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Sample records for neural development synaptic

  1. Synaptic inputs compete during rapid formation of the calyx of Held: a new model system for neural development.

    Science.gov (United States)

    Holcomb, Paul S; Hoffpauir, Brian K; Hoyson, Mitchell C; Jackson, Dakota R; Deerinck, Thomas J; Marrs, Glenn S; Dehoff, Marlin; Wu, Jonathan; Ellisman, Mark H; Spirou, George A

    2013-08-07

    Hallmark features of neural circuit development include early exuberant innervation followed by competition and pruning to mature innervation topography. Several neural systems, including the neuromuscular junction and climbing fiber innervation of Purkinje cells, are models to study neural development in part because they establish a recognizable endpoint of monoinnervation of their targets and because the presynaptic terminals are large and easily monitored. We demonstrate here that calyx of Held (CH) innervation of its target, which forms a key element of auditory brainstem binaural circuitry, exhibits all of these characteristics. To investigate CH development, we made the first application of serial block-face scanning electron microscopy to neural development with fine temporal resolution and thereby accomplished the first time series for 3D ultrastructural analysis of neural circuit formation. This approach revealed a growth spurt of added apposed surface area (ASA)>200 μm2/d centered on a single age at postnatal day 3 in mice and an initial rapid phase of growth and competition that resolved to monoinnervation in two-thirds of cells within 3 d. This rapid growth occurred in parallel with an increase in action potential threshold, which may mediate selection of the strongest input as the winning competitor. ASAs of competing inputs were segregated on the cell body surface. These data suggest mechanisms to select "winning" inputs by regional reinforcement of postsynaptic membrane to mediate size and strength of competing synaptic inputs.

  2. Statistical mechanics of attractor neural network models with synaptic depression

    International Nuclear Information System (INIS)

    Igarashi, Yasuhiko; Oizumi, Masafumi; Otsubo, Yosuke; Nagata, Kenji; Okada, Masato

    2009-01-01

    Synaptic depression is known to control gain for presynaptic inputs. Since cortical neurons receive thousands of presynaptic inputs, and their outputs are fed into thousands of other neurons, the synaptic depression should influence macroscopic properties of neural networks. We employ simple neural network models to explore the macroscopic effects of synaptic depression. Systems with the synaptic depression cannot be analyzed due to asymmetry of connections with the conventional equilibrium statistical-mechanical approach. Thus, we first propose a microscopic dynamical mean field theory. Next, we derive macroscopic steady state equations and discuss the stabilities of steady states for various types of neural network models.

  3. Attractor neural networks with resource-efficient synaptic connectivity

    Science.gov (United States)

    Pehlevan, Cengiz; Sengupta, Anirvan

    Memories are thought to be stored in the attractor states of recurrent neural networks. Here we explore how resource constraints interplay with memory storage function to shape synaptic connectivity of attractor networks. We propose that given a set of memories, in the form of population activity patterns, the neural circuit choses a synaptic connectivity configuration that minimizes a resource usage cost. We argue that the total synaptic weight (l1-norm) in the network measures the resource cost because synaptic weight is correlated with synaptic volume, which is a limited resource, and is proportional to neurotransmitter release and post-synaptic current, both of which cost energy. Using numerical simulations and replica theory, we characterize optimal connectivity profiles in resource-efficient attractor networks. Our theory explains several experimental observations on cortical connectivity profiles, 1) connectivity is sparse, because synapses are costly, 2) bidirectional connections are overrepresented and 3) are stronger, because attractor states need strong recurrence.

  4. Memristor-based neural networks: Synaptic versus neuronal stochasticity

    KAUST Repository

    Naous, Rawan; Alshedivat, Maruan; Neftci, Emre; Cauwenberghs, Gert; Salama, Khaled N.

    2016-01-01

    In neuromorphic circuits, stochasticity in the cortex can be mapped into the synaptic or neuronal components. The hardware emulation of these stochastic neural networks are currently being extensively studied using resistive memories or memristors

  5. Binocular Rivalry in a Competitive Neural Network with Synaptic Depression

    KAUST Repository

    Kilpatrick, Zachary P.; Bressloff, Paul C.

    2010-01-01

    We study binocular rivalry in a competitive neural network with synaptic depression. In particular, we consider two coupled hypercolums within primary visual cortex (V1), representing orientation selective cells responding to either left or right

  6. Activity-dependent modulation of neural circuit synaptic connectivity

    Directory of Open Access Journals (Sweden)

    Charles R Tessier

    2009-07-01

    Full Text Available In many nervous systems, the establishment of neural circuits is known to proceed via a two-stage process; 1 early, activity-independent wiring to produce a rough map characterized by excessive synaptic connections, and 2 subsequent, use-dependent pruning to eliminate inappropriate connections and reinforce maintained synapses. In invertebrates, however, evidence of the activity-dependent phase of synaptic refinement has been elusive, and the dogma has long been that invertebrate circuits are “hard-wired” in a purely activity-independent manner. This conclusion has been challenged recently through the use of new transgenic tools employed in the powerful Drosophila system, which have allowed unprecedented temporal control and single neuron imaging resolution. These recent studies reveal that activity-dependent mechanisms are indeed required to refine circuit maps in Drosophila during precise, restricted windows of late-phase development. Such mechanisms of circuit refinement may be key to understanding a number of human neurological diseases, including developmental disorders such as Fragile X syndrome (FXS and autism, which are hypothesized to result from defects in synaptic connectivity and activity-dependent circuit function. This review focuses on our current understanding of activity-dependent synaptic connectivity in Drosophila, primarily through analyzing the role of the fragile X mental retardation protein (FMRP in the Drosophila FXS disease model. The particular emphasis of this review is on the expanding array of new genetically-encoded tools that are allowing cellular events and molecular players to be dissected with ever greater precision and detail.

  7. SYNAPTIC DEPRESSION IN DEEP NEURAL NETWORKS FOR SPEECH PROCESSING.

    Science.gov (United States)

    Zhang, Wenhao; Li, Hanyu; Yang, Minda; Mesgarani, Nima

    2016-03-01

    A characteristic property of biological neurons is their ability to dynamically change the synaptic efficacy in response to variable input conditions. This mechanism, known as synaptic depression, significantly contributes to the formation of normalized representation of speech features. Synaptic depression also contributes to the robust performance of biological systems. In this paper, we describe how synaptic depression can be modeled and incorporated into deep neural network architectures to improve their generalization ability. We observed that when synaptic depression is added to the hidden layers of a neural network, it reduces the effect of changing background activity in the node activations. In addition, we show that when synaptic depression is included in a deep neural network trained for phoneme classification, the performance of the network improves under noisy conditions not included in the training phase. Our results suggest that more complete neuron models may further reduce the gap between the biological performance and artificial computing, resulting in networks that better generalize to novel signal conditions.

  8. Short-term synaptic plasticity and heterogeneity in neural systems

    Science.gov (United States)

    Mejias, J. F.; Kappen, H. J.; Longtin, A.; Torres, J. J.

    2013-01-01

    We review some recent results on neural dynamics and information processing which arise when considering several biophysical factors of interest, in particular, short-term synaptic plasticity and neural heterogeneity. The inclusion of short-term synaptic plasticity leads to enhanced long-term memory capacities, a higher robustness of memory to noise, and irregularity in the duration of the so-called up cortical states. On the other hand, considering some level of neural heterogeneity in neuron models allows neural systems to optimize information transmission in rate coding and temporal coding, two strategies commonly used by neurons to codify information in many brain areas. In all these studies, analytical approximations can be made to explain the underlying dynamics of these neural systems.

  9. Synaptic E-I Balance Underlies Efficient Neural Coding.

    Science.gov (United States)

    Zhou, Shanglin; Yu, Yuguo

    2018-01-01

    Both theoretical and experimental evidence indicate that synaptic excitation and inhibition in the cerebral cortex are well-balanced during the resting state and sensory processing. Here, we briefly summarize the evidence for how neural circuits are adjusted to achieve this balance. Then, we discuss how such excitatory and inhibitory balance shapes stimulus representation and information propagation, two basic functions of neural coding. We also point out the benefit of adopting such a balance during neural coding. We conclude that excitatory and inhibitory balance may be a fundamental mechanism underlying efficient coding.

  10. Neuromodulation, development and synaptic plasticity.

    Science.gov (United States)

    Foehring, R C; Lorenzon, N M

    1999-03-01

    We discuss parallels in the mechanisms underlying use-dependent synaptic plasticity during development and long-term potentiation (LTP) and long-term depression (LTD) in neocortical synapses. Neuromodulators, such as norepinephrine, serotonin, and acetylcholine have also been implicated in regulating both developmental plasticity and LTP/LTD. There are many potential levels of interaction between neuromodulators and plasticity. Ion channels are substrates for modulation in many cell types. We discuss examples of modulation of voltage-gated Ca2+ channels and Ca(2+)-dependent K+ channels and the consequences for neocortical pyramidal cell firing behaviour. At the time when developmental plasticity is most evident in rat cortex, the substrate for modulation is changing as the densities and relative proportions of various ion channels types are altered during ontogeny. We discuss examples of changes in K+ and Ca2+ channels and the consequence for modulation of neuronal activity.

  11. Synaptic model for spontaneous activity in developing networks

    DEFF Research Database (Denmark)

    Lerchner, Alexander; Rinzel, J.

    2005-01-01

    Spontaneous rhythmic activity occurs in many developing neural networks. The activity in these hyperexcitable networks is comprised of recurring "episodes" consisting of "cycles" of high activity that alternate with "silent phases" with little or no activity. We introduce a new model of synaptic...... dynamics that takes into account that only a fraction of the vesicles stored in a synaptic terminal is readily available for release. We show that our model can reproduce spontaneous rhythmic activity with the same general features as observed in experiments, including a positive correlation between...

  12. Spiking Neural Networks with Unsupervised Learning Based on STDP Using Resistive Synaptic Devices and Analog CMOS Neuron Circuit.

    Science.gov (United States)

    Kwon, Min-Woo; Baek, Myung-Hyun; Hwang, Sungmin; Kim, Sungjun; Park, Byung-Gook

    2018-09-01

    We designed the CMOS analog integrate and fire (I&F) neuron circuit can drive resistive synaptic device. The neuron circuit consists of a current mirror for spatial integration, a capacitor for temporal integration, asymmetric negative and positive pulse generation part, a refractory part, and finally a back-propagation pulse generation part for learning of the synaptic devices. The resistive synaptic devices were fabricated using HfOx switching layer by atomic layer deposition (ALD). The resistive synaptic device had gradual set and reset characteristics and the conductance was adjusted by spike-timing-dependent-plasticity (STDP) learning rule. We carried out circuit simulation of synaptic device and CMOS neuron circuit. And we have developed an unsupervised spiking neural networks (SNNs) for 5 × 5 pattern recognition and classification using the neuron circuit and synaptic devices. The hardware-based SNNs can autonomously and efficiently control the weight updates of the synapses between neurons, without the aid of software calculations.

  13. Binocular Rivalry in a Competitive Neural Network with Synaptic Depression

    KAUST Repository

    Kilpatrick, Zachary P.

    2010-01-01

    We study binocular rivalry in a competitive neural network with synaptic depression. In particular, we consider two coupled hypercolums within primary visual cortex (V1), representing orientation selective cells responding to either left or right eye inputs. Coupling between hypercolumns is dominated by inhibition, especially for neurons with dissimilar orientation preferences. Within hypercolumns, recurrent connectivity is excitatory for similar orientations and inhibitory for different orientations. All synaptic connections are modifiable by local synaptic depression. When the hypercolumns are driven by orthogonal oriented stimuli, it is possible to induce oscillations that are representative of binocular rivalry. We first analyze the occurrence of oscillations in a space-clamped version of the model using a fast-slow analys is, taking advantage of the fact that depression evolves much slower than population activity. We th en analyze the onset of oscillations in the full spatially extended system by carrying out a piecewise smooth stability analysis of single (winner-take-all) and double (fusion) bumps within the network. Although our stability analysis takes into account only instabilities associated with real eigenvalues, it identifies points of instability that are consistent with what is found numerically. In particular, we show that, in regions of parameter space where double bumps are unstable and no single bumps exist, binocular rivalry can arise as a slow alternation between either population supporting a bump. © 2010 Society for Industrial and Applied Mathematics.

  14. Memristor-based neural networks: Synaptic versus neuronal stochasticity

    KAUST Repository

    Naous, Rawan

    2016-11-02

    In neuromorphic circuits, stochasticity in the cortex can be mapped into the synaptic or neuronal components. The hardware emulation of these stochastic neural networks are currently being extensively studied using resistive memories or memristors. The ionic process involved in the underlying switching behavior of the memristive elements is considered as the main source of stochasticity of its operation. Building on its inherent variability, the memristor is incorporated into abstract models of stochastic neurons and synapses. Two approaches of stochastic neural networks are investigated. Aside from the size and area perspective, the impact on the system performance, in terms of accuracy, recognition rates, and learning, among these two approaches and where the memristor would fall into place are the main comparison points to be considered.

  15. 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.

  16. 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.

  17. Characterizing synaptic protein development in human visual cortex enables alignment of synaptic age with rat visual cortex

    Directory of Open Access Journals (Sweden)

    Joshua G.A Pinto

    2015-02-01

    Full Text Available Although many potential neuroplasticity based therapies have been developed in the lab, few have translated into established clinical treatments for human neurologic or neuropsychiatric diseases. Animal models, especially of the visual system, have shaped our understanding of neuroplasticity by characterizing the mechanisms that promote neural changes and defining timing of the sensitive period. The lack of knowledge about development of synaptic plasticity mechanisms in human cortex, and about alignment of synaptic age between animals and humans, has limited translation of neuroplasticity therapies. In this study, we quantified expression of a set of highly conserved pre- and post-synaptic proteins (Synapsin, Synaptophysin, PSD-95, Gephyrin and found that synaptic development in human primary visual cortex continues into late childhood. Indeed, this is many years longer than suggested by neuroanatomical studies and points to a prolonged sensitive period for plasticity in human sensory cortex. In addition, during childhood we found waves of inter-individual variability that are different for the 4 proteins and include a stage during early development (<1 year when only Gephyrin has high inter-individual variability. We also found that pre- and post-synaptic protein balances develop quickly, suggesting that maturation of certain synaptic functions happens within the first year or two of life. A multidimensional analysis (principle component analysis showed that most of the variance was captured by the sum of the 4 synaptic proteins. We used that sum to compare development of human and rat visual cortex and identified a simple linear equation that provides robust alignment of synaptic age between humans and rats. Alignment of synaptic ages is important for age-appropriate targeting and effective translation of neuroplasticity therapies from the lab to the clinic.

  18. Characterizing synaptic protein development in human visual cortex enables alignment of synaptic age with rat visual cortex

    Science.gov (United States)

    Pinto, Joshua G. A.; Jones, David G.; Williams, C. Kate; Murphy, Kathryn M.

    2015-01-01

    Although many potential neuroplasticity based therapies have been developed in the lab, few have translated into established clinical treatments for human neurologic or neuropsychiatric diseases. Animal models, especially of the visual system, have shaped our understanding of neuroplasticity by characterizing the mechanisms that promote neural changes and defining timing of the sensitive period. The lack of knowledge about development of synaptic plasticity mechanisms in human cortex, and about alignment of synaptic age between animals and humans, has limited translation of neuroplasticity therapies. In this study, we quantified expression of a set of highly conserved pre- and post-synaptic proteins (Synapsin, Synaptophysin, PSD-95, Gephyrin) and found that synaptic development in human primary visual cortex (V1) continues into late childhood. Indeed, this is many years longer than suggested by neuroanatomical studies and points to a prolonged sensitive period for plasticity in human sensory cortex. In addition, during childhood we found waves of inter-individual variability that are different for the four proteins and include a stage during early development (visual cortex and identified a simple linear equation that provides robust alignment of synaptic age between humans and rats. Alignment of synaptic ages is important for age-appropriate targeting and effective translation of neuroplasticity therapies from the lab to the clinic. PMID:25729353

  19. Learning and retrieval behavior in recurrent neural networks with pre-synaptic dependent homeostatic plasticity

    Science.gov (United States)

    Mizusaki, Beatriz E. P.; Agnes, Everton J.; Erichsen, Rubem; Brunnet, Leonardo G.

    2017-08-01

    The plastic character of brain synapses is considered to be one of the foundations for the formation of memories. There are numerous kinds of such phenomenon currently described in the literature, but their role in the development of information pathways in neural networks with recurrent architectures is still not completely clear. In this paper we study the role of an activity-based process, called pre-synaptic dependent homeostatic scaling, in the organization of networks that yield precise-timed spiking patterns. It encodes spatio-temporal information in the synaptic weights as it associates a learned input with a specific response. We introduce a correlation measure to evaluate the precision of the spiking patterns and explore the effects of different inhibitory interactions and learning parameters. We find that large learning periods are important in order to improve the network learning capacity and discuss this ability in the presence of distinct inhibitory currents.

  20. Characterizing synaptic protein development in human visual cortex enables alignment of synaptic age with rat visual cortex

    OpenAIRE

    Pinto, Joshua G. A.; Jones, David G.; Williams, C. Kate; Murphy, Kathryn M.

    2015-01-01

    Although many potential neuroplasticity based therapies have been developed in the lab, few have translated into established clinical treatments for human neurologic or neuropsychiatric diseases. Animal models, especially of the visual system, have shaped our understanding of neuroplasticity by characterizing the mechanisms that promote neural changes and defining timing of the sensitive period. The lack of knowledge about development of synaptic plasticity mechanisms in human cortex, and abo...

  1. Characterizing synaptic protein development in human visual cortex enables alignment of synaptic age with rat visual cortex

    OpenAIRE

    Joshua G.A Pinto; David G Jones; Kate eWilliams; Kathryn M Murphy; Kathryn M Murphy

    2015-01-01

    Although many potential neuroplasticity based therapies have been developed in the lab, few have translated into established clinical treatments for human neurologic or neuropsychiatric diseases. Animal models, especially of the visual system, have shaped our understanding of neuroplasticity by characterizing the mechanisms that promote neural changes and defining timing of the sensitive period. The lack of knowledge about development of synaptic plasticity mechanisms in human cortex, and a...

  2. Spike timing analysis in neural networks with unsupervised synaptic plasticity

    Science.gov (United States)

    Mizusaki, B. E. P.; Agnes, E. J.; Brunnet, L. G.; Erichsen, R., Jr.

    2013-01-01

    The synaptic plasticity rules that sculpt a neural network architecture are key elements to understand cortical processing, as they may explain the emergence of stable, functional activity, while avoiding runaway excitation. For an associative memory framework, they should be built in a way as to enable the network to reproduce a robust spatio-temporal trajectory in response to an external stimulus. Still, how these rules may be implemented in recurrent networks and the way they relate to their capacity of pattern recognition remains unclear. We studied the effects of three phenomenological unsupervised rules in sparsely connected recurrent networks for associative memory: spike-timing-dependent-plasticity, short-term-plasticity and an homeostatic scaling. The system stability is monitored during the learning process of the network, as the mean firing rate converges to a value determined by the homeostatic scaling. Afterwards, it is possible to measure the recovery efficiency of the activity following each initial stimulus. This is evaluated by a measure of the correlation between spike fire timings, and we analysed the full memory separation capacity and limitations of this system.

  3. Variable synaptic strengths controls the firing rate distribution in feedforward neural networks.

    Science.gov (United States)

    Ly, Cheng; Marsat, Gary

    2018-02-01

    Heterogeneity of firing rate statistics is known to have severe consequences on neural coding. Recent experimental recordings in weakly electric fish indicate that the distribution-width of superficial pyramidal cell firing rates (trial- and time-averaged) in the electrosensory lateral line lobe (ELL) depends on the stimulus, and also that network inputs can mediate changes in the firing rate distribution across the population. We previously developed theoretical methods to understand how two attributes (synaptic and intrinsic heterogeneity) interact and alter the firing rate distribution in a population of integrate-and-fire neurons with random recurrent coupling. Inspired by our experimental data, we extend these theoretical results to a delayed feedforward spiking network that qualitatively capture the changes of firing rate heterogeneity observed in in-vivo recordings. We demonstrate how heterogeneous neural attributes alter firing rate heterogeneity, accounting for the effect with various sensory stimuli. The model predicts how the strength of the effective network connectivity is related to intrinsic heterogeneity in such delayed feedforward networks: the strength of the feedforward input is positively correlated with excitability (threshold value for spiking) when firing rate heterogeneity is low and is negatively correlated with excitability with high firing rate heterogeneity. We also show how our theory can be used to predict effective neural architecture. We demonstrate that neural attributes do not interact in a simple manner but rather in a complex stimulus-dependent fashion to control neural heterogeneity and discuss how it can ultimately shape population codes.

  4. Presynaptic Active Zone Density during Development and Synaptic Plasticity.

    Science.gov (United States)

    Clarke, Gwenaëlle L; Chen, Jie; Nishimune, Hiroshi

    2012-01-01

    Neural circuits transmit information through synapses, and the efficiency of synaptic transmission is closely related to the density of presynaptic active zones, where synaptic vesicles are released. The goal of this review is to highlight recent insights into the molecular mechanisms that control the number of active zones per presynaptic terminal (active zone density) during developmental and stimulus-dependent changes in synaptic efficacy. At the neuromuscular junctions (NMJs), the active zone density is preserved across species, remains constant during development, and is the same between synapses with different activities. However, the NMJ active zones are not always stable, as exemplified by the change in active zone density during acute experimental manipulation or as a result of aging. Therefore, a mechanism must exist to maintain its density. In the central nervous system (CNS), active zones have restricted maximal size, exist in multiple numbers in larger presynaptic terminals, and maintain a constant density during development. These findings suggest that active zone density in the CNS is also controlled. However, in contrast to the NMJ, active zone density in the CNS can also be increased, as observed in hippocampal synapses in response to synaptic plasticity. Although the numbers of known active zone proteins and protein interactions have increased, less is known about the mechanism that controls the number or spacing of active zones. The following molecules are known to control active zone density and will be discussed herein: extracellular matrix laminins and voltage-dependent calcium channels, amyloid precursor proteins, the small GTPase Rab3, an endocytosis mechanism including synaptojanin, cytoskeleton protein spectrins and β-adducin, and a presynaptic web including spectrins. The molecular mechanisms that organize the active zone density are just beginning to be elucidated.

  5. Two-Dimensional Bumps in Piecewise Smooth Neural Fields with Synaptic Depression

    KAUST Repository

    Bressloff, Paul C.

    2011-01-01

    We analyze radially symmetric bumps in a two-dimensional piecewise-smooth neural field model with synaptic depression. The continuum dynamics is described in terms of a nonlocal integrodifferential equation, in which the integral kernel represents the spatial distribution of synaptic weights between populations of neurons whose mean firing rate is taken to be a Heaviside function of local activity. Synaptic depression dynamically reduces the strength of synaptic weights in response to increases in activity. We show that in the case of a Mexican hat weight distribution, sufficiently strong synaptic depression can destabilize a stationary bump solution that would be stable in the absence of depression. Numerically it is found that the resulting instability leads to the formation of a traveling spot. The local stability of a bump is determined by solutions to a system of pseudolinear equations that take into account the sign of perturbations around the circular bump boundary. © 2011 Society for Industrial and Applied Mathematics.

  6. Synaptic energy drives the information processing mechanisms in spiking neural networks.

    Science.gov (United States)

    El Laithy, Karim; Bogdan, Martin

    2014-04-01

    Flow of energy and free energy minimization underpins almost every aspect of naturally occurring physical mechanisms. Inspired by this fact this work establishes an energy-based framework that spans the multi-scale range of biological neural systems and integrates synaptic dynamic, synchronous spiking activity and neural states into one consistent working paradigm. Following a bottom-up approach, a hypothetical energy function is proposed for dynamic synaptic models based on the theoretical thermodynamic principles and the Hopfield networks. We show that a synapse exposes stable operating points in terms of its excitatory postsynaptic potential as a function of its synaptic strength. We postulate that synapses in a network operating at these stable points can drive this network to an internal state of synchronous firing. The presented analysis is related to the widely investigated temporal coherent activities (cell assemblies) over a certain range of time scales (binding-by-synchrony). This introduces a novel explanation of the observed (poly)synchronous activities within networks regarding the synaptic (coupling) functionality. On a network level the transitions from one firing scheme to the other express discrete sets of neural states. The neural states exist as long as the network sustains the internal synaptic energy.

  7. Changed Synaptic Plasticity in Neural Circuits of Depressive-Like and Escitalopram-Treated Rats

    Science.gov (United States)

    Li, Xiao-Li; Yuan, Yong-Gui; Xu, Hua; Wu, Di; Gong, Wei-Gang; Geng, Lei-Yu; Wu, Fang-Fang; Tang, Hao; Xu, Lin

    2015-01-01

    Background: Although progress has been made in the detection and characterization of neural plasticity in depression, it has not been fully understood in individual synaptic changes in the neural circuits under chronic stress and antidepressant treatment. Methods: Using electron microscopy and Western-blot analyses, the present study quantitatively examined the changes in the Gray’s Type I synaptic ultrastructures and the expression of synapse-associated proteins in the key brain regions of rats’ depressive-related neural circuit after chronic unpredicted mild stress and/or escitalopram administration. Meanwhile, their depressive behaviors were also determined by several tests. Results: The Type I synapses underwent considerable remodeling after chronic unpredicted mild stress, which resulted in the changed width of the synaptic cleft, length of the active zone, postsynaptic density thickness, and/or synaptic curvature in the subregions of medial prefrontal cortex and hippocampus, as well as the basolateral amygdaloid nucleus of the amygdala, accompanied by changed expression of several synapse-associated proteins. Chronic escitalopram administration significantly changed the above alternations in the chronic unpredicted mild stress rats but had little effect on normal controls. Also, there was a positive correlation between the locomotor activity and the maximal synaptic postsynaptic density thickness in the stratum radiatum of the Cornu Ammonis 1 region and a negative correlation between the sucrose preference and the length of the active zone in the basolateral amygdaloid nucleus region in chronic unpredicted mild stress rats. Conclusion: These findings strongly indicate that chronic stress and escitalopram can alter synaptic plasticity in the neural circuits, and the remodeled synaptic ultrastructure was correlated with the rats’ depressive behaviors, suggesting a therapeutic target for further exploration. PMID:25899067

  8. Spatiotemporal discrimination in neural networks with short-term synaptic plasticity

    Science.gov (United States)

    Shlaer, Benjamin; Miller, Paul

    2015-03-01

    Cells in recurrently connected neural networks exhibit bistability, which allows for stimulus information to persist in a circuit even after stimulus offset, i.e. short-term memory. However, such a system does not have enough hysteresis to encode temporal information about the stimuli. The biophysically described phenomenon of synaptic depression decreases synaptic transmission strengths due to increased presynaptic activity. This short-term reduction in synaptic strengths can destabilize attractor states in excitatory recurrent neural networks, causing the network to move along stimulus dependent dynamical trajectories. Such a network can successfully separate amplitudes and durations of stimuli from the number of successive stimuli. Stimulus number, duration and intensity encoding in randomly connected attractor networks with synaptic depression. Front. Comput. Neurosci. 7:59., and so provides a strong candidate network for the encoding of spatiotemporal information. Here we explicitly demonstrate the capability of a recurrent neural network with short-term synaptic depression to discriminate between the temporal sequences in which spatial stimuli are presented.

  9. Synaptic plasticity in a recurrent neural network for versatile and adaptive behaviors of a walking robot

    DEFF Research Database (Denmark)

    Grinke, Eduard; Tetzlaff, Christian; Wörgötter, Florentin

    2015-01-01

    correlation-based learning with synaptic scaling is applied to adequately change the connections of the network. By doing so, we can effectively exploit neural dynamics (i.e., hysteresis effects and single attractors) in the network to generate different turning angles with short-term memory for a walking...... dynamics, plasticity, sensory feedback, and biomechanics. Generating such versatile and adaptive behaviors for a many degrees-of-freedom (DOFs) walking robot is a challenging task. Thus, in this study, we present a bio-inspired approach to solve this task. Specifically, the approach combines neural...... mechanisms with plasticity, exteroceptive sensory feedback, and biomechanics. The neural mechanisms consist of adaptive neural sensory processing and modular neural locomotion control. The sensory processing is based on a small recurrent neural network consisting of two fully connected neurons. Online...

  10. A neuromorphic implementation of multiple spike-timing synaptic plasticity rules for large-scale neural networks

    Directory of Open Access Journals (Sweden)

    Runchun Mark Wang

    2015-05-01

    Full Text Available We present a neuromorphic implementation of multiple synaptic plasticity learning rules, which include both Spike Timing Dependent Plasticity (STDP and Spike Timing Dependent Delay Plasticity (STDDP. We present a fully digital implementation as well as a mixed-signal implementation, both of which use a novel dynamic-assignment time-multiplexing approach and support up to 2^26 (64M synaptic plasticity elements. Rather than implementing dedicated synapses for particular types of synaptic plasticity, we implemented a more generic synaptic plasticity adaptor array that is separate from the neurons in the neural network. Each adaptor performs synaptic plasticity according to the arrival times of the pre- and post-synaptic spikes assigned to it, and sends out a weighted and/or delayed pre-synaptic spike to the target synapse in the neural network. This strategy provides great flexibility for building complex large-scale neural networks, as a neural network can be configured for multiple synaptic plasticity rules without changing its structure. We validate the proposed neuromorphic implementations with measurement results and illustrate that the circuits are capable of performing both STDP and STDDP. We argue that it is practical to scale the work presented here up to 2^36 (64G synaptic adaptors on a current high-end FPGA platform.

  11. A scalable neural chip with synaptic electronics using CMOS integrated memristors

    International Nuclear Information System (INIS)

    Cruz-Albrecht, Jose M; Derosier, Timothy; Srinivasa, Narayan

    2013-01-01

    The design and simulation of a scalable neural chip with synaptic electronics using nanoscale memristors fully integrated with complementary metal–oxide–semiconductor (CMOS) is presented. The circuit consists of integrate-and-fire neurons and synapses with spike-timing dependent plasticity (STDP). The synaptic conductance values can be stored in memristors with eight levels, and the topology of connections between neurons is reconfigurable. The circuit has been designed using a 90 nm CMOS process with via connections to on-chip post-processed memristor arrays. The design has about 16 million CMOS transistors and 73 728 integrated memristors. We provide circuit level simulations of the entire chip performing neuronal and synaptic computations that result in biologically realistic functional behavior. (paper)

  12. Synaptic plasticity, neural circuits, and the emerging role of altered short-term information processing in schizophrenia

    Science.gov (United States)

    Crabtree, Gregg W.; Gogos, Joseph A.

    2014-01-01

    Synaptic plasticity alters the strength of information flow between presynaptic and postsynaptic neurons and thus modifies the likelihood that action potentials in a presynaptic neuron will lead to an action potential in a postsynaptic neuron. As such, synaptic plasticity and pathological changes in synaptic plasticity impact the synaptic computation which controls the information flow through the neural microcircuits responsible for the complex information processing necessary to drive adaptive behaviors. As current theories of neuropsychiatric disease suggest that distinct dysfunctions in neural circuit performance may critically underlie the unique symptoms of these diseases, pathological alterations in synaptic plasticity mechanisms may be fundamental to the disease process. Here we consider mechanisms of both short-term and long-term plasticity of synaptic transmission and their possible roles in information processing by neural microcircuits in both health and disease. As paradigms of neuropsychiatric diseases with strongly implicated risk genes, we discuss the findings in schizophrenia and autism and consider the alterations in synaptic plasticity and network function observed in both human studies and genetic mouse models of these diseases. Together these studies have begun to point toward a likely dominant role of short-term synaptic plasticity alterations in schizophrenia while dysfunction in autism spectrum disorders (ASDs) may be due to a combination of both short-term and long-term synaptic plasticity alterations. PMID:25505409

  13. Effect of Neuroinflammation on Synaptic Organization and Function in the Developing Brain: Implications for Neurodevelopmental and Neurodegenerative Disorders

    Directory of Open Access Journals (Sweden)

    Amin Mottahedin

    2017-07-01

    Full Text Available The brain is a plastic organ where both the intrinsic CNS milieu and extrinsic cues play important roles in shaping and wiring neural connections. The perinatal period constitutes a critical time in central nervous system development with extensive refinement of neural connections, which are highly sensitive to fetal and neonatal compromise, such as inflammatory challenges. Emerging evidence suggests that inflammatory cells in the brain such as microglia and astrocytes are pivotal in regulating synaptic structure and function. In this article, we will review the role of glia cells in synaptic physiology and pathophysiology, including microglia-mediated elimination of synapses. We propose that activation of the immune system dynamically affects synaptic organization and function in the developing brain. We will discuss the role of neuroinflammation in altered synaptic plasticity following perinatal inflammatory challenges and potential implications for neurodevelopmental and neurodegenerative disorders.

  14. Silicon synaptic transistor for hardware-based spiking neural network and neuromorphic system

    Science.gov (United States)

    Kim, Hyungjin; Hwang, Sungmin; Park, Jungjin; Park, Byung-Gook

    2017-10-01

    Brain-inspired neuromorphic systems have attracted much attention as new computing paradigms for power-efficient computation. Here, we report a silicon synaptic transistor with two electrically independent gates to realize a hardware-based neural network system without any switching components. The spike-timing dependent plasticity characteristics of the synaptic devices are measured and analyzed. With the help of the device model based on the measured data, the pattern recognition capability of the hardware-based spiking neural network systems is demonstrated using the modified national institute of standards and technology handwritten dataset. By comparing systems with and without inhibitory synapse part, it is confirmed that the inhibitory synapse part is an essential element in obtaining effective and high pattern classification capability.

  15. Encoding neural and synaptic functionalities in electron spin: A pathway to efficient neuromorphic computing

    Science.gov (United States)

    Sengupta, Abhronil; Roy, Kaushik

    2017-12-01

    Present day computers expend orders of magnitude more computational resources to perform various cognitive and perception related tasks that humans routinely perform every day. This has recently resulted in a seismic shift in the field of computation where research efforts are being directed to develop a neurocomputer that attempts to mimic the human brain by nanoelectronic components and thereby harness its efficiency in recognition problems. Bridging the gap between neuroscience and nanoelectronics, this paper attempts to provide a review of the recent developments in the field of spintronic device based neuromorphic computing. Description of various spin-transfer torque mechanisms that can be potentially utilized for realizing device structures mimicking neural and synaptic functionalities is provided. A cross-layer perspective extending from the device to the circuit and system level is presented to envision the design of an All-Spin neuromorphic processor enabled with on-chip learning functionalities. Device-circuit-algorithm co-simulation framework calibrated to experimental results suggest that such All-Spin neuromorphic systems can potentially achieve almost two orders of magnitude energy improvement in comparison to state-of-the-art CMOS implementations.

  16. Synaptic plasticity, memory and the hippocampus: a neural network approach to causality.

    Science.gov (United States)

    Neves, Guilherme; Cooke, Sam F; Bliss, Tim V P

    2008-01-01

    Two facts about the hippocampus have been common currency among neuroscientists for several decades. First, lesions of the hippocampus in humans prevent the acquisition of new episodic memories; second, activity-dependent synaptic plasticity is a prominent feature of hippocampal synapses. Given this background, the hypothesis that hippocampus-dependent memory is mediated, at least in part, by hippocampal synaptic plasticity has seemed as cogent in theory as it has been difficult to prove in practice. Here we argue that the recent development of transgenic molecular devices will encourage a shift from mechanistic investigations of synaptic plasticity in single neurons towards an analysis of how networks of neurons encode and represent memory, and we suggest ways in which this might be achieved. In the process, the hypothesis that synaptic plasticity is necessary and sufficient for information storage in the brain may finally be validated.

  17. The synaptic properties of cells define the hallmarks of interval timing in a recurrent neural network.

    Science.gov (United States)

    Pérez, Oswaldo; Merchant, Hugo

    2018-04-03

    Extensive research has described two key features of interval timing. The bias property is associated with accuracy and implies that time is overestimated for short intervals and underestimated for long intervals. The scalar property is linked to precision and states that the variability of interval estimates increases as a function of interval duration. The neural mechanisms behind these properties are not well understood. Here we implemented a recurrent neural network that mimics a cortical ensemble and includes cells that show paired-pulse facilitation and slow inhibitory synaptic currents. The network produces interval selective responses and reproduces both bias and scalar properties when a Bayesian decoder reads its activity. Notably, the interval-selectivity, timing accuracy, and precision of the network showed complex changes as a function of the decay time constants of the modeled synaptic properties and the level of background activity of the cells. These findings suggest that physiological values of the time constants for paired-pulse facilitation and GABAb, as well as the internal state of the network, determine the bias and scalar properties of interval timing. Significant Statement Timing is a fundamental element of complex behavior, including music and language. Temporal processing in a wide variety of contexts shows two primary features: time estimates exhibit a shift towards the mean (the bias property) and are more variable for longer intervals (the scalar property). We implemented a recurrent neural network that includes long-lasting synaptic currents, which can not only produce interval selective responses but also follow the bias and scalar properties. Interestingly, only physiological values of the time constants for paired-pulse facilitation and GABAb, as well as intermediate background activity within the network can reproduce the two key features of interval timing. Copyright © 2018 the authors.

  18. Unsupervised discrimination of patterns in spiking neural networks with excitatory and inhibitory synaptic plasticity.

    Science.gov (United States)

    Srinivasa, Narayan; Cho, Youngkwan

    2014-01-01

    A spiking neural network model is described for learning to discriminate among spatial patterns in an unsupervised manner. The network anatomy consists of source neurons that are activated by external inputs, a reservoir that resembles a generic cortical layer with an excitatory-inhibitory (EI) network and a sink layer of neurons for readout. Synaptic plasticity in the form of STDP is imposed on all the excitatory and inhibitory synapses at all times. While long-term excitatory STDP enables sparse and efficient learning of the salient features in inputs, inhibitory STDP enables this learning to be stable by establishing a balance between excitatory and inhibitory currents at each neuron in the network. The synaptic weights between source and reservoir neurons form a basis set for the input patterns. The neural trajectories generated in the reservoir due to input stimulation and lateral connections between reservoir neurons can be readout by the sink layer neurons. This activity is used for adaptation of synapses between reservoir and sink layer neurons. A new measure called the discriminability index (DI) is introduced to compute if the network can discriminate between old patterns already presented in an initial training session. The DI is also used to compute if the network adapts to new patterns without losing its ability to discriminate among old patterns. The final outcome is that the network is able to correctly discriminate between all patterns-both old and new. This result holds as long as inhibitory synapses employ STDP to continuously enable current balance in the network. The results suggest a possible direction for future investigation into how spiking neural networks could address the stability-plasticity question despite having continuous synaptic plasticity.

  19. Rich spectrum of neural field dynamics in the presence of short-term synaptic depression

    Science.gov (United States)

    Wang, He; Lam, Kin; Fung, C. C. Alan; Wong, K. Y. Michael; Wu, Si

    2015-09-01

    In continuous attractor neural networks (CANNs), spatially continuous information such as orientation, head direction, and spatial location is represented by Gaussian-like tuning curves that can be displaced continuously in the space of the preferred stimuli of the neurons. We investigate how short-term synaptic depression (STD) can reshape the intrinsic dynamics of the CANN model and its responses to a single static input. In particular, CANNs with STD can support various complex firing patterns and chaotic behaviors. These chaotic behaviors have the potential to encode various stimuli in the neuronal system.

  20. A decision-making model based on a spiking neural circuit and synaptic plasticity.

    Science.gov (United States)

    Wei, Hui; Bu, Yijie; Dai, Dawei

    2017-10-01

    To adapt to the environment and survive, most animals can control their behaviors by making decisions. The process of decision-making and responding according to cues in the environment is stable, sustainable, and learnable. Understanding how behaviors are regulated by neural circuits and the encoding and decoding mechanisms from stimuli to responses are important goals in neuroscience. From results observed in Drosophila experiments, the underlying decision-making process is discussed, and a neural circuit that implements a two-choice decision-making model is proposed to explain and reproduce the observations. Compared with previous two-choice decision making models, our model uses synaptic plasticity to explain changes in decision output given the same environment. Moreover, biological meanings of parameters of our decision-making model are discussed. In this paper, we explain at the micro-level (i.e., neurons and synapses) how observable decision-making behavior at the macro-level is acquired and achieved.

  1. Synaptic plasticity in a recurrent neural network for versatile and adaptive behaviors of a walking robot

    Directory of Open Access Journals (Sweden)

    Eduard eGrinke

    2015-10-01

    Full Text Available Walking animals, like insects, with little neural computing can effectively perform complex behaviors. They can walk around their environment, escape from corners/deadlocks, and avoid or climb over obstacles. While performing all these behaviors, they can also adapt their movements to deal with an unknown situation. As a consequence, they successfully navigate through their complex environment. The versatile and adaptive abilities are the result of an integration of several ingredients embedded in their sensorimotor loop. Biological studies reveal that the ingredients include neural dynamics, plasticity, sensory feedback, and biomechanics. Generating such versatile and adaptive behaviors for a walking robot is a challenging task. In this study, we present a bio-inspired approach to solve this task. Specifically, the approach combines neural mechanisms with plasticity, sensory feedback, and biomechanics. The neural mechanisms consist of adaptive neural sensory processing and modular neural locomotion control. The sensory processing is based on a small recurrent network consisting of two fully connected neurons. Online correlation-based learning with synaptic scaling is applied to adequately change the connections of the network. By doing so, we can effectively exploit neural dynamics (i.e., hysteresis effects and single attractors in the network to generate different turning angles with short-term memory for a biomechanical walking robot. The turning information is transmitted as descending steering signals to the locomotion control which translates the signals into motor actions. As a result, the robot can walk around and adapt its turning angle for avoiding obstacles in different situations as well as escaping from sharp corners or deadlocks. Using backbone joint control embedded in the locomotion control allows the robot to climb over small obstacles. Consequently, it can successfully explore and navigate in complex environments.

  2. Synaptic plasticity in a recurrent neural network for versatile and adaptive behaviors of a walking robot.

    Science.gov (United States)

    Grinke, Eduard; Tetzlaff, Christian; Wörgötter, Florentin; Manoonpong, Poramate

    2015-01-01

    Walking animals, like insects, with little neural computing can effectively perform complex behaviors. For example, they can walk around their environment, escape from corners/deadlocks, and avoid or climb over obstacles. While performing all these behaviors, they can also adapt their movements to deal with an unknown situation. As a consequence, they successfully navigate through their complex environment. The versatile and adaptive abilities are the result of an integration of several ingredients embedded in their sensorimotor loop. Biological studies reveal that the ingredients include neural dynamics, plasticity, sensory feedback, and biomechanics. Generating such versatile and adaptive behaviors for a many degrees-of-freedom (DOFs) walking robot is a challenging task. Thus, in this study, we present a bio-inspired approach to solve this task. Specifically, the approach combines neural mechanisms with plasticity, exteroceptive sensory feedback, and biomechanics. The neural mechanisms consist of adaptive neural sensory processing and modular neural locomotion control. The sensory processing is based on a small recurrent neural network consisting of two fully connected neurons. Online correlation-based learning with synaptic scaling is applied to adequately change the connections of the network. By doing so, we can effectively exploit neural dynamics (i.e., hysteresis effects and single attractors) in the network to generate different turning angles with short-term memory for a walking robot. The turning information is transmitted as descending steering signals to the neural locomotion control which translates the signals into motor actions. As a result, the robot can walk around and adapt its turning angle for avoiding obstacles in different situations. The adaptation also enables the robot to effectively escape from sharp corners or deadlocks. Using backbone joint control embedded in the the locomotion control allows the robot to climb over small obstacles

  3. A Mechanistic Neural Field Theory of How Anesthesia Suppresses Consciousness: Synaptic Drive Dynamics, Bifurcations, Attractors, and Partial State Equipartitioning.

    Science.gov (United States)

    Hou, Saing Paul; Haddad, Wassim M; Meskin, Nader; Bailey, James M

    2015-12-01

    With the advances in biochemistry, molecular biology, and neurochemistry there has been impressive progress in understanding the molecular properties of anesthetic agents. However, there has been little focus on how the molecular properties of anesthetic agents lead to the observed macroscopic property that defines the anesthetic state, that is, lack of responsiveness to noxious stimuli. In this paper, we use dynamical system theory to develop a mechanistic mean field model for neural activity to study the abrupt transition from consciousness to unconsciousness as the concentration of the anesthetic agent increases. The proposed synaptic drive firing-rate model predicts the conscious-unconscious transition as the applied anesthetic concentration increases, where excitatory neural activity is characterized by a Poincaré-Andronov-Hopf bifurcation with the awake state transitioning to a stable limit cycle and then subsequently to an asymptotically stable unconscious equilibrium state. Furthermore, we address the more general question of synchronization and partial state equipartitioning of neural activity without mean field assumptions. This is done by focusing on a postulated subset of inhibitory neurons that are not themselves connected to other inhibitory neurons. Finally, several numerical experiments are presented to illustrate the different aspects of the proposed theory.

  4. Optogenetic Examination of Prefrontal-Amygdala Synaptic Development.

    Science.gov (United States)

    Arruda-Carvalho, Maithe; Wu, Wan-Chen; Cummings, Kirstie A; Clem, Roger L

    2017-03-15

    A brain network comprising the medial prefrontal cortex (mPFC) and amygdala plays important roles in developmentally regulated cognitive and emotional processes. However, very little is known about the maturation of mPFC-amygdala circuitry. We conducted anatomical tracing of mPFC projections and optogenetic interrogation of their synaptic connections with neurons in the basolateral amygdala (BLA) at neonatal to adult developmental stages in mice. Results indicate that mPFC-BLA projections exhibit delayed emergence relative to other mPFC pathways and establish synaptic transmission with BLA excitatory and inhibitory neurons in late infancy, events that coincide with a massive increase in overall synaptic drive. During subsequent adolescence, mPFC-BLA circuits are further modified by excitatory synaptic strengthening as well as a transient surge in feedforward inhibition. The latter was correlated with increased spontaneous inhibitory currents in excitatory neurons, suggesting that mPFC-BLA circuit maturation culminates in a period of exuberant GABAergic transmission. These findings establish a time course for the onset and refinement of mPFC-BLA transmission and point to potential sensitive periods in the development of this critical network. SIGNIFICANCE STATEMENT Human mPFC-amygdala functional connectivity is developmentally regulated and figures prominently in numerous psychiatric disorders with a high incidence of adolescent onset. However, it remains unclear when synaptic connections between these structures emerge or how their properties change with age. Our work establishes developmental windows and cellular substrates for synapse maturation in this pathway involving both excitatory and inhibitory circuits. The engagement of these substrates by early life experience may support the ontogeny of fundamental behaviors but could also lead to inappropriate circuit refinement and psychopathology in adverse situations. Copyright © 2017 the authors 0270-6474/17/372976-10$15.00/0.

  5. Differential regulation of polarized synaptic vesicle trafficking and synapse stability in neural circuit rewiring in Caenorhabditis elegans.

    Directory of Open Access Journals (Sweden)

    Naina Kurup

    2017-06-01

    Full Text Available Neural circuits are dynamic, with activity-dependent changes in synapse density and connectivity peaking during different phases of animal development. In C. elegans, young larvae form mature motor circuits through a dramatic switch in GABAergic neuron connectivity, by concomitant elimination of existing synapses and formation of new synapses that are maintained throughout adulthood. We have previously shown that an increase in microtubule dynamics during motor circuit rewiring facilitates new synapse formation. Here, we further investigate cellular control of circuit rewiring through the analysis of mutants obtained in a forward genetic screen. Using live imaging, we characterize novel mutations that alter cargo binding in the dynein motor complex and enhance anterograde synaptic vesicle movement during remodeling, providing in vivo evidence for the tug-of-war between kinesin and dynein in fast axonal transport. We also find that a casein kinase homolog, TTBK-3, inhibits stabilization of nascent synapses in their new locations, a previously unexplored facet of structural plasticity of synapses. Our study delineates temporally distinct signaling pathways that are required for effective neural circuit refinement.

  6. The Effects of GABAergic Polarity Changes on Episodic Neural Network Activity in Developing Neural Systems

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    Wilfredo Blanco

    2017-09-01

    Full Text Available Early in development, neural systems have primarily excitatory coupling, where even GABAergic synapses are excitatory. Many of these systems exhibit spontaneous episodes of activity that have been characterized through both experimental and computational studies. As development progress the neural system goes through many changes, including synaptic remodeling, intrinsic plasticity in the ion channel expression, and a transformation of GABAergic synapses from excitatory to inhibitory. What effect each of these, and other, changes have on the network behavior is hard to know from experimental studies since they all happen in parallel. One advantage of a computational approach is that one has the ability to study developmental changes in isolation. Here, we examine the effects of GABAergic synapse polarity change on the spontaneous activity of both a mean field and a neural network model that has both glutamatergic and GABAergic coupling, representative of a developing neural network. We find some intuitive behavioral changes as the GABAergic neurons go from excitatory to inhibitory, shared by both models, such as a decrease in the duration of episodes. We also find some paradoxical changes in the activity that are only present in the neural network model. In particular, we find that during early development the inter-episode durations become longer on average, while later in development they become shorter. In addressing this unexpected finding, we uncover a priming effect that is particularly important for a small subset of neurons, called the “intermediate neurons.” We characterize these neurons and demonstrate why they are crucial to episode initiation, and why the paradoxical behavioral change result from priming of these neurons. The study illustrates how even arguably the simplest of developmental changes that occurs in neural systems can present non-intuitive behaviors. It also makes predictions about neural network behavioral changes

  7. IL-6 is increased in the cerebellum of autistic brain and alters neural cell adhesion, migration and synaptic formation.

    Science.gov (United States)

    Wei, Hongen; Zou, Hua; Sheikh, Ashfaq M; Malik, Mazhar; Dobkin, Carl; Brown, W Ted; Li, Xiaohong

    2011-05-19

    Although the cellular mechanisms responsible for the pathogenesis of autism are not understood, a growing number of studies have suggested that localized inflammation of the central nervous system (CNS) may contribute to the development of autism. Recent evidence shows that IL-6 has a crucial role in the development and plasticity of CNS. Immunohistochemistry studies were employed to detect the IL-6 expression in the cerebellum of study subjects. In vitro adenoviral gene delivery approach was used to over-express IL-6 in cultured cerebellar granule cells. Cell adhesion and migration assays, DiI labeling, TO-PRO-3 staining and immunofluorescence were used to examine cell adhesion and migration, dendritic spine morphology, cell apoptosis and synaptic protein expression respectively. In this study, we found that IL-6 was significantly increased in the cerebellum of autistic subjects. We investigated how IL-6 affects neural cell development and function by transfecting cultured mouse cerebellar granule cells with an IL-6 viral expression vector. We demonstrated that IL-6 over-expression in granule cells caused impairments in granule cell adhesion and migration but had little effect on the formation of dendritic spines or granule cell apoptosis. However, IL-6 over-expression stimulated the formation of granule cell excitatory synapses, without affecting inhibitory synapses. Our results provide further evidence that aberrant IL-6 may be associated with autism. In addition, our results suggest that the elevated IL-6 in the autistic brain could alter neural cell adhesion, migration and also cause an imbalance of excitatory and inhibitory circuits. Thus, increased IL-6 expression may be partially responsible for the pathogenesis of autism.

  8. IL-6 is increased in the cerebellum of autistic brain and alters neural cell adhesion, migration and synaptic formation

    Directory of Open Access Journals (Sweden)

    Dobkin Carl

    2011-05-01

    Full Text Available Abstract Background Although the cellular mechanisms responsible for the pathogenesis of autism are not understood, a growing number of studies have suggested that localized inflammation of the central nervous system (CNS may contribute to the development of autism. Recent evidence shows that IL-6 has a crucial role in the development and plasticity of CNS. Methods Immunohistochemistry studies were employed to detect the IL-6 expression in the cerebellum of study subjects. In vitro adenoviral gene delivery approach was used to over-express IL-6 in cultured cerebellar granule cells. Cell adhesion and migration assays, DiI labeling, TO-PRO-3 staining and immunofluorescence were used to examine cell adhesion and migration, dendritic spine morphology, cell apoptosis and synaptic protein expression respectively. Results In this study, we found that IL-6 was significantly increased in the cerebellum of autistic subjects. We investigated how IL-6 affects neural cell development and function by transfecting cultured mouse cerebellar granule cells with an IL-6 viral expression vector. We demonstrated that IL-6 over-expression in granule cells caused impairments in granule cell adhesion and migration but had little effect on the formation of dendritic spines or granule cell apoptosis. However, IL-6 over-expression stimulated the formation of granule cell excitatory synapses, without affecting inhibitory synapses. Conclusions Our results provide further evidence that aberrant IL-6 may be associated with autism. In addition, our results suggest that the elevated IL-6 in the autistic brain could alter neural cell adhesion, migration and also cause an imbalance of excitatory and inhibitory circuits. Thus, increased IL-6 expression may be partially responsible for the pathogenesis of autism.

  9. Study of GABAergic extra-synaptic tonic inhibition in single neurons and neural populations by traversing neural scales: application to propofol-induced anaesthesia.

    Science.gov (United States)

    Hutt, Axel; Buhry, Laure

    2014-12-01

    Anaesthetic agents are known to affect extra-synaptic GABAergic receptors, which induce tonic inhibitory currents. Since these receptors are very sensitive to small concentrations of agents, they are supposed to play an important role in the underlying neural mechanism of general anaesthesia. Moreover anaesthetic agents modulate the encephalographic activity (EEG) of subjects and hence show an effect on neural populations. To understand better the tonic inhibition effect in single neurons on neural populations and hence how it affects the EEG, the work considers single neurons and neural populations in a steady-state and studies numerically and analytically the modulation of their firing rate and nonlinear gain with respect to different levels of tonic inhibition. We consider populations of both type-I (Leaky Integrate-and-Fire model) and type-II (Morris-Lecar model) neurons. To bridge the single neuron description to the population description analytically, a recently proposed statistical approach is employed which allows to derive new analytical expressions for the population firing rate for type-I neurons. In addition, the work shows the derivation of a novel transfer function for type-I neurons as considered in neural mass models and studies briefly the interaction of synaptic and extra-synaptic inhibition. We reveal a strong subtractive and divisive effect of tonic inhibition in type-I neurons, i.e. a shift of the firing rate to higher excitation levels accompanied by a change of the nonlinear gain. Tonic inhibition shortens the excitation window of type-II neurons and their populations while maintaining the nonlinear gain. The gained results are interpreted in the context of recent experimental findings under propofol-induced anaesthesia.

  10. The Thouless-Anderson-Palmer equation for an analogue neural network with temporally fluctuating white synaptic noise

    International Nuclear Information System (INIS)

    Ichiki, Akihisa; Shiino, Masatoshi

    2007-01-01

    Effects of synaptic noise on the retrieval process of associative memory neural networks are studied from the viewpoint of neurobiological and biophysical understanding of information processing in the brain. We investigate the statistical mechanical properties of stochastic analogue neural networks with temporally fluctuating synaptic noise, which is assumed to be white noise. Such networks, in general, defy the use of the replica method, since they have no energy concept. The self-consistent signal-to-noise analysis (SCSNA), which is an alternative to the replica method for deriving a set of order parameter equations, requires no energy concept and thus becomes available in studying networks without energy functions. Applying the SCSNA to stochastic networks requires the knowledge of the Thouless-Anderson-Palmer (TAP) equation which defines the deterministic networks equivalent to the original stochastic ones. The study of the TAP equation which is of particular interest for the case without energy concept is very less, while it is closely related to the SCSNA in the case with energy concept. This paper aims to derive the TAP equation for networks with synaptic noise together with a set of order parameter equations by a hybrid use of the cavity method and the SCSNA

  11. The Impulse-Refractive Mode in the Neural Network with Ring Synaptic Interaction

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    Margarita M. Preobrazhenskaia

    2017-01-01

    Full Text Available In the paper, a mathematical model of a neural network with an even number of ring synaptic interaction elements is considered. The model is a system of scalar nonlinear differentialdifference equations, the right parts of which depend on large parameters. The unknown functions included in the system characterize the membrane potentials of the neurons. The search of special impulse-refraction cycles within the system of equations is of interest. The functions with odd numbers of the impulse-refraction cycle have an asymptotically high pulses and the functions with even numbers are asymptotically small. Two changes allow to study a two-dimension nonlinear differential-difference system with two delays instead of the system. Further, a limit object that represents a relay system with two delays is defined by a large parameter tending to infinity. There exists the only periodic solution of the relay system with the initial function from a suitable function class. This is structurally proved, by using the step method. Next, the existence of relaxation periodic solutions of the two-dimension singularly perturbed system is proved by using the Poincare operator and the Schauder principle. The asymptotics of this solution is constructed, and it is proved that the solution is close to the decision of the relay system. Because of the exponential estimate of the Frechet derivative of the Poincare operator it implies the uniqueness and stability of solutions of the two-dimension differential-difference equation with two delays. Furthermore, with the help of reverse replacement the proved result is transferred to the original system. 

  12. EDITORIAL: Synaptic electronics Synaptic electronics

    Science.gov (United States)

    Demming, Anna; Gimzewski, James K.; Vuillaume, Dominique

    2013-09-01

    neuromorphic circuit composed of a nanoscale 1-kbit resistive random-access memory (RRAM) cross-point array of synapses and complementary metal-oxide-semiconductor (CMOS) neuron circuits [13]; a WO3-x-based nanoionics device from Masakazu Aono's group with a wide scale of reprogrammable memorization functions [14]; a new spike-timing dependent plasticity scheme based on a MOS transistor as a selector and a RRAM as a variable resistance device [15]; a new hybrid memristor-CMOS neuromorphic circuit [16]; and a photo-assisted atomic switch [17]. Synaptic electronics evidently has many emerging facets, and Duygu Kuzum, Shimeng Yu, and H-S Philip Wong in the US provide a review of the field, including the materials, devices and applications [18]. In embracing the expertise acquired over thousands of years of evolution, biomimetics and bio-inspired design is a common, smart approach to technological innovation. Yet in successfully mimicking the physiological mechanisms of the human mind synaptic electronics research has a potential impact that is arguably unprecedented. That the quirks and eccentricities recently unearthed in the behaviour of nanomaterials should lend themselves so accommodatingly to emulating synaptic functions promises some very exciting developments in the field, as the articles in this special issue emphasize. References [1] von Neumann J (ed) 2012 The Computer and the Brain 3rd edn (Yale: Yale University Press) [2] Strukov D B, Snider G S, Stewart D R and Williams R S 2008 The missing memristor found Nature 453 80-3 [3] Chua L O 1971 Memristor—the missing circuit element IEEE Trans. Circuit Theory 18 507-19 [4] Chua L O 2013 Memristor, Hodgkin-Huxley, and Edge of Chaos Nanotechnology 24 383001 [5] Pickett M D and Williams R S 2013 Phase transitions enable computational universality in neuristor-based cellular automata Nanotechnology 24 384002 [6] Cruz-Albrecht J M, Derosier T and Srinivasa N 2013 Scalable neural chip with synaptic electronics using CMOS

  13. Changes in hippocampal synaptic functions and protein expression in monosodium glutamate-treated obese mice during development of glucose intolerance.

    Science.gov (United States)

    Sasaki-Hamada, Sachie; Hojo, Yuki; Koyama, Hajime; Otsuka, Hayuma; Oka, Jun-Ichiro

    2015-05-01

    Glucose is the sole neural fuel for the brain and is essential for cognitive function. Abnormalities in glucose tolerance may be associated with impairments in cognitive function. Experimental obese model mice can be generated by an intraperitoneal injection of monosodium glutamate (MSG; 2 mg/g) once a day for 5 days from 1 day after birth. MSG-treated mice have been shown to develop glucose intolerance and exhibit chronic neuroendocrine dysfunction associated with marked cognitive malfunctions at 28-29  weeks old. Although hippocampal synaptic plasticity is impaired in MSG-treated mice, changes in synaptic transmission remain unknown. Here, we investigated whether glucose intolerance influenced cognitive function, synaptic properties and protein expression in the hippocampus. We demonstrated that MSG-treated mice developed glucose intolerance due to an impairment in the effectiveness of insulin actions, and showed cognitive impairments in the Y-maze test. Moreover, long-term potentiation (LTP) at Schaffer collateral-CA1 pyramidal synapses in hippocampal slices was impaired, and the relationship between the slope of extracellular field excitatory postsynaptic potential and stimulus intensity of synaptic transmission was weaker in MSG-treated mice. The protein levels of vesicular glutamate transporter 1 and GluA1 glutamate receptor subunits decreased in the CA1 region of MSG-treated mice. These results suggest that deficits in glutamatergic presynapses as well as postsynapses lead to impaired synaptic plasticity in MSG-treated mice during the development of glucose intolerance, though it remains unknown whether impaired LTP is due to altered inhibitory transmission. It may be important to examine changes in glucose tolerance in order to prevent cognitive malfunctions associated with diabetes. © 2015 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

  14. Association of contextual cues with morphine reward increases neural and synaptic plasticity in the ventral hippocampus of rats.

    Science.gov (United States)

    Alvandi, Mina Sadighi; Bourmpoula, Maria; Homberg, Judith R; Fathollahi, Yaghoub

    2017-11-01

    Drug addiction is associated with aberrant memory and permanent functional changes in neural circuits. It is known that exposure to drugs like morphine is associated with positive emotional states and reward-related memory. However, the underlying mechanisms in terms of neural plasticity in the ventral hippocampus, a region involved in associative memory and emotional behaviors, are not fully understood. Therefore, we measured adult neurogenesis, dendritic spine density and brain-derived neurotrophic factor (BDNF) and TrkB mRNA expression as parameters for synaptic plasticity in the ventral hippocampus. Male Sprague Dawley rats were subjected to the CPP (conditioned place preference) paradigm and received 10 mg/kg morphine. Half of the rats were used to evaluate neurogenesis by immunohistochemical markers Ki67 and doublecortin (DCX). The other half was used for Golgi staining to measure spine density and real-time quantitative reverse transcription-polymerase chain reaction to assess BDNF/TrkB expression levels. We found that morphine-treated rats exhibited more place conditioning as compared with saline-treated rats and animals that were exposed to the CPP without any injections. Locomotor activity did not change significantly. Morphine-induced CPP significantly increased the number of Ki67 and DCX-labeled cells in the ventral dentate gyrus. Additionally, we found increased dendritic spine density in both CA1 and dentate gyrus and an enhancement of BDNF/TrkB mRNA levels in the whole ventral hippocampus. Ki67, DCX and spine density were significantly correlated with CPP scores. In conclusion, we show that morphine-induced reward-related memory is associated with neural and synaptic plasticity changes in the ventral hippocampus. Such neural changes could underlie context-induced drug relapse. © 2017 Society for the Study of Addiction.

  15. Secreted factors as synaptic organizers.

    Science.gov (United States)

    Johnson-Venkatesh, Erin M; Umemori, Hisashi

    2010-07-01

    A critical step in synaptic development is the differentiation of presynaptic and postsynaptic compartments. This complex process is regulated by a variety of secreted factors that serve as synaptic organizers. Specifically, fibroblast growth factors, Wnts, neurotrophic factors and various other intercellular signaling molecules are proposed to regulate presynaptic and/or postsynaptic differentiation. Many of these factors appear to function at both the neuromuscular junction and in the central nervous system, although the specific function of the molecules differs between the two. Here we review secreted molecules that organize the synaptic compartments and discuss how these molecules shape synaptic development, focusing on mammalian in vivo systems. Their critical role in shaping a functional neural circuit is underscored by their possible link to a wide range of neurological and psychiatric disorders both in animal models and by mutations identified in human patients. © The Authors (2010). Journal Compilation © Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

  16. Remodeling of the postsynaptic plasma membrane during neural development.

    Science.gov (United States)

    Tulodziecka, Karolina; Diaz-Rohrer, Barbara B; Farley, Madeline M; Chan, Robin B; Di Paolo, Gilbert; Levental, Kandice R; Waxham, M Neal; Levental, Ilya

    2016-11-07

    Neuronal synapses are the fundamental units of neural signal transduction and must maintain exquisite signal fidelity while also accommodating the plasticity that underlies learning and development. To achieve these goals, the molecular composition and spatial organization of synaptic terminals must be tightly regulated; however, little is known about the regulation of lipid composition and organization in synaptic membranes. Here we quantify the comprehensive lipidome of rat synaptic membranes during postnatal development and observe dramatic developmental lipidomic remodeling during the first 60 postnatal days, including progressive accumulation of cholesterol, plasmalogens, and sphingolipids. Further analysis of membranes associated with isolated postsynaptic densities (PSDs) suggests the PSD-associated postsynaptic plasma membrane (PSD-PM) as one specific location of synaptic remodeling. We analyze the biophysical consequences of developmental remodeling in reconstituted synaptic membranes and observe remarkably stable microdomains, with the stability of domains increasing with developmental age. We rationalize the developmental accumulation of microdomain-forming lipids in synapses by proposing a mechanism by which palmitoylation of the immobilized scaffold protein PSD-95 nucleates domains at the postsynaptic plasma membrane. These results reveal developmental changes in lipid composition and palmitoylation that facilitate the formation of postsynaptic membrane microdomains, which may serve key roles in the function of the neuronal synapse. © 2016 Tulodziecka 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).

  17. Reversed synaptic effects of hypocretin and NPY mediated by excitatory GABA-dependent synaptic activity in developing MCH neurons.

    Science.gov (United States)

    Li, Ying; Xu, Youfen; van den Pol, Anthony N

    2013-03-01

    In mature neurons, GABA is the primary inhibitory neurotransmitter. In contrast, in developing neurons, GABA exerts excitatory actions, and in some neurons GABA-mediated excitatory synaptic activity is more prevalent than glutamate-mediated excitation. Hypothalamic neuropeptides that modulate cognitive arousal and energy homeostasis, hypocretin/orexin and neuropeptide Y (NPY), evoked reversed effects on synaptic actions that were dependent on presynaptic GABA release onto melanin-concentrating hormone (MCH) neurons. MCH neurons were identified by selective green fluorescent protein (GFP) expression in transgenic mice. In adults, hypocretin increased GABA release leading to reduced excitation. In contrast, in the developing brain as studied here with analysis of miniature excitatory postsynaptic currents, paired-pulse ratios, and evoked potentials, hypocretin acted presynaptically to enhance the excitatory actions of GABA. The ability of hypocretin to enhance GABA release increases inhibition in adult neurons but paradoxically enhances excitation in developing MCH neurons. In contrast, NPY attenuation of GABA release reduced inhibition in mature neurons but enhanced inhibition during development by attenuating GABA excitation. Both hypocretin and NPY also evoked direct actions on developing MCH neurons. Hypocretin excited MCH cells by activating a sodium-calcium exchanger and by reducing potassium currents; NPY reduced activity by increasing an inwardly rectifying potassium current. These data for the first time show that both hypocretin and NPY receptors are functional presynaptically during early postnatal hypothalamic development and that both neuropeptides modulate GABA actions during development with a valence of enhanced excitation or inhibition opposite to that of the adult state, potentially allowing neuropeptide modulation of use-dependent synapse stabilization.

  18. Causal role of thalamic interneurons on brain state transitions: a study using a neural mass model implementing synaptic kinetics

    Directory of Open Access Journals (Sweden)

    Basabdatta Sen Bhattacharya

    2016-11-01

    Full Text Available Experimental studies on the Lateral Geniculate Nucleus (LGN of mammals and rodents show that the inhibitory interneurons (IN receive around 47.1% of their afferents from the retinal spiking neurons, and constitute around 20 - 25% of the LGN cell population. However, there is a definite gap in knowledge about the role and impact of IN on thalamocortical dynamics in both experimental and model-based research. We use a neural mass computational model of the LGN with three neural populations viz. IN, thalamocortical relay (TCR, thalamic reticular nucleus (TRN, to study the causality of IN on LGN oscillations and state-transitions. The synaptic information transmission in the model is implemented with kinetic modelling, facilitating the linking of low-level cellular attributes with high-level population dynamics. The model is parameterised and tuned to simulate both Local Field Potential (LFP of LGN and electroencephalogram (EEG of visual cortex in an awake resting state with eyes closed and dominant frequency within the alpha (8-13 Hz band. The results show that: First, the response of the TRN is suppressed in the presence of IN in the circuit; disconnecting the IN from the circuit effects a dramatic change in the model output, displaying high amplitude synchronous oscillations within the alpha band in both TCR and TRN. These observations conform to experimental reports implicating the IN as the primary inhibitory modulator of LGN dynamics in a cognitive state, and that reduced cognition is achieved by suppressing the TRN response. Second, the model validates steady state visually evoked potential response in humans corresponding to periodic input stimuli; however, when the IN is disconnected from the circuit, the output power spectra do not reflect the input frequency. This agrees with experimental reports underpinning the role of IN in efficient retino-geniculate information transmission. Third, a smooth transition from alpha to theta band is

  19. Proposal for an All-Spin Artificial Neural Network: Emulating Neural and Synaptic Functionalities Through Domain Wall Motion in Ferromagnets.

    Science.gov (United States)

    Sengupta, Abhronil; Shim, Yong; Roy, Kaushik

    2016-12-01

    Non-Boolean computing based on emerging post-CMOS technologies can potentially pave the way for low-power neural computing platforms. However, existing work on such emerging neuromorphic architectures have either focused on solely mimicking the neuron, or the synapse functionality. While memristive devices have been proposed to emulate biological synapses, spintronic devices have proved to be efficient at performing the thresholding operation of the neuron at ultra-low currents. In this work, we propose an All-Spin Artificial Neural Network where a single spintronic device acts as the basic building block of the system. The device offers a direct mapping to synapse and neuron functionalities in the brain while inter-layer network communication is accomplished via CMOS transistors. To the best of our knowledge, this is the first demonstration of a neural architecture where a single nanoelectronic device is able to mimic both neurons and synapses. The ultra-low voltage operation of low resistance magneto-metallic neurons enables the low-voltage operation of the array of spintronic synapses, thereby leading to ultra-low power neural architectures. Device-level simulations, calibrated to experimental results, was used to drive the circuit and system level simulations of the neural network for a standard pattern recognition problem. Simulation studies indicate energy savings by  ∼  100× in comparison to a corresponding digital/analog CMOS neuron implementation.

