important to the membranes separation processes. Only after these characteristics are known is it possible to determine the type and to choose a particular membrane for a specific application. In this work, two ultrasonic non destructive techniques were used to determine the porosity of membranes: pulse echo and transmission. A 25 MHz immersion transducer was used. Ultrasonic signals were acquired, for both techniques, after the ultrasonic waves passed through a microfiltration polymeric membrane of pore size of 0.45 μm and thickness of 180 μm. After the emitted ultrasonic signal crossed the membrane, the received signal brought several information on the influence of the membrane porosity in the standard signal of the ultrasonic wave. The ultrasonic signals were acquired in the time domain and changed to the frequency domain by application of the Fourier Fast Transform (FFT), thus generating the material frequency spectrum. For the pulse echo technique, the ultrasonic spectrum frequency changed after the ultrasonic wave crossed the membrane. With the transmission technique there was only a displacement of the ultrasonic signal at the time domain. (author)

Membrane-associated proteomics of chickpea identifies Sad1/UNC-84 protein (CaSUN1), a novel component of dehydration signaling

Science.gov (United States)

Jaiswal, Dinesh Kumar; Mishra, Poonam; Subba, Pratigya; Rathi, Divya; Chakraborty, Subhra; Chakraborty, Niranjan

2014-02-01

Dehydration affects almost all the physiological processes including those that result in the accumulation of misfolded proteins in the endoplasmic reticulum (ER), which in turn elicits a highly conserved signaling, the unfolded protein response (UPR). We investigated the dehydration-responsive membrane-associated proteome of a legume, chickpea, by 2-DE coupled with mass spectrometry. A total of 184 protein spots were significantly altered over a dehydration treatment of 120 h. Among the differentially expressed proteins, a non-canonical SUN domain protein, designated CaSUN1 (Cicer arietinum Sad1/UNC-84), was identified. CaSUN1 localized to the nuclear membrane and ER, besides small vacuolar vesicles. The transcripts were downregulated by both abiotic and biotic stresses, but not by abscisic acid treatment. Overexpression of CaSUN1 conferred stress tolerance in transgenic Arabidopsis. Furthermore, functional complementation of the yeast mutant, slp1, could rescue its growth defects. We propose that the function of CaSUN1 in stress response might be regulated via UPR signaling.

Pressure modulation of Ras-membrane interactions and intervesicle transfer.

Science.gov (United States)

Kapoor, Shobhna; Werkmüller, Alexander; Goody, Roger S; Waldmann, Herbert; Winter, Roland

2013-04-24

Proteins attached to the plasma membrane frequently encounter mechanical stresses, including high hydrostatic pressure (HHP) stress. Signaling pathways involving membrane-associated small GTPases (e.g., Ras) have been identified as critical loci for pressure perturbation. However, the impact of mechanical stimuli on biological outputs is still largely terra incognita. The present study explores the effect of HHP on the membrane association, dissociation, and intervesicle transfer process of N-Ras by using a FRET-based assay to obtain the kinetic parameters and volumetric properties along the reaction path of these processes. Notably, membrane association is fostered upon pressurization. Conversely, depending on the nature and lateral organization of the lipid membrane, acceleration or retardation is observed for the dissociation step. In addition, HHP can be inferred as a positive regulator of N-Ras clustering, in particular in heterogeneous membranes. The susceptibility of membrane interaction to pressure raises the idea of a role of lipidated signaling molecules as mechanosensors, transducing mechanical stimuli to chemical signals by regulating their membrane binding and dissociation. Finally, our results provide first insights into the influence of pressure on membrane-associated Ras-controlled signaling events in organisms living under extreme environmental conditions such as those that are encountered in the deep sea and sub-seafloor environments, where pressures reach the kilobar (100 MPa) range.

Dynamic neural network-based methods for compensation of nonlinear effects in multimode communication lines

Science.gov (United States)

Sidelnikov, O. S.; Redyuk, A. A.; Sygletos, S.

2017-12-01

We consider neural network-based schemes of digital signal processing. It is shown that the use of a dynamic neural network-based scheme of signal processing ensures an increase in the optical signal transmission quality in comparison with that provided by other methods for nonlinear distortion compensation.

Augmented Indian hedgehog signaling in cranial neural crest cells leads to craniofacial abnormalities and dysplastic temporomandibular joint in mice.

Science.gov (United States)

Yang, Ling; Gu, Shuping; Ye, Wenduo; Song, Yingnan; Chen, YiPing

2016-04-01

Extensive studies have pinpointed the crucial role of Indian hedgehog (Ihh) signaling in the development of the appendicular skeleton and the essential function of Ihh in the formation of the temporomandibular joint (TMJ). In this study, we have investigated the effect of augmented Ihh signaling in TMJ development. We took a transgenic gain-of-function approach by overexpressing Ihh in the cranial neural crest (CNC) cells using a conditional Ihh transgenic allele and the Wnt1-Cre allele. We found that Wnt1-Cre-mediated tissue-specific overexpression of Ihh in the CNC lineage caused severe craniofacial abnormalities, including cleft lip/palate, encephalocele, anophthalmos, micrognathia, and defective TMJ development. In the mutant TMJ, the glenoid fossa was completely absent, whereas the condyle and the articular disc appeared relatively normal with slightly delayed chondrocyte differentiation. Our findings thus demonstrate that augmented Ihh signaling is detrimental to craniofacial development, and that finely tuned Ihh signaling is critical for TMJ formation. Our results also provide additional evidence that the development of the condyle and articular disc is independent of the glenoid fossa.

Membrane structure in disease and drug therapy

National Research Council Canada - National Science Library

Zimmer, G

2000-01-01

...) interaction with membranous transport systems (opening or closing of ion or substrate channels); (2) reaction with receptors; (3) activation or inhibition of membrane enzymes; or (4) cytosolic membranous signaling and exchange. These consequences within the membrane influence intracellular wellbeing: life is possible only if a bala...

Wnt/Yes-Associated Protein Interactions During Neural Tissue Patterning of Human Induced Pluripotent Stem Cells.

Science.gov (United States)

Bejoy, Julie; Song, Liqing; Zhou, Yi; Li, Yan

2018-04-01

Human induced pluripotent stem cells (hiPSCs) have special ability to self-assemble into neural spheroids or mini-brain-like structures. During the self-assembly process, Wnt signaling plays an important role in regional patterning and establishing positional identity of hiPSC-derived neural progenitors. Recently, the role of Wnt signaling in regulating Yes-associated protein (YAP) expression (nuclear or cytoplasmic), the pivotal regulator during organ growth and tissue generation, has attracted increasing interests. However, the interactions between Wnt and YAP expression for neural lineage commitment of hiPSCs remain poorly explored. The objective of this study is to investigate the effects of Wnt signaling and YAP expression on the cellular population in three-dimensional (3D) neural spheroids derived from hiPSCs. In this study, Wnt signaling was activated using CHIR99021 for 3D neural spheroids derived from human iPSK3 cells through embryoid body formation. Our results indicate that Wnt activation induces nuclear localization of YAP and upregulates the expression of HOXB4, the marker for hindbrain/spinal cord. By contrast, the cells exhibit more rostral forebrain neural identity (expression of TBR1) without Wnt activation. Cytochalasin D was then used to induce cytoplasmic YAP and the results showed the decreased HOXB4 expression. In addition, the incorporation of microparticles in the neural spheroids was investigated for the perturbation of neural patterning. This study may indicate the bidirectional interactions of Wnt signaling and YAP expression during neural tissue patterning, which have the significance in neurological disease modeling, drug screening, and neural tissue regeneration.

Synaptic input correlations leading to membrane potential decorrelation of spontaneous activity in cortex.

Science.gov (United States)

Graupner, Michael; Reyes, Alex D

2013-09-18

Correlations in the spiking activity of neurons have been found in many regions of the cortex under multiple experimental conditions and are postulated to have important consequences for neural population coding. While there is a large body of extracellular data reporting correlations of various strengths, the subthreshold events underlying the origin and magnitude of signal-independent correlations (called noise or spike count correlations) are unknown. Here we investigate, using intracellular recordings, how synaptic input correlations from shared presynaptic neurons translate into membrane potential and spike-output correlations. Using a pharmacologically activated thalamocortical slice preparation, we perform simultaneous recordings from pairs of layer IV neurons in the auditory cortex of mice and measure synaptic potentials/currents, membrane potentials, and spiking outputs. We calculate cross-correlations between excitatory and inhibitory inputs to investigate correlations emerging from the network. We furthermore evaluate membrane potential correlations near resting potential to study how excitation and inhibition combine and affect spike-output correlations. We demonstrate directly that excitation is correlated with inhibition thereby partially canceling each other and resulting in weak membrane potential and spiking correlations between neurons. Our data suggest that cortical networks are set up to partially cancel correlations emerging from the connections between neurons. This active decorrelation is achieved because excitation and inhibition closely track each other. Our results suggest that the numerous shared presynaptic inputs do not automatically lead to increased spiking correlations.

Curcumin increased the differentiation rate of neurons in neural stem cells via wnt signaling in vitro study.

Science.gov (United States)

Chen, Fei; Wang, Haoxiang; Xiang, Xin; Yuan, Jichao; Chu, Weihua; Xue, Xingsen; Zhu, Haitao; Ge, Hongfei; Zou, Mingming; Feng, Hua; Lin, Jiangkai

2014-12-01

The objective of the present study was to clarify the relationship between the neuroprotective effects of curcumin and the classical wnt signaling pathway. Using Sprague-Dawley rats at a gestational age of 14.5 d, we isolated neural stem cells from the anterior two-thirds of the fetal rat brain. The neural stem cells were passaged three times using the half media replacement method and identified using cellular immunofluorescence. After passaging for three generations, we cultured cells in media without basic fibroblast growth factor and epidermal growth factor. Then we treated cells in five different ways, including a blank control group, a group treated with IWR1 (10 μmol/L), a group treated with curcumin (500 nmol/L), a group treated with IWR1 + curcumin, and a group treated with dimethyl sulfoxide (10 μmol/L). We then measured the protein and RNA expression levels for wnt3a and β-catenin using Western blotting and Reverse transcription-polymerase chain reaction (RT-PCR). Western-blotting: after the third generation of cells had been treated for 72 h, we observed that wnt3a and β-catenin expression was significantly increased in the group receiving 500 nmol/L curcumin but not in the other groups. Furthermore, cells in the IWR1-treated group showed decreased wnt3a and β-catenin expression, and wnt3a and β-catenin was also decreased in the IWR1 + 500 nmol/L curcumin group. No obvious change was observed in the dimethyl sulfoxide group. RT-PCR showed similar changes to those observed with the Western blotting experiments. Our study suggests that curcumin can activate the wnt signaling pathway, which provides evidence that curcumin exhibits a neuroprotective effect through the classical wnt signaling pathway. Copyright © 2014 Elsevier Inc. All rights reserved.

Low-dimensional recurrent neural network-based Kalman filter for speech enhancement.

Science.gov (United States)

Xia, Youshen; Wang, Jun

2015-07-01

This paper proposes a new recurrent neural network-based Kalman filter for speech enhancement, based on a noise-constrained least squares estimate. The parameters of speech signal modeled as autoregressive process are first estimated by using the proposed recurrent neural network and the speech signal is then recovered from Kalman filtering. The proposed recurrent neural network is globally asymptomatically stable to the noise-constrained estimate. Because the noise-constrained estimate has a robust performance against non-Gaussian noise, the proposed recurrent neural network-based speech enhancement algorithm can minimize the estimation error of Kalman filter parameters in non-Gaussian noise. Furthermore, having a low-dimensional model feature, the proposed neural network-based speech enhancement algorithm has a much faster speed than two existing recurrent neural networks-based speech enhancement algorithms. Simulation results show that the proposed recurrent neural network-based speech enhancement algorithm can produce a good performance with fast computation and noise reduction. Copyright © 2015 Elsevier Ltd. All rights reserved.

Ninth International Workshop on Plant Membrane Biology

Energy Technology Data Exchange (ETDEWEB)

1993-12-31

This report is a compilation of abstracts from papers which were discussed at a workshop on plant membrane biology. Topics include: plasma membrane ATP-ases; plant-environment interactions, membrane receptors; signal transduction; ion channel physiology; biophysics and molecular biology; vaculor H+ pumps; sugar carriers; membrane transport; and cellular structure and function.

A unifying mechanism accounts for sensing of membrane curvature by BAR domains, amphipathic helices and membrane-anchored proteins

DEFF Research Database (Denmark)

Bhatia, Vikram Kjøller; Hatzakis, Nikos; Stamou, Dimitrios

2010-01-01

itself. We thus anticipate that membrane curvature will promote the redistribution of proteins that are anchored in membranes through any type of hydrophobic moiety, a thesis that broadens tremendously the implications of membrane curvature for protein sorting, trafficking and signaling in cell biology....

Processing of cell-surface signalling anti-sigma factors prior to signal recognition is aconserved autoproteolytic mechanism that produces two functional domains.

NARCIS (Netherlands)

Bastiaansen, K.C.J.T.; Otero-Asman, J.R.; Luirink, J.; Bitter, W.; Llamas, M.A.

2015-01-01

Cell-surface signalling (CSS) enables Gram-negative bacteria to transduce an environmental signal into a cytosolic response. This regulatory cascade involves an outer membrane receptor that transmits the signal to an anti-sigma factor in the cytoplasmic membrane, allowing the activation of an

Melanopsin-expressing amphioxus photoreceptors transduce light via a phospholipase C signaling cascade.

Directory of Open Access Journals (Sweden)

Juan Manuel Angueyra

Full Text Available Melanopsin, the receptor molecule that underlies light sensitivity in mammalian 'circadian' receptors, is homologous to invertebrate rhodopsins and has been proposed to operate via a similar signaling pathway. Its downstream effectors, however, remain elusive. Melanopsin also expresses in two distinct light-sensitive cell types in the neural tube of amphioxus. This organism is the most basal extant chordate and can help outline the evolutionary history of different photoreceptor lineages and their transduction mechanisms; moreover, isolated amphioxus photoreceptors offer unique advantages, because they are unambiguously identifiable and amenable to single-cell physiological assays. In the present study whole-cell patch clamp recording, pharmacological manipulations, and immunodetection were utilized to investigate light transduction in amphioxus photoreceptors. A G(q was identified and selectively localized to the photosensitive microvillar membrane, while the pivotal role of phospholipase C was established pharmacologically. The photocurrent was profoundly depressed by IP₃ receptor antagonists, highlighting the importance of IP₃ receptors in light signaling. By contrast, surrogates of diacylglycerol (DAG, as well as poly-unsaturated fatty acids failed to activate a membrane conductance or to alter the light response. The results strengthen the notion that calcium released from the ER via IP₃-sensitive channels may fulfill a key role in conveying--directly or indirectly--the melanopsin-initiated light signal to the photoconductance; moreover, they challenge the dogma that microvillar photoreceptors and phoshoinositide-based light transduction are a prerogative of invertebrate eyes.

Novel membrane-based electrochemical sensor for real-time bio-applications

DEFF Research Database (Denmark)

Al Atraktchi, Fatima Al-Zahraa; Bakmand, Tanya; Dimaki, Maria

2014-01-01

This article presents a novel membrane-based sensor for real-time electrochemical investigations of cellular- or tissue cultures. The membrane sensor enables recording of electrical signals from a cell culture without any signal dilution, thus avoiding loss of sensitivity. Moreover, the porosity...... of the membrane provides optimal culturing conditions similar to existing culturing techniques allowing more efficient nutrient uptake and molecule release. The patterned sensor electrodes were fabricated on a porous membrane by electron-beam evaporation. The electrochemical performance of the membrane electrodes...

All-trans retinoic acid promotes neural lineage entry by pluripotent embryonic stem cells via multiple pathways

Directory of Open Access Journals (Sweden)

Fang Bo

2009-07-01

Full Text Available Abstract Background All-trans retinoic acid (RA is one of the most important morphogens with pleiotropic actions. Its embryonic distribution correlates with neural differentiation in the developing central nervous system. To explore the precise effects of RA on neural differentiation of mouse embryonic stem cells (ESCs, we detected expression of RA nuclear receptors and RA-metabolizing enzymes in mouse ESCs and investigated the roles of RA in adherent monolayer culture. Results Upon addition of RA, cell differentiation was directed rapidly and exclusively into the neural lineage. Conversely, pharmacological interference with RA signaling suppressed this neural differentiation. Inhibition of fibroblast growth factor (FGF signaling did not suppress significantly neural differentiation in RA-treated cultures. Pharmacological interference with extracellular signal-regulated kinase (ERK pathway or activation of Wnt pathway effectively blocked the RA-promoted neural specification. ERK phosphorylation was enhanced in RA-treated cultures at the early stage of differentiation. Conclusion RA can promote neural lineage entry by ESCs in adherent monolayer culture systems. This effect depends on RA signaling and its crosstalk with the ERK and Wnt pathways.

Energy efficient neural stimulation: coupling circuit design and membrane biophysics.

Science.gov (United States)

Foutz, Thomas J; Ackermann, D Michael; Kilgore, Kevin L; McIntyre, Cameron C

2012-01-01

The delivery of therapeutic levels of electrical current to neural tissue is a well-established treatment for numerous indications such as Parkinson's disease and chronic pain. While the neuromodulation medical device industry has experienced steady clinical growth over the last two decades, much of the core technology underlying implanted pulse generators remain unchanged. In this study we propose some new methods for achieving increased energy-efficiency during neural stimulation. The first method exploits the biophysical features of excitable tissue through the use of a centered-triangular stimulation waveform. Neural activation with this waveform is achieved with a statistically significant reduction in energy compared to traditional rectangular waveforms. The second method demonstrates energy savings that could be achieved by advanced circuitry design. We show that the traditional practice of using a fixed compliance voltage for constant-current stimulation results in substantial energy loss. A portion of this energy can be recuperated by adjusting the compliance voltage to real-time requirements. Lastly, we demonstrate the potential impact of axon fiber diameter on defining the energy-optimal pulse-width for stimulation. When designing implantable pulse generators for energy efficiency, we propose that the future combination of a variable compliance system, a centered-triangular stimulus waveform, and an axon diameter specific stimulation pulse-width has great potential to reduce energy consumption and prolong battery life in neuromodulation devices.

Energy efficient neural stimulation: coupling circuit design and membrane biophysics.

Directory of Open Access Journals (Sweden)

Thomas J Foutz

Full Text Available The delivery of therapeutic levels of electrical current to neural tissue is a well-established treatment for numerous indications such as Parkinson's disease and chronic pain. While the neuromodulation medical device industry has experienced steady clinical growth over the last two decades, much of the core technology underlying implanted pulse generators remain unchanged. In this study we propose some new methods for achieving increased energy-efficiency during neural stimulation. The first method exploits the biophysical features of excitable tissue through the use of a centered-triangular stimulation waveform. Neural activation with this waveform is achieved with a statistically significant reduction in energy compared to traditional rectangular waveforms. The second method demonstrates energy savings that could be achieved by advanced circuitry design. We show that the traditional practice of using a fixed compliance voltage for constant-current stimulation results in substantial energy loss. A portion of this energy can be recuperated by adjusting the compliance voltage to real-time requirements. Lastly, we demonstrate the potential impact of axon fiber diameter on defining the energy-optimal pulse-width for stimulation. When designing implantable pulse generators for energy efficiency, we propose that the future combination of a variable compliance system, a centered-triangular stimulus waveform, and an axon diameter specific stimulation pulse-width has great potential to reduce energy consumption and prolong battery life in neuromodulation devices.

Control of neural stem cell survival by electroactive polymer substrates.

Directory of Open Access Journals (Sweden)

Vanessa Lundin

Full Text Available Stem cell function is regulated by intrinsic as well as microenvironmental factors, including chemical and mechanical signals. Conducting polymer-based cell culture substrates provide a powerful tool to control both chemical and physical stimuli sensed by stem cells. Here we show that polypyrrole (PPy, a commonly used conducting polymer, can be tailored to modulate survival and maintenance of rat fetal neural stem cells (NSCs. NSCs cultured on PPy substrates containing different counter ions, dodecylbenzenesulfonate (DBS, tosylate (TsO, perchlorate (ClO(4 and chloride (Cl, showed a distinct correlation between PPy counter ion and cell viability. Specifically, NSC viability was high on PPy(DBS but low on PPy containing TsO, ClO(4 and Cl. On PPy(DBS, NSC proliferation and differentiation was comparable to standard NSC culture on tissue culture polystyrene. Electrical reduction of PPy(DBS created a switch for neural stem cell viability, with widespread cell death upon polymer reduction. Coating the PPy(DBS films with a gel layer composed of a basement membrane matrix efficiently prevented loss of cell viability upon polymer reduction. Here we have defined conditions for the biocompatibility of PPy substrates with NSC culture, critical for the development of devices based on conducting polymers interfacing with NSCs.

Fragile X Mental Retardation Protein Regulates Activity-Dependent Membrane Trafficking and Trans-Synaptic Signaling Mediating Synaptic Remodeling

Science.gov (United States)

Sears, James C.; Broadie, Kendal

2018-01-01

Fragile X syndrome (FXS) is the leading monogenic cause of autism and intellectual disability. The disease arises through loss of fragile X mental retardation protein (FMRP), which normally exhibits peak expression levels in early-use critical periods, and is required for activity-dependent synaptic remodeling during this transient developmental window. FMRP canonically binds mRNA to repress protein translation, with targets that regulate cytoskeleton dynamics, membrane trafficking, and trans-synaptic signaling. We focus here on recent advances emerging in these three areas from the Drosophila disease model. In the well-characterized central brain mushroom body (MB) olfactory learning/memory circuit, FMRP is required for activity-dependent synaptic remodeling of projection neurons innervating the MB calyx, with function tightly restricted to an early-use critical period. FMRP loss is phenocopied by conditional removal of FMRP only during this critical period, and rescued by FMRP conditional expression only during this critical period. Consistent with FXS hyperexcitation, FMRP loss defects are phenocopied by heightened sensory experience and targeted optogenetic hyperexcitation during this critical period. FMRP binds mRNA encoding Drosophila ESCRTIII core component Shrub (human CHMP4 homolog) to restrict Shrub translation in an activity-dependent mechanism only during this same critical period. Shrub mediates endosomal membrane trafficking, and perturbing Shrub expression is known to interfere with neuronal process pruning. Consistently, FMRP loss and Shrub overexpression targeted to projection neurons similarly causes endosomal membrane trafficking defects within synaptic boutons, and genetic reduction of Shrub strikingly rescues Drosophila FXS model defects. In parallel work on the well-characterized giant fiber (GF) circuit, FMRP limits iontophoretic dye loading into central interneurons, demonstrating an FMRP role controlling core neuronal properties through the

Complex-Valued Neural Networks

CERN Document Server

Hirose, Akira

2012-01-01

This book is the second enlarged and revised edition of the first successful monograph on complex-valued neural networks (CVNNs) published in 2006, which lends itself to graduate and undergraduate courses in electrical engineering, informatics, control engineering, mechanics, robotics, bioengineering, and other relevant fields. In the second edition the recent trends in CVNNs research are included, resulting in e.g. almost a doubled number of references. The parametron invented in 1954 is also referred to with discussion on analogy and disparity. Also various additional arguments on the advantages of the complex-valued neural networks enhancing the difference to real-valued neural networks are given in various sections. The book is useful for those beginning their studies, for instance, in adaptive signal processing for highly functional sensing and imaging, control in unknown and changing environment, robotics inspired by human neural systems, and brain-like information processing, as well as interdisciplina...

Differential roles of AVP and VIP signaling in the postnatal changes of neural networks for coherent circadian rhythms in the SCN

Science.gov (United States)

Ono, Daisuke; Honma, Sato; Honma, Ken-ichi

2016-01-01

The suprachiasmatic nucleus (SCN) is the site of the master circadian clock in mammals. The SCN neural network plays a critical role in expressing the tissue-level circadian rhythm. Previously, we demonstrated postnatal changes in the SCN network in mice, in which the clock gene products CRYPTOCHROMES (CRYs) are involved. Here, we show that vasoactive intestinal polypeptide (VIP) signaling is essential for the tissue-level circadian PER2::LUC rhythm in the neonatal SCN of CRY double-deficient mice (Cry1,2−/−). VIP and arginine vasopressin (AVP) signaling showed redundancy in expressing the tissue-level circadian rhythm in the SCN. AVP synthesis was significantly attenuated in the Cry1,2−/− SCN, which contributes to aperiodicity in the adult mice together with an attenuation of VIP signaling as a natural process of ontogeny. The SCN network consists of multiple clusters of cellular circadian rhythms that are differentially integrated by AVP and VIP signaling, depending on the postnatal period. PMID:27626074

Classification of a Driver's cognitive workload levels using artificial neural network on ECG signals.

Science.gov (United States)

Tjolleng, Amir; Jung, Kihyo; Hong, Wongi; Lee, Wonsup; Lee, Baekhee; You, Heecheon; Son, Joonwoo; Park, Seikwon

2017-03-01

An artificial neural network (ANN) model was developed in the present study to classify the level of a driver's cognitive workload based on electrocardiography (ECG). ECG signals were measured on 15 male participants while they performed a simulated driving task as a primary task with/without an N-back task as a secondary task. Three time-domain ECG measures (mean inter-beat interval (IBI), standard deviation of IBIs, and root mean squared difference of adjacent IBIs) and three frequencydomain ECG measures (power in low frequency, power in high frequency, and ratio of power in low and high frequencies) were calculated. To compensate for individual differences in heart response during the driving tasks, a three-step data processing procedure was performed to ECG signals of each participant: (1) selection of two most sensitive ECG measures, (2) definition of three (low, medium, and high) cognitive workload levels, and (3) normalization of the selected ECG measures. An ANN model was constructed using a feed-forward network and scaled conjugate gradient as a back-propagation learning rule. The accuracy of the ANN classification model was found satisfactory for learning data (95%) and testing data (82%). Copyright © 2016 Elsevier Ltd. All rights reserved.

INTERLEUKIN-6 TRANS-SIGNALING SYSTEM IN INTRA-AMNIOTIC INFLAMMATION, PRETERM BIRTH AND PRETERM PREMATURE RUPTURE OF THE MEMBRANES

Science.gov (United States)

Lee, Sarah Y.; Buhimschi, Irina A.; Dulay, Antonette T.; Ali, Unzila A.; Zhao, Guomao; Abdel-Razeq, Sonya S.; Bahtiyar, Mert O.; Thung, Stephen F.; Funai, Edmund F.; Buhimschi, Catalin S.

2013-01-01

Classic IL-6 signaling is conditioned by the transmembrane receptor (IL-6R) and homodimerization of gp130. During trans-signaling, IL-6 binds to soluble IL-6R (sIL-6R) enabling activation of cells expressing solely gp130. Soluble gp130 (sgp130) selectively inhibits IL-6 trans-signaling. To characterize amniotic fluid IL-6 trans-signaling molecules (IL-6, sIL-6R, sgp130) in normal gestations and pregnancies complicated by intra-amniotic inflammation (IAI) we studied 301 women during second trimester (n=39), third trimester (n=40) and preterm labor with intact (n=131, 85 IAI negative & 46 IAI positive) or preterm premature rupture of membranes (PPROM: n=91, 61 IAI negative & 30 IAI positive). ELISA, Western blotting and RT-PCR were used to investigate amniotic fluid, placenta and amniochorion for protein and mRNA expression of sIL-6R, sgp130, IL-6R and gp130. Tissues were immunostained for IL-6R, gp130, CD15+ (polymorphonuclear) and CD3+ (T-cell) inflammatory cells. The ability of sIL-6R and sgp130 to modulate basal and LPS-stimulated release of amniochorion matrix-metalloprotease-9 (MMP-9) was tested ex-vivo. We showed that in physiologic gestations amniotic fluid sgp130 decreases toward term. Amniotic fluid IL-6 and sIL-6R were elevated in IAI whereas sgp130 was decreased in PPROM. Our results suggested that fetal membranes are the probable source of amniotic fluid sIL-6R and sgp130. Immunohistochemistry and RT-PCR revealed increased IL-6R and decreased gp130 expression in amniochorion of women with IAI. Ex-vivo, sIL-6R and LPS augmented amniochorion MMP-9 release whereas sgp130 opposed this effect. We conclude that IL-6 trans-signaling molecules are physiologic constituents of the amniotic fluid regulated by gestational age and inflammation. PPROM likely involves functional loss of sgp130. PMID:21282511

IL-6 trans-signaling system in intra-amniotic inflammation, preterm birth, and preterm premature rupture of the membranes.

Science.gov (United States)

Lee, Sarah Y; Buhimschi, Irina A; Dulay, Antonette T; Ali, Unzila A; Zhao, Guomao; Abdel-Razeq, Sonya S; Bahtiyar, Mert O; Thung, Stephen F; Funai, Edmund F; Buhimschi, Catalin S

2011-03-01

Classic IL-6 signaling is conditioned by the transmembrane receptor (IL-6R) and homodimerization of gp130. During trans-signaling, IL-6 binds to soluble IL-6R (sIL-6R), enabling activation of cells expressing solely gp130. Soluble gp130 (sgp130) selectively inhibits IL-6 trans-signaling. To characterize amniotic fluid (AF) IL-6 trans-signaling molecules (IL-6, sIL-6R, sgp130) in normal gestations and pregnancies complicated by intra-amniotic inflammation (IAI), we studied 301 women during second trimester (n = 39), third trimester (n = 40), and preterm labor with intact (n = 131, 85 negative IAI and 46 positive IAI) or preterm premature rupture of membranes (PPROM; n = 91, 61 negative IAI and 30 positive IAI). ELISA, Western blotting, and real-time RT-PCR were used to investigate AF, placenta, and amniochorion for protein and mRNA expression of sIL-6R, sgp130, IL-6R, and gp130. Tissues were immunostained for IL-6R, gp130, CD15(+) (polymorphonuclear), and CD3(+) (T cell) inflammatory cells. The ability of sIL-6R and sgp130 to modulate basal and LPS-stimulated release of amniochorion matrix metalloprotease-9 was tested ex vivo. We showed that in physiologic gestations, AF sgp130 decreases toward term. AF IL-6 and sIL-6R were increased in IAI, whereas sgp130 was decreased in PPROM. Our results suggested that fetal membranes are the probable source of AF sIL-6R and sgp130. Immunohistochemistry and RT-PCR revealed increased IL-6R and decreased gp130 expression in amniochorion of women with IAI. Ex vivo, sIL-6R and LPS augmented amniochorion matrix metalloprotease-9 release, whereas sgp130 opposed this effect. We conclude that IL-6 trans-signaling molecules are physiologic constituents of the AF regulated by gestational age and inflammation. PPROM likely involves functional loss of sgp130.

Shuttling of G protein subunits between the plasma membrane and intracellular membranes.

Science.gov (United States)

Chisari, Mariangela; Saini, Deepak Kumar; Kalyanaraman, Vani; Gautam, Narasimhan

2007-08-17

Heterotrimeric G proteins (alphabetagamma) mediate the majority of signaling pathways in mammalian cells. It is long held that G protein function is localized to the plasma membrane. Here we examined the spatiotemporal dynamics of G protein localization using fluorescence recovery after photobleaching, fluorescence loss in photobleaching, and a photoswitchable fluorescent protein, Dronpa. Unexpectedly, G protein subunits shuttle rapidly (t1/2 plasma membrane and intracellular membranes. We show that consistent with such shuttling, G proteins constitutively reside in endomembranes. Furthermore, we show that shuttling is inhibited by 2-bromopalmitate. Thus, contrary to present thought, G proteins do not reside permanently on the plasma membrane but are constantly testing the cytoplasmic surfaces of the plasma membrane and endomembranes to maintain G protein pools in intracellular membranes to establish direct communication between receptors and endomembranes.

Wet gas metering with the v-cone and neural nets

Energy Technology Data Exchange (ETDEWEB)

Toral, Haluk; Cai, Shiqian; Peters, Robert

2005-07-01

The paper presents analysis of extensive measurements taken at NEL, K-Lab and CEESI wet gas test loops. Differential and absolute pressure signals were sampled at high frequency across V-Cone meters. Turbulence characteristics of the flow captured in the sampled signals were characterized by pattern recognition techniques and related to the fractions and flow rates of individual phases. The sensitivity of over-reading to first and higher order features of the high frequency signals were investigated qualitatively. The sensitivities were quantified by means of the saliency test based on back propagating neural nets. A self contained wet gas meter based on neural net characterization of first and higher order features of the pressure, differential pressure and capacitance signals was proposed. Alternatively, a wet gas meter based on a neural net model of just pressure sensor inputs (based on currently available data) and liquid Froude number was shown to offer an accuracy of under 5% if the Froude number could be estimated with 25% accuracy. (author) (tk)

Meninges: from protective membrane to stem cell niche

OpenAIRE

Decimo, Ilaria; Fumagalli, Guido; Berton, Valeria; Krampera, Mauro; Bifari, Francesco

2012-01-01

Meninges are a three tissue membrane primarily known as coverings of the brain. More in depth studies on meningeal function and ultrastructure have recently changed the view of meninges as a merely protective membrane. Accurate evaluation of the anatomical distribution in the CNS reveals that meninges largely penetrate inside the neural tissue. Meninges enter the CNS by projecting between structures, in the stroma of choroid plexus and form the perivascular space (Virchow-Robin) of every pare...

Augmented BMPRIA-mediated BMP signaling in cranial neural crest lineage leads to cleft palate formation and delayed tooth differentiation.

Directory of Open Access Journals (Sweden)

Lu Li

Full Text Available The importance of BMP receptor Ia (BMPRIa mediated signaling in the development of craniofacial organs, including the tooth and palate, has been well illuminated in several mouse models of loss of function, and by its mutations associated with juvenile polyposis syndrome and facial defects in humans. In this study, we took a gain-of-function approach to further address the role of BMPR-IA-mediated signaling in the mesenchymal compartment during tooth and palate development. We generated transgenic mice expressing a constitutively active form of BmprIa (caBmprIa in cranial neural crest (CNC cells that contributes to the dental and palatal mesenchyme. Mice bearing enhanced BMPRIa-mediated signaling in CNC cells exhibit complete cleft palate and delayed odontogenic differentiation. We showed that the cleft palate defect in the transgenic animals is attributed to an altered cell proliferation rate in the anterior palatal mesenchyme and to the delayed palatal elevation in the posterior portion associated with ectopic cartilage formation. Despite enhanced activity of BMP signaling in the dental mesenchyme, tooth development and patterning in transgenic mice appeared normal except delayed odontogenic differentiation. These data support the hypothesis that a finely tuned level of BMPRIa-mediated signaling is essential for normal palate and tooth development.

Sample Entropy Analysis of EEG Signals via Artificial Neural Networks to Model Patients’ Consciousness Level Based on Anesthesiologists Experience

Directory of Open Access Journals (Sweden)

George J. A. Jiang

2015-01-01

Full Text Available Electroencephalogram (EEG signals, as it can express the human brain’s activities and reflect awareness, have been widely used in many research and medical equipment to build a noninvasive monitoring index to the depth of anesthesia (DOA. Bispectral (BIS index monitor is one of the famous and important indicators for anesthesiologists primarily using EEG signals when assessing the DOA. In this study, an attempt is made to build a new indicator using EEG signals to provide a more valuable reference to the DOA for clinical researchers. The EEG signals are collected from patients under anesthetic surgery which are filtered using multivariate empirical mode decomposition (MEMD method and analyzed using sample entropy (SampEn analysis. The calculated signals from SampEn are utilized to train an artificial neural network (ANN model through using expert assessment of consciousness level (EACL which is assessed by experienced anesthesiologists as the target to train, validate, and test the ANN. The results that are achieved using the proposed system are compared to BIS index. The proposed system results show that it is not only having similar characteristic to BIS index but also more close to experienced anesthesiologists which illustrates the consciousness level and reflects the DOA successfully.

Learning Data Set Influence on Identification Accuracy of Gas Turbine Neural Network Model

Science.gov (United States)

Kuznetsov, A. V.; Makaryants, G. M.

2018-01-01

There are many gas turbine engine identification researches via dynamic neural network models. It should minimize errors between model and real object during identification process. Questions about training data set processing of neural networks are usually missed. This article presents a study about influence of data set type on gas turbine neural network model accuracy. The identification object is thermodynamic model of micro gas turbine engine. The thermodynamic model input signal is the fuel consumption and output signal is the engine rotor rotation frequency. Four types input signals was used for creating training and testing data sets of dynamic neural network models - step, fast, slow and mixed. Four dynamic neural networks were created based on these types of training data sets. Each neural network was tested via four types test data sets. In the result 16 transition processes from four neural networks and four test data sets from analogous solving results of thermodynamic model were compared. The errors comparison was made between all neural network errors in each test data set. In the comparison result it was shown error value ranges of each test data set. It is shown that error values ranges is small therefore the influence of data set types on identification accuracy is low.

Event-driven processing for hardware-efficient neural spike sorting

Science.gov (United States)

Liu, Yan; Pereira, João L.; Constandinou, Timothy G.

2018-02-01

Objective. The prospect of real-time and on-node spike sorting provides a genuine opportunity to push the envelope of large-scale integrated neural recording systems. In such systems the hardware resources, power requirements and data bandwidth increase linearly with channel count. Event-based (or data-driven) processing can provide here a new efficient means for hardware implementation that is completely activity dependant. In this work, we investigate using continuous-time level-crossing sampling for efficient data representation and subsequent spike processing. Approach. (1) We first compare signals (synthetic neural datasets) encoded with this technique against conventional sampling. (2) We then show how such a representation can be directly exploited by extracting simple time domain features from the bitstream to perform neural spike sorting. (3) The proposed method is implemented in a low power FPGA platform to demonstrate its hardware viability. Main results. It is observed that considerably lower data rates are achievable when using 7 bits or less to represent the signals, whilst maintaining the signal fidelity. Results obtained using both MATLAB and reconfigurable logic hardware (FPGA) indicate that feature extraction and spike sorting accuracies can be achieved with comparable or better accuracy than reference methods whilst also requiring relatively low hardware resources. Significance. By effectively exploiting continuous-time data representation, neural signal processing can be achieved in a completely event-driven manner, reducing both the required resources (memory, complexity) and computations (operations). This will see future large-scale neural systems integrating on-node processing in real-time hardware.

The challenges of neural mind-reading paradigms

OpenAIRE

Vilarroya, Oscar

2013-01-01

Neural mind-reading studies, based on multivariate pattern analysis (MVPA) methods, are providing exciting new studies. Some of the results obtained with these paradigms have raised high expectations, such as the possibility of creating brain reading devices. However, such hopes are based on the assumptions that: (a) the BOLD signal is a marker of neural activity; (b) the BOLD pattern identified by a MVPA is a neurally sound pattern; (c) the MVPA's feature space is a good mapping of the neura...

More About Thin-Membrane Biosensor

Science.gov (United States)

Case, George D.; Worley, Jennings F., III

1994-01-01

Report presents additional information about device described in "Thin-Membrane Sensor With Biochemical Switch" (MFS-26121). Device is modular sensor that puts out electrical signal indicative of chemical or biological agent. Signal produced as membrane-crossing ion current triggered by chemical reaction between agent and recognition protein conjugated to channel blocker. Prototype of biosensor useful in numerous laboratory, industrial, or field applications; such as to detect bacterial toxins in food, to screen for disease-producing micro-organisms, or to warn of toxins or pollutants in air.

3D silicon neural probe with integrated optical fibers for optogenetic modulation.

Science.gov (United States)

Kim, Eric G R; Tu, Hongen; Luo, Hao; Liu, Bin; Bao, Shaowen; Zhang, Jinsheng; Xu, Yong

2015-07-21

Optogenetics is a powerful modality for neural modulation that can be useful for a wide array of biomedical studies. Penetrating microelectrode arrays provide a means of recording neural signals with high spatial resolution. It is highly desirable to integrate optics with neural probes to allow for functional study of neural tissue by optogenetics. In this paper, we report the development of a novel 3D neural probe coupled simply and robustly to optical fibers using a hollow parylene tube structure. The device shanks are hollow tubes with rigid silicon tips, allowing the insertion and encasement of optical fibers within the shanks. The position of the fiber tip can be precisely controlled relative to the electrodes on the shank by inherent design features. Preliminary in vivo rat studies indicate that these devices are capable of optogenetic modulation simultaneously with 3D neural signal recording.

Transcriptional Profiling of Hypoxic Neural Stem Cells Identifies Calcineurin-NFATc4 Signaling as a Major Regulator of Neural Stem Cell Biology

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Moreno, Marta; Fernández, Virginia; Monllau, Josep M.; Borrell, Víctor; Lerin, Carles; de la Iglesia, Núria

2015-01-01

Summary Neural stem cells (NSCs) reside in a hypoxic microenvironment within the brain. However, the crucial transcription factors (TFs) that regulate NSC biology under physiologic hypoxia are poorly understood. Here we have performed gene set enrichment analysis (GSEA) of microarray datasets from hypoxic versus normoxic NSCs with the aim of identifying pathways and TFs that are activated under oxygen concentrations mimicking normal brain tissue microenvironment. Integration of TF target (TFT) and pathway enrichment analysis identified the calcium-regulated TF NFATc4 as a major candidate to regulate hypoxic NSC functions. Nfatc4 expression was coordinately upregulated by top hypoxia-activated TFs, while NFATc4 target genes were enriched in hypoxic NSCs. Loss-of-function analyses further revealed that the calcineurin-NFATc4 signaling axis acts as a major regulator of NSC self-renewal and proliferation in vitro and in vivo by promoting the expression of TFs, including Id2, that contribute to the maintenance of the NSC state. PMID:26235896

Orientation Encoding and Viewpoint Invariance in Face Recognition: Inferring Neural Properties from Large-Scale Signals.

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Ramírez, Fernando M

2018-05-01

Viewpoint-invariant face recognition is thought to be subserved by a distributed network of occipitotemporal face-selective areas that, except for the human anterior temporal lobe, have been shown to also contain face-orientation information. This review begins by highlighting the importance of bilateral symmetry for viewpoint-invariant recognition and face-orientation perception. Then, monkey electrophysiological evidence is surveyed describing key tuning properties of face-selective neurons-including neurons bimodally tuned to mirror-symmetric face-views-followed by studies combining functional magnetic resonance imaging (fMRI) and multivariate pattern analyses to probe the representation of face-orientation and identity information in humans. Altogether, neuroimaging studies suggest that face-identity is gradually disentangled from face-orientation information along the ventral visual processing stream. The evidence seems to diverge, however, regarding the prevalent form of tuning of neural populations in human face-selective areas. In this context, caveats possibly leading to erroneous inferences regarding mirror-symmetric coding are exposed, including the need to distinguish angular from Euclidean distances when interpreting multivariate pattern analyses. On this basis, this review argues that evidence from the fusiform face area is best explained by a view-sensitive code reflecting head angular disparity, consistent with a role of this area in face-orientation perception. Finally, the importance is stressed of explicit models relating neural properties to large-scale signals.

Is the C-terminal insertional signal in Gram-negative bacterial outer membrane proteins species-specific or not?

Directory of Open Access Journals (Sweden)

Paramasivam Nagarajan

2012-09-01

Full Text Available Abstract Background In Gram-negative bacteria, the outer membrane is composed of an asymmetric lipid bilayer of phopspholipids and lipopolysaccharides, and the transmembrane proteins that reside in this membrane are almost exclusively β-barrel proteins. These proteins are inserted into the membrane by a highly conserved and essential machinery, the BAM complex. It recognizes its substrates, unfolded outer membrane proteins (OMPs, through a C-terminal motif that has been speculated to be species-specific, based on theoretical and experimental results from only two species, Escherichia coli and Neisseria meningitidis, where it was shown on the basis of individual sequences and motifs that OMPs from the one cannot easily be over expressed in the other, unless the C-terminal motif was adapted. In order to determine whether this species specificity is a general phenomenon, we undertook a large-scale bioinformatics study on all predicted OMPs from 437 fully sequenced proteobacterial strains. Results We were able to verify the incompatibility reported between Escherichia coli and Neisseria meningitidis, using clustering techniques based on the pairwise Hellinger distance between sequence spaces for the C-terminal motifs of individual organisms. We noticed that the amino acid position reported to be responsible for this incompatibility between Escherichia coli and Neisseria meningitidis does not play a major role for determining species specificity of OMP recognition by the BAM complex. Instead, we found that the signal is more diffuse, and that for most organism pairs, the difference between the signals is hard to detect. Notable exceptions are the Neisseriales, and Helicobacter spp. For both of these organism groups, we describe the specific sequence requirements that are at the basis of the observed difference. Conclusions Based on the finding that the differences between the recognition motifs of almost all organisms are small, we assume that

Fault diagnosis system of electromagnetic valve using neural network filter

International Nuclear Information System (INIS)

Hayashi, Shoji; Odaka, Tomohiro; Kuroiwa, Jousuke; Ogura, Hisakazu

2008-01-01

This paper is concerned with the gas leakage fault detection of electromagnetic valve using a neural network filter. In modern plants, the ability to detect and identify gas leakage faults is becoming increasingly important. The main difficulty in detecting gas leakage faults by sound signals lies in the fact that the practical plants are usually very noisy. To solve this difficulty, a neural network filter is used to eliminate background noise and raise the signal noise ratio of the sound signal. The background noise is assumed as a dynamic system, and an accurate mathematical model of the dynamic system can be established using a neural network filter. The predicted error between predicted values and practical ones constitutes the output of the filter. If the predicted error is zero, then there is no leakage. If the predicted error is greater than a certain value, then there is a leakage fault. Through application to practical pneumatic systems, it is verified that the neural network filter was effective in gas leakage detection. (author)

Signal analysis for failure detection

International Nuclear Information System (INIS)

Parpaglione, M.C.; Perez, L.V.; Rubio, D.A.; Czibener, D.; D'Attellis, C.E.; Brudny, P.I.; Ruzzante, J.E.

1994-01-01

Several methods for analysis of acoustic emission signals are presented. They are mainly oriented to detection of changes in noisy signals and characterization of higher amplitude discrete pulses or bursts. The aim was to relate changes and events with failure, crack or wear in materials, being the final goal to obtain automatic means of detecting such changes and/or events. Performance evaluation was made using both simulated and laboratory test signals. The methods being presented are the following: 1. Application of the Hopfield Neural Network (NN) model for classifying faults in pipes and detecting wear of a bearing. 2. Application of the Kohonnen and Back Propagation Neural Network model for the same problem. 3. Application of Kalman filtering to determine time occurrence of bursts. 4. Application of a bank of Kalman filters (KF) for failure detection in pipes. 5. Study of amplitude distribution of signals for detecting changes in their shape. 6. Application of the entropy distance to measure differences between signals. (author). 10 refs, 11 figs

Membrane Lipid Oscillation: An Emerging System of Molecular Dynamics in the Plant Membrane.

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Nakamura, Yuki

2018-03-01

Biological rhythm represents a major biological process of living organisms. However, rhythmic oscillation of membrane lipid content is poorly described in plants. The development of lipidomic technology has led to the illustration of precise molecular profiles of membrane lipids under various growth conditions. Compared with conventional lipid signaling, which produces unpredictable lipid changes in response to ever-changing environmental conditions, lipid oscillation generates a fairly predictable lipid profile, adding a new layer of biological function to the membrane system and possible cross-talk with the other chronobiological processes. This mini review covers recent studies elucidating membrane lipid oscillation in plants.

Plasma Membrane CRPK1-Mediated Phosphorylation of 14-3-3 Proteins Induces Their Nuclear Import to Fine-Tune CBF Signaling during Cold Response.

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Liu, Ziyan; Jia, Yuxin; Ding, Yanglin; Shi, Yiting; Li, Zhen; Guo, Yan; Gong, Zhizhong; Yang, Shuhua

2017-04-06

In plant cells, changes in fluidity of the plasma membrane may serve as the primary sensor of cold stress; however, the precise mechanism and how the cell transduces and fine-tunes cold signals remain elusive. Here we show that the cold-activated plasma membrane protein cold-responsive protein kinase 1 (CRPK1) phosphorylates 14-3-3 proteins. The phosphorylated 14-3-3 proteins shuttle from the cytosol to the nucleus, where they interact with and destabilize the key cold-responsive C-repeat-binding factor (CBF) proteins. Consistent with this, the crpk1 and 14-3-3κλ mutants show enhanced freezing tolerance, and transgenic plants overexpressing 14-3-3λ show reduced freezing tolerance. Further study shows that CRPK1 is essential for the nuclear translocation of 14-3-3 proteins and for 14-3-3 function in freezing tolerance. Thus, our study reveals that the CRPK1-14-3-3 module transduces the cold signal from the plasma membrane to the nucleus to modulate CBF stability, which ensures a faithfully adjusted response to cold stress of plants. Copyright © 2017 Elsevier Inc. All rights reserved.

Activation of interfacial enzymes at membrane surfaces

DEFF Research Database (Denmark)

Mouritsen, Ole G.; Andresen, Thomas Lars; Halperin, Avi

2006-01-01

A host of water-soluble enzymes are active at membrane surfaces and in association with membranes. Some of these enzymes are involved in signalling and in modification and remodelling of the membranes. A special class of enzymes, the phospholipases, and in particular secretory phospholipase A2 (s...

Continuous detection of weak sensory signals in afferent spike trains: the role of anti-correlated interspike intervals in detection performance.

Science.gov (United States)

Goense, J B M; Ratnam, R

2003-10-01

An important problem in sensory processing is deciding whether fluctuating neural activity encodes a stimulus or is due to variability in baseline activity. Neurons that subserve detection must examine incoming spike trains continuously, and quickly and reliably differentiate signals from baseline activity. Here we demonstrate that a neural integrator can perform continuous signal detection, with performance exceeding that of trial-based procedures, where spike counts in signal- and baseline windows are compared. The procedure was applied to data from electrosensory afferents of weakly electric fish (Apteronotus leptorhynchus), where weak perturbations generated by small prey add approximately 1 spike to a baseline of approximately 300 spikes s(-1). The hypothetical postsynaptic neuron, modeling an electrosensory lateral line lobe cell, could detect an added spike within 10-15 ms, achieving near ideal detection performance (80-95%) at false alarm rates of 1-2 Hz, while trial-based testing resulted in only 30-35% correct detections at that false alarm rate. The performance improvement was due to anti-correlations in the afferent spike train, which reduced both the amplitude and duration of fluctuations in postsynaptic membrane activity, and so decreased the number of false alarms. Anti-correlations can be exploited to improve detection performance only if there is memory of prior decisions.

Model-based Bayesian signal extraction algorithm for peripheral nerves

Science.gov (United States)

Eggers, Thomas E.; Dweiri, Yazan M.; McCallum, Grant A.; Durand, Dominique M.

2017-10-01

Objective. Multi-channel cuff electrodes have recently been investigated for extracting fascicular-level motor commands from mixed neural recordings. Such signals could provide volitional, intuitive control over a robotic prosthesis for amputee patients. Recent work has demonstrated success in extracting these signals in acute and chronic preparations using spatial filtering techniques. These extracted signals, however, had low signal-to-noise ratios and thus limited their utility to binary classification. In this work a new algorithm is proposed which combines previous source localization approaches to create a model based method which operates in real time. Approach. To validate this algorithm, a saline benchtop setup was created to allow the precise placement of artificial sources within a cuff and interference sources outside the cuff. The artificial source was taken from five seconds of chronic neural activity to replicate realistic recordings. The proposed algorithm, hybrid Bayesian signal extraction (HBSE), is then compared to previous algorithms, beamforming and a Bayesian spatial filtering method, on this test data. An example chronic neural recording is also analyzed with all three algorithms. Main results. The proposed algorithm improved the signal to noise and signal to interference ratio of extracted test signals two to three fold, as well as increased the correlation coefficient between the original and recovered signals by 10-20%. These improvements translated to the chronic recording example and increased the calculated bit rate between the recovered signals and the recorded motor activity. Significance. HBSE significantly outperforms previous algorithms in extracting realistic neural signals, even in the presence of external noise sources. These results demonstrate the feasibility of extracting dynamic motor signals from a multi-fascicled intact nerve trunk, which in turn could extract motor command signals from an amputee for the end goal of

Application of Artificial Neural Networks in the Heart Electrical Axis Position Conclusion Modeling

Science.gov (United States)

Bakanovskaya, L. N.

2016-08-01

The article touches upon building of a heart electrical axis position conclusion model using an artificial neural network. The input signals of the neural network are the values of deflections Q, R and S; and the output signal is the value of the heart electrical axis position. Training of the network is carried out by the error propagation method. The test results allow concluding that the created neural network makes a conclusion with a high degree of accuracy.

Neural network for recognizing signal-shape of nuclear detector output

International Nuclear Information System (INIS)

Mardiyanto M Panitra

2006-01-01

The use of artificial intelligent technique in the engineering field has been familiar especially in the field of pattern recognition. By using this technique, either simple routine works or complicated routine works can be done by the help of a digital camera and a personal computer. One of the complicated works that can not be solved easily is how to separate two kinds of nuclear radiation types which are mixed in the same field. The separation of the two kinds of radiation become is very important for the radiation dosimetry purposes. For doing this we have carried out a preliminary research in applying a neural network technique for recognizing C and T letters with right, left, up, and down positions. We arranged a three-layer neural network i.e. input layer (9 neurons with/without bias neuron), hidden layer (11 neurons), and output layer (1 neuron). From this preliminary study the use of a bias neuron gave faster learning process compared with the one without the bias neuron. The neural network could work successfully in determining the letter S and T without any mistake. (author)

KSHV Entry and Trafficking in Target Cells—Hijacking of Cell Signal Pathways, Actin and Membrane Dynamics

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Binod Kumar

2016-11-01

Full Text Available Kaposi’s sarcoma associated herpesvirus (KSHV is etiologically associated with human endothelial cell hyperplastic Kaposi’s sarcoma and B-cell primary effusion lymphoma. KSHV infection of adherent endothelial and fibroblast cells are used as in vitro models for infection and KSHV enters these cells by host membrane bleb and actin mediated macropinocytosis or clathrin endocytosis pathways, respectively. Infection in endothelial and fibroblast cells is initiated by the interactions between multiple viral envelope glycoproteins and cell surface associated heparan sulfate (HS, integrins (α3β1, αVβ3 and αVβ5, and EphA2 receptor tyrosine kinase (EphA2R. This review summarizes the accumulated studies demonstrating that KSHV manipulates the host signal pathways to enter and traffic in the cytoplasm of the target cells, to deliver the viral genome into the nucleus, and initiate viral gene expression. KSHV interactions with the cell surface receptors is the key platform for the manipulations of host signal pathways which results in the simultaneous induction of FAK, Src, PI3-K, Rho-GTPase, ROS, Dia-2, PKC ζ, c-Cbl, CIB1, Crk, p130Cas and GEF-C3G signal and adaptor molecules that play critical roles in the modulation of membrane and actin dynamics, and in the various steps of the early stages of infection such as entry and trafficking towards the nucleus. The Endosomal Sorting Complexes Required for Transport (ESCRT proteins are also recruited to assist in viral entry and trafficking. In addition, KSHV interactions with the cell surface receptors also induces the host transcription factors NF-κB, ERK1/2, and Nrf2 early during infection to initiate and modulate viral and host gene expression. Nuclear delivery of the viral dsDNA genome is immediately followed by the host innate responses such as the DNA damage response (DDR, inflammasome and interferon responses. Overall, these studies form the initial framework for further studies of

Neurosecurity: security and privacy for neural devices.

Science.gov (United States)

Denning, Tamara; Matsuoka, Yoky; Kohno, Tadayoshi

2009-07-01

An increasing number of neural implantable devices will become available in the near future due to advances in neural engineering. This discipline holds the potential to improve many patients' lives dramatically by offering improved-and in some cases entirely new-forms of rehabilitation for conditions ranging from missing limbs to degenerative cognitive diseases. The use of standard engineering practices, medical trials, and neuroethical evaluations during the design process can create systems that are safe and that follow ethical guidelines; unfortunately, none of these disciplines currently ensure that neural devices are robust against adversarial entities trying to exploit these devices to alter, block, or eavesdrop on neural signals. The authors define "neurosecurity"-a version of computer science security principles and methods applied to neural engineering-and discuss why neurosecurity should be a critical consideration in the design of future neural devices.

Optimization of a neural network model for signal-to-background prediction in gamma-ray spectrometry

International Nuclear Information System (INIS)

Dragovic, S.; Onjia, A. . E-mail address of corresponding author: sdragovic@inep.co.yu; Dragovic, S.)

2005-01-01

The artificial neural network (ANN) model was optimized for the prediction of signal-to-background (SBR) ratio as a function of the measurement time in gamma-ray spectrometry. The network parameters: learning rate (α), momentum (μ), number of epochs (E) and number of nodes in hidden layer (N) were optimized simultaneously employing variable-size simplex method. The most accurate model with the root mean square (RMS) error of 0.073 was obtained using ANN with online backpropagation randomized (OBPR) algorithm with α = 0.27, μ 0.36, E = 14800 and N = 9. Most of the predicted and experimental SBR values for the eight radionuclides ( 226 Ra, 214 Bi, 235 U, 40 K, 232 Th, 134 Cs, 137 Cs and 7 Be), studied in this work, reasonably agreed to within 15 %, which was satisfactory accuracy. (author)

Energy-efficient neural information processing in individual neurons and neuronal networks.

Science.gov (United States)

Yu, Lianchun; Yu, Yuguo

2017-11-01

Brains are composed of networks of an enormous number of neurons interconnected with synapses. Neural information is carried by the electrical signals within neurons and the chemical signals among neurons. Generating these electrical and chemical signals is metabolically expensive. The fundamental issue raised here is whether brains have evolved efficient ways of developing an energy-efficient neural code from the molecular level to the circuit level. Here, we summarize the factors and biophysical mechanisms that could contribute to the energy-efficient neural code for processing input signals. The factors range from ion channel kinetics, body temperature, axonal propagation of action potentials, low-probability release of synaptic neurotransmitters, optimal input and noise, the size of neurons and neuronal clusters, excitation/inhibition balance, coding strategy, cortical wiring, and the organization of functional connectivity. Both experimental and computational evidence suggests that neural systems may use these factors to maximize the efficiency of energy consumption in processing neural signals. Studies indicate that efficient energy utilization may be universal in neuronal systems as an evolutionary consequence of the pressure of limited energy. As a result, neuronal connections may be wired in a highly economical manner to lower energy costs and space. Individual neurons within a network may encode independent stimulus components to allow a minimal number of neurons to represent whole stimulus characteristics efficiently. This basic principle may fundamentally change our view of how billions of neurons organize themselves into complex circuits to operate and generate the most powerful intelligent cognition in nature. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Agent-specific learning signals for self-other distinction during mentalising.

Directory of Open Access Journals (Sweden)

Sam Ereira

2018-04-01

Full Text Available Humans have a remarkable ability to simulate the minds of others. How the brain distinguishes between mental states attributed to self and mental states attributed to someone else is unknown. Here, we investigated how fundamental neural learning signals are selectively attributed to different agents. Specifically, we asked whether learning signals are encoded in agent-specific neural patterns or whether a self-other distinction depends on encoding agent identity separately from this learning signal. To examine this, we tasked subjects to learn continuously 2 models of the same environment, such that one was selectively attributed to self and the other was selectively attributed to another agent. Combining computational modelling with magnetoencephalography (MEG enabled us to track neural representations of prediction errors (PEs and beliefs attributed to self, and of simulated PEs and beliefs attributed to another agent. We found that the representational pattern of a PE reliably predicts the identity of the agent to whom the signal is attributed, consistent with a neural self-other distinction implemented via agent-specific learning signals. Strikingly, subjects exhibiting a weaker neural self-other distinction also had a reduced behavioural capacity for self-other distinction and displayed more marked subclinical psychopathological traits. The neural self-other distinction was also modulated by social context, evidenced in a significantly reduced decoding of agent identity in a nonsocial control task. Thus, we show that self-other distinction is realised through an encoding of agent identity intrinsic to fundamental learning signals. The observation that the fidelity of this encoding predicts psychopathological traits is of interest as a potential neurocomputational psychiatric biomarker.

Analysis of Protein-Membrane Interactions

DEFF Research Database (Denmark)

Kemmer, Gerdi Christine

Cellular membranes are complex structures, consisting of hundreds of different lipids and proteins. These membranes act as barriers between distinct environments, constituting hot spots for many essential functions of the cell, including signaling, energy conversion, and transport. These functions....... Discovered interactions were then probed on the level of the membrane using liposome-based assays. In the second part, a transmembrane protein was investigated. Assays to probe activity of the plasma membrane ATPase (Arabidopsis thaliana H+ -ATPase isoform 2 (AHA2)) in single liposomes using both giant...... are implemented by soluble proteins reversibly binding to, as well as by integral membrane proteins embedded in, cellular membranes. The activity and interaction of these proteins is furthermore modulated by the lipids of the membrane. Here, liposomes were used as model membrane systems to investigate...

Xenopus reduced folate carrier regulates neural crest development epigenetically.

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Jiejing Li

Full Text Available Folic acid deficiency during pregnancy causes birth neurocristopathic malformations resulting from aberrant development of neural crest cells. The Reduced folate carrier (RFC is a membrane-bound receptor for facilitating transfer of reduced folate into the cells. RFC knockout mice are embryonic lethal and develop multiple malformations, including neurocristopathies. Here we show that XRFC is specifically expressed in neural crest tissues in Xenopus embryos and knockdown of XRFC by specific morpholino results in severe neurocristopathies. Inhibition of RFC blocked the expression of a series of neural crest marker genes while overexpression of RFC or injection of 5-methyltetrahydrofolate expanded the neural crest territories. In animal cap assays, knockdown of RFC dramatically reduced the mono- and trimethyl-Histone3-K4 levels and co-injection of the lysine methyltransferase hMLL1 largely rescued the XRFC morpholino phenotype. Our data revealed that the RFC mediated folate metabolic pathway likely potentiates neural crest gene expression through epigenetic modifications.

Microdomains in the membrane landscape shape antigen-presenting cell function.

Science.gov (United States)

Zuidscherwoude, Malou; de Winde, Charlotte M; Cambi, Alessandra; van Spriel, Annemiek B

2014-02-01

The plasma membrane of immune cells is a highly organized cell structure that is key to the initiation and regulation of innate and adaptive immune responses. It is well-established that immunoreceptors embedded in the plasma membrane have a nonrandom spatial distribution that is important for coupling to components of intracellular signaling cascades. In the last two decades, specialized membrane microdomains, including lipid rafts and TEMs, have been identified. These domains are preformed structures ("physical entities") that compartmentalize proteins, lipids, and signaling molecules into multimolecular assemblies. In APCs, different microdomains containing immunoreceptors (MHC proteins, PRRs, integrins, among others) have been reported that are imperative for efficient pathogen recognition, the formation of the immunological synapse, and subsequent T cell activation. In addition, recent work has demonstrated that tetraspanin microdomains and lipid rafts are involved in BCR signaling and B cell activation. Research into the molecular mechanisms underlying membrane domain formation is fundamental to a comprehensive understanding of membrane-proximal signaling and APC function. This review will also discuss the advances in the microscopy field for the visualization of the plasma membrane, as well as the recent progress in targeting microdomains as novel, therapeutic approach for infectious and malignant diseases.

High sugar-induced insulin resistance in Drosophila relies on the lipocalin Neural Lazarillo.

Directory of Open Access Journals (Sweden)

Matthieu Y Pasco

Full Text Available In multicellular organisms, insulin/IGF signaling (IIS plays a central role in matching energy needs with uptake and storage, participating in functions as diverse as metabolic homeostasis, growth, reproduction and ageing. In mammals, this pleiotropy of action relies in part on a dichotomy of action of insulin, IGF-I and their respective membrane-bound receptors. In organisms with simpler IIS, this functional separation is questionable. In Drosophila IIS consists of several insulin-like peptides called Dilps, activating a unique membrane receptor and its downstream signaling cascade. During larval development, IIS is involved in metabolic homeostasis and growth. We have used feeding conditions (high sugar diet, HSD that induce an important change in metabolic homeostasis to monitor possible effects on growth. Unexpectedly we observed that HSD-fed animals exhibited severe growth inhibition as a consequence of peripheral Dilp resistance. Dilp-resistant animals present several metabolic disorders similar to those observed in type II diabetes (T2D patients. By exploring the molecular mechanisms involved in Drosophila Dilp resistance, we found a major role for the lipocalin Neural Lazarillo (NLaz, a target of JNK signaling. NLaz expression is strongly increased upon HSD and animals heterozygous for an NLaz null mutation are fully protected from HSD-induced Dilp resistance. NLaz is a secreted protein homologous to the Retinol-Binding Protein 4 involved in the onset of T2D in human and mice. These results indicate that insulin resistance shares common molecular mechanisms in flies and human and that Drosophila could emerge as a powerful genetic system to study some aspects of this complex syndrome.