Refinement and Pattern Formation in Neural Circuits by the Interaction of Traveling Waves with Spike-Timing Dependent Plasticity

PubMed Central

Bennett, James E. M.; Bair, Wyeth

2015-01-01

Traveling waves in the developing brain are a prominent source of highly correlated spiking activity that may instruct the refinement of neural circuits. A candidate mechanism for mediating such refinement is spike-timing dependent plasticity (STDP), which translates correlated activity patterns into changes in synaptic strength. To assess the potential of these phenomena to build useful structure in developing neural circuits, we examined the interaction of wave activity with STDP rules in simple, biologically plausible models of spiking neurons. We derive an expression for the synaptic strength dynamics showing that, by mapping the time dependence of STDP into spatial interactions, traveling waves can build periodic synaptic connectivity patterns into feedforward circuits with a broad class of experimentally observed STDP rules. The spatial scale of the connectivity patterns increases with wave speed and STDP time constants. We verify these results with simulations and demonstrate their robustness to likely sources of noise. We show how this pattern formation ability, which is analogous to solutions of reaction-diffusion systems that have been widely applied to biological pattern formation, can be harnessed to instruct the refinement of postsynaptic receptive fields. Our results hold for rich, complex wave patterns in two dimensions and over several orders of magnitude in wave speeds and STDP time constants, and they provide predictions that can be tested under existing experimental paradigms. Our model generalizes across brain areas and STDP rules, allowing broad application to the ubiquitous occurrence of traveling waves and to wave-like activity patterns induced by moving stimuli. PMID:26308406

Refinement and Pattern Formation in Neural Circuits by the Interaction of Traveling Waves with Spike-Timing Dependent Plasticity.

PubMed

Bennett, James E M; Bair, Wyeth

2015-08-01

Traveling waves in the developing brain are a prominent source of highly correlated spiking activity that may instruct the refinement of neural circuits. A candidate mechanism for mediating such refinement is spike-timing dependent plasticity (STDP), which translates correlated activity patterns into changes in synaptic strength. To assess the potential of these phenomena to build useful structure in developing neural circuits, we examined the interaction of wave activity with STDP rules in simple, biologically plausible models of spiking neurons. We derive an expression for the synaptic strength dynamics showing that, by mapping the time dependence of STDP into spatial interactions, traveling waves can build periodic synaptic connectivity patterns into feedforward circuits with a broad class of experimentally observed STDP rules. The spatial scale of the connectivity patterns increases with wave speed and STDP time constants. We verify these results with simulations and demonstrate their robustness to likely sources of noise. We show how this pattern formation ability, which is analogous to solutions of reaction-diffusion systems that have been widely applied to biological pattern formation, can be harnessed to instruct the refinement of postsynaptic receptive fields. Our results hold for rich, complex wave patterns in two dimensions and over several orders of magnitude in wave speeds and STDP time constants, and they provide predictions that can be tested under existing experimental paradigms. Our model generalizes across brain areas and STDP rules, allowing broad application to the ubiquitous occurrence of traveling waves and to wave-like activity patterns induced by moving stimuli.

Long-term depression of inhibitory synaptic transmission induced by spike-timing dependent plasticity requires coactivation of endocannabinoid and muscarinic receptors.

PubMed

Ahumada, Juan; Fernández de Sevilla, David; Couve, Alejandro; Buño, Washington; Fuenzalida, Marco

2013-12-01

The precise timing of pre-postsynaptic activity is vital for the induction of long-term potentiation (LTP) or depression (LTD) at many central synapses. We show in synapses of rat CA1 pyramidal neurons in vitro that spike timing dependent plasticity (STDP) protocols that induce LTP at glutamatergic synapses can evoke LTD of inhibitory postsynaptic currents or STDP-iLTD. The STDP-iLTD requires a postsynaptic Ca(2+) increase, a release of endocannabinoids (eCBs), the activation of type-1 endocananabinoid receptors and presynaptic muscarinic receptors that mediate a decreased probability of GABA release. In contrast, the STDP-iLTD is independent of the activation of nicotinic receptors, GABAB Rs and G protein-coupled postsynaptic receptors at pyramidal neurons. We determine that the downregulation of presynaptic Cyclic adenosine monophosphate/protein Kinase A pathways is essential for the induction of STDP-iLTD. These results suggest a novel mechanism by which the activation of cholinergic neurons and retrograde signaling by eCBs can modulate the efficacy of GABAergic synaptic transmission in ways that may contribute to information processing and storage in the hippocampus. Copyright © 2013 Wiley Periodicals, Inc.

Dendritic small conductance calcium-activated potassium channels activated by action potentials suppress EPSPs and gate spike-timing dependent synaptic plasticity.

PubMed

Jones, Scott L; To, Minh-Son; Stuart, Greg J

2017-10-23

Small conductance calcium-activated potassium channels (SK channels) are present in spines and can be activated by backpropagating action potentials (APs). This suggests they may play a critical role in spike-timing dependent synaptic plasticity (STDP). Consistent with this idea, EPSPs in both cortical and hippocampal pyramidal neurons were suppressed by preceding APs in an SK-dependent manner. In cortical pyramidal neurons EPSP suppression by preceding APs depended on their precise timing as well as the distance of activated synapses from the soma, was dendritic in origin, and involved SK-dependent suppression of NMDA receptor activation. As a result SK channel activation by backpropagating APs gated STDP induction during low-frequency AP-EPSP pairing, with both LTP and LTD absent under control conditions but present after SK channel block. These findings indicate that activation of SK channels in spines by backpropagating APs plays a key role in regulating both EPSP amplitude and STDP induction.

Spike-timing-dependent plasticity in the human dorso-lateral prefrontal cortex.

PubMed

Casula, Elias Paolo; Pellicciari, Maria Concetta; Picazio, Silvia; Caltagirone, Carlo; Koch, Giacomo

2016-12-01

Changes in the synaptic strength of neural connections are induced by repeated coupling of activity of interconnected neurons with precise timing, a phenomenon known as spike-timing-dependent plasticity (STDP). It is debated if this mechanism exists in large-scale cortical networks in humans. We combined transcranial magnetic stimulation (TMS) with concurrent electroencephalography (EEG) to directly investigate the effects of two paired associative stimulation (PAS) protocols (fronto-parietal and parieto-frontal) of pre and post-synaptic inputs within the human fronto-parietal network. We found evidence that the dorsolateral prefrontal cortex (DLPFC) has the potential to form robust STDP. Long-term potentiation/depression of TMS-evoked cortical activity is prompted after that DLPFC stimulation is followed/preceded by posterior parietal stimulation. Such bidirectional changes are paralleled by sustained increase/decrease of high-frequency oscillatory activity, likely reflecting STDP responsivity. The current findings could be important to drive plasticity of damaged cortical circuits in patients with cognitive or psychiatric disorders. Copyright © 2016 Elsevier Inc. All rights reserved.

Does Spike-Timing-Dependent Synaptic Plasticity Couple or Decouple Neurons Firing in Synchrony?

PubMed Central

Knoblauch, Andreas; Hauser, Florian; Gewaltig, Marc-Oliver; Körner, Edgar; Palm, Günther

2012-01-01

Spike synchronization is thought to have a constructive role for feature integration, attention, associative learning, and the formation of bidirectionally connected Hebbian cell assemblies. By contrast, theoretical studies on spike-timing-dependent plasticity (STDP) report an inherently decoupling influence of spike synchronization on synaptic connections of coactivated neurons. For example, bidirectional synaptic connections as found in cortical areas could be reproduced only by assuming realistic models of STDP and rate coding. We resolve this conflict by theoretical analysis and simulation of various simple and realistic STDP models that provide a more complete characterization of conditions when STDP leads to either coupling or decoupling of neurons firing in synchrony. In particular, we show that STDP consistently couples synchronized neurons if key model parameters are matched to physiological data: First, synaptic potentiation must be significantly stronger than synaptic depression for small (positive or negative) time lags between presynaptic and postsynaptic spikes. Second, spike synchronization must be sufficiently imprecise, for example, within a time window of 5–10 ms instead of 1 ms. Third, axonal propagation delays should not be much larger than dendritic delays. Under these assumptions synchronized neurons will be strongly coupled leading to a dominance of bidirectional synaptic connections even for simple STDP models and low mean firing rates at the level of spontaneous activity. PMID:22936909

Presynaptic Ionotropic Receptors Controlling and Modulating the Rules for Spike Timing-Dependent Plasticity

PubMed Central

Verhoog, Matthijs B.; Mansvelder, Huibert D.

2011-01-01

Throughout life, activity-dependent changes in neuronal connection strength enable the brain to refine neural circuits and learn based on experience. In line with predictions made by Hebb, synapse strength can be modified depending on the millisecond timing of action potential firing (STDP). The sign of synaptic plasticity depends on the spike order of presynaptic and postsynaptic neurons. Ionotropic neurotransmitter receptors, such as NMDA receptors and nicotinic acetylcholine receptors, are intimately involved in setting the rules for synaptic strengthening and weakening. In addition, timing rules for STDP within synapses are not fixed. They can be altered by activation of ionotropic receptors located at, or close to, synapses. Here, we will highlight studies that uncovered how network actions control and modulate timing rules for STDP by activating presynaptic ionotropic receptors. Furthermore, we will discuss how interaction between different types of ionotropic receptors may create “timing” windows during which particular timing rules lead to synaptic changes. PMID:21941664

Emergence of small-world structure in networks of spiking neurons through STDP plasticity.

PubMed

Basalyga, Gleb; Gleiser, Pablo M; Wennekers, Thomas

2011-01-01

In this work, we use a complex network approach to investigate how a neural network structure changes under synaptic plasticity. In particular, we consider a network of conductance-based, single-compartment integrate-and-fire excitatory and inhibitory neurons. Initially the neurons are connected randomly with uniformly distributed synaptic weights. The weights of excitatory connections can be strengthened or weakened during spiking activity by the mechanism known as spike-timing-dependent plasticity (STDP). We extract a binary directed connection matrix by thresholding the weights of the excitatory connections at every simulation step and calculate its major topological characteristics such as the network clustering coefficient, characteristic path length and small-world index. We numerically demonstrate that, under certain conditions, a nontrivial small-world structure can emerge from a random initial network subject to STDP learning.

Depression-Biased Reverse Plasticity Rule Is Required for Stable Learning at Top-Down Connections

PubMed Central

Burbank, Kendra S.; Kreiman, Gabriel

2012-01-01

Top-down synapses are ubiquitous throughout neocortex and play a central role in cognition, yet little is known about their development and specificity. During sensory experience, lower neocortical areas are activated before higher ones, causing top-down synapses to experience a preponderance of post-synaptic activity preceding pre-synaptic activity. This timing pattern is the opposite of that experienced by bottom-up synapses, which suggests that different versions of spike-timing dependent synaptic plasticity (STDP) rules may be required at top-down synapses. We consider a two-layer neural network model and investigate which STDP rules can lead to a distribution of top-down synaptic weights that is stable, diverse and avoids strong loops. We introduce a temporally reversed rule (rSTDP) where top-down synapses are potentiated if post-synaptic activity precedes pre-synaptic activity. Combining analytical work and integrate-and-fire simulations, we show that only depression-biased rSTDP (and not classical STDP) produces stable and diverse top-down weights. The conclusions did not change upon addition of homeostatic mechanisms, multiplicative STDP rules or weak external input to the top neurons. Our prediction for rSTDP at top-down synapses, which are distally located, is supported by recent neurophysiological evidence showing the existence of temporally reversed STDP in synapses that are distal to the post-synaptic cell body. PMID:22396630

Minimizing the effect of process mismatch in a neuromorphic system using spike-timing-dependent adaptation.

PubMed

Cameron, Katherine; Murray, Alan

2008-05-01

This paper investigates whether spike-timing-dependent plasticity (STDP) can minimize the effect of mismatch within the context of a depth-from-motion algorithm. To improve noise rejection, this algorithm contains a spike prediction element, whose performance is degraded by analog very large scale integration (VLSI) mismatch. The error between the actual spike arrival time and the prediction is used as the input to an STDP circuit, to improve future predictions. Before STDP adaptation, the error reflects the degree of mismatch within the prediction circuitry. After STDP adaptation, the error indicates to what extent the adaptive circuitry can minimize the effect of transistor mismatch. The circuitry is tested with static and varying prediction times and chip results are presented. The effect of noisy spikes is also investigated. Under all conditions the STDP adaptation is shown to improve performance.

Bayesian Computation Emerges in Generic Cortical Microcircuits through Spike-Timing-Dependent Plasticity

PubMed Central

Nessler, Bernhard; Pfeiffer, Michael; Buesing, Lars; Maass, Wolfgang

2013-01-01

The principles by which networks of neurons compute, and how spike-timing dependent plasticity (STDP) of synaptic weights generates and maintains their computational function, are unknown. Preceding work has shown that soft winner-take-all (WTA) circuits, where pyramidal neurons inhibit each other via interneurons, are a common motif of cortical microcircuits. We show through theoretical analysis and computer simulations that Bayesian computation is induced in these network motifs through STDP in combination with activity-dependent changes in the excitability of neurons. The fundamental components of this emergent Bayesian computation are priors that result from adaptation of neuronal excitability and implicit generative models for hidden causes that are created in the synaptic weights through STDP. In fact, a surprising result is that STDP is able to approximate a powerful principle for fitting such implicit generative models to high-dimensional spike inputs: Expectation Maximization. Our results suggest that the experimentally observed spontaneous activity and trial-to-trial variability of cortical neurons are essential features of their information processing capability, since their functional role is to represent probability distributions rather than static neural codes. Furthermore it suggests networks of Bayesian computation modules as a new model for distributed information processing in the cortex. PMID:23633941

Excitatory and inhibitory STDP jointly tune feedforward neural circuits to selectively propagate correlated spiking activity

PubMed Central

Kleberg, Florence I.; Fukai, Tomoki; Gilson, Matthieu

2014-01-01

Spike-timing-dependent plasticity (STDP) has been well established between excitatory neurons and several computational functions have been proposed in various neural systems. Despite some recent efforts, however, there is a significant lack of functional understanding of inhibitory STDP (iSTDP) and its interplay with excitatory STDP (eSTDP). Here, we demonstrate by analytical and numerical methods that iSTDP contributes crucially to the balance of excitatory and inhibitory weights for the selection of a specific signaling pathway among other pathways in a feedforward circuit. This pathway selection is based on the high sensitivity of STDP to correlations in spike times, which complements a recent proposal for the role of iSTDP in firing-rate based selection. Our model predicts that asymmetric anti-Hebbian iSTDP exceeds asymmetric Hebbian iSTDP for supporting pathway-specific balance, which we show is useful for propagating transient neuronal responses. Furthermore, we demonstrate how STDPs at excitatory–excitatory, excitatory–inhibitory, and inhibitory–excitatory synapses cooperate to improve the pathway selection. We propose that iSTDP is crucial for shaping the network structure that achieves efficient processing of synchronous spikes. PMID:24847242

A Learning Theory for Reward-Modulated Spike-Timing-Dependent Plasticity with Application to Biofeedback

PubMed Central

Maass, Wolfgang

2008-01-01

Reward-modulated spike-timing-dependent plasticity (STDP) has recently emerged as a candidate for a learning rule that could explain how behaviorally relevant adaptive changes in complex networks of spiking neurons could be achieved in a self-organizing manner through local synaptic plasticity. However, the capabilities and limitations of this learning rule could so far only be tested through computer simulations. This article provides tools for an analytic treatment of reward-modulated STDP, which allows us to predict under which conditions reward-modulated STDP will achieve a desired learning effect. These analytical results imply that neurons can learn through reward-modulated STDP to classify not only spatial but also temporal firing patterns of presynaptic neurons. They also can learn to respond to specific presynaptic firing patterns with particular spike patterns. Finally, the resulting learning theory predicts that even difficult credit-assignment problems, where it is very hard to tell which synaptic weights should be modified in order to increase the global reward for the system, can be solved in a self-organizing manner through reward-modulated STDP. This yields an explanation for a fundamental experimental result on biofeedback in monkeys by Fetz and Baker. In this experiment monkeys were rewarded for increasing the firing rate of a particular neuron in the cortex and were able to solve this extremely difficult credit assignment problem. Our model for this experiment relies on a combination of reward-modulated STDP with variable spontaneous firing activity. Hence it also provides a possible functional explanation for trial-to-trial variability, which is characteristic for cortical networks of neurons but has no analogue in currently existing artificial computing systems. In addition our model demonstrates that reward-modulated STDP can be applied to all synapses in a large recurrent neural network without endangering the stability of the network dynamics. PMID:18846203

Stability versus neuronal specialization for STDP: long-tail weight distributions solve the dilemma.

PubMed

Gilson, Matthieu; Fukai, Tomoki

2011-01-01

Spike-timing-dependent plasticity (STDP) modifies the weight (or strength) of synaptic connections between neurons and is considered to be crucial for generating network structure. It has been observed in physiology that, in addition to spike timing, the weight update also depends on the current value of the weight. The functional implications of this feature are still largely unclear. Additive STDP gives rise to strong competition among synapses, but due to the absence of weight dependence, it requires hard boundaries to secure the stability of weight dynamics. Multiplicative STDP with linear weight dependence for depression ensures stability, but it lacks sufficiently strong competition required to obtain a clear synaptic specialization. A solution to this stability-versus-function dilemma can be found with an intermediate parametrization between additive and multiplicative STDP. Here we propose a novel solution to the dilemma, named log-STDP, whose key feature is a sublinear weight dependence for depression. Due to its specific weight dependence, this new model can produce significantly broad weight distributions with no hard upper bound, similar to those recently observed in experiments. Log-STDP induces graded competition between synapses, such that synapses receiving stronger input correlations are pushed further in the tail of (very) large weights. Strong weights are functionally important to enhance the neuronal response to synchronous spike volleys. Depending on the input configuration, multiple groups of correlated synaptic inputs exhibit either winner-share-all or winner-take-all behavior. When the configuration of input correlations changes, individual synapses quickly and robustly readapt to represent the new configuration. We also demonstrate the advantages of log-STDP for generating a stable structure of strong weights in a recurrently connected network. These properties of log-STDP are compared with those of previous models. Through long-tail weight distributions, log-STDP achieves both stable dynamics for and robust competition of synapses, which are crucial for spike-based information processing.

Artificial neuron operations and spike-timing-dependent plasticity using memristive devices for brain-inspired computing

NASA Astrophysics Data System (ADS)

Marukame, Takao; Nishi, Yoshifumi; Yasuda, Shin-ichi; Tanamoto, Tetsufumi

2018-04-01

The use of memristive devices for creating artificial neurons is promising for brain-inspired computing from the viewpoints of computation architecture and learning protocol. We present an energy-efficient multiplier accumulator based on a memristive array architecture incorporating both analog and digital circuitries. The analog circuitry is used to full advantage for neural networks, as demonstrated by the spike-timing-dependent plasticity (STDP) in fabricated AlO x /TiO x -based metal-oxide memristive devices. STDP protocols for controlling periodic analog resistance with long-range stability were experimentally verified using a variety of voltage amplitudes and spike timings.

Acetylcholine-modulated plasticity in reward-driven navigation: a computational study.

PubMed

Zannone, Sara; Brzosko, Zuzanna; Paulsen, Ole; Clopath, Claudia

2018-06-21

Neuromodulation plays a fundamental role in the acquisition of new behaviours. In previous experimental work, we showed that acetylcholine biases hippocampal synaptic plasticity towards depression, and the subsequent application of dopamine can retroactively convert depression into potentiation. We also demonstrated that incorporating this sequentially neuromodulated Spike-Timing-Dependent Plasticity (STDP) rule in a network model of navigation yields effective learning of changing reward locations. Here, we employ computational modelling to further characterize the effects of cholinergic depression on behaviour. We find that acetylcholine, by allowing learning from negative outcomes, enhances exploration over the action space. We show that this results in a variety of effects, depending on the structure of the model, the environment and the task. Interestingly, sequentially neuromodulated STDP also yields flexible learning, surpassing the performance of other reward-modulated plasticity rules.

Role of AMPA and NMDA receptors and back-propagating action potentials in spike timing-dependent plasticity.

PubMed

Fuenzalida, Marco; Fernández de Sevilla, David; Couve, Alejandro; Buño, Washington

2010-01-01

The cellular mechanisms that mediate spike timing-dependent plasticity (STDP) are largely unknown. We studied in vitro in CA1 pyramidal neurons the contribution of AMPA and N-methyl-d-aspartate (NMDA) components of Schaffer collateral (SC) excitatory postsynaptic potentials (EPSPs; EPSP(AMPA) and EPSP(NMDA)) and of the back-propagating action potential (BAP) to the long-term potentiation (LTP) induced by a STDP protocol that consisted in pairing an EPSP and a BAP. Transient blockade of EPSP(AMPA) with 7-nitro-2,3-dioxo-1,4-dihydroquinoxaline-6-carbonitrile (CNQX) during the STDP protocol prevented LTP. Contrastingly LTP was induced under transient inhibition of EPSP(AMPA) by combining SC stimulation, an imposed EPSP(AMPA)-like depolarization, and BAP or by coupling the EPSP(NMDA) evoked under sustained depolarization (approximately -40 mV) and BAP. In Mg(2+)-free solution EPSP(NMDA) and BAP also produced LTP. Suppression of EPSP(NMDA) or BAP always prevented LTP. Thus activation of NMDA receptors and BAPs are needed but not sufficient because AMPA receptor activation is also obligatory for STDP. However, a transient depolarization of another origin that unblocks NMDA receptors and a BAP may also trigger LTP.

Diverse spike-timing-dependent plasticity based on multilevel HfO x memristor for neuromorphic computing

NASA Astrophysics Data System (ADS)

Lu, Ke; Li, Yi; He, Wei-Fan; Chen, Jia; Zhou, Ya-Xiong; Duan, Nian; Jin, Miao-Miao; Gu, Wei; Xue, Kan-Hao; Sun, Hua-Jun; Miao, Xiang-Shui

2018-06-01

Memristors have emerged as promising candidates for artificial synaptic devices, serving as the building block of brain-inspired neuromorphic computing. In this letter, we developed a Pt/HfO x /Ti memristor with nonvolatile multilevel resistive switching behaviors due to the evolution of the conductive filaments and the variation in the Schottky barrier. Diverse state-dependent spike-timing-dependent-plasticity (STDP) functions were implemented with different initial resistance states. The measured STDP forms were adopted as the learning rule for a three-layer spiking neural network which achieves a 75.74% recognition accuracy for MNIST handwritten digit dataset. This work has shown the capability of memristive synapse in spiking neural networks for pattern recognition application.

A Re-Examination of Hebbian-Covariance Rules and Spike Timing-Dependent Plasticity in Cat Visual Cortex in vivo

PubMed Central

Frégnac, Yves; Pananceau, Marc; René, Alice; Huguet, Nazyed; Marre, Olivier; Levy, Manuel; Shulz, Daniel E.

2010-01-01

Spike timing-dependent plasticity (STDP) is considered as an ubiquitous rule for associative plasticity in cortical networks in vitro. However, limited supporting evidence for its functional role has been provided in vivo. In particular, there are very few studies demonstrating the co-occurrence of synaptic efficiency changes and alteration of sensory responses in adult cortex during Hebbian or STDP protocols. We addressed this issue by reviewing and comparing the functional effects of two types of cellular conditioning in cat visual cortex. The first one, referred to as the “covariance” protocol, obeys a generalized Hebbian framework, by imposing, for different stimuli, supervised positive and negative changes in covariance between postsynaptic and presynaptic activity rates. The second protocol, based on intracellular recordings, replicated in vivo variants of the theta-burst paradigm (TBS), proven successful in inducing long-term potentiation in vitro. Since it was shown to impose a precise correlation delay between the electrically activated thalamic input and the TBS-induced postsynaptic spike, this protocol can be seen as a probe of causal (“pre-before-post”) STDP. By choosing a thalamic region where the visual field representation was in retinotopic overlap with the intracellularly recorded cortical receptive field as the afferent site for supervised electrical stimulation, this protocol allowed to look for possible correlates between STDP and functional reorganization of the conditioned cortical receptive field. The rate-based “covariance protocol” induced significant and large amplitude changes in receptive field properties, in both kitten and adult V1 cortex. The TBS STDP-like protocol produced in the adult significant changes in the synaptic gain of the electrically activated thalamic pathway, but the statistical significance of the functional correlates was detectable mostly at the population level. Comparison of our observations with the literature leads us to re-examine the experimental status of spike timing-dependent potentiation in adult cortex. We propose the existence of a correlation-based threshold in vivo, limiting the expression of STDP-induced changes outside the critical period, and which accounts for the stability of synaptic weights during sensory cortical processing in the absence of attention or reward-gated supervision. PMID:21423533

Computational modeling of spiking neural network with learning rules from STDP and intrinsic plasticity

NASA Astrophysics Data System (ADS)

Li, Xiumin; Wang, Wei; Xue, Fangzheng; Song, Yongduan

2018-02-01

Recently there has been continuously increasing interest in building up computational models of spiking neural networks (SNN), such as the Liquid State Machine (LSM). The biologically inspired self-organized neural networks with neural plasticity can enhance the capability of computational performance, with the characteristic features of dynamical memory and recurrent connection cycles which distinguish them from the more widely used feedforward neural networks. Despite a variety of computational models for brain-like learning and information processing have been proposed, the modeling of self-organized neural networks with multi-neural plasticity is still an important open challenge. The main difficulties lie in the interplay among different forms of neural plasticity rules and understanding how structures and dynamics of neural networks shape the computational performance. In this paper, we propose a novel approach to develop the models of LSM with a biologically inspired self-organizing network based on two neural plasticity learning rules. The connectivity among excitatory neurons is adapted by spike-timing-dependent plasticity (STDP) learning; meanwhile, the degrees of neuronal excitability are regulated to maintain a moderate average activity level by another learning rule: intrinsic plasticity (IP). Our study shows that LSM with STDP+IP performs better than LSM with a random SNN or SNN obtained by STDP alone. The noticeable improvement with the proposed method is due to the better reflected competition among different neurons in the developed SNN model, as well as the more effectively encoded and processed relevant dynamic information with its learning and self-organizing mechanism. This result gives insights to the optimization of computational models of spiking neural networks with neural plasticity.

Optimal Design for Hetero-Associative Memory: Hippocampal CA1 Phase Response Curve and Spike-Timing-Dependent Plasticity

PubMed Central

Miyata, Ryota; Ota, Keisuke; Aonishi, Toru

2013-01-01

Recently reported experimental findings suggest that the hippocampal CA1 network stores spatio-temporal spike patterns and retrieves temporally reversed and spread-out patterns. In this paper, we explore the idea that the properties of the neural interactions and the synaptic plasticity rule in the CA1 network enable it to function as a hetero-associative memory recalling such reversed and spread-out spike patterns. In line with Lengyel’s speculation (Lengyel et al., 2005), we firstly derive optimally designed spike-timing-dependent plasticity (STDP) rules that are matched to neural interactions formalized in terms of phase response curves (PRCs) for performing the hetero-associative memory function. By maximizing object functions formulated in terms of mutual information for evaluating memory retrieval performance, we search for STDP window functions that are optimal for retrieval of normal and doubly spread-out patterns under the constraint that the PRCs are those of CA1 pyramidal neurons. The system, which can retrieve normal and doubly spread-out patterns, can also retrieve reversed patterns with the same quality. Finally, we demonstrate that purposely designed STDP window functions qualitatively conform to typical ones found in CA1 pyramidal neurons. PMID:24204822

Learning complex temporal patterns with resource-dependent spike timing-dependent plasticity.

PubMed

Hunzinger, Jason F; Chan, Victor H; Froemke, Robert C

2012-07-01

Studies of spike timing-dependent plasticity (STDP) have revealed that long-term changes in the strength of a synapse may be modulated substantially by temporal relationships between multiple presynaptic and postsynaptic spikes. Whereas long-term potentiation (LTP) and long-term depression (LTD) of synaptic strength have been modeled as distinct or separate functional mechanisms, here, we propose a new shared resource model. A functional consequence of our model is fast, stable, and diverse unsupervised learning of temporal multispike patterns with a biologically consistent spiking neural network. Due to interdependencies between LTP and LTD, dendritic delays, and proactive homeostatic aspects of the model, neurons are equipped to learn to decode temporally coded information within spike bursts. Moreover, neurons learn spike timing with few exposures in substantial noise and jitter. Surprisingly, despite having only one parameter, the model also accurately predicts in vitro observations of STDP in more complex multispike trains, as well as rate-dependent effects. We discuss candidate commonalities in natural long-term plasticity mechanisms.

RM-SORN: a reward-modulated self-organizing recurrent neural network.

PubMed

Aswolinskiy, Witali; Pipa, Gordon

2015-01-01

Neural plasticity plays an important role in learning and memory. Reward-modulation of plasticity offers an explanation for the ability of the brain to adapt its neural activity to achieve a rewarded goal. Here, we define a neural network model that learns through the interaction of Intrinsic Plasticity (IP) and reward-modulated Spike-Timing-Dependent Plasticity (STDP). IP enables the network to explore possible output sequences and STDP, modulated by reward, reinforces the creation of the rewarded output sequences. The model is tested on tasks for prediction, recall, non-linear computation, pattern recognition, and sequence generation. It achieves performance comparable to networks trained with supervised learning, while using simple, biologically motivated plasticity rules, and rewarding strategies. The results confirm the importance of investigating the interaction of several plasticity rules in the context of reward-modulated learning and whether reward-modulated self-organization can explain the amazing capabilities of the brain.

Competitive STDP Learning of Overlapping Spatial Patterns.

PubMed

Krunglevicius, Dalius

2015-08-01

Spike-timing-dependent plasticity (STDP) is a set of Hebbian learning rules firmly based on biological evidence. It has been demonstrated that one of the STDP learning rules is suited for learning spatiotemporal patterns. When multiple neurons are organized in a simple competitive spiking neural network, this network is capable of learning multiple distinct patterns. If patterns overlap significantly (i.e., patterns are mutually inclusive), however, competition would not preclude trained neuron's responding to a new pattern and adjusting synaptic weights accordingly. This letter presents a simple neural network that combines vertical inhibition and Euclidean distance-dependent synaptic strength factor. This approach helps to solve the problem of pattern size-dependent parameter optimality and significantly reduces the probability of a neuron's forgetting an already learned pattern. For demonstration purposes, the network was trained for the first ten letters of the Braille alphabet.

Dynamic Hebbian Cross-Correlation Learning Resolves the Spike Timing Dependent Plasticity Conundrum.

PubMed

Olde Scheper, Tjeerd V; Meredith, Rhiannon M; Mansvelder, Huibert D; van Pelt, Jaap; van Ooyen, Arjen

2017-01-01

Spike Timing-Dependent Plasticity has been found to assume many different forms. The classic STDP curve, with one potentiating and one depressing window, is only one of many possible curves that describe synaptic learning using the STDP mechanism. It has been shown experimentally that STDP curves may contain multiple LTP and LTD windows of variable width, and even inverted windows. The underlying STDP mechanism that is capable of producing such an extensive, and apparently incompatible, range of learning curves is still under investigation. In this paper, it is shown that STDP originates from a combination of two dynamic Hebbian cross-correlations of local activity at the synapse. The correlation of the presynaptic activity with the local postsynaptic activity is a robust and reliable indicator of the discrepancy between the presynaptic neuron and the postsynaptic neuron's activity. The second correlation is between the local postsynaptic activity with dendritic activity which is a good indicator of matching local synaptic and dendritic activity. We show that this simple time-independent learning rule can give rise to many forms of the STDP learning curve. The rule regulates synaptic strength without the need for spike matching or other supervisory learning mechanisms. Local differences in dendritic activity at the synapse greatly affect the cross-correlation difference which determines the relative contributions of different neural activity sources. Dendritic activity due to nearby synapses, action potentials, both forward and back-propagating, as well as inhibitory synapses will dynamically modify the local activity at the synapse, and the resulting STDP learning rule. The dynamic Hebbian learning rule ensures furthermore, that the resulting synaptic strength is dynamically stable, and that interactions between synapses do not result in local instabilities. The rule clearly demonstrates that synapses function as independent localized computational entities, each contributing to the global activity, not in a simply linear fashion, but in a manner that is appropriate to achieve local and global stability of the neuron and the entire dendritic structure.

Emergence of network structure due to spike-timing-dependent plasticity in recurrent neuronal networks IV: structuring synaptic pathways among recurrent connections.

PubMed

Gilson, Matthieu; Burkitt, Anthony N; Grayden, David B; Thomas, Doreen A; van Hemmen, J Leo

2009-12-01

In neuronal networks, the changes of synaptic strength (or weight) performed by spike-timing-dependent plasticity (STDP) are hypothesized to give rise to functional network structure. This article investigates how this phenomenon occurs for the excitatory recurrent connections of a network with fixed input weights that is stimulated by external spike trains. We develop a theoretical framework based on the Poisson neuron model to analyze the interplay between the neuronal activity (firing rates and the spike-time correlations) and the learning dynamics, when the network is stimulated by correlated pools of homogeneous Poisson spike trains. STDP can lead to both a stabilization of all the neuron firing rates (homeostatic equilibrium) and a robust weight specialization. The pattern of specialization for the recurrent weights is determined by a relationship between the input firing-rate and correlation structures, the network topology, the STDP parameters and the synaptic response properties. We find conditions for feed-forward pathways or areas with strengthened self-feedback to emerge in an initially homogeneous recurrent network.

Effects of spike-time-dependent plasticity on the stochastic resonance of small-world neuronal networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yu, Haitao; Guo, Xinmeng; Wang, Jiang, E-mail: jiangwang@tju.edu.cn

2014-09-01

The phenomenon of stochastic resonance in Newman-Watts small-world neuronal networks is investigated when the strength of synaptic connections between neurons is adaptively adjusted by spike-time-dependent plasticity (STDP). It is shown that irrespective of the synaptic connectivity is fixed or adaptive, the phenomenon of stochastic resonance occurs. The efficiency of network stochastic resonance can be largely enhanced by STDP in the coupling process. Particularly, the resonance for adaptive coupling can reach a much larger value than that for fixed one when the noise intensity is small or intermediate. STDP with dominant depression and small temporal window ratio is more efficient formore » the transmission of weak external signal in small-world neuronal networks. In addition, we demonstrate that the effect of stochastic resonance can be further improved via fine-tuning of the average coupling strength of the adaptive network. Furthermore, the small-world topology can significantly affect stochastic resonance of excitable neuronal networks. It is found that there exists an optimal probability of adding links by which the noise-induced transmission of weak periodic signal peaks.« less

Channel Noise-Enhanced Synchronization Transitions Induced by Time Delay in Adaptive Neuronal Networks with Spike-Timing-Dependent Plasticity

NASA Astrophysics Data System (ADS)

Xie, Huijuan; Gong, Yubing; Wang, Baoying

In this paper, we numerically study the effect of channel noise on synchronization transitions induced by time delay in adaptive scale-free Hodgkin-Huxley neuronal networks with spike-timing-dependent plasticity (STDP). It is found that synchronization transitions by time delay vary as channel noise intensity is changed and become most pronounced when channel noise intensity is optimal. This phenomenon depends on STDP and network average degree, and it can be either enhanced or suppressed as network average degree increases depending on channel noise intensity. These results show that there are optimal channel noise and network average degree that can enhance the synchronization transitions by time delay in the adaptive neuronal networks. These findings could be helpful for better understanding of the regulation effect of channel noise on synchronization of neuronal networks. They could find potential implications for information transmission in neural systems.

Correlation-based model of artificially induced plasticity in motor cortex by a bidirectional brain-computer interface.

PubMed

Lajoie, Guillaume; Krouchev, Nedialko I; Kalaska, John F; Fairhall, Adrienne L; Fetz, Eberhard E

2017-02-01

Experiments show that spike-triggered stimulation performed with Bidirectional Brain-Computer-Interfaces (BBCI) can artificially strengthen connections between separate neural sites in motor cortex (MC). When spikes from a neuron recorded at one MC site trigger stimuli at a second target site after a fixed delay, the connections between sites eventually strengthen. It was also found that effective spike-stimulus delays are consistent with experimentally derived spike-timing-dependent plasticity (STDP) rules, suggesting that STDP is key to drive these changes. However, the impact of STDP at the level of circuits, and the mechanisms governing its modification with neural implants remain poorly understood. The present work describes a recurrent neural network model with probabilistic spiking mechanisms and plastic synapses capable of capturing both neural and synaptic activity statistics relevant to BBCI conditioning protocols. Our model successfully reproduces key experimental results, both established and new, and offers mechanistic insights into spike-triggered conditioning. Using analytical calculations and numerical simulations, we derive optimal operational regimes for BBCIs, and formulate predictions concerning the efficacy of spike-triggered conditioning in different regimes of cortical activity.

Correlation-based model of artificially induced plasticity in motor cortex by a bidirectional brain-computer interface

PubMed Central

Lajoie, Guillaume; Kalaska, John F.; Fairhall, Adrienne L.; Fetz, Eberhard E.

2017-01-01

Experiments show that spike-triggered stimulation performed with Bidirectional Brain-Computer-Interfaces (BBCI) can artificially strengthen connections between separate neural sites in motor cortex (MC). When spikes from a neuron recorded at one MC site trigger stimuli at a second target site after a fixed delay, the connections between sites eventually strengthen. It was also found that effective spike-stimulus delays are consistent with experimentally derived spike-timing-dependent plasticity (STDP) rules, suggesting that STDP is key to drive these changes. However, the impact of STDP at the level of circuits, and the mechanisms governing its modification with neural implants remain poorly understood. The present work describes a recurrent neural network model with probabilistic spiking mechanisms and plastic synapses capable of capturing both neural and synaptic activity statistics relevant to BBCI conditioning protocols. Our model successfully reproduces key experimental results, both established and new, and offers mechanistic insights into spike-triggered conditioning. Using analytical calculations and numerical simulations, we derive optimal operational regimes for BBCIs, and formulate predictions concerning the efficacy of spike-triggered conditioning in different regimes of cortical activity. PMID:28151957

Delay selection by spike-timing-dependent plasticity in recurrent networks of spiking neurons receiving oscillatory inputs.

PubMed

Kerr, Robert R; Burkitt, Anthony N; Thomas, Doreen A; Gilson, Matthieu; Grayden, David B

2013-01-01

Learning rules, such as spike-timing-dependent plasticity (STDP), change the structure of networks of neurons based on the firing activity. A network level understanding of these mechanisms can help infer how the brain learns patterns and processes information. Previous studies have shown that STDP selectively potentiates feed-forward connections that have specific axonal delays, and that this underlies behavioral functions such as sound localization in the auditory brainstem of the barn owl. In this study, we investigate how STDP leads to the selective potentiation of recurrent connections with different axonal and dendritic delays during oscillatory activity. We develop analytical models of learning with additive STDP in recurrent networks driven by oscillatory inputs, and support the results using simulations with leaky integrate-and-fire neurons. Our results show selective potentiation of connections with specific axonal delays, which depended on the input frequency. In addition, we demonstrate how this can lead to a network becoming selective in the amplitude of its oscillatory response to this frequency. We extend this model of axonal delay selection within a single recurrent network in two ways. First, we show the selective potentiation of connections with a range of both axonal and dendritic delays. Second, we show axonal delay selection between multiple groups receiving out-of-phase, oscillatory inputs. We discuss the application of these models to the formation and activation of neuronal ensembles or cell assemblies in the cortex, and also to missing fundamental pitch perception in the auditory brainstem.

Delay Selection by Spike-Timing-Dependent Plasticity in Recurrent Networks of Spiking Neurons Receiving Oscillatory Inputs

PubMed Central

Kerr, Robert R.; Burkitt, Anthony N.; Thomas, Doreen A.; Gilson, Matthieu; Grayden, David B.

2013-01-01

Learning rules, such as spike-timing-dependent plasticity (STDP), change the structure of networks of neurons based on the firing activity. A network level understanding of these mechanisms can help infer how the brain learns patterns and processes information. Previous studies have shown that STDP selectively potentiates feed-forward connections that have specific axonal delays, and that this underlies behavioral functions such as sound localization in the auditory brainstem of the barn owl. In this study, we investigate how STDP leads to the selective potentiation of recurrent connections with different axonal and dendritic delays during oscillatory activity. We develop analytical models of learning with additive STDP in recurrent networks driven by oscillatory inputs, and support the results using simulations with leaky integrate-and-fire neurons. Our results show selective potentiation of connections with specific axonal delays, which depended on the input frequency. In addition, we demonstrate how this can lead to a network becoming selective in the amplitude of its oscillatory response to this frequency. We extend this model of axonal delay selection within a single recurrent network in two ways. First, we show the selective potentiation of connections with a range of both axonal and dendritic delays. Second, we show axonal delay selection between multiple groups receiving out-of-phase, oscillatory inputs. We discuss the application of these models to the formation and activation of neuronal ensembles or cell assemblies in the cortex, and also to missing fundamental pitch perception in the auditory brainstem. PMID:23408878

Spike-Timing Dependent Plasticity in Unipolar Silicon Oxide RRAM Devices

PubMed Central

Zarudnyi, Konstantin; Mehonic, Adnan; Montesi, Luca; Buckwell, Mark; Hudziak, Stephen; Kenyon, Anthony J.

2018-01-01

Resistance switching, or Resistive RAM (RRAM) devices show considerable potential for application in hardware spiking neural networks (neuro-inspired computing) by mimicking some of the behavior of biological synapses, and hence enabling non-von Neumann computer architectures. Spike-timing dependent plasticity (STDP) is one such behavior, and one example of several classes of plasticity that are being examined with the aim of finding suitable algorithms for application in many computing tasks such as coincidence detection, classification and image recognition. In previous work we have demonstrated that the neuromorphic capabilities of silicon-rich silicon oxide (SiOx) resistance switching devices extend beyond plasticity to include thresholding, spiking, and integration. We previously demonstrated such behaviors in devices operated in the unipolar mode, opening up the question of whether we could add plasticity to the list of features exhibited by our devices. Here we demonstrate clear STDP in unipolar devices. Significantly, we show that the response of our devices is broadly similar to that of biological synapses. This work further reinforces the potential of simple two-terminal RRAM devices to mimic neuronal functionality in hardware spiking neural networks. PMID:29472837

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

PubMed Central

Wang, Runchun M.; Hamilton, Tara J.; Tapson, Jonathan C.; van Schaik, André

2015-01-01

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 226 (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 or delayed pre-synaptic spike to the post-synaptic neuron 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 236 (64G) synaptic adaptors on a current high-end FPGA platform. PMID:26041985

Channel noise-induced temporal coherence transitions and synchronization transitions in adaptive neuronal networks with time delay

NASA Astrophysics Data System (ADS)

Gong, Yubing; Xie, Huijuan

2017-09-01

Using spike-timing-dependent plasticity (STDP), we study the effect of channel noise on temporal coherence and synchronization of adaptive scale-free Hodgkin-Huxley neuronal networks with time delay. It is found that the spiking regularity and spatial synchronization of the neurons intermittently increase and decrease as channel noise intensity is varied, exhibiting transitions of temporal coherence and synchronization. Moreover, this phenomenon depends on time delay, STDP, and network average degree. As time delay increases, the phenomenon is weakened, however, there are optimal STDP and network average degree by which the phenomenon becomes strongest. These results show that channel noise can intermittently enhance the temporal coherence and synchronization of the delayed adaptive neuronal networks. These findings provide a new insight into channel noise for the information processing and transmission in neural systems.

Interplay between Short- and Long-Term Plasticity in Cell-Assembly Formation

PubMed Central

Hiratani, Naoki; Fukai, Tomoki

2014-01-01

Various hippocampal and neocortical synapses of mammalian brain show both short-term plasticity and long-term plasticity, which are considered to underlie learning and memory by the brain. According to Hebb’s postulate, synaptic plasticity encodes memory traces of past experiences into cell assemblies in cortical circuits. However, it remains unclear how the various forms of long-term and short-term synaptic plasticity cooperatively create and reorganize such cell assemblies. Here, we investigate the mechanism in which the three forms of synaptic plasticity known in cortical circuits, i.e., spike-timing-dependent plasticity (STDP), short-term depression (STD) and homeostatic plasticity, cooperatively generate, retain and reorganize cell assemblies in a recurrent neuronal network model. We show that multiple cell assemblies generated by external stimuli can survive noisy spontaneous network activity for an adequate range of the strength of STD. Furthermore, our model predicts that a symmetric temporal window of STDP, such as observed in dopaminergic modulations on hippocampal neurons, is crucial for the retention and integration of multiple cell assemblies. These results may have implications for the understanding of cortical memory processes. PMID:25007209

Reaction-diffusion-like formalism for plastic neural networks reveals dissipative solitons at criticality

NASA Astrophysics Data System (ADS)

Grytskyy, Dmytro; Diesmann, Markus; Helias, Moritz

2016-06-01

Self-organized structures in networks with spike-timing dependent synaptic plasticity (STDP) are likely to play a central role for information processing in the brain. In the present study we derive a reaction-diffusion-like formalism for plastic feed-forward networks of nonlinear rate-based model neurons with a correlation sensitive learning rule inspired by and being qualitatively similar to STDP. After obtaining equations that describe the change of the spatial shape of the signal from layer to layer, we derive a criterion for the nonlinearity necessary to obtain stable dynamics for arbitrary input. We classify the possible scenarios of signal evolution and find that close to the transition to the unstable regime metastable solutions appear. The form of these dissipative solitons is determined analytically and the evolution and interaction of several such coexistent objects is investigated.

Mixed Signal Learning by Spike Correlation Propagation in Feedback Inhibitory Circuits

PubMed Central

Hiratani, Naoki; Fukai, Tomoki

2015-01-01

The brain can learn and detect mixed input signals masked by various types of noise, and spike-timing-dependent plasticity (STDP) is the candidate synaptic level mechanism. Because sensory inputs typically have spike correlation, and local circuits have dense feedback connections, input spikes cause the propagation of spike correlation in lateral circuits; however, it is largely unknown how this secondary correlation generated by lateral circuits influences learning processes through STDP, or whether it is beneficial to achieve efficient spike-based learning from uncertain stimuli. To explore the answers to these questions, we construct models of feedforward networks with lateral inhibitory circuits and study how propagated correlation influences STDP learning, and what kind of learning algorithm such circuits achieve. We derive analytical conditions at which neurons detect minor signals with STDP, and show that depending on the origin of the noise, different correlation timescales are useful for learning. In particular, we show that non-precise spike correlation is beneficial for learning in the presence of cross-talk noise. We also show that by considering excitatory and inhibitory STDP at lateral connections, the circuit can acquire a lateral structure optimal for signal detection. In addition, we demonstrate that the model performs blind source separation in a manner similar to the sequential sampling approximation of the Bayesian independent component analysis algorithm. Our results provide a basic understanding of STDP learning in feedback circuits by integrating analyses from both dynamical systems and information theory. PMID:25910189

Learning through ferroelectric domain dynamics in solid-state synapses

NASA Astrophysics Data System (ADS)

Boyn, Sören; Grollier, Julie; Lecerf, Gwendal; Xu, Bin; Locatelli, Nicolas; Fusil, Stéphane; Girod, Stéphanie; Carrétéro, Cécile; Garcia, Karin; Xavier, Stéphane; Tomas, Jean; Bellaiche, Laurent; Bibes, Manuel; Barthélémy, Agnès; Saïghi, Sylvain; Garcia, Vincent

2017-04-01

In the brain, learning is achieved through the ability of synapses to reconfigure the strength by which they connect neurons (synaptic plasticity). In promising solid-state synapses called memristors, conductance can be finely tuned by voltage pulses and set to evolve according to a biological learning rule called spike-timing-dependent plasticity (STDP). Future neuromorphic architectures will comprise billions of such nanosynapses, which require a clear understanding of the physical mechanisms responsible for plasticity. Here we report on synapses based on ferroelectric tunnel junctions and show that STDP can be harnessed from inhomogeneous polarization switching. Through combined scanning probe imaging, electrical transport and atomic-scale molecular dynamics, we demonstrate that conductance variations can be modelled by the nucleation-dominated reversal of domains. Based on this physical model, our simulations show that arrays of ferroelectric nanosynapses can autonomously learn to recognize patterns in a predictable way, opening the path towards unsupervised learning in spiking neural networks.

STDP allows fast rate-modulated coding with Poisson-like spike trains.

PubMed

Gilson, Matthieu; Masquelier, Timothée; Hugues, Etienne

2011-10-01

Spike timing-dependent plasticity (STDP) has been shown to enable single neurons to detect repeatedly presented spatiotemporal spike patterns. This holds even when such patterns are embedded in equally dense random spiking activity, that is, in the absence of external reference times such as a stimulus onset. Here we demonstrate, both analytically and numerically, that STDP can also learn repeating rate-modulated patterns, which have received more experimental evidence, for example, through post-stimulus time histograms (PSTHs). Each input spike train is generated from a rate function using a stochastic sampling mechanism, chosen to be an inhomogeneous Poisson process here. Learning is feasible provided significant covarying rate modulations occur within the typical timescale of STDP (~10-20 ms) for sufficiently many inputs (~100 among 1000 in our simulations), a condition that is met by many experimental PSTHs. Repeated pattern presentations induce spike-time correlations that are captured by STDP. Despite imprecise input spike times and even variable spike counts, a single trained neuron robustly detects the pattern just a few milliseconds after its presentation. Therefore, temporal imprecision and Poisson-like firing variability are not an obstacle to fast temporal coding. STDP provides an appealing mechanism to learn such rate patterns, which, beyond sensory processing, may also be involved in many cognitive tasks.

STDP Allows Fast Rate-Modulated Coding with Poisson-Like Spike Trains

PubMed Central

Hugues, Etienne

2011-01-01

Spike timing-dependent plasticity (STDP) has been shown to enable single neurons to detect repeatedly presented spatiotemporal spike patterns. This holds even when such patterns are embedded in equally dense random spiking activity, that is, in the absence of external reference times such as a stimulus onset. Here we demonstrate, both analytically and numerically, that STDP can also learn repeating rate-modulated patterns, which have received more experimental evidence, for example, through post-stimulus time histograms (PSTHs). Each input spike train is generated from a rate function using a stochastic sampling mechanism, chosen to be an inhomogeneous Poisson process here. Learning is feasible provided significant covarying rate modulations occur within the typical timescale of STDP (∼10–20 ms) for sufficiently many inputs (∼100 among 1000 in our simulations), a condition that is met by many experimental PSTHs. Repeated pattern presentations induce spike-time correlations that are captured by STDP. Despite imprecise input spike times and even variable spike counts, a single trained neuron robustly detects the pattern just a few milliseconds after its presentation. Therefore, temporal imprecision and Poisson-like firing variability are not an obstacle to fast temporal coding. STDP provides an appealing mechanism to learn such rate patterns, which, beyond sensory processing, may also be involved in many cognitive tasks. PMID:22046113

Distributed Cerebellar Motor Learning: A Spike-Timing-Dependent Plasticity Model

PubMed Central

Luque, Niceto R.; Garrido, Jesús A.; Naveros, Francisco; Carrillo, Richard R.; D'Angelo, Egidio; Ros, Eduardo

2016-01-01

Deep cerebellar nuclei neurons receive both inhibitory (GABAergic) synaptic currents from Purkinje cells (within the cerebellar cortex) and excitatory (glutamatergic) synaptic currents from mossy fibers. Those two deep cerebellar nucleus inputs are thought to be also adaptive, embedding interesting properties in the framework of accurate movements. We show that distributed spike-timing-dependent plasticity mechanisms (STDP) located at different cerebellar sites (parallel fibers to Purkinje cells, mossy fibers to deep cerebellar nucleus cells, and Purkinje cells to deep cerebellar nucleus cells) in close-loop simulations provide an explanation for the complex learning properties of the cerebellum in motor learning. Concretely, we propose a new mechanistic cerebellar spiking model. In this new model, deep cerebellar nuclei embed a dual functionality: deep cerebellar nuclei acting as a gain adaptation mechanism and as a facilitator for the slow memory consolidation at mossy fibers to deep cerebellar nucleus synapses. Equipping the cerebellum with excitatory (e-STDP) and inhibitory (i-STDP) mechanisms at deep cerebellar nuclei afferents allows the accommodation of synaptic memories that were formed at parallel fibers to Purkinje cells synapses and then transferred to mossy fibers to deep cerebellar nucleus synapses. These adaptive mechanisms also contribute to modulate the deep-cerebellar-nucleus-output firing rate (output gain modulation toward optimizing its working range). PMID:26973504

Neuromodulated Synaptic Plasticity on the SpiNNaker Neuromorphic System

PubMed Central

Mikaitis, Mantas; Pineda García, Garibaldi; Knight, James C.; Furber, Steve B.

2018-01-01

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. PMID:29535600

A framework for plasticity implementation on the SpiNNaker neural architecture.

PubMed

Galluppi, Francesco; Lagorce, Xavier; Stromatias, Evangelos; Pfeiffer, Michael; Plana, Luis A; Furber, Steve B; Benosman, Ryad B

2014-01-01

Many of the precise biological mechanisms of synaptic plasticity remain elusive, but simulations of neural networks have greatly enhanced our understanding of how specific global functions arise from the massively parallel computation of neurons and local Hebbian or spike-timing dependent plasticity rules. For simulating large portions of neural tissue, this has created an increasingly strong need for large scale simulations of plastic neural networks on special purpose hardware platforms, because synaptic transmissions and updates are badly matched to computing style supported by current architectures. Because of the great diversity of biological plasticity phenomena and the corresponding diversity of models, there is a great need for testing various hypotheses about plasticity before committing to one hardware implementation. Here we present a novel framework for investigating different plasticity approaches on the SpiNNaker distributed digital neural simulation platform. The key innovation of the proposed architecture is to exploit the reconfigurability of the ARM processors inside SpiNNaker, dedicating a subset of them exclusively to process synaptic plasticity updates, while the rest perform the usual neural and synaptic simulations. We demonstrate the flexibility of the proposed approach by showing the implementation of a variety of spike- and rate-based learning rules, including standard Spike-Timing dependent plasticity (STDP), voltage-dependent STDP, and the rate-based BCM rule. We analyze their performance and validate them by running classical learning experiments in real time on a 4-chip SpiNNaker board. The result is an efficient, modular, flexible and scalable framework, which provides a valuable tool for the fast and easy exploration of learning models of very different kinds on the parallel and reconfigurable SpiNNaker system.

A framework for plasticity implementation on the SpiNNaker neural architecture

PubMed Central

Galluppi, Francesco; Lagorce, Xavier; Stromatias, Evangelos; Pfeiffer, Michael; Plana, Luis A.; Furber, Steve B.; Benosman, Ryad B.

2015-01-01

Many of the precise biological mechanisms of synaptic plasticity remain elusive, but simulations of neural networks have greatly enhanced our understanding of how specific global functions arise from the massively parallel computation of neurons and local Hebbian or spike-timing dependent plasticity rules. For simulating large portions of neural tissue, this has created an increasingly strong need for large scale simulations of plastic neural networks on special purpose hardware platforms, because synaptic transmissions and updates are badly matched to computing style supported by current architectures. Because of the great diversity of biological plasticity phenomena and the corresponding diversity of models, there is a great need for testing various hypotheses about plasticity before committing to one hardware implementation. Here we present a novel framework for investigating different plasticity approaches on the SpiNNaker distributed digital neural simulation platform. The key innovation of the proposed architecture is to exploit the reconfigurability of the ARM processors inside SpiNNaker, dedicating a subset of them exclusively to process synaptic plasticity updates, while the rest perform the usual neural and synaptic simulations. We demonstrate the flexibility of the proposed approach by showing the implementation of a variety of spike- and rate-based learning rules, including standard Spike-Timing dependent plasticity (STDP), voltage-dependent STDP, and the rate-based BCM rule. We analyze their performance and validate them by running classical learning experiments in real time on a 4-chip SpiNNaker board. The result is an efficient, modular, flexible and scalable framework, which provides a valuable tool for the fast and easy exploration of learning models of very different kinds on the parallel and reconfigurable SpiNNaker system. PMID:25653580

Different propagation speeds of recalled sequences in plastic spiking neural networks

NASA Astrophysics Data System (ADS)

Huang, Xuhui; Zheng, Zhigang; Hu, Gang; Wu, Si; Rasch, Malte J.

2015-03-01

Neural networks can generate spatiotemporal patterns of spike activity. Sequential activity learning and retrieval have been observed in many brain areas, and e.g. is crucial for coding of episodic memory in the hippocampus or generating temporal patterns during song production in birds. In a recent study, a sequential activity pattern was directly entrained onto the neural activity of the primary visual cortex (V1) of rats and subsequently successfully recalled by a local and transient trigger. It was observed that the speed of activity propagation in coordinates of the retinotopically organized neural tissue was constant during retrieval regardless how the speed of light stimulation sweeping across the visual field during training was varied. It is well known that spike-timing dependent plasticity (STDP) is a potential mechanism for embedding temporal sequences into neural network activity. How training and retrieval speeds relate to each other and how network and learning parameters influence retrieval speeds, however, is not well described. We here theoretically analyze sequential activity learning and retrieval in a recurrent neural network with realistic synaptic short-term dynamics and STDP. Testing multiple STDP rules, we confirm that sequence learning can be achieved by STDP. However, we found that a multiplicative nearest-neighbor (NN) weight update rule generated weight distributions and recall activities that best matched the experiments in V1. Using network simulations and mean-field analysis, we further investigated the learning mechanisms and the influence of network parameters on recall speeds. Our analysis suggests that a multiplicative STDP rule with dominant NN spike interaction might be implemented in V1 since recall speed was almost constant in an NMDA-dominant regime. Interestingly, in an AMPA-dominant regime, neural circuits might exhibit recall speeds that instead follow the change in stimulus speeds. This prediction could be tested in experiments.

Learning through ferroelectric domain dynamics in solid-state synapses

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boyn, Soren; Grollier, Julie; Lecerf, Gwendal

In the brain, learning is achieved through the ability of synapses to reconfigure the strength by which they connect neurons (synaptic plasticity). In promising solid-state synapses called memristors, conductance can be finely tuned by voltage pulses and set to evolve according to a biological learning rule called spike-timing-dependent plasticity (STDP). Future neuromorphic architectures will comprise billions of such nanosynapses, which require a clear understanding of the physical mechanisms responsible for plasticity. Here we report on synapses based on ferroelectric tunnel junctions and show that STDP can be harnessed from inhomogeneous polarization switching. Through combined scanning probe imaging, electrical transport andmore » atomic-scale molecular dynamics, we demonstrate that conductance variations can be modelled by the nucleation-dominated reversal of domains. Finally, based on this physical model, our simulations show that arrays of ferroelectric nanosynapses can autonomously learn to recognize patterns in a predictable way, opening the path towards unsupervised learning in spiking neural networks.« less

Learning through ferroelectric domain dynamics in solid-state synapses

DOE PAGES

Boyn, Soren; Grollier, Julie; Lecerf, Gwendal; ...

2017-04-03

In the brain, learning is achieved through the ability of synapses to reconfigure the strength by which they connect neurons (synaptic plasticity). In promising solid-state synapses called memristors, conductance can be finely tuned by voltage pulses and set to evolve according to a biological learning rule called spike-timing-dependent plasticity (STDP). Future neuromorphic architectures will comprise billions of such nanosynapses, which require a clear understanding of the physical mechanisms responsible for plasticity. Here we report on synapses based on ferroelectric tunnel junctions and show that STDP can be harnessed from inhomogeneous polarization switching. Through combined scanning probe imaging, electrical transport andmore » atomic-scale molecular dynamics, we demonstrate that conductance variations can be modelled by the nucleation-dominated reversal of domains. Finally, based on this physical model, our simulations show that arrays of ferroelectric nanosynapses can autonomously learn to recognize patterns in a predictable way, opening the path towards unsupervised learning in spiking neural networks.« less

Triphasic spike-timing-dependent plasticity organizes networks to produce robust sequences of neural activity

PubMed Central

Waddington, Amelia; Appleby, Peter A.; De Kamps, Marc; Cohen, Netta

2012-01-01

Synfire chains have long been proposed to generate precisely timed sequences of neural activity. Such activity has been linked to numerous neural functions including sensory encoding, cognitive and motor responses. In particular, it has been argued that synfire chains underlie the precise spatiotemporal firing patterns that control song production in a variety of songbirds. Previous studies have suggested that the development of synfire chains requires either initial sparse connectivity or strong topological constraints, in addition to any synaptic learning rules. Here, we show that this necessity can be removed by using a previously reported but hitherto unconsidered spike-timing-dependent plasticity (STDP) rule and activity-dependent excitability. Under this rule the network develops stable synfire chains that possess a non-trivial, scalable multi-layer structure, in which relative layer sizes appear to follow a universal function. Using computational modeling and a coarse grained random walk model, we demonstrate the role of the STDP rule in growing, molding and stabilizing the chain, and link model parameters to the resulting structure. PMID:23162457

Long-Term Memory Stabilized by Noise-Induced Rehearsal

PubMed Central

Wei, Yi

2014-01-01

Cortical networks can maintain memories for decades despite the short lifetime of synaptic strengths. Can a neural network store long-lasting memories in unstable synapses? Here, we study the effects of ongoing spike-timing-dependent plasticity (STDP) on the stability of memory patterns stored in synapses of an attractor neural network. We show that certain classes of STDP rules can stabilize all stored memory patterns despite a short lifetime of synapses. In our model, unstructured neural noise, after passing through the recurrent network connections, carries the imprint of all memory patterns in temporal correlations. STDP, combined with these correlations, leads to reinforcement of all stored patterns, even those that are never explicitly visited. Our findings may provide the functional reason for irregular spiking displayed by cortical neurons and justify models of system memory consolidation. Therefore, we propose that irregular neural activity is the feature that helps cortical networks maintain stable connections. PMID:25411507

Oscillation, Conduction Delays, and Learning Cooperate to Establish Neural Competition in Recurrent Networks

PubMed Central

Kato, Hideyuki; Ikeguchi, Tohru

2016-01-01

Specific memory might be stored in a subnetwork consisting of a small population of neurons. To select neurons involved in memory formation, neural competition might be essential. In this paper, we show that excitable neurons are competitive and organize into two assemblies in a recurrent network with spike timing-dependent synaptic plasticity (STDP) and axonal conduction delays. Neural competition is established by the cooperation of spontaneously induced neural oscillation, axonal conduction delays, and STDP. We also suggest that the competition mechanism in this paper is one of the basic functions required to organize memory-storing subnetworks into fine-scale cortical networks. PMID:26840529

Ultrafast Synaptic Events in a Chalcogenide Memristor

NASA Astrophysics Data System (ADS)

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.

Ultrafast synaptic events in a chalcogenide memristor.

PubMed

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

2013-01-01

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 10(5) 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.

Long-term memory stabilized by noise-induced rehearsal.

PubMed

Wei, Yi; Koulakov, Alexei A

2014-11-19

Cortical networks can maintain memories for decades despite the short lifetime of synaptic strengths. Can a neural network store long-lasting memories in unstable synapses? Here, we study the effects of ongoing spike-timing-dependent plasticity (STDP) on the stability of memory patterns stored in synapses of an attractor neural network. We show that certain classes of STDP rules can stabilize all stored memory patterns despite a short lifetime of synapses. In our model, unstructured neural noise, after passing through the recurrent network connections, carries the imprint of all memory patterns in temporal correlations. STDP, combined with these correlations, leads to reinforcement of all stored patterns, even those that are never explicitly visited. Our findings may provide the functional reason for irregular spiking displayed by cortical neurons and justify models of system memory consolidation. Therefore, we propose that irregular neural activity is the feature that helps cortical networks maintain stable connections. Copyright © 2014 the authors 0270-6474/14/3415804-12$15.00/0.

Spike Pattern Structure Influences Synaptic Efficacy Variability under STDP and Synaptic Homeostasis. II: Spike Shuffling Methods on LIF Networks

PubMed Central

Bi, Zedong; Zhou, Changsong

2016-01-01

Synapses may undergo variable changes during plasticity because of the variability of spike patterns such as temporal stochasticity and spatial randomness. Here, we call the variability of synaptic weight changes during plasticity to be efficacy variability. In this paper, we investigate how four aspects of spike pattern statistics (i.e., synchronous firing, burstiness/regularity, heterogeneity of rates and heterogeneity of cross-correlations) influence the efficacy variability under pair-wise additive spike-timing dependent plasticity (STDP) and synaptic homeostasis (the mean strength of plastic synapses into a neuron is bounded), by implementing spike shuffling methods onto spike patterns self-organized by a network of excitatory and inhibitory leaky integrate-and-fire (LIF) neurons. With the increase of the decay time scale of the inhibitory synaptic currents, the LIF network undergoes a transition from asynchronous state to weak synchronous state and then to synchronous bursting state. We first shuffle these spike patterns using a variety of methods, each designed to evidently change a specific pattern statistics; and then investigate the change of efficacy variability of the synapses under STDP and synaptic homeostasis, when the neurons in the network fire according to the spike patterns before and after being treated by a shuffling method. In this way, we can understand how the change of pattern statistics may cause the change of efficacy variability. Our results are consistent with those of our previous study which implements spike-generating models on converging motifs. We also find that burstiness/regularity is important to determine the efficacy variability under asynchronous states, while heterogeneity of cross-correlations is the main factor to cause efficacy variability when the network moves into synchronous bursting states (the states observed in epilepsy). PMID:27555816

On the applicability of STDP-based learning mechanisms to spiking neuron network models

NASA Astrophysics Data System (ADS)

Sboev, A.; Vlasov, D.; Serenko, A.; Rybka, R.; Moloshnikov, I.

2016-11-01

The ways to creating practically effective method for spiking neuron networks learning, that would be appropriate for implementing in neuromorphic hardware and at the same time based on the biologically plausible plasticity rules, namely, on STDP, are discussed. The influence of the amount of correlation between input and output spike trains on the learnability by different STDP rules is evaluated. A usability of alternative combined learning schemes, involving artificial and spiking neuron models is demonstrated on the iris benchmark task and on the practical task of gender recognition.

Emergent gamma synchrony in all-to-all interneuronal networks.

PubMed

Ratnadurai-Giridharan, Shivakeshavan; Khargonekar, Pramod P; Talathi, Sachin S

2015-01-01

We investigate the emergence of in-phase synchronization in a heterogeneous network of coupled inhibitory interneurons in the presence of spike timing dependent plasticity (STDP). Using a simple network of two mutually coupled interneurons (2-MCI), we first study the effects of STDP on in-phase synchronization. We demonstrate that, with STDP, the 2-MCI network can evolve to either a state of stable 1:1 in-phase synchronization or exhibit multiple regimes of higher order synchronization states. We show that the emergence of synchronization induces a structural asymmetry in the 2-MCI network such that the synapses onto the high frequency firing neurons are potentiated, while those onto the low frequency firing neurons are de-potentiated, resulting in the directed flow of information from low frequency firing neurons to high frequency firing neurons. Finally, we demonstrate that the principal findings from our analysis of the 2-MCI network contribute to the emergence of robust synchronization in the Wang-Buzsaki network (Wang and Buzsáki, 1996) of all-to-all coupled inhibitory interneurons (100-MCI) for a significantly larger range of heterogeneity in the intrinsic firing rate of the neurons in the network. We conclude that STDP of inhibitory synapses provide a viable mechanism for robust neural synchronization.

Emergent gamma synchrony in all-to-all interneuronal networks

PubMed Central

Ratnadurai-Giridharan, Shivakeshavan; Khargonekar, Pramod P.; Talathi, Sachin S.

2015-01-01

We investigate the emergence of in-phase synchronization in a heterogeneous network of coupled inhibitory interneurons in the presence of spike timing dependent plasticity (STDP). Using a simple network of two mutually coupled interneurons (2-MCI), we first study the effects of STDP on in-phase synchronization. We demonstrate that, with STDP, the 2-MCI network can evolve to either a state of stable 1:1 in-phase synchronization or exhibit multiple regimes of higher order synchronization states. We show that the emergence of synchronization induces a structural asymmetry in the 2-MCI network such that the synapses onto the high frequency firing neurons are potentiated, while those onto the low frequency firing neurons are de-potentiated, resulting in the directed flow of information from low frequency firing neurons to high frequency firing neurons. Finally, we demonstrate that the principal findings from our analysis of the 2-MCI network contribute to the emergence of robust synchronization in the Wang-Buzsaki network (Wang and Buzsáki, 1996) of all-to-all coupled inhibitory interneurons (100-MCI) for a significantly larger range of heterogeneity in the intrinsic firing rate of the neurons in the network. We conclude that STDP of inhibitory synapses provide a viable mechanism for robust neural synchronization. PMID:26528174

A model of human motor sequence learning explains facilitation and interference effects based on spike-timing dependent plasticity.

PubMed

Wang, Quan; Rothkopf, Constantin A; Triesch, Jochen

2017-08-01

The ability to learn sequential behaviors is a fundamental property of our brains. Yet a long stream of studies including recent experiments investigating motor sequence learning in adult human subjects have produced a number of puzzling and seemingly contradictory results. In particular, when subjects have to learn multiple action sequences, learning is sometimes impaired by proactive and retroactive interference effects. In other situations, however, learning is accelerated as reflected in facilitation and transfer effects. At present it is unclear what the underlying neural mechanism are that give rise to these diverse findings. Here we show that a recently developed recurrent neural network model readily reproduces this diverse set of findings. The self-organizing recurrent neural network (SORN) model is a network of recurrently connected threshold units that combines a simplified form of spike-timing dependent plasticity (STDP) with homeostatic plasticity mechanisms ensuring network stability, namely intrinsic plasticity (IP) and synaptic normalization (SN). When trained on sequence learning tasks modeled after recent experiments we find that it reproduces the full range of interference, facilitation, and transfer effects. We show how these effects are rooted in the network's changing internal representation of the different sequences across learning and how they depend on an interaction of training schedule and task similarity. Furthermore, since learning in the model is based on fundamental neuronal plasticity mechanisms, the model reveals how these plasticity mechanisms are ultimately responsible for the network's sequence learning abilities. In particular, we find that all three plasticity mechanisms are essential for the network to learn effective internal models of the different training sequences. This ability to form effective internal models is also the basis for the observed interference and facilitation effects. This suggests that STDP, IP, and SN may be the driving forces behind our ability to learn complex action sequences.

Precise Synaptic Efficacy Alignment Suggests Potentiation Dominated Learning.

PubMed

Hartmann, Christoph; Miner, Daniel C; Triesch, Jochen

2015-01-01

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 after sleep compared to after sleep deprivation. In conclusion, we show that synaptic normalization in conjunction with coordinated potentiation--in this case, from STDP in the presence of correlated pre- and post-synaptic activity--naturally leads to an alignment of parallel synapses.

A forecast-based STDP rule suitable for neuromorphic implementation.

PubMed

Davies, S; Galluppi, F; Rast, A D; Furber, S B

2012-08-01

Artificial neural networks increasingly involve spiking dynamics to permit greater computational efficiency. This becomes especially attractive for on-chip implementation using dedicated neuromorphic hardware. However, both spiking neural networks and neuromorphic hardware have historically found difficulties in implementing efficient, effective learning rules. The best-known spiking neural network learning paradigm is Spike Timing Dependent Plasticity (STDP) which adjusts the strength of a connection in response to the time difference between the pre- and post-synaptic spikes. Approaches that relate learning features to the membrane potential of the post-synaptic neuron have emerged as possible alternatives to the more common STDP rule, with various implementations and approximations. Here we use a new type of neuromorphic hardware, SpiNNaker, which represents the flexible "neuromimetic" architecture, to demonstrate a new approach to this problem. Based on the standard STDP algorithm with modifications and approximations, a new rule, called STDP TTS (Time-To-Spike) relates the membrane potential with the Long Term Potentiation (LTP) part of the basic STDP rule. Meanwhile, we use the standard STDP rule for the Long Term Depression (LTD) part of the algorithm. We show that on the basis of the membrane potential it is possible to make a statistical prediction of the time needed by the neuron to reach the threshold, and therefore the LTP part of the STDP algorithm can be triggered when the neuron receives a spike. In our system these approximations allow efficient memory access, reducing the overall computational time and the memory bandwidth required. The improvements here presented are significant for real-time applications such as the ones for which the SpiNNaker system has been designed. We present simulation results that show the efficacy of this algorithm using one or more input patterns repeated over the whole time of the simulation. On-chip results show that the STDP TTS algorithm allows the neural network to adapt and detect the incoming pattern with improvements both in the reliability of, and the time required for, consistent output. Through the approximations we suggest in this paper, we introduce a learning rule that is easy to implement both in event-driven simulators and in dedicated hardware, reducing computational complexity relative to the standard STDP rule. Such a rule offers a promising solution, complementary to standard STDP evaluation algorithms, for real-time learning using spiking neural networks in time-critical applications. Copyright © 2012 Elsevier Ltd. All rights reserved.

Unsupervised Feature Learning With Winner-Takes-All Based STDP

PubMed Central

Ferré, Paul; Mamalet, Franck; Thorpe, Simon J.

2018-01-01

We present a novel strategy for unsupervised feature learning in image applications inspired by the Spike-Timing-Dependent-Plasticity (STDP) biological learning rule. We show equivalence between rank order coding Leaky-Integrate-and-Fire neurons and ReLU artificial neurons when applied to non-temporal data. We apply this to images using rank-order coding, which allows us to perform a full network simulation with a single feed-forward pass using GPU hardware. Next we introduce a binary STDP learning rule compatible with training on batches of images. Two mechanisms to stabilize the training are also presented : a Winner-Takes-All (WTA) framework which selects the most relevant patches to learn from along the spatial dimensions, and a simple feature-wise normalization as homeostatic process. This learning process allows us to train multi-layer architectures of convolutional sparse features. We apply our method to extract features from the MNIST, ETH80, CIFAR-10, and STL-10 datasets and show that these features are relevant for classification. We finally compare these results with several other state of the art unsupervised learning methods. PMID:29674961

A compound memristive synapse model for statistical learning through STDP in spiking neural networks

PubMed Central

Bill, Johannes; Legenstein, Robert

2014-01-01

Memristors have recently emerged as promising circuit elements to mimic the function of biological synapses in neuromorphic computing. The fabrication of reliable nanoscale memristive synapses, that feature continuous conductance changes based on the timing of pre- and postsynaptic spikes, has however turned out to be challenging. In this article, we propose an alternative approach, the compound memristive synapse, that circumvents this problem by the use of memristors with binary memristive states. A compound memristive synapse employs multiple bistable memristors in parallel to jointly form one synapse, thereby providing a spectrum of synaptic efficacies. We investigate the computational implications of synaptic plasticity in the compound synapse by integrating the recently observed phenomenon of stochastic filament formation into an abstract model of stochastic switching. Using this abstract model, we first show how standard pulsing schemes give rise to spike-timing dependent plasticity (STDP) with a stabilizing weight dependence in compound synapses. In a next step, we study unsupervised learning with compound synapses in networks of spiking neurons organized in a winner-take-all architecture. Our theoretical analysis reveals that compound-synapse STDP implements generalized Expectation-Maximization in the spiking network. Specifically, the emergent synapse configuration represents the most salient features of the input distribution in a Mixture-of-Gaussians generative model. Furthermore, the network's spike response to spiking input streams approximates a well-defined Bayesian posterior distribution. We show in computer simulations how such networks learn to represent high-dimensional distributions over images of handwritten digits with high fidelity even in presence of substantial device variations and under severe noise conditions. Therefore, the compound memristive synapse may provide a synaptic design principle for future neuromorphic architectures. PMID:25565943

Enabling an Integrated Rate-temporal Learning Scheme on Memristor

NASA Astrophysics Data System (ADS)

He, Wei; Huang, Kejie; Ning, Ning; Ramanathan, Kiruthika; Li, Guoqi; Jiang, Yu; Sze, Jiayin; Shi, Luping; Zhao, Rong; Pei, Jing

2014-04-01

Learning scheme is the key to the utilization of spike-based computation and the emulation of neural/synaptic behaviors toward realization of cognition. The biological observations reveal an integrated spike time- and spike rate-dependent plasticity as a function of presynaptic firing frequency. However, this integrated rate-temporal learning scheme has not been realized on any nano devices. In this paper, such scheme is successfully demonstrated on a memristor. Great robustness against the spiking rate fluctuation is achieved by waveform engineering with the aid of good analog properties exhibited by the iron oxide-based memristor. The spike-time-dependence plasticity (STDP) occurs at moderate presynaptic firing frequencies and spike-rate-dependence plasticity (SRDP) dominates other regions. This demonstration provides a novel approach in neural coding implementation, which facilitates the development of bio-inspired computing systems.

