Chemical synthesis and characterization of hollow dopamine coated, pentagonal and flower shaped magnetic iron oxide nanoparticles

Science.gov (United States)

Riasat, Rabia; Kaynat, Sumbal

2018-04-01

Iron oxide nanoparticles have gained attention recently in the field of nanoscience and technology due to their unique physicochemical properties. We hereby chemically synthesized novel pentagonal flower shaped iron oxide nanoparticles by thermal decomposition of iron penta-carbonyl in a two way annealing process. Controlled oxidation by acid etching was performed for these nanoparticles. At first 13 nm core shell nanoparticles of iron oxide (Fe/Fe3O4) were synthesized at 120°C annealing temperature that act as template material. The core shell nanoparticles then converted into porous hollow core shell nanoparticles (PH Fe/ Fe3O4) in a two way annealing process of heating, first at 100°C then at 250°C and heating rate of 5°C was kept constant throughout the reaction time. X-Ray diffraction (XRD) was done for the phase confirmation of as synthesized nanoparticles. Transmission electron microscopy (TEM) and higher resolution transmission electron microscopy (HRTEM) clearly shows the flower like nanoparticles that are approx. 16 nm-18 nm in size having the 4-5 nm core of Fe and 1-2 nm of the pores in the shell while the cavity between the shell and core is about 2 nm and the shell is 4-5 nm in diameter according to the TEM micrographs. The as prepared nanoparticles were then surface functionalized by dopamine polymer to make them water dispersible. Fourier transform Infrared spectroscopy confirmed the dopamine coating on the nanoparticles and the magnetic saturation of 38 emu/g of nanoparticles was analyzed by vibrating sample magnetometer (VSM). Magnetic saturation persists in the dopamine coated nanoparticles. These nanoparticles were surface functionalized with dopamine and show dispersity in the aqueous media and can further be exploited in many nano-biotechnological applications including target specific therapeutic applications for several diseases.

An Unsupervised Online Spike-Sorting Framework.

Science.gov (United States)

Knieling, Simeon; Sridharan, Kousik S; Belardinelli, Paolo; Naros, Georgios; Weiss, Daniel; Mormann, Florian; Gharabaghi, Alireza

2016-08-01

Extracellular neuronal microelectrode recordings can include action potentials from multiple neurons. To separate spikes from different neurons, they can be sorted according to their shape, a procedure referred to as spike-sorting. Several algorithms have been reported to solve this task. However, when clustering outcomes are unsatisfactory, most of them are difficult to adjust to achieve the desired results. We present an online spike-sorting framework that uses feature normalization and weighting to maximize the distinctiveness between different spike shapes. Furthermore, multiple criteria are applied to either facilitate or prevent cluster fusion, thereby enabling experimenters to fine-tune the sorting process. We compare our method to established unsupervised offline (Wave_Clus (WC)) and online (OSort (OS)) algorithms by examining their performance in sorting various test datasets using two different scoring systems (AMI and the Adamos metric). Furthermore, we evaluate sorting capabilities on intra-operative recordings using established quality metrics. Compared to WC and OS, our algorithm achieved comparable or higher scores on average and produced more convincing sorting results for intra-operative datasets. Thus, the presented framework is suitable for both online and offline analysis and could substantially improve the quality of microelectrode-based data evaluation for research and clinical application.

Dopamine-imprinted monolithic column for capillary electrochromatography.

Science.gov (United States)

Aşır, Süleyman; Sarı, Duygu; Derazshamshir, Ali; Yılmaz, Fatma; Şarkaya, Koray; Denizli, Adil

2017-11-01

A dopamine-imprinted monolithic column was prepared and used in capillary electrochromatography as stationary phase for the first time. Dopamine was selectively separated from aqueous solution containing the competitor molecule norepinephrine, which is similar in size and shape to the template molecule. Morphology of the dopamine-imprinted column was observed by scanning electron microscopy. The influence of the organic solvent content of mobile phase, applied pressure and pH of the mobile phase on the recognition of dopamine by the imprinted monolithic column has been evaluated, and the imprinting effect in the dopamine-imprinted monolithic polymer was verified. Developed dopamine-imprinted monolithic column resulted in excellent separation of dopamine from structurally related competitor molecule, norepinephrine. Separation was achieved in a short period of 10 min, with the electrophoretic mobility of 5.81 × 10 -5  m 2 V -1 s -1 at pH 5.0 and 500 mbar pressure. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Reinforcement learning using a continuous time actor-critic framework with spiking neurons.

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Nicolas Frémaux

2013-04-01

Full Text Available Animals repeat rewarded behaviors, but the physiological basis of reward-based learning has only been partially elucidated. On one hand, experimental evidence shows that the neuromodulator dopamine carries information about rewards and affects synaptic plasticity. On the other hand, the theory of reinforcement learning provides a framework for reward-based learning. Recent models of reward-modulated spike-timing-dependent plasticity have made first steps towards bridging the gap between the two approaches, but faced two problems. First, reinforcement learning is typically formulated in a discrete framework, ill-adapted to the description of natural situations. Second, biologically plausible models of reward-modulated spike-timing-dependent plasticity require precise calculation of the reward prediction error, yet it remains to be shown how this can be computed by neurons. Here we propose a solution to these problems by extending the continuous temporal difference (TD learning of Doya (2000 to the case of spiking neurons in an actor-critic network operating in continuous time, and with continuous state and action representations. In our model, the critic learns to predict expected future rewards in real time. Its activity, together with actual rewards, conditions the delivery of a neuromodulatory TD signal to itself and to the actor, which is responsible for action choice. In simulations, we show that such an architecture can solve a Morris water-maze-like navigation task, in a number of trials consistent with reported animal performance. We also use our model to solve the acrobot and the cartpole problems, two complex motor control tasks. Our model provides a plausible way of computing reward prediction error in the brain. Moreover, the analytically derived learning rule is consistent with experimental evidence for dopamine-modulated spike-timing-dependent plasticity.