  20. A constructive mean-field analysis of multi-population neural networks with random synaptic weights and stochastic inputs.

    Science.gov (United States)

    Faugeras, Olivier; Touboul, Jonathan; Cessac, Bruno

    2009-01-01

    We deal with the problem of bridging the gap between two scales in neuronal modeling. At the first (microscopic) scale, neurons are considered individually and their behavior described by stochastic differential equations that govern the time variations of their membrane potentials. They are coupled by synaptic connections acting on their resulting activity, a nonlinear function of their membrane potential. At the second (mesoscopic) scale, interacting populations of neurons are described individually by similar equations. The equations describing the dynamical and the stationary mean-field behaviors are considered as functional equations on a set of stochastic processes. Using this new point of view allows us to prove that these equations are well-posed on any finite time interval and to provide a constructive method for effectively computing their unique solution. This method is proved to converge to the unique solution and we characterize its complexity and convergence rate. We also provide partial results for the stationary problem on infinite time intervals. These results shed some new light on such neural mass models as the one of Jansen and Rit (1995): their dynamics appears as a coarse approximation of the much richer dynamics that emerges from our analysis. Our numerical experiments confirm that the framework we propose and the numerical methods we derive from it provide a new and powerful tool for the exploration of neural behaviors at different scales.

  1. Synaptic convergence regulates synchronization-dependent spike transfer in feedforward neural networks.

    Science.gov (United States)

    Sailamul, Pachaya; Jang, Jaeson; Paik, Se-Bum

    2017-12-01

    Correlated neural activities such as synchronizations can significantly alter the characteristics of spike transfer between neural layers. However, it is not clear how this synchronization-dependent spike transfer can be affected by the structure of convergent feedforward wiring. To address this question, we implemented computer simulations of model neural networks: a source and a target layer connected with different types of convergent wiring rules. In the Gaussian-Gaussian (GG) model, both the connection probability and the strength are given as Gaussian distribution as a function of spatial distance. In the Uniform-Constant (UC) and Uniform-Exponential (UE) models, the connection probability density is a uniform constant within a certain range, but the connection strength is set as a constant value or an exponentially decaying function, respectively. Then we examined how the spike transfer function is modulated under these conditions, while static or synchronized input patterns were introduced to simulate different levels of feedforward spike synchronization. We observed that the synchronization-dependent modulation of the transfer function appeared noticeably different for each convergence condition. The modulation of the spike transfer function was largest in the UC model, and smallest in the UE model. Our analysis showed that this difference was induced by the different spike weight distributions that was generated from convergent synapses in each model. Our results suggest that, the structure of the feedforward convergence is a crucial factor for correlation-dependent spike control, thus must be considered important to understand the mechanism of information transfer in the brain.

  2. SynGAP regulates protein synthesis and homeostatic synaptic plasticity in developing cortical networks.

    Directory of Open Access Journals (Sweden)

    Chih-Chieh Wang

    Full Text Available Disrupting the balance between excitatory and inhibitory neurotransmission in the developing brain has been causally linked with intellectual disability (ID and autism spectrum disorders (ASD. Excitatory synapse strength is regulated in the central nervous system by controlling the number of postsynaptic α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors (AMPARs. De novo genetic mutations of the synaptic GTPase-activating protein (SynGAP are associated with ID and ASD. SynGAP is enriched at excitatory synapses and genetic suppression of SynGAP increases excitatory synaptic strength. However, exactly how SynGAP acts to maintain synaptic AMPAR content is unclear. We show here that SynGAP limits excitatory synaptic strength, in part, by suppressing protein synthesis in cortical neurons. The data presented here from in vitro, rat and mouse cortical networks, demonstrate that regulation of translation by SynGAP involves ERK, mTOR, and the small GTP-binding protein Rheb. Furthermore, these data show that GluN2B-containing NMDARs and the cognitive kinase CaMKII act upstream of SynGAP and that this signaling cascade is required for proper translation-dependent homeostatic synaptic plasticity of excitatory synapses in developing cortical networks.

  3. A realistic neural mass model of the cortex with laminar-specific connections and synaptic plasticity - evaluation with auditory habituation.

    Directory of Open Access Journals (Sweden)

    Peng Wang

    Full Text Available In this work we propose a biologically realistic local cortical circuit model (LCCM, based on neural masses, that incorporates important aspects of the functional organization of the brain that have not been covered by previous models: (1 activity dependent plasticity of excitatory synaptic couplings via depleting and recycling of neurotransmitters and (2 realistic inter-laminar dynamics via laminar-specific distribution of and connections between neural populations. The potential of the LCCM was demonstrated by accounting for the process of auditory habituation. The model parameters were specified using Bayesian inference. It was found that: (1 besides the major serial excitatory information pathway (layer 4 to layer 2/3 to layer 5/6, there exists a parallel "short-cut" pathway (layer 4 to layer 5/6, (2 the excitatory signal flow from the pyramidal cells to the inhibitory interneurons seems to be more intra-laminar while, in contrast, the inhibitory signal flow from inhibitory interneurons to the pyramidal cells seems to be both intra- and inter-laminar, and (3 the habituation rates of the connections are unsymmetrical: forward connections (from layer 4 to layer 2/3 are more strongly habituated than backward connections (from Layer 5/6 to layer 4. Our evaluation demonstrates that the novel features of the LCCM are of crucial importance for mechanistic explanations of brain function. The incorporation of these features into a mass model makes them applicable to modeling based on macroscopic data (like EEG or MEG, which are usually available in human experiments. Our LCCM is therefore a valuable building block for future realistic models of human cognitive function.

  4. Histone Deacetylase (HDAC) Inhibitors - emerging roles in neuronal memory, learning, synaptic plasticity and neural regeneration.

    Science.gov (United States)

    Ganai, Shabir Ahmad; Ramadoss, Mahalakshmi; Mahadevan, Vijayalakshmi

    2016-01-01

    Epigenetic regulation of neuronal signalling through histone acetylation dictates transcription programs that govern neuronal memory, plasticity and learning paradigms. Histone Acetyl Transferases (HATs) and Histone Deacetylases (HDACs) are antagonistic enzymes that regulate gene expression through acetylation and deacetylation of histone proteins around which DNA is wrapped inside a eukaryotic cell nucleus. The epigenetic control of HDACs and the cellular imbalance between HATs and HDACs dictate disease states and have been implicated in muscular dystrophy, loss of memory, neurodegeneration and autistic disorders. Altering gene expression profiles through inhibition of HDACs is now emerging as a powerful technique in therapy. This review presents evolving applications of HDAC inhibitors as potential drugs in neurological research and therapy. Mechanisms that govern their expression profiles in neuronal signalling, plasticity and learning will be covered. Promising and exciting possibilities of HDAC inhibitors in memory formation, fear conditioning, ischemic stroke and neural regeneration have been detailed.

  5. Neural plasticity of development and learning.

    Science.gov (United States)

    Galván, Adriana

    2010-06-01

    Development and learning are powerful agents of change across the lifespan that induce robust structural and functional plasticity in neural systems. An unresolved question in developmental cognitive neuroscience is whether development and learning share the same neural mechanisms associated with experience-related neural plasticity. In this article, I outline the conceptual and practical challenges of this question, review insights gleaned from adult studies, and describe recent strides toward examining this topic across development using neuroimaging methods. I suggest that development and learning are not two completely separate constructs and instead, that they exist on a continuum. While progressive and regressive changes are central to both, the behavioral consequences associated with these changes are closely tied to the existing neural architecture of maturity of the system. Eventually, a deeper, more mechanistic understanding of neural plasticity will shed light on behavioral changes across development and, more broadly, about the underlying neural basis of cognition. (c) 2010 Wiley-Liss, Inc.

  6. Distributed Recurrent Neural Forward Models with Synaptic Adaptation and CPG-based control for Complex Behaviors of Walking Robots

    Directory of Open Access Journals (Sweden)

    Sakyasingha eDasgupta

    2015-09-01

    Full Text Available Walking animals, like stick insects, cockroaches or ants, demonstrate a fascinating range of locomotive abilities and complex behaviors. The locomotive behaviors can consist of a variety of walking patterns along with adaptation that allow the animals to deal with changes in environmental conditions, like uneven terrains, gaps, obstacles etc. Biological study has revealed that such complex behaviors are a result of a combination of biomechanics and neural mechanism thus representing the true nature of embodied interactions. While the biomechanics helps maintain flexibility and sustain a variety of movements, the neural mechanisms generate movements while making appropriate predictions crucial for achieving adaptation. Such predictions or planning ahead can be achieved by way of internal models that are grounded in the overall behavior of the animal. Inspired by these findings, we present here, an artificial bio-inspired walking system which effectively combines biomechanics (in terms of the body and leg structures with the underlying neural mechanisms. The neural mechanisms consist of 1 central pattern generator based control for generating basic rhythmic patterns and coordinated movements, 2 distributed (at each leg recurrent neural network based adaptive forward models with efference copies as internal models for sensory predictions and instantaneous state estimations, and 3 searching and elevation control for adapting the movement of an individual leg to deal with different environmental conditions. Using simulations we show that this bio-inspired approach with adaptive internal models allows the walking robot to perform complex locomotive behaviors as observed in insects, including walking on undulated terrains, crossing large gaps as well as climbing over high obstacles. Furthermore we demonstrate that the newly developed recurrent network based approach to sensorimotor prediction outperforms the previous state of the art adaptive neuron

  7. Circuit and synaptic mechanisms of repeated stress: Perspectives from differing contexts, duration, and development.

    Science.gov (United States)

    Bath, Kevin G; Russo, Scott J; Pleil, Kristen E; Wohleb, Eric S; Duman, Ronald S; Radley, Jason J

    2017-12-01

    The current review is meant to synthesize research presented as part of a symposium at the 2016 Neurobiology of Stress workshop in Irvine California. The focus of the symposium was "Stress and the Synapse: New Concepts and Methods" and featured the work of several junior investigators. The presentations focused on the impact of various forms of stress (altered maternal care, binge alcohol drinking, chronic social defeat, and chronic unpredictable stress) on synaptic function, neurodevelopment, and behavioral outcomes. One of the goals of the symposium was to highlight the mechanisms accounting for how the nervous system responds to stress and their impact on outcome measures with converging effects on the development of pathological behavior. Dr. Kevin Bath's presentation focused on the impact of disruptions in early maternal care and its impact on the timing of hippocampus maturation in mice, finding that this form of stress drove accelerated synaptic and behavioral maturation, and contributed to the later emergence of risk for cognitive and emotional disturbance. Dr. Scott Russo highlighted the impact of chronic social defeat stress in adolescent mice on the development and plasticity of reward circuity, with a focus on glutamatergic development in the nucleus accumbens and mesolimbic dopamine system, and the implications of these changes for disruptions in social and hedonic response, key processes disturbed in depressive pathology. Dr. Kristen Pleil described synaptic changes in the bed nuclei of the stria terminalis that underlie the behavioral consequences of allostatic load produced by repeated cycles of alcohol binge drinking and withdrawal. Dr. Eric Wohleb and Dr. Ron Duman provided new data associating decreased mammalian target of rapamycin (mTOR) signaling and neurobiological changes in the synapses in response to chronic unpredictable stress, and highlighted the potential for the novel antidepressant ketamine to rescue synaptic and behavioral effects

  8. Lack of paternal care affects synaptic development in the anterior cingulate cortex.

    Science.gov (United States)

    Ovtscharoff, Wladimir; Helmeke, Carina; Braun, Katharina

    2006-10-20

    Exposure to enriched or impoverished environmental conditions, experience and learning are factors which influence brain development, and it has been shown that neonatal emotional experience significantly interferes with the synaptic development of higher associative forebrain areas. Here, we analyzed the impact of paternal care, i.e. the father's emotional contribution towards his offspring, on the synaptic development of the anterior cingulate cortex. Our light and electron microscopic comparison of biparentally raised control animals and animals which were raised in single-mother families revealed no significant differences in spine densities on the apical dendrites of layer II/III pyramidal neurons and of asymmetric and symmetric spine synapses. However, significantly reduced densities (-33%) of symmetric shaft synapses were found in layer II of the fatherless animals compared to controls. This finding indicates an imbalance between excitatory and inhibitory synapses in the anterior cingulate cortex of father-deprived animals. Our results query the general assumption that a father has less impact on the synaptic maturation of his offspring's brain than the mother.

  9. DPP6 Loss Impacts Hippocampal Synaptic Development and Induces Behavioral Impairments in Recognition, Learning and Memory

    Directory of Open Access Journals (Sweden)

    Lin Lin

    2018-03-01

    Full Text Available DPP6 is well known as an auxiliary subunit of Kv4-containing, A-type K+ channels which regulate dendritic excitability in hippocampal CA1 pyramidal neurons. We have recently reported, however, a novel role for DPP6 in regulating dendritic filopodia formation and stability, affecting synaptic development and function. These results are notable considering recent clinical findings associating DPP6 with neurodevelopmental and intellectual disorders. Here we assessed the behavioral consequences of DPP6 loss. We found that DPP6 knockout (DPP6-KO mice are impaired in hippocampus-dependent learning and memory. Results from the Morris water maze and T-maze tasks showed that DPP6-KO mice exhibit slower learning and reduced memory performance. DPP6 mouse brain weight is reduced throughout development compared with WT, and in vitro imaging results indicated that DPP6 loss affects synaptic structure and motility. Taken together, these results show impaired synaptic development along with spatial learning and memory deficiencies in DPP6-KO mice.

  10. Involvement of neurotrophin-3 (NT-3) in the functional elimination of synaptic contacts during neuromuscular development.

    Science.gov (United States)

    Garcia, Neus; Santafé, Manel M; Tomàs, Marta; Lanuza, Maria A; Besalduch, Nuria; Tomàs, Josep

    2010-04-05

    Confocal immunohistochemistry shows that neurotrophin-3 (NT-3) and its receptor tropomyosin-related tyrosin kinase C (trkC) are present in both neonatal (P6) and adult (P45) mouse motor nerve terminals in neuromuscular junctions (NMJ) colocalized with several synaptic proteins. NT-3 incubation (1-3h, in the range 10-200ng/ml) does not change the size of the evoked and spontaneous endplate potentials at P45. However, NT-3 (1h, 100ng/ml) strongly potentiates evoked ACh release from the weak (70%) and the strong (50%) axonal inputs on dually innervated postnatal endplates (P6) but not in the most developed postnatal singly innervated synapses at P6. The present results indicate that NT-3 has a role in the developmental mechanism that eliminates redundant synapses though it cannot modulate synaptic transmission locally as the NMJ matures.

  11. Reversing the outcome of synapse elimination at developing neuromuscular junctions in vivo: evidence for synaptic competition and its mechanism.

    Directory of Open Access Journals (Sweden)

    Stephen G Turney

    Full Text Available During mammalian development, neuromuscular junctions and some other postsynaptic cells transition from multiple- to single-innervation as synaptic sites are exchanged between different axons. It is unclear whether one axon invades synaptic sites to drive off other inputs or alternatively axons expand their territory in response to sites vacated by other axons. Here we show that soon-to-be-eliminated axons rapidly reverse fate and grow to occupy vacant sites at a neuromuscular junction after laser removal of a stronger input. This reversal supports the idea that axons take over sites that were previously vacated. Indeed, during normal development we observed withdrawal followed by takeover. The stimulus for axon growth is not postsynaptic cell inactivity because axons grow into unoccupied sites even when target cells are functionally innervated. These results demonstrate competition at the synaptic level and enable us to provide a conceptual framework for understanding this form of synaptic plasticity.

  12. Reversing the outcome of synapse elimination at developing neuromuscular junctions in vivo: evidence for synaptic competition and its mechanism.

    Science.gov (United States)

    Turney, Stephen G; Lichtman, Jeff W

    2012-01-01

    During mammalian development, neuromuscular junctions and some other postsynaptic cells transition from multiple- to single-innervation as synaptic sites are exchanged between different axons. It is unclear whether one axon invades synaptic sites to drive off other inputs or alternatively axons expand their territory in response to sites vacated by other axons. Here we show that soon-to-be-eliminated axons rapidly reverse fate and grow to occupy vacant sites at a neuromuscular junction after laser removal of a stronger input. This reversal supports the idea that axons take over sites that were previously vacated. Indeed, during normal development we observed withdrawal followed by takeover. The stimulus for axon growth is not postsynaptic cell inactivity because axons grow into unoccupied sites even when target cells are functionally innervated. These results demonstrate competition at the synaptic level and enable us to provide a conceptual framework for understanding this form of synaptic plasticity.

  13. Taurine Induces Proliferation of Neural Stem Cells and Synapse Development in the Developing Mouse Brain

    Science.gov (United States)

    Shivaraj, Mattu Chetana; Marcy, Guillaume; Low, Guoliang; Ryu, Jae Ryun; Zhao, Xianfeng; Rosales, Francisco J.; Goh, Eyleen L. K.

    2012-01-01

    Taurine is a sulfur-containing amino acid present in high concentrations in mammalian tissues. It has been implicated in several processes involving brain development and neurotransmission. However, the role of taurine in hippocampal neurogenesis during brain development is still unknown. Here we show that taurine regulates neural progenitor cell (NPC) proliferation in the dentate gyrus of the developing brain as well as in cultured early postnatal (P5) hippocampal progenitor cells and hippocampal slices derived from P5 mice brains. Taurine increased cell proliferation without having a significant effect on neural differentiation both in cultured P5 NPCs as well as cultured hippocampal slices and in vivo. Expression level analysis of synaptic proteins revealed that taurine increases the expression of Synapsin 1 and PSD 95. We also found that taurine stimulates the phosphorylation of ERK1/2 indicating a possible role of the ERK pathway in mediating the changes that we observed, especially in proliferation. Taken together, our results demonstrate a role for taurine in neural stem/progenitor cell proliferation in developing brain and suggest the involvement of the ERK1/2 pathways in mediating these actions. Our study also shows that taurine influences the levels of proteins associated with synapse development. This is the first evidence showing the effect of taurine on early postnatal neuronal development using a combination of in vitro, ex-vivo and in vivo systems. PMID:22916184

  14. Synaptic control of motoneuronal excitability

    DEFF Research Database (Denmark)

    Rekling, J C; Funk, G D; Bayliss, D A

    2000-01-01

    important in understanding the transformation of neural activity to motor behavior. Here, we review recent studies on the control of motoneuronal excitability, focusing on synaptic and cellular properties. We first present a background description of motoneurons: their development, anatomical organization......, and membrane properties, both passive and active. We then describe the general anatomical organization of synaptic input to motoneurons, followed by a description of the major transmitter systems that affect motoneuronal excitability, including ligands, receptor distribution, pre- and postsynaptic actions...... and norepinephrine, and neuropeptides, as well as the glutamate and GABA acting at metabotropic receptors, modulate motoneuronal excitability through pre- and postsynaptic actions. Acting principally via second messenger systems, their actions converge on common effectors, e.g., leak K(+) current, cationic inward...

  15. Circuit and synaptic mechanisms of repeated stress: Perspectives from differing contexts, duration, and development

    Directory of Open Access Journals (Sweden)

    Kevin G. Bath

    2017-12-01

    Full Text Available The current review is meant to synthesize research presented as part of a symposium at the 2016 Neurobiology of Stress workshop in Irvine California. The focus of the symposium was “Stress and the Synapse: New Concepts and Methods” and featured the work of several junior investigators. The presentations focused on the impact of various forms of stress (altered maternal care, binge alcohol drinking, chronic social defeat, and chronic unpredictable stress on synaptic function, neurodevelopment, and behavioral outcomes. One of the goals of the symposium was to highlight the mechanisms accounting for how the nervous system responds to stress and their impact on outcome measures with converging effects on the development of pathological behavior. Dr. Kevin Bath's presentation focused on the impact of disruptions in early maternal care and its impact on the timing of hippocampus maturation in mice, finding that this form of stress drove accelerated synaptic and behavioral maturation, and contributed to the later emergence of risk for cognitive and emotional disturbance. Dr. Scott Russo highlighted the impact of chronic social defeat stress in adolescent mice on the development and plasticity of reward circuity, with a focus on glutamatergic development in the nucleus accumbens and mesolimbic dopamine system, and the implications of these changes for disruptions in social and hedonic response, key processes disturbed in depressive pathology. Dr. Kristen Pleil described synaptic changes in the bed nuclei of the stria terminalis that underlie the behavioral consequences of allostatic load produced by repeated cycles of alcohol binge drinking and withdrawal. Dr. Eric Wohleb and Dr. Ron Duman provided new data associating decreased mammalian target of rapamycin (mTOR signaling and neurobiological changes in the synapses in response to chronic unpredictable stress, and highlighted the potential for the novel antidepressant ketamine to rescue

  16. Association of contextual cues with morphine reward increases neural and synaptic plasticity in the ventral hippocampus of rats

    NARCIS (Netherlands)

    Alvandi, M.S.; Bourmpoula, M.; Homberg, J.R.; Fathollahi, Y.

    2017-01-01

    Drug addiction is associated with aberrant memory and permanent functional changes in neural circuits. It is known that exposure to drugs like morphine is associated with positive emotional states and reward-related memory. However, the underlying mechanisms in terms of neural plasticity in the

  17. Paired-pulse facilitation achieved in protonic/electronic hybrid indium gallium zinc oxide synaptic transistors

    Energy Technology Data Exchange (ETDEWEB)

    Guo, Li Qiang, E-mail: guoliqiang@ujs.edu.cn; Ding, Jian Ning; Huang, Yu Kai [Micro/Nano Science & Technology Center, Jiangsu University, Zhenjiang, 212013 (China); Zhu, Li Qiang, E-mail: lqzhu@nimte.ac.cn [Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201 (China)

    2015-08-15

    Neuromorphic devices with paired pulse facilitation emulating that of biological synapses are the key to develop artificial neural networks. Here, phosphorus-doped nanogranular SiO{sub 2} electrolyte is used as gate dielectric for protonic/electronic hybrid indium gallium zinc oxide (IGZO) synaptic transistor. In such synaptic transistors, protons within the SiO{sub 2} electrolyte are deemed as neurotransmitters of biological synapses. Paired-pulse facilitation (PPF) behaviors for the analogous information were mimicked. The temperature dependent PPF behaviors were also investigated systematically. The results indicate that the protonic/electronic hybrid IGZO synaptic transistors would be promising candidates for inorganic synapses in artificial neural network applications.

  18. Paired-pulse facilitation achieved in protonic/electronic hybrid indium gallium zinc oxide synaptic transistors

    Directory of Open Access Journals (Sweden)

    Li Qiang Guo

    2015-08-01

    Full Text Available Neuromorphic devices with paired pulse facilitation emulating that of biological synapses are the key to develop artificial neural networks. Here, phosphorus-doped nanogranular SiO2 electrolyte is used as gate dielectric for protonic/electronic hybrid indium gallium zinc oxide (IGZO synaptic transistor. In such synaptic transistors, protons within the SiO2 electrolyte are deemed as neurotransmitters of biological synapses. Paired-pulse facilitation (PPF behaviors for the analogous information were mimicked. The temperature dependent PPF behaviors were also investigated systematically. The results indicate that the protonic/electronic hybrid IGZO synaptic transistors would be promising candidates for inorganic synapses in artificial neural network applications.

  19. Effects of Ethanol Exposure during Distinct Periods of Brain Development on Hippocampal Synaptic Plasticity

    Directory of Open Access Journals (Sweden)

    Brian R. Christie

    2013-07-01

    Full Text Available Fetal alcohol spectrum disorders occur when a mother drinks during pregnancy and can greatly influence synaptic plasticity and cognition in the offspring. In this study we determined whether there are periods during brain development that are more susceptible to the effects of ethanol exposure on hippocampal synaptic plasticity. In particular, we evaluated how the ability to elicit long-term potentiation (LTP in the hippocampal dentate gyrus (DG was affected in young adult rats that were exposed to ethanol during either the 1st, 2nd, or 3rd trimester equivalent. As expected, the effects of ethanol on young adult DG LTP were less severe when exposure was limited to a particular trimester equivalent when compared to exposure throughout gestation. In males, ethanol exposure during the 1st, 2nd or 3rd trimester equivalent did not significantly reduce LTP in the DG. In females, ethanol exposure during either the 1st or 2nd trimester equivalents did not impact LTP in early adulthood, but following exposure during the 3rd trimester equivalent alone, LTP was significantly increased in the female DG. These results further exemplify the disparate effects between the ability to elicit LTP in the male and female brain following perinatal ethanol exposure (PNEE.

  20. The epigenetic switches for neural development and psychiatric disorders.

    Science.gov (United States)

    Lv, Jingwen; Xin, Yongjuan; Zhou, Wenhao; Qiu, Zilong

    2013-07-20

    The most remarkable feature of the nervous system is that the development and functions of the brain are largely reshaped by postnatal experiences, in joint with genetic landscapes. The nature vs. nurture argument reminds us that both genetic and epigenetic information is indispensable for the normal function of the brain. The epigenetic regulatory mechanisms in the central nervous system have been revealed over last a decade. Moreover, the mutations of epigenetic modulator genes have been shown to be implicated in neuropsychiatric disorders, such as autism spectrum disorders. The epigenetic study has initiated in the neuroscience field for a relative short period of time. In this review, we will summarize recent discoveries about epigenetic regulation on neural development, synaptic plasticity, learning and memory, as well as neuropsychiatric disorders. Although the comprehensive view of how epigenetic regulation contributes to the function of the brain is still not completed, the notion that brain, the most complicated organ of organisms, is profoundly shaped by epigenetic switches is widely accepted. Copyright © 2013. Published by Elsevier Ltd.

  1. Stress-altered synaptic plasticity and DAMP signaling in the hippocampus-PFC axis; elucidating the significance of IGF-1/IGF-1R/CaMKIIα expression in neural changes associated with a prolonged exposure therapy.

    Science.gov (United States)

    Ogundele, Olalekan M; Ebenezer, Philip J; Lee, Charles C; Francis, Joseph

    2017-06-14

    Traumatic stress patients showed significant improvement in behavior after a prolonged exposure to an unrelated stimulus. This treatment method attempts to promote extinction of the fear memory associated with the initial traumatic experience. However, the subsequent prolonged exposure to such stimulus creates an additional layer of neural stress. Although the mechanism remains unclear, prolonged exposure therapy (PET) likely involves changes in synaptic plasticity, neurotransmitter function and inflammation; especially in parts of the brain concerned with the formation and retrieval of fear memory (Hippocampus and Prefrontal Cortex: PFC). Since certain synaptic proteins are also involved in danger-associated molecular pattern signaling (DAMP), we identified the significance of IGF-1/IGF-1R/CaMKIIα expression as a potential link between the concurrent progression of synaptic and inflammatory changes in stress. Thus, a comparison between IGF-1/IGF-1R/CaMKIIα, synaptic and DAMP proteins in stress and PET may highlight the significance of PET on synaptic morphology and neuronal inflammatory response. In behaviorally characterized Sprague-Dawley rats, there was a significant decline in neural IGF-1 (pIGF-1R expression. These animals showed a significant loss of presynaptic markers (synaptophysin; pIGF-1 (pIGF-1R was recorded in the Stress-PET group (pIGF-1/IGF-1R, an increase in activated hippocampal and cortical microglia was seen in stress (pIGF1/IGF-1R/CaMKIIα. Firstly, we showed a direct relationship between IGF-1/IGF-1R expression, presynaptic function (synaptophysin) and neurotransmitter activity in stress and PET. Secondly, we identified the possible role of CaMKIIα in post-synaptic function and regulation of small ion conductance channels. Lastly, we highlighted some of the possible links between IGF1/IGF-1R/CaMKIIα, the expression of DAMP proteins, Microglia activation, and its implication on synaptic plasticity during stress and PET. Copyright © 2017

  2. Impaired development of cortico-striatal synaptic connectivity in a cell culture model of Huntington's disease.

    Science.gov (United States)

    Buren, Caodu; Parsons, Matthew P; Smith-Dijak, Amy; Raymond, Lynn A

    2016-03-01

    Huntington's disease (HD) is a genetically inherited neurodegenerative disease caused by a mutation in the gene encoding the huntingtin protein. This mutation results in progressive cell death that is particularly striking in the striatum. Recent evidence indicates that early HD is initially a disease of the synapse, in which subtle alterations in synaptic neurotransmission, particularly at the cortico-striatal (C-S) synapse, can be detected well in advance of cell death. Here, we used a cell culture model in which striatal neurons are co-cultured with cortical neurons, and monitored the development of C-S connectivity up to 21days in vitro (DIV) in cells cultured from either the YAC128 mouse model of HD or the background strain, FVB/N (wild-type; WT) mice. Our data demonstrate that while C-S connectivity in WT co-cultures develops rapidly and continuously from DIV 7 to 21, YAC128 C-S connectivity shows no significant growth from DIV 14 onward. Morphological and electrophysiological data suggest that a combination of pre- and postsynaptic mechanisms contribute to this effect, including a reduction in both the postsynaptic dendritic arborization and the size and replenishment rate of the presynaptic readily releasable pool of excitatory vesicles. Moreover, a chimeric culture strategy confirmed that the most robust impairment in C-S connectivity was only observed when mutant huntingtin was expressed both pre- and postsynaptically. In all, our data demonstrate a progressive HD synaptic phenotype in this co-culture system that may be exploited as a platform for identifying promising therapeutic strategies to prevent early HD-associated synaptopathy. Copyright © 2015 Elsevier Inc. All rights reserved.

  3. Neural Development Under Conditions of Spaceflight

    Science.gov (United States)

    Kosik, Kenneth S.; Steward, Oswald; Temple, Meredith D.; Denslow, Maria J.

    2003-01-01

    One of the key tasks the developing brain must learn is how to navigate within the environment. This skill depends on the brain's ability to establish memories of places and things in the environment so that it can form cognitive maps. Earth's gravity defines the plane of orientation of the spatial environment in which animals navigate, and cognitive maps are based on this plane of orientation. Given that experience during early development plays a key role in the development of other aspects of brain function, experience in a gravitational environment is likely to be essential for the proper organization of brain regions mediating learning and memory of spatial information. Since the hippocampus is the brain region responsible for cognitive mapping abilities, this study evaluated the development of hippocampal structure and function in rats that spent part of their early development in microgravity. Litters of male and female Sprague-Dawley rats were launched into space aboard the Space Shuttle Columbia on either postnatal day eight (P8) or 14 (P14) and remained in space for 16 days. Upon return to Earth, the rats were tested for their ability to remember spatial information and navigate using a variety of tests (the Morris water maze, a modified radial arm maze, and an open field apparatus). These rats were then tested physiologically to determine whether they exhibited normal synaptic plasticity in the hippocampus. In a separate group of rats (flight and controls), the hippocampus was analyzed using anatomical, molecular biological, and biochemical techniques immediately postlanding. There were remarkably few differences between the flight groups and their Earth-bound controls in either the navigation and spatial memory tasks or activity-induced synaptic plasticity. Microscopic and immunocytochemical analyses of the brain also did not reveal differences between flight animals and ground-based controls. These data suggest that, within the developmental window

  4. Optogenetics in the Teaching Laboratory: Using Channelrhodopsin-2 to Study the Neural Basis of Behavior and Synaptic Physiology in "Drosophila"

    Science.gov (United States)

    Pulver, Stefan R.; Hornstein, Nicholas J.; Land, Bruce L.; Johnson, Bruce R.

    2011-01-01

    Here we incorporate recent advances in "Drosophila" neurogenetics and "optogenetics" into neuroscience laboratory exercises. We used the light-activated ion channel channelrhodopsin-2 (ChR2) and tissue-specific genetic expression techniques to study the neural basis of behavior in "Drosophila" larvae. We designed and implemented exercises using…

  5. A Neural Circuit for Acoustic Navigation combining Heterosynaptic and Non-synaptic Plasticity that learns Stable Trajectories

    DEFF Research Database (Denmark)

    Shaikh, Danish; Manoonpong, Poramate

    2017-01-01

    controllers be resolved in a manner that generates consistent and stable robot trajectories? We propose a neural circuit that minimises this conflict by learning sensorimotor mappings as neuronal transfer functions between the perceived sound direction and wheel velocities of a simulated non-holonomic mobile...

  6. Development and function of human cerebral cortex neural networks from pluripotent stem cells in vitro.

    Science.gov (United States)

    Kirwan, Peter; Turner-Bridger, Benita; Peter, Manuel; Momoh, Ayiba; Arambepola, Devika; Robinson, Hugh P C; Livesey, Frederick J

    2015-09-15

    A key aspect of nervous system development, including that of the cerebral cortex, is the formation of higher-order neural networks. Developing neural networks undergo several phases with distinct activity patterns in vivo, which are thought to prune and fine-tune network connectivity. We report here that human pluripotent stem cell (hPSC)-derived cerebral cortex neurons form large-scale networks that reflect those found in the developing cerebral cortex in vivo. Synchronised oscillatory networks develop in a highly stereotyped pattern over several weeks in culture. An initial phase of increasing frequency of oscillations is followed by a phase of decreasing frequency, before giving rise to non-synchronous, ordered activity patterns. hPSC-derived cortical neural networks are excitatory, driven by activation of AMPA- and NMDA-type glutamate receptors, and can undergo NMDA-receptor-mediated plasticity. Investigating single neuron connectivity within PSC-derived cultures, using rabies-based trans-synaptic tracing, we found two broad classes of neuronal connectivity: most neurons have small numbers (40). These data demonstrate that the formation of hPSC-derived cortical networks mimics in vivo cortical network development and function, demonstrating the utility of in vitro systems for mechanistic studies of human forebrain neural network biology. © 2015. Published by The Company of Biologists Ltd.

  7. Dynamic Control of Synaptic Adhesion and Organizing Molecules in Synaptic Plasticity

    Energy Technology Data Exchange (ETDEWEB)

    Rudenko, Gabby (Texas-MED)

    2017-01-01

    Synapses play a critical role in establishing and maintaining neural circuits, permitting targeted information transfer throughout the brain. A large portfolio of synaptic adhesion/organizing molecules (SAMs) exists in the mammalian brain involved in synapse development and maintenance. SAMs bind protein partners, formingtrans-complexes spanning the synaptic cleft orcis-complexes attached to the same synaptic membrane. SAMs play key roles in cell adhesion and in organizing protein interaction networks; they can also provide mechanisms of recognition, generate scaffolds onto which partners can dock, and likely take part in signaling processes as well. SAMs are regulated through a portfolio of different mechanisms that affect their protein levels, precise localization, stability, and the availability of their partners at synapses. Interaction of SAMs with their partners can further be strengthened or weakened through alternative splicing, competing protein partners, ectodomain shedding, or astrocytically secreted factors. Given that numerous SAMs appear altered by synaptic activity, in vivo, these molecules may be used to dynamically scale up or scale down synaptic communication. Many SAMs, including neurexins, neuroligins, cadherins, and contactins, are now implicated in neuropsychiatric and neurodevelopmental diseases, such as autism spectrum disorder, schizophrenia, and bipolar disorder and studying their molecular mechanisms holds promise for developing novel therapeutics.

  8. Insights into neural crest development from studies of avian embryos

    OpenAIRE

    Gandhi, Shashank; Bronner, Marianne E.

    2018-01-01

    The neural crest is a multipotent and highly migratory cell type that contributes to many of the defining features of vertebrates, including the skeleton of the head and most of the peripheral nervous system. 150 years after the discovery of the neural crest, avian embryos remain one of the most important model organisms for studying neural crest development. In this review, we describe aspects of neural crest induction, migration and axial level differences, highlighting what is known about ...

  9. Long-Term Synaptic Plasticity Emulated in Modified Graphene Oxide Electrolyte Gated IZO-Based Thin-Film Transistors.

    Science.gov (United States)

    Yang, Yi; Wen, Juan; Guo, Liqiang; Wan, Xiang; Du, Peifu; Feng, Ping; Shi, Yi; Wan, Qing

    2016-11-09

    Emulating neural behaviors at the synaptic level is of great significance for building neuromorphic computational systems and realizing artificial intelligence. Here, oxide-based electric double-layer (EDL) thin-film transistors were fabricated using 3-triethoxysilylpropylamine modified graphene oxide (KH550-GO) electrolyte as the gate dielectrics. Resulting from the EDL effect and electrochemical doping between mobile protons and the indium-zinc-oxide channel layer, long-term synaptic plasticity was emulated in our devices. Synaptic functions including long-term memory, synaptic temporal integration, and dynamic filters were successfully reproduced. In particular, spike rate-dependent plasticity (SRDP), one of the basic learning rules of long-term plasticity in the neural network where the synaptic weight changes according to the rate of presynaptic spikes, was emulated in our devices. Our results may facilitate the development of neuromorphic computational systems.

  10. Mechanisms of input and output synaptic specificity: finding partners, building synapses, and fine-tuning communication.

    Science.gov (United States)

    Rawson, Randi L; Martin, E Anne; Williams, Megan E

    2017-08-01

    For most neurons to function properly, they need to develop synaptic specificity. This requires finding specific partner neurons, building the correct types of synapses, and fine-tuning these synapses in response to neural activity. Synaptic specificity is common at both a neuron's input and output synapses, whereby unique synapses are built depending on the partnering neuron. Neuroscientists have long appreciated the remarkable specificity of neural circuits but identifying molecular mechanisms mediating synaptic specificity has only recently accelerated. Here, we focus on recent progress in understanding input and output synaptic specificity in the mammalian brain. We review newly identified circuit examples for both and the latest research identifying molecular mediators including Kirrel3, FGFs, and DGLα. Lastly, we expect the pace of research on input and output specificity to continue to accelerate with the advent of new technologies in genomics, microscopy, and proteomics. Copyright © 2017 Elsevier Ltd. All rights reserved.

  11. Targeting of NF-κB to Dendritic Spines Is Required for Synaptic Signaling and Spine Development.

    Science.gov (United States)

    Dresselhaus, Erica C; Boersma, Matthew C H; Meffert, Mollie K

    2018-04-25

    Long-term forms of brain plasticity share a requirement for changes in gene expression induced by neuronal activity. Mechanisms that determine how the distinct and overlapping functions of multiple activity-responsive transcription factors, including nuclear factor κB (NF-κB), give rise to stimulus-appropriate neuronal responses remain unclear. We report that the p65/RelA subunit of NF-κB confers subcellular enrichment at neuronal dendritic spines and engineer a p65 mutant that lacks spine enrichment (p65ΔSE) but retains inherent transcriptional activity equivalent to wild-type p65. Wild-type p65 or p65ΔSE both rescue NF-κB-dependent gene expression in p65-deficient murine hippocampal neurons responding to diffuse (PMA/ionomycin) stimulation. In contrast, neurons lacking spine-enriched NF-κB are selectively impaired in NF-κB-dependent gene expression induced by elevated excitatory synaptic stimulation (bicuculline or glycine). We used the setting of excitatory synaptic activity during development that produces NF-κB-dependent growth of dendritic spines to test physiological function of spine-enriched NF-κB in an activity-dependent response. Expression of wild-type p65, but not p65ΔSE, is capable of rescuing spine density to normal levels in p65-deficient pyramidal neurons. Collectively, these data reveal that spatial localization in dendritic spines contributes unique capacities to the NF-κB transcription factor in synaptic activity-dependent responses. SIGNIFICANCE STATEMENT Extensive research has established a model in which the regulation of neuronal gene expression enables enduring forms of plasticity and learning. However, mechanisms imparting stimulus specificity to gene regulation, ensuring biologically appropriate responses, remain incompletely understood. NF-κB is a potent transcription factor with evolutionarily conserved functions in learning and the growth of excitatory synaptic contacts. Neuronal NF-κB is localized in both synapse and

  12. TrkB and PKMζ regulate synaptic localization of PSD-95 in developing cortex

    Science.gov (United States)

    Yoshii, Akira; Murata, Yasunobu; Kim, Jihye; Zhang, Chao; Shokat, Kevan M.; Constantine-Paton, Martha

    2011-01-01

    Post-synaptic density 95 (PSD-95), the major scaffold at excitatory synapses, is critical for synapse maturation and learning. In rodents, eye opening, the onset of pattern vision, triggers a rapid movement of PSD-95 from visual neuron somata to synapses. We previously showed that the PI3 kinase-Akt pathway downstream of BDNF/TrkB signaling stimulates synaptic delivery of PSD-95 via vesicular transport. However, vesicular transport requires PSD-95 palmitoylation to attach it to a lipid membrane. Also PSD-95 insertion at synapses is known to require this lipid modification. Here, we show that BDNF/TrkB signaling is also necessary for PSD-95 palmitoylation and its transport to synapses in mouse visual cortical layer 2/3 neurons. However, palmitoylation of PSD-95 requires the activation of another pathway downstream of BDNF/TrkB, namely signaling through PLCγ and the brain-specific PKC variant PKMζ. We find that PKMζ selectively regulates phosphorylation of the palmitoylation enzyme ZDHHC8. Inhibition of PKMζ results in a reduction of synaptic PSD-95 accumulation in vivo, which can be rescued by over-expression ZDHHC8. Therefore, TrkB and PKMζ, two critical regulators of synaptic plasticity, facilitate PSD-95 targeting to synapses. These results also indicate that palmitoylation can be regulated by a trophic factor. Our findings have implications for neurodevelopmental disorders as well as ageing brains. PMID:21849550

  13. Effects of Spaceflight on Drosophila Neural Development

    Science.gov (United States)

    Keshishian, Haig S.

    1997-01-01

    The major goal from the animal side, however, has been achieved, namely to develop Drosophila lines where we can assay individual neuromuscular endings directly without dissection. This was achieved by means of using the GAL4-UAS system, where we have succeeded in establishing stocks of flies where the key neuromuscular connections can be assayed directly in undissected larvae by means of the expression of endogenously fluorescent reporters in the specific motor endings. The green fluorescent protein (GFP) as a reporter allows scoring of neural anatomy en-masse in whole mount using fluorescent microscopy without the need for either dissection or specific labeling. Two stocks have been developed. The first, which we developed first, uses the S65T mutant form, which has a dramatically brighter expression than the native protein. This animal will use GAL4 drivers with expression under the control of the elav gene, and which will ensure expression in all neurons of the embryo and larva. The second transgenic animal we have developed is of a novel kind, and makes use of dicistronic design, so that two copies of the protein will be expressed per insert. We have also developed a tricistronic form, but this has not yet been transformed into flies, and we do not imagine that this third line will be ready in time for the flight.

  14. Requirement of mouse BCCIP for neural development and progenitor proliferation.

    Directory of Open Access Journals (Sweden)

    Yi-Yuan Huang

    Full Text Available Multiple DNA repair pathways are involved in the orderly development of neural systems at distinct stages. The homologous recombination (HR pathway is required to resolve stalled replication forks and critical for the proliferation of progenitor cells during neural development. BCCIP is a BRCA2 and CDKN1A interacting protein implicated in HR and inhibition of DNA replication stress. In this study, we determined the role of BCCIP in neural development using a conditional BCCIP knock-down mouse model. BCCIP deficiency impaired embryonic and postnatal neural development, causing severe ataxia, cerebral and cerebellar defects, and microcephaly. These development defects are associated with spontaneous DNA damage and subsequent cell death in the proliferative cell populations of the neural system during embryogenesis. With in vitro neural spheroid cultures, BCCIP deficiency impaired neural progenitor's self-renewal capability, and spontaneously activated p53. These data suggest that BCCIP and its anti-replication stress functions are essential for normal neural development by maintaining an orderly proliferation of neural progenitors.

  15. Coupling an aVLSI neuromorphic vision chip to a neurotrophic model of synaptic plasticity: the development of topography.

    Science.gov (United States)

    Elliott, Terry; Kramer, Jörg

    2002-10-01

    We couple a previously studied, biologically inspired neurotrophic model of activity-dependent competitive synaptic plasticity and neuronal development to a neuromorphic retina chip. Using this system, we examine the development and refinement of a topographic mapping between an array of afferent neurons (the retinal ganglion cells) and an array of target neurons. We find that the plasticity model can indeed drive topographic refinement in the presence of afferent activity patterns generated by a real-world device. We examine the resilience of the developing system to the presence of high levels of noise by adjusting the spontaneous firing rate of the silicon neurons.

  16. Synaptic and Cellular Organization of Layer 1 of the Developing Rat Somatosensory Cortex

    Directory of Open Access Journals (Sweden)

    Shruti eMuralidhar

    2014-01-01

    Full Text Available We have performed a systematic and quantitative study of the neuronal and synaptic organisation of neocortical layer 1 in the somatosensory cortex in juvenile rats (P13 – P16 using multi-neuron patch-clamp and 3D morphology reconstructions. We used both subjective expert based and objective classification to establish distinct morphological groups. According to expert based subjective classification, the neurons were classified into six morphological types: (1 the dense axon neurogliaform cell (NGC-DA and (2 a sparse axon neurogliaform cell (NGC-SA, (3 the horizontal axon cell (HAC and (4 those with descending axonal colaterals (DAC, (5 the large axon cell (LAC and (6 the small axon cell (SAC. We also used objective supervised and unsupervised analyses that confirmed 4 out of the 6 expert proposed groups, namely, DAC, HAC, LAC and a combined NGC. The cells were also classified into 5 electrophysiological types based on the Petilla convention; classical non-adapting (cNAC, burst non-adapting (bNAC, classical adapting (cAC, classical stuttering (cSTUT and classical irregular spiking (cIR. The most common electrophysiological type was the cNAC type (40% and the most commonly encountered morpho-electrical type of neuron was the NGC-DA - cNAC. Layer 1 cells are connected by GABAergic inhibitory synaptic connections with a 7.9% connection probability, as well gap junctions with 5.2% connection probability. Most synaptic connections were mediated by both GABAA and GABAB receptors (62.6%, as observed from the response characteristics to single pulse and train stimulations. A smaller fraction of synaptic connections were mediated exclusively by GABAA (15.4% or GABAB (21.8% receptors. Based on the morphological reconstructions, we found multi-synapse connections with an average of 9 putative synapses per connection. These putative touches were widely distributed with 39% on somata and 61% on dendrites.

  17. AKT signaling displays multifaceted functions in neural crest development.

    Science.gov (United States)

    Sittewelle, Méghane; Monsoro-Burq, Anne H

    2018-05-31

    AKT signaling is an essential intracellular pathway controlling cell homeostasis, cell proliferation and survival, as well as cell migration and differentiation in adults. Alterations impacting the AKT pathway are involved in many pathological conditions in human disease. Similarly, during development, multiple transmembrane molecules, such as FGF receptors, PDGF receptors or integrins, activate AKT to control embryonic cell proliferation, migration, differentiation, and also cell fate decisions. While many studies in mouse embryos have clearly implicated AKT signaling in the differentiation of several neural crest derivatives, information on AKT functions during the earliest steps of neural crest development had remained relatively scarce until recently. However, recent studies on known and novel regulators of AKT signaling demonstrate that this pathway plays critical roles throughout the development of neural crest progenitors. Non-mammalian models such as fish and frog embryos have been instrumental to our understanding of AKT functions in neural crest development, both in neural crest progenitors and in the neighboring tissues. This review combines current knowledge acquired from all these different vertebrate animal models to describe the various roles of AKT signaling related to neural crest development in vivo. We first describe the importance of AKT signaling in patterning the tissues involved in neural crest induction, namely the dorsal mesoderm and the ectoderm. We then focus on AKT signaling functions in neural crest migration and differentiation. Copyright © 2018 Elsevier Inc. All rights reserved.

  18. Evolving networks and the development of neural systems

    International Nuclear Information System (INIS)

    Johnson, Samuel; Marro, J; Torres, Joaquín J

    2010-01-01

    It is now generally assumed that the heterogeneity of most networks in nature probably arises via preferential attachment of some sort. However, the origin of various other topological features, such as degree–degree correlations and related characteristics, is often not clear, and they may arise from specific functional conditions. We show how it is possible to analyse a very general scenario in which nodes can gain or lose edges according to any (e.g., nonlinear) function of local and/or global degree information. Applying our method to two rather different examples of brain development—synaptic pruning in humans and the neural network of the worm C. Elegans—we find that simple biologically motivated assumptions lead to very good agreement with experimental data. In particular, many nontrivial topological features of the worm's brain arise naturally at a critical point

  19. proBDNF Negatively Regulates Neuronal Remodeling, Synaptic Transmission, and Synaptic Plasticity in Hippocampus

    Directory of Open Access Journals (Sweden)

    Jianmin Yang

    2014-05-01

    Full Text Available Experience-dependent plasticity shapes postnatal development of neural circuits, but the mechanisms that refine dendritic arbors, remodel spines, and impair synaptic activity are poorly understood. Mature brain-derived neurotrophic factor (BDNF modulates neuronal morphology and synaptic plasticity, including long-term potentiation (LTP via TrkB activation. BDNF is initially translated as proBDNF, which binds p75NTR. In vitro, recombinant proBDNF modulates neuronal structure and alters hippocampal long-term plasticity, but the actions of endogenously expressed proBDNF are unclear. Therefore, we generated a cleavage-resistant probdnf knockin mouse. Our results demonstrate that proBDNF negatively regulates hippocampal dendritic complexity and spine density through p75NTR. Hippocampal slices from probdnf mice exhibit depressed synaptic transmission, impaired LTP, and enhanced long-term depression (LTD in area CA1. These results suggest that proBDNF acts in vivo as a biologically active factor that regulates hippocampal structure, synaptic transmission, and plasticity, effects that are distinct from those of mature BDNF.

  20. Advances in Artificial Neural Networks - Methodological Development and Application

    Science.gov (United States)

    Artificial neural networks as a major soft-computing technology have been extensively studied and applied during the last three decades. Research on backpropagation training algorithms for multilayer perceptron networks has spurred development of other neural network training algorithms for other ne...

  1. Synaptic Cell Adhesion

    OpenAIRE

    Missler, Markus; Südhof, Thomas C.; Biederer, Thomas

    2012-01-01

    Chemical synapses are asymmetric intercellular junctions that mediate synaptic transmission. Synaptic junctions are organized by trans-synaptic cell adhesion molecules bridging the synaptic cleft. Synaptic cell adhesion molecules not only connect pre- and postsynaptic compartments, but also mediate trans-synaptic recognition and signaling processes that are essential for the establishment, specification, and plasticity of synapses. A growing number of synaptic cell adhesion molecules that inc...

  2. Xenopus reduced folate carrier regulates neural crest development epigenetically.

    Directory of Open Access Journals (Sweden)

    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.

  3. Novel roles for immune molecules in neural development: Implications for neurodevelopmental disoders

    Directory of Open Access Journals (Sweden)

    Paula A Garay

    2010-09-01

    Full Text Available Although the brain has classically been considered "immune-privileged," current research suggests extensive communication between the nervous and the immune systems in both health and disease. Recent studies demonstrate that immune molecules are present at the right place and time to modulate the development and function of the healthy and diseased CNS. Indeed, immune molecules play integral roles in the CNS throughout neural development, including affecting neurogenesis, neuronal migration, axon guidance, synapse formation, activity-dependent refinement of circuits, and synaptic plasticity. Moreover, the roles of individual immune molecules in the nervous system may change over development. This review focuses on the effects of immune molecules on neuronal connections in the mammalian central nervous system—specifically the roles for MHCI and its receptors, complement, and cytokines on the function, refinement, and plasticity of cortical and hippocampal synapses and their relationship to neurodevelopmental disorders. These functions for immune molecules during neural development suggest that they could also mediate pathological responses to chronic elevations of cytokines in neurodevelopmental disorders, including autism spectrum disorders (ASD and schizophrenia.

  4. Spike Pattern Structure Influences Synaptic Efficacy Variability Under STDP and Synaptic Homeostasis. I: Spike Generating Models on Converging Motifs

    Directory of Open Access Journals (Sweden)

    Zedong eBi

    2016-02-01

    Full Text Available In neural systems, synaptic plasticity is usually driven by spike trains. Due to the inherent noises of neurons and synapses as well as the randomness of connection details, spike trains typically exhibit variability such as spatial randomness and temporal stochasticity, resulting in variability of synaptic changes under plasticity, which we call efficacy variability. How the variability of spike trains influences the efficacy variability of synapses remains unclear. In this paper, we try to understand this influence under pair-wise additive spike-timing dependent plasticity (STDP when the mean strength of plastic synapses into a neuron is bounded (synaptic homeostasis. Specifically, we systematically study, analytically and numerically, how four aspects of statistical features, i.e. synchronous firing, burstiness/regularity, heterogeneity of rates and heterogeneity of cross-correlations, as well as their interactions influence the efficacy variability in converging motifs (simple networks in which one neuron receives from many other neurons. Neurons (including the post-synaptic neuron in a converging motif generate spikes according to statistical models with tunable parameters. In this way, we can explicitly control the statistics of the spike patterns, and investigate their influence onto the efficacy variability, without worrying about the feedback from synaptic changes onto the dynamics of the post-synaptic neuron. We separate efficacy variability into two parts: the drift part (DriftV induced by the heterogeneity of change rates of different synapses, and the diffusion part (DiffV induced by weight diffusion caused by stochasticity of spike trains. Our main findings are: (1 synchronous firing and burstiness tend to increase DiffV, (2 heterogeneity of rates induces DriftV when potentiation and depression in STDP are not balanced, and (3 heterogeneity of cross-correlations induces DriftV together with heterogeneity of rates. We anticipate our

  5. Brain-Derived Neurotrophic Factor Increases Synaptic Protein Levels via the MAPK/Erk Signaling Pathway and Nrf2/Trx Axis Following the Transplantation of Neural Stem Cells in a Rat Model of Traumatic Brain Injury.

    Science.gov (United States)

    Chen, Tao; Wu, Yu; Wang, Yuzi; Zhu, Jigao; Chu, Haiying; Kong, Li; Yin, Liangwei; Ma, Haiying

    2017-11-01

    Brain-derived neurotrophic factor (BDNF) plays an important role in promoting the growth, differentiation, survival and synaptic stability of neurons. Presently, the transplantation of neural stem cells (NSCs) is known to induce neural repair to some extent after injury or disease. In this study, to investigate whether NSCs genetically modified to encode the BDNF gene (BDNF/NSCs) would further enhance synaptogenesis, BDNF/NSCs or naive NSCs were directly engrafted into lesions in a rat model of traumatic brain injury (TBI). Immunohistochemistry, western blotting and RT-PCR were performed to detect synaptic proteins, BDNF-TrkB and its downstream signaling pathways, at 1, 2, 3 or 4 weeks after transplantation. Our results showed that BDNF significantly increased the expression levels of the TrkB receptor gene and the phosphorylation of the TrkB protein in the lesions. The expression levels of Ras, phosphorylated Erk1/2 and postsynaptic density protein-95 were elevated in the BDNF/NSCs-transplanted groups compared with those in the NSCs-transplanted groups throughout the experimental period. Moreover, the nuclear factor (erythroid-derived 2)-like 2/Thioredoxin (Nrf2/Trx) axis, which is a specific therapeutic target for the treatment of injury or cell death, was upregulated by BDNF overexpression. Therefore, we determined that the increased synaptic proteins level implicated in synaptogenesis might be associated with the activation of the MAPK/Erk1/2 signaling pathway and the upregulation of the antioxidant agent Trx modified by BDNF-TrkB following the BDNF/NSCs transplantation after TBI.

  6. Synaptic neurochemistry: Potential targets for the development of new tracer imaging methods

    International Nuclear Information System (INIS)

    Frey, K.A.

    1991-01-01

    Radiotracer techniques for measuring biochemical and pharmacologic processes unique to the synapse and to chemically defined neuronal populations are now under investigation. These methods make use of neuronal biochemical specializations determined by invasive animal experiments and confirmed by human biopsy and autopsy. Early investigators focused on determination of neurotransmitter receptors. More recently, attention has turned to evaluation of presynaptic markers such as steps in neurotransmitter synthesis, storage and degradation, and to the potential evaluation of new postsynaptic markers, including chemical second-messenger activities and receptor-grated ion channel distributions. In this review, synaptic neurochemistry is presented with attention to potential radiotracer imaging methods. Strategies for selecting and applying neuropharmacologic methods to disorders of the human brain are outlined. The methodological requirements of new radiotracer imaging techniques are summarized according to their desired application. Finally, distinctions between in vitro and in vivo measurements of these processes are outlined, along with strategies for detecting such differences

  7. Cyclic adenosine monophosphate metabolism in synaptic growth, strength, and precision: neural and behavioral phenotype-specific counterbalancing effects between dnc phosphodiesterase and rut adenylyl cyclase mutations.

    Science.gov (United States)

    Ueda, Atsushi; Wu, Chun-Fang

    2012-03-01

    Two classic learning mutants in Drosophila, rutabaga (rut) and dunce (dnc), are defective in cyclic adenosine monophosphate (cAMP) synthesis and degradation, respectively, exhibiting a variety of neuronal and behavioral defects. We ask how the opposing effects of these mutations on cAMP levels modify subsets of phenotypes, and whether any specific phenotypes could be ameliorated by biochemical counter balancing effects in dnc rut double mutants. Our study at larval neuromuscular junctions (NMJs) demonstrates that dnc mutations caused severe defects in nerve terminal morphology, characterized by unusually large synaptic boutons and aberrant innervation patterns. Interestingly, a counterbalancing effect led to rescue of the aberrant innervation patterns but the enlarged boutons in dnc rut double mutant remained as extreme as those in dnc. In contrast to dnc, rut mutations strongly affect synaptic transmission. Focal loose-patch recording data accumulated over 4 years suggest that synaptic currents in rut boutons were characterized by unusually large temporal dispersion and a seasonal variation in the amount of transmitter release, with diminished synaptic currents in summer months. Experiments with different rearing temperatures revealed that high temperature (29-30°C) decreased synaptic transmission in rut, but did not alter dnc and wild-type (WT). Importantly, the large temporal dispersion and abnormal temperature dependence of synaptic transmission, characteristic of rut, still persisted in dnc rut double mutants. To interpret these results in a proper perspective, we reviewed previously documented differential effects of dnc and rut mutations and their genetic interactions in double mutants on a variety of physiological and behavioral phenotypes. The cases of rescue in double mutants are associated with gradual developmental and maintenance processes whereas many behavioral and physiological manifestations on faster time scales could not be rescued. We discuss

  8. Cyclic-AMP metabolism in synaptic growth, strength and precision: Neural and behavioral phenotype-specific counterbalancing effects between dnc PDE and rut AC mutations

    Science.gov (United States)

    Ueda, Atsushi; Wu, Chun-Fang

    2012-01-01

    Two classic learning mutants in Drosophila, rutabaga (rut) and dunce (dnc), are defective in cAMP synthesis and degradation, respectively, exhibiting a variety of neuronal and behavioral defects. We ask how the opposing effects of these mutations on cAMP levels modify subsets of phenotypes, and whether any specific phenotypes could be ameliorated by biochemical counter balancing effects in dnc rut double mutants. Our study at larval neuromuscular junctions (NMJs) demonstrate that dnc mutations caused severe defects in nerve terminal morphology, characterized by unusually large synaptic boutons and aberrant innervation patterns. Interestingly, a counterbalancing effect led to rescue of the aberrant innervation patterns but the enlarged boutons in dnc rut double mutant remained as extreme as those in dnc. In contrast to dnc, rut mutations strongly affect synaptic transmission. Focal loose-patch recording data accumulated over 4 years suggest that synaptic currents in rut boutons were characterized by unusually large temporal dispersion and a seasonal variation in the amount of transmitter release, with diminished synaptic currents in summer months. Experiments with different rearing temperatures revealed that high temperature (29–30 °C) decreased synaptic transmission in rut, but did not alter dnc and WT. Importantly, the large temporal dispersion and abnormal temperature dependence of synaptic transmission, characteristic of rut, still persisted in dnc rut double mutants. To interpret these results in a proper perspective, we reviewed previously documented differential effects of dnc and rut mutations and their genetic interactions in double mutants on a variety of physiological and behavioral phenotypes. The cases of rescue in double mutants are associated with gradual developmental and maintenance processes whereas many behavioral and physiological manifestations on faster time scales could not be rescued. We discuss factors that could contribute to the

  9. Factors Influencing Short-term Synaptic Plasticity in the Avian Cochlear Nucleus Magnocellularis

    Directory of Open Access Journals (Sweden)

    Jason Tait Sanchez Quinones

    2015-01-01

    Full Text Available Defined as reduced neural responses during high rates of activity, synaptic depression is a form of short-term plasticity important for the temporal filtering of sound. In the avian cochlear nucleus magnocellularis (NM, an auditory brainstem structure, mechanisms regulating short-term synaptic depression include pre-, post-, and extrasynaptic factors. Using varied paired-pulse stimulus intervals, we found that the time course of synaptic depression lasts up to four seconds at late-developing NM synapses. Synaptic depression was largely reliant on exogenous Ca 2+ -dependent probability of presynaptic neurotransmitter release, and to a lesser extent, on the desensitization of postsynaptic α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid-type glutamate receptor (AMPA-R. Interestingly, although extrasynaptic glutamate clearance did not play a significant role in regulating synaptic depression, blocking glutamate clearance at early-developing synapses altered synaptic dynamics, changing responses from depression to facilitation. These results suggest a developmental shift in the relative reliance on pre-, post-, and extrasynaptic factors in regulating short-term synaptic plasticity in NM.

  10. Calsyntenins Are Expressed in a Dynamic and Partially Overlapping Manner during Neural Development

    Directory of Open Access Journals (Sweden)

    Gemma de Ramon Francàs

    2017-08-01

    Full Text Available Calsyntenins form a family of linker proteins between distinct populations of vesicles and kinesin motors for axonal transport. They were implicated in synapse formation and synaptic plasticity by findings in worms, mice and humans. These findings were in accordance with the postsynaptic localization of the Calsyntenins in the adult brain. However, they also affect the formation of neural circuits, as loss of Calsyntenin-1 (Clstn1 was shown to interfere with axonal branching and axon guidance. Despite the fact that Calsyntenins were discovered originally in embryonic chicken motoneurons, their distribution in the developing nervous system has not been analyzed in detail so far. Here, we summarize our analysis of the temporal and spatial expression patterns of the cargo-docking proteins Clstn1, Clstn2 and Clstn3 during neural development by comparing the dynamic distribution of their mRNAs by in situ hybridization in the spinal cord, the cerebellum, the retina and the tectum, as well as in the dorsal root ganglia (DRG.

  11. Advances in Artificial Neural Networks – Methodological Development and Application

    Directory of Open Access Journals (Sweden)

    Yanbo Huang

    2009-08-01

    Full Text Available Artificial neural networks as a major soft-computing technology have been extensively studied and applied during the last three decades. Research on backpropagation training algorithms for multilayer perceptron networks has spurred development of other neural network training algorithms for other networks such as radial basis function, recurrent network, feedback network, and unsupervised Kohonen self-organizing network. These networks, especially the multilayer perceptron network with a backpropagation training algorithm, have gained recognition in research and applications in various scientific and engineering areas. In order to accelerate the training process and overcome data over-fitting, research has been conducted to improve the backpropagation algorithm. Further, artificial neural networks have been integrated with other advanced methods such as fuzzy logic and wavelet analysis, to enhance the ability of data interpretation and modeling and to avoid subjectivity in the operation of the training algorithm. In recent years, support vector machines have emerged as a set of high-performance supervised generalized linear classifiers in parallel with artificial neural networks. A review on development history of artificial neural networks is presented and the standard architectures and algorithms of artificial neural networks are described. Furthermore, advanced artificial neural networks will be introduced with support vector machines, and limitations of ANNs will be identified. The future of artificial neural network development in tandem with support vector machines will be discussed in conjunction with further applications to food science and engineering, soil and water relationship for crop management, and decision support for precision agriculture. Along with the network structures and training algorithms, the applications of artificial neural networks will be reviewed as well, especially in the fields of agricultural and biological

  12. Quantum neural networks: Current status and prospects for development

    Science.gov (United States)

    Altaisky, M. V.; Kaputkina, N. E.; Krylov, V. A.

    2014-11-01

    The idea of quantum artificial neural networks, first formulated in [34], unites the artificial neural network concept with the quantum computation paradigm. Quantum artificial neural networks were first systematically considered in the PhD thesis by T. Menneer (1998). Based on the works of Menneer and Narayanan [42, 43], Kouda, Matsui, and Nishimura [35, 36], Altaisky [2, 68], Zhou [67], and others, quantum-inspired learning algorithms for neural networks were developed, and are now used in various training programs and computer games [29, 30]. The first practically realizable scaled hardware-implemented model of the quantum artificial neural network is obtained by D-Wave Systems, Inc. [33]. It is a quantum Hopfield network implemented on the basis of superconducting quantum interference devices (SQUIDs). In this work we analyze possibilities and underlying principles of an alternative way to implement quantum neural networks on the basis of quantum dots. A possibility of using quantum neural network algorithms in automated control systems, associative memory devices, and in modeling biological and social networks is examined.

  13. Development of nuclear power plant diagnosis technique using neural networks

    International Nuclear Information System (INIS)

    Horiguchi, Masahiro; Fukawa, Naohiro; Nishimura, Kazuo

    1991-01-01

    A nuclear power plant diagnosis technique has been developed, called transient phenomena analysis, which employs neural network. The neural networks identify malfunctioning equipment by recognizing the pattern of main plant parameters, making it possible to locate the cause of an abnormality when a plant is in a transient state. In a case where some piece of equipment shows abnormal behavior, many plant parameters either directly or indirectly related to that equipment change simultaneously. When an abrupt change in a plant parameter is detected, changes in the 49 main plant parameters are classified into three types and a characteristic change pattern consisting of 49 data is defined. The neural networks then judge the cause of the abnormality from this pattern. This neural-network-based technique can recognize 100 patterns that are characterized by the causes of plant abnormality. (author)

  14. Molecular parallels between neural and vascular development.

    Science.gov (United States)

    Eichmann, Anne; Thomas, Jean-Léon

    2013-01-01

    The human central nervous system (CNS) features a network of ~400 miles of blood vessels that receives >20% of the body's cardiac output and uses most of its blood glucose. Many human diseases, including stroke, retinopathy, and cancer, are associated with the biology of CNS blood vessels. These vessels originate from extrinsic cell populations, including endothelial cells and pericytes that colonize the CNS and interact with glia and neurons to establish the blood-brain barrier and control cerebrovascular exchanges. Neurovascular interactions also play important roles in adult neurogenic niches, which harbor a unique population of neural stem cells that are intimately associated with blood vessels. We here review the cellular and molecular mechanisms required to establish the CNS vascular network, with a special focus on neurovascular interactions and the functions of vascular endothelial growth factors.

  15. A Voltage Mode Memristor Bridge Synaptic Circuit with Memristor Emulators

    Directory of Open Access Journals (Sweden)

    Leon Chua

    2012-03-01

    Full Text Available A memristor bridge neural circuit which is able to perform signed synaptic weighting was proposed in our previous study, where the synaptic operation was verified via software simulation of the mathematical model of the HP memristor. This study is an extension of the previous work advancing toward the circuit implementation where the architecture of the memristor bridge synapse is built with memristor emulator circuits. In addition, a simple neural network which performs both synaptic weighting and summation is built by combining memristor emulators-based synapses and differential amplifier circuits. The feasibility of the memristor bridge neural circuit is verified via SPICE simulations.

  16. Active hippocampal networks undergo spontaneous synaptic modification.

    Directory of Open Access Journals (Sweden)

    Masako Tsukamoto-Yasui

    Full Text Available The brain is self-writable; as the brain voluntarily adapts itself to a changing environment, the neural circuitry rearranges its functional connectivity by referring to its own activity. How the internal activity modifies synaptic weights is largely unknown, however. Here we report that spontaneous activity causes complex reorganization of synaptic connectivity without any external (or artificial stimuli. Under physiologically relevant ionic conditions, CA3 pyramidal cells in hippocampal slices displayed spontaneous spikes with bistable slow oscillations of membrane potential, alternating between the so-called UP and DOWN states. The generation of slow oscillations did not require fast synaptic transmission, but their patterns were coordinated by local circuit activity. In the course of generating spontaneous activity, individual neurons acquired bidirectional long-lasting synaptic modification. The spontaneous synaptic plasticity depended on a rise in intracellular calcium concentrations of postsynaptic cells, but not on NMDA receptor activity. The direction and amount of the plasticity varied depending on slow oscillation patterns and synapse locations, and thus, they were diverse in a network. Once this global synaptic refinement occurred, the same neurons now displayed different patterns of spontaneous activity, which in turn exhibited different levels of synaptic plasticity. Thus, active networks continuously update their internal states through ongoing synaptic plasticity. With computational simulations, we suggest that with this slow oscillation-induced plasticity, a recurrent network converges on a more specific state, compared to that with spike timing-dependent plasticity alone.

  17. Development of target-tracking algorithms using neural network

    Energy Technology Data Exchange (ETDEWEB)

    Park, Dong Sun; Lee, Joon Whaoan; Yoon, Sook; Baek, Seong Hyun; Lee, Myung Jae [Chonbuk National University, Chonjoo (Korea)

    1998-04-01

    The utilization of remote-control robot system in atomic power plants or nuclear-related facilities grows rapidly, to protect workers form high radiation environments. Such applications require complete stability of the robot system, so that precisely tracking the robot is essential for the whole system. This research is to accomplish the goal by developing appropriate algorithms for remote-control robot systems. A neural network tracking system is designed and experimented to trace a robot Endpoint. This model is aimed to utilized the excellent capabilities of neural networks; nonlinear mapping between inputs and outputs, learning capability, and generalization capability. The neural tracker consists of two networks for position detection and prediction. Tracking algorithms are developed and experimented for the two models. Results of the experiments show that both models are promising as real-time target-tracking systems for remote-control robot systems. (author). 10 refs., 47 figs.