Using the virtual brain to reveal the role of oscillations and plasticity in shaping brain's dynamical landscape.

PubMed

Roy, Dipanjan; Sigala, Rodrigo; Breakspear, Michael; McIntosh, Anthony Randal; Jirsa, Viktor K; Deco, Gustavo; Ritter, Petra

2014-12-01

Spontaneous brain activity, that is, activity in the absence of controlled stimulus input or an explicit active task, is topologically organized in multiple functional networks (FNs) maintaining a high degree of coherence. These "resting state networks" are constrained by the underlying anatomical connectivity between brain areas. They are also influenced by the history of task-related activation. The precise rules that link plastic changes and ongoing dynamics of resting-state functional connectivity (rs-FC) remain unclear. Using the framework of the open source neuroinformatics platform "The Virtual Brain," we identify potential computational mechanisms that alter the dynamical landscape, leading to reconfigurations of FNs. Using a spiking neuron model, we first demonstrate that network activity in the absence of plasticity is characterized by irregular oscillations between low-amplitude asynchronous states and high-amplitude synchronous states. We then demonstrate the capability of spike-timing-dependent plasticity (STDP) combined with intrinsic alpha (8-12 Hz) oscillations to efficiently influence learning. Further, we show how alpha-state-dependent STDP alters the local area dynamics from an irregular to a highly periodic alpha-like state. This is an important finding, as the cortical input from the thalamus is at the rate of alpha. We demonstrate how resulting rhythmic cortical output in this frequency range acts as a neuronal tuner and, hence, leads to synchronization or de-synchronization between brain areas. Finally, we demonstrate that locally restricted structural connectivity changes influence local as well as global dynamics and lead to altered rs-FC.

Bimodal stimulus timing-dependent plasticity in primary auditory cortex is altered after noise exposure with and without tinnitus

PubMed Central

Koehler, Seth D.; Shore, Susan E.

2015-01-01

Central auditory circuits are influenced by the somatosensory system, a relationship that may underlie tinnitus generation. In the guinea pig dorsal cochlear nucleus (DCN), pairing spinal trigeminal nucleus (Sp5) stimulation with tones at specific intervals and orders facilitated or suppressed subsequent tone-evoked neural responses, reflecting spike timing-dependent plasticity (STDP). Furthermore, after noise-induced tinnitus, bimodal responses in DCN were shifted from Hebbian to anti-Hebbian timing rules with less discrete temporal windows, suggesting a role for bimodal plasticity in tinnitus. Here, we aimed to determine if multisensory STDP principles like those in DCN also exist in primary auditory cortex (A1), and whether they change following noise-induced tinnitus. Tone-evoked and spontaneous neural responses were recorded before and 15 min after bimodal stimulation in which the intervals and orders of auditory-somatosensory stimuli were randomized. Tone-evoked and spontaneous firing rates were influenced by the interval and order of the bimodal stimuli, and in sham-controls Hebbian-like timing rules predominated as was seen in DCN. In noise-exposed animals with and without tinnitus, timing rules shifted away from those found in sham-controls to more anti-Hebbian rules. Only those animals with evidence of tinnitus showed increased spontaneous firing rates, a purported neurophysiological correlate of tinnitus in A1. Together, these findings suggest that bimodal plasticity is also evident in A1 following noise damage and may have implications for tinnitus generation and therapeutic intervention across the central auditory circuit. PMID:26289461

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

PubMed Central

Bi, Zedong; Zhou, Changsong

2016-01-01

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 work important for understanding functional processes of neuronal networks (such as memory) and neural development. PMID:26941634

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

PubMed Central

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. PMID:25566045

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

PubMed

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.

STDP-based spiking deep convolutional neural networks for object recognition.

PubMed

Kheradpisheh, Saeed Reza; Ganjtabesh, Mohammad; Thorpe, Simon J; Masquelier, Timothée

2018-03-01

Previous studies have shown that spike-timing-dependent plasticity (STDP) can be used in spiking neural networks (SNN) to extract visual features of low or intermediate complexity in an unsupervised manner. These studies, however, used relatively shallow architectures, and only one layer was trainable. Another line of research has demonstrated - using rate-based neural networks trained with back-propagation - that having many layers increases the recognition robustness, an approach known as deep learning. We thus designed a deep SNN, comprising several convolutional (trainable with STDP) and pooling layers. We used a temporal coding scheme where the most strongly activated neurons fire first, and less activated neurons fire later or not at all. The network was exposed to natural images. Thanks to STDP, neurons progressively learned features corresponding to prototypical patterns that were both salient and frequent. Only a few tens of examples per category were required and no label was needed. After learning, the complexity of the extracted features increased along the hierarchy, from edge detectors in the first layer to object prototypes in the last layer. Coding was very sparse, with only a few thousands spikes per image, and in some cases the object category could be reasonably well inferred from the activity of a single higher-order neuron. More generally, the activity of a few hundreds of such neurons contained robust category information, as demonstrated using a classifier on Caltech 101, ETH-80, and MNIST databases. We also demonstrate the superiority of STDP over other unsupervised techniques such as random crops (HMAX) or auto-encoders. Taken together, our results suggest that the combination of STDP with latency coding may be a key to understanding the way that the primate visual system learns, its remarkable processing speed and its low energy consumption. These mechanisms are also interesting for artificial vision systems, particularly for hardware solutions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Self-organization in Balanced State Networks by STDP and Homeostatic Plasticity

PubMed Central

Effenberger, Felix; Jost, Jürgen; Levina, Anna

2015-01-01

Structural inhomogeneities in synaptic efficacies have a strong impact on population response dynamics of cortical networks and are believed to play an important role in their functioning. However, little is known about how such inhomogeneities could evolve by means of synaptic plasticity. Here we present an adaptive model of a balanced neuronal network that combines two different types of plasticity, STDP and synaptic scaling. The plasticity rules yield both long-tailed distributions of synaptic weights and firing rates. Simultaneously, a highly connected subnetwork of driver neurons with strong synapses emerges. Coincident spiking activity of several driver cells can evoke population bursts and driver cells have similar dynamical properties as leader neurons found experimentally. Our model allows us to observe the delicate interplay between structural and dynamical properties of the emergent inhomogeneities. It is simple, robust to parameter changes and able to explain a multitude of different experimental findings in one basic network. PMID:26335425

A Neuromorphic Architecture for Object Recognition and Motion Anticipation Using Burst-STDP

PubMed Central

Balduzzi, David; Tononi, Giulio

2012-01-01

In this work we investigate the possibilities offered by a minimal framework of artificial spiking neurons to be deployed in silico. Here we introduce a hierarchical network architecture of spiking neurons which learns to recognize moving objects in a visual environment and determine the correct motor output for each object. These tasks are learned through both supervised and unsupervised spike timing dependent plasticity (STDP). STDP is responsible for the strengthening (or weakening) of synapses in relation to pre- and post-synaptic spike times and has been described as a Hebbian paradigm taking place both in vitro and in vivo. We utilize a variation of STDP learning, called burst-STDP, which is based on the notion that, since spikes are expensive in terms of energy consumption, then strong bursting activity carries more information than single (sparse) spikes. Furthermore, this learning algorithm takes advantage of homeostatic renormalization, which has been hypothesized to promote memory consolidation during NREM sleep. Using this learning rule, we design a spiking neural network architecture capable of object recognition, motion detection, attention towards important objects, and motor control outputs. We demonstrate the abilities of our design in a simple environment with distractor objects, multiple objects moving concurrently, and in the presence of noise. Most importantly, we show how this neural network is capable of performing these tasks using a simple leaky-integrate-and-fire (LIF) neuron model with binary synapses, making it fully compatible with state-of-the-art digital neuromorphic hardware designs. As such, the building blocks and learning rules presented in this paper appear promising for scalable fully neuromorphic systems to be implemented in hardware chips. PMID:22615855

Synaptic dynamics regulation in response to high frequency stimulation in neuronal networks

NASA Astrophysics Data System (ADS)

Su, Fei; Wang, Jiang; Li, Huiyan; Wei, Xile; Yu, Haitao; Deng, Bin

2018-02-01

High frequency stimulation (HFS) has confirmed its ability in modulating the pathological neural activities. However its detailed mechanism is unclear. This study aims to explore the effects of HFS on neuronal networks dynamics. First, the two-neuron FitzHugh-Nagumo (FHN) networks with static coupling strength and the small-world FHN networks with spike-time-dependent plasticity (STDP) modulated synaptic coupling strength are constructed. Then, the multi-scale method is used to transform the network models into equivalent averaged models, where the HFS intensity is modeled as the ratio between stimulation amplitude and frequency. Results show that in static two-neuron networks, there is still synaptic current projected to the postsynaptic neuron even if the presynaptic neuron is blocked by the HFS. In the small-world networks, the effects of the STDP adjusting rate parameter on the inactivation ratio and synchrony degree increase with the increase of HFS intensity. However, only when the HFS intensity becomes very large can the STDP time window parameter affect the inactivation ratio and synchrony index. Both simulation and numerical analysis demonstrate that the effects of HFS on neuronal network dynamics are realized through the adjustment of synaptic variable and conductance.

A real-time spiking cerebellum model for learning robot control.

PubMed

Carrillo, Richard R; Ros, Eduardo; Boucheny, Christian; Coenen, Olivier J-M D

2008-01-01

We describe a neural network model of the cerebellum based on integrate-and-fire spiking neurons with conductance-based synapses. The neuron characteristics are derived from our earlier detailed models of the different cerebellar neurons. We tested the cerebellum model in a real-time control application with a robotic platform. Delays were introduced in the different sensorimotor pathways according to the biological system. The main plasticity in the cerebellar model is a spike-timing dependent plasticity (STDP) at the parallel fiber to Purkinje cell connections. This STDP is driven by the inferior olive (IO) activity, which encodes an error signal using a novel probabilistic low frequency model. We demonstrate the cerebellar model in a robot control system using a target-reaching task. We test whether the system learns to reach different target positions in a non-destructive way, therefore abstracting a general dynamics model. To test the system's ability to self-adapt to different dynamical situations, we present results obtained after changing the dynamics of the robotic platform significantly (its friction and load). The experimental results show that the cerebellar-based system is able to adapt dynamically to different contexts.

Learning to Generate Sequences with Combination of Hebbian and Non-hebbian Plasticity in Recurrent Spiking Neural Networks

PubMed Central

Panda, Priyadarshini; Roy, Kaushik

2017-01-01

Synaptic Plasticity, the foundation for learning and memory formation in the human brain, manifests in various forms. Here, we combine the standard spike timing correlation based Hebbian plasticity with a non-Hebbian synaptic decay mechanism for training a recurrent spiking neural model to generate sequences. We show that inclusion of the adaptive decay of synaptic weights with standard STDP helps learn stable contextual dependencies between temporal sequences, while reducing the strong attractor states that emerge in recurrent models due to feedback loops. Furthermore, we show that the combined learning scheme suppresses the chaotic activity in the recurrent model substantially, thereby enhancing its' ability to generate sequences consistently even in the presence of perturbations. PMID:29311774

Limits to high-speed simulations of spiking neural networks using general-purpose computers.

PubMed

Zenke, Friedemann; Gerstner, Wulfram

2014-01-01

To understand how the central nervous system performs computations using recurrent neuronal circuitry, simulations have become an indispensable tool for theoretical neuroscience. To study neuronal circuits and their ability to self-organize, increasing attention has been directed toward synaptic plasticity. In particular spike-timing-dependent plasticity (STDP) creates specific demands for simulations of spiking neural networks. On the one hand a high temporal resolution is required to capture the millisecond timescale of typical STDP windows. On the other hand network simulations have to evolve over hours up to days, to capture the timescale of long-term plasticity. To do this efficiently, fast simulation speed is the crucial ingredient rather than large neuron numbers. Using different medium-sized network models consisting of several thousands of neurons and off-the-shelf hardware, we compare the simulation speed of the simulators: Brian, NEST and Neuron as well as our own simulator Auryn. Our results show that real-time simulations of different plastic network models are possible in parallel simulations in which numerical precision is not a primary concern. Even so, the speed-up margin of parallelism is limited and boosting simulation speeds beyond one tenth of real-time is difficult. By profiling simulation code we show that the run times of typical plastic network simulations encounter a hard boundary. This limit is partly due to latencies in the inter-process communications and thus cannot be overcome by increased parallelism. Overall, these results show that to study plasticity in medium-sized spiking neural networks, adequate simulation tools are readily available which run efficiently on small clusters. However, to run simulations substantially faster than real-time, special hardware is a prerequisite.

The Convallis Rule for Unsupervised Learning in Cortical Networks

PubMed Central

Yger, Pierre; Harris, Kenneth D.

2013-01-01

The phenomenology and cellular mechanisms of cortical synaptic plasticity are becoming known in increasing detail, but the computational principles by which cortical plasticity enables the development of sensory representations are unclear. Here we describe a framework for cortical synaptic plasticity termed the “Convallis rule”, mathematically derived from a principle of unsupervised learning via constrained optimization. Implementation of the rule caused a recurrent cortex-like network of simulated spiking neurons to develop rate representations of real-world speech stimuli, enabling classification by a downstream linear decoder. Applied to spike patterns used in in vitro plasticity experiments, the rule reproduced multiple results including and beyond STDP. However STDP alone produced poorer learning performance. The mathematical form of the rule is consistent with a dual coincidence detector mechanism that has been suggested by experiments in several synaptic classes of juvenile neocortex. Based on this confluence of normative, phenomenological, and mechanistic evidence, we suggest that the rule may approximate a fundamental computational principle of the neocortex. PMID:24204224

Regulation of Local Ambient GABA Levels via Transporter-Mediated GABA Import and Export for Subliminal Learning.

PubMed

Hoshino, Osamu

2015-06-01

Perception of supraliminal stimuli might in general be reflected in bursts of action potentials (spikes), and their memory traces could be formed through spike-timing-dependent plasticity (STDP). Memory traces for subliminal stimuli might be formed in a different manner, because subliminal stimulation evokes a fraction (but not a burst) of spikes. Simulations of a cortical neural network model showed that a subliminal stimulus that was too brief (10 msec) to perceive transiently (more than about 500 msec) depolarized stimulus-relevant principal cells and hyperpolarized stimulus-irrelevant principal cells in a subthreshold manner. This led to a small increase or decrease in ongoing-spontaneous spiking activity frequency (less than 1 Hz). Synaptic modification based on STDP during this period effectively enhanced relevant synaptic weights, by which subliminal learning was improved. GABA transporters on GABAergic interneurons modulated local levels of ambient GABA. Ambient GABA molecules acted on extrasynaptic receptors, provided principal cells with tonic inhibitory currents, and contributed to achieving the subthreshold neuronal state. We suggest that ongoing-spontaneous synaptic alteration through STDP following subliminal stimulation may be a possible neuronal mechanism for leaving its memory trace in cortical circuitry. Regulation of local ambient GABA levels by transporter-mediated GABA import and export may be crucial for subliminal learning.

Synthetic Modeling of Autonomous Learning with a Chaotic Neural Network

NASA Astrophysics Data System (ADS)

Funabashi, Masatoshi

We investigate the possible role of intermittent chaotic dynamics called chaotic itinerancy, in interaction with nonsupervised learnings that reinforce and weaken the neural connection depending on the dynamics itself. We first performed hierarchical stability analysis of the Chaotic Neural Network model (CNN) according to the structure of invariant subspaces. Irregular transition between two attractor ruins with positive maximum Lyapunov exponent was triggered by the blowout bifurcation of the attractor spaces, and was associated with riddled basins structure. We secondly modeled two autonomous learnings, Hebbian learning and spike-timing-dependent plasticity (STDP) rule, and simulated the effect on the chaotic itinerancy state of CNN. Hebbian learning increased the residence time on attractor ruins, and produced novel attractors in the minimum higher-dimensional subspace. It also augmented the neuronal synchrony and established the uniform modularity in chaotic itinerancy. STDP rule reduced the residence time on attractor ruins, and brought a wide range of periodicity in emerged attractors, possibly including strange attractors. Both learning rules selectively destroyed and preserved the specific invariant subspaces, depending on the neuron synchrony of the subspace where the orbits are situated. Computational rationale of the autonomous learning is discussed in connectionist perspective.

The effect of synaptic plasticity on orientation selectivity in a balanced model of primary visual cortex

PubMed Central

Gonzalo Cogno, Soledad; Mato, Germán

2015-01-01

Orientation selectivity is ubiquitous in the primary visual cortex (V1) of mammals. In cats and monkeys, V1 displays spatially ordered maps of orientation preference. Instead, in mice, squirrels, and rats, orientation selective neurons in V1 are not spatially organized, giving rise to a seemingly random pattern usually referred to as a salt-and-pepper layout. The fact that such different organizations can sharpen orientation tuning leads to question the structural role of the intracortical connections; specifically the influence of plasticity and the generation of functional connectivity. In this work, we analyze the effect of plasticity processes on orientation selectivity for both scenarios. We study a computational model of layer 2/3 and a reduced one-dimensional model of orientation selective neurons, both in the balanced state. We analyze two plasticity mechanisms. The first one involves spike-timing dependent plasticity (STDP), while the second one considers the reconnection of the interactions according to the preferred orientations of the neurons. We find that under certain conditions STDP can indeed improve selectivity but it works in a somehow unexpected way, that is, effectively decreasing the modulated part of the intracortical connectivity as compared to the non-modulated part of it. For the reconnection mechanism we find that increasing functional connectivity leads, in fact, to a decrease in orientation selectivity if the network is in a stable balanced state. Both counterintuitive results are a consequence of the dynamics of the balanced state. We also find that selectivity can increase due to a reconnection process if the resulting connections give rise to an unstable balanced state. We compare these findings with recent experimental results. PMID:26347615

Implementation of a spike-based perceptron learning rule using TiO2-x memristors.

PubMed

Mostafa, Hesham; Khiat, Ali; Serb, Alexander; Mayr, Christian G; Indiveri, Giacomo; Prodromakis, Themis

2015-01-01

Synaptic plasticity plays a crucial role in allowing neural networks to learn and adapt to various input environments. Neuromorphic systems need to implement plastic synapses to obtain basic "cognitive" capabilities such as learning. One promising and scalable approach for implementing neuromorphic synapses is to use nano-scale memristors as synaptic elements. In this paper we propose a hybrid CMOS-memristor system comprising CMOS neurons interconnected through TiO2-x memristors, and spike-based learning circuits that modulate the conductance of the memristive synapse elements according to a spike-based Perceptron plasticity rule. We highlight a number of advantages for using this spike-based plasticity rule as compared to other forms of spike timing dependent plasticity (STDP) rules. We provide experimental proof-of-concept results with two silicon neurons connected through a memristive synapse that show how the CMOS plasticity circuits can induce stable changes in memristor conductances, giving rise to increased synaptic strength after a potentiation episode and to decreased strength after a depression episode.

Self-Organization of Microcircuits in Networks of Spiking Neurons with Plastic Synapses.

PubMed

Ocker, Gabriel Koch; Litwin-Kumar, Ashok; Doiron, Brent

2015-08-01

The synaptic connectivity of cortical networks features an overrepresentation of certain wiring motifs compared to simple random-network models. This structure is shaped, in part, by synaptic plasticity that promotes or suppresses connections between neurons depending on their joint spiking activity. Frequently, theoretical studies focus on how feedforward inputs drive plasticity to create this network structure. We study the complementary scenario of self-organized structure in a recurrent network, with spike timing-dependent plasticity driven by spontaneous dynamics. We develop a self-consistent theory for the evolution of network structure by combining fast spiking covariance with a slow evolution of synaptic weights. Through a finite-size expansion of network dynamics we obtain a low-dimensional set of nonlinear differential equations for the evolution of two-synapse connectivity motifs. With this theory in hand, we explore how the form of the plasticity rule drives the evolution of microcircuits in cortical networks. When potentiation and depression are in approximate balance, synaptic dynamics depend on weighted divergent, convergent, and chain motifs. For additive, Hebbian STDP these motif interactions create instabilities in synaptic dynamics that either promote or suppress the initial network structure. Our work provides a consistent theoretical framework for studying how spiking activity in recurrent networks interacts with synaptic plasticity to determine network structure.

Self-Organization of Microcircuits in Networks of Spiking Neurons with Plastic Synapses

PubMed Central

Ocker, Gabriel Koch; Litwin-Kumar, Ashok; Doiron, Brent

2015-01-01

The synaptic connectivity of cortical networks features an overrepresentation of certain wiring motifs compared to simple random-network models. This structure is shaped, in part, by synaptic plasticity that promotes or suppresses connections between neurons depending on their joint spiking activity. Frequently, theoretical studies focus on how feedforward inputs drive plasticity to create this network structure. We study the complementary scenario of self-organized structure in a recurrent network, with spike timing-dependent plasticity driven by spontaneous dynamics. We develop a self-consistent theory for the evolution of network structure by combining fast spiking covariance with a slow evolution of synaptic weights. Through a finite-size expansion of network dynamics we obtain a low-dimensional set of nonlinear differential equations for the evolution of two-synapse connectivity motifs. With this theory in hand, we explore how the form of the plasticity rule drives the evolution of microcircuits in cortical networks. When potentiation and depression are in approximate balance, synaptic dynamics depend on weighted divergent, convergent, and chain motifs. For additive, Hebbian STDP these motif interactions create instabilities in synaptic dynamics that either promote or suppress the initial network structure. Our work provides a consistent theoretical framework for studying how spiking activity in recurrent networks interacts with synaptic plasticity to determine network structure. PMID:26291697

The BDNF Val66Met polymorphism impairs synaptic transmission and plasticity in the infralimbic medial prefrontal cortex

PubMed Central

Pattwell, Siobhan S.; Bath, Kevin G.; Perez-Castro, Rosalia; Lee, Francis S.; Chao, Moses V.; Ninan, Ipe

2012-01-01

The brain-derived neurotrophic factor (BDNF) Val66Met polymorphism is a common human single nucleotide polymorphism (SNP) that affects the regulated release of BDNF, and has been implicated in affective disorders and cognitive dysfunction. A decreased activation of the infralimbic medial prefrontal cortex (IL-mPFC), a brain region critical for the regulation of affective behaviors, has been described in BDNFMet carriers. However, it is unclear whether and how the Val66Met polymorphism affects the IL-mPFC synapses. Here we report that spike timing-dependent plasticity (STDP) was absent in the IL-mPFC pyramidal neurons from BDNFMet/Met mice, a mouse that recapitulates the specific phenotypic properties of the human BDNF Val66Met polymorphism. Also, we observed a decrease in N-methyl-D-aspartic acid (NMDA) and γ-aminobutyric acid (GABA) receptor-mediated synaptic transmission in the pyramidal neurons of BDNFMet/Met mice. While BDNF enhanced non-NMDA receptor transmission and depressed GABA receptor transmission in the wild-type mice, both effects were absent in BDNFMet/Met mice after BDNF treatment. Indeed, exogenous BDNF reversed the deficits in STDP and NMDA receptor transmission in BDNFMet/Met neurons. BDNF-mediated selective reversal of the deficit in plasticity and NMDA receptor transmission, but its lack of effect on GABA and non-NMDA receptor transmission in BDNFMet/Met mice, suggests separate mechanisms of Val66Met polymorphism upon synaptic transmission. The effect of the Val66Met polymorphism on synaptic transmission and plasticity in the IL-mPFC represents a mechanism to account for this SNP's impact on affective disorders and cognitive dysfunction. PMID:22396415

On building a memory evolutive system for application to learning and cognition modeling.

PubMed

de Lima do Rego Monteiro, Julio; Kogler, Joao Eduardo; Ribeiro, Joao Henrique Ranhel; Netto, Marcio Lobo

2010-01-01

We address here aspects of the implementation of a memory evolutive system (MES), based on the model proposed by A. Ehresmann and J. Vanbremeersch (2007), by means of a simulated network of spiking neurons with time dependent plasticity. We point out the advantages and challenges of applying category theory for the representation of cognition, by using the MES architecture. Then we discuss the issues concerning the minimum requirements that an artificial neural network (ANN) should fulfill in order that it would be capable of expressing the categories and mappings between them, underlying the MES. We conclude that a pulsed ANN based on Izhikevich's formal neuron with STDP (spike time-dependent plasticity) has sufficient dynamical properties to achieve these requirements, provided it can cope with the topological requirements. Finally, we present some perspectives of future research concerning the proposed ANN topology.

Unsupervised learning of temporal features for word categorization in a spiking neural network model of the auditory brain.

PubMed

Higgins, Irina; Stringer, Simon; Schnupp, Jan

2017-01-01

The nature of the code used in the auditory cortex to represent complex auditory stimuli, such as naturally spoken words, remains a matter of debate. Here we argue that such representations are encoded by stable spatio-temporal patterns of firing within cell assemblies known as polychronous groups, or PGs. We develop a physiologically grounded, unsupervised spiking neural network model of the auditory brain with local, biologically realistic, spike-time dependent plasticity (STDP) learning, and show that the plastic cortical layers of the network develop PGs which convey substantially more information about the speaker independent identity of two naturally spoken word stimuli than does rate encoding that ignores the precise spike timings. We furthermore demonstrate that such informative PGs can only develop if the input spatio-temporal spike patterns to the plastic cortical areas of the model are relatively stable.

Unsupervised learning of temporal features for word categorization in a spiking neural network model of the auditory brain

PubMed Central

Stringer, Simon

2017-01-01

The nature of the code used in the auditory cortex to represent complex auditory stimuli, such as naturally spoken words, remains a matter of debate. Here we argue that such representations are encoded by stable spatio-temporal patterns of firing within cell assemblies known as polychronous groups, or PGs. We develop a physiologically grounded, unsupervised spiking neural network model of the auditory brain with local, biologically realistic, spike-time dependent plasticity (STDP) learning, and show that the plastic cortical layers of the network develop PGs which convey substantially more information about the speaker independent identity of two naturally spoken word stimuli than does rate encoding that ignores the precise spike timings. We furthermore demonstrate that such informative PGs can only develop if the input spatio-temporal spike patterns to the plastic cortical areas of the model are relatively stable. PMID:28797034

Memristive neural network for on-line learning and tracking with brain-inspired spike timing dependent plasticity.

PubMed

Pedretti, G; Milo, V; Ambrogio, S; Carboni, R; Bianchi, S; Calderoni, A; Ramaswamy, N; Spinelli, A S; Ielmini, D

2017-07-13

Brain-inspired computation can revolutionize information technology by introducing machines capable of recognizing patterns (images, speech, video) and interacting with the external world in a cognitive, humanlike way. Achieving this goal requires first to gain a detailed understanding of the brain operation, and second to identify a scalable microelectronic technology capable of reproducing some of the inherent functions of the human brain, such as the high synaptic connectivity (~10 4 ) and the peculiar time-dependent synaptic plasticity. Here we demonstrate unsupervised learning and tracking in a spiking neural network with memristive synapses, where synaptic weights are updated via brain-inspired spike timing dependent plasticity (STDP). The synaptic conductance is updated by the local time-dependent superposition of pre- and post-synaptic spikes within a hybrid one-transistor/one-resistor (1T1R) memristive synapse. Only 2 synaptic states, namely the low resistance state (LRS) and the high resistance state (HRS), are sufficient to learn and recognize patterns. Unsupervised learning of a static pattern and tracking of a dynamic pattern of up to 4 × 4 pixels are demonstrated, paving the way for intelligent hardware technology with up-scaled memristive neural networks.

Synchronization and Inter-Layer Interactions of Noise-Driven Neural Networks

PubMed Central

Yuniati, Anis; Mai, Te-Lun; Chen, Chi-Ming

2017-01-01

In this study, we used the Hodgkin-Huxley (HH) model of neurons to investigate the phase diagram of a developing single-layer neural network and that of a network consisting of two weakly coupled neural layers. These networks are noise driven and learn through the spike-timing-dependent plasticity (STDP) or the inverse STDP rules. We described how these networks transited from a non-synchronous background activity state (BAS) to a synchronous firing state (SFS) by varying the network connectivity and the learning efficacy. In particular, we studied the interaction between a SFS layer and a BAS layer, and investigated how synchronous firing dynamics was induced in the BAS layer. We further investigated the effect of the inter-layer interaction on a BAS to SFS repair mechanism by considering three types of neuron positioning (random, grid, and lognormal distributions) and two types of inter-layer connections (random and preferential connections). Among these scenarios, we concluded that the repair mechanism has the largest effect for a network with the lognormal neuron positioning and the preferential inter-layer connections. PMID:28197088

Synchronization in a noise-driven developing neural network

NASA Astrophysics Data System (ADS)

Lin, I.-H.; Wu, R.-K.; Chen, C.-M.

2011-11-01

We use computer simulations to investigate the structural and dynamical properties of a developing neural network whose activity is driven by noise. Structurally, the constructed neural networks in our simulations exhibit the small-world properties that have been observed in several neural networks. The dynamical change of neuronal membrane potential is described by the Hodgkin-Huxley model, and two types of learning rules, including spike-timing-dependent plasticity (STDP) and inverse STDP, are considered to restructure the synaptic strength between neurons. Clustered synchronized firing (SF) of the network is observed when the network connectivity (number of connections/maximal connections) is about 0.75, in which the firing rate of neurons is only half of the network frequency. At the connectivity of 0.86, all neurons fire synchronously at the network frequency. The network SF frequency increases logarithmically with the culturing time of a growing network and decreases exponentially with the delay time in signal transmission. These conclusions are consistent with experimental observations. The phase diagrams of SF in a developing network are investigated for both learning rules.

Synchronization and Inter-Layer Interactions of Noise-Driven Neural Networks.

PubMed

Yuniati, Anis; Mai, Te-Lun; Chen, Chi-Ming

2017-01-01

In this study, we used the Hodgkin-Huxley (HH) model of neurons to investigate the phase diagram of a developing single-layer neural network and that of a network consisting of two weakly coupled neural layers. These networks are noise driven and learn through the spike-timing-dependent plasticity (STDP) or the inverse STDP rules. We described how these networks transited from a non-synchronous background activity state (BAS) to a synchronous firing state (SFS) by varying the network connectivity and the learning efficacy. In particular, we studied the interaction between a SFS layer and a BAS layer, and investigated how synchronous firing dynamics was induced in the BAS layer. We further investigated the effect of the inter-layer interaction on a BAS to SFS repair mechanism by considering three types of neuron positioning (random, grid, and lognormal distributions) and two types of inter-layer connections (random and preferential connections). Among these scenarios, we concluded that the repair mechanism has the largest effect for a network with the lognormal neuron positioning and the preferential inter-layer connections.

Energy-efficient STDP-based learning circuits with memristor synapses

NASA Astrophysics Data System (ADS)

Wu, Xinyu; Saxena, Vishal; Campbell, Kristy A.

2014-05-01

It is now accepted that the traditional von Neumann architecture, with processor and memory separation, is ill suited to process parallel data streams which a mammalian brain can efficiently handle. Moreover, researchers now envision computing architectures which enable cognitive processing of massive amounts of data by identifying spatio-temporal relationships in real-time and solving complex pattern recognition problems. Memristor cross-point arrays, integrated with standard CMOS technology, are expected to result in massively parallel and low-power Neuromorphic computing architectures. Recently, significant progress has been made in spiking neural networks (SNN) which emulate data processing in the cortical brain. These architectures comprise of a dense network of neurons and the synapses formed between the axons and dendrites. Further, unsupervised or supervised competitive learning schemes are being investigated for global training of the network. In contrast to a software implementation, hardware realization of these networks requires massive circuit overhead for addressing and individually updating network weights. Instead, we employ bio-inspired learning rules such as the spike-timing-dependent plasticity (STDP) to efficiently update the network weights locally. To realize SNNs on a chip, we propose to use densely integrating mixed-signal integrate-andfire neurons (IFNs) and cross-point arrays of memristors in back-end-of-the-line (BEOL) of CMOS chips. Novel IFN circuits have been designed to drive memristive synapses in parallel while maintaining overall power efficiency (<1 pJ/spike/synapse), even at spike rate greater than 10 MHz. We present circuit design details and simulation results of the IFN with memristor synapses, its response to incoming spike trains and STDP learning characterization.

Synaptic plasticity modulates autonomous transitions between waking and sleep states: Insights from a Morris-Lecar model

NASA Astrophysics Data System (ADS)

Ciszak, Marzena; Bellesi, Michele

2011-12-01

The transitions between waking and sleep states are characterized by considerable changes in neuronal firing. During waking, neurons fire tonically at irregular intervals and a desynchronized activity is observed at the electroencephalogram. This activity becomes synchronized with slow wave sleep onset when neurons start to oscillate between periods of firing (up-states) and periods of silence (down-states). Recently, it has been proposed that the connections between neurons undergo potentiation during waking, whereas they weaken during slow wave sleep. Here, we propose a dynamical model to describe basic features of the autonomous transitions between such states. We consider a network of coupled neurons in which the strength of the interactions is modulated by synaptic long term potentiation and depression, according to the spike time-dependent plasticity rule (STDP). The model shows that the enhancement of synaptic strength between neurons occurring in waking increases the propensity of the network to synchronize and, conversely, desynchronization appears when the strength of the connections become weaker. Both transitions appear spontaneously, but the transition from sleep to waking required a slight modification of the STDP rule with the introduction of a mechanism which becomes active during sleep and changes the proportion between potentiation and depression in accordance with biological data. At the neuron level, transitions from desynchronization to synchronization and vice versa can be described as a bifurcation between two different states, whose dynamical regime is modulated by synaptic strengths, thus suggesting that transition from a state to an another can be determined by quantitative differences between potentiation and depression.

When Long-Range Zero-Lag Synchronization is Feasible in Cortical Networks

PubMed Central

Viriyopase, Atthaphon; Bojak, Ingo; Zeitler, Magteld; Gielen, Stan

2012-01-01

Many studies have reported long-range synchronization of neuronal activity between brain areas, in particular in the beta and gamma bands with frequencies in the range of 14–30 and 40–80 Hz, respectively. Several studies have reported synchrony with zero phase lag, which is remarkable considering the synaptic and conduction delays inherent in the connections between distant brain areas. This result has led to many speculations about the possible functional role of zero-lag synchrony, such as for neuronal communication, attention, memory, and feature binding. However, recent studies using recordings of single-unit activity and local field potentials report that neuronal synchronization may occur with non-zero phase lags. This raises the questions whether zero-lag synchrony can occur in the brain and, if so, under which conditions. We used analytical methods and computer simulations to investigate which connectivity between neuronal populations allows or prohibits zero-lag synchrony. We did so for a model where two oscillators interact via a relay oscillator. Analytical results and computer simulations were obtained for both type I Mirollo–Strogatz neurons and type II Hodgkin–Huxley neurons. We have investigated the dynamics of the model for various types of synaptic coupling and importantly considered the potential impact of Spike-Timing Dependent Plasticity (STDP) and its learning window. We confirm previous results that zero-lag synchrony can be achieved in this configuration. This is much easier to achieve with Hodgkin–Huxley neurons, which have a biphasic phase response curve, than for type I neurons. STDP facilitates zero-lag synchrony as it adjusts the synaptic strengths such that zero-lag synchrony is feasible for a much larger range of parameters than without STDP. PMID:22866034

Spiking neural network model for memorizing sequences with forward and backward recall.

PubMed

Borisyuk, Roman; Chik, David; Kazanovich, Yakov; da Silva Gomes, João

2013-06-01

We present an oscillatory network of conductance based spiking neurons of Hodgkin-Huxley type as a model of memory storage and retrieval of sequences of events (or objects). The model is inspired by psychological and neurobiological evidence on sequential memories. The building block of the model is an oscillatory module which contains excitatory and inhibitory neurons with all-to-all connections. The connection architecture comprises two layers. A lower layer represents consecutive events during their storage and recall. This layer is composed of oscillatory modules. Plastic excitatory connections between the modules are implemented using an STDP type learning rule for sequential storage. Excitatory neurons in the upper layer project star-like modifiable connections toward the excitatory lower layer neurons. These neurons in the upper layer are used to tag sequences of events represented in the lower layer. Computer simulations demonstrate good performance of the model including difficult cases when different sequences contain overlapping events. We show that the model with STDP type or anti-STDP type learning rules can be applied for the simulation of forward and backward replay of neural spikes respectively. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Where’s the Noise? Key Features of Spontaneous Activity and Neural Variability Arise through Learning in a Deterministic Network

PubMed Central

Hartmann, Christoph; Lazar, Andreea; Nessler, Bernhard; Triesch, Jochen

2015-01-01

Even in the absence of sensory stimulation the brain is spontaneously active. This background “noise” seems to be the dominant cause of the notoriously high trial-to-trial variability of neural recordings. Recent experimental observations have extended our knowledge of trial-to-trial variability and spontaneous activity in several directions: 1. Trial-to-trial variability systematically decreases following the onset of a sensory stimulus or the start of a motor act. 2. Spontaneous activity states in sensory cortex outline the region of evoked sensory responses. 3. Across development, spontaneous activity aligns itself with typical evoked activity patterns. 4. The spontaneous brain activity prior to the presentation of an ambiguous stimulus predicts how the stimulus will be interpreted. At present it is unclear how these observations relate to each other and how they arise in cortical circuits. Here we demonstrate that all of these phenomena can be accounted for by a deterministic self-organizing recurrent neural network model (SORN), which learns a predictive model of its sensory environment. The SORN comprises recurrently coupled populations of excitatory and inhibitory threshold units and learns via a combination of spike-timing dependent plasticity (STDP) and homeostatic plasticity mechanisms. Similar to balanced network architectures, units in the network show irregular activity and variable responses to inputs. Additionally, however, the SORN exhibits sequence learning abilities matching recent findings from visual cortex and the network’s spontaneous activity reproduces the experimental findings mentioned above. Intriguingly, the network’s behaviour is reminiscent of sampling-based probabilistic inference, suggesting that correlates of sampling-based inference can develop from the interaction of STDP and homeostasis in deterministic networks. We conclude that key observations on spontaneous brain activity and the variability of neural responses can be accounted for by a simple deterministic recurrent neural network which learns a predictive model of its sensory environment via a combination of generic neural plasticity mechanisms. PMID:26714277

Learning touch preferences with a tactile robot using dopamine modulated STDP in a model of insular cortex

PubMed Central

Chou, Ting-Shuo; Bucci, Liam D.; Krichmar, Jeffrey L.

2015-01-01

Neurorobots enable researchers to study how behaviors are produced by neural mechanisms in an uncertain, noisy, real-world environment. To investigate how the somatosensory system processes noisy, real-world touch inputs, we introduce a neurorobot called CARL-SJR, which has a full-body tactile sensory area. The design of CARL-SJR is such that it encourages people to communicate with it through gentle touch. CARL-SJR provides feedback to users by displaying bright colors on its surface. In the present study, we show that CARL-SJR is capable of learning associations between conditioned stimuli (CS; a color pattern on its surface) and unconditioned stimuli (US; a preferred touch pattern) by applying a spiking neural network (SNN) with neurobiologically inspired plasticity. Specifically, we modeled the primary somatosensory cortex, prefrontal cortex, striatum, and the insular cortex, which is important for hedonic touch, to process noisy data generated directly from CARL-SJR's tactile sensory area. To facilitate learning, we applied dopamine-modulated Spike Timing Dependent Plasticity (STDP) to our simulated prefrontal cortex, striatum, and insular cortex. To cope with noisy, varying inputs, the SNN was tuned to produce traveling waves of activity that carried spatiotemporal information. Despite the noisy tactile sensors, spike trains, and variations in subject hand swipes, the learning was quite robust. Further, insular cortex activities in the incremental pathway of dopaminergic reward system allowed us to control CARL-SJR's preference for touch direction without heavily pre-processed inputs. The emerged behaviors we found in this model match animal's behaviors wherein they prefer touch in particular areas and directions. Thus, the results in this paper could serve as an explanation on the underlying neural mechanisms for developing tactile preferences and hedonic touch. PMID:26257639

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

PubMed

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

2013-09-27

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.

Unsupervised learning in neural networks with short range synapses

NASA Astrophysics Data System (ADS)

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

2013-01-01

Different areas of the brain are involved in specific aspects of the information being processed both in learning and in memory formation. For example, the hippocampus is important in the consolidation of information from short-term memory to long-term memory, while emotional memory seems to be dealt by the amygdala. On the microscopic scale the underlying structures in these areas differ in the kind of neurons involved, in their connectivity, or in their clustering degree but, at this level, learning and memory are attributed to neuronal synapses mediated by longterm potentiation and long-term depression. In this work we explore the properties of a short range synaptic connection network, a nearest neighbor lattice composed mostly by excitatory neurons and a fraction of inhibitory ones. The mechanism of synaptic modification responsible for the emergence of memory is Spike-Timing-Dependent Plasticity (STDP), a Hebbian-like rule, where potentiation/depression is acquired when causal/non-causal spikes happen in a synapse involving two neurons. The system is intended to store and recognize memories associated to spatial external inputs presented as simple geometrical forms. The synaptic modifications are continuously applied to excitatory connections, including a homeostasis rule and STDP. In this work we explore the different scenarios under which a network with short range connections can accomplish the task of storing and recognizing simple connected patterns.

STDP in lateral connections creates category-based perceptual cycles for invariance learning with multiple stimuli.

PubMed

Evans, Benjamin D; Stringer, Simon M

2015-04-01

Learning to recognise objects and faces is an important and challenging problem tackled by the primate ventral visual system. One major difficulty lies in recognising an object despite profound differences in the retinal images it projects, due to changes in view, scale, position and other identity-preserving transformations. Several models of the ventral visual system have been successful in coping with these issues, but have typically been privileged by exposure to only one object at a time. In natural scenes, however, the challenges of object recognition are typically further compounded by the presence of several objects which should be perceived as distinct entities. In the present work, we explore one possible mechanism by which the visual system may overcome these two difficulties simultaneously, through segmenting unseen (artificial) stimuli using information about their category encoded in plastic lateral connections. We demonstrate that these experience-guided lateral interactions robustly organise input representations into perceptual cycles, allowing feed-forward connections trained with spike-timing-dependent plasticity to form independent, translation-invariant output representations. We present these simulations as a functional explanation for the role of plasticity in the lateral connectivity of visual cortex.

Reward-based learning under hardware constraints-using a RISC processor embedded in a neuromorphic substrate.

PubMed

Friedmann, Simon; Frémaux, Nicolas; Schemmel, Johannes; Gerstner, Wulfram; Meier, Karlheinz

2013-01-01

In this study, we propose and analyze in simulations a new, highly flexible method of implementing synaptic plasticity in a wafer-scale, accelerated neuromorphic hardware system. The study focuses on globally modulated STDP, as a special use-case of this method. Flexibility is achieved by embedding a general-purpose processor dedicated to plasticity into the wafer. To evaluate the suitability of the proposed system, we use a reward modulated STDP rule in a spike train learning task. A single layer of neurons is trained to fire at specific points in time with only the reward as feedback. This model is simulated to measure its performance, i.e., the increase in received reward after learning. Using this performance as baseline, we then simulate the model with various constraints imposed by the proposed implementation and compare the performance. The simulated constraints include discretized synaptic weights, a restricted interface between analog synapses and embedded processor, and mismatch of analog circuits. We find that probabilistic updates can increase the performance of low-resolution weights, a simple interface between analog synapses and processor is sufficient for learning, and performance is insensitive to mismatch. Further, we consider communication latency between wafer and the conventional control computer system that is simulating the environment. This latency increases the delay, with which the reward is sent to the embedded processor. Because of the time continuous operation of the analog synapses, delay can cause a deviation of the updates as compared to the not delayed situation. We find that for highly accelerated systems latency has to be kept to a minimum. This study demonstrates the suitability of the proposed implementation to emulate the selected reward modulated STDP learning rule. It is therefore an ideal candidate for implementation in an upgraded version of the wafer-scale system developed within the BrainScaleS project.

Reward-based learning under hardware constraints—using a RISC processor embedded in a neuromorphic substrate

PubMed Central

Friedmann, Simon; Frémaux, Nicolas; Schemmel, Johannes; Gerstner, Wulfram; Meier, Karlheinz

2013-01-01

In this study, we propose and analyze in simulations a new, highly flexible method of implementing synaptic plasticity in a wafer-scale, accelerated neuromorphic hardware system. The study focuses on globally modulated STDP, as a special use-case of this method. Flexibility is achieved by embedding a general-purpose processor dedicated to plasticity into the wafer. To evaluate the suitability of the proposed system, we use a reward modulated STDP rule in a spike train learning task. A single layer of neurons is trained to fire at specific points in time with only the reward as feedback. This model is simulated to measure its performance, i.e., the increase in received reward after learning. Using this performance as baseline, we then simulate the model with various constraints imposed by the proposed implementation and compare the performance. The simulated constraints include discretized synaptic weights, a restricted interface between analog synapses and embedded processor, and mismatch of analog circuits. We find that probabilistic updates can increase the performance of low-resolution weights, a simple interface between analog synapses and processor is sufficient for learning, and performance is insensitive to mismatch. Further, we consider communication latency between wafer and the conventional control computer system that is simulating the environment. This latency increases the delay, with which the reward is sent to the embedded processor. Because of the time continuous operation of the analog synapses, delay can cause a deviation of the updates as compared to the not delayed situation. We find that for highly accelerated systems latency has to be kept to a minimum. This study demonstrates the suitability of the proposed implementation to emulate the selected reward modulated STDP learning rule. It is therefore an ideal candidate for implementation in an upgraded version of the wafer-scale system developed within the BrainScaleS project. PMID:24065877

Reversible optical switching memristors with tunable STDP synaptic plasticity: a route to hierarchical control in artificial intelligent systems.

PubMed

Jaafar, Ayoub H; Gray, Robert J; Verrelli, Emanuele; O'Neill, Mary; Kelly, Stephen M; Kemp, Neil T

2017-11-09

Optical control of memristors opens the route to new applications in optoelectronic switching and neuromorphic computing. Motivated by the need for reversible and latched optical switching we report on the development of a memristor with electronic properties tunable and switchable by wavelength and polarization specific light. The device consists of an optically active azobenzene polymer, poly(disperse red 1 acrylate), overlaying a forest of vertically aligned ZnO nanorods. Illumination induces trans-cis isomerization of the azobenzene molecules, which expands or contracts the polymer layer and alters the resistance of the off/on states, their ratio and retention time. The reversible optical effect enables dynamic control of a memristor's learning properties including control of synaptic potentiation and depression, optical switching between short-term and long-term memory and optical modulation of the synaptic efficacy via spike timing dependent plasticity. The work opens the route to the dynamic patterning of memristor networks both spatially and temporally by light, thus allowing the development of new optically reconfigurable neural networks and adaptive electronic circuits.

Event-driven contrastive divergence for spiking neuromorphic systems.

PubMed

Neftci, Emre; Das, Srinjoy; Pedroni, Bruno; Kreutz-Delgado, Kenneth; Cauwenberghs, Gert

2013-01-01

Restricted Boltzmann Machines (RBMs) and Deep Belief Networks have been demonstrated to perform efficiently in a variety of applications, such as dimensionality reduction, feature learning, and classification. Their implementation on neuromorphic hardware platforms emulating large-scale networks of spiking neurons can have significant advantages from the perspectives of scalability, power dissipation and real-time interfacing with the environment. However, the traditional RBM architecture and the commonly used training algorithm known as Contrastive Divergence (CD) are based on discrete updates and exact arithmetics which do not directly map onto a dynamical neural substrate. Here, we present an event-driven variation of CD to train a RBM constructed with Integrate & Fire (I&F) neurons, that is constrained by the limitations of existing and near future neuromorphic hardware platforms. Our strategy is based on neural sampling, which allows us to synthesize a spiking neural network that samples from a target Boltzmann distribution. The recurrent activity of the network replaces the discrete steps of the CD algorithm, while Spike Time Dependent Plasticity (STDP) carries out the weight updates in an online, asynchronous fashion. We demonstrate our approach by training an RBM composed of leaky I&F neurons with STDP synapses to learn a generative model of the MNIST hand-written digit dataset, and by testing it in recognition, generation and cue integration tasks. Our results contribute to a machine learning-driven approach for synthesizing networks of spiking neurons capable of carrying out practical, high-level functionality.

Event-driven contrastive divergence for spiking neuromorphic systems

PubMed Central

Neftci, Emre; Das, Srinjoy; Pedroni, Bruno; Kreutz-Delgado, Kenneth; Cauwenberghs, Gert

2014-01-01

Restricted Boltzmann Machines (RBMs) and Deep Belief Networks have been demonstrated to perform efficiently in a variety of applications, such as dimensionality reduction, feature learning, and classification. Their implementation on neuromorphic hardware platforms emulating large-scale networks of spiking neurons can have significant advantages from the perspectives of scalability, power dissipation and real-time interfacing with the environment. However, the traditional RBM architecture and the commonly used training algorithm known as Contrastive Divergence (CD) are based on discrete updates and exact arithmetics which do not directly map onto a dynamical neural substrate. Here, we present an event-driven variation of CD to train a RBM constructed with Integrate & Fire (I&F) neurons, that is constrained by the limitations of existing and near future neuromorphic hardware platforms. Our strategy is based on neural sampling, which allows us to synthesize a spiking neural network that samples from a target Boltzmann distribution. The recurrent activity of the network replaces the discrete steps of the CD algorithm, while Spike Time Dependent Plasticity (STDP) carries out the weight updates in an online, asynchronous fashion. We demonstrate our approach by training an RBM composed of leaky I&F neurons with STDP synapses to learn a generative model of the MNIST hand-written digit dataset, and by testing it in recognition, generation and cue integration tasks. Our results contribute to a machine learning-driven approach for synthesizing networks of spiking neurons capable of carrying out practical, high-level functionality. PMID:24574952

Integrated neuron circuit for implementing neuromorphic system with synaptic device

NASA Astrophysics Data System (ADS)

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).

Timing-dependent LTP and LTD in mouse primary visual cortex following different visual deprivation models

PubMed Central

Chen, Xia; Fu, Junhong; Cheng, Wenbo; Song, Desheng; Qu, Xiaolei; Yang, Zhuo; Zhao, Kanxing

2017-01-01

Visual deprivation during the critical period induces long-lasting changes in cortical circuitry by adaptively modifying neuro-transmission and synaptic connectivity at synapses. Spike timing-dependent plasticity (STDP) is considered a strong candidate for experience-dependent changes. However, the visual deprivation forms that affect timing-dependent long-term potentiation(LTP) and long-term depression(LTD) remain unclear. Here, we demonstrated the temporal window changes of tLTP and tLTD, elicited by coincidental pre- and post-synaptic firing, following different modes of 6-day visual deprivation. Markedly broader temporal windows were found in robust tLTP and tLTD in the V1M of the deprived visual cortex in mice after 6-day MD and DE. The underlying mechanism for the changes seen with visual deprivation in juvenile mice using 6 days of dark exposure or monocular lid suture involves an increased fraction of NR2b-containing NMDAR and the consequent prolongation of NMDAR-mediated response duration. Moreover, a decrease in NR2A protein expression at the synapse is attributable to the reduction of the NR2A/2B ratio in the deprived cortex. PMID:28520739

Categorization and decision-making in a neurobiologically plausible spiking network using a STDP-like learning rule.

PubMed

Beyeler, Michael; Dutt, Nikil D; Krichmar, Jeffrey L

2013-12-01

Understanding how the human brain is able to efficiently perceive and understand a visual scene is still a field of ongoing research. Although many studies have focused on the design and optimization of neural networks to solve visual recognition tasks, most of them either lack neurobiologically plausible learning rules or decision-making processes. Here we present a large-scale model of a hierarchical spiking neural network (SNN) that integrates a low-level memory encoding mechanism with a higher-level decision process to perform a visual classification task in real-time. The model consists of Izhikevich neurons and conductance-based synapses for realistic approximation of neuronal dynamics, a spike-timing-dependent plasticity (STDP) synaptic learning rule with additional synaptic dynamics for memory encoding, and an accumulator model for memory retrieval and categorization. The full network, which comprised 71,026 neurons and approximately 133 million synapses, ran in real-time on a single off-the-shelf graphics processing unit (GPU). The network was constructed on a publicly available SNN simulator that supports general-purpose neuromorphic computer chips. The network achieved 92% correct classifications on MNIST in 100 rounds of random sub-sampling, which is comparable to other SNN approaches and provides a conservative and reliable performance metric. Additionally, the model correctly predicted reaction times from psychophysical experiments. Because of the scalability of the approach and its neurobiological fidelity, the current model can be extended to an efficient neuromorphic implementation that supports more generalized object recognition and decision-making architectures found in the brain. Copyright © 2013 Elsevier Ltd. All rights reserved.

Outcome Research on Short-Term Psychodynamic Psychotherapy: A Preliminary Review.

ERIC Educational Resources Information Center

White, Scott Allyn

This paper reviews the empirical research on short-term psychodynamic psychotherapy (STDP). It begins with a brief history of STDP, identifying current developers and researchers of STDP and listing commonalities among various short-term dynamic psychotherapies. In this review, research is grouped broadly into two categories: controlled…

Emergent Auditory Feature Tuning in a Real-Time Neuromorphic VLSI System.

PubMed

Sheik, Sadique; Coath, Martin; Indiveri, Giacomo; Denham, Susan L; Wennekers, Thomas; Chicca, Elisabetta

2012-01-01

Many sounds of ecological importance, such as communication calls, are characterized by time-varying spectra. However, most neuromorphic auditory models to date have focused on distinguishing mainly static patterns, under the assumption that dynamic patterns can be learned as sequences of static ones. In contrast, the emergence of dynamic feature sensitivity through exposure to formative stimuli has been recently modeled in a network of spiking neurons based on the thalamo-cortical architecture. The proposed network models the effect of lateral and recurrent connections between cortical layers, distance-dependent axonal transmission delays, and learning in the form of Spike Timing Dependent Plasticity (STDP), which effects stimulus-driven changes in the pattern of network connectivity. In this paper we demonstrate how these principles can be efficiently implemented in neuromorphic hardware. In doing so we address two principle problems in the design of neuromorphic systems: real-time event-based asynchronous communication in multi-chip systems, and the realization in hybrid analog/digital VLSI technology of neural computational principles that we propose underlie plasticity in neural processing of dynamic stimuli. The result is a hardware neural network that learns in real-time and shows preferential responses, after exposure, to stimuli exhibiting particular spectro-temporal patterns. The availability of hardware on which the model can be implemented, makes this a significant step toward the development of adaptive, neurobiologically plausible, spike-based, artificial sensory systems.

Emergent Auditory Feature Tuning in a Real-Time Neuromorphic VLSI System

PubMed Central

Sheik, Sadique; Coath, Martin; Indiveri, Giacomo; Denham, Susan L.; Wennekers, Thomas; Chicca, Elisabetta

2011-01-01

Many sounds of ecological importance, such as communication calls, are characterized by time-varying spectra. However, most neuromorphic auditory models to date have focused on distinguishing mainly static patterns, under the assumption that dynamic patterns can be learned as sequences of static ones. In contrast, the emergence of dynamic feature sensitivity through exposure to formative stimuli has been recently modeled in a network of spiking neurons based on the thalamo-cortical architecture. The proposed network models the effect of lateral and recurrent connections between cortical layers, distance-dependent axonal transmission delays, and learning in the form of Spike Timing Dependent Plasticity (STDP), which effects stimulus-driven changes in the pattern of network connectivity. In this paper we demonstrate how these principles can be efficiently implemented in neuromorphic hardware. In doing so we address two principle problems in the design of neuromorphic systems: real-time event-based asynchronous communication in multi-chip systems, and the realization in hybrid analog/digital VLSI technology of neural computational principles that we propose underlie plasticity in neural processing of dynamic stimuli. The result is a hardware neural network that learns in real-time and shows preferential responses, after exposure, to stimuli exhibiting particular spectro-temporal patterns. The availability of hardware on which the model can be implemented, makes this a significant step toward the development of adaptive, neurobiologically plausible, spike-based, artificial sensory systems. PMID:22347163

A geographic information system analysis of the impact of a statewide acute stroke emergency medical services routing protocol on community hospital bypass.

PubMed

Asimos, Andrew W; Ward, Shana; Brice, Jane H; Enright, Dianne; Rosamond, Wayne D; Goldstein, Larry B; Studnek, Jonathan

2014-01-01

Our goal was to determine if a statewide Emergency Medical Services (EMSs) Stroke Triage and Destination Plan (STDP), specifying bypass of hospitals unable to routinely treat stroke patients with thrombolytics (community hospitals), changed bypass frequency of those hospitals. Using a statewide EMS database, we identified stroke patients eligible for community hospital bypass and compared bypass frequency 1-year before and after STDP implementation. Symptom onset time was missing for 48% of pre-STDP (n = 2385) and 29% of post-STDP (n = 1612) cases. Of the remaining cases with geocodable scene addresses, 58% (1301) in the pre-STDP group and 61% (2,078) in the post-STDP group were ineligible for bypass, because a community hospital was not the closest hospital to the stroke event location. Because of missing data records for some EMS agencies in 1 or both study periods, we included EMS agencies from only 49 of 100 North Carolina counties in our analysis. Additionally, we found conflicting hospital classifications by different EMS agencies for 35% of all hospitals (n = 38 of 108). Given these limitations, we found similar community hospital bypass rates before and after STDP implementation (64%, n = 332 of 520 vs. 63%, n = 345 of 552; P = .65). Missing symptom duration time and data records in our state's EMS data system, along with conflicting hospital classifications between EMS agencies limit the ability to study statewide stroke routing protocols. Bypass policies may apply to a minority of patients because a community hospital is not the closest hospital to most stroke events. Given these limitations, we found no difference in community hospital bypass rates after implementation of the STDP. Copyright © 2014 National Stroke Association. Published by Elsevier Inc. All rights reserved.

A neuromorphic model of motor overflow in focal hand dystonia due to correlated sensory input

NASA Astrophysics Data System (ADS)

Sohn, Won Joon; Niu, Chuanxin M.; Sanger, Terence D.

2016-10-01

Objective. Motor overflow is a common and frustrating symptom of dystonia, manifested as unintentional muscle contraction that occurs during an intended voluntary movement. Although it is suspected that motor overflow is due to cortical disorganization in some types of dystonia (e.g. focal hand dystonia), it remains elusive which mechanisms could initiate and, more importantly, perpetuate motor overflow. We hypothesize that distinct motor elements have low risk of motor overflow if their sensory inputs remain statistically independent. But when provided with correlated sensory inputs, pre-existing crosstalk among sensory projections will grow under spike-timing-dependent-plasticity (STDP) and eventually produce irreversible motor overflow. Approach. We emulated a simplified neuromuscular system comprising two anatomically distinct digital muscles innervated by two layers of spiking neurons with STDP. The synaptic connections between layers included crosstalk connections. The input neurons received either independent or correlated sensory drive during 4 days of continuous excitation. The emulation is critically enabled and accelerated by our neuromorphic hardware created in previous work. Main results. When driven by correlated sensory inputs, the crosstalk synapses gained weight and produced prominent motor overflow; the growth of crosstalk synapses resulted in enlarged sensory representation reflecting cortical reorganization. The overflow failed to recede when the inputs resumed their original uncorrelated statistics. In the control group, no motor overflow was observed. Significance. Although our model is a highly simplified and limited representation of the human sensorimotor system, it allows us to explain how correlated sensory input to anatomically distinct muscles is by itself sufficient to cause persistent and irreversible motor overflow. Further studies are needed to locate the source of correlation in sensory input.

Dual coding with STDP in a spiking recurrent neural network model of the hippocampus.

PubMed

Bush, Daniel; Philippides, Andrew; Husbands, Phil; O'Shea, Michael

2010-07-01

The firing rate of single neurons in the mammalian hippocampus has been demonstrated to encode for a range of spatial and non-spatial stimuli. It has also been demonstrated that phase of firing, with respect to the theta oscillation that dominates the hippocampal EEG during stereotype learning behaviour, correlates with an animal's spatial location. These findings have led to the hypothesis that the hippocampus operates using a dual (rate and temporal) coding system. To investigate the phenomenon of dual coding in the hippocampus, we examine a spiking recurrent network model with theta coded neural dynamics and an STDP rule that mediates rate-coded Hebbian learning when pre- and post-synaptic firing is stochastic. We demonstrate that this plasticity rule can generate both symmetric and asymmetric connections between neurons that fire at concurrent or successive theta phase, respectively, and subsequently produce both pattern completion and sequence prediction from partial cues. This unifies previously disparate auto- and hetero-associative network models of hippocampal function and provides them with a firmer basis in modern neurobiology. Furthermore, the encoding and reactivation of activity in mutually exciting Hebbian cell assemblies demonstrated here is believed to represent a fundamental mechanism of cognitive processing in the brain.

Demonstration of Synaptic Behaviors and Resistive Switching Characterizations by Proton Exchange Reactions in Silicon Oxide

PubMed Central

Chang, Yao-Feng; Fowler, Burt; Chen, Ying-Chen; Zhou, Fei; Pan, Chih-Hung; Chang, Ting-Chang; Lee, Jack C.

2016-01-01

We realize a device with biological synaptic behaviors by integrating silicon oxide (SiOx) resistive switching memory with Si diodes. Minimal synaptic power consumption due to sneak-path current is achieved and the capability for spike-induced synaptic behaviors is demonstrated, representing critical milestones for the use of SiO2–based materials in future neuromorphic computing applications. Biological synaptic behaviors such as long-term potentiation (LTP), long-term depression (LTD) and spike-timing dependent plasticity (STDP) are demonstrated systematically using a comprehensive analysis of spike-induced waveforms, and represent interesting potential applications for SiOx-based resistive switching materials. The resistive switching SET transition is modeled as hydrogen (proton) release from (SiH)2 to generate the hydrogen bridge defect, and the RESET transition is modeled as an electrochemical reaction (proton capture) that re-forms (SiH)2. The experimental results suggest a simple, robust approach to realize programmable neuromorphic chips compatible with large-scale CMOS manufacturing technology. PMID:26880381

Demonstration of Synaptic Behaviors and Resistive Switching Characterizations by Proton Exchange Reactions in Silicon Oxide

NASA Astrophysics Data System (ADS)

Chang, Yao-Feng; Fowler, Burt; Chen, Ying-Chen; Zhou, Fei; Pan, Chih-Hung; Chang, Ting-Chang; Lee, Jack C.

2016-02-01

We realize a device with biological synaptic behaviors by integrating silicon oxide (SiOx) resistive switching memory with Si diodes. Minimal synaptic power consumption due to sneak-path current is achieved and the capability for spike-induced synaptic behaviors is demonstrated, representing critical milestones for the use of SiO2-based materials in future neuromorphic computing applications. Biological synaptic behaviors such as long-term potentiation (LTP), long-term depression (LTD) and spike-timing dependent plasticity (STDP) are demonstrated systematically using a comprehensive analysis of spike-induced waveforms, and represent interesting potential applications for SiOx-based resistive switching materials. The resistive switching SET transition is modeled as hydrogen (proton) release from (SiH)2 to generate the hydrogen bridge defect, and the RESET transition is modeled as an electrochemical reaction (proton capture) that re-forms (SiH)2. The experimental results suggest a simple, robust approach to realize programmable neuromorphic chips compatible with large-scale CMOS manufacturing technology.

Spontaneously emerging direction selectivity maps in visual cortex through STDP.

PubMed

Wenisch, Oliver G; Noll, Joachim; Hemmen, J Leo van

2005-10-01

It is still an open question as to whether, and how, direction-selective neuronal responses in primary visual cortex are generated by feedforward thalamocortical or recurrent intracortical connections, or a combination of both. Here we present an investigation that concentrates on and, only for the sake of simplicity, restricts itself to intracortical circuits, in particular, with respect to the developmental aspects of direction selectivity through spike-timing-dependent synaptic plasticity. We show that directional responses can emerge in a recurrent network model of visual cortex with spiking neurons that integrate inputs mainly from a particular direction, thus giving rise to an asymmetrically shaped receptive field. A moving stimulus that enters the receptive field from this (preferred) direction will activate a neuron most strongly because of the increased number and/or strength of inputs from this direction and since delayed isotropic inhibition will neither overlap with, nor cancel excitation, as would be the case for other stimulus directions. It is demonstrated how direction-selective responses result from spatial asymmetries in the distribution of synaptic contacts or weights of inputs delivered to a neuron by slowly conducting intracortical axonal delay lines. By means of spike-timing-dependent synaptic plasticity with an asymmetric learning window this kind of coupling asymmetry develops naturally in a recurrent network of stochastically spiking neurons in a scenario where the neurons are activated by unidirectionally moving bar stimuli and even when only intrinsic spontaneous activity drives the learning process. We also present simulation results to show the ability of this model to produce direction preference maps similar to experimental findings.

Self-organization of synchronous activity propagation in neuronal networks driven by local excitation

PubMed Central

Bayati, Mehdi; Valizadeh, Alireza; Abbassian, Abdolhossein; Cheng, Sen

2015-01-01

Many experimental and theoretical studies have suggested that the reliable propagation of synchronous neural activity is crucial for neural information processing. The propagation of synchronous firing activity in so-called synfire chains has been studied extensively in feed-forward networks of spiking neurons. However, it remains unclear how such neural activity could emerge in recurrent neuronal networks through synaptic plasticity. In this study, we investigate whether local excitation, i.e., neurons that fire at a higher frequency than the other, spontaneously active neurons in the network, can shape a network to allow for synchronous activity propagation. We use two-dimensional, locally connected and heterogeneous neuronal networks with spike-timing dependent plasticity (STDP). We find that, in our model, local excitation drives profound network changes within seconds. In the emergent network, neural activity propagates synchronously through the network. This activity originates from the site of the local excitation and propagates through the network. The synchronous activity propagation persists, even when the local excitation is removed, since it derives from the synaptic weight matrix. Importantly, once this connectivity is established it remains stable even in the presence of spontaneous activity. Our results suggest that synfire-chain-like activity can emerge in a relatively simple way in realistic neural networks by locally exciting the desired origin of the neuronal sequence. PMID:26089794

Enhanced polychronization in a spiking network with metaplasticity.

PubMed

Guise, Mira; Knott, Alistair; Benuskova, Lubica

2015-01-01

Computational models of metaplasticity have usually focused on the modeling of single synapses (Shouval et al., 2002). In this paper we study the effect of metaplasticity on network behavior. Our guiding assumption is that the primary purpose of metaplasticity is to regulate synaptic plasticity, by increasing it when input is low and decreasing it when input is high. For our experiments we adopt a model of metaplasticity that demonstrably has this effect for a single synapse; our primary interest is in how metaplasticity thus defined affects network-level phenomena. We focus on a network-level phenomenon called polychronicity, that has a potential role in representation and memory. A network with polychronicity has the ability to produce non-synchronous but precisely timed sequences of neural firing events that can arise from strongly connected groups of neurons called polychronous neural groups (Izhikevich et al., 2004). Polychronous groups (PNGs) develop readily when spiking networks are exposed to repeated spatio-temporal stimuli under the influence of spike-timing-dependent plasticity (STDP), but are sensitive to changes in synaptic weight distribution. We use a technique we have recently developed called Response Fingerprinting to show that PNGs formed in the presence of metaplasticity are significantly larger than those with no metaplasticity. A potential mechanism for this enhancement is proposed that links an inherent property of integrator type neurons called spike latency to an increase in the tolerance of PNG neurons to jitter in their inputs.

A memristive plasticity model of voltage-based STDP suitable for recurrent bidirectional neural networks in the hippocampus.

PubMed

Diederich, Nick; Bartsch, Thorsten; Kohlstedt, Hermann; Ziegler, Martin

2018-06-19

Memristive systems have gained considerable attention in the field of neuromorphic engineering, because they allow the emulation of synaptic functionality in solid state nano-physical systems. In this study, we show that memristive behavior provides a broad working framework for the phenomenological modelling of cellular synaptic mechanisms. In particular, we seek to understand how close a memristive system can account for the biological realism. The basic characteristics of memristive systems, i.e. voltage and memory behavior, are used to derive a voltage-based plasticity rule. We show that this model is suitable to account for a variety of electrophysiology plasticity data. Furthermore, we incorporate the plasticity model into an all-to-all connecting network scheme. Motivated by the auto-associative CA3 network of the hippocampus, we show that the implemented network allows the discrimination and processing of mnemonic pattern information, i.e. the formation of functional bidirectional connections resulting in the formation of local receptive fields. Since the presented plasticity model can be applied to real memristive devices as well, the presented theoretical framework can support both, the design of appropriate memristive devices for neuromorphic computing and the development of complex neuromorphic networks, which account for the specific advantage of memristive devices.

Learning tinnitus

NASA Astrophysics Data System (ADS)

van Hemmen, J. Leo

Tinnitus, implying the perception of sound without the presence of any acoustical stimulus, is a chronic and serious problem for about 2% of the human population. In many cases, tinnitus is a pitch-like sensation associated with a hearing loss that confines the tinnitus frequency to an interval of the tonotopic axis. Even in patients with a normal audiogram the presence of tinnitus may be associated with damage of hair-cell function in this interval. It has been suggested that homeostatic regulation and, hence, increase of activity leads to the emergence of tinnitus. For patients with hearing loss, we present spike-timing-dependent Hebbian plasticity (STDP) in conjunction with homeostasis as a mechanism for ``learning'' tinnitus in a realistic neuronal network with tonotopically arranged synaptic excitation and inhibition. In so doing we use both dynamical scaling of the synaptic strengths and altering the resting potential of the cells. The corresponding simulations are robust to parameter changes. Understanding the mechanisms of tinnitus induction, such as here, may help improving therapy. Work done in collaboration with Julie Goulet and Michael Schneider. JLvH has been supported partially by BCCN - Munich.

[Spectrofluorometric detection of protein with a novel hydrophilic cyanine dye].

PubMed

Lin, Xu-Cong; Guo, Liang-Qia; Lin, Yan-Xia; Xie, Zeng-Hong

2007-09-01

A sensitive fluorescence quantitative determination for bovine serum albumin (BSA) or human serum albumin (HSA) has been developed by using a new hydrophilic cyanine dye 1, 1'-sulfonopropyl-3,3,3', 3'-tetramethylindolium-5,5'-disulfonic potassium (STDP) as a fluorescence probe. Using BSA as a representative protein, characteristics of the fluorescence reaction of STDP with protein were investigated. Effects of the concentration of the hydrophilic cyanine dye, pH value of the buffer solution, and ion-intensity of NaCl were also studied as well as the ratio of ethanol. In the citrate-HCl buffer solution, the fluorescence emission wavelength of BSA-STDP system was 562 nm with the maximum excitation wavelength of 548 nm, and the Stokes displacement was 14 nm. With the pH ranging from 1.0 to 2.0, the fluorescence was increasing and up to the maximum at pH 2.0. However, in the pH range of 3.0-5.0, the interaction of BSA and STDP was weakened due to the decrease in positive charge on the BSA chain, which resulted in an observable decrease of the enhancement of the fluorescence intensity. At the optimum pH of 2.0, electrostatic interactions of positive charges of the BSA chain and negative charges on the sulfonic groups of STDP were carried out. The interactions of the indole group of STDP and some active groups of BSA (viz. amido, carboxyl or sulfhydryl) were also achieved, and resulted in the combination of indole group of cyanine dye into the chain of BSA. So the hydrophobic effect and the protection provided by the skeleton chain of BSA were both improved to prevent the fluorescent energy of STDP from losing in the solution, which caused a notable fluorescence increase with an observable shift to the longer emission wavelength. Furthermore, with the augmentation of BSA, the alpha-helix structure of BSA molecular turned from the unwrapped state to the enfolded state, in favor of restraining free-oscillation of fluorescence probe in the solution and maintaining a high energy transfer efficiency. Such a fact fueled a highly enhancement of the fluorescence too. Besides, effects of the concentration of cyanine dye on the determination of BSA were also investigated. The fluorescence intensity (DeltaF) was enhanced with the increase in the quantity of STDP and gained the peak at 1.00 micromol x L(-1). However, when STDP ranged from 1.50 to 5.00 micromol x L(-1), some negative congregate effects on the nature of cyanine dye might happen and resulted in a too high fluorescence background. A rapid decrease of the fluorescence intensity was observed. The effects of ion-intensity of NaCl and ethanol on the fluorescence of BSA-STDP system were obvious. Though the fluorescence still remained high at the level of NaCl of 0.025 mol x L(-1), a rapid decrease happen at the level of NaCl from 0.05 to 0.15 mol x L(-1). With the addition of ethanol, the dissolvation capacity of both STDP and BSA was improved and their interactions were accelerated. An increasing fluorescence with the augment of ethanol was obtained and the maximum was achieved with the ratio of ethanol at 10%. Influences of coexistent substances such as amino acid, metal ions such as Cu2+, Na+, Ca2+, Mg2+, Al3+ and Fe3+ were also investigated. Most substances had no notable influences on the determination of BSA except Fe3+ and Cu2+ ions. Under the optimum conditions, the fluorescence of STDP was enhanced markedly with the addition of the BSA or HSA protein. Good calibration curves of the proteins were obtained in the range of 0.20-15.00 microg x mL(-1) for BSA and 0.20-12.00 microg x mL(-1) for HSA with detection limits (3sigma/K) of 0.01 microg x mL(-1). Applied to simulant BSA samples, this method was adaptable. And the results were satisfied with good recoveries ranging from 94.5% to 103.3% at the revels of 4.00, 6.00 and 8.00 microg x mL(-1) respectively.

Color opponent receptive fields self-organize in a biophysical model of visual cortex via spike-timing dependent plasticity

PubMed Central

Eguchi, Akihiro; Neymotin, Samuel A.; Stringer, Simon M.

2014-01-01

Although many computational models have been proposed to explain orientation maps in primary visual cortex (V1), it is not yet known how similar clusters of color-selective neurons in macaque V1/V2 are connected and develop. In this work, we address the problem of understanding the cortical processing of color information with a possible mechanism of the development of the patchy distribution of color selectivity via computational modeling. Each color input is decomposed into a red, green, and blue representation and transmitted to the visual cortex via a simulated optic nerve in a luminance channel and red–green and blue–yellow opponent color channels. Our model of the early visual system consists of multiple topographically-arranged layers of excitatory and inhibitory neurons, with sparse intra-layer connectivity and feed-forward connectivity between layers. Layers are arranged based on anatomy of early visual pathways, and include a retina, lateral geniculate nucleus, and layered neocortex. Each neuron in the V1 output layer makes synaptic connections to neighboring neurons and receives the three types of signals in the different channels from the corresponding photoreceptor position. Synaptic weights are randomized and learned using spike-timing-dependent plasticity (STDP). After training with natural images, the neurons display heightened sensitivity to specific colors. Information-theoretic analysis reveals mutual information between particular stimuli and responses, and that the information reaches a maximum with fewer neurons in the higher layers, indicating that estimations of the input colors can be done using the output of fewer cells in the later stages of cortical processing. In addition, cells with similar color receptive fields form clusters. Analysis of spiking activity reveals increased firing synchrony between neurons when particular color inputs are presented or removed (ON-cell/OFF-cell). PMID:24659956

A plastic corticostriatal circuit model of adaptation in perceptual decision making

PubMed Central

Hsiao, Pao-Yueh; Lo, Chung-Chuan

2013-01-01

The ability to optimize decisions and adapt them to changing environments is a crucial brain function that increase survivability. Although much has been learned about the neuronal activity in various brain regions that are associated with decision making, and about how the nervous systems may learn to achieve optimization, the underlying neuronal mechanisms of how the nervous systems optimize decision strategies with preference given to speed or accuracy, and how the systems adapt to changes in the environment, remain unclear. Based on extensive empirical observations, we addressed the question by extending a previously described cortico-basal ganglia circuit model of perceptual decisions with the inclusion of a dynamic dopamine (DA) system that modulates spike-timing dependent plasticity (STDP). We found that, once an optimal model setting that maximized the reward rate was selected, the same setting automatically optimized decisions across different task environments through dynamic balancing between the facilitating and depressing components of the DA dynamics. Interestingly, other model parameters were also optimal if we considered the reward rate that was weighted by the subject's preferences for speed or accuracy. Specifically, the circuit model favored speed if we increased the phasic DA response to the reward prediction error, whereas the model favored accuracy if we reduced the tonic DA activity or the phasic DA responses to the estimated reward probability. The proposed model provides insight into the roles of different components of DA responses in decision adaptation and optimization in a changing environment. PMID:24339814

Characterization of emergent synaptic topologies in noisy neural networks

NASA Astrophysics Data System (ADS)

Miller, Aaron James

Learned behaviors are one of the key contributors to an animal's ultimate survival. It is widely believed that the brain's microcircuitry undergoes structural changes when a new behavior is learned. In particular, motor learning, during which an animal learns a sequence of muscular movements, often requires precisely-timed coordination between muscles and becomes very natural once ingrained. Experiments show that neurons in the motor cortex exhibit precisely-timed spike activity when performing a learned motor behavior, and constituent stereotypical elements of the behavior can last several hundred milliseconds. The subject of this manuscript concerns how organized synaptic structures that produce stereotypical spike sequences emerge from random, dynamical networks. After a brief introduction in Chapter 1, we begin Chapter 2 by introducing a spike-timing-dependent plasticity (STDP) rule that defines how the activity of the network drives changes in network topology. The rule is then applied to idealized networks of leaky integrate-and-fire neurons (LIF). These neurons are not subjected to the variability that typically characterize neurons in vivo. In noiseless networks, synapses develop closed loops of strong connectivity that reproduce stereotypical, precisely-timed spike patterns from an initially random network. We demonstrate the characteristics of the asymptotic synaptic configuration are dependent on the statistics of the initial random network. The spike timings of the neurons simulated in Chapter 2 are generated exactly by a computationally economical, nonlinear mapping which is extended to LIF neurons injected with fluctuating current in Chapter 3. Development of an economical mapping that incorporates noise provides a practical solution to the long simulation times required to produce asymptotic synaptic topologies in networks with STDP in the presence of realistic neuronal variability. The mapping relies on generating numerical solutions to the dynamics of a LIF neuron subjected to Gaussian white noise (GWN). The system reduces to the Ornstein-Uhlenbeck first passage time problem, the solution of which we build into the mapping method of Chapter 2. We demonstrate that simulations using the stochastic mapping have reduced computation time compared to traditional Runge-Kutta methods by more than a factor of 150. In Chapter 4, we use the stochastic mapping to study the dynamics of emerging synaptic topologies in noisy networks. With the addition of membrane noise, networks with dynamical synapses can admit states in which the distribution of the synaptic weights is static under spontaneous activity, but the random connectivity between neurons is dynamical. The widely cited problem of instabilities in networks with STDP is avoided with the implementation of a synaptic decay and an activation threshold on each synapse. When such networks are presented with stimulus modeled by a focused excitatory current, chain-like networks can emerge with the addition of an axon-remodeling plasticity rule, a topological constraint on the connectivity modeling the finite resources available to each neuron. The emergent topologies are the result of an iterative stochastic process. The dynamics of the growth process suggest a strong interplay between the network topology and the spike sequences they produce during development. Namely, the existence of an embedded spike sequence alters the distribution of synaptic weights through the entire network. The roles of model parameters that affect the interplay between network structure and activity are elucidated. Finally, we propose two mathematical growth models, which are complementary, that capture the essence of the growth dynamics observed in simulations. In Chapter 5, we present an extension of the stochastic mapping that allows the possibility of neuronal cooperation. We demonstrate that synaptic topologies admitting stereotypical sequences can emerge in yet higher, biologically realistic levels of membrane potential variability when neurons cooperate to innervate shared targets. The structure that is most robust to the variability is that of a synfire chain. The principles of growth dynamics detailed in Chapter 4 are the same that sculpt the emergent synfire topologies. We conclude by discussing avenues for extensions of these results.

Network models of frequency modulated sweep detection.

PubMed

Skorheim, Steven; Razak, Khaleel; Bazhenov, Maxim

2014-01-01

Frequency modulated (FM) sweeps are common in species-specific vocalizations, including human speech. Auditory neurons selective for the direction and rate of frequency change in FM sweeps are present across species, but the synaptic mechanisms underlying such selectivity are only beginning to be understood. Even less is known about mechanisms of experience-dependent changes in FM sweep selectivity. We present three network models of synaptic mechanisms of FM sweep direction and rate selectivity that explains experimental data: (1) The 'facilitation' model contains frequency selective cells operating as coincidence detectors, summing up multiple excitatory inputs with different time delays. (2) The 'duration tuned' model depends on interactions between delayed excitation and early inhibition. The strength of delayed excitation determines the preferred duration. Inhibitory rebound can reinforce the delayed excitation. (3) The 'inhibitory sideband' model uses frequency selective inputs to a network of excitatory and inhibitory cells. The strength and asymmetry of these connections results in neurons responsive to sweeps in a single direction of sufficient sweep rate. Variations of these properties, can explain the diversity of rate-dependent direction selectivity seen across species. We show that the inhibitory sideband model can be trained using spike timing dependent plasticity (STDP) to develop direction selectivity from a non-selective network. These models provide a means to compare the proposed synaptic and spectrotemporal mechanisms of FM sweep processing and can be utilized to explore cellular mechanisms underlying experience- or training-dependent changes in spectrotemporal processing across animal models. Given the analogy between FM sweeps and visual motion, these models can serve a broader function in studying stimulus movement across sensory epithelia.

NeuroFlow: A General Purpose Spiking Neural Network Simulation Platform using Customizable Processors.

PubMed

Cheung, Kit; Schultz, Simon R; Luk, Wayne

2015-01-01

NeuroFlow is a scalable spiking neural network simulation platform for off-the-shelf high performance computing systems using customizable hardware processors such as Field-Programmable Gate Arrays (FPGAs). Unlike multi-core processors and application-specific integrated circuits, the processor architecture of NeuroFlow can be redesigned and reconfigured to suit a particular simulation to deliver optimized performance, such as the degree of parallelism to employ. The compilation process supports using PyNN, a simulator-independent neural network description language, to configure the processor. NeuroFlow supports a number of commonly used current or conductance based neuronal models such as integrate-and-fire and Izhikevich models, and the spike-timing-dependent plasticity (STDP) rule for learning. A 6-FPGA system can simulate a network of up to ~600,000 neurons and can achieve a real-time performance of 400,000 neurons. Using one FPGA, NeuroFlow delivers a speedup of up to 33.6 times the speed of an 8-core processor, or 2.83 times the speed of GPU-based platforms. With high flexibility and throughput, NeuroFlow provides a viable environment for large-scale neural network simulation.

NeuroFlow: A General Purpose Spiking Neural Network Simulation Platform using Customizable Processors

PubMed Central

Cheung, Kit; Schultz, Simon R.; Luk, Wayne

2016-01-01

NeuroFlow is a scalable spiking neural network simulation platform for off-the-shelf high performance computing systems using customizable hardware processors such as Field-Programmable Gate Arrays (FPGAs). Unlike multi-core processors and application-specific integrated circuits, the processor architecture of NeuroFlow can be redesigned and reconfigured to suit a particular simulation to deliver optimized performance, such as the degree of parallelism to employ. The compilation process supports using PyNN, a simulator-independent neural network description language, to configure the processor. NeuroFlow supports a number of commonly used current or conductance based neuronal models such as integrate-and-fire and Izhikevich models, and the spike-timing-dependent plasticity (STDP) rule for learning. A 6-FPGA system can simulate a network of up to ~600,000 neurons and can achieve a real-time performance of 400,000 neurons. Using one FPGA, NeuroFlow delivers a speedup of up to 33.6 times the speed of an 8-core processor, or 2.83 times the speed of GPU-based platforms. With high flexibility and throughput, NeuroFlow provides a viable environment for large-scale neural network simulation. PMID:26834542

The Achievement of Therapeutic Objectives Scale: Interrater Reliability and Sensitivity to Change in Short-Term Dynamic Psychotherapy and Cognitive Therapy

ERIC Educational Resources Information Center

Valen, Jakob; Ryum, Truls; Svartberg, Martin; Stiles, Tore C.; McCullough, Leigh

2011-01-01

This study examined interrater reliability and sensitivity to change of the Achievement of Therapeutic Objectives Scale (ATOS; McCullough, Larsen, et al., 2003) in short-term dynamic psychotherapy (STDP) and cognitive therapy (CT). The ATOS is a process scale originally developed to assess patients' achievements of treatment objectives in STDP,…

A Hybrid CMOS-Memristor Neuromorphic Synapse.

PubMed

Azghadi, Mostafa Rahimi; Linares-Barranco, Bernabe; Abbott, Derek; Leong, Philip H W

2017-04-01

Although data processing technology continues to advance at an astonishing rate, computers with brain-like processing capabilities still elude us. It is envisioned that such computers may be achieved by the fusion of neuroscience and nano-electronics to realize a brain-inspired platform. This paper proposes a high-performance nano-scale Complementary Metal Oxide Semiconductor (CMOS)-memristive circuit, which mimics a number of essential learning properties of biological synapses. The proposed synaptic circuit that is composed of memristors and CMOS transistors, alters its memristance in response to timing differences among its pre- and post-synaptic action potentials, giving rise to a family of Spike Timing Dependent Plasticity (STDP). The presented design advances preceding memristive synapse designs with regards to the ability to replicate essential behaviours characterised in a number of electrophysiological experiments performed in the animal brain, which involve higher order spike interactions. Furthermore, the proposed hybrid device CMOS area is estimated as [Formula: see text] in a [Formula: see text] process-this represents a factor of ten reduction in area with respect to prior CMOS art. The new design is integrated with silicon neurons in a crossbar array structure amenable to large-scale neuromorphic architectures and may pave the way for future neuromorphic systems with spike timing-dependent learning features. These systems are emerging for deployment in various applications ranging from basic neuroscience research, to pattern recognition, to Brain-Machine-Interfaces.

STDP Installs in Winner-Take-All Circuits an Online Approximation to Hidden Markov Model Learning

PubMed Central

Kappel, David; Nessler, Bernhard; Maass, Wolfgang

2014-01-01

In order to cross a street without being run over, we need to be able to extract very fast hidden causes of dynamically changing multi-modal sensory stimuli, and to predict their future evolution. We show here that a generic cortical microcircuit motif, pyramidal cells with lateral excitation and inhibition, provides the basis for this difficult but all-important information processing capability. This capability emerges in the presence of noise automatically through effects of STDP on connections between pyramidal cells in Winner-Take-All circuits with lateral excitation. In fact, one can show that these motifs endow cortical microcircuits with functional properties of a hidden Markov model, a generic model for solving such tasks through probabilistic inference. Whereas in engineering applications this model is adapted to specific tasks through offline learning, we show here that a major portion of the functionality of hidden Markov models arises already from online applications of STDP, without any supervision or rewards. We demonstrate the emergent computing capabilities of the model through several computer simulations. The full power of hidden Markov model learning can be attained through reward-gated STDP. This is due to the fact that these mechanisms enable a rejection sampling approximation to theoretically optimal learning. We investigate the possible performance gain that can be achieved with this more accurate learning method for an artificial grammar task. PMID:24675787

Control of Abnormal Synchronization in Neurological Disorders

PubMed Central

Popovych, Oleksandr V.; Tass, Peter A.

2014-01-01

In the nervous system, synchronization processes play an important role, e.g., in the context of information processing and motor control. However, pathological, excessive synchronization may strongly impair brain function and is a hallmark of several neurological disorders. This focused review addresses the question of how an abnormal neuronal synchronization can specifically be counteracted by invasive and non-invasive brain stimulation as, for instance, by deep brain stimulation for the treatment of Parkinson’s disease, or by acoustic stimulation for the treatment of tinnitus. On the example of coordinated reset (CR) neuromodulation, we illustrate how insights into the dynamics of complex systems contribute to successful model-based approaches, which use methods from synergetics, non-linear dynamics, and statistical physics, for the development of novel therapies for normalization of brain function and synaptic connectivity. Based on the intrinsic multistability of the neuronal populations induced by spike timing-dependent plasticity (STDP), CR neuromodulation utilizes the mutual interdependence between synaptic connectivity and dynamics of the neuronal networks in order to restore more physiological patterns of connectivity via desynchronization of neuronal activity. The very goal is to shift the neuronal population by stimulation from an abnormally coupled and synchronized state to a desynchronized regime with normalized synaptic connectivity, which significantly outlasts the stimulation cessation, so that long-lasting therapeutic effects can be achieved. PMID:25566174

Neuromodulation and Synaptic Plasticity for the Control of Fast Periodic Movement: Energy Efficiency in Coupled Compliant Joints via PCA.

PubMed

Stratmann, Philipp; Lakatos, Dominic; Albu-Schäffer, Alin

2016-01-01

There are multiple indications that the nervous system of animals tunes muscle output to exploit natural dynamics of the elastic locomotor system and the environment. This is an advantageous strategy especially in fast periodic movements, since the elastic elements store energy and increase energy efficiency and movement speed. Experimental evidence suggests that coordination among joints involves proprioceptive input and neuromodulatory influence originating in the brain stem. However, the neural strategies underlying the coordination of fast periodic movements remain poorly understood. Based on robotics control theory, we suggest that the nervous system implements a mechanism to accomplish coordination between joints by a linear coordinate transformation from the multi-dimensional space representing proprioceptive input at the joint level into a one-dimensional controller space. In this one-dimensional subspace, the movements of a whole limb can be driven by a single oscillating unit as simple as a reflex interneuron. The output of the oscillating unit is transformed back to joint space via the same transformation. The transformation weights correspond to the dominant principal component of the movement. In this study, we propose a biologically plausible neural network to exemplify that the central nervous system (CNS) may encode our controller design. Using theoretical considerations and computer simulations, we demonstrate that spike-timing-dependent plasticity (STDP) for the input mapping and serotonergic neuromodulation for the output mapping can extract the dominant principal component of sensory signals. Our simulations show that our network can reliably control mechanical systems of different complexity and increase the energy efficiency of ongoing cyclic movements. The proposed network is simple and consistent with previous biologic experiments. Thus, our controller could serve as a candidate to describe the neural control of fast, energy-efficient, periodic movements involving multiple coupled joints.

Neuromodulation and Synaptic Plasticity for the Control of Fast Periodic Movement: Energy Efficiency in Coupled Compliant Joints via PCA

PubMed Central

Stratmann, Philipp; Lakatos, Dominic; Albu-Schäffer, Alin

2016-01-01

There are multiple indications that the nervous system of animals tunes muscle output to exploit natural dynamics of the elastic locomotor system and the environment. This is an advantageous strategy especially in fast periodic movements, since the elastic elements store energy and increase energy efficiency and movement speed. Experimental evidence suggests that coordination among joints involves proprioceptive input and neuromodulatory influence originating in the brain stem. However, the neural strategies underlying the coordination of fast periodic movements remain poorly understood. Based on robotics control theory, we suggest that the nervous system implements a mechanism to accomplish coordination between joints by a linear coordinate transformation from the multi-dimensional space representing proprioceptive input at the joint level into a one-dimensional controller space. In this one-dimensional subspace, the movements of a whole limb can be driven by a single oscillating unit as simple as a reflex interneuron. The output of the oscillating unit is transformed back to joint space via the same transformation. The transformation weights correspond to the dominant principal component of the movement. In this study, we propose a biologically plausible neural network to exemplify that the central nervous system (CNS) may encode our controller design. Using theoretical considerations and computer simulations, we demonstrate that spike-timing-dependent plasticity (STDP) for the input mapping and serotonergic neuromodulation for the output mapping can extract the dominant principal component of sensory signals. Our simulations show that our network can reliably control mechanical systems of different complexity and increase the energy efficiency of ongoing cyclic movements. The proposed network is simple and consistent with previous biologic experiments. Thus, our controller could serve as a candidate to describe the neural control of fast, energy-efficient, periodic movements involving multiple coupled joints. PMID:27014051

Unsupervised heart-rate estimation in wearables with Liquid states and a probabilistic readout.

PubMed

Das, Anup; Pradhapan, Paruthi; Groenendaal, Willemijn; Adiraju, Prathyusha; Rajan, Raj Thilak; Catthoor, Francky; Schaafsma, Siebren; Krichmar, Jeffrey L; Dutt, Nikil; Van Hoof, Chris

2018-03-01

Heart-rate estimation is a fundamental feature of modern wearable devices. In this paper we propose a machine learning technique to estimate heart-rate from electrocardiogram (ECG) data collected using wearable devices. The novelty of our approach lies in (1) encoding spatio-temporal properties of ECG signals directly into spike train and using this to excite recurrently connected spiking neurons in a Liquid State Machine computation model; (2) a novel learning algorithm; and (3) an intelligently designed unsupervised readout based on Fuzzy c-Means clustering of spike responses from a subset of neurons (Liquid states), selected using particle swarm optimization. Our approach differs from existing works by learning directly from ECG signals (allowing personalization), without requiring costly data annotations. Additionally, our approach can be easily implemented on state-of-the-art spiking-based neuromorphic systems, offering high accuracy, yet significantly low energy footprint, leading to an extended battery-life of wearable devices. We validated our approach with CARLsim, a GPU accelerated spiking neural network simulator modeling Izhikevich spiking neurons with Spike Timing Dependent Plasticity (STDP) and homeostatic scaling. A range of subjects is considered from in-house clinical trials and public ECG databases. Results show high accuracy and low energy footprint in heart-rate estimation across subjects with and without cardiac irregularities, signifying the strong potential of this approach to be integrated in future wearable devices. Copyright © 2018 Elsevier Ltd. All rights reserved.

Unsupervised Learning in an Ensemble of Spiking Neural Networks Mediated by ITDP.

PubMed

Shim, Yoonsik; Philippides, Andrew; Staras, Kevin; Husbands, Phil

2016-10-01

We propose a biologically plausible architecture for unsupervised ensemble learning in a population of spiking neural network classifiers. A mixture of experts type organisation is shown to be effective, with the individual classifier outputs combined via a gating network whose operation is driven by input timing dependent plasticity (ITDP). The ITDP gating mechanism is based on recent experimental findings. An abstract, analytically tractable model of the ITDP driven ensemble architecture is derived from a logical model based on the probabilities of neural firing events. A detailed analysis of this model provides insights that allow it to be extended into a full, biologically plausible, computational implementation of the architecture which is demonstrated on a visual classification task. The extended model makes use of a style of spiking network, first introduced as a model of cortical microcircuits, that is capable of Bayesian inference, effectively performing expectation maximization. The unsupervised ensemble learning mechanism, based around such spiking expectation maximization (SEM) networks whose combined outputs are mediated by ITDP, is shown to perform the visual classification task well and to generalize to unseen data. The combined ensemble performance is significantly better than that of the individual classifiers, validating the ensemble architecture and learning mechanisms. The properties of the full model are analysed in the light of extensive experiments with the classification task, including an investigation into the influence of different input feature selection schemes and a comparison with a hierarchical STDP based ensemble architecture.

Unsupervised Learning in an Ensemble of Spiking Neural Networks Mediated by ITDP

PubMed Central

Staras, Kevin

2016-01-01

We propose a biologically plausible architecture for unsupervised ensemble learning in a population of spiking neural network classifiers. A mixture of experts type organisation is shown to be effective, with the individual classifier outputs combined via a gating network whose operation is driven by input timing dependent plasticity (ITDP). The ITDP gating mechanism is based on recent experimental findings. An abstract, analytically tractable model of the ITDP driven ensemble architecture is derived from a logical model based on the probabilities of neural firing events. A detailed analysis of this model provides insights that allow it to be extended into a full, biologically plausible, computational implementation of the architecture which is demonstrated on a visual classification task. The extended model makes use of a style of spiking network, first introduced as a model of cortical microcircuits, that is capable of Bayesian inference, effectively performing expectation maximization. The unsupervised ensemble learning mechanism, based around such spiking expectation maximization (SEM) networks whose combined outputs are mediated by ITDP, is shown to perform the visual classification task well and to generalize to unseen data. The combined ensemble performance is significantly better than that of the individual classifiers, validating the ensemble architecture and learning mechanisms. The properties of the full model are analysed in the light of extensive experiments with the classification task, including an investigation into the influence of different input feature selection schemes and a comparison with a hierarchical STDP based ensemble architecture. PMID:27760125

Relative age effects in Swiss talent development - a nationwide analysis of all sports.

PubMed

Romann, Michael; Rössler, Roland; Javet, Marie; Faude, Oliver

2018-09-01

Relative age effects (RAE) generate consistent participation inequalities and selection biases in sports. The study aimed to investigate RAE across all sports of the national Swiss talent development programme (STDP). In this study, 18 859 youth athletes (female N = 5353; mean age: 14.8 ± 2.5 y and male N = 13 506; mean age: 14.4 ± 2.4 y) in 70 sports who participated in the 2014 competitive season were evaluated. The sample was subdivided by sex and the national level selection (NLS, N = 2464). Odds ratios (ORs) of relative age quarters (Q1-Q4) and 95% confidence intervals (CI) were calculated. In STDP, small RAE were evident for females (OR 1.35 (95%-CI 1.24, 1.47)) and males (OR 1.84 (95%-CI 1.74, 1.95)). RAE were similar in female NLS athletes (OR 1.30 (95%-CI 1.08, 1.57)) and larger in male NLS athletes (OR 2.40 (95%-CI 1.42, 1.97)) compared to athletes in the lower selection level. In STDP, RAE are evident for both sexes in several sports with popular sports showing higher RAE. RAE were larger in males than females. A higher selection level showed higher RAE only for males. In Switzerland, talent identification and development should be considered as a long-term process.

Patient affect experiencing following therapist interventions in short-term dynamic psychotherapy.

PubMed

Town, Joel M; Hardy, Gillian E; McCullough, Leigh; Stride, Chris

2012-01-01

The aim of this research was to examine the relationship between therapist interventions and patient affect responses in Short-Term Dynamic Psychotherapy (STDP). The Affect Experiencing subscale from the Achievement of Therapeutic Objectives Scale (ATOS) was adapted to measure individual immediate affect experiencing (I-AES) responses in relation to therapist interventions coded within the preceding speaking turn, using the Psychotherapy Interaction Coding (PIC) system. A hierarchical linear modelling procedure was used to assess the change in affect experiencing and the relationship between affect experiencing and therapist interventions within and across segments of therapy. Process data was taken from six STDP cases; in total 24 hours of video-taped sessions were examined. Therapist interventions were found to account for a statistically significant amount of variance in immediate affect experiencing. Higher levels of immediate affect experiencing followed the therapist's use of Confrontation, Clarification and Support compared to Questions, Self-disclosure and Information interventions. Therapist Confrontation interventions that attempted to direct pressure towards either the visceral experience of affect or a patient's defences against feelings led to the highest levels of immediate affect experiencing. The type of therapist intervention accounts for a small but significant amount of the variation observed in a patient's immediate emotional arousal. Empirical findings support clinical theory in STDP that suggests strategic verbal responses promote the achievement of this specific therapeutic objective.

Role of the site of synaptic competition and the balance of learning forces for Hebbian encoding of probabilistic Markov sequences

PubMed Central

Bouchard, Kristofer E.; Ganguli, Surya; Brainard, Michael S.

2015-01-01

The majority of distinct sensory and motor events occur as temporally ordered sequences with rich probabilistic structure. Sequences can be characterized by the probability of transitioning from the current state to upcoming states (forward probability), as well as the probability of having transitioned to the current state from previous states (backward probability). Despite the prevalence of probabilistic sequencing of both sensory and motor events, the Hebbian mechanisms that mold synapses to reflect the statistics of experienced probabilistic sequences are not well understood. Here, we show through analytic calculations and numerical simulations that Hebbian plasticity (correlation, covariance, and STDP) with pre-synaptic competition can develop synaptic weights equal to the conditional forward transition probabilities present in the input sequence. In contrast, post-synaptic competition can develop synaptic weights proportional to the conditional backward probabilities of the same input sequence. We demonstrate that to stably reflect the conditional probability of a neuron's inputs and outputs, local Hebbian plasticity requires balance between competitive learning forces that promote synaptic differentiation and homogenizing learning forces that promote synaptic stabilization. The balance between these forces dictates a prior over the distribution of learned synaptic weights, strongly influencing both the rate at which structure emerges and the entropy of the final distribution of synaptic weights. Together, these results demonstrate a simple correspondence between the biophysical organization of neurons, the site of synaptic competition, and the temporal flow of information encoded in synaptic weights by Hebbian plasticity while highlighting the utility of balancing learning forces to accurately encode probability distributions, and prior expectations over such probability distributions. PMID:26257637

VLSI circuits implementing computational models of neocortical circuits.

PubMed

Wijekoon, Jayawan H B; Dudek, Piotr

2012-09-15

This paper overviews the design and implementation of three neuromorphic integrated circuits developed for the COLAMN ("Novel Computing Architecture for Cognitive Systems based on the Laminar Microcircuitry of the Neocortex") project. The circuits are implemented in a standard 0.35 μm CMOS technology and include spiking and bursting neuron models, and synapses with short-term (facilitating/depressing) and long-term (STDP and dopamine-modulated STDP) dynamics. They enable execution of complex nonlinear models in accelerated-time, as compared with biology, and with low power consumption. The neural dynamics are implemented using analogue circuit techniques, with digital asynchronous event-based input and output. The circuits provide configurable hardware blocks that can be used to simulate a variety of neural networks. The paper presents experimental results obtained from the fabricated devices, and discusses the advantages and disadvantages of the analogue circuit approach to computational neural modelling. Copyright © 2012 Elsevier B.V. All rights reserved.

The race to learn: spike timing and STDP can coordinate learning and recall in CA3.

PubMed

Nolan, Christopher R; Wyeth, Gordon; Milford, Michael; Wiles, Janet

2011-06-01

The CA3 region of the hippocampus has long been proposed as an autoassociative network performing pattern completion on known inputs. The dentate gyrus (DG) region is often proposed as a network performing the complementary function of pattern separation. Neural models of pattern completion and separation generally designate explicit learning phases to encode new information and assume an ideal fixed threshold at which to stop learning new patterns and begin recalling known patterns. Memory systems are significantly more complex in practice, with the degree of memory recall depending on context-specific goals. Here, we present our spike-timing separation and completion (STSC) model of the entorhinal cortex (EC), DG, and CA3 network, ascribing to each region a role similar to that in existing models but adding a temporal dimension by using a spiking neural network. Simulation results demonstrate that (a) spike-timing dependent plasticity in the EC-CA3 synapses provides a pattern completion ability without recurrent CA3 connections, (b) the race between activation of CA3 cells via EC-CA3 synapses and activation of the same cells via DG-CA3 synapses distinguishes novel from known inputs, and (c) modulation of the EC-CA3 synapses adjusts the learned versus test input similarity required to evoke a direct CA3 response prior to any DG activity, thereby adjusting the pattern completion threshold. These mechanisms suggest that spike timing can arbitrate between learning and recall based on the novelty of each individual input, ensuring control of the learn-recall decision resides in the same subsystem as the learned memories themselves. The proposed modulatory signal does not override this decision but biases the system toward either learning or recall. The model provides an explanation for empirical observations that a reduction in novelty produces a corresponding reduction in the latency of responses in CA3 and CA1. Copyright © 2010 Wiley-Liss, Inc.

Magnetic Tunnel Junction Based Long-Term Short-Term Stochastic Synapse for a Spiking Neural Network with On-Chip STDP Learning

NASA Astrophysics Data System (ADS)

Srinivasan, Gopalakrishnan; Sengupta, Abhronil; Roy, Kaushik

2016-07-01

Spiking Neural Networks (SNNs) have emerged as a powerful neuromorphic computing paradigm to carry out classification and recognition tasks. Nevertheless, the general purpose computing platforms and the custom hardware architectures implemented using standard CMOS technology, have been unable to rival the power efficiency of the human brain. Hence, there is a need for novel nanoelectronic devices that can efficiently model the neurons and synapses constituting an SNN. In this work, we propose a heterostructure composed of a Magnetic Tunnel Junction (MTJ) and a heavy metal as a stochastic binary synapse. Synaptic plasticity is achieved by the stochastic switching of the MTJ conductance states, based on the temporal correlation between the spiking activities of the interconnecting neurons. Additionally, we present a significance driven long-term short-term stochastic synapse comprising two unique binary synaptic elements, in order to improve the synaptic learning efficiency. We demonstrate the efficacy of the proposed synaptic configurations and the stochastic learning algorithm on an SNN trained to classify handwritten digits from the MNIST dataset, using a device to system-level simulation framework. The power efficiency of the proposed neuromorphic system stems from the ultra-low programming energy of the spintronic synapses.

Magnetic Tunnel Junction Based Long-Term Short-Term Stochastic Synapse for a Spiking Neural Network with On-Chip STDP Learning.

PubMed

Srinivasan, Gopalakrishnan; Sengupta, Abhronil; Roy, Kaushik

2016-07-13

Spiking Neural Networks (SNNs) have emerged as a powerful neuromorphic computing paradigm to carry out classification and recognition tasks. Nevertheless, the general purpose computing platforms and the custom hardware architectures implemented using standard CMOS technology, have been unable to rival the power efficiency of the human brain. Hence, there is a need for novel nanoelectronic devices that can efficiently model the neurons and synapses constituting an SNN. In this work, we propose a heterostructure composed of a Magnetic Tunnel Junction (MTJ) and a heavy metal as a stochastic binary synapse. Synaptic plasticity is achieved by the stochastic switching of the MTJ conductance states, based on the temporal correlation between the spiking activities of the interconnecting neurons. Additionally, we present a significance driven long-term short-term stochastic synapse comprising two unique binary synaptic elements, in order to improve the synaptic learning efficiency. We demonstrate the efficacy of the proposed synaptic configurations and the stochastic learning algorithm on an SNN trained to classify handwritten digits from the MNIST dataset, using a device to system-level simulation framework. The power efficiency of the proposed neuromorphic system stems from the ultra-low programming energy of the spintronic synapses.

Two New Real-Time PCR-based Surveillance Systems for “Candidatus Liberibacter” Species Detection

USDA-ARS?s Scientific Manuscript database

We developed two novel surveillance systems for “Candidatus Liberibacter” (CL) species detection and identification. The first system is called “single tube dual primer Taq-Man PCR” (STDP). The procedure involves two sequential rounds of PCR using the CL asiaticus species-specific outer and inner pr...

Role of the visual experience-dependent nascent proteome in neuronal plasticity

PubMed Central

Liu, Han-Hsuan; McClatchy, Daniel B; Schiapparelli, Lucio; Shen, Wanhua; Yates, John R

2018-01-01

Experience-dependent synaptic plasticity refines brain circuits during development. To identify novel protein synthesis-dependent mechanisms contributing to experience-dependent plasticity, we conducted a quantitative proteomic screen of the nascent proteome in response to visual experience in Xenopus optic tectum using bio-orthogonal metabolic labeling (BONCAT). We identified 83 differentially synthesized candidate plasticity proteins (CPPs). The CPPs form strongly interconnected networks and are annotated to a variety of biological functions, including RNA splicing, protein translation, and chromatin remodeling. Functional analysis of select CPPs revealed the requirement for eukaryotic initiation factor three subunit A (eIF3A), fused in sarcoma (FUS), and ribosomal protein s17 (RPS17) in experience-dependent structural plasticity in tectal neurons and behavioral plasticity in tadpoles. These results demonstrate that the nascent proteome is dynamic in response to visual experience and that de novo synthesis of machinery that regulates RNA splicing and protein translation is required for experience-dependent plasticity. PMID:29412139

Synapse-Centric Mapping of Cortical Models to the SpiNNaker Neuromorphic Architecture

PubMed Central

Knight, James C.; Furber, Steve B.

2016-01-01

While the adult human brain has approximately 8.8 × 1010 neurons, this number is dwarfed by its 1 × 1015 synapses. From the point of view of neuromorphic engineering and neural simulation in general this makes the simulation of these synapses a particularly complex problem. SpiNNaker is a digital, neuromorphic architecture designed for simulating large-scale spiking neural networks at speeds close to biological real-time. Current solutions for simulating spiking neural networks on SpiNNaker are heavily inspired by work on distributed high-performance computing. However, while SpiNNaker shares many characteristics with such distributed systems, its component nodes have much more limited resources and, as the system lacks global synchronization, the computation performed on each node must complete within a fixed time step. We first analyze the performance of the current SpiNNaker neural simulation software and identify several problems that occur when it is used to simulate networks of the type often used to model the cortex which contain large numbers of sparsely connected synapses. We then present a new, more flexible approach for mapping the simulation of such networks to SpiNNaker which solves many of these problems. Finally we analyze the performance of our new approach using both benchmarks, designed to represent cortical connectivity, and larger, functional cortical models. In a benchmark network where neurons receive input from 8000 STDP synapses, our new approach allows 4× more neurons to be simulated on each SpiNNaker core than has been previously possible. We also demonstrate that the largest plastic neural network previously simulated on neuromorphic hardware can be run in real time using our new approach: double the speed that was previously achieved. Additionally this network contains two types of plastic synapse which previously had to be trained separately but, using our new approach, can be trained simultaneously. PMID:27683540

An investigation of the inelastic behaviour of trabecular bone during the press-fit implantation of a tibial component in total knee arthroplasty.

PubMed

Kelly, N; Cawley, D T; Shannon, F J; McGarry, J P

2013-11-01

The stress distribution and plastic deformation of peri-prosthetic trabecular bone during press-fit tibial component implantation in total knee arthroplasty is investigated using experimental and finite element techniques. It is revealed that the computed stress distribution, implantation force and plastic deformation in the trabecular bone is highly dependent on the plasticity formulation implemented. By incorporating pressure dependent yielding using a crushable foam plasticity formulation to simulate the trabecular bone during implantation, highly localised stress concentrations and plastic deformation are computed at the bone-implant interface. If the pressure dependent yield is neglected using a traditional von Mises plasticity formulation, a significantly different stress distribution and implantation force is computed in the peri-prosthetic trabecular bone. The results of the study highlight the importance of: (i) simulating the insertion process of press-fit stem implantation; (ii) implementing a pressure dependent plasticity formulation, such as the crushable foam plasticity formulation, for the trabecular bone; (iii) incorporating friction at the implant-bone interface during stem insertion. Simulation of the press-fit implantation process with an appropriate pressure dependent plasticity formulation should be implemented in the design and assessment of arthroplasty prostheses. Copyright © 2013 IPEM. Published by Elsevier Ltd. All rights reserved.

Blocking c-Fos Expression Reveals the Role of Auditory Cortex Plasticity in Sound Frequency Discrimination Learning.

PubMed

de Hoz, Livia; Gierej, Dorota; Lioudyno, Victoria; Jaworski, Jacek; Blazejczyk, Magda; Cruces-Solís, Hugo; Beroun, Anna; Lebitko, Tomasz; Nikolaev, Tomasz; Knapska, Ewelina; Nelken, Israel; Kaczmarek, Leszek

2018-05-01

The behavioral changes that comprise operant learning are associated with plasticity in early sensory cortices as well as with modulation of gene expression, but the connection between the behavioral, electrophysiological, and molecular changes is only partially understood. We specifically manipulated c-Fos expression, a hallmark of learning-induced synaptic plasticity, in auditory cortex of adult mice using a novel approach based on RNA interference. Locally blocking c-Fos expression caused a specific behavioral deficit in a sound discrimination task, in parallel with decreased cortical experience-dependent plasticity, without affecting baseline excitability or basic auditory processing. Thus, c-Fos-dependent experience-dependent cortical plasticity is necessary for frequency discrimination in an operant behavioral task. Our results connect behavioral, molecular and physiological changes and demonstrate a role of c-Fos in experience-dependent plasticity and learning.

Deficient plasticity in the primary visual cortex of alpha-calcium/calmodulin-dependent protein kinase II mutant mice.

PubMed

Gordon, J A; Cioffi, D; Silva, A J; Stryker, M P

1996-09-01

The recent characterization of plasticity in the mouse visual cortex permits the use of mutant mice to investigate the cellular mechanisms underlying activity-dependent development. As calcium-dependent signaling pathways have been implicated in neuronal plasticity, we examined visual cortical plasticity in mice lacking the alpha-isoform of calcium/calmodulin-dependent protein kinase II (alpha CaMKII). In wild-type mice, brief occlusion of vision in one eye during a critical period reduces responses in the visual cortex. In half of the alpha CaMKII-deficient mice, visual cortical responses developed normally, but visual cortical plasticity was greatly diminished. After intensive training, spatial learning in the Morris water maze was severely impaired in a similar fraction of mutant animals. These data indicate that loss of alpha CaMKII results in a severe but variable defect in neuronal plasticity.

Discrete dislocation plasticity analysis of loading rate-dependent static friction.

PubMed

Song, H; Deshpande, V S; Van der Giessen, E

2016-08-01

From a microscopic point of view, the frictional force associated with the relative sliding of rough surfaces originates from deformation of the material in contact, by adhesion in the contact interface or both. We know that plastic deformation at the size scale of micrometres is not only dependent on the size of the contact, but also on the rate of deformation. Moreover, depending on its physical origin, adhesion can also be size and rate dependent, albeit different from plasticity. We present a two-dimensional model that incorporates both discrete dislocation plasticity inside a face-centred cubic crystal and adhesion in the interface to understand the rate dependence of friction caused by micrometre-size asperities. The friction strength is the outcome of the competition between adhesion and discrete dislocation plasticity. As a function of contact size, the friction strength contains two plateaus: at small contact length [Formula: see text], the onset of sliding is fully controlled by adhesion while for large contact length [Formula: see text], the friction strength approaches the size-independent plastic shear yield strength. The transition regime at intermediate contact size is a result of partial de-cohesion and size-dependent dislocation plasticity, and is determined by dislocation properties, interfacial properties as well as by the loading rate.

Dosage-dependent non-linear effect of L-dopa on human motor cortex plasticity.

PubMed

Monte-Silva, Katia; Liebetanz, David; Grundey, Jessica; Paulus, Walter; Nitsche, Michael A

2010-09-15

The neuromodulator dopamine affects learning and memory formation and their likely physiological correlates, long-term depression and potentiation, in animals and humans. It is known from animal experiments that dopamine exerts a dosage-dependent, inverted U-shaped effect on these functions. However, this has not been explored in humans so far. In order to reveal a non-linear dose-dependent effect of dopamine on cortical plasticity in humans, we explored the impact of 25, 100 and 200 mg of L-dopa on transcranial direct current (tDCS)-induced plasticity in twelve healthy human subjects. The primary motor cortex served as a model system, and plasticity was monitored by motor evoked potential amplitudes elicited by transcranial magnetic stimulation. As compared to placebo medication, low and high dosages of L-dopa abolished facilitatory as well as inhibitory plasticity, whereas the medium dosage prolonged inhibitory plasticity, and turned facilitatory plasticity into inhibition. Thus the results show clear non-linear, dosage-dependent effects of dopamine on both facilitatory and inhibitory plasticity, and support the assumption of the importance of a specific dosage of dopamine optimally suited to improve plasticity. This might be important for the therapeutic application of dopaminergic agents, especially for rehabilitative purposes, and explain some opposing results in former studies.

Oxygen transport in congenital heart disease: influence of fetal hemoglobin, red cell pH, and 2,3-diphosphoglycerate.

PubMed

Versmold, H T; Linderkamp, C; Döhlemann, C; Riegel, K P

1976-06-01

In 48 individuals (age 1 day to 13 years) with congenital heart disease, blood oxygen transport function was studied in order to evaluate adaptive changes in shunt hypoxemia and to investigate the in vivo regulation of erythrocyte 2, 3-diphosphoglycerate concentration (RBC 2, 3-DPG) in the presence of fetal hemoglobin (HbF). Arterial pO2 and oxygen content, oxygen capacity, acid base status, oxygen affinity, HbF fraction, plasma pH, red cell pH, and RBC 2, 3-DPG were determined. During the first 50 days of life values of standard P50 (stdP50) (37, pH 7.4), actual in vivo P50 (actP50), RBC 2, 3-DPG, O2 capacity, arterial plasma pH, and red cell pH were scattered around the normal range, although tending to low values for stdP50 and arterial plasma pH and to high values for O2 capacity. After the third month, stdP50 actP50, RBC 2, 3-DPG, O2 capacity, and red cell pH were found to be elevated. Plasma pH and actP50 were scattered around the normal range (Figs. 1 and 2). Intraerythrocytic pH in hypoxemic infants was increased compared with normal children when related to plasma pH (Fig. 3). A close to normal intraerythrocytic pH was therefore found in the hypoxemic infants with low plasma pH, and an increased intraerythrocytic pH in the hypoxemic children with normal plasma pH (Fig. 1). A significant negative correlation exists between erythrocyte H+ ion and 2, 3-DPG concentration (Fig. 5); regression constants derived from data at high (mean 47%) and low (mean 9%) fractions of HbF are not significantly different (Regression Equations 8 and 11 in Table 1). Thus, the known difference in 2, 3-DPG binding to fetal or adult deoxyhemoglobin does not measurably influence the erythrocyte 2, 3-DPG concentration, indicating that in vivo the 2, 3-DPG synthesis in hypoxia is virtually regulated by the erythrocyte pH, which in turn is determined by plasma pH and the oxygenation state of hemoglobin.

Multilevel Resistance Programming in Conductive Bridge Resistive Memory

NASA Astrophysics Data System (ADS)

Mahalanabis, Debayan

This work focuses on the existence of multiple resistance states in a type of emerging non-volatile resistive memory device known commonly as Programmable Metallization Cell (PMC) or Conductive Bridge Random Access Memory (CBRAM), which can be important for applications such as multi-bit memory as well as non-volatile logic and neuromorphic computing. First, experimental data from small signal, quasi-static and pulsed mode electrical characterization of such devices are presented which clearly demonstrate the inherent multi-level resistance programmability property in CBRAM devices. A physics based analytical CBRAM compact model is then presented which simulates the ion-transport dynamics and filamentary growth mechanism that causes resistance change in such devices. Simulation results from the model are fitted to experimental dynamic resistance switching characteristics. The model designed using Verilog-a language is computation-efficient and can be integrated with industry standard circuit simulation tools for design and analysis of hybrid circuits involving both CMOS and CBRAM devices. Three main circuit applications for CBRAM devices are explored in this work. Firstly, the susceptibility of CBRAM memory arrays to single event induced upsets is analyzed via compact model simulation and experimental heavy ion testing data that show possibility of both high resistance to low resistance and low resistance to high resistance transitions due to ion strikes. Next, a non-volatile sense amplifier based flip-flop architecture is proposed which can help make leakage power consumption negligible by allowing complete shutdown of power supply while retaining its output data in CBRAM devices. Reliability and energy consumption of the flip-flop circuit for different CBRAM low resistance levels and supply voltage values are analyzed and compared to CMOS designs. Possible extension of this architecture for threshold logic function computation using the CBRAM devices as re-configurable resistive weights is also discussed. Lastly, Spike timing dependent plasticity (STDP) based gradual resistance change behavior in CBRAM device fabricated in back-end-of-line on a CMOS die containing integrate and fire CMOS neuron circuits is demonstrated for the first time which indicates the feasibility of using CBRAM devices as electronic synapses in spiking neural network hardware implementations for non-Boolean neuromorphic computing.

Gap effects on leaf traits of tropical rainforest trees differing in juvenile light requirement.

PubMed

Houter, Nico C; Pons, Thijs L

2014-05-01

The relationships of 16 leaf traits and their plasticity with the dependence of tree species on gaps for regeneration (gap association index; GAI) were examined in a Neotropical rainforest. Young saplings of 24 species with varying GAI were grown under a closed canopy, in a medium-sized and in a large gap, thus capturing the full range of plasticity with respect to canopy openness. Structural, biomechanical, chemical and photosynthetic traits were measured. At the chloroplast level, the chlorophyll a/b ratio and plasticity in this variable were not related to the GAI. However, plasticity in total carotenoids per unit chlorophyll was larger in shade-tolerant species. At the leaf level, leaf mass per unit area (LMA) decreased with the GAI under the closed canopy and in the medium gap, but did not significantly decrease with the GAI in the large gap. This was a reflection of the larger plasticity in LMA and leaf thickness of gap-dependent species. The well-known opposite trends in LMA for adaptation and acclimation to high irradiance in evergreen tropical trees were thus not invariably found. Although leaf strength was dependent on LMA and thickness, plasticity in this trait was not related to the GAI. Photosynthetic capacity expressed on each basis increased with the GAI, but the large plasticity in these traits was not clearly related to the GAI. Although gap-dependent species tended to have a greater plasticity overall, as evident from a principle component analysis, leaf traits of gap-dependent species are thus not invariably more phenotypically plastic.

Sleep, Plasticity and the Pathophysiology of Neurodevelopmental Disorders: The Potential Roles of Protein Synthesis and Other Cellular Processes

PubMed Central

Picchioni, Dante; Reith, R. Michelle; Nadel, Jeffrey L.; Smith, Carolyn B.

2014-01-01

Sleep is important for neural plasticity, and plasticity underlies sleep-dependent memory consolidation. It is widely appreciated that protein synthesis plays an essential role in neural plasticity. Studies of sleep-dependent memory and sleep-dependent plasticity have begun to examine alterations in these functions in populations with neurological and psychiatric disorders. Such an approach acknowledges that disordered sleep may have functional consequences during wakefulness. Although neurodevelopmental disorders are not considered to be sleep disorders per se, recent data has revealed that sleep abnormalities are among the most prevalent and common symptoms and may contribute to the progression of these disorders. The main goal of this review is to highlight the role of disordered sleep in the pathology of neurodevelopmental disorders and to examine some potential mechanisms by which sleep-dependent plasticity may be altered. We will also briefly attempt to extend the same logic to the other end of the developmental spectrum and describe a potential role of disordered sleep in the pathology of neurodegenerative diseases. We conclude by discussing ongoing studies that might provide a more integrative approach to the study of sleep, plasticity, and neurodevelopmental disorders. PMID:24839550

Regulating Critical Period Plasticity: Insight from the Visual System to Fear Circuitry for Therapeutic Interventions

PubMed Central

Nabel, Elisa M.; Morishita, Hirofumi

2013-01-01

Early temporary windows of heightened brain plasticity called critical periods developmentally sculpt neural circuits and contribute to adult behavior. Regulatory mechanisms of visual cortex development – the preeminent model of experience-dependent critical period plasticity-actively limit adult plasticity and have proved fruitful therapeutic targets to reopen plasticity and rewire faulty visual system connections later in life. Interestingly, these molecular mechanisms have been implicated in the regulation of plasticity in other functions beyond vision. Applying mechanistic understandings of critical period plasticity in the visual cortex to fear circuitry may provide a conceptual framework for developing novel therapeutic tools to mitigate aberrant fear responses in post traumatic stress disorder. In this review, we turn to the model of experience-dependent visual plasticity to provide novel insights for the mechanisms regulating plasticity in the fear system. Fear circuitry, particularly fear memory erasure, also undergoes age-related changes in experience-dependent plasticity. We consider the contributions of molecular brakes that halt visual critical period plasticity to circuitry underlying fear memory erasure. A major molecular brake in the visual cortex, perineuronal net formation, recently has been identified in the development of fear systems that are resilient to fear memory erasure. The roles of other molecular brakes, myelin-related Nogo receptor signaling and Lynx family proteins – endogenous inhibitors for nicotinic acetylcholine receptor, are explored in the context of fear memory plasticity. Such fear plasticity regulators, including epigenetic effects, provide promising targets for therapeutic interventions. PMID:24273519

Laminar distribution of cholinergic- and serotonergic-dependent plasticity within kitten visual cortex.

PubMed

Kojic, L; Gu, Q; Douglas, R M; Cynader, M S

2001-02-28

Both cholinergic and serotonergic modulatory projections to mammalian striate cortex have been demonstrated to be involved in the regulation of postnatal plasticity, and a striking alteration in the number and intracortical distribution of cholinergic and serotonergic receptors takes place during the critical period for cortical plasticity. As well, agonists of cholinergic and serotonergic receptors have been demonstrated to facilitate induction of long-term synaptic plasticity in visual cortical slices supporting their involvement in the control of activity-dependent plasticity. We recorded field potentials from layers 4 and 2/3 in visual cortex slices of 60--80 day old kittens after white matter stimulation, before and after a period of high frequency stimulation (HFS), in the absence or presence of either cholinergic or serotonergic agonists. At these ages, the HFS protocol alone almost never induced long-term changes of synaptic plasticity in either layers 2/3 or 4. In layer 2/3, agonist stimulation of m1 receptors facilitated induction of long-term potentiation (LTP) with HFS stimulation, while the activation of serotonergic receptors had only a modest effect. By contrast, a strong serotonin-dependent LTP facilitation and insignificant muscarinic effects were observed after HFS within layer 4. The results show that receptor-dependent laminar stratification of synaptic modifiability occurs in the cortex at these ages. This plasticity may underly a control system gating the experience-dependent changes of synaptic organization within developing visual cortex.

Learning to learn – intrinsic plasticity as a metaplasticity mechanism for memory formation

PubMed Central

Sehgal, Megha; Song, Chenghui; Ehlers, Vanessa L.; Moyer, James R.

2013-01-01

“Use it or lose it” is a popular adage often associated with use-dependent enhancement of cognitive abilities. Much research has focused on understanding exactly how the brain changes as a function of experience. Such experience-dependent plasticity involves both structural and functional alterations that contribute to adaptive behaviors, such as learning and memory, as well as maladaptive behaviors, including anxiety disorders, phobias, and posttraumatic stress disorder. With the advancing age of our population, understanding how use-dependent plasticity changes across the lifespan may also help to promote healthy brain aging. A common misconception is that such experience-dependent plasticity (e.g., associative learning) is synonymous with synaptic plasticity. Other forms of plasticity also play a critical role in shaping adaptive changes within the nervous system, including intrinsic plasticity – a change in the intrinsic excitability of a neuron. Intrinsic plasticity can result from a change in the number, distribution or activity of various ion channels located throughout the neuron. Here, we review evidence that intrinsic plasticity is an important and evolutionarily conserved neural correlate of learning. Intrinsic plasticity acts as a metaplasticity mechanism by lowering the threshold for synaptic changes. Thus, learning-related intrinsic changes can facilitate future synaptic plasticity and learning. Such intrinsic changes can impact the allocation of a memory trace within a brain structure, and when compromised, can contribute to cognitive decline during the aging process. This unique role of intrinsic excitability can provide insight into how memories are formed and, more interestingly, how neurons that participate in a memory trace are selected. Most importantly, modulation of intrinsic excitability can allow for regulation of learning ability – this can prevent or provide treatment for cognitive decline not only in patients with clinical disorders but also in the aging population. PMID:23871744

Maladaptive spinal plasticity opposes spinal learning and recovery in spinal cord injury

PubMed Central

Ferguson, Adam R.; Huie, J. Russell; Crown, Eric D.; Baumbauer, Kyle M.; Hook, Michelle A.; Garraway, Sandra M.; Lee, Kuan H.; Hoy, Kevin C.; Grau, James W.

2012-01-01

Synaptic plasticity within the spinal cord has great potential to facilitate recovery of function after spinal cord injury (SCI). Spinal plasticity can be induced in an activity-dependent manner even without input from the brain after complete SCI. A mechanistic basis for these effects is provided by research demonstrating that spinal synapses have many of the same plasticity mechanisms that are known to underlie learning and memory in the brain. In addition, the lumbar spinal cord can sustain several forms of learning and memory, including limb-position training. However, not all spinal plasticity promotes recovery of function. Central sensitization of nociceptive (pain) pathways in the spinal cord may emerge in response to various noxious inputs, demonstrating that plasticity within the spinal cord may contribute to maladaptive pain states. In this review we discuss interactions between adaptive and maladaptive forms of activity-dependent plasticity in the spinal cord below the level of SCI. The literature demonstrates that activity-dependent plasticity within the spinal cord must be carefully tuned to promote adaptive spinal training. Prior work from our group has shown that stimulation that is delivered in a limb position-dependent manner or on a fixed interval can induce adaptive plasticity that promotes future spinal cord learning and reduces nociceptive hyper-reactivity. On the other hand, stimulation that is delivered in an unsynchronized fashion, such as randomized electrical stimulation or peripheral skin injuries, can generate maladaptive spinal plasticity that undermines future spinal cord learning, reduces recovery of locomotor function, and promotes nociceptive hyper-reactivity after SCI. We review these basic phenomena, how these findings relate to the broader spinal plasticity literature, discuss the cellular and molecular mechanisms, and finally discuss implications of these and other findings for improved rehabilitative therapies after SCI. PMID:23087647

Learning of Precise Spike Times with Homeostatic Membrane Potential Dependent Synaptic Plasticity.

PubMed

Albers, Christian; Westkott, Maren; Pawelzik, Klaus

2016-01-01

Precise spatio-temporal patterns of neuronal action potentials underly e.g. sensory representations and control of muscle activities. However, it is not known how the synaptic efficacies in the neuronal networks of the brain adapt such that they can reliably generate spikes at specific points in time. Existing activity-dependent plasticity rules like Spike-Timing-Dependent Plasticity are agnostic to the goal of learning spike times. On the other hand, the existing formal and supervised learning algorithms perform a temporally precise comparison of projected activity with the target, but there is no known biologically plausible implementation of this comparison. Here, we propose a simple and local unsupervised synaptic plasticity mechanism that is derived from the requirement of a balanced membrane potential. Since the relevant signal for synaptic change is the postsynaptic voltage rather than spike times, we call the plasticity rule Membrane Potential Dependent Plasticity (MPDP). Combining our plasticity mechanism with spike after-hyperpolarization causes a sensitivity of synaptic change to pre- and postsynaptic spike times which can reproduce Hebbian spike timing dependent plasticity for inhibitory synapses as was found in experiments. In addition, the sensitivity of MPDP to the time course of the voltage when generating a spike allows MPDP to distinguish between weak (spurious) and strong (teacher) spikes, which therefore provides a neuronal basis for the comparison of actual and target activity. For spatio-temporal input spike patterns our conceptually simple plasticity rule achieves a surprisingly high storage capacity for spike associations. The sensitivity of the MPDP to the subthreshold membrane potential during training allows robust memory retrieval after learning even in the presence of activity corrupted by noise. We propose that MPDP represents a biophysically plausible mechanism to learn temporal target activity patterns.

Learning of Precise Spike Times with Homeostatic Membrane Potential Dependent Synaptic Plasticity

PubMed Central

Albers, Christian; Westkott, Maren; Pawelzik, Klaus

2016-01-01

Precise spatio-temporal patterns of neuronal action potentials underly e.g. sensory representations and control of muscle activities. However, it is not known how the synaptic efficacies in the neuronal networks of the brain adapt such that they can reliably generate spikes at specific points in time. Existing activity-dependent plasticity rules like Spike-Timing-Dependent Plasticity are agnostic to the goal of learning spike times. On the other hand, the existing formal and supervised learning algorithms perform a temporally precise comparison of projected activity with the target, but there is no known biologically plausible implementation of this comparison. Here, we propose a simple and local unsupervised synaptic plasticity mechanism that is derived from the requirement of a balanced membrane potential. Since the relevant signal for synaptic change is the postsynaptic voltage rather than spike times, we call the plasticity rule Membrane Potential Dependent Plasticity (MPDP). Combining our plasticity mechanism with spike after-hyperpolarization causes a sensitivity of synaptic change to pre- and postsynaptic spike times which can reproduce Hebbian spike timing dependent plasticity for inhibitory synapses as was found in experiments. In addition, the sensitivity of MPDP to the time course of the voltage when generating a spike allows MPDP to distinguish between weak (spurious) and strong (teacher) spikes, which therefore provides a neuronal basis for the comparison of actual and target activity. For spatio-temporal input spike patterns our conceptually simple plasticity rule achieves a surprisingly high storage capacity for spike associations. The sensitivity of the MPDP to the subthreshold membrane potential during training allows robust memory retrieval after learning even in the presence of activity corrupted by noise. We propose that MPDP represents a biophysically plausible mechanism to learn temporal target activity patterns. PMID:26900845

A study of microindentation hardness tests by mechanism-based strain gradient plasticity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Y.; Xue, Z.; Gao, H.

2000-08-01

We recently proposed a theory of mechanism-based strain gradient (MSG) plasticity to account for the size dependence of plastic deformation at micron- and submicron-length scales. The MSG plasticity theory connects micron-scale plasticity to dislocation theories via a multiscale, hierarchical framework linking Taylor's dislocation hardening model to strain gradient plasticity. Here we show that the theory of MSG plasticity, when used to study micro-indentation, indeed reproduces the linear dependence observed in experiments, thus providing an important self-consistent check of the theory. The effects of pileup, sink-in, and the radius of indenter tip have been taken into account in the indentation model.more » In accomplishing this objective, we have generalized the MSG plasticity theory to include the elastic deformation in the hierarchical framework. (c) 2000 Materials Research Society.« less

Neuromodulatory influence of norepinephrine during developmental experience-dependent plasticity.

PubMed

Golovin, Randall M; Ward, Nicholas J

2016-07-01

Critical periods represent phases of development during which neuronal circuits and their responses can be readily shaped by stimuli. Experience-dependent plasticity that occurs within these critical periods can be influenced in many ways; however, Shepard et al. (J Neurosci 35: 2432-2437, 2015) recently singled out norepinephrine as an essential driver of this plasticity within the auditory cortex. This work provides novel insight into the mechanisms of critical period plasticity and challenges previous conceptions that a functional redundancy exists between noradrenergic and cholinergic influences on cortical plasticity. Copyright © 2016 the American Physiological Society.

Softening and Hardening of Alloys of the Al - Zn System Under Plastic Deformation

NASA Astrophysics Data System (ADS)

Skvortsov, A. I.; Polev, V. V.

2017-11-01

The proportion of hardening and softening under plastic deformation at room temperature in metals and alloys of the Al - Zn system has been studied as dependent on the regime of preliminary heat treatment. The influence of the strain rate on the dependence of alloy hardness on the degree of plastic deformation is estimated.

Associative memory of phase-coded spatiotemporal patterns in leaky Integrate and Fire networks.

PubMed

Scarpetta, Silvia; Giacco, Ferdinando

2013-04-01

We study the collective dynamics of a Leaky Integrate and Fire network in which precise relative phase relationship of spikes among neurons are stored, as attractors of the dynamics, and selectively replayed at different time scales. Using an STDP-based learning process, we store in the connectivity several phase-coded spike patterns, and we find that, depending on the excitability of the network, different working regimes are possible, with transient or persistent replay activity induced by a brief signal. We introduce an order parameter to evaluate the similarity between stored and recalled phase-coded pattern, and measure the storage capacity. Modulation of spiking thresholds during replay changes the frequency of the collective oscillation or the number of spikes per cycle, keeping preserved the phases relationship. This allows a coding scheme in which phase, rate and frequency are dissociable. Robustness with respect to noise and heterogeneity of neurons parameters is studied, showing that, since dynamics is a retrieval process, neurons preserve stable precise phase relationship among units, keeping a unique frequency of oscillation, even in noisy conditions and with heterogeneity of internal parameters of the units.

Arc restores juvenile plasticity in adult mouse visual cortex

PubMed Central

Jenks, Kyle R.; Kim, Taekeun; Pastuzyn, Elissa D.; Okuno, Hiroyuki; Taibi, Andrew V.; Bear, Mark F.

2017-01-01

The molecular basis for the decline in experience-dependent neural plasticity over age remains poorly understood. In visual cortex, the robust plasticity induced in juvenile mice by brief monocular deprivation during the critical period is abrogated by genetic deletion of Arc, an activity-dependent regulator of excitatory synaptic modification. Here, we report that augmenting Arc expression in adult mice prolongs juvenile-like plasticity in visual cortex, as assessed by recordings of ocular dominance (OD) plasticity in vivo. A distinguishing characteristic of juvenile OD plasticity is the weakening of deprived-eye responses, believed to be accounted for by the mechanisms of homosynaptic long-term depression (LTD). Accordingly, we also found increased LTD in visual cortex of adult mice with augmented Arc expression and impaired LTD in visual cortex of juvenile mice that lack Arc or have been treated in vivo with a protein synthesis inhibitor. Further, we found that although activity-dependent expression of Arc mRNA does not change with age, expression of Arc protein is maximal during the critical period and declines in adulthood. Finally, we show that acute augmentation of Arc expression in wild-type adult mouse visual cortex is sufficient to restore juvenile-like plasticity. Together, our findings suggest a unifying molecular explanation for the age- and activity-dependent modulation of synaptic sensitivity to deprivation. PMID:28790183

Unified pre- and postsynaptic long-term plasticity enables reliable and flexible learning.

PubMed

Costa, Rui Ponte; Froemke, Robert C; Sjöström, P Jesper; van Rossum, Mark Cw

2015-08-26

Although it is well known that long-term synaptic plasticity can be expressed both pre- and postsynaptically, the functional consequences of this arrangement have remained elusive. We show that spike-timing-dependent plasticity with both pre- and postsynaptic expression develops receptive fields with reduced variability and improved discriminability compared to postsynaptic plasticity alone. These long-term modifications in receptive field statistics match recent sensory perception experiments. Moreover, learning with this form of plasticity leaves a hidden postsynaptic memory trace that enables fast relearning of previously stored information, providing a cellular substrate for memory savings. Our results reveal essential roles for presynaptic plasticity that are missed when only postsynaptic expression of long-term plasticity is considered, and suggest an experience-dependent distribution of pre- and postsynaptic strength changes.

Mecp2 Mediates Experience-Dependent Transcriptional Upregulation of Ryanodine Receptor Type-3.

PubMed

Torres, Rodrigo F; Hidalgo, Cecilia; Kerr, Bredford

2017-01-01

Mecp2 is a DNA methylation reader that plays a critical role in experience-dependent plasticity. Increasing evidence supports a role for epigenetic modifications in activity-induced gene expression. Hence, candidate genes related to such phenomena are of great interest. Ryanodine receptors are intracellular calcium channels that contribute to hippocampal synaptic plasticity, dendritic spine remodeling, and participate in learning and memory processes. Here we exposed mice to the enriched environment (EE) paradigm, which through increased stimulation induces experience dependent-plasticity, to explore a role for methyl-cytosines, and Mecp2 in directing Ryanodine receptor 3 ( Ryr3 ) transcriptional activity. EE induced a hippocampal-specific increase in the methylation of discrete cytosines located at a Ryr3 isoform promoter; chromatin immunoprecipitation experiments revealed that EE increased Mecp2 binding to this Ryr3 isoform promoter. Interestingly, the experimental paradigm induced robust Ryr3 upregulation, accompanied by miR132 -dependent suppression of p250GAP , a pathway driving synaptogenesis. In contrast to WT mice, Mecp2-null mice showed diminished levels of Ryr3 and displayed impaired EE-induced Ryr3 upregulation, compromising miR132 dependent suppression of p250GAP and experience-dependent structural plasticity. Based on these results, we propose that Mecp2 acts as a transcriptional activator of Ryr3 , contributing to experience-dependent plasticity.

Sleep and protein synthesis-dependent synaptic plasticity: impacts of sleep loss and stress

PubMed Central

Grønli, Janne; Soulé, Jonathan; Bramham, Clive R.

2014-01-01

Sleep has been ascribed a critical role in cognitive functioning. Several lines of evidence implicate sleep in the consolidation of synaptic plasticity and long-term memory. Stress disrupts sleep while impairing synaptic plasticity and cognitive performance. Here, we discuss evidence linking sleep to mechanisms of protein synthesis-dependent synaptic plasticity and synaptic scaling. We then consider how disruption of sleep by acute and chronic stress may impair these mechanisms and degrade sleep function. PMID:24478645

Plasticity-related genes in brain development and amygdala-dependent learning.

PubMed

Ehrlich, D E; Josselyn, S A

2016-01-01

Learning about motivationally important stimuli involves plasticity in the amygdala, a temporal lobe structure. Amygdala-dependent learning involves a growing number of plasticity-related signaling pathways also implicated in brain development, suggesting that learning-related signaling in juveniles may simultaneously influence development. Here, we review the pleiotropic functions in nervous system development and amygdala-dependent learning of a signaling pathway that includes brain-derived neurotrophic factor (BDNF), extracellular signaling-related kinases (ERKs) and cyclic AMP-response element binding protein (CREB). Using these canonical, plasticity-related genes as an example, we discuss the intersection of learning-related and developmental plasticity in the immature amygdala, when aversive and appetitive learning may influence the developmental trajectory of amygdala function. We propose that learning-dependent activation of BDNF, ERK and CREB signaling in the immature amygdala exaggerates and accelerates neural development, promoting amygdala excitability and environmental sensitivity later in life. © 2015 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.

Fragile X Mental Retardation Protein Is Required to Maintain Visual Conditioning-Induced Behavioral Plasticity by Limiting Local Protein Synthesis

PubMed Central

Liu, Han-Hsuan

2016-01-01

Fragile X mental retardation protein (FMRP) is thought to regulate neuronal plasticity by limiting dendritic protein synthesis, but direct demonstration of a requirement for FMRP control of local protein synthesis during behavioral plasticity is lacking. Here we tested whether FMRP knockdown in Xenopus optic tectum affects local protein synthesis in vivo and whether FMRP knockdown affects protein synthesis-dependent visual avoidance behavioral plasticity. We tagged newly synthesized proteins by incorporation of the noncanonical amino acid azidohomoalanine and visualized them with fluorescent noncanonical amino acid tagging (FUNCAT). Visual conditioning and FMRP knockdown produce similar increases in FUNCAT in tectal neuropil. Induction of visual conditioning-dependent behavioral plasticity occurs normally in FMRP knockdown animals, but plasticity degrades over 24 h. These results indicate that FMRP affects visual conditioning-induced local protein synthesis and is required to maintain the visual conditioning-induced behavioral plasticity. SIGNIFICANCE STATEMENT Fragile X syndrome (FXS) is the most common form of inherited intellectual disability. Exaggerated dendritic protein synthesis resulting from loss of fragile X mental retardation protein (FMRP) is thought to underlie cognitive deficits in FXS, but no direct evidence has demonstrated that FMRP-regulated dendritic protein synthesis affects behavioral plasticity in intact animals. Xenopus tadpoles exhibit a visual avoidance behavior that improves with visual conditioning in a protein synthesis-dependent manner. We showed that FMRP knockdown and visual conditioning dramatically increase protein synthesis in neuronal processes. Furthermore, induction of visual conditioning-dependent behavioral plasticity occurs normally after FMRP knockdown, but performance rapidly deteriorated in the absence of FMRP. These studies show that FMRP negatively regulates local protein synthesis and is required to maintain visual conditioning-induced behavioral plasticity in vivo. PMID:27383604

Fragile X Mental Retardation Protein Is Required to Maintain Visual Conditioning-Induced Behavioral Plasticity by Limiting Local Protein Synthesis.

PubMed

Liu, Han-Hsuan; Cline, Hollis T

2016-07-06

Fragile X mental retardation protein (FMRP) is thought to regulate neuronal plasticity by limiting dendritic protein synthesis, but direct demonstration of a requirement for FMRP control of local protein synthesis during behavioral plasticity is lacking. Here we tested whether FMRP knockdown in Xenopus optic tectum affects local protein synthesis in vivo and whether FMRP knockdown affects protein synthesis-dependent visual avoidance behavioral plasticity. We tagged newly synthesized proteins by incorporation of the noncanonical amino acid azidohomoalanine and visualized them with fluorescent noncanonical amino acid tagging (FUNCAT). Visual conditioning and FMRP knockdown produce similar increases in FUNCAT in tectal neuropil. Induction of visual conditioning-dependent behavioral plasticity occurs normally in FMRP knockdown animals, but plasticity degrades over 24 h. These results indicate that FMRP affects visual conditioning-induced local protein synthesis and is required to maintain the visual conditioning-induced behavioral plasticity. Fragile X syndrome (FXS) is the most common form of inherited intellectual disability. Exaggerated dendritic protein synthesis resulting from loss of fragile X mental retardation protein (FMRP) is thought to underlie cognitive deficits in FXS, but no direct evidence has demonstrated that FMRP-regulated dendritic protein synthesis affects behavioral plasticity in intact animals. Xenopus tadpoles exhibit a visual avoidance behavior that improves with visual conditioning in a protein synthesis-dependent manner. We showed that FMRP knockdown and visual conditioning dramatically increase protein synthesis in neuronal processes. Furthermore, induction of visual conditioning-dependent behavioral plasticity occurs normally after FMRP knockdown, but performance rapidly deteriorated in the absence of FMRP. These studies show that FMRP negatively regulates local protein synthesis and is required to maintain visual conditioning-induced behavioral plasticity in vivo. Copyright © 2016 the authors 0270-6474/16/367325-15$15.00/0.

The microglial fractalkine receptor is not required for activity-dependent plasticity in the mouse visual system.

PubMed

Lowery, Rebecca L; Tremblay, Marie-Eve; Hopkins, Brittany E; Majewska, Ania K

2017-11-01

Microglia have recently been implicated as key regulators of activity-dependent plasticity, where they contribute to the removal of inappropriate or excess synapses. However, the molecular mechanisms that mediate this microglial function are still not well understood. Although multiple studies have implicated fractalkine signaling as a mediator of microglia-neuron communications during synaptic plasticity, it is unclear whether this is a universal signaling mechanism or whether its role is limited to specific brain regions and stages of the lifespan. Here, we examined whether fractalkine signaling mediates microglial contributions to activity-dependent plasticity in the developing and adolescent visual system. Using genetic ablation of fractalkine's cognate receptor, CX 3 CR1, and both ex vivo characterization and in vivo imaging in mice, we examined whether fractalkine signaling is required for microglial dynamics and modulation of synapses, as well as activity-dependent plasticity in the visual system. We did not find a role for fractalkine signaling in mediating microglial properties during visual plasticity. Ablation of CX 3 CR1 had no effect on microglial density, distribution, morphology, or motility, in either adolescent or young adult mice across brain regions that include the visual cortex. Ablation of CX 3 CR1 also had no effect on baseline synaptic turnover or contact dynamics between microglia and neurons. Finally, we found that fractalkine signaling is not required for either early or late forms of activity-dependent visual system plasticity. These findings suggest that fractalkine is not a universal regulator of synaptic plasticity, but rather has heterogeneous roles in specific brain regions and life stages. © 2017 Wiley Periodicals, Inc.

Manipulation of BDNF signaling modifies the experience-dependent plasticity induced by pure tone exposure during the critical period in the primary auditory cortex.

PubMed

Anomal, Renata; de Villers-Sidani, Etienne; Merzenich, Michael M; Panizzutti, Rogerio

2013-01-01

Sensory experience powerfully shapes cortical sensory representations during an early developmental "critical period" of plasticity. In the rat primary auditory cortex (A1), the experience-dependent plasticity is exemplified by significant, long-lasting distortions in frequency representation after mere exposure to repetitive frequencies during the second week of life. In the visual system, the normal unfolding of critical period plasticity is strongly dependent on the elaboration of brain-derived neurotrophic factor (BDNF), which promotes the establishment of inhibition. Here, we tested the hypothesis that BDNF signaling plays a role in the experience-dependent plasticity induced by pure tone exposure during the critical period in the primary auditory cortex. Elvax resin implants filled with either a blocking antibody against BDNF or the BDNF protein were placed on the A1 of rat pups throughout the critical period window. These pups were then exposed to 7 kHz pure tone for 7 consecutive days and their frequency representations were mapped. BDNF blockade completely prevented the shaping of cortical tuning by experience and resulted in poor overall frequency tuning in A1. By contrast, BDNF infusion on the developing A1 amplified the effect of 7 kHz tone exposure compared to control. These results indicate that BDNF signaling participates in the experience-dependent plasticity induced by pure tone exposure during the critical period in A1.

Neuralized1 activates CPEB3: a function for nonproteolytic ubiquitin in synaptic plasticity and memory storage.

PubMed

Pavlopoulos, Elias; Trifilieff, Pierre; Chevaleyre, Vivien; Fioriti, Luana; Zairis, Sakellarios; Pagano, Andrew; Malleret, Gaël; Kandel, Eric R

2011-12-09

The cytoplasmic polyadenylation element-binding protein 3 (CPEB3), a regulator of local protein synthesis, is the mouse homolog of ApCPEB, a functional prion protein in Aplysia. Here, we provide evidence that CPEB3 is activated by Neuralized1, an E3 ubiquitin ligase. In hippocampal cultures, CPEB3 activated by Neuralized1-mediated ubiquitination leads both to the growth of new dendritic spines and to an increase of the GluA1 and GluA2 subunits of AMPA receptors, two CPEB3 targets essential for synaptic plasticity. Conditional overexpression of Neuralized1 similarly increases GluA1 and GluA2 and the number of spines and functional synapses in the hippocampus and is reflected in enhanced hippocampal-dependent memory and synaptic plasticity. By contrast, inhibition of Neuralized1 reduces GluA1 and GluA2 levels and impairs hippocampal-dependent memory and synaptic plasticity. These results suggest a model whereby Neuralized1-dependent ubiquitination facilitates hippocampal plasticity and hippocampal-dependent memory storage by modulating the activity of CPEB3 and CPEB3-dependent protein synthesis and synapse formation. Copyright © 2011 Elsevier Inc. All rights reserved.

Mecp2 Mediates Experience-Dependent Transcriptional Upregulation of Ryanodine Receptor Type-3

PubMed Central

Torres, Rodrigo F.; Hidalgo, Cecilia; Kerr, Bredford

2017-01-01

Mecp2 is a DNA methylation reader that plays a critical role in experience-dependent plasticity. Increasing evidence supports a role for epigenetic modifications in activity-induced gene expression. Hence, candidate genes related to such phenomena are of great interest. Ryanodine receptors are intracellular calcium channels that contribute to hippocampal synaptic plasticity, dendritic spine remodeling, and participate in learning and memory processes. Here we exposed mice to the enriched environment (EE) paradigm, which through increased stimulation induces experience dependent-plasticity, to explore a role for methyl-cytosines, and Mecp2 in directing Ryanodine receptor 3 (Ryr3) transcriptional activity. EE induced a hippocampal-specific increase in the methylation of discrete cytosines located at a Ryr3 isoform promoter; chromatin immunoprecipitation experiments revealed that EE increased Mecp2 binding to this Ryr3 isoform promoter. Interestingly, the experimental paradigm induced robust Ryr3 upregulation, accompanied by miR132-dependent suppression of p250GAP, a pathway driving synaptogenesis. In contrast to WT mice, Mecp2-null mice showed diminished levels of Ryr3 and displayed impaired EE-induced Ryr3 upregulation, compromising miR132 dependent suppression of p250GAP and experience-dependent structural plasticity. Based on these results, we propose that Mecp2 acts as a transcriptional activator of Ryr3, contributing to experience-dependent plasticity. PMID:28659760

Endocrine mediated phenotypic plasticity: condition-dependent effects of juvenile hormone on dominance and fertility of wasp queens.

PubMed

Tibbetts, Elizabeth A; Izzo, Amanda S

2009-11-01

There has been increasing interest in the mechanisms that mediate behavioral and physiological plasticity across individuals with similar genotypes. Some of the most dramatic plasticity is found within and between social insect castes. For example, Polistes wasp queens can nest alone, dominate a group of cooperative queens, or act as worker-like subordinates who rarely reproduce. Previous work suggests that condition-dependent endocrine responses may play a role in plasticity between castes in the hymenoptera. Here, we test whether condition-dependent endocrine responses influence plasticity within castes in the wasp Polistes dominulus. We experimentally manipulate juvenile hormone (JH) titers in nest-founding queens and assess whether JH mediates variation in behavior and physiology. JH generally increased dominance and fertility of queens, but JH's effects were not uniform across individuals. JH had a stronger effect on the dominance and fertility of large individuals and individuals with facial patterns advertising high quality than on the dominance and fertility of small individuals and those advertising low quality. These results demonstrate that JH has condition-dependent effects. As such, they clarify how JH can mediate different behaviors in well nourished queens and poorly nourished workers. Many Polistes queens nest cooperatively with other queens, so condition-dependent hormonal responses provide a mechanism for queens to adaptively allocate energy based on their probability of successfully becoming the dominant queen. Research on the endocrine basis of plasticity often focuses on variation in endocrine titers alone. However, differential endocrine responses are likely to be a widespread mechanism mediating behavioral and physiological plasticity.

Emergence of Slow Collective Oscillations in Neural Networks with Spike-Timing Dependent Plasticity

NASA Astrophysics Data System (ADS)

Mikkelsen, Kaare; Imparato, Alberto; Torcini, Alessandro

2013-05-01

The collective dynamics of excitatory pulse coupled neurons with spike-timing dependent plasticity is studied. The introduction of spike-timing dependent plasticity induces persistent irregular oscillations between strongly and weakly synchronized states, reminiscent of brain activity during slow-wave sleep. We explain the oscillations by a mechanism, the Sisyphus Effect, caused by a continuous feedback between the synaptic adjustments and the coherence in the neural firing. Due to this effect, the synaptic weights have oscillating equilibrium values, and this prevents the system from relaxing into a stationary macroscopic state.

Learning-dependent plasticity in human auditory cortex during appetitive operant conditioning.

PubMed

Puschmann, Sebastian; Brechmann, André; Thiel, Christiane M

2013-11-01

Animal experiments provide evidence that learning to associate an auditory stimulus with a reward causes representational changes in auditory cortex. However, most studies did not investigate the temporal formation of learning-dependent plasticity during the task but rather compared auditory cortex receptive fields before and after conditioning. We here present a functional magnetic resonance imaging study on learning-related plasticity in the human auditory cortex during operant appetitive conditioning. Participants had to learn to associate a specific category of frequency-modulated tones with a reward. Only participants who learned this association developed learning-dependent plasticity in left auditory cortex over the course of the experiment. No differential responses to reward predicting and nonreward predicting tones were found in auditory cortex in nonlearners. In addition, learners showed similar learning-induced differential responses to reward-predicting and nonreward-predicting tones in the ventral tegmental area and the nucleus accumbens, two core regions of the dopaminergic neurotransmitter system. This may indicate a dopaminergic influence on the formation of learning-dependent plasticity in auditory cortex, as it has been suggested by previous animal studies. Copyright © 2012 Wiley Periodicals, Inc.

Activity-Dependent Downscaling of Subthreshold Synaptic Inputs during Slow-Wave-Sleep-like Activity In Vivo.

PubMed

González-Rueda, Ana; Pedrosa, Victor; Feord, Rachael C; Clopath, Claudia; Paulsen, Ole

2018-03-21

Activity-dependent synaptic plasticity is critical for cortical circuit refinement. The synaptic homeostasis hypothesis suggests that synaptic connections are strengthened during wake and downscaled during sleep; however, it is not obvious how the same plasticity rules could explain both outcomes. Using whole-cell recordings and optogenetic stimulation of presynaptic input in urethane-anesthetized mice, which exhibit slow-wave-sleep (SWS)-like activity, we show that synaptic plasticity rules are gated by cortical dynamics in vivo. While Down states support conventional spike timing-dependent plasticity, Up states are biased toward depression such that presynaptic stimulation alone leads to synaptic depression, while connections contributing to postsynaptic spiking are protected against this synaptic weakening. We find that this novel activity-dependent and input-specific downscaling mechanism has two important computational advantages: (1) improved signal-to-noise ratio, and (2) preservation of previously stored information. Thus, these synaptic plasticity rules provide an attractive mechanism for SWS-related synaptic downscaling and circuit refinement. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

Myosin IIb-dependent Regulation of Actin Dynamics Is Required for N-Methyl-D-aspartate Receptor Trafficking during Synaptic Plasticity.

PubMed

Bu, Yunfei; Wang, Ning; Wang, Shaoli; Sheng, Tao; Tian, Tian; Chen, Linlin; Pan, Weiwei; Zhu, Minsheng; Luo, Jianhong; Lu, Wei

2015-10-16

N-Methyl-d-aspartate receptor (NMDAR) synaptic incorporation changes the number of NMDARs at synapses and is thus critical to various NMDAR-dependent brain functions. To date, the molecules involved in NMDAR trafficking and the underlying mechanisms are poorly understood. Here, we report that myosin IIb is an essential molecule in NMDAR synaptic incorporation during PKC- or θ burst stimulation-induced synaptic plasticity. Moreover, we demonstrate that myosin light chain kinase (MLCK)-dependent actin reorganization contributes to NMDAR trafficking. The findings from additional mutual occlusion experiments demonstrate that PKC and MLCK share a common signaling pathway in NMDAR-mediated synaptic regulation. Because myosin IIb is the primary substrate of MLCK and can regulate actin dynamics during synaptic plasticity, we propose that the MLCK- and myosin IIb-dependent regulation of actin dynamics is required for NMDAR trafficking during synaptic plasticity. This study provides important insights into a mechanical framework for understanding NMDAR trafficking associated with synaptic plasticity. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

Endocannabinoid signaling is required for development and critical period plasticity of the whisker map in somatosensory cortex

PubMed Central

Li, Lu; Bender, Kevin J.; Drew, Patrick J.; Jadhav, Shantanu P.; Sylwestrak, Emily; Feldman, Daniel E.

2009-01-01

Summary Type 1 cannabinoid (CB1) receptors mediate widespread synaptic plasticity, but how this contributes to systems-level plasticity and development in vivo is unclear. We tested whether CB1 signaling is required for development and plasticity of the whisker map in rat somatosensory cortex. Treatment with the CB1 antagonist AM251 during an early critical period for layer (L) 2/3 development (beginning postnatal day [P] 12–16) disrupted whisker map development, leading to inappropriate whisker tuning in L2/3 column edges and a blurred map. Early AM251 treatment also prevented experience-dependent plasticity in L2/3, including deprivation-induced synapse weakening and weakening of deprived whisker responses. CB1 blockade after P25 did not disrupt map development or plasticity. AM251 had no acute effect on sensory-evoked spiking, and only modestly affected field potentials, suggesting that plasticity effects were not secondary to gross activity changes. These findings implicate CB1-dependent plasticity in systems-level development and early postnatal plasticity of the whisker map. PMID:19945395

Studies on the effect of storage time and plasticizers on the structural variations in thermoplastic starch.

PubMed

Schmitt, H; Guidez, A; Prashantha, K; Soulestin, J; Lacrampe, M F; Krawczak, P

2015-01-22

Starch was combined with plasticizers such as glycerol, sorbitol, glycerol/sorbitol and urea/ethanolamine blends by means of high shear extrusion process to prepare thermoplastic starch (TPS). Effect of storage time and plasticizers on the structural stability of melt processed TPS was investigated. Morphological observation, X-ray diffraction (XRD) and Fourier transform infrared (FTIR) spectroscopy reveal that melt extrusion process is efficient in transforming granular starch into a plasticized starch for all plasticizer compositions. XRD analysis highlights major changes in the microstructure of plasticized starch, and dependence of crystalline type and degree of crystallinity mainly on the plasticizer composition and storage time. Dynamical mechanical analysis (DMA) yields a decrease of the peak intensity of loss factor with aging time. The effect of ageing on tensile strength also appears to be highly dependent on the plasticizer composition. Thus, through different plasticizer combinations and ageing, starch-based materials with significant differences in tensile properties can be obtained, which may be tuned to meet the requirements of a wide range of applications. Copyright © 2014 Elsevier Ltd. All rights reserved.

Age-Dependent Glutamate Induction of Synaptic Plasticity in Cultured Hippocampal Neurons

ERIC Educational Resources Information Center

Ivenshitz, Miriam; Segal, Menahem; Sapoznik, Stav

2006-01-01

A common denominator for the induction of morphological and functional plasticity in cultured hippocampal neurons involves the activation of excitatory synapses. We now demonstrate massive morphological plasticity in mature cultured hippocampal neurons caused by a brief exposure to glutamate. This plasticity involves a slow, 70%-80% increase in…

T-type calcium channels in synaptic plasticity

PubMed Central

Lambert, Régis C.

2017-01-01

ABSTRACT The role of T-type calcium currents is rarely considered in the extensive literature covering the mechanisms of long-term synaptic plasticity. This situation reflects the lack of suitable T-type channel antagonists that till recently has hampered investigations of the functional roles of these channels. However, with the development of new pharmacological and genetic tools, a clear involvement of T-type channels in synaptic plasticity is starting to emerge. Here, we review a number of studies showing that T-type channels participate to numerous homo- and hetero-synaptic plasticity mechanisms that involve different molecular partners and both pre- and post-synaptic modifications. The existence of T-channel dependent and independent plasticity at the same synapse strongly suggests a subcellular localization of these channels and their partners that allows specific interactions. Moreover, we illustrate the functional importance of T-channel dependent synaptic plasticity in neocortex and thalamus. PMID:27653665

State of the Science White Paper: Effects of Plastics Pollution on Aquatic Life and Aquatic-Dependent Wildlife

EPA Pesticide Factsheets

This document is a state-of-the-science review – one that summarizes available scientific information on the effects of chemicals associated with plastic pollution and their potential impacts on aquatic life and aquatic-dependent wildlife.

Activity-dependent plasticity in spinal cord injury

PubMed Central

Lynskey, James V.; Belanger, Adam; Jung, Ranu

2008-01-01

The adult mammalian central nervous system (CNS) is capable of considerable plasticity, both in health and disease. After spinal neurotrauma, the degrees and extent of neuroplasticity and recovery depend on multiple factors, including the level and extent of injury, postinjury medical and surgical care, and rehabilitative interventions. Rehabilitation strategies focus less on repairing lost connections and more on influencing CNS plasticity for regaining function. Current evidence indicates that strategies for rehabilitation, including passive exercise, active exercise with some voluntary control, and use of neuroprostheses, can enhance sensorimotor recovery after spinal cord injury (SCI) by promoting adaptive structural and functional plasticity while mitigating maladaptive changes at multiple levels of the neuraxis. In this review, we will discuss CNS plasticity that occurs both spontaneously after SCI and in response to rehabilitative therapies. PMID:18566941

Temperature dependence of plastic scintillators

NASA Astrophysics Data System (ADS)

Peralta, L.

2018-03-01

Plastic scintillator detectors have been studied as dosimeters, since they provide a cost-effective alternative to conventional ionization chambers. Several articles have reported undesired response dependencies on beam energy and temperature, which provides the motivation to determine appropriate correction factors. In this work, we studied the light yield temperature dependency of four plastic scintillators, BCF-10, BCF-60, BC-404, RP-200A and two clear fibers, BCF-98 and SK-80. Measurements were made using a 50 kVp X-ray beam to produce the scintillation and/or radioluminescence signal. The 0 to 40 °C temperature range was scanned for each scintillator, and temperature coefficients were obtained.

Internal state variable plasticity-damage modeling of AISI 4140 steel including microstructure-property relations: temperature and strain rate effects

NASA Astrophysics Data System (ADS)

Nacif el Alaoui, Reda

Mechanical structure-property relations have been quantified for AISI 4140 steel. under different strain rates and temperatures. The structure-property relations were used. to calibrate a microstructure-based internal state variable plasticity-damage model for. monotonic tension, compression and torsion plasticity, as well as damage evolution. Strong stress state and temperature dependences were observed for the AISI 4140 steel. Tension tests on three different notched Bridgman specimens were undertaken to study. the damage-triaxiality dependence for model validation purposes. Fracture surface. analysis was performed using Scanning Electron Microscopy (SEM) to quantify the void. nucleation and void sizes in the different specimens. The stress-strain behavior exhibited. a fairly large applied stress state (tension, compression dependence, and torsion), a. moderate temperature dependence, and a relatively small strain rate dependence.

The Role of CREB, SRF, and MEF2 in Activity-Dependent Neuronal Plasticity in the Visual Cortex.

PubMed

Pulimood, Nisha S; Rodrigues, Wandilson Dos Santos; Atkinson, Devon A; Mooney, Sandra M; Medina, Alexandre E

2017-07-12

The transcription factors CREB (cAMP response element binding factor), SRF (serum response factor), and MEF2 (myocyte enhancer factor 2) play critical roles in the mechanisms underlying neuronal plasticity. However, the role of the activation of these transcription factors in the different components of plasticity in vivo is not well known. In this study, we tested the role of CREB, SRF, and MEF2 in ocular dominance plasticity (ODP), a paradigm of activity-dependent neuronal plasticity in the visual cortex. These three proteins bind to the synaptic activity response element (SARE), an enhancer sequence found upstream of many plasticity-related genes (Kawashima et al., 2009; Rodríguez-Tornos et al., 2013), and can act cooperatively to express Arc , a gene required for ODP (McCurry et al., 2010). We used viral-mediated gene transfer to block the transcription function of CREB, SRF, and MEF2 in the visual cortex, and measured visually evoked potentials in awake male and female mice before and after a 7 d monocular deprivation, which allowed us to examine both the depression component (Dc-ODP) and potentiation component (Pc-ODP) of plasticity independently. We found that CREB, SRF, and MEF2 are all required for ODP, but have differential effects on Dc-ODP and Pc-ODP. CREB is necessary for both Dc-ODP and Pc-ODP, whereas SRF and MEF2 are only needed for Dc-ODP. This finding supports previous reports implicating SRF and MEF2 in long-term depression (required for Dc-ODP), and CREB in long-term potentiation (required for Pc-ODP). SIGNIFICANCE STATEMENT Activity-dependent neuronal plasticity is the cellular basis for learning and memory, and it is crucial for the refinement of neuronal circuits during development. Identifying the mechanisms of activity-dependent neuronal plasticity is crucial to finding therapeutic interventions in the myriad of disorders where it is disrupted, such as Fragile X syndrome, Rett syndrome, epilepsy, major depressive disorder, and autism spectrum disorder. Transcription factors are essential nuclear proteins that trigger the expression of gene programs required for long-term functional and structural plasticity changes. Our results elucidate the specific role of the transcription factors CREB, SRF, and MEF2 in the depression and potentiation components of ODP in vivo , therefore better informing future attempts to find therapeutic targets for diseases where activity-dependent plasticity is disrupted. Copyright © 2017 the authors 0270-6474/17/376628-10$15.00/0.

The Role of CREB, SRF, and MEF2 in Activity-Dependent Neuronal Plasticity in the Visual Cortex

PubMed Central

Rodrigues, Wandilson dos Santos; Mooney, Sandra M.

2017-01-01

The transcription factors CREB (cAMP response element binding factor), SRF (serum response factor), and MEF2 (myocyte enhancer factor 2) play critical roles in the mechanisms underlying neuronal plasticity. However, the role of the activation of these transcription factors in the different components of plasticity in vivo is not well known. In this study, we tested the role of CREB, SRF, and MEF2 in ocular dominance plasticity (ODP), a paradigm of activity-dependent neuronal plasticity in the visual cortex. These three proteins bind to the synaptic activity response element (SARE), an enhancer sequence found upstream of many plasticity-related genes (Kawashima et al., 2009; Rodríguez-Tornos et al., 2013), and can act cooperatively to express Arc, a gene required for ODP (McCurry et al., 2010). We used viral-mediated gene transfer to block the transcription function of CREB, SRF, and MEF2 in the visual cortex, and measured visually evoked potentials in awake male and female mice before and after a 7 d monocular deprivation, which allowed us to examine both the depression component (Dc-ODP) and potentiation component (Pc-ODP) of plasticity independently. We found that CREB, SRF, and MEF2 are all required for ODP, but have differential effects on Dc-ODP and Pc-ODP. CREB is necessary for both Dc-ODP and Pc-ODP, whereas SRF and MEF2 are only needed for Dc-ODP. This finding supports previous reports implicating SRF and MEF2 in long-term depression (required for Dc-ODP), and CREB in long-term potentiation (required for Pc-ODP). SIGNIFICANCE STATEMENT Activity-dependent neuronal plasticity is the cellular basis for learning and memory, and it is crucial for the refinement of neuronal circuits during development. Identifying the mechanisms of activity-dependent neuronal plasticity is crucial to finding therapeutic interventions in the myriad of disorders where it is disrupted, such as Fragile X syndrome, Rett syndrome, epilepsy, major depressive disorder, and autism spectrum disorder. Transcription factors are essential nuclear proteins that trigger the expression of gene programs required for long-term functional and structural plasticity changes. Our results elucidate the specific role of the transcription factors CREB, SRF, and MEF2 in the depression and potentiation components of ODP in vivo, therefore better informing future attempts to find therapeutic targets for diseases where activity-dependent plasticity is disrupted. PMID:28607167

Conceptualizing withdrawal-induced escalation of alcohol self-administration as a learned, plasticity-dependent process

PubMed Central

Walker, Brendan M.

2013-01-01

This article represents one of five contributions focusing on the topic “Plasticity and neuroadaptive responses within the extended amygdala in response to chronic or excessive alcohol exposure” that were developed by awardees participating in the Young Investigator Award Symposium at the “Alcoholism and Stress: A Framework for Future Treatment Strategies” conference in Volterra, Italy on May 3–6, 2011 that was organized/chaired by Drs. Antonio Noronha and Fulton Crews and sponsored by the National Institute on Alcohol Abuse and Alcoholism. This review discusses the dependence-induced neuroadaptations in affective systems that provide a basis for negative reinforcement learning and presents evidence demonstrating that escalated alcohol consumption during withdrawal is a learned, plasticity-dependent process. The review concludes by identifying changes within extended amygdala dynorphin/kappa-opioid receptor systems that could serve as the foundation for the occurrence of negative reinforcement processes. While some evidence contained herein may be specific to alcohol dependence-related learning and plasticity, much of the information will be of relevance to any addictive disorder involving negative reinforcement mechanisms. Collectively, the information presented within this review provides a framework to assess the negative reinforcing effects of alcohol in a manner that distinguishes neuroadaptations produced by chronic alcohol exposure from the actual plasticity that is associated with negative reinforcement learning in dependent organisms. PMID:22459874

Recycling of plastic: accounting of greenhouse gases and global warming contributions.

PubMed

Astrup, Thomas; Fruergaard, Thilde; Christensen, Thomas H

2009-11-01

Major greenhouse gas (GHG) emissions related to plastic waste recycling were evaluated with respect to three management alternatives: recycling of clean, single-type plastic, recycling of mixed/contaminated plastic, and use of plastic waste as fuel in industrial processes. Source-separated plastic waste was received at a material recovery facility (MRF) and processed for granulation and subsequent downstream use. In the three alternatives, plastic was assumed to be substituting virgin plastic in new products, wood in low-strength products (outdoor furniture, fences, etc.), and coal or fuel oil in the case of energy utilization. GHG accounting was organized in terms of indirect upstream emissions (e.g. provision of energy, fuels, and materials), direct emissions at the MRF (e.g. fuel combustion), and indirect downstream emissions (e.g. avoided emissions from production of virgin plastic, wood, or coal/oil). Combined, upstream and direct emissions were estimated to be roughly between 5 and 600 kg CO(2)-eq. tonne( -1) of plastic waste depending on treatment at the MRF and CO(2) emissions from electricity production. Potential downstream savings arising from substitution of virgin plastic, wood, and energy fuels were estimated to be around 60- 1600 kg CO(2)-eq. tonne( -1) of plastic waste depending on substitution ratios and CO(2) emissions from electricity production. Based on the reviewed data, it was concluded that substitution of virgin plastic should be preferred. If this is not viable due to a mixture of different plastic types and/or contamination, the plastic should be used for energy utilization. Recycling of plastic waste for substitution of other materials such as wood provided no savings with respect to global warming.

Morphofunctional Experience-Dependent Plasticity in the Honeybee Brain

ERIC Educational Resources Information Center

Andrione, Mara; Timberlake, Benjamin F.; Vallortigara, Giorgio; Antolini, Renzo; Haase, Albrecht

2017-01-01

Repeated or prolonged exposure to an odorant without any positive or negative reinforcement produces experience-dependent plasticity, which results in habituation and latent inhibition. In the honeybee ("Apis mellifera"), it has been demonstrated that, even if the absolute neural representation of an odor in the primary olfactory center,…

NR2B-dependent plasticity of adult-born granule cells is necessary for context discrimination.

PubMed

Kheirbek, Mazen A; Tannenholz, Lindsay; Hen, René

2012-06-20

Adult-generated granule cells (GCs) in the dentate gyrus (DG) exhibit a period of heightened plasticity 4-6 weeks postmitosis. However, the functional contribution of this critical window of plasticity to hippocampal neurogenesis and behavior remains unknown. Here, we show that deletion of NR2B-containing NMDA receptors from adult-born GCs impairs a neurogenesis-dependent form of LTP in the DG and reduces dendritic complexity of adult-born GCs, but does not impact their survival. Mice in which the NR2B-containing NMDA receptor was deleted from adult-born GCs did not differ from controls in baseline anxiety-like behavior or discrimination of very different contexts, but were impaired in discrimination of highly similar contexts. These results indicate that NR2B-dependent plasticity of adult-born GCs is necessary for fine contextual discrimination and is consistent with their proposed role in pattern separation.

CCR5 is a suppressor for cortical plasticity and hippocampal learning and memory

PubMed Central

Zhou, Miou; Greenhill, Stuart; Huang, Shan; Silva, Tawnie K; Sano, Yoshitake; Wu, Shumin; Cai, Ying; Nagaoka, Yoshiko; Sehgal, Megha; Cai, Denise J; Lee, Yong-Seok; Fox, Kevin; Silva, Alcino J

2016-01-01

Although the role of CCR5 in immunity and in HIV infection has been studied widely, its role in neuronal plasticity, learning and memory is not understood. Here, we report that decreasing the function of CCR5 increases MAPK/CREB signaling, long-term potentiation (LTP), and hippocampus-dependent memory in mice, while neuronal CCR5 overexpression caused memory deficits. Decreasing CCR5 function in mouse barrel cortex also resulted in enhanced spike timing dependent plasticity and consequently, dramatically accelerated experience-dependent plasticity. These results suggest that CCR5 is a powerful suppressor for plasticity and memory, and CCR5 over-activation by viral proteins may contribute to HIV-associated cognitive deficits. Consistent with this hypothesis, the HIV V3 peptide caused LTP, signaling and memory deficits that were prevented by Ccr5 knockout or knockdown. Overall, our results demonstrate that CCR5 plays an important role in neuroplasticity, learning and memory, and indicate that CCR5 has a role in the cognitive deficits caused by HIV. DOI: http://dx.doi.org/10.7554/eLife.20985.001 PMID:27996938

Nonlinear dielectric spectroscopy in a fragile plastic crystal

NASA Astrophysics Data System (ADS)

Michl, M.; Bauer, Th.; Lunkenheimer, P.; Loidl, A.

2016-03-01

In this work we provide a thorough examination of the nonlinear dielectric properties of a succinonitrile-glutaronitrile mixture, representing one of the rare examples of a plastic crystal with fragile glassy dynamics. The detected alteration of the complex dielectric permittivity under high fields can be explained considering the heterogeneous nature of glassy dynamics and a field-induced variation of entropy. While the first mechanism was also found in structural glass formers, the latter effect seems to be more pronounced in plastic crystals. Moreover, the third harmonic component of the dielectric susceptibility is reported, revealing a hump-like spectral shape as predicted, e.g., within a model considering cooperative molecular dynamics. If assuming the validity of this model, one can deduce the temperature dependence of the number of correlated molecules Ncorr from these data. In accord with the fragile nature of the glass transition in this plastic crystal, we obtain a relatively strong temperature dependence of Ncorr, in contrast to the much weaker temperature dependence in plastic-crystalline cyclo-octanol, whose glass transition is of strong nature.

[Experimental determination of the time-dependent extent of after-burning with reference to possibilities of the plastic surgery reconstruction of 3d degree burns].

PubMed

Bäumer, F; Henrich, H A; Ussmüller, J

1986-02-01

The present experiments try to answer the question as to the time-dependent extent of the after-burning process after full-thickness burn (third degree). For an early plastic surgical treatment it was of interest to determine the most early time of escharotomy. The time-dependent spreading of the after-burning area reached its maximum five days after the burn injury. The after-burning area was marked by intravenous injections of Patentblau which caused distinct intravital colouring. Subsequently no further progress could be observed. In the present experiments we suggest this time as the earliest time for plastic covering in case it would be dependent upon the end of the after-burning process.

Cognitive plasticity as a moderator of functional dependency in elderly patients hospitalized for bone fractures.

PubMed

Calero-García, M J; Calero, M D; Navarro, E; Ortega, A R

2015-01-01

Bone fractures in older adults involve hospitalization and surgical intervention, aspects that have been related to loss of autonomy and independence. Several variables have been studied as moderators of how these patients recover. However, the implications of cognitive plasticity for functional recovery have not been studied to date. The present study analyzes the relationship between cognitive plasticity--defined as the capacity for learning or improved performance under conditions of training or performance optimization--and functional recovery in older adults hospitalized following a bone fracture. The study comprised 165 older adults who underwent surgery for bone fractures at a hospital in southern Spain. Participants were evaluated at different time points thereafter, with instruments that measure activities of daily life (ADL), namely the Barthel Index (BI) and the Lawton Index, as well as with a learning potential (cognitive plasticity) assessment test (Auditory Verbal Learning Test of Learning Potential, AVLT-LP). Results show that most of the participants have improved their level of independence 3 months after the intervention. However, some patients continue to have medium to high levels of dependency and this dependency is related to cognitive plasticity. The results of this study reveal the importance of the cognitive plasticity variable for evaluating older adults hospitalized for a fracture. They indicate a possible benefit to be obtained by implementing programs that reduce the degree of long-term dependency or decrease the likelihood of it arising.

Neuromodulation, development and synaptic plasticity.

PubMed

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.

Fragile X Mental Retardation Protein and Dendritic Local Translation of the Alpha Subunit of the Calcium/Calmodulin-Dependent Kinase II Messenger RNA Are Required for the Structural Plasticity Underlying Olfactory Learning.

PubMed

Daroles, Laura; Gribaudo, Simona; Doulazmi, Mohamed; Scotto-Lomassese, Sophie; Dubacq, Caroline; Mandairon, Nathalie; Greer, Charles August; Didier, Anne; Trembleau, Alain; Caillé, Isabelle

2016-07-15

In the adult brain, structural plasticity allowing gain or loss of synapses remodels circuits to support learning. In fragile X syndrome, the absence of fragile X mental retardation protein (FMRP) leads to defects in plasticity and learning deficits. FMRP is a master regulator of local translation but its implication in learning-induced structural plasticity is unknown. Using an olfactory learning task requiring adult-born olfactory bulb neurons and cell-specific ablation of FMRP, we investigated whether learning shapes adult-born neuron morphology during their synaptic integration and its dependence on FMRP. We used alpha subunit of the calcium/calmodulin-dependent kinase II (αCaMKII) mutant mice with altered dendritic localization of αCaMKII messenger RNA, as well as a reporter of αCaMKII local translation to investigate the role of this FMRP messenger RNA target in learning-dependent structural plasticity. Learning induces profound changes in dendritic architecture and spine morphology of adult-born neurons that are prevented by ablation of FMRP in adult-born neurons and rescued by an metabotropic glutamate receptor 5 antagonist. Moreover, dendritically translated αCaMKII is necessary for learning and associated structural modifications and learning triggers an FMRP-dependent increase of αCaMKII dendritic translation in adult-born neurons. Our results strongly suggest that FMRP mediates structural plasticity of olfactory bulb adult-born neurons to support olfactory learning through αCaMKII local translation. This reveals a new role for FMRP-regulated dendritic local translation in learning-induced structural plasticity. This might be of clinical relevance for the understanding of critical periods disruption in autism spectrum disorder patients, among which fragile X syndrome is the primary monogenic cause. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Leaf age dependent changes in within-canopy variation in leaf functional traits: a meta-analysis

PubMed Central

Niinemets, Ülo

2018-01-01

Within-canopy variation in leaf structural and photosynthetic characteristics is a major means by which whole canopy photosynthesis is maximized at given total canopy nitrogen. As key acclimatory modifications, leaf nitrogen content (NA) and photosynthetic capacity (AA) per unit area increase with increasing light availability in the canopy and these increases are associated with increases in leaf dry mass per unit area (MA) and/or nitrogen content per dry mass and/or allocation. However, leaf functional characteristics change with increasing leaf age during leaf development and aging, but the importance of these alterations for within-canopy trait gradients is unknown. I conducted a meta-analysis based on 71 canopies that were sampled at different time periods or, in evergreens, included measurements for different-aged leaves to understand how within-canopy variations in leaf traits (trait plasticity) depend on leaf age. The analysis demonstrated that in evergreen woody species, MA and NA plasticity decreased with increasing leaf age, but the change in AA plasticity was less suggesting a certain re-acclimation of AA to altered light. In deciduous woody species, MA and NA gradients in flush-type species increased during leaf development and were almost invariable through the rest of the season, while in continuously leaf-forming species, trait gradients increased constantly with increasing leaf age. In forbs, NA plasticity increased, while in grasses, NA plasticity decreased with increasing leaf age, reflecting life form differences in age-dependent changes in light availability and in nitrogen resorption for growth of generative organs. Although more work is needed to improve the coverage of age-dependent plasticity changes in some plant life forms, I argue that the age-dependent variation in trait plasticity uncovered in this study is large enough to warrant incorporation in simulations of canopy photosynthesis through the growing period. PMID:27033356

Experimental and numerical characterisation of the elasto-plastic properties of bovine trabecular bone and a trabecular bone analogue.

PubMed

Kelly, Nicola; McGarry, J Patrick

2012-05-01

The inelastic pressure dependent compressive behaviour of bovine trabecular bone is investigated through experimental and computational analysis. Two loading configurations are implemented, uniaxial and confined compression, providing two distinct loading paths in the von Mises-pressure stress plane. Experimental results reveal distinctive yielding followed by a constant nominal stress plateau for both uniaxial and confined compression. Computational simulation of the experimental tests using the Drucker-Prager and Mohr-Coulomb plasticity models fails to capture the confined compression behaviour of trabecular bone. The high pressure developed during confined compression does not result in plastic deformation using these formulations, and a near elastic response is computed. In contrast, the crushable foam plasticity models provide accurate simulation of the confined compression tests, with distinctive yield and plateau behaviour being predicted. The elliptical yield surfaces of the crushable foam formulations in the von Mises-pressure stress plane accurately characterise the plastic behaviour of trabecular bone. Results reveal that the hydrostatic yield stress is equal to the uniaxial yield stress for trabecular bone, demonstrating the importance of accurate characterisation and simulation of the pressure dependent plasticity. It is also demonstrated in this study that a commercially available trabecular bone analogue material, cellular rigid polyurethane foam, exhibits similar pressure dependent yield behaviour, despite having a lower stiffness and strength than trabecular bone. This study provides a novel insight into the pressure dependent yield behaviour of trabecular bone, demonstrating the inadequacy of uniaxial testing alone. For the first time, crushable foam plasticity formulations are implemented for trabecular bone. The enhanced understanding of the inelastic behaviour of trabecular bone established in this study will allow for more realistic simulation of orthopaedic device implantation and failure. Copyright © 2011 Elsevier Ltd. All rights reserved.

Development of a Pressure-Dependent Constitutive Model with Combined Multilinear Kinematic and Isotropic Hardening

NASA Technical Reports Server (NTRS)

Allen Phillip A.; Wilson, Christopher D.

2003-01-01

The development of a pressure-dependent constitutive model with combined multilinear kinematic and isotropic hardening is presented. The constitutive model is developed using the ABAQUS user material subroutine (UMAT). First the pressure-dependent plasticity model is derived. Following this, the combined bilinear and combined multilinear hardening equations are developed for von Mises plasticity theory. The hardening rule equations are then modified to include pressure dependency. The method for implementing the new constitutive model into ABAQUS is given.

The Current Status of Somatostatin-Interneurons in Inhibitory Control of Brain Function and Plasticity

PubMed Central

2016-01-01

The mammalian neocortex contains many distinct inhibitory neuronal populations to balance excitatory neurotransmission. A correct excitation/inhibition equilibrium is crucial for normal brain development, functioning, and controlling lifelong cortical plasticity. Knowledge about how the inhibitory network contributes to brain plasticity however remains incomplete. Somatostatin- (SST-) interneurons constitute a large neocortical subpopulation of interneurons, next to parvalbumin- (PV-) and vasoactive intestinal peptide- (VIP-) interneurons. Unlike the extensively studied PV-interneurons, acknowledged as key components in guiding ocular dominance plasticity, the contribution of SST-interneurons is less understood. Nevertheless, SST-interneurons are ideally situated within cortical networks to integrate unimodal or cross-modal sensory information processing and therefore likely to be important mediators of experience-dependent plasticity. The lack of knowledge on SST-interneurons partially relates to the wide variety of distinct subpopulations present in the sensory neocortex. This review informs on those SST-subpopulations hitherto described based on anatomical, molecular, or electrophysiological characteristics and whose functional roles can be attributed based on specific cortical wiring patterns. A possible role for these subpopulations in experience-dependent plasticity will be discussed, emphasizing on learning-induced plasticity and on unimodal and cross-modal plasticity upon sensory loss. This knowledge will ultimately contribute to guide brain plasticity into well-defined directions to restore sensory function and promote lifelong learning. PMID:27403348

Context-dependent plasticity in the subcortical encoding of linguistic pitch patterns

PubMed Central

Lau, Joseph C. Y.; Wong, Patrick C. M.

2016-01-01

We examined the mechanics of online experience-dependent auditory plasticity by assessing the influence of prior context on the frequency-following responses (FFRs), which reflect phase-locked responses from neural ensembles within the subcortical auditory system. FFRs were elicited to a Cantonese falling lexical pitch pattern from 24 native speakers of Cantonese in a variable context, wherein the falling pitch pattern randomly occurred in the context of two other linguistic pitch patterns; in a patterned context, wherein, the falling pitch pattern was presented in a predictable sequence along with two other pitch patterns, and in a repetitive context, wherein the falling pitch pattern was presented with 100% probability. We found that neural tracking of the stimulus pitch contour was most faithful and accurate when listening context was patterned and least faithful when the listening context was variable. The patterned context elicited more robust pitch tracking relative to the repetitive context, suggesting that context-dependent plasticity is most robust when the context is predictable but not repetitive. Our study demonstrates a robust influence of prior listening context that works to enhance online neural encoding of linguistic pitch patterns. We interpret these results as indicative of an interplay between contextual processes that are responsive to predictability as well as novelty in the presentation context. NEW & NOTEWORTHY Human auditory perception in dynamic listening environments requires fine-tuning of sensory signal based on behaviorally relevant regularities in listening context, i.e., online experience-dependent plasticity. Our finding suggests what partly underlie online experience-dependent plasticity are interplaying contextual processes in the subcortical auditory system that are responsive to predictability as well as novelty in listening context. These findings add to the literature that looks to establish the neurophysiological bases of auditory system plasticity, a central issue in auditory neuroscience. PMID:27832606

Context-dependent plasticity in the subcortical encoding of linguistic pitch patterns.

PubMed

Lau, Joseph C Y; Wong, Patrick C M; Chandrasekaran, Bharath

2017-02-01

We examined the mechanics of online experience-dependent auditory plasticity by assessing the influence of prior context on the frequency-following responses (FFRs), which reflect phase-locked responses from neural ensembles within the subcortical auditory system. FFRs were elicited to a Cantonese falling lexical pitch pattern from 24 native speakers of Cantonese in a variable context, wherein the falling pitch pattern randomly occurred in the context of two other linguistic pitch patterns; in a patterned context, wherein, the falling pitch pattern was presented in a predictable sequence along with two other pitch patterns, and in a repetitive context, wherein the falling pitch pattern was presented with 100% probability. We found that neural tracking of the stimulus pitch contour was most faithful and accurate when listening context was patterned and least faithful when the listening context was variable. The patterned context elicited more robust pitch tracking relative to the repetitive context, suggesting that context-dependent plasticity is most robust when the context is predictable but not repetitive. Our study demonstrates a robust influence of prior listening context that works to enhance online neural encoding of linguistic pitch patterns. We interpret these results as indicative of an interplay between contextual processes that are responsive to predictability as well as novelty in the presentation context. Human auditory perception in dynamic listening environments requires fine-tuning of sensory signal based on behaviorally relevant regularities in listening context, i.e., online experience-dependent plasticity. Our finding suggests what partly underlie online experience-dependent plasticity are interplaying contextual processes in the subcortical auditory system that are responsive to predictability as well as novelty in listening context. These findings add to the literature that looks to establish the neurophysiological bases of auditory system plasticity, a central issue in auditory neuroscience. Copyright © 2017 the American Physiological Society.

Contrasting roles for parvalbumin-expressing inhibitory neurons in two forms of adult visual cortical plasticity

PubMed Central

Kaplan, Eitan S; Cooke, Sam F; Komorowski, Robert W; Chubykin, Alexander A; Thomazeau, Aurore; Khibnik, Lena A; Gavornik, Jeffrey P; Bear, Mark F

2016-01-01

The roles played by cortical inhibitory neurons in experience-dependent plasticity are not well understood. Here we evaluate the participation of parvalbumin-expressing (PV+) GABAergic neurons in two forms of experience-dependent modification of primary visual cortex (V1) in adult mice: ocular dominance (OD) plasticity resulting from monocular deprivation and stimulus-selective response potentiation (SRP) resulting from enriched visual experience. These two forms of plasticity are triggered by different events but lead to a similar increase in visual cortical response. Both also require the NMDA class of glutamate receptor (NMDAR). However, we find that PV+ inhibitory neurons in V1 play a critical role in the expression of SRP and its behavioral correlate of familiarity recognition, but not in the expression of OD plasticity. Furthermore, NMDARs expressed within PV+ cells, reversibly inhibited by the psychotomimetic drug ketamine, play a critical role in SRP, but not in the induction or expression of adult OD plasticity. DOI: http://dx.doi.org/10.7554/eLife.11450.001 PMID:26943618

The limitations of staggered grid finite differences in plasticity problems

NASA Astrophysics Data System (ADS)

Pranger, Casper; Herrendörfer, Robert; Le Pourhiet, Laetitia

2017-04-01

Most crustal-scale applications operate at grid sizes much larger than those at which plasticity occurs in nature. As a consequence, plastic shear bands often localize to the scale of one grid cell, and numerical ploys — like introducing an artificial length scale — are needed to counter this. If for whatever reasons (good or bad) this is not done, we find that problems may arise due to the fact that in the staggered grid finite difference discretization, unknowns like components of the stress tensor and velocity vector are located in physically different positions. This incurs frequent interpolation, reducing the accuracy of the discretization. For purely stress-dependent plasticity problems the adverse effects might be contained because the magnitude of the stress discontinuity across a plastic shear band is limited. However, we find that when rate-dependence of friction is added in the mix, things become ugly really fast and the already hard-to-solve and highly nonlinear problem of plasticity incurs an extra penalty.

Indentation-derived elastic modulus of multilayer thin films: Effect of unloading induced plasticity

DOE PAGES

Jamison, Ryan Dale; Shen, Yu -Lin

2015-08-13

Nanoindentation is useful for evaluating the mechanical properties, such as elastic modulus, of multilayer thin film materials. A fundamental assumption in the derivation of the elastic modulus from nanoindentation is that the unloading process is purely elastic. In this work, the validity of elastic assumption as it applies to multilayer thin films is studied using the finite element method. The elastic modulus and hardness from the model system are compared to experimental results to show validity of the model. Plastic strain is shown to increase in the multilayer system during the unloading process. Additionally, the indentation-derived modulus of a monolayermore » material shows no dependence on unloading plasticity while the modulus of the multilayer system is dependent on unloading-induced plasticity. Lastly, the cyclic behavior of the multilayer thin film is studied in relation to the influence of unloading-induced plasticity. Furthermore, it is found that several cycles are required to minimize unloading-induced plasticity.« less

Integrative Analysis of Disease Signatures Shows Inflammation Disrupts Juvenile Experience-Dependent Cortical Plasticity

PubMed Central

Smith, Milo R.; Burman, Poromendro

2016-01-01

Throughout childhood and adolescence, periods of heightened neuroplasticity are critical for the development of healthy brain function and behavior. Given the high prevalence of neurodevelopmental disorders, such as autism, identifying disruptors of developmental plasticity represents an essential step for developing strategies for prevention and intervention. Applying a novel computational approach that systematically assessed connections between 436 transcriptional signatures of disease and multiple signatures of neuroplasticity, we identified inflammation as a common pathological process central to a diverse set of diseases predicted to dysregulate plasticity signatures. We tested the hypothesis that inflammation disrupts developmental cortical plasticity in vivo using the mouse ocular dominance model of experience-dependent plasticity in primary visual cortex. We found that the administration of systemic lipopolysaccharide suppressed plasticity during juvenile critical period with accompanying transcriptional changes in a particular set of molecular regulators within primary visual cortex. These findings suggest that inflammation may have unrecognized adverse consequences on the postnatal developmental trajectory and indicate that treating inflammation may reduce the burden of neurodevelopmental disorders. PMID:28101530

Evolution of phenotypic plasticity and environmental tolerance of a labile quantitative character in a fluctuating environment.

PubMed

Lande, R

2014-05-01

Quantitative genetic models of evolution of phenotypic plasticity are used to derive environmental tolerance curves for a population in a changing environment, providing a theoretical foundation for integrating physiological and community ecology with evolutionary genetics of plasticity and norms of reaction. Plasticity is modelled for a labile quantitative character undergoing continuous reversible development and selection in a fluctuating environment. If there is no cost of plasticity, a labile character evolves expected plasticity equalling the slope of the optimal phenotype as a function of the environment. This contrasts with previous theory for plasticity influenced by the environment at a critical stage of early development determining a constant adult phenotype on which selection acts, for which the expected plasticity is reduced by the environmental predictability over the discrete time lag between development and selection. With a cost of plasticity in a labile character, the expected plasticity depends on the cost and on the environmental variance and predictability averaged over the continuous developmental time lag. Environmental tolerance curves derived from this model confirm traditional assumptions in physiological ecology and provide new insights. Tolerance curve width increases with larger environmental variance, but can only evolve within a limited range. The strength of the trade-off between tolerance curve height and width depends on the cost of plasticity. Asymmetric tolerance curves caused by male sterility at high temperature are illustrated. A simple condition is given for a large transient increase in plasticity and tolerance curve width following a sudden change in average environment. © 2014 The Author. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

Reelin Supplementation Enhances Cognitive Ability, Synaptic Plasticity, and Dendritic Spine Density

ERIC Educational Resources Information Center

Rogers, Justin T.; Rusiana, Ian; Trotter, Justin; Zhao, Lisa; Donaldson, Erika; Pak, Daniel T.S.; Babus, Lenard W.; Peters, Melinda; Banko, Jessica L.; Chavis, Pascale; Rebeck, G. William; Hoe, Hyang-Sook; Weeber, Edwin J.

2011-01-01

Apolipoprotein receptors belong to an evolutionarily conserved surface receptor family that has intimate roles in the modulation of synaptic plasticity and is necessary for proper hippocampal-dependent memory formation. The known lipoprotein receptor ligand Reelin is important for normal synaptic plasticity, dendritic morphology, and cognitive…

Neuronal plasticity and neurotrophic factors in drug responses

PubMed Central

Castrén, Eero; Antila, Hanna

2017-01-01

Neurotrophic factors, particularly brain-derived neurotrophic factor (BDNF) and other members of the neurotrophin family, are central mediators of the activity-dependent plasticity through which environmental experiences, such as sensory information are translated into the structure and function of neuronal networks. Synthesis, release and action of BDNF is regulated by neuronal activity and BDNF in turn leads to trophic effects such as formation, stabilization and potentiation of synapses through its high-affinity TrkB receptors. Several clinically available drugs directly activate neurotrophins and neuronal plasticity. In particular, antidepressant drugs rapidly activate TrkB signaling and gradually increase BDNF expression, and the behavioral effects of antidepressants are mediated by and dependent on BDNF signaling through TrkB at least in rodents. These findings indicate that antidepressants, widely used drugs, effectively act as TrkB activators. They further imply that neuronal plasticity is a central mechanism in the action of antidepressant drugs. Indeed, it was recently discovered that antidepressants reactivate a state of plasticity in the adult cerebral cortex that closely resembles the enhanced plasticity normally observed during postnatal critical periods. This state of induced plasticity, known as iPlasticity, allows environmental stimuli to beneficially reorganize networks abnormally wired during early life. iPlasticity has been observed in cortical as well as subcortical networks and is induced by several pharmacological and non-pharmacological treatments. iPlasticity is a new pharmacological principle where drug treatment and rehabilitation cooperate: the drug acts permissively to enhance plasticity and rehabilitation provides activity to guide the appropriate wiring of the plastic network. Optimization of iPlastic drug treatment with novel means of rehabilitation may help improve the efficacy of available drug treatments and expand the use of currently existing drugs into new indications. PMID:28397840

Principles of Experience-Dependent Neural Plasticity: Implications for Rehabilitation after Brain Damage

ERIC Educational Resources Information Center

Kleim, Jeffrey A.; Jones, Theresa A.

2008-01-01

Purpose: This paper reviews 10 principles of experience-dependent neural plasticity and considerations in applying them to the damaged brain. Method: Neuroscience research using a variety of models of learning, neurological disease, and trauma are reviewed from the perspective of basic neuroscientists but in a manner intended to be useful for the…

Reconstructing regulatory networks from the dynamic plasticity of gene expression by mutual information

PubMed Central

Wang, Jianxin; Chen, Bo; Wang, Yaqun; Wang, Ningtao; Garbey, Marc; Tran-Son-Tay, Roger; Berceli, Scott A.; Wu, Rongling

2013-01-01

The capacity of an organism to respond to its environment is facilitated by the environmentally induced alteration of gene and protein expression, i.e. expression plasticity. The reconstruction of gene regulatory networks based on expression plasticity can gain not only new insights into the causality of transcriptional and cellular processes but also the complex regulatory mechanisms that underlie biological function and adaptation. We describe an approach for network inference by integrating expression plasticity into Shannon’s mutual information. Beyond Pearson correlation, mutual information can capture non-linear dependencies and topology sparseness. The approach measures the network of dependencies of genes expressed in different environments, allowing the environment-induced plasticity of gene dependencies to be tested in unprecedented details. The approach is also able to characterize the extent to which the same genes trigger different amounts of expression in response to environmental changes. We demonstrated the usefulness of this approach through analysing gene expression data from a rabbit vein graft study that includes two distinct blood flow environments. The proposed approach provides a powerful tool for the modelling and analysis of dynamic regulatory networks using gene expression data from distinct environments. PMID:23470995

Experience-Dependent Synaptic Plasticity in V1 Occurs without Microglial CX3CR1

PubMed Central

Stevens, Beth

2017-01-01

Brief monocular deprivation (MD) shifts ocular dominance and reduces the density of thalamic synapses in layer 4 of the mouse primary visual cortex (V1). We found that microglial lysosome content is also increased as a result of MD. Previous studies have shown that the microglial fractalkine receptor CX3CR1 is involved in synaptic development and hippocampal plasticity. We therefore tested the hypothesis that neuron-to-microglial communication via CX3CR1 is an essential component of visual cortical development and plasticity in male mice. Our data show that CX3CR1 is not required for normal development of V1 responses to visual stimulation, multiple forms of experience-dependent plasticity, or the synapse loss that accompanies MD in layer 4. By ruling out an essential role for fractalkine signaling, our study narrows the search for understanding how microglia respond to active synapse modification in the visual cortex. SIGNIFICANCE STATEMENT Microglia in the visual cortex respond to monocular deprivation with increased lysosome content, but signaling through the fractalkine receptor CX3CR1 is not an essential component in the mechanisms of visual cortical development or experience-dependent synaptic plasticity. PMID:28951447

Global Existence Results for Viscoplasticity at Finite Strain

NASA Astrophysics Data System (ADS)

Mielke, Alexander; Rossi, Riccarda; Savaré, Giuseppe

2018-01-01

We study a model for rate-dependent gradient plasticity at finite strain based on the multiplicative decomposition of the strain tensor, and investigate the existence of global-in-time solutions to the related PDE system. We reveal its underlying structure as a generalized gradient system, where the driving energy functional is highly nonconvex and features the geometric nonlinearities related to finite-strain elasticity as well as the multiplicative decomposition of finite-strain plasticity. Moreover, the dissipation potential depends on the left-invariant plastic rate, and thus depends on the plastic state variable. The existence theory is developed for a class of abstract, nonsmooth, and nonconvex gradient systems, for which we introduce suitable notions of solutions, namely energy-dissipation-balance and energy-dissipation-inequality solutions. Hence, we resort to the toolbox of the direct method of the calculus of variations to check that the specific energy and dissipation functionals for our viscoplastic models comply with the conditions of the general theory.

Fast-Spiking Interneurons Supply Feedforward Control of Bursting, Calcium, and Plasticity for Efficient Learning.

PubMed

Owen, Scott F; Berke, Joshua D; Kreitzer, Anatol C

2018-02-08

Fast-spiking interneurons (FSIs) are a prominent class of forebrain GABAergic cells implicated in two seemingly independent network functions: gain control and network plasticity. Little is known, however, about how these roles interact. Here, we use a combination of cell-type-specific ablation, optogenetics, electrophysiology, imaging, and behavior to describe a unified mechanism by which striatal FSIs control burst firing, calcium influx, and synaptic plasticity in neighboring medium spiny projection neurons (MSNs). In vivo silencing of FSIs increased bursting, calcium transients, and AMPA/NMDA ratios in MSNs. In a motor sequence task, FSI silencing increased the frequency of calcium transients but reduced the specificity with which transients aligned to individual task events. Consistent with this, ablation of FSIs disrupted the acquisition of striatum-dependent egocentric learning strategies. Together, our data support a model in which feedforward inhibition from FSIs temporally restricts MSN bursting and calcium-dependent synaptic plasticity to facilitate striatum-dependent sequence learning. Copyright © 2018 Elsevier Inc. All rights reserved.

Gradient-type modeling of the effects of plastic recovery and surface passivation in thin films

NASA Astrophysics Data System (ADS)

Liu, Jinxing; Kah Soh, Ai

2016-08-01

The elasto-plastic responses of thin films subjected to cyclic tension-compression loading and bending are studied, with a focus on Bauschinger and size effects. For this purpose, a model is established by incorporating plastic recovery into the strain gradient plasticity theory we proposed recently. Elastic and plastic parts of strain and strain gradient, which are determined by the elasto-plastic decomposition according to the associative rule, are assumed to have a degree of material-dependent reversibility. Based on the above assumption, a dislocation reversibility-dependent rule is built to describe evolutions of different deformation components under cyclic loadings. Furthermore, a simple strategy is provided to implement the passivated boundary effects by introducing a gradual change to relevant material parameters in the yield function. Based on this theory, both bulge and bending tests under cyclic loading conditions are investigated. By comparing the present predictions with the existing experimental data, it is found that the yield function is able to exhibit the size effect, the Bauschinger effect, the influence of surface passivation and the hysteresis-loop phenomenon. Thus, the proposed model is deemed helpful in studying plastic deformations of micron-scale films.

H3 and H4 Lysine Acetylation Correlates with Developmental and Experimentally Induced Adult Experience-Dependent Plasticity in the Mouse Visual Cortex

PubMed Central

Vierci, Gabriela; Pannunzio, Bruno; Bornia, Natalia; Rossi, Francesco M.

2016-01-01

Histone posttranslational modifications play a fundamental role in orchestrating gene expression. In this work, we analyzed the acetylation of H3 and H4 histones (AcH3–AcH4) and its modulation by visual experience in the mouse visual cortex (VC) during normal development and in two experimental conditions that restore juvenile-like plasticity levels in adults (fluoxetine treatment and enriched environment). We found that AcH3–AcH4 declines with age and is upregulated by treatments restoring plasticity in the adult. We also found that visual experience modulates AcH3–AcH4 in young and adult plasticity-restored mice but not in untreated ones. Finally, we showed that the transporter vGAT is downregulated in adult plasticity-restored models. In summary, we identified a dynamic regulation of AcH3–AcH4, which is associated with high plasticity levels and enhanced by visual experience. These data, along with recent ones, indicate H3–H4 acetylation as a central hub in the control of experience-dependent plasticity in the VC. PMID:27891053

Leaf-trait plasticity and species vulnerability to climate change in a Mongolian steppe.

PubMed

Liancourt, Pierre; Boldgiv, Bazartseren; Song, Daniel S; Spence, Laura A; Helliker, Brent R; Petraitis, Peter S; Casper, Brenda B

2015-09-01

Climate change is expected to modify plant assemblages in ways that will have major consequences for ecosystem functions. How climate change will affect community composition will depend on how individual species respond, which is likely related to interspecific differences in functional traits. The extraordinary plasticity of some plant traits is typically neglected in assessing how climate change will affect different species. In the Mongolian steppe, we examined whether leaf functional traits under ambient conditions and whether plasticity in these traits under altered climate could explain climate-induced biomass responses in 12 co-occurring plant species. We experimentally created three probable climate change scenarios and used a model selection procedure to determine the set of baseline traits or plasticity values that best explained biomass response. Under all climate change scenarios, plasticity for at least one leaf trait correlated with change in species performance, while functional leaf-trait values in ambient conditions did not. We demonstrate that trait plasticity could play a critical role in vulnerability of species to a rapidly changing environment. Plasticity should be considered when examining how climate change will affect plant performance, species' niche spaces, and ecological processes that depend on plant community composition. © 2015 John Wiley & Sons Ltd.

Learning-Dependent Plasticity of the Barrel Cortex Is Impaired by Restricting GABA-Ergic Transmission.

PubMed

Posluszny, Anna; Liguz-Lecznar, Monika; Turzynska, Danuta; Zakrzewska, Renata; Bielecki, Maksymilian; Kossut, Malgorzata

2015-01-01

Experience-induced plastic changes in the cerebral cortex are accompanied by alterations in excitatory and inhibitory transmission. Increased excitatory drive, necessary for plasticity, precedes the occurrence of plastic change, while decreased inhibitory signaling often facilitates plasticity. However, an increase of inhibitory interactions was noted in some instances of experience-dependent changes. We previously reported an increase in the number of inhibitory markers in the barrel cortex of mice after fear conditioning engaging vibrissae, observed concurrently with enlargement of the cortical representational area of the row of vibrissae receiving conditioned stimulus (CS). We also observed that an increase of GABA level accompanied the conditioning. Here, to find whether unaltered GABAergic signaling is necessary for learning-dependent rewiring in the murine barrel cortex, we locally decreased GABA production in the barrel cortex or reduced transmission through GABAA receptors (GABAARs) at the time of the conditioning. Injections of 3-mercaptopropionic acid (3-MPA), an inhibitor of glutamic acid decarboxylase (GAD), into the barrel cortex prevented learning-induced enlargement of the conditioned vibrissae representation. A similar effect was observed after injection of gabazine, an antagonist of GABAARs. At the behavioral level, consistent conditioned response (cessation of head movements in response to CS) was impaired. These results show that appropriate functioning of the GABAergic system is required for both manifestation of functional cortical representation plasticity and for the development of a conditioned response.

Ground Robotic Hand Applications for the Space Program study (GRASP)

NASA Astrophysics Data System (ADS)

Grissom, William A.; Rafla, Nader I.

1992-04-01

This document reports on a NASA-STDP effort to address research interests of the NASA Kennedy Space Center (KSC) through a study entitled, Ground Robotic-Hand Applications for the Space Program (GRASP). The primary objective of the GRASP study was to identify beneficial applications of specialized end-effectors and robotic hand devices for automating any ground operations which are performed at the Kennedy Space Center. Thus, operations for expendable vehicles, the Space Shuttle and its components, and all payloads were included in the study. Typical benefits of automating operations, or augmenting human operators performing physical tasks, include: reduced costs; enhanced safety and reliability; and reduced processing turnaround time.

Ground Robotic Hand Applications for the Space Program study (GRASP)

NASA Technical Reports Server (NTRS)

Grissom, William A.; Rafla, Nader I. (Editor)

1992-01-01

This document reports on a NASA-STDP effort to address research interests of the NASA Kennedy Space Center (KSC) through a study entitled, Ground Robotic-Hand Applications for the Space Program (GRASP). The primary objective of the GRASP study was to identify beneficial applications of specialized end-effectors and robotic hand devices for automating any ground operations which are performed at the Kennedy Space Center. Thus, operations for expendable vehicles, the Space Shuttle and its components, and all payloads were included in the study. Typical benefits of automating operations, or augmenting human operators performing physical tasks, include: reduced costs; enhanced safety and reliability; and reduced processing turnaround time.

GRASP1 regulates synaptic plasticity and learning through endosomal recycling of AMPA receptors

PubMed Central

Chiu, Shu-Ling; Diering, Graham Hugh; Ye, Bing; Takamiya, Kogo; Chen, Chih-Ming; Jiang, Yuwu; Niranjan, Tejasvi; Schwartz, Charles E.; Wang, Tao; Huganir, Richard L.

2017-01-01

Summary Learning depends on experience-dependent modification of synaptic efficacy and neuronal connectivity in the brain. We provide direct evidence for physiological roles of the recycling endosome protein GRASP1 in glutamatergic synapse function and animal behavior. Mice lacking GRASP1 showed abnormal excitatory synapse number, synaptic plasticity and hippocampal-dependent learning and memory due to a failure in learning-induced synaptic AMPAR incorporation. We identified two GRASP1 point mutations from intellectual disability (ID) patients that showed convergent disruptive effects on AMPAR recycling and glutamate uncaging-induced structural and functional plasticity. Wild-type GRASP1, but not ID mutants, rescues spine loss in hippocampal CA1 neurons of Grasp1 knockout mice. Together, these results demonstrate a requirement for normal recycling endosome function in AMPAR-dependent synaptic function and neuronal connectivity in vivo, and suggest a potential role for GRASP1 in the pathophysiology of human cognitive disorders. PMID:28285821

Analytical, Numerical and Experimental Examination of Reinforced Composites Beams Covered with Carbon Fiber Reinforced Plastic

NASA Astrophysics Data System (ADS)

Kasimzade, A. A.; Tuhta, S.

2012-03-01

In the article, analytical, numerical (Finite Element Method) and experimental investigation results of beam that was strengthened with fiber reinforced plastic-FRP composite has been given as comparative, the effect of FRP wrapping number to the maximum load and moment capacity has been evaluated depending on this results. Carbon FRP qualitative dependences have been occurred between wrapping number and beam load and moment capacity for repair-strengthen the reinforced concrete beams with carbon fiber. Shown possibilities of application traditional known analysis programs, for the analysis of Carbon Fiber Reinforced Plastic (CFRP) strengthened structures.

Stress-dependent grain size evolution of nanocrystalline Ni-W and its impact on friction behavior

DOE PAGES

Argibay, N.; Furnish, T. A.; Boyce, B. L.; ...

2016-06-07

The friction behavior of ultra-nanocrystalline Ni-W coatings was investigated. A critical stress threshold was identified below which friction remained low, and above which a time-dependent evolution toward higher friction behavior occurred. Founded on established plasticity models we propose a correlation between surface grain size and applied stress that can be used to predict the critical stress separating the two friction regimes. Lastly, this interpretation of plasticity models suggests that macro-scale low and high friction regimes are respectively associated with the nano-scale mechanisms of grain boundary and dislocation-mediated plasticity.

Avalanches and plasticity for colloids in a time dependent optical trap

DOE PAGES

Olson Reichhardt, Cynthia Jane; McDermott, Danielle Marie; Reichhardt, Charles

2015-08-25

Here, with the use of optical traps it is possible to confine assemblies of colloidal particles in two-dimensional and quasi-one-dimensional arrays. Here we examine how colloidal particles rearrange in a quasi-one-dimensional trap with a time dependent confining potential. The particle motion occurs both through slow elastic uniaxial distortions as well as through abrupt large-scale two-dimensional avalanches associated with plastic rearrangements. During the avalanches the particle velocity distributions extend over a broad range and can be fit to a power law consistent with other studies of plastic events mediated by dislocations.

Temperature-dependent plastic hysteresis in highly confined polycrystalline Nb films

NASA Astrophysics Data System (ADS)

Waheed, S.; Hao, R.; Zheng, Z.; Wheeler, J. M.; Michler, J.; Balint, D. S.; Giuliani, F.

2018-02-01

In this study, the effect of temperature on the cyclic deformation behaviour of a confined polycrystalline Nb film is investigated. Micropillars encapsulating a thin niobium interlayer are deformed under cyclic axial compression at different test temperatures. A distinct plastic hysteresis is observed for samples tested at elevated temperatures, whereas negligible plastic hysteresis is observed for samples tested at room temperature. These results are interpreted using planar discrete dislocation plasticity incorporating slip transmission across grain boundaries. The effect of temperature-dependent grain boundary energy and dislocation mobility on dislocation penetration and, consequently, the size of plastic hysteresis is simulated to correlate with the experimental results. It is found that the decrease in grain boundary energy barrier caused by the increase in temperature does not lead to any appreciable change in the cyclic response. However, dislocation mobility significantly affects the size of plastic hysteresis, with high mobilities leading to a larger hysteresis. Therefore, it is postulated that the experimental observations are predominantly caused by an increase in dislocation mobility as the temperature is increased above the critical temperature of body-centred cubic niobium.

Plastic scintillation detectors for dose monitoring in digital breast tomosynthesis

NASA Astrophysics Data System (ADS)

Antunes, J.; Machado, J.; Peralta, L.; Matela, N.

2018-01-01

Plastic scintillators detectors (PSDs) have been studied as dosimeters, since they provide a cost-effective alternative to conventional ionization chambers. Measurement and analysis of energy dependency were performed on a Siemens Mammomat tomograph for two different peak kilovoltages: 26 kV and 35 kV. Both PSD displayed good linearity for each energy considered and almost no energy dependence.

A 2D Material based Gate Tunable Memristive Device for Emulating Modulatory Input-dependent Hetero-synaptic Plasticity.

NASA Astrophysics Data System (ADS)

Yan, Xiaodong; Tian, He; Xie, Yujun; Kostelec, Andrew; Zhao, Huan; Cha, Judy J.; Tice, Jesse; Wang, Han

Modulatory input-dependent plasticity is a well-known type of hetero-synaptic response where the release of neuromodulators can alter the efficacy of neurotransmission in a nearby chemical synapse. Solid-state devices that can mimic such phenomenon are desirable for enhancing the functionality and reconfigurability of neuromorphic electronics. In this work, we demonstrated a tunable artificial synaptic device concept based on the properties of graphene and tin oxide that can mimic the modulatory input-dependent plasticity. By using graphene as the contact electrode, a third electrode terminal can be used to modulate the conductive filament formation in the vertical tin oxide based resistive memory device. The resulting synaptic characteristics of this device, in terms of the profile of synaptic weight change and the spike-timing-dependent-plasticity, is tunable with the bias at the modulating terminal. Furthermore, the synaptic response can be reconfigured between excitatory and inhibitory modes by this modulating bias. The operation mechanism of the device is studied with combined experimental and theoretical analysis. The device is attractive for application in neuromorphic electronics. This work is supported by ARO and NG-ION2 at USC.

Motor Learning Enhances Use-Dependent Plasticity

PubMed Central

2017-01-01

Motor behaviors are shaped not only by current sensory signals but also by the history of recent experiences. For instance, repeated movements toward a particular target bias the subsequent movements toward that target direction. This process, called use-dependent plasticity (UDP), is considered a basic and goal-independent way of forming motor memories. Most studies consider movement history as the critical component that leads to UDP (Classen et al., 1998; Verstynen and Sabes, 2011). However, the effects of learning (i.e., improved performance) on UDP during movement repetition have not been investigated. Here, we used transcranial magnetic stimulation in two experiments to assess plasticity changes occurring in the primary motor cortex after individuals repeated reinforced and nonreinforced actions. The first experiment assessed whether learning a skill task modulates UDP. We found that a group that successfully learned the skill task showed greater UDP than a group that did not accumulate learning, but made comparable repeated actions. The second experiment aimed to understand the role of reinforcement learning in UDP while controlling for reward magnitude and action kinematics. We found that providing subjects with a binary reward without visual feedback of the cursor led to increased UDP effects. Subjects in the group that received comparable reward not associated with their actions maintained the previously induced UDP. Our findings illustrate how reinforcing consistent actions strengthens use-dependent memories and provide insight into operant mechanisms that modulate plastic changes in the motor cortex. SIGNIFICANCE STATEMENT Performing consistent motor actions induces use-dependent plastic changes in the motor cortex. This plasticity reflects one of the basic forms of human motor learning. Past studies assumed that this form of learning is exclusively affected by repetition of actions. However, here we showed that success-based reinforcement signals could affect the human use-dependent plasticity (UDP) process. Our results indicate that learning augments and interacts with UDP. This effect is important to the understanding of the interplay between the different forms of motor learning and suggests that reinforcement is not only important to learning new behaviors, but can shape our subsequent behavior via its interaction with UDP. PMID:28143961

Time course of the induction of homeostatic plasticity generated by repeated transcranial direct current stimulation of the human motor cortex.

PubMed

Fricke, K; Seeber, A A; Thirugnanasambandam, N; Paulus, W; Nitsche, M A; Rothwell, J C

2011-03-01

Several mechanisms have been proposed that control the amount of plasticity in neuronal circuits and guarantee dynamic stability of neuronal networks. Homeostatic plasticity suggests that the ease with which a synaptic connection is facilitated/suppressed depends on the previous amount of network activity. We describe how such homeostatic-like interactions depend on the time interval between two conditioning protocols and on the duration of the preconditioning protocol. We used transcranial direct current stimulation (tDCS) to produce short-lasting plasticity in the motor cortex of healthy humans. In the main experiment, we compared the aftereffect of a single 5-min session of anodal or cathodal tDCS with the effect of a 5-min tDCS session preceded by an identical 5-min conditioning session administered 30, 3, or 0 min beforehand. Five-minute anodal tDCS increases excitability for about 5 min. The same duration of cathodal tDCS reduces excitability. Increasing the duration of tDCS to 10 min prolongs the duration of the effects. If two 5-min periods of tDCS are applied with a 30-min break between them, the effect of the second period of tDCS is identical to that of 5-min stimulation alone. If the break is only 3 min, then the second session has the opposite effect to 5-min tDCS given alone. Control experiments show that these shifts in the direction of plasticity evolve during the 10 min after the first tDCS session and depend on the duration of the first tDCS but not on intracortical inhibition and facilitation. The results are compatible with a time-dependent "homeostatic-like" rule governing the response of the human motor cortex to plasticity probing protocols.

Myelin Associated Inhibitors: A Link Between Injury-Induced and Experience-Dependent Plasticity

PubMed Central

Akbik, Feras; Cafferty, William B. J.; Strittmatter, Stephen M.

2011-01-01

SUMMARY In the adult, both neurologic recovery and anatomical growth after a CNS injury are limited. Two classes of growth inhibitors, myelin associated inhibitors (MAIs) and extracellular matrix associated inhibitors, limit both functional recovery and anatomical rearrangements in animal models of spinal cord injury. Here we focus on how MAIs limit a wide spectrum of growth that includes regeneration, sprouting, and plasticity in both the intact and lesioned CNS. Three classic myelin associated inhibitors, Nogo-A, MAG, and OMgp, signal through their common receptors, Nogo-66 Receptor-1 (NgR1) and Paired-Immunoglobulin-like-Receptor-1 (PirB), to regulate cytoskeletal dynamics and inhibit growth. Initially described as inhibitors of axonal regeneration, subsequent work has demonstrated that MAIs also limit activity and experience-dependent plasticity in the intact, adult CNS. MAIs therefore represent a point of convergence for plasticity that limits anatomical rearrangements regardless of the inciting stimulus, blurring the distinction between injury studies and more “basic” plasticity studies. PMID:21699896

Gap junction plasticity as a mechanism to regulate network-wide oscillations

PubMed Central

Nicola, Wilten; Clopath, Claudia

2018-01-01

Cortical oscillations are thought to be involved in many cognitive functions and processes. Several mechanisms have been proposed to regulate oscillations. One prominent but understudied mechanism is gap junction coupling. Gap junctions are ubiquitous in cortex between GABAergic interneurons. Moreover, recent experiments indicate their strength can be modified in an activity-dependent manner, similar to chemical synapses. We hypothesized that activity-dependent gap junction plasticity acts as a mechanism to regulate oscillations in the cortex. We developed a computational model of gap junction plasticity in a recurrent cortical network based on recent experimental findings. We showed that gap junction plasticity can serve as a homeostatic mechanism for oscillations by maintaining a tight balance between two network states: asynchronous irregular activity and synchronized oscillations. This homeostatic mechanism allows for robust communication between neuronal assemblies through two different mechanisms: transient oscillations and frequency modulation. This implies a direct functional role for gap junction plasticity in information transmission in cortex. PMID:29529034

Temperature effect on refractive index sensing performance of a U-shape tapered plastic optical fiber

NASA Astrophysics Data System (ADS)

Teng, Chuanxin; Yu, Fangda; Jing, Ning; Zheng, Jie

2016-11-01

The temperature dependence of a refractive index (RI) sensing probe based on a U-shape tapered plastic optical fiber (POF) was investigated experimentally. The changes in light propagation loss in the probe induced by temperature are of the same order of magnitude as those induced by measured RI changes. The temperature dependence loss and temperature dependence RI deviation of the sensing probe were measured (at the wavelength of 635 nm) in temperature of 10-60 °C. By extracting pure temperature dependence of the sensing probe alone, the influence of temperature to the sensor was characterized.

The influence of temperature to a refractive index sensor based on a macro-bending tapered plastic optical fiber

NASA Astrophysics Data System (ADS)

Teng, Chuan-xin; Yu, Fang-da; Jing, Ning; Zheng, Jie

2016-09-01

The temperature influence to a refractive index (RI) sensor based on a macro-bending tapered plastic optical fiber (POF) was investigated experimentally. The total temperature dependence loss (TDLtotal) and total temperature dependence RI deviation (TDRtotal) were measured at different temperature (10-60 °C) over an RI range of 1.33-1.41. The temperature dependence RI deviation of the sensor itself was obtained by subtracting the temperature dependence RI of measured liquid from TDRtotal. Therefore, the influence of temperature variation to the sensor was characterized and corrected.

Dysregulation of synaptic plasticity precedes appearance of morphological defects in a Pten conditional knockout mouse model of autism.

PubMed

Takeuchi, Koichi; Gertner, Michael J; Zhou, Jing; Parada, Luis F; Bennett, Michael V L; Zukin, R Suzanne

2013-03-19

The phosphoinositide signaling system is a crucial regulator of neural development, cell survival, and plasticity. Phosphatase and tensin homolog deleted on chromosome 10 (PTEN) negatively regulates phosphatidylinositol 3-kinase signaling and downstream targets. Nse-Cre Pten conditional knockout mice, in which Pten is ablated in granule cells of the dentate gyrus and pyramidal neurons of the hippocampal CA3, but not CA1, recapitulate many of the symptoms of humans with inactivating PTEN mutations, including progressive hypertrophy of the dentate gyrus and deficits in hippocampus-based social and cognitive behaviors. However, the impact of Pten loss on activity-dependent synaptic plasticity in this clinically relevant mouse model of Pten inactivation remains unclear. Here, we show that two phosphatidylinositol 3-kinase- and protein synthesis-dependent forms of synaptic plasticity, theta burst-induced long-term potentiation and metabotropic glutamate receptor (mGluR)-dependent long-term depression, are dysregulated at medial perforant path-to-dentate gyrus synapses of young Nse-Cre Pten conditional knockout mice before the onset of visible morphological abnormalities. In contrast, long-term potentiation and mGluR-dependent long-term depression are normal at CA3-CA1 pyramidal cell synapses at this age. Our results reveal that deletion of Pten in dentate granule cells dysregulates synaptic plasticity, a defect that may underlie abnormal social and cognitive behaviors observed in humans with Pten inactivating mutations and potentially other autism spectrum disorders.

Plasticity of orientation preference maps in the visual cortex of adult cats.

PubMed

Godde, Ben; Leonhardt, Ralph; Cords, Sven M; Dinse, Hubert R

2002-04-30

In contrast to the high degree of experience-dependent plasticity usually exhibited by cortical representational maps, a number of experiments performed in visual cortex suggest that the basic layout of orientation preference maps is only barely susceptible to activity-dependent modifications. In fact, most of what we know about activity-dependent plasticity in adults comes from experiments in somatosensory, auditory, or motor cortex. Applying a stimulation protocol that has been proven highly effective in other cortical areas, we demonstrate here that enforced synchronous cortical activity induces major changes of orientation preference maps (OPMs) in adult cats. Combining optical imaging of intrinsic signals and electrophysiological single-cell recordings, we show that a few hours of intracortical microstimulation (ICMS) lead to an enlargement of the cortical representational zone at the ICMS site and an extensive restructuring of the entire OPM layout up to several millimeters away, paralleled by dramatic changes of pinwheel numbers and locations. At the single-cell level, we found that the preferred orientation was shifted toward the orientation of the ICMS site over a region of up to 4 mm. Our results show that manipulating the synchronicity of cortical activity locally without invoking training, attention, or reinforcement, OPMs undergo large-scale reorganization reminiscent of plastic changes observed for nonvisual cortical maps. However, changes were much more widespread and enduring. Such large-scale restructuring of the visual cortical networks indicates a substantial capability for activity-dependent plasticity of adult visual cortex and may provide the basis for cognitive learning processes.

Categorizing experience-based foraging plasticity in mites: age dependency, primacy effects and memory persistence

PubMed Central

Davaasambuu, Undarmaa; Saussure, Stéphanie; Christiansen, Inga C.

2018-01-01

Behavioural plasticity can be categorized into activational (also termed contextual) and developmental plasticity. Activational plasticity allows immediate contextual behavioural changes, whereas developmental plasticity is characterized by time-lagged changes based on memory of previous experiences (learning). Behavioural plasticity tends to decline with age but whether this holds true for both plasticity categories and the effects of first-in-life experiences is poorly understood. We tackled this issue by assessing the foraging plasticity of plant-inhabiting predatory mites, Amblyseius swirskii, on thrips and spider mites following age-dependent prey experience, i.e. after hatching or after reaching maturity. Juvenile and young adult predator females were alternately presented thrips and spider mites, for establishing 1st and 2nd prey-in-life experiences, and tested, as gravid females, for their foraging plasticity when offered both prey species. Prey experience by juvenile predators resulted in clear learning effects, which were evident in likelier and earlier attacks on familiar prey, and higher proportional inclusion of familiar prey in total diet. First prey-in-life experience by juvenile but not adult predators resulted in primacy effects regarding attack latency. Prey experience by adult predators resulted mainly in prey-unspecific physiological changes, with easy-to-grasp spider mites providing higher net energy gains than difficult-to-grasp thrips. Prey experience by juvenile, but not adult, predators was adaptive, which was evident in a negative correlation between attack latencies and egg production. Overall, our study provides key evidence that similar experiences by juvenile and adult predators, including first-in-life experiences, may be associated with different types of behavioural plasticity, i.e. developmental and activational plasticity. PMID:29765663

Categorizing experience-based foraging plasticity in mites: age dependency, primacy effects and memory persistence.

PubMed

Schausberger, Peter; Davaasambuu, Undarmaa; Saussure, Stéphanie; Christiansen, Inga C

2018-04-01

Behavioural plasticity can be categorized into activational (also termed contextual) and developmental plasticity. Activational plasticity allows immediate contextual behavioural changes, whereas developmental plasticity is characterized by time-lagged changes based on memory of previous experiences (learning). Behavioural plasticity tends to decline with age but whether this holds true for both plasticity categories and the effects of first-in-life experiences is poorly understood. We tackled this issue by assessing the foraging plasticity of plant-inhabiting predatory mites, Amblyseius swirskii , on thrips and spider mites following age-dependent prey experience, i.e. after hatching or after reaching maturity. Juvenile and young adult predator females were alternately presented thrips and spider mites, for establishing 1st and 2nd prey-in-life experiences, and tested, as gravid females, for their foraging plasticity when offered both prey species. Prey experience by juvenile predators resulted in clear learning effects, which were evident in likelier and earlier attacks on familiar prey, and higher proportional inclusion of familiar prey in total diet. First prey-in-life experience by juvenile but not adult predators resulted in primacy effects regarding attack latency. Prey experience by adult predators resulted mainly in prey-unspecific physiological changes, with easy-to-grasp spider mites providing higher net energy gains than difficult-to-grasp thrips. Prey experience by juvenile, but not adult, predators was adaptive, which was evident in a negative correlation between attack latencies and egg production. Overall, our study provides key evidence that similar experiences by juvenile and adult predators, including first-in-life experiences, may be associated with different types of behavioural plasticity, i.e. developmental and activational plasticity.

Mechanical and time-dependent behavior of wood-plastic composites subjected to tension and compression

Treesearch

Scott E. Hamel; John C. Hermanson; Steven M. Cramer

2012-01-01

The thermoplastics within wood—plastic composites (WPCs) are known to experience significant time-dependent deformation or creep. In some formulations, creep deformation can be twice as much as the initial quasi-static strain in as little as 4 days. While extensive work has been done on the creep behavior of pure polymers, little information is available on the...

Neurometaplasticity: Glucoallostasis control of plasticity of the neural networks of error commission, detection, and correction modulates neuroplasticity to influence task precision

NASA Astrophysics Data System (ADS)

Welcome, Menizibeya O.; Dane, Şenol; Mastorakis, Nikos E.; Pereverzev, Vladimir A.

2017-12-01

The term "metaplasticity" is a recent one, which means plasticity of synaptic plasticity. Correspondingly, neurometaplasticity simply means plasticity of neuroplasticity, indicating that a previous plastic event determines the current plasticity of neurons. Emerging studies suggest that neurometaplasticity underlie many neural activities and neurobehavioral disorders. In our previous work, we indicated that glucoallostasis is essential for the control of plasticity of the neural network that control error commission, detection and correction. Here we review recent works, which suggest that task precision depends on the modulatory effects of neuroplasticity on the neural networks of error commission, detection, and correction. Furthermore, we discuss neurometaplasticity and its role in error commission, detection, and correction.

Two Back Stress Hardening Models in Rate Independent Rigid Plastic Deformation

NASA Astrophysics Data System (ADS)

Yun, Su-Jin

In the present work, the constitutive relations based on the combination of two back stresses are developed using the Armstrong-Frederick, Phillips and Ziegler’s type hardening rules. Various evolutions of the kinematic hardening parameter can be obtained by means of a simple combination of back stress rate using the rule of mixtures. Thus, a wide range of plastic deformation behavior can be depicted depending on the dominant back stress evolution. The ultimate back stress is also determined for the present combined kinematic hardening models. Since a kinematic hardening rule is assumed in the finite deformation regime, the stress rate is co-rotated with respect to the spin of substructure obtained by incorporating the plastic spin concept. A comparison of the various co-rotational rates is also included. Assuming rigid plasticity, the continuum body consists of the elastic deformation zone and the plastic deformation zone to form a hybrid finite element formulation. Then, the plastic deformation behavior is investigated under various loading conditions with an assumption of the J2 deformation theory. The plastic deformation localization turns out to be strongly dependent on the description of back stress evolution and its associated hardening parameters. The analysis for the shear deformation with fixed boundaries is carried out to examine the deformation localization behavior and the evolution of state variables.

Phenotypic Plasticity of Cuticular Hydrocarbon Profiles in Insects.

PubMed

Otte, Tobias; Hilker, Monika; Geiselhardt, Sven

2018-03-01

The insect integument is covered by cuticular hydrocarbons (CHCs) which provide protection against environmental stresses, but are also used for communication. Here we review current knowledge on environmental and insect-internal factors which shape phenotypic plasticity of solitary living insects, especially herbivorous ones. We address the dynamics of changes which may occur within minutes, but may also last weeks, depending on the species and conditions. Two different modes of changes are suggested, i.e. stepwise and gradual. A switch between two distinct environments (e.g. host plant switch by phytophagous insects) results in stepwise formation of two distinct adaptive phenotypes, while a gradual environmental change (e.g. temperature gradients) induces a gradual change of numerous adaptive CHC phenotypes. We further discuss the ecological and evolutionary consequences of phenotypic plasticity of insect CHC profiles by addressing the question at which conditions is CHC phenotypic plasticity beneficial. The high plasticity of CHC profiles might be a trade-off for insects using CHCs for communication. We discuss how insects cope with the challenge to produce and "understand" a highly plastic, environmentally dependent CHC pattern that conveys reliable and comprehensible information. Finally, we outline how phenotypic plasticity of CHC profiles may promote speciation in insects that rely on CHCs for mate recognition.

A study on the uniqueness of the plastic flow direction for granular assemblies of ductile particles using discrete finite-element simulations

NASA Astrophysics Data System (ADS)

Abdelmoula, Nouha; Harthong, Barthélémy; Imbault, Didier; Dorémus, Pierre

2017-12-01

The multi-particle finite element method involving assemblies of meshed particles interacting through finite-element contact conditions is adopted to study the plastic flow of a granular material with highly deformable elastic-plastic grains. In particular, it is investigated whether the flow rule postulate applies for such materials. Using a spherical stress probing method, the influence of incremental stress on plastic strain increment vectors was assessed for numerical samples compacted along two different loading paths up to different values of relative density. Results show that the numerical samples studied behave reasonably well according to an associated flow rule, except in the vicinity of the loading point where the influence of the stress increment proved to be very significant. A plausible explanation for the non-uniqueness of the direction of plastic flow is proposed, based on the idea that the resistance of the numerical sample to plastic straining can vary by an order of magnitude depending on the direction of the accumulated stress. The above-mentioned dependency of the direction of plastic flow on the direction of the stress increment was related to the difference in strength between shearing and normal stressing at the scale of contact surfaces between particles.

Pannexin 1 regulates bidirectional hippocampal synaptic plasticity in adult mice.

PubMed

Ardiles, Alvaro O; Flores-Muñoz, Carolina; Toro-Ayala, Gabriela; Cárdenas, Ana M; Palacios, Adrian G; Muñoz, Pablo; Fuenzalida, Marco; Sáez, Juan C; Martínez, Agustín D

2014-01-01

The threshold for bidirectional modification of synaptic plasticity is known to be controlled by several factors, including the balance between protein phosphorylation and dephosphorylation, postsynaptic free Ca(2+) concentration and NMDA receptor (NMDAR) composition of GluN2 subunits. Pannexin 1 (Panx1), a member of the integral membrane protein family, has been shown to form non-selective channels and to regulate the induction of synaptic plasticity as well as hippocampal-dependent learning. Although Panx1 channels have been suggested to play a role in excitatory long-term potentiation (LTP), it remains unknown whether these channels also modulate long-term depression (LTD) or the balance between both types of synaptic plasticity. To study how Panx1 contributes to excitatory synaptic efficacy, we examined the age-dependent effects of eliminating or blocking Panx1 channels on excitatory synaptic plasticity within the CA1 region of the mouse hippocampus. By using different protocols to induce bidirectional synaptic plasticity, Panx1 channel blockade or lack of Panx1 were found to enhance LTP, whereas both conditions precluded the induction of LTD in adults, but not in young animals. These findings suggest that Panx1 channels restrain the sliding threshold for the induction of synaptic plasticity and underlying brain mechanisms of learning and memory.

Pannexin 1 regulates bidirectional hippocampal synaptic plasticity in adult mice

PubMed Central

Ardiles, Alvaro O.; Flores-Muñoz, Carolina; Toro-Ayala, Gabriela; Cárdenas, Ana M.; Palacios, Adrian G.; Muñoz, Pablo; Fuenzalida, Marco; Sáez, Juan C.; Martínez, Agustín D.

2014-01-01

The threshold for bidirectional modification of synaptic plasticity is known to be controlled by several factors, including the balance between protein phosphorylation and dephosphorylation, postsynaptic free Ca2+ concentration and NMDA receptor (NMDAR) composition of GluN2 subunits. Pannexin 1 (Panx1), a member of the integral membrane protein family, has been shown to form non-selective channels and to regulate the induction of synaptic plasticity as well as hippocampal-dependent learning. Although Panx1 channels have been suggested to play a role in excitatory long-term potentiation (LTP), it remains unknown whether these channels also modulate long-term depression (LTD) or the balance between both types of synaptic plasticity. To study how Panx1 contributes to excitatory synaptic efficacy, we examined the age-dependent effects of eliminating or blocking Panx1 channels on excitatory synaptic plasticity within the CA1 region of the mouse hippocampus. By using different protocols to induce bidirectional synaptic plasticity, Panx1 channel blockade or lack of Panx1 were found to enhance LTP, whereas both conditions precluded the induction of LTD in adults, but not in young animals. These findings suggest that Panx1 channels restrain the sliding threshold for the induction of synaptic plasticity and underlying brain mechanisms of learning and memory. PMID:25360084

Explicit 2-D Hydrodynamic FEM Program

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lin, Jerry

1996-08-07

DYNA2D* is a vectorized, explicit, two-dimensional, axisymmetric and plane strain finite element program for analyzing the large deformation dynamic and hydrodynamic response of inelastic solids. DYNA2D* contains 13 material models and 9 equations of state (EOS) to cover a wide range of material behavior. The material models implemented in all machine versions are: elastic, orthotropic elastic, kinematic/isotropic elastic plasticity, thermoelastoplastic, soil and crushable foam, linear viscoelastic, rubber, high explosive burn, isotropic elastic-plastic, temperature-dependent elastic-plastic. The isotropic and temperature-dependent elastic-plastic models determine only the deviatoric stresses. Pressure is determined by one of 9 equations of state including linear polynomial, JWL highmore » explosive, Sack Tuesday high explosive, Gruneisen, ratio of polynomials, linear polynomial with energy deposition, ignition and growth of reaction in HE, tabulated compaction, and tabulated.« less

Estimating Tunnel Strain in the Weak and Schistose Rock Mass Influenced by Stress Anisotropy: An Evaluation Based on Three Tunnel Cases from Nepal

NASA Astrophysics Data System (ADS)

Panthi, Krishna Kanta; Shrestha, Pawan Kumar

2018-06-01

Total plastic deformation in tunnels passing through weak and schistose rock mass consists of both time-independent and time-dependent deformations. The extent of this total deformation is heavily influenced by the rock mass deformability properties and in situ stress condition prevailing in the area. If in situ stress is not isotropic, the deformation magnitude is not only different along the longitudinal alignment but also along the periphery of the tunnel wall. This manuscript first evaluates the long-term plastic deformation records of three tunnel projects from the Nepal Himalaya and identifies interlink between the time-independent and time-dependent deformations using the convergence law proposed by Sulem et al. (Int J Rock Mech Min Sci Geomech 24(3):145-154, 1987a, Int J Rock Mech Min Sci Geomech 24(3):155-164, 1987b). Secondly, the manuscript attempts to establish a correlation between plastic deformations (tunnel strain) and rock mass deformable properties, support pressure and in situ stress conditions. Finally, patterns of time-independent and time-dependent plastic deformations are also evaluated and discussed. The long-term plastic deformation records of 24 tunnel sections representing four different rock types of three different headrace tunnel cases from Nepal Himalaya are extensively used in this endeavor. The authors believe that the proposed findings will be a step further in analysis of plastic deformations in tunnels passing through weak and schistose rock mass and along the anisotropic stress conditions.

Dopaminergic tone persistently regulates voltage-gated ion current densities through the D1R-PKA axis, RNA polymerase II transcription, RNAi, mTORC1, and translation

PubMed Central

Krenz, Wulf-Dieter C.; Parker, Anna R.; Rodgers, Edmund W.; Baro, Deborah J.

2014-01-01

Long-term intrinsic and synaptic plasticity must be coordinated to ensure stability and flexibility in neuronal circuits. Coordination might be achieved through shared transduction components. Dopamine (DA) is a well-established participant in many forms of long-term synaptic plasticity. Recent work indicates that DA is also involved in both activity-dependent and -independent forms of long-term intrinsic plasticity. We previously examined DA-enabled long-term intrinsic plasticity in a single identified neuron. The lateral pyloric (LP) neuron is a component of the pyloric network in the crustacean stomatogastric nervous system (STNS). LP expresses type 1 DA receptors (D1Rs). A 1 h bath application of 5 nM DA followed by washout produced a significant increase in the maximal conductance (Gmax) of the LP transient potassium current (IA) that peaked ~4 h after the start of DA application; furthermore, if a change in neuronal activity accompanied the DA application, then a persistent increase in the LP hyperpolarization activated current (Ih) was also observed. Here, we repeated these experiments with pharmacological and peptide inhibitors to determine the cellular processes and signaling proteins involved. We discovered that the persistent, DA-induced activity-independent (IA) and activity-dependent (Ih) changes in ionic conductances depended upon many of the same elements that enable long-term synaptic plasticity, including: the D1R-protein kinase A (PKA) axis, RNA polymerase II transcription, RNA interference (RNAi), and mechanistic target of rapamycin (mTOR)-dependent translation. We interpret the data to mean that increasing the tonic DA concentration enhances expression of a microRNA(s) (miRs), resulting in increased cap-dependent translation of an unidentified protein(s). PMID:24596543

A Review on Landfill Management in the Utilization of Plastic Waste as an Alternative Fuel

NASA Astrophysics Data System (ADS)

Hidayah, Nurul; Syafrudin

2018-02-01

Wastes from landfills originate from many spheres of life. These are produces as a result of human activities either domestically or industrially. The global plastic production increased over years due to the vast applications of plastics in many sectors. The continuous demand of plastics caused the plastic wastes accumulation in the landfill consumed a lot of spaces that contributed to the environmental. In addition, economic growth and development also increased our demand and dependency on plastics which leads to its accumulation in landfills imposing risk on human health, animals and cause environmental pollution problems such as ground water contamination, sanitary related issues, etc. The management and disposal of plastic waste have become a major concern, especially in developing cities. The idea of waste to energy recovery is one of the promising techniques used for managing the waste of plastic. Hence, this paper aims review at utilizing of plastic as an alternative fuel.

The dependence of granular plasticity on particle shape

NASA Astrophysics Data System (ADS)

Murphy, Kieran; Jaeger, Heinrich

Granular materials plastically deform through reworking an intricate network of particle-particle contacts. Some particle rearrangements have only a fleeting effect before being forgotten while others set in motion global restructuring. How particle shape affects local interactions and how those, in turn, influence the nature of the aggregate's plasticity is far from clear, especially in three dimensions. Here we investigate the remarkably wide range of behaviors in the yielding regime, from quiescent flow to violent jerks, depending on particle shape. We study this complex dependence via uniaxial compression experiments on aggregates of 3D-printed particles, and complement stress-strain data with simultaneous x-ray videos and volumetric strain measurements. We find power law distributions of the slip magnitudes, and discuss their universality. Our data show that the multitude of small slips serves to gradually dilate the packing whereas the fewer large ones accompany significant compaction events. Our findings provide new insights into general features of granular materials during plastic deformation and highlight how small changes in particle shape can give rise to drastic differences in yielding behavior.

Experience-dependent plasticity from eye opening enables lasting, visual cortex-dependent enhancement of motion vision.

PubMed

Prusky, Glen T; Silver, Byron D; Tschetter, Wayne W; Alam, Nazia M; Douglas, Robert M

2008-09-24

Developmentally regulated plasticity of vision has generally been associated with "sensitive" or "critical" periods in juvenile life, wherein visual deprivation leads to loss of visual function. Here we report an enabling form of visual plasticity that commences in infant rats from eye opening, in which daily threshold testing of optokinetic tracking, amid otherwise normal visual experience, stimulates enduring, visual cortex-dependent enhancement (>60%) of the spatial frequency threshold for tracking. The perceptual ability to use spatial frequency in discriminating between moving visual stimuli is also improved by the testing experience. The capacity for inducing enhancement is transitory and effectively limited to infancy; however, enhanced responses are not consolidated and maintained unless in-kind testing experience continues uninterrupted into juvenile life. The data show that selective visual experience from infancy can alone enable visual function. They also indicate that plasticity associated with visual deprivation may not be the only cause of developmental visual dysfunction, because we found that experientially inducing enhancement in late infancy, without subsequent reinforcement of the experience in early juvenile life, can lead to enduring loss of function.

Myelination: an overlooked mechanism of synaptic plasticity?

PubMed

Fields, R Douglas

2005-12-01

Myelination of the brain continues through childhood into adolescence and early adulthood--the question is, Why? Two new articles provide intriguing evidence that myelination may be an underappreciated mechanism of activity-dependent nervous system plasticity: one study reported increased myelination associated with extensive piano playing, another indicated that rats have increased myelination of the corpus callosum when raised in environments providing increased social interaction and cognitive stimulation. These articles make it clear that activity-dependent effects on myelination cannot be considered strictly a developmental event. They raise the question of whether myelination is an overlooked mechanism of activity-dependent plasticity, extending in humans until at least age 30. It has been argued that regulating the speed of conduction across long fiber tracts would have a major influence on synaptic response, by coordinating the timing of afferent input to maximize temporal summation. The increase in synaptic amplitude could be as large as neurotransmitter-based mechanisms of plasticity, such as LTP. These new findings raise a larger question: How did the oligodendrocytes know they were practicing the piano or that their environment was socially complex?

Climate change and temperature-dependent sex determination: can individual plasticity in nesting phenology prevent extreme sex ratios?

PubMed

Schwanz, Lisa E; Janzen, Fredric J

2008-01-01

Under temperature-dependent sex determination (TSD), temperatures experienced by embryos during development determine the sex of the offspring. Consequently, populations of organisms with TSD have the potential to be strongly impacted by climatic warming that could bias offspring sex ratio, a fundamental demographic parameter involved in population dynamics. Moreover, many taxa with TSD are imperiled, so research on this phenomenon, particularly long-term field study, has assumed great urgency. Recently, turtles with TSD have joined the diverse list of taxa that have demonstrated population-level changes in breeding phenology in response to recent climate change. This raises the possibility that any adverse impacts of climate change on populations may be alleviated by individual plasticity in nesting phenology. Here, we examine data from a long-term study on a population of painted turtles (Chrysemys picta) to determine whether changes in phenology are due to individual plasticity and whether individual plasticity in the timing of nesting has the capacity to offset the sex ratio effects of a rise in climatic temperature. We find that individual females show plasticity in the date of first nesting each year, and that this plasticity depends on the climate from the previous winter. First nesting date is not repeatable within individuals, suggesting that it would not respond to selection. Sex ratios of hatchlings within a nest declined nonsignificantly over the nesting season. However, small increases in summer temperature had a much stronger effect on nest sex ratios than did laying nests earlier in the season. For this and other reasons, it seems unlikely that individual plasticity in the timing of nesting will offset the effects of climate change on sex ratios in this population, and we hypothesize that this conclusion applies to other populations with TSD.

Analysis and Modeling of Process of Residual Deformations Accumulation in Soils and Granular Materials

NASA Astrophysics Data System (ADS)

Aleksandrov, A. S.; Dolgih, G. V.; Kalinin, A. L.

2017-11-01

It is established that under the influence of repeated loads the process of plastic deformation in soils and discrete materials is hereditary. To perform the mathematical modeling of plastic deformation, the authors applied the integral equation by solution of which they manage to obtain the power and logarithmic dependencies connecting plastic deformation with the number of repeated loads, the parameters of the material and components of the stress tensor in the principal axes. It is shown that these dependences generalize a number of models proposed earlier in Russia and abroad. Based on the analysis of the experimental data obtained during material testing in the dynamic devices of triaxial compression at different values of the stress deviator, the coefficients in the proposed models of deformation are determined. The authors determined the application domain for logarithmic and degree dependences.

Spatial Object Recognition Enables Endogenous LTD that Curtails LTP in the Mouse Hippocampus

PubMed Central

Goh, Jinzhong Jeremy

2013-01-01

Although synaptic plasticity is believed to comprise the cellular substrate for learning and memory, limited direct evidence exists that hippocampus-dependent learning actually triggers synaptic plasticity. It is likely, however, that long-term potentiation (LTP) works in concert with its counterpart, long-term depression (LTD) in the creation of spatial memory. It has been reported in rats that weak synaptic plasticity is facilitated into persistent plasticity if afferent stimulation is coupled with a novel spatial learning event. It is not known if this phenomenon also occurs in other species. We recorded from the hippocampal CA1 of freely behaving mice and observed that novel spatial learning triggers endogenous LTD. Specifically, we observed that LTD is enabled when test-pulse afferent stimulation is given during the learning of object constellations or during a spatial object recognition task. Intriguingly, LTP is significantly impaired by the same tasks, suggesting that LTD is the main cellular substrate for this type of learning. These data indicate that learning-facilitated plasticity is not exclusive to rats and that spatial learning leads to endogenous LTD in the hippocampus, suggesting an important role for this type of synaptic plasticity in the creation of hippocampus-dependent memory. PMID:22510536

Development of mathematical models for automation of strength calculation during plastic deformation processing

NASA Astrophysics Data System (ADS)

Steposhina, S. V.; Fedonin, O. N.

2018-03-01

Dependencies that make it possible to automate the force calculation during surface plastic deformation (SPD) processing and, thus, to shorten the time for technological preparation of production have been developed.

Inhibition of Morphine Tolerance and Dependence by the NMDA Receptor Antagonist MK-801

NASA Astrophysics Data System (ADS)

Trujillo, Keith A.; Akil, Huda

1991-01-01

The N-methyl-D-aspartate (NMDA) subtype of the glutamate receptor is an important mediator of several forms of neural and behavioral plasticity. The present studies examined whether NMDA receptors might be involved in the development of opiate tolerance and dependence, two examples of behavioral plasticity. The noncompetitive NMDA receptor antagonist MK-801 attenuated the development of tolerance to the analgesic effect of morphine without affecting acute morphine analgesia. In addition, MK-801 attenuated the development of morphine dependence as assessed by naloxone-precipitated withdrawal. These results suggest that NMDA receptors may be important in the development of opiate tolerance and dependence.

Properties of vapor detector arrays formed through plasticization of carbon black-organic polymer composites.

PubMed

Koscho, Michael E; Grubbs, Robert H; Lewis, Nathan S

2002-03-15

Arrays of vapor detectors have been formed through addition of varying mass fractions of the plasticizer diethylene glycol dibenzoate to carbon black-polymer composites of poly(vinyl acetate) (PVAc) or of poly(N-vinylpyrrolidone). Addition of plasticizer in 5% mass fraction increments produced 20 compositionally different detectors from each polymer composite. Differences in vapor sorption and permeability that effected changes in the dc electrical resistance response of these compositionally different detectors allowed identification and classification of various test analytes using standard chemometric methods. Glass transition temperatures, Tg, were measured using differential scanning calorimetry for plasticized polymers having a mass fraction of 0, 0.10, 0.20, 0.30, 0.40, or 0.50 of plasticizer in the composite. The plasticized PVAc composites with Tg < 25 degrees C showed rapid responses at room temperature to all of the test analyte vapors studied in this work, whereas composites with Tg > 25 degrees C showed response times that were highly dependent on the polymer/analyte combination. These composites showed a discontinuity in the temperature dependence of their resistance, and this discontinuity provided a simple method for determining the Tg of the composite and for determining the temperature or plasticizer mass fraction above which rapid resistance responses could be obtained for all members of the test set of analyte vapors. The plasticization approach provides a method for achieving rapid detector response times as well as for producing a large number of chemically different vapor detectors from a limited number of initial chemical feedstocks.

JIP1-Mediated JNK Activation Negatively Regulates Synaptic Plasticity and Spatial Memory.

PubMed

Morel, Caroline; Sherrin, Tessi; Kennedy, Norman J; Forest, Kelly H; Avcioglu Barutcu, Seda; Robles, Michael; Carpenter-Hyland, Ezekiel; Alfulaij, Naghum; Standen, Claire L; Nichols, Robert A; Benveniste, Morris; Davis, Roger J; Todorovic, Cedomir

2018-04-11

The c-Jun N-terminal kinase (JNK) signal transduction pathway is implicated in learning and memory. Here, we examined the role of JNK activation mediated by the JNK-interacting protein 1 (JIP1) scaffold protein. We compared male wild-type mice with a mouse model harboring a point mutation in the Jip1 gene that selectively blocks JIP1-mediated JNK activation. These male mutant mice exhibited increased NMDAR currents, increased NMDAR-mediated gene expression, and a lower threshold for induction of hippocampal long-term potentiation. The JIP1 mutant mice also displayed improved hippocampus-dependent spatial memory and enhanced associative fear conditioning. These results were confirmed using a second JIP1 mutant mouse model that suppresses JNK activity. Together, these observations establish that JIP1-mediated JNK activation contributes to the regulation of hippocampus-dependent, NMDAR-mediated synaptic plasticity and learning. SIGNIFICANCE STATEMENT The results of this study demonstrate that c-Jun N-terminal kinase (JNK) activation induced by the JNK-interacting protein 1 (JIP1) scaffold protein negatively regulates the threshold for induction of long-term synaptic plasticity through the NMDA-type glutamate receptor. This change in plasticity threshold influences learning. Indeed, mice with defects in JIP1-mediated JNK activation display enhanced memory in hippocampus-dependent tasks, such as contextual fear conditioning and Morris water maze, indicating that JIP1-JNK constrains spatial memory. This study identifies JIP1-mediated JNK activation as a novel molecular pathway that negatively regulates NMDAR-dependent synaptic plasticity and memory. Copyright © 2018 the authors 0270-6474/18/383708-21$15.00/0.

The Dependence of Strength in Plastics upon Polymer Chain Length and Chain Orientation: An Experiment Emphasizing the Statistical Handling and Evaluation of Data.

ERIC Educational Resources Information Center

Spencer, R. Donald

1984-01-01

Describes an experiment (using plastic bags) designed to give students practical understanding on using statistics to evaluate data and how statistical treatment of experimental results can enhance their value in solving scientific problems. Students also gain insight into the orientation and structure of polymers by examining the plastic bags.…

Environmental enrichment accelerates ocular dominance plasticity in mouse visual cortex whereas transfer to standard cages resulted in a rapid loss of increased plasticity.

PubMed

Kalogeraki, Evgenia; Pielecka-Fortuna, Justyna; Löwel, Siegrid

2017-01-01

In standard cage (SC) raised mice, experience-dependent ocular dominance (OD) plasticity in the primary visual cortex (V1) rapidly declines with age: in postnatal day 25-35 (critical period) mice, 4 days of monocular deprivation (MD) are sufficient to induce OD-shifts towards the open eye; thereafter, 7 days of MD are needed. Beyond postnatal day 110, even 14 days of MD failed to induce OD-plasticity in mouse V1. In contrast, mice raised in a so-called "enriched environment" (EE), exhibit lifelong OD-plasticity. EE-mice have more voluntary physical exercise (running wheels), and experience more social interactions (bigger housing groups) and more cognitive stimulation (regularly changed labyrinths or toys). Whether experience-dependent shifts of V1-activation happen faster in EE-mice and how long the plasticity promoting effect would persist after transferring EE-mice back to SCs has not yet been investigated. To this end, we used intrinsic signal optical imaging to visualize V1-activation i) before and after MD in EE-mice of different age groups (from 1-9 months), and ii) after transferring mice back to SCs after postnatal day 130. Already after 2 days of MD, and thus much faster than in SC-mice, EE-mice of all tested age groups displayed a significant OD-shift towards the open eye. Transfer of EE-mice to SCs immediately abolished OD-plasticity: already after 1 week of SC-housing and MD, OD-shifts could no longer be visualized. In an attempt to rescue abolished OD-plasticity of these mice, we either administered the anti-depressant fluoxetine (in drinking water) or supplied a running wheel in the SCs. OD-plasticity was only rescued for the running wheel- mice. Altogether our results show that raising mice in less deprived environments like large EE-cages strongly accelerates experience-dependent changes in V1-activation compared to the impoverished SC-raising. Furthermore, preventing voluntary physical exercise of EE-mice in adulthood immediately precludes OD-shifts in V1.

Environmental enrichment accelerates ocular dominance plasticity in mouse visual cortex whereas transfer to standard cages resulted in a rapid loss of increased plasticity

PubMed Central

Pielecka-Fortuna, Justyna; Löwel, Siegrid

2017-01-01

In standard cage (SC) raised mice, experience-dependent ocular dominance (OD) plasticity in the primary visual cortex (V1) rapidly declines with age: in postnatal day 25–35 (critical period) mice, 4 days of monocular deprivation (MD) are sufficient to induce OD-shifts towards the open eye; thereafter, 7 days of MD are needed. Beyond postnatal day 110, even 14 days of MD failed to induce OD-plasticity in mouse V1. In contrast, mice raised in a so-called “enriched environment” (EE), exhibit lifelong OD-plasticity. EE-mice have more voluntary physical exercise (running wheels), and experience more social interactions (bigger housing groups) and more cognitive stimulation (regularly changed labyrinths or toys). Whether experience-dependent shifts of V1-activation happen faster in EE-mice and how long the plasticity promoting effect would persist after transferring EE-mice back to SCs has not yet been investigated. To this end, we used intrinsic signal optical imaging to visualize V1-activation i) before and after MD in EE-mice of different age groups (from 1–9 months), and ii) after transferring mice back to SCs after postnatal day 130. Already after 2 days of MD, and thus much faster than in SC-mice, EE-mice of all tested age groups displayed a significant OD-shift towards the open eye. Transfer of EE-mice to SCs immediately abolished OD-plasticity: already after 1 week of SC-housing and MD, OD-shifts could no longer be visualized. In an attempt to rescue abolished OD-plasticity of these mice, we either administered the anti-depressant fluoxetine (in drinking water) or supplied a running wheel in the SCs. OD-plasticity was only rescued for the running wheel- mice. Altogether our results show that raising mice in less deprived environments like large EE-cages strongly accelerates experience-dependent changes in V1-activation compared to the impoverished SC-raising. Furthermore, preventing voluntary physical exercise of EE-mice in adulthood immediately precludes OD-shifts in V1. PMID:29073219

Determination of the ductile-brittle transition temperature from the microplastic-strain rate

NASA Astrophysics Data System (ADS)

Andreev, A. K.; Solntsev, Yu. P.

2008-04-01

The possibility of the determination of the tendency of cast and deformed steels to brittle fracture using the temperature dependence of the small-plastic-strain rate is studied. The temperature corresponding to the maximum in this curve is found to indicate an abrupt decrease in the steel plasticity, which makes it possible to interpret it as the ductile-brittle transition temperature depending only on the structure of a material.

Atomistic basis for the plastic yield criterion of metallic glass.

PubMed

Schuh, Christopher A; Lund, Alan C

2003-07-01

Because of their disordered atomic structure, amorphous metals (termed metallic glasses) have fundamentally different deformation mechanisms compared with polycrystalline metals. These different mechanisms give metallic glasses high strength, but the extent to which they affect other macroscopic deformation properties is uncertain. For example, the nature of the plastic-yield criterion is a point of contention, with some studies reporting yield behaviour roughly in line with that of polycrystalline metals, and others indicating strong fundamental differences. In particular, it is unclear whether pressure- or normal stress-dependence needs to be included in the plastic-yield criterion of metallic glasses, and how such a dependence could arise from their disordered structure. In this work we provide an atomic-level explanation for pressure-dependent yield in amorphous metals, based on an elementary unit of deformation. This simple model compares favourably with new atomistic simulations of metallic glasses, as well as existing experimental data.

Neuromodulated Spike-Timing-Dependent Plasticity, and Theory of Three-Factor Learning Rules.

PubMed

Frémaux, Nicolas; Gerstner, Wulfram

2015-01-01

Classical Hebbian learning puts the emphasis on joint pre- and postsynaptic activity, but neglects the potential role of neuromodulators. Since neuromodulators convey information about novelty or reward, the influence of neuromodulators on synaptic plasticity is useful not just for action learning in classical conditioning, but also to decide "when" to create new memories in response to a flow of sensory stimuli. In this review, we focus on timing requirements for pre- and postsynaptic activity in conjunction with one or several phasic neuromodulatory signals. While the emphasis of the text is on conceptual models and mathematical theories, we also discuss some experimental evidence for neuromodulation of Spike-Timing-Dependent Plasticity. We highlight the importance of synaptic mechanisms in bridging the temporal gap between sensory stimulation and neuromodulatory signals, and develop a framework for a class of neo-Hebbian three-factor learning rules that depend on presynaptic activity, postsynaptic variables as well as the influence of neuromodulators.

Spike-timing dependent plasticity in primate corticospinal connections induced during free behavior

PubMed Central

Nishimura, Yukio; Perlmutter, Steve I.; Eaton, Ryan W.; Fetz, Eberhard E.

2014-01-01

Motor learning and functional recovery from brain damage involve changes in the strength of synaptic connections between neurons. Relevant in vivo evidence on the underlying cellular mechanisms remains limited and indirect. We found that the strength of neural connections between motor cortex and spinal cord in monkeys can be modified with an autonomous recurrent neural interface that delivers electrical stimuli in the spinal cord triggered by action potentials of corticospinal cells during free behavior. The activity-dependent stimulation modified the strength of the terminal connections of single corticomotoneuronal cells, consistent with a bidirectional spike-timing dependent plasticity rule previously derived from in vitro experiments. For some cells the changes lasted for days after the end of conditioning, but most effects eventually reverted to preconditioning levels. These results provide the first direct evidence of corticospinal synaptic plasticity in vivo at the level of single neurons induced by normal firing patterns during free behavior. PMID:24210907

MicroRNA-132 regulates recognition memory and synaptic plasticity in the perirhinal cortex

PubMed Central

Scott, Helen L; Tamagnini, Francesco; Narduzzo, Katherine E; Howarth, Joanna L; Lee, Youn-Bok; Wong, Liang-Fong; Brown, Malcolm W; Warburton, Elizabeth C; Bashir, Zafar I; Uney, James B

2012-01-01

Evidence suggests that the acquisition of recognition memory depends upon CREB-dependent long-lasting changes in synaptic plasticity in the perirhinal cortex. The CREB-responsive microRNA miR-132 has been shown to regulate synaptic transmission and we set out to investigate a role for this microRNA in recognition memory and its underlying plasticity mechanisms. To this end we mediated the specific overexpression of miR-132 selectively in the rat perirhinal cortex and demonstrated impairment in short-term recognition memory. This functional deficit was associated with a reduction in both long-term depression and long-term potentiation. These results confirm that microRNAs are key coordinators of the intracellular pathways that mediate experience-dependent changes in the brain. In addition, these results demonstrate a role for miR-132 in the neuronal mechanisms underlying the formation of short-term recognition memory. PMID:22845676

Activity-Dependent NPAS4 Expression and the Regulation of Gene Programs Underlying Plasticity in the Central Nervous System

PubMed Central

2013-01-01

The capability of the brain to change functionally in response to sensory experience is most active during early stages of development but it decreases later in life when major alterations of neuronal network structures no longer take place in response to experience. This view has been recently challenged by experimental strategies based on the enhancement of environmental stimulation levels, genetic manipulations, and pharmacological treatments, which all have demonstrated that the adult brain retains a degree of plasticity that allows for a rewiring of neuronal circuitries over the entire life course. A hot spot in the field of neuronal plasticity centres on gene programs that underlie plastic phenomena in adulthood. Here, I discuss the role of the recently discovered neuronal-specific and activity-dependent transcription factor NPAS4 as a critical mediator of plasticity in the nervous system. A better understanding of how modifications in the connectivity of neuronal networks occur may shed light on the treatment of pathological conditions such as brain damage or disease in adult life, some of which were once considered untreatable. PMID:24024041

Scattering by tilted plastic cylinders having curved ends and truncated plastic cones

NASA Astrophysics Data System (ADS)

Espana, Aubrey; Baik, Kyungmin; Marston, Philip L.

2005-04-01

In prior research an acoustic backscattering enhancement was demonstrated for a bluntly truncated plastic cylinder caused by a merged caustic [F. J. Blonigen and P. L. Marston, J. Acoust. Soc. Am. 107, 689-698 (2000)]. This was confirmed with analogous light scattering experiments [P. L. Marston, Y. B. Zhang, and D. B. Thiessen, Appl. Opt. 42, 412-417 (2003)]. In recent work a different backscattering enhancement associated with a caustic was identified for tilted plastic cylinders having curved ends. When the cylinder is tilted so as to focus a shear wave at the point of internal specular reflection, the curvature of the outgoing acoustic wavefront vanishes orthogonal to the meridional plane. This was verified with analogous light scattering experiments. The flatness of the outgoing wavefront enhances the scattering. Backscattering by truncated plastic cones as a function of tilt also shows enhancements associated with the composition of the target. The time dependence of the backscattering envelope as a function of tilt reveals different features depending on whether the top or bottom of the cone is illuminated by tone bursts. [Work supported by the Office of Naval Research.

A study on emission of phthalate esters from plastic materials using a passive flux sampler

NASA Astrophysics Data System (ADS)

Fujii, M.; Shinohara, N.; Lim, A.; Otake, T.; Kumagai, K.; Yanagisawa, Y.

Phthalate esters are used as plasticizer in many plastics, and several studies have shown their toxicity. Phthalate esters are gradually emitted over time, and so it is conceivable that they pose a significant health risk. This study aims to investigate the temperature dependence of the emissions of various phthalate esters and to estimate the health risks of these emissions at various temperatures. A passive-type sampler was developed to measure the flux of phthalate esters from the surface of plastic materials. With this sampler, we examined three widely used plastic materials: synthetic leather, wallpaper and vinyl flooring. The observed maximum emissions of diethyl phthalate, dibutyl phthalate, and diethylhexyl phthalate (DEHP) from these materials at 20°C were 0.89, 0.77, and 14 μg m -2 h -1, respectively. Emissions at 80°C were 2.8, 4.5×10 2, and 1.5×10 3 μg m -2 h -1, respectively. The results showed this temperature dependence is determined primarily by the type of phthalate ester and less so by the type of material. The estimation from the results of temperature dependence indicated the concentration of DEHP in a vehicle left out in the sunshine during the day can exceed the recommended levels of Japan Ministry of Health, Labour and Welfare.

Abiotic degradation of plastic films

NASA Astrophysics Data System (ADS)

Ángeles-López, Y. G.; Gutiérrez-Mayen, A. M.; Velasco-Pérez, M.; Beltrán-Villavicencio, M.; Vázquez-Morillas, A.; Cano-Blanco, M.

2017-01-01

Degradable plastics have been promoted as an option to mitigate the environmental impacts of plastic waste. However, there is no certainty about its degradability under different environmental conditions. The effect of accelerated weathering (AW), natural weathering (NW) and thermal oxidation (TO) on different plastics (high density polyethylene, HDPE; oxodegradable high density polyethylene, HDPE-oxo; compostable plastic, Ecovio ® metalized polypropylene, PP; and oxodegradable metalized polypropylene, PP-oxo) was studied. Plastics films were exposed to AW per 110 hours; to NW per 90 days; and to TO per 30 days. Plastic films exposed to AW and NW showed a general loss on mechanical properties. The highest reduction in elongation at break on AW occurred to HDPE-oxo (from 400.4% to 20.9%) and was higher than 90% for HDPE, HDPE-oxo, Ecovio ® and PP-oxo in NW. No substantial evidence of degradation was found on plastics exposed to TO. Oxo-plastics showed higher degradation rates than their conventional counterparts, and the compostable plastic was resistant to degradation in the studied abiotic conditions. This study shows that degradation of plastics in real life conditions will vary depending in both, their composition and the environment.

Lattice Rotation Patterns and Strain Gradient Effects in Face-Centered-Cubic Single Crystals Under Spherical Indentation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gao, Y. F.; Larson, B. C.; Lee, J. H.

Strain gradient effects are commonly modeled as the origin of the size dependence of material strength, such as the dependence of indentation hardness on contact depth and spherical indenter radius. However, studies on the microstructural comparisons of experiments and theories are limited. First, we have extended a strain gradient Mises-plasticity model to its crystal plasticity version and implemented a finite element method to simulate the load-displacement response and the lattice rotation field of Cu single crystals under spherical indentation. The strain gradient simulations demonstrate that the forming of distinct sectors of positive and negative angles in the lattice rotation fieldmore » is governed primarily by the slip geometry and crystallographic orientations, depending only weakly on strain gradient effects, although hardness depends strongly on strain gradients. Second, the lattice rotation simulations are compared quantitatively with micron resolution, three-dimensional X-ray microscopy (3DXM) measurements of the lattice rotation fields under 100mN force, 100 mu m radius spherical indentations in < 111 >, < 110 >, and < 001 > oriented Cu single crystals. Third, noting the limitation of continuum strain gradient crystal plasticity models, two-dimensional discrete dislocation simulation results suggest that the hardness in the nanocontact regime is governed synergistically by a combination of strain gradients and source-limited plasticity. However, the lattice rotation field in the discrete dislocation simulations is found to be insensitive to these two factors but to depend critically on dislocation obstacle densities and strengths.« less

Functional requirements for reward-modulated spike-timing-dependent plasticity.

PubMed

Frémaux, Nicolas; Sprekeler, Henning; Gerstner, Wulfram

2010-10-06

Recent experiments have shown that spike-timing-dependent plasticity is influenced by neuromodulation. We derive theoretical conditions for successful learning of reward-related behavior for a large class of learning rules where Hebbian synaptic plasticity is conditioned on a global modulatory factor signaling reward. We show that all learning rules in this class can be separated into a term that captures the covariance of neuronal firing and reward and a second term that presents the influence of unsupervised learning. The unsupervised term, which is, in general, detrimental for reward-based learning, can be suppressed if the neuromodulatory signal encodes the difference between the reward and the expected reward-but only if the expected reward is calculated for each task and stimulus separately. If several tasks are to be learned simultaneously, the nervous system needs an internal critic that is able to predict the expected reward for arbitrary stimuli. We show that, with a critic, reward-modulated spike-timing-dependent plasticity is capable of learning motor trajectories with a temporal resolution of tens of milliseconds. The relation to temporal difference learning, the relevance of block-based learning paradigms, and the limitations of learning with a critic are discussed.

Respiratory Plasticity Following Spinal Injury: Role of Chloride-Dependent Inhibitory Neurotransmission

DTIC Science & Technology

2016-12-01

respiratory pathways following spinal cord injury. J Appl Physiol. 94(2):795-810. Raineteau O and Schwab ME (2001). Plasticity of motor systems after incomplete spinal cord injury. Nat Rev Neurosci. 2(4):262-73. APPENDICES : None

Field based plastic contamination sensing

USDA-ARS?s Scientific Manuscript database

The United States has a long-held reputation of being a dependable source of high quality, contaminant-free cotton. Recently, increased incidence of plastic contamination from sources such as shopping bags, vegetable mulch, surface irrigation tubing, and module covers has threatened the reputation o...

Plasticity of Neuron-Glial Transmission: Equipping Glia for Long-Term Integration of Network Activity.

PubMed

Croft, Wayne; Dobson, Katharine L; Bellamy, Tomas C

2015-01-01

The capacity of synaptic networks to express activity-dependent changes in strength and connectivity is essential for learning and memory processes. In recent years, glial cells (most notably astrocytes) have been recognized as active participants in the modulation of synaptic transmission and synaptic plasticity, implicating these electrically nonexcitable cells in information processing in the brain. While the concept of bidirectional communication between neurons and glia and the mechanisms by which gliotransmission can modulate neuronal function are well established, less attention has been focussed on the computational potential of neuron-glial transmission itself. In particular, whether neuron-glial transmission is itself subject to activity-dependent plasticity and what the computational properties of such plasticity might be has not been explored in detail. In this review, we summarize current examples of plasticity in neuron-glial transmission, in many brain regions and neurotransmitter pathways. We argue that induction of glial plasticity typically requires repetitive neuronal firing over long time periods (minutes-hours) rather than the short-lived, stereotyped trigger typical of canonical long-term potentiation. We speculate that this equips glia with a mechanism for monitoring average firing rates in the synaptic network, which is suited to the longer term roles proposed for astrocytes in neurophysiology.

Epigenetic Basis of Neuronal and Synaptic Plasticity.

PubMed

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.

Microelectrode array recordings of cultured hippocampal networks reveal a simple model for transcription and protein synthesis-dependent plasticity

PubMed Central

Arnold, Fiona JL; Hofmann, Frank; Bengtson, C. Peter; Wittmann, Malte; Vanhoutte, Peter; Bading, Hilmar

2005-01-01

A simplified cell culture system was developed to study neuronal plasticity. As changes in synaptic strength may alter network activity patterns, we grew hippocampal neurones on a microelectrode array (MEA) and monitored their collective behaviour with 60 electrodes simultaneously. We found that exposure of the network for 15 min to the GABAA receptor antagonist bicuculline induced an increase in synaptic efficacy at excitatory synapses that was associated with an increase in the frequency of miniature AMPA receptor-mediated EPSCs and a change in network activity from uncoordinated firing of neurones (lacking any recognizable pattern) to a highly organized, periodic and synchronous burst pattern. Induction of recurrent synchronous bursting was dependent on NMDA receptor activation and required extracellular signal-regulated kinase (ERK)1/2 signalling and translation of pre-existing mRNAs. Once induced, the burst pattern persisted for several days; its maintenance phase (> 4 h) was dependent on gene transcription taking place in a critical period of 120 min following induction. Thus, cultured hippocampal neurones display a simple, transcription and protein synthesis-dependent form of plasticity. The non-invasive nature of MEA recordings provides a significant advantage over traditional assays for synaptic connectivity (i.e. long-term potentiation in brain slices) and facilitates the search for activity-regulated genes critical for late-phase plasticity. PMID:15618268

Microelectrode array recordings of cultured hippocampal networks reveal a simple model for transcription and protein synthesis-dependent plasticity.

PubMed

Arnold, Fiona J L; Hofmann, Frank; Bengtson, C Peter; Wittmann, Malte; Vanhoutte, Peter; Bading, Hilmar

2005-04-01

A simplified cell culture system was developed to study neuronal plasticity. As changes in synaptic strength may alter network activity patterns, we grew hippocampal neurones on a microelectrode array (MEA) and monitored their collective behaviour with 60 electrodes simultaneously. We found that exposure of the network for 15 min to the GABA(A) receptor antagonist bicuculline induced an increase in synaptic efficacy at excitatory synapses that was associated with an increase in the frequency of miniature AMPA receptor-mediated EPSCs and a change in network activity from uncoordinated firing of neurones (lacking any recognizable pattern) to a highly organized, periodic and synchronous burst pattern. Induction of recurrent synchronous bursting was dependent on NMDA receptor activation and required extracellular signal-regulated kinase (ERK)1/2 signalling and translation of pre-existing mRNAs. Once induced, the burst pattern persisted for several days; its maintenance phase (> 4 h) was dependent on gene transcription taking place in a critical period of 120 min following induction. Thus, cultured hippocampal neurones display a simple, transcription and protein synthesis-dependent form of plasticity. The non-invasive nature of MEA recordings provides a significant advantage over traditional assays for synaptic connectivity (i.e. long-term potentiation in brain slices) and facilitates the search for activity-regulated genes critical for late-phase plasticity.

Effects of flow rate on the migration of different plasticizers from PVC infusion medical devices

PubMed Central

Eljezi, Teuta; Clauson, Hélène; Lambert, Céline; Bouattour, Yassine; Chennell, Philip; Pereira, Bruno; Sautou, Valérie

2018-01-01

Infusion medical devices (MDs) used in hospitals are often made of plasticized polyvinylchloride (PVC). These plasticizers may leach out into infused solutions during clinical practice, especially during risk-situations, e.g multiple infusions in Intensive Care Units and thus may enter into contact with the patients. The migrability of the plasticizers is dependent of several clinical parameters such as temperature, contact time, nature of the simulant, etc… However, no data is available about the influence of the flow rate at which drug solutions are administrated. In this study, we evaluated the impact of different flow rates on the release of the different plasticizers during an infusion procedure in order to assess if they could expose the patients to more toxic amounts of plasticizers. Migration assays with different PVC infusion sets and extension lines were performed with different flow rates that are used in clinical practice during 1h, 2h, 4h, 8h and 24h, using a lipophilic drug simulant. From a clinical point of view, the results showed that, regardless of the plasticizer, the faster the flow rate, the higher the infused volume and the higher the quantities of plasticizers released, both from infusion sets and extension lines, leading to higher patient exposure. However, physically, there was no significant difference of the migration kinetics linked to the flow rate for a same medical device, reflecting complex interactions between the PVC matrix and the simulant. The migration was especially dependent on the nature and the composition of the medical device. PMID:29474357

Application of an Uncoupled Elastic-plastic-creep Constitutive Model to Metals at High Temperature

NASA Technical Reports Server (NTRS)

Haisler, W. E.

1983-01-01

A uniaxial, uncoupled constitutive model to predict the response of thermal and rate dependent elastic-plastic material behavior is presented. The model is based on an incremental classicial plasticity theory extended to account for thermal, creep, and transient temperature conditions. Revisions to he combined hardening rule of the theory allow for better representation of cyclic phenomenon including the high rate of strain hardening upon cyclic reyield and cyclic saturation. An alternative approach is taken to model the rate dependent inelastic deformation which utilizes hysteresis loops and stress relaxation test data at various temperatures. The model is evaluated and compared to experiments which involve various thermal and mechanical load histories on 5086 aluminum alloy, 304 stainless steel and Hastelloy-X.

Optimizing cholinergic tone through lynx modulators of nicotinic receptors: implications for plasticity and nicotine addiction.

PubMed

Miwa, Julie M; Lester, Henry A; Walz, Andreas

2012-08-01

The cholinergic system underlies both adaptive (learning and memory) and nonadaptive (addiction and dependency) behavioral changes through its ability to shape and regulate plasticity. Protein modulators such as lynx family members can fine tune the activity of the cholinergic system and contribute to the graded response of the cholinergic system, stabilizing neural circuitry through direct interaction with nicotinic receptors. Release of this molecular brake can unmask cholinergic-dependent mechanisms in the brain. Lynx proteins have the potential to provide top-down control over plasticity mechanisms, including addictive propensity. If this is indeed the case, then, what regulates the regulator? Transcriptional changes of lynx genes in response to pharmacological, physiological, and pathological alterations are explored in this review.

Prevention of plasticity of endocannabinoid signaling inhibits persistent limbic hyperexcitability caused by developmental seizures.

PubMed

Chen, Kang; Neu, Axel; Howard, Allyson L; Földy, Csaba; Echegoyen, Julio; Hilgenberg, Lutz; Smith, Martin; Mackie, Ken; Soltesz, Ivan

2007-01-03

Depolarization-induced suppression of inhibition (DSI) is an endocannabinoid-mediated short-term plasticity mechanism that couples postsynaptic Ca2+ rises to decreased presynaptic GABA release. Whether the gain of this retrograde synaptic mechanism is subject to long-term modulation by glutamatergic excitatory inputs is not known. Here, we demonstrate that activity-dependent long-term DSI potentiation takes place in hippocampal slices after tetanic stimulation of Schaffer collateral synapses. This activity-dependent, long-term plasticity of endocannabinoid signaling was specific to GABAergic synapses, as it occurred without increases in the depolarization-induced suppression of excitation. Induction of tetanus-induced DSI potentiation in vitro required a complex pathway involving AMPA/kainate and metabotropic glutamate receptor as well as CB1 receptor activation. Because DSI potentiation has been suggested to play a role in persistent limbic hyperexcitability after prolonged seizures in the developing brain, we used these mechanistic insights into activity-dependent DSI potentiation to test whether interference with the induction of DSI potentiation prevents seizure-induced long-term hyperexcitability. The results showed that the in vitro, tetanus-induced DSI potentiation was occluded by previous in vivo fever-induced (febrile) seizures, indicating a common pathway. Accordingly, application of CB1 receptor antagonists during febrile seizures in vivo blocked the seizure-induced persistent DSI potentiation, abolished the seizure-induced upregulation of CB1 receptors, and prevented the emergence of long-term limbic hyperexcitability. These results reveal a new form of activity-dependent, long-term plasticity of endocannabinoid signaling at perisomatic GABAergic synapses, and demonstrate that blocking the induction of this plasticity abolishes the long-term effects of prolonged febrile seizures in the developing brain.

Production of Methane and Water from Crew Plastic Waste

NASA Technical Reports Server (NTRS)

Captain, Janine; Santiago, Eddie; Parrish, Clyde; Strayer, Richard F.; Garland, Jay L.

2008-01-01

Recycling is a technology that will be key to creating a self sustaining lunar outpost. The plastics used for food packaging provide a source of material that could be recycled to produce water and methane. The recycling of these plastics will require some additional resources that will affect the initial estimate of starting materials that will have to be transported from earth, mainly oxygen, energy and mass. These requirements will vary depending on the recycling conditions. The degredation products of these plastics will vary under different atmospheric conditions. An estimate of the the production rate of methane and water using typical ISRU processes along with the plastic recycling will be presented.

Nicotinic modulation of hippocampal cell signaling and associated effects on learning and memory.

PubMed

Kutlu, Munir Gunes; Gould, Thomas J

2016-03-01

The hippocampus is a key brain structure involved in synaptic plasticity associated with long-term declarative memory formation. Importantly, nicotine and activation of nicotinic acetylcholine receptors (nAChRs) can alter hippocampal plasticity and these changes may occur through modulation of hippocampal kinases and transcription factors. Hippocampal kinases such as cAMP-dependent protein kinase (PKA), calcium/calmodulin-dependent protein kinases (CAMKs), extracellular signal-regulated kinases 1 and 2 (ERK1/2), and c-jun N-terminal kinase 1 (JNK1), and the transcription factor cAMP-response element-binding protein (CREB) that are activated either directly or indirectly by nicotine may modulate hippocampal plasticity and in parallel hippocampus-dependent learning and memory. Evidence suggests that nicotine may alter hippocampus-dependent learning by changing the time and magnitude of activation of kinases and transcription factors normally involved in learning and by recruiting additional cell signaling molecules. Understanding how nicotine alters learning and memory will advance basic understanding of the neural substrates of learning and aid in understanding mental disorders that involve cognitive and learning deficits. Copyright © 2015 Elsevier Inc. All rights reserved.

Plastic strain is a mixture of avalanches and quasireversible deformations: Study of various sizes

NASA Astrophysics Data System (ADS)

Szabó, Péter; Ispánovity, Péter Dusán; Groma, István

2015-02-01

The size dependence of plastic flow is studied by discrete dislocation dynamical simulations of systems with various amounts of interacting dislocations while the stress is slowly increased. The regions between avalanches in the individual stress curves as functions of the plastic strain were found to be nearly linear and reversible where the plastic deformation obeys an effective equation of motion with a nearly linear force. For small plastic deformation, the mean values of the stress-strain curves obey a power law over two decades. Here and for somewhat larger plastic deformations, the mean stress-strain curves converge for larger sizes, while their variances shrink, both indicating the existence of a thermodynamical limit. The converging averages decrease with increasing size, in accordance with size effects from experiments. For large plastic deformations, where steady flow sets in, the thermodynamical limit was not realized in this model system.

The missing piece in the 'use it or lose it' puzzle: is inhibition regulated by activity or does it act on its own accord?

PubMed

Sun, Qian-Quan

2007-01-01

We have gained enormous insight into the mechanisms underlying both activity-dependent and (to a lesser degree) -independent plasticity of excitatory synapses. Recently, cortical inhibition has been shown to play a vital role in the formation of critical periods for sensory plasticity. As such, sculpting of neuronal circuits by inhibition may be a common mechanism by which activity organizes or reorganizes brain circuits. Disturbances in the balance of excitation and inhibition in the neocortex provoke abnormal activities, such as epileptic seizures and abnormal cortical development. However, both the process of experience-dependent postnatal maturation of neocortical inhibitory networks and its underlying mechanisms remain elusive. Mechanisms that match excitation and inhibition are central to achieving balanced function at the level of individual circuits. The goal of this review is to reinforce our understanding of the mechanisms by which developing inhibitory networks are able to adapt to sensory inputs, and to maintain their balance with developing excitatory networks. Discussion is centered on the following questions related to experience-dependent plasticity of neocortical inhibitory networks: 1) What are the roles of GABAergic inhibition in the postnatal maturation of neocortical circuits? 2) Does the maturation of neocortical inhibitory circuits proceed in an activity-dependent manner or do they develop independently of sensory inputs? 3) Does activity regulate inhibitory networks in the same way it regulates excitatory networks? 4) What are the molecular and cellular mechanisms that underlie the activity-dependent maturation of inhibitory networks? 5) What are the functional advantages of experience-dependent plasticity of inhibitory networks to network processing in sensory cortices?

Repeated Exposure to Ketamine-Xylazine during Early Development Impairs Motor Learning-dependent Dendritic Spine Plasticity in Adulthood

PubMed Central

Huang, Lianyan; Yang, Guang

2014-01-01

Background Recent studies in rodents suggest that repeated and prolonged anesthetic exposure at early stages of development leads to cognitive and behavioral impairments later in life. However, the underlying mechanism remains unknown. In this study, we tested whether exposure to general anesthesia during early development will disrupt the maturation of synaptic circuits and compromise learning-related synaptic plasticity later in life. Methods Mice received ketamine/xylazine (20/3 mg/kg) anesthesia for one or three times, starting at either early [postnatal day 14 (P14)] or late (P21) stages of development (n=105). Control mice received saline injections (n=34). At P30, mice were subjected to rotarod motor training and fear conditioning. Motor learning-induced synaptic remodeling was examined in vivo by repeatedly imaging fluorescently-labeled postsynaptic dendritic spines in the primary motor cortex before and after training using two-photon microscopy. Results Three exposures to ketamine/xylazine anesthesia between P14–18 impair the animals’ motor learning and learning-dependent dendritic spine plasticity [new spine formation, 8.4 ± 1.3% (mean ± SD) versus 13.4 ± 1.8%, P = 0.002] without affecting fear memory and cell apoptosis. One exposure at P14 or three exposures between P21–25 has no effects on the animals’ motor learning or spine plasticity. Finally, enriched motor experience ameliorates anesthesia-induced motor learning impairment and synaptic deficits. Conclusion Our study demonstrates that repeated exposures to ketamine/xylazine during early development impair motor learning and learning-dependent dendritic spine plasticity later in life. The reduction in synaptic structural plasticity may underlie anesthesia-induced behavioral impairment. PMID:25575163

Genetic deletion of melanin-concentrating hormone neurons impairs hippocampal short-term synaptic plasticity and hippocampal-dependent forms of short-term memory.

PubMed

Le Barillier, Léa; Léger, Lucienne; Luppi, Pierre-Hervé; Fort, Patrice; Malleret, Gaël; Salin, Paul-Antoine

2015-11-01

The cognitive role of melanin-concentrating hormone (MCH) neurons, a neuronal population located in the mammalian postero-lateral hypothalamus sending projections to all cortical areas, remains poorly understood. Mainly activated during paradoxical sleep (PS), MCH neurons have been implicated in sleep regulation. The genetic deletion of the only known MCH receptor in rodent leads to an impairment of hippocampal dependent forms of memory and to an alteration of hippocampal long-term synaptic plasticity. By using MCH/ataxin3 mice, a genetic model characterized by a selective deletion of MCH neurons in the adult, we investigated the role of MCH neurons in hippocampal synaptic plasticity and hippocampal-dependent forms of memory. MCH/ataxin3 mice exhibited a deficit in the early part of both long-term potentiation and depression in the CA1 area of the hippocampus. Post-tetanic potentiation (PTP) was diminished while synaptic depression induced by repetitive stimulation was enhanced suggesting an alteration of pre-synaptic forms of short-term plasticity in these mice. Behaviorally, MCH/ataxin3 mice spent more time and showed a higher level of hesitation as compared to their controls in performing a short-term memory T-maze task, displayed retardation in acquiring a reference memory task in a Morris water maze, and showed a habituation deficit in an open field task. Deletion of MCH neurons could thus alter spatial short-term memory by impairing short-term plasticity in the hippocampus. Altogether, these findings could provide a cellular mechanism by which PS may facilitate memory encoding. Via MCH neuron activation, PS could prepare the day's learning by increasing and modulating short-term synaptic plasticity in the hippocampus. © 2015 Wiley Periodicals, Inc.

Generalized continuum modeling of scale-dependent crystalline plasticity

NASA Astrophysics Data System (ADS)

Mayeur, Jason R.

The use of metallic material systems (e.g. pure metals, alloys, metal matrix composites) in a wide range of engineering applications from medical devices to electronic components to automobiles continues to motivate the development of improved constitutive models to meet increased performance demands while minimizing cost. Emerging technologies often incorporate materials in which the dominant microstructural features have characteristic dimensions reaching into the submicron and nanometer regime. Metals comprised of such fine microstructures often exhibit unique and size-dependent mechanical response, and classical approaches to constitutive model development at engineering (continuum) scales, being local in nature, are inadequate for describing such behavior. Therefore, traditional modeling frameworks must be augmented and/or reformulated to account for such phenomena. Crystal plasticity constitutive models have proven quite capable of capturing first-order microstructural effects such as grain orientation (elastic/plastic anisotropy), grain morphology, phase distribution, etc. on the deformation behavior of both single and polycrystals, yet suffer from the same limitations as other local continuum theories with regard to capturing scale-dependent mechanical response. This research is focused on the development, numerical implementation, and application of a generalized (nonlocal) theory of single crystal plasticity capable of describing the scale-dependent mechanical response of both single and polycrystalline metals that arises as a result of heterogeneous deformation. This research developed a dislocation-based theory of micropolar single crystal plasticity. The majority of nonlocal crystal plasticity theories are predicated on the connection between gradients of slip and geometrically necessary dislocations. Due to the diversity of existing nonlocal crystal plasticity theories, a review, summary, and comparison of representative model classes is presented in Chapter 2 from a unified dislocation-based perspective. The discussion of the continuum crystal plasticity theories is prefaced by a brief review of discrete dislocation plasticity, which facilitates the comparison of certain model aspects and also serves as a reference for latter segments of the research which make connection to this constitutive description. Chapter 2 has utility not only as a literature review, but also as a synthesis and analysis of competing and alternative nonlocal crystal plasticity modeling strategies from a common viewpoint. The micropolar theory of single crystal plasticity is presented in Chapter 3. Two different types of flow criteria are considered - the so-called single and multicriterion theories, and several variations of the dislocation-based strength models appropriate for each theory are presented and discussed. The numerical implementation of the two-dimensional version of the constitutive theory is given in Chapter 4. A user element subroutine for the implicit commercial finite element code Abaqus/Standard is developed and validated through the solution of initial-boundary value problems with closed-form solutions. Convergent behavior of the subroutine is also demonstrated for an initial-boundary value problem exhibiting strain localization. In Chapter 5, the models are employed to solve several standard initial-boundary value problems for heterogeneously deforming single crystals including simple shearing of a semi-infinite constrained thin film, pure bending of thin films, and simple shearing of a metal matrix composite with elastic inclusions. The simulation results are compared to those obtained from the solution of equivalent boundary value problems using discrete dislocation dynamics and alternative generalized crystal plasticity theories. Comparison and calibration with respect to the former provides guidance in the specification of non-traditional material parameters that arise in the model formulation and demonstrates its effectiveness at capturing the heterogeneous deformation fields and size-dependent mechanical behavior predicted by a finer scale constitutive description. Finally, in Chapter 6, the models are applied to simulate the deformation behavior of small polycrystalline ensembles. Several grain boundary constitutive descriptions are explored and the response characteristics are analyzed with respect to experimental observations as well as results obtained from discrete dislocation dynamics and alternative nonlocal crystal plasticity theories. Particular attention is focused on how the various grain boundary descriptions serve to either locally concentrate or diffuse deformation heterogeneity as a function of grain size.

Constraints on the evolution of phenotypic plasticity: limits and costs of phenotype and plasticity

PubMed Central

Murren, C J; Auld, J R; Callahan, H; Ghalambor, C K; Handelsman, C A; Heskel, M A; Kingsolver, J G; Maclean, H J; Masel, J; Maughan, H; Pfennig, D W; Relyea, R A; Seiter, S; Snell-Rood, E; Steiner, U K; Schlichting, C D

2015-01-01

Phenotypic plasticity is ubiquitous and generally regarded as a key mechanism for enabling organisms to survive in the face of environmental change. Because no organism is infinitely or ideally plastic, theory suggests that there must be limits (for example, the lack of ability to produce an optimal trait) to the evolution of phenotypic plasticity, or that plasticity may have inherent significant costs. Yet numerous experimental studies have not detected widespread costs. Explicitly differentiating plasticity costs from phenotype costs, we re-evaluate fundamental questions of the limits to the evolution of plasticity and of generalists vs specialists. We advocate for the view that relaxed selection and variable selection intensities are likely more important constraints to the evolution of plasticity than the costs of plasticity. Some forms of plasticity, such as learning, may be inherently costly. In addition, we examine opportunities to offset costs of phenotypes through ontogeny, amelioration of phenotypic costs across environments, and the condition-dependent hypothesis. We propose avenues of further inquiry in the limits of plasticity using new and classic methods of ecological parameterization, phylogenetics and omics in the context of answering questions on the constraints of plasticity. Given plasticity's key role in coping with environmental change, approaches spanning the spectrum from applied to basic will greatly enrich our understanding of the evolution of plasticity and resolve our understanding of limits. PMID:25690179

Modeling the Temperature Rise at the Tip of a Fast Crack

DTIC Science & Technology

1989-08-01

plastic deformation in the plastic zone, the strain rate and the temperature dependence of the flow stress have been incorporated in the determination ...of dislocation generation in the plastic zone. The stress field 1 associated with a moving elastic crack tip is used to determine the increment of...yield stress and the crack tip stress field for a given mode of the applied stress. The fracture toughness of several materials, determined

The influence of plasticizers on the release of theophylline from microporous-controlled tablets.

PubMed

Lin, W J; Lee, H K; Wang, D M

2004-10-19

The aim of present work was to investigate the influence of plasticizer on the release of theophylline from microporous-controlled tablets. Three plasticizers, acetyltributyl citrate (ATBC), castor oil, and triacetin, were included in this study. These plasticizers reduced the crystallinity of poly(epsilon-caprolactone) (PCL)/poly(ethylene glycol) (PEG)-blended films, and the most prominent change of enthalpy of fusion was the film plasticized by triacetin. This might be due to triacetin penetrating into both PCL and PEG domains. However, the lipophilic property of castor oil only allowed it to alter the crystallization of hydrophobic PCL domain. The Young's modulus and the tensile strength of films showed a decreased tendency while increasing the amount of plasticizer. The change of elongation of plasticized blended films was irregular and was dependent of the type of plasticizer. The size of micropores formed in the presence of plasticizer was larger than those micropores formed in its absence. The fatty plasticizer, castor oil, altered the thermal and mechanical performance and pore size of films via soluble in PCL domain, which resulted in the release of theophylline from castor oil plasticized-coated tablets, which in turn enhanced and closed to a constant release pattern.

Contribution of plastic waste recovery to greenhouse gas (GHG) savings in Spain.

PubMed

Sevigné-Itoiz, Eva; Gasol, Carles M; Rieradevall, Joan; Gabarrell, Xavier

2015-12-01

This paper concentrates on the quantification of greenhouse gas (GHG) emissions of post-consumer plastic waste recovery (material or energy) by considering the influence of the plastic waste quality (high or low), the recycled plastic applications (virgin plastic substitution or non-plastic substitution) and the markets of recovered plastic (regional or global). The aim is to quantify the environmental consequences of different alternatives in order to evaluate opportunities and limitations to select the best and most feasible plastic waste recovery option to decrease the GHG emissions. The methodologies of material flow analysis (MFA) for a time period of thirteen years and consequential life cycle assessment (CLCA) have been integrated. The study focuses on Spain as a representative country for Europe. The results show that to improve resource efficiency and avoid more GHG emissions, the options for plastic waste management are dependent on the quality of the recovered plastic. The results also show that there is an increasing trend of exporting plastic waste for recycling, mainly to China, that reduces the GHG benefits from recycling, suggesting that a new focus should be introduced to take into account the split between local recycling and exporting. Copyright © 2015 Elsevier Ltd. All rights reserved.

Sustained Hypoxia Elicits Competing Spinal Mechanisms of Phrenic Motor Facilitation

PubMed Central

Devinney, Michael J.; Nichols, Nicole L.

2016-01-01

Acute intermittent hypoxia (AIH) induces phrenic long-term facilitation (pLTF), a form of spinal motor plasticity. Competing mechanisms give rise to phrenic motor facilitation (pMF; a general term including pLTF) depending on the severity of hypoxia within episodes. In contrast, moderate acute sustained hypoxia (mASH) does not elicit pMF. By varying the severity of ASH and targeting competing mechanisms of pMF, we sought to illustrate why moderate AIH (mAIH) elicits pMF but mASH does not. Although mAIH elicits serotonin-dependent pLTF, mASH does not; thus, mAIH-induced pLTF is pattern sensitive. In contrast, severe AIH (sAIH) elicits pLTF through adenosine-dependent mechanisms, likely from greater extracellular adenosine accumulation. Because serotonin- and adenosine-dependent pMF interact via cross talk inhibition, we hypothesized that pMF is obscured because the competing mechanisms of pMF are balanced and offsetting during mASH. Here, we demonstrate the following: (1) blocking spinal A2A receptors with MSX-3 reveals mASH-induced pMF; and (2) sASH elicits A2A-dependent pMF. In anesthetized rats pretreated with intrathecal A2A receptor antagonist injections before mASH (PaO2 = 40–54 mmHg) or sASH (PaO2 = 25–36 mmHg), (1) mASH induced a serotonin-dependent pMF and (2) sASH induced an adenosine-dependent pMF, which was enhanced by spinal serotonin receptor inhibition. Thus, competing adenosine- and serotonin-dependent mechanisms contribute differentially to pMF depending on the pattern/severity of hypoxia. Understanding interactions between these mechanisms has clinical relevance as we develop therapies to treat severe neuromuscular disorders that compromise somatic motor behaviors, including breathing. Moreover, these results demonstrate how competing mechanisms of plasticity can give rise to pattern sensitivity in pLTF. SIGNIFICANCE STATEMENT Intermittent hypoxia elicits pattern-sensitive spinal plasticity and improves motor function after spinal injury or during neuromuscular disease. Specific mechanisms of pattern sensitivity in this form of plasticity are unknown. We provide evidence that competing mechanisms of phrenic motor facilitation mediated by adenosine 2A and serotonin 2 receptors are differentially expressed, depending on the pattern/severity of hypoxia. Understanding how these distinct mechanisms interact during hypoxic exposures differing in severity and duration will help explain interesting properties of plasticity, such as pattern sensitivity, and may help optimize therapies to restore motor function in patients with neuromuscular disorders that compromise movement. PMID:27466333

Temperature dependence of the plastic scintillator detector for DAMPE

NASA Astrophysics Data System (ADS)

Wang, Zhao-Min; Yu, Yu-Hong; Sun, Zhi-Yu; Yue, Ke; Yan, Duo; Zhang, Yong-Jie; Zhou, Yong; Fang, Fang; Huang, Wen-Xue; Chen, Jun-Ling

2017-01-01

The Plastic Scintillator Detector (PSD) is one of the main sub-detectors in the DArk Matter Particle Explorer (DAMPE) project. It will be operated over a large temperature range from -10 to 30 °C, so the temperature effect of the whole detection system should be studied in detail. The temperature dependence of the PSD system is mainly contributed by the three parts: the plastic scintillator bar, the photomultiplier tube (PMT), and the Front End Electronics (FEE). These three parts have been studied in detail and the contribution of each part has been obtained and discussed. The temperature coefficient of the PMT is -0.320(±0.033)%/°C, and the coefficient of the plastic scintillator bar is -0.036(±0.038)%/°C. This result means that after subtracting the FEE pedestal, the variation of the signal amplitude of the PMT-scintillator system due to temperature mainly comes from the PMT, and the plastic scintillator bar is not sensitive to temperature over the operating range. Since the temperature effect cannot be ignored, the temperature dependence of the whole PSD has been also studied and a correction has been made to minimize this effect. The correction result shows that the effect of temperature on the signal amplitude of the PSD system can be suppressed. Supported by Strategic Priority Research Program on Space Science of the Chinese Academy of Sciences (XDA04040202-3) and Youth Innovation Promotion Association, CAS

Experimental evaluation criteria for constitutive models of time dependent cyclic plasticity

NASA Technical Reports Server (NTRS)

Martin, J. F.

1986-01-01

Notched members were tested at temperatures far above those recorded till now. Simulation of the notch root stress response was accomplished to establish notch stress-strain behavior. Cyclic stress-strain profiles across the net-section were recorded and on-line direct notch strain control was accomplished. Data are compared to three analysis techniques with good results. The objective of the study is to generate experimental data that can be used to evaluate the accuracy of constitutive models of time dependent cyclic plasticity.

Determination of post-shakedown quantities of a pipe bend via the simplified theory of plastic zones compared with load history dependent incremental analysis

NASA Astrophysics Data System (ADS)

Vollrath, Bastian; Hübel, Hartwig

2018-01-01

The Simplified Theory of Plastic Zones (STPZ) may be used to determine post-shakedown quantities such as strain ranges and accumulated strains at plastic or elastic shakedown. The principles of the method are summarized. Its practical applicability is shown by the example of a pipe bend subjected to constant internal pressure along with cyclic in-plane bending or/and cyclic radial temperature gradient. The results are compared with incremental analyses performed step-by-step throughout the entire load history until the state of plastic shakedown is achieved.

Activity-dependent synaptic plasticity of a chalcogenide electronic synapse for neuromorphic systems.

PubMed

Li, Yi; Zhong, Yingpeng; Zhang, Jinjian; Xu, Lei; Wang, Qing; Sun, Huajun; Tong, Hao; Cheng, Xiaoming; Miao, Xiangshui

2014-05-09

Nanoscale inorganic electronic synapses or synaptic devices, which are capable of emulating the functions of biological synapses of brain neuronal systems, are regarded as the basic building blocks for beyond-Von Neumann computing architecture, combining information storage and processing. Here, we demonstrate a Ag/AgInSbTe/Ag structure for chalcogenide memristor-based electronic synapses. The memristive characteristics with reproducible gradual resistance tuning are utilised to mimic the activity-dependent synaptic plasticity that serves as the basis of memory and learning. Bidirectional long-term Hebbian plasticity modulation is implemented by the coactivity of pre- and postsynaptic spikes, and the sign and degree are affected by assorted factors including the temporal difference, spike rate and voltage. Moreover, synaptic saturation is observed to be an adjustment of Hebbian rules to stabilise the growth of synaptic weights. Our results may contribute to the development of highly functional plastic electronic synapses and the further construction of next-generation parallel neuromorphic computing architecture.

Sensory Cortical Plasticity Participates in the Epigenetic Regulation of Robust Memory Formation

PubMed Central

Phan, Mimi L.; Bieszczad, Kasia M.

2016-01-01

Neuroplasticity remodels sensory cortex across the lifespan. A function of adult sensory cortical plasticity may be capturing available information during perception for memory formation. The degree of experience-dependent remodeling in sensory cortex appears to determine memory strength and specificity for important sensory signals. A key open question is how plasticity is engaged to induce different degrees of sensory cortical remodeling. Neural plasticity for long-term memory requires the expression of genes underlying stable changes in neuronal function, structure, connectivity, and, ultimately, behavior. Lasting changes in transcriptional activity may depend on epigenetic mechanisms; some of the best studied in behavioral neuroscience are DNA methylation and histone acetylation and deacetylation, which, respectively, promote and repress gene expression. One purpose of this review is to propose epigenetic regulation of sensory cortical remodeling as a mechanism enabling the transformation of significant information from experiences into content-rich memories of those experiences. Recent evidence suggests how epigenetic mechanisms regulate highly specific reorganization of sensory cortical representations that establish a widespread network for memory. Thus, epigenetic mechanisms could initiate events to establish exceptionally persistent and robust memories at a systems-wide level by engaging sensory cortical plasticity for gating what and how much information becomes encoded. PMID:26881129

Crash simulation of hybrid structures considering the stress and strain rate dependent material behavior of thermoplastic materials

NASA Astrophysics Data System (ADS)

Hopmann, Ch.; Schöngart, M.; Weber, M.; Klein, J.

2015-05-01

Thermoplastic materials are more and more used as a light weight replacement for metal, especially in the automotive industry. Since these materials do not provide the mechanical properties, which are required to manufacture supporting elements like an auto body or a cross bearer, plastics are combined with metals in so called hybrid structures. Normally, the plastics components are joined to the metal structures using different technologies like welding or screwing. Very often, the hybrid structures are made of flat metal parts, which are stiffened by a reinforcement structure made of thermoplastic materials. The loads on these structures are very often impulsive, for example in the crash situation of an automobile. Due to the large stiffness variation of metal and thermoplastic materials, complex states of stress and very high local strain rates occur in the contact zone under impact conditions. Since the mechanical behavior of thermoplastic materials is highly dependent on these types of load, the crash failure of metal plastic hybrid parts is very complex. The problem is that the normally used strain rate dependent elastic/plastic material models are not capable to simulate the mechanical behavior of thermoplastic materials depended on the state of stress. As part of a research project, a method to simulate the mechanical behavior of hybrid structures under impact conditions is developed at the IKV. For this purpose, a specimen for the measurement of mechanical properties dependet on the state of stress and a method for the strain rate depended characterization of thermoplastic materials were developed. In the second step impact testing is performed. A hybrid structure made from a metal sheet and a reinforcement structure of a Polybutylenterephthalat Polycarbonate blend is tested under impact conditions. The measured stress and strain rate depended material data are used to simulate the mechanical behavior of the hybrid structure under highly dynamic load with impact velocities up to 5 m/s. The mechanical behavior of the plastics structure is simulated using a quadratic yield surface, which takes the state of stress and the strain rate into account. The FE model is made from mid surface elements to reduce the computing time.

The multisensory brain and its ability to learn music.

PubMed

Zimmerman, Emily; Lahav, Amir

2012-04-01

Playing a musical instrument requires a complex skill set that depends on the brain's ability to quickly integrate information from multiple senses. It has been well documented that intensive musical training alters brain structure and function within and across multisensory brain regions, supporting the experience-dependent plasticity model. Here, we argue that this experience-dependent plasticity occurs because of the multisensory nature of the brain and may be an important contributing factor to musical learning. This review highlights key multisensory regions within the brain and discusses their role in the context of music learning and rehabilitation. © 2012 New York Academy of Sciences.

Recyclable plastics as substrata for settlement and growth of bryozoans Bugula neritina and barnacles Amphibalanus amphitrite.

PubMed

Li, Heng-Xiang; Orihuela, Beatriz; Zhu, Mei; Rittschof, Daniel

2016-11-01

Plastics are common and pervasive anthropogenic debris in marine environments. Floating plastics provide opportunities to alter the abundance, distribution and invasion potential of sessile organisms that colonize them. We selected plastics from seven recycle categories and quantified settlement of (i) bryozoans Bugula neritina (Linnaeus, 1758) in the lab and in the field, and of (ii) barnacles Amphibalanus (= Balanus) amphitrite (Darwin, 1854) in the field. In the laboratory we cultured barnacles on the plastics for 8 weeks and quantified growth, mortality, and breaking strength of the side plates. In the field all recyclable plastics were settlement substrata for bryozoans and barnacles. Settlement depended on the type of plastic. Fewer barnacles settled on plastic surfaces compared to glass. In the lab and in the field, bryozoan settlement was higher on plastics than on glass. In static laboratory rearing, barnacles growing on plastics were initially significantly smaller than on glass. This suggested juvenile barnacles were adversely impacted by materials leaching from the plastics. Barnacle mortality was not significantly different between plastic and glass surfaces, but breaking strength of side plates of barnacles on polyvinyl chloride (PVC) and polycarbonate (PC) were significantly lower than breakage strength on glass. Plastics impact marine ecosystems directly by providing new surfaces for colonization with fouling organisms and by contaminants shown previously to leach out of plastics and impact biological processes. Published by Elsevier Ltd.

Unravelling how βCaMKII controls the direction of plasticity at parallel fibre-Purkinje cell synapses

NASA Astrophysics Data System (ADS)

Pinto, Thiago M.; Schilstra, Maria J.; Steuber, Volker; Roque, Antonio C.

2015-12-01

Long-term plasticity at parallel fibre (PF)-Purkinje cell (PC) synapses is thought to mediate cerebellar motor learning. It is known that calcium-calmodulin dependent protein kinase II (CaMKII) is essential for plasticity in the cerebellum. Recently, Van Woerden et al. demonstrated that the β isoform of CaMKII regulates the bidirectional inversion of PF-PC plasticity. Because the cellular events that underlie these experimental findings are still poorly understood, our work aims at unravelling how β CaMKII controls the direction of plasticity at PF-PC synapses. We developed a bidirectional plasticity model that replicates the experimental observations by Van Woerden et al. Simulation results obtained from this model indicate the mechanisms that underlie the bidirectional inversion of cerebellar plasticity. As suggested by Van Woerden et al., the filamentous actin binding enables β CaMKII to regulate the bidirectional plasticity at PF-PC synapses. Our model suggests that the reversal of long-term plasticity in PCs is based on a combination of mechanisms that occur at different calcium concentrations.

How consumers of plastic water bottles are responding to environmental policies?

PubMed

Orset, Caroline; Barret, Nicolas; Lemaire, Aurélien

2017-03-01

Although plastic induces environmental damages, almost all water bottles are made from plastic and the consumption never stops increasing. This study evaluates the consumers' willingness to pay (WTP) for different plastics used for water packaging. Successive messages emphasizing the characteristics of plastic are delivered to consumers allowing explaining the influence of information on the consumers' WTP. We find that information has a manifest effect on the WTP. We show there is a significant premium associated with recycled plastic packaging and biodegradable bioplastic packaging. As there is no consensus on the plastic which is the most or the least dangerous for the environment, we propose different policies for protecting the environment. We discuss about the impact of these policies on consumer's purchasing decisions: switching one plastic packaging for another, or leaving water plastic bottles market. We present the environmental policies that are effective according to the point of view adopted. Choosing between these policies then depends on the priorities of the regulator and pressure of lobbies. Copyright © 2017 Elsevier Ltd. All rights reserved.

Neuromodulated Spike-Timing-Dependent Plasticity, and Theory of Three-Factor Learning Rules

PubMed Central

Frémaux, Nicolas; Gerstner, Wulfram

2016-01-01

Classical Hebbian learning puts the emphasis on joint pre- and postsynaptic activity, but neglects the potential role of neuromodulators. Since neuromodulators convey information about novelty or reward, the influence of neuromodulators on synaptic plasticity is useful not just for action learning in classical conditioning, but also to decide “when” to create new memories in response to a flow of sensory stimuli. In this review, we focus on timing requirements for pre- and postsynaptic activity in conjunction with one or several phasic neuromodulatory signals. While the emphasis of the text is on conceptual models and mathematical theories, we also discuss some experimental evidence for neuromodulation of Spike-Timing-Dependent Plasticity. We highlight the importance of synaptic mechanisms in bridging the temporal gap between sensory stimulation and neuromodulatory signals, and develop a framework for a class of neo-Hebbian three-factor learning rules that depend on presynaptic activity, postsynaptic variables as well as the influence of neuromodulators. PMID:26834568

Activity-Dependent Bidirectional Regulation of GAD Expression in a Homeostatic Fashion Is Mediated by BDNF-Dependent and Independent Pathways

PubMed Central

Hanno-Iijima, Yoko; Tanaka, Masami; Iijima, Takatoshi

2015-01-01

Homeostatic synaptic plasticity, or synaptic scaling, is a mechanism that tunes neuronal transmission to compensate for prolonged, excessive changes in neuronal activity. Both excitatory and inhibitory neurons undergo homeostatic changes based on synaptic transmission strength, which could effectively contribute to a fine-tuning of circuit activity. However, gene regulation that underlies homeostatic synaptic plasticity in GABAergic (GABA, gamma aminobutyric) neurons is still poorly understood. The present study demonstrated activity-dependent dynamic scaling in which NMDA-R (N-methyl-D-aspartic acid receptor) activity regulated the expression of GABA synthetic enzymes: glutamic acid decarboxylase 65 and 67 (GAD65 and GAD67). Results revealed that activity-regulated BDNF (brain-derived neurotrophic factor) release is necessary, but not sufficient, for activity-dependent up-scaling of these GAD isoforms. Bidirectional forms of activity-dependent GAD expression require both BDNF-dependent and BDNF-independent pathways, both triggered by NMDA-R activity. Additional results indicated that these two GAD genes differ in their responsiveness to chronic changes in neuronal activity, which could be partially caused by differential dependence on BDNF. In parallel to activity-dependent bidirectional scaling in GAD expression, the present study further observed that a chronic change in neuronal activity leads to an alteration in neurotransmitter release from GABAergic neurons in a homeostatic, bidirectional fashion. Therefore, the differential expression of GAD65 and 67 during prolonged changes in neuronal activity may be implicated in some aspects of bidirectional homeostatic plasticity within mature GABAergic presynapses. PMID:26241953

Activity-Dependent Bidirectional Regulation of GAD Expression in a Homeostatic Fashion Is Mediated by BDNF-Dependent and Independent Pathways.

PubMed

Hanno-Iijima, Yoko; Tanaka, Masami; Iijima, Takatoshi

2015-01-01

Homeostatic synaptic plasticity, or synaptic scaling, is a mechanism that tunes neuronal transmission to compensate for prolonged, excessive changes in neuronal activity. Both excitatory and inhibitory neurons undergo homeostatic changes based on synaptic transmission strength, which could effectively contribute to a fine-tuning of circuit activity. However, gene regulation that underlies homeostatic synaptic plasticity in GABAergic (GABA, gamma aminobutyric) neurons is still poorly understood. The present study demonstrated activity-dependent dynamic scaling in which NMDA-R (N-methyl-D-aspartic acid receptor) activity regulated the expression of GABA synthetic enzymes: glutamic acid decarboxylase 65 and 67 (GAD65 and GAD67). Results revealed that activity-regulated BDNF (brain-derived neurotrophic factor) release is necessary, but not sufficient, for activity-dependent up-scaling of these GAD isoforms. Bidirectional forms of activity-dependent GAD expression require both BDNF-dependent and BDNF-independent pathways, both triggered by NMDA-R activity. Additional results indicated that these two GAD genes differ in their responsiveness to chronic changes in neuronal activity, which could be partially caused by differential dependence on BDNF. In parallel to activity-dependent bidirectional scaling in GAD expression, the present study further observed that a chronic change in neuronal activity leads to an alteration in neurotransmitter release from GABAergic neurons in a homeostatic, bidirectional fashion. Therefore, the differential expression of GAD65 and 67 during prolonged changes in neuronal activity may be implicated in some aspects of bidirectional homeostatic plasticity within mature GABAergic presynapses.

Post-cyclic behavior of low plasticity silt under full and limited liquefaction using triaxial compression testing.

DOT National Transportation Integrated Search

2010-02-01

During an earthquake, liquefaction does not happen all the time. It depends on the duration and magnitude of the earthquake and the properties (with relationship to resistance of liquefaction) of the low plasticity silt. Under low duration or magnitu...

Mean-field theory of a plastic network of integrate-and-fire neurons.

PubMed

Chen, Chun-Chung; Jasnow, David

2010-01-01

We consider a noise-driven network of integrate-and-fire neurons. The network evolves as result of the activities of the neurons following spike-timing-dependent plasticity rules. We apply a self-consistent mean-field theory to the system to obtain the mean activity level for the system as a function of the mean synaptic weight, which predicts a first-order transition and hysteresis between a noise-dominated regime and a regime of persistent neural activity. Assuming Poisson firing statistics for the neurons, the plasticity dynamics of a synapse under the influence of the mean-field environment can be mapped to the dynamics of an asymmetric random walk in synaptic-weight space. Using a master equation for small steps, we predict a narrow distribution of synaptic weights that scales with the square root of the plasticity rate for the stationary state of the system given plausible physiological parameter values describing neural transmission and plasticity. The dependence of the distribution on the synaptic weight of the mean-field environment allows us to determine the mean synaptic weight self-consistently. The effect of fluctuations in the total synaptic conductance and plasticity step sizes are also considered. Such fluctuations result in a smoothing of the first-order transition for low number of afferent synapses per neuron and a broadening of the synaptic-weight distribution, respectively.

Stochastic approach to plasticity and yield in amorphous solids.

PubMed

Hentschel, H G E; Jaiswal, Prabhat K; Procaccia, Itamar; Sastry, Srikanth

2015-12-01

We focus on the probability distribution function (PDF) P(Δγ;γ) where Δγ are the measured strain intervals between plastic events in a athermal strained amorphous solids, and γ measures the accumulated strain. The tail of this distribution as Δγ→0 (in the thermodynamic limit) scales like Δγ(η). The exponent η is related via scaling relations to the tail of the PDF of the eigenvalues of the plastic modes of the Hessian matrix P(λ) which scales like λ(θ), η=(θ-1)/2. The numerical values of η or θ can be determined easily in the unstrained material and in the yielded state of plastic flow. Special care is called for in the determination of these exponents between these states as γ increases. Determining the γ dependence of the PDF P(Δγ;γ) can shed important light on plasticity and yield. We conclude that the PDF's of both Δγ and λ are not continuous functions of γ. In slowly quenched amorphous solids they undergo two discontinuous transitions, first at γ=0(+) and then at the yield point γ=γ(Y) to plastic flow. In quickly quenched amorphous solids the second transition is smeared out due to the nonexisting stress peak before yield. The nature of these transitions and scaling relations with the system size dependence of 〈Δγ〉 are discussed.

The impact law of confining pressure and plastic parameter on Dilatancy of rock

NASA Astrophysics Data System (ADS)

Wang, Bin; Zhang, Zhenjie; Zhu, Jiebing

2017-08-01

Based on cyclic loading-unloading triaxle test of marble, the double parameter dilation angle model is established considering confining pressure effect and plastic parameter. Research shows that not only the strength but also the militancy behavior is highly depended on its confining pressure and plastic parameter during process of failure. Dilation angle evolution law shows obvious nonlinear characteristic almost with a rapid increase to the peak and then decrease gradually with plastic increasing, and the peak dilation angle value is inversely proportional with confining pressure. The proposed double parameter nonlinear dilation angle model can be used to well describe the Dilatancy of rock, which helps to understand the failure mechanism of surrounding rock mass and predict the range of plastic zone.

On numerical integration and computer implementation of viscoplastic models

NASA Technical Reports Server (NTRS)

Chang, T. Y.; Chang, J. P.; Thompson, R. L.

1985-01-01

Due to the stringent design requirement for aerospace or nuclear structural components, considerable research interests have been generated on the development of constitutive models for representing the inelastic behavior of metals at elevated temperatures. In particular, a class of unified theories (or viscoplastic constitutive models) have been proposed to simulate material responses such as cyclic plasticity, rate sensitivity, creep deformations, strain hardening or softening, etc. This approach differs from the conventional creep and plasticity theory in that both the creep and plastic deformations are treated as unified time-dependent quantities. Although most of viscoplastic models give better material behavior representation, the associated constitutive differential equations have stiff regimes which present numerical difficulties in time-dependent analysis. In this connection, appropriate solution algorithm must be developed for viscoplastic analysis via finite element method.

Regulation of AMPA receptors by phosphorylation.

PubMed

Carvalho, A L; Duarte, C B; Carvalho, A P

2000-10-01

The AMPA receptors for glutamate are oligomeric structures that mediate fast excitatory responses in the central nervous system. Phosphorylation of AMPA receptors is an important mechanism for short-term modulation of their function, and is thought to play an important role in synaptic plasticity in different brain regions. Recent studies have shown that phosphorylation of AMPA receptors by cAMP-dependent protein kinase (PKA) and Ca2+- and calmodulin-dependent protein kinase II (CaMKII) potentiates their activity, but phosphorylation of the receptor subunits may also affect their interaction with intracellular proteins, and their expression at the plasma membrane. Phosphorylation of AMPA receptor subunits has also been investigated in relation to processes of synaptic plasticity. This review focuses on recent advances in understanding the molecular mechanisms of regulation of AMPA receptors, and their implications in synaptic plasticity.

Metabolic plasticity during mammalian development is directionally dependent on early nutritional status.

PubMed

Gluckman, Peter D; Lillycrop, Karen A; Vickers, Mark H; Pleasants, Anthony B; Phillips, Emma S; Beedle, Alan S; Burdge, Graham C; Hanson, Mark A

2007-07-31

Developmental plasticity in response to environmental cues can take the form of polyphenism, as for the discrete morphs of some insects, or of an apparently continuous spectrum of phenotype, as for most mammalian traits. The metabolic phenotype of adult rats, including the propensity to obesity, hyperinsulinemia, and hyperphagia, shows plasticity in response to prenatal nutrition and to neonatal administration of the adipokine leptin. Here, we report that the effects of neonatal leptin on hepatic gene expression and epigenetic status in adulthood are directionally dependent on the animal's nutritional status in utero. These results demonstrate that, during mammalian development, the direction of the response to one cue can be determined by previous exposure to another, suggesting the potential for a discontinuous distribution of environmentally induced phenotypes, analogous to the phenomenon of polyphenism.

Roles of somatic A-type K(+) channels in the synaptic plasticity of hippocampal neurons.

PubMed

Yang, Yoon-Sil; Kim, Kyeong-Deok; Eun, Su-Yong; Jung, Sung-Cherl

2014-06-01

In the mammalian brain, information encoding and storage have been explained by revealing the cellular and molecular mechanisms of synaptic plasticity at various levels in the central nervous system, including the hippocampus and the cerebral cortices. The modulatory mechanisms of synaptic excitability that are correlated with neuronal tasks are fundamental factors for synaptic plasticity, and they are dependent on intracellular Ca(2+)-mediated signaling. In the present review, the A-type K(+) (IA) channel, one of the voltage-dependent cation channels, is considered as a key player in the modulation of Ca(2+) influx through synaptic NMDA receptors and their correlated signaling pathways. The cellular functions of IA channels indicate that they possibly play as integral parts of synaptic and somatic complexes, completing the initiation and stabilization of memory.

Enabling Functional Neural Circuit Simulations with Distributed Computing of Neuromodulated Plasticity

PubMed Central

Potjans, Wiebke; Morrison, Abigail; Diesmann, Markus

2010-01-01

A major puzzle in the field of computational neuroscience is how to relate system-level learning in higher organisms to synaptic plasticity. Recently, plasticity rules depending not only on pre- and post-synaptic activity but also on a third, non-local neuromodulatory signal have emerged as key candidates to bridge the gap between the macroscopic and the microscopic level of learning. Crucial insights into this topic are expected to be gained from simulations of neural systems, as these allow the simultaneous study of the multiple spatial and temporal scales that are involved in the problem. In particular, synaptic plasticity can be studied during the whole learning process, i.e., on a time scale of minutes to hours and across multiple brain areas. Implementing neuromodulated plasticity in large-scale network simulations where the neuromodulatory signal is dynamically generated by the network itself is challenging, because the network structure is commonly defined purely by the connectivity graph without explicit reference to the embedding of the nodes in physical space. Furthermore, the simulation of networks with realistic connectivity entails the use of distributed computing. A neuromodulated synapse must therefore be informed in an efficient way about the neuromodulatory signal, which is typically generated by a population of neurons located on different machines than either the pre- or post-synaptic neuron. Here, we develop a general framework to solve the problem of implementing neuromodulated plasticity in a time-driven distributed simulation, without reference to a particular implementation language, neuromodulator, or neuromodulated plasticity mechanism. We implement our framework in the simulator NEST and demonstrate excellent scaling up to 1024 processors for simulations of a recurrent network incorporating neuromodulated spike-timing dependent plasticity. PMID:21151370

Reorganization of Motor Cortex by Vagus Nerve Stimulation Requires Cholinergic Innervation.

PubMed

Hulsey, Daniel R; Hays, Seth A; Khodaparast, Navid; Ruiz, Andrea; Das, Priyanka; Rennaker, Robert L; Kilgard, Michael P

2016-01-01

Vagus nerve stimulation (VNS) paired with forelimb training drives robust, specific reorganization of movement representations in the motor cortex. The mechanisms that underlie VNS-dependent enhancement of map plasticity are largely unknown. The cholinergic nucleus basalis (NB) is a critical substrate in cortical plasticity, and several studies suggest that VNS activates cholinergic circuitry. We examined whether the NB is required for VNS-dependent enhancement of map plasticity in the motor cortex. Rats were trained to perform a lever pressing task and then received injections of the immunotoxin 192-IgG-saporin to selectively lesion cholinergic neurons of the NB. After lesion, rats underwent five days of motor training during which VNS was paired with successful trials. At the conclusion of behavioral training, intracortical microstimulation was used to document movement representations in motor cortex. VNS paired with forelimb training resulted in a substantial increase in the representation of proximal forelimb in rats with an intact NB compared to untrained controls. NB lesions prevent this VNS-dependent increase in proximal forelimb area and result in representations similar to untrained controls. Motor performance was similar between groups, suggesting that differences in forelimb function cannot account for the difference in proximal forelimb representation. Together, these findings indicate that the NB is required for VNS-dependent enhancement of plasticity in the motor cortex and may provide insight into the mechanisms that underlie the benefits of VNS therapy. Copyright © 2016 Elsevier Inc. All rights reserved.

Dynamic modulation of spike timing-dependent calcium influx during corticostriatal upstates

PubMed Central

Evans, R. C.; Maniar, Y. M.

2013-01-01

The striatum of the basal ganglia demonstrates distinctive upstate and downstate membrane potential oscillations during slow-wave sleep and under anesthetic. The upstates generate calcium transients in the dendrites, and the amplitude of these calcium transients depends strongly on the timing of the action potential (AP) within the upstate. Calcium is essential for synaptic plasticity in the striatum, and these large calcium transients during the upstates may control which synapses undergo plastic changes. To investigate the mechanisms that underlie the relationship between calcium and AP timing, we have developed a realistic biophysical model of a medium spiny neuron (MSN). We have implemented sophisticated calcium dynamics including calcium diffusion, buffering, and pump extrusion, which accurately replicate published data. Using this model, we found that either the slow inactivation of dendritic sodium channels (NaSI) or the calcium inactivation of voltage-gated calcium channels (CDI) can cause high calcium corresponding to early APs and lower calcium corresponding to later APs. We found that only CDI can account for the experimental observation that sensitivity to AP timing is dependent on NMDA receptors. Additional simulations demonstrated a mechanism by which MSNs can dynamically modulate their sensitivity to AP timing and show that sensitivity to specifically timed pre- and postsynaptic pairings (as in spike timing-dependent plasticity protocols) is altered by the timing of the pairing within the upstate. These findings have implications for synaptic plasticity in vivo during sleep when the upstate-downstate pattern is prominent in the striatum. PMID:23843436

Feedback Inhibition Shapes Emergent Computational Properties of Cortical Microcircuit Motifs.

PubMed

Jonke, Zeno; Legenstein, Robert; Habenschuss, Stefan; Maass, Wolfgang

2017-08-30

Cortical microcircuits are very complex networks, but they are composed of a relatively small number of stereotypical motifs. Hence, one strategy for throwing light on the computational function of cortical microcircuits is to analyze emergent computational properties of these stereotypical microcircuit motifs. We are addressing here the question how spike timing-dependent plasticity shapes the computational properties of one motif that has frequently been studied experimentally: interconnected populations of pyramidal cells and parvalbumin-positive inhibitory cells in layer 2/3. Experimental studies suggest that these inhibitory neurons exert some form of divisive inhibition on the pyramidal cells. We show that this data-based form of feedback inhibition, which is softer than that of winner-take-all models that are commonly considered in theoretical analyses, contributes to the emergence of an important computational function through spike timing-dependent plasticity: The capability to disentangle superimposed firing patterns in upstream networks, and to represent their information content through a sparse assembly code. SIGNIFICANCE STATEMENT We analyze emergent computational properties of a ubiquitous cortical microcircuit motif: populations of pyramidal cells that are densely interconnected with inhibitory neurons. Simulations of this model predict that sparse assembly codes emerge in this microcircuit motif under spike timing-dependent plasticity. Furthermore, we show that different assemblies will represent different hidden sources of upstream firing activity. Hence, we propose that spike timing-dependent plasticity enables this microcircuit motif to perform a fundamental computational operation on neural activity patterns. Copyright © 2017 the authors 0270-6474/17/378511-13$15.00/0.

Astrocyte and Neuronal Plasticity in the Somatosensory System

PubMed Central

Sims, Robert E.; Butcher, John B.; Parri, H. Rheinallt; Glazewski, Stanislaw

2015-01-01

Changing the whisker complement on a rodent's snout can lead to two forms of experience-dependent plasticity (EDP) in the neurons of the barrel cortex, where whiskers are somatotopically represented. One form, termed coding plasticity, concerns changes in synaptic transmission and connectivity between neurons. This is thought to underlie learning and memory processes and so adaptation to a changing environment. The second, called homeostatic plasticity, serves to maintain a restricted dynamic range of neuronal activity thus preventing its saturation or total downregulation. Current explanatory models of cortical EDP are almost exclusively neurocentric. However, in recent years, increasing evidence has emerged on the role of astrocytes in brain function, including plasticity. Indeed, astrocytes appear as necessary partners of neurons at the core of the mechanisms of coding and homeostatic plasticity recorded in neurons. In addition to neuronal plasticity, several different forms of astrocytic plasticity have recently been discovered. They extend from changes in receptor expression and dynamic changes in morphology to alteration in gliotransmitter release. It is however unclear how astrocytic plasticity contributes to the neuronal EDP. Here, we review the known and possible roles for astrocytes in the barrel cortex, including its plasticity. PMID:26345481

CORRELATION OF THE GLASS TRANSITION TEMPERATURE OF PLASTICIZED PVC USING A LATTICE FLUID MODEL

EPA Science Inventory

A model has been developed to describe the composition dependence of the glass transition temperature (Tg) of polyvinyl chloride (PVC) + plasticizer mixtures. The model is based on Sanchez-Lacombe equation of state and the Gibbs-Di Marzio criterion, which states that th...

Thermal Equilibrium in Plastic and Glass Microscale Containers

ERIC Educational Resources Information Center

Curbelo, Estela; Cerda, Maria F.; Mendez, Eduardo

2007-01-01

The study describes the various thermal equilibrium conditions, which should be taken care for while designing or selecting the plastic and glass microscale containers for physical chemistry experiments. The results show that the thermal equilibrium completely depends on the material of the container for the same volume and thickness.

Eigendeformation-Based Homogenization of Concrete

DTIC Science & Technology

2009-03-26

The inelastic behavior of concrete is modeled using three types of eigenstrains . The eigenstrains in the mortar phase include pore compaction (or...lock-in), rate-dependent damage and plasticity eigenstrains , whereas the inelastic behavior of aggregates is assumed to be governed by plasticity...3  3. Microscale Inelastic Properties of Concrete: Eigenstrain

Growth and physiological plasticity among differentially adapted genotypes of a widespread C4 grass under altered precipitation

USDA-ARS?s Scientific Manuscript database

Background/Question/Methods Variation in precipitation expected with climate change may impact plant fitness and alter ecosystem dynamics by modifying species phenology, productivity, and physiology. Species responses to varied precipitation will depend in part on plastic responses of genotypes ad...

Neural Circuitry and Plasticity Mechanisms Underlying Delay Eyeblink Conditioning

ERIC Educational Resources Information Center

Freeman, John H.; Steinmetz, Adam B.

2011-01-01

Pavlovian eyeblink conditioning has been used extensively as a model system for examining the neural mechanisms underlying associative learning. Delay eyeblink conditioning depends on the intermediate cerebellum ipsilateral to the conditioned eye. Evidence favors a two-site plasticity model within the cerebellum with long-term depression of…

Dependence of Plastic TATB Shock-Wave Sensitivity on Temperature, Density and Technology Factors

NASA Astrophysics Data System (ADS)

Vlasov, Yu. A.; Kosolapov, V. B.; Fomicheva, L. V.; Khabarov, I. P.

1999-06-01

Mixed TATB-based HE is the most perspective because of the manufacture and exploitation safety of its items. At the same time the safety of these explosive, at high temperatures, which take place at emergencies, causes the certain anxiety. Plastic TATB shock-wave sensitivity (SWS) researches has shown that temperature as one of the important factors of external influence is not always the determining reason of SWS change. It is known that density influence on SWS significantly. At the same time density depends on temperature and technology of details manufacturing. In this connection in this work the temperature dependence of plastic TATB SWS was studied in view of convertible and irreversible changes of density (p) under heating at -50[C up to 90[C . It is shown that during these influences the dependence of threshold pressure of initiation (P) from temperature is explained, first of all, by change of HE density, caused by its thermal expansion (compression), and also by irreversible changes of p and HE structure, arising at heating. It is found also that the share of irreversible change of density depends on technology of HE details manufacturing and is explained by relaxation of residual pressure in them. The mentioned relaxation is finished after the first cycles of thermal influence. The value of density change, caused by this factor, depends on temperature and duration of heating.

Temperature and food mediate long-term thermotactic behavioral plasticity by association-independent mechanisms in C. elegans.

PubMed

Chi, Cynthia A; Clark, Damon A; Lee, Stella; Biron, David; Luo, Linjiao; Gabel, Christopher V; Brown, Jeffrey; Sengupta, Piali; Samuel, Aravinthan D T

2007-11-01

Thermotactic behavior in the nematode Caenorhabditis elegans exhibits long-term plasticity. On a spatial thermal gradient, C. elegans tracks isotherms near a remembered set-point (T(S)) corresponding to its previous cultivation temperature. When navigating at temperatures above its set-point (T>T(S)), C. elegans crawls down spatial thermal gradients towards the T(S) in what is called cryophilic movement. The T(S) retains plasticity in the adult stage and is reset by approximately 4 h of sustained exposure to a new temperature. Long-term plasticity in C. elegans thermotactic behavior has been proposed to represent an associative learning of specific temperatures conditioned in the presence or absence of bacterial food. Here, we use quantitative behavioral assays to define the temperature and food-dependent determinants of long-term plasticity in the different modes of thermotactic behavior. Under our experimental conditions, we find that starvation at a specific temperature neither disrupts T(S) resetting toward the starvation temperature nor induces learned avoidance of the starvation temperature. We find that prolonged starvation suppresses the cryophilic mode of thermotactic behavior. The hen-1 and tax-6 genes have been reported to affect associative learning between temperature and food-dependent cues. Under our experimental conditions, mutation in the hen-1 gene, which encodes a secreted protein with an LDL receptor motif, does not significantly affect thermotactic behavior or long-term plasticity. Mutation in the tax-6 calcineurin gene abolishes thermotactic behavior altogether. In summary, we do not find evidence that long-term plasticity requires association between temperature and the presence or absence of bacterial food.

Similarities in temperature-dependent gene expression plasticity across timescales in threespine stickleback (Gasterosteus aculeatus).

PubMed

Metzger, David C H; Schulte, Patricia M

2018-04-14

Phenotypic plasticity occurs at a variety of timescales, but little is known about the degree to which plastic responses at different timescales are associated with similar underlying molecular processes, which is critical for assessing the effects of plasticity on evolutionary trajectories. To address this issue, we identified differential gene expression in response to developmental temperature in the muscle transcriptome of adult threespine stickleback (Gasterosteus aculeatus) exposed to 12, 18 and 24°C until hatch and then held at 18°C for 9 months and compared these results to differential gene expression in response to adult thermal acclimation in stickleback developed at 18°C and then acclimated to 5 and 25°C as adults. Adult thermal acclimation affected the expression of 7,940 and 7,015 genes in response to cold and warm acclimation, respectively, and 4,851 of these genes responded in both treatments. In contrast, the expression of only 33 and 29 genes was affected by cold and warm development, respectively. The majority of the genes affected by developmental temperature were also affected by adult acclimation temperature. Many genes that were differentially expressed as a result of adult acclimation were associated with previously identified temperature-dependent effects on DNA methylation patterns, suggesting a role of epigenetic mechanisms in regulating gene expression plasticity during acclimation. Taken together, these results demonstrate similarities between the persistent effects of developmental plasticity on gene expression and the effects of adult thermal acclimation, emphasizing the potential for mechanistic links between plasticity acting at these different life stages. © 2018 John Wiley & Sons Ltd.

miR-132, an experience-dependent microRNA, is essential for visual cortex plasticity

PubMed Central

Mellios, Nikolaos; Sugihara, Hiroki; Castro, Jorge; Banerjee, Abhishek; Le, Chuong; Kumar, Arooshi; Crawford, Benjamin; Strathmann, Julia; Tropea, Daniela; Levine, Stuart S.; Edbauer, Dieter; Sur, Mriganka

2011-01-01

Using multiple quantitative analyses, we discovered microRNAs (miRNAs) abundantly expressed in visual cortex that respond to dark-rearing (DR) and/or monocular deprivation (MD). The most significantly altered miRNA, miR-132, was rapidly upregulated after eye-opening and delayed by DR. In vivo inhibition of miR-132 prevented ocular dominance plasticity in identified neurons following MD, and affected maturation of dendritic spines, demonstrating its critical role in the plasticity of visual cortex circuits. PMID:21892155

Plastic mistaken for prey by a colony-breeding Eleonora's falcon (Falco eleonorae) in the Mediterranean Sea, revealed by camera-trap.

PubMed

Steen, Ronny; Torjussen, Cathrine S; Jones, Dean W; Tsimpidis, Thodoris; Miliou, Anastasia

2016-05-15

Discarded plastic is known to be harmful for marine animals through ingestion and entanglement. Here we report the first documentation of Eleonora's falcons providing plastic waste to dependent nestlings. Eleonora's falcons breed colonially on sea cliffs and islets in areas of the Mediterranean Sea and the Canary Islands in which they normally feed their nestlings exclusively with small migratory birds. Copyright © 2016 Elsevier Ltd. All rights reserved.

Interclonal proteomic responses to predator exposure in Daphnia magna may depend on predator composition of habitats.

PubMed

Otte, Kathrin A; Schrank, Isabella; Fröhlich, Thomas; Arnold, Georg J; Laforsch, Christian

2015-08-01

Phenotypic plasticity, the ability of one genotype to express different phenotypes in response to changing environmental conditions, is one of the most common phenomena characterizing the living world and is not only relevant for the ecology but also for the evolution of species. Daphnia, the water flea, is a textbook example for predator-induced phenotypic plastic defences; however, the analysis of molecular mechanisms underlying these inducible defences is still in its early stages. We exposed Daphnia magna to chemical cues of the predator Triops cancriformis to identify key processes underlying plastic defensive trait formation. To get a more comprehensive idea of this phenomenon, we studied four genotypes with five biological replicates each, originating from habitats characterized by different predator composition, ranging from predator-free habitats to habitats containing T. cancriformis. We analysed the morphologies as well as proteomes of predator-exposed and control animals. Three genotypes showed morphological changes when the predator was present. Using a high-throughput proteomics approach, we found 294 proteins which were significantly altered in their abundance after predator exposure in a general or genotype-dependent manner. Proteins connected to genotype-dependent responses were related to the cuticle, protein synthesis and calcium binding, whereas the yolk protein vitellogenin increased in abundance in all genotypes, indicating their involvement in a more general response. Furthermore, genotype-dependent responses at the proteome level were most distinct for the only genotype that shares its habitat with Triops. Altogether, our study provides new insights concerning genotype-dependent and general molecular processes involved in predator-induced phenotypic plasticity in D. magna. © 2015 John Wiley & Sons Ltd.

Investigation of thermal treatment on selective separation of post consumer plastics prior to froth flotation.

PubMed

Guney, Ali; Poyraz, M Ibrahim; Kangal, Olgac; Burat, Firat

2013-09-01

Plastics have become the widely used materials because of their advantages, such as cheapness, endurance, lightness, and hygiene. However, they cause waste and soil pollution and they do not easily decompose. Many promising technologies are being investigated for separating mixed thermoplastics, but they are still uneconomical and unreliable. Depending on their surface characteristics, these plastics can be separated from each other by flotation method which is useful mineral processing technique with its low cost and simplicity. The main objective of this study is to investigate the flotation characteristics of PET and PVC and determine the effect of plasticizer reagents on efficient plastic separation. For that purpose, various parameters such as pH, plasticizer concentration, plasticizer type, conditioning temperature and thermal conditioning were investigated. As a result, PET particles were floated with 95.1% purity and 65.3% efficiency while PVC particles were obtained with 98.1% purity and 65.3% efficiency. Copyright © 2013 Elsevier Ltd. All rights reserved.

Daily accumulation rates of marine debris on sub-Antarctic island beaches.

PubMed

Eriksson, Cecilia; Burton, Harry; Fitch, Stuart; Schulz, Martin; van den Hoff, John

2013-01-15

The worlds' oceans contain a large but unknown amount of plastic debris. We made daily collections of marine debris stranded at two sub-Antarctic islands to establish (a) physical causes of strandings, and (b) a sampling protocol to better estimate the oceans' plastic loading. Accumulation rates at some beaches were dependent on tide and onshore winds. Most of the 6389 items collected were plastic (Macquarie 95%, Heard 94%) and discarded or lost fishing gear comprised 22% of those plastic items. Stalked barnacles (Lepas spp.) were a regular attachment on Macquarie debris but not at Heard Island. The daily accumulation rate of plastic debris on Macquarie Island was an order of magnitude higher than that estimated from monthly surveys during the same 4 months in the previous 5 years. This finding suggests that estimates of the oceans' plastic loading are an order of magnitude too low. Copyright © 2012 Elsevier Ltd. All rights reserved.

Phyllosphere yeasts rapidly break down biodegradable plastics

PubMed Central

2011-01-01

The use of biodegradable plastics can reduce the accumulation of environmentally persistent plastic wastes. The rate of degradation of biodegradable plastics depends on environmental conditions and is highly variable. Techniques for achieving more consistent degradation are needed. However, only a few microorganisms involved in the degradation process have been isolated so far from the environment. Here, we show that Pseudozyma spp. yeasts, which are common in the phyllosphere and are easily isolated from plant surfaces, displayed strong degradation activity on films made from poly-butylene succinate or poly-butylene succinate-co-adipate. Strains of P. antarctica isolated from leaves and husks of paddy rice displayed strong degradation activity on these films at 30°C. The type strain, P. antarctica JCM 10317, and Pseudozyma spp. strains from phyllosphere secreted a biodegradable plastic-degrading enzyme with a molecular mass of about 22 kDa. Reliable source of biodegradable plastic-degrading microorganisms are now in our hands. PMID:22126328

Phyllosphere yeasts rapidly break down biodegradable plastics.

PubMed

Kitamoto, Hiroko K; Shinozaki, Yukiko; Cao, Xiao-Hong; Morita, Tomotake; Konishi, Masaaki; Tago, Kanako; Kajiwara, Hideyuki; Koitabashi, Motoo; Yoshida, Shigenobu; Watanabe, Takashi; Sameshima-Yamashita, Yuka; Nakajima-Kambe, Toshiaki; Tsushima, Seiya

2011-11-29

The use of biodegradable plastics can reduce the accumulation of environmentally persistent plastic wastes. The rate of degradation of biodegradable plastics depends on environmental conditions and is highly variable. Techniques for achieving more consistent degradation are needed. However, only a few microorganisms involved in the degradation process have been isolated so far from the environment. Here, we show that Pseudozyma spp. yeasts, which are common in the phyllosphere and are easily isolated from plant surfaces, displayed strong degradation activity on films made from poly-butylene succinate or poly-butylene succinate-co-adipate. Strains of P. antarctica isolated from leaves and husks of paddy rice displayed strong degradation activity on these films at 30°C. The type strain, P. antarctica JCM 10317, and Pseudozyma spp. strains from phyllosphere secreted a biodegradable plastic-degrading enzyme with a molecular mass of about 22 kDa. Reliable source of biodegradable plastic-degrading microorganisms are now in our hands.

Interneuron- and GABAA receptor-specific inhibitory synaptic plasticity in cerebellar Purkinje cells

NASA Astrophysics Data System (ADS)

He, Qionger; Duguid, Ian; Clark, Beverley; Panzanelli, Patrizia; Patel, Bijal; Thomas, Philip; Fritschy, Jean-Marc; Smart, Trevor G.

2015-07-01

Inhibitory synaptic plasticity is important for shaping both neuronal excitability and network activity. Here we investigate the input and GABAA receptor subunit specificity of inhibitory synaptic plasticity by studying cerebellar interneuron-Purkinje cell (PC) synapses. Depolarizing PCs initiated a long-lasting increase in GABA-mediated synaptic currents. By stimulating individual interneurons, this plasticity was observed at somatodendritic basket cell synapses, but not at distal dendritic stellate cell synapses. Basket cell synapses predominantly express β2-subunit-containing GABAA receptors; deletion of the β2-subunit ablates this plasticity, demonstrating its reliance on GABAA receptor subunit composition. The increase in synaptic currents is dependent upon an increase in newly synthesized cell surface synaptic GABAA receptors and is abolished by preventing CaMKII phosphorylation of GABAA receptors. Our results reveal a novel GABAA receptor subunit- and input-specific form of inhibitory synaptic plasticity that regulates the temporal firing pattern of the principal output cells of the cerebellum.

Synaptic plasticity functions in an organic electrochemical transistor

NASA Astrophysics Data System (ADS)

Gkoupidenis, Paschalis; Schaefer, Nathan; Strakosas, Xenofon; Fairfield, Jessamyn A.; Malliaras, George G.

2015-12-01

Synaptic plasticity functions play a crucial role in the transmission of neural signals in the brain. Short-term plasticity is required for the transmission, encoding, and filtering of the neural signal, whereas long-term plasticity establishes more permanent changes in neural microcircuitry and thus underlies memory and learning. The realization of bioinspired circuits that can actually mimic signal processing in the brain demands the reproduction of both short- and long-term aspects of synaptic plasticity in a single device. Here, we demonstrate the implementation of neuromorphic functions similar to biological memory, such as short- to long-term memory transition, in non-volatile organic electrochemical transistors (OECTs). Depending on the training of the OECT, the device displays either short- or long-term plasticity, therefore, exhibiting non von Neumann characteristics with merged processing and storing functionalities. These results are a first step towards the implementation of organic-based neuromorphic circuits.

Polymer blends used for the aqueous coating of solid dosage forms: importance of the type of plasticizer.

PubMed

Lecomte, F; Siepmann, J; Walther, M; MacRae, R J; Bodmeier, R

2004-09-14

The aim of this study was to investigate the importance of the type of plasticizer in polymer blends used for the coating of solid dosage forms, comparing a lipophilic and a hydrophilic plasticizer (dibutyl sebacate (DBS) and triethyl citrate (TEC)). In vitro drug release from propranolol hydrochloride (propranolol HCl)-loaded pellets coated with blends of ethyl cellulose (EC) and Eudragit L (100:0, 75:25, 50:50, 25:75 and 0:100 w/w) was investigated at low as well as at high pH. To better understand the underlying mass transport mechanisms, the physicochemical properties of the film coatings (e.g. mechanical resistance, water uptake and dry weight loss behavior) were determined. Interestingly, drug release strongly depended on the type of plasticizer. Importantly, not only the slope but also the shape of the release curves was affected, indicating that the chemical nature of the plasticizer plays a major role for the underlying drug release mechanisms. Diffusion through the intact polymer coatings and/or through water-filled cracks was found to be dominating for the control of drug release. The relative importance of these pathways strongly depended on the polymer blend ratio and type of plasticizer. In contrast to DBS, TEC rapidly leached out of the coatings, resulting in decreasing mechanical resistances of the films and, thus, facilitated crack formation. In addition, the hydrophilicity of the plasticizer significantly affected the water uptake behavior of the film coatings and, hence, changes in the coatings' toughness and drug permeability. Also the relative affinity of the plasticizer to the different polymers was found to be of significance. In contrast to TEC, DBS has a higher affinity to EC than to Eudragit L, resulting in potential redistributions of this plasticizer within the polymeric systems and changes in the release profiles during storage. Importantly, these effects could be avoided with appropriate curing conditions and preparation techniques for the coating dispersions.

Spermidine boosts autophagy to protect from synapse aging.

PubMed

Bhukel, Anuradha; Madeo, Frank; Sigrist, Stephan J

2017-02-01

All animals form memories to adapt their behavior in a context-dependent manner. With increasing age, however, forming new memories becomes less efficient. While synaptic plasticity promotes memory formation, the etiology of age-induced memory formation remained enigmatic. Previous work showed that simple feeding of polyamine spermidine protects from age-induced memory impairment in Drosophila. Most recent work now shows that spermidine operates directly at synapses, allowing for an autophagy-dependent homeostatic regulation of presynaptic specializations. How exactly autophagic regulations intersect with synaptic plasticity should be an interesting subject for future research.

EDITORIAL: Proceedings of the IUTAM Symposium on Plasticity at the Micron Scale, Technical University of Denmark, 21 25 Mark 2006

NASA Astrophysics Data System (ADS)

Tvergaard, Viggo

2007-01-01

This special issue constitutes the Proceedings of the IUTAM Symposium on Plasticity at the Micron Scale, held at the Technical University of Denmark, 21-25 May 2006. The purpose of this symposium was to gather a group of leading scientists working in areas of importance to length scale dependent plasticity. This includes work on phenomenological strain gradient plasticity models, studies making use of discrete dislocation models, and even atomic level models. Experimental investigations are central to all this, as all the models focus on developing an improved understanding of real observed phenomena. The opening lecture by Professor N A Fleck, Cambridge University, discussed experimental as well as theoretical approaches. Also, recent results for the surface roughness at grain boundaries were presented based on experiments and crystal plasticity modelling. A number of presentations focused on experiments for metals at a small length scale, e.g. using indenters or a small single crystal compression test. It was found that there are causes of the size effects other than the geometrically necessary dislocations related to strain gradients. Several lectures on scale dependent phenomenological plasticity theories discussed different methods of incorporating the characteristic material length. This included lower order plasticity theories as well as higher order theories, within standard plasticity models or crystal plasticity. Differences in the ways of incorporating higher order boundary conditions were the subject of much discussion. Various methods for discrete dislocation modelling of plastic deformation were used in some of the presentations to obtain a more detailed understanding of length scale effects in metals. This included large scale computations for dislocation dynamics as well as new statistical mechanics approaches to averaging of dislocation plasticity. Furthermore, at a somewhat larger length scale, applications of scale dependent plasticity to granular media and to cellular solids were discussed. The symposium consisted of thirty-six lectures, all of which were invited based on strong expertise in the area. Some of the lectures are not represented in this special issue, mainly because of prior commitments to publish elsewhere. The international Scientific Committee responsible for the symposium comprised the following: Professor V Tvergaard (Chairman) Denmark Professor A Benallal France Professor N A Fleck UK Professor L B Freund (IUTAM Representative) USA Professor E van der Giessen The Netherlands Professor J W Hutchinson USA Professor A Needleman USA Professor B Svendsen Germany The Committee gratefully acknowledges financial support for the symposium from the International Union of Theoretical and Applied Mechanics, from Novo Nordisk A/S and from the Villum Kann Rasmussen Foundation. In the organization of all parts of the symposium the enthusiastic participation of Dr C F Niordson and Dr P Redanz was invaluable. The smooth running of the symposium also owes much to the efforts and organizational skills of Bente Andersen.

Biphasic Somatic A-Type K+ Channel Downregulation Mediates Intrinsic Plasticity in Hippocampal CA1 Pyramidal Neurons

PubMed Central

Jung, Sung-Cherl; Hoffman, Dax A.

2009-01-01

Since its original description, the induction of synaptic long-term potentiation (LTP) has been known to be accompanied by a lasting increase in the intrinsic excitability (intrinsic plasticity) of hippocampal neurons. Recent evidence shows that dendritic excitability can be enhanced by an activity-dependent decrease in the activity of A-type K+ channels. In the present manuscript, we examined the role of A-type K+ channels in regulating intrinsic excitability of CA1 pyramidal neurons of the hippocampus after synapse-specific LTP induction. In electrophysiological recordings we found that LTP induced a potentiation of excitability which was accompanied by a two-phased change in A-type K+ channel activity recorded in nucleated patches from organotypic slices of rat hippocampus. Induction of LTP resulted in an immediate but short lasting hyperpolarization of the voltage-dependence of steady-state A-type K+ channel inactivation along with a progressive, long-lasting decrease in peak A-current density. Blocking clathrin-mediated endocytosis prevented the A-current decrease and most measures of intrinsic plasticity. These results suggest that two temporally distinct but overlapping mechanisms of A-channel downregulation together contribute to the plasticity of intrinsic excitability. Finally we show that intrinsic plasticity resulted in a global enhancement of EPSP-spike coupling. PMID:19662093

Diversity in Long-Term Synaptic Plasticity at Inhibitory Synapses of Striatal Spiny Neurons

ERIC Educational Resources Information Center

Rueda-Orozco, Pavel E.; Mendoza, Ernesto; Hernandez, Ricardo; Aceves, Jose J.; Ibanez-Sandoval, Osvaldo; Galarraga, Elvira; Bargas, Jose

2009-01-01

Procedural memories and habits are posited to be stored in the basal ganglia, whose intrinsic circuitries possess important inhibitory connections arising from striatal spiny neurons. However, no information about long-term plasticity at these synapses is available. Therefore, this work describes a novel postsynaptically dependent long-term…

Introduction of starch into plastic films: Advent of starch in plastic

USDA-ARS?s Scientific Manuscript database

Following the oil crises of the 1970’s, scientists started thinking of alternative sources of materials that are not so dependent on foreign supplies. Probably riding on this concern, in part, came Griffin’s idea for creating a matted surface on low density polyethylene (LDPE) films in order to impr...

Serotonin- and Training-Induced Dynamic Regulation of CREB2 in "Aplysia"

ERIC Educational Resources Information Center

Liu, Rong-Yu; Shah, Shreyansh; Cleary, Leonard J.; Byrne, John H.

2011-01-01

Long-term memory and plasticity, including long-term synaptic facilitation (LTF) of the "Aplysia" sensorimotor synapse, depend on the activation of transcription factors that regulate genes necessary for synaptic plasticity. In the present study we found that treatment with 5-HT and behavioral training produce biphasic changes in the expression of…

Protein Phosphatase 1-Dependent Transcriptional Programs for Long-Term Memory and Plasticity

ERIC Educational Resources Information Center

Graff, Johannes; Koshibu, Kyoko; Jouvenceau, Anne; Dutar, Patrick; Mansuy, Isabelle M.

2010-01-01

Gene transcription is essential for the establishment and the maintenance of long-term memory (LTM) and for long-lasting forms of synaptic plasticity. The molecular mechanisms that control gene transcription in neuronal cells are complex and recruit multiple signaling pathways in the cytoplasm and the nucleus. Protein kinases (PKs) and…

A Presynaptic Role for FMRP during Protein Synthesis-Dependent Long-Term Plasticity in "Aplysia"

ERIC Educational Resources Information Center

Till, Sally M.; Li, Hsiu-Ling; Miniaci, Maria Concetta; Kandel, Eric R.; Choi, Yun-Beom

2011-01-01

Loss of the Fragile X mental retardation protein (FMRP) is associated with presumed postsynaptic deficits in mouse models of Fragile X syndrome. However, the possible presynaptic roles of FMRP in learning-related plasticity have received little attention. As a result, the mechanisms whereby FMRP influences synaptic function remain poorly…

A Postsynaptic AMPK→p21-Activated Kinase Pathway Drives Fasting-Induced Synaptic Plasticity in AgRP Neurons.

PubMed

Kong, Dong; Dagon, Yossi; Campbell, John N; Guo, Yikun; Yang, Zongfang; Yi, Xinchi; Aryal, Pratik; Wellenstein, Kerry; Kahn, Barbara B; Sabatini, Bernardo L; Lowell, Bradford B

2016-07-06

AMP-activated protein kinase (AMPK) plays an important role in regulating food intake. The downstream AMPK substrates and neurobiological mechanisms responsible for this, however, are ill defined. Agouti-related peptide (AgRP)-expressing neurons in the arcuate nucleus regulate hunger. Their firing increases with fasting, and once engaged they cause feeding. AgRP neuron activity is regulated by state-dependent synaptic plasticity: fasting increases dendritic spines and excitatory synaptic activity; feeding does the opposite. The signaling mechanisms underlying this, however, are also unknown. Using neuron-specific approaches to measure and manipulate kinase activity specifically within AgRP neurons, we establish that fasting increases AMPK activity in AgRP neurons, that increased AMPK activity in AgRP neurons is both necessary and sufficient for fasting-induced spinogenesis and excitatory synaptic activity, and that the AMPK phosphorylation target mediating this plasticity is p21-activated kinase. This provides a signaling and neurobiological basis for both AMPK regulation of energy balance and AgRP neuron state-dependent plasticity. Copyright © 2016 Elsevier Inc. All rights reserved.

Presynaptic serotonin 2A receptors modulate thalamocortical plasticity and associative learning

PubMed Central

Barre, Alexander; Berthoux, Coralie; De Bundel, Dimitri; Valjent, Emmanuel; Bockaert, Joël; Marin, Philippe; Bécamel, Carine

2016-01-01

Higher-level cognitive processes strongly depend on a complex interplay between mediodorsal thalamus nuclei and the prefrontal cortex (PFC). Alteration of thalamofrontal connectivity has been involved in cognitive deficits of schizophrenia. Prefrontal serotonin (5-HT)2A receptors play an essential role in cortical network activity, but the mechanism underlying their modulation of glutamatergic transmission and plasticity at thalamocortical synapses remains largely unexplored. Here, we show that 5-HT2A receptor activation enhances NMDA transmission and gates the induction of temporal-dependent plasticity mediated by NMDA receptors at thalamocortical synapses in acute PFC slices. Expressing 5-HT2A receptors in the mediodorsal thalamus (presynaptic site) of 5-HT2A receptor-deficient mice, but not in the PFC (postsynaptic site), using a viral gene-delivery approach, rescued the otherwise absent potentiation of NMDA transmission, induction of temporal plasticity, and deficit in associative memory. These results provide, to our knowledge, the first physiological evidence of a role of presynaptic 5-HT2A receptors located at thalamocortical synapses in the control of thalamofrontal connectivity and the associated cognitive functions. PMID:26903620

Activity-dependent stochastic resonance in recurrent neuronal networks

NASA Astrophysics Data System (ADS)

Volman, Vladislav

2009-03-01

An important source of noise for neuronal networks is that of the stochastic nature of synaptic transmission. In particular, there can occur spontaneous asynchronous release of neurotransmitter at a rate that is strongly dependent on the presynaptic Ca2+ concentration and hence strongly dependent on the rate of spike induced Ca2+. Here it is shown that this noise can lead to a new form of stochastic resonance for local circuits consisting of roughly 100 neurons - a ``microcolumn''- coupled via noisy plastic synapses. Furthermore, due to the plastic coupling and activity-dependent noise component, the detection of weak stimuli will also depend on the structure of the latter. In addition, the circuit can exhibit short-term memory, by which we mean that spiking will continue to occur for a transient period following removal of the stimulus. These results can be directly tested in experiments on cultured networks.

Different universality classes at the yielding transition of amorphous systems

NASA Astrophysics Data System (ADS)

Jagla, E. A.

2017-08-01

We study the yielding transition of a two-dimensional amorphous system under shear by using a mesoscopic elasto-plastic model. The model combines a full (tensorial) description of the elastic interactions in the system and the possibility of structural reaccommodations that are responsible for the plastic behavior. The possible structural reaccommodations are encoded in the form of a "plastic disorder" potential, which is chosen independently at each position of the sample to account for local heterogeneities. We observe that the stress must exceed a critical value σc in order for the system to yield. In addition, when the system yields a flow curve (relating stress σ and strain rate γ ˙) of the form γ ˙˜(σ-σc) β is obtained. Remarkably, we observe the value of β to depend on some details of the plastic disorder potential. For smooth potentials a value of β ≃2.0 is obtained, whereas for potentials obtained as a concatenation of smooth pieces a value β ≃1.5 is observed in the simulations. This indicates a dependence of critical behavior on details of the plastic behavior. In addition, by integrating out nonessential, harmonic degrees of freedom, we derive a simplified scalar version of the model that represents a collection of interacting Prandtl-Tomlinson particles. A mean-field treatment of this interaction reproduces the difference of β exponents for the two classes of plastic disorder potentials and provides values of β that compare favorably with those found in the full simulations.

Evolution of plasticity and adaptive responses to climate change along climate gradients.

PubMed

Kingsolver, Joel G; Buckley, Lauren B

2017-08-16

The relative contributions of phenotypic plasticity and adaptive evolution to the responses of species to recent and future climate change are poorly understood. We combine recent (1960-2010) climate and phenotypic data with microclimate, heat balance, demographic and evolutionary models to address this issue for a montane butterfly, Colias eriphyle , along an elevational gradient. Our focal phenotype, wing solar absorptivity, responds plastically to developmental (pupal) temperatures and plays a central role in thermoregulatory adaptation in adults. Here, we show that both the phenotypic and adaptive consequences of plasticity vary with elevation. Seasonal changes in weather generate seasonal variation in phenotypic selection on mean and plasticity of absorptivity, especially at lower elevations. In response to climate change in the past 60 years, our models predict evolutionary declines in mean absorptivity (but little change in plasticity) at high elevations, and evolutionary increases in plasticity (but little change in mean) at low elevation. The importance of plasticity depends on the magnitude of seasonal variation in climate relative to interannual variation. Our results suggest that selection and evolution of both trait means and plasticity can contribute to adaptive response to climate change in this system. They also illustrate how plasticity can facilitate rather than retard adaptive evolutionary responses to directional climate change in seasonal environments. © 2017 The Author(s).

Toxicity of leachate from weathering plastics: An exploratory screening study with Nitocra spinipes.

PubMed

Bejgarn, Sofia; MacLeod, Matthew; Bogdal, Christian; Breitholtz, Magnus

2015-08-01

Between 60% and 80% of all marine litter is plastic. Leachate from plastics has previously been shown to cause acute toxicity in the freshwater species Daphnia magna. Here, we present an initial screening of the marine environmental hazard properties of leachates from weathering plastics to the marine harpacticoid copepod [Crustacea] Nitocra spinipes. Twenty-one plastic products made of different polymeric materials were leached and irradiated with artificial sunlight. Eight of the twenty-one plastics (38%) produced leachates that caused acute toxicity. Differences in toxicity were seen for different plastic products, and depending on the duration of irradiation. There was no consistent trend in how toxicity of leachate from plastics changed as a function of irradiation time. Leachate from four plastics became significantly more toxic after irradiation, two became significantly less toxic and two did not change significantly. Analysis of leachates from polyvinyl chloride (PVC) by liquid chromatography coupled to a full-scan high-resolution mass spectrometer showed that the leachates were a mixture of substances, but did not show evidence of degradation of the polymer backbone. This screening study demonstrates that leachates from different plastics differ in toxicity to N. spinipes and that the toxicity varies under simulated weathering. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nusrat, H; Pang, G; Au, P

Purpose: The doping of plastic scintillators with high-Z elements changes the radiation interaction cross section of the medium and therefore changes the intrinsic response of the detector. The selection of doped plastic scintillators available commercially is limited. This research aims to develop a novel methodology for the mechanical doping of plastic scintillating materials. The ultimate goal of this project is to use doped scintillators of varying intrinsic behavior to unfold the LET (energy) spectrum of any radiation beam. Methods: Commercially available BC408 plastic scintillator was obtained and crushed into uniform powder (using ball mill). Two separate materials were tested formore » light output signal: uncrushed scintillator and scintillating powder bound by glue. Commercially available U301 UV-hardening glue was used. Scintillation response was measured by creating a thin housing of black acrylic that allowed light from each scintillator to be guided to an optical fiber via a taper. The optical fiber was connected to a PMT; signal was measured using an electrometer. Tests were conducted to determine if crushing+bonding distorted linearity and energy dependence of detector response. Linearity was tested for by irradiating (uncrushed and crushed+glued) for varying durations ensuring signal scaled accordingly; this was done using 300kV x-rays and 6MeV electrons. The effect on energy dependence was examined by obtaining a signal ratio (100kV vs. 300kV; 6MeV vs. 18MeV) for both uncrushed and crushed+glued scintillating material. Results: Crushing and binding with U301 glue did not have an effect on linearity. Energy dependence was changed by 20.3%; crushing+bonding decreased the sensitivity at low energy radiation. Conclusion: This work indicates that crushing and binding of plastic scintillating material does not change the linearity of its response to radiation but does have an effect on the energy dependence. Future work involves addition of high-Z dopants (W, Mo, Pb) and characterization of the detector response.« less

[Independence in Plastic Surgery - Benefit or Barrier? Analysis of the Publication Performance in Academic Plastic Surgery Depending on Varying Organisational Structures].

PubMed

Schubert, C D; Leitsch, S; Haertnagl, F; Haas, E M; Giunta, R E

2015-08-01

Despite its recognition as an independent specialty, at German university hospitals the field of plastic surgery is still underrepresented in terms of independent departments with a dedicated research focus. The aim of this study was to analyse the publication performance within the German academic plastic surgery environment and to compare independent departments and dependent, subordinate organisational structures regarding their publication performance. Organisational structures and number of attending doctors in German university hospitals were examined via a website analysis. A pubmed analysis was applied to assess the publication performance (number of publications, cumulative impact factor, impact factor/publication, number of publications/MD, number of publications/unit) between 2009 and 2013. In a journal analysis the distribution of the cumulative impact factor and number of publications in different journals as well as the development of the impact factor in the top journals were analysed. Out of all 35 university hospitals there exist 12 independent departments for plastic surgery and 8 subordinate organisational structures. In 15 university hospitals there were no designated plastic surgery units. The number of attending doctors differed considerably between independent departments (3.6 attending doctors/unit) and subordinate organisational structures (1.1 attending doctors/unit). The majority of publications (89.0%) and of the cumulative impact factor (91.2%) as well as most of the publications/MD (54 publications/year) and publications/unit (61 publications/year) were created within the independent departments. Only in departments top publications with an impact factor > 5 were published. In general a negative trend regarding the number of publications (- 13.4%) and cumulative impact factor (- 28.9%) was observed. 58.4% of all publications were distributed over the top 10 journals. Within the latter the majority of articles were published in English journals (60% of publications, 79.9% of the cumulative impact factor). The average impact factor of the top 10 journals increased by 13.5% from 2009 to 2013. In contrast to subordinate and dependent organisational structures, independent departments of plastic surgery are the key performers within German academic plastic surgery which, however, suffers from a general declining publication performance. Hence, the type of organisational structure has a crucial influence on the research performance. © Georg Thieme Verlag KG Stuttgart · New York.

A unified dislocation density-dependent physical-based constitutive model for cold metal forming

NASA Astrophysics Data System (ADS)

Schacht, K.; Motaman, A. H.; Prahl, U.; Bleck, W.

2017-10-01

Dislocation-density-dependent physical-based constitutive models of metal plasticity while are computationally efficient and history-dependent, can accurately account for varying process parameters such as strain, strain rate and temperature; different loading modes such as continuous deformation, creep and relaxation; microscopic metallurgical processes; and varying chemical composition within an alloy family. Since these models are founded on essential phenomena dominating the deformation, they have a larger range of usability and validity. Also, they are suitable for manufacturing chain simulations since they can efficiently compute the cumulative effect of the various manufacturing processes by following the material state through the entire manufacturing chain and also interpass periods and give a realistic prediction of the material behavior and final product properties. In the physical-based constitutive model of cold metal plasticity introduced in this study, physical processes influencing cold and warm plastic deformation in polycrystalline metals are described using physical/metallurgical internal variables such as dislocation density and effective grain size. The evolution of these internal variables are calculated using adequate equations that describe the physical processes dominating the material behavior during cold plastic deformation. For validation, the model is numerically implemented in general implicit isotropic elasto-viscoplasticity algorithm as a user-defined material subroutine (UMAT) in ABAQUS/Standard and used for finite element simulation of upsetting tests and a complete cold forging cycle of case hardenable MnCr steel family.

Transport and release of chemicals from plastics to the environment and to wildlife.

PubMed

Teuten, Emma L; Saquing, Jovita M; Knappe, Detlef R U; Barlaz, Morton A; Jonsson, Susanne; Björn, Annika; Rowland, Steven J; Thompson, Richard C; Galloway, Tamara S; Yamashita, Rei; Ochi, Daisuke; Watanuki, Yutaka; Moore, Charles; Viet, Pham Hung; Tana, Touch Seang; Prudente, Maricar; Boonyatumanond, Ruchaya; Zakaria, Mohamad P; Akkhavong, Kongsap; Ogata, Yuko; Hirai, Hisashi; Iwasa, Satoru; Mizukawa, Kaoruko; Hagino, Yuki; Imamura, Ayako; Saha, Mahua; Takada, Hideshige

2009-07-27

Plastics debris in the marine environment, including resin pellets, fragments and microscopic plastic fragments, contain organic contaminants, including polychlorinated biphenyls (PCBs), polycyclic aromatic hydrocarbons, petroleum hydrocarbons, organochlorine pesticides (2,2'-bis(p-chlorophenyl)-1,1,1-trichloroethane, hexachlorinated hexanes), polybrominated diphenylethers, alkylphenols and bisphenol A, at concentrations from sub ng g(-1) to microg g(-1). Some of these compounds are added during plastics manufacture, while others adsorb from the surrounding seawater. Concentrations of hydrophobic contaminants adsorbed on plastics showed distinct spatial variations reflecting global pollution patterns. Model calculations and experimental observations consistently show that polyethylene accumulates more organic contaminants than other plastics such as polypropylene and polyvinyl chloride. Both a mathematical model using equilibrium partitioning and experimental data have demonstrated the transfer of contaminants from plastic to organisms. A feeding experiment indicated that PCBs could transfer from contaminated plastics to streaked shearwater chicks. Plasticizers, other plastics additives and constitutional monomers also present potential threats in terrestrial environments because they can leach from waste disposal sites into groundwater and/or surface waters. Leaching and degradation of plasticizers and polymers are complex phenomena dependent on environmental conditions in the landfill and the chemical properties of each additive. Bisphenol A concentrations in leachates from municipal waste disposal sites in tropical Asia ranged from sub microg l(-1) to mg l(-1) and were correlated with the level of economic development.

Transport and release of chemicals from plastics to the environment and to wildlife

PubMed Central

Teuten, Emma L.; Saquing, Jovita M.; Knappe, Detlef R. U.; Barlaz, Morton A.; Jonsson, Susanne; Björn, Annika; Rowland, Steven J.; Thompson, Richard C.; Galloway, Tamara S.; Yamashita, Rei; Ochi, Daisuke; Watanuki, Yutaka; Moore, Charles; Viet, Pham Hung; Tana, Touch Seang; Prudente, Maricar; Boonyatumanond, Ruchaya; Zakaria, Mohamad P.; Akkhavong, Kongsap; Ogata, Yuko; Hirai, Hisashi; Iwasa, Satoru; Mizukawa, Kaoruko; Hagino, Yuki; Imamura, Ayako; Saha, Mahua; Takada, Hideshige

2009-01-01

Plastics debris in the marine environment, including resin pellets, fragments and microscopic plastic fragments, contain organic contaminants, including polychlorinated biphenyls (PCBs), polycyclic aromatic hydrocarbons, petroleum hydrocarbons, organochlorine pesticides (2,2′-bis(p-chlorophenyl)-1,1,1-trichloroethane, hexachlorinated hexanes), polybrominated diphenylethers, alkylphenols and bisphenol A, at concentrations from sub ng g–1 to µg g–1. Some of these compounds are added during plastics manufacture, while others adsorb from the surrounding seawater. Concentrations of hydrophobic contaminants adsorbed on plastics showed distinct spatial variations reflecting global pollution patterns. Model calculations and experimental observations consistently show that polyethylene accumulates more organic contaminants than other plastics such as polypropylene and polyvinyl chloride. Both a mathematical model using equilibrium partitioning and experimental data have demonstrated the transfer of contaminants from plastic to organisms. A feeding experiment indicated that PCBs could transfer from contaminated plastics to streaked shearwater chicks. Plasticizers, other plastics additives and constitutional monomers also present potential threats in terrestrial environments because they can leach from waste disposal sites into groundwater and/or surface waters. Leaching and degradation of plasticizers and polymers are complex phenomena dependent on environmental conditions in the landfill and the chemical properties of each additive. Bisphenol A concentrations in leachates from municipal waste disposal sites in tropical Asia ranged from sub µg l–1 to mg l–1 and were correlated with the level of economic development. PMID:19528054

The Thermal and Microstructural Effect of Plasticizing HMX-Nitrocellulose Composites

DOE PAGES

Yeager, John David; Watkins, Erik Benjamin; Duque, Amanda Lynn; ...

2017-03-15

Thermal ignition via self-heating (cook-off) of cyclotetramethylene-tetranitramine (HMX)-containing plastic-bonded explosives (PBXs) is driven by the β → δ phase transition in the HMX, which is affected if not dominated by microstructure. Here, we studied the HMX-binder interface and phase transition for several variations of PBX 9404 (HMX with plasticized nitrocellulose [NC] binder). Neutron reflectometry was used to examine the interface under several conditions—pristine, after aging, and after thermal treatment. The initial interfacial structure depended on the plasticizer, but the interface homogenized over time. Thermal and optical analyses showed that all formulated materials had higher transition temperatures than neat HMX. Thismore » effect increased with NC content.« less

MAGNETIC MEASUREMENT OF THE PLASTIC STRESS-STRAIN CURVE OF MULTICRYSTALLINE NICKEL (in German)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schwink, Ch.; Zankl, G.

1962-01-01

Ballistic measurements of the coercive force H/sub c/ and the initial permeability mu /sub alpha / were made on nlckel wires, and their dependence on plastic tensile deformation was followed. The results are shown graphically. H/ sub c/ and 1/ mu /sub alpha / start to increase at a given tensile stress with the introduction of plastic expansion and increases almost linearly with the tensile stress applied. At a tensile stress of 7.2 plus or minus 0.5 kp/mm/sup 2/ both curves have noticable bends. The bend point is related by a special process to the plastic deformation of the multicrystallinemore » material. (J.S.R.)« less

Phenotypic plasticity and longevity in plants and animals: cause and effect?

PubMed

Borges, Renee M

2009-10-01

Immobile plants and immobile modular animals outlive unitary animals. This paper discusses competing but not necessarily mutually exclusive theories to explain this extreme longevity, especially from the perspective of phenotypic plasticity. Stem cell immortality, vascular autonomy, and epicormic branching are some important features of the phenotypic plasticity of plants that contribute to their longevity. Monocarpy versus polycarpy can also influence the kind of senescent processes experienced by plants. How density-dependent phenomena affecting the establishment of juveniles in these immobile organisms can influence the evolution of senescence, and consequently longevity, is reviewed and discussed. Whether climate change scenarios will favour long-lived or short-lived organisms, with their attendant levels of plasticity, is also presented.

The Thermal and Microstructural Effect of Plasticizing HMX-Nitrocellulose Composites

NASA Astrophysics Data System (ADS)

Yeager, John D.; Watkins, Erik B.; Higginbotham Duque, Amanda L.; Majewski, Jaroslaw

2018-01-01

Thermal ignition via self-heating (cook-off) of cyclotetramethylene-tetranitramine (HMX)-containing plastic-bonded explosives (PBXs) is driven by the β → δ phase transition in the HMX, which is affected if not dominated by microstructure. Here, the HMX-binder interface and phase transition were studied for several variations of PBX 9404 (HMX with plasticized nitrocellulose [NC] binder). Neutron reflectometry was used to examine the interface under several conditions-pristine, after aging, and after thermal treatment. The initial interfacial structure depended on the plasticizer, but the interface homogenized over time. Thermal and optical analyses showed that all formulated materials had higher transition temperatures than neat HMX. This effect increased with NC content.

Correlational selection on personality and social plasticity: morphology and social context determine behavioural effects on mating success.

PubMed

Montiglio, Pierre-Olivier; Wey, Tina W; Chang, Ann T; Fogarty, Sean; Sih, Andrew

2017-03-01

Despite a central line of research aimed at quantifying relationships between mating success and sexually dimorphic traits (e.g., ornaments), individual variation in sexually selected traits often explains only a modest portion of the variation in mating success. Another line of research suggests that a significant portion of the variation in mating success observed in animal populations could be explained by correlational selection, where the fitness advantage of a given trait depends on other components of an individual's phenotype and/or its environment. We tested the hypothesis that interactions between multiple traits within an individual (phenotype dependence) or between an individual's phenotype and its social environment (context dependence) can select for individual differences in behaviour (i.e., personality) and social plasticity. To quantify the importance of phenotype- and context-dependent selection on mating success, we repeatedly measured the behaviour, social environment and mating success of about 300 male stream water striders, Aquarius remigis. Rather than explaining individual differences in long-term mating success, we instead quantified how the combination of a male's phenotype interacted with the immediate social context to explain variation in hour-by-hour mating decisions. We suggest that this analysis captures more of the mechanisms leading to differences in mating success. Males differed consistently in activity, aggressiveness and social plasticity. The mating advantage of these behavioural traits depended on male morphology and varied with the number of rival males in the pool, suggesting mechanisms selecting for consistent differences in behaviour and social plasticity. Accounting for phenotype and context dependence improved the amount of variation in male mating success we explained statistically by 30-274%. Our analysis of the determinants of male mating success provides important insights into the evolutionary forces that shape phenotypic variation. In particular, our results suggest that sexual selection is likely to favour individual differences in behaviour, social plasticity (i.e., individuals adjusting their behaviour), niche preference (i.e., individuals dispersing to particular social conditions) or social niche construction (i.e., individuals modifying the social environment). The true effect of sexual traits can only be understood in interaction with the individual's phenotype and environment. © 2016 The Authors. Journal of Animal Ecology © 2016 British Ecological Society.

NGL-2 Deletion Leads to Autistic-like Behaviors Responsive to NMDAR Modulation.

PubMed

Um, Seung Min; Ha, Seungmin; Lee, Hyejin; Kim, Jihye; Kim, Kyungdeok; Shin, Wangyong; Cho, Yi Sul; Roh, Junyeop Daniel; Kang, Jaeseung; Yoo, Taesun; Noh, Young Woo; Choi, Yeonsoo; Bae, Yong Chul; Kim, Eunjoon

2018-06-26

Netrin-G ligand 2 (NGL-2)/LRRC4, implicated in autism spectrum disorders and schizophrenia, is a leucine-rich repeat-containing postsynaptic adhesion molecule that interacts intracellularly with the excitatory postsynaptic scaffolding protein PSD-95 and trans-synaptically with the presynaptic adhesion molecule netrin-G2. Functionally, NGL-2 regulates excitatory synapse development and synaptic transmission. However, whether it regulates synaptic plasticity and disease-related specific behaviors is not known. Here, we report that mice lacking NGL-2 (Lrrc4 -/- mice) show suppressed N-Methyl-D-aspartate receptor (NMDAR)-dependent synaptic plasticity in the hippocampus. NGL-2 associates with NMDARs through both PSD-95-dependent and -independent mechanisms. Moreover, Lrrc4 -/- mice display mild social interaction deficits and repetitive behaviors that are rapidly improved by pharmacological NMDAR activation. These results suggest that NGL-2 promotes synaptic stabilization of NMDARs, regulates NMDAR-dependent synaptic plasticity, and prevents autistic-like behaviors from developing in mice, supporting the hypothesis that NMDAR dysfunction contributes to autism spectrum disorders. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

Homeostatic Presynaptic Plasticity Is Specifically Regulated by P/Q-type Ca2+ Channels at Mammalian Hippocampal Synapses.

PubMed

Jeans, Alexander F; van Heusden, Fran C; Al-Mubarak, Bashayer; Padamsey, Zahid; Emptage, Nigel J

2017-10-10

Voltage-dependent Ca 2+ channels (VGCC) represent the principal source of Ca 2+ ions driving evoked neurotransmitter release at presynaptic boutons. In mammals, presynaptic Ca 2+ influx is mediated mainly via P/Q-type and N-type VGCC, which differ in their properties. Changes in their relative contributions tune neurotransmission both during development and in Hebbian plasticity. However, whether this represents a functional motif also present in other forms of activity-dependent regulation is unknown. Here, we study the role of VGCC in homeostatic plasticity (HSP) in mammalian hippocampal neurons using optical techniques. We find that changes in evoked Ca 2+ currents specifically through P/Q-type, but not N-type, VGCC mediate bidirectional homeostatic regulation of both neurotransmitter release efficacy and the size of the major synaptic vesicle pools. Selective dependence of HSP on P/Q-type VGCC in mammalian terminals has important implications for phenotypes associated with P/Q-type channelopathies, including migraine and epilepsy. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

Beneficial effects of benzodiazepine diazepam on chronic stress-induced impairment of hippocampal structural plasticity and depression-like behavior in mice.

PubMed

Zhao, Yunan; Wang, Zhongli; Dai, Jianguo; Chen, Lin; Huang, Yufang; Zhan, Zhen

2012-03-17

Whether benzodiazepines (BZDs) have beneficial effects on the progress of chronic stress-induced impairment of hippocampal structural plasticity and major depression is uncertain. The present study designed four preclinical experiments to determine the effects of BZDs using chronic unpredictable stress model. In Experiment 1, several time course studies on behavior and hippocampus response to stress were conducted using the forced swim and tail suspension tests (FST and TST) as well as hippocampal structural plasticity markers. Chronic stress induced depression-like behavior in the FST and TST as well as decreased hippocampal structural plasticity that returned to normal within 3 wk. In Experiment 2, mice received p.o. administration of three diazepam dosages prior to each variate stress session for 4 wk. This treatment significantly antagonized the elevation of stress-induced corticosterone levels. Only low- (0.5mg/kg) and medium-dose (1mg/kg) diazepam blocked the detrimental effects of chronic stress. In Experiment 3, after 7 wk of stress sessions, daily p.o. diazepam administration during 1 wk recovery phase dose-dependently accelerated the recovery of stressed mice. In Experiment 4, 1 wk diazepam administration to control mice enhanced significantly hippocampal structural plasticity and induced an antidepressant-like behavioral effect, whereas 4 wk diazepam administration produced opposite effects. Hence, diazepam can slow the progress of chronic stress-induced detrimental consequences by normalizing glucocorticoid hormones. Considering the adverse effect of long-term diazepam administration on hippocampal plasticity, the preventive effects of diazepam may depend on the proper dose. Short-term diazepam treatment enhances hippocampal structural plasticity and is beneficial to recovery following chronic stress. Copyright © 2011 Elsevier B.V. All rights reserved.

Size effects in olivine control strength in low-temperature plasticity regime

NASA Astrophysics Data System (ADS)

Kumamoto, K. M.; Thom, C.; Wallis, D.; Hansen, L. N.; Armstrong, D. E. J.; Goldsby, D. L.; Warren, J. M.; Wilkinson, A. J.

2017-12-01

The strength of the lithospheric mantle during deformation by low-temperature plasticity controls a range of geological phenomena, including lithospheric-scale strain localization, the evolution of friction on deep seismogenic faults, and the flexure of tectonic plates. However, constraints on the strength of olivine in this deformation regime are difficult to obtain from conventional rock-deformation experiments, and previous results vary considerably. We demonstrate via nanoindentation that the strength of olivine in the low-temperature plasticity regime is dependent on the length-scale of the test, with experiments on smaller volumes of material exhibiting larger yield stresses. This "size effect" has previously been explained in engineering materials as a result of the role of strain gradients and associated geometrically necessary dislocations in modifying plastic behavior. The Hall-Petch effect, in which a material with a small grain size exhibits a higher strength than one with a large grain size, is thought to arise from the same mechanism. The presence of a size effect resolves discrepancies among previous experimental measurements of olivine, which were either conducted using indentation methods or were conducted on polycrystalline samples with small grain sizes. An analysis of different low-temperature plasticity flow laws extrapolated to room temperature reveals a power-law relationship between length-scale (grain size for polycrystalline deformation and contact radius for indentation tests) and yield strength. This suggests that data from samples with large inherent length scales best represent the plastic strength of the coarse-grained lithospheric mantle. Additionally, the plastic deformation of nanometer- to micrometer-sized asperities on fault surfaces may control the evolution of fault roughness due to their size-dependent strength.

Restoring auditory cortex plasticity in adult mice by restricting thalamic adenosine signaling

DOE PAGES

Blundon, Jay A.; Roy, Noah C.; Teubner, Brett J. W.; ...

2017-06-30

Circuits in the auditory cortex are highly susceptible to acoustic influences during an early postnatal critical period. The auditory cortex selectively expands neural representations of enriched acoustic stimuli, a process important for human language acquisition. Adults lack this plasticity. We show in the murine auditory cortex that juvenile plasticity can be reestablished in adulthood if acoustic stimuli are paired with disruption of ecto-5'-nucleotidase–dependent adenosine production or A1–adenosine receptor signaling in the auditory thalamus. This plasticity occurs at the level of cortical maps and individual neurons in the auditory cortex of awake adult mice and is associated with long-term improvement ofmore » tone-discrimination abilities. We determined that, in adult mice, disrupting adenosine signaling in the thalamus rejuvenates plasticity in the auditory cortex and improves auditory perception.« less

Restoring auditory cortex plasticity in adult mice by restricting thalamic adenosine signaling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Blundon, Jay A.; Roy, Noah C.; Teubner, Brett J. W.

Circuits in the auditory cortex are highly susceptible to acoustic influences during an early postnatal critical period. The auditory cortex selectively expands neural representations of enriched acoustic stimuli, a process important for human language acquisition. Adults lack this plasticity. We show in the murine auditory cortex that juvenile plasticity can be reestablished in adulthood if acoustic stimuli are paired with disruption of ecto-5'-nucleotidase–dependent adenosine production or A1–adenosine receptor signaling in the auditory thalamus. This plasticity occurs at the level of cortical maps and individual neurons in the auditory cortex of awake adult mice and is associated with long-term improvement ofmore » tone-discrimination abilities. We determined that, in adult mice, disrupting adenosine signaling in the thalamus rejuvenates plasticity in the auditory cortex and improves auditory perception.« less

Characterizing energy dependence and count rate performance of a dual scintillator fiber-optic detector for computed tomography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hoerner, Matthew R., E-mail: mrh5038@ufl.edu; Stepusin, Elliott J.; Hyer, Daniel E.

Purpose: Kilovoltage (kV) x-rays pose a significant challenge for radiation dosimetry. In the kV energy range, even small differences in material composition can result in significant variations in the absorbed energy between soft tissue and the detector. In addition, the use of electronic systems in light detection has demonstrated measurement losses at high photon fluence rates incident to the detector. This study investigated the feasibility of using a novel dual scintillator detector and whether its response to changes in beam energy from scatter and hardening is readily quantified. The detector incorporates a tissue-equivalent plastic scintillator and a gadolinium oxysulfide scintillator,more » which has a higher sensitivity to scatter x-rays. Methods: The detector was constructed by coupling two scintillators: (1) small cylindrical plastic scintillator, 500 μm in diameter and 2 mm in length, and (2) 100 micron sheet of gadolinium oxysulfide 500 μm in diameter, each to a 2 m long optical fiber, which acts as a light guide to transmit scintillation photons from the sensitive element to a photomultiplier tube. Count rate linearity data were obtained from a wide range of exposure rates delivered from a radiological x-ray tube by adjusting the tube current. The data were fitted to a nonparalyzable dead time model to characterize the time response. The true counting rate was related to the reference free air dose air rate measured with a 0.6 cm{sup 3} Radcal{sup ®} thimble chamber as described in AAPM Report No. 111. Secondary electron and photon spectra were evaluated using Monte Carlo techniques to analyze ionization quenching and photon energy-absorption characteristics from free-in-air and in phantom measurements. The depth/energy dependence of the detector was characterized using a computed tomography dose index QA phantom consisting of nested adult head and body segments. The phantom provided up to 32 cm of acrylic with a compatible 0.6 cm{sup 3} calibrated ionization chamber to measure the reference air kerma. Results: Each detector exhibited counting losses of 5% when irradiated at a dose rate of 26.3 mGy/s (Gadolinium) and 324.3 mGy/s (plastic). The dead time of the gadolinium oxysulfide detector was determined to be 48 ns, while the dead time of the plastic scintillating detector was unable to accurately be calculated due to poor counting statistics from low detected count rates. Noticeable depth/energy dependence was observed for the plastic scintillator for depths greater than 16 cm of acrylic that was not present for measurements using the gadolinium oxysulfide scintillator, leading us to believe that quenching may play a larger role in the depth dependence of the plastic scintillator than the incident x-ray energy spectrum. When properly corrected for dead time effects, the energy response of the gadolinium oxysulfide scintillator is consistent with the plastic scintillator. Using the integrated dual detector method was superior to each detector individually as the depth-dependent measure of dose was correctable to less than 8% between 100 and 135 kV. Conclusions: The dual scintillator fiber-optic detector accommodates a methodology for energy dependent corrections of the plastic scintillator, improving the overall accuracy of the dosimeter across the range of diagnostic energies.« less

Characterizing energy dependence and count rate performance of a dual scintillator fiber-optic detector for computed tomography.

PubMed

Hoerner, Matthew R; Stepusin, Elliott J; Hyer, Daniel E; Hintenlang, David E

2015-03-01

Kilovoltage (kV) x-rays pose a significant challenge for radiation dosimetry. In the kV energy range, even small differences in material composition can result in significant variations in the absorbed energy between soft tissue and the detector. In addition, the use of electronic systems in light detection has demonstrated measurement losses at high photon fluence rates incident to the detector. This study investigated the feasibility of using a novel dual scintillator detector and whether its response to changes in beam energy from scatter and hardening is readily quantified. The detector incorporates a tissue-equivalent plastic scintillator and a gadolinium oxysulfide scintillator, which has a higher sensitivity to scatter x-rays. The detector was constructed by coupling two scintillators: (1) small cylindrical plastic scintillator, 500 μm in diameter and 2 mm in length, and (2) 100 micron sheet of gadolinium oxysulfide 500 μm in diameter, each to a 2 m long optical fiber, which acts as a light guide to transmit scintillation photons from the sensitive element to a photomultiplier tube. Count rate linearity data were obtained from a wide range of exposure rates delivered from a radiological x-ray tube by adjusting the tube current. The data were fitted to a nonparalyzable dead time model to characterize the time response. The true counting rate was related to the reference free air dose air rate measured with a 0.6 cm(3) Radcal(®) thimble chamber as described in AAPM Report No. 111. Secondary electron and photon spectra were evaluated using Monte Carlo techniques to analyze ionization quenching and photon energy-absorption characteristics from free-in-air and in phantom measurements. The depth/energy dependence of the detector was characterized using a computed tomography dose index QA phantom consisting of nested adult head and body segments. The phantom provided up to 32 cm of acrylic with a compatible 0.6 cm(3) calibrated ionization chamber to measure the reference air kerma. Each detector exhibited counting losses of 5% when irradiated at a dose rate of 26.3 mGy/s (Gadolinium) and 324.3 mGy/s (plastic). The dead time of the gadolinium oxysulfide detector was determined to be 48 ns, while the dead time of the plastic scintillating detector was unable to accurately be calculated due to poor counting statistics from low detected count rates. Noticeable depth/energy dependence was observed for the plastic scintillator for depths greater than 16 cm of acrylic that was not present for measurements using the gadolinium oxysulfide scintillator, leading us to believe that quenching may play a larger role in the depth dependence of the plastic scintillator than the incident x-ray energy spectrum. When properly corrected for dead time effects, the energy response of the gadolinium oxysulfide scintillator is consistent with the plastic scintillator. Using the integrated dual detector method was superior to each detector individually as the depth-dependent measure of dose was correctable to less than 8% between 100 and 135 kV. The dual scintillator fiber-optic detector accommodates a methodology for energy dependent corrections of the plastic scintillator, improving the overall accuracy of the dosimeter across the range of diagnostic energies.

All about running: synaptic plasticity, growth factors and adult hippocampal neurogenesis.

PubMed

Vivar, Carmen; Potter, Michelle C; van Praag, Henriette

2013-01-01

Accumulating evidence from animal and human research shows exercise benefits learning and memory, which may reduce the risk of neurodegenerative diseases, and could delay age-related cognitive decline. Exercise-induced improvements in learning and memory are correlated with enhanced adult hippocampal neurogenesis and increased activity-dependent synaptic plasticity. In this present chapter we will highlight the effects of physical activity on cognition in rodents, as well as on dentate gyrus (DG) neurogenesis, synaptic plasticity, spine density, neurotransmission and growth factors, in particular brain-derived nerve growth factor (BDNF).

TH-9 (a theophylline derivative) induces long-lasting enhancement in excitatory synaptic transmission in the rat hippocampus that is occluded by frequency-dependent plasticity in vitro.

PubMed

Nashawi, H; Bartl, T; Bartl, P; Novotny, L; Oriowo, M A; Kombian, S B

2012-09-18

Dementia, especially Alzheimer's disease, is a rapidly increasing medical condition that presents with enormous challenge for treatment. It is characterized by impairment in memory and cognitive function often accompanied by changes in synaptic transmission and plasticity in relevant brain regions such as the hippocampus. We recently synthesized TH-9, a conjugate racetam-methylxanthine compound and tested if it had potential for enhancing synaptic function and possibly, plasticity, by examining its effect on hippocampal fast excitatory synaptic transmission and plasticity. Field excitatory postsynaptic potentials (fEPSPs) were recorded in the CA1 hippocampal area of naïve juvenile male Sprague-Dawley rats using conventional electrophysiological recording techniques. TH-9 caused a concentration-dependent, long-lasting enhancement in fEPSPs. This effect was blocked by adenosine A1, acetylcholine (muscarinic and nicotinic) and glutamate (N-methyl-d-aspartate) receptor antagonists but not by a γ-aminobutyric acid receptor type B (GABA(B)) receptor antagonist. The TH-9 effect was also blocked by enhancing intracellular cyclic adenosine monophosphate and inhibiting protein kinase A. Pretreatment with TH-9 did not prevent the induction of long-term potentiation (LTP) or long-term depression (LTD). Conversely, induction of LTP or LTD completely occluded the ability of TH-9 to enhance fEPSPs. Thus, TH-9 utilizes cholinergic and adenosinergic mechanisms to cause long-lasting enhancement in fEPSPs which were occluded by LTP and LTD. TH-9 may therefore employ similar or convergent mechanisms with frequency-dependent synaptic plasticities to produce the observed long-lasting enhancement in synaptic transmission and may thus, have potential for use in improving memory. Copyright © 2012 IBRO. Published by Elsevier Ltd. All rights reserved.

Cell type dependence and variability in the short-term plasticity of EPSCs in identified mouse hippocampal interneurones

PubMed Central

Losonczy, Attila; Zhang, Limei; Shigemoto, Ryuichi; Somogyi, Peter; Nusser, Zoltan

2002-01-01

Synapses exhibit different short-term plasticity patterns and this behaviour influences information processing in neuronal networks. We tested how the short-term plasticity of excitatory postsynaptic currents (EPSCs) depends on the postsynaptic cell type, identified by axonal arborizations and molecular markers in the hippocampal CA1 area. Three distinct types of short-term synaptic behaviour (facilitating, depressing and combined facilitating–depressing) were defined by fitting a dynamic neurotransmission model to the data. Approximately 75 % of the oriens-lacunosum-moleculare (O-LM) interneurones received facilitating EPSCs, but in three of 12 O-LM cells EPSCs also showed significant depression. Over 90 % of the O-LM cells were immunopositive for somatostatin and mGluR1α and all tested cells were decorated by strongly mGluR7a positive axon terminals. Responses in eight of 12 basket cells were described well with a model involving only depression, but the other cells displayed combined facilitating–depressing EPSCs. No apparent difference was found between the plasticity of EPSCs in cholecystokinin- or parvalbumin-containing basket cells. In oriens-bistratified cells (O-Bi), two of nine cells showed facilitating EPSCs, another two depressing, and the remaining five cells combined facilitating–depressing EPSCs. Seven of 10 cells tested for somatostatin were immunopositive, but mGluR1α was detectable only in two of 11 tested cells. Furthermore, most O-Bi cells projected to the CA3 area and the subiculum, as well as outside the hippocampal formation. Postsynaptic responses to action potentials recorded in vivo from a CA1 place cell were modelled, and revealed great differences between and within cell types. Our results demonstrate that the short-term plasticity of EPSCs is cell type dependent, but with significant heterogeneity within all three interneurone populations. PMID:12096061

Origin of the spike-timing-dependent plasticity rule

NASA Astrophysics Data System (ADS)

Cho, Myoung Won; Choi, M. Y.

2016-08-01

A biological synapse changes its efficacy depending on the difference between pre- and post-synaptic spike timings. Formulating spike-timing-dependent interactions in terms of the path integral, we establish a neural-network model, which makes it possible to predict relevant quantities rigorously by means of standard methods in statistical mechanics and field theory. In particular, the biological synaptic plasticity rule is shown to emerge as the optimal form for minimizing the free energy. It is further revealed that maximization of the entropy of neural activities gives rise to the competitive behavior of biological learning. This demonstrates that statistical mechanics helps to understand rigorously key characteristic behaviors of a neural network, thus providing the possibility of physics serving as a useful and relevant framework for probing life.

High temperature low-cycle fatigue mechanisms in single crystals of nickel-based superalloy Mar-M 200

NASA Technical Reports Server (NTRS)

Milligan, W. W.; Jayaraman, N.

1984-01-01

Twenty three high temperature low-cycle fatigue tests were conducted on single crystals of the nickel-based superalloy Mar-M 200. Tests were conducted at 760 and 870 C. SEM fractography and transmission electron microscopy were used to determine mechanisms responsible for the observed orientation dependent fatigue behavior. It has been concluded that the plastic characteristics of the alloy lead to orientation-dependent strain hardening and fatigue lives at 760 C. At 870 C, the elastic characteristics of the alloy dominated the behavior, even though the plastic strain ranges were about the same as they were at 760 C. This led to orientation-dependent fatigue lives, but the trends were not the same as they were at 760 C.

In utero exposure to di(n)butyl phthalate reduces testicular testosterone and testis size in a dose-dependent manner in Harlan Sprague Dawley fetal rats

EPA Science Inventory

Phthalate esters are widely used to impart flexibility to plastics (e.g. plastic medical devices and children’s toys) as well as other uses in health and beauty products and some pharmaceuticals. Certain phthalate esters cause reproductive malformations and decrease androgen-dep...

Managing malignant biliary obstruction in pancreas cancer: Choosing the appropriate strategy

PubMed Central

Boulay, Brian R; Parepally, Mayur

2014-01-01

Most patients with pancreatic cancer develop malignant biliary obstruction. Treatment of obstruction is generally indicated to relieve symptoms and improve morbidity and mortality. First-line therapy consists of endoscopic biliary stent placement. Recent data comparing plastic stents to self-expanding metallic stents (SEMS) has shown improved patency with SEMS. The decision of whether to treat obstruction and the means for doing so depends on the clinical scenario. For patients with resectable disease, preoperative biliary decompression is only indicated when surgery will be delayed or complications of jaundice exist. For patients with locally advanced disease, self-expanding metal stents are superior to plastic stents for long-term patency. For patients with advanced disease, the choice of metallic or plastic stent depends on life expectancy. When endoscopic stent placement fails, percutaneous or surgical treatments are appropriate. Endoscopic therapy or surgical approach can be used to treat concomitant duodenal and biliary obstruction. PMID:25071329

Oxytocin mediates early experience-dependent cross-modal plasticity in the sensory cortices.

PubMed

Zheng, Jing-Jing; Li, Shu-Jing; Zhang, Xiao-Di; Miao, Wan-Ying; Zhang, Dinghong; Yao, Haishan; Yu, Xiang

2014-03-01

Sensory experience is critical to development and plasticity of neural circuits. Here we report a new form of plasticity in neonatal mice, where early sensory experience cross-modally regulates development of all sensory cortices via oxytocin signaling. Unimodal sensory deprivation from birth through whisker deprivation or dark rearing reduced excitatory synaptic transmission in the correspondent sensory cortex and cross-modally in other sensory cortices. Sensory experience regulated synthesis and secretion of the neuropeptide oxytocin as well as its level in the cortex. Both in vivo oxytocin injection and increased sensory experience elevated excitatory synaptic transmission in multiple sensory cortices and significantly rescued the effects of sensory deprivation. Together, these results identify a new function for oxytocin in promoting cross-modal, experience-dependent cortical development. This link between sensory experience and oxytocin is particularly relevant to autism, where hypersensitivity or hyposensitivity to sensory inputs is prevalent and oxytocin is a hotly debated potential therapy.

Regularized finite element modeling of progressive failure in soils within nonlocal softening plasticity

NASA Astrophysics Data System (ADS)

Huang, Maosong; Qu, Xie; Lü, Xilin

2017-11-01

By solving a nonlinear complementarity problem for the consistency condition, an improved implicit stress return iterative algorithm for a generalized over-nonlocal strain softening plasticity was proposed, and the consistent tangent matrix was obtained. The proposed algorithm was embodied into existing finite element codes, and it enables the nonlocal regularization of ill-posed boundary value problem caused by the pressure independent and dependent strain softening plasticity. The algorithm was verified by the numerical modeling of strain localization in a plane strain compression test. The results showed that a fast convergence can be achieved and the mesh-dependency caused by strain softening can be effectively eliminated. The influences of hardening modulus and material characteristic length on the simulation were obtained. The proposed algorithm was further used in the simulations of the bearing capacity of a strip footing; the results are mesh-independent, and the progressive failure process of the soil was well captured.

Matrix metalloproteinase 9 (MMP-9) is indispensable for long term potentiation in the central and basal but not in the lateral nucleus of the amygdala.

PubMed

Gorkiewicz, Tomasz; Balcerzyk, Marcin; Kaczmarek, Leszek; Knapska, Ewelina

2015-01-01

It has been shown that matrix metalloproteinase 9 (MMP-9) is required for synaptic plasticity, learning and memory. In particular, MMP-9 involvement in long-term potentiation (LTP, the model of synaptic plasticity) in the hippocampus and prefrontal cortex has previously been demonstrated. Recent data suggest the role of MMP-9 in amygdala-dependent learning and memory. Nothing is known, however, about its physiological correlates in the specific pathways in the amygdala. In the present study we show that LTP in the basal and central but not lateral amygdala (LA) is affected by MMP-9 knock-out. The MMP-9 dependency of LTP was confirmed in brain slices treated with a specific MMP-9 inhibitor. The results suggest that MMP-9 plays different roles in synaptic plasticity in different nuclei of the amygdala.

Non-adaptive plasticity potentiates rapid adaptive evolution of gene expression in nature.

PubMed

Ghalambor, Cameron K; Hoke, Kim L; Ruell, Emily W; Fischer, Eva K; Reznick, David N; Hughes, Kimberly A

2015-09-17

Phenotypic plasticity is the capacity for an individual genotype to produce different phenotypes in response to environmental variation. Most traits are plastic, but the degree to which plasticity is adaptive or non-adaptive depends on whether environmentally induced phenotypes are closer or further away from the local optimum. Existing theories make conflicting predictions about whether plasticity constrains or facilitates adaptive evolution. Debate persists because few empirical studies have tested the relationship between initial plasticity and subsequent adaptive evolution in natural populations. Here we show that the direction of plasticity in gene expression is generally opposite to the direction of adaptive evolution. We experimentally transplanted Trinidadian guppies (Poecilia reticulata) adapted to living with cichlid predators to cichlid-free streams, and tested for evolutionary divergence in brain gene expression patterns after three to four generations. We find 135 transcripts that evolved parallel changes in expression within the replicated introduction populations. These changes are in the same direction exhibited in a native cichlid-free population, suggesting rapid adaptive evolution. We find 89% of these transcripts exhibited non-adaptive plastic changes in expression when the source population was reared in the absence of predators, as they are in the opposite direction to the evolved changes. By contrast, the remaining transcripts exhibiting adaptive plasticity show reduced population divergence. Furthermore, the most plastic transcripts in the source population evolved reduced plasticity in the introduction populations, suggesting strong selection against non-adaptive plasticity. These results support models predicting that adaptive plasticity constrains evolution, whereas non-adaptive plasticity potentiates evolution by increasing the strength of directional selection. The role of non-adaptive plasticity in evolution has received relatively little attention; however, our results suggest that it may be an important mechanism that predicts evolutionary responses to new environments.

Impacts of changing ocean circulation on the distribution of marine microplastic litter.

PubMed

Welden, Natalie Ac; Lusher, Amy L

2017-05-01

Marine plastic pollution is currently a major scientific focus, with attention paid to its distribution and impacts within ecosystems. With recent estimates indicating that the mass of plastic released to the marine environment may reach 250 million metric tons by 2025, the effects of plastic on our oceans are set to increase. Distribution of microplastics, those plastics measuring less than 5 mm, are of increasing concern because they represent an increasing proportion of marine litter and are known to interact with species in a range of marine habitats. The local abundance of microplastic is dependent on a complex interaction between the scale of local plastic sources and prevailing environmental conditions; as a result, microplastic distribution is highly heterogeneous. Circulation models have been used to predict plastic distribution; however, current models do not consider future variation in circulation patterns and weather systems caused by a changing climate. In this study, we discuss the potential impacts of global climate change on the abundance and distribution of marine plastic pollution. Integr Environ Assess Manag 2017;13:483-487. © 2017 SETAC. © 2017 SETAC.

Hormone signaling and phenotypic plasticity in nematode development and evolution.

PubMed

Sommer, Ralf J; Ogawa, Akira

2011-09-27

Phenotypic plasticity refers to the ability of an organism to adopt different phenotypes depending on environmental conditions. In animals and plants, the progression of juvenile development and the formation of dormant stages are often associated with phenotypic plasticity, indicating the importance of phenotypic plasticity for life-history theory. Phenotypic plasticity has long been emphasized as a crucial principle in ecology and as facilitator of phenotypic evolution. In nematodes, several examples of phenotypic plasticity have been studied at the genetic and developmental level. In addition, the influence of different environmental factors has been investigated under laboratory conditions. These studies have provided detailed insight into the molecular basis of phenotypic plasticity and its ecological and evolutionary implications. Here, we review recent studies on the formation of dauer larvae in Caenorhabditis elegans, the evolution of nematode parasitism and the generation of a novel feeding trait in Pristionchus pacificus. These examples reveal a conserved and co-opted role of an endocrine signaling module involving the steroid hormone dafachronic acid. We will discuss how hormone signaling might facilitate life-history and morphological evolution. Copyright © 2011 Elsevier Ltd. All rights reserved.

Characterizing Brain Cortical Plasticity and Network Dynamics Across the Age-Span in Health and Disease with TMS-EEG and TMS-fMRI

PubMed Central

Pascual-Leone, Alvaro; Freitas, Catarina; Oberman, Lindsay; Horvath, Jared C.; Halko, Mark; Eldaief, Mark; Bashir, Shahid; Vernet, Marine; Shafi, Mouhshin; Westover, Brandon; Vahabzadeh-Hagh, Andrew M.; Rotenberg, Alexander

2012-01-01

Brain plasticity can be conceptualized as nature’s invention to overcome limitations of the genome and adapt to a rapidly changing environment. As such, plasticity is an intrinsic property of the brain across the life-span. However, mechanisms of plasticity may vary with age. The combination of transcranial magnetic stimulation (TMS) with electroencephalography (EEG) or functional magnetic resonance imaging (fMRI) enables clinicians and researchers to directly study local and network cortical plasticity, in humans in vivo, and characterize their changes across the age-span. Parallel, translational studies in animals can provide mechanistic insights. Here, we argue that, for each individual, the efficiency of neuronal plasticity declines throughout the age-span and may do so more or less prominently depending on variable ‘starting-points’ and different ‘slopes of change’ defined by genetic, biological, and environmental factors. Furthermore, aberrant, excessive, insufficient, or mistimed plasticity may represent the proximal pathogenic cause of neurodevelopmental and neurodegenerative disorders such as autism spectrum disorders or Alzheimer’s disease. PMID:21842407

Global research priorities to mitigate plastic pollution impacts on marine wildlife

USGS Publications Warehouse

Vegter, Amanda C.; Barletta, Mário; Beck, Cathy A.; Borrero, Jose C.; Burton, Harry; Campbell, Marnie L.; Costa, Monica F.; Eriksen, Marcus; Eriksson, Cecilia; Estrades, Andres; Gilardi, Kirsten V.; Hardesty, Britta D.; do Sul, Juliana A. Ivar; Lavers, Jennifer L.; Lazar, Bojan; Lebreton, Laurent; Nichols, Wallace J.; Ribic, Christine A.; Ryan, Peter G.; Schuyler, Qamar A.; Smith, Stephen D. A.; Takada, Hideshige; Townsend, Kathy A.; Wabnitz, Colette C. C.; Wilcox, Chris; Young, Lindsay C.; Hamann, Mark

2014-01-01

Marine wildlife faces a growing number of threats across the globe, and the survival of many species and populations will be dependent on conservation action. One threat in particular that has emerged over the last 4 decades is the pollution of oceanic and coastal habitats with plastic debris. The increased occurrence of plastics in marine ecosystems mirrors the increased prevalence of plastics in society, and reflects the high durability and persistence of plastics in the environment. In an effort to guide future research and assist mitigation approaches to marine conservation, we have generated a list of 16 priority research questions based on the expert opinions of 26 researchers from around the world, whose research expertise spans several disciplines, and covers each of the world’s oceans and the taxa most at risk from plastic pollution. This paper highlights a growing concern related to threats posed to marine wildlife from microplastics and fragmented debris, the need for data at scales relevant to management, and the urgent need to develop interdisciplinary research and management partnerships to limit the release of plastics into the environment and curb the future impacts of plastic pollution.

Focal Stroke in the Developing Rat Motor Cortex Induces Age- and Experience-Dependent Maladaptive Plasticity of Corticospinal System

PubMed Central

Gennaro, Mariangela; Mattiello, Alessandro; Mazziotti, Raffaele; Antonelli, Camilla; Gherardini, Lisa; Guzzetta, Andrea; Berardi, Nicoletta; Cioni, Giovanni; Pizzorusso, Tommaso

2017-01-01

Motor system development is characterized by an activity-dependent competition between ipsilateral and contralateral corticospinal tracts (CST). Clinical evidence suggests that age is crucial for developmental stroke outcome, with early lesions inducing a “maladaptive” strengthening of ipsilateral projections from the healthy hemisphere and worse motor impairment. Here, we investigated in developing rats the relation between lesion timing, motor outcome and CST remodeling pattern. We induced a focal ischemia into forelimb motor cortex (fM1) at two distinct pre-weaning ages: P14 and P21. We compared long-term motor outcome with changes in axonal sprouting of contralesional CST at red nucleus and spinal cord level using anterograde tracing. We found that P14 stroke caused a more severe long-term motor impairment than at P21, and induced a strong and aberrant contralesional CST sprouting onto denervated spinal cord and red nucleus. The mistargeted sprouting of CST, and the worse motor outcome of the P14 stroke rats were reversed by an early skilled motor training, underscoring the potential of early activity-dependent plasticity in modulating lesion outcome. Thus, changes in the mechanisms controlling CST plasticity occurring during the third postnatal week are associated with age-dependent regulation of the motor outcome after stroke. PMID:28706475

Focal Stroke in the Developing Rat Motor Cortex Induces Age- and Experience-Dependent Maladaptive Plasticity of Corticospinal System.

PubMed

Gennaro, Mariangela; Mattiello, Alessandro; Mazziotti, Raffaele; Antonelli, Camilla; Gherardini, Lisa; Guzzetta, Andrea; Berardi, Nicoletta; Cioni, Giovanni; Pizzorusso, Tommaso

2017-01-01

Motor system development is characterized by an activity-dependent competition between ipsilateral and contralateral corticospinal tracts (CST). Clinical evidence suggests that age is crucial for developmental stroke outcome, with early lesions inducing a "maladaptive" strengthening of ipsilateral projections from the healthy hemisphere and worse motor impairment. Here, we investigated in developing rats the relation between lesion timing, motor outcome and CST remodeling pattern. We induced a focal ischemia into forelimb motor cortex (fM1) at two distinct pre-weaning ages: P14 and P21. We compared long-term motor outcome with changes in axonal sprouting of contralesional CST at red nucleus and spinal cord level using anterograde tracing. We found that P14 stroke caused a more severe long-term motor impairment than at P21, and induced a strong and aberrant contralesional CST sprouting onto denervated spinal cord and red nucleus. The mistargeted sprouting of CST, and the worse motor outcome of the P14 stroke rats were reversed by an early skilled motor training, underscoring the potential of early activity-dependent plasticity in modulating lesion outcome. Thus, changes in the mechanisms controlling CST plasticity occurring during the third postnatal week are associated with age-dependent regulation of the motor outcome after stroke.

Combined effects of physiological condition and environmental attributes in determining call plasticity.

PubMed

Ziegler, Lucia; Arim, Matias; Bozinovic, Francisco

2018-05-07

Evidence is growing on the ability of anurans to make immediate call adjustments in response to the propagation properties of the environment. However, our understanding of such flexibility is typically based on dichotomous stimuli (i.e. presence/absence), while its condition-dependence has been little explored. We experimentally studied the ability of adjustment and its condition dependence of advertisement calls of Hypsiboas pulchellus in response to different levels of attenuation. Individuals modified most call parameters analyzed, although the direction of adjustments was contingent on individual identity, level of attenuation and trait category (i.e. spectral or temporal). Under low attenuation conditions males lengthened some call elements, partially supporting the hypothesis of plasticity oriented towards maintaining signal transmission, but this trend was not present in the high attenuation treatment. Also, under both attenuation treatments males gave higher frequency notes, as expected from an energy-saving response to changes in social environment or reducing attractiveness due to risk perception. Across treatments individuals in better condition tended to exhibit higher plasticity. These results indicate that call structure could depend on the integration of different cues such as habitat propagation characteristics, acoustic competition for females, and predation risk, while the ability to behave flexibly depends on current body reserves. Copyright © 2018 Elsevier B.V. All rights reserved.

Mechanical properties of thin-film materials evaluated from amplitude-dependent internal friction

NASA Astrophysics Data System (ADS)

Nishino, Yoichi

1999-09-01

A method is presented to evaluate the mechanical properties of thin-film materials from measurements of the amplitude-dependent internal friction. According to the constitutive equation, the internal friction in the film can be determined separately from measured damping of the film/substrate composite. The internal friction in aluminum films is dependent on the strain amplitude that is approximately two orders of magnitude higher than that for bulk aluminum. On the basis of the microplasticity theory, the amplitude-dependent internal friction in the film can be converted into the plastic strain as a function of effective stress on dislocation motion. The mechanical responses thus obtained for aluminum films show that the plastic strain of the order of 10-9 increases nonlinearly with increasing stress. These curves tend to shift to a higher stress with decreasing film thickness and also with decreasing temperature, both indicating a suppression of microplastic flow. The microflow stress at a constant level of the plastic strain varies inversely with the film thickness, provided the grain size is larger than the film thickness. The film thickness effect in the microplastic range can be well explained by the bowing of a dislocation segment whose ends are pinned at the film surface and at the film/substrate interface.

Focal adhesion kinase regulates neuronal growth, synaptic plasticity and hippocampus-dependent spatial learning and memory.

PubMed

Monje, Francisco J; Kim, Eun-Jung; Pollak, Daniela D; Cabatic, Maureen; Li, Lin; Baston, Arthur; Lubec, Gert

2012-01-01

The focal adhesion kinase (FAK) is a non-receptor tyrosine kinase abundantly expressed in the mammalian brain and highly enriched in neuronal growth cones. Inhibitory and facilitatory activities of FAK on neuronal growth have been reported and its role in neuritic outgrowth remains controversial. Unlike other tyrosine kinases, such as the neurotrophin receptors regulating neuronal growth and plasticity, the relevance of FAK for learning and memory in vivo has not been clearly defined yet. A comprehensive study aimed at determining the role of FAK in neuronal growth, neurotransmitter release and synaptic plasticity in hippocampal neurons and in hippocampus-dependent learning and memory was therefore undertaken using the mouse model. Gain- and loss-of-function experiments indicated that FAK is a critical regulator of hippocampal cell morphology. FAK mediated neurotrophin-induced neuritic outgrowth and FAK inhibition affected both miniature excitatory postsynaptic potentials and activity-dependent hippocampal long-term potentiation prompting us to explore the possible role of FAK in spatial learning and memory in vivo. Our data indicate that FAK has a growth-promoting effect, is importantly involved in the regulation of the synaptic function and mediates in vivo hippocampus-dependent spatial learning and memory. Copyright © 2011 S. Karger AG, Basel.

Spatiotemporal Computations of an Excitable and Plastic Brain: Neuronal Plasticity Leads to Noise-Robust and Noise-Constructive Computations

PubMed Central

Toutounji, Hazem; Pipa, Gordon

2014-01-01

It is a long-established fact that neuronal plasticity occupies the central role in generating neural function and computation. Nevertheless, no unifying account exists of how neurons in a recurrent cortical network learn to compute on temporally and spatially extended stimuli. However, these stimuli constitute the norm, rather than the exception, of the brain's input. Here, we introduce a geometric theory of learning spatiotemporal computations through neuronal plasticity. To that end, we rigorously formulate the problem of neural representations as a relation in space between stimulus-induced neural activity and the asymptotic dynamics of excitable cortical networks. Backed up by computer simulations and numerical analysis, we show that two canonical and widely spread forms of neuronal plasticity, that is, spike-timing-dependent synaptic plasticity and intrinsic plasticity, are both necessary for creating neural representations, such that these computations become realizable. Interestingly, the effects of these forms of plasticity on the emerging neural code relate to properties necessary for both combating and utilizing noise. The neural dynamics also exhibits features of the most likely stimulus in the network's spontaneous activity. These properties of the spatiotemporal neural code resulting from plasticity, having their grounding in nature, further consolidate the biological relevance of our findings. PMID:24651447

A review on thermal and catalytic pyrolysis of plastic solid waste (PSW).

PubMed

Al-Salem, S M; Antelava, A; Constantinou, A; Manos, G; Dutta, A

2017-07-15

Plastic plays an important role in our daily lives due to its versatility, light weight and low production cost. Plastics became essential in many sectors such as construction, medical, engineering applications, automotive, aerospace, etc. In addition, economic growth and development also increased our demand and dependency on plastics which leads to its accumulation in landfills imposing risk on human health, animals and cause environmental pollution problems such as ground water contamination, sanitary related issues, etc. Hence, a sustainable and an efficient plastic waste treatment is essential to avoid such issues. Pyrolysis is a thermo-chemical plastic waste treatment technique which can solve such pollution problems, as well as, recover valuable energy and products such as oil and gas. Pyrolysis of plastic solid waste (PSW) has gained importance due to having better advantages towards environmental pollution and reduction of carbon footprint of plastic products by minimizing the emissions of carbon monoxide and carbon dioxide compared to combustion and gasification. This paper presents the existing techniques of pyrolysis, the parameters which affect the products yield and selectivity and identify major research gaps in this technology. The influence of different catalysts on the process as well as review and comparative assessment of pyrolysis with other thermal and catalytic plastic treatment methods, is also presented. Copyright © 2017 Elsevier Ltd. All rights reserved.

Prentice Award Lecture 2011: Removing the Brakes on Plasticity in the Amblyopic Brain

PubMed Central

Levi, Dennis M.

2012-01-01

Experience-dependent plasticity is closely linked with the development of sensory function. Beyond this sensitive period, developmental plasticity is actively limited; however, new studies provide growing evidence for plasticity in the adult visual system. The amblyopic visual system is an excellent model for examining the “brakes” that limit recovery of function beyond the critical period. While amblyopia can often be reversed when treated early, conventional treatment is generally not undertaken in older children and adults. However new clinical and experimental studies in both animals and humans provide evidence for neural plasticity beyond the critical period. The results suggest that perceptual learning and video game play may be effective in improving a range of visual performance measures and importantly the improvements may transfer to better visual acuity and stereopsis. These findings, along with the results of new clinical trials, suggest that it might be time to re-consider our notions about neural plasticity in amblyopia. PMID:22581119

Plastic Organic Scintillator Chemistry

NASA Astrophysics Data System (ADS)

Brightwell, C. R.; Temanson, E. S.; Febbraro, M. T.

2017-09-01

Due to their high light output, quick decay time, affordability, durability and ability to be molded, plastic organic scintillators are increasingly becoming a more viable method of particle detection. Since the plastic is composed entirely of single molecular chains with repeating units, scintillating properties remain stable despite changes in experimental conditions. Different scintillating plastics can be modified and tailored to suit specific experiments depending on a variety of requirements such as light output, scintillating wavelength, and PMT compatibility. The synthesis chemistry of a recent but well-known scintillating polyester, polyethylene naphthalate (PEN) will be presented to demonstrate how plastic organic scintillators can be modified for different particle detection experiments. PEN has been successfully synthesized at ORNL, and procedures are currently being investigated to modify PEN using different reactants and catalysts. The goal is to achieve a transparent scintillating plastic with an incorporated wavelength shifter in the chain that scintillates with a wavelength around 440 nm. The status of this project will be presented. This research is supported by the U. S. Department of Energy Office of Science.

Solubility and durability of cardanol derived plasticizers for soft PVC

NASA Astrophysics Data System (ADS)

Greco, Antonio; Ferrari, Francesca; Velardi, Rosario; Frigione, Mariaenrica; Maffezzoli, Alfonso

2015-12-01

This work is aimed to study the suitability of cardanol derivatives as primary plasticizer for PVC. The innovative plasticizer is obtained by chemical modification of cardanol, a natural, renewable resource, obtained as a by-product of the cashew nut shell industry. Cardanol derived plasticizers (CDP) were prepared by following various procedures, that allow obtaining different degrees of conversion of cardanol. Rheological and ageing tests were made on soft PVC produced by the addition of CDP;results obtained were compared to soft PVC attained by the use of di-ethyl-hexyl-phthalate (DEHP) and other natural derived plasticizers already used in PVC industry (epoxidated soybean oil, ESBO, and acetic acid ester, AAE).A high dependence on the degree of conversion was found: CDP with a good degree of conversion have similar gelation temperature and diffusion coefficient compared to DEHP based plastisols. Otherwise,CDP with a low degree of conversionshow a higher diffusion coefficient, index of a fast migration of the plasticizer from soft PVC.

The Effects of Plastic Anisotropy in Warm and Hot Forming of Magnesium Sheet Materials

NASA Astrophysics Data System (ADS)

Taleff, Eric M.; Antoniswamy, Aravindha R.; Carpenter, Alexander J.; Yavuz, Emre

Mg alloy sheet materials often exhibit plastic anisotropy at room temperature as a result of the limited slip systems available in the HCP lattice combined with a commonly strong basal texture. Less well studied is plastic anisotropy developed at the elevated temperatures associated with warm and hot forming. At these elevated temperatures, particularly above 200°C, the activation of additional slip systems significantly increases ductility. However, plastic anisotropy is also induced at elevated temperatures by a strong crystallographic texture, and it can require an accounting in material constitutive models to achieve accurate forming simulations. The type and degree of anisotropy under these conditions depend on both texture and deformation mechanism. The current understanding of plastic anisotropy in Mg AZ31B and ZEK100 sheet materials at elevated temperatures is reviewed in this article. The recent construction of material forming cases is also reviewed with strategies to account for plastic anisotropy in forming simulations.

Evaluation of beach cleanup effects using linear system analysis.

PubMed

Kataoka, Tomoya; Hinata, Hirofumi

2015-02-15

We established a method for evaluating beach cleanup effects (BCEs) based on a linear system analysis, and investigated factors determining BCEs. Here we focus on two BCEs: decreasing the total mass of toxic metals that could leach into a beach from marine plastics and preventing the fragmentation of marine plastics on the beach. Both BCEs depend strongly on the average residence time of marine plastics on the beach (τ(r)) and the period of temporal variability of the input flux of marine plastics (T). Cleanups on the beach where τ(r) is longer than T are more effective than those where τ(r) is shorter than T. In addition, both BCEs are the highest near the time when the remnants of plastics reach the local maximum (peak time). Therefore, it is crucial to understand the following three factors for effective cleanups: the average residence time, the plastic input period and the peak time. Copyright © 2014 Elsevier Ltd. All rights reserved.

Critical neural networks with short- and long-term plasticity.

PubMed

Michiels van Kessenich, L; Luković, M; de Arcangelis, L; Herrmann, H J

2018-03-01

In recent years self organized critical neuronal models have provided insights regarding the origin of the experimentally observed avalanching behavior of neuronal systems. It has been shown that dynamical synapses, as a form of short-term plasticity, can cause critical neuronal dynamics. Whereas long-term plasticity, such as Hebbian or activity dependent plasticity, have a crucial role in shaping the network structure and endowing neural systems with learning abilities. In this work we provide a model which combines both plasticity mechanisms, acting on two different time scales. The measured avalanche statistics are compatible with experimental results for both the avalanche size and duration distribution with biologically observed percentages of inhibitory neurons. The time series of neuronal activity exhibits temporal bursts leading to 1/f decay in the power spectrum. The presence of long-term plasticity gives the system the ability to learn binary rules such as xor, providing the foundation of future research on more complicated tasks such as pattern recognition.

Critical neural networks with short- and long-term plasticity

NASA Astrophysics Data System (ADS)

Michiels van Kessenich, L.; Luković, M.; de Arcangelis, L.; Herrmann, H. J.

2018-03-01

In recent years self organized critical neuronal models have provided insights regarding the origin of the experimentally observed avalanching behavior of neuronal systems. It has been shown that dynamical synapses, as a form of short-term plasticity, can cause critical neuronal dynamics. Whereas long-term plasticity, such as Hebbian or activity dependent plasticity, have a crucial role in shaping the network structure and endowing neural systems with learning abilities. In this work we provide a model which combines both plasticity mechanisms, acting on two different time scales. The measured avalanche statistics are compatible with experimental results for both the avalanche size and duration distribution with biologically observed percentages of inhibitory neurons. The time series of neuronal activity exhibits temporal bursts leading to 1 /f decay in the power spectrum. The presence of long-term plasticity gives the system the ability to learn binary rules such as xor, providing the foundation of future research on more complicated tasks such as pattern recognition.

Multiscale Modeling of Structurally-Graded Materials Using Discrete Dislocation Plasticity Models and Continuum Crystal Plasticity Models

NASA Technical Reports Server (NTRS)

Saether, Erik; Hochhalter, Jacob D.; Glaessgen, Edward H.

2012-01-01

A multiscale modeling methodology that combines the predictive capability of discrete dislocation plasticity and the computational efficiency of continuum crystal plasticity is developed. Single crystal configurations of different grain sizes modeled with periodic boundary conditions are analyzed using discrete dislocation plasticity (DD) to obtain grain size-dependent stress-strain predictions. These relationships are mapped into crystal plasticity parameters to develop a multiscale DD/CP model for continuum level simulations. A polycrystal model of a structurally-graded microstructure is developed, analyzed and used as a benchmark for comparison between the multiscale DD/CP model and the DD predictions. The multiscale DD/CP model follows the DD predictions closely up to an initial peak stress and then follows a strain hardening path that is parallel but somewhat offset from the DD predictions. The difference is believed to be from a combination of the strain rate in the DD simulation and the inability of the DD/CP model to represent non-monotonic material response.

Inventory and transport of plastic debris in the Laurentian Great Lakes.

PubMed

Hoffman, Matthew J; Hittinger, Eric

2017-02-15

Plastic pollution in the world's oceans has received much attention, but there has been increasing concern about the high concentrations of plastic debris in the Laurentian Great Lakes. Using census data and methodologies used to study ocean debris we derive a first estimate of 9887 metric tonnes per year of plastic debris entering the Great Lakes. These estimates are translated into population-dependent particle inputs which are advected using currents from a hydrodynamic model to map the spatial distribution of plastic debris in the Great Lakes. Model results compare favorably with previously published sampling data. The samples are used to calibrate the model to derive surface microplastic mass estimates of 0.0211 metric tonnes in Lake Superior, 1.44 metric tonnes in Huron, and 4.41 metric tonnes in Erie. These results have many applications, including informing cleanup efforts, helping target pollution prevention, and understanding the inter-state or international flows of plastic pollution. Copyright © 2016 Elsevier Ltd. All rights reserved.

The Role of Neuromodulators in Cortical Plasticity. A Computational Perspective

PubMed Central

Pedrosa, Victor; Clopath, Claudia

2017-01-01

Neuromodulators play a ubiquitous role across the brain in regulating plasticity. With recent advances in experimental techniques, it is possible to study the effects of diverse neuromodulatory states in specific brain regions. Neuromodulators are thought to impact plasticity predominantly through two mechanisms: the gating of plasticity and the upregulation of neuronal activity. However, the consequences of these mechanisms are poorly understood and there is a need for both experimental and theoretical exploration. Here we illustrate how neuromodulatory state affects cortical plasticity through these two mechanisms. First, we explore the ability of neuromodulators to gate plasticity by reshaping the learning window for spike-timing-dependent plasticity. Using a simple computational model, we implement four different learning rules and demonstrate their effects on receptive field plasticity. We then compare the neuromodulatory effects of upregulating learning rate versus the effects of upregulating neuronal activity. We find that these seemingly similar mechanisms do not yield the same outcome: upregulating neuronal activity can lead to either a broadening or a sharpening of receptive field tuning, whereas upregulating learning rate only intensifies the sharpening of receptive field tuning. This simple model demonstrates the need for further exploration of the rich landscape of neuromodulator-mediated plasticity. Future experiments, coupled with biologically detailed computational models, will elucidate the diversity of mechanisms by which neuromodulatory state regulates cortical plasticity. PMID:28119596

Interaction of rate- and size-effect using a dislocation density based strain gradient viscoplasticity model

NASA Astrophysics Data System (ADS)

Nguyen, Trung N.; Siegmund, Thomas; Tomar, Vikas; Kruzic, Jamie J.

2017-12-01

Size effects occur in non-uniform plastically deformed metals confined in a volume on the scale of micrometer or sub-micrometer. Such problems have been well studied using strain gradient rate-independent plasticity theories. Yet, plasticity theories describing the time-dependent behavior of metals in the presence of size effects are presently limited, and there is no consensus about how the size effects vary with strain rates or whether there is an interaction between them. This paper introduces a constitutive model which enables the analysis of complex load scenarios, including loading rate sensitivity, creep, relaxation and interactions thereof under the consideration of plastic strain gradient effects. A strain gradient viscoplasticity constitutive model based on the Kocks-Mecking theory of dislocation evolution, namely the strain gradient Kocks-Mecking (SG-KM) model, is established and allows one to capture both rate and size effects, and their interaction. A formulation of the model in the finite element analysis framework is derived. Numerical examples are presented. In a special virtual creep test with the presence of plastic strain gradients, creep rates are found to diminish with the specimen size, and are also found to depend on the loading rate in an initial ramp loading step. Stress relaxation in a solid medium containing cylindrical microvoids is predicted to increase with decreasing void radius and strain rate in a prior ramp loading step.

Enhancement of vision by monocular deprivation in adult mice.

PubMed

Prusky, Glen T; Alam, Nazia M; Douglas, Robert M

2006-11-08

Plasticity of vision mediated through binocular interactions has been reported in mammals only during a "critical" period in juvenile life, wherein monocular deprivation (MD) causes an enduring loss of visual acuity (amblyopia) selectively through the deprived eye. Here, we report a different form of interocular plasticity of vision in adult mice in which MD leads to an enhancement of the optokinetic response (OKR) selectively through the nondeprived eye. Over 5 d of MD, the spatial frequency sensitivity of the OKR increased gradually, reaching a plateau of approximately 36% above pre-deprivation baseline. Eye opening initiated a gradual decline, but sensitivity was maintained above pre-deprivation baseline for 5-6 d. Enhanced function was restricted to the monocular visual field, notwithstanding the dependence of the plasticity on binocular interactions. Activity in visual cortex ipsilateral to the deprived eye was necessary for the characteristic induction of the enhancement, and activity in visual cortex contralateral to the deprived eye was necessary for its maintenance after MD. The plasticity also displayed distinct learning-like properties: Active testing experience was required to attain maximal enhancement and for enhancement to persist after MD, and the duration of enhanced sensitivity after MD was extended by increasing the length of MD, and by repeating MD. These data show that the adult mouse visual system maintains a form of experience-dependent plasticity in which the visual cortex can modulate the normal function of subcortical visual pathways.

Creep of Ni(3)Al in the temperature regime of anomalous flow behavior

NASA Astrophysics Data System (ADS)

Uchic, Michael David

Much attention has been paid to understanding the dynamics of dislocation motion and substructure formation in Ni3Al in the anomalous flow regime. However, most of the experimental work that has been performed in the lowest temperatures of the anomalous flow regime has been under constant-strain-rate conditions. An alternative and perhaps more fundamental way to probe the plastic behavior of materials is a monotonic creep test, in which the stress and temperature are held constant while the time-dependent strain is measured. The aim of this study is to use constant-stress experiments to further explore the plastic flow anomaly in L12 alloys at low temperatures. Tension creep experiments have been carried out on <123> oriented single crystals of Ni75Al24Ta1 at temperatures between 293 and 473 K. We have observed primary creep leading to exhaustion at all temperatures and stresses, with creep rates declining faster than predicted by the logarithmic creep law. The total strain and creep strain have an anomalous dependence on temperature, which is consistent with the flow stress anomaly. We have also observed other unusual behavior in our creep experiments; for example, the reinitiation of plastic flow at low temperatures after a modest increment in applied stress shows a sigmoidal response, i.e., there is a significant time delay before the plastic strain rate accelerates to a maximum value. We also examined the ability to reinitiate plastic flow in samples that have been crept to exhaustion by simply lowering the test temperature. In addition, we have also performed conventional constant-displacement-rate experiments in the same temperature range. From these experiments, we have discovered that unlike most metals, Ni3Al displays a negative dependence of the work hardening rate (WHR) with increasing strain rate. For tests at intermediate temperatures (373 and 423 K), the WHRs of crystals tested at moderately high strain rates (10-2 s-1) are half the WHRs of crystals tested at conventional strain rates (10 -5 s-1), and this anomalous dependence has also been shown to be reversible with changes in strain rate. The implications of all results are discussed in light of our efforts to model plastic deformation in these alloys.

The expression of plasticity-related genes in an acute model of stress is modulated by chronic desipramine in a time-dependent manner within medial prefrontal cortex.

PubMed

Nava, Nicoletta; Treccani, Giulia; Müller, Heidi Kaastrup; Popoli, Maurizio; Wegener, Gregers; Elfving, Betina

2017-01-01

It is well established that stress plays a major role in the pathogenesis of neuropsychiatric diseases. Stress-induced alteration of synaptic plasticity has been hypothesized to underlie the morphological changes observed by neuroimaging in psychiatric patients in key regions such as hippocampus and prefrontal cortex (PFC). We have recently shown that a single acute stress exposure produces significant short-term alterations of structural plasticity within medial PFC. These alterations were partially prevented by previous treatment with chronic desipramine (DMI). In the present study we evaluated the effects of acute Foot-shock (FS)-stress and pre-treatment with the traditional antidepressant DMI on the gene expression of key regulators of synaptic plasticity and structure. Expression of Homer, Shank, Spinophilin, Densin-180, and the small RhoGTPase related gene Rac1 and downstream target genes, Limk1, Cofilin1 and Rock1 were investigated 1 day (1d), 7 d and 14d after FS-stress exposure. We found that DMI specifically increases the short-term expression of Spinophilin, as well as Homer and Shank family genes, and that both acute stress and DMI exert significant long-term effects on mRNA levels of genes involved in spine plasticity. These findings support the knowledge that acute FS stress and antidepressant treatment induce both rapid and sustained time-dependent alterations in structural components of synaptic plasticity in rodent medial PFC. Copyright © 2016 Elsevier B.V. and ECNP. All rights reserved.

On a phase field approach for martensitic transformations in a crystal plastic material at a loaded surface

NASA Astrophysics Data System (ADS)

Schmitt, Regina; Kuhn, Charlotte; Müller, Ralf

2017-07-01

A continuum phase field model for martensitic transformations is introduced, including crystal plasticity with different slip systems for the different phases. In a 2D setting, the transformation-induced eigenstrain is taken into account for two martensitic orientation variants. With aid of the model, the phase transition and its dependence on the volume change, crystal plastic material behavior, and the inheritance of plastic deformations from austenite to martensite are studied in detail. The numerical setup is motivated by the process of cryogenic turning. The resulting microstructure qualitatively coincides with an experimentally obtained martensite structure. For the numerical calculations, finite elements together with global and local implicit time integration scheme are employed.

Interaction of heat production, strain rate and stress power in a plastically deforming body under tensile test

NASA Technical Reports Server (NTRS)

Paglietti, A.

1982-01-01

At high strain rates the heat produced by plastic deformation can give rise to a rate dependent response even if the material has rate independent constitutive equations. This effect has to be evaluated when interpreting a material test, or else it could erroneously be ascribed to viscosity. A general thermodynamic theory of tensile testing of elastic-plastic materials is given in this paper; it is valid for large strain at finite strain rates. It enables discovery of the parameters governing the thermodynamic strain rate effect, provides a method for proper interpretation of the results of the tests of dynamic plasticity, and suggests a way of planning experiments in order to detect the real contribution of viscosity.

Modulatory role of androgenic and estrogenic neurosteroids in determining the direction of synaptic plasticity in the CA1 hippocampal region of male rats

PubMed Central

Pettorossi, Vito Enrico; Di Mauro, Michela; Scarduzio, Mariangela; Panichi, Roberto; Tozzi, Alessandro; Calabresi, Paolo; Grassi, Silvarosa

2013-01-01

Abstract Estrogenic and androgenic neurosteroids can rapidly modulate synaptic plasticity in the brain through interaction with membrane receptors for estrogens (ERs) and androgens (ARs). We used electrophysiological recordings in slices of young and adolescent male rats to explore the influence of sex neurosteroids on synaptic plasticity in the CA1 hippocampal region, by blocking ARs or ERs during induction of long‐term depression (LTD) and depotentiation (DP) by low‐frequency stimulation (LFS) and long‐term potentiation (LTP) by high‐frequency stimulation (HFS). We found that LTD and DP depend on ARs, while LTP on ERs in both age groups. Accordingly, the AR blocker flutamide affected induction of LTD reverting it into LTP, and prevented DP, while having no effect on HFS‐dependent LTP. Conversely, ER blockade with ICI 182,780 (ICI) markedly reduced LTP, but did not influence LTD and DP. However, the receptor blockade did not affect the maintenance of either LTD or LTP. Moreover, we found that similar to LTP and LTD induced in control condition, the LTP unveiled by flutamide during LFS and residual LTP induced by HFS under ICI depended on N‐methyl‐d aspartate receptor (NMDAR) activation. Furthermore, as the synaptic paired‐pulse facilitation (PPF) was not affected by either AR or ER blockade, we suggest that sex neurosteroids act primarily at a postsynaptic level. This study demonstrates for the first time the crucial role of estrogenic and androgenic neurosteroids in determining the sign of hippocampal synaptic plasticity in male rat and the activity‐dependent recruitment of androgenic and estrogenic pathways leading to LTD and LTP, respectively. PMID:24744863

Modulatory role of androgenic and estrogenic neurosteroids in determining the direction of synaptic plasticity in the CA1 hippocampal region of male rats.

PubMed

Pettorossi, Vito Enrico; Di Mauro, Michela; Scarduzio, Mariangela; Panichi, Roberto; Tozzi, Alessandro; Calabresi, Paolo; Grassi, Silvarosa

2013-12-01

Estrogenic and androgenic neurosteroids can rapidly modulate synaptic plasticity in the brain through interaction with membrane receptors for estrogens (ERs) and androgens (ARs). We used electrophysiological recordings in slices of young and adolescent male rats to explore the influence of sex neurosteroids on synaptic plasticity in the CA1 hippocampal region, by blocking ARs or ERs during induction of long-term depression (LTD) and depotentiation (DP) by low-frequency stimulation (LFS) and long-term potentiation (LTP) by high-frequency stimulation (HFS). We found that LTD and DP depend on ARs, while LTP on ERs in both age groups. Accordingly, the AR blocker flutamide affected induction of LTD reverting it into LTP, and prevented DP, while having no effect on HFS-dependent LTP. Conversely, ER blockade with ICI 182,780 (ICI) markedly reduced LTP, but did not influence LTD and DP. However, the receptor blockade did not affect the maintenance of either LTD or LTP. Moreover, we found that similar to LTP and LTD induced in control condition, the LTP unveiled by flutamide during LFS and residual LTP induced by HFS under ICI depended on N-methyl-d aspartate receptor (NMDAR) activation. Furthermore, as the synaptic paired-pulse facilitation (PPF) was not affected by either AR or ER blockade, we suggest that sex neurosteroids act primarily at a postsynaptic level. This study demonstrates for the first time the crucial role of estrogenic and androgenic neurosteroids in determining the sign of hippocampal synaptic plasticity in male rat and the activity-dependent recruitment of androgenic and estrogenic pathways leading to LTD and LTP, respectively.

Effects of Adiabatic Heating on the High Strain Rate Deformation of Polymer Matrix Composites

NASA Technical Reports Server (NTRS)

Sorini, Chris; Chattopadhyay, Aditi; Goldberg, Robert K.

2017-01-01

Polymer matrix composites (PMCs) are increasingly being used in aerospace structures that are expected to experience complex dynamic loading conditions throughout their lifetime. As such, a detailed understanding of the high strain rate behavior of the constituents, particularly the strain rate, temperature, and pressure dependent polymer matrix, is paramount. In this paper, preliminary efforts in modeling experimentally observed temperature rises due to plastic deformation in PMCs subjected to dynamic loading are presented. To this end, an existing isothermal viscoplastic polymer constitutive formulation is extended to model adiabatic conditions by incorporating temperature dependent elastic properties and modifying the components of the inelastic strain rate tensor to explicitly depend on temperature. It is demonstrated that the modified polymer constitutive model is capable of capturing strain rate and temperature dependent yield as well as thermal softening associated with the conversion of plastic work to heat at high rates of strain. The modified constitutive model is then embedded within a strength of materials based micromechanics framework to investigate the manifestation of matrix thermal softening, due to the conversion of plastic work to heat, on the high strain rate response of a T700Epon 862 (T700E862) unidirectional composite. Adiabatic model predictions for high strain rate composite longitudinal tensile, transverse tensile, and in-plane shear loading are presented. Results show a substantial deviation from isothermal conditions; significant thermal softening is observed for matrix dominated deformation modes (transverse tension and in-plane shear), highlighting the importance of accounting for the conversion of plastic work to heat in the polymer matrix in the high strain rate analysis of PMC structures.

Determination of the diffusion coefficient and solubility of radon in plastics.

PubMed

Pressyanov, D; Georgiev, S; Dimitrova, I; Mitev, K; Boshkova, T

2011-05-01

This paper describes a method for determination of the diffusion coefficient and the solubility of radon in plastics. The method is based on the absorption and desorption of radon in plastics. Firstly, plastic specimens are exposed for controlled time to referent (222)Rn concentrations. After exposure, the activity of the specimens is followed by HPGe gamma spectrometry. Using the mathematical algorithm described in this report and the decrease of activity as a function of time, the diffusion coefficient can be determined. In addition, if the referent (222)Rn concentration during the exposure is known, the solubility of radon can be determined. The algorithm has been experimentally applied for different plastics. The results show that this approach allows the specified quantities to be determined with a rather high accuracy-depending on the quality of the counting equipment, it can be better than 10 %.

Plasticity of preferred body temperatures as means of coping with climate change?

PubMed Central

Gvoždík, Lumír

2012-01-01

Thermoregulatory behaviour represents an important component of ectotherm non-genetic adaptive capacity that mitigates the impact of ongoing climate change. The buffering role of behavioural thermoregulation has been attributed solely to the ability to maintain near optimal body temperature for sufficiently extended periods under altered thermal conditions. The widespread occurrence of plastic modification of target temperatures that an ectotherm aims to achieve (preferred body temperatures) has been largely overlooked. I argue that plasticity of target temperatures may significantly contribute to an ectotherm's adaptive capacity. Its contribution to population persistence depends on both the effectiveness of acute thermoregulatory adjustments (reactivity) in buffering selection pressures in a changing thermal environment, and the total costs of thermoregulation (i.e. reactivity and plasticity) in a given environment. The direction and magnitude of plastic shifts in preferred body temperatures can be incorporated into mechanistic models, to improve predictions of the impact of global climate change on ectotherm populations. PMID:22072284

Plasticity of preferred body temperatures as means of coping with climate change?

PubMed

Gvozdík, Lumír

2012-04-23

Thermoregulatory behaviour represents an important component of ectotherm non-genetic adaptive capacity that mitigates the impact of ongoing climate change. The buffering role of behavioural thermoregulation has been attributed solely to the ability to maintain near optimal body temperature for sufficiently extended periods under altered thermal conditions. The widespread occurrence of plastic modification of target temperatures that an ectotherm aims to achieve (preferred body temperatures) has been largely overlooked. I argue that plasticity of target temperatures may significantly contribute to an ectotherm's adaptive capacity. Its contribution to population persistence depends on both the effectiveness of acute thermoregulatory adjustments (reactivity) in buffering selection pressures in a changing thermal environment, and the total costs of thermoregulation (i.e. reactivity and plasticity) in a given environment. The direction and magnitude of plastic shifts in preferred body temperatures can be incorporated into mechanistic models, to improve predictions of the impact of global climate change on ectotherm populations.

Crystal plasticity in Cu damascene interconnect lines undergoing electromigration as revealed by synchrotron x-ray microdiffraction

NASA Astrophysics Data System (ADS)

Budiman, A. S.; Nix, W. D.; Tamura, N.; Valek, B. C.; Gadre, K.; Maiz, J.; Spolenak, R.; Patel, J. R.

2006-06-01

Plastic deformation was observed in damascene Cu interconnect test structures during an in situ electromigration experiment and before the onset of visible microstructural damage (voiding, hillock formation). We show here, using a synchrotron technique of white beam x-ray microdiffraction, that the extent of this electromigration-induced plasticity is dependent on the linewidth. In wide lines, plastic deformation manifests itself as grain bending and the formation of subgrain structures, while only grain rotation is observed in the narrower lines. The deformation geometry leads us to conclude that dislocations introduced by plastic flow lie predominantly in the direction of electron flow and may provide additional easy paths for the transport of point defects. Since these findings occur long before any observable voids or hillocks are formed, they may have direct bearing on the final failure stages of electromigration.

Different Compartments of Apical CA1 Dendrites Have Different Plasticity Thresholds for Expressing Synaptic Tagging and Capture

ERIC Educational Resources Information Center

Sajikumar, Sreedharan; Korte, Martin

2011-01-01

The consolidation process from short- to long-term memory depends on the type of stimulation received from a specific neuronal network and on the cooperativity and associativity between different synaptic inputs converging onto a specific neuron. We show here that the plasticity thresholds for inducing LTP are different in proximal and distal…

SRC Inhibition Reduces NR2B Surface Expression and Synaptic Plasticity in the Amygdala

ERIC Educational Resources Information Center

Sinai, Laleh; Duffy, Steven; Roder, John C.

2010-01-01

The Src protein tyrosine kinase plays a central role in the regulation of N-methyl-d-aspartate receptor (NMDAR) activity by regulating NMDAR subunit 2B (NR2B) surface expression. In the amygdala, NMDA-dependent synaptic plasticity resulting from convergent somatosensory and auditory inputs contributes to emotional memory; however, the role of Src…

Size-dependent plastic deformation of twinned nanopillars in body-centered cubic tungsten

NASA Astrophysics Data System (ADS)

Xu, Shuozhi; Startt, Jacob K.; Payne, Thomas G.; Deo, Chaitanya S.; McDowell, David L.

2017-05-01

Compared with face-centered cubic metals, twinned nanopillars in body-centered cubic (BCC) systems are much less explored partly due to the more complicated plastic deformation behavior and a lack of reliable interatomic potentials for the latter. In this paper, the fault energies predicted by two semi-empirical interatomic potentials in BCC tungsten (W) are first benchmarked against density functional theory calculations. Then, the more accurate potential is employed in large scale molecular dynamics simulations of tensile and compressive loading of twinned nanopillars in BCC W with different cross sectional shapes and sizes. A single crystal, a twinned crystal, and single crystalline nanopillars are also studied as references. Analyses of the stress-strain response and defect nucleation reveal a strong tension-compression asymmetry and a weak pillar size dependence in the yield strength. Under both tensile and compressive loading, plastic deformation in the twinned nanopillars is dominated by dislocation slip on {110} planes that are nucleated from the intersections between the twin boundary and the pillar surface. It is also found that the cross sectional shape of nanopillars affects the strength and the initial site of defect nucleation but not the overall stress-strain response and plastic deformation behavior.

Remodeling of Dendritic Spines in the Avian Vocal Motor Cortex Following Deafening Depends on the Basal Ganglia Circuit.

PubMed

Zhou, Xin; Fu, Xin; Lin, Chun; Zhou, Xiaojuan; Liu, Jin; Wang, Li; Zhang, Xinwen; Zuo, Mingxue; Fan, Xiaolong; Li, Dapeng; Sun, Yingyu

2017-05-01

Deafening elicits a deterioration of learned vocalization, in both humans and songbirds. In songbirds, learned vocal plasticity has been shown to depend on the basal ganglia-cortical circuit, but the underlying cellular basis remains to be clarified. Using confocal imaging and electron microscopy, we examined the effect of deafening on dendritic spines in avian vocal motor cortex, the robust nucleus of the arcopallium (RA), and investigated the role of the basal ganglia circuit in motor cortex plasticity. We found rapid structural changes to RA dendritic spines in response to hearing loss, accompanied by learned song degradation. In particular, the morphological characters of RA spine synaptic contacts between 2 major pathways were altered differently. However, experimental disruption of the basal ganglia circuit, through lesions in song-specialized basal ganglia nucleus Area X, largely prevented both the observed changes to RA dendritic spines and the song deterioration after hearing loss. Our results provide cellular evidence to highlight a key role of the basal ganglia circuit in the motor cortical plasticity that underlies learned vocal plasticity. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Calcium/Calmodulin-dependent Protein Kinase II is a Ubiquitous Molecule in Human Long-term Memory Synaptic Plasticity: A Systematic Review

PubMed Central

Ataei, Negar; Sabzghabaee, Ali Mohammad; Movahedian, Ahmad

2015-01-01

Background: Long-term memory is based on synaptic plasticity, a series of biochemical mechanisms include changes in structure and proteins of brain's neurons. In this article, we systematically reviewed the studies that indicate calcium/calmodulin kinase II (CaMKII) is a ubiquitous molecule among different enzymes involved in human long-term memory and the main downstream signaling pathway of long-term memory. Methods: All of the observational, case–control and review studies were considered and evaluated by the search engines PubMed, Cochrane Central Register of Controlled Trials and ScienceDirect Scopus between 1990 and February 2015. We did not carry out meta-analysis. Results: At the first search, it was fined 1015 articles which included “synaptic plasticity” OR “neuronal plasticity” OR “synaptic density” AND memory AND “molecular mechanism” AND “calcium/calmodulin-dependent protein kinase II” OR CaMKII as the keywords. A total of 335 articles were duplicates in the databases and eliminated. A total of 680 title articles were evaluated. Finally, 40 articles were selected as reference. Conclusions: The studies have shown the most important intracellular signal of long-term memory is calcium-dependent signals. Calcium linked calmodulin can activate CaMKII. After receiving information for learning and memory, CaMKII is activated by Glutamate, the most important neurotransmitter for memory-related plasticity. Glutamate activates CaMKII and it plays some important roles in synaptic plasticity modification and long-term memory. PMID:26445635

Spike-timing dependent inhibitory plasticity to learn a selective gating of backpropagating action potentials.

PubMed

Wilmes, Katharina Anna; Schleimer, Jan-Hendrik; Schreiber, Susanne

2017-04-01

Inhibition is known to influence the forward-directed flow of information within neurons. However, also regulation of backward-directed signals, such as backpropagating action potentials (bAPs), can enrich the functional repertoire of local circuits. Inhibitory control of bAP spread, for example, can provide a switch for the plasticity of excitatory synapses. Although such a mechanism is possible, it requires a precise timing of inhibition to annihilate bAPs without impairment of forward-directed excitatory information flow. Here, we propose a specific learning rule for inhibitory synapses to automatically generate the correct timing to gate bAPs in pyramidal cells when embedded in a local circuit of feedforward inhibition. Based on computational modeling of multi-compartmental neurons with physiological properties, we demonstrate that a learning rule with anti-Hebbian shape can establish the required temporal precision. In contrast to classical spike-timing dependent plasticity of excitatory synapses, the proposed inhibitory learning mechanism does not necessarily require the definition of an upper bound of synaptic weights because of its tendency to self-terminate once annihilation of bAPs has been reached. Our study provides a functional context in which one of the many time-dependent learning rules that have been observed experimentally - specifically, a learning rule with anti-Hebbian shape - is assigned a relevant role for inhibitory synapses. Moreover, the described mechanism is compatible with an upregulation of excitatory plasticity by disinhibition. © 2016 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

CX3CR1 Deficiency Alters Hippocampal-Dependent Plasticity Phenomena Blunting the Effects of Enriched Environment

PubMed Central

Maggi, Laura; Scianni, Maria; Branchi, Igor; D’Andrea, Ivana; Lauro, Clotilde; Limatola, Cristina

2011-01-01

In recent years several evidence demonstrated that some features of hippocampal biology, like neurogenesis, synaptic transmission, learning, and memory performances are deeply modulated by social, motor, and sensorial experiences. Fractalkine/CX3CL1 is a transmembrane chemokine abundantly expressed in the brain by neurons, where it modulates glutamatergic transmission and long-term plasticity processes regulating the intercellular communication between glia and neurons, being its specific receptor CX3CR1 expressed by microglia. In this paper we investigated the role of CX3CL1/CX3CR1 signaling on experience-dependent hippocampal plasticity processes. At this aim wt and CX3CR1GFP/GFP mice were exposed to long-lasting-enriched environment (EE) and the effects on hippocampal functions were studied by electrophysiological recordings of long-term potentiation of synaptic activity, behavioral tests of learning and memory in the Morris water maze paradigm and analysis of neurogenesis in the subgranular zone of the dentate gyrus (DG). We found that CX3CR1 deficiency increases hippocampal plasticity and spatial memory, blunting the potentiating effects of EE. In contrast, exposure to EE increased the number and migration of neural progenitors in the DG of both wt and CX3CR1GFP/GFP mice. These data indicate that CX3CL1/CX3CR1-mediated signaling is crucial for a normal experience-dependent modulation of hippocampal functions. PMID:22025910

The beneficial effects of treadmill step training on activity-dependent synaptic and cellular plasticity markers after complete spinal cord injury.

PubMed

Ilha, Jocemar; Centenaro, Lígia A; Broetto Cunha, Núbia; de Souza, Daniela F; Jaeger, Mariane; do Nascimento, Patrícia S; Kolling, Janaína; Ben, Juliana; Marcuzzo, Simone; Wyse, Angela T S; Gottfried, Carmem; Achaval, Matilde

2011-06-01

Several studies have shown that treadmill training improves neurological outcomes and promotes plasticity in lumbar spinal cord of spinal animals. The morphological and biochemical mechanisms underlying these phenomena remain unclear. The purpose of this study was to provide evidence of activity-dependent plasticity in spinal cord segment (L5) below a complete spinal cord transection (SCT) at T8-9 in rats in which the lower spinal cord segments have been fully separated from supraspinal control and that subsequently underwent treadmill step training. Five days after SCT, spinal animals started a step-training program on a treadmill with partial body weight support and manual step help. Hindlimb movements were evaluated over time and scored on the basis of the open-field BBB scale and were significantly improved at post-injury weeks 8 and 10 in trained spinal animals. Treadmill training also showed normalization of withdrawal reflex in trained spinal animals, which was significantly different from the untrained animals at post-injury weeks 8 and 10. Additionally, compared to controls, spinal rats had alpha motoneuronal soma size atrophy and reduced synaptophysin protein expression and Na(+), K(+)-ATPase activity in lumbar spinal cord. Step-trained rats had motoneuronal soma size, synaptophysin expression and Na(+), K(+)-ATPase activity similar to control animals. These findings suggest that treadmill step training can promote activity-dependent neural plasticity in lumbar spinal cord, which may lead to neurological improvements without supraspinal descending control after complete spinal cord injury.

Pre-attentive, context-specific representation of fear memory in the auditory cortex of rat.

PubMed

Funamizu, Akihiro; Kanzaki, Ryohei; Takahashi, Hirokazu

2013-01-01

Neural representation in the auditory cortex is rapidly modulated by both top-down attention and bottom-up stimulus properties, in order to improve perception in a given context. Learning-induced, pre-attentive, map plasticity has been also studied in the anesthetized cortex; however, little attention has been paid to rapid, context-dependent modulation. We hypothesize that context-specific learning leads to pre-attentively modulated, multiplex representation in the auditory cortex. Here, we investigate map plasticity in the auditory cortices of anesthetized rats conditioned in a context-dependent manner, such that a conditioned stimulus (CS) of a 20-kHz tone and an unconditioned stimulus (US) of a mild electrical shock were associated only under a noisy auditory context, but not in silence. After the conditioning, although no distinct plasticity was found in the tonotopic map, tone-evoked responses were more noise-resistive than pre-conditioning. Yet, the conditioned group showed a reduced spread of activation to each tone with noise, but not with silence, associated with a sharpening of frequency tuning. The encoding accuracy index of neurons showed that conditioning deteriorated the accuracy of tone-frequency representations in noisy condition at off-CS regions, but not at CS regions, suggesting that arbitrary tones around the frequency of the CS were more likely perceived as the CS in a specific context, where CS was associated with US. These results together demonstrate that learning-induced plasticity in the auditory cortex occurs in a context-dependent manner.

Hunger States Control the Directions of Synaptic Plasticity via Switching Cell Type-Specific Subunits of NMDA Receptors.

PubMed

Qi, Yong; Yang, Yunlei

2015-09-23

It remains largely unknown whether and how hunger states control activity-dependent synaptic plasticity, such as long-term potentiation (LTP) and long-term depression (LTD). We here report that both LTP and LTD of excitatory synaptic strength within the appetite control circuits residing in hypothalamic arcuate nucleus (ARC) behave in a manner of hunger states dependence and cell type specificity. For instance, we find that tetanic stimulation induces LTP at orexigenic agouti-related protein (AgRP) neurons in ad libitum fed mice, whereas it induces LTD in food-deprived mice. In an opposite direction, the same induction protocol induces LTD at anorexigenic pro-opiomelanocortin (POMC) neurons in fed mice but weak LTP in deprived mice. Mechanistically, we also find that food deprivation increases the expressions of NR2C/NR2D/NR3-containing NMDA receptors (NMDARs) at AgRP neurons that contribute to the inductions of LTD, whereas it decreases their expressions at POMC neurons. Collectively, our data reveal that hunger states control the directions of activity-dependent synaptic plasticity by switching NMDA receptor subpopulations in a cell type-specific manner, providing insights into NMDAR-mediated interactions between energy states and associative memory. Significance statement: Based on the experiments performed in this study, we demonstrate that activity-dependent synaptic plasticity is also under the control of energy states by regulating NMDAR subpopulations in a cell type-specific manner. We thus propose a reversible memory configuration constructed from energy states-dependent cell type-specific bidirectional conversions of LTP and LTD. Together with the distinct functional roles played by NMDAR signaling in the control of food intake and energy states, these findings reveal a new reciprocal interaction between energy states and associative memory, one that might serve as a target for therapeutic treatments of the energy-related memory disorders or vice versa. Copyright © 2015 the authors 0270-6474/15/3513171-12$15.00/0.

Network reconfiguration and neuronal plasticity in rhythm-generating networks.

PubMed

Koch, Henner; Garcia, Alfredo J; Ramirez, Jan-Marino

2011-12-01

Neuronal networks are highly plastic and reconfigure in a state-dependent manner. The plasticity at the network level emerges through multiple intrinsic and synaptic membrane properties that imbue neurons and their interactions with numerous nonlinear properties. These properties are continuously regulated by neuromodulators and homeostatic mechanisms that are critical to maintain not only network stability and also adapt networks in a short- and long-term manner to changes in behavioral, developmental, metabolic, and environmental conditions. This review provides concrete examples from neuronal networks in invertebrates and vertebrates, and illustrates that the concepts and rules that govern neuronal networks and behaviors are universal.

Nanosized carbon modifier used to control plastic deformations of asphalt concrete

NASA Astrophysics Data System (ADS)

Vysotskaya, M. A.; Shekhovtsova, S. Yu; Barkovsky, D. V.

2018-03-01

Aspects related to plastic track, the formation of which directly depends on the properties of the binder in the composition of asphalt concrete, are considered in this article. The effect of primary carbon nanomaterials on the quality of polymer and bitumen binder in comparison with the traditional binder including cross-linking agent is evaluated. The influence of binders on the resistance to the track formation of type B asphalt concrete is studied. To quantify the service life of surfacing, a calculation method based on the criteria for the resistance of surfacing material to plastic deformations is used.

Correlation between elastic and plastic deformations of partially cured epoxy networks

NASA Astrophysics Data System (ADS)

Müller, Michael; Böhm, Robert; Geller, Sirko; Kupfer, Robert; Jäger, Hubert; Gude, Maik

2018-05-01

The thermo-mechanical behavior of polymer matrix materials is strongly dependent on the curing reaction as well as temperature and time. To date, investigations of epoxy resins and their composites mainly focused on the elastic domain because plastic deformation of cross-linked polymer networks was considered as irrelevant or not feasible. This paper presents a novel approach which combines both elastic and plastic domain. Based on an analytical framework describing the storage modulus, analogous parameter combinations are defined in order to reduce complexity when variations in temperature, strain rate and degree of cure are encountered.

Muscarinic acetylcholine receptors control baseline activity and Hebbian stimulus timing-dependent plasticity in fusiform cells of the dorsal cochlear nucleus.

PubMed

Stefanescu, Roxana A; Shore, Susan E

2017-03-01

Cholinergic modulation contributes to adaptive sensory processing by controlling spontaneous and stimulus-evoked neural activity and long-term synaptic plasticity. In the dorsal cochlear nucleus (DCN), in vitro activation of muscarinic acetylcholine receptors (mAChRs) alters the spontaneous activity of DCN neurons and interacts with N -methyl-d-aspartate (NMDA) and endocannabinoid receptors to modulate the plasticity of parallel fiber synapses onto fusiform cells by converting Hebbian long-term potentiation to anti-Hebbian long-term depression. Because noise exposure and tinnitus are known to increase spontaneous activity in fusiform cells as well as alter stimulus timing-dependent plasticity (StTDP), it is important to understand the contribution of mAChRs to in vivo spontaneous activity and plasticity in fusiform cells. In the present study, we blocked mAChRs actions by infusing atropine, a mAChR antagonist, into the DCN fusiform cell layer in normal hearing guinea pigs. Atropine delivery leads to decreased spontaneous firing rates and increased synchronization of fusiform cell spiking activity. Consistent with StTDP alterations observed in tinnitus animals, atropine infusion induced a dominant pattern of inversion of StTDP mean population learning rule from a Hebbian to an anti-Hebbian profile. Units preserving their initial Hebbian learning rules shifted toward more excitatory changes in StTDP, whereas units with initial suppressive learning rules transitioned toward a Hebbian profile. Together, these results implicate muscarinic cholinergic modulation as a factor in controlling in vivo fusiform cell baseline activity and plasticity, suggesting a central role in the maladaptive plasticity associated with tinnitus pathology. NEW & NOTEWORTHY This study is the first to use a novel method of atropine infusion directly into the fusiform cell layer of the dorsal cochlear nucleus coupled with simultaneous recordings of neural activity to clarify the contribution of muscarinic acetylcholine receptors (mAChRs) to in vivo fusiform cell baseline activity and auditory-somatosensory plasticity. We have determined that blocking the mAChRs increases the synchronization of spiking activity across the fusiform cell population and induces a dominant pattern of inversion in their stimulus timing-dependent plasticity. These modifications are consistent with similar changes established in previous tinnitus studies, suggesting that mAChRs might have a critical contribution in mediating the maladaptive alterations associated with tinnitus pathology. Blocking mAChRs also resulted in decreased fusiform cell spontaneous firing rates, which is in contrast with their tinnitus hyperactivity, suggesting that changes in the interactions between the cholinergic and GABAergic systems might also be an underlying factor in tinnitus pathology. Copyright © 2017 the American Physiological Society.

Kinetic Modeling of the Release of Ethylene Oxide from Sterilized Plastic Containers and its Interaction with Monoclonal Antibodies.

PubMed

Yu, Bryan Lei; Han, Jun; Hammond, Matthew; Wang, Xuemei; Zhang, Qingchun; Clausen, Andrew; Forster, Ronald; Eu, Mingda

Ethylene oxide (ETO) is commonly used to sterilize plastic containers, but the effects of residual amounts left after sterilization on protein therapeutics are still not well understood. Here we focus primarily on the factors that influence concentrations of ETO migrating from ETO-treated plastic containers into aqueous solution. A study was designed to investigate the kinetics of this process at various temperatures, and the kinetic data could be fit with a model based on a combination of Fickean diffusion and first-order chemical reaction (to account for observed hydrolysis of ETO). The diffusion and reaction rate constants thus obtained obey Arrhenius-like temperature dependence. These results indicate that for analytical methods involving extraction into water, measurements of residual ETO in a container must account for the effects of ETO hydrolysis. Further, the effects of salt concentration and pH of the fluid in the container on accumulated ETO levels were explored. Finally, interactions of ETO with anti-streptavidin (AntiSA) Immunoglobulin G1 (IgG1) and IgG2 antibodies were studied, with ETO adducts found on all methionine residues when incubated in solutions spiked with ETO at concentrations that could be reached (based on the kinetic studies) in ETO-treated plastic vials. Overall, the likelihood of observable ETO-protein modifications upon storage in ETO-sterilized containers will depend on a complex interplay of protein properties, formulation details, storage conditions, and amount of residual ETO initially in the container. Ethylene oxide (ETO) is commonly used to sterilize plastic containers, but the effects of residual amounts left after sterilization on protein therapeutics are still not well understood. Here we describe experiments exploring the factors that influence concentrations of ETO migrating from ETO-treated plastic containers into aqueous solution over time. Additionally, interactions of ETO with model antibodies were studied, with ETO adducts found on all methionine residues when incubated in solutions spiked with ETO at concentrations that could potentially be reached in ETO-treated plastic vials. Overall, the likelihood of observable ETO-protein modifications upon storage in ETO-sterilized containers will depend on a complex interplay of protein properties, formulation details, storage conditions, and amount of residual ETO initially in the container. © PDA, Inc. 2017.

Retinohypothalamic Tract Synapses in the Rat Suprachiasmatic Nucleus Demonstrate Short-Term Synaptic Plasticity

PubMed Central

Moldavan, Mykhaylo G.

2010-01-01

The master circadian pacemaker located in the suprachiasmatic nucleus (SCN) is entrained by light intensity–dependent signals transmitted via the retinohypothalamic tract (RHT). Short-term plasticity at glutamatergic RHT–SCN synapses was studied using stimulus frequencies that simulated the firing of light sensitive retinal ganglion cells. The evoked excitatory postsynaptic current (eEPSC) was recorded from SCN neurons located in hypothalamic brain slices. The eEPSC amplitude was stable during 0.08 Hz stimulation and exhibited frequency-dependent short-term synaptic depression (SD) during 0.5 to 100 Hz stimulus trains in 95 of 99 (96%) recorded neurons. During SD the steady-state eEPSC amplitude decreased, whereas the cumulative charge transfer increased in a frequency-dependent manner and saturated at 20 Hz. SD was similar during subjective day and night and decreased with increasing temperature. Paired-pulse stimulation (PPS) and voltage-dependent Ca2+ channel (VDCC) blockers were used to characterize a presynaptic release mechanism. Facilitation was present in 30% and depression in 70% of studied neurons during PPS. Synaptic transmission was reduced by blocking both N- and P/Q-type presynaptic VDCCs, but only the N-type channel blocker significantly relieved SD. Aniracetam inhibited AMPA receptor desensitization but did not alter SD. Thus we concluded that SD is the principal form of short-term plasticity at RHT synapses, which presynaptically and frequency-dependently attenuates light-induced glutamatergic RHT synaptic transmission protecting SCN neurons against excessive excitation. PMID:20220078

A Synaptic Basis for Memory Storage in the Cerebral Cortex

NASA Astrophysics Data System (ADS)

Bear, Mark F.

1996-11-01

A cardinal feature of neurons in the cerebral cortex is stimulus selectivity, and experience-dependent shifts in selectivity are a common correlate of memory formation. We have used a theoretical ``learning rule,'' devised to account for experience-dependent shifts in neuronal selectivity, to guide experiments on the elementary mechanisms of synaptic plasticity in hippocampus and neocortex. These experiments reveal that many synapses in hippocampus and neocortex are bidirectionally modifiable, that the modifications persist long enough to contribute to long-term memory storage, and that key variables governing the sign of synaptic plasticity are the amount of NMDA receptor activation and the recent history of cortical activity.

Grain Orientation Dependence of the Residual Lattice Strain in a Cold Rolled Interstitial-Free Steel

DOE PAGES

Xie, Qingge; Gorti, Sarma B.; Sidor, Jurij; ...

2018-01-10

The experimentally measured grain-orientation-dependent residual lattice strains, evolved in an interstitia-free steel after 70% cold rolling reduction, are studied by means of crystal elastic visco-plastic finite element simulations, which provides a very satisfactory prediction of deformation texture. The calculated residual lattice strain pole figure matches well with the experimentally measured counterpart within the highest density regions of major texture components observed. Both experimental evidence and results of modeling clearly indicate that the residual lattice strain is orientation dependent, based on comprehensive information on the evolution of residual lattice strain in various crystallographic orientations during plastic deformation. It appears that inmore » a cold rolled material, there is a general correlation between the stresses developed just prior to unloading and the residual lattice strains in particular directions. Here, it is also shown that the cumulative plastic shear does not reveal a clear correlation with the components of residual lattice strain while presented in the normal correlation plot, however, this relationship can be better understood by means of the orientation distribution function of residual lattice strain, which can be derived from the neutron or X-ray diffraction experiments.« less

Grain Orientation Dependence of the Residual Lattice Strain in a Cold Rolled Interstitial-Free Steel

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xie, Qingge; Gorti, Sarma B.; Sidor, Jurij

The experimentally measured grain-orientation-dependent residual lattice strains, evolved in an interstitia-free steel after 70% cold rolling reduction, are studied by means of crystal elastic visco-plastic finite element simulations, which provides a very satisfactory prediction of deformation texture. The calculated residual lattice strain pole figure matches well with the experimentally measured counterpart within the highest density regions of major texture components observed. Both experimental evidence and results of modeling clearly indicate that the residual lattice strain is orientation dependent, based on comprehensive information on the evolution of residual lattice strain in various crystallographic orientations during plastic deformation. It appears that inmore » a cold rolled material, there is a general correlation between the stresses developed just prior to unloading and the residual lattice strains in particular directions. Here, it is also shown that the cumulative plastic shear does not reveal a clear correlation with the components of residual lattice strain while presented in the normal correlation plot, however, this relationship can be better understood by means of the orientation distribution function of residual lattice strain, which can be derived from the neutron or X-ray diffraction experiments.« less

Pharmacological rescue of Ras signaling, GluA1-dependent synaptic plasticity, and learning deficits in a fragile X model.

PubMed

Lim, Chae-Seok; Hoang, Elizabeth T; Viar, Kenneth E; Stornetta, Ruth L; Scott, Michael M; Zhu, J Julius

2014-02-01

Fragile X syndrome, caused by the loss of Fmr1 gene function, is the most common form of inherited mental retardation, with no effective treatment. Using a tractable animal model, we investigated mechanisms of action of a few FDA-approved psychoactive drugs that modestly benefit the cognitive performance in fragile X patients. Here we report that compounds activating serotonin (5HT) subtype 2B receptors (5HT2B-Rs) or dopamine (DA) subtype 1-like receptors (D1-Rs) and/or those inhibiting 5HT2A-Rs or D2-Rs moderately enhance Ras-PI3K/PKB signaling input, GluA1-dependent synaptic plasticity, and learning in Fmr1 knockout mice. Unexpectedly, combinations of these 5HT and DA compounds at low doses synergistically stimulate Ras-PI3K/PKB signal transduction and GluA1-dependent synaptic plasticity and remarkably restore normal learning in Fmr1 knockout mice without causing anxiety-related side effects. These findings suggest that properly dosed and combined FDA-approved psychoactive drugs may effectively treat the cognitive impairment associated with fragile X syndrome.

Endocrine regulation of predator-induced phenotypic plasticity.

PubMed

Dennis, Stuart R; LeBlanc, Gerald A; Beckerman, Andrew P

2014-11-01

Elucidating the developmental and genetic control of phenotypic plasticity remains a central agenda in evolutionary ecology. Here, we investigate the physiological regulation of phenotypic plasticity induced by another organism, specifically predator-induced phenotypic plasticity in the model ecological and evolutionary organism Daphnia pulex. Our research centres on using molecular tools to test among alternative mechanisms of developmental control tied to hormone titres, receptors and their timing in the life cycle. First, we synthesize detail about predator-induced defenses and the physiological regulation of arthropod somatic growth and morphology, leading to a clear prediction that morphological defences are regulated by juvenile hormone and life-history plasticity by ecdysone and juvenile hormone. We then show how a small network of genes can differentiate phenotype expression between the two primary developmental control pathways in arthropods: juvenoid and ecdysteroid hormone signalling. Then, by applying an experimental gradient of predation risk, we show dose-dependent gene expression linking predator-induced plasticity to the juvenoid hormone pathway. Our data support three conclusions: (1) the juvenoid signalling pathway regulates predator-induced phenotypic plasticity; (2) the hormone titre (ligand), rather than receptor, regulates predator-induced developmental plasticity; (3) evolution has favoured the harnessing of a major, highly conserved endocrine pathway in arthropod development to regulate the response to cues about changing environments (risk) from another organism (predator).

Stress Wave Propagation in Viscoelastic-Plastic Rock-Like Materials.

PubMed

Lang, Liu; Song, Ki-Il; Zhai, Yue; Lao, Dezheng; Lee, Hang-Lo

2016-05-17

Rock-like materials are composites that can be regarded as a mixture composed of elastic, plastic, and viscous components. They exhibit viscoelastic-plastic behavior under a high-strain-rate loading according to element model theory. This paper presents an analytical solution for stress wave propagation in viscoelastic-plastic rock-like materials under a high-strain-rate loading and verifies the solution through an experimental test. A constitutive equation of viscoelastic-plastic rock-like materials was first established, and then kinematic and kinetic equations were then solved to derive the analytic solution for stress wave propagation in viscoelastic-plastic rock-like materials. An experimental test using the SHPB (Split Hopkinson Pressure Bar) for a concrete specimen was conducted to obtain a stress-strain curve under a high-strain-rate loading. Inverse analysis based on differential evolution was conducted to estimate undetermined variables for constitutive equations. Finally, the relationship between the attenuation factor and the strain rate in viscoelastic-plastic rock-like materials was investigated. According to the results, the frequency of the stress wave, viscosity coefficient, modulus of elasticity, and density play dominant roles in the attenuation of the stress wave. The attenuation decreases with increasing strain rate, demonstrating strongly strain-dependent attenuation in viscoelastic-plastic rock-like materials.

Charge carrier dynamics in PMMA-LiClO4 based polymer electrolytes plasticized with different plasticizers

NASA Astrophysics Data System (ADS)

Pal, P.; Ghosh, A.

2017-07-01

We have studied the charge carrier dynamics in poly(methylmethacrylate)-LiClO4 polymer electrolytes plasticized with different plasticizers such as ethylene carbonate (EC), propylene carbonate (PC), polyethylene glycol (PEG), and dimethyl carbonate (DMC). We have measured the broadband complex conductivity spectra of these electrolytes in the frequency range of 0.01 Hz-3 GHz and in the temperature range of 203 K-363 K and analyzed the conductivity spectra in the framework of the random barrier model by taking into account the contribution of the electrode polarization observed at low frequencies and/or at high temperatures. It is observed that the temperature dependences of the ionic conductivity and relaxation time follow the Vogel-Tammann-Fulcher relation for all plasticized electrolytes. We have also performed the scaling of the conductivity spectra, which indicates that the charge carrier dynamics is almost independent of temperature and plasticizers in a limited frequency range. The existence of nearly constant loss in these electrolytes has been observed at low temperatures and/or high frequencies. We have studied the dielectric relaxation in these electrolytes using electric modulus formalism and obtained the stretched exponent and the decay function. We have observed less cooperative ion dynamics in electrolytes plasticized with DMC compared to electrolytes plasticized with EC, PC, and PEG.

Mechanisms of Neuroplasticity and Ethanol’s Effects on Plasticity in the Striatum and Bed Nucleus of the Stria Terminalis

PubMed Central

Lovinger, David M.; Kash, Thomas L.

2015-01-01

Long-lasting changes in synaptic function (i.e., synaptic plasticity) have long been thought to contribute to information storage in the nervous system. Although synaptic plasticity mainly has adaptive functions that allow the organism to function in complex environments, it is now clear that certain events or exposure to various substances can produce plasticity that has negative consequences for organisms. Exposure to drugs of abuse, in particular ethanol, is a life experience that can activate or alter synaptic plasticity, often resulting in increased drug seeking and taking and in many cases addiction. Two brain regions subject to alcohol’s effects on synaptic plasticity are the striatum and bed nucleus of the stria terminalis (BNST), both of which have key roles in alcohol’s actions and control of intake. The specific effects depend on both the brain region analyzed (e.g., specific subregions of the striatum and BNST) and the duration of ethanol exposure (i.e., acute vs. chronic). Plastic changes in synaptic transmission in these two brain regions following prolonged ethanol exposure are thought to contribute to excessive alcohol drinking and relapse to drinking. Understanding the mechanisms underlying this plasticity may lead to new therapies for treatment of these and other aspects of alcohol use disorder. PMID:26259092

Genetic evolution, plasticity, and bet-hedging as adaptive responses to temporally autocorrelated fluctuating selection: A quantitative genetic model.

PubMed

Tufto, Jarle

2015-08-01

Adaptive responses to autocorrelated environmental fluctuations through evolution in mean reaction norm elevation and slope and an independent component of the phenotypic variance are analyzed using a quantitative genetic model. Analytic approximations expressing the mutual dependencies between all three response modes are derived and solved for the joint evolutionary outcome. Both genetic evolution in reaction norm elevation and plasticity are favored by slow temporal fluctuations, with plasticity, in the absence of microenvironmental variability, being the dominant evolutionary outcome for reasonable parameter values. For fast fluctuations, tracking of the optimal phenotype through genetic evolution and plasticity is limited. If residual fluctuations in the optimal phenotype are large and stabilizing selection is strong, selection then acts to increase the phenotypic variance (bet-hedging adaptive). Otherwise, canalizing selection occurs. If the phenotypic variance increases with plasticity through the effect of microenvironmental variability, this shifts the joint evolutionary balance away from plasticity in favor of genetic evolution. If microenvironmental deviations experienced by each individual at the time of development and selection are correlated, however, more plasticity evolves. The adaptive significance of evolutionary fluctuations in plasticity and the phenotypic variance, transient evolution, and the validity of the analytic approximations are investigated using simulations. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

Stress Wave Propagation in Viscoelastic-Plastic Rock-Like Materials

PubMed Central

Lang, Liu; Song, KI-IL; Zhai, Yue; Lao, Dezheng; Lee, Hang-Lo

2016-01-01

Rock-like materials are composites that can be regarded as a mixture composed of elastic, plastic, and viscous components. They exhibit viscoelastic-plastic behavior under a high-strain-rate loading according to element model theory. This paper presents an analytical solution for stress wave propagation in viscoelastic-plastic rock-like materials under a high-strain-rate loading and verifies the solution through an experimental test. A constitutive equation of viscoelastic-plastic rock-like materials was first established, and then kinematic and kinetic equations were then solved to derive the analytic solution for stress wave propagation in viscoelastic-plastic rock-like materials. An experimental test using the SHPB (Split Hopkinson Pressure Bar) for a concrete specimen was conducted to obtain a stress-strain curve under a high-strain-rate loading. Inverse analysis based on differential evolution was conducted to estimate undetermined variables for constitutive equations. Finally, the relationship between the attenuation factor and the strain rate in viscoelastic-plastic rock-like materials was investigated. According to the results, the frequency of the stress wave, viscosity coefficient, modulus of elasticity, and density play dominant roles in the attenuation of the stress wave. The attenuation decreases with increasing strain rate, demonstrating strongly strain-dependent attenuation in viscoelastic-plastic rock-like materials. PMID:28773500

Transcriptional and Translational Plasticity in Rodent Urinary Bladder TRP Channels with Urinary Bladder Inflammation, Bladder Dysfunction or Postnatal Maturation

PubMed Central

Merrill, Liana; Girard, Beatrice M.; May, Victor; Vizzard, Margaret A.

2013-01-01

These studies examined transcriptional and translational plasticity of three transient receptor potential (TRP) channels (TRPA1, TRPV1, TRPV4) with established neuronal and non-neuronal expression and functional roles in the lower urinary tract. Mechanosensor and nociceptor roles in either physiological or pathological lower urinary tract states have been suggested for TRPA1, TRPV1 and TRPV4. We have previously demonstrated neurochemical, organizational and functional plasticity in micturition reflex pathways following induction of urinary bladder inflammation using the antineoplastic agent, cyclophosphamide (CYP). More recently, we have characterized similar plasticity in micturition reflex pathways in a transgenic mouse model with chronic urothelial overexpression (OE) of nerve growth factor (NGF) and in a transgenic mouse model with deletion of vasoactive intestinal polypeptide (VIP). In addition, the micturition reflex undergoes postnatal maturation that may also reflect plasticity in urinary bladder TRP channel expression. Thus, we examined plasticity in urinary bladder TRP channel expression in diverse contexts using a combination of quantitative, real-time PCR and western blotting approaches. We demonstrate transcriptional and translational plasticity of urinary bladder TRPA1, TRPV1 and TRVP4 expression. Although the functional significance of urinary bladder TRP channel plasticity awaits further investigation, these studies demonstrate context-(inflammation, postnatal development, NGF-OE, VIP deletion) and tissue-dependent (urothelium + suburothelium, detrusor) plasticity. PMID:22865090

Structural Synaptic Plasticity Has High Memory Capacity and Can Explain Graded Amnesia, Catastrophic Forgetting, and the Spacing Effect

PubMed Central

Knoblauch, Andreas; Körner, Edgar; Körner, Ursula; Sommer, Friedrich T.

2014-01-01

Although already William James and, more explicitly, Donald Hebb's theory of cell assemblies have suggested that activity-dependent rewiring of neuronal networks is the substrate of learning and memory, over the last six decades most theoretical work on memory has focused on plasticity of existing synapses in prewired networks. Research in the last decade has emphasized that structural modification of synaptic connectivity is common in the adult brain and tightly correlated with learning and memory. Here we present a parsimonious computational model for learning by structural plasticity. The basic modeling units are “potential synapses” defined as locations in the network where synapses can potentially grow to connect two neurons. This model generalizes well-known previous models for associative learning based on weight plasticity. Therefore, existing theory can be applied to analyze how many memories and how much information structural plasticity can store in a synapse. Surprisingly, we find that structural plasticity largely outperforms weight plasticity and can achieve a much higher storage capacity per synapse. The effect of structural plasticity on the structure of sparsely connected networks is quite intuitive: Structural plasticity increases the “effectual network connectivity”, that is, the network wiring that specifically supports storage and recall of the memories. Further, this model of structural plasticity produces gradients of effectual connectivity in the course of learning, thereby explaining various cognitive phenomena including graded amnesia, catastrophic forgetting, and the spacing effect. PMID:24858841

Three dimensional grain boundary modeling in polycrystalline plasticity

NASA Astrophysics Data System (ADS)

Yalçinkaya, Tuncay; Özdemir, Izzet; Fırat, Ali Osman

2018-05-01

At grain scale, polycrystalline materials develop heterogeneous plastic deformation fields, localizations and stress concentrations due to variation of grain orientations, geometries and defects. Development of inter-granular stresses due to misorientation are crucial for a range of grain boundary (GB) related failure mechanisms, such as stress corrosion cracking (SCC) and fatigue cracking. Local crystal plasticity finite element modelling of polycrystalline metals at micron scale results in stress jumps at the grain boundaries. Moreover, the concepts such as the transmission of dislocations between grains and strength of the grain boundaries are not included in the modelling. The higher order strain gradient crystal plasticity modelling approaches offer the possibility of defining grain boundary conditions. However, these conditions are mostly not dependent on misorientation of grains and can define only extreme cases. For a proper definition of grain boundary behavior in plasticity, a model for grain boundary behavior should be incorporated into the plasticity framework. In this context, a particular grain boundary model ([l]) is incorporated into a strain gradient crystal plasticity framework ([2]). In a 3-D setting, both bulk and grain boundary models are implemented as user-defined elements in Abaqus. The strain gradient crystal plasticity model works in the bulk elements and considers displacements and plastic slips as degree of freedoms. Interface elements model the plastic slip behavior, yet they do not possess any kind of mechanical cohesive behavior. The physical aspects of grain boundaries and the performance of the model are addressed through numerical examples.

Gender Authorship Trends of Plastic Surgery Research in the United States.

PubMed

Silvestre, Jason; Wu, Liza C; Lin, Ines C; Serletti, Joseph M

2016-07-01

An increasing number of women are entering the medical profession, but plastic surgery remains a male-dominated profession, especially within academia. As academic aspirations and advancement depend largely on research productivity, the authors assessed the number of articles authored by women published in the journal Plastic and Reconstructive Surgery. Original articles in Plastic and Reconstructive Surgery published during the years 1970, 1980, 1990, 2000, 2004, and 2014 were analyzed. First and senior authors with an M.D. degree and U.S. institutional affiliation were categorized by gender. Authorship trends were compared with those from other specialties. Findings were placed in the context of gender trends among plastic surgery residents in the United States. The percentage of female authors in Plastic and Reconstructive Surgery increased from 2.4 percent in 1970 to 13.3 percent in 2014. Over the same time period, the percentage of female plastic surgery residents increased from 2.6 percent to 32.5 percent. By 2014, there were more female first authors (19.1 percent) than senior authors (7.7 percent) (p < 0.001). As a field, plastic surgery had fewer female authors than other medical specialties including pediatrics, obstetrics and gynecology, general surgery, internal medicine, and radiation oncology (p < 0.05). The increase in representation of female authors in plastic surgery is encouraging but lags behind advances in other specialties. Understanding reasons for these trends may help improve gender equity in academic plastic surgery.

Simulation of finite-strain inelastic phenomena governed by creep and plasticity

NASA Astrophysics Data System (ADS)

Li, Zhen; Bloomfield, Max O.; Oberai, Assad A.

2017-11-01

Inelastic mechanical behavior plays an important role in many applications in science and engineering. Phenomenologically, this behavior is often modeled as plasticity or creep. Plasticity is used to represent the rate-independent component of inelastic deformation and creep is used to represent the rate-dependent component. In several applications, especially those at elevated temperatures and stresses, these processes occur simultaneously. In order to model these process, we develop a rate-objective, finite-deformation constitutive model for plasticity and creep. The plastic component of this model is based on rate-independent J_2 plasticity, and the creep component is based on a thermally activated Norton model. We describe the implementation of this model within a finite element formulation, and present a radial return mapping algorithm for it. This approach reduces the additional complexity of modeling plasticity and creep, over thermoelasticity, to just solving one nonlinear scalar equation at each quadrature point. We implement this algorithm within a multiphysics finite element code and evaluate the consistent tangent through automatic differentiation. We verify and validate the implementation, apply it to modeling the evolution of stresses in the flip chip manufacturing process, and test its parallel strong-scaling performance.

IGF-1 Restores Visual Cortex Plasticity in Adult Life by Reducing Local GABA Levels

PubMed Central

Maya-Vetencourt, José Fernando; Baroncelli, Laura; Viegi, Alessandro; Tiraboschi, Ettore; Castren, Eero; Cattaneo, Antonino; Maffei, Lamberto

2012-01-01

The central nervous system architecture is markedly modified by sensory experience during early life, but a decline of plasticity occurs with age. Recent studies have challenged this dogma providing evidence that both pharmacological treatments and paradigms based on the manipulation of environmental stimulation levels can be successfully employed as strategies for enhancing plasticity in the adult nervous system. Insulin-like growth factor 1 (IGF-1) is a peptide implicated in prenatal and postnatal phases of brain development such as neurogenesis, neuronal differentiation, synaptogenesis, and experience-dependent plasticity. Here, using the visual system as a paradigmatic model, we report that IGF-1 reactivates neural plasticity in the adult brain. Exogenous administration of IGF-1 in the adult visual cortex, indeed, restores the susceptibility of cortical neurons to monocular deprivation and promotes the recovery of normal visual functions in adult amblyopic animals. These effects were accompanied by a marked reduction of intracortical GABA levels. Moreover, we show that a transitory increase of IGF-1 expression is associated to the plasticity reinstatement induced by environmental enrichment (EE) and that blocking IGF-1 action by means of the IGF-1 receptor antagonist JB1 prevents EE effects on plasticity processes. PMID:22720172

The relative importance of genetic and nongenetic inheritance in relation to trait plasticity in Callosobruchus maculatus.

PubMed

Hallsson, L R; Chenoweth, S F; Bonduriansky, R

2012-12-01

A trait's response to natural selection will reflect the nature of the inheritance mechanisms that mediate the transmission of variation across generations. The relative importance of genetic and nongenetic mechanisms of inheritance is predicted to be related to the degree of trait plasticity, with nongenetic inheritance playing a greater role in the cross-generational transmission of more plastic traits. However, this prediction has never been tested. We investigated the influence of genetic effects and nongenetic parental effects in two morphological traits differing in degree of plasticity by manipulating larval diet quality within a cross-generational split-brood experiment using the seed beetle Callososbuchus maculatus. In line with predictions, we found that the more plastic trait (elytron length) is strongly influenced by both maternal and paternal effects whereas genetic variance is undetectable. In contrast, the less plastic trait (first abdominal sternite length) is not influenced by parental effects but exhibits abundant genetic variance. Our findings support the hypothesis that environment-dependent parental effects may play a particularly important role in highly plastic traits and thereby affect the evolutionary response of such traits. © 2012 The Authors. Journal of Evolutionary Biology © 2012 European Society For Evolutionary Biology.

Visual Cortex Plasticity: A Complex Interplay of Genetic and Environmental Influences

PubMed Central

Maya-Vetencourt, José Fernando; Origlia, Nicola

2012-01-01

The central nervous system architecture is highly dynamic and continuously modified by sensory experience through processes of neuronal plasticity. Plasticity is achieved by a complex interplay of environmental influences and physiological mechanisms that ultimately activate intracellular signal transduction pathways regulating gene expression. In addition to the remarkable variety of transcription factors and their combinatorial interaction at specific gene promoters, epigenetic mechanisms that regulate transcription have emerged as conserved processes by which the nervous system accomplishes the induction of plasticity. Experience-dependent changes of DNA methylation patterns and histone posttranslational modifications are, in fact, recruited as targets of plasticity-associated signal transduction mechanisms. Here, we shall concentrate on structural and functional consequences of early sensory deprivation in the visual system and discuss how intracellular signal transduction pathways associated with experience regulate changes of chromatin structure and gene expression patterns that underlie these plastic phenomena. Recent experimental evidence for mechanisms of cross-modal plasticity following congenital or acquired sensory deprivation both in human and animal models will be considered as well. We shall also review different experimental strategies that can be used to achieve the recovery of sensory functions after long-term deprivation in humans. PMID:22852098

The eIF2a Kinase PERK Limits the Expression of Hippocampal Metabotropic Glutamate Receptor-Dependent Long-Term Depression

ERIC Educational Resources Information Center

Trinh, Mimi A.; Ma, Tao; Kaphzan, Hanoch; Bhattacharya, Aditi; Antion, Marcia D.; Cavener, Douglas R.; Hoeffer, Charles A.; Klann, Eric

2014-01-01

The proper regulation of translation is required for the expression of long-lasting synaptic plasticity. A major site of translational control involves the phosphorylation of eukaryotic initiation factor 2 a (eIF2a) by PKR-like endoplasmic reticulum (ER) kinase (PERK). To determine the role of PERK in hippocampal synaptic plasticity, we used the…

Physicomechanical Characteristics of Spray-On Rigid Polyurethane Foams at Normal and Low Temperatures

NASA Astrophysics Data System (ADS)

Yakushin, V. A.; Zhmud', N. P.; Stirna, U. K.

2002-05-01

The effect of processing factors on the inhomogeneity and physicomechanical characteristics of spray-on polyurethane foams is studied. The dependences of the basic characteristics of foam plastics on the apparent density and cell-shape factor are determined. A method is offered for evaluating the effect of the technological surface skin on the tensile characteristics of foam plastics under normal and low temperatures.

Numerical analysis of the effect of surface roughness on mechanical fields in polycrystalline aggregates

NASA Astrophysics Data System (ADS)

Guilhem, Yoann; Basseville, Stéphanie; Curtit, François; Stéphan, Jean-Michel; Cailletaud, Georges

2018-06-01

This paper is dedicated to the study of the influence of surface roughness on local stress and strain fields in polycrystalline aggregates. Finite element computations are performed with a crystal plasticity model on a 316L stainless steel polycrystalline material element with different roughness states on its free surface. The subsequent analysis of the plastic strain localization patterns shows that surface roughness strongly affects the plastic strain localization induced by crystallography. Nevertheless, this effect mainly takes place at the surface and vanishes under the first layer of grains, which implies the existence of a critical perturbed depth. A statistical analysis based on the plastic strain distribution obtained for different roughness levels provides a simple rule to define the size of the affected zone depending on the rough surface parameters.

The synaptic plasticity and memory hypothesis: encoding, storage and persistence

PubMed Central

Takeuchi, Tomonori; Duszkiewicz, Adrian J.; Morris, Richard G. M.

2014-01-01

The synaptic plasticity and memory hypothesis asserts that activity-dependent synaptic plasticity is induced at appropriate synapses during memory formation and is both necessary and sufficient for the encoding and trace storage of the type of memory mediated by the brain area in which it is observed. Criteria for establishing the necessity and sufficiency of such plasticity in mediating trace storage have been identified and are here reviewed in relation to new work using some of the diverse techniques of contemporary neuroscience. Evidence derived using optical imaging, molecular-genetic and optogenetic techniques in conjunction with appropriate behavioural analyses continues to offer support for the idea that changing the strength of connections between neurons is one of the major mechanisms by which engrams are stored in the brain. PMID:24298167

Loss of Tsc1 in vivo impairs hippocampal mGluR-LTD and increases excitatory synaptic function.

PubMed

Bateup, Helen S; Takasaki, Kevin T; Saulnier, Jessica L; Denefrio, Cassandra L; Sabatini, Bernardo L

2011-06-15

The autism spectrum disorder tuberous sclerosis complex (TSC) is caused by mutations in the Tsc1 or Tsc2 genes, whose protein products form a heterodimeric complex that negatively regulates mammalian target of rapamycin-dependent protein translation. Although several forms of synaptic plasticity, including metabotropic glutamate receptor (mGluR)-dependent long-term depression (LTD), depend on protein translation at the time of induction, it is unknown whether these forms of plasticity require signaling through the Tsc1/2 complex. To examine this possibility, we postnatally deleted Tsc1 in vivo in a subset of hippocampal CA1 neurons using viral delivery of Cre recombinase in mice. We found that hippocampal mGluR-LTD was abolished by loss of Tsc1, whereas a protein synthesis-independent form of NMDA receptor-dependent LTD was preserved. Additionally, AMPA and NMDA receptor-mediated EPSCs and miniature spontaneous EPSC frequency were enhanced in Tsc1 KO neurons. These changes in synaptic function occurred in the absence of alterations in spine density, morphology, or presynaptic release probability. Our findings indicate that signaling through Tsc1/2 is required for the expression of specific forms of hippocampal synaptic plasticity as well as the maintenance of normal excitatory synaptic strength. Furthermore, these data suggest that perturbations of synaptic signaling may contribute to the pathogenesis of TSC.

A saturation hypothesis to explain both enhanced and impaired learning with enhanced plasticity

PubMed Central

Nguyen-Vu, TD Barbara; Zhao, Grace Q; Lahiri, Subhaneil; Kimpo, Rhea R; Lee, Hanmi; Ganguli, Surya; Shatz, Carla J; Raymond, Jennifer L

2017-01-01

Across many studies, animals with enhanced synaptic plasticity exhibit either enhanced or impaired learning, raising a conceptual puzzle: how enhanced plasticity can yield opposite learning outcomes? Here, we show that the recent history of experience can determine whether mice with enhanced plasticity exhibit enhanced or impaired learning in response to the same training. Mice with enhanced cerebellar LTD, due to double knockout (DKO) of MHCI H2-Kb/H2-Db (KbDb−/−), exhibited oculomotor learning deficits. However, the same mice exhibited enhanced learning after appropriate pre-training. Theoretical analysis revealed that synapses with history-dependent learning rules could recapitulate the data, and suggested that saturation may be a key factor limiting the ability of enhanced plasticity to enhance learning. Optogenetic stimulation designed to saturate LTD produced the same impairment in WT as observed in DKO mice. Overall, our results suggest that the recent history of activity and the threshold for synaptic plasticity conspire to effect divergent learning outcomes. DOI: http://dx.doi.org/10.7554/eLife.20147.001 PMID:28234229

DOE Office of Scientific and Technical Information (OSTI.GOV)

Guney, Ali; Poyraz, M. Ibrahim; Kangal, Olgac, E-mail: kangal@itu.edu.tr

Highlights: • Both PET and PVC have nearly the same densities. • The best pH value will be 4 for optimizing pH values. • Malic acid gave the best results for selective separation of PET and PVC. - Abstract: Plastics have become the widely used materials because of their advantages, such as cheapness, endurance, lightness, and hygiene. However, they cause waste and soil pollution and they do not easily decompose. Many promising technologies are being investigated for separating mixed thermoplastics, but they are still uneconomical and unreliable. Depending on their surface characteristics, these plastics can be separated from each othermore » by flotation method which is useful mineral processing technique with its low cost and simplicity. The main objective of this study is to investigate the flotation characteristics of PET and PVC and determine the effect of plasticizer reagents on efficient plastic separation. For that purpose, various parameters such as pH, plasticizer concentration, plasticizer type, conditioning temperature and thermal conditioning were investigated. As a result, PET particles were floated with 95.1% purity and 65.3% efficiency while PVC particles were obtained with 98.1% purity and 65.3% efficiency.« less

Evaluation of a disposable plastic Neubauer counting chamber for semen analysis.

PubMed

Kirkman-Brown, Jackson; Björndahl, Lars

2009-02-01

To evaluate whether disposable plastic counting chambers effectively could replace nondisposable, time-consuming, and potentially dangerous glass hemocytometers. Evaluation of equipment in modern laboratory andrology. Comparison of results obtained with plastic chambers with results obtained with "gold-standard" glass hemocytometer counts. Diagnostic laboratory for andrology. Twenty-one patients undergoing investigation for infertility problems. No interventions with patients; sperm in diluted semen samples were used when patients had allowed the use for research and training. Sperm concentration, difference from results obtained with standard equipment. In the first three experimental series, with use of standard routine phase-contrast microscopy, significantly lower count results were obtained consistently from the plastic chambers than from standard chambers. In the fourth series, with use of specialized equipment, equivalent results were obtained but with a considerably greater time commitment because of difficulties in distinguishing sperm adjacent to the gridlines in the plastic chambers. The plastic disposable chamber type was not suitable for routine semen analysis because results are variable depending on the microscope used, and increased time is necessary to do the assessment accurately.

Developmental phenotypic plasticity helps bridge stochastic weather events associated with climate change.

PubMed

Burggren, Warren

2018-05-10

The slow, inexorable rise in annual average global temperatures and acidification of the oceans are often advanced as consequences of global change. However, many environmental changes, especially those involving weather (as opposed to climate), are often stochastic, variable and extreme, particularly in temperate terrestrial or freshwater habitats. Moreover, few studies of animal and plant phenotypic plasticity employ realistic (i.e. short-term, stochastic) environmental change in their protocols. Here, I posit that the frequently abrupt environmental changes (days, weeks, months) accompanying much longer-term general climate change (e.g. global warming over decades or centuries) require consideration of the true nature of environmental change (as opposed to statistical means) coupled with an expansion of focus to consider developmental phenotypic plasticity. Such plasticity can be in multiple forms - obligatory/facultative, beneficial/deleterious - depending upon the degree and rate of environmental variability at specific points in organismal development. Essentially, adult phenotypic plasticity, as important as it is, will be irrelevant if developing offspring lack sufficient plasticity to create modified phenotypes necessary for survival. © 2018. Published by The Company of Biologists Ltd.

Plasticity in Major Ampullate Silk Production in Relation to Spider Phylogeny and Ecology

PubMed Central

Boutry, Cecilia; Řezáč, Milan; Blackledge, Todd Alan

2011-01-01

Spider major ampullate silk is a high-performance biomaterial that has received much attention. However, most studies ignore plasticity in silk properties. A better understanding of silk plasticity could clarify the relative importance of chemical composition versus processing of silk dope for silk properties. It could also provide insight into how control of silk properties relates to spider ecology and silk uses. We compared silk plasticity (defined as variation in the properties of silk spun by a spider under different conditions) between three spider clades in relation to their anatomy and silk biochemistry. We found that silk plasticity exists in RTA clade and orbicularian spiders, two clades that differ in their silk biochemistry. Orbiculariae seem less dependent on external spinning conditions. They probably use a valve in their spinning duct to control friction forces and speed during spinning. Our results suggest that plasticity results from different processing of the silk dope in the spinning duct. Orbicularian spiders seem to display better control of silk properties, perhaps in relation to their more complex spinning duct valve. PMID:21818328

Advances in Discrete Dislocation Dynamics Modeling of Size-Affected Plasticity

NASA Astrophysics Data System (ADS)

El-Awady, Jaafar A.; Fan, Haidong; Hussein, Ahmed M.

In dislocation-mediated plasticity of crystalline materials, discrete dislocation dynamics (DDD) methods have been widely used to predict the plastic deformation in a number of technologically important problems. These simulations have led to significant improvement in the understanding of the different mechanism that controls the mechanical properties of crystalline materials, which can greatly accelerate the future development of materials with superior properties. This chapter provides an overview of different practical applications of both two-dimensional and three-dimensional DDD simulations in the field of size-affected dislocation-mediated plasticity. The chapter is divided into two major tracks. First, DDD simulations focusing on aspects of modeling size-dependent plasticity in single crystals in uniaxial micro-compression/tension, microtorsion, microbending, and nanoindentation are discussed. Special attention is directed towards the role of cross-slip and dislocation nucleation on the overall response. Second, DDD simulations focusing on the role of interfaces, including grain and twin boundaries, on dislocation-mediated plasticity are discussed. Finally, a number of challenges that are withholding DDD simulations from reaching their full potential are discussed.

Long-Term Plasticity of Neurotransmitter Release: Emerging Mechanisms and Contributions to Brain Function and Disease.

PubMed

Monday, Hannah R; Younts, Thomas J; Castillo, Pablo E

2018-04-25

Long-lasting changes of brain function in response to experience rely on diverse forms of activity-dependent synaptic plasticity. Chief among them are long-term potentiation and long-term depression of neurotransmitter release, which are widely expressed by excitatory and inhibitory synapses throughout the central nervous system and can dynamically regulate information flow in neural circuits. This review article explores recent advances in presynaptic long-term plasticity mechanisms and contributions to circuit function. Growing evidence indicates that presynaptic plasticity may involve structural changes, presynaptic protein synthesis, and transsynaptic signaling. Presynaptic long-term plasticity can alter the short-term dynamics of neurotransmitter release, thereby contributing to circuit computations such as novelty detection, modifications of the excitatory/inhibitory balance, and sensory adaptation. In addition, presynaptic long-term plasticity underlies forms of learning and its dysregulation participates in several neuropsychiatric conditions, including schizophrenia, autism, intellectual disabilities, neurodegenerative diseases, and drug abuse. Expected final online publication date for the Annual Review of Neuroscience Volume 41 is July 8, 2018. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Using Education as the Solution to Plastic Pollution. Plastic pollution is now considered one of the largest environmental threats facing humans and animals globally, yet our education system has not even embraced the concept. Teaching the next generation of leaders how to immediately start being the solution is vital to correcting the problem.

NASA Astrophysics Data System (ADS)

Ries, J.; Ries, C. A.; Ries, O. N.

2016-02-01

Plastic pollution can be found in virtually every body of water on this planet and as the number of people inhabiting this planet continues to spiral out of control, our acceptance and dependency on single use plastics grows exponentially. It is estimated that over 100,000 marine mammals and over 1-million seabirds die each year from ingesting plastic and now with the discovery of micro-beads in many or our day to day products, even the smallest of creatures are no longer safe… nor are we who depend on food from the oceans Current educational programs fail to teach the next generation of leaders how to deal with the issue of plastic pollution and no one is giving them the tools needed for families to start being the solution. The two young founders of One More Generation want to change all of that. They have authored an award winning Plastic and Recycling Awareness Curriculum, which has been written to match the latest National Standards for science, and they even have math, literacy and art infused throughout. The program is currently being evaluated by the US Department of State and has already been introduced in South Africa and thanks to a grant from Global Ocean UK, will soon be launched in their first school in the UK and Australia. The in-depth program is designed to make the students the teacher by providing them with knowledge on the issue that most parents are not even aware of. By doing so, the child is the one driving change in the household, which increases the `buy-in' from the parents, and results in immediate change throughout the community.

Age-Dependent Ocular Dominance Plasticity in Adult Mice

PubMed Central

Lehmann, Konrad; Löwel, Siegrid

2008-01-01

Background Short monocular deprivation (4 days) induces a shift in the ocular dominance of binocular neurons in the juvenile mouse visual cortex but is ineffective in adults. Recently, it has been shown that an ocular dominance shift can still be elicited in young adults (around 90 days of age) by longer periods of deprivation (7 days). Whether the same is true also for fully mature animals is not yet known. Methodology/Principal Findings We therefore studied the effects of different periods of monocular deprivation (4, 7, 14 days) on ocular dominance in C57Bl/6 mice of different ages (25 days, 90–100 days, 109–158 days, 208–230 days) using optical imaging of intrinsic signals. In addition, we used a virtual optomotor system to monitor visual acuity of the open eye in the same animals during deprivation. We observed that ocular dominance plasticity after 7 days of monocular deprivation was pronounced in young adult mice (90–100 days) but significantly weaker already in the next age group (109–158 days). In animals older than 208 days, ocular dominance plasticity was absent even after 14 days of monocular deprivation. Visual acuity of the open eye increased in all age groups, but this interocular plasticity also declined with age, although to a much lesser degree than the optically detected ocular dominance shift. Conclusions/Significance These data indicate that there is an age-dependence of both ocular dominance plasticity and the enhancement of vision after monocular deprivation in mice: ocular dominance plasticity in binocular visual cortex is most pronounced in young animals, reduced but present in adolescence and absent in fully mature animals older than 110 days of age. Mice are thus not basically different in ocular dominance plasticity from cats and monkeys which is an absolutely essential prerequisite for their use as valid model systems of human visual disorders. PMID:18769674

Activity-Dependent Exocytosis of Lysosomes Regulates the Structural Plasticity of Dendritic Spines.

PubMed

Padamsey, Zahid; McGuinness, Lindsay; Bardo, Scott J; Reinhart, Marcia; Tong, Rudi; Hedegaard, Anne; Hart, Michael L; Emptage, Nigel J

2017-01-04

Lysosomes have traditionally been viewed as degradative organelles, although a growing body of evidence suggests that they can function as Ca 2+ stores. Here we examined the function of these stores in hippocampal pyramidal neurons. We found that back-propagating action potentials (bpAPs) could elicit Ca 2+ release from lysosomes in the dendrites. This Ca 2+ release triggered the fusion of lysosomes with the plasma membrane, resulting in the release of Cathepsin B. Cathepsin B increased the activity of matrix metalloproteinase 9 (MMP-9), an enzyme involved in extracellular matrix (ECM) remodelling and synaptic plasticity. Inhibition of either lysosomal Ca 2+ signaling or Cathepsin B release prevented the maintenance of dendritic spine growth induced by Hebbian activity. This impairment could be rescued by exogenous application of active MMP-9. Our findings suggest that activity-dependent exocytosis of Cathepsin B from lysosomes regulates the long-term structural plasticity of dendritic spines by triggering MMP-9 activation and ECM remodelling. Crown Copyright © 2017. Published by Elsevier Inc. All rights reserved.

Using Inspiration from Synaptic Plasticity Rules to Optimize Traffic Flow in Distributed Engineered Networks.

PubMed

Suen, Jonathan Y; Navlakha, Saket

2017-05-01

Controlling the flow and routing of data is a fundamental problem in many distributed networks, including transportation systems, integrated circuits, and the Internet. In the brain, synaptic plasticity rules have been discovered that regulate network activity in response to environmental inputs, which enable circuits to be stable yet flexible. Here, we develop a new neuro-inspired model for network flow control that depends only on modifying edge weights in an activity-dependent manner. We show how two fundamental plasticity rules, long-term potentiation and long-term depression, can be cast as a distributed gradient descent algorithm for regulating traffic flow in engineered networks. We then characterize, both by simulation and analytically, how different forms of edge-weight-update rules affect network routing efficiency and robustness. We find a close correspondence between certain classes of synaptic weight update rules derived experimentally in the brain and rules commonly used in engineering, suggesting common principles to both.

Length-Scale Effects and Material Models at Numerical Simulations of Nanoindentation of A Metallic Alloy

NASA Astrophysics Data System (ADS)

Nikolov, N.; Avdjieva, T.; Altaparmakov, I.

2014-06-01

Some specially designed metallic alloys crystallize during process of rapid quenching which aims their amorphization. Nevertheless, change in their mechanical properties could be seen compared to these obtained during conventional technological regimes of cooling. That attracts the attention in this elaboration. Full 3-D numerical simulations of nanoindentation process of two material models are performed. The models reflect equivalent elastic and different plastic material properties. The plastic behaviour of the first one is subjected to yield criterion of Dracker-Prager and this of the second one to yield criterion of Mises. The reported numerical results depending on the nanoindentation scale length of 1000 nanometers, suggest different adequacy of the two yield criteria to the data obtained experimentally with a Zr-Al-Cu-Ni-Mo alloy. It could be speculated that the different effects developed depending on the indenter travel of 1000 nanometers and taken into account in the two yield criteria stand behind this fact and determinate three structural levels of plastic deformation.

Cerebellar Plasticity and Motor Learning Deficits in a Copy Number Variation Mouse Model of Autism

PubMed Central

Piochon, Claire; Kloth, Alexander D; Grasselli, Giorgio; Titley, Heather K; Nakayama, Hisako; Hashimoto, Kouichi; Wan, Vivian; Simmons, Dana H; Eissa, Tahra; Nakatani, Jin; Cherskov, Adriana; Miyazaki, Taisuke; Watanabe, Masahiko; Takumi, Toru; Kano, Masanobu; Wang, Samuel S-H; Hansel, Christian

2014-01-01

A common feature of autism spectrum disorder (ASD) is the impairment of motor control and learning, occurring in a majority of children with autism, consistent with perturbation in cerebellar function. Here we report alterations in motor behavior and cerebellar synaptic plasticity in a mouse model (patDp/+) for the human 15q11-13 duplication, one of the most frequently observed genetic aberrations in autism. These mice show ASD-resembling social behavior deficits. We find that in patDp/+ mice delay eyeblink conditioning—a form of cerebellum-dependent motor learning—is impaired, and observe deregulation of a putative cellular mechanism for motor learning, long-term depression (LTD) at parallel fiber-Purkinje cell synapses. Moreover, developmental elimination of surplus climbing fibers—a model for activity-dependent synaptic pruning—is impaired. These findings point to deficits in synaptic plasticity and pruning as potential causes for motor problems and abnormal circuit development in autism. PMID:25418414

Fibronectin domains of extracellular matrix molecule tenascin-C modulate hippocampal learning and synaptic plasticity.

PubMed

Strekalova, Tatyana; Sun, Mu; Sibbe, Mirjam; Evers, Matthias; Dityatev, Alexander; Gass, Peter; Schachner, Melitta

2002-09-01

The extracellular matrix molecule tenascin-C (TN-C) has been shown to be involved in hippocampal synaptic plasticity in vitro. Here, we describe a deficit in hippocampus-dependent contextual memory in TN-C-deficient mice using the step-down avoidance paradigm. We further show that a fragment of TN-C containing the fibronectin type-III repeats 6-8 (FN6-8), but not a fragment containing repeats 3-5, bound to pyramidal and granule cell somata in the hippocampal formation of C57BL/6J mice and repelled axons of pyramidal neurons when presented as a border in vitro. Injection of the FN6-8 fragment into the hippocampus inhibited retention of memory in the step-down paradigm and reduced levels of long-term potentiation in the CA1 region of the hippocampus. In summary, our data show that TN-C is involved in hippocampus-dependent contextual memory and synaptic plasticity and identify the FN6-8 domain as one of molecular determinants mediating these functions.

miR-191 and miR-135 are required for long-lasting spine remodelling associated with synaptic long-term depression

NASA Astrophysics Data System (ADS)

Hu, Zhonghua; Yu, Danni; Gu, Qin-Hua; Yang, Yanqin; Tu, Kang; Zhu, Jun; Li, Zheng

2014-02-01

Activity-dependent modification of dendritic spines, subcellular compartments accommodating postsynaptic specializations in the brain, is an important cellular mechanism for brain development, cognition and synaptic pathology of brain disorders. NMDA receptor-dependent long-term depression (NMDAR-LTD), a prototypic form of synaptic plasticity, is accompanied by prolonged remodelling of spines. The mechanisms underlying long-lasting spine remodelling in NMDAR-LTD, however, are largely unclear. Here we show that LTD induction causes global changes in miRNA transcriptomes affecting many cellular activities. Specifically, we show that expression changes of miR-191 and miR-135 are required for maintenance but not induction of spine restructuring. Moreover, we find that actin depolymerization and AMPA receptor exocytosis are regulated for extended periods of time by miRNAs to support long-lasting spine plasticity. These findings reveal a miRNA-mediated mechanism and a role for AMPA receptor exocytosis in long-lasting spine plasticity, and identify a number of candidate miRNAs involved in LTD.

GABAB receptor-mediated, layer-specific synaptic plasticity reorganizes gamma-frequency neocortical response to stimulation

PubMed Central

Ainsworth, Matthew; Lee, Shane; Kaiser, Marcus; Simonotto, Jennifer; Kopell, Nancy J.

2016-01-01

Repeated presentations of sensory stimuli generate transient gamma-frequency (30–80 Hz) responses in neocortex that show plasticity in a task-dependent manner. Complex relationships between individual neuronal outputs and the mean, local field potential (population activity) accompany these changes, but little is known about the underlying mechanisms responsible. Here we show that transient stimulation of input layer 4 sufficient to generate gamma oscillations induced two different, lamina-specific plastic processes that correlated with lamina-specific changes in responses to further, repeated stimulation: Unit rates and recruitment showed overall enhancement in supragranular layers and suppression in infragranular layers associated with excitatory or inhibitory synaptic potentiation onto principal cells, respectively. Both synaptic processes were critically dependent on activation of GABAB receptors and, together, appeared to temporally segregate the cortical representation. These data suggest that adaptation to repetitive sensory input dramatically alters the spatiotemporal properties of the neocortical response in a manner that may both refine and minimize cortical output simultaneously. PMID:27118845

GABAB receptor-mediated, layer-specific synaptic plasticity reorganizes gamma-frequency neocortical response to stimulation.

PubMed

Ainsworth, Matthew; Lee, Shane; Kaiser, Marcus; Simonotto, Jennifer; Kopell, Nancy J; Whittington, Miles A

2016-05-10

Repeated presentations of sensory stimuli generate transient gamma-frequency (30-80 Hz) responses in neocortex that show plasticity in a task-dependent manner. Complex relationships between individual neuronal outputs and the mean, local field potential (population activity) accompany these changes, but little is known about the underlying mechanisms responsible. Here we show that transient stimulation of input layer 4 sufficient to generate gamma oscillations induced two different, lamina-specific plastic processes that correlated with lamina-specific changes in responses to further, repeated stimulation: Unit rates and recruitment showed overall enhancement in supragranular layers and suppression in infragranular layers associated with excitatory or inhibitory synaptic potentiation onto principal cells, respectively. Both synaptic processes were critically dependent on activation of GABAB receptors and, together, appeared to temporally segregate the cortical representation. These data suggest that adaptation to repetitive sensory input dramatically alters the spatiotemporal properties of the neocortical response in a manner that may both refine and minimize cortical output simultaneously.

Experience-Dependent Plasticity in Accessory Olfactory Bulb Interneurons following Male-Male Social Interaction.

PubMed

Cansler, Hillary L; Maksimova, Marina A; Meeks, Julian P

2017-07-26

Chemosensory information processing in the mouse accessory olfactory system guides the expression of social behavior. After salient chemosensory encounters, the accessory olfactory bulb (AOB) experiences changes in the balance of excitation and inhibition at reciprocal synapses between mitral cells (MCs) and local interneurons. The mechanisms underlying these changes remain controversial. Moreover, it remains unclear whether MC-interneuron plasticity is unique to specific behaviors, such as mating, or whether it is a more general feature of the AOB circuit. Here, we describe targeted electrophysiological studies of AOB inhibitory internal granule cells (IGCs), many of which upregulate the immediate-early gene Arc after male-male social experience. Following the resident-intruder paradigm, Arc -expressing IGCs in acute AOB slices from resident males displayed stronger excitation than nonexpressing neighbors when sensory inputs were stimulated. The increased excitability of Arc -expressing IGCs was not correlated with changes in the strength or number of excitatory synapses with MCs but was instead associated with increased intrinsic excitability and decreased HCN channel-mediated I H currents. Consistent with increased inhibition by IGCs, MCs responded to sensory input stimulation with decreased depolarization and spiking following resident-intruder encounters. These results reveal that nonmating behaviors drive AOB inhibitory plasticity and indicate that increased MC inhibition involves intrinsic excitability changes in Arc -expressing interneurons. SIGNIFICANCE STATEMENT The accessory olfactory bulb (AOB) is a site of experience-dependent plasticity between excitatory mitral cells (MCs) and inhibitory internal granule cells (IGCs), but the physiological mechanisms and behavioral conditions driving this plasticity remain unclear. Here, we report studies of AOB neuronal plasticity following male-male social chemosensory encounters. We show that the plasticity-associated immediate-early gene Arc is selectively expressed in IGCs from resident males following the resident-intruder assay. After behavior, Arc -expressing IGCs are more strongly excited by sensory input stimulation and MC activation is suppressed. Arc -expressing IGCs do not show increased excitatory synaptic drive but instead show increased intrinsic excitability. These data indicate that MC-IGC plasticity is induced after male-male social chemosensory encounters, resulting in enhanced MC suppression by Arc -expressing IGCs. Copyright © 2017 the authors 0270-6474/17/377240-13$15.00/0.

Experience-Dependent Plasticity in Accessory Olfactory Bulb Interneurons following Male–Male Social Interaction

PubMed Central

Maksimova, Marina A.

2017-01-01

Chemosensory information processing in the mouse accessory olfactory system guides the expression of social behavior. After salient chemosensory encounters, the accessory olfactory bulb (AOB) experiences changes in the balance of excitation and inhibition at reciprocal synapses between mitral cells (MCs) and local interneurons. The mechanisms underlying these changes remain controversial. Moreover, it remains unclear whether MC–interneuron plasticity is unique to specific behaviors, such as mating, or whether it is a more general feature of the AOB circuit. Here, we describe targeted electrophysiological studies of AOB inhibitory internal granule cells (IGCs), many of which upregulate the immediate-early gene Arc after male–male social experience. Following the resident–intruder paradigm, Arc-expressing IGCs in acute AOB slices from resident males displayed stronger excitation than nonexpressing neighbors when sensory inputs were stimulated. The increased excitability of Arc-expressing IGCs was not correlated with changes in the strength or number of excitatory synapses with MCs but was instead associated with increased intrinsic excitability and decreased HCN channel-mediated IH currents. Consistent with increased inhibition by IGCs, MCs responded to sensory input stimulation with decreased depolarization and spiking following resident–intruder encounters. These results reveal that nonmating behaviors drive AOB inhibitory plasticity and indicate that increased MC inhibition involves intrinsic excitability changes in Arc-expressing interneurons. SIGNIFICANCE STATEMENT The accessory olfactory bulb (AOB) is a site of experience-dependent plasticity between excitatory mitral cells (MCs) and inhibitory internal granule cells (IGCs), but the physiological mechanisms and behavioral conditions driving this plasticity remain unclear. Here, we report studies of AOB neuronal plasticity following male–male social chemosensory encounters. We show that the plasticity-associated immediate-early gene Arc is selectively expressed in IGCs from resident males following the resident–intruder assay. After behavior, Arc-expressing IGCs are more strongly excited by sensory input stimulation and MC activation is suppressed. Arc-expressing IGCs do not show increased excitatory synaptic drive but instead show increased intrinsic excitability. These data indicate that MC–IGC plasticity is induced after male–male social chemosensory encounters, resulting in enhanced MC suppression by Arc-expressing IGCs. PMID:28659282

Separation of plastics by froth flotation. The role of size, shape and density of the particles.

PubMed

Pita, Fernando; Castilho, Ana

2017-02-01

Over the last few years, new methods for plastic separation in mining have been developed. Froth flotation is one of these techniques, which is based on hydrophobicity differences between particles. Unlike minerals, most of the plastics are naturally hydrophobic, thus requiring the addition of chemicals that promote the selective wettability of one of its components, for a flotation separation. The floatability of six granulated post-consumer plastic - Polystyrene (PS), Polymethyl methacrylate (PMMA), Polyethylene Terephthalate (PET-S, PET-D) and Polyvinyl Chloride (PVC-M, PVC-D) - in the presence of tannic acid (wetting agent), and the performance of the flotation separation of five bi-component plastic mixtures - PS/PMMA, PS/PET-S, PS/PET-D, PS/PVC-M and PS/PVC-D - were evaluated. Moreover, the effect of the contact angle, density, size and shape of the particles was also analysed. Results showed that all plastics were naturally hydrophobic, with PS exhibiting the highest floatability. The contact angle and the flotation recovery of six plastics decreased with increasing tannic acid concentration, occurring depression of plastics at very low concentrations. Floatability differed also with the size and shape of plastic particles. For regular-shaped plastics (PS, PMMA and PVC-D) floatability decreased with the increase of particle size, while for lamellar-shaped particles (PET-D) floatability was slightly greater for coarser particles. Thus, plastic particles with small size, lamellar shape and low density present a greater floatability. The quality of separation varied with the mixture type, depending not only on the plastics hydrophobicity, but also on the size, density and shape of the particles, i.e. the particle weight. Flotation separation of plastics can be enhanced by differences in hydrophobicity. In addition, flotation separation improves if the most hydrophobic plastic, that floats, has a lamellar shape and lower density and if the most hydrophilic plastic, that sinks, has a regular shape and higher density. The results obtained show that froth flotation is a potential method for plastics separation, in particular for plastics with particle size greater than 2.0mm. Copyright © 2016 Elsevier Ltd. All rights reserved.