AgRP neurons regulate development of dopamine neuronal plasticity and nonfood-associated behaviors

Science.gov (United States)

Dietrich, Marcelo O; Bober, Jeremy; Ferreira, Jozélia G; Tellez, Luis A; Mineur, Yann S; Souza, Diogo O; Gao, Xiao-Bing; Picciotto, Marina R; Araújo, Ivan; Liu, Zhong-Wu; Horvath, Tamas L

2012-01-01

It is not known whether behaviors unrelated to feeding are affected by hypothalamic regulators of hunger. We found that impairment of Agouti-related protein (AgRP) circuitry by either Sirt1 knockdown in AgRP-expressing neurons or early postnatal ablation of these neurons increased exploratory behavior and enhanced responses to cocaine. In AgRP circuit–impaired mice, ventral tegmental dopamine neurons exhibited enhanced spike timing–dependent long-term potentiation, altered amplitude of miniature postsynaptic currents and elevated dopamine in basal forebrain. Thus, AgRP neurons determine the set point of the reward circuitry and associated behaviors. PMID:22729177

Characterizing neural activities evoked by manual acupuncture through spiking irregularity measures

International Nuclear Information System (INIS)

Xue Ming; Wang Jiang; Deng Bin; Wei Xi-Le; Yu Hai-Tao; Chen Ying-Yuan

2013-01-01

The neural system characterizes information in external stimulations by different spiking patterns. In order to examine how neural spiking patterns are related to acupuncture manipulations, experiments are designed in such a way that different types of manual acupuncture (MA) manipulations are taken at the ‘Zusanli’ point of experimental rats, and the induced electrical signals in the spinal dorsal root ganglion are detected and recorded. The interspike interval (ISI) statistical histogram is fitted by the gamma distribution, which has two parameters: one is the time-dependent firing rate and the other is a shape parameter characterizing the spiking irregularities. The shape parameter is the measure of spiking irregularities and can be used to identify the type of MA manipulations. The coefficient of variation is mostly used to measure the spike time irregularity, but it overestimates the irregularity in the case of pronounced firing rate changes. However, experiments show that each acupuncture manipulation will lead to changes in the firing rate. So we combine four relatively rate-independent measures to study the irregularity of spike trains evoked by different types of MA manipulations. Results suggest that the MA manipulations possess unique spiking statistics and characteristics and can be distinguished according to the spiking irregularity measures. These studies have offered new insights into the coding processes and information transfer of acupuncture. (interdisciplinary physics and related areas of science and technology)

Dopamine

International Nuclear Information System (INIS)

Walters, L.

1983-01-01

Dopamine is an important neurotransmittor in the central nervous system. The physiological function of the peripheral dopamine receptors is unknown, but they are of therapeutic importance as dopamine is used to improve renal blood flow in shocked patients. There are 4 dopamine receptors. The classification of these dopamine receptors has been made possible by research with radiopharmaceuticals. Dopamine sensitive adenylate cyclase is an inherent part of the dopamine-1-receptor. Dopamine-1-receptors are stimulated by micromolar (physiological) concentrations of dopamine and inhibited by micromolar (supratherapeutic) concentrations of the antipsychotic drugs. The vascular effect of dopamine is mediated through the dopamine-1-receptors. Dopamine-2-receptors are responsible for the effect of dopamine at the mesolimbic, nigrostriatal and chemoreceptortrigger areas. It is activated by micromolar concentrations of dopamine and blocked by nanomolar (therapeutic) concentrations of the anti-psychotic drugs. Dopamine-3-receptors are activated by nanomolar concentrations of dopamine and inhibited by micromolar concentrations of the antipsychotic drugs. They occur on presynaptic nerve terminals and have a negative feedback effect on the liberation of dopamine, noradrenaline and serotonin. The dopamine-4-receptors are activated by nanomolar concentrations of dopamine. These are the only dopamine receptors that could be responsible for effects in the hypophysis as only nanomolar concentrations of dopamine occur there. These receptors are blocked by nanomolar concentrations of the antipsychotic drugs

Reinforcement learning of targeted movement in a spiking neuronal model of motor cortex.