  18. Temporal and spatial expression of Drosophila DLGS97 during neural development.

    Science.gov (United States)

    Albornoz, Valeria; Mendoza-Topaz, Carolina; Oliva, Carlos; Tello, Judith; Olguín, Patricio; Sierralta, Jimena

    2008-07-01

    The products of the Drosophila discs-large (dlg) gene are members of the MAGUK family of proteins, a group of proteins involved in localization, transport and recycling of receptors and channels in cell junctions, including the synapse. In vertebrates, four genes with multiple splice variants homologous to dlg are described. dlg originates two main proteins, DLGA, similar to the vertebrate neuronal protein PSD95, and DLGS97, similar to the vertebrate neuronal and epithelial protein SAP97. DLGA is expressed in epithelia, neural tissue and muscle. DLGS97 is expressed in neural tissue and muscle but not in epithelia. The distinctive difference between them is the presence in DLGS97 of an L27 domain. The differential expression between these variants makes the study of DLGS97 of key relevance to understand the in vivo role of synaptic MAGUKs in neurons. Here we present the temporal and spatial expression pattern of DLGS97 during embryonic and larval nervous system development, during eye development and in adult brain. Our results show that DLGS97 is expressed zygotically, in neurons in the embryo, larvae and adult, and is absent at all stages in glial cells. During eye development DLGS97 starts to be expressed in photoreceptor cells at early stages of differentiation and localizes basal to the basolateral junctions. In the brain, DLGS97 is expressed in the mushroom bodies and optic lobes at larval and adult stages; and in the antennal lobe in the adult stage. In addition we show that both, dlgS97 and dlgA transcripts, express during development multiple splice variants with differences in the use of exons in two sites.

  19. Synaptic long-term potentiation and depression in the rat medial vestibular nuclei depend on neural activation of estrogenic and androgenic signals.

    Science.gov (United States)

    Scarduzio, Mariangela; Panichi, Roberto; Pettorossi, Vito Enrico; Grassi, Silvarosa

    2013-01-01

    Estrogenic and androgenic steroids can be synthesised in the brain and rapidly modulate synaptic transmission and plasticity through direct interaction with membrane receptors for estrogens (ERs) and androgens (ARs). We used whole cell patch clamp recordings in brainstem slices of male rats to explore the influence of ER and AR activation and local synthesis of 17β-estradiol (E2) and 5α-dihydrotestosterone (DHT) on the long-term synaptic changes induced in the neurons of the medial vestibular nucleus (MVN). Long-term depression (LTD) and long-term potentiation (LTP) caused by different patterns of high frequency stimulation (HFS) of the primary vestibular afferents were assayed under the blockade of ARs and ERs or in the presence of inhibitors for enzymes synthesizing DHT (5α-reductase) and E2 (P450-aromatase) from testosterone (T). We found that LTD is mediated by interaction of locally produced androgens with ARs and LTP by interaction of locally synthesized E2 with ERs. In fact, the AR block with flutamide prevented LTD while did not affect LTP, and the blockade of ERs with ICI 182,780 abolished LTP without influencing LTD. Moreover, the block of P450-aromatase with letrozole not only prevented the LTP induction, but inverted LTP into LTD. This LTD is likely due to the local activation of androgens, since it was abolished under blockade of ARs. Conversely, LTD was still induced in the presence of finasteride the inhibitor of 5α-reductase demonstrating that T is able to activate ARs and induce LTD even when DHT is not synthesized. This study demonstrates a key and opposite role of sex neurosteroids in the long-term synaptic changes of the MVN with a specific role of T-DHT for LTD and of E2 for LTP. Moreover, it suggests that different stimulation patterns can lead to LTD or LTP by specifically activating the enzymes involved in the synthesis of androgenic or estrogenic neurosteroids.

  20. Podocalyxin Is a Novel Polysialylated Neural Adhesion Protein with Multiple Roles in Neural Development and Synapse Formation

    Science.gov (United States)

    Vitureira, Nathalia; Andrés, Rosa; Pérez-Martínez, Esther; Martínez, Albert; Bribián, Ana; Blasi, Juan; Chelliah, Shierley; López-Doménech, Guillermo; De Castro, Fernando; Burgaya, Ferran; McNagny, Kelly; Soriano, Eduardo

    2010-01-01

    Neural development and plasticity are regulated by neural adhesion proteins, including the polysialylated form of NCAM (PSA-NCAM). Podocalyxin (PC) is a renal PSA-containing protein that has been reported to function as an anti-adhesin in kidney podocytes. Here we show that PC is widely expressed in neurons during neural development. Neural PC interacts with the ERM protein family, and with NHERF1/2 and RhoA/G. Experiments in vitro and phenotypic analyses of podxl-deficient mice indicate that PC is involved in neurite growth, branching and axonal fasciculation, and that PC loss-of-function reduces the number of synapses in the CNS and in the neuromuscular system. We also show that whereas some of the brain PC functions require PSA, others depend on PC per se. Our results show that PC, the second highly sialylated neural adhesion protein, plays multiple roles in neural development. PMID:20706633

  1. msh/Msx gene family in neural development.

    Science.gov (United States)

    Ramos, Casto; Robert, Benoît

    2005-11-01

    The involvement of Msx homeobox genes in skull and tooth formation has received a great deal of attention. Recent studies also indicate a role for the msh/Msx gene family in development of the nervous system. In this article, we discuss the functions of these transcription factors in neural-tissue organogenesis. We will deal mainly with the interactions of the Drosophila muscle segment homeobox (msh) gene with other homeobox genes and the repressive cascade that leads to neuroectoderm patterning; the role of Msx genes in neural-crest induction, focusing especially on the differences between lower and higher vertebrates; their implication in patterning of the vertebrate neural tube, particularly in diencephalon midline formation. Finally, we will examine the distinct activities of Msx1, Msx2 and Msx3 genes during neurogenesis, taking into account their relationships with signalling molecules such as BMP.

  2. A Constructive Neural-Network Approach to Modeling Psychological Development

    Science.gov (United States)

    Shultz, Thomas R.

    2012-01-01

    This article reviews a particular computational modeling approach to the study of psychological development--that of constructive neural networks. This approach is applied to a variety of developmental domains and issues, including Piagetian tasks, shift learning, language acquisition, number comparison, habituation of visual attention, concept…

  3. Development of a hybrid system of artificial neural networks and ...

    African Journals Online (AJOL)

    Development of a hybrid system of artificial neural networks and artificial bee colony algorithm for prediction and modeling of customer choice in the market. ... attempted to present a new method for the modeling and prediction of customer choice in the market using the combination of artificial intelligence and data mining.

  4. Hopfield neural network in HEP track reconstruction

    International Nuclear Information System (INIS)

    Muresan, R.; Pentia, M.

    1997-01-01

    In experimental particle physics, pattern recognition problems, specifically for neural network methods, occur frequently in track finding or feature extraction. Track finding is a combinatorial optimization problem. Given a set of points in Euclidean space, one tries the reconstruction of particle trajectories, subject to smoothness constraints.The basic ingredients in a neural network are the N binary neurons and the synaptic strengths connecting them. In our case the neurons are the segments connecting all possible point pairs.The dynamics of the neural network is given by a local updating rule wich evaluates for each neuron the sign of the 'upstream activity'. An updating rule in the form of sigmoid function is given. The synaptic strengths are defined in terms of angle between the segments and the lengths of the segments implied in the track reconstruction. An algorithm based on Hopfield neural network has been developed and tested on the track coordinates measured by silicon microstrip tracking system

  5. Development of inhibitory synaptic inputs on layer 2/3 pyramidal neurons in the rat medial prefrontal cortex

    KAUST Repository

    Virtanen, Mari A.; Lacoh, Claudia Marvine; Fiumelli, Hubert; Kosel, Markus; Tyagarajan, Shiva; de Roo, Mathias; Vutskits, Laszlo

    2018-01-01

    Inhibitory control of pyramidal neurons plays a major role in governing the excitability in the brain. While spatial mapping of inhibitory inputs onto pyramidal neurons would provide important structural data on neuronal signaling, studying their distribution at the single cell level is difficult due to the lack of easily identifiable anatomical proxies. Here, we describe an approach where in utero electroporation of a plasmid encoding for fluorescently tagged gephyrin into the precursors of pyramidal cells along with ionotophoretic injection of Lucifer Yellow can reliably and specifically detect GABAergic synapses on the dendritic arbour of single pyramidal neurons. Using this technique and focusing on the basal dendritic arbour of layer 2/3 pyramidal cells of the medial prefrontal cortex, we demonstrate an intense development of GABAergic inputs onto these cells between postnatal days 10 and 20. While the spatial distribution of gephyrin clusters was not affected by the distance from the cell body at postnatal day 10, we found that distal dendritic segments appeared to have a higher gephyrin density at later developmental stages. We also show a transient increase around postnatal day 20 in the percentage of spines that are carrying a gephyrin cluster, indicative of innervation by a GABAergic terminal. Since the precise spatial arrangement of synaptic inputs is an important determinant of neuronal responses, we believe that the method described in this work may allow a better understanding of how inhibition settles together with excitation, and serve as basics for further modelling studies focusing on the geometry of dendritic inhibition during development.

  6. Development of inhibitory synaptic inputs on layer 2/3 pyramidal neurons in the rat medial prefrontal cortex

    KAUST Repository

    Virtanen, Mari A.

    2018-01-10

    Inhibitory control of pyramidal neurons plays a major role in governing the excitability in the brain. While spatial mapping of inhibitory inputs onto pyramidal neurons would provide important structural data on neuronal signaling, studying their distribution at the single cell level is difficult due to the lack of easily identifiable anatomical proxies. Here, we describe an approach where in utero electroporation of a plasmid encoding for fluorescently tagged gephyrin into the precursors of pyramidal cells along with ionotophoretic injection of Lucifer Yellow can reliably and specifically detect GABAergic synapses on the dendritic arbour of single pyramidal neurons. Using this technique and focusing on the basal dendritic arbour of layer 2/3 pyramidal cells of the medial prefrontal cortex, we demonstrate an intense development of GABAergic inputs onto these cells between postnatal days 10 and 20. While the spatial distribution of gephyrin clusters was not affected by the distance from the cell body at postnatal day 10, we found that distal dendritic segments appeared to have a higher gephyrin density at later developmental stages. We also show a transient increase around postnatal day 20 in the percentage of spines that are carrying a gephyrin cluster, indicative of innervation by a GABAergic terminal. Since the precise spatial arrangement of synaptic inputs is an important determinant of neuronal responses, we believe that the method described in this work may allow a better understanding of how inhibition settles together with excitation, and serve as basics for further modelling studies focusing on the geometry of dendritic inhibition during development.

  7. Synaptic long-term potentiation and depression in the rat medial vestibular nuclei depend on neural activation of estrogenic and androgenic signals.

    Directory of Open Access Journals (Sweden)

    Mariangela Scarduzio

    Full Text Available Estrogenic and androgenic steroids can be synthesised in the brain and rapidly modulate synaptic transmission and plasticity through direct interaction with membrane receptors for estrogens (ERs and androgens (ARs. We used whole cell patch clamp recordings in brainstem slices of male rats to explore the influence of ER and AR activation and local synthesis of 17β-estradiol (E2 and 5α-dihydrotestosterone (DHT on the long-term synaptic changes induced in the neurons of the medial vestibular nucleus (MVN. Long-term depression (LTD and long-term potentiation (LTP caused by different patterns of high frequency stimulation (HFS of the primary vestibular afferents were assayed under the blockade of ARs and ERs or in the presence of inhibitors for enzymes synthesizing DHT (5α-reductase and E2 (P450-aromatase from testosterone (T. We found that LTD is mediated by interaction of locally produced androgens with ARs and LTP by interaction of locally synthesized E2 with ERs. In fact, the AR block with flutamide prevented LTD while did not affect LTP, and the blockade of ERs with ICI 182,780 abolished LTP without influencing LTD. Moreover, the block of P450-aromatase with letrozole not only prevented the LTP induction, but inverted LTP into LTD. This LTD is likely due to the local activation of androgens, since it was abolished under blockade of ARs. Conversely, LTD was still induced in the presence of finasteride the inhibitor of 5α-reductase demonstrating that T is able to activate ARs and induce LTD even when DHT is not synthesized. This study demonstrates a key and opposite role of sex neurosteroids in the long-term synaptic changes of the MVN with a specific role of T-DHT for LTD and of E2 for LTP. Moreover, it suggests that different stimulation patterns can lead to LTD or LTP by specifically activating the enzymes involved in the synthesis of androgenic or estrogenic neurosteroids.

  8. Palmitoylation-dependent CDKL5–PSD-95 interaction regulates synaptic targeting of CDKL5 and dendritic spine development

    Science.gov (United States)

    Zhu, Yong-Chuan; Li, Dan; Wang, Lu; Lu, Bin; Zheng, Jing; Zhao, Shi-Lin; Zeng, Rong; Xiong, Zhi-Qi

    2013-01-01

    The X-linked gene cyclin-dependent kinase-like 5 (CDKL5) is mutated in severe neurodevelopmental disorders, including some forms of atypical Rett syndrome, but the function and regulation of CDKL5 protein in neurons remain to be elucidated. Here, we show that CDKL5 binds to the scaffolding protein postsynaptic density (PSD)-95, and that this binding promotes the targeting of CDKL5 to excitatory synapses. Interestingly, this binding is not constitutive, but governed by palmitate cycling on PSD-95. Furthermore, pathogenic mutations that truncate the C-terminal tail of CDKL5 diminish its binding to PSD-95 and synaptic accumulation. Importantly, down-regulation of CDKL5 by RNA interference (RNAi) or interference with the CDKL5–PSD-95 interaction inhibits dendritic spine formation and growth. These results demonstrate a critical role of the palmitoylation-dependent CDKL5–PSD-95 interaction in localizing CDKL5 to synapses for normal spine development and suggest that disruption of this interaction by pathogenic mutations may be implicated in the pathogenesis of CDKL5-related disorders. PMID:23671101

  9. Palmitoylation-dependent CDKL5-PSD-95 interaction regulates synaptic targeting of CDKL5 and dendritic spine development.

    Science.gov (United States)

    Zhu, Yong-Chuan; Li, Dan; Wang, Lu; Lu, Bin; Zheng, Jing; Zhao, Shi-Lin; Zeng, Rong; Xiong, Zhi-Qi

    2013-05-28

    The X-linked gene cyclin-dependent kinase-like 5 (CDKL5) is mutated in severe neurodevelopmental disorders, including some forms of atypical Rett syndrome, but the function and regulation of CDKL5 protein in neurons remain to be elucidated. Here, we show that CDKL5 binds to the scaffolding protein postsynaptic density (PSD)-95, and that this binding promotes the targeting of CDKL5 to excitatory synapses. Interestingly, this binding is not constitutive, but governed by palmitate cycling on PSD-95. Furthermore, pathogenic mutations that truncate the C-terminal tail of CDKL5 diminish its binding to PSD-95 and synaptic accumulation. Importantly, down-regulation of CDKL5 by RNA interference (RNAi) or interference with the CDKL5-PSD-95 interaction inhibits dendritic spine formation and growth. These results demonstrate a critical role of the palmitoylation-dependent CDKL5-PSD-95 interaction in localizing CDKL5 to synapses for normal spine development and suggest that disruption of this interaction by pathogenic mutations may be implicated in the pathogenesis of CDKL5-related disorders.

  10. A neural cell adhesion molecule-derived fibroblast growth factor receptor agonist, the FGL-peptide, promotes early postnatal sensorimotor development and enhances social memory retention

    DEFF Research Database (Denmark)

    Secher, Thomas; Novitskaia, V; Berezin, Vladimir

    2006-01-01

    of coordination skills. In adult animals s.c. administration of FGL resulted in a prolonged retention of social memory. We found that FGL rapidly penetrated into the blood and cerebrospinal fluid after both intranasal and s.c. administration and remained detectable in the fluids for up to 5 hours.......The neural cell adhesion molecule (NCAM) belongs to the immunoglobulin (Ig) superfamily and is composed extracellularly of five Ig-like and two fibronectin type III (F3) modules. It plays a pivotal role in neuronal development and synaptic plasticity. NCAM signals via a direct interaction...

  11. Efficient Coding and Energy Efficiency Are Promoted by Balanced Excitatory and Inhibitory Synaptic Currents in Neuronal Network.

    Science.gov (United States)

    Yu, Lianchun; Shen, Zhou; Wang, Chen; Yu, Yuguo

    2018-01-01

    Selective pressure may drive neural systems to process as much information as possible with the lowest energy cost. Recent experiment evidence revealed that the ratio between synaptic excitation and inhibition (E/I) in local cortex is generally maintained at a certain value which may influence the efficiency of energy consumption and information transmission of neural networks. To understand this issue deeply, we constructed a typical recurrent Hodgkin-Huxley network model and studied the general principles that governs the relationship among the E/I synaptic current ratio, the energy cost and total amount of information transmission. We observed in such a network that there exists an optimal E/I synaptic current ratio in the network by which the information transmission achieves the maximum with relatively low energy cost. The coding energy efficiency which is defined as the mutual information divided by the energy cost, achieved the maximum with the balanced synaptic current. Although background noise degrades information transmission and imposes an additional energy cost, we find an optimal noise intensity that yields the largest information transmission and energy efficiency at this optimal E/I synaptic transmission ratio. The maximization of energy efficiency also requires a certain part of energy cost associated with spontaneous spiking and synaptic activities. We further proved this finding with analytical solution based on the response function of bistable neurons, and demonstrated that optimal net synaptic currents are capable of maximizing both the mutual information and energy efficiency. These results revealed that the development of E/I synaptic current balance could lead a cortical network to operate at a highly efficient information transmission rate at a relatively low energy cost. The generality of neuronal models and the recurrent network configuration used here suggest that the existence of an optimal E/I cell ratio for highly efficient energy

  12. The Synaptic Proteome during Development and Plasticity of the Mouse Visual Cortex

    NARCIS (Netherlands)

    Dahlhaus, M.; Li, K.W.; van der Schors, R.C.; Saiepour, M.H.; van Nierop, P.; Heimel, J.A.; Hermans, J.M.; Loos, M.; Smit, A.B.; Levelt, C.N.

    2011-01-01

    During brain development, the neocortex shows periods of enhanced plasticity, which enables the acquisition of knowledge and skills that we use and build on in adult life. Key to persistent modifications of neuronal connectivity and plasticity of the neocortex are molecular changes occurring at the

  13. Neurotrophin-3 Regulates Synapse Development by Modulating TrkC-PTPσ Synaptic Adhesion and Intracellular Signaling Pathways.

    Science.gov (United States)

    Han, Kyung Ah; Woo, Doyeon; Kim, Seungjoon; Choii, Gayoung; Jeon, Sangmin; Won, Seoung Youn; Kim, Ho Min; Heo, Won Do; Um, Ji Won; Ko, Jaewon

    2016-04-27

    Neurotrophin-3 (NT-3) is a secreted neurotrophic factor that binds neurotrophin receptor tyrosine kinase C (TrkC), which in turn binds to presynaptic protein tyrosine phosphatase σ (PTPσ) to govern excitatory synapse development. However, whether and how NT-3 cooperates with the TrkC-PTPσ synaptic adhesion pathway and TrkC-mediated intracellular signaling pathways in rat cultured neurons has remained unclear. Here, we report that NT-3 enhances TrkC binding affinity for PTPσ. Strikingly, NT-3 treatment bidirectionally regulates the synaptogenic activity of TrkC: at concentrations of 10-25 ng/ml, NT-3 further enhanced the increase in synapse density induced by TrkC overexpression, whereas at higher concentrations, NT-3 abrogated TrkC-induced increases in synapse density. Semiquantitative immunoblotting and optogenetics-based imaging showed that 25 ng/ml NT-3 or light stimulation at a power that produced a comparable level of NT-3 (6.25 μW) activated only extracellular signal-regulated kinase (ERK) and Akt, whereas 100 ng/ml NT-3 (light intensity, 25 μW) further triggered the activation of phospholipase C-γ1 and CREB independently of PTPσ. Notably, disruption of TrkC intracellular signaling pathways, extracellular ligand binding, or kinase activity by point mutations compromised TrkC-induced increases in synapse density. Furthermore, only sparse, but not global, TrkC knock-down in cultured rat neurons significantly decreased synapse density, suggesting that intercellular differences in TrkC expression level are critical for its synapse-promoting action. Together, our data demonstrate that NT-3 is a key factor in excitatory synapse development that may direct higher-order assembly of the TrkC/PTPσ complex and activate distinct intracellular signaling cascades in a concentration-dependent manner to promote competition-based synapse development processes. In this study, we present several lines of experimental evidences to support the conclusion that

  14. Extracellular matrix and its receptors in Drosophila neural development

    Science.gov (United States)

    Broadie, Kendal; Baumgartner, Stefan; Prokop, Andreas

    2011-01-01

    Extracellular matrix (ECM) and matrix receptors are intimately involved in most biological processes. The ECM plays fundamental developmental and physiological roles in health and disease, including processes underlying the development, maintenance and regeneration of the nervous system. To understand the principles of ECM-mediated functions in the nervous system, genetic model organisms like Drosophila provide simple, malleable and powerful experimental platforms. This article provides an overview of ECM proteins and receptors in Drosophila. It then focuses on their roles during three progressive phases of neural development: 1) neural progenitor proliferation, 2) axonal growth and pathfinding and 3) synapse formation and function. Each section highlights known ECM and ECM-receptor components and recent studies done in mutant conditions to reveal their in vivo functions, all illustrating the enormous opportunities provided when merging work on the nervous system with systematic research into ECM-related gene functions. PMID:21688401

  15. Programmed Cell Death and Caspase Functions During Neural Development.

    Science.gov (United States)

    Yamaguchi, Yoshifumi; Miura, Masayuki

    2015-01-01

    Programmed cell death (PCD) is a fundamental component of nervous system development. PCD serves as the mechanism for quantitative matching of the number of projecting neurons and their target cells through direct competition for neurotrophic factors in the vertebrate peripheral nervous system. In addition, PCD plays roles in regulating neural cell numbers, canceling developmental errors or noise, and tissue remodeling processes. These findings are mainly derived from genetic studies that prevent cells from dying by apoptosis, which is a major form of PCD and is executed by activation of evolutionarily conserved cysteine protease caspases. Recent studies suggest that caspase activation can be coordinated in time and space at multiple levels, which might underlie nonapoptotic roles of caspases in neural development in addition to apoptotic roles. © 2015 Elsevier Inc. All rights reserved.

  16. Structural synaptic plasticity in the hippocampus induced by spatial experience and its implications in information processing.

    Science.gov (United States)

    Carasatorre, M; Ramírez-Amaya, V; Díaz Cintra, S

    2016-10-01

    Long-lasting memory formation requires that groups of neurons processing new information develop the ability to reproduce the patterns of neural activity acquired by experience. Changes in synaptic efficiency let neurons organise to form ensembles that repeat certain activity patterns again and again. Among other changes in synaptic plasticity, structural modifications tend to be long-lasting which suggests that they underlie long-term memory. There is a large body of evidence supporting that experience promotes changes in the synaptic structure, particularly in the hippocampus. Structural changes to the hippocampus may be functionally implicated in stabilising acquired memories and encoding new information. Copyright © 2012 Sociedad Española de Neurología. Publicado por Elsevier España, S.L.U. All rights reserved.

  17. The wiring of developing sensory circuits - from patterned spontaneous activity to mechanisms of synaptic plasticity

    Directory of Open Access Journals (Sweden)

    Alexandra Helen Leighton

    2016-09-01

    Full Text Available In order to accurately process incoming sensory stimuli, neurons must be organized into functional networks, with both genetic and environmental factors influencing the precise arrangement of connections between cells. Teasing apart the relative contributions of molecular guidance cues, spontaneous activity and visual experience during this maturation is on-going. During development of the sensory system, the first, rough organization of connections is created by molecular factors. These connections are then modulated by the intrinsically generated activity of neurons, even before the senses have become operational. Spontaneous waves of depolarisations sweep across the nervous system, placing them in a prime position to strengthen correct connections and weaken others, shaping synapses into a useful network. A large body of work now supports the idea that, rather than being a mere side-effect of the system, spontaneous activity actually contains information which readies the nervous system so that, as soon as the senses become active, sensory information can be utilized by the animal. An example is the neonatal mouse. As soon as the eyelids first open, neurons in the cortex respond to visual information without the animal having previously encountered structured sensory input (Cang et al., 2005a; Ko et al., 2013; Rochefort et al., 2011; Zhang et al., 2012. In vivo imaging techniques have advanced considerably, allowing observation of the natural activity in the brain of living animals down to the level of the individual synapse. New (optogenetic methods make it possible to subtly modulate the spatio-temporal properties of activity, aiding our understanding of how these characteristics relate to the function of spontaneous activity. Such experiments have had a huge impact on our knowledge by permitting direct testing of ideas about the plasticity mechanisms at play in the intact system, opening up a provocative range of fresh questions. Here, we

  18. Development switch in neural circuitry underlying odor-malaise learning.

    Science.gov (United States)

    Shionoya, Kiseko; Moriceau, Stephanie; Lunday, Lauren; Miner, Cathrine; Roth, Tania L; Sullivan, Regina M

    2006-01-01

    Fetal and infant rats can learn to avoid odors paired with illness before development of brain areas supporting this learning in adults, suggesting an alternate learning circuit. Here we begin to document the transition from the infant to adult neural circuit underlying odor-malaise avoidance learning using LiCl (0.3 M; 1% of body weight, ip) and a 30-min peppermint-odor exposure. Conditioning groups included: Paired odor-LiCl, Paired odor-LiCl-Nursing, LiCl, and odor-saline. Results showed that Paired LiCl-odor conditioning induced a learned odor aversion in postnatal day (PN) 7, 12, and 23 pups. Odor-LiCl Paired Nursing induced a learned odor preference in PN7 and PN12 pups but blocked learning in PN23 pups. 14C 2-deoxyglucose (2-DG) autoradiography indicated enhanced olfactory bulb activity in PN7 and PN12 pups with odor preference and avoidance learning. The odor aversion in weanling aged (PN23) pups resulted in enhanced amygdala activity in Paired odor-LiCl pups, but not if they were nursing. Thus, the neural circuit supporting malaise-induced aversions changes over development, indicating that similar infant and adult-learned behaviors may have distinct neural circuits.

  19. Bioelectrochemical control of neural cell development on conducting polymers.

    Science.gov (United States)

    Collazos-Castro, Jorge E; Polo, José L; Hernández-Labrado, Gabriel R; Padial-Cañete, Vanesa; García-Rama, Concepción

    2010-12-01

    Electrically conducting polymers hold promise for developing advanced neuroprostheses, bionic systems and neural repair devices. Among them, poly(3, 4-ethylenedioxythiophene) doped with polystyrene sulfonate (PEDOT:PSS) exhibits superior physicochemical properties but biocompatibility issues have limited its use. We describe combinations of electrochemical and molecule self-assembling methods to consistently control neural cell development on PEDOT:PSS while maintaining very low interfacial impedance. Electro-adsorbed polylysine enabled long-term neuronal survival and growth on the nanostructured polymer. Neurite extension was strongly inhibited by an additional layer of PSS or heparin, which in turn could be either removed electrically or further coated with spermine to activate cell growth. Binding basic fibroblast growth factor (bFGF) to the heparin layer inhibited neurons but promoted proliferation and migration of precursor cells. This methodology may orchestrate neural cell behavior on electroactive polymers, thus improving cell/electrode communication in prosthetic devices and providing a platform for tissue repair strategies. Copyright © 2010 Elsevier Ltd. All rights reserved.

  20. Epigenetic Basis of Neuronal and Synaptic Plasticity.

    Science.gov (United States)

    Karpova, Nina N; Sales, Amanda J; Joca, Samia R

    2017-01-01

    Neuronal network and plasticity change as a function of experience. Altered neural connectivity leads to distinct transcriptional programs of neuronal plasticity-related genes. The environmental challenges throughout life may promote long-lasting reprogramming of gene expression and the development of brain disorders. The modifications in neuronal epigenome mediate gene-environmental interactions and are required for activity-dependent regulation of neuronal differentiation, maturation and plasticity. Here, we highlight the latest advances in understanding the role of the main players of epigenetic machinery (DNA methylation and demethylation, histone modifications, chromatin-remodeling enzymes, transposons, and non-coding RNAs) in activity-dependent and long- term neural and synaptic plasticity. The review focuses on both the transcriptional and post-transcriptional regulation of gene expression levels, including the processes of promoter activation, alternative splicing, regulation of stability of gene transcripts by natural antisense RNAs, and alternative polyadenylation. Further, we discuss the epigenetic aspects of impaired neuronal plasticity and the pathogenesis of neurodevelopmental (Rett syndrome, Fragile X Syndrome, genomic imprinting disorders, schizophrenia, and others), stressrelated (mood disorders) and neurodegenerative Alzheimer's, Parkinson's and Huntington's disorders. The review also highlights the pharmacological compounds that modulate epigenetic programming of gene expression, the potential treatment strategies of discussed brain disorders, and the questions that should be addressed during the development of effective and safe approaches for the treatment of brain disorders.

  1. Lateral regulation of synaptic transmission by astrocytes.

    Science.gov (United States)

    Covelo, A; Araque, A

    2016-05-26

    Fifteen years ago the concept of the "tripartite synapse" was proposed to conceptualize the functional view that astrocytes are integral elements of synapses. The signaling exchange between astrocytes and neurons within the tripartite synapse results in the synaptic regulation of synaptic transmission and plasticity through an autocrine form of communication. However, recent evidence indicates that the astrocyte synaptic regulation is not restricted to the active tripartite synapse but can be manifested through astrocyte signaling at synapses relatively distant from active synapses, a process termed lateral astrocyte synaptic regulation. This phenomenon resembles the classical heterosynaptic modulation but is mechanistically different because it involves astrocytes and its properties critically depend on the morphological and functional features of astrocytes. Therefore, the functional concept of the tripartite synapse as a fundamental unit must be expanded to include the interaction between tripartite synapses. Through lateral synaptic regulation, astrocytes serve as an active processing bridge for synaptic interaction and crosstalk between synapses with no direct neuronal connectivity, supporting the idea that neural network function results from the coordinated activity of astrocytes and neurons. Copyright © 2015 IBRO. Published by Elsevier Ltd. All rights reserved.

  2. Role of the adhesion molecule F3/Contactin in synaptic plasticity and memory.

    Science.gov (United States)

    Gulisano, Walter; Bizzoca, Antonella; Gennarini, Gianfranco; Palmeri, Agostino; Puzzo, Daniela

    2017-06-01

    Cell adhesion molecules (CAMs) have a pivotal role in building and maintaining synaptic structures during brain development participating in axonal elongation and pathfinding, glial guidance of neuronal migration, as well as myelination. CAMs expression persists in the adult brain particularly in structures undergoing postnatal neurogenesis and involved in synaptic plasticity and memory as the hippocampus. Among the neural CAMs, we have recently focused on F3/Contactin, a glycosylphosphatidyl inositol-anchored glycoprotein belonging to the immunoglobulin superfamily, involved in neuronal development, synaptic maintenance and organization of neuronal networks. Here, we discuss our recent data suggesting that F3/Contactin exerts a role in hippocampal synaptic plasticity and memory in adult and aged mice. In particular, we have studied long-term potentiation (LTP), spatial and object recognition memory, and phosphorylation of the transcription factor cAMP-Responsive-Element Binding protein (CREB) in a transgenic mouse model of F3/Contactin overexpression. We also investigated whether F3/Contactin might influence neuronal apoptosis and the production of amyloid-beta peptide (Aβ), known to be one of the main pathogenetic hallmarks of Alzheimer's disease (AD). In conclusion, a further understanding of F3/Contactin role in synaptic plasticity and memory might have interesting clinical outcomes in cognitive disorders, such as aging and AD, offering innovative therapeutic opportunities. Copyright © 2016 Elsevier Inc. All rights reserved.

  3. Analysis of synaptic growth and function in Drosophila with an extended larval stage.

    Science.gov (United States)

    Miller, Daniel L; Ballard, Shannon L; Ganetzky, Barry

    2012-10-03

    The Drosophila larval neuromuscular junction (NMJ) is a powerful system for the genetic and molecular analysis of neuronal excitability, synaptic transmission, and synaptic development. However, its use for studying age-dependent processes, such as maintenance of neuronal viability and synaptic stability, are temporally limited by the onset of pupariation and metamorphosis. Here we characterize larval NMJ growth, growth regulation, structure, and function in a developmental variant with an extended third instar (ETI). RNAi-knockdown of the prothoracicotropic hormone receptor, torso, in the ring gland of developing larvae leaves the timing of first and second instar molts largely unchanged, but triples duration of the third instar from 3 to 9.5 d (McBrayer et al., 2007; Rewitz et al., 2009). During this ETI period, NMJs undergo additional growth (adding >50 boutons/NMJ), and this growth remains under the control of the canonical regulators Highwire and the TGFβ/BMP pathway. NMJ growth during the ETI period occurs via addition of new branches, satellite boutons, and interstitial boutons, and continues even after muscle growth levels off. Throughout the ETI, organization of synapses and active zones remains normal, and synaptic transmission is unchanged. These results establish the ETI larval system as a viable model for studying motor neuron diseases and for investigating time-dependent effects of perturbations that impair mechanisms of neuroprotection, synaptic maintenance, and response to neural injury.

  4. Neural control of left ventricular contractility in the dog heart: synaptic interactions of negative inotropic vagal preganglionic neurons in the nucleus ambiguus with tyrosine hydroxylase immunoreactive terminals.

    Science.gov (United States)

    Massari, V J; Dickerson, L W; Gray, A L; Lauenstein, J M; Blinder, K J; Newsome, J T; Rodak, D J; Fleming, T J; Gatti, P J; Gillis, R A

    1998-08-17

    Recent physiological evidence indicates that vagal postganglionic control of left ventricular contractility is mediated by neurons found in a ventricular epicardial fat pad ganglion. In the dog this region has been referred to as the cranial medial ventricular (CMV) ganglion [J.L. Ardell, Structure and function of mammalian intrinsic cardiac neurons, in: J.A. Armour, J.L. Ardell (Eds.). Neurocardiology, Oxford Univ. Press, New York, 1994, pp. 95-114; B.X. Yuan, J.L. Ardell, D.A. Hopkins, A.M. Losier, J.A. Armour, Gross and microscopic anatomy of the canine intrinsic cardiac nervous system, Anat. Rec., 239 (1994) 75-87]. Since activation of the vagal neuronal input to the CMV ganglion reduces left ventricular contractility without influencing cardiac rate or AV conduction, this ganglion contains a functionally selective pool of negative inotropic parasympathetic postganglionic neurons. In the present report we have defined the light microscopic distribution of preganglionic negative inotropic neurons in the CNS which are retrogradely labeled from the CMV ganglion. Some tissues were also processed for the simultaneous immunocytochemical visualization of tyrosine hydroxylase (TH: a marker for catecholaminergic neurons) and examined with both light microscopic and electron microscopic methods. Histochemically visualized neurons were observed in a long slender column in the ventrolateral nucleus ambiguus (NA-VL). The greatest number of retrogradely labeled neurons were observed just rostral to the level of the area postrema. TH perikarya and dendrites were commonly observed interspersed with vagal motoneurons in the NA-VL. TH nerve terminals formed axo-dendritic synapses upon negative inotropic vagal motoneurons, however the origin of these terminals remains to be determined. We conclude that synaptic interactions exist which would permit the parasympathetic preganglionic vagal control of left ventricular contractility to be modulated monosynaptically by

  5. Memristor-based neural networks

    International Nuclear Information System (INIS)

    Thomas, Andy

    2013-01-01

    The synapse is a crucial element in biological neural networks, but a simple electronic equivalent has been absent. This complicates the development of hardware that imitates biological architectures in the nervous system. Now, the recent progress in the experimental realization of memristive devices has renewed interest in artificial neural networks. The resistance of a memristive system depends on its past states and exactly this functionality can be used to mimic the synaptic connections in a (human) brain. After a short introduction to memristors, we present and explain the relevant mechanisms in a biological neural network, such as long-term potentiation and spike time-dependent plasticity, and determine the minimal requirements for an artificial neural network. We review the implementations of these processes using basic electric circuits and more complex mechanisms that either imitate biological systems or could act as a model system for them. (topical review)

  6. The Puzzle of Visual Development: Behavior and Neural Limits.

    Science.gov (United States)

    Kiorpes, Lynne

    2016-11-09

    The development of visual function takes place over many months or years in primate infants. Visual sensitivity is very poor near birth and improves over different times courses for different visual functions. The neural mechanisms that underlie these processes are not well understood despite many decades of research. The puzzle arises because research into the factors that limit visual function in infants has found surprisingly mature neural organization and adult-like receptive field properties in very young infants. The high degree of visual plasticity that has been documented during the sensitive period in young children and animals leaves the brain vulnerable to abnormal visual experience. Abnormal visual experience during the sensitive period can lead to amblyopia, a developmental disorder of vision affecting ∼3% of children. This review provides a historical perspective on research into visual development and the disorder amblyopia. The mismatch between the status of the primary visual cortex and visual behavior, both during visual development and in amblyopia, is discussed, and several potential resolutions are considered. It seems likely that extrastriate visual areas further along the visual pathways may set important limits on visual function and show greater vulnerability to abnormal visual experience. Analyses based on multiunit, population activity may provide useful representations of the information being fed forward from primary visual cortex to extrastriate processing areas and to the motor output. Copyright © 2016 the authors 0270-6474/16/3611384-10$15.00/0.

  7. DNA methyltransferase 3b is dispensable for mouse neural crest development.

    Directory of Open Access Journals (Sweden)

    Bridget T Jacques-Fricke

    Full Text Available The neural crest is a population of multipotent cells that migrates extensively throughout vertebrate embryos to form diverse structures. Mice mutant for the de novo DNA methyltransferase DNMT3b exhibit defects in two neural crest derivatives, the craniofacial skeleton and cardiac ventricular septum, suggesting that DNMT3b activity is necessary for neural crest development. Nevertheless, the requirement for DNMT3b specifically in neural crest cells, as opposed to interacting cell types, has not been determined. Using a conditional DNMT3b allele crossed to the neural crest cre drivers Wnt1-cre and Sox10-cre, neural crest DNMT3b mutants were generated. In both neural crest-specific and fully DNMT3b-mutant embryos, cranial neural crest cells exhibited only subtle migration defects, with increased numbers of dispersed cells trailing organized streams in the head. In spite of this, the resulting cranial ganglia, craniofacial skeleton, and heart developed normally when neural crest cells lacked DNMT3b. This indicates that DNTM3b is not necessary in cranial neural crest cells for their development. We conclude that defects in neural crest derivatives in DNMT3b mutant mice reflect a requirement for DNMT3b in lineages such as the branchial arch mesendoderm or the cardiac mesoderm that interact with neural crest cells during formation of these structures.

  8. Synaptic Remodeling in the Dentate Gyrus, CA3, CA1, Subiculum, and Entorhinal Cortex of Mice: Effects of Deprived Rearing and Voluntary Running

    Directory of Open Access Journals (Sweden)

    Andrea T. U. Schaefers

    2010-01-01

    Full Text Available Hippocampal cell proliferation is strongly increased and synaptic turnover decreased after rearing under social and physical deprivation in gerbils (Meriones unguiculatus. We examined if a similar epigenetic effect of rearing environment on adult neuroplastic responses can be found in mice (Mus musculus. We examined synaptic turnover rates in the dentate gyrus, CA3, CA1, subiculum, and entorhinal cortex. No direct effects of deprived rearing on rates of synaptic turnover were found in any of the studied regions. However, adult wheel running had the effect of leveling layer-specific differences in synaptic remodeling in the dentate gyrus, CA3, and CA1, but not in the entorhinal cortex and subiculum of animals of both rearing treatments. Epigenetic effects during juvenile development affected adult neural plasticity in mice, but seemed to be less pronounced than in gerbils.

  9. Neural correlates of socioeconomic status in the developing human brain.

    Science.gov (United States)

    Noble, Kimberly G; Houston, Suzanne M; Kan, Eric; Sowell, Elizabeth R

    2012-07-01

    Socioeconomic disparities in childhood are associated with remarkable differences in cognitive and socio-emotional development during a time when dramatic changes are occurring in the brain. Yet, the neurobiological pathways through which socioeconomic status (SES) shapes development remain poorly understood. Behavioral evidence suggests that language, memory, social-emotional processing, and cognitive control exhibit relatively large differences across SES. Here we investigated whether volumetric differences could be observed across SES in several neural regions that support these skills. In a sample of 60 socioeconomically diverse children, highly significant SES differences in regional brain volume were observed in the hippocampus and the amygdala. In addition, SES × age interactions were observed in the left superior temporal gyrus and left inferior frontal gyrus, suggesting increasing SES differences with age in these regions. These results were not explained by differences in gender, race or IQ. Likely mechanisms include differences in the home linguistic environment and exposure to stress, which may serve as targets for intervention at a time of high neural plasticity. © 2012 Blackwell Publishing Ltd.

  10. Toward the Development of an Artificial Brain on a Micropatterned and Material-Regulated Biochip by Guiding and Promoting the Differentiation and Neurite Outgrowth of Neural Stem/Progenitor Cells.

    Science.gov (United States)

    Liu, Yung-Chiang; Lee, I-Chi; Lei, Kin Fong

    2018-02-14

    An in vitro model mimicking the in vivo environment of the brain must be developed to study neural communication and regeneration and to obtain an understanding of cellular and molecular responses. In this work, a multilayered neural network was successfully constructed on a biochip by guiding and promoting neural stem/progenitor cell differentiation and network formation. The biochip consisted of 3 × 3 arrays of cultured wells connected with channels. Neurospheroids were cultured on polyelectrolyte multilayer (PEM) films in the culture wells. Neurite outgrowth and neural differentiation were guided and promoted by the micropatterns and the PEM films. After 5 days in culture, a 3 × 3 neural network was constructed on the biochip. The function and the connections of the network were evaluated by immunocytochemistry and impedance measurements. Neurons were generated and produced functional and recyclable synaptic vesicles. Moreover, the electrical connections of the neural network were confirmed by measuring the impedance across the neurospheroids. The current work facilitates the development of an artificial brain on a chip for investigations of electrical stimulations and recordings of multilayered neural communication and regeneration.

  11. Mechanisms of glycine release, which build up synaptic and extrasynaptic glycine levels: the role of synaptic and non-synaptic glycine transporters.

    Science.gov (United States)

    Harsing, Laszlo G; Matyus, Peter

    2013-04-01

    Glycine is an amino acid neurotransmitter that is involved in both inhibitory and excitatory neurochemical transmission in the central nervous system. The role of glycine in excitatory neurotransmission is related to its coagonist action at glutamatergic N-methyl-D-aspartate receptors. The glycine levels in the synaptic cleft rise many times higher during synaptic activation assuring that glycine spills over into the extrasynaptic space. Another possible origin of extrasynaptic glycine is the efflux of glycine occurring from astrocytes associated with glutamatergic synapses. The release of glycine from neuronal or glial origins exhibits several differences compared to that of biogenic amines or other amino acid neurotransmitters. These differences appear in an external Ca(2+)- and temperature-dependent manner, conferring unique characteristics on glycine as a neurotransmitter. Glycine transporter type-1 at synapses may exhibit neural and glial forms and plays a role in controlling synaptic glycine levels and the spill over rate of glycine from the synaptic cleft into the extrasynaptic biophase. Non-synaptic glycine transporter type-1 regulates extrasynaptic glycine concentrations, either increasing or decreasing them depending on the reverse or normal mode operation of the carrier molecule. While we can, at best, only estimate synaptic glycine levels at rest and during synaptic activation, glycine concentrations are readily measurable via brain microdialysis technique applied in the extrasynaptic space. The non-synaptic N-methyl-D-aspartate receptor may obtain glycine for activation following its spill over from highly active synapses or from its release mediated by the reverse operation of non-synaptic glycine transporter-1. The sensitivity of non-synaptic N-methyl-D-aspartate receptors to glutamate and glycine is many times higher than that of synaptic N-methyl-D-aspartate receptors making the former type of receptor the primary target for drug action. Synaptic

  12. Ongoing neural development of affective theory of mind in adolescence.

    Science.gov (United States)

    Vetter, Nora C; Weigelt, Sarah; Döhnel, Katrin; Smolka, Michael N; Kliegel, Matthias

    2014-07-01

    Affective Theory of Mind (ToM), an important aspect of ToM, involves the understanding of affective mental states. This ability is critical in the developmental phase of adolescence, which is often related with socio-emotional problems. Using a developmentally sensitive behavioral task in combination with functional magnetic resonance imaging, the present study investigated the neural development of affective ToM throughout adolescence. Eighteen adolescent (ages 12-14 years) and 18 young adult women (aged 19-25 years) were scanned while evaluating complex affective mental states depicted by actors in video clips. The ventromedial prefrontal cortex (vmPFC) showed significantly stronger activation in adolescents in comparison to adults in the affective ToM condition. Current results indicate that the vmPFC might be involved in the development of affective ToM processing in adolescence. © The Author (2013). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  13. Development of an accident diagnosis system using a dynamic neural network for nuclear power plants

    International Nuclear Information System (INIS)

    Lee, Seung Jun; Kim, Jong Hyun; Seong, Poong Hyun

    2004-01-01

    In this work, an accident diagnosis system using the dynamic neural network is developed. In order to help the plant operators to quickly identify the problem, perform diagnosis and initiate recovery actions ensuring the safety of the plant, many operator support system and accident diagnosis systems have been developed. Neural networks have been recognized as a good method to implement an accident diagnosis system. However, conventional accident diagnosis systems that used neural networks did not consider a time factor sufficiently. If the neural network could be trained according to time, it is possible to perform more efficient and detailed accidents analysis. Therefore, this work suggests a dynamic neural network which has different features from existing dynamic neural networks. And a simple accident diagnosis system is implemented in order to validate the dynamic neural network. After training of the prototype, several accident diagnoses were performed. The results show that the prototype can detect the accidents correctly with good performances

  14. Leucine-rich repeat-containing synaptic adhesion molecules as organizers of synaptic specificity and diversity.

    Science.gov (United States)

    Schroeder, Anna; de Wit, Joris

    2018-04-09

    The brain harbors billions of neurons that form distinct neural circuits with exquisite specificity. Specific patterns of connectivity between distinct neuronal cell types permit the transfer and computation of information. The molecular correlates that give rise to synaptic specificity are incompletely understood. Recent studies indicate that cell-surface molecules are important determinants of cell type identity and suggest that these are essential players in the specification of synaptic connectivity. Leucine-rich repeat (LRR)-containing adhesion molecules in particular have emerged as key organizers of excitatory and inhibitory synapses. Here, we discuss emerging evidence that LRR proteins regulate the assembly of specific connectivity patterns across neural circuits, and contribute to the diverse structural and functional properties of synapses, two key features that are critical for the proper formation and function of neural circuits.

  15. DFsn collaborates with Highwire to down-regulate the Wallenda/DLK kinase and restrain synaptic terminal growth

    Directory of Open Access Journals (Sweden)

    DiAntonio Aaron

    2007-08-01

    Full Text Available Abstract Background The growth of new synapses shapes the initial formation and subsequent rearrangement of neural circuitry. Genetic studies have demonstrated that the ubiquitin ligase Highwire restrains synaptic terminal growth by down-regulating the MAP kinase kinase kinase Wallenda/dual leucine zipper kinase (DLK. To investigate the mechanism of Highwire action, we have identified DFsn as a binding partner of Highwire and characterized the roles of DFsn in synapse development, synaptic transmission, and the regulation of Wallenda/DLK kinase abundance. Results We identified DFsn as an F-box protein that binds to the RING-domain ubiquitin ligase Highwire and that can localize to the Drosophila neuromuscular junction. Loss-of-function mutants for DFsn have a phenotype that is very similar to highwire mutants – there is a dramatic overgrowth of synaptic termini, with a large increase in the number of synaptic boutons and branches. In addition, synaptic transmission is impaired in DFsn mutants. Genetic interactions between DFsn and highwire mutants indicate that DFsn and Highwire collaborate to restrain synaptic terminal growth. Finally, DFsn regulates the levels of the Wallenda/DLK kinase, and wallenda is necessary for DFsn-dependent synaptic terminal overgrowth. Conclusion The F-box protein DFsn binds the ubiquitin ligase Highwire and is required to down-regulate the levels of the Wallenda/DLK kinase and restrain synaptic terminal growth. We propose that DFsn and Highwire participate in an evolutionarily conserved ubiquitin ligase complex whose substrates regulate the structure and function of synapses.

  16. A peptide derived from a trans-homophilic binding site in neural cell adhesion molecule induces neurite outgrowth and neuronal survival

    DEFF Research Database (Denmark)

    Køhler, Lene B; Soroka, Vladislav; Korshunova, Irina

    2010-01-01

    The neural cell adhesion molecule (NCAM) plays a key role in neural development, regeneration, and synaptic plasticity. The crystal structure of a fragment of NCAM comprising the three N-terminal immunoglobulin (Ig)-like modules indicates that the first and second Ig modules bind to each other, t...

  17. Synaptic Plasticity and Nociception

    Institute of Scientific and Technical Information of China (English)

    ChenJianguo

    2004-01-01

    Synaptic plasticity is one of the fields that progresses rapidly and has a lot of success in neuroscience. The two major types of synaptie plasticity: long-term potentiation ( LTP and long-term depression (LTD are thought to be the cellular mochanisms of learning and memory. Recently, accumulating evidence suggests that, besides serving as a cellular model for learning and memory, the synaptic plasticity involves in other physiological or pathophysiological processes, such as the perception of pain and the regulation of cardiovascular system. This minireview will focus on the relationship between synaptic plasticity and nociception.

  18. Banach Synaptic Algebras

    Science.gov (United States)

    Foulis, David J.; Pulmannov, Sylvia

    2018-04-01

    Using a representation theorem of Erik Alfsen, Frederic Schultz, and Erling Størmer for special JB-algebras, we prove that a synaptic algebra is norm complete (i.e., Banach) if and only if it is isomorphic to the self-adjoint part of a Rickart C∗-algebra. Also, we give conditions on a Banach synaptic algebra that are equivalent to the condition that it is isomorphic to the self-adjoint part of an AW∗-algebra. Moreover, we study some relationships between synaptic algebras and so-called generalized Hermitian algebras.

  19. Epithelial–Mesenchymal Transitions during Neural Crest and Somite Development

    Directory of Open Access Journals (Sweden)

    Chaya Kalcheim

    2015-12-01

    Full Text Available Epithelial-to-mesenchymal transition (EMT is a central process during embryonic development that affects selected progenitor cells of all three germ layers. In addition to driving the onset of cellular migrations and subsequent tissue morphogenesis, the dynamic conversions of epithelium into mesenchyme and vice-versa are intimately associated with the segregation of homogeneous precursors into distinct fates. The neural crest and somites, progenitors of the peripheral nervous system and of skeletal tissues, respectively, beautifully illustrate the significance of EMT to the above processes. Ongoing studies progressively elucidate the gene networks underlying EMT in each system, highlighting the similarities and differences between them. Knowledge of the mechanistic logic of this normal ontogenetic process should provide important insights to the understanding of pathological conditions such as cancer metastasis, which shares some common molecular themes.

  20. 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.

  1. Self-organised criticality via retro-synaptic signals

    Science.gov (United States)

    Hernandez-Urbina, Victor; Herrmann, J. Michael

    2016-12-01

    The brain is a complex system par excellence. In the last decade the observation of neuronal avalanches in neocortical circuits suggested the presence of self-organised criticality in brain networks. The occurrence of this type of dynamics implies several benefits to neural computation. However, the mechanisms that give rise to critical behaviour in these systems, and how they interact with other neuronal processes such as synaptic plasticity are not fully understood. In this paper, we present a long-term plasticity rule based on retro-synaptic signals that allows the system to reach a critical state in which clusters of activity are distributed as a power-law, among other observables. Our synaptic plasticity rule coexists with other synaptic mechanisms such as spike-timing-dependent plasticity, which implies that the resulting synaptic modulation captures not only the temporal correlations between spiking times of pre- and post-synaptic units, which has been suggested as requirement for learning and memory in neural systems, but also drives the system to a state of optimal neural information processing.

  2. Statistical theory of synaptic connectivity in the neocortex

    Science.gov (United States)

    Escobar, Gina

    Learning and long-term memory rely on plasticity of neural circuits. In adult cerebral cortex plasticity can be mediated by modulation of existing synapses and structural reorganization of circuits through growth and retraction of dendritic spines. In the first part of this thesis, we describe a theoretical framework for the analysis of spine remodeling plasticity. New synaptic contacts appear in the neuropil where gaps between axonal and dendritic branches can be bridged by dendritic spines. Such sites are termed potential synapses. We derive expressions for the densities of potential synapses in the neuropil. We calculate the ratio of actual to potential synapses, called the connectivity fraction, and use it to find the number of structurally different circuits attainable with spine remodeling. These parameters are calculated in four systems: mouse occipital cortex, rat hippocampal area CA1, monkey primary visual (V1), and human temporal cortex. The neurogeometric results indicate that a dendritic spine can choose among an average of 4-7 potential targets in rodents, while in primates it can choose from 10-20 potential targets. The potential of the neuropil to undergo circuit remodeling is found to be highest in rat CA1 (4.9-6.0 nats/mum 3) and lowest in monkey V1 (0.9-1.0 nats/mum3). We evaluate the lower bound of neuron selectivity in the choice of synaptic partners and find that post-synaptic excitatory neurons in rodents make synaptic contacts with more than 21-30% of pre-synaptic axons encountered with new spine growth. Primate neurons appear to be more selective, making synaptic connections with more than 7-15% of encountered axons. Another plasticity mechanism is included in the second part of this work: long-term potentiation and depression of excitatory synaptic connections. Because synaptic strength is correlated with the size of the synapse, the former can be inferred from the distribution of spine head volumes. To this end we analyze and compare 166

  3. Prototype to product—developing a commercially viable neural prosthesis

    Science.gov (United States)

    Seligman, Peter

    2009-12-01

    The Cochlear implant or 'Bionic ear' is a device that enables people who do not get sufficient benefit from a hearing aid to communicate with the hearing world. The Cochlear implant is not an amplifier, but a device that electrically stimulates the auditory nerve in a way that crudely mimics normal hearing, thus providing a hearing percept. Many recipients are able to understand running speech without the help of lipreading. Cochlear implants have reached a stage of maturity where there are now 170 000 recipients implanted worldwide. The commercial development of these devices has occurred over the last 30 years. This development has been multidisciplinary, including audiologists, engineers, both mechanical and electrical, histologists, materials scientists, physiologists, surgeons and speech pathologists. This paper will trace the development of the device we have today, from the engineering perspective. The special challenges of designing an active device that will work in the human body for a lifetime will be outlined. These challenges include biocompatibility, extreme reliability, safety, patient fitting and surgical issues. It is emphasized that the successful development of a neural prosthesis requires the partnership of academia and industry.

  4. Models of neural dynamics in brain information processing - the developments of 'the decade'

    International Nuclear Information System (INIS)

    Borisyuk, G N; Borisyuk, R M; Kazanovich, Yakov B; Ivanitskii, Genrikh R

    2002-01-01

    Neural network models are discussed that have been developed during the last decade with the purpose of reproducing spatio-temporal patterns of neural activity in different brain structures. The main goal of the modeling was to test hypotheses of synchronization, temporal and phase relations in brain information processing. The models being considered are those of temporal structure of spike sequences, of neural activity dynamics, and oscillatory models of attention and feature integration. (reviews of topical problems)

  5. Development of neural retina in retinopathy of prematurity

    Directory of Open Access Journals (Sweden)

    Yi Luo

    2015-10-01

    Full Text Available Retinopathy of prematurity(ROPis an important cause of infant blindness and visual impairment in the world, of which main clinical characteristics are peripheral retinal vascular abnormalities, including large non-perfusion area and abnormal neovascularization. Numerous researches have demonstrated that ROP affects the differentiation and maturity of retinal photoreceptor cells, with more significantly effect on rods than cones, and later mostly caused ametropia, strabismus, amblyopia and a series of abnormal visual functions, the specific mechanism remains unclear. After treatments, even the retinal vascular proliferation lesions disappear itself, but the abnormal development of photoreceptor cells and the resulting visual dysfunction will persist. Currently the best evaluation mean of clinical assessment about retinal function is mainly visual electrophysiology, especially flash electroretinogram(f-ERG, which can reflect the whole retinal functional status before ganglion cells, has a unique significance for the evaluation of retinal photoreceptor cells function. In this review, we aims at the development of neural retina(mainly photoreceptor cellsand its related mechanisms, also the visual function changes appeared in the late period about ROP and its mechanisms, guiding us to pursuit better methods for treatment.

  6. Development of a neural net paradigm that predicts simulator sickness

    Energy Technology Data Exchange (ETDEWEB)

    Allgood, G.O.

    1993-03-01

    A disease exists that affects pilots and aircrew members who use Navy Operational Flight Training Systems. This malady, commonly referred to as simulator sickness and whose symptomatology closely aligns with that of motion sickness, can compromise the use of these systems because of a reduced utilization factor, negative transfer of training, and reduction in combat readiness. A report is submitted that develops an artificial neural network (ANN) and behavioral model that predicts the onset and level of simulator sickness in the pilots and aircrews who sue these systems. It is proposed that the paradigm could be implemented in real time as a biofeedback monitor to reduce the risk to users of these systems. The model captures the neurophysiological impact of use (human-machine interaction) by developing a structure that maps the associative and nonassociative behavioral patterns (learned expectations) and vestibular (otolith and semicircular canals of the inner ear) and tactile interaction, derived from system acceleration profiles, onto an abstract space that predicts simulator sickness for a given training flight.

  7. Adrenergic innervation of the developing chick heart: neural crest ablations to produce sympathetically aneural hearts

    International Nuclear Information System (INIS)

    Kirby, M.; Stewart, D.

    1984-01-01

    Ablation of various regions of premigratory trunk neural crest which gives rise to the sympathetic trunks was used to remove sympathetic cardiac innervation. Neuronal uptake of [ 3 H]-norepinephrine was used as an index of neuronal development in the chick atrium. Following ablation of neural crest over somites 10-15 or 15-20, uptake was significantly decreased in the atrium at 16 and 17 days of development. Ablation of neural crest over somites 5-10 and 20-25 caused no decrease in [ 3 H]-norepinephrine uptake. Removal of neural crest over somites 5-25 or 10-20 caused approximately equal depletions of [ 3 H]-norepinephrine uptake in the atrium. Cardiac norepinephrine concentration was significantly depressed following ablation of neural crest over somites 5-25 but not over somites 10-20. Light-microscopic and histofluorescent preparations confirmed the absence of sympathetic trunks in the region of the normal origin of the sympathetic cardiac nerves following neural crest ablation over somites 10-20. The neural tube and dorsal root ganglia were damaged in the area of the neural-crest ablation; however, all of these structures were normal cranial and caudal to the lesioned area. Development of most of the embryos as well as the morphology of all of the hearts was normal following the lesion. These results indicate that it is possible to produce sympathetically aneural hearts by neural-crest ablation; however, sympathetic cardiac nerves account for an insignificant amount of cardiac norepinephrine

  8. Synaptic conductances during interictal discharges in pyramidal neurons of rat entorhinal cortex

    Directory of Open Access Journals (Sweden)

    Dmitry V. Amakhin

    2016-10-01

    Full Text Available In epilepsy, the balance of excitation and inhibition underlying the basis of neural network activity shifts, resulting in neuronal network hyperexcitability and recurrent seizure-associated discharges. Mechanisms involved in ictal and interictal events are not fully understood, in particular, because of controversial data regarding the dynamics of excitatory and inhibitory synaptic conductances. In the present study, we estimated AMPAR-, NMDAR-, and GABAAR-mediated conductances during two distinct types of interictal discharge (IID in pyramidal neurons of rat entorhinal cortex in cortico-hippocampal slices. Repetitively emerging seizure-like events and IIDs were recorded in high extracellular potassium, 4-aminopyridine, and reduced magnesium-containing solution. An original procedure for estimating synaptic conductance during IIDs was based on the differences among the current-voltage characteristics of the synaptic components. The synaptic conductance dynamics obtained revealed that the first type of IID is determined by activity of GABAAR channels with depolarized reversal potential. The second type of IID is determined by the interplay between excitation and inhibition, with prominent early AMPAR and prolonged depolarized GABAAR and NMDAR-mediated components. The study then validated the contribution of these components to IIDs by intracellular pharmacological isolation. These data provide new insights into the mechanisms of seizures generation, development, and cessation.

  9. Familiarity Detection is an Intrinsic Property of Cortical Microcircuits with Bidirectional Synaptic Plasticity.

    Science.gov (United States)

    Zhang, Xiaoyu; Ju, Han; Penney, Trevor B; VanDongen, Antonius M J

    2017-01-01

    Humans instantly recognize a previously seen face as "familiar." To deepen our understanding of familiarity-novelty detection, we simulated biologically plausible neural network models of generic cortical microcircuits consisting of spiking neurons with random recurrent synaptic connections. NMDA receptor (NMDAR)-dependent synaptic plasticity was implemented to allow for unsupervised learning and bidirectional modifications. Network spiking activity evoked by sensory inputs consisting of face images altered synaptic efficacy, which resulted in the network responding more strongly to a previously seen face than a novel face. Network size determined how many faces could be accurately recognized as familiar. When the simulated model became sufficiently complex in structure, multiple familiarity traces could be retained in the same network by forming partially-overlapping subnetworks that differ slightly from each other, thereby resulting in a high storage capacity. Fisher's discriminant analysis was applied to identify critical neurons whose spiking activity predicted familiar input patterns. Intriguingly, as sensory exposure was prolonged, the selected critical neurons tended to appear at deeper layers of the network model, suggesting recruitment of additional circuits in the network for incremental information storage. We conclude that generic cortical microcircuits with bidirectional synaptic plasticity have an intrinsic ability to detect familiar inputs. This ability does not require a specialized wiring diagram or supervision and can therefore be expected to emerge naturally in developing cortical circuits.

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

    Energy Technology Data Exchange (ETDEWEB)

    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

  11. Applying Fuzzy Artificial Neural Network OSPF to develop Smart ...

    African Journals Online (AJOL)

    pc

    2018-03-05

    Mar 5, 2018 ... Fuzzy Artificial Neural Network to create Smart Routing. Protocol Algorithm. ... manufactured mental aptitude strategy. The capacity to study .... Based Energy Efficiency in Wireless Sensor Networks: A Survey",. International ...

  12. Developing Scene Understanding Neural Software for Realistic Autonomous Outdoor Missions

    Science.gov (United States)

    2017-09-01

    computer using a single graphics processing unit (GPU). To the best of our knowledge, an implementation of the open-source Python -based AlexNet CNN on...1. Introduction Neurons in the brain enable us to understand scenes by assessing the spatial, temporal, and feature relations of objects in the...effort to use computer neural networks to augment human neural intelligence to improve our scene understanding (Krizhevsky et al. 2012; Zhou et al

  13. Synaptic theory of Replicator-like melioration

    Directory of Open Access Journals (Sweden)

    Yonatan Loewenstein

    2010-06-01

    Full Text Available According to the theory of Melioration, organisms in repeated choice settings shift their choice preference in favor of the alternative that provides the highest return. The goal of this paper is to explain how this learning behavior can emerge from microscopic changes in the efficacies of synapses, in the context of two-alternative repeated-choice experiment. I consider a large family of synaptic plasticity rules in which changes in synaptic efficacies are driven by the covariance between reward and neural activity. I construct a general framework that predicts the learning dynamics of any decision-making neural network that implements this synaptic plasticity rule and show that melioration naturally emerges in such networks. Moreover, the resultant learning dynamics follows the Replicator equation which is commonly used to phenomenologically describe changes in behavior in operant conditioning experiments. Several examples demonstrate how the learning rate of the network is affected by its properties and by the specifics of the plasticity rule. These results help bridge the gap between cellular physiology and learning behavior.

  14. Neural correlates of gesture processing across human development.

    Science.gov (United States)

    Wakefield, Elizabeth M; James, Thomas W; James, Karin H

    2013-01-01

    Co-speech gesture facilitates learning to a greater degree in children than in adults, suggesting that the mechanisms underlying the processing of co-speech gesture differ as a function of development. We suggest that this may be partially due to children's lack of experience producing gesture, leading to differences in the recruitment of sensorimotor networks when comparing adults to children. Here, we investigated the neural substrates of gesture processing in a cross-sectional sample of 5-, 7.5-, and 10-year-old children and adults and focused on relative recruitment of a sensorimotor system that included the precentral gyrus (PCG) and the posterior middle temporal gyrus (pMTG). Children and adults were presented with videos in which communication occurred through different combinations of speech and gesture during a functional magnetic resonance imaging (fMRI) session. Results demonstrated that the PCG and pMTG were recruited to different extents in the two populations. We interpret these novel findings as supporting the idea that gesture perception (pMTG) is affected by a history of gesture production (PCG), revealing the importance of considering gesture processing as a sensorimotor process.

  15. Development of neural basis for chinese orthographic neighborhood size effect.

    Science.gov (United States)

    Zhao, Jing; Li, Qing-Lin; Ding, Guo-Sheng; Bi, Hong-Yan

    2016-02-01

    The brain activity of orthographic neighborhood size (N size) effect in Chinese character naming has been studied in adults, meanwhile behavioral studies have revealed a developmental trend of Chinese N-size effect in developing readers. However, it is unclear whether and how the neural mechanism of N-size effect changes in Chinese children along with development. Here we address this issue using functional magnetic resonance imaging. Forty-four students from the 3(rd) , 5(th) , and 7(th) grades were scanned during silent naming of Chinese characters. After scanning, all participants took part in an overt naming test outside the scanner, and results of the naming task showed that the 3(rd) graders named characters from large neighborhoods faster than those from small neighborhoods, revealing a facilitatory N-size effect; the 5(th) graders showed null N-size effect while the 7(th) graders showed an inhibitory N-size effect. Neuroimaging results revealed that only the 3(rd) graders exhibited a significant N-size effect in the left middle occipital activity, with greater activation for large N-size characters. Results of 5(th) and 7(th) graders showed significant N-size effects in the left middle frontal gyrus, in which 5(th) graders induced greater activation in large N-size condition than in small N-size condition, while 7(th) graders exhibited an opposite effect which was similar to the adult pattern reported in a previous study. The current findings suggested the transition from broadly tuned to finely tuned orthographic representation with reading development, and the inhibition from neighbors' phonology for higher graders. Hum Brain Mapp 37:632-647, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

  16. Development of an in situ evaluation system for neural cells using extracellular matrix-modeled gel culture.

    Science.gov (United States)

    Nagai, Takayuki; Ikegami, Yasuhiro; Mizumachi, Hideyuki; Shirakigawa, Nana; Ijima, Hiroyuki

    2017-10-01

    Two-dimensional monolayer culture is the most popular cell culture method. However, the cells may not respond as they do in vivo because the culture conditions are different from in vivo conditions. However, hydrogel-embedding culture, which cultures cells in a biocompatible culture substrate, can produce in vivo-like cell responses, but in situ evaluation of cells in a gel is difficult. In this study, we realized an in vivo-like environment in vitro to produce cell responses similar to those in vivo and established an in situ evaluation system for hydrogel-embedded cell responses. The extracellular matrix (ECM)-modeled gel consisted of collagen and heparin (Hep-col) to mimic an in vivo-like environment. The Hep-col gel could immobilize growth factors, which is important for ECM functions. Neural stem/progenitor cells cultured in the Hep-col gel grew and differentiated more actively than in collagen, indicating an in vivo-like environment in the Hep-col gel. Second, a thin-layered gel culture system was developed to realize in situ evaluation of the gel-embedded cells. Cells in a 200-μm-thick gel could be evaluated clearly by a phase-contrast microscope and immunofluorescence staining through reduced optical and diffusional effects. Finally, we found that the neural cells cultured in this system had synaptic connections and neuronal action potentials by immunofluorescence staining and Ca 2+ imaging. In conclusion, this culture method may be a valuable evaluation system for neurotoxicity testing. Copyright © 2017 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

  17. Time-lapse imaging of neural development: zebrafish lead the way into the fourth dimension.

    Science.gov (United States)

    Rieger, Sandra; Wang, Fang; Sagasti, Alvaro

    2011-07-01

    Time-lapse imaging is often the only way to appreciate fully the many dynamic cell movements critical to neural development. Zebrafish possess many advantages that make them the best vertebrate model organism for live imaging of dynamic development events. This review will discuss technical considerations of time-lapse imaging experiments in zebrafish, describe selected examples of imaging studies in zebrafish that revealed new features or principles of neural development, and consider the promise and challenges of future time-lapse studies of neural development in zebrafish embryos and adults. Copyright © 2011 Wiley-Liss, Inc.

  18. Low-Frequency rTMS Ameliorates Autistic-Like Behaviors in Rats Induced by Neonatal Isolation Through Regulating the Synaptic GABA Transmission

    Directory of Open Access Journals (Sweden)

    Tao Tan

    2018-02-01

    Full Text Available Patients with autism spectrum disorder (ASD display abnormalities in neuronal development, synaptic function and neural circuits. The imbalance of excitatory and inhibitory (E/I synaptic transmission has been proposed to cause the main behavioral characteristics of ASD. Repetitive transcranial magnetic stimulation (rTMS can directly or indirectly induce excitability and synaptic plasticity changes in the brain noninvasively. However, whether rTMS can ameliorate autistic-like behaviors in animal model via regulating the balance of E/I synaptic transmission is unknown. By using our recent reported animal model with autistic-like behaviors induced by neonatal isolation (postnatal days 1–9, we found that low-frequency rTMS (LF-rTMS, 1 Hz treatment for 2 weeks effectively alleviated the acquired autistic-like symptoms, as reflected by an increase in social interaction and decrease in self-grooming, anxiety- and depressive-like behaviors in young adult rats compared to those in untreated animals. Furthermore, the amelioration in autistic-like behavior was accompanied by a restoration of the balance between E/I activity, especially at the level of synaptic transmission and receptors in synaptosomes. These findings indicated that LF-rTMS may alleviate the symptoms of ASD-like behaviors caused by neonatal isolation through regulating the synaptic GABA transmission, suggesting that LF-rTMS may be a potential therapeutic technique to treat ASD.

  19. Neuro-inspired computing using resistive synaptic devices

    CERN Document Server

    2017-01-01

    This book summarizes the recent breakthroughs in hardware implementation of neuro-inspired computing using resistive synaptic devices. The authors describe how two-terminal solid-state resistive memories can emulate synaptic weights in a neural network. Readers will benefit from state-of-the-art summaries of resistive synaptic devices, from the individual cell characteristics to the large-scale array integration. This book also discusses peripheral neuron circuits design challenges and design strategies. Finally, the authors describe the impact of device non-ideal properties (e.g. noise, variation, yield) and their impact on the learning performance at the system-level, using a device-algorithm co-design methodology. • Provides single-source reference to recent breakthroughs in resistive synaptic devices, not only at individual cell-level, but also at integrated array-level; • Includes detailed discussion of the peripheral circuits and array architecture design of the neuro-crossbar system; • Focuses on...

  20. Development and application of deep convolutional neural network in target detection

    Science.gov (United States)

    Jiang, Xiaowei; Wang, Chunping; Fu, Qiang

    2018-04-01

    With the development of big data and algorithms, deep convolution neural networks with more hidden layers have more powerful feature learning and feature expression ability than traditional machine learning methods, making artificial intelligence surpass human level in many fields. This paper first reviews the development and application of deep convolutional neural networks in the field of object detection in recent years, then briefly summarizes and ponders some existing problems in the current research, and the future development of deep convolutional neural network is prospected.

  1. The malleable brain: plasticity of neural circuits and behavior - a review from students to students.

    Science.gov (United States)

    Schaefer, Natascha; Rotermund, Carola; Blumrich, Eva-Maria; Lourenco, Mychael V; Joshi, Pooja; Hegemann, Regina U; Jamwal, Sumit; Ali, Nilufar; García Romero, Ezra Michelet; Sharma, Sorabh; Ghosh, Shampa; Sinha, Jitendra K; Loke, Hannah; Jain, Vishal; Lepeta, Katarzyna; Salamian, Ahmad; Sharma, Mahima; Golpich, Mojtaba; Nawrotek, Katarzyna; Paidi, Ramesh K; Shahidzadeh, Sheila M; Piermartiri, Tetsade; Amini, Elham; Pastor, Veronica; Wilson, Yvette; Adeniyi, Philip A; Datusalia, Ashok K; Vafadari, Benham; Saini, Vedangana; Suárez-Pozos, Edna; Kushwah, Neetu; Fontanet, Paula; Turner, Anthony J

    2017-06-20

    One of the most intriguing features of the brain is its ability to be malleable, allowing it to adapt continually to changes in the environment. Specific neuronal activity patterns drive long-lasting increases or decreases in the strength of synaptic connections, referred to as long-term potentiation and long-term depression, respectively. Such phenomena have been described in a variety of model organisms, which are used to study molecular, structural, and functional aspects of synaptic plasticity. This review originated from the first International Society for Neurochemistry (ISN) and Journal of Neurochemistry (JNC) Flagship School held in Alpbach, Austria (Sep 2016), and will use its curriculum and discussions as a framework to review some of the current knowledge in the field of synaptic plasticity. First, we describe the role of plasticity during development and the persistent changes of neural circuitry occurring when sensory input is altered during critical developmental stages. We then outline the signaling cascades resulting in the synthesis of new plasticity-related proteins, which ultimately enable sustained changes in synaptic strength. Going beyond the traditional understanding of synaptic plasticity conceptualized by long-term potentiation and long-term depression, we discuss system-wide modifications and recently unveiled homeostatic mechanisms, such as synaptic scaling. Finally, we describe the neural circuits and synaptic plasticity mechanisms driving associative memory and motor learning. Evidence summarized in this review provides a current view of synaptic plasticity in its various forms, offers new insights into the underlying mechanisms and behavioral relevance, and provides directions for future research in the field of synaptic plasticity. Read the Editorial Highlight for this article on doi: 10.1111/jnc.14102. © 2017 International Society for Neurochemistry.

  2. INTEGRATING ARTIFICIAL NEURAL NETWORKS FOR DEVELOPING TELEMEDICINE SOLUTION

    Directory of Open Access Journals (Sweden)

    Mihaela GHEORGHE

    2015-06-01

    Full Text Available Artificial intelligence is assuming an increasing important role in the telemedicine field, especially neural networks with their ability to achieve meaning from large sets of data characterized by lacking exactness and accuracy. These can be used for assisting physicians or other clinical staff in the process of taking decisions under uncertainty. Thus, machine learning methods which are specific to this technology are offering an approach for prediction based on pattern classification. This paper aims to present the importance of neural networks in detecting trends and extracting patterns which can be used within telemedicine domains, particularly for taking medical diagnosis decisions.

  3. Development of neural network simulating power distribution of a BWR fuel bundle

    International Nuclear Information System (INIS)

    Tanabe, A.; Yamamoto, T.; Shinfuku, K.; Nakamae, T.

    1992-01-01

    A neural network model is developed to simulate the precise nuclear physics analysis program code for quick scoping survey calculations. The relation between enrichment and local power distribution of BWR fuel bundles was learned using two layers neural network (ENET). A new model is to introduce burnable neutron absorber (Gadolinia), added to several fuel rods to decrease initial reactivity of fresh bundle. The 2nd stages three layers neural network (GNET) is added on the 1st stage network ENET. GNET studies the local distribution difference caused by Gadolinia. Using this method, it becomes possible to survey of the gradients of sigmoid functions and back propagation constants with reasonable time. Using 99 learning patterns of zero burnup, good error convergence curve is obtained after many trials. This neural network model is able to simulate no learned cases fairly as well as the learned cases. Computer time of this neural network model is about 100 times faster than a precise analysis model. (author)

  4. Human Embryonic Stem Cells: A Model for the Study of Neural Development and Neurological Diseases

    Directory of Open Access Journals (Sweden)

    Piya Prajumwongs

    2016-01-01

    Full Text Available Although the mechanism of neurogenesis has been well documented in other organisms, there might be fundamental differences between human and those species referring to species-specific context. Based on principles learned from other systems, it is found that the signaling pathways required for neural induction and specification of human embryonic stem cells (hESCs recapitulated those in the early embryo development in vivo at certain degree. This underscores the usefulness of hESCs in understanding early human neural development and reinforces the need to integrate the principles of developmental biology and hESC biology for an efficient neural differentiation.

  5. PEDOT:PSS interfaces support the development of neuronal synaptic networks with reduced neuroglia response in vitro

    Directory of Open Access Journals (Sweden)

    Giada eCellot

    2016-01-01

    Full Text Available The design of electrodes based on conductive polymers in brain-machine interface technology offers the opportunity to exploit variably manufactured materials to reduce gliosis, indeed the most common brain response to chronically implanted neural electrodes. In fact, the use of conductive polymers, finely tailored in their physical-chemical properties, might result in electrodes with improved adaptability to the brain tissue and increased charge-transfer efficiency. Here we interfaced poly(3,4-ethylenedioxythiophene:poly(styrene sulfonate (PEDOT:PSS doped with different amounts of ethylene glycol (EG with rat hippocampal primary cultures grown for 3 weeks on these synthetic substrates. We used immunofluorescence and scanning electron microscopy combined to single cell electrophysiology to assess the biocompatibility of PEDOT:PSS in terms of neuronal growth and synapse formation. We investigated neuronal morphology, density and electrical activity. We reported the novel observation that opposite to neurons, glial cell density was progressively reduced, hinting at the ability of this material to down regulate glial reaction. Thus PEDOT:PSS is an attractive candidate for the design of new implantable electrodes, controlling the extent of glial reactivity without affecting neuronal viability and function.

  6. Morphological neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Ritter, G.X.; Sussner, P. [Univ. of Florida, Gainesville, FL (United States)

    1996-12-31

    The theory of artificial neural networks has been successfully applied to a wide variety of pattern recognition problems. In this theory, the first step in computing the next state of a neuron or in performing the next layer neural network computation involves the linear operation of multiplying neural values by their synaptic strengths and adding the results. Thresholding usually follows the linear operation in order to provide for nonlinearity of the network. In this paper we introduce a novel class of neural networks, called morphological neural networks, in which the operations of multiplication and addition are replaced by addition and maximum (or minimum), respectively. By taking the maximum (or minimum) of sums instead of the sum of products, morphological network computation is nonlinear before thresholding. As a consequence, the properties of morphological neural networks are drastically different than those of traditional neural network models. In this paper we consider some of these differences and provide some particular examples of morphological neural network.

  7. Development of the disable software reporting system on the basis of the neural network

    Science.gov (United States)

    Gavrylenko, S.; Babenko, O.; Ignatova, E.

    2018-04-01

    The PE structure of malicious and secure software is analyzed, features are highlighted, binary sign vectors are obtained and used as inputs for training the neural network. A software model for detecting malware based on the ART-1 neural network was developed, optimal similarity coefficients were found, and testing was performed. The obtained research results showed the possibility of using the developed system of identifying malicious software in computer systems protection systems

  8. Synaptic remodeling, synaptic growth and the storage of long-term memory in Aplysia.

    Science.gov (United States)

    Bailey, Craig H; Kandel, Eric R

    2008-01-01

    Synaptic remodeling and synaptic growth accompany various forms of long-term memory. Storage of the long-term memory for sensitization of the gill-withdrawal reflex in Aplysia has been extensively studied in this respect and is associated with the growth of new synapses by the sensory neurons onto their postsynaptic target neurons. Recent time-lapse imaging studies of living sensory-to-motor neuron synapses in culture have monitored both functional and structural changes simultaneously so as to follow remodeling and growth at the same specific synaptic connections continuously over time and to examine the functional contribution of these learning-related structural changes to the different time-dependent phases of memory storage. Insights provided by these studies suggest the synaptic differentiation and growth induced by learning in the mature nervous system are highly dynamic and often rapid processes that can recruit both molecules and mechanisms used for de novo synapse formation during development.

  9. The visual development of hand-centered receptive fields in a neural network model of the primate visual system trained with experimentally recorded human gaze changes.

    Science.gov (United States)

    Galeazzi, Juan M; Navajas, Joaquín; Mender, Bedeho M W; Quian Quiroga, Rodrigo; Minini, Loredana; Stringer, Simon M

    2016-01-01

    Neurons have been found in the primate brain that respond to objects in specific locations in hand-centered coordinates. A key theoretical challenge is to explain how such hand-centered neuronal responses may develop through visual experience. In this paper we show how hand-centered visual receptive fields can develop using an artificial neural network model, VisNet, of the primate visual system when driven by gaze changes recorded from human test subjects as they completed a jigsaw. A camera mounted on the head captured images of the hand and jigsaw, while eye movements were recorded using an eye-tracking device. This combination of data allowed us to reconstruct the retinal images seen as humans undertook the jigsaw task. These retinal images were then fed into the neural network model during self-organization of its synaptic connectivity using a biologically plausible trace learning rule. A trace learning mechanism encourages neurons in the model to learn to respond to input images that tend to occur in close temporal proximity. In the data recorded from human subjects, we found that the participant's gaze often shifted through a sequence of locations around a fixed spatial configuration of the hand and one of the jigsaw pieces. In this case, trace learning should bind these retinal images together onto the same subset of output neurons. The simulation results consequently confirmed that some cells learned to respond selectively to the hand and a jigsaw piece in a fixed spatial configuration across different retinal views.

  10. Designing neural networks that process mean values of random variables

    International Nuclear Information System (INIS)

    Barber, Michael J.; Clark, John W.

    2014-01-01

    We develop a class of neural networks derived from probabilistic models posed in the form of Bayesian networks. Making biologically and technically plausible assumptions about the nature of the probabilistic models to be represented in the networks, we derive neural networks exhibiting standard dynamics that require no training to determine the synaptic weights, that perform accurate calculation of the mean values of the relevant random variables, that can pool multiple sources of evidence, and that deal appropriately with ambivalent, inconsistent, or contradictory evidence. - Highlights: • High-level neural computations are specified by Bayesian belief networks of random variables. • Probability densities of random variables are encoded in activities of populations of neurons. • Top-down algorithm generates specific neural network implementation of given computation. • Resulting “neural belief networks” process mean values of random variables. • Such networks pool multiple sources of evidence and deal properly with inconsistent evidence

  11. Designing neural networks that process mean values of random variables

    Energy Technology Data Exchange (ETDEWEB)

    Barber, Michael J. [AIT Austrian Institute of Technology, Innovation Systems Department, 1220 Vienna (Austria); Clark, John W. [Department of Physics and McDonnell Center for the Space Sciences, Washington University, St. Louis, MO 63130 (United States); Centro de Ciências Matemáticas, Universidade de Madeira, 9000-390 Funchal (Portugal)

    2014-06-13

    We develop a class of neural networks derived from probabilistic models posed in the form of Bayesian networks. Making biologically and technically plausible assumptions about the nature of the probabilistic models to be represented in the networks, we derive neural networks exhibiting standard dynamics that require no training to determine the synaptic weights, that perform accurate calculation of the mean values of the relevant random variables, that can pool multiple sources of evidence, and that deal appropriately with ambivalent, inconsistent, or contradictory evidence. - Highlights: • High-level neural computations are specified by Bayesian belief networks of random variables. • Probability densities of random variables are encoded in activities of populations of neurons. • Top-down algorithm generates specific neural network implementation of given computation. • Resulting “neural belief networks” process mean values of random variables. • Such networks pool multiple sources of evidence and deal properly with inconsistent evidence.

  12. Behavior control in the sensorimotor loop with short-term synaptic dynamics induced by self-regulating neurons

    Directory of Open Access Journals (Sweden)

    Hazem eToutounji

    2014-05-01

    Full Text Available The behavior and skills of living systems depend on the distributed control provided by specialized and highly recurrent neural networks. Learning and memory in these systems is mediated by a set of adaptation mechanisms, known collectively as neuronal plasticity. Translating principles of recurrent neural control and plasticity to artificial agents has seen major strides, but is usually hampered by the complex interactions between the agent's body and its environment. One of the important standing issues is for the agent to support multiple stable states of behavior, so that its behavioral repertoire matches the requirements imposed by these interactions. The agent also must have the capacity to switch between these states in time scales that are comparable to those by which sensory stimulation varies. Achieving this requires a mechanism of short-term memory that allows the neurocontroller to keep track of the recent history of its input, which finds its biological counterpart in short-term synaptic plasticity. This issue is approached here by deriving synaptic dynamics in recurrent neural networks. Neurons are introduced as self-regulating units with a rich repertoire of dynamics. They exhibit homeostatic properties for certain parameter domains, which result in a set of stable states and the required short-term memory. They can also operate as oscillators, which allow them to surpass the level of activity imposed by their homeostatic operation conditions. Neural systems endowed with the derived synaptic dynamics can be utilized for the neural behavior control of autonomous mobile agents. The resulting behavior depends also on the underlying network structure, which is either engineered, or developed by evolutionary techniques. The effectiveness of these self-regulating units is demonstrated by controlling locomotion of a hexapod with eighteen degrees of freedom, and obstacle-avoidance of a wheel-driven robot.

  13. Animal models for studying neural crest development: is the mouse different?

    Science.gov (United States)

    Barriga, Elias H; Trainor, Paul A; Bronner, Marianne; Mayor, Roberto

    2015-05-01

    The neural crest is a uniquely vertebrate cell type and has been well studied in a number of model systems. Zebrafish, Xenopus and chick embryos largely show consistent requirements for specific genes in early steps of neural crest development. By contrast, knockouts of homologous genes in the mouse often do not exhibit comparable early neural crest phenotypes. In this Spotlight article, we discuss these species-specific differences, suggest possible explanations for the divergent phenotypes in mouse and urge the community to consider these issues and the need for further research in complementary systems. © 2015. Published by The Company of Biologists Ltd.

  14. A neural flow estimator

    DEFF Research Database (Denmark)

    Jørgensen, Ivan Harald Holger; Bogason, Gudmundur; Bruun, Erik

    1995-01-01

    This paper proposes a new way to estimate the flow in a micromechanical flow channel. A neural network is used to estimate the delay of random temperature fluctuations induced in a fluid. The design and implementation of a hardware efficient neural flow estimator is described. The system...... is implemented using switched-current technique and is capable of estimating flow in the μl/s range. The neural estimator is built around a multiplierless neural network, containing 96 synaptic weights which are updated using the LMS1-algorithm. An experimental chip has been designed that operates at 5 V...

  15. Germ layers, the neural crest and emergent organization in development and evolution.

    Science.gov (United States)

    Hall, Brian K

    2018-04-10

    Discovered in chick embryos by Wilhelm His in 1868 and named the neural crest by Arthur Milnes Marshall in 1879, the neural crest cells that arise from the neural folds have since been shown to differentiate into almost two dozen vertebrate cell types and to have played major roles in the evolution of such vertebrate features as bone, jaws, teeth, visceral (pharyngeal) arches, and sense organs. I discuss the discovery that ectodermal neural crest gave rise to mesenchyme and the controversy generated by that finding; the germ layer theory maintained that only mesoderm could give rise to mesenchyme. A second topic of discussion is germ layers (including the neural crest) as emergent levels of organization in animal development and evolution that facilitated major developmental and evolutionary change. The third topic is gene networks, gene co-option, and the evolution of gene-signaling pathways as key to developmental and evolutionary transitions associated with the origin and evolution of the neural crest and neural crest cells. © 2018 Wiley Periodicals, Inc.

  16. Nuclear Receptor TLX Regulates Cell Cycle Progression in Neural Stem Cells of the Developing Brain

    OpenAIRE

    Li, Wenwu; Sun, Guoqiang; Yang, Su; Qu, Qiuhao; Nakashima, Kinichi; Shi, Yanhong

    2007-01-01

    TLX is an orphan nuclear receptor that is expressed exclusively in vertebrate forebrains. Although TLX is known to be expressed in embryonic brains, the mechanism by which it influences neural development remains largely unknown. We show here that TLX is expressed specifically in periventricular neural stem cells in embryonic brains. Significant thinning of neocortex was observed in embryonic d 14.5 TLX-null brains with reduced nestin labeling and decreased cell proliferation in the germinal ...

  17. Influence and timing of arrival of murine neural crest on pancreatic beta cell development and maturation.

    Science.gov (United States)

    Plank, Jennifer L; Mundell, Nathan A; Frist, Audrey Y; LeGrone, Alison W; Kim, Thomas; Musser, Melissa A; Walter, Teagan J; Labosky, Patricia A

    2011-01-15

    Interactions between cells from the ectoderm and mesoderm influence development of the endodermally-derived pancreas. While much is known about how mesoderm regulates pancreatic development, relatively little is understood about how and when the ectodermally-derived neural crest regulates pancreatic development and specifically, beta cell maturation. A previous study demonstrated that signals from the neural crest regulate beta cell proliferation and ultimately, beta cell mass. Here, we expand on that work to describe timing of neural crest arrival at the developing pancreatic bud and extend our knowledge of the non-cell autonomous role for neural crest derivatives in the process of beta cell maturation. We demonstrated that murine neural crest entered the pancreatic mesenchyme between the 26 and 27 somite stages (approximately 10.0 dpc) and became intermingled with pancreatic progenitors as the epithelium branched into the surrounding mesenchyme. Using a neural crest-specific deletion of the Forkhead transcription factor Foxd3, we ablated neural crest cells that migrate to the pancreatic primordium. Consistent with previous data, in the absence of Foxd3, and therefore the absence of neural crest cells, proliferation of insulin-expressing cells and insulin-positive area are increased. Analysis of endocrine cell gene expression in the absence of neural crest demonstrated that, although the number of insulin-expressing cells was increased, beta cell maturation was significantly impaired. Decreased MafA and Pdx1 expression illustrated the defect in beta cell maturation; we discovered that without neural crest, there was a reduction in the percentage of insulin-positive cells that co-expressed Glut2 and Pdx1 compared to controls. In addition, transmission electron microscopy analyses revealed decreased numbers of characteristic insulin granules and the presence of abnormal granules in insulin-expressing cells from mutant embryos. Together, these data demonstrate that

  18. Maternal Dexamethasone Exposure Alters Synaptic Inputs to Gonadotropin-Releasing Hormone Neurons in the Early Postnatal Rat

    Directory of Open Access Journals (Sweden)

    Wei Ling Lim

    2016-08-01

    Full Text Available Maternal dexamethasone (DEX; a glucocorticoid receptor agonist exposure delays pubertal onset and alters reproductive behaviour in the adult offspring. However, little is known whether maternal DEX exposure affects the offspring’s reproductive function by disrupting the gonadotropin-releasing hormone (GnRH neuronal function in the brain. Therefore, this study determined the exposure of maternal DEX on the GnRH neuronal spine development and synaptic cluster inputs to GnRH neurons using transgenic rats expressing enhanced green fluorescent protein (EGFP under the control of GnRH promoter. Pregnant females were administered with DEX (0.1mg/kg or vehicle (VEH, water daily during gestation day 13-20. Confocal imaging was used to examine the spine density of EGFP-GnRH neurons by three-dimensional rendering and synaptic cluster inputs to EGFP-GnRH neurons by synapsin I immunohistochemistry on postnatal day 0 (P0 males. The spine morphology and number on GnRH neurons did not change between the P0 males following maternal DEX and VEH treatment. The number of synaptic clusters within the organum vasculosum of the lamina terminalis (OVLT was decreased by maternal DEX exposure in P0 males. Furthermore, the number and levels of synaptic cluster inputs in close apposition with GnRH neurons was decreased following maternal DEX exposure in the OVLT region of P0 males. In addition, the post synaptic marker molecule, post-synaptic density 95 was observed in GnRH neurons following both DEX and VEH treatment. These results suggest that maternal DEX exposure alters neural afferent inputs to GnRH neurons during early postnatal stage, which could lead to reproductive dysfunction during adulthood.

  19. Chromatin Remodeling BAF (SWI/SNF Complexes in Neural Development and Disorders

    Directory of Open Access Journals (Sweden)

    Godwin Sokpor

    2017-08-01

    Full Text Available The ATP-dependent BRG1/BRM associated factor (BAF chromatin remodeling complexes are crucial in regulating gene expression by controlling chromatin dynamics. Over the last decade, it has become increasingly clear that during neural development in mammals, distinct ontogenetic stage-specific BAF complexes derived from combinatorial assembly of their subunits are formed in neural progenitors and post-mitotic neural cells. Proper functioning of the BAF complexes plays critical roles in neural development, including the establishment and maintenance of neural fates and functionality. Indeed, recent human exome sequencing and genome-wide association studies have revealed that mutations in BAF complex subunits are linked to neurodevelopmental disorders such as Coffin-Siris syndrome, Nicolaides-Baraitser syndrome, Kleefstra's syndrome spectrum, Hirschsprung's disease, autism spectrum disorder, and schizophrenia. In this review, we focus on the latest insights into the functions of BAF complexes during neural development and the plausible mechanistic basis of how mutations in known BAF subunits are associated with certain neurodevelopmental disorders.

  20. Chromatin Remodeling BAF (SWI/SNF) Complexes in Neural Development and Disorders

    Science.gov (United States)

    Sokpor, Godwin; Xie, Yuanbin; Rosenbusch, Joachim; Tuoc, Tran

    2017-01-01

    The ATP-dependent BRG1/BRM associated factor (BAF) chromatin remodeling complexes are crucial in regulating gene expression by controlling chromatin dynamics. Over the last decade, it has become increasingly clear that during neural development in mammals, distinct ontogenetic stage-specific BAF complexes derived from combinatorial assembly of their subunits are formed in neural progenitors and post-mitotic neural cells. Proper functioning of the BAF complexes plays critical roles in neural development, including the establishment and maintenance of neural fates and functionality. Indeed, recent human exome sequencing and genome-wide association studies have revealed that mutations in BAF complex subunits are linked to neurodevelopmental disorders such as Coffin-Siris syndrome, Nicolaides-Baraitser syndrome, Kleefstra's syndrome spectrum, Hirschsprung's disease, autism spectrum disorder, and schizophrenia. In this review, we focus on the latest insights into the functions of BAF complexes during neural development and the plausible mechanistic basis of how mutations in known BAF subunits are associated with certain neurodevelopmental disorders. PMID:28824374

  1. Chromatin Remodeling BAF (SWI/SNF) Complexes in Neural Development and Disorders.

    Science.gov (United States)

    Sokpor, Godwin; Xie, Yuanbin; Rosenbusch, Joachim; Tuoc, Tran

    2017-01-01

    The ATP-dependent BRG1/BRM associated factor (BAF) chromatin remodeling complexes are crucial in regulating gene expression by controlling chromatin dynamics. Over the last decade, it has become increasingly clear that during neural development in mammals, distinct ontogenetic stage-specific BAF complexes derived from combinatorial assembly of their subunits are formed in neural progenitors and post-mitotic neural cells. Proper functioning of the BAF complexes plays critical roles in neural development, including the establishment and maintenance of neural fates and functionality. Indeed, recent human exome sequencing and genome-wide association studies have revealed that mutations in BAF complex subunits are linked to neurodevelopmental disorders such as Coffin-Siris syndrome, Nicolaides-Baraitser syndrome, Kleefstra's syndrome spectrum, Hirschsprung's disease, autism spectrum disorder, and schizophrenia. In this review, we focus on the latest insights into the functions of BAF complexes during neural development and the plausible mechanistic basis of how mutations in known BAF subunits are associated with certain neurodevelopmental disorders.

  2. The neural correlates of attachment security in typically developing children.

    Science.gov (United States)

    Choi, Eun Jung; Taylor, Margot J; Hong, Soon-Beom; Kim, Changdai; Yi, Soon-Hyung

    2018-07-01

    This study investigated neural correlates of children's attachment security using functional magnetic resonance imaging. Fifty-one boys' attachment styles (age mean = 9.5 years, SD = 0.61) were assessed with the Separation Anxiety Test (SAT). We created an fMRI version of the SAT to activate children's attachment system in fMRI environment and contrasted two conditions in which children were instructed to infer the specific feeling of the boy in the picture or to identify objects or physical activities. In the final fMRI analysis (N = 21), attachment security could be detected at the neural level corresponding to the behavioural differences in the attachment interview. Securely attached children showed greater activation in the frontal, limbic and basal ganglia area which included the dorsolateral prefrontal cortex, amygdala, cingulate cortex and striatum, compared to other children who had lower quality of attachment. These regions have a key role in socio-emotional information processing and also represent a brain network related to approach and avoidance motivation in humans. Especially the striatum, strongly linked to reward processing underpinning social approach and avoidance motivation, showed the largest effects in these differences and also positively correlated with emotional openness scores in SAT. This suggests that the quality of attachment configures the approach and avoidance motivational system in our brain mediated by the striatum. Copyright © 2018 Elsevier Inc. All rights reserved.

  3. 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.

  4. Synaptic Vesicle Endocytosis in Different Model Systems

    Directory of Open Access Journals (Sweden)

    Quan Gan

    2018-06-01

    Full Text Available Neurotransmission in complex animals depends on a choir of functionally distinct synapses releasing neurotransmitters in a highly coordinated manner. During synaptic signaling, vesicles fuse with the plasma membrane to release their contents. The rate of vesicle fusion is high and can exceed the rate at which synaptic vesicles can be re-supplied by distant sources. Thus, local compensatory endocytosis is needed to replenish the synaptic vesicle pools. Over the last four decades, various experimental methods and model systems have been used to study the cellular and molecular mechanisms underlying synaptic vesicle cycle. Clathrin-mediated endocytosis is thought to be the predominant mechanism for synaptic vesicle recycling. However, recent studies suggest significant contribution from other modes of endocytosis, including fast compensatory endocytosis, activity-dependent bulk endocytosis, ultrafast endocytosis, as well as kiss-and-run. Currently, it is not clear whether a universal model of vesicle recycling exist for all types of synapses. It is possible that each synapse type employs a particular mode of endocytosis. Alternatively, multiple modes of endocytosis operate at the same synapse, and the synapse toggles between different modes depending on its activity level. Here we compile review and research articles based on well-characterized model systems: frog neuromuscular junctions, C. elegans neuromuscular junctions, Drosophila neuromuscular junctions, lamprey reticulospinal giant axons, goldfish retinal ribbon synapses, the calyx of Held, and rodent hippocampal synapses. We will compare these systems in terms of their known modes and kinetics of synaptic vesicle endocytosis, as well as the underlying molecular machineries. We will also provide the future development of this field.

  5. The role of gamma-aminobutyric acid/glycinergic synaptic transmission in mediating bilirubin-induced hyperexcitation in developing auditory neurons.

    Science.gov (United States)

    Yin, Xin-Lu; Liang, Min; Shi, Hai-Bo; Wang, Lu-Yang; Li, Chun-Yan; Yin, Shan-Kai

    2016-01-05

    Hyperbilirubinemia is a common clinical phenomenon observed in human newborns. A high level of bilirubin can result in severe jaundice and bilirubin encephalopathy. However, the cellular mechanisms underlying bilirubin excitotoxicity are unclear. Our previous studies showed the action of gamma-aminobutyric acid (GABA)/glycine switches from excitatory to inhibitory during development in the ventral cochlear nucleus (VCN), one of the most sensitive auditory nuclei to bilirubin toxicity. In the present study, we investigated the roles of GABAA/glycine receptors in the induction of bilirubin hyperexcitation in early developing neurons. Using the patch clamp technique, GABAA/glycine receptor-mediated spontaneous inhibitory synaptic currents (sIPSCs) were recorded from bushy and stellate cells in acute brainstem slices from young mice (postnatal day 2-6). Bilirubin significantly increased the frequency of sIPSCs, and this effect was prevented by pretreatments of slices with either fast or slow Ca(2+) chelators BAPTA-AM and EGTA-AM suggesting that bilirubin can increase the release of GABA/glycine via Ca(2+)-dependent mechanisms. Using cell-attached recording configuration, we found that antagonists of GABAA and glycine receptors strongly attenuated spontaneous spiking firings in P2-6 neurons but produced opposite effect in P15-19 neurons. Furthermore, these antagonists reversed bilirubin-evoked hyperexcitability in P2-6 neurons, indicating that excitatory action of GABA/glycinergic transmission specifically contribute to bilirubin-induced hyperexcitability in the early stage of development. Our results suggest that bilirubin-induced enhancement of presynaptic release GABA/Glycine via Ca(2+)-dependent mechanisms may play a critical role in mediating neuronal hyperexcitation associated with jaundice, implicating potential new strategies for predicting, preventing, and treating bilirubin neurotoxicity. Copyright © 2015. Published by Elsevier Ireland Ltd.

  6. MAGUKs: multifaceted synaptic organizers.

    Science.gov (United States)

    Won, Sehoon; Levy, Jon M; Nicoll, Roger A; Roche, Katherine W

    2017-04-01

    The PSD-95 family of proteins, known as MAGUKs, have long been recognized to be central building blocks of the PSD. They are categorized as scaffolding proteins, which link surface-expressed receptors to the intracellular signaling molecules. Although the four members of the PSD-95 family (PSD-95, PSD-93, SAP102, and SAP97) have many shared roles in regulating synaptic function, recent studies have begun to delineate specific binding partners and roles in plasticity. In the current review, we will highlight the conserved and unique roles of these proteins. Published by Elsevier Ltd.

  7. Meninges harbor cells expressing neural precursor markers during development and adulthood.

    Science.gov (United States)

    Bifari, Francesco; Berton, Valeria; Pino, Annachiara; Kusalo, Marijana; Malpeli, Giorgio; Di Chio, Marzia; Bersan, Emanuela; Amato, Eliana; Scarpa, Aldo; Krampera, Mauro; Fumagalli, Guido; Decimo, Ilaria

    2015-01-01

    Brain and skull developments are tightly synchronized, allowing the cranial bones to dynamically adapt to the brain shape. At the brain-skull interface, meninges produce the trophic signals necessary for normal corticogenesis and bone development. Meninges harbor different cell populations, including cells forming the endosteum of the cranial vault. Recently, we and other groups have described the presence in meninges of a cell population endowed with neural differentiation potential in vitro and, after transplantation, in vivo. However, whether meninges may be a niche for neural progenitor cells during embryonic development and in adulthood remains to be determined. In this work we provide the first description of the distribution of neural precursor markers in rat meninges during development up to adulthood. We conclude that meninges share common properties with the classical neural stem cell niche, as they: (i) are a highly proliferating tissue; (ii) host cells expressing neural precursor markers such as nestin, vimentin, Sox2 and doublecortin; and (iii) are enriched in extracellular matrix components (e.g., fractones) known to bind and concentrate growth factors. This study underlines the importance of meninges as a potential niche for endogenous precursor cells during development and in adulthood.

  8. Development and aging of a brain neural stem cell niche.

    Science.gov (United States)

    Conover, Joanne C; Todd, Krysti L

    2017-08-01

    In the anterior forebrain, along the lateral wall of the lateral ventricles, a neurogenic stem cell niche is found in a region referred to as the ventricular-subventricular zone (V-SVZ). In rodents, robust V-SVZ neurogenesis provides new neurons to the olfactory bulb throughout adulthood; however, with increasing age stem cell numbers are reduced and neurogenic capacity is significantly diminished, but new olfactory bulb neurons continue to be produced even in old age. Humans, in contrast, show little to no new neurogenesis after two years of age and whether V-SVZ neural stem cells persist in the adult human brain remains unclear. Here, we review functional and organizational differences in the V-SVZ stem cell niche of mice and humans, and examine how aging affects the V-SVZ niche and its associated functions. Copyright © 2016 Elsevier Inc. All rights reserved.

  9. Synaptic organization and division of labor in the exceptionally polymorphic ant Pheidole rhea.

    Science.gov (United States)

    Gordon, Darcy G; Traniello, James F A

    2018-05-29

    Social insect polyphenisms provide models to examine the neural basis of division of labor and anatomy of the invertebrate social brain. Worker size-related behavior is hypothesized to enhance task performance, raising questions concerning the integration of morphology, behavior, and cellular neuroarchitecture, and how variation in sensory inputs and cognitive demands of behaviorally differentiated workers is reflected in higher-order processing ability. We used the highly polymorphic ant Pheidole rhea, which has three distinct worker size classes - minors, soldiers, and supersoldiers - to examine variation in synaptic circuitry across worker size and social role. We hypothesized that the density and size of synaptic complexes (microglomeruli, MG) would be positively associated with behavioral repertoire and the relative size of the mushroom bodies (MB). Supersoldiers had significantly larger and less dense MG in the lip (olfactory region) of the MB calyx (MBC), and larger MG in the collar (visual region) compared to minors. Soldiers were intermediate in synaptic phenotype: they did not differ significantly in MG density from minors and supersoldiers, had MG of similar size to minors in the lip, and did not differ from these two worker groups in MG size in the collar. Results suggest a complex relationship between MG density, size, behavior, and worker body size involving a conserved and plastic neurobiological development plan, although workers show strong variation in size and social role. Copyright © 2018 Elsevier B.V. All rights reserved.

  10. Oxytocin as a Modulator of Synaptic Plasticity: Implications for Neurodevelopmental Disorders

    Directory of Open Access Journals (Sweden)

    Keerthi Thirtamara Rajamani

    2018-06-01

    Full Text Available The neuropeptide oxytocin (OXT is a crucial mediator of parturition and milk ejection and a major modulator of various social behaviors, including social recognition, aggression and parenting. In the past decade, there has been significant excitement around the possible use of OXT to treat behavioral deficits in neurodevelopmental disorders, including autism spectrum disorder (ASD. Yet, despite the fast move to clinical trials with OXT, little attention has been paid to the possibility that the OXT system in the brain is perturbed in these disorders and to what extent such perturbations may contribute to social behavior deficits. Large-scale whole-exome sequencing studies in subjects with ASD, along with biochemical and electrophysiological studies in animal models of the disorder, indicate several risk genes that play an essential role in brain synapses, suggesting that deficits in synaptic activity and plasticity underlie the pathophysiology in a considerable portion of these cases. OXT has been repeatedly shown, both in vitro and in vivo, to modify synaptic properties and plasticity and to modulate neural activity in circuits that regulate social behavior. Together, these findings led us to hypothesize that failure of the OXT system during early development, as a direct or indirect consequence of genetic mutations, may impact social behavior by altering synaptic activity and plasticity. In this article, we review the evidence that support our hypothesis.

  11. Development of Fast-Running Simulation Methodology Using Neural Networks for Load Follow Operation

    International Nuclear Information System (INIS)

    Seong, Seung-Hwan; Park, Heui-Youn; Kim, Dong-Hoon; Suh, Yong-Suk; Hur, Seop; Koo, In-Soo; Lee, Un-Chul; Jang, Jin-Wook; Shin, Yong-Chul

    2002-01-01

    A new fast-running analytic model has been developed for analyzing the load follow operation. The new model was based on the neural network theory, which has the capability of modeling the input/output relationships of a nonlinear system. The new model is made up of two error back-propagation neural networks and procedures to calculate core parameters, such as the distributions and density of xenon in a quasi-steady-state core like load follow operation. One neural network is designed to retrieve the axial offset of power distribution, and the other is for reactivity corresponding to a given core condition. The training data sets for learning the neural networks in the new model are generated with a three-dimensional nodal code and, also, the measured data of the first-day test of load follow operation. Using the new model, the simulation results of the 5-day load follow test in a pressurized water reactor show a good agreement between the simulation data and the actual measured data. Required computing time for simulating a load follow operation is comparable to that of a fast-running lumped model. Moreover, the new model does not require additional engineering factors to compensate for the difference between the actual measurements and analysis results because the neural network has the inherent learning capability of neural networks to new situations

  12. Glutamatergic synaptic plasticity in the mesocorticolimbic system in addiction

    Directory of Open Access Journals (Sweden)

    Aile evan Huijstee

    2015-01-01

    Full Text Available Addictive drugs remodel the brain’s reward circuitry, the mesocorticolimbic dopamine system, by inducing widespread adaptations of glutamatergic synapses. This drug-induced synaptic plasticity is thought to contribute to both the development and the persistence of addiction. This review highlights the synaptic modifications that are induced by in vivo exposure to addictive drugs and describes how these drug-induced synaptic changes may contribute to the different components of addictive behaviour, such as compulsive drug use despite negative consequences and relapse. Initially, exposure to an addictive drug induces synaptic changes in the ventral tegmental area (VTA. This drug-induced synaptic potentiation in the VTA subsequently triggers synaptic changes in downstream areas of the mesocorticolimbic system, such as the nucleus accumbens (NAc and the prefrontal cortex (PFC, with further drug exposure. These glutamatergic synaptic alterations are then thought to mediate many of the behavioural symptoms that characterize addiction. The later stages of glutamatergic synaptic plasticity in the NAc and in particular in the PFC play a role in maintaining addiction and drive relapse to drug-taking induced by drug-associated cues. Remodelling of PFC glutamatergic circuits can persist into adulthood, causing a lasting vulnerability to relapse. We will discuss how these neurobiological changes produced by drugs of abuse may provide novel targets for potential treatment strategies for addiction.

  13. Glutamatergic synaptic plasticity in the mesocorticolimbic system in addiction

    Science.gov (United States)

    van Huijstee, Aile N.; Mansvelder, Huibert D.

    2015-01-01

    Addictive drugs remodel the brain’s reward circuitry, the mesocorticolimbic dopamine (DA) system, by inducing widespread adaptations of glutamatergic synapses. This drug-induced synaptic plasticity is thought to contribute to both the development and the persistence of addiction. This review highlights the synaptic modifications that are induced by in vivo exposure to addictive drugs and describes how these drug-induced synaptic changes may contribute to the different components of addictive behavior, such as compulsive drug use despite negative consequences and relapse. Initially, exposure to an addictive drug induces synaptic changes in the ventral tegmental area (VTA). This drug-induced synaptic potentiation in the VTA subsequently triggers synaptic changes in downstream areas of the mesocorticolimbic system, such as the nucleus accumbens (NAc) and the prefrontal cortex (PFC), with further drug exposure. These glutamatergic synaptic alterations are then thought to mediate many of the behavioral symptoms that characterize addiction. The later stages of glutamatergic synaptic plasticity in the NAc and in particular in the PFC play a role in maintaining addiction and drive relapse to drug-taking induced by drug-associated cues. Remodeling of PFC glutamatergic circuits can persist into adulthood, causing a lasting vulnerability to relapse. We will discuss how these neurobiological changes produced by drugs of abuse may provide novel targets for potential treatment strategies for addiction. PMID:25653591

  14. Nicotinic mechanisms influencing synaptic plasticity in the hippocampus

    Institute of Scientific and Technical Information of China (English)

    Andon Nicholas PLACZEK; Tao A ZHANG; John Anthony DANI

    2009-01-01

    Nicotinic acetylcholine receptors (nAChRs) are expressed throughout the hippocampus, and nicotinic signaling plays an important role in neuronal function. In the context of learning and memory related behaviors associated with hippocampal function, a potentially significant feature of nAChR activity is the impact it has on synaptic plasticity. Synaptic plasticity in hippocampal neurons has long been considered a contributing cellular mechanism of learning and memory. These same kinds of cellular mechanisms are a factor in the development of nicotine addiction. Nicotinic signaling has been demonstrated by in vitro studies to affect synaptic plasticity in hippocampal neurons via multiple steps, and the signaling has also been shown to evoke synaptic plasticity in vivo. This review focuses on the nAChRs subtypes that contribute to hippocampal synaptic plasticity at the cellular and circuit level. It also considers nicotinic influences over long-term changes in the hippocampus that may contribute to addiction.

  15. Integrated neuron circuit for implementing neuromorphic system with synaptic device

    Science.gov (United States)

    Lee, Jeong-Jun; Park, Jungjin; Kwon, Min-Woo; Hwang, Sungmin; Kim, Hyungjin; Park, Byung-Gook

    2018-02-01

    In this paper, we propose and fabricate Integrate & Fire neuron circuit for implementing neuromorphic system. Overall operation of the circuit is verified by measuring discrete devices and the output characteristics of the circuit. Since the neuron circuit shows asymmetric output characteristic that can drive synaptic device with Spike-Timing-Dependent-Plasticity (STDP) characteristic, the autonomous weight update process is also verified by connecting the synaptic device and the neuron circuit. The timing difference of the pre-neuron and the post-neuron induce autonomous weight change of the synaptic device. Unlike 2-terminal devices, which is frequently used to implement neuromorphic system, proposed scheme of the system enables autonomous weight update and simple configuration by using 4-terminal synapse device and appropriate neuron circuit. Weight update process in the multi-layer neuron-synapse connection ensures implementation of the hardware-based artificial intelligence, based on Spiking-Neural- Network (SNN).

  16. Corticotropin-releasing factor receptor types 1 and 2 are differentially expressed in pre- and post-synaptic elements in the post-natal developing rat cerebellum

    NARCIS (Netherlands)

    Swinny, JD; Kalicharan, D; Blaauw, EH; Ijkema-Paassen, J; Shi, F; Gramsbergen, A; van der Want, JJL

    Corticotropin-releasing factor (CRF)-like proteins act via two G-protein-coupled receptors (CRF-R1 and CRF-R2) playing important neuromodulatory roles in stress responses and synaptic plasticity. The cerebellar expression of corticotropin-releasing factor-like ligands has been well documented, but

  17. Development of biomaterial scaffold for nerve tissue engineering: Biomaterial mediated neural regeneration

    Directory of Open Access Journals (Sweden)

    Sethuraman Swaminathan

    2009-11-01

    Full Text Available Abstract Neural tissue repair and regeneration strategies have received a great deal of attention because it directly affects the quality of the patient's life. There are many scientific challenges to regenerate nerve while using conventional autologous nerve grafts and from the newly developed therapeutic strategies for the reconstruction of damaged nerves. Recent advancements in nerve regeneration have involved the application of tissue engineering principles and this has evolved a new perspective to neural therapy. The success of neural tissue engineering is mainly based on the regulation of cell behavior and tissue progression through the development of a synthetic scaffold that is analogous to the natural extracellular matrix and can support three-dimensional cell cultures. As the natural extracellular matrix provides an ideal environment for topographical, electrical and chemical cues to the adhesion and proliferation of neural cells, there exists a need to develop a synthetic scaffold that would be biocompatible, immunologically inert, conducting, biodegradable, and infection-resistant biomaterial to support neurite outgrowth. This review outlines the rationale for effective neural tissue engineering through the use of suitable biomaterials and scaffolding techniques for fabrication of a construct that would allow the neurons to adhere, proliferate and eventually form nerves.

  18. Development of biomaterial scaffold for nerve tissue engineering: Biomaterial mediated neural regeneration

    Science.gov (United States)

    2009-01-01

    Neural tissue repair and regeneration strategies have received a great deal of attention because it directly affects the quality of the patient's life. There are many scientific challenges to regenerate nerve while using conventional autologous nerve grafts and from the newly developed therapeutic strategies for the reconstruction of damaged nerves. Recent advancements in nerve regeneration have involved the application of tissue engineering principles and this has evolved a new perspective to neural therapy. The success of neural tissue engineering is mainly based on the regulation of cell behavior and tissue progression through the development of a synthetic scaffold that is analogous to the natural extracellular matrix and can support three-dimensional cell cultures. As the natural extracellular matrix provides an ideal environment for topographical, electrical and chemical cues to the adhesion and proliferation of neural cells, there exists a need to develop a synthetic scaffold that would be biocompatible, immunologically inert, conducting, biodegradable, and infection-resistant biomaterial to support neurite outgrowth. This review outlines the rationale for effective neural tissue engineering through the use of suitable biomaterials and scaffolding techniques for fabrication of a construct that would allow the neurons to adhere, proliferate and eventually form nerves. PMID:19939265

  19. Nuclear receptor TLX regulates cell cycle progression in neural stem cells of the developing brain.

    Science.gov (United States)

    Li, Wenwu; Sun, Guoqiang; Yang, Su; Qu, Qiuhao; Nakashima, Kinichi; Shi, Yanhong

    2008-01-01

    TLX is an orphan nuclear receptor that is expressed exclusively in vertebrate forebrains. Although TLX is known to be expressed in embryonic brains, the mechanism by which it influences neural development remains largely unknown. We show here that TLX is expressed specifically in periventricular neural stem cells in embryonic brains. Significant thinning of neocortex was observed in embryonic d 14.5 TLX-null brains with reduced nestin labeling and decreased cell proliferation in the germinal zone. Cell cycle analysis revealed both prolonged cell cycles and increased cell cycle exit in TLX-null embryonic brains. Increased expression of a cyclin-dependent kinase inhibitor p21 and decreased expression of cyclin D1 provide a molecular basis for the deficiency of cell cycle progression in embryonic brains of TLX-null mice. Furthermore, transient knockdown of TLX by in utero electroporation led to precocious cell cycle exit and differentiation of neural stem cells followed by outward migration. Together these results indicate that TLX plays an important role in neural development by regulating cell cycle progression and exit of neural stem cells in the developing brain.

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

    Science.gov (United States)

    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.

  1. Artificial neural network decision support systems for new product development project selection

    NARCIS (Netherlands)

    Thieme, R.J.; Song, Michael; Calantone, R.J.

    2000-01-01

    The authors extend and develop an artificial neural network decision support system and demonstrate how it can guide managers when they make complex new product development decisions. The authors use data from 612 projects to compare this new method with traditional methods for predicting various

  2. Measuring and Reconstructing the Brain at the Synaptic Scale: Towards a Biofidelic Human Brain in silico

    OpenAIRE

    NeuroData; CE, Priebe; Burns, R.; RJ, Vogelstein

    2015-01-01

    Vogelstein JT, Priebe CE, Burns R, Vogelstein RJ, Lichtman J. Measuring and Reconstructing the Brain at the Synaptic Scale: Towards a Biofidelic Human Brain in silico. DARPA Neural Engineering, Science and Technology Forum, 2010

  3. Presenilins are required for maintenance of neural stem cells in the developing brain

    Directory of Open Access Journals (Sweden)

    Kim Woo-Young

    2008-01-01

    Full Text Available Abstract The early embryonic lethality of mutant mice bearing germ-line deletions of both presenilin genes precluded the study of their functions in neural development. We therefore employed the Cre-loxP technology to generate presenilin conditional double knockout (PS cDKO mice, in which expression of both presenilins is inactivated in neural progenitor cells (NPC or neural stem cells and their derivative neurons and glia beginning at embryonic day 11 (E11. In PS cDKO mice, dividing NPCs labeled by BrdU are decreased in number beginning at E13.5. By E15.5, fewer than 20% of NPCs remain in PS cDKO mice. The depletion of NPCs is accompanied by severe morphological defects and hemorrhages in the PS cDKO embryonic brain. Interkinetic nuclear migration of NPCs is also disrupted in PS cDKO embryos, as evidenced by displacement of S-phase and M-phase nuclei in the ventricular zone of the telencephalon. Furthermore, the depletion of neural progenitor cells in PS cDKO embryos is due to NPCs exiting cell cycle and differentiating into neurons rather than reentering cell cycle between E13.5 and E14.5 following PS inactivation in most NPCs. The length of cell cycle, however, is unchanged in PS cDKO embryos. Expression of Notch target genes, Hes1 and Hes5, is significantly decreased in PS cDKO brains, whereas Dll1 expression is up-regulated, indicating that Notch signaling is effectively blocked by PS inactivation. These findings demonstrate that presenilins are essential for neural progenitor cells to re-enter cell cycle and thus ensure proper expansion of neural progenitor pool during embryonic neural development.

  4. Genetic attack on neural cryptography.

    Science.gov (United States)

    Ruttor, Andreas; Kinzel, Wolfgang; Naeh, Rivka; Kanter, Ido

    2006-03-01

    Different scaling properties for the complexity of bidirectional synchronization and unidirectional learning are essential for the security of neural cryptography. Incrementing the synaptic depth of the networks increases the synchronization time only polynomially, but the success of the geometric attack is reduced exponentially and it clearly fails in the limit of infinite synaptic depth. This method is improved by adding a genetic algorithm, which selects the fittest neural networks. The probability of a successful genetic attack is calculated for different model parameters using numerical simulations. The results show that scaling laws observed in the case of other attacks hold for the improved algorithm, too. The number of networks needed for an effective attack grows exponentially with increasing synaptic depth. In addition, finite-size effects caused by Hebbian and anti-Hebbian learning are analyzed. These learning rules converge to the random walk rule if the synaptic depth is small compared to the square root of the system size.

  5. Genetic attack on neural cryptography

    International Nuclear Information System (INIS)

    Ruttor, Andreas; Kinzel, Wolfgang; Naeh, Rivka; Kanter, Ido

    2006-01-01

    Different scaling properties for the complexity of bidirectional synchronization and unidirectional learning are essential for the security of neural cryptography. Incrementing the synaptic depth of the networks increases the synchronization time only polynomially, but the success of the geometric attack is reduced exponentially and it clearly fails in the limit of infinite synaptic depth. This method is improved by adding a genetic algorithm, which selects the fittest neural networks. The probability of a successful genetic attack is calculated for different model parameters using numerical simulations. The results show that scaling laws observed in the case of other attacks hold for the improved algorithm, too. The number of networks needed for an effective attack grows exponentially with increasing synaptic depth. In addition, finite-size effects caused by Hebbian and anti-Hebbian learning are analyzed. These learning rules converge to the random walk rule if the synaptic depth is small compared to the square root of the system size

  6. Genetic attack on neural cryptography

    Science.gov (United States)

    Ruttor, Andreas; Kinzel, Wolfgang; Naeh, Rivka; Kanter, Ido

    2006-03-01

    Different scaling properties for the complexity of bidirectional synchronization and unidirectional learning are essential for the security of neural cryptography. Incrementing the synaptic depth of the networks increases the synchronization time only polynomially, but the success of the geometric attack is reduced exponentially and it clearly fails in the limit of infinite synaptic depth. This method is improved by adding a genetic algorithm, which selects the fittest neural networks. The probability of a successful genetic attack is calculated for different model parameters using numerical simulations. The results show that scaling laws observed in the case of other attacks hold for the improved algorithm, too. The number of networks needed for an effective attack grows exponentially with increasing synaptic depth. In addition, finite-size effects caused by Hebbian and anti-Hebbian learning are analyzed. These learning rules converge to the random walk rule if the synaptic depth is small compared to the square root of the system size.

  7. Synaptic electronics: materials, devices and applications.

    Science.gov (United States)

    Kuzum, Duygu; Yu, Shimeng; Wong, H-S Philip

    2013-09-27

    In this paper, the recent progress of synaptic electronics is reviewed. The basics of biological synaptic plasticity and learning are described. The material properties and electrical switching characteristics of a variety of synaptic devices are discussed, with a focus on the use of synaptic devices for neuromorphic or brain-inspired computing. Performance metrics desirable for large-scale implementations of synaptic devices are illustrated. A review of recent work on targeted computing applications with synaptic devices is presented.

  8. Synaptic electronics: materials, devices and applications

    International Nuclear Information System (INIS)

    Kuzum, Duygu; Yu, Shimeng; Philip Wong, H-S

    2013-01-01

    In this paper, the recent progress of synaptic electronics is reviewed. The basics of biological synaptic plasticity and learning are described. The material properties and electrical switching characteristics of a variety of synaptic devices are discussed, with a focus on the use of synaptic devices for neuromorphic or brain-inspired computing. Performance metrics desirable for large-scale implementations of synaptic devices are illustrated. A review of recent work on targeted computing applications with synaptic devices is presented. (topical review)

  9. Molecular regionalization of the developing amphioxus neural tube challenges major partitions of the vertebrate brain.

    Science.gov (United States)

    Albuixech-Crespo, Beatriz; López-Blanch, Laura; Burguera, Demian; Maeso, Ignacio; Sánchez-Arrones, Luisa; Moreno-Bravo, Juan Antonio; Somorjai, Ildiko; Pascual-Anaya, Juan; Puelles, Eduardo; Bovolenta, Paola; Garcia-Fernàndez, Jordi; Puelles, Luis; Irimia, Manuel; Ferran, José Luis

    2017-04-01

    All vertebrate brains develop following a common Bauplan defined by anteroposterior (AP) and dorsoventral (DV) subdivisions, characterized by largely conserved differential expression of gene markers. However, it is still unclear how this Bauplan originated during evolution. We studied the relative expression of 48 genes with key roles in vertebrate neural patterning in a representative amphioxus embryonic stage. Unlike nonchordates, amphioxus develops its central nervous system (CNS) from a neural plate that is homologous to that of vertebrates, allowing direct topological comparisons. The resulting genoarchitectonic model revealed that the amphioxus incipient neural tube is unexpectedly complex, consisting of several AP and DV molecular partitions. Strikingly, comparison with vertebrates indicates that the vertebrate thalamus, pretectum, and midbrain domains jointly correspond to a single amphioxus region, which we termed Di-Mesencephalic primordium (DiMes). This suggests that these domains have a common developmental and evolutionary origin, as supported by functional experiments manipulating secondary organizers in zebrafish and mice.

  10. Strategies influence neural activity for feedback learning across child and adolescent development.

    Science.gov (United States)

    Peters, Sabine; Koolschijn, P Cédric M P; Crone, Eveline A; Van Duijvenvoorde, Anna C K; Raijmakers, Maartje E J

    2014-09-01

    Learning from feedback is an important aspect of executive functioning that shows profound improvements during childhood and adolescence. This is accompanied by neural changes in the feedback-learning network, which includes pre-supplementary motor area (pre- SMA)/anterior cingulate cortex (ACC), dorsolateral prefrontal cortex (DLPFC), superior parietal cortex (SPC), and the basal ganglia. However, there can be considerable differences within age ranges in performance that are ascribed to differences in strategy use. This is problematic for traditional approaches of analyzing developmental data, in which age groups are assumed to be homogenous in strategy use. In this study, we used latent variable models to investigate if underlying strategy groups could be detected for a feedback-learning task and whether there were differences in neural activation patterns between strategies. In a sample of 268 participants between ages 8 to 25 years, we observed four underlying strategy groups, which were cut across age groups and varied in the optimality of executive functioning. These strategy groups also differed in neural activity during learning; especially the most optimal performing group showed more activity in DLPFC, SPC and pre-SMA/ACC compared to the other groups. However, age differences remained an important contributor to neural activation, even when correcting for strategy. These findings contribute to the debate of age versus performance predictors of neural development, and highlight the importance of studying individual differences in strategy use when studying development. Copyright © 2014 Elsevier Ltd. All rights reserved.

  11. The role of BAF (mSWI/SNF) complexes in mammalian neural development.

    Science.gov (United States)

    Son, Esther Y; Crabtree, Gerald R

    2014-09-01

    The BAF (mammalian SWI/SNF) complexes are a family of multi-subunit ATP-dependent chromatin remodelers that use ATP hydrolysis to alter chromatin structure. Distinct BAF complex compositions are possible through combinatorial assembly of homologous subunit families and can serve non-redundant functions. In mammalian neural development, developmental stage-specific BAF assemblies are found in embryonic stem cells, neural progenitors and postmitotic neurons. In particular, the neural progenitor-specific BAF complexes are essential for controlling the kinetics and mode of neural progenitor cell division, while neuronal BAF function is necessary for the maturation of postmitotic neuronal phenotypes as well as long-term memory formation. The microRNA-mediated mechanism for transitioning from npBAF to nBAF complexes is instructive for the neuronal fate and can even convert fibroblasts into neurons. The high frequency of BAF subunit mutations in neurological disorders underscores the rate-determining role of BAF complexes in neural development, homeostasis, and plasticity. © 2014 Wiley Periodicals, Inc.

  12. Neuronal cytoskeleton in synaptic plasticity and regeneration.

    Science.gov (United States)

    Gordon-Weeks, Phillip R; Fournier, Alyson E

    2014-04-01

    During development, dynamic changes in the axonal growth cone and dendrite are necessary for exploratory movements underlying initial axo-dendritic contact and ultimately the formation of a functional synapse. In the adult central nervous system, an impressive degree of plasticity is retained through morphological and molecular rearrangements in the pre- and post-synaptic compartments that underlie the strengthening or weakening of synaptic pathways. Plasticity is regulated by the interplay of permissive and inhibitory extracellular cues, which signal through receptors at the synapse to regulate the closure of critical periods of developmental plasticity as well as by acute changes in plasticity in response to experience and activity in the adult. The molecular underpinnings of synaptic plasticity are actively studied and it is clear that the cytoskeleton is a key substrate for many cues that affect plasticity. Many of the cues that restrict synaptic plasticity exhibit residual activity in the injured adult CNS and restrict regenerative growth by targeting the cytoskeleton. Here, we review some of the latest insights into how cytoskeletal remodeling affects neuronal plasticity and discuss how the cytoskeleton is being targeted in an effort to promote plasticity and repair following traumatic injury in the central nervous system. © 2013 International Society for Neurochemistry.

  13. Neural crest stem cell population in craniomaxillofacial development and tissue repair

    Directory of Open Access Journals (Sweden)

    M La Noce

    2014-10-01

    Full Text Available Neural crest cells, delaminating from the neural tube during migration, undergo an epithelial-mesenchymal transition and differentiate into several cell types strongly reinforcing the mesoderm of the craniofacial body area – giving rise to bone, cartilage and other tissues and cells of this human body area. Recent studies on craniomaxillofacial neural crest-derived cells have provided evidence for the tremendous plasticity of these cells. Actually, neural crest cells can respond and adapt to the environment in which they migrate and the cranial mesoderm plays an important role toward patterning the identity of the migrating neural crest cells. In our experience, neural crest-derived stem cells, such as dental pulp stem cells, can actively proliferate, repair bone and give rise to other tissues and cytotypes, including blood vessels, smooth muscle, adipocytes and melanocytes, highlighting that their use in tissue engineering is successful. In this review, we provide an overview of the main pathways involved in neural crest formation, delamination, migration and differentiation; and, in particular, we concentrate our attention on the translatability of the latest scientific progress. Here we try to suggest new ideas and strategies that are needed to fully develop the clinical use of these cells. This effort should involve both researchers/clinicians and improvements in good manufacturing practice procedures. It is important to address studies towards clinical application or take into consideration that studies must have an effective therapeutic prospect for humans. New approaches and ideas must be concentrated also toward stem cell recruitment and activation within the human body, overcoming the classical grafting.

  14. Characterization and extraction of the synaptic apposition surface for synaptic geometry analysis

    Science.gov (United States)

    Morales, Juan; Rodríguez, Angel; Rodríguez, José-Rodrigo; DeFelipe, Javier; Merchán-Pérez, Angel

    2013-01-01

    Geometrical features of chemical synapses are relevant to their function. Two critical components of the synaptic junction are the active zone (AZ) and the postsynaptic density (PSD), as they are related to the probability of synaptic release and the number of postsynaptic receptors, respectively. Morphological studies of these structures are greatly facilitated by the use of recent electron microscopy techniques, such as combined focused ion beam milling and scanning electron microscopy (FIB/SEM), and software tools that permit reconstruction of large numbers of synapses in three dimensions. Since the AZ and the PSD are in close apposition and have a similar surface area, they can be represented by a single surface—the synaptic apposition surface (SAS). We have developed an efficient computational technique to automatically extract this surface from synaptic junctions that have previously been three-dimensionally reconstructed from actual tissue samples imaged by automated FIB/SEM. Given its relationship with the release probability and the number of postsynaptic receptors, the surface area of the SAS is a functionally relevant measure of the size of a synapse that can complement other geometrical features like the volume of the reconstructed synaptic junction, the equivalent ellipsoid size and the Feret's diameter. PMID:23847474

  15. Stereotyped Synaptic Connectivity Is Restored during Circuit Repair in the Adult Mammalian Retina.

    Science.gov (United States)

    Beier, Corinne; Palanker, Daniel; Sher, Alexander

    2018-06-04

    Proper function of the central nervous system (CNS) depends on the specificity of synaptic connections between cells of various types. Cellular and molecular mechanisms responsible for the establishment and refinement of these connections during development are the subject of an active area of research [1-6]. However, it is unknown if the adult mammalian CNS can form new type-selective synapses following neural injury or disease. Here, we assess whether selective synaptic connections can be reestablished after circuit disruption in the adult mammalian retina. The stereotyped circuitry at the first synapse in the retina, as well as the relatively short distances new neurites must travel compared to other areas of the CNS, make the retina well suited to probing for synaptic specificity during circuit reassembly. Selective connections between short-wavelength sensitive cone photoreceptors (S-cones) and S-cone bipolar cells provides the foundation of the primordial blue-yellow vision, common to all mammals [7-18]. We take advantage of the ground squirrel retina, which has a one-to-one S-cone-to-S-cone-bipolar-cell connection, to test if this connectivity can be reestablished following local photoreceptor loss [8, 19]. We find that after in vivo selective photoreceptor ablation, deafferented S-cone bipolar cells expand their dendritic trees. The new dendrites randomly explore the proper synaptic layer, bypass medium-wavelength sensitive cone photoreceptors (M-cones), and selectively synapse with S-cones. However, non-connected dendrites are not pruned back to resemble unperturbed S-cone bipolar cells. We show, for the first time, that circuit repair in the adult mammalian retina can recreate stereotypic selective wiring. Copyright © 2018 Elsevier Ltd. All rights reserved.

  16. Amplification of neural stem cell proliferation by intermediate progenitor cells in Drosophila brain development

    Directory of Open Access Journals (Sweden)

    Bello Bruno C

    2008-02-01

    Full Text Available Abstract Background In the mammalian brain, neural stem cells divide asymmetrically and often amplify the number of progeny they generate via symmetrically dividing intermediate progenitors. Here we investigate whether specific neural stem cell-like neuroblasts in the brain of Drosophila might also amplify neuronal proliferation by generating symmetrically dividing intermediate progenitors. Results Cell lineage-tracing and genetic marker analysis show that remarkably large neuroblast lineages exist in the dorsomedial larval brain of Drosophila. These lineages are generated by brain neuroblasts that divide asymmetrically to self renew but, unlike other brain neuroblasts, do not segregate the differentiating cell fate determinant Prospero to their smaller daughter cells. These daughter cells continue to express neuroblast-specific molecular markers and divide repeatedly to produce neural progeny, demonstrating that they are proliferating intermediate progenitors. The proliferative divisions of these intermediate progenitors have novel cellular and molecular features; they are morphologically symmetrical, but molecularly asymmetrical in that key differentiating cell fate determinants are segregated into only one of the two daughter cells. Conclusion Our findings provide cellular and molecular evidence for a new mode of neurogenesis in the larval brain of Drosophila that involves the amplification of neuroblast proliferation through intermediate progenitors. This type of neurogenesis bears remarkable similarities to neurogenesis in the mammalian brain, where neural stem cells as primary progenitors amplify the number of progeny they generate through generation of secondary progenitors. This suggests that key aspects of neural stem cell biology might be conserved in brain development of insects and mammals.

  17. Development of neural network for analysis of local power distributions in BWR fuel bundles

    International Nuclear Information System (INIS)

    Tanabe, Akira; Yamamoto, Toru; Shinfuku, Kimihiro; Nakamae, Takuji.

    1993-01-01

    A neural network model has been developed to learn the local power distributions in a BWR fuel bundle. A two layers neural network with total 128 elements is used for this model. The neural network learns 33 cases of local power peaking factors of fuel rods with given enrichment distribution as the teacher signals, which were calculated by a fuel bundle nuclear analysis code based on precise physical models. This neural network model studied well the teacher signals within 1 % error. It is also able to calculate the local power distributions within several % error for the different enrichment distributions from the teacher signals when the average enrichment is close to 2 %. This neural network is simple and the computing speed of this model is 300 times faster than that of the precise nuclear analysis code. This model was applied to survey the enrichment distribution to meet a target local power distribution in a fuel bundle, and the enrichment distribution with flat power shape are obtained within short computing time. (author)

  18. 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)

  19. Development of test algorithm for semiconductor package with defects by using probabilistic neural network

    International Nuclear Information System (INIS)

    Kim, Jae Yeol; Sim, Jae Gi; Ko, Myoung Soo; Kim, Chang Hyun; Kim, Hun Cho

    2001-01-01

    In this study, researchers developing the estimative algorithm for artificial defects in semiconductor packages and performing it by pattern recognition technology. For this purpose, the estimative algorithm was included that researchers made software with MATLAB. The software consists of some procedures including ultrasonic image acquisition, equalization filtering, Self-Organizing Map and Probabilistic Neural Network. Self-Organizing Map and Probabilistic Neural Network are belong to methods of Neural Networks. And the pattern recognition technology has applied to classify three kinds of detective patterns in semiconductor packages. This study presumes probability density function from a sample of learning and present which is automatically determine method. PNN can distinguish flaws very difficult distinction as well as. This can do parallel process to stand in a row we confirm that is very efficiently classifier if we applied many data real the process.

  20. Dissecting Repulsive Guidance Molecule/Neogenin function and signaling during neural development

    NARCIS (Netherlands)

    van den Heuvel, D.M.A.

    2013-01-01

    During neural development a series of precisely ordered cellular processes acts to establish a functional brain comprising millions of neurons and many more neuronal connections. Neogenin and its repulsive guidance molecule (RGM) ligands contribute to neuronal network formation by inducing axon

  1. Characterization of Early Cortical Neural Network Development in Multiwell Microelectrode Array Plates

    Science.gov (United States)

    We examined the development of neural network activity using microelectrode array (MEA) recordings made in multi-well MEA plates (mwMEAs) over the first 12 days in vitro (DIV). In primary cortical cultures made from postnatal rats, action potential spiking activity was essentiall...

  2. 17β-Estradiol-Induced Synaptic Rearrangements Are Accompanied by Altered Ectonucleotidase Activities in Male Rat Hippocampal Synaptosomes.

    Science.gov (United States)

    Mitrović, Nataša; Zarić, Marina; Drakulić, Dunja; Martinović, Jelena; Sévigny, Jean; Stanojlović, Miloš; Nedeljković, Nadežda; Grković, Ivana

    2017-03-01

    17β-Estradiol (E2) rapidly, by binding to membrane estrogen receptors, activates cell signaling cascades which induce formation of new dendritic spines in the hippocampus of males as in females, but the interaction with other metabolic processes, such as extracellular adenine nucleotides metabolism, are currently unknown. Extracellular adenine nucleotides play significant roles, controlling excitatory glutamatergic synapses and development of neural circuits and synaptic plasticity. Their precise regulation in the synaptic cleft is tightly controlled by ecto-nucleoside triphosphate diphosphohydrolase (NTPDase)/ecto-5'-nucleotidase (eN) enzyme chain. Therefore, we sought to clarify whether a single systemic injection of E2 in male rats is accompanied by changes in the expression of the pre- and postsynaptic proteins and downstream kinases linked to E2-induced synaptic rearrangement as well as alterations in NTPDase/eN pathway in the hippocampal synaptosomes. Obtained data showed activation of mammalian target of rapamycin and upregulation of key synaptic proteins necessary for spine formation, 24 h after systemic E2 administration. In E2-mediated conditions, we found downregulation of NTPDase1 and NTPDase2 and attenuation of adenine nucleotide hydrolysis by NTPDase/eN enzyme chain, without changes in NTPDase3 properties and augmentation of synaptic tissue-nonspecific alkaline phosphatase (TNAP) activity. Despite reduced NTPDase activities, increased TNAP activity probably prevents toxic accumulation of ATP in the extracellular milieu and also hydrolyzes accumulated ADP due to unchanged NTPDase3 activity. Thus, our initial evaluation supports idea of specific roles of different ectonucleotidases and their coordinated actions in E2-mediated spine remodeling and maintenance.

  3. Isolation of Synaptosomes, Synaptic Plasma Membranes, and Synaptic Junctional Complexes.

    Science.gov (United States)

    Michaelis, Mary L; Jiang, Lei; Michaelis, Elias K

    2017-01-01

    Isolation of synaptic nerve terminals or synaptosomes provides an opportunity to study the process of neurotransmission at many levels and with a variety of approaches. For example, structural features of the synaptic terminals and the organelles within them, such as synaptic vesicles and mitochondria, have been elucidated with electron microscopy. The postsynaptic membranes are joined to the presynaptic "active zone" of transmitter release through cell adhesion molecules and remain attached throughout the isolation of synaptosomes. These "post synaptic densities" or "PSDs" contain the receptors for the transmitters released from the nerve terminals and can easily be seen with electron microscopy. Biochemical and cell biological studies with synaptosomes have revealed which proteins and lipids are most actively involved in synaptic release of neurotransmitters. The functional properties of the nerve terminals, such as responses to depolarization and the uptake or release of signaling molecules, have also been characterized through the use of fluorescent dyes, tagged transmitters, and transporter substrates. In addition, isolated synaptosomes can serve as the starting material for the isolation of relatively pure synaptic plasma membranes (SPMs) that are devoid of organelles from the internal environment of the nerve terminal, such as mitochondria and synaptic vesicles. The isolated SPMs can reseal and form vesicular structures in which transport of ions such as sodium and calcium, as well as solutes such as neurotransmitters can be studied. The PSDs also remain associated with the presynaptic membranes during isolation of SPM fractions, making it possible to isolate the synaptic junctional complexes (SJCs) devoid of the rest of the plasma membranes of the nerve terminals and postsynaptic membrane components. Isolated SJCs can be used to identify the proteins that constitute this highly specialized region of neurons. In this chapter, we describe the steps involved

  4. Neural Correlates of Socioeconomic Status in the Developing Human Brain

    Science.gov (United States)

    Noble, Kimberly G.; Houston, Suzanne M.; Kan, Eric; Sowell, Elizabeth R.

    2012-01-01

    Socioeconomic disparities in childhood are associated with remarkable differences in cognitive and socio-emotional development during a time when dramatic changes are occurring in the brain. Yet, the neurobiological pathways through which socioeconomic status (SES) shapes development remain poorly understood. Behavioral evidence suggests that…

  5. Music and Cognitive Development: From Notes to Neural Networks

    Science.gov (United States)

    Shore, Rebecca Ann

    2010-01-01

    This article investigates research on early childhood development and on both listening to music and participation in music activities by young children. Research is reviewed that explores possible relationships between various music-related experiences and cognitive development, from the "Mozart Effect" studies to participation in piano lessons…

  6. Models of neural dynamics in brain information processing - the developments of 'the decade'

    Energy Technology Data Exchange (ETDEWEB)

    Borisyuk, G N; Borisyuk, R M; Kazanovich, Yakov B [Institute of Mathematical Problems of Biology, Russian Academy of Sciences, Pushchino, Moscow region (Russian Federation); Ivanitskii, Genrikh R [Institute for Theoretical and Experimental Biophysics, Russian Academy of Sciences, Pushchino, Moscow region (Russian Federation)

    2002-10-31

    Neural network models are discussed that have been developed during the last decade with the purpose of reproducing spatio-temporal patterns of neural activity in different brain structures. The main goal of the modeling was to test hypotheses of synchronization, temporal and phase relations in brain information processing. The models being considered are those of temporal structure of spike sequences, of neural activity dynamics, and oscillatory models of attention and feature integration. (reviews of topical problems)

  7. Identification of BDNF sensitive electrophysiological markers of synaptic activity and their structural correlates in healthy subjects using a genetic approach utilizing the functional BDNF Val66Met polymorphism.

    Directory of Open Access Journals (Sweden)

    Fruzsina Soltész

    Full Text Available Increasing evidence suggests that synaptic dysfunction is a core pathophysiological hallmark of neurodegenerative disorders. Brain-derived neurotropic factor (BDNF is key synaptogenic molecule and targeting synaptic repair through modulation of BDNF signalling has been suggested as a potential drug discovery strategy. The development of such "synaptogenic" therapies depend on the availability of BDNF sensitive markers of synaptic function that could be utilized as biomarkers for examining target engagement or drug efficacy in humans. Here we have utilized the BDNF Val66Met genetic polymorphism to examine the effect of the polymorphism and genetic load (i.e. Met allele load on electrophysiological (EEG markers of synaptic activity and their structural (MRI correlates. Sixty healthy adults were prospectively recruited into the three genetic groups (Val/Val, Val/Met, Met/Met. Subjects also underwent fMRI, tDCS/TMS, and cognitive assessments as part of a larger study. Overall, some of the EEG markers of synaptic activity and brain structure measured with MRI were the most sensitive markers of the polymorphism. Met carriers showed decreased oscillatory activity and synchrony in the neural network subserving error-processing, as measured during a flanker task (ERN; and showed increased slow-wave activity during resting. There was no evidence for a Met load effect on the EEG measures and the polymorphism had no effects on MMN and P300. Met carriers also showed reduced grey matter volume in the anterior cingulate and in the (left prefrontal cortex. Furthermore, anterior cingulate grey matter volume, and oscillatory EEG power during the flanker task predicted subsequent behavioural adaptation, indicating a BDNF dependent link between brain structure, function and behaviour associated with error processing and monitoring. These findings suggest that EEG markers such as ERN and resting EEG could be used as BDNF sensitive functional markers in early

  8. dNTP deficiency induced by HU via inhibiting ribonucleotide reductase affects neural tube development

    International Nuclear Information System (INIS)

    Guan, Zhen; Wang, Xiuwei; Dong, Yanting; Xu, Lin; Zhu, Zhiqiang; Wang, Jianhua; Zhang, Ting; Niu, Bo

    2015-01-01

    Highlights: • Murine NTDs were successfully induced by means of hydroxyurea (HU). • The impairment of dNTP was induced via inhibition of ribonucleotide reductase. • dNTP deficiency induced by HU caused defective DNA synthesis and repair. • Abnormal apoptosis and proliferation induced by HU affected neural tube development. - Abstract: Exposure to environmental toxic chemicals in utero during the neural tube development period can cause developmental disorders. To evaluate the disruption of neural tube development programming, the murine neural tube defects (NTDs) model was induced by interrupting folate metabolism using methotrexate in our previous study. The present study aimed to examine the effects of dNTP deficiency induced by hydroxyurea (HU), a specific ribonucleotide reductase (RNR) inhibitor, during murine neural tube development. Pregnant C57BL/6J mice were intraperitoneally injected with various doses of HU on gestation day (GD) 7.5, and the embryos were checked on GD 11.5. RNR activity and deoxynucleoside triphosphate (dNTP) levels were measured in the optimal dose. Additionally, DNA damage was examined by comet analysis and terminal deoxynucleotidyl transferase mediated dUTP nick end-labeling (TUNEL) assay. Cellular behaviors in NTDs embryos were evaluated with phosphorylation of histone H3 (PH-3) and caspase-3 using immunohistochemistry and western blot analysis. The results showed that NTDs were observed mostly with HU treatment at an optimal dose of 225 mg/kg b/w. RNR activity was inhibited and dNTP levels were decreased in HU-treated embryos with NTDs. Additionally, increased DNA damage, decreased proliferation, and increased caspase-3 were significant in NTDs embryos compared to the controls. Results indicated that HU induced murine NTDs model by disturbing dNTP metabolism and further led to the abnormal cell balance between proliferation and apoptosis

  9. Development of Artificial Neural Network Model for Diesel Fuel Properties Prediction using Vibrational Spectroscopy.

    Science.gov (United States)

    Bolanča, Tomislav; Marinović, Slavica; Ukić, Sime; Jukić, Ante; Rukavina, Vinko

    2012-06-01

    This paper describes development of artificial neural network models which can be used to correlate and predict diesel fuel properties from several FTIR-ATR absorbances and Raman intensities as input variables. Multilayer feed forward and radial basis function neural networks have been used to rapid and simultaneous prediction of cetane number, cetane index, density, viscosity, distillation temperatures at 10% (T10), 50% (T50) and 90% (T90) recovery, contents of total aromatics and polycyclic aromatic hydrocarbons of commercial diesel fuels. In this study two-phase training procedures for multilayer feed forward networks were applied. While first phase training algorithm was constantly the back propagation one, two second phase training algorithms were varied and compared, namely: conjugate gradient and quasi Newton. In case of radial basis function network, radial layer was trained using K-means radial assignment algorithm and three different radial spread algorithms: explicit, isotropic and K-nearest neighbour. The number of hidden layer neurons and experimental data points used for the training set have been optimized for both neural networks in order to insure good predictive ability by reducing unnecessary experimental work. This work shows that developed artificial neural network models can determine main properties of diesel fuels simultaneously based on a single and fast IR or Raman measurement.

  10. Imidacloprid Exposure Suppresses Neural Crest Cells Generation during Early Chick Embryo Development.

    Science.gov (United States)

    Wang, Chao-Jie; Wang, Guang; Wang, Xiao-Yu; Liu, Meng; Chuai, Manli; Lee, Kenneth Ka Ho; He, Xiao-Song; Lu, Da-Xiang; Yang, Xuesong

    2016-06-15

    Imidacloprid is a neonicotinoid pesticide that is widely used in the control pests found on crops and fleas on pets. However, it is still unclear whether imidacloprid exposure could affect early embryo development-despite some studies having been conducted on the gametes. In this study, we demonstrated that imidacloprid exposure could lead to abnormal craniofacial osteogenesis in the developing chick embryo. Cranial neural crest cells (NCCs) are the progenitor cells of the chick cranial skull. We found that the imidacloprid exposure retards the development of gastrulating chick embryos. HNK-1, PAX7, and Ap-2α immunohistological stainings indicated that cranial NCCs generation was inhibited after imidacloprid exposure. Double immunofluorescent staining (Ap-2α and PHIS3 or PAX7 and c-Caspase3) revealed that imidacloprid exposure inhibited both NCC proliferation and apoptosis. In addition, it inhibited NCCs production by repressing Msx1 and BMP4 expression in the developing neural tube and by altering expression of EMT-related adhesion molecules (Cad6B, E-Cadherin, and N-cadherin) in the developing neural crests. We also determined that imidacloprid exposure suppressed cranial NCCs migration and their ability to differentiate. In sum, we have provided experimental evidence that imidacloprid exposure during embryogenesis disrupts NCCs development, which in turn causes defective cranial bone development.

  11. A Ca2+-based computational model for NDMA receptor-dependent synaptic plasticity at individual post-synaptic spines in the hippocampus

    Directory of Open Access Journals (Sweden)

    Owen Rackham

    2010-07-01

    Full Text Available Associative synaptic plasticity is synapse specific and requires coincident activity in presynaptic and postsynaptic neurons to activate NMDA receptors (NMDARs. The resultant Ca2+ influx is the critical trigger for the induction of synaptic plasticity. Given its centrality for the induction of synaptic plasticity, a model for NMDAR activation incorporating the timing of presynaptic glutamate release and postsynaptic depolarization by back-propagating action potentials could potentially predict the pre- and post-synaptic spike patterns required to induce synaptic plasticity. We have developed such a model by incorporating currently available data on the timecourse and amplitude of the postsynaptic membrane potential within individual spines. We couple this with data on the kinetics of synaptic NMDARs and then use the model to predict the continuous spine [Ca2+] in response to regular or irregular pre- and post-synaptic spike patterns. We then incorporate experimental data from synaptic plasticity induction protocols by regular activity patterns to couple the predicted local peak [Ca2+] to changes in synaptic strength. We find that our model accurately describes [Ca2+] in dendritic spines resulting from NMDAR activation during presynaptic and postsynaptic activity when compared to previous experimental observations. The model also replicates the experimentally determined plasticity outcome of regular and irregular spike patterns when applied to a single synapse. This model could therefore be used to predict the induction of synaptic plasticity under a variety of experimental conditions and spike patterns.

  12. Optical Calibration Process Developed for Neural-Network-Based Optical Nondestructive Evaluation Method

    Science.gov (United States)

    Decker, Arthur J.

    2004-01-01

    A completely optical calibration process has been developed at Glenn for calibrating a neural-network-based nondestructive evaluation (NDE) method. The NDE method itself detects very small changes in the characteristic patterns or vibration mode shapes of vibrating structures as discussed in many references. The mode shapes or characteristic patterns are recorded using television or electronic holography and change when a structure experiences, for example, cracking, debonds, or variations in fastener properties. An artificial neural network can be trained to be very sensitive to changes in the mode shapes, but quantifying or calibrating that sensitivity in a consistent, meaningful, and deliverable manner has been challenging. The standard calibration approach has been difficult to implement, where the response to damage of the trained neural network is compared with the responses of vibration-measurement sensors. In particular, the vibration-measurement sensors are intrusive, insufficiently sensitive, and not numerous enough. In response to these difficulties, a completely optical alternative to the standard calibration approach was proposed and tested successfully. Specifically, the vibration mode to be monitored for structural damage was intentionally contaminated with known amounts of another mode, and the response of the trained neural network was measured as a function of the peak-to-peak amplitude of the contaminating mode. The neural network calibration technique essentially uses the vibration mode shapes of the undamaged structure as standards against which the changed mode shapes are compared. The published response of the network can be made nearly independent of the contaminating mode, if enough vibration modes are used to train the net. The sensitivity of the neural network can be adjusted for the environment in which the test is to be conducted. The response of a neural network trained with measured vibration patterns for use on a vibration isolation

  13. Development and Evaluation of Micro-Electrocorticography Arrays for Neural Interfacing Applications

    Science.gov (United States)

    Schendel, Amelia Ann

    Neural interfaces have great promise for both electrophysiological research and therapeutic applications. Whether for the study of neural circuitry or for neural prosthetic or other therapeutic applications, micro-electrocorticography (micro-ECoG) arrays have proven extremely useful as neural interfacing devices. These devices strike a balance between invasiveness and signal resolution, an important step towards eventual human application. The objective of this research was to make design improvements to micro-ECoG devices to enhance both biocompatibility and device functionality. To best evaluate the effectiveness of these improvements, a cranial window imaging method for in vivo monitoring of the longitudinal tissue response post device implant was developed. Employment of this method provided valuable insight into the way tissue grows around micro-ECoG arrays after epidural implantation, spurring a study of the effects of substrate geometry on the meningeal tissue response. The results of the substrate footprint comparison suggest that a more open substrate geometry provides an easy path for the tissue to grow around to the top side of the device, whereas a solid device substrate encourages the tissue to thicken beneath the device, between the electrode sites and the brain. The formation of thick scar tissue between the recording electrode sites and the neural tissue is disadvantageous for long-term recorded signal quality, and thus future micro-ECoG device designs should incorporate open-architecture substrates for enhanced longitudinal in vivo function. In addition to investigating improvements for long-term device reliability, it was also desired to enhance the functionality of micro-ECoG devices for neural electrophysiology research applications. To achieve this goal, a completely transparent graphene-based device was fabricated for use with the cranial window imaging method and optogenetic techniques. The use of graphene as the conductive material provided

  14. Two Classes of Secreted Synaptic Organizers in the Central Nervous System.

    Science.gov (United States)

    Yuzaki, Michisuke

    2018-02-10

    Research in the last two decades has identified many synaptic organizers in the central nervous system that directly regulate the assembly of pre- and/or postsynaptic molecules, such as synaptic vesicles, active zone proteins, and neurotransmitter receptors. They are classified into secreted factors and cell adhesion molecules, such as neurexins and neuroligins. Certain secreted factors are termed extracellular scaffolding proteins (ESPs) because they are components of the synaptic extracellular matrix and serve as a scaffold at the synaptic cleft. These include Lgi1, Cbln1, neuronal pentraxins, Hevin, thrombospondins, and glypicans. Diffusible secreted factors, such as Wnts, fibroblast growth factors, and semaphorins, tend to act from a distance. In contrast, ESPs remain at the synaptic cleft and often help synaptic adhesion and/or accumulation of postsynaptic receptors. Many fundamental questions remain about when, how, and why various synaptic organizers establish and modify the vast numbers of connections during development and throughout life.

  15. Self-organized critical neural networks

    International Nuclear Information System (INIS)

    Bornholdt, Stefan; Roehl, Torsten

    2003-01-01

    A mechanism for self-organization of the degree of connectivity in model neural networks is studied. Network connectivity is regulated locally on the basis of an order parameter of the global dynamics, which is estimated from an observable at the single synapse level. This principle is studied in a two-dimensional neural network with randomly wired asymmetric weights. In this class of networks, network connectivity is closely related to a phase transition between ordered and disordered dynamics. A slow topology change is imposed on the network through a local rewiring rule motivated by activity-dependent synaptic development: Neighbor neurons whose activity is correlated, on average develop a new connection while uncorrelated neighbors tend to disconnect. As a result, robust self-organization of the network towards the order disorder transition occurs. Convergence is independent of initial conditions, robust against thermal noise, and does not require fine tuning of parameters

  16. Operant conditioning of synaptic and spiking activity patterns in single hippocampal neurons.

    Science.gov (United States)

    Ishikawa, Daisuke; Matsumoto, Nobuyoshi; Sakaguchi, Tetsuya; Matsuki, Norio; Ikegaya, Yuji

    2014-04-02

    Learning is a process of plastic adaptation through which a neural circuit generates a more preferable outcome; however, at a microscopic level, little is known about how synaptic activity is patterned into a desired configuration. Here, we report that animals can generate a specific form of synaptic activity in a given neuron in the hippocampus. In awake, head-restricted mice, we applied electrical stimulation to the lateral hypothalamus, a reward-associated brain region, when whole-cell patch-clamped CA1 neurons exhibited spontaneous synaptic activity that met preset criteria. Within 15 min, the mice learned to generate frequently the excitatory synaptic input pattern that satisfied the criteria. This reinforcement learning of synaptic activity was not observed for inhibitory input patterns. When a burst unit activity pattern was conditioned in paired and nonpaired paradigms, the frequency of burst-spiking events increased and decreased, respectively. The burst reinforcement occurred in the conditioned neuron but not in other adjacent neurons; however, ripple field oscillations were concomitantly reinforced. Neural conditioning depended on activation of NMDA receptors and dopamine D1 receptors. Acutely stressed mice and depression model mice that were subjected to forced swimming failed to exhibit the neural conditioning. This learning deficit was rescued by repetitive treatment with fluoxetine, an antidepressant. Therefore, internally motivated animals are capable of routing an ongoing action potential series into a specific neural pathway of the hippocampal network.

  17. Deletion of OTX2 in neural ectoderm delays anterior pituitary development

    Science.gov (United States)

    Mortensen, Amanda H.; Schade, Vanessa; Lamonerie, Thomas; Camper, Sally A.

    2015-01-01

    OTX2 is a homeodomain transcription factor that is necessary for normal head development in mouse and man. Heterozygosity for loss-of-function alleles causes an incompletely penetrant, haploinsufficiency disorder. Affected individuals exhibit a spectrum of features that range from developmental defects in eye and/or pituitary development to acephaly. To investigate the mechanism underlying the pituitary defects, we used different cre lines to inactivate Otx2 in early head development and in the prospective anterior and posterior lobes. Mice homozygous for Otx2 deficiency in early head development and pituitary oral ectoderm exhibit craniofacial defects and pituitary gland dysmorphology, but normal pituitary cell specification. The morphological defects mimic those observed in humans and mice with OTX2 heterozygous mutations. Mice homozygous for Otx2 deficiency in the pituitary neural ectoderm exhibited altered patterning of gene expression and ablation of FGF signaling. The posterior pituitary lobe and stalk, which normally arise from neural ectoderm, were extremely hypoplastic. Otx2 expression was intact in Rathke's pouch, the precursor to the anterior lobe, but the anterior lobe was hypoplastic. The lack of FGF signaling from the neural ectoderm was sufficient to impair anterior lobe growth, but not the differentiation of hormone-producing cells. This study demonstrates that Otx2 expression in the neural ectoderm is important intrinsically for the development of the posterior lobe and pituitary stalk, and it has significant extrinsic effects on anterior pituitary growth. Otx2 expression early in head development is important for establishing normal craniofacial features including development of the brain, eyes and pituitary gland. PMID:25315894

  18. Reduced Synaptic Vesicle Recycling during Hypoxia in Cultured Cortical Neurons

    OpenAIRE

    Fedorovich, Sergei; Hofmeijer, Jeannette; van Putten, Michel Johannes Antonius Maria; le Feber, Jakob

    2017-01-01

    Improvement of neuronal recovery in the ischemic penumbra, an area around the core of a brain infarct with some remaining perfusion, has a large potential for the development of therapy against acute ischemic stroke. However, mechanisms that lead to either recovery or secondary damage in the penumbra largely remain unclear. Recent studies in cultured networks of cortical neurons showed that failure of synaptic transmission (referred to as synaptic failure) is a critical factor in the penumbra...

  19. Agrin and synaptic laminin are required to maintain adult neuromuscular junctions.

    Directory of Open Access Journals (Sweden)

    Melanie A Samuel

    Full Text Available As synapses form and mature the synaptic partners produce organizing molecules that regulate each other's differentiation and ensure precise apposition of pre- and post-synaptic specializations. At the skeletal neuromuscular junction (NMJ, these molecules include agrin, a nerve-derived organizer of postsynaptic differentiation, and synaptic laminins, muscle-derived organizers of presynaptic differentiation. Both become concentrated in the synaptic cleft as the NMJ develops and are retained in adulthood. Here, we used mutant mice to ask whether these organizers are also required for synaptic maintenance. Deletion of agrin from a subset of adult motor neurons resulted in the loss of acetylcholine receptors and other components of the postsynaptic apparatus and synaptic cleft. Nerve terminals also atrophied and eventually withdrew from muscle fibers. On the other hand, mice lacking the presynaptic organizer laminin-α4 retained most of the synaptic cleft components but exhibited synaptic alterations reminiscent of those observed in aged animals. Although we detected no marked decrease in laminin or agrin levels at aged NMJs, we observed alterations in the distribution and organization of these synaptic cleft components suggesting that such changes could contribute to age-related synaptic disassembly. Together, these results demonstrate that pre- and post-synaptic organizers actively function to maintain the structure and function of adult NMJs.

  20. Differentiation-Dependent Motility-Responses of Developing Neural Progenitors to Optogenetic Stimulation

    Directory of Open Access Journals (Sweden)

    Tímea Köhidi

    2017-12-01

    Full Text Available During neural tissue genesis, neural stem/progenitor cells are exposed to bioelectric stimuli well before synaptogenesis and neural circuit formation. Fluctuations in the electrochemical potential in the vicinity of developing cells influence the genesis, migration and maturation of neuronal precursors. The complexity of the in vivo environment and the coexistence of various progenitor populations hinder the understanding of the significance of ionic/bioelectric stimuli in the early phases of neuronal differentiation. Using optogenetic stimulation, we investigated the in vitro motility responses of radial glia-like neural stem/progenitor populations to ionic stimuli. Radial glia-like neural stem cells were isolated from CAGloxpStoploxpChR2(H134-eYFP transgenic mouse embryos. After transfection with Cre-recombinase, ChR2(channelrhodopsin-2-expressing and non-expressing cells were separated by eYFP fluorescence. Expression of light-gated ion channels were checked by patch clamp and fluorescence intensity assays. Neurogenesis by ChR2-expressing and non-expressing cells was induced by withdrawal of EGF from the medium. Cells in different (stem cell, migrating progenitor and maturing precursor stages of development were illuminated with laser light (λ = 488 nm; 1.3 mW/mm2; 300 ms in every 5 min for 12 h. The displacement of the cells was analyzed on images taken at the end of each light pulse. Results demonstrated that the migratory activity decreased with the advancement of neuronal differentiation regardless of stimulation. Light-sensitive cells, however, responded on a differentiation-dependent way. In non-differentiated ChR2-expressing stem cell populations, the motility did not change significantly in response to light-stimulation. The displacement activity of migrating progenitors was enhanced, while the motility of differentiating neuronal precursors was markedly reduced by illumination.

  1. DEVELOPMENT OF A COMPUTER SYSTEM FOR IDENTITY AUTHENTICATION USING ARTIFICIAL NEURAL NETWORKS

    Directory of Open Access Journals (Sweden)

    Timur Kartbayev

    2017-03-01

    Full Text Available The aim of the study is to increase the effectiveness of automated face recognition to authenticate identity, considering features of change of the face parameters over time. The improvement of the recognition accuracy, as well as consideration of the features of temporal changes in a human face can be based on the methodology of artificial neural networks. Hybrid neural networks, combining the advantages of classical neural networks and fuzzy logic systems, allow using the network learnability along with the explanation of the findings. The structural scheme of intelligent system for identification based on artificial neural networks is proposed in this work. It realizes the principles of digital information processing and identity recognition taking into account the forecast of key characteristics’ changes over time (e.g., due to aging. The structural scheme has a three-tier architecture and implements preliminary processing, recognition and identification of images obtained as a result of monitoring. On the basis of expert knowledge, the fuzzy base of products is designed. It allows assessing possible changes in key characteristics, used to authenticate identity based on the image. To take this possibility into consideration, a neuro-fuzzy network of ANFIS type was used, which implements the algorithm of Tagaki-Sugeno. The conducted experiments showed high efficiency of the developed neural network and a low value of learning errors, which allows recommending this approach for practical implementation. Application of the developed system of fuzzy production rules that allow predicting changes in individuals over time, will improve the recognition accuracy, reduce the number of authentication failures and improve the efficiency of information processing and decision-making in applications, such as authentication of bank customers, users of mobile applications, or in video monitoring systems of sensitive sites.

  2. Male-specific alteration in excitatory post-synaptic development and social interaction in pre-natal valproic acid exposure model of autism spectrum disorder.

    Science.gov (United States)

    Kim, Ki Chan; Kim, Pitna; Go, Hyo Sang; Choi, Chang Soon; Park, Jin Hee; Kim, Hee Jin; Jeon, Se Jin; Dela Pena, Ike Campomayor; Han, Seol-Heui; Cheong, Jae Hoon; Ryu, Jong Hoon; Shin, Chan Young

    2013-03-01

    Autism spectrum disorder (ASD) is a pervasive developmental disorder characterized by three main behavioral symptoms including social deficits, impaired communication, and stereotyped and repetitive behaviors. ASD prevalence shows gender bias to male. Prenatal exposure to valproic acid (VPA), a drug used in epilepsy and bipolar disorder, induces autistic symptoms in both human and rodents. As we reported previously, prenatally VPA-exposed animals at E12 showed impairment in social behavior without any overt reproductive toxicity. Social interactions were not significantly different between male and female rats in control condition. However, VPA-exposed male offspring showed significantly impaired social interaction while female offspring showed only marginal deficits in social interaction. Similar male inclination was observed in hyperactivity behavior induced by VPA. In addition to the ASD-like behavioral phenotype, prenatally VPA-exposed rat offspring shows crooked tail phenotype, which was not different between male and female groups. Both male and female rat showed reduced GABAergic neuronal marker GAD and increased glutamatergic neuronal marker vGluT1 expression. Interestingly, despite of the similar increased expression of vGluT1, post-synaptic marker proteins such as PSD-95 and α-CAMKII expression was significantly elevated only in male offspring. Electron microscopy showed increased number of post-synapse in male but not in female at 4 weeks of age. These results might suggest that the altered glutamatergic neuronal differentiation leads to deranged post-synaptic maturation only in male offspring prenatally exposed to VPA. Consistent with the increased post-synaptic compartment, VPA-exposed male rats showed higher sensitivity to electric shock than VPA-exposed female rats. These results suggest that prenatally VPA-exposed rats show the male preponderance of ASD-like behaviors including defective social interaction similar to human autistic patients, which

  3. Histone deacetylase 1 and 2 are essential for murine neural crest proliferation, pharyngeal arch development, and craniofacial morphogenesis.

    Science.gov (United States)

    Milstone, Zachary J; Lawson, Grace; Trivedi, Chinmay M

    2017-12-01

    Craniofacial anomalies involve defective pharyngeal arch development and neural crest function. Copy number variation at 1p35, containing histone deacetylase 1 (Hdac1), or 6q21-22, containing Hdac2, are implicated in patients with craniofacial defects, suggesting an important role in guiding neural crest development. However, the roles of Hdac1 and Hdac2 within neural crest cells remain unknown. The neural crest and its derivatives express both Hdac1 and Hdac2 during early murine development. Ablation of Hdac1 and Hdac2 within murine neural crest progenitor cells cause severe hemorrhage, atrophic pharyngeal arches, defective head morphogenesis, and complete embryonic lethality. Embryos lacking Hdac1 and Hdac2 in the neural crest exhibit decreased proliferation and increased apoptosis in both the neural tube and the first pharyngeal arch. Mechanistically, loss of Hdac1 and Hdac2 upregulates cyclin-dependent kinase inhibitors Cdkn1a, Cdkn1b, Cdkn1c, Cdkn2b, Cdkn2c, and Tp53 within the first pharyngeal arch. Our results show that Hdac1 and Hdac2 function redundantly within the neural crest to regulate proliferation and the development of the pharyngeal arches by means of repression of cyclin-dependent kinase inhibitors. Developmental Dynamics 246:1015-1026, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  4. The murine homeobox gene Msx-3 shows highly restricted expression in the developing neural tube.

    Science.gov (United States)

    Shimeld, S M; McKay, I J; Sharpe, P T

    1996-04-01

    The mouse homeobox-genes Msx-1 and Msx-2 are expressed in several areas of the developing embryo, including the neural tube, neural crest, facial processes and limb buds. Here we report the characterisation of a third mouse Msx gene, which we designate Msx-3. The embryonic expression of Msx-3 was found to differ from that of Msx-1 and -2 in that it was confined to the dorsal neural tube. In embryos with 5-8 somites a segmental pattern of expression was observed in the hindbrain, with rhombomeres 3 and 5 lacking Msx-3 while other rhombomeres expressed Msx-3. This pattern was transient, however, such that in embryos with 18 or more somites expression was continuous throughout the dorsal hindbrain and anterior dorsal spinal cord. Differentiation of dorsal cell types in the neural tube can be induced by addition of members of the Tgf-beta family. Additionally, Msx-1 and -2 have been shown to be activated by addition of the Tgf-beta family member Bmp-4. To determine if Bmp-4 could activate Msx-3, we incubated embryonic hindbrain explants with exogenous Bmp-4. The dorsal expression of Msx-3 was seen to expand into more ventral regions of the neurectoderm in Bmp-4-treated cultures, implying that Bmp-4 may be able to mimic an in vivo signal that induces Msx-3.

  5. Development of distributed topographical forecasting model for wind resource assessment using artificial neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Narayana, P.B. [Green Life Energy Solutions LLP, Secunderabad (India); Rao, S.S. [National Institute of Technology. Dept. of Mechanical Engineering, Warangal (India); Reddy, K.H. [JNT Univ.. Dept. of Mechanical Engineering, Anantapur (India)

    2012-07-01

    Economics of wind power projects largely depend on the availability of wind power density. Wind resource assessment is a study estimating wind speeds and wind power densities in the region under consideration. The accuracy and reliability of data sets comprising of wind speeds and wind power densities at different heights per topographic region characterized by elevation or mean sea level, is important for wind power projects. Indian Wind Resource Assessment program conducted in 80's consisted of wind data measured by monitoring stations at different topographies in order to measure wind power density values at 25 and 50 meters above the ground level. In this paper, an attempt has been made to assess wind resource at a given location using artificial neural networks. Existing wind resource data has been used to train the neural networks. Location topography (characterized by longitude, latitude and mean sea level), air density, mean annual wind speed (MAWS) are used as inputs to the neural network. Mean annual wind power density (MAWPD) in watt/m{sup 2} is predicted for a new topographic location. Simple back propagation based neural network has been found to be sufficient for predicting these values with suitable accuracy. This model is closely linked to the problem of wind energy forecasting considering the variations of specific atmospheric variables with time horizons. This model will help the wind farm developers to have an initial estimation of the wind energy potential at a particular topography. (Author)

  6. Developing and using expert systems and neural networks in medicine: a review on benefits and challenges.

    Science.gov (United States)

    Sheikhtaheri, Abbas; Sadoughi, Farahnaz; Hashemi Dehaghi, Zahra

    2014-09-01

    Complicacy of clinical decisions justifies utilization of information systems such as artificial intelligence (e.g. expert systems and neural networks) to achieve better decisions, however, application of these systems in the medical domain faces some challenges. We aimed at to review the applications of these systems in the medical domain and discuss about such challenges. Following a brief introduction of expert systems and neural networks by representing few examples, the challenges of these systems in the medical domain are discussed. We found that the applications of expert systems and artificial neural networks have been increased in the medical domain. These systems have shown many advantages such as utilization of experts' knowledge, gaining rare knowledge, more time for assessment of the decision, more consistent decisions, and shorter decision-making process. In spite of all these advantages, there are challenges ahead of developing and using such systems including maintenance, required experts, inputting patients' data into the system, problems for knowledge acquisition, problems in modeling medical knowledge, evaluation and validation of system performance, wrong recommendations and responsibility, limited domains of such systems and necessity of integrating such systems into the routine work flows. We concluded that expert systems and neural networks can be successfully used in medicine; however, there are many concerns and questions to be answered through future studies and discussions.

  7. Precise synaptic efficacy alignment suggests potentiation dominated learning

    Directory of Open Access Journals (Sweden)

    Christoph eHartmann

    2016-01-01

    Full Text Available Recent evidence suggests that parallel synapses from the same axonal branch onto the same dendritic branch have almost identical strength. It has been proposed that this alignment is only possible through learning rules that integrate activity over long time spans. However, learning mechanisms such as spike-timing-dependent plasticity (STDP are commonly assumed to be temporally local. Here, we propose that the combination of temporally local STDP and a multiplicative synaptic normalization mechanism is sufficient to explain the alignment of parallel synapses.To address this issue, we introduce three increasingly complex models: First, we model the idealized interaction of STDP and synaptic normalization in a single neuron as a simple stochastic process and derive analytically that the alignment effect can be described by a so-called Kesten process. From this we can derive that synaptic efficacy alignment requires potentiation-dominated learning regimes. We verify these conditions in a single-neuron model with independent spiking activities but more realistic synapses. As expected, we only observe synaptic efficacy alignment for long-term potentiation-biased STDP. Finally, we explore how well the findings transfer to recurrent neural networks where the learning mechanisms interact with the correlated activity of the network. We find that due to the self-reinforcing correlations in recurrent circuits under STDP, alignment occurs for both long-term potentiation- and depression-biased STDP, because the learning will be potentiation dominated in both cases due to the potentiating events induced by correlated activity. This is in line with recent results demonstrating a dominance of potentiation over depression during waking and normalization during sleep. This leads us to predict that individual spine pairs will be more similar in the morning than they are after sleep depriviation.In conclusion, we show that synaptic normalization in conjunction with

  8. Synaptic consolidation across multiple timescales

    Directory of Open Access Journals (Sweden)

    Lorric Ziegler

    2014-03-01

    Full Text Available The brain is bombarded with a continuous stream of sensory events, but retains only a small subset in memory. The selectivity of memory formation prevents our memory from being overloaded with irrelevant items that would rapidly bring the brain to its storage limit; moreover, selectivity also prevents overwriting previously formed memories with new ones. Memory formation in the hippocampus, as well as in other brain regions, is thought to be linked to changes in the synaptic connections between neurons. In this view, sensory events imprint traces at the level of synapses that reflect potential memory items. The question of memory selectivity can therefore be reformulated as follows: what are the reasons and conditions that some synaptic traces fade away whereas others are consolidated and persist? Experimentally, changes in synaptic strength induced by 'Hebbian' protocols fade away over a few hours (early long-term potentiation or e-LTP, unless these changes are consolidated. The experiments and conceptual theory of synaptic tagging and capture (STC provide a mechanistic explanation for the processes involved in consolidation. This theory suggests that the initial trace of synaptic plasticity sets a tag at the synapse, which then serves as a marker for potential consolidation of the changes in synaptic efficacy. The actual consolidation processes, transforming e-LTP into late LTP (l-LTP, require the capture of plasticity-related proteins (PRP. We translate the above conceptual model into a compact computational model that accounts for a wealth of in vitro data including experiments on cross-tagging, tag-resetting and depotentiation. A central ingredient is that synaptic traces are described with several variables that evolve on different time scales. Consolidation requires the transmission of information from a 'fast' synaptic trace to a 'slow' one through a 'write' process, including the formation of tags and the production of PRP for the

  9. Ultrafast Synaptic Events in a Chalcogenide Memristor

    Science.gov (United States)

    Li, Yi; Zhong, Yingpeng; Xu, Lei; Zhang, Jinjian; Xu, Xiaohua; Sun, Huajun; Miao, Xiangshui

    2013-04-01

    Compact and power-efficient plastic electronic synapses are of fundamental importance to overcoming the bottlenecks of developing a neuromorphic chip. Memristor is a strong contender among the various electronic synapses in existence today. However, the speeds of synaptic events are relatively slow in most attempts at emulating synapses due to the material-related mechanism. Here we revealed the intrinsic memristance of stoichiometric crystalline Ge2Sb2Te5 that originates from the charge trapping and releasing by the defects. The device resistance states, representing synaptic weights, were precisely modulated by 30 ns potentiating/depressing electrical pulses. We demonstrated four spike-timing-dependent plasticity (STDP) forms by applying programmed pre- and postsynaptic spiking pulse pairs in different time windows ranging from 50 ms down to 500 ns, the latter of which is 105 times faster than the speed of STDP in human brain. This study provides new opportunities for building ultrafast neuromorphic computing systems and surpassing Von Neumann architecture.

  10. The development of neural stimulators: a review of preclinical safety and efficacy studies.

    Science.gov (United States)

    Shepherd, Robert K; Villalobos, Joel; Burns, Owen; Nayagam, David

    2018-05-14

    Given the rapid expansion of the field of neural stimulation and the rigorous regulatory approval requirements required before these devices can be applied clinically, it is important that there is clarity around conducting preclinical safety and efficacy studies required for the development of this technology. The present review examines basic design principles associated with the development of a safe neural stimulator and describes the suite of preclinical safety studies that need to be considered when taking a device to clinical trial. Neural stimulators are active implantable devices that provide therapeutic intervention, sensory feedback or improved motor control via electrical stimulation of neural or neuro-muscular tissue in response to trauma or disease. Because of their complexity, regulatory bodies classify these devices in the highest risk category (Class III), and they are therefore required to go through a rigorous regulatory approval process before progressing to market. The successful development of these devices is achieved through close collaboration across disciplines including engineers, scientists and a surgical/clinical team, and the adherence to clear design principles. Preclinical studies form one of several key components in the development pathway from concept to product release of neural stimulators. Importantly, these studies provide iterative feedback in order to optimise the final design of the device. Key components of any preclinical evaluation include: in vitro studies that are focussed on device reliability and include accelerated testing under highly controlled environments; in vivo studies using animal models of the disease or injury in order to assess safety and, given an appropriate animal model, the efficacy of the technology under both passive and electrically active conditions; and human cadaver and ex vivo studies designed to ensure the device's form factor conforms to human anatomy, to optimise the surgical approach and to

  11. Optimal autaptic and synaptic delays enhanced synchronization transitions induced by each other in Newman–Watts neuronal networks

    International Nuclear Information System (INIS)

    Wang, Baoying; Gong, Yubing; Xie, Huijuan; Wang, Qi

    2016-01-01

    Highlights: • Optimal autaptic delay enhanced synchronization transitions induced by synaptic delay in neuronal networks. • Optimal synaptic delay enhanced synchronization transitions induced by autaptic delay. • Optimal coupling strength enhanced synchronization transitions induced by autaptic or synaptic delay. - Abstract: In this paper, we numerically study the effect of electrical autaptic and synaptic delays on synchronization transitions induced by each other in Newman–Watts Hodgkin–Huxley neuronal networks. It is found that the synchronization transitions induced by synaptic delay vary with varying autaptic delay and become strongest when autaptic delay is optimal. Similarly, the synchronization transitions induced by autaptic delay vary with varying synaptic delay and become strongest at optimal synaptic delay. Also, there is optimal coupling strength by which the synchronization transitions induced by either synaptic or autaptic delay become strongest. These results show that electrical autaptic and synaptic delays can enhance synchronization transitions induced by each other in the neuronal networks. This implies that electrical autaptic and synaptic delays can cooperate with each other and more efficiently regulate the synchrony state of the neuronal networks. These findings could find potential implications for the information transmission in neural systems.

  12. Maternal Diabetes Alters Expression of MicroRNAs that Regulate Genes Critical for Neural Tube Development

    Directory of Open Access Journals (Sweden)

    Seshadri Ramya

    2017-07-01

    Full Text Available Maternal diabetes is known to cause neural tube defects (NTDs in embryos and neuropsychological deficits in infants. Several metabolic pathways and a plethora of genes have been identified to be deregulated in developing brain of embryos by maternal diabetes, although the exact mechanism remains unknown. Recently, miRNAs have been shown to regulate genes involved in brain development and maturation. Therefore, we hypothesized that maternal diabetes alters the expression of miRNAs that regulate genes involved in biological pathways critical for neural tube development and closure during embryogenesis. To address this, high throughput miRNA expression profiling in neural stem cells (NSCs isolated from the forebrain of embryos from normal or streptozotocin-induced diabetic pregnancy was carried out. It is known that maternal diabetes results in fetal hypoglycemia/hyperglycemia or hypoxia. Hence, NSCs from embryos of control pregnant mice were exposed to low or high glucose or hypoxia in vitro. miRNA pathway analysis revealed distinct deregulation of several biological pathways, including axon guidance pathway, which are critical for brain development in NSCs exposed to different treatments. Among the differentially expressed miRNAs, the miRNA-30 family members which are predicted to target genes involved in brain development was upregulated in NSCs from embryos of diabetic pregnancy when compared to control. miRNA-30b was found to be upregulated while its target gene Sirtuin 1 (Sirt1, as revealed by luciferase assay, was down regulated in NSCs from embryos of diabetic pregnancy. Further, overexpression of miRNA-30b in NSCs, resulted in decreased expression of Sirt1 protein, and altered the neuron/glia ratio. On the other hand, siRNA mediated knockdown of Sirt1 in NSCs promoted astrogenesis, indicating that miRNA-30b alters lineage specification via Sirt1. Overall, these results suggest that maternal diabetes alters the genes involved in neural tube

  13. Neural network-based survey analysis of risk management practices in new product development

    DEFF Research Database (Denmark)

    Kampianakis, Andreas N.; Oehmen, Josef

    2017-01-01

    The current study investigates the applicability of Artificial Neural Networks (ANNs) to analyse survey data on the effectiveness of risk management practices in product development (PD) projects, and its ability to forecast project outcomes. Moreover, this study presents the relations between risk...... Neural Networks. Dataset used is a filtered survey of 291 product development programs. Answers of this survey are used as training input and target output, in pattern recognition two-layer feed forward networks, using various transfer functions. Using this method, relations among 6 project practices...... and 13 outcome metrics were revealed. Results of this analysis are compared with existent results made through statistical analysis in prior work of one of the authors. Future investigation is needed in order to tackle the lack of data and create an easy to use platform for industrial use....

  14. Development of a neoclassical transport database by neural network fitting in LHD

    International Nuclear Information System (INIS)

    Wakasa, Arimitsu; Oikawa, Shun-ichi; Murakami, Sadayoshi; Yamada, Hiroshi; Yokoyama, Masayuki; Watanabe, Kiyomasa; Maassberg, Hening; Beidler, Craig D.

    2004-01-01

    A database of neoclassical transport coefficients for the Large Helical Device is developed using normalized mono-energetic diffusion coefficients evaluated by Monte Carlo simulation code; DCOM. A neural network fitting method is applied to take energy convolutions with the given distribution function, e.g. Maxwellian. The database gives the diffusion coefficients as a function of the collision frequency, the radial electric field and the minor radius position. (author)

  15. The role of BDNF in depression on the basis of its location in the neural circuitry

    Institute of Scientific and Technical Information of China (English)

    Hui YU; Zhe-yu CHEN

    2011-01-01

    Depression is one of the most prevalent and life-threatening forms of mental illnesses and the neural circuitry underlying depression remains incompletely understood. Most attention in the field has focused on hippocampal and frontal cortical regions for their roles in depression and antidepressant action. While these regions no doubt play important roles in the mental illness, there is compelling evi-dence that other brain regions are also involved. Brain-derived neurotrophic factor (BDNF) is broadly expressed in the developing and adult mammalian brain and has been implicated in development, neural regeneration, synaptic transmission, synaptic plasticity and neurogenesis. Recently BDNF has been shown to play an important role in the pathophysiology of depression, however there are con-troversial reports about the effects of BDNF on depression. Here, we present an overview of the current knowledge concerning BDNF actions and associated intracellular signaling in hippocampus, prefrontal cortex, nucleus accumbens (NAc) and amygdala as their rela-tion to depression.

  16. Characterization of Pax3 and Sox10 transgenic Xenopus laevis embryos as tools to study neural crest development.

    Science.gov (United States)

    Alkobtawi, Mansour; Ray, Heather; Barriga, Elias H; Moreno, Mauricio; Kerney, Ryan; Monsoro-Burq, Anne-Helene; Saint-Jeannet, Jean-Pierre; Mayor, Roberto

    2018-03-06

    The neural crest is a multipotent population of cells that originates a variety of cell types. Many animal models are used to study neural crest induction, migration and differentiation, with amphibians and birds being the most widely used systems. A major technological advance to study neural crest development in mouse, chick and zebrafish has been the generation of transgenic animals in which neural crest specific enhancers/promoters drive the expression of either fluorescent proteins for use as lineage tracers, or modified genes for use in functional studies. Unfortunately, no such transgenic animals currently exist for the amphibians Xenopus laevis and tropicalis, key model systems for studying neural crest development. Here we describe the generation and characterization of two transgenic Xenopus laevis lines, Pax3-GFP and Sox10-GFP, in which GFP is expressed in the pre-migratory and migratory neural crest, respectively. We show that Pax3-GFP could be a powerful tool to study neural crest induction, whereas Sox10-GFP could be used in the study of neural crest migration in living embryos. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

  17. Goal-seeking neural net for recall and recognition

    Science.gov (United States)

    Omidvar, Omid M.

    1990-07-01

    Neural networks have been used to mimic cognitive processes which take place in animal brains. The learning capability inherent in neural networks makes them suitable candidates for adaptive tasks such as recall and recognition. The synaptic reinforcements create a proper condition for adaptation, which results in memorization, formation of perception, and higher order information processing activities. In this research a model of a goal seeking neural network is studied and the operation of the network with regard to recall and recognition is analyzed. In these analyses recall is defined as retrieval of stored information where little or no matching is involved. On the other hand recognition is recall with matching; therefore it involves memorizing a piece of information with complete presentation. This research takes the generalized view of reinforcement in which all the signals are potential reinforcers. The neuronal response is considered to be the source of the reinforcement. This local approach to adaptation leads to the goal seeking nature of the neurons as network components. In the proposed model all the synaptic strengths are reinforced in parallel while the reinforcement among the layers is done in a distributed fashion and pipeline mode from the last layer inward. A model of complex neuron with varying threshold is developed to account for inhibitory and excitatory behavior of real neuron. A goal seeking model of a neural network is presented. This network is utilized to perform recall and recognition tasks. The performance of the model with regard to the assigned tasks is presented.

  18. Is a 4-bit synaptic weight resolution enough? - constraints on enabling spike-timing dependent plasticity in neuromorphic hardware.

    Science.gov (United States)

    Pfeil, Thomas; Potjans, Tobias C; Schrader, Sven; Potjans, Wiebke; Schemmel, Johannes; Diesmann, Markus; Meier, Karlheinz

    2012-01-01

    Large-scale neuromorphic hardware systems typically bear the trade-off between detail level and required chip resources. Especially when implementing spike-timing dependent plasticity, reduction in resources leads to limitations as compared to floating point precision. By design, a natural modification that saves resources would be reducing synaptic weight resolution. In this study, we give an estimate for the impact of synaptic weight discretization on different levels, ranging from random walks of individual weights to computer simulations of spiking neural networks. The FACETS wafer-scale hardware system offers a 4-bit resolution of synaptic weights, which is shown to be sufficient within the scope of our network benchmark. Our findings indicate that increasing the resolution may not even be useful in light of further restrictions of customized mixed-signal synapses. In addition, variations due to production imperfections are investigated and shown to be uncritical in the context of the presented study. Our results represent a general framework for setting up and configuring hardware-constrained synapses. We suggest how weight discretization could be considered for other backends dedicated to large-scale simulations. Thus, our proposition of a good hardware verification practice may rise synergy effects between hardware developers and neuroscientists.

  19. Growing adaptive machines combining development and learning in artificial neural networks

    CERN Document Server

    Bredeche, Nicolas; Doursat, René

    2014-01-01

    The pursuit of artificial intelligence has been a highly active domain of research for decades, yielding exciting scientific insights and productive new technologies. In terms of generating intelligence, however, this pursuit has yielded only limited success. This book explores the hypothesis that adaptive growth is a means of moving forward. By emulating the biological process of development, we can incorporate desirable characteristics of natural neural systems into engineered designs, and thus move closer towards the creation of brain-like systems. The particular focus is on how to design artificial neural networks for engineering tasks. The book consists of contributions from 18 researchers, ranging from detailed reviews of recent domains by senior scientists, to exciting new contributions representing the state of the art in machine learning research. The book begins with broad overviews of artificial neurogenesis and bio-inspired machine learning, suitable both as an introduction to the domains and as a...

  20. Application of artificial neural networks for response surface modelling in HPLC method development

    Directory of Open Access Journals (Sweden)

    Mohamed A. Korany

    2012-01-01

    Full Text Available This paper discusses the usefulness of artificial neural networks (ANNs for response surface modelling in HPLC method development. In this study, the combined effect of pH and mobile phase composition on the reversed-phase liquid chromatographic behaviour of a mixture of salbutamol (SAL and guaiphenesin (GUA, combination I, and a mixture of ascorbic acid (ASC, paracetamol (PAR and guaiphenesin (GUA, combination II, was investigated. The results were compared with those produced using multiple regression (REG analysis. To examine the respective predictive power of the regression model and the neural network model, experimental and predicted response factor values, mean of squares error (MSE, average error percentage (Er%, and coefficients of correlation (r were compared. It was clear that the best networks were able to predict the experimental responses more accurately than the multiple regression analysis.

  1. Cut loose and run: The complex role of ADAM proteases during neural crest cell development.

    Science.gov (United States)

    Alfandari, Dominique; Taneyhill, Lisa A

    2018-02-24

    ADAM metalloproteases have been shown to play critical roles during development. In this review, we will describe functional evidence that implicates ADAM proteins during the genesis, migration and differentiation of neural crest cells. We will restrict our analysis to the transmembrane ADAMs as other reviews have addressed the role of extracellular metalloproteases (Christian et al. [2013] Critical Reviews in Biochemistry and Molecular Biology 48:544-560). This review will describe advances that have been obtained mainly through the use of two vertebrate model systems, the frog, and avian embryos. The role of the principal substrates of ADAMs, the cadherins, has been extensively described in other reviews, most recently in (Cousin [1997] Mechanisms of Development 148:79-88; Taneyhill and Schiffmacher [2017] Genesis, 55). The function of ADAMs in the migration of other cell types, including the immune system, wound healing and cancer has been described previously in (Dreymueller et al. [2017] Mediators of Inflammation 2017: 9621724). Our goal is to illustrate both the importance of ADAMs in controlling neural crest behavior and how neural crest cells have helped us understand the molecular interactions, substrates, and functions of ADAM proteins in vivo. © 2018 Wiley Periodicals, Inc.

  2. Hyperactivity of newborn Pten knock-out neurons results from increased excitatory synaptic drive.

    Science.gov (United States)

    Williams, Michael R; DeSpenza, Tyrone; Li, Meijie; Gulledge, Allan T; Luikart, Bryan W

    2015-01-21

    Developing neurons must regulate morphology, intrinsic excitability, and synaptogenesis to form neural circuits. When these processes go awry, disorders, including autism spectrum disorder (ASD) or epilepsy, may result. The phosphatase Pten is mutated in some patients having ASD and seizures, suggesting that its mutation disrupts neurological function in part through increasing neuronal activity. Supporting this idea, neuronal knock-out of Pten in mice can cause macrocephaly, behavioral changes similar to ASD, and seizures. However, the mechanisms through which excitability is enhanced following Pten depletion are unclear. Previous studies have separately shown that Pten-depleted neurons can drive seizures, receive elevated excitatory synaptic input, and have abnormal dendrites. We therefore tested the hypothesis that developing Pten-depleted neurons are hyperactive due to increased excitatory synaptogenesis using electrophysiology, calcium imaging, morphological analyses, and modeling. This was accomplished by coinjecting retroviruses to either "birthdate" or birthdate and knock-out Pten in granule neurons of the murine neonatal dentate gyrus. We found that Pten knock-out neurons, despite a rapid onset of hypertrophy, were more active in vivo. Pten knock-out neurons fired at more hyperpolarized membrane potentials, displayed greater peak spike rates, and were more sensitive to depolarizing synaptic input. The increased sensitivity of Pten knock-out neurons was due, in part, to a higher density of synapses located more proximal to the soma. We determined that increased synaptic drive was sufficient to drive hypertrophic Pten knock-out neurons beyond their altered action potential threshold. Thus, our work contributes a developmental mechanism for the increased activity of Pten-depleted neurons. Copyright © 2015 the authors 0270-6474/15/350943-17$15.00/0.

  3. Neural network development in late adolescents during observation of risk-taking action.

    Directory of Open Access Journals (Sweden)

    Miyuki Tamura

    Full Text Available Emotional maturity and social awareness are important for adolescents, particularly college students beginning to face the challenges and risks of the adult world. However, there has been relatively little research into personality maturation and psychological development during late adolescence and the neural changes underlying this development. We investigated the correlation between psychological properties (neuroticism, extraversion, anxiety, and depression and age among late adolescents (n = 25, from 18 years and 1 month to 22 years and 8 months. The results revealed that late adolescents became less neurotic, less anxious, less depressive and more extraverted as they aged. Participants then observed video clips depicting hand movements with and without a risk of harm (risk-taking or safe actions during functional magnetic resonance imaging (fMRI. The results revealed that risk-taking actions elicited significantly stronger activation in the bilateral inferior parietal lobule, temporal visual regions (superior/middle temporal areas, and parieto-occipital visual areas (cuneus, middle occipital gyri, precuneus. We found positive correlations of age and extraversion with neural activation in the insula, middle temporal gyrus, lingual gyrus, and precuneus. We also found a negative correlation of age and anxiety with activation in the angular gyrus, precentral gyrus, and red nucleus/substantia nigra. Moreover, we found that insula activation mediated the relationship between age and extraversion. Overall, our results indicate that late adolescents become less anxious and more extraverted with age, a process involving functional neural changes in brain networks related to social cognition and emotional processing. The possible neural mechanisms of psychological and social maturation during late adolescence are discussed.

  4. Synaptic Effects of Electric Fields

    Science.gov (United States)

    Rahman, Asif

    Learning and sensory processing in the brain relies on the effective transmission of information across synapses. The strength and efficacy of synaptic transmission is modifiable through training and can be modulated with noninvasive electrical brain stimulation. Transcranial electrical stimulation (TES), specifically, induces weak intensity and spatially diffuse electric fields in the brain. Despite being weak, electric fields modulate spiking probability and the efficacy of synaptic transmission. These effects critically depend on the direction of the electric field relative to the orientation of the neuron and on the level of endogenous synaptic activity. TES has been used to modulate a wide range of neuropsychiatric indications, for various rehabilitation applications, and cognitive performance in diverse tasks. How can a weak and diffuse electric field, which simultaneously polarizes neurons across the brain, have precise changes in brain function? Designing therapies to maximize desired outcomes and minimize undesired effects presents a challenging problem. A series of experiments and computational models are used to define the anatomical and functional factors leading to specificity of TES. Anatomical specificity derives from guiding current to targeted brain structures and taking advantage of the direction-sensitivity of neurons with respect to the electric field. Functional specificity originates from preferential modulation of neuronal networks that are already active. Diffuse electric fields may recruit connected brain networks involved in a training task and promote plasticity along active synaptic pathways. In vitro, electric fields boost endogenous synaptic plasticity and raise the ceiling for synaptic learning with repeated stimulation sessions. Synapses undergoing strong plasticity are preferentially modulated over weak synapses. Therefore, active circuits that are involved in a task could be more susceptible to stimulation than inactive circuits

  5. Synaptic network activity induces neuronal differentiation of adult hippocampal precursor cells through BDNF signaling

    Directory of Open Access Journals (Sweden)

    Harish Babu

    2009-09-01

    Full Text Available Adult hippocampal neurogenesis is regulated by activity. But how do neural precursor cells in the hippocampus respond to surrounding network activity and translate increased neural activity into a developmental program? Here we show that long-term potential (LTP-like synaptic activity within a cellular network of mature hippocampal neurons promotes neuronal differentiation of newly generated cells. In co-cultures of precursor cells with primary hippocampal neurons, LTP-like synaptic plasticity induced by addition of glycine in Mg2+-free media for 5 min, produced synchronous network activity and subsequently increased synaptic strength between neurons. Furthermore, this synchronous network activity led to a significant increase in neuronal differentiation from the co-cultured neural precursor cells. When applied directly to precursor cells, glycine and Mg2+-free solution did not induce neuronal differentiation. Synaptic plasticity-induced neuronal differentiation of precursor cells was observed in the presence of GABAergic neurotransmission blockers but was dependent on NMDA-mediated Ca2+ influx. Most importantly, neuronal differentiation required the release of brain-derived neurotrophic factor (BDNF from the underlying substrate hippocampal neurons as well as TrkB receptor phosphorylation in precursor cells. This suggests that activity-dependent stem cell differentiation within the hippocampal network is mediated via synaptically evoked BDNF signaling.

  6. ADAM10 is essential for cranial neural crest-derived maxillofacial bone development

    Energy Technology Data Exchange (ETDEWEB)

    Tan, Yu, E-mail: tanyu2048@163.com; Fu, Runqing, E-mail: furunqing@sjtu.edu.cn; Liu, Jiaqiang, E-mail: liujqmj@163.com; Wu, Yong, E-mail: wyonger@gmail.com; Wang, Bo, E-mail: wb228@126.com; Jiang, Ning, E-mail: 179639060@qq.com; Nie, Ping, E-mail: nieping1011@sina.com; Cao, Haifeng, E-mail: 0412chf@163.com; Yang, Zhi, E-mail: wcums1981@163.com; Fang, Bing, E-mail: fangbing@sjtu.edu.cn

    2016-07-08

    Growth disorders of the craniofacial bones may lead to craniofacial deformities. The majority of maxillofacial bones are derived from cranial neural crest cells via intramembranous bone formation. Any interruption of the craniofacial skeleton development process might lead to craniofacial malformation. A disintegrin and metalloprotease (ADAM)10 plays an essential role in organ development and tissue integrity in different organs. However, little is known about its function in craniofacial bone formation. Therefore, we investigated the role of ADAM10 in the developing craniofacial skeleton, particularly during typical mandibular bone development. First, we showed that ADAM10 was expressed in a specific area of the craniofacial bone and that the expression pattern dynamically changed during normal mouse craniofacial development. Then, we crossed wnt1-cre transgenic mice with adam10-flox mice to generate ADAM10 conditional knockout mice. The stereomicroscopic, radiographic, and von Kossa staining results showed that conditional knockout of ADAM10 in cranial neural crest cells led to embryonic death, craniofacial dysmorphia and bone defects. Furthermore, we demonstrated that impaired mineralization could be triggered by decreased osteoblast differentiation, increased cell death. Overall, these findings show that ADAM10 plays an essential role in craniofacial bone development. -- Highlights: •We firstly reported that ADAM10 was essentially involved in maxillofacial bone development. •ADAM10 cKO mice present craniofacial dysmorphia and bone defects. •Impaired osteoblast differentiation,proliferation and apoptosis underlie the bone deformity.

  7. ADAM10 is essential for cranial neural crest-derived maxillofacial bone development

    International Nuclear Information System (INIS)

    Tan, Yu; Fu, Runqing; Liu, Jiaqiang; Wu, Yong; Wang, Bo; Jiang, Ning; Nie, Ping; Cao, Haifeng; Yang, Zhi; Fang, Bing

    2016-01-01

    Growth disorders of the craniofacial bones may lead to craniofacial deformities. The majority of maxillofacial bones are derived from cranial neural crest cells via intramembranous bone formation. Any interruption of the craniofacial skeleton development process might lead to craniofacial malformation. A disintegrin and metalloprotease (ADAM)10 plays an essential role in organ development and tissue integrity in different organs. However, little is known about its function in craniofacial bone formation. Therefore, we investigated the role of ADAM10 in the developing craniofacial skeleton, particularly during typical mandibular bone development. First, we showed that ADAM10 was expressed in a specific area of the craniofacial bone and that the expression pattern dynamically changed during normal mouse craniofacial development. Then, we crossed wnt1-cre transgenic mice with adam10-flox mice to generate ADAM10 conditional knockout mice. The stereomicroscopic, radiographic, and von Kossa staining results showed that conditional knockout of ADAM10 in cranial neural crest cells led to embryonic death, craniofacial dysmorphia and bone defects. Furthermore, we demonstrated that impaired mineralization could be triggered by decreased osteoblast differentiation, increased cell death. Overall, these findings show that ADAM10 plays an essential role in craniofacial bone development. -- Highlights: •We firstly reported that ADAM10 was essentially involved in maxillofacial bone development. •ADAM10 cKO mice present craniofacial dysmorphia and bone defects. •Impaired osteoblast differentiation,proliferation and apoptosis underlie the bone deformity.

  8. Does autophagy work in synaptic plasticity and memory?

    Science.gov (United States)

    Shehata, Mohammad; Inokuchi, Kaoru

    2014-01-01

    Many studies have reported the roles played by regulated proteolysis in neural plasticity and memory. Within this context, most of the research focused on the ubiquitin-proteasome system and the endosome-lysosome system while giving lesser consideration to another major protein degradation system, namely, autophagy. Although autophagy intersects with many of the pathways known to underlie synaptic plasticity and memory, only few reports related autophagy to synaptic remodeling. These pathways include PI3K-mTOR pathway and endosome-dependent proteolysis. In this review, we will discuss several lines of evidence supporting a physiological role of autophagy in memory processes, and the possible mechanistic scenarios for how autophagy could fulfill this function.

  9. Emulating short-term synaptic dynamics with memristive devices

    Science.gov (United States)

    Berdan, Radu; Vasilaki, Eleni; Khiat, Ali; Indiveri, Giacomo; Serb, Alexandru; Prodromakis, Themistoklis

    2016-01-01

    Neuromorphic architectures offer great promise for achieving computation capacities beyond conventional Von Neumann machines. The essential elements for achieving this vision are highly scalable synaptic mimics that do not undermine biological fidelity. Here we demonstrate that single solid-state TiO2 memristors can exhibit non-associative plasticity phenomena observed in biological synapses, supported by their metastable memory state transition properties. We show that, contrary to conventional uses of solid-state memory, the existence of rate-limiting volatility is a key feature for capturing short-term synaptic dynamics. We also show how the temporal dynamics of our prototypes can be exploited to implement spatio-temporal computation, demonstrating the memristors full potential for building biophysically realistic neural processing systems.

  10. Development of a Compact Gamma-ray Detector for a Neural-Network Radiation Monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Kim, H. S.; Ha, J. H.; Lee, K. H. [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of); Lee, C. H. [Hanyang Univ., Seoul (Korea, Republic of)

    2012-03-15

    Radiation monitoring is very important to secure safety in nuclear-related facilities and against nuclear terrorism. For wide range of radiation monitoring, neutral network system of radiation detection is most efficient way. Thus, a compact radiation detector is useful to install in wide range to be concerned. A compact gamma-ray detector was fabricated by using a CsI(Tl) scintillator, which was matched with the formerly developed PIN photodiode, for a neural network radiation monitoring. At room temperature, the fabricated compact gamma-ray detector demonstrates an energy resolution of 13.3 % for 662 keV 6.9% for 1330 keV. The compactness, the low-voltage power consumption and the physical hardness are very useful features for a neural network radiation monitoring. In this study, characteristics of a fabricated compact gamma-ray detector were presented. An important aspect to consider in a neural-network radiation monitoring such as reaction probability of the fabricated compact detector for angle of incident gamma-ray was also addressed.

  11. Synaptic scaling enables dynamically distinct short- and long-term memory formation.

    Directory of Open Access Journals (Sweden)

    Christian Tetzlaff

    2013-10-01

    Full Text Available Memory storage in the brain relies on mechanisms acting on time scales from minutes, for long-term synaptic potentiation, to days, for memory consolidation. During such processes, neural circuits distinguish synapses relevant for forming a long-term storage, which are consolidated, from synapses of short-term storage, which fade. How time scale integration and synaptic differentiation is simultaneously achieved remains unclear. Here we show that synaptic scaling - a slow process usually associated with the maintenance of activity homeostasis - combined with synaptic plasticity may simultaneously achieve both, thereby providing a natural separation of short- from long-term storage. The interaction between plasticity and scaling provides also an explanation for an established paradox where memory consolidation critically depends on the exact order of learning and recall. These results indicate that scaling may be fundamental for stabilizing memories, providing a dynamic link between early and late memory formation processes.

  12. Synaptic scaling enables dynamically distinct short- and long-term memory formation.

    Science.gov (United States)

    Tetzlaff, Christian; Kolodziejski, Christoph; Timme, Marc; Tsodyks, Misha; Wörgötter, Florentin

    2013-10-01

    Memory storage in the brain relies on mechanisms acting on time scales from minutes, for long-term synaptic potentiation, to days, for memory consolidation. During such processes, neural circuits distinguish synapses relevant for forming a long-term storage, which are consolidated, from synapses of short-term storage, which fade. How time scale integration and synaptic differentiation is simultaneously achieved remains unclear. Here we show that synaptic scaling - a slow process usually associated with the maintenance of activity homeostasis - combined with synaptic plasticity may simultaneously achieve both, thereby providing a natural separation of short- from long-term storage. The interaction between plasticity and scaling provides also an explanation for an established paradox where memory consolidation critically depends on the exact order of learning and recall. These results indicate that scaling may be fundamental for stabilizing memories, providing a dynamic link between early and late memory formation processes.

  13. Decreased spinal synaptic inputs to phrenic motor neurons elicit localized inactivity-induced phrenic motor facilitation

    OpenAIRE

    Streeter, K.A.; Baker-Herman, T.L.

    2014-01-01

    Phrenic motor neurons receive rhythmic synaptic inputs throughout life. Since even brief disruption in phrenic neural activity is detrimental to life, on-going neural activity may play a key role in shaping phrenic motor output. To test the hypothesis that spinal mechanisms sense and respond to reduced phrenic activity, anesthetized, ventilated rats received micro-injections of procaine in the C2 ventrolateral funiculus (VLF) to transiently (~30 min) block axon conduction in bulbospinal axons...

  14. Experience-Dependent Equilibration of AMPAR-Mediated Synaptic Transmission during the Critical Period

    Directory of Open Access Journals (Sweden)

    Kyung-Seok Han

    2017-01-01

    Full Text Available Experience-dependent synapse refinement is essential for functional optimization of neural circuits. However, how sensory experience sculpts excitatory synaptic transmission is poorly understood. Here, we show that despite substantial remodeling of synaptic connectivity, AMPAR-mediated synaptic transmission remains at equilibrium during the critical period in the mouse primary visual cortex. The maintenance of this equilibrium requires neurogranin (Ng, a postsynaptic calmodulin-binding protein important for synaptic plasticity. With normal visual experience, loss of Ng decreased AMPAR-positive synapse numbers, prevented AMPAR-silent synapse maturation, and increased spine elimination. Importantly, visual deprivation halted synapse loss caused by loss of Ng, revealing that Ng coordinates experience-dependent AMPAR-silent synapse conversion to AMPAR-active synapses and synapse elimination. Loss of Ng also led to sensitized long-term synaptic depression (LTD and impaired visually guided behavior. Our synaptic interrogation reveals that experience-dependent coordination of AMPAR-silent synapse conversion and synapse elimination hinges upon Ng-dependent mechanisms for constructive synaptic refinement during the critical period.

  15. 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

  16. 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.

  17. Intermittent reductions in respiratory neural activity elicit spinal TNF-α-independent, atypical PKC-dependent inactivity-induced phrenic motor facilitation.

    Science.gov (United States)

    Baertsch, Nathan A; Baker-Herman, Tracy L

    2015-04-15

    In many neural networks, mechanisms of compensatory plasticity respond to prolonged reductions in neural activity by increasing cellular excitability or synaptic strength. In the respiratory control system, a prolonged reduction in synaptic inputs to the phrenic motor pool elicits a TNF-α- and atypical PKC-dependent form of spinal plasticity known as inactivity-induced phrenic motor facilitation (iPMF). Although iPMF may be elicited by a prolonged reduction in respiratory neural activity, iPMF is more efficiently induced when reduced respiratory neural activity (neural apnea) occurs intermittently. Mechanisms giving rise to iPMF following intermittent neural apnea are unknown. The purpose of this study was to test the hypothesis that iPMF following intermittent reductions in respiratory neural activity requires spinal TNF-α and aPKC. Phrenic motor output was recorded in anesthetized and ventilated rats exposed to brief intermittent (5, ∼1.25 min), brief sustained (∼6.25 min), or prolonged sustained (30 min) neural apnea. iPMF was elicited following brief intermittent and prolonged sustained neural apnea, but not following brief sustained neural apnea. Unlike iPMF following prolonged neural apnea, spinal TNF-α was not required to initiate iPMF during intermittent neural apnea; however, aPKC was still required for its stabilization. These results suggest that different patterns of respiratory neural activity induce iPMF through distinct cellular mechanisms but ultimately converge on a similar downstream pathway. Understanding the diverse cellular mechanisms that give rise to inactivity-induced respiratory plasticity may lead to development of novel therapeutic strategies to treat devastating respiratory control disorders when endogenous compensatory mechanisms fail. Copyright © 2015 the American Physiological Society.

  18. GABA regulates synaptic integration of newly generated neurons in the adult brain

    Science.gov (United States)

    Ge, Shaoyu; Goh, Eyleen L. K.; Sailor, Kurt A.; Kitabatake, Yasuji; Ming, Guo-Li; Song, Hongjun

    2006-02-01

    Adult neurogenesis, the birth and integration of new neurons from adult neural stem cells, is a striking form of structural plasticity and highlights the regenerative capacity of the adult mammalian brain. Accumulating evidence suggests that neuronal activity regulates adult neurogenesis and that new neurons contribute to specific brain functions. The mechanism that regulates the integration of newly generated neurons into the pre-existing functional circuitry in the adult brain is unknown. Here we show that newborn granule cells in the dentate gyrus of the adult hippocampus are tonically activated by ambient GABA (γ-aminobutyric acid) before being sequentially innervated by GABA- and glutamate-mediated synaptic inputs. GABA, the major inhibitory neurotransmitter in the adult brain, initially exerts an excitatory action on newborn neurons owing to their high cytoplasmic chloride ion content. Conversion of GABA-induced depolarization (excitation) into hyperpolarization (inhibition) in newborn neurons leads to marked defects in their synapse formation and dendritic development in vivo. Our study identifies an essential role for GABA in the synaptic integration of newly generated neurons in the adult brain, and suggests an unexpected mechanism for activity-dependent regulation of adult neurogenesis, in which newborn neurons may sense neuronal network activity through tonic and phasic GABA activation.

  19. Anthropogenic changes in sodium affect neural and muscle development in butterflies

    Science.gov (United States)

    Snell-Rood, Emilie C.; Espeset, Anne; Boser, Christopher J.; White, William A.; Smykalski, Rhea

    2014-01-01

    The development of organisms is changing drastically because of anthropogenic changes in once-limited nutrients. Although the importance of changing macronutrients, such as nitrogen and phosphorus, is well-established, it is less clear how anthropogenic changes in micronutrients will affect organismal development, potentially changing dynamics of selection. We use butterflies as a study system to test whether changes in sodium availability due to road salt runoff have significant effects on the development of sodium-limited traits, such as neural and muscle tissue. We first document how road salt runoff can elevate sodium concentrations in the tissue of some plant groups by 1.5–30 times. Using monarch butterflies reared on roadside- and prairie-collected milkweed, we then show that road salt runoff can result in increased muscle mass (in males) and neural investment (in females). Finally, we use an artificial diet manipulation in cabbage white butterflies to show that variation in sodium chloride per se positively affects male flight muscle and female brain size. Variation in sodium not only has different effects depending on sex, but also can have opposing effects on the same tissue: across both species, males increase investment in flight muscle with increasing sodium, whereas females show the opposite pattern. Taken together, our results show that anthropogenic changes in sodium availability can affect the development of traits in roadside-feeding herbivores. This research suggests that changing micronutrient availability could alter selection on foraging behavior for some roadside-developing invertebrates. PMID:24927579

  20. Anthropogenic changes in sodium affect neural and muscle development in butterflies.

    Science.gov (United States)

    Snell-Rood, Emilie C; Espeset, Anne; Boser, Christopher J; White, William A; Smykalski, Rhea

    2014-07-15

    The development of organisms is changing drastically because of anthropogenic changes in once-limited nutrients. Although the importance of changing macronutrients, such as nitrogen and phosphorus, is well-established, it is less clear how anthropogenic changes in micronutrients will affect organismal development, potentially changing dynamics of selection. We use butterflies as a study system to test whether changes in sodium availability due to road salt runoff have significant effects on the development of sodium-limited traits, such as neural and muscle tissue. We first document how road salt runoff can elevate sodium concentrations in the tissue of some plant groups by 1.5-30 times. Using monarch butterflies reared on roadside- and prairie-collected milkweed, we then show that road salt runoff can result in increased muscle mass (in males) and neural investment (in females). Finally, we use an artificial diet manipulation in cabbage white butterflies to show that variation in sodium chloride per se positively affects male flight muscle and female brain size. Variation in sodium not only has different effects depending on sex, but also can have opposing effects on the same tissue: across both species, males increase investment in flight muscle with increasing sodium, whereas females show the opposite pattern. Taken together, our results show that anthropogenic changes in sodium availability can affect the development of traits in roadside-feeding herbivores. This research suggests that changing micronutrient availability could alter selection on foraging behavior for some roadside-developing invertebrates.

  1. Development of objective flow regime identification method using self-organizing neural network

    International Nuclear Information System (INIS)

    Lee, Jae Young; Kim, Nam Seok; Kwak, Nam Yee

    2004-01-01

    Two-phase flow shows various flow patterns according to the amount of the void and its relative velocity to the liquid flow. This variation directly affect the interfacial transfer which is the key factor for the design or analysis of the phase change systems. Especially the safety analysis of the nuclear power plant has been performed based on the numerical code furnished with the proper constitutive relations depending highly upon the flow regimes. Heavy efforts have been focused to identify the flow regime and at this moment we stand on relative very stable engineering background compare to the other research field. However, the issues related to objectiveness and transient flow regime are still open to study. Lee et al. and Ishii developed the method for the objective and instantaneous flow regime identification based on the neural network and new index of probability distribution of the flow regime which allows just one second observation for the flow regime identification. In the present paper, we developed the self-organized neural network for more objective approach to this problem. Kohonen's Self-Organizing Map (SOM) has been used for clustering, visualization, and abstraction. The SOM is trained through unsupervised competitive learning using a 'winner takes it all' policy. Therefore, its unsupervised training character delete the possible interference of the regime developer to the neural network training. After developing the computer code, we evaluate the performance of the code with the vertically upward two-phase flow in the pipes of 25.4 and 50.4 cmm I.D. Also, the sensitivity of the number of the clusters to the flow regime identification was made

  2. Development of artificial neural network models for supercritical fluid solvency in presence of co-solvents

    Energy Technology Data Exchange (ETDEWEB)

    Shokir, Eissa Mohamed El-Moghawry; El-Midany, Ayman Abdel-Hamid [Cairo University, Giza (Egypt); Al-Homadhi, Emad Souliman; Al-Mahdy, Osama [King Saud University, Riyadh (Saudi Arabia)

    2014-08-15

    This paper presents the application of artificial neural networks (ANN) to develop new models of liquid solvent dissolution of supercritical fluids with solutes in the presence of cosolvents. The neural network model of the liquid solvent dissolution of CO{sub 2} was built as a function of pressure, temperature, and concentrations of the solutes and cosolvents. Different experimental measurements of liquid solvent dissolution of supercritical fluids (CO{sub 2}) with solutes in the presence of cosolvents were collected. The collected data are divided into two parts. The first part was used in building the models, and the second part was used to test and validate the developed models against the Peng- Robinson equation of state. The developed ANN models showed high accuracy, within the studied variables range, in predicting the solubility of the 2-naphthol, anthracene, and aspirin in the supercritical fluid in the presence and absence of co-solvents compared to (EoS). Therefore, the developed ANN models could be considered as a good tool in predicting the solubility of tested solutes in supercritical fluid.

  3. Multi-GPU Development of a Neural Networks Based Reconstructor for Adaptive Optics

    Directory of Open Access Journals (Sweden)

    Carlos González-Gutiérrez

    2018-01-01

    Full Text Available Aberrations introduced by the atmospheric turbulence in large telescopes are compensated using adaptive optics systems, where the use of deformable mirrors and multiple sensors relies on complex control systems. Recently, the development of larger scales of telescopes as the E-ELT or TMT has created a computational challenge due to the increasing complexity of the new adaptive optics systems. The Complex Atmospheric Reconstructor based on Machine Learning (CARMEN is an algorithm based on artificial neural networks, designed to compensate the atmospheric turbulence. During recent years, the use of GPUs has been proved to be a great solution to speed up the learning process of neural networks, and different frameworks have been created to ease their development. The implementation of CARMEN in different Multi-GPU frameworks is presented in this paper, along with its development in a language originally developed for GPU, like CUDA. This implementation offers the best response for all the presented cases, although its advantage of using more than one GPU occurs only in large networks.

  4. Interleukin-6 Regulates Adult Neural Stem Cell Numbers during Normal and Abnormal Post-natal Development

    Directory of Open Access Journals (Sweden)

    Mekayla A. Storer

    2018-05-01

    Full Text Available Summary: Circulating systemic factors can regulate adult neural stem cell (NSC biology, but the identity of these circulating cues is still being defined. Here, we have focused on the cytokine interleukin-6 (IL-6, since increased circulating levels of IL-6 are associated with neural pathologies such as autism and bipolar disorder. We show that IL-6 promotes proliferation of post-natal murine forebrain NSCs and that, when the IL-6 receptor is inducibly knocked out in post-natal or adult neural precursors, this causes a long-term decrease in forebrain NSCs. Moreover, a transient circulating surge of IL-6 in perinatal or adult mice causes an acute increase in neural precursor proliferation followed by long-term depletion of adult NSC pools. Thus, IL-6 signaling is both necessary and sufficient for adult NSC self-renewal, and acute perturbations in circulating IL-6, as observed in many pathological situations, have long-lasting effects on the size of adult NSC pools. : In this report, Storer and colleagues demonstrate that the circulating cytokine IL-6, which is elevated in humans in different pathological situations, can perturb neural stem cell biology after birth. They show that IL-6 signaling is essential for self-renewal and maintenance of post-natal and adult NSCs in the murine forebrain under normal homeostatic conditions. Keywords: interleukin-6, neural stem cell, adult neurogenesis, CNS cytokines, postnatal brain development, stem cell depletion, neural stem cell niche, circulating stem cell factors, olfactory bulb

  5. Shank synaptic scaffold proteins: keys to understanding the pathogenesis of autism and other synaptic disorders.

    Science.gov (United States)

    Sala, Carlo; Vicidomini, Cinzia; Bigi, Ilaria; Mossa, Adele; Verpelli, Chiara

    2015-12-01

    Shank/ProSAP proteins are essential to synaptic formation, development, and function. Mutations in the family of SHANK genes are strongly associated with autism spectrum disorders (ASD) and other neurodevelopmental and neuropsychiatric disorders, such as intellectual disability (ID), and schizophrenia. Thus, the term 'Shankopathies' identifies a number of neuronal diseases caused by alteration of Shank protein expression leading to abnormal synaptic development. With this review we want to summarize the major genetic, molecular, behavior and electrophysiological studies that provide new clues into the function of Shanks and pave the way for the discovery of new therapeutic drugs targeted to treat patients with SHANK mutations and also patients affected by other neurodevelopmental and neuropsychiatric disorders. Shank/ProSAP proteins are essential to synaptic formation, development, and function. Mutations in the family of SHANK genes are strongly associated with autism spectrum disorders (ASD) and other neurodevelopmental and neuropsychiatric disorders, such as intellectual disability (ID), and schizophrenia (SCZ). With this review we want to summarize the major genetic, molecular, behavior and electrophysiological studies that provide new clues into the function of Shanks and pave the way for the discovery of new therapeutic drugs targeted to treat patients with SHANK mutations. © 2015 International Society for Neurochemistry.

  6. Development of neural network techniques for the analysis of JET ECE data

    International Nuclear Information System (INIS)

    Bartlett, D.V.; Bishop, C.M.

    1993-01-01

    This paper reports on a project currently in progress to develop neutral network techniques for the conversion of JET ECE spectra to electron temperature profiles. The aim is to obtain profiles with reduced measurement uncertainties by incorporating data from the LIDAR Thomson scattering diagnostic in the analysis, while retaining the faster time resolution of the ECE measurements. The properties of neural networks are briefly reviewed, and the reasons for using them in this application are explained. Some preliminary results are presented and the direction of future work is outlined. (orig.)

  7. Development of a diagnostic system for Klystron modulators using a neural network

    International Nuclear Information System (INIS)

    Mutoh, M.; Oonuma, T.; Shibasaki, Y.; Abe, I.; Nakahara, K.

    1992-01-01

    The diagnostic system for klystron modulators using a neural network has been developed. Large changes in the voltage and current of the main circuit in a klystron modulator were observed just several ten milli-seconds before the modulator experienced trouble. These changes formed a peculiar pattern that depended on the parts with problems. Diagnosis was possible by means of pattern recognition. The recognition test of patterns using a neutral network has shown good results. This system, which is built in a linac control system, is presently being operated so as to collect new trouble patterns and to carry out tests for practical use. (author)

  8. Development-dependent behavioral change toward pups and synaptic transmission in the rhomboid nucleus of the bed nucleus of the stria terminalis.

    Science.gov (United States)

    Amano, Taiju; Shindo, Sayaka; Yoshihara, Chihiro; Tsuneoka, Yousuke; Uki, Haruka; Minami, Masabumi; Kuroda, Kumi O

    2017-05-15

    Sexually naïve male C57BL/6 mice aggressively bite unfamiliar pups. This behavior, called infanticide, is considered an adaptive reproductive strategy of males of polygamous species. We recently found that the rhomboid nucleus of the bed nucleus of the stria terminalis (BSTrh) is activated during infanticide and that the bilateral excitotoxic lesions of BSTrh suppress infanticidal behavior. Here we show that 3-week-old male C57BL/6 mice rarely engaged in infanticide and instead, provided parental care toward unfamiliar pups, consistent with observations in rats and other rodent species. This inhibition of infanticide at the periweaning period is functional because the next litter will be born at approximately the time of weaning of the previous litter through maternal postpartum ovulation. However, the mechanism of this age-dependent behavioral change is unknown. Therefore, we performed whole-cell patch clamp recordings of BSTrh and compared evoked neurotransmission in response to the stimulation of the stria terminalis of adult and 3-week-old male mice. Although we were unable to detect a significant difference in the amplitudes of inhibitory neurotransmission, the amplitudes and the paired-pulse ratio of evoked excitatory postsynaptic currents differed between adult and 3-week-old mice. These data suggest that maturation of the synaptic terminal in BSTrh that occurred later than 3 weeks after birth may mediate by the adaptive change from parental to infanticidal behavior in male mice. Copyright © 2016 Elsevier B.V. All rights reserved.

  9. The F-box protein Cdc4/Fbxw7 is a novel regulator of neural crest development in Xenopus laevis

    Directory of Open Access Journals (Sweden)

    Hartley Rebecca S

    2010-01-01

    Full Text Available Abstract Background The neural crest is a unique population of cells that arise in the vertebrate ectoderm at the neural plate border after which they migrate extensively throughout the embryo, giving rise to a wide range of derivatives. A number of proteins involved in neural crest development have dynamic expression patterns, and it is becoming clear that ubiquitin-mediated protein degradation is partly responsible for this. Results Here we demonstrate a novel role for the F-box protein Cdc4/Fbxw7 in neural crest development. Two isoforms of Xenopus laevis Cdc4 were identified, and designated xCdc4α and xCdc4β. These are highly conserved with vertebrate Cdc4 orthologs, and the Xenopus proteins are functionally equivalent in terms of their ability to degrade Cyclin E, an established vertebrate Cdc4 target. Blocking xCdc4 function specifically inhibited neural crest development at an early stage, prior to expression of c-Myc, Snail2 and Snail. Conclusions We demonstrate that Cdc4, an ubiquitin E3 ligase subunit previously identified as targeting primarily cell cycle regulators for proteolysis, has additional roles in control of formation of the neural crest. Hence, we identify Cdc4 as a protein with separable but complementary functions in control of cell proliferation and differentiation.

  10. Epigenetic Regulation of the Neural Transcriptome and Alcohol Interference During Development

    Directory of Open Access Journals (Sweden)

    Marisol eResendiz

    2014-08-01

    Full Text Available Alcohol intoxicated cells broadly alter their metabolites–– among them methyl and acetic acid can alter the DNA and histone epigenetic codes. Together with the promiscuous effect of alcohol on enzyme activities (including DNA methyltransferases and the downstream effect on microRNA and transposable elements, alcohol is well placed to affect intrinsic transcriptional programs of developing cells. Considering that the developmental consequences of early alcohol exposure so profoundly affect neural systems, it is not unfounded to reason that alcohol exploits transcriptional regulators to challenge canonical gene expression and in effect, intrinsic developmental pathways to achieve widespread damage in the developing nervous system. To fully evaluate the role of epigenetic regulation in alcohol-related developmental disease, it is important to first gather the targets of epigenetic players in neurodevelopmental models. Here, we attempt to review the cellular and genomic windows of opportunity for alcohol to act on intrinsic neurodevelopmental programs. We also discuss some established targets of fetal alcohol exposure and propose pathways for future study. Overall, this review hopes to illustrate the known epigenetic program and its alterations in normal neural stem cell development and further, aims to depict how alcohol, through neuroepigenetics, may lead to neurodevelopmental deficits observed in fetal alcohol spectrum disorders.

  11. Epigenetic regulation of the neural transcriptome and alcohol interference during development.

    Science.gov (United States)

    Resendiz, Marisol; Mason, Stephen; Lo, Chiao-Ling; Zhou, Feng C

    2014-01-01

    Alcohol intoxicated cells broadly alter their metabolites - among them methyl and acetic acid can alter the DNA and histone epigenetic codes. Together with the promiscuous effect of alcohol on enzyme activities (including DNA methyltransferases) and the downstream effect on microRNA and transposable elements, alcohol is well placed to affect intrinsic transcriptional programs of developing cells. Considering that the developmental consequences of early alcohol exposure so profoundly affect neural systems, it is not unfounded to reason that alcohol exploits transcriptional regulators to challenge canonical gene expression and in effect, intrinsic developmental pathways to achieve widespread damage in the developing nervous system. To fully evaluate the role of epigenetic regulation in alcohol-related developmental disease, it is important to first gather the targets of epigenetic players in neurodevelopmental models. Here, we attempt to review the cellular and genomic windows of opportunity for alcohol to act on intrinsic neurodevelopmental programs. We also discuss some established targets of fetal alcohol exposure and propose pathways for future study. Overall, this review hopes to illustrate the known epigenetic program and its alterations in normal neural stem cell development and further, aims to depict how alcohol, through neuroepigenetics, may lead to neurodevelopmental deficits observed in fetal alcohol spectrum disorders.

  12. Dishevelled 2 is essential for cardiac outflow tract development, somite segmentation and neural tube closure.

    Science.gov (United States)

    Hamblet, Natasha S; Lijam, Nardos; Ruiz-Lozano, Pilar; Wang, Jianbo; Yang, Yasheng; Luo, Zhenge; Mei, Lin; Chien, Kenneth R; Sussman, Daniel J; Wynshaw-Boris, Anthony

    2002-12-01

    The murine dishevelled 2 (Dvl2) gene is an ortholog of the Drosophila segment polarity gene Dishevelled, a member of the highly conserved Wingless/Wnt developmental pathway. Dvl2-deficient mice were produced to determine the role of Dvl2 in mammalian development. Mice containing null mutations in Dvl2 present with 50% lethality in both inbred 129S6 and in a hybrid 129S6-NIH Black Swiss background because of severe cardiovascular outflow tract defects, including double outlet right ventricle, transposition of the great arteries and persistent truncus arteriosis. The majority of the surviving Dvl2(-/-) mice were female, suggesting that penetrance was influenced by sex. Expression of Pitx2 and plexin A2 was attenuated in Dvl2 null mutants, suggesting a defect in cardiac neural crest development during outflow tract formation. In addition, approximately 90% of Dvl2(-/-) mice have vertebral and rib malformations that affect the proximal as well as the distal parts of the ribs. These skeletal abnormalities were more pronounced in mice deficient for both Dvl1 and Dvl2. Somite differentiation markers used to analyze Dvl2(-/-) and Dvl1(-/-);Dvl2(-/-) mutant embryos revealed mildly aberrant expression of Uncx4.1, delta 1 and myogenin, suggesting defects in somite segmentation. Finally, 2-3% of Dvl2(-/-) embryos displayed thoracic spina bifida, while virtually all Dvl1/2 double mutant embryos displayed craniorachishisis, a completely open neural tube from the midbrain to the tail. Thus, Dvl2 is essential for normal cardiac morphogenesis, somite segmentation and neural tube closure, and there is functional redundancy between Dvl1 and Dvl2 in some phenotypes.

  13. Brief Report: Robo1 Regulates the Migration of Human Subventricular Zone Neural Progenitor Cells During Development.

    Science.gov (United States)

    Guerrero-Cazares, Hugo; Lavell, Emily; Chen, Linda; Schiapparelli, Paula; Lara-Velazquez, Montserrat; Capilla-Gonzalez, Vivian; Clements, Anna Christina; Drummond, Gabrielle; Noiman, Liron; Thaler, Katrina; Burke, Anne; Quiñones-Hinojosa, Alfredo

    2017-07-01

    Human neural progenitor cell (NPC) migration within the subventricular zone (SVZ) of the lateral ganglionic eminence is an active process throughout early brain development. The migration of human NPCs from the SVZ to the olfactory bulb during fetal stages resembles what occurs in adult rodents. As the human brain develops during infancy, this migratory stream is drastically reduced in cell number and becomes barely evident in adults. The mechanisms regulating human NPC migration are unknown. The Slit-Robo signaling pathway has been defined as a chemorepulsive cue involved in axon guidance and neuroblast migration in rodents. Slit and Robo proteins expressed in the rodent brain help guide neuroblast migration from the SVZ through the rostral migratory stream to the olfactory bulb. Here, we present the first study on the role that Slit and Robo proteins play in human-derived fetal neural progenitor cell migration (hfNPC). We describe that Robo1 and Robo2 isoforms are expressed in the human fetal SVZ. Furthermore, we demonstrate that Slit2 is able to induce a chemorepellent effect on the migration of hfNPCs derived from the human fetal SVZ. In addition, when Robo1 expression is inhibited, hfNPCs are unable to migrate to the olfactory bulb of mice when injected in the anterior SVZ. Our findings indicate that the migration of human NPCs from the SVZ is partially regulated by the Slit-Robo axis. This pathway could be regulated to direct the migration of NPCs in human endogenous neural cell therapy. Stem Cells 2017;35:1860-1865. © 2017 AlphaMed Press.

  14. The Sustainable Development Assessment of Reservoir Resettlement Based on a BP Neural Network.

    Science.gov (United States)

    Huang, Li; Huang, Jian; Wang, Wei

    2018-01-18

    Resettlement affects not only the resettlers' production activities and life but also, directly or indirectly, the normal operation of power stations, the sustainable development of the resettlers, and regional social stability. Therefore, a scientific evaluation index system for the sustainable development of reservoir resettlement must be established that fits Chinese national conditions and not only promotes reservoir resettlement research but also improves resettlement practice. This essay builds an evaluation index system for resettlers' sustainable development based on a back-propagation (BP) neural network, which can be adopted in China, taking the resettlement necessitated by step hydropower stations along the Wujiang River cascade as an example. The assessment results show that the resettlement caused by step power stations along the Wujiang River is sustainable, and this evaluation supports the conclusion that national policies and regulations, which are undergoing constant improvement, and resettlement has increasingly improved. The results provide a reference for hydropower reservoir resettlement in developing countries.

  15. The Sustainable Development Assessment of Reservoir Resettlement Based on a BP Neural Network

    Science.gov (United States)

    Huang, Li; Huang, Jian

    2018-01-01

    Resettlement affects not only the resettlers’ production activities and life but also, directly or indirectly, the normal operation of power stations, the sustainable development of the resettlers, and regional social stability. Therefore, a scientific evaluation index system for the sustainable development of reservoir resettlement must be established that fits Chinese national conditions and not only promotes reservoir resettlement research but also improves resettlement practice. This essay builds an evaluation index system for resettlers’ sustainable development based on a back-propagation (BP) neural network, which can be adopted in China, taking the resettlement necessitated by step hydropower stations along the Wujiang River cascade as an example. The assessment results show that the resettlement caused by step power stations along the Wujiang River is sustainable, and this evaluation supports the conclusion that national policies and regulations, which are undergoing constant improvement, and resettlement has increasingly improved. The results provide a reference for hydropower reservoir resettlement in developing countries. PMID:29346305

  16. The Sustainable Development Assessment of Reservoir Resettlement Based on a BP Neural Network

    Directory of Open Access Journals (Sweden)

    Li Huang

    2018-01-01

    Full Text Available Resettlement affects not only the resettlers’ production activities and life but also, directly or indirectly, the normal operation of power stations, the sustainable development of the resettlers, and regional social stability. Therefore, a scientific evaluation index system for the sustainable development of reservoir resettlement must be established that fits Chinese national conditions and not only promotes reservoir resettlement research but also improves resettlement practice. This essay builds an evaluation index system for resettlers’ sustainable development based on a back-propagation (BP neural network, which can be adopted in China, taking the resettlement necessitated by step hydropower stations along the Wujiang River cascade as an example. The assessment results show that the resettlement caused by step power stations along the Wujiang River is sustainable, and this evaluation supports the conclusion that national policies and regulations, which are undergoing constant improvement, and resettlement has increasingly improved. The results provide a reference for hydropower reservoir resettlement in developing countries.

  17. A Robust Single Primate Neuroepithelial Cell Clonal Expansion System for Neural Tube Development and Disease Studies

    Directory of Open Access Journals (Sweden)

    Xiaoqing Zhu

    2016-02-01

    Full Text Available Developing a model of primate neural tube (NT development is important to promote many NT disorder studies in model organisms. Here, we report a robust and stable system to allow for clonal expansion of single monkey neuroepithelial stem cells (NESCs to develop into miniature NT-like structures. Single NESCs can produce functional neurons in vitro, survive, and extensively regenerate neuron axons in monkey brain. NT formation and NESC maintenance depend on high metabolism activity and Wnt signaling. NESCs are regionally restricted to a telencephalic fate. Moreover, single NESCs can turn into radial glial progenitors (RGPCs. The transition is accurately regulated by Wnt signaling through regulation of Notch signaling and adhesion molecules. Finally, using the “NESC-TO-NTs” system, we model the functions of folic acid (FA on NT closure and demonstrate that FA can regulate multiple mechanisms to prevent NT defects. Our system is ideal for studying NT development and diseases.

  18. DIAGNOSIS AND PREDICTION OF CHOLECYSTITIS DEVELOPMENT ON THE BASIS OF NEURAL NETWORK ANALYSIS OF RISK FACTORS

    Directory of Open Access Journals (Sweden)

    V. A. Lazarenko

    2017-01-01

    Full Text Available Purpose. To develop an artificial neural network for diagnosing and predicting the development of cholecystitis based on an analysis of data on risk factors, and to explore the possibilities of its application in real clinical practice.Materials and methods. The collection of materials was held in at the hospitals of the city of Kursk and included a survey of 488 patients with hepatopancreatoduodenal diseases. 203 patients were suffering from cholecystitis, in 285 patients the diagnosis of cholecystitis was excluded. Analysis of risk factors’ data (such as sex, age, bad habits, profession, family relationships, etc. was carried out using an internally developed artificial neural network (multilayer perceptron with hyperbolic tangent as the activation function. The computer program “System of Intellectual Analysis and Diagnosis of Diseases” was registered in accordance with established procedure (Certificate No. 2017613090.Results. The use of neural network analysis of data on risk factors in comparison with the processing of information that forms a clinical picture allows the diagnosis of a potential disease with cholecystitis before the onset of symptoms. The training of the artificial neural network with a quantitative output coding the age of probable hospitalization made it possible to generate an array of values, signifficantly (α ≤ 0.001 not differing from the empirical data. The difference between the mean calculated and mean empirical values was 0.45 for the training set and 1.75 for the clinical approbation group. The mean absolute error was within the range of 1.87–2.07 years.Conclusion. 1. The proposed new approach to the diagnosis and prognosis of cholecystitis has demonstrated its effectiveness, which is confirmed in clinical approbation by the levels of sensitivity (94.44%, m = 2.26 and specificity (80.6%, m = 3.9.2. The error in predicting the age of probable hospitalization of patients with cholecystitis did not

  19. Development of teeth in chick embryos after mouse neural crest transplantations

    OpenAIRE

    Mitsiadis, Thimios A.; Chéraud, Yvonnick; Sharpe, Paul; Fontaine-Pérus, Josiane

    2003-01-01

    Teeth were lost in birds 70–80 million years ago. Current thinking holds that it is the avian cranial neural crest-derived mesenchyme that has lost odontogenic capacity, whereas the oral epithelium retains the signaling properties required to induce odontogenesis. To investigate the odontogenic capacity of ectomesenchyme, we have used neural tube transplantations from mice to chick embryos to replace the chick neural crest cell populations with mouse neural crest cells. The mouse/chick ...

  20. Review: the development of neural stem cell biology and technology in regenerative medicine

    OpenAIRE

    Shanmuganathan, Divyanjali; Sivakumaran, Nivethika

    2018-01-01

    In the middle of the last century, it has been known that neural stem cells (NSCs) play a key role in regenerative medicine to cure the neurodegenerative disease. This review article covers about the introduction to neural stem cell biology and the isolation, differentiation and transplantation methods/techniques of neural stem cells. The neural stem cells can be transplanted into the human brain in the future to replace the damaged and dead neurons. The highly limited access to embryonic ste...

  1. Zebrafish msxB, msxC and msxE function together to refine the neural-nonneural border and regulate cranial placodes and neural crest development.

    Science.gov (United States)

    Phillips, Bryan T; Kwon, Hye-Joo; Melton, Colt; Houghtaling, Paul; Fritz, Andreas; Riley, Bruce B

    2006-06-15

    The zebrafish muscle segment homeobox genes msxB, msxC and msxE are expressed in partially overlapping domains in the neural crest and preplacodal ectoderm. We examined the roles of these msx genes in early development. Disrupting individual msx genes causes modest variable defects, whereas disrupting all three produces a reproducible severe phenotype, suggesting functional redundancy. Neural crest differentiation is blocked at an early stage. Preplacodal development begins normally, but placodes arising from the msx expression domain later show elevated apoptosis and are reduced in size. Cell proliferation is normal in these tissues. Unexpectedly, Msx-deficient embryos become ventralized by late gastrulation whereas misexpression of msxB dorsalizes the embryo. These effects appear to involve Distal-less (Dlx) protein activity, as loss of dlx3b and dlx4b suppresses ventralization in Msx-depleted embryos. At the same time, Msx-depletion restores normal preplacodal gene expression to dlx3b-dlx4b mutants. These data suggest that mutual antagonism between Msx and Dlx proteins achieves a balance of function required for normal preplacodal differentiation and placement of the neural-nonneural border.

  2. Hurricane Sandy Exposure Alters the Development of Neural Reactivity to Negative Stimuli in Children.

    Science.gov (United States)

    Kessel, Ellen M; Nelson, Brady D; Kujawa, Autumn; Hajcak, Greg; Kotov, Roman; Bromet, Evelyn J; Carlson, Gabrielle A; Klein, Daniel N

    2018-03-01

    This study examined whether exposure to Hurricane Sandy-related stressors altered children's brain response to emotional information. An average of 8 months (M age  = 9.19) before and 9 months after (M age  = 10.95) Hurricane Sandy, 77 children experiencing high (n = 37) and low (n = 40) levels of hurricane-related stress exposure completed a task in which the late positive potential, a neural index of emotional reactivity, was measured in response to pleasant and unpleasant, compared to neutral, images. From pre- to post-Hurricane Sandy, children with high stress exposure failed to show the same decrease in emotional reactivity to unpleasant versus neutral stimuli as those with low stress exposure. Results provide compelling evidence that exposure to natural disaster-related stressors alters neural emotional reactivity to negatively valenced information. © 2016 The Authors. Child Development © 2016 Society for Research in Child Development, Inc.

  3. USE OF DASHBOARDS IN PREDICTING THE DEVELOPMENT OF THE COMPANY USING NEURAL NETWORKS IN HOTEL MANAGEMENT

    Directory of Open Access Journals (Sweden)

    Peter GALLO

    2018-04-01

    Full Text Available Tourism development currently represents a very important part of national economics and its development and growth. To ensure growth, managers are looking for new effective tools to optimize decision making. This paper addresses the issue of dashboards based on neural networks and their utilization in managerial decision-making processes. Dashboard based reporting is oriented towards the tourism sector in Slovakia. The result of the research is the proposed balanced ranking and prediction model using financial and nonfinancial indicators with the application of artificial intelligence which allows to reach high level of efficiency and accuracy in evaluation of financial and nonfinancial health of companies operating in the hospitality sector. The proposed model also brings a new managerial and scientific point of view on the in-depth analysis of performance of these facilities. The main function of the proposed model is to classify health of a hotel. For this purpose, the MLP (Multi-Layer Perceptron feedforward artificial neural network using backward propagation of errors was chosen as a training method.

  4. Development of Sorting System for Fishes by Feed-forward Neural Networks Using Rotation Invariant Features

    Science.gov (United States)

    Shiraishi, Yuhki; Takeda, Fumiaki

    In this research, we have developed a sorting system for fishes, which is comprised of a conveyance part, a capturing image part, and a sorting part. In the conveyance part, we have developed an independent conveyance system in order to separate one fish from an intertwined group of fishes. After the image of the separated fish is captured in the capturing part, a rotation invariant feature is extracted using two-dimensional fast Fourier transform, which is the mean value of the power spectrum with the same distance from the origin in the spectrum field. After that, the fishes are classified by three-layered feed-forward neural networks. The experimental results show that the developed system classifies three kinds of fishes captured in various angles with the classification ratio of 98.95% for 1044 captured images of five fishes. The other experimental results show the classification ratio of 90.7% for 300 fishes by 10-fold cross validation method.

  5. Limited distal organelles and synaptic function in extensive monoaminergic innervation.

    Science.gov (United States)

    Tao, Juan; Bulgari, Dinara; Deitcher, David L; Levitan, Edwin S

    2017-08-01

    Organelles such as neuropeptide-containing dense-core vesicles (DCVs) and mitochondria travel down axons to supply synaptic boutons. DCV distribution among en passant boutons in small axonal arbors is mediated by circulation with bidirectional capture. However, it is not known how organelles are distributed in extensive arbors associated with mammalian dopamine neuron vulnerability, and with volume transmission and neuromodulation by monoamines and neuropeptides. Therefore, we studied presynaptic organelle distribution in Drosophila octopamine neurons that innervate ∼20 muscles with ∼1500 boutons. Unlike in smaller arbors, distal boutons in these arbors contain fewer DCVs and mitochondria, although active zones are present. Absence of vesicle circulation is evident by proximal nascent DCV delivery, limited impact of retrograde transport and older distal DCVs. Traffic studies show that DCV axonal transport and synaptic capture are not scaled for extensive innervation, thus limiting distal delivery. Activity-induced synaptic endocytosis and synaptic neuropeptide release are also reduced distally. We propose that limits in organelle transport and synaptic capture compromise distal synapse maintenance and function in extensive axonal arbors, thereby affecting development, plasticity and vulnerability to neurodegenerative disease. © 2017. Published by The Company of Biologists Ltd.

  6. Synaptic contacts impaired by styrene-7,8-oxide toxicity

    International Nuclear Information System (INIS)

    Corsi, P.; D'Aprile, A.; Nico, B.; Costa, G.L.; Assennato, G.

    2007-01-01

    Styrene-7,8-oxide (SO), a chemical compound widely used in industrial applications, is a potential hazard for humans, particularly in occupational settings. Neurobehavioral changes are consistently observed in occupationally exposed individuals and alterations of neurotransmitters associated with neuronal loss have been reported in animal models. Although the toxic effects of styrene have been extensively documented, the molecular mechanisms responsible for SO-induced neurotoxicity are still unclear. A possible dopamine-mediated effect of styrene neurotoxicity has been previously demonstrated, since styrene oxide alters dopamine neurotransmission in the brain. Thus, the present study hypothesizes that styrene neurotoxicity may involve synaptic contacts. Primary striatal neurons were exposed to styrene oxide at different concentrations (0.1-1 mM) for different time periods (8, 16, and 24 h) to evaluate the dose able to induce synaptic impairments. The expression of proteins crucial for synaptic transmission such as Synapsin, Synaptophysin, and RAC-1 were considered. The levels of Synaptophysin and RAC-1 decreased in a dose-dependent manner. Accordingly, morphological alterations, observed at the ultrastructural level, primarily involved the pre-synaptic compartment. In SO-exposed cultures, the biochemical cascade of caspases was activated affecting the cytoskeleton components as their target. Thus the impairments in synaptic contacts observed in SO-exposed cultures might reflect a primarily morphological alteration of neuronal cytoskeleton. In addition, our data support the hypothesis developed by previous authors of reactive oxygen species (ROS) initiating events of SO cytotoxicity

  7. Development of teeth in chick embryos after mouse neural crest transplantations.

    Science.gov (United States)

    Mitsiadis, Thimios A; Chéraud, Yvonnick; Sharpe, Paul; Fontaine-Pérus, Josiane

    2003-05-27

    Teeth were lost in birds 70-80 million years ago. Current thinking holds that it is the avian cranial neural crest-derived mesenchyme that has lost odontogenic capacity, whereas the oral epithelium retains the signaling properties required to induce odontogenesis. To investigate the odontogenic capacity of ectomesenchyme, we have used neural tube transplantations from mice to chick embryos to replace the chick neural crest cell populations with mouse neural crest cells. The mouse/chick chimeras obtained show evidence of tooth formation showing that avian oral epithelium is able to induce a nonavian developmental program in mouse neural crest-derived mesenchymal cells.

  8. Design principles of electrical synaptic plasticity.

    Science.gov (United States)

    O'Brien, John

    2017-09-08

    Essentially all animals with nervous systems utilize electrical synapses as a core element of communication. Electrical synapses, formed by gap junctions between neurons, provide rapid, bidirectional communication that accomplishes tasks distinct from and complementary to chemical synapses. These include coordination of neuron activity, suppression of voltage noise, establishment of electrical pathways that define circuits, and modulation of high order network behavior. In keeping with the omnipresent demand to alter neural network function in order to respond to environmental cues and perform tasks, electrical synapses exhibit extensive plasticity. In some networks, this plasticity can have dramatic effects that completely remodel circuits or remove the influence of certain cell types from networks. Electrical synaptic plasticity occurs on three distinct time scales, ranging from milliseconds to days, with different mechanisms accounting for each. This essay highlights principles that dictate the properties of electrical coupling within networks and the plasticity of the electrical synapses, drawing examples extensively from retinal networks. Copyright © 2017 The Author. Published by Elsevier B.V. All rights reserved.

  9. Robust Short-Term Memory without Synaptic Learning

    Science.gov (United States)

    Johnson, Samuel; Marro, J.; Torres, Joaquín J.

    2013-01-01

    Short-term memory in the brain cannot in general be explained the way long-term memory can – as a gradual modification of synaptic weights – since it takes place too quickly. Theories based on some form of cellular bistability, however, do not seem able to account for the fact that noisy neurons can collectively store information in a robust manner. We show how a sufficiently clustered network of simple model neurons can be instantly induced into metastable states capable of retaining information for a short time (a few seconds). The mechanism is robust to different network topologies and kinds of neural model. This could constitute a viable means available to the brain for sensory and/or short-term memory with no need of synaptic learning. Relevant phenomena described by neurobiology and psychology, such as local synchronization of synaptic inputs and power-law statistics of forgetting avalanches, emerge naturally from this mechanism, and we suggest possible experiments to test its viability in more biological settings. PMID:23349664

  10. Robust short-term memory without synaptic learning.

    Directory of Open Access Journals (Sweden)

    Samuel Johnson

    Full Text Available Short-term memory in the brain cannot in general be explained the way long-term memory can--as a gradual modification of synaptic weights--since it takes place too quickly. Theories based on some form of cellular bistability, however, do not seem able to account for the fact that noisy neurons can collectively store information in a robust manner. We show how a sufficiently clustered network of simple model neurons can be instantly induced into metastable states capable of retaining information for a short time (a few seconds. The mechanism is robust to different network topologies and kinds of neural model. This could constitute a viable means available to the brain for sensory and/or short-term memory with no need of synaptic learning. Relevant phenomena described by neurobiology and psychology, such as local synchronization of synaptic inputs and power-law statistics of forgetting avalanches, emerge naturally from this mechanism, and we suggest possible experiments to test its viability in more biological settings.

  11. Robust short-term memory without synaptic learning.

    Science.gov (United States)

    Johnson, Samuel; Marro, J; Torres, Joaquín J

    2013-01-01

    Short-term memory in the brain cannot in general be explained the way long-term memory can--as a gradual modification of synaptic weights--since it takes place too quickly. Theories based on some form of cellular bistability, however, do not seem able to account for the fact that noisy neurons can collectively store information in a robust manner. We show how a sufficiently clustered network of simple model neurons can be instantly induced into metastable states capable of retaining information for a short time (a few seconds). The mechanism is robust to different network topologies and kinds of neural model. This could constitute a viable means available to the brain for sensory and/or short-term memory with no need of synaptic learning. Relevant phenomena described by neurobiology and psychology, such as local synchronization of synaptic inputs and power-law statistics of forgetting avalanches, emerge naturally from this mechanism, and we suggest possible experiments to test its viability in more biological settings.

  12. Evolution of the aging brain transcriptome and synaptic regulation.

    Directory of Open Access Journals (Sweden)

    Patrick M Loerch

    Full Text Available Alzheimer's disease and other neurodegenerative disorders of aging are characterized by clinical and pathological features that are relatively specific to humans. To obtain greater insight into how brain aging has evolved, we compared age-related gene expression changes in the cortex of humans, rhesus macaques, and mice on a genome-wide scale. A small subset of gene expression changes are conserved in all three species, including robust age-dependent upregulation of the neuroprotective gene apolipoprotein D (APOD and downregulation of the synaptic cAMP signaling gene calcium/calmodulin-dependent protein kinase IV (CAMK4. However, analysis of gene ontology and cell type localization shows that humans and rhesus macaques have diverged from mice due to a dramatic increase in age-dependent repression of neuronal genes. Many of these age-regulated neuronal genes are associated with synaptic function. Notably, genes associated with GABA-ergic inhibitory function are robustly age-downregulated in humans but not in mice at the level of both mRNA and protein. Gene downregulation was not associated with overall neuronal or synaptic loss. Thus, repression of neuronal gene expression is a prominent and recently evolved feature of brain aging in humans and rhesus macaques that may alter neural networks and contribute to age-related cognitive changes.

  13. Postnatal Ablation of Synaptic Retinoic Acid Signaling Impairs Cortical Information Processing and Sensory Discrimination in Mice.

    Science.gov (United States)

    Park, Esther; Tjia, Michelle; Zuo, Yi; Chen, Lu

    2018-06-06

    Retinoic acid (RA) and its receptors (RARs) are well established essential transcriptional regulators during embryonic development. Recent findings in cultured neurons identified an independent and critical post-transcriptional role of RA and RARα in the homeostatic regulation of excitatory and inhibitory synaptic transmission in mature neurons. However, the functional relevance of synaptic RA signaling in vivo has not been established. Here, using somatosensory cortex as a model system and the RARα conditional knock-out mouse as a tool, we applied multiple genetic manipulations to delete RARα postnatally in specific populations of cortical neurons, and asked whether synaptic RA signaling observed in cultured neurons is involved in cortical information processing in vivo Indeed, conditional ablation of RARα in mice via a CaMKIIα-Cre or a layer 5-Cre driver line or via somatosensory cortex-specific viral expression of Cre-recombinase impaired whisker-dependent texture discrimination, suggesting a critical requirement of RARα expression in L5 pyramidal neurons of somatosensory cortex for normal tactile sensory processing. Transcranial two-photon imaging revealed a significant increase in dendritic spine elimination on apical dendrites of somatosensory cortical layer 5 pyramidal neurons in these mice. Interestingly, the enhancement of spine elimination is whisker experience-dependent as whisker trimming rescued the spine elimination phenotype. Additionally, experiencing an enriched environment improved texture discrimination in RARα-deficient mice and reduced excessive spine pruning. Thus, RA signaling is essential for normal experience-dependent cortical circuit remodeling and sensory processing. SIGNIFICANCE STATEMENT The importance of synaptic RA signaling has been demonstrated in in vitro studies. However, whether RA signaling mediated by RARα contributes to neural circuit functions in vivo remains largely unknown. In this study, using a RARα conditional

  14. Synaptic proteins and receptors defects in autism spectrum disorders

    Directory of Open Access Journals (Sweden)

    Jianling eChen

    2014-09-01

    Full Text Available Recent studies have found that hundreds of genetic variants, including common and rare variants, rare and de novo mutations, and common polymorphisms have contributed to the occurrence of autism spectrum disorders (ASDs. The mutations in a number of genes such as neurexin, neuroligin, postsynaptic density protein 95 (PSD-95, SH3 and multiple ankyrin repeat domains 3 (SHANK3, synapsin, gephyrin, cadherin (CDH and protocadherin (PCDH, thousand-and-one-amino acid 2 kinase (TAOK2, and contactin (CNTN, have been shown to play important roles in the development and function of synapses. In addition, synaptic receptors, such as gamma-aminobutyric acid (GABA receptors and glutamate receptors, have also been associated with ASDs. This review will primarily focus on the defects of synaptic proteins and receptors associated with ASDs and their roles in the pathogenesis of ASDs via synaptic pathways.

  15. Interregional synaptic maps among engram cells underlie memory formation.

    Science.gov (United States)

    Choi, Jun-Hyeok; Sim, Su-Eon; Kim, Ji-Il; Choi, Dong Il; Oh, Jihae; Ye, Sanghyun; Lee, Jaehyun; Kim, TaeHyun; Ko, Hyoung-Gon; Lim, Chae-Seok; Kaang, Bong-Kiun

    2018-04-27

    Memory resides in engram cells distributed across the brain. However, the site-specific substrate within these engram cells remains theoretical, even though it is generally accepted that synaptic plasticity encodes memories. We developed the dual-eGRASP (green fluorescent protein reconstitution across synaptic partners) technique to examine synapses between engram cells to identify the specific neuronal site for memory storage. We found an increased number and size of spines on CA1 engram cells receiving input from CA3 engram cells. In contextual fear conditioning, this enhanced connectivity between engram cells encoded memory strength. CA3 engram to CA1 engram projections strongly occluded long-term potentiation. These results indicate that enhanced structural and functional connectivity between engram cells across two directly connected brain regions forms the synaptic correlate for memory formation. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

  16. PRRT2: from Paroxysmal Disorders to Regulation of Synaptic Function.

    Science.gov (United States)

    Valtorta, Flavia; Benfenati, Fabio; Zara, Federico; Meldolesi, Jacopo

    2016-10-01

    In the past few years, proline-rich transmembrane protein (PRRT)2 has been identified as the causative gene for several paroxysmal neurological disorders. Recently, an important role of PRRT2 in synapse development and function has emerged. Knock down of the protein strongly impairs the formation of synaptic contacts and neurotransmitter release. At the nerve terminal, PRRT2 endows synaptic vesicle exocytosis with Ca 2+ sensitivity by interacting with proteins of the fusion complex and with the Ca 2+ sensors synaptotagmins (Syts). In the postsynaptic compartment, PRRT2 interacts with glutamate receptors. The study of PRRT2 and of its mutations may help in refining our knowledge of the process of synaptic transmission and elucidating the pathogenetic mechanisms leading to derangement of network function in paroxysmal disorders. Copyright © 2016 Elsevier Ltd. All rights reserved.

  17. Inca: a novel p21-activated kinase-associated protein required for cranial neural crest development.

    Science.gov (United States)

    Luo, Ting; Xu, Yanhua; Hoffman, Trevor L; Zhang, Tailin; Schilling, Thomas; Sargent, Thomas D

    2007-04-01

    Inca (induced in neural crest by AP2) is a novel protein discovered in a microarray screen for genes that are upregulated in Xenopus embryos by the transcriptional activator protein Tfap2a. It has no significant similarity to any known protein, but is conserved among vertebrates. In Xenopus, zebrafish and mouse embryos, Inca is expressed predominantly in the premigratory and migrating neural crest (NC). Knockdown experiments in frog and fish using antisense morpholinos reveal essential functions for Inca in a subset of NC cells that form craniofacial cartilage. Cells lacking Inca migrate successfully but fail to condense into skeletal primordia. Overexpression of Inca disrupts cortical actin and prevents formation of actin "purse strings", which are required for wound healing in Xenopus embryos. We show that Inca physically interacts with p21-activated kinase 5 (PAK5), a known regulator of the actin cytoskeleton that is co-expressed with Inca in embryonic ectoderm, including in the NC. These results suggest that Inca and PAK5 cooperate in restructuring cytoskeletal organization and in the regulation of cell adhesion in the early embryo and in NC cells during craniofacial development.

  18. 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

  19. Development of social skills in children: neural and behavioral evidence for the elaboration of cognitive models

    Science.gov (United States)

    Soto-Icaza, Patricia; Aboitiz, Francisco; Billeke, Pablo

    2015-01-01

    Social skills refer to a wide group of abilities that allow us to interact and communicate with others. Children learn how to solve social situations by predicting and understanding other's behaviors. The way in which humans learn to interact successfully with others encompasses a complex interaction between neural, behavioral, and environmental elements. These have a role in the accomplishment of positive developmental outcomes, including peer acceptance, academic achievement, and mental health. All these social abilities depend on widespread brain networks that are recently being studied by neuroscience. In this paper, we will first review the studies on this topic, aiming to clarify the behavioral and neural mechanisms related to the acquisition of social skills during infancy and their appearance in time. Second, we will briefly describe how developmental diseases like Autism Spectrum Disorders (ASD) can inform about the neurobiological mechanisms of social skills. We finally sketch a general framework for the elaboration of cognitive models in order to facilitate the comprehension of human social development. PMID:26483621

  20. Learning Structure of Sensory Inputs with Synaptic Plasticity Leads to Interference

    Directory of Open Access Journals (Sweden)

    Joseph eChrol-Cannon

    2015-08-01

    Full Text Available Synaptic plasticity is often explored as a form of unsupervised adaptationin cortical microcircuits to learn the structure of complex sensoryinputs and thereby improve performance of classification and prediction. The question of whether the specific structure of the input patterns is encoded in the structure of neural networks has been largely neglected. Existing studies that have analyzed input-specific structural adaptation have used simplified, synthetic inputs in contrast to complex and noisy patterns found in real-world sensory data.In this work, input-specific structural changes are analyzed forthree empirically derived models of plasticity applied to three temporal sensory classification tasks that include complex, real-world visual and auditory data. Two forms of spike-timing dependent plasticity (STDP and the Bienenstock-Cooper-Munro (BCM plasticity rule are used to adapt the recurrent network structure during the training process before performance is tested on the pattern recognition tasks.It is shown that synaptic adaptation is highly sensitive to specific classes of input pattern. However, plasticity does not improve the performance on sensory pattern recognition tasks, partly due to synaptic interference between consecutively presented input samples. The changes in synaptic strength produced by one stimulus are reversed by thepresentation of another, thus largely preventing input-specific synaptic changes from being retained in the structure of the network.To solve the problem of interference, we suggest that models of plasticitybe extended to restrict neural activity and synaptic modification to a subset of the neural circuit, which is increasingly found to be the casein experimental neuroscience.

  1. Emergence of Functional Specificity in Balanced Networks with Synaptic Plasticity.

    Directory of Open Access Journals (Sweden)

    Sadra Sadeh

    2015-06-01

    Full Text Available In rodent visual cortex, synaptic connections between orientation-selective neurons are unspecific at the time of eye opening, and become to some degree functionally specific only later during development. An explanation for this two-stage process was proposed in terms of Hebbian plasticity based on visual experience that would eventually enhance connections between neurons with similar response features. For this to work, however, two conditions must be satisfied: First, orientation selective neuronal responses must exist before specific recurrent synaptic connections can be established. Second, Hebbian learning must be compatible with the recurrent network dynamics contributing to orientation selectivity, and the resulting specific connectivity must remain stable for unspecific background activity. Previous studies have mainly focused on very simple models, where the receptive fields of neurons were essentially determined by feedforward mechanisms, and where the recurrent network was small, lacking the complex recurrent dynamics of large-scale networks of excitatory and inhibitory neurons. Here we studied the emergence of functionally specific connectivity in large-scale recurrent networks with synaptic plasticity. Our results show that balanced random networks, which already exhibit highly selective responses at eye opening, can develop feature-specific connectivity if appropriate rules of synaptic plasticity are invoked within and between excitatory and inhibitory populations. If these conditions are met, the initial orientation selectivity guides the process of Hebbian learning and, as a result, functionally specific and a surplus of bidirectional connections emerge. Our results thus demonstrate the cooperation of synaptic plasticity and recurrent dynamics in large-scale functional networks with realistic receptive fields, highlight the role of inhibition as a critical element in this process, and paves the road for further computational

  2. Hardwiring of fine synaptic layers in the zebrafish visual pathway

    Directory of Open Access Journals (Sweden)

    Taylor Michael R

    2008-12-01

    Full Text Available Abstract Background Neuronal connections are often arranged in layers, which are divided into sublaminae harboring synapses with similar response properties. It is still debated how fine-grained synaptic layering is established during development. Here we investigated two stratified areas of the zebrafish visual pathway, the inner plexiform layer (IPL of the retina and the neuropil of the optic tectum, and determined if activity is required for their organization. Results The IPL of 5-day-old zebrafish larvae is composed of at least nine sublaminae, comprising the connections between different types of amacrine, bipolar, and ganglion cells (ACs, BCs, GCs. These sublaminae were distinguished by their expression of cell type-specific transgenic fluorescent reporters and immunohistochemical markers, including protein kinase Cβ (PKC, parvalbumin (Parv, zrf3, and choline acetyltransferase (ChAT. In the tectum, four retinal input layers abut a laminated array of neurites of tectal cells, which differentially express PKC and Parv. We investigated whether these patterns were affected by experimental disruptions of retinal activity in developing fish. Neither elimination of light inputs by dark rearing, nor a D, L-amino-phosphono-butyrate-induced reduction in the retinal response to light onset (but not offset altered IPL or tectal lamination. Moreover, thorough elimination of chemical synaptic transmission with Botulinum toxin B left laminar synaptic arrays intact. Conclusion Our results call into question a role for activity-dependent mechanisms – instructive light signals, balanced on and off BC activity, Hebbian plasticity, or a permissive role for synaptic transmission – in the synaptic stratification we examined. We propose that genetically encoded cues are sufficient to target groups of neurites to synaptic layers in this vertebrate visual system.

  3. SpikingLab: modelling agents controlled by Spiking Neural Networks in Netlogo.

    Science.gov (United States)

    Jimenez-Romero, Cristian; Johnson, Jeffrey

    2017-01-01

    The scientific interest attracted by Spiking Neural Networks (SNN) has lead to the development of tools for the simulation and study of neuronal dynamics ranging from phenomenological models to the more sophisticated and biologically accurate Hodgkin-and-Huxley-based and multi-compartmental models. However, despite the multiple features offered by neural modelling tools, their integration with environments for the simulation of robots and agents can be challenging and time consuming. The implementation of artificial neural circuits to control robots generally involves the following tasks: (1) understanding the simulation tools, (2) creating the neural circuit in the neural simulator, (3) linking the simulated neural circuit with the environment of the agent and (4) programming the appropriate interface in the robot or agent to use the neural controller. The accomplishment of the above-mentioned tasks can be challenging, especially for undergraduate students or novice researchers. This paper presents an alternative tool which facilitates the simulation of simple SNN circuits using the multi-agent simulation and the programming environment Netlogo (educational software that simplifies the study and experimentation of complex systems). The engine proposed and implemented in Netlogo for the simulation of a functional model of SNN is a simplification of integrate and fire (I&F) models. The characteristics of the engine (including neuronal dynamics, STDP learning and synaptic delay) are demonstrated through the implementation of an agent representing an artificial insect controlled by a simple neural circuit. The setup of the experiment and its outcomes are described in this work.

  4. Controllable SET process in O-Ti-Sb-Te based phase change memory for synaptic application

    Science.gov (United States)

    Ren, Kun; Li, Ruiheng; Chen, Xin; Wang, Yong; Shen, Jiabin; Xia, Mengjiao; Lv, Shilong; Ji, Zhenguo; Song, Zhitang

    2018-02-01

    The nonlinear resistance change and small bit resolution of phase change memory (PCM) under identical operation pulses will limit its performance as a synaptic device. The octahedral Ti-Te units in Ti-Sb-Te, regarded as nucleation seeds, are degenerated when Ti is bonded with O, causing a slower crystallization and a controllable SET process in PCM cells. A linear resistance change under identical pulses, a resolution of ˜8 bits, and an ON/OFF ratio of ˜102 has been achieved in O-Ti-Sb-Te based PCM, showing its potential application as a synaptic device to improve recognition performance of the neural network.

  5. Predictions on the Development Dimensions of Provincial Tourism Discipline Based on the Artificial Neural Network BP Model

    Science.gov (United States)

    Yang, Yang; Hu, Jun; Lv, Yingchun; Zhang, Mu

    2013-01-01

    As the tourism industry has gradually become the strategic mainstay industry of the national economy, the scope of the tourism discipline has developed rigorously. This paper makes a predictive study on the development of the scope of Guangdong provincial tourism discipline based on the artificial neural network BP model in order to find out how…

  6. Effects of topography on the functional development of human neural progenitor cells.

    Science.gov (United States)

    Wu, Ze-Zhi; Kisaalita, William S; Wang, Lina; Zachman, Angela L; Zhao, Yiping; Hasneen, Kowser; Machacek, Dave; Stice, Steven L

    2010-07-01

    We have fabricated a topographical substrate with a packed polystyrene bead array for the development of cell-based assay systems targeting voltage-gated calcium channels (VGCCs). Human neural progenitor cells (H945RB.3) cultured on both flat and topographical substrates were analyzed in terms of morphological spreading, neuronal commitment, resting membrane potential (V(m)) establishment and VGCC function development. We found, by SEM imaging, that arrayed substrates, formed with both sub-micrometer (of 0.51 microm in mean diameter) and micrometer (of 1.98 microm in mean diameter) beads, were capable of promoting the spreading of the progenitor cells as compared with the flat polystyrene surfaces. With the micrometer beads, it was found that arrayed substrates facilitated the neural progenitor cells' maintenance of less negative V(m) values upon differentiation with bFGF starvation, which favored predominant neuronal commitment. Almost all the progenitor cells were responsive to 50 mM K(+) depolarization with an increase in [Ca(2+)](i) either before or upon differentiation, suggesting the expression of functional VGCCs. Compared to the flat polystyrene surfaces, microbead arrayed substrates facilitated the development of higher VGCC responsiveness by the progenitor cells upon differentiation. The enhancement of both VGCC responsiveness and cell spreading by arrays of micrometer beads was most significant on day 14 into differentiation, which was the latest time point of measurement in this study. This study thus rationalized the possibility for future substrate topography engineering to manipulate ion channel function and to meet the challenge of low VGCC responsiveness found in early drug discovery.

  7. Development of an ultrasonic weld inspection system based on image processing and neural networks

    Science.gov (United States)

    Roca Barceló, Fernando; Jaén del Hierro, Pedro; Ribes Llario, Fran; Real Herráiz, Julia

    2018-04-01

    Several types of discontinuities and defects may be present on a weld, thus leading to a considerable reduction of its resistance. Therefore, ensuring a high welding quality and reliability has become a matter of key importance for many construction and industrial activities. Among the non-destructive weld testing and inspection techniques, the time-of-flight diffraction (TOFD) arises as a very safe (no ionising radiation), precise, reliable and versatile practice. However, this technique presents a relevant drawback, associated to the appearance of speckle noise that should be addressed. In this regard, this paper presents a new, intelligent and automatic method for weld inspection and analysis, based on TOFD, image processing and neural networks. The developed system is capable of detecting weld defects and imperfections with accuracy, and classify them into different categories.

  8. First step in developing SWNT nano-sensor for C17.2 neural stem cells

    Science.gov (United States)

    Ignatova, Tetyana; Pirbhai, Massooma; Chandrasekar, Swetha; Rotkin, Slava V.; Jedlicka, Sabrina

    Nanomaterials are widely used for biomedical applications and diagnostics, including as drug and gene delivery agents, imaging objects, and biosensors. As single-wall carbon nanotubes (SWNTs) possess a size similar to intracellular components, including fibrillar proteins and some organelles, the potential for use in a wide variety of intracellular applications is significant. However, implementation of an SWNT based nano-sensor is difficult due to lack of understanding of SWNT-cell interaction on both the cellular and molecular level. In this study, C17.2 neural stem cells have been tested after uptake of SWNTs wrapped with ssDNA over a wide variety of time periods, allowing for broad localization of SWNTs inside of the cells over long time periods. The localization data is being used to develop a predictive model of how, upon uptake of SWNT, the cytoskeleton and other cellular structures of the adherent cells is perturbed.

  9. Glutamatergic synaptic plasticity in the mesocorticolimbic system in addiction.

    NARCIS (Netherlands)

    van Huijstee, A.N.; Mansvelder, H.D.

    2015-01-01

    Addictive drugs remodel the brain’s reward circuitry, the mesocorticolimbic dopamine (DA) system, by inducing widespread adaptations of glutamatergic synapses. This drug-induced synaptic plasticity is thought to contribute to both the development and the persistence of addiction. This review

  10. GABA and Gap Junctions in the Development of Synchronized Activity in Human Pluripotent Stem Cell-Derived Neural Networks

    Directory of Open Access Journals (Sweden)

    Meeri Eeva-Liisa Mäkinen

    2018-03-01

    Full Text Available The electrical activity of the brain arises from single neurons communicating with each other. However, how single neurons interact during early development to give rise to neural network activity remains poorly understood. We studied the emergence of synchronous neural activity in human pluripotent stem cell (hPSC-derived neural networks simultaneously on a single-neuron level and network level. The contribution of gamma-aminobutyric acid (GABA and gap junctions to the development of synchronous activity in hPSC-derived neural networks was studied with GABA agonist and antagonist and by blocking gap junctional communication, respectively. We characterized the dynamics of the network-wide synchrony in hPSC-derived neural networks with high spatial resolution (calcium imaging and temporal resolution microelectrode array (MEA. We found that the emergence of synchrony correlates with a decrease in very strong GABA excitation. However, the synchronous network was found to consist of a heterogeneous mixture of synchronously active cells with variable responses to GABA, GABA agonists and gap junction blockers. Furthermore, we show how single-cell distributions give rise to the network effect of GABA, GABA agonists and gap junction blockers. Finally, based on our observations, we suggest that the earliest form of synchronous neuronal activity depends on gap junctions and a decrease in GABA induced depolarization but not on GABAA mediated signaling.

  11. GABA and Gap Junctions in the Development of Synchronized Activity in Human Pluripotent Stem Cell-Derived Neural Networks

    Science.gov (United States)

    Mäkinen, Meeri Eeva-Liisa; Ylä-Outinen, Laura; Narkilahti, Susanna

    2018-01-01

    The electrical activity of the brain arises from single neurons communicating with each other. However, how single neurons interact during early development to give rise to neural network activity remains poorly understood. We studied the emergence of synchronous neural activity in human pluripotent stem cell (hPSC)-derived neural networks simultaneously on a single-neuron level and network level. The contribution of gamma-aminobutyric acid (GABA) and gap junctions to the development of synchronous activity in hPSC-derived neural networks was studied with GABA agonist and antagonist and by blocking gap junctional communication, respectively. We characterized the dynamics of the network-wide synchrony in hPSC-derived neural networks with high spatial resolution (calcium imaging) and temporal resolution microelectrode array (MEA). We found that the emergence of synchrony correlates with a decrease in very strong GABA excitation. However, the synchronous network was found to consist of a heterogeneous mixture of synchronously active cells with variable responses to GABA, GABA agonists and gap junction blockers. Furthermore, we show how single-cell distributions give rise to the network effect of GABA, GABA agonists and gap junction blockers. Finally, based on our observations, we suggest that the earliest form of synchronous neuronal activity depends on gap junctions and a decrease in GABA induced depolarization but not on GABAA mediated signaling. PMID:29559893

  12. Evaluating the negative or valuing the positive? Neural mechanisms supporting feedback-based learning across development.

    Science.gov (United States)

    van Duijvenvoorde, Anna C K; Zanolie, Kiki; Rombouts, Serge A R B; Raijmakers, Maartje E J; Crone, Eveline A

    2008-09-17

    How children learn from positive and negative performance feedback lies at the foundation of successful learning and is therefore of great importance for educational practice. In this study, we used functional magnetic resonance imaging (fMRI) to examine the neural developmental changes related to feedback-based learning when performing a rule search and application task. Behavioral results from three age groups (8-9, 11-13, and 18-25 years of age) demonstrated that, compared with adults, 8- to 9-year-old children performed disproportionally more inaccurately after receiving negative feedback relative to positive feedback. Additionally, imaging data pointed toward a qualitative difference in how children and adults use performance feedback. That is, dorsolateral prefrontal cortex and superior parietal cortex were more active after negative feedback for adults, but after positive feedback for children (8-9 years of age). For 11- to 13-year-olds, these regions did not show differential feedback sensitivity, suggesting that the transition occurs around this age. Pre-supplementary motor area/anterior cingulate cortex, in contrast, was more active after negative feedback in both 11- to 13-year-olds and adults, but not 8- to 9-year-olds. Together, the current data show that cognitive control areas are differentially engaged during feedback-based learning across development. Adults engage these regions after signals of response adjustment (i.e., negative feedback). Young children engage these regions after signals of response continuation (i.e., positive feedback). The neural activation patterns found in 11- to 13-year-olds indicate a transition around this age toward an increased influence of negative feedback on performance adjustment. This is the first developmental fMRI study to compare qualitative changes in brain activation during feedback learning across distinct stages of development.

  13. Adolescent development of context-dependent stimulus-reward association memory and its neural correlates.

    Science.gov (United States)

    Voss, Joel L; O'Neil, Jonathan T; Kharitonova, Maria; Briggs-Gowan, Margaret J; Wakschlag, Lauren S

    2015-01-01

    Expression of learned stimulus-reward associations based on context is essential for regulation of behavior to meet situational demands. Contextual regulation improves during development, although the developmental progression of relevant neural and cognitive processes is not fully specified. We therefore measured neural correlates of flexible, contextual expression of stimulus-reward associations in pre/early-adolescent children (ages 9-13 years) and young adults (ages 19-22 years). After reinforcement learning using standard parameters, a contextual reversal manipulation was used whereby contextual cues indicated that stimulus-reward associations were the same as previously reinforced for some trials (consistent trials) or were reversed on other trials (inconsistent trials). Subjects were thus required to respond according to original stimulus-reward associations vs. reversed associations based on trial-specific contextual cues. Children and young adults did not differ in reinforcement learning or in relevant functional magnetic resonance imaging (fMRI) correlates. In contrast, adults outperformed children during contextual reversal, with better performance specifically for inconsistent trials. fMRI signals corresponding to this selective advantage included greater activity in lateral prefrontal cortex (LPFC), hippocampus, and dorsal striatum for young adults relative to children. Flexible expression of stimulus-reward associations based on context thus improves via adolescent development, as does recruitment of brain regions involved in reward learning and contextual expression of memory. HighlightsEarly-adolescent children and young adults were equivalent in reinforcement learning.Adults outperformed children in contextual expression of stimulus-reward associations.Adult advantages correlated with increased activity of relevant brain regions.Specific neurocognitive developmental changes support better contextual regulation.

  14. Postotic and preotic cranial neural crest cells differently contribute to thyroid development.

    Science.gov (United States)

    Maeda, Kazuhiro; Asai, Rieko; Maruyama, Kazuaki; Kurihara, Yukiko; Nakanishi, Toshio; Kurihara, Hiroki; Miyagawa-Tomita, Sachiko

    2016-01-01

    Thyroid development and formation vary among species, but in most species the thyroid morphogenesis consists of five stages: specification, budding, descent, bilobation and folliculogenesis. The detailed mechanisms of these stages have not been fully clarified. During early development, the cranial neural crest (CNC) contributes to the thyroid gland. The removal of the postotic CNC (corresponding to rhombomeres 6, 7 and 8, also known as the cardiac neural crest) results in abnormalities of the cardiovascular system, thymus, parathyroid glands, and thyroid gland. To investigate the influence of the CNC on thyroid bilobation process, we divided the CNC into two regions, the postotic CNC and the preotic CNC (from the mesencephalon to rhombomere 5) regions and examined. We found that preotic CNC-ablated embryos had a unilateral thyroid lobe, and confirmed the presence of a single lobe or the absence of lobes in postotic CNC-ablated chick embryos. The thyroid anlage in each region-ablated embryos was of a normal size at the descent stage, but at a later stage, the thyroid in preotic CNC-ablated embryos was of a normal size, conflicting with a previous report in which the thyroid was reduced in size in the postotic CNC-ablated embryos. The postotic CNC cells differentiated into connective tissues of the thyroid in quail-to-chick chimeras. In contrast, the preotic CNC cells did not differentiate into connective tissues of the thyroid. We found that preotic CNC cells encompassed the thyroid anlage from the specification stage to the descent stage. Finally, we found that endothelin-1 and endothelin type A receptor-knockout mice and bosentan (endothelin receptor antagonist)-treated chick embryos showed bilobation anomalies that included single-lobe formation. Therefore, not only the postotic CNC, but also the preotic CNC plays an important role in thyroid morphogenesis. Copyright © 2015 Elsevier Inc. All rights reserved.

  15. Neural crest contribution to lingual mesenchyme, epithelium and developing taste papillae and taste buds.

    Science.gov (United States)

    Liu, Hong-Xiang; Komatsu, Yoshihiro; Mishina, Yuji; Mistretta, Charlotte M

    2012-08-15

    The epithelium of mammalian tongue hosts most of the taste buds that transduce gustatory stimuli into neural signals. In the field of taste biology, taste bud cells have been described as arising from "local epithelium", in distinction from many other receptor organs that are derived from neurogenic ectoderm including neural crest (NC). In fact, contribution of NC to both epithelium and mesenchyme in the developing tongue is not fully understood. In the present study we used two independent, well-characterized mouse lines, Wnt1-Cre and P0-Cre that express Cre recombinase in a NC-specific manner, in combination with two Cre reporter mouse lines, R26R and ZEG, and demonstrate a contribution of NC-derived cells to both tongue mesenchyme and epithelium including taste papillae and taste buds. In tongue mesenchyme, distribution of NC-derived cells is in close association with taste papillae. In tongue epithelium, labeled cells are observed in an initial scattered distribution and progress to a clustered pattern between papillae, and within papillae and early taste buds. This provides evidence for a contribution of NC to lingual epithelium. Together with previous reports for the origin of taste bud cells from local epithelium in postnatal mouse, we propose that NC cells migrate into and reside in the epithelium of the tongue primordium at an early embryonic stage, acquire epithelial cell phenotypes, and undergo cell proliferation and differentiation that is involved in the development of taste papillae and taste buds. Our findings lead to a new concept about derivation of taste bud cells that include a NC origin. Copyright © 2012 Elsevier Inc. All rights reserved.

  16. U-tube steam generator empirical model development and validation using neural networks

    International Nuclear Information System (INIS)

    Parlos, A.G.; Chong, K.T.; Atiya, A.

    1992-01-01

    Empirical modeling techniques that use model structures motivated from neural networks research have proven effective in identifying complex process dynamics. A recurrent multilayer perception (RMLP) network was developed as a nonlinear state-space model structure along with a static learning algorithm for estimating the parameter associated with it. The methods developed were demonstrated by identifying two submodels of a U-tube steam generator (UTSG), each valid around an operating power level. A significant drawback of this approach is the long off-line training times required for the development of even a simplified model of a UTSG. Subsequently, a dynamic gradient descent-based learning algorithm was developed as an accelerated alternative to train an RMLP network for use in empirical modeling of power plants. The two main advantages of this learning algorithm are its ability to consider past error gradient information for future use and the two forward passes associated with its implementation. The enhanced learning capabilities provided by the dynamic gradient descent-based learning algorithm were demonstrated via the case study of a simple steam boiler power plant. In this paper, the dynamic gradient descent-based learning algorithm is used for the development and validation of a complete UTSG empirical model

  17. Artificial Neural Network Test Support Development for the Space Shuttle PRCS Thrusters

    Science.gov (United States)

    Lehr, Mark E.

    2005-01-01

    A significant anomaly, Fuel Valve Pilot Seal Extrusion, is affecting the Shuttle Primary Reaction Control System (PRCS) Thrusters, and has caused 79 to fail. To help address this problem, a Shuttle PRCS Thruster Process Evaluation Team (TPET) was formed. The White Sands Test Facility (WSTF) and Boeing members of the TPET have identified many discrete valve current trace characteristics that are predictive of the problem. However, these are difficult and time consuming to identify and trend by manual analysis. Based on this exhaustive analysis over months, 22 thrusters previously delivered by the Depot were identified as high risk for flight failures. Although these had only recently been installed, they had to be removed from Shuttles OV103 and OV104 for reprocessing, by directive of the Shuttle Project Office. The resulting impact of the thruster removal, replacement, and valve replacement was significant (months of work and hundreds of thousands of dollars). Much of this could have been saved had the proposed Neural Network (NN) tool described in this paper been in place. In addition to the significant benefits to the Shuttle indicated above, the development and implementation of this type of testing will be the genesis for potential Quality improvements across many areas of WSTF test data analysis and will be shared with other NASA centers. Future tests can be designed to incorporate engineering experience via Artificial Neural Nets (ANN) into depot level acceptance of hardware. Additionally, results were shared with a NASA Engineering and Safety Center (NESC) Super Problem Response Team (SPRT). There was extensive interest voiced among many different personnel from several centers. There are potential spin-offs of this effort that can be directly applied to other data acquisition systems as well as vehicle health management for current and future flight vehicles.

  18. Development of modularity in the neural activity of children's brains

    International Nuclear Information System (INIS)

    Chen, Man; Deem, Michael W

    2015-01-01

    We study how modularity of the human brain changes as children develop into adults. Theory suggests that modularity can enhance the response function of a networked system subject to changing external stimuli. Thus, greater cognitive performance might be achieved for more modular neural activity, and modularity might likely increase as children develop. The value of modularity calculated from functional magnetic resonance imaging (fMRI) data is observed to increase during childhood development and peak in young adulthood. Head motion is deconvolved from the fMRI data, and it is shown that the dependence of modularity on age is independent of the magnitude of head motion. A model is presented to illustrate how modularity can provide greater cognitive performance at short times, i.e. task switching. A fitness function is extracted from the model. Quasispecies theory is used to predict how the average modularity evolves with age, illustrating the increase of modularity during development from children to adults that arises from selection for rapid cognitive function in young adults. Experiments exploring the effect of modularity on cognitive performance are suggested. Modularity may be a potential biomarker for injury, rehabilitation, or disease. (paper)

  19. Early warning of illegal development for protected areas by integrating cellular automata with neural networks.

    Science.gov (United States)

    Li, Xia; Lao, Chunhua; Liu, Yilun; Liu, Xiaoping; Chen, Yimin; Li, Shaoying; Ai, Bing; He, Zijian

    2013-11-30

    Ecological security has become a major issue under fast urbanization in China. As the first two cities in this country, Shenzhen and Dongguan issued the ordinance of Eco-designated Line of Control (ELC) to "wire" ecologically important areas for strict protection in 2005 and 2009 respectively. Early warning systems (EWS) are a useful tool for assisting the implementation ELC. In this study, a multi-model approach is proposed for the early warning of illegal development by integrating cellular automata (CA) and artificial neural networks (ANN). The objective is to prevent the ecological risks or catastrophe caused by such development at an early stage. The integrated model is calibrated by using the empirical information from both remote sensing and handheld GPS (global positioning systems). The MAR indicator which is the ratio of missing alarms to all the warnings is proposed for better assessment of the model performance. It is found that the fast urban development has caused significant threats to natural-area protection in the study area. The integration of CA, ANN and GPS provides a powerful tool for describing and predicting illegal development which is in highly non-linear and fragmented forms. The comparison shows that this multi-model approach has much better performances than the single-model approach for the early warning. Compared with the single models of CA and ANN, this integrated multi-model can improve the value of MAR by 65.48% and 5.17% respectively. Copyright © 2013 Elsevier Ltd. All rights reserved.

  20. Ca(2+) coding and decoding strategies for the specification of neural and renal precursor cells during development.

    Science.gov (United States)

    Moreau, Marc; Néant, Isabelle; Webb, Sarah E; Miller, Andrew L; Riou, Jean-François; Leclerc, Catherine

    2016-03-01

    During embryogenesis, a rise in intracellular Ca(2+) is known to be a widespread trigger for directing stem cells towards a specific tissue fate, but the precise Ca(2+) signalling mechanisms involved in achieving these pleiotropic effects are still poorly understood. In this review, we compare the Ca(2+) signalling events that appear to be one of the first steps in initiating and regulating both neural determination (neural induction) and kidney development (nephrogenesis). We have highlighted the necessary and sufficient role played by Ca(2+) influx and by Ca(2+) transients in the determination and differentiation of pools of neural or renal precursors. We have identified new Ca(2+) target genes involved in neural induction and we showed that the same Ca(2+) early target genes studied are not restricted to neural tissue but are also present in other tissues, principally in the pronephros. In this review, we also described a mechanism whereby the transcriptional control of gene expression during neurogenesis and nephrogenesis might be directly controlled by Ca(2+) signalling. This mechanism involves members of the Kcnip family such that a change in their binding properties to specific DNA sites is a result of Ca(2+) binding to EF-hand motifs. The different functions of Ca(2+) signalling during these two events illustrate the versatility of Ca(2+) as a second messenger. Copyright © 2015 Elsevier Ltd. All rights reserved.

  1. Involvement of Atm and Trp53 in neural cell loss due to Terf2 inactivation during mouse brain development.

    Science.gov (United States)

    Kim, Jusik; Choi, Inseo; Lee, Youngsoo

    2017-11-01

    Maintenance of genomic integrity is one of the critical features for proper neurodevelopment and inhibition of neurological diseases. The signals from both ATM and ATR to TP53 are well-known mechanisms to remove neural cells with DNA damage during neurogenesis. Here we examined the involvement of Atm and Atr in genomic instability due to Terf2 inactivation during mouse brain development. Selective inactivation of Terf2 in neural progenitors induced apoptosis, resulting in a complete loss of the brain structure. This neural loss was rescued partially in both Atm and Trp53 deficiency, but not in an Atr-deficient background in the mouse. Atm inactivation resulted in incomplete brain structures, whereas p53 deficiency led to the formation of multinucleated giant neural cells and the disruption of the brain structure. These giant neural cells disappeared in Lig4 deficiency. These data demonstrate ATM and TP53 are important for the maintenance of telomere homeostasis and the surveillance of telomere dysfunction during neurogenesis.

  2. Bidirectional control of social hierarchy by synaptic efficacy in medial prefrontal cortex.

    Science.gov (United States)

    Wang, Fei; Zhu, Jun; Zhu, Hong; Zhang, Qi; Lin, Zhanmin; Hu, Hailan

    2011-11-04

    Dominance hierarchy has a profound impact on animals' survival, health, and reproductive success, but its neural circuit mechanism is virtually unknown. We found that dominance ranking in mice is transitive, relatively stable, and highly correlates among multiple behavior measures. Recording from layer V pyramidal neurons of the medial prefrontal cortex (mPFC) showed higher strength of excitatory synaptic inputs in mice with higher ranking, as compared with their subordinate cage mates. Furthermore, molecular manipulations that resulted in an increase and decrease in the synaptic efficacy in dorsal mPFC neurons caused an upward and downward movement in the social rank, respectively. These results provide direct evidence for mPFC's involvement in social hierarchy and suggest that social rank is plastic and can be tuned by altering synaptic strength in mPFC pyramidal cells.

  3. Plasticity of Hippocampal Excitatory-Inhibitory Balance: Missing the Synaptic Control in the Epileptic Brain

    Directory of Open Access Journals (Sweden)

    Christian Bonansco

    2016-01-01

    Full Text Available Synaptic plasticity is the capacity generated by experience to modify the neural function and, thereby, adapt our behaviour. Long-term plasticity of glutamatergic and GABAergic transmission occurs in a concerted manner, finely adjusting the excitatory-inhibitory (E/I balance. Imbalances of E/I function are related to several neurological diseases including epilepsy. Several evidences have demonstrated that astrocytes are able to control the synaptic plasticity, with astrocytes being active partners in synaptic physiology and E/I balance. Here, we revise molecular evidences showing the epileptic stage as an abnormal form of long-term brain plasticity and propose the possible participation of astrocytes to the abnormal increase of glutamatergic and decrease of GABAergic neurotransmission in epileptic networks.

  4. Synaptic molecular imaging in spared and deprived columns of mouse barrel cortex with array tomography.

    Science.gov (United States)

    Weiler, Nicholas C; Collman, Forrest; Vogelstein, Joshua T; Burns, Randal; Smith, Stephen J

    2014-01-01

    A major question in neuroscience is how diverse subsets of synaptic connections in neural circuits are affected by experience dependent plasticity to form the basis for behavioral learning and memory. Differences in protein expression patterns at individual synapses could constitute a key to understanding both synaptic diversity and the effects of plasticity at different synapse populations. Our approach to this question leverages the immunohistochemical multiplexing capability of array tomography (ATomo) and the columnar organization of mouse barrel cortex to create a dataset comprising high resolution volumetric images of spared and deprived cortical whisker barrels stained for over a dozen synaptic molecules each. These dataset has been made available through the Open Connectome Project for interactive online viewing, and may also be downloaded for offline analysis using web, Matlab, and other interfaces.

  5. Implications of a neural network model of early sensori-motor development for the field of developmental neurology

    NARCIS (Netherlands)

    van Heijst, JJ; Touwen, BCL; Vos, JE

    This paper reports on a neural network model for early sensori-motor development and on the possible implications of this research for our understanding and, eventually, treatment of motor disorders like cerebral palsy. We recapitulate the results we published in detail in a series of papers [1-4].

  6. MAPK3 at the Autism-Linked Human 16p11.2 Locus Influences Precise Synaptic Target Selection at Drosophila Larval Neuromuscular Junctions.

    Science.gov (United States)

    Park, Sang Mee; Park, Hae Ryoun; Lee, Ji Hye

    2017-02-01

    Proper synaptic function in neural circuits requires precise pairings between correct pre- and post-synaptic partners. Errors in this process may underlie development of neuropsychiatric disorders, such as autism spectrum disorder (ASD). Development of ASD can be influenced by genetic factors, including copy number variations (CNVs). In this study, we focused on a CNV occurring at the 16p11.2 locus in the human genome and investigated potential defects in synaptic connectivity caused by reduced activities of genes located in this region at Drosophila larval neuromuscular junctions, a well-established model synapse with stereotypic synaptic structures. A mutation of rolled , a Drosophila homolog of human mitogen-activated protein kinase 3 ( MAPK3 ) at the 16p11.2 locus, caused ectopic innervation of axonal branches and their abnormal defasciculation. The specificity of these phenotypes was confirmed by expression of wild-type rolled in the mutant background. Albeit to a lesser extent, we also observed ectopic innervation patterns in mutants defective in Cdk2, Gα q , and Gp93, all of which were expected to interact with Rolled MAPK3. A further genetic analysis in double heterozygous combinations revealed a synergistic interaction between rolled and Gp93 . In addition, results from RT-qPCR analyses indicated consistently reduced rolled mRNA levels in Cdk2 , Gα q , and Gp93 mutants. Taken together, these data suggest a central role of MAPK3 in regulating the precise targeting of presynaptic axons to proper postsynaptic targets, a critical step that may be altered significantly in ASD.

  7. Optical implementation of neural learning algorithms based on cross-gain modulation in a semiconductor optical amplifier

    Science.gov (United States)

    Li, Qiang; Wang, Zhi; Le, Yansi; Sun, Chonghui; Song, Xiaojia; Wu, Chongqing

    2016-10-01

    Neuromorphic engineering has a wide range of applications in the fields of machine learning, pattern recognition, adaptive control, etc. Photonics, characterized by its high speed, wide bandwidth, low power consumption and massive parallelism, is an ideal way to realize ultrafast spiking neural networks (SNNs). Synaptic plasticity is believed to be critical for learning, memory and development in neural circuits. Experimental results have shown that changes of synapse are highly dependent on the relative timing of pre- and postsynaptic spikes. Synaptic plasticity in which presynaptic spikes preceding postsynaptic spikes results in strengthening, while the opposite timing results in weakening is called antisymmetric spike-timing-dependent plasticity (STDP) learning rule. And synaptic plasticity has the opposite effect under the same conditions is called antisymmetric anti-STDP learning rule. We proposed and experimentally demonstrated an optical implementation of neural learning algorithms, which can achieve both of antisymmetric STDP and anti-STDP learning rule, based on the cross-gain modulation (XGM) within a single semiconductor optical amplifier (SOA). The weight and height of the potentitation and depression window can be controlled by adjusting the injection current of the SOA, to mimic the biological antisymmetric STDP and anti-STDP learning rule more realistically. As the injection current increases, the width of depression and potentitation window decreases and height increases, due to the decreasing of recovery time and increasing of gain under a stronger injection current. Based on the demonstrated optical STDP circuit, ultrafast learning in optical SNNs can be realized.

  8. Cocaine Promotes Coincidence Detection and Lowers Induction Threshold during Hebbian Associative Synaptic Potentiation in Prefrontal Cortex.

    Science.gov (United States)

    Ruan, Hongyu; Yao, Wei-Dong

    2017-01-25

    Addictive drugs usurp neural plasticity mechanisms that normally serve reward-related learning and memory, primarily by evoking changes in glutamatergic synaptic strength in the mesocorticolimbic dopamine circuitry. Here, we show that repeated cocaine exposure in vivo does not alter synaptic strength in the mouse prefrontal cortex during an early period of withdrawal, but instead modifies a Hebbian quantitative synaptic learning rule by broadening the temporal window and lowers the induction threshold for spike-timing-dependent LTP (t-LTP). After repeated, but not single, daily cocaine injections, t-LTP in layer V pyramidal neurons is induced at +30 ms, a normally ineffective timing interval for t-LTP induction in saline-exposed mice. This cocaine-induced, extended-timing t-LTP lasts for ∼1 week after terminating cocaine and is accompanied by an increased susceptibility to potentiation by fewer pre-post spike pairs, indicating a reduced t-LTP induction threshold. Basal synaptic strength and the maximal attainable t-LTP magnitude remain unchanged after cocaine exposure. We further show that the cocaine facilitation of t-LTP induction is caused by sensitized D1-cAMP/protein kinase A dopamine signaling in pyramidal neurons, which then pathologically recruits voltage-gated l-type Ca 2+ channels that synergize with GluN2A-containing NMDA receptors to drive t-LTP at extended timing. Our results illustrate a mechanism by which cocaine, acting on a key neuromodulation pathway, modifies the coincidence detection window during Hebbian plasticity to facilitate associative synaptic potentiation in prefrontal excitatory circuits. By modifying rules that govern activity-dependent synaptic plasticity, addictive drugs can derail the experience-driven neural circuit remodeling process important for executive control of reward and addiction. It is believed that addictive drugs often render an addict's brain reward system hypersensitive, leaving the individual more susceptible to

  9. Music training relates to the development of neural mechanisms of selective auditory attention.

    Science.gov (United States)

    Strait, Dana L; Slater, Jessica; O'Connell, Samantha; Kraus, Nina

    2015-04-01

    Selective attention decreases trial-to-trial variability in cortical auditory-evoked activity. This effect increases over the course of maturation, potentially reflecting the gradual development of selective attention and inhibitory control. Work in adults indicates that music training may alter the development of this neural response characteristic, especially over brain regions associated with executive control: in adult musicians, attention decreases variability in auditory-evoked responses recorded over prefrontal cortex to a greater extent than in nonmusicians. We aimed to determine whether this musician-associated effect emerges during childhood, when selective attention and inhibitory control are under development. We compared cortical auditory-evoked variability to attended and ignored speech streams in musicians and nonmusicians across three age groups: preschoolers, school-aged children and young adults. Results reveal that childhood music training is associated with reduced auditory-evoked response variability recorded over prefrontal cortex during selective auditory attention in school-aged child and adult musicians. Preschoolers, on the other hand, demonstrate no impact of selective attention on cortical response variability and no musician distinctions. This finding is consistent with the gradual emergence of attention during this period and may suggest no pre-existing differences in this attention-related cortical metric between children who undergo music training and those who do not. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

  10. Combined application of mixture experimental design and artificial neural networks in the solid dispersion development.

    Science.gov (United States)

    Medarević, Djordje P; Kleinebudde, Peter; Djuriš, Jelena; Djurić, Zorica; Ibrić, Svetlana

    2016-01-01

    This study for the first time demonstrates combined application of mixture experimental design and artificial neural networks (ANNs) in the solid dispersions (SDs) development. Ternary carbamazepine-Soluplus®-poloxamer 188 SDs were prepared by solvent casting method to improve carbamazepine dissolution rate. The influence of the composition of prepared SDs on carbamazepine dissolution rate was evaluated using d-optimal mixture experimental design and multilayer perceptron ANNs. Physicochemical characterization proved the presence of the most stable carbamazepine polymorph III within the SD matrix. Ternary carbamazepine-Soluplus®-poloxamer 188 SDs significantly improved carbamazepine dissolution rate compared to pure drug. Models developed by ANNs and mixture experimental design well described the relationship between proportions of SD components and percentage of carbamazepine released after 10 (Q10) and 20 (Q20) min, wherein ANN model exhibit better predictability on test data set. Proportions of carbamazepine and poloxamer 188 exhibited the highest influence on carbamazepine release rate. The highest carbamazepine release rate was observed for SDs with the lowest proportions of carbamazepine and the highest proportions of poloxamer 188. ANNs and mixture experimental design can be used as powerful data modeling tools in the systematic development of SDs. Taking into account advantages and disadvantages of both techniques, their combined application should be encouraged.

  11. Synaptic vesicle distribution by conveyor belt.

    Science.gov (United States)

    Moughamian, Armen J; Holzbaur, Erika L F

    2012-03-02

    The equal distribution of synaptic vesicles among synapses along the axon is critical for robust neurotransmission. Wong et al. show that the continuous circulation of synaptic vesicles throughout the axon driven by molecular motors ultimately yields this even distribution. Copyright © 2012 Elsevier Inc. All rights reserved.

  12. Spontaneous Vesicle Recycling in the Synaptic Bouton

    Directory of Open Access Journals (Sweden)

    Sven eTruckenbrodt

    2014-12-01

    Full Text Available The trigger for synaptic vesicle exocytosis is Ca2+, which enters the synaptic bouton following action potential stimulation. However, spontaneous release of neurotransmitter also occurs in the absence of stimulation in virtually all synaptic boutons. It has long been thought that this represents exocytosis driven by fluctuations in local Ca2+ levels. The vesicles responding to these fluctuations are thought to be the same ones that release upon stimulation, albeit potentially triggered by different Ca2+ sensors. This view has been challenged by several recent works, which have suggested that spontaneous release is driven by a separate pool of synaptic vesicles. Numerous articles appeared during the last few years in support of each of these hypotheses, and it has been challenging to bring them into accord. We speculate here on the origins of this controversy, and propose a solution that is related to developmental effects. Constitutive membrane traffic, needed for the biogenesis of vesicles and synapses, is responsible for high levels of spontaneous membrane fusion in young neurons, probably independent of Ca2+. The vesicles releasing spontaneously in such neurons are not related to other synaptic vesicle pools and may represent constitutively releasing vesicles (CRVs rather than bona fide synaptic vesicles. In mature neurons, constitutive traffic is much dampened, and the few remaining spontaneous release events probably represent bona fide spontaneously releasing synaptic vesicles (SRSVs responding to Ca2+ fluctuations, along with a handful of CRVs that participate in synaptic vesicle turnover.

  13. DEVELOPMENT OF FUZZY NEURAL NETWORK FOR THE INTERPRETATION OF THE RESULTS OF DISSOLVED IN OIL GASES ANALYSIS

    Directory of Open Access Journals (Sweden)

    V.Е. Bondarenko

    2017-04-01

    Full Text Available Purpose. The purpose of this paper is a diagnosis of power transformers on the basis of the results of the analysis of gases dissolved in oil. Methodology. To solve this problem a fuzzy neural network has been developed, tested and trained. Results. The analysis of neural network to recognize the possibility of developing defects at an early stage of their development, or growth of gas concentrations in the healthy transformers, made after the emergency actions on the part of electric networks is made. It has been established greatest difficulty in making a diagnosis on the criterion of the boundary gas concentrations, are the results of DGA obtained for the healthy transformers in which the concentration of gases dissolved in oil exceed their limit values, as well as defective transformers at an early stage development defects. The analysis showed that the accuracy of recognition of fuzzy neural networks has its limitations, which are determined by the peculiarities of the DGA method, used diagnostic features and the selected decision rule. Originality. Unlike similar studies in the training of the neural network, the membership functions of linguistic terms were chosen taking into account the functions gas concentrations density distribution transformers with various diagnoses, allowing to consider a particular gas content of oils that are typical of a leaky transformer, and the operating conditions of the equipment. Practical value. Developed fuzzy neural network allows to perform diagnostics of power transformers on the basis of the result of the analysis of gases dissolved in oil, with a high level of reliability.

  14. Neural cell adhesion molecule-180-mediated homophilic binding induces epidermal growth factor receptor (EGFR) down-regulation and uncouples the inhibitory function of EGFR in neurite outgrowth

    DEFF Research Database (Denmark)

    Povlsen, Gro Klitgaard; Berezin, Vladimir; Bock, Elisabeth

    2008-01-01

    The neural cell adhesion molecule (NCAM) plays important roles in neuronal development, regeneration, and synaptic plasticity. NCAM homophilic binding mediates cell adhesion and induces intracellular signals, in which the fibroblast growth factor receptor plays a prominent role. Recent studies...... this NCAM-180-induced EGFR down-regulation involves increased EGFR ubiquitination and lysosomal EGFR degradation. Furthermore, NCAM-180-mediated EGFR down-regulation requires NCAM homophilic binding and interactions of the cytoplasmic domain of NCAM-180 with intracellular interaction partners, but does...

  15. Synaptic plasticity in drug reward circuitry.

    Science.gov (United States)

    Winder, Danny G; Egli, Regula E; Schramm, Nicole L; Matthews, Robert T

    2002-11-01

    Drug addiction is a major public health issue worldwide. The persistence of drug craving coupled with the known recruitment of learning and memory centers in the brain has led investigators to hypothesize that the alterations in glutamatergic synaptic efficacy brought on by synaptic plasticity may play key roles in the addiction process. Here we review the present literature, examining the properties of synaptic plasticity within drug reward circuitry, and the effects that drugs of abuse have on these forms of plasticity. Interestingly, multiple forms of synaptic plasticity can be induced at glutamatergic synapses within the dorsal striatum, its ventral extension the nucleus accumbens, and the ventral tegmental area, and at least some of these forms of plasticity are regulated by behaviorally meaningful administration of cocaine and/or amphetamine. Thus, the present data suggest that regulation of synaptic plasticity in reward circuits is a tractable candidate mechanism underlying aspects of addiction.

  16. Synaptic Correlates of Low-Level Perception in V1.

    Science.gov (United States)

    Gerard-Mercier, Florian; Carelli, Pedro V; Pananceau, Marc; Troncoso, Xoana G; Frégnac, Yves

    2016-04-06

    The computational role of primary visual cortex (V1) in low-level perception remains largely debated. A dominant view assumes the prevalence of higher cortical areas and top-down processes in binding information across the visual field. Here, we investigated the role of long-distance intracortical connections in form and motion processing by measuring, with intracellular recordings, their synaptic impact on neurons in area 17 (V1) of the anesthetized cat. By systematically mapping synaptic responses to stimuli presented in the nonspiking surround of V1 receptive fields, we provide the first quantitative characterization of the lateral functional connectivity kernel of V1 neurons. Our results revealed at the population level two structural-functional biases in the synaptic integration and dynamic association properties of V1 neurons. First, subthreshold responses to oriented stimuli flashed in isolation in the nonspiking surround exhibited a geometric organization around the preferred orientation axis mirroring the psychophysical "association field" for collinear contour perception. Second, apparent motion stimuli, for which horizontal and feedforward synaptic inputs summed in-phase, evoked dominantly facilitatory nonlinear interactions, specifically during centripetal collinear activation along the preferred orientation axis, at saccadic-like speeds. This spatiotemporal integration property, which could constitute the neural correlate of a human perceptual bias in speed detection, suggests that local (orientation) and global (motion) information is already linked within V1. We propose the existence of a "dynamic association field" in V1 neurons, whose spatial extent and anisotropy are transiently updated and reshaped as a function of changes in the retinal flow statistics imposed during natural oculomotor exploration. The computational role of primary visual cortex in low-level perception remains debated. The expression of this "pop-out" perception is often assumed

  17. Neural tissue-spheres

    DEFF Research Database (Denmark)

    Andersen, Rikke K; Johansen, Mathias; Blaabjerg, Morten

    2007-01-01

    By combining new and established protocols we have developed a procedure for isolation and propagation of neural precursor cells from the forebrain subventricular zone (SVZ) of newborn rats. Small tissue blocks of the SVZ were dissected and propagated en bloc as free-floating neural tissue...... content, thus allowing experimental studies of neural precursor cells and their niche...

  18. The lysine acetyltransferase activator Brpf1 governs dentate gyrus development through neural stem cells and progenitors.

    Directory of Open Access Journals (Sweden)

    Linya You

    2015-03-01

    Full Text Available Lysine acetylation has recently emerged as an important post-translational modification in diverse organisms, but relatively little is known about its roles in mammalian development and stem cells. Bromodomain- and PHD finger-containing protein 1 (BRPF1 is a multidomain histone binder and a master activator of three lysine acetyltransferases, MOZ, MORF and HBO1, which are also known as KAT6A, KAT6B and KAT7, respectively. While the MOZ and MORF genes are rearranged in leukemia, the MORF gene is also mutated in prostate and other cancers and in four genetic disorders with intellectual disability. Here we show that forebrain-specific inactivation of the mouse Brpf1 gene causes hypoplasia in the dentate gyrus, including underdevelopment of the suprapyramidal blade and complete loss of the infrapyramidal blade. We trace the developmental origin to compromised Sox2+ neural stem cells and Tbr2+ intermediate neuronal progenitors. We further demonstrate that Brpf1 loss deregulates neuronal migration, cell cycle progression and transcriptional control, thereby causing abnormal morphogenesis of the hippocampus. These results link histone binding and acetylation control to hippocampus development and identify an important epigenetic regulator for patterning the dentate gyrus, a brain structure critical for learning, memory and adult neurogenesis.

  19. Neural Correlates of Cognitive Intervention in Persons at Risk of Developing Alzheimer’s disease

    Directory of Open Access Journals (Sweden)

    SM Hadi eHosseini

    2014-08-01

    Full Text Available Cognitive training is an emergent approach that has begun to receive increased attention in recent years as a non-pharmacological, cost-effective intervention for Alzheimer’s disease (AD. There has been increasing behavioral evidence regarding training-related improvement in cognitive performance in early stages of AD. Although these studies provide important insight about the efficacy of cognitive training, neuroimaging studies are crucial to pinpoint changes in brain structure and function associated with training and to examine their overlap with pathology in AD. In this study, we reviewed the existing neuroimaging studies on cognitive training in persons at risk of developing AD to provide an overview of the overlap between neural networks rehabilitated by the current training methods and those affected in AD. The data suggest a consistent training-related increase in brain activity in medial temporal, prefrontal, and posterior default mode networks, as well as increase in gray matter structure in frontoparietal and entorhinal regions. This pattern differs from the observed pattern in healthy older adults that shows a combination of increased and decreased activity in response to training. Detailed investigation of the data suggests that training in persons at risk of developing AD mainly improves compensatory mechanisms and partly restores the affected functions. While current neuroimaging studies are quite helpful in identifying the mechanisms underlying cognitive training, the data calls for future multi-modal neuroimaging studies with focus on multi-domain cognitive training, network level connectivity, and individual differences in response to training.

  20. Neural correlates of cognitive intervention in persons at risk of developing Alzheimer’s disease

    Science.gov (United States)

    Hosseini, S. M. Hadi; Kramer, Joel H.; Kesler, Shelli R.

    2014-01-01

    Cognitive training is an emergent approach that has begun to receive increased attention in recent years as a non-pharmacological, cost-effective intervention for Alzheimer’s disease (AD). There has been increasing behavioral evidence regarding training-related improvement in cognitive performance in early stages of AD. Although these studies provide important insight about the efficacy of cognitive training, neuroimaging studies are crucial to pinpoint changes in brain structure and function associated with training and to examine their overlap with pathology in AD. In this study, we reviewed the existing neuroimaging studies on cognitive training in persons at risk of developing AD to provide an overview of the overlap between neural networks rehabilitated by the current training methods and those affected in AD. The data suggest a consistent training-related increase in brain activity in medial temporal, prefrontal, and posterior default mode networks, as well as increase in gray matter structure in frontoparietal and entorhinal regions. This pattern differs from the observed pattern in healthy older adults that shows a combination of increased and decreased activity in response to training. Detailed investigation of the data suggests that training in persons at risk of developing AD mainly improves compensatory mechanisms and partly restores the affected functions. While current neuroimaging studies are quite helpful in identifying the mechanisms underlying cognitive training, the data calls for future multi-modal neuroimaging studies with focus on multi-domain cognitive training, network level connectivity, and individual differences in response to training. PMID:25206335

  1. Excessive Sensory Stimulation during Development Alters Neural Plasticity and Vulnerability to Cocaine in Mice.

    Science.gov (United States)

    Ravinder, Shilpa; Donckels, Elizabeth A; Ramirez, Julian S B; Christakis, Dimitri A; Ramirez, Jan-Marino; Ferguson, Susan M

    2016-01-01

    Early life experiences affect the formation of neuronal networks, which can have a profound impact on brain function and behavior later in life. Previous work has shown that mice exposed to excessive sensory stimulation during development are hyperactive and novelty seeking, and display impaired cognition compared with controls. In this study, we addressed the issue of whether excessive sensory stimulation during development could alter behaviors related to addiction and underlying circuitry in CD-1 mice. We found that the reinforcing properties of cocaine were significantly enhanced in mice exposed to excessive sensory stimulation. Moreover, although these mice displayed hyperactivity that became more pronounced over time, they showed impaired persistence of cocaine-induced locomotor sensitization. These behavioral effects were associated with alterations in glutamatergic transmission in the nucleus accumbens and amygdala. Together, these findings suggest that excessive sensory stimulation in early life significantly alters drug reward and the neural circuits that regulate addiction and attention deficit hyperactivity. These observations highlight the consequences of early life experiences and may have important implications for children growing up in today's complex technological environment.

  2. Murine cytomegalovirus infection of neural stem cells alters neurogenesis in the developing brain.

    Directory of Open Access Journals (Sweden)

    Manohar B Mutnal

    2011-01-01

    Full Text Available Congenital cytomegalovirus (CMV brain infection causes serious neuro-developmental sequelae including: mental retardation, cerebral palsy, and sensorineural hearing loss. But, the mechanisms of injury and pathogenesis to the fetal brain are not completely understood. The present study addresses potential pathogenic mechanisms by which this virus injures the CNS using a neonatal mouse model that mirrors congenital brain infection. This investigation focused on, analysis of cell types infected with mouse cytomegalovirus (MCMV and the pattern of injury to the developing brain.We used our MCMV infection model and a multi-color flow cytometry approach to quantify the effect of viral infection on the developing brain, identifying specific target cells and the consequent effect on neurogenesis. In this study, we show that neural stem cells (NSCs and neuronal precursor cells are the principal target cells for MCMV in the developing brain. In addition, viral infection was demonstrated to cause a loss of NSCs expressing CD133 and nestin. We also showed that infection of neonates leads to subsequent abnormal brain development as indicated by loss of CD24(hi cells that incorporated BrdU. This neonatal brain infection was also associated with altered expression of Oct4, a multipotency marker; as well as down regulation of the neurotrophins BDNF and NT3, which are essential to regulate the birth and differentiation of neurons during normal brain development. Finally, we report decreased expression of doublecortin, a marker to identify young neurons, following viral brain infection.MCMV brain infection of newborn mice causes significant loss of NSCs, decreased proliferation of neuronal precursor cells, and marked loss of young neurons.

  3. Feedforward inhibition and synaptic scaling--two sides of the same coin?

    Directory of Open Access Journals (Sweden)

    Christian Keck

    Full Text Available Feedforward inhibition and synaptic scaling are important adaptive processes that control the total input a neuron can receive from its afferents. While often studied in isolation, the two have been reported to co-occur in various brain regions. The functional implications of their interactions remain unclear, however. Based on a probabilistic modeling approach, we show here that fast feedforward inhibition and synaptic scaling interact synergistically during unsupervised learning. In technical terms, we model the input to a neural circuit using a normalized mixture model with Poisson noise. We demonstrate analytically and numerically that, in the presence of lateral inhibition introducing competition between different neurons, Hebbian plasticity and synaptic scaling approximate the optimal maximum likelihood solutions for this model. Our results suggest that, beyond its conventional use as a mechanism to remove undesired pattern variations, input normalization can make typical neural interaction and learning rules optimal on the stimulus subspace defined through feedforward inhibition. Furthermore, learning within this subspace is more efficient in practice, as it helps avoid locally optimal solutions. Our results suggest a close connection between feedforward inhibition and synaptic scaling which may have important functional implications for general cortical processing.

  4. Feedforward inhibition and synaptic scaling--two sides of the same coin?

    Science.gov (United States)

    Keck, Christian; Savin, Cristina; Lücke, Jörg

    2012-01-01

    Feedforward inhibition and synaptic scaling are important adaptive processes that control the total input a neuron can receive from its afferents. While often studied in isolation, the two have been reported to co-occur in various brain regions. The functional implications of their interactions remain unclear, however. Based on a probabilistic modeling approach, we show here that fast feedforward inhibition and synaptic scaling interact synergistically during unsupervised learning. In technical terms, we model the input to a neural circuit using a normalized mixture model with Poisson noise. We demonstrate analytically and numerically that, in the presence of lateral inhibition introducing competition between different neurons, Hebbian plasticity and synaptic scaling approximate the optimal maximum likelihood solutions for this model. Our results suggest that, beyond its conventional use as a mechanism to remove undesired pattern variations, input normalization can make typical neural interaction and learning rules optimal on the stimulus subspace defined through feedforward inhibition. Furthermore, learning within this subspace is more efficient in practice, as it helps avoid locally optimal solutions. Our results suggest a close connection between feedforward inhibition and synaptic scaling which may have important functional implications for general cortical processing.

  5. Feedforward Inhibition and Synaptic Scaling – Two Sides of the Same Coin?

    Science.gov (United States)

    Lücke, Jörg

    2012-01-01

    Feedforward inhibition and synaptic scaling are important adaptive processes that control the total input a neuron can receive from its afferents. While often studied in isolation, the two have been reported to co-occur in various brain regions. The functional implications of their interactions remain unclear, however. Based on a probabilistic modeling approach, we show here that fast feedforward inhibition and synaptic scaling interact synergistically during unsupervised learning. In technical terms, we model the input to a neural circuit using a normalized mixture model with Poisson noise. We demonstrate analytically and numerically that, in the presence of lateral inhibition introducing competition between different neurons, Hebbian plasticity and synaptic scaling approximate the optimal maximum likelihood solutions for this model. Our results suggest that, beyond its conventional use as a mechanism to remove undesired pattern variations, input normalization can make typical neural interaction and learning rules optimal on the stimulus subspace defined through feedforward inhibition. Furthermore, learning within this subspace is more efficient in practice, as it helps avoid locally optimal solutions. Our results suggest a close connection between feedforward inhibition and synaptic scaling which may have important functional implications for general cortical processing. PMID:22457610

  6. An Attractive Reelin Gradient Establishes Synaptic Lamination in the Vertebrate Visual System.

    Science.gov (United States)

    Di Donato, Vincenzo; De Santis, Flavia; Albadri, Shahad; Auer, Thomas Oliver; Duroure, Karine; Charpentier, Marine; Concordet, Jean-Paul; Gebhardt, Christoph; Del Bene, Filippo

    2018-03-07

    A conserved organizational and functional principle of neural networks is the segregation of axon-dendritic synaptic connections into laminae. Here we report that targeting of synaptic laminae by retinal ganglion cell (RGC) arbors in the vertebrate visual system is regulated by a signaling system relying on target-derived Reelin and VLDLR/Dab1a on the projecting neurons. Furthermore, we find that Reelin is distributed as a gradient on the target tissue and stabilized by heparan sulfate proteoglycans (HSPGs) in the extracellular matrix (ECM). Through genetic manipulations, we show that this Reelin gradient is important for laminar targeting and that it is attractive for RGC axons. Finally, we suggest a comprehensive model of synaptic lamina formation in which attractive Reelin counter-balances repulsive Slit1, thereby guiding RGC axons toward single synaptic laminae. We establish a mechanism that may represent a general principle for neural network assembly in vertebrate species and across different brain areas. Copyright © 2018 Elsevier Inc. All rights reserved.

  7. DISC1 Protein Regulates γ-Aminobutyric Acid, Type A (GABAA) Receptor Trafficking and Inhibitory Synaptic Transmission in Cortical Neurons.

    Science.gov (United States)

    Wei, Jing; Graziane, Nicholas M; Gu, Zhenglin; Yan, Zhen

    2015-11-13

    Association studies have suggested that Disrupted-in-Schizophrenia 1 (DISC1) confers a genetic risk at the level of endophenotypes that underlies many major mental disorders. Despite the progress in understanding the significance of DISC1 at neural development, the mechanisms underlying DISC1 regulation of synaptic functions remain elusive. Because alterations in the cortical GABA system have been strongly linked to the pathophysiology of schizophrenia, one potential target of DISC1 that is critically involved in the regulation of cognition and emotion is the GABAA receptor (GABAAR). We found that cellular knockdown of DISC1 significantly reduced GABAAR-mediated synaptic and whole-cell current, whereas overexpression of wild-type DISC1, but not the C-terminal-truncated DISC1 (a schizophrenia-related mutant), significantly increased GABAAR currents in pyramidal neurons of the prefrontal cortex. These effects were accompanied by DISC1-induced changes in surface GABAAR expression. Moreover, the regulation of GABAARs by DISC1 knockdown or overexpression depends on the microtubule motor protein kinesin 1 (KIF5). Our results suggest that DISC1 exerts an important effect on GABAergic inhibitory transmission by regulating KIF5/microtubule-based GABAAR trafficking in the cortex. The knowledge gained from this study would shed light on how DISC1 and the GABA system are linked mechanistically and how their interactions are critical for maintaining a normal mental state. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

  8. Synaptic transmission modulates while non-synaptic processes govern the transition from pre-ictal to seizure activity in vitro

    OpenAIRE

    Jefferys, John; Fox, John; Jiruska, Premysl; Kronberg, Greg; Miranda, Dolores; Ruiz-Nuño, Ana; Bikson, Marom

    2018-01-01

    It is well established that non-synaptic mechanisms can generate electrographic seizures after blockade of synaptic function. We investigated the interaction of intact synaptic activity with non-synaptic mechanisms in the isolated CA1 region of rat hippocampal slices using the 'elevated-K+' model of epilepsy. Elevated K+ ictal bursts share waveform features with other models of electrographic seizures, including non-synaptic models where chemical synaptic transmission is suppressed, such as t...

  9. Enrichment of conserved synaptic activity-responsive element in neuronal genes predicts a coordinated response of MEF2, CREB and SRF.

    Directory of Open Access Journals (Sweden)

    Fernanda M Rodríguez-Tornos

    Full Text Available A unique synaptic activity-responsive element (SARE sequence, composed of the consensus binding sites for SRF, MEF2 and CREB, is necessary for control of transcriptional upregulation of the Arc gene in response to synaptic activity. We hypothesize that this sequence is a broad mechanism that regulates gene expression in response to synaptic activation and during plasticity; and that analysis of SARE-containing genes could identify molecular mechanisms involved in brain disorders. To search for conserved SARE sequences in the mammalian genome, we used the SynoR in silico tool, and found the SARE cluster predominantly in the regulatory regions of genes expressed specifically in the nervous system; most were related to neural development and homeostatic maintenance. Two of these SARE sequences were tested in luciferase assays and proved to promote transcription in response to neuronal activation. Supporting the predictive capacity of our candidate list, up-regulation of several SARE containing genes in response to neuronal activity was validated using external data and also experimentally using primary cortical neurons and quantitative real time RT-PCR. The list of SARE-containing genes includes several linked to mental retardation and cognitive disorders, and is significantly enriched in genes that encode mRNA targeted by FMRP (fragile X mental retardation protein. Our study thus supports the idea that SARE sequences are relevant transcriptional regulatory elements that participate in plasticity. In addition, it offers a comprehensive view of how activity-responsive transcription factors coordinate their actions and increase the selectivity of their targets. Our data suggest that analysis of SARE-containing genes will reveal yet-undescribed pathways of synaptic plasticity and additional candidate genes disrupted in mental disease.

  10. Motor unit recruitment strategies and muscle properties determine the influence of synaptic noise on force steadiness

    Science.gov (United States)

    Dideriksen, Jakob L.; Negro, Francesco; Enoka, Roger M.

    2012-01-01

    Motoneurons receive synaptic inputs from tens of thousands of connections that cause membrane potential to fluctuate continuously (synaptic noise), which introduces variability in discharge times of action potentials. We hypothesized that the influence of synaptic noise on force steadiness during voluntary contractions is limited to low muscle forces. The hypothesis was examined with an analytical description of transduction of motor unit spike trains into muscle force, a computational model of motor unit recruitment and rate coding, and experimental analysis of interspike interval variability during steady contractions with the abductor digiti minimi muscle. Simulations varied contraction force, level of synaptic noise, size of motor unit population, recruitment range, twitch contraction times, and level of motor unit short-term synchronization. Consistent with the analytical derivations, simulations and experimental data showed that force variability at target forces above a threshold was primarily due to low-frequency oscillations in neural drive, whereas the influence of synaptic noise was almost completely attenuated by two low-pass filters, one related to convolution of motoneuron spike trains with motor unit twitches (temporal summation) and the other attributable to summation of single motor unit forces (spatial summation). The threshold force above which synaptic noise ceased to influence force steadiness depended on recruitment range, size of motor unit population, and muscle contractile properties. This threshold was low (motor unit recruitment and muscle properties of a typical muscle are tuned to limit the influence of synaptic noise on force steadiness to low forces and that the inability to produce a constant force during stronger contractions is mainly attributable to the common low-frequency oscillations in motoneuron discharge rates. PMID:22423000

  11. The Less Things Change, the More They Are Different: Contributions of Long-Term Synaptic Plasticity and Homeostasis to Memory

    Science.gov (United States)

    Schacher, Samuel; Hu, Jiang-Yuan

    2014-01-01

    An important cellular mechanism contributing to the strength and duration of memories is activity-dependent alterations in the strength of synaptic connections within the neural circuit encoding the memory. Reversal of the memory is typically correlated with a reversal of the cellular changes to levels expressed prior to the stimulation. Thus, for…

  12. Synaptic integration of transplanted interneuron progenitor cells into native cortical networks.

    Science.gov (United States)

    Howard, MacKenzie A; Baraban, Scott C

    2016-08-01

    Interneuron-based cell transplantation is a powerful method to modify network function in a variety of neurological disorders, including epilepsy. Whether new interneurons integrate into native neural networks in a subtype-specific manner is not well understood, and the therapeutic mechanisms underlying interneuron-based cell therapy, including the role of synaptic inhibition, are debated. In this study, we tested subtype-specific integration of transplanted interneurons using acute cortical brain slices and visualized patch-clamp recordings to measure excitatory synaptic inputs, intrinsic properties, and inhibitory synaptic outputs. Fluorescently labeled progenitor cells from the embryonic medial ganglionic eminence (MGE) were used for transplantation. At 5 wk after transplantation, MGE-derived parvalbumin-positive (PV+) interneurons received excitatory synaptic inputs, exhibited mature interneuron firing properties, and made functional synaptic inhibitory connections to native pyramidal cells that were comparable to those of native PV+ interneurons. These findings demonstrate that MGE-derived PV+ interneurons functionally integrate into subtype-appropriate physiological niches within host networks following transplantation. Copyright © 2016 the American Physiological Society.

  13. The Roles of Cortical Slow Waves in Synaptic Plasticity and Memory Consolidation.

    Science.gov (United States)

    Miyamoto, Daisuke; Hirai, Daichi; Murayama, Masanori

    2017-01-01

    Sleep plays important roles in sensory and motor memory consolidation. Sleep oscillations, reflecting neural population activity, involve the reactivation of learning-related neurons and regulate synaptic strength and, thereby affect memory consolidation. Among sleep oscillations, slow waves (0.5-4 Hz) are closely associated with memory consolidation. For example, slow-wave power is regulated in an experience-dependent manner and correlates with acquired memory. Furthermore, manipulating slow waves can enhance or impair memory consolidation. During slow wave sleep, inter-areal interactions between the cortex and hippocampus (HC) have been proposed to consolidate declarative memory; however, interactions for non-declarative (HC-independent) memory remain largely uninvestigated. We recently showed that the directional influence in a slow-wave range through a top-down cortical long-range circuit is involved in the consolidation of non-declarative memory. At the synaptic level, the average cortical synaptic strength is known to be potentiated during wakefulness and depressed during sleep. Moreover, learning causes plasticity in a subset of synapses, allocating memory to them. Sleep may help to differentiate synaptic strength between allocated and non-allocated synapses (i.e., improving the signal-to-noise ratio, which may facilitate memory consolidation). Herein, we offer perspectives on inter-areal interactions and synaptic plasticity for memory consolidation during sleep.

  14. The Roles of Cortical Slow Waves in Synaptic Plasticity and Memory Consolidation

    Directory of Open Access Journals (Sweden)

    Daisuke Miyamoto

    2017-11-01

    Full Text Available Sleep plays important roles in sensory and motor memory consolidation. Sleep oscillations, reflecting neural population activity, involve the reactivation of learning-related neurons and regulate synaptic strength and, thereby affect memory consolidation. Among sleep oscillations, slow waves (0.5–4 Hz are closely associated with memory consolidation. For example, slow-wave power is regulated in an experience-dependent manner and correlates with acquired memory. Furthermore, manipulating slow waves can enhance or impair memory consolidation. During slow wave sleep, inter-areal interactions between the cortex and hippocampus (HC have been proposed to consolidate declarative memory; however, interactions for non-declarative (HC-independent memory remain largely uninvestigated. We recently showed that the directional influence in a slow-wave range through a top-down cortical long-range circuit is involved in the consolidation of non-declarative memory. At the synaptic level, the average cortical synaptic strength is known to be potentiated during wakefulness and depressed during sleep. Moreover, learning causes plasticity in a subset of synapses, allocating memory to them. Sleep may help to differentiate synaptic strength between allocated and non-allocated synapses (i.e., improving the signal-to-noise ratio, which may facilitate memory consolidation. Herein, we offer perspectives on inter-areal interactions and synaptic plasticity for memory consolidation during sleep.

  15. Transformation-invariant visual representations in self-organizing spiking neural networks.

    Science.gov (United States)

    Evans, Benjamin D; Stringer, Simon M

    2012-01-01

    The ventral visual pathway achieves object and face recognition by building transformation-invariant representations from elementary visual features. In previous computer simulation studies with rate-coded neural networks, the development of transformation-invariant representations has been demonstrated using either of two biologically plausible learning mechanisms, Trace learning and Continuous Transformation (CT) learning. However, it has not previously been investigated how transformation-invariant representations may be learned in a more biologically accurate spiking neural network. A key issue is how the synaptic connection strengths in such a spiking network might self-organize through Spike-Time Dependent Plasticity (STDP) where the change in synaptic strength is dependent on the relative times of the spikes emitted by the presynaptic and postsynaptic neurons rather than simply correlated activity driving changes in synaptic efficacy. Here we present simulations with conductance-based integrate-and-fire (IF) neurons using a STDP learning rule to address these gaps in our understanding. It is demonstrated that with the appropriate selection of model parameters and training regime, the spiking network model can utilize either Trace-like or CT-like learning mechanisms to achieve transform-invariant representations.

  16. Transform-invariant visual representations in self-organizing spiking neural networks

    Directory of Open Access Journals (Sweden)

    Benjamin eEvans

    2012-07-01

    Full Text Available The ventral visual pathway achieves object and face recognition by building transform-invariant representations from elementary visual features. In previous computer simulation studies with rate-coded neural networks, the development of transform invariant representations has been demonstrated using either of two biologically plausible learning mechanisms, Trace learning and Continuous Transformation (CT learning. However, it has not previously been investigated how transform invariant representations may be learned in a more biologically accurate spiking neural network. A key issue is how the synaptic connection strengths in such a spiking network might self-organize through Spike-Time Dependent Plasticity (STDP where the change in synaptic strength is dependent on the relative times of the spikes emitted by the pre- and postsynaptic neurons rather than simply correlated activity driving changes in synaptic efficacy. Here we present simulations with conductance-based integrate-and-fire (IF neurons using a STDP learning rule to address these gaps in our understanding. It is demonstrated that with the appropriate selection of model pa- rameters and training regime, the spiking network model can utilize either Trace-like or CT-like learning mechanisms to achieve transform-invariant representations.

  17. Niche-dependent development of functional neuronal networks from embryonic stem cell-derived neural populations

    Directory of Open Access Journals (Sweden)

    Siebler Mario

    2009-08-01

    Full Text Available Abstract Background The present work was performed to investigate the ability of two different embryonic stem (ES cell-derived neural precursor populations to generate functional neuronal networks in vitro. The first ES cell-derived neural precursor population was cultivated as free-floating neural aggregates which are known to form a developmental niche comprising different types of neural cells, including neural precursor cells (NPCs, progenitor cells and even further matured cells. This niche provides by itself a variety of different growth factors and extracellular matrix proteins that influence the proliferation and differentiation of neural precursor and progenitor cells. The second population was cultivated adherently in monolayer cultures to control most stringently the extracellular environment. This population comprises highly homogeneous NPCs which are supposed to represent an attractive way to provide well-defined neuronal progeny. However, the ability of these different ES cell-derived immature neural cell populations to generate functional neuronal networks has not been assessed so far. Results While both precursor populations were shown to differentiate into sufficient quantities of mature NeuN+ neurons that also express GABA or vesicular-glutamate-transporter-2 (vGlut2, only aggregate-derived neuronal populations exhibited a synchronously oscillating network activity 2–4 weeks after initiating the differentiation as detected by the microelectrode array technology. Neurons derived from homogeneous NPCs within monolayer cultures did merely show uncorrelated spiking activity even when differentiated for up to 12 weeks. We demonstrated that these neurons exhibited sparsely ramified neurites and an embryonic vGlut2 distribution suggesting an inhibited terminal neuronal maturation. In comparison, neurons derived from heterogeneous populations within neural aggregates appeared as fully mature with a dense neurite network and punctuated

  18. Development of infill drilling recovery models for carbonates reservoirs using neural networks and multivariate statistical as a novel method

    International Nuclear Information System (INIS)

    Soto, R; Wu, Ch. H; Bubela, A M

    1999-01-01

    This work introduces a novel methodology to improve reservoir characterization models. In this methodology we integrated multivariate statistical analyses, and neural network models for forecasting the infill drilling ultimate oil recovery from reservoirs in San Andres and Clearfork carbonate formations in west Texas. Development of the oil recovery forecast models help us to understand the relative importance of dominant reservoir characteristics and operational variables, reproduce recoveries for units included in the database, forecast recoveries for possible new units in similar geological setting, and make operational (infill drilling) decisions. The variety of applications demands the creation of multiple recovery forecast models. We have developed intelligent software (Soto, 1998), oilfield intelligence (01), as an engineering tool to improve the characterization of oil and gas reservoirs. 01 integrates neural networks and multivariate statistical analysis. It is composed of five main subsystems: data input, preprocessing, architecture design, graphic design, and inference engine modules. One of the challenges in this research was to identify the dominant and the optimum number of independent variables. The variables include porosity, permeability, water saturation, depth, area, net thickness, gross thickness, formation volume factor, pressure, viscosity, API gravity, number of wells in initial water flooding, number of wells for primary recovery, number of infill wells over the initial water flooding, PRUR, IWUR, and IDUR. Multivariate principal component analysis is used to identify the dominant and the optimum number of independent variables. We compared the results from neural network models with the non-parametric approach. The advantage of the non-parametric regression is that it is easy to use. The disadvantage is that it retains a large variance of forecast results for a particular data set. We also used neural network concepts to develop recovery

  19. Glial processes at the Drosophila larval neuromuscular junction match synaptic growth.

    Directory of Open Access Journals (Sweden)

    Deidre L Brink

    Full Text Available Glia are integral participants in synaptic physiology, remodeling and maturation from blowflies to humans, yet how glial structure is coordinated with synaptic growth is unknown. To investigate the dynamics of glial development at the Drosophila larval neuromuscular junction (NMJ, we developed a live imaging system to establish the relationship between glia, neuronal boutons, and the muscle subsynaptic reticulum. Using this system we observed processes from two classes of peripheral glia present at the NMJ. Processes from the subperineurial glia formed a blood-nerve barrier around the axon proximal to the first bouton. Processes from the perineurial glial extended beyond the end of the blood-nerve barrier into the NMJ where they contacted synapses and extended across non-synaptic muscle. Growth of the glial processes was coordinated with NMJ growth and synaptic activity. Increasing synaptic size through elevated temperature or the highwire mutation increased the extent of glial processes at the NMJ and conversely blocking synaptic activity and size decreased the presence and size of glial processes. We found that elevated temperature was required during embryogenesis in order to increase glial expansion at the nmj. Therefore, in our live imaging system, glial processes at the NMJ are likely indirectly regulated by synaptic changes to ensure the coordinated growth of all components of the tripartite larval NMJ.

  20. Plasticity resembling spike-timing dependent synaptic plasticity: the evidence in human cortex

    Directory of Open Access Journals (Sweden)

    Florian Müller-Dahlhaus

    2010-07-01

    Full Text Available Spike-timing dependent plasticity (STDP has been studied extensively in a variety of animal models during the past decade but whether it can be studied at the systems level of the human cortex has been a matter of debate. Only recently newly developed non-invasive brain stimulation techniques such as transcranial magnetic stimulation (TMS have made it possible to induce and assess timing dependent plasticity in conscious human subjects. This review will present a critical synopsis of these experiments, which suggest that several of the principal characteristics and molecular mechanisms of TMS-induced plasticity correspond to those of STDP as studied at a cellular level. TMS combined with a second phasic stimulation modality can induce bidirectional long-lasting changes in the excitability of the stimulated cortex, whose polarity depends on the order of the associated stimulus-evoked events within a critical time window of tens of milliseconds. Pharmacological evidence suggests an NMDA receptor mediated form of synaptic plasticity. Studies in human motor cortex demonstrated that motor learning significantly modulates TMS-induced timing dependent plasticity, and, conversely, may be modulated bidirectionally by prior TMS-induced plasticity, providing circumstantial evidence that long-term potentiation-like mechanisms may be involved in motor learning. In summary, convergent evidence is being accumulated for the contention that it is now possible to induce STDP-like changes in the intact human central nervous system by means of TMS to study and interfere with synaptic plasticity in neural circuits in the context of behaviour such as learning and memory.

  1. Nanowire FET Based Neural Element for Robotic Tactile Sensing Skin

    Directory of Open Access Journals (Sweden)

    William Taube Navaraj

    2017-09-01

    Full Text Available This paper presents novel Neural Nanowire Field Effect Transistors (υ-NWFETs based hardware-implementable neural network (HNN approach for tactile data processing in electronic skin (e-skin. The viability of Si nanowires (NWs as the active material for υ-NWFETs in HNN is explored through modeling and demonstrated by fabricating the first device. Using υ-NWFETs to realize HNNs is an interesting approach as by printing NWs on large area flexible substrates it will be possible to develop a bendable tactile skin with distributed neural elements (for local data processing, as in biological skin in the backplane. The modeling and simulation of υ-NWFET based devices show that the overlapping areas between individual gates and the floating gate determines the initial synaptic weights of the neural network - thus validating the working of υ-NWFETs as the building block for HNN. The simulation has been further extended to υ-NWFET based circuits and neuronal computation system and this has been validated by interfacing it with a transparent tactile skin prototype (comprising of 6 × 6 ITO based capacitive tactile sensors array integrated on the palm of a 3D printed robotic hand. In this regard, a tactile data coding system is presented to detect touch gesture and the direction of touch. Following these simulation studies, a four-gated υ-NWFET is fabricated with Pt/Ti metal stack for gates, source and drain, Ni floating gate, and Al2O3 high-k dielectric layer. The current-voltage characteristics of fabricated υ-NWFET devices confirm the dependence of turn-off voltages on the (synaptic weight of each gate. The presented υ-NWFET approach is promising for a neuro-robotic tactile sensory system with distributed computing as well as numerous futuristic applications such as prosthetics, and electroceuticals.

  2. Kalirin-7 is necessary for normal NMDA receptor-dependent synaptic plasticity

    KAUST Repository

    Lemtiri-Chlieh, Fouad; Zhao, Liangfang; Kiraly, Drew D; Eipper, Betty A; Mains, Richard E; Levine, Eric S

    2011-01-01

    to stimulation is considered to be of paramount importance during the development of synaptic plasticity. Indeed, long-term potentiation (LTP), widely believed to be a cellular correlate of learning and memory, has been repeatedly shown to induce both spine

  3. Amine Neurotransmitter Regulation of Long-Term Synaptic Plasticity in Hippocampus.

    Science.gov (United States)

    1987-04-27

    T.H. ontrol theory applied to neural networks illuminates synaptic basis of interictal epileptiform activity. In: Basic Mechanimw of the Epilepsies...the activity of voltage-dqmxfdm* calcium dwas in hixocaupal nerone . Nature (in press). atecir.U P. A., pebeda,# F. J., a nd Jduutoni, D. 4...Annual Synposium on Networks in Brain and ompiter Arhitecture at North Texas State University in Denton. Oct. 22-25 Attended Neurdehavioral Research

  4. The Roles of Cortical Slow Waves in Synaptic Plasticity and Memory Consolidation

    OpenAIRE

    Miyamoto, Daisuke; Hirai, Daichi; Murayama, Masanori

    2017-01-01

    Sleep plays important roles in sensory and motor memory consolidation. Sleep oscillations, reflecting neural population activity, involve the reactivation of learning-related neurons and regulate synaptic strength and, thereby affect memory consolidation. Among sleep oscillations, slow waves (0.5–4 Hz) are closely associated with memory consolidation. For example, slow-wave power is regulated in an experience-dependent manner and correlates with acquired memory. Furthermore, manipulating slow...

  5. Development of relative humidity models by using optimized neural network structures

    Energy Technology Data Exchange (ETDEWEB)

    Martinez-romero, A.; Ortega, J. F.; Juan, J. A.; Tarjuelo, J. M.; Moreno, M. A.

    2010-07-01

    Climate has always had a very important role in life on earth, as well as human activity and health. The influence of relative humidity (RH) in controlled environments (e.g. industrial processes in agro-food processing, cold storage of foods such as fruits, vegetables and meat, or controls in greenhouses) is very important. Relative humidity is a main factor in agricultural production and crop yield (due to the influence on crop water demand or the development and distribution of pests and diseases, for example). The main objective of this paper is to estimate RH [maximum (RHmax), average (RHave), and minimum (RHmin)] data in a specific area, being applied to the Region of Castilla-La Mancha (C-LM) in this case, from available data at thermo-pluviometric weather stations. In this paper Artificial neural networks (ANN) are used to generate RH considering maximum and minimum temperatures and extraterrestrial solar radiation data. Model validation and generation is based on data from the years 2000 to 2008 from 44 complete agroclimatic weather stations. Relative errors are estimated as 1) spatial errors of 11.30%, 6.80% and 10.27% and 2) temporal errors of 10.34%, 6.59% and 9.77% for RHmin, RHmax and RHave, respectively. The use of ANNs is interesting in generating climate parameters from available climate data. For determining optimal ANN structure in estimating RH values, model calibration and validation is necessary, considering spatial and temporal variability. (Author) 44 refs.

  6. Neural development of mentalizing in moral judgment from adolescence to adulthood.

    Science.gov (United States)

    Harenski, Carla L; Harenski, Keith A; Shane, Matthew S; Kiehl, Kent A

    2012-01-01

    The neural mechanisms underlying moral judgment have been extensively studied in healthy adults. How these mechanisms evolve from adolescence to adulthood has received less attention. Brain regions that have been consistently implicated in moral judgment in adults, including the superior temporal cortex and prefrontal cortex, undergo extensive developmental changes from adolescence to adulthood. Thus, their role in moral judgment may also change over time. In the present study, 51 healthy male participants age 13–53 were scanned with functional magnetic resonance imaging (fMRI) while they viewed pictures that did or did not depict situations considered by most individuals to represent moral violations, and rated their degree of moral violation severity. Consistent with predictions, a regression analysis revealed a positive correlation between age and hemodynamic activity in the temporo-parietal junction when participants made decisions regarding moral severity.This region is known to contribute to mentalizing processes during moral judgment in adults and suggests that adolescents use these types of inferences less during moral judgment than do adults. A positive correlation with age was also present in the posterior cingulate. Overall, the results suggest that the brain regions utilized in moral judgment change over development.

  7. The SWI/SNF BAF-A complex is essential for neural crest development.

    Science.gov (United States)

    Chandler, Ronald L; Magnuson, Terry

    2016-03-01

    Growing evidence indicates that chromatin remodeler mutations underlie the pathogenesis of human neurocristopathies or disorders that affect neural crest cells (NCCs). However, causal relationships among chromatin remodeler subunit mutations and NCC defects remain poorly understood. Here we show that homozygous loss of ARID1A-containing, SWI/SNF chromatin remodeling complexes (BAF-A) in NCCs results in embryonic lethality in mice, with mutant embryos succumbing to heart defects. Strikingly, monoallelic loss of ARID1A in NCCs led to craniofacial defects in adult mice, including shortened snouts and low set ears, and these defects were more pronounced following homozygous loss of ARID1A, with the ventral cranial bones being greatly reduced in size. Early NCC specification and expression of the BRG1 NCC target gene, PLEXINA2, occurred normally in the absence of ARID1A. Nonetheless, mutant embryos displayed incomplete conotruncal septation of the cardiac outflow tract and defects in the posterior pharyngeal arteries, culminating in persistent truncus arteriosus and agenesis of the ductus arteriosus. Consistent with this, migrating cardiac NCCs underwent apoptosis within the circumpharyngeal ridge. Our data support the notion that multiple, distinct chromatin remodeling complexes govern genetically separable events in NCC development and highlight a potential pathogenic role for NCCs in the human BAF complex disorder, Coffin-Siris Syndrome. Copyright © 2016 Elsevier Inc. All rights reserved.

  8. Effects of stevia on synaptic plasticity and NADPH oxidase level of CNS in conditions of metabolic disorders caused by fructose.

    Science.gov (United States)

    Chavushyan, V A; Simonyan, K V; Simonyan, R M; Isoyan, A S; Simonyan, G M; Babakhanyan, M A; Hovhannisyian, L E; Nahapetyan, Kh H; Avetisyan, L G; Simonyan, M A

    2017-12-19

    Excess dietary fructose intake associated with metabolic syndrome and insulin resistance and increased risk of developing type 2 diabetes. Previous animal studies have reported that diabetic animals have significantly impaired behavioural and cognitive functions, pathological synaptic function and impaired expression of glutamate receptors. Correction of the antioxidant status of laboratory rodents largely prevents the development of fructose-induced plurimetabolic changes in the nervous system. We suggest a novel concept of efficiency of Stevia leaves for treatment of central diabetic neuropathy. By in vivo extracellular studies induced spike activity of hippocampal neurons during high frequency stimulation of entorhinal cortex, as well as neurons of basolateral amygdala to high-frequency stimulation of the hippocampus effects of Stevia rebaudiana Bertoni plant evaluated in synaptic activity in the brain of fructose-enriched diet rats. In the conditions of metabolic disorders caused by fructose, antioxidant activity of Stevia rebaudiana was assessed by measuring the NOX activity of the hippocampus, amygdala and spinal cord. In this study, the characteristic features of the metabolic effects of dietary fructose on synaptic plasticity in hippocampal neurons and basolateral amygdala and the state of the NADPH oxidase (NOX) oxidative system of these brain formations are revealed, as well as the prospects for development of multitarget and polyfunctional phytopreparations (with adaptogenic, antioxidant, antidiabetic, nootropic activity) from native raw material of Stevia rebaudiana. Stevia modulates degree of expressiveness of potentiation/depression (approaches but fails to achieve the norm) by shifting the percentage balance in favor of depressor type of responses during high-frequency stimulation, indicating its adaptogenic role in plasticity of neural networks. Under the action of fructose an increase (3-5 times) in specific quantity of total fraction of NOX

  9. Forebrain deletion of αGDI in adult mice worsens the pre-synaptic deficit at cortico-lateral amygdala synaptic connections.

    Directory of Open Access Journals (Sweden)

    Veronica Bianchi

    Full Text Available The GDI1 gene encodes αGDI, which retrieves inactive GDP-bound RAB from membranes to form a cytosolic pool awaiting vesicular release. Mutations in GDI1 are responsible for X-linked Intellectual Disability. Characterization of the Gdi1-null mice has revealed alterations in the total number and distribution of hippocampal and cortical synaptic vesicles, hippocampal short-term synaptic plasticity and specific short-term memory deficits in adult mice, which are possibly caused by alterations of different synaptic vesicle recycling pathways controlled by several RAB GTPases. However, interpretation of these studies is complicated by the complete ablation of Gdi1 in all cells in the brain throughout development. In this study, we generated conditionally gene-targeted mice in which the knockout of Gdi1 is restricted to the forebrain, hippocampus, cortex and amygdala and occurs only during postnatal development. Adult mutant mice reproduce the short-term memory deficit previously reported in Gdi1-null mice. Surprisingly, the delayed ablation of Gdi1 worsens the pre-synaptic phenotype at cortico-amygdala synaptic connections compared to Gdi1-null mice. These results suggest a pivotal role of αGDI via specific RAB GTPases acting specifically in forebrain regions at the pre-synaptic sites involved in memory formation.

  10. NETS - A NEURAL NETWORK DEVELOPMENT TOOL, VERSION 3.0 (MACHINE INDEPENDENT VERSION)

    Science.gov (United States)

    Baffes, P. T.

    1994-01-01

    NETS, A Tool for the Development and Evaluation of Neural Networks, provides a simulation of Neural Network algorithms plus an environment for developing such algorithms. Neural Networks are a class of systems modeled after the human brain. Artificial Neural Networks are formed from hundreds or thousands of simulated neurons, connected to each other in a manner similar to brain neurons. Problems which involve pattern matching readily fit the class of problems which NETS is designed to solve. NETS uses the back propagation learning method for all of the networks which it creates. The nodes of a network are usually grouped together into clumps called layers. Generally, a network will have an input layer through which the various environment stimuli are presented to the network, and an output layer for determining the network's response. The number of nodes in these two layers is usually tied to some features of the problem being solved. Other layers, which form intermediate stops between the input and output layers, are called hidden layers. NETS allows the user to customize the patterns of connections between layers of a network. NETS also provides features for saving the weight values of a network during the learning process, which allows for more precise control over the learning process. NETS is an interpreter. Its method of execution is the familiar "read-evaluate-print" loop found in interpreted languages such as BASIC and LISP. The user is presented with a prompt which is the simulator's way of asking for input. After a command is issued, NETS will attempt to evaluate the command, which may produce more prompts requesting specific information or an error if the command is not understood. The typical process involved when using NETS consists of translating the problem into a format which uses input/output pairs, designing a network configuration for the problem, and finally training the network with input/output pairs until an acceptable error is reached. NETS

  11. NETS - A NEURAL NETWORK DEVELOPMENT TOOL, VERSION 3.0 (MACINTOSH VERSION)

    Science.gov (United States)

    Phillips, T. A.

    1994-01-01

    NETS, A Tool for the Development and Evaluation of Neural Networks, provides a simulation of Neural Network algorithms plus an environment for developing such algorithms. Neural Networks are a class of systems modeled after the human brain. Artificial Neural Networks are formed from hundreds or thousands of simulated neurons, connected to each other in a manner similar to brain neurons. Problems which involve pattern matching readily fit the class of problems which NETS is designed to solve. NETS uses the back propagation learning method for all of the networks which it creates. The nodes of a network are usually grouped together into clumps called layers. Generally, a network will have an input layer through which the various environment stimuli are presented to the network, and an output layer for determining the network's response. The number of nodes in these two layers is usually tied to some features of the problem being solved. Other layers, which form intermediate stops between the input and output layers, are called hidden layers. NETS allows the user to customize the patterns of connections between layers of a network. NETS also provides features for saving the weight values of a network during the learning process, which allows for more precise control over the learning process. NETS is an interpreter. Its method of execution is the familiar "read-evaluate-print" loop found in interpreted languages such as BASIC and LISP. The user is presented with a prompt which is the simulator's way of asking for input. After a command is issued, NETS will attempt to evaluate the command, which may produce more prompts requesting specific information or an error if the command is not understood. The typical process involved when using NETS consists of translating the problem into a format which uses input/output pairs, designing a network configuration for the problem, and finally training the network with input/output pairs until an acceptable error is reached. NETS

  12. 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

  13. Compensating for Thalamocortical Synaptic Loss in Alzheimer’s Disease

    Directory of Open Access Journals (Sweden)

    Kamal eAbuhassan

    2014-06-01

    Full Text Available The study presents a thalamocortical network model which oscillates within the alpha frequency band (8-13 Hz as recorded in the wakeful relaxed state with closed eyes to study the neural causes of abnormal oscillatory activity in Alzheimer’s disease (AD. Incorporated within the model are various types of cortical excitatory and inhibitory neurons, recurrently connected to thalamic and reticular thalamic regions with the ratios and distances derived from the mammalian thalamocortical system. The model is utilized to study the impacts of four types of connectivity loss on the model’s spectral dynamics. The study focuses on investigating degeneration of corticocortical, thalamocortical, corticothalamic and corticoreticular couplings, with an emphasis on the influence of each modelled case on the spectral output of the model. Synaptic compensation has been included in each model to examine the interplay between synaptic deletion and compensation mechanisms, and the oscillatory activity of the network. The results of power spectra and event related desynchronisation/synchronisation (ERD/S analyses show that the dynamics of the thalamic and cortical oscillations are significantly influenced by corticocortical synaptic loss. Interestingly, the patterns of changes in thalamic spectral activity are correlated with those in the cortical model. Similarly, the thalamic oscillatory activity is diminished after partial corticothalamic denervation. The results suggest that thalamic atrophy is a secondary pathology to cortical shrinkage in Alzheimer’s disease. In addition, this study finds that the inhibition from neurons in the thalamic reticular nucleus (RTN to thalamic relay (TCR neurons plays a key role in regulating thalamic oscillations; disinhibition disrupts thalamic oscillatory activity even though TCR neurons are more depolarized after being released from RTN inhibition. This study provides information that can be explored experimentally to

  14. 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.

  15. Chronic Swimming Exercise Ameliorates Low-Soybean-Oil Diet-Induced Spatial Memory Impairment by Enhancing BDNF-Mediated Synaptic Potentiation in Developing Spontaneously Hypertensive Rats.

    Science.gov (United States)

    Cheng, Mei; Cong, Jiyan; Wu, Yulong; Xie, Jiacun; Wang, Siyuan; Zhao, Yue; Zang, Xiaoying

    2018-05-01

    Exercise and low-fat diets are common lifestyle modifications used for the treatment of hypertension besides drug therapy. However, unrestrained low-fat diets may result in deficiencies of low-unsaturated fatty acids and carry contingent risks of delaying neurodevelopment. While aerobic exercise shows positive neuroprotective effects, it is still unclear whether exercise could alleviate the impairment of neurodevelopment that may be induced by certain low-fat diets. In this research, developing spontaneously hypertensive rats (SHR) were treated with chronic swimming exercise and/or a low-soybean-oil diet for 6 weeks. We found that performance in the Morris water maze was reduced and long-term potentiation in the hippocampus was suppressed by the diet, while a combination treatment of exercise and diet alleviated the impairment induced by the specific low-fat diet. Moreover, the combination treatment effectively increased the expression of brain-derived neurotrophic factor (BDNF) and N-methyl-D-aspartic acid receptor (NMDAR), which were both down-regulated by the low-soybean-oil diet in the hippocampus of developing SHR. These findings suggest that chronic swimming exercise can ameliorate the low-soybean-oil diet-induced learning and memory impairment in developing SHR through the up-regulation of BDNF and NMDAR expression.

  16. Neural Synchronization and Cryptography

    Science.gov (United States)

    Ruttor, Andreas

    2007-11-01

    Neural networks can synchronize by learning from each other. In the case of discrete weights full synchronization is achieved in a finite number of steps. Additional networks can be trained by using the inputs and outputs generated during this process as examples. Several learning rules for both tasks are presented and analyzed. In the case of Tree Parity Machines synchronization is much faster than learning. Scaling laws for the number of steps needed for full synchronization and successful learning are derived using analytical models. They indicate that the difference between both processes can be controlled by changing the synaptic depth. In the case of bidirectional interaction the synchronization time increases proportional to the square of this parameter, but it grows exponentially, if information is transmitted in one direction only. Because of this effect neural synchronization can be used to construct a cryptographic key-exchange protocol. Here the partners benefit from mutual interaction, so that a passive attacker is usually unable to learn the generated key in time. The success probabilities of different attack methods are determined by numerical simulations and scaling laws are derived from the data. They show that the partners can reach any desired level of security by just increasing the synaptic depth. Then the complexity of a successful attack grows exponentially, but there is only a polynomial increase of the effort needed to generate a key. Further improvements of security are possible by replacing the random inputs with queries generated by the partners.

  17. Myopic (HD-PTP, PTPN23) selectively regulates synaptic neuropeptide release.

    Science.gov (United States)

    Bulgari, Dinara; Jha, Anupma; Deitcher, David L; Levitan, Edwin S

    2018-02-13

    Neurotransmission is mediated by synaptic exocytosis of neuropeptide-containing dense-core vesicles (DCVs) and small-molecule transmitter-containing small synaptic vesicles (SSVs). Exocytosis of both vesicle types depends on Ca 2+ and shared secretory proteins. Here, we show that increasing or decreasing expression of Myopic (mop, HD-PTP, PTPN23), a Bro1 domain-containing pseudophosphatase implicated in neuronal development and neuropeptide gene expression, increases synaptic neuropeptide stores at the Drosophila neuromuscular junction (NMJ). This occurs without altering DCV content or transport, but synaptic DCV number and age are increased. The effect on synaptic neuropeptide stores is accounted for by inhibition of activity-induced Ca 2+ -dependent neuropeptide release. cAMP-evoked Ca 2+ -independent synaptic neuropeptide release also requires optimal Myopic expression, showing that Myopic affects the DCV secretory machinery shared by cAMP and Ca 2+ pathways. Presynaptic Myopic is abundant at early endosomes, but interaction with the endosomal sorting complex required for transport III (ESCRT III) protein (CHMP4/Shrub) that mediates Myopic's effect on neuron pruning is not required for control of neuropeptide release. Remarkably, in contrast to the effect on DCVs, Myopic does not affect release from SSVs. Therefore, Myopic selectively regulates synaptic DCV exocytosis that mediates peptidergic transmission at the NMJ.

  18. Synaptic heterogeneity and stimulus-induced modulation of depression in central synapses.

    Science.gov (United States)

    Hunter, J D; Milton, J G

    2001-08-01

    Short-term plasticity is a pervasive feature of synapses. Synapses exhibit many forms of plasticity operating over a range of time scales. We develop an optimization method that allows rapid characterization of synapses with multiple time scales of facilitation and depression. Investigation of paired neurons that are postsynaptic to the same identified interneuron in the buccal ganglion of Aplysia reveals that the responses of the two neurons differ in the magnitude of synaptic depression. Also, for single neurons, prolonged stimulation of the presynaptic neuron causes stimulus-induced increases in the early phase of synaptic depression. These observations can be described by a model that incorporates two availability factors, e.g., depletable vesicle pools or desensitizing receptor populations, with different time courses of recovery, and a single facilitation component. This model accurately predicts the responses to novel stimuli. The source of synaptic heterogeneity is identified with variations in the relative sizes of the two availability factors, and the stimulus-induced decrement in the early synaptic response is explained by a slowing of the recovery rate of one of the availability factors. The synaptic heterogeneity and stimulus-induced modifications in synaptic depression observed here emphasize that synaptic efficacy depends on both the individual properties of synapses and their past history.

  19. Development of 99mTc agents for imaging central neural system receptors

    International Nuclear Information System (INIS)

    2004-01-01

    Radiopharmaceuticals that bind to central neural system (CNS) receptors in vivo are potentially useful for understanding the pathophysiology of anumber of neurological and psychiatric disorders, their diagnosis and treatment. Carbon-11 labelled compounds and positron emission tomography(PET) imaging have played a vital role in establishing the usefulness of imaging the dopaminergic, cholinergic, serotonergic and benzodiazapine receptors, and relating the receptor density to disease status. Since the use of 11C agents is constrained due to their 20 min half-life, various radiohalogenated analogues based on the structure of 11C compounds have been successfully developed, providing comparable information. Iodine- 123 is the most widely employed of these radioisotopes; it has a longer, 13 h, half-life. Through the use of 123I, there has been a steady growth in CNS receptor imaging studies employing single photon emission computerized tomography (SPECT). SPECT, as compared with PET, has slightly inferior image resolution but has the advantage of being readily available worldwide. However, the 123I radiopharmaceutical is expensive and the distribution system outside of the major markets is not well developed for its supply on a routine basis. The ideal radioisotope for SPECT imaging is 99mTc, due to its low cost per dose, availability through commercially available generator systems and physical decay characteristics. Over 80% of all diagnostic nuclear medicine imaging studies worldwide are conducted using this radioisotope. Development of 99mTc radiopharmaceuticals for imaging CNS receptors is therefore of considerable importance. On the basis of the recommendations of a consultants meeting, the International Atomic Energy Agency (IAEA) initiated in 1996 a Co-ordinated Research Project (CRP) on Development of Agents for Imaging CNS Receptors based on 99mTc. At that time there were no 99mTc CNS receptor imaging radiopharmaceuticals available even though work on

  20. Neural substrates of view-invariant object recognition developed without experiencing rotations of the objects.

    Science.gov (United States)

    Okamura, Jun-Ya; Yamaguchi, Reona; Honda, Kazunari; Wang, Gang; Tanaka, Keiji

    2014-11-05

    One fails to recognize an unfamiliar object across changes in viewing angle when it must be discriminated from similar distractor objects. View-invariant recognition gradually develops as the viewer repeatedly sees the objects in rotation. It is assumed that different views of each object are associated with one another while their successive appearance is experienced in rotation. However, natural experience of objects also contains ample opportunities to discriminate among objects at each of the multiple viewing angles. Our previous behavioral experiments showed that after experiencing a new set of object stimuli during a task that required only discrimination at each of four viewing angles at 30° intervals, monkeys could recognize the objects across changes in viewing angle up to 60°. By recording activities of neurons from the inferotemporal cortex after various types of preparatory experience, we here found a possible neural substrate for the monkeys' performance. For object sets that the monkeys had experienced during the task that required only discrimination at each of four viewing angles, many inferotemporal neurons showed object selectivity covering multiple views. The degree of view generalization found for these object sets was similar to that found for stimulus sets with which the monkeys had been trained to conduct view-invariant recognition. These results suggest that the experience of discriminating new objects in each of several viewing angles develops the partially view-generalized object selectivity distributed over many neurons in the inferotemporal cortex, which in turn bases the monkeys' emergent capability to discriminate the objects across changes in viewing angle. Copyright © 2014 the authors 0270-6474/14/3415047-13$15.00/0.

  1. Music perception and cognition: development, neural basis, and rehabilitative use of music.

    Science.gov (United States)

    Särkämö, Teppo; Tervaniemi, Mari; Huotilainen, Minna

    2013-07-01

    Music is a highly versatile form of art and communication that has been an essential part of human society since its early days. Neuroimaging studies indicate that music is a powerful stimulus also for the human brain, engaging not just the auditory cortex but also a vast, bilateral network of temporal, frontal, parietal, cerebellar, and limbic brain areas that govern auditory perception, syntactic and semantic processing, attention and memory, emotion and mood control, and motor skills. Studies of amusia, a severe form of musical impairment, highlight the right temporal and frontal cortices as the core neural substrates for adequate perception and production of music. Many of the basic auditory and musical skills, such as pitch and timbre perception, start developing already in utero, and babies are born with a natural preference for music and singing. Music has many important roles and functions throughout life, ranging from emotional self-regulation, mood enhancement, and identity formation to promoting the development of verbal, motor, cognitive, and social skills and maintaining their healthy functioning in old age. Music is also used clinically as a part of treatment in many illnesses, which involve affective, attention, memory, communication, or motor deficits. Although more research is still needed, current evidence suggests that music-based rehabilitation can be effective in many developmental, psychiatric, and neurological disorders, such as autism, depression, schizophrenia, and stroke, as well as in many chronic somatic illnesses that cause pain and anxiety. WIREs Cogn Sci 2013, 4:441-451. doi: 10.1002/wcs.1237 The authors have declared no conflicts of interest for this article. For further resources related to this article, please visit the WIREs website. Copyright © 2013 John Wiley & Sons, Ltd.

  2. Supervised Learning in Spiking Neural Networks for Precise Temporal Encoding.

    Science.gov (United States)

    Gardner, Brian; Grüning, André

    2016-01-01

    Precise spike timing as a means to encode information in neural networks is biologically supported, and is advantageous over frequency-based codes by processing input features on a much shorter time-scale. For these reasons, much recent attention has been focused on the development of supervised learning rules for spiking neural networks that utilise a temporal coding scheme. However, despite significant progress in this area, there still lack rules that have a theoretical basis, and yet can be considered biologically relevant. Here we examine the general conditions under which synaptic plasticity most effectively takes place to support the supervised learning of a precise temporal code. As part of our analysis we examine two spike-based learning methods: one of which relies on an instantaneous error signal to modify synaptic weights in a network (INST rule), and the other one relying on a filtered error signal for smoother synaptic weight modifications (FILT rule). We test the accuracy of the solutions provided by each rule with respect to their temporal encoding precision, and then measure the maximum number of input patterns they can learn to memorise using the precise timings of individual spikes as an indication of their storage capacity. Our results demonstrate the high performance of the FILT rule in most cases, underpinned by the rule's error-filtering mechanism, which is predicted to provide smooth convergence towards a desired solution during learning. We also find the FILT rule to be most efficient at performing input pattern memorisations, and most noticeably when patterns are identified using spikes with sub-millisecond temporal precision. In comparison with existing work, we determine the performance of the FILT rule to be consistent with that of the highly efficient E-learning Chronotron rule, but with the distinct advantage that our FILT rule is also implementable as an online method for increased biological realism.

  3. Myostatin-like proteins regulate synaptic function and neuronal morphology.

    Science.gov (United States)

    Augustin, Hrvoje; McGourty, Kieran; Steinert, Joern R; Cochemé, Helena M; Adcott, Jennifer; Cabecinha, Melissa; Vincent, Alec; Halff, Els F; Kittler, Josef T; Boucrot, Emmanuel; Partridge, Linda

    2017-07-01

    Growth factors of the TGFβ superfamily play key roles in regulating neuronal and muscle function. Myostatin (or GDF8) and GDF11 are potent negative regulators of skeletal muscle mass. However, expression of myostatin and its cognate receptors in other tissues, including brain and peripheral nerves, suggests a potential wider biological role. Here, we show that Myoglianin (MYO), the Drosophila homolog of myostatin and GDF11, regulates not only body weight and muscle size, but also inhibits neuromuscular synapse strength and composition in a Smad2-dependent manner. Both myostatin and GDF11 affected synapse formation in isolated rat cortical neuron cultures, suggesting an effect on synaptogenesis beyond neuromuscular junctions. We also show that MYO acts in vivo to inhibit synaptic transmission between neurons in the escape response neural circuit of adult flies. Thus, these anti-myogenic proteins act as important inhibitors of synapse function and neuronal growth. © 2017. Published by The Company of Biologists Ltd.

  4. Development and evaluation of neural network models to estimate daily solar radiation at Córdoba, Argentina

    International Nuclear Information System (INIS)

    Bocco, M.

    2006-01-01

    The objective of this work was to develop neural network models of backpropagation type to estimate solar radiation based on extraterrestrial radiation data, daily temperature range, precipitation, cloudiness and relative sunshine duration. Data from Córdoba, Argentina, were used for development and validation. The behaviour and adjustment between values observed and estimates obtained by neural networks for different combinations of input were assessed. These estimations showed root mean square error between 3.15 and 3.88 MJ m -2 d -1 . The latter corresponds to the model that calculates radiation using only precipitation and daily temperature range. In all models, results show good adjustment to seasonal solar radiation. These results allow inferring the adequate performance and pertinence of this methodology to estimate complex phenomena, such as solar radiation [pt

  5. Molecular mechanisms of synaptic remodeling in alcoholism.

    Science.gov (United States)

    Kyzar, Evan J; Pandey, Subhash C

    2015-08-05

    Alcohol use and alcohol addiction represent dysfunctional brain circuits resulting from neuroadaptive changes during protracted alcohol exposure and its withdrawal. Alcohol exerts a potent effect on synaptic plasticity and dendritic spine formation in specific brain regions, providing a neuroanatomical substrate for the pathophysiology of alcoholism. Epigenetics has recently emerged as a critical regulator of gene expression and synaptic plasticity-related events in the brain. Alcohol exposure and withdrawal induce changes in crucial epigenetic processes in the emotional brain circuitry (amygdala) that may be relevant to the negative affective state defined as the "dark side" of addiction. Here, we review the literature concerning synaptic plasticity and epigenetics, with a particular focus on molecular events related to dendritic remodeling during alcohol abuse and alcoholism. Targeting epigenetic processes that modulate synaptic plasticity may yield novel treatments for alcoholism. Published by Elsevier Ireland Ltd.

  6. Dissecting CNBP, a zinc-finger protein required for neural crest development, in its structural and functional domains.

    Science.gov (United States)

    Armas, Pablo; Agüero, Tristán H; Borgognone, Mariana; Aybar, Manuel J; Calcaterra, Nora B

    2008-10-17

    Cellular nucleic-acid-binding protein (CNBP) plays an essential role in forebrain and craniofacial development by controlling cell proliferation and survival to mediate neural crest expansion. CNBP binds to single-stranded nucleic acids and displays nucleic acid chaperone activity in vitro. The CNBP family shows a conserved modular organization of seven Zn knuckles and an arginine-glycine-glycine (RGG) box between the first and second Zn knuckles. The participation of these structural motifs in CNBP biochemical activities has still not been addressed. Here, we describe the generation of CNBP mutants that dissect the protein into regions with structurally and functionally distinct properties. Mutagenesis approaches were followed to generate: (i) an amino acid replacement that disrupted the fifth Zn knuckle; (ii) N-terminal deletions that removed the first Zn knuckle and the RGG box, or the RGG box alone; and (iii) a C-terminal deletion that eliminated the three last Zn knuckles. Mutant proteins were overexpressed in Escherichia coli, purified, and used to analyze their biochemical features in vitro, or overexpressed in Xenopus laevis embryos to study their function in vivo during neural crest cell development. We found that the Zn knuckles are required, but not individually essential, for CNBP biochemical activities, whereas the RGG box is essential for RNA-protein binding and nucleic acid chaperone activity. Removal of the RGG box allowed CNBP to preserve a weak single-stranded-DNA-binding capability. A mutant mimicking the natural N-terminal proteolytic CNBP form behaved as the RGG-deleted mutant. By gain-of-function and loss-of-function experiments in Xenopus embryos, we confirmed the participation of CNBP in neural crest development, and we demonstrated that the CNBP mutants lacking the N-terminal region or the RGG box alone may act as dominant negatives in vivo. Based on these data, we speculate about the existence of a specific proteolytic mechanism for the

  7. Development of a neural network technique for KSTAR Thomson scattering diagnostics

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Seung Hun, E-mail: leesh81@nfri.re.kr; Lee, J. H. [National Fusion Research Institute, 169-148 Gwahak-ro, Yuseong-gu, Daejeon 34133 (Korea, Republic of); Yamada, I. [National Institute Fusion Science, Toki, Gifu 509-5292 (Japan); Park, Jae Sun [Department of Physics, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon 34141 (Korea, Republic of)

    2016-11-15

    Neural networks provide powerful approaches of dealing with nonlinear data and have been successfully applied to fusion plasma diagnostics and control systems. Controlling tokamak plasmas in real time is essential to measure the plasma parameters in situ. However, the χ{sup 2} method traditionally used in Thomson scattering diagnostics hampers real-time measurement due to the complexity of the calculations involved. In this study, we applied a neural network approach to Thomson scattering diagnostics in order to calculate the electron temperature, comparing the results to those obtained with the χ{sup 2} method. The best results were obtained for 10{sup 3} training cycles and eight nodes in the hidden layer. Our neural network approach shows good agreement with the χ{sup 2} method and performs the calculation twenty times faster.

  8. Development of an artificial neural network to predict critical heat flux based on the look up tables

    Energy Technology Data Exchange (ETDEWEB)

    Terng, Nilton; Carajilescov, Pedro, E-mail: Nil.terng@gmail.com, E-mail: pedro.carajilescov@ufabc.edu.br [Universidade Federal do ABC (UFABC), Santo Andre, SP (Brazil). Centro de Engenharia, Modelagem e Ciencias Sociais

    2015-07-01

    The critical heat flux (CHF) is one of the principal thermal hydraulic limits of PWR type nuclear reactors. The present work consists in the development of an artificial neural network (ANN) to estimate the CHF, based on Look Up Table CHF data, published by Groeneveld (2006). Three parameters were considered in the development of the ANN: the pressure in the range of 1 to 21 MPa, the mass flux in the range of 50 to 8000 kg m{sup -2} s{sup -1} and the thermodynamic quality in the range of - 0.5 to 0.9. The ANN model considered was a multi feed forward net, which have two feedforward ANN. The first one, called main neural network, is used to calculate the result of CHF, and the second, denominated spacenet, is responsible to modify the main neural network according to the input. Comparing the ANN predictions with the data of the Look Up Table, it was observed an average of the ratio of 0.993 and a root mean square error of 13.3%. With the developed ANN, a parametric study of CHF was performed to observe the influence of each parameter in the CHF. It was possible to note that the CHF decreases with the increase of pressure and thermodynamic quality, while CHF increases with the mass flow rate, as expected. However, some erratic trends were also observed which can be attributed to either unknown aspect of the CHF phenomenon or uncertainties in the data. (author)

  9. Diprosopia revisited in light of the recognized role of neural crest cells in facial development.

    Science.gov (United States)

    Carles, D; Weichhold, W; Alberti, E M; Léger, F; Pigeau, F; Horovitz, J

    1995-01-01

    The aim of this study is to compare the theory of embryogenesis of the face with human diprosopia. This peculiar form of conjoined twinning is of great interest because 1) only the facial structures are duplicated and 2) almost all cases have a rather monomorphic pattern. The hypothesis is that an initial duplication of the notochord leads to two neural plates and subsequently duplicated neural crests. In those conditions, derivatives of the neural crests will be partially or totally duplicated; therefore, in diprosopia, the duplicated facial structures would be considered to be neural crest derivatives. If these structures are identical to those that are experimentally demonstrated to be neural crest derivatives in animals, these findings are an argument to apply this theory of facial embryogenesis in man. Serial horizontal sections of the face of two diprosopic fetuses (11 and 21 weeks gestation) were studied macro- and microscopically to determine the external and internal structures that are duplicated. Complete postmortem examination was performed in search for additional malformations. The face of both fetuses showed a very similar morphologic pattern with duplication of ocular, nasal, and buccal structures. The nasal fossae and the anterior part of the tongue were also duplicated, albeit the posterior part and the pharyngolaryngeal structures were unique. Additional facial clefts were present in both fetuses. Extrafacial anomalies were represented by a craniorachischisis, two fused vertebral columns and, in the older fetus, by a complex cardiac malformation morphologically identical to malformations induced by removal or grafting of additional cardiac neural crest cells in animals. These pathological findings could identify the facial structures that are neural crest derivatives in man. They are similar to those experimentally demonstrated to be neural crest derivatives in animals. In this respect, diprosopia could be considered as the end of a spectrum

  10. Delayed development of neural language organization in very preterm born children.

    Science.gov (United States)

    Mürner-Lavanchy, Ines; Steinlin, Maja; Kiefer, Claus; Weisstanner, Christian; Ritter, Barbara Catherine; Perrig, Walter; Everts, Regula

    2014-01-01

    This study investigates neural language organization in very preterm born children compared to control children and examines the relationship between language organization, age, and language performance. Fifty-six preterms and 38 controls (7-12 y) completed a functional magnetic resonance imaging language task. Lateralization and signal change were computed for language-relevant brain regions. Younger preterms showed a bilateral language network whereas older preterms revealed left-sided language organization. No age-related differences in language organization were observed in controls. Results indicate that preterms maintain atypical bilateral language organization longer than term born controls. This might reflect a delay of neural language organization due to very premature birth.

  11. Development of Novel Gas Brand Anti-Piracy System based on BP Neural Networks

    Energy Technology Data Exchange (ETDEWEB)

    Wang, L [School of Aeronautics and Astronautics, Tongji University, Shanghai (China); Zhang, Y Y [Chinese-German School of Postgraduate Studies, Tongji University (China); Ding, L [Chinese-German School of Postgraduate Studies, Tongji University (China)

    2006-10-15

    The Wireless-net Close-loop gas brand anti-piracy system introduced in this paper is a new type of brand piracy technical product based on BP neural network. It is composed by gas brand piracy label possessing gas exhalation resource, ARM embedded gas-detector, GPRS wireless module and data base of merchandise information. First, the system obtains the information on the special label through gas sensor array ,then the attained signals are transferred into ARM Embedded board and identified by artificial neural network, and finally turns back the outcome of data collection and identification to the manufactures with the help of GPRS module.

  12. Development of Novel Gas Brand Anti-Piracy System based on BP Neural Networks

    Science.gov (United States)

    Wang, L.; Zhang, Y. Y.; Ding, L.

    2006-10-01

    The Wireless-net Close-loop gas brand anti-piracy system introduced in this paper is a new type of brand piracy technical product based on BP neural network. It is composed by gas brand piracy label possessing gas exhalation resource, ARM embedded gas-detector, GPRS wireless module and data base of merchandise information. First, the system obtains the information on the special label through gas sensor array ,then the attained signals are transferred into ARM Embedded board and identified by artificial neural network, and finally turns back the outcome of data collection and identification to the manufactures with the help of GPRS module.

  13. Development of Novel Gas Brand Anti-Piracy System based on BP Neural Networks

    International Nuclear Information System (INIS)

    Wang, L; Zhang, Y Y; Ding, L

    2006-01-01

    The Wireless-net Close-loop gas brand anti-piracy system introduced in this paper is a new type of brand piracy technical product based on BP neural network. It is composed by gas brand piracy label possessing gas exhalation resource, ARM embedded gas-detector, GPRS wireless module and data base of merchandise information. First, the system obtains the information on the special label through gas sensor array ,then the attained signals are transferred into ARM Embedded board and identified by artificial neural network, and finally turns back the outcome of data collection and identification to the manufactures with the help of GPRS module

  14. Development of surrogate models using artificial neural network for building shell energy labelling

    International Nuclear Information System (INIS)

    Melo, A.P.; Cóstola, D.; Lamberts, R.; Hensen, J.L.M.

    2014-01-01

    Surrogate models are an important part of building energy labelling programs, but these models still present low accuracy, particularly in cooling-dominated climates. The objective of this study was to evaluate the feasibility of using an artificial neural network (ANN) to improve the accuracy of surrogate models for labelling purposes. An ANN was applied to model the building stock of a city in Brazil, based on the results of extensive simulations using the high-resolution building energy simulation program EnergyPlus. Sensitivity and uncertainty analyses were carried out to evaluate the behaviour of the ANN model, and the variations in the best and worst performance for several typologies were analysed in relation to variations in the input parameters and building characteristics. The results obtained indicate that an ANN can represent the interaction between input and output data for a vast and diverse building stock. Sensitivity analysis showed that no single input parameter can be identified as the main factor responsible for the building energy performance. The uncertainty associated with several parameters plays a major role in assessing building energy performance, together with the facade area and the shell-to-floor ratio. The results of this study may have a profound impact as ANNs could be applied in the future to define regulations in many countries, with positive effects on optimizing the energy consumption. - Highlights: • We model several typologies which have variation in input parameters. • We evaluate the accuracy of surrogate models for labelling purposes. • ANN is applied to model the building stock. • Uncertainty in building plays a major role in the building energy performance. • Results show that ANN could help to develop building energy labelling systems

  15. Left-Right Asymmetry of Maturation Rates in Human Embryonic Neural Development.

    Science.gov (United States)

    de Kovel, Carolien G F; Lisgo, Steven; Karlebach, Guy; Ju, Jia; Cheng, Gang; Fisher, Simon E; Francks, Clyde

    2017-08-01

    Left-right asymmetry is a fundamental organizing feature of the human brain, and neuropsychiatric disorders such as schizophrenia sometimes involve alterations of brain asymmetry. As early as 8 weeks postconception, the majority of human fetuses move their right arms more than their left arms, but because nerve fiber tracts are still descending from the forebrain at this stage, spinal-muscular asymmetries are likely to play an important developmental role. We used RNA sequencing to measure gene expression levels in the left and right spinal cords, and the left and right hindbrains, of 18 postmortem human embryos aged 4 to 8 weeks postconception. Genes showing embryonic lateralization were tested for an enrichment of signals in genome-wide association data for schizophrenia. The left side of the embryonic spinal cord was found to mature faster than the right side. Both sides transitioned from transcriptional profiles associated with cell division and proliferation at earlier stages to neuronal differentiation and function at later stages, but the two sides were not in synchrony (p = 2.2 E-161). The hindbrain showed a left-right mirrored pattern compared with the spinal cord, consistent with the well-known crossing over of function between these two structures. Genes that showed lateralization in the embryonic spinal cord were enriched for association signals with schizophrenia (p = 4.3 E-05). These are the earliest stage left-right differences of human neural development ever reported. Disruption of the lateralized developmental program may play a role in the genetic susceptibility to schizophrenia. Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

  16. The Pleiotropic MET Receptor Network: Circuit Development and the Neural-Medical Interface of Autism.

    Science.gov (United States)

    Eagleson, Kathie L; Xie, Zhihui; Levitt, Pat

    2017-03-01

    People with autism spectrum disorder and other neurodevelopmental disorders (NDDs) are behaviorally and medically heterogeneous. The combination of polygenicity and gene pleiotropy-the influence of one gene on distinct phenotypes-raises questions of how specific genes and their protein products interact to contribute to NDDs. A preponderance of evidence supports developmental and pathophysiological roles for the MET receptor tyrosine kinase, a multifunctional receptor that mediates distinct biological responses depending upon cell context. MET influences neuron architecture and synapse maturation in the forebrain and regulates homeostasis in gastrointestinal and immune systems, both commonly disrupted in NDDs. Peak expression of synapse-enriched MET is conserved across rodent and primate forebrain, yet regional differences in primate neocortex are pronounced, with enrichment in circuits that participate in social information processing. A functional risk allele in the MET promoter, enriched in subgroups of children with autism spectrum disorder, reduces transcription and disrupts socially relevant neural circuits structurally and functionally. In mice, circuit-specific deletion of Met causes distinct atypical behaviors. MET activation increases dendritic complexity and nascent synapse number, but synapse maturation requires reductions in MET. MET mediates its specific biological effects through different intracellular signaling pathways and has a complex protein interactome that is enriched in autism spectrum disorder and other NDD candidates. The interactome is coregulated in developing human neocortex. We suggest that a gene as pleiotropic and highly regulated as MET, together with its interactome, is biologically relevant in normal and pathophysiological contexts, affecting central and peripheral phenotypes that contribute to NDD risk and clinical symptoms. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

  17. Convergent synaptic and circuit substrates underlying autism genetic risks.

    Science.gov (United States)

    McGee, Aaron; Li, Guohui; Lu, Zhongming; Qiu, Shenfeng

    2014-02-01

    There has been a surge of diagnosis of autism spectrum disorders (ASD) over the past decade. While large, high powered genome screening studies of children with ASD have identified numerous genetic risk factors, research efforts to understanding how each of these risk factors contributes to the development autism has met with limited success. Revealing the mechanisms by which these genetic risk factors affect brain development and predispose a child to autism requires mechanistic understanding of the neurobiological changes underlying this devastating group of developmental disorders at multifaceted molecular, cellular and system levels. It has been increasingly clear that the normal trajectory of neurodevelopment is compromised in autism, in multiple domains as much as aberrant neuronal production, growth, functional maturation, patterned connectivity, and balanced excitation and inhibition of brain networks. Many autism risk factors identified in humans have been now reconstituted in experimental mouse models to allow mechanistic interrogation of the biological role of the risk gene. Studies utilizing these mouse models have revealed that underlying the enormous heterogeneity of perturbed cellular events, mechanisms directing synaptic and circuit assembly may provide a unifying explanation for the pathophysiological changes and behavioral endophenotypes seen in autism, although synaptic perturbations are far from being the only alterations relevant for ASD. In this review, we discuss synaptic and circuit abnormalities obtained from several prevalent mouse models, particularly those reflecting syndromic forms of ASD that are caused by single gene perturbations. These compiled results reveal that ASD risk genes contribute to proper signaling of the developing gene networks that maintain synaptic and circuit homeostasis, which is fundamental to normal brain development.

  18. Development of Self-Assembled Nanoribbon Bound Peptide-Polyaniline Composite Scaffolds and Their Interactions with Neural Cortical Cells

    Directory of Open Access Journals (Sweden)

    Andrew M. Smith

    2018-01-01

    Full Text Available Degenerative neurological disorders and traumatic brain injuries cause significant damage to quality of life and often impact survival. As a result, novel treatments are necessary that can allow for the regeneration of neural tissue. In this work, a new biomimetic scaffold was designed with potential for applications in neural tissue regeneration. To develop the scaffold, we first prepared a new bolaamphiphile that was capable of undergoing self-assembly into nanoribbons at pH 7. Those nanoribbons were then utilized as templates for conjugation with specific proteins known to play a critical role in neural tissue growth. The template (Ile-TMG-Ile was prepared by conjugating tetramethyleneglutaric acid with isoleucine and the ability of the bolaamphiphile to self-assemble was probed at a pH range of 4 through 9. The nanoribbons formed under neutral conditions were then functionalized step-wise with the basement membrane protein laminin, the neurotropic factor artemin and Type IV collagen. The conductive polymer polyaniline (PANI was then incorporated through electrostatic and π–π stacking interactions to the scaffold to impart electrical properties. Distinct morphology changes were observed upon conjugation with each layer, which was also accompanied by an increase in Young’s Modulus as well as surface roughness. The Young’s Modulus of the dried PANI-bound biocomposite scaffolds was found to be 5.5 GPa, indicating the mechanical strength of the scaffold. Thermal phase changes studied indicated broad endothermic peaks upon incorporation of the proteins which were diminished upon binding with PANI. The scaffolds also exhibited in vitro biodegradable behavior over a period of three weeks. Furthermore, we observed cell proliferation and short neurite outgrowths in the presence of rat neural cortical cells, confirming that the scaffolds may be applicable in neural tissue regeneration. The electrochemical properties of the scaffolds were also

  19. Development of Self-Assembled Nanoribbon Bound Peptide-Polyaniline Composite Scaffolds and Their Interactions with Neural Cortical Cells

    Science.gov (United States)

    Smith, Andrew M.; Pajovich, Harrison T.; Banerjee, Ipsita A.

    2018-01-01

    Degenerative neurological disorders and traumatic brain injuries cause significant damage to quality of life and often impact survival. As a result, novel treatments are necessary that can allow for the regeneration of neural tissue. In this work, a new biomimetic scaffold was designed with potential for applications in neural tissue regeneration. To develop the scaffold, we first prepared a new bolaamphiphile that was capable of undergoing self-assembly into nanoribbons at pH 7. Those nanoribbons were then utilized as templates for conjugation with specific proteins known to play a critical role in neural tissue growth. The template (Ile-TMG-Ile) was prepared by conjugating tetramethyleneglutaric acid with isoleucine and the ability of the bolaamphiphile to self-assemble was probed at a pH range of 4 through 9. The nanoribbons formed under neutral conditions were then functionalized step-wise with the basement membrane protein laminin, the neurotropic factor artemin and Type IV collagen. The conductive polymer polyaniline (PANI) was then incorporated through electrostatic and π–π stacking interactions to the scaffold to impart electrical properties. Distinct morphology changes were observed upon conjugation with each layer, which was also accompanied by an increase in Young’s Modulus as well as surface roughness. The Young’s Modulus of the dried PANI-bound biocomposite scaffolds was found to be 5.5 GPa, indicating the mechanical strength of the scaffold. Thermal phase changes studied indicated broad endothermic peaks upon incorporation of the proteins which were diminished upon binding with PANI. The scaffolds also exhibited in vitro biodegradable behavior over a period of three weeks. Furthermore, we observed cell proliferation and short neurite outgrowths in the presence of rat neural cortical cells, confirming that the scaffolds may be applicable in neural tissue regeneration. The electrochemical properties of the scaffolds were also studied by

  20. Neuromodulated Synaptic Plasticity on the SpiNNaker Neuromorphic System

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    Mantas Mikaitis

    2018-02-01

    Full Text Available SpiNNaker is a digital neuromorphic architecture, designed specifically for the low power simulation of large-scale spiking neural networks at speeds close to biological real-time. Unlike other neuromorphic systems, SpiNNaker allows users to develop their own neuron and synapse models as well as specify arbitrary connectivity. As a result SpiNNaker has proved to be a powerful tool for studying different neuron models as well as synaptic plasticity—believed to be one of the main mechanisms behind learning and memory in the brain. A number of Spike-Timing-Dependent-Plasticity(STDP rules have already been implemented on SpiNNaker and have been shown to be capable of solving various learning tasks in real-time. However, while STDP is an important biological theory of learning, it is a form of Hebbian or unsupervised learning and therefore does not explain behaviors that depend on feedback from the environment. Instead, learning rules based on neuromodulated STDP (three-factor learning rules have been shown to be capable of solving reinforcement learning tasks in a biologically plausible manner. In this paper we demonstrate for the first time how a model of three-factor STDP, with the third-factor representing spikes from dopaminergic neurons, can be implemented on the SpiNNaker neuromorphic system. Using this learning rule we first show how reward and punishment signals can be delivered to a single synapse before going on to demonstrate it in a larger network which solves the credit assignment problem in a Pavlovian conditioning experiment. Because of its extra complexity, we find that our three-factor learning rule requires approximately 2× as much processing time as the existing SpiNNaker STDP learning rules. However, we show that it is still possible to run our Pavlovian conditioning model with up to 1 × 104 neurons in real-time, opening up new research opportunities for modeling behavioral learning on SpiNNaker.

  1. Modular Neural Tile Architecture for Compact Embedded Hardware Spiking Neural Network

    NARCIS (Netherlands)

    Pande, Sandeep; Morgan, Fearghal; Cawley, Seamus; Bruintjes, Tom; Smit, Gerardus Johannes Maria; McGinley, Brian; Carrillo, Snaider; Harkin, Jim; McDaid, Liam

    2013-01-01

    Biologically-inspired packet switched network on chip (NoC) based hardware spiking neural network (SNN) architectures have been proposed as an embedded computing platform for classification, estimation and control applications. Storage of large synaptic connectivity (SNN topology) information in

  2. Firing rate dynamics in recurrent spiking neural networks with intrinsic and network heterogeneity.

    Science.gov (United States)

    Ly, Cheng

    2015-12-01

    Heterogeneity of neural attributes has recently gained a lot of attention and is increasing recognized as a crucial feature in neural processing. Despite its importance, this physiological feature has traditionally been neglected in theoretical studies of cortical neural networks. Thus, there is still a lot unknown about the consequences of cellular and circuit heterogeneity in spiking neural networks. In particular, combining network or synaptic heterogeneity and intrinsic heterogeneity has yet to be considered systematically despite the fact that both are known to exist and likely have significant roles in neural network dynamics. In a canonical recurrent spiking neural network model, we study how these two forms of heterogeneity lead to different distributions of excitatory firing rates. To analytically characterize how these types of heterogeneities affect the network, we employ a dimension reduction method that relies on a combination of Monte Carlo simulations and probability density function equations. We find that the relationship between intrinsic and network heterogeneity has a strong effect on the overall level of heterogeneity of the firing rates. Specifically, this relationship can lead to amplification or attenuation of firing rate heterogeneity, and these effects depend on whether the recurrent network is firing asynchronously or rhythmically firing. These observations are captured with the aforementioned reduction method, and furthermore simpler analytic descriptions based on this dimension reduction method are developed. The final analytic descriptions provide compact and descriptive formulas for how the relationship between intrinsic and network heterogeneity determines the firing rate heterogeneity dynamics in various settings.

  3. GABA type a receptor trafficking and the architecture of synaptic inhibition.

    Science.gov (United States)

    Lorenz-Guertin, Joshua M; Jacob, Tija C

    2018-03-01

    Ubiquitous expression of GABA type A receptors (GABA A R) in the central nervous system establishes their central role in coordinating most aspects of neural function and development. Dysregulation of GABAergic neurotransmission manifests in a number of human health disorders and conditions that in certain cases can be alleviated by drugs targeting these receptors. Precise changes in the quantity or activity of GABA A Rs localized at the cell surface and at GABAergic postsynaptic sites directly impact the strength of inhibition. The molecular mechanisms constituting receptor trafficking to and from these compartments therefore dictate the efficacy of GABA A R function. Here we review the current understanding of how GABA A Rs traffic through biogenesis, plasma membrane transport, and degradation. Emphasis is placed on discussing novel GABAergic synaptic proteins, receptor and scaffolding post-translational modifications, activity-dependent changes in GABA A R confinement, and neuropeptide and neurosteroid mediated changes. We further highlight modern techniques currently advancing the knowledge of GABA A R trafficking and clinically relevant neurodevelopmental diseases connected to GABAergic dysfunction. © 2017 Wiley Periodicals, Inc. Develop Neurobiol 78: 238-270, 2018. © 2017 Wiley Periodicals, Inc.

  4. Neural ECM in laminar organization and connectivity development in healthy and diseased human brain

    NARCIS (Netherlands)

    Jovanov Milošević, Nataša; Judaš, Miloš; Aronica, Eleonora; Kostovic, Ivica

    2014-01-01

    The neural extracellular matrix (ECM) provides a supportive framework for differentiating cells and their processes and regulates morphogenetic events by spatially and temporally relevant localization of signaling molecules and by direct signaling via receptor and/or coreceptor-mediated action. The

  5. Development of surrogate models using artificial neural network for building shell energy labelling

    NARCIS (Netherlands)

    Melo, A.P.; Costola, D.; Lamberts, R.; Hensen, J.L.M.

    2014-01-01

    Surrogate models are an important part of building energy labelling programs, but these models still present low accuracy, particularly in cooling-dominated climates. The objective of this study was to evaluate the feasibility of using an artificial neural network (ANN) to improve the accuracy of

  6. Meis2 is essential for cranial and cardiac neural crest development

    Czech Academy of Sciences Publication Activity Database

    Machoň, Ondřej; Mašek, Jan; Machoňová, Olga; Krauss, S.; Kozmik, Zbyněk

    2015-01-01

    Roč. 15, Nov 6 (2015) ISSN 1471-213X R&D Projects: GA ČR GAP305/12/2042; GA MŠk(CZ) LK11214 Institutional support: RVO:68378050 Keywords : Meis2 * Persistent truncus arteriosus * Neural crest * Craniofacial skeleton * Cranial nerves Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 2.096, year: 2015

  7. The neural coding of feedback learning across child and adolescent development

    NARCIS (Netherlands)

    Peters, S.; Braams, B.R.; Raijmakers, M.E.J.; Koolschijn, P.C.M.P.; Crone, E.A.

    2014-01-01

    The ability to learn from environmental cues is an important contributor to successful performance in a variety of settings, including school. Despite the progress in unraveling the neural correlates of cognitive control in childhood and adolescence, relatively little is known about how these brain

  8. Imbalanced pattern completion vs. separation in cognitive disease: network simulations of synaptic pathologies predict a personalized therapeutics strategy

    Directory of Open Access Journals (Sweden)

    Hanson Jesse E

    2010-08-01

    Full Text Available Abstract Background Diverse Mouse genetic models of neurodevelopmental, neuropsychiatric, and neurodegenerative causes of impaired cognition exhibit at least four convergent points of synaptic malfunction: 1 Strength of long-term potentiation (LTP, 2 Strength of long-term depression (LTD, 3 Relative inhibition levels (Inhibition, and 4 Excitatory connectivity levels (Connectivity. Results To test the hypothesis that pathological increases or decreases in these synaptic properties could underlie imbalances at the level of basic neural network function, we explored each type of malfunction in a simulation of autoassociative memory. These network simulations revealed that one impact of impairments or excesses in each of these synaptic properties is to shift the trade-off between pattern separation and pattern completion performance during memory storage and recall. Each type of synaptic pathology either pushed the network balance towards intolerable error in pattern separation or intolerable error in pattern completion. Imbalances caused by pathological impairments or excesses in LTP, LTD, inhibition, or connectivity, could all be exacerbated, or rescued, by the simultaneous modulation of any of the other three synaptic properties. Conclusions Because appropriate modulation of any of the synaptic properties could help re-balance network function, regardless of the origins of the imbalance, we propose a new strategy of personalized cognitive therapeutics guided by assay of pattern completion vs. pattern separation function. Simulated examples and testable predictions of this theorized approach to cognitive therapeutics are presented.

  9. "The seven sins" of the Hebbian synapse: can the hypothesis of synaptic plasticity explain long-term memory consolidation?

    Science.gov (United States)

    Arshavsky, Yuri I

    2006-10-01

    Memorizing new facts and events means that entering information produces specific physical changes within the brain. According to the commonly accepted view, traces of memory are stored through the structural modifications of synaptic connections, which result in changes of synaptic efficiency and, therefore, in formations of new patterns of neural activity (the hypothesis of synaptic plasticity). Most of the current knowledge on learning and initial stages of memory consolidation ("synaptic consolidation") is based on this hypothesis. However, the hypothesis of synaptic plasticity faces a number of conceptual and experimental difficulties when it deals with potentially permanent consolidation of declarative memory ("system consolidation"). These difficulties are rooted in the major intrinsic self-contradiction of the hypothesis: stable declarative memory is unlikely to be based on such a non-stable foundation as synaptic plasticity. Memory that can last throughout an entire lifespan should be "etched in stone." The only "stone-like" molecules within living cells are DNA molecules. Therefore, I advocate an alternative, genomic hypothesis of memory, which suggests that acquired information is persistently stored within individual neurons through modifications of DNA, and that these modifications serve as the carriers of elementary memory traces.

  10. Comparative Analysis Between Flaviviruses Reveals Specific Neural Stem Cell Tropism for Zika Virus in the Mouse Developing Neocortex

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    Jean-Baptiste Brault

    2016-08-01

    Full Text Available The recent Zika outbreak in South America and French Polynesia was associated with an epidemic of microcephaly, a disease characterized by a reduced size of the cerebral cortex. Other members of the Flavivirus genus, including West Nile virus (WNV, can cause encephalitis but were not demonstrated to cause microcephaly. It remains unclear whether Zika virus (ZIKV and other flaviviruses may infect different cell populations in the developing neocortex and lead to distinct developmental defects. Here, we describe an assay to infect mouse E15 embryonic brain slices with ZIKV, WNV and dengue virus serotype 4 (DENV-4. We show that this tissue is able to support viral replication of ZIKV and WNV, but not DENV-4. Cell fate analysis reveals a remarkable tropism of ZIKV infection for neural stem cells. Closely related WNV displays a very different tropism of infection, with a bias towards neurons. We further show that ZIKV infection, but not WNV infection, impairs cell cycle progression of neural stem cells. Both viruses inhibited apoptosis at early stages of infection. This work establishes a powerful comparative approach to identify ZIKV-specific alterations in the developing neocortex and reveals specific preferential infection of neural stem cells by ZIKV.

  11. Fragile X mental retardation protein regulates trans-synaptic signaling in Drosophila

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    Samuel H. Friedman

    2013-11-01

    Fragile X syndrome (FXS, the most common inherited determinant of intellectual disability and autism spectrum disorders, is caused by loss of the fragile X mental retardation 1 (FMR1 gene product (FMRP, an mRNA-binding translational repressor. A number of conserved FMRP targets have been identified in the well-characterized Drosophila FXS disease model, but FMRP is highly pleiotropic in function and the full spectrum of FMRP targets has yet to be revealed. In this study, screens for upregulated neural proteins in Drosophila fmr1 (dfmr1 null mutants reveal strong elevation of two synaptic heparan sulfate proteoglycans (HSPGs: GPI-anchored glypican Dally-like protein (Dlp and transmembrane Syndecan (Sdc. Our recent work has shown that Dlp and Sdc act as co-receptors regulating extracellular ligands upstream of intracellular signal transduction in multiple trans-synaptic pathways that drive synaptogenesis. Consistently, dfmr1 null synapses exhibit altered WNT signaling, with changes in both Wingless (Wg ligand abundance and downstream Frizzled-2 (Fz2 receptor C-terminal nuclear import. Similarly, a parallel anterograde signaling ligand, Jelly belly (Jeb, and downstream ERK phosphorylation (dpERK are depressed at dfmr1 null synapses. In contrast, the retrograde BMP ligand Glass bottom boat (Gbb and downstream signaling via phosphorylation of the transcription factor MAD (pMAD seem not to be affected. To determine whether HSPG upregulation is causative for synaptogenic defects, HSPGs were genetically reduced to control levels in the dfmr1 null background. HSPG correction restored both (1 Wg and Jeb trans-synaptic signaling, and (2 synaptic architecture and transmission strength back to wild-type levels. Taken together, these data suggest that FMRP negatively regulates HSPG co-receptors controlling trans-synaptic signaling during synaptogenesis, and that loss of this regulation causes synaptic structure and function defects characterizing the FXS disease state.

  12. cables1 Is Required for Embryonic Neural Development: Molecular, Cellular, and Behavioral Evidence From the Zebrafish

    Science.gov (United States)

    GROENEWEG, JOLIJN W.; WHITE, YVONNE A.R.; KOKEL, DAVID; PETERSON, RANDALL T.; ZUKERBERG, LAWRENCE R.; BERIN, INNA; RUEDA, BO R.; WOOD, ANTONY W.

    2014-01-01

    SUMMARY In vitro studies have suggested that the Cables1 gene regulates epithelial cell proliferation, whereas other studies suggest a role in promoting neural differentiation. In efforts to clarify the functions of Cables1 in vivo, we conducted gain- and loss-of-function studies targeting its ortholog (cables1) in the zebrafish embryo. Similar to rodents, zebrafish cables1 mRNA expression is detected most robustly in embryonic neural tissues. Antisense knockdown of cables1 leads to increased numbers of apoptotic cells, particularly in brain tissue, in addition to a distinct behavioral phenotype, characterized by hyperactivity in response to stimulation. Apoptosis and the behavioral abnormality could be rescued by co-expression of a morpholino-resistant cables1 construct. Suppression of p53 expression in cables1 morphants partially rescued both apoptosis and the behavioral phenotype, suggesting that the phenotype of cables1 morphants is due in part to p53-dependent apoptosis. Alterations in the expression patterns of several neural transcription factors were observed in cables1 morphants during early neurulation, suggesting that cables1 is required for early neural differentiation. Ectopic overexpression of cables1 strongly disrupted embryonic morphogenesis, while overexpression of a cables1 mutant lacking the C-terminal cyclin box had little effect, suggesting functional importance of the cyclin box. Lastly, marked reductions in p35, but not Cdk5, were observed in cables1 morphants. Collectively, these data suggest that cables1 is important for neural differentiation during embryogenesis, in a mechanism that likely involves interactions with the Cdk5/p35 kinase pathway. PMID:21268180

  13. Developing a hippocampal neural prosthetic to facilitate human memory encoding and recall

    Science.gov (United States)

    Hampson, Robert E.; Song, Dong; Robinson, Brian S.; Fetterhoff, Dustin; Dakos, Alexander S.; Roeder, Brent M.; She, Xiwei; Wicks, Robert T.; Witcher, Mark R.; Couture, Daniel E.; Laxton, Adrian W.; Munger-Clary, Heidi; Popli, Gautam; Sollman, Myriam J.; Whitlow, Christopher T.; Marmarelis, Vasilis Z.; Berger, Theodore W.; Deadwyler, Sam A.

    2018-06-01

    Objective. We demonstrate here the first successful implementation in humans of a proof-of-concept system for restoring and improving memory function via facilitation of memory encoding using the patient’s own hippocampal spatiotemporal neural codes for memory. Memory in humans is subject to disruption by drugs, disease and brain injury, yet previous attempts to restore or rescue memory function in humans typically involved only nonspecific, modulation of brain areas and neural systems related to memory retrieval. Approach. We have constructed a model of processes by which the hippocampus encodes memory items via spatiotemporal firing of neural ensembles that underlie the successful encoding of short-term memory. A nonlinear multi-input, multi-output (MIMO) model of hippocampal CA3 and CA1 neural firing is computed that predicts activation patterns of CA1 neurons during the encoding (sample) phase of a delayed match-to-sample (DMS) human short-term memory task. Main results. MIMO model-derived electrical stimulation delivered to the same CA1 locations during the sample phase of DMS trials facilitated short-term/working memory by 37% during the task. Longer term memory retention was also tested in the same human subjects with a delayed recognition (DR) task that utilized images from the DMS task, along with images that were not from the task. Across the subjects, the stimulated trials exhibited significant improvement (35%) in both short-term and long-term retention of visual information. Significance. These results demonstrate the facilitation of memory encoding which is an important feature for the construction of an implantable neural prosthetic to improve human memory.

  14. Neural network regulation driven by autonomous neural firings

    Science.gov (United States)

    Cho, Myoung Won

    2016-07-01

    Biological neurons naturally fire spontaneously due to the existence of a noisy current. Such autonomous firings may provide a driving force for network formation because synaptic connections can be modified due to neural firings. Here, we study the effect of autonomous firings on network formation. For the temporally asymmetric Hebbian learning, bidirectional connections lose their balance easily and become unidirectional ones. Defining the difference between reciprocal connections as new variables, we could express the learning dynamics as if Ising model spins interact with each other in magnetism. We present a theoretical method to estimate the interaction between the new variables in a neural system. We apply the method to some network systems and find some tendencies of autonomous neural network regulation.

  15. Bio-mimicked atomic-layer-deposited iron oxide-based memristor with synaptic potentiation and depression functions

    Science.gov (United States)

    Wan, Xiang; Gao, Fei; Lian, Xiaojuan; Ji, Xincun; Hu, Ertao; He, Lin; Tong, Yi; Guo, Yufeng

    2018-06-01

    In this study, an iron oxide (FeO x )-based memristor was investigated for the realization of artificial synapses. An FeO x resistive switching layer was prepared by self-limiting atomic layer deposition (ALD). The movement of oxygen vacancies enabled the device to have history-dependent synaptic functions, which was further demonstrated by device modeling and simulation. Analog synaptic potentiation/depression in conductance was emulated by applying consecutive voltage pulses in the simulation. Our results suggest that the ALD FeO x -based memristor can be used as the basic building block for neural networks, neuromorphic systems, and brain-inspired computers.

  16. Comparison of multiple linear regression and artificial neural network in developing the objective functions of the orthopaedic screws.

    Science.gov (United States)

    Hsu, Ching-Chi; Lin, Jinn; Chao, Ching-Kong

    2011-12-01

    Optimizing the orthopaedic screws can greatly improve their biomechanical performances. However, a methodical design optimization approach requires a long time to search the best design. Thus, the surrogate objective functions of the orthopaedic screws should be accurately developed. To our knowledge, there is no study to evaluate the strengths and limitations of the surrogate methods in developing the objective functions of the orthopaedic screws. Three-dimensional finite element models for both the tibial locking screws and the spinal pedicle screws were constructed and analyzed. Then, the learning data were prepared according to the arrangement of the Taguchi orthogonal array, and the verification data were selected with use of a randomized selection. Finally, the surrogate objective functions were developed by using either the multiple linear regression or the artificial neural network. The applicability and accuracy of those surrogate methods were evaluated and discussed. The multiple linear regression method could successfully construct the objective function of the tibial locking screws, but it failed to develop the objective function of the spinal pedicle screws. The artificial neural network method showed a greater capacity of prediction in developing the objective functions for the tibial locking screws and the spinal pedicle screws than the multiple linear regression method. The artificial neural network method may be a useful option for developing the objective functions of the orthopaedic screws with a greater structural complexity. The surrogate objective functions of the orthopaedic screws could effectively decrease the time and effort required for the design optimization process. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

  17. Quantitative Live Imaging of Human Embryonic Stem Cell Derived Neural Rosettes Reveals Structure-Function Dynamics Coupled to Cortical Development.

    Science.gov (United States)

    Ziv, Omer; Zaritsky, Assaf; Yaffe, Yakey; Mutukula, Naresh; Edri, Reuven; Elkabetz, Yechiel

    2015-10-01

    Neural stem cells (NSCs) are progenitor cells for brain development, where cellular spatial composition (cytoarchitecture) and dynamics are hypothesized to be linked to critical NSC capabilities. However, understanding cytoarchitectural dynamics of this process has been limited by the difficulty to quantitatively image brain development in vivo. Here, we study NSC dynamics within Neural Rosettes--highly organized multicellular structures derived from human pluripotent stem cells. Neural rosettes contain NSCs with strong epithelial polarity and are expected to perform apical-basal interkinetic nuclear migration (INM)--a hallmark of cortical radial glial cell development. We developed a quantitative live imaging framework to characterize INM dynamics within rosettes. We first show that the tendency of cells to follow the INM orientation--a phenomenon we referred to as radial organization, is associated with rosette size, presumably via mechanical constraints of the confining structure. Second, early forming rosettes, which are abundant with founder NSCs and correspond to the early proliferative developing cortex, show fast motions and enhanced radial organization. In contrast, later derived rosettes, which are characterized by reduced NSC capacity and elevated numbers of differentiated neurons, and thus correspond to neurogenesis mode in the developing cortex, exhibit slower motions and decreased radial organization. Third, later derived rosettes are characterized by temporal instability in INM measures, in agreement with progressive loss in rosette integrity at later developmental stages. Finally, molecular perturbations of INM by inhibition of actin or non-muscle myosin-II (NMII) reduced INM measures. Our framework enables quantification of cytoarchitecture NSC dynamics and may have implications in functional molecular studies, drug screening, and iPS cell-based platforms for disease modeling.

  18. Quantitative Live Imaging of Human Embryonic Stem Cell Derived Neural Rosettes Reveals Structure-Function Dynamics Coupled to Cortical Development.

    Directory of Open Access Journals (Sweden)

    Omer Ziv

    2015-10-01

    Full Text Available Neural stem cells (NSCs are progenitor cells for brain development, where cellular spatial composition (cytoarchitecture and dynamics are hypothesized to be linked to critical NSC capabilities. However, understanding cytoarchitectural dynamics of this process has been limited by the difficulty to quantitatively image brain development in vivo. Here, we study NSC dynamics within Neural Rosettes--highly organized multicellular structures derived from human pluripotent stem cells. Neural rosettes contain NSCs with strong epithelial polarity and are expected to perform apical-basal interkinetic nuclear migration (INM--a hallmark of cortical radial glial cell development. We developed a quantitative live imaging framework to characterize INM dynamics within rosettes. We first show that the tendency of cells to follow the INM orientation--a phenomenon we referred to as radial organization, is associated with rosette size, presumably via mechanical constraints of the confining structure. Second, early forming rosettes, which are abundant with founder NSCs and correspond to the early proliferative developing cortex, show fast motions and enhanced radial organization. In contrast, later derived rosettes, which are characterized by reduced NSC capacity and elevated numbers of differentiated neurons, and thus correspond to neurogenesis mode in the developing cortex, exhibit slower motions and decreased radial organization. Third, later derived rosettes are characterized by temporal instability in INM measures, in agreement with progressive loss in rosette integrity at later developmental stages. Finally, molecular perturbations of INM by inhibition of actin or non-muscle myosin-II (NMII reduced INM measures. Our framework enables quantification of cytoarchitecture NSC dynamics and may have implications in functional molecular studies, drug screening, and iPS cell-based platforms for disease modeling.

  19. Artificial neural network surrogate development of equivalence models for nuclear data uncertainty propagation in scenario studies

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    Krivtchik Guillaume

    2017-01-01

    Full Text Available Scenario studies simulate the whole fuel cycle over a period of time, from extraction of natural resources to geological storage. Through the comparison of different reactor fleet evolutions and fuel management options, they constitute a decision-making support. Consequently uncertainty propagation studies, which are necessary to assess the robustness of the studies, are strategic. Among numerous types of physical model in scenario computation that generate uncertainty, the equivalence models, built for calculating fresh fuel enrichment (for instance plutonium content in PWR MOX so as to be representative of nominal fuel behavior, are very important. The equivalence condition is generally formulated in terms of end-of-cycle mean core reactivity. As this results from a physical computation, it is therefore associated with an uncertainty. A state-of-the-art of equivalence models is exposed and discussed. It is shown that the existing equivalent models implemented in scenario codes, such as COSI6, are not suited to uncertainty propagation computation, for the following reasons: (i existing analytical models neglect irradiation, which has a strong impact on the result and its uncertainty; (ii current black-box models are not suited to cross-section perturbations management; and (iii models based on transport and depletion codes are too time-consuming for stochastic uncertainty propagation. A new type of equivalence model based on Artificial Neural Networks (ANN has been developed, constructed with data calculated with neutron transport and depletion codes. The model inputs are the fresh fuel isotopy, the irradiation parameters (burnup, core fractionation, etc., cross-sections perturbations and the equivalence criterion (for instance the core target reactivity in pcm at the end of the irradiation cycle. The model output is the fresh fuel content such that target reactivity is reached at the end of the irradiation cycle. Those models are built and

  20. Artificial Neural Network approach to develop unique Classification and Raga identification tools for Pattern Recognition in Carnatic Music

    Science.gov (United States)

    Srimani, P. K.; Parimala, Y. G.

    2011-12-01

    A unique approach has been developed to study patterns in ragas of Carnatic Classical music based on artificial neural networks. Ragas in Carnatic music which have found their roots in the Vedic period, have grown on a Scientific foundation over thousands of years. However owing to its vastness and complexities it has always been a challenge for scientists and musicologists to give an all encompassing perspective both qualitatively and quantitatively. Cognition, comprehension and perception of ragas in Indian classical music have always been the subject of intensive research, highly intriguing and many facets of these are hitherto not unravelled. This paper is an attempt to view the melakartha ragas with a cognitive perspective using artificial neural network based approach which has given raise to very interesting results. The 72 ragas of the melakartha system were defined through the combination of frequencies occurring in each of them. The data sets were trained using several neural networks. 100% accurate pattern recognition and classification was obtained using linear regression, TLRN, MLP and RBF networks. Performance of the different network topologies, by varying various network parameters, were compared. Linear regression was found to be the best performing network.

  1. A homolog of Subtilisin-like Proprotein Convertase 7 is essential to anterior neural development in Xenopus.

    Directory of Open Access Journals (Sweden)

    Sema Senturker

    Full Text Available BACKGROUND: Subtilisin-like Proprotein Convertase 7 (SPC7 is a member of the subtilisin/kexin family of pro-protein convertases. It cleaves many pro-proteins to release their active proteins, including members of the bone morphogenetic protein (BMP family of signaling molecules. Other SPCs are known to be required during embryonic development but corresponding data regarding SPC7 have not been reported previously. METHODOLOGY/PRINCIPAL FINDINGS: We demonstrated that Xenopus SPC7 (SPC7 was expressed predominantly in the developing brain and eye, throughout the neural plate initially, then more specifically in the lens and retina primordia as development progressed. Since no prior functional information has been reported for SPC7, we used gain- and loss-of-function experiments to investigate the possibility that it may also convey patterning or tissue specification information similarly to Furin, SPC4, and SPC6. Overexpression of SPC7 was without effect. In contrast, injection of SPC7 antisense morpholino oligonucleotides (MO into a single blastomere at the 2- or 4-cell stage produced marked disruption of head structures; anophthalmia was salient. Bilateral injections suppressed head and eye formation completely. In parallel with suppression of eye and brain development by SPC7 knockdown, expression of early anterior neural markers (Sox2, Otx2, Rx2, and Pax6 and late eye-specific markers (β-Crystallin and Opsin, and of BMP target genes such as Tbx2 and Tbx3, was reduced or eliminated. Taken together, these findings suggest a critical role for SPC7-perhaps, at least in part, due to activation of one or more BMPs-in early patterning of the anterior neural plate and its derivatives. CONCLUSION/SIGNIFICANCE: SPC7 is required for normal development of the eye and brain, possibly through processing BMPs, though other potential substrates cannot be excluded.

  2. A Homolog of Subtilisin-Like Proprotein Convertase 7 Is Essential to Anterior Neural Development in Xenopus

    Science.gov (United States)

    Senturker, Sema; Thomas, John Terrig; Mateshaytis, Jennifer; Moos, Malcolm

    2012-01-01

    Background Subtilisin-like Proprotein Convertase 7 (SPC7) is a member of the subtilisin/kexin family of pro-protein convertases. It cleaves many pro-proteins to release their active proteins, including members of the bone morphogenetic protein (BMP) family of signaling molecules. Other SPCs are known to be required during embryonic development but corresponding data regarding SPC7 have not been reported previously. Methodology/Principal Findings We demonstrated that Xenopus SPC7 (SPC7) was expressed predominantly in the developing brain and eye, throughout the neural plate initially, then more specifically in the lens and retina primordia as development progressed. Since no prior functional information has been reported for SPC7, we used gain- and loss-of-function experiments to investigate the possibility that it may also convey patterning or tissue specification information similarly to Furin, SPC4, and SPC6. Overexpression of SPC7 was without effect. In contrast, injection of SPC7 antisense morpholino oligonucleotides (MO) into a single blastomere at the 2- or 4-cell stage produced marked disruption of head structures; anophthalmia was salient. Bilateral injections suppressed head and eye formation completely. In parallel with suppression of eye and brain development by SPC7 knockdown, expression of early anterior neural markers (Sox2, Otx2, Rx2, and Pax6) and late eye-specific markers (β-Crystallin and Opsin), and of BMP target genes such as Tbx2 and Tbx3, was reduced or eliminated. Taken together, these findings suggest a critical role for SPC7–perhaps, at least in part, due to activation of one or more BMPs–in early patterning of the anterior neural plate and its derivatives. Conclusion/Significance SPC7 is required for normal development of the eye and brain, possibly through processing BMPs, though other potential substrates cannot be excluded. PMID:22761776

  3. Diacylglycerol kinases in the coordination of synaptic plasticity

    Directory of Open Access Journals (Sweden)

    Dongwon Lee

    2016-08-01

    Full Text Available Synaptic plasticity is activity-dependent modification of the efficacy of synaptic transmission. Although detailed mechanisms underlying synaptic plasticity are diverse and vary at different types of synapses, diacylglycerol (DAG-associated signaling has been considered as an important regulator of many forms of synaptic plasticity, including long-term potentiation (LTP and long-term depression (LTD. Recent evidence indicate that DAG kinases (DGKs, which phosphorylate DAG to phosphatidic acid to terminate DAG signaling, are important regulators of LTP and LTD, as supported by the results from mice lacking specific DGK isoforms. This review will summarize these studies and discuss how specific DGK isoforms distinctly regulate different forms of synaptic plasticity at pre- and postsynaptic sites. In addition, we propose a general role of DGKs as coordinators of synaptic plasticity that make local synaptic environments more permissive for synaptic plasticity by regulating DAG concentration and interacting with other synaptic proteins.

  4. New Computer Simulations of Macular Neural Functioning

    Science.gov (United States)

    Ross, Muriel D.; Doshay, D.; Linton, S.; Parnas, B.; Montgomery, K.; Chimento, T.

    1994-01-01

    We use high performance graphics workstations and supercomputers to study the functional significance of the three-dimensional (3-D) organization of gravity sensors. These sensors have a prototypic architecture foreshadowing more complex systems. Scaled-down simulations run on a Silicon Graphics workstation and scaled-up, 3-D versions run on a Cray Y-MP supercomputer. A semi-automated method of reconstruction of neural tissue from serial sections studied in a transmission electron microscope has been developed to eliminate tedious conventional photography. The reconstructions use a mesh as a step in generating a neural surface for visualization. Two meshes are required to model calyx surfaces. The meshes are connected and the resulting prisms represent the cytoplasm and the bounding membranes. A finite volume analysis method is employed to simulate voltage changes along the calyx in response to synapse activation on the calyx or on calyceal processes. The finite volume method insures that charge is conserved at the calyx-process junction. These and other models indicate that efferent processes act as voltage followers, and that the morphology of some afferent processes affects their functioning. In a final application, morphological information is symbolically represented in three dimensions in a computer. The possible functioning of the connectivities is tested using mathematical interpretations of physiological parameters taken from the literature. Symbolic, 3-D simulations are in progress to probe the functional significance of the connectivities. This research is expected to advance computer-based studies of macular functioning and of synaptic plasticity.

  5. Metabolic Turnover of Synaptic Proteins: Kinetics, Interdependencies and Implications for Synaptic Maintenance

    Science.gov (United States)

    Cohen, Laurie D.; Zuchman, Rina; Sorokina, Oksana; Müller, Anke; Dieterich, Daniela C.; Armstrong, J. Douglas; Ziv, Tamar; Ziv, Noam E.

    2013-01-01

    Chemical synapses contain multitudes of proteins, which in common with all proteins, have finite lifetimes and therefore need to be continuously replaced. Given the huge numbers of synaptic connections typical neurons form, the demand to maintain the protein contents of these connections might be expected to place considerable metabolic demands on each neuron. Moreover, synaptic proteostasis might differ according to distance from global protein synthesis sites, the availability of distributed protein synthesis facilities, trafficking rates and synaptic protein dynamics. To date, the turnover kinetics of synaptic proteins have not been studied or analyzed systematically, and thus metabolic demands or the aforementioned relationships remain largely unknown. In the current study we used dynamic Stable Isotope Labeling with Amino acids in Cell culture (SILAC), mass spectrometry (MS), Fluorescent Non–Canonical Amino acid Tagging (FUNCAT), quantitative immunohistochemistry and bioinformatics to systematically measure the metabolic half-lives of hundreds of synaptic proteins, examine how these depend on their pre/postsynaptic affiliation or their association with particular molecular complexes, and assess the metabolic load of synaptic proteostasis. We found that nearly all synaptic proteins identified here exhibited half-lifetimes in the range of 2–5 days. Unexpectedly, metabolic turnover rates were not significantly different for presynaptic and postsynaptic proteins, or for proteins for which mRNAs are consistently found in dendrites. Some functionally or structurally related proteins exhibited very similar turnover rates, indicating that their biogenesis and degradation might be coupled, a possibility further supported by bioinformatics-based analyses. The relatively low turnover rates measured here (∼0.7% of synaptic protein content per hour) are in good agreement with imaging-based studies of synaptic protein trafficking, yet indicate that the metabolic load

  6. Birth order dependent growth cone segregation determines synaptic layer identity in the Drosophila visual system.

    Science.gov (United States)

    Kulkarni, Abhishek; Ertekin, Deniz; Lee, Chi-Hon; Hummel, Thomas

    2016-03-17

    The precise recognition of appropriate synaptic partner neurons is a critical step during neural circuit assembly. However, little is known about the developmental context in which recognition specificity is important to establish synaptic contacts. We show that in the Drosophila visual system, sequential segregation of photoreceptor afferents, reflecting their birth order, lead to differential positioning of their grow