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George L Chadderdon

Full Text Available Sensorimotor control has traditionally been considered from a control theory perspective, without relation to neurobiology. In contrast, here we utilized a spiking-neuron model of motor cortex and trained it to perform a simple movement task, which consisted of rotating a single-joint "forearm" to a target. Learning was based on a reinforcement mechanism analogous to that of the dopamine system. This provided a global reward or punishment signal in response to decreasing or increasing distance from hand to target, respectively. Output was partially driven by Poisson motor babbling, creating stochastic movements that could then be shaped by learning. The virtual forearm consisted of a single segment rotated around an elbow joint, controlled by flexor and extensor muscles. The model consisted of 144 excitatory and 64 inhibitory event-based neurons, each with AMPA, NMDA, and GABA synapses. Proprioceptive cell input to this model encoded the 2 muscle lengths. Plasticity was only enabled in feedforward connections between input and output excitatory units, using spike-timing-dependent eligibility traces for synaptic credit or blame assignment. Learning resulted from a global 3-valued signal: reward (+1, no learning (0, or punishment (-1, corresponding to phasic increases, lack of change, or phasic decreases of dopaminergic cell firing, respectively. Successful learning only occurred when both reward and punishment were enabled. In this case, 5 target angles were learned successfully within 180 s of simulation time, with a median error of 8 degrees. Motor babbling allowed exploratory learning, but decreased the stability of the learned behavior, since the hand continued moving after reaching the target. Our model demonstrated that a global reinforcement signal, coupled with eligibility traces for synaptic plasticity, can train a spiking sensorimotor network to perform goal-directed motor behavior.

Reinforcement learning of targeted movement in a spiking neuronal model of motor cortex.

Science.gov (United States)

Chadderdon, George L; Neymotin, Samuel A; Kerr, Cliff C; Lytton, William W

2012-01-01

Sensorimotor control has traditionally been considered from a control theory perspective, without relation to neurobiology. In contrast, here we utilized a spiking-neuron model of motor cortex and trained it to perform a simple movement task, which consisted of rotating a single-joint "forearm" to a target. Learning was based on a reinforcement mechanism analogous to that of the dopamine system. This provided a global reward or punishment signal in response to decreasing or increasing distance from hand to target, respectively. Output was partially driven by Poisson motor babbling, creating stochastic movements that could then be shaped by learning. The virtual forearm consisted of a single segment rotated around an elbow joint, controlled by flexor and extensor muscles. The model consisted of 144 excitatory and 64 inhibitory event-based neurons, each with AMPA, NMDA, and GABA synapses. Proprioceptive cell input to this model encoded the 2 muscle lengths. Plasticity was only enabled in feedforward connections between input and output excitatory units, using spike-timing-dependent eligibility traces for synaptic credit or blame assignment. Learning resulted from a global 3-valued signal: reward (+1), no learning (0), or punishment (-1), corresponding to phasic increases, lack of change, or phasic decreases of dopaminergic cell firing, respectively. Successful learning only occurred when both reward and punishment were enabled. In this case, 5 target angles were learned successfully within 180 s of simulation time, with a median error of 8 degrees. Motor babbling allowed exploratory learning, but decreased the stability of the learned behavior, since the hand continued moving after reaching the target. Our model demonstrated that a global reinforcement signal, coupled with eligibility traces for synaptic plasticity, can train a spiking sensorimotor network to perform goal-directed motor behavior.

Statistical properties of superimposed stationary spike trains.

Science.gov (United States)

Deger, Moritz; Helias, Moritz; Boucsein, Clemens; Rotter, Stefan

2012-06-01

The Poisson process is an often employed model for the activity of neuronal populations. It is known, though, that superpositions of realistic, non- Poisson spike trains are not in general Poisson processes, not even for large numbers of superimposed processes. Here we construct superimposed spike trains from intracellular in vivo recordings from rat neocortex neurons and compare their statistics to specific point process models. The constructed superimposed spike trains reveal strong deviations from the Poisson model. We find that superpositions of model spike trains that take the effective refractoriness of the neurons into account yield a much better description. A minimal model of this kind is the Poisson process with dead-time (PPD). For this process, and for superpositions thereof, we obtain analytical expressions for some second-order statistical quantities-like the count variability, inter-spike interval (ISI) variability and ISI correlations-and demonstrate the match with the in vivo data. We conclude that effective refractoriness is the key property that shapes the statistical properties of the superposition spike trains. We present new, efficient algorithms to generate superpositions of PPDs and of gamma processes that can be used to provide more realistic background input in simulations of networks of spiking neurons. Using these generators, we show in simulations that neurons which receive superimposed spike trains as input are highly sensitive for the statistical effects induced by neuronal refractoriness.

Implementing Signature Neural Networks with Spiking Neurons.

Science.gov (United States)

Carrillo-Medina, José Luis; Latorre, Roberto

2016-01-01

Spiking Neural Networks constitute the most promising approach to develop realistic Artificial Neural Networks (ANNs). Unlike traditional firing rate-based paradigms, information coding in spiking models is based on the precise timing of individual spikes. It has been demonstrated that spiking ANNs can be successfully and efficiently applied to multiple realistic problems solvable with traditional strategies (e.g., data classification or pattern recognition). In recent years, major breakthroughs in neuroscience research have discovered new relevant computational principles in different living neural systems. Could ANNs benefit from some of these recent findings providing novel elements of inspiration? This is an intriguing question for the research community and the development of spiking ANNs including novel bio-inspired information coding and processing strategies is gaining attention. From this perspective, in this work, we adapt the core concepts of the recently proposed Signature Neural Network paradigm-i.e., neural signatures to identify each unit in the network, local information contextualization during the processing, and multicoding strategies for information propagation regarding the origin and the content of the data-to be employed in a spiking neural network. To the best of our knowledge, none of these mechanisms have been used yet in the context of ANNs of spiking neurons. This paper provides a proof-of-concept for their applicability in such networks. Computer simulations show that a simple network model like the discussed here exhibits complex self-organizing properties. The combination of multiple simultaneous encoding schemes allows the network to generate coexisting spatio-temporal patterns of activity encoding information in different spatio-temporal spaces. As a function of the network and/or intra-unit parameters shaping the corresponding encoding modality, different forms of competition among the evoked patterns can emerge even in the absence

How adaptation shapes spike rate oscillations in recurrent neuronal networks

Directory of Open Access Journals (Sweden)

Moritz eAugustin

2013-02-01

Full Text Available Neural mass signals from in-vivo recordings often show oscillations with frequencies ranging from <1 Hz to 100 Hz. Fast rhythmic activity in the beta and gamma range can be generated by network based mechanisms such as recurrent synaptic excitation-inhibition loops. Slower oscillations might instead depend on neuronal adaptation currents whose timescales range from tens of milliseconds to seconds. Here we investigate how the dynamics of such adaptation currents contribute to spike rate oscillations and resonance properties in recurrent networks of excitatory and inhibitory neurons. Based on a network of sparsely coupled spiking model neurons with two types of adaptation current and conductance based synapses with heterogeneous strengths and delays we use a mean-field approach to analyze oscillatory network activity. For constant external input, we find that spike-triggered adaptation currents provide a mechanism to generate slow oscillations over a wide range of adaptation timescales as long as recurrent synaptic excitation is sufficiently strong. Faster rhythms occur when recurrent inhibition is slower than excitation and oscillation frequency increases with the strength of inhibition. Adaptation facilitates such network based oscillations for fast synaptic inhibition and leads to decreased frequencies. For oscillatory external input, adaptation currents amplify a narrow band of frequencies and cause phase advances for low frequencies in addition to phase delays at higher frequencies. Our results therefore identify the different key roles of neuronal adaptation dynamics for rhythmogenesis and selective signal propagation in recurrent networks.

Salsolinol facilitates glutamatergic transmission to dopamine neurons in the posterior ventral tegmental area of rats.

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Guiqin Xie

Full Text Available Although in vivo evidence indicates that salsolinol, the condensation product of acetaldehyde and dopamine, has properties that may contribute to alcohol abuse, the underlying mechanisms have not been fully elucidated. We have reported previously that salsolinol stimulates dopamine neurons in the posterior ventral tegmental area (p-VTA partly by reducing inhibitory GABAergic transmission, and that ethanol increases glutamatergic transmission to VTA-dopamine neurons via the activation of dopamine D(1 receptors (D(1Rs. In this study, we tested the hypothesis that salsolinol stimulates dopamine neurons involving activation of D(1Rs. By using whole-cell recordings on p-VTA-dopamine neurons in acute brain slices of rats, we found that salsolinol-induced increase in spike frequency of dopamine neurons was substantially attenuated by DL-2-amino-5-phosphono-valeric acid and 6, 7-dinitroquinoxaline-2, 3-dione, the antagonists of glutamatergic N-Methyl-D-aspartic acid and α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors. Moreover, salsolinol increased the amplitude of evoked excitatory postsynaptic currents (EPSCs and the frequency but not the amplitude of spontaneous EPSCs. Additionally, SKF83566, a D(1R antagonist attenuated the salsolinol-induced facilitation of EPSCs and of spontaneous firing of dopamine neurons. Our data reveal that salsolinol enhances glutamatergic transmission onto dopamine neurons via activation of D(1Rs at the glutamatergic afferents in dopamine neurons, which contributes to salsolinol's stimulating effect on p-VTA dopamine neurons. This appears to be a novel mechanism which contributes toward rewarding properties of salsolinol.

Striatal dopamine release codes uncertainty in pathological gambling

DEFF Research Database (Denmark)

Linnet, Jakob; Mouridsen, Kim; Peterson, Ericka

2012-01-01

Two mechanisms of midbrain and striatal dopaminergic projections may be involved in pathological gambling: hypersensitivity to reward and sustained activation toward uncertainty. The midbrain—striatal dopamine system distinctly codes reward and uncertainty, where dopaminergic activation is a linear...... function of expected reward and an inverse U-shaped function of uncertainty. In this study, we investigated the dopaminergic coding of reward and uncertainty in 18 pathological gambling sufferers and 16 healthy controls. We used positron emission tomography (PET) with the tracer [11C]raclopride to measure...... dopamine release, and we used performance on the Iowa Gambling Task (IGT) to determine overall reward and uncertainty. We hypothesized that we would find a linear function between dopamine release and IGT performance, if dopamine release coded reward in pathological gambling. If, on the other hand...

Striatal dopamine release codes uncertainty in pathological gambling

DEFF Research Database (Denmark)

Linnet, Jakob; Mouridsen, Kim; Peterson, Ericka

2012-01-01

Two mechanisms of midbrain and striatal dopaminergic projections may be involved in pathological gambling: hypersensitivity to reward and sustained activation toward uncertainty. The midbrain-striatal dopamine system distinctly codes reward and uncertainty, where dopaminergic activation is a linear...... function of expected reward and an inverse U-shaped function of uncertainty. In this study, we investigated the dopaminergic coding of reward and uncertainty in 18 pathological gambling sufferers and 16 healthy controls. We used positron emission tomography (PET) with the tracer [(11)C......]raclopride to measure dopamine release, and we used performance on the Iowa Gambling Task (IGT) to determine overall reward and uncertainty. We hypothesized that we would find a linear function between dopamine release and IGT performance, if dopamine release coded reward in pathological gambling. If, on the other hand...

Solving constraint satisfaction problems with networks of spiking neurons

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Zeno eJonke

2016-03-01

Full Text Available Network of neurons in the brain apply – unlike processors in our current generation ofcomputer hardware – an event-based processing strategy, where short pulses (spikes areemitted sparsely by neurons to signal the occurrence of an event at a particular point intime. Such spike-based computations promise to be substantially more power-efficient thantraditional clocked processing schemes. However it turned out to be surprisingly difficult todesign networks of spiking neurons that can solve difficult computational problems on the levelof single spikes (rather than rates of spikes. We present here a new method for designingnetworks of spiking neurons via an energy function. Furthermore we show how the energyfunction of a network of stochastically firing neurons can be shaped in a quite transparentmanner by composing the networks of simple stereotypical network motifs. We show that thisdesign approach enables networks of spiking neurons to produce approximate solutions todifficult (NP-hard constraint satisfaction problems from the domains of planning/optimizationand verification/logical inference. The resulting networks employ noise as a computationalresource. Nevertheless the timing of spikes (rather than just spike rates plays an essential rolein their computations. Furthermore, networks of spiking neurons carry out for the Traveling Salesman Problem a more efficient stochastic search for good solutions compared with stochastic artificial neural networks (Boltzmann machines and Gibbs sampling.

Solving Constraint Satisfaction Problems with Networks of Spiking Neurons.

Science.gov (United States)

Jonke, Zeno; Habenschuss, Stefan; Maass, Wolfgang

2016-01-01

Network of neurons in the brain apply-unlike processors in our current generation of computer hardware-an event-based processing strategy, where short pulses (spikes) are emitted sparsely by neurons to signal the occurrence of an event at a particular point in time. Such spike-based computations promise to be substantially more power-efficient than traditional clocked processing schemes. However, it turns out to be surprisingly difficult to design networks of spiking neurons that can solve difficult computational problems on the level of single spikes, rather than rates of spikes. We present here a new method for designing networks of spiking neurons via an energy function. Furthermore, we show how the energy function of a network of stochastically firing neurons can be shaped in a transparent manner by composing the networks of simple stereotypical network motifs. We show that this design approach enables networks of spiking neurons to produce approximate solutions to difficult (NP-hard) constraint satisfaction problems from the domains of planning/optimization and verification/logical inference. The resulting networks employ noise as a computational resource. Nevertheless, the timing of spikes plays an essential role in their computations. Furthermore, networks of spiking neurons carry out for the Traveling Salesman Problem a more efficient stochastic search for good solutions compared with stochastic artificial neural networks (Boltzmann machines) and Gibbs sampling.

Magnetic restricted-access microspheres for extraction of adrenaline, dopamine and noradrenaline from biological samples

International Nuclear Information System (INIS)

Xiao, Deli; Liu, Shubo; Liang, Liyun; Bi, Yanping

2016-01-01

Epoxy propyl bonded magnetic microspheres were prepared by atomic layer deposition using Fe 3 O 4 -SiO 2 microspheres as a core support material. Then, a restricted-access magnetic sorbent was prepared that contains diol groups on the external surface and m-aminophenylboronic acid groups on the internal surface. This kind of microspheres achieved excellent specific adsorption of the ortho-dihydroxy compounds (dopamine, adrenaline and noradrenaline). Following desorption with sorbitol, the ortho-dihydroxy compounds were quantified by HPLC. The limits of detection for dopamine, adrenaline and noradrenaline were 0.074, 0.053 and 0.095 μg mL −1 , respectively. Recoveries from spiked mice serum samples range from 80.2 to 89.1 %. (author)

Orthobunyavirus ultrastructure and the curious tripodal glycoprotein spike.

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Thomas A Bowden

Full Text Available The genus Orthobunyavirus within the family Bunyaviridae constitutes an expanding group of emerging viruses, which threaten human and animal health. Despite the medical importance, little is known about orthobunyavirus structure, a prerequisite for understanding virus assembly and entry. Here, using electron cryo-tomography, we report the ultrastructure of Bunyamwera virus, the prototypic member of this genus. Whilst Bunyamwera virions are pleomorphic in shape, they display a locally ordered lattice of glycoprotein spikes. Each spike protrudes 18 nm from the viral membrane and becomes disordered upon introduction to an acidic environment. Using sub-tomogram averaging, we derived a three-dimensional model of the trimeric pre-fusion glycoprotein spike to 3-nm resolution. The glycoprotein spike consists mainly of the putative class-II fusion glycoprotein and exhibits a unique tripod-like arrangement. Protein-protein contacts between neighbouring spikes occur at membrane-proximal regions and intra-spike contacts at membrane-distal regions. This trimeric assembly deviates from previously observed fusion glycoprotein arrangements, suggesting a greater than anticipated repertoire of viral fusion glycoprotein oligomerization. Our study provides evidence of a pH-dependent conformational change that occurs during orthobunyaviral entry into host cells and a blueprint for the structure of this group of emerging pathogens.

Spiking, Bursting, and Population Dynamics in a Network of Growth Transform Neurons.

Science.gov (United States)

Gangopadhyay, Ahana; Chakrabartty, Shantanu

2017-04-27

This paper investigates the dynamical properties of a network of neurons, each of which implements an asynchronous mapping based on polynomial growth transforms. In the first part of this paper, we present a geometric approach for visualizing the dynamics of the network where each of the neurons traverses a trajectory in a dual optimization space, whereas the network itself traverses a trajectory in an equivalent primal optimization space. We show that as the network learns to solve basic classification tasks, different choices of primal-dual mapping produce unique but interpretable neural dynamics like noise shaping, spiking, and bursting. While the proposed framework is general enough, in this paper, we demonstrate its use for designing support vector machines (SVMs) that exhibit noise-shaping properties similar to those of ΣΔ modulators, and for designing SVMs that learn to encode information using spikes and bursts. It is demonstrated that the emergent switching, spiking, and burst dynamics produced by each neuron encodes its respective margin of separation from a classification hyperplane whose parameters are encoded by the network population dynamics. We believe that the proposed growth transform neuron model and the underlying geometric framework could serve as an important tool to connect well-established machine learning algorithms like SVMs to neuromorphic principles like spiking, bursting, population encoding, and noise shaping.

Spike sorting based upon machine learning algorithms (SOMA).

Science.gov (United States)

Horton, P M; Nicol, A U; Kendrick, K M; Feng, J F

2007-02-15

We have developed a spike sorting method, using a combination of various machine learning algorithms, to analyse electrophysiological data and automatically determine the number of sampled neurons from an individual electrode, and discriminate their activities. We discuss extensions to a standard unsupervised learning algorithm (Kohonen), as using a simple application of this technique would only identify a known number of clusters. Our extra techniques automatically identify the number of clusters within the dataset, and their sizes, thereby reducing the chance of misclassification. We also discuss a new pre-processing technique, which transforms the data into a higher dimensional feature space revealing separable clusters. Using principal component analysis (PCA) alone may not achieve this. Our new approach appends the features acquired using PCA with features describing the geometric shapes that constitute a spike waveform. To validate our new spike sorting approach, we have applied it to multi-electrode array datasets acquired from the rat olfactory bulb, and from the sheep infero-temporal cortex, and using simulated data. The SOMA sofware is available at http://www.sussex.ac.uk/Users/pmh20/spikes.

SuperSpike: Supervised Learning in Multilayer Spiking Neural Networks.

Science.gov (United States)

Zenke, Friedemann; Ganguli, Surya

2018-04-13

A vast majority of computation in the brain is performed by spiking neural networks. Despite the ubiquity of such spiking, we currently lack an understanding of how biological spiking neural circuits learn and compute in vivo, as well as how we can instantiate such capabilities in artificial spiking circuits in silico. Here we revisit the problem of supervised learning in temporally coding multilayer spiking neural networks. First, by using a surrogate gradient approach, we derive SuperSpike, a nonlinear voltage-based three-factor learning rule capable of training multilayer networks of deterministic integrate-and-fire neurons to perform nonlinear computations on spatiotemporal spike patterns. Second, inspired by recent results on feedback alignment, we compare the performance of our learning rule under different credit assignment strategies for propagating output errors to hidden units. Specifically, we test uniform, symmetric, and random feedback, finding that simpler tasks can be solved with any type of feedback, while more complex tasks require symmetric feedback. In summary, our results open the door to obtaining a better scientific understanding of learning and computation in spiking neural networks by advancing our ability to train them to solve nonlinear problems involving transformations between different spatiotemporal spike time patterns.

Dopamine transporters govern diurnal variation in extracellular dopamine tone

OpenAIRE

Ferris, Mark J.; España, Rodrigo A.; Locke, Jason L.; Konstantopoulos, Joanne K.; Rose, Jamie H.; Chen, Rong; Jones, Sara R.

2014-01-01

The mechanism for diurnal (i.e., light/dark) oscillations in extracellular dopamine tone in mesolimbic and nigrostriatal systems is unknown. This is because, unlike other neurotransmitter systems, variation in dopamine tone does not correlate with variation in dopamine cell firing. The current research pinpoints the dopamine transporter as a critical governor of diurnal variation in both extracellular dopamine tone and the intracellular availability of releasable dopamine. These data describe...

Spiking neural network for recognizing spatiotemporal sequences of spikes

International Nuclear Information System (INIS)

Jin, Dezhe Z.

2004-01-01

Sensory neurons in many brain areas spike with precise timing to stimuli with temporal structures, and encode temporally complex stimuli into spatiotemporal spikes. How the downstream neurons read out such neural code is an important unsolved problem. In this paper, we describe a decoding scheme using a spiking recurrent neural network. The network consists of excitatory neurons that form a synfire chain, and two globally inhibitory interneurons of different types that provide delayed feedforward and fast feedback inhibition, respectively. The network signals recognition of a specific spatiotemporal sequence when the last excitatory neuron down the synfire chain spikes, which happens if and only if that sequence was present in the input spike stream. The recognition scheme is invariant to variations in the intervals between input spikes within some range. The computation of the network can be mapped into that of a finite state machine. Our network provides a simple way to decode spatiotemporal spikes with diverse types of neurons

Fast EEG spike detection via eigenvalue analysis and clustering of spatial amplitude distribution

Science.gov (United States)

Fukami, Tadanori; Shimada, Takamasa; Ishikawa, Bunnoshin

2018-06-01

Objective. In the current study, we tested a proposed method for fast spike detection in electroencephalography (EEG). Approach. We performed eigenvalue analysis in two-dimensional space spanned by gradients calculated from two neighboring samples to detect high-amplitude negative peaks. We extracted the spike candidates by imposing restrictions on parameters regarding spike shape and eigenvalues reflecting detection characteristics of individual medical doctors. We subsequently performed clustering, classifying detected peaks by considering the amplitude distribution at 19 scalp electrodes. Clusters with a small number of candidates were excluded. We then defined a score for eliminating spike candidates for which the pattern of detected electrodes differed from the overall pattern in a cluster. Spikes were detected by setting the score threshold. Main results. Based on visual inspection by a psychiatrist experienced in EEG, we evaluated the proposed method using two statistical measures of precision and recall with respect to detection performance. We found that precision and recall exhibited a trade-off relationship. The average recall value was 0.708 in eight subjects with the score threshold that maximized the F-measure, with 58.6  ±  36.2 spikes per subject. Under this condition, the average precision was 0.390, corresponding to a false positive rate 2.09 times higher than the true positive rate. Analysis of the required processing time revealed that, using a general-purpose computer, our method could be used to perform spike detection in 12.1% of the recording time. The process of narrowing down spike candidates based on shape occupied most of the processing time. Significance. Although the average recall value was comparable with that of other studies, the proposed method significantly shortened the processing time.

Amphetamine Paradoxically Augments Exocytotic Dopamine Release and Phasic Dopamine Signals

Science.gov (United States)

Daberkow, DP; Brown, HD; Bunner, KD; Kraniotis, SA; Doellman, MA; Ragozzino, ME; Garris, PA; Roitman, MF

2013-01-01

Drugs of abuse hijack brain reward circuitry during the addiction process by augmenting action potential-dependent phasic dopamine release events associated with learning and goal-directed behavior. One prominent exception to this notion would appear to be amphetamine (AMPH) and related analogs, which are proposed instead to disrupt normal patterns of dopamine neurotransmission by depleting vesicular stores and promoting non-exocytotic dopamine efflux via reverse transport. This mechanism of AMPH action, though, is inconsistent with its therapeutic effects and addictive properties - which are thought to be reliant on phasic dopamine signaling. Here we used fast-scan cyclic voltammetry in freely moving rats to interrogate principal neurochemical responses to AMPH in the striatum and relate these changes to behavior. First, we showed that AMPH dose-dependently enhanced evoked dopamine responses to phasic-like current pulse trains for up to two hours. Modeling the data revealed that AMPH inhibited dopamine uptake but also unexpectedly potentiated vesicular dopamine release. Second, we found that AMPH increased the amplitude, duration and frequency of spontaneous dopamine transients, the naturally occurring, non-electrically evoked, phasic increases in extracellular dopamine. Finally, using an operant sucrose reward paradigm, we showed that low-dose AMPH augmented dopamine transients elicited by sucrose-predictive cues. However, operant behavior failed at high-dose AMPH, which was due to phasic dopamine hyperactivity and the decoupling of dopamine transients from the reward predictive cue. These findings identify up-regulation of exocytotic dopamine release as a key AMPH action in behaving animals and support a unified mechanism of abused drugs to activate phasic dopamine signaling. PMID:23303926

iSpike: a spiking neural interface for the iCub robot

International Nuclear Information System (INIS)

Gamez, D; Fidjeland, A K; Lazdins, E

2012-01-01

This paper presents iSpike: a C++ library that interfaces between spiking neural network simulators and the iCub humanoid robot. It uses a biologically inspired approach to convert the robot’s sensory information into spikes that are passed to the neural network simulator, and it decodes output spikes from the network into motor signals that are sent to control the robot. Applications of iSpike range from embodied models of the brain to the development of intelligent robots using biologically inspired spiking neural networks. iSpike is an open source library that is available for free download under the terms of the GPL. (paper)

Firing properties of dopamine neurons in freely moving dopamine-deficient mice: Effects of dopamine receptor activation and anesthesia

OpenAIRE

Robinson, Siobhan; Smith, David M.; Mizumori, Sheri J. Y.; Palmiter, Richard D.

2004-01-01

To examine the regulation of midbrain dopamine neurons, recordings were obtained from single neurons of freely moving, genetically engineered dopamine-deficient (DD) mice. DD mice were tested without dopamine signaling (basal state) and with endogenous dopamine signaling (after L-dopa administration). In the basal state, when dopamine concentration in DD mice is

Timed Synaptic Inhibition Shapes NMDA Spikes, Influencing Local Dendritic Processing and Global I/O Properties of Cortical Neurons

Directory of Open Access Journals (Sweden)

Michael Doron

2017-11-01

Full Text Available The NMDA spike is a long-lasting nonlinear phenomenon initiated locally in the dendritic branches of a variety of cortical neurons. It plays a key role in synaptic plasticity and in single-neuron computations. Combining dynamic system theory and computational approaches, we now explore how the timing of synaptic inhibition affects the NMDA spike and its associated membrane current. When impinging on its early phase, individual inhibitory synapses strongly, but transiently, dampen the NMDA spike; later inhibition prematurely terminates it. A single inhibitory synapse reduces the NMDA-mediated Ca2+ current, a key player in plasticity, by up to 45%. NMDA spikes in distal dendritic branches/spines are longer-lasting and more resilient to inhibition, enhancing synaptic plasticity at these branches. We conclude that NMDA spikes are highly sensitive to dendritic inhibition; sparse weak inhibition can finely tune synaptic plasticity both locally at the dendritic branch level and globally at the level of the neuron’s output.

Training spiking neural networks to associate spatio-temporal input-output spike patterns

OpenAIRE

Mohemmed, A; Schliebs, S; Matsuda, S; Kasabov, N

2013-01-01

In a previous work (Mohemmed et al., Method for training a spiking neuron to associate input–output spike trains) [1] we have proposed a supervised learning algorithm based on temporal coding to train a spiking neuron to associate input spatiotemporal spike patterns to desired output spike patterns. The algorithm is based on the conversion of spike trains into analogue signals and the application of the Widrow–Hoff learning rule. In this paper we present a mathematical formulation of the prop...

Spike persistence and normalization in benign epilepsy with centrotemporal spikes - Implications for management.

Science.gov (United States)

Kim, Hunmin; Kim, Soo Yeon; Lim, Byung Chan; Hwang, Hee; Chae, Jong-Hee; Choi, Jieun; Kim, Ki Joong; Dlugos, Dennis J

2018-05-10

This study was performed 1) to determine the timing of spike normalization in patients with benign epilepsy with centrotemporal spikes (BECTS); 2) to identify relationships between age of seizure onset, age of spike normalization, years of spike persistence and treatment; and 3) to assess final outcomes between groups of patients with or without spikes at the time of medication tapering. Retrospective analysis of BECTS patients confirmed by clinical data, including age of onset, seizure semiology and serial electroencephalography (EEG) from diagnosis to remission. Age at spike normalization, years of spike persistence, and time of treatment onset to spike normalization were assessed. Final seizure and EEG outcome were compared between the groups with or without spikes at the time of AED tapering. One hundred and thirty-four patients were included. Mean age at seizure onset was 7.52 ± 2.11 years. Mean age at spike normalization was 11.89 ± 2.11 (range: 6.3-16.8) years. Mean time of treatment onset to spike normalization was 4.11 ± 2.13 (range: 0.24-10.08) years. Younger age of seizure onset was correlated with longer duration of spike persistence (r = -0.41, p < 0.001). In treated patients, spikes persisted for 4.1 ± 1.95 years, compared with 2.9 ± 1.97 years in untreated patients. No patients had recurrent seizures after AED was discontinued, regardless of the presence/absence of spikes at time of AED tapering. Years of spike persistence was longer in early onset BECTS patients. Treatment with AEDs did not shorten years of spike persistence. Persistence of spikes at time of treatment withdrawal was not associated with seizure recurrence. Copyright © 2018 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.

Psychostimulants affect dopamine transmission through both dopamine transporter-dependent and independent mechanisms

Science.gov (United States)

dela Peña, Ike; Gevorkiana, Ruzanna; Shi, Wei-Xing

2015-01-01

The precise mechanisms by which cocaine and amphetamine-like psychostimulants exert their reinforcing effects are not yet fully defined. It is widely believed, however, that these drugs produce their effects by enhancing dopamine neurotransmission in the brain, especially in limbic areas such as the nucleus accumbens, by inducing dopamine transporter-mediated reverse transport and/or blocking dopamine reuptake though the dopamine transporter. Here, we present the evidence that aside from dopamine transporter, non-dopamine transporter-mediated mechanisms also participate in psychostimulant-induced dopamine release and contribute to the behavioral effects of these drugs, such as locomotor activation and reward. Accordingly, psychostimulants could increase norepinephrine release in the prefrontal cortex, the latter then alters the firing pattern of dopamine neurons resulting in changes in action potential-dependent dopamine release. These alterations would further affect the temporal pattern of dopamine release in the nucleus accumbens, thereby modifying information processing in that area. Hence, a synaptic input to a nucleus accumbens neuron may be enhanced or inhibited by dopamine depending on its temporal relationship to dopamine release. Specific temporal patterns of dopamine release may also be required for certain forms of synaptic plasticity in the nucleus accumbens. Together, these effects induced by psychostimulants, mediated through a non-dopamine transporter-mediated mechanism involving norepinephrine and the prefrontal cortex, may also contribute importantly to the reinforcing properties of these drugs. PMID:26209364

Linking structure and activity in nonlinear spiking networks.

Directory of Open Access Journals (Sweden)

Gabriel Koch Ocker

2017-06-01

Full Text Available Recent experimental advances are producing an avalanche of data on both neural connectivity and neural activity. To take full advantage of these two emerging datasets we need a framework that links them, revealing how collective neural activity arises from the structure of neural connectivity and intrinsic neural dynamics. This problem of structure-driven activity has drawn major interest in computational neuroscience. Existing methods for relating activity and architecture in spiking networks rely on linearizing activity around a central operating point and thus fail to capture the nonlinear responses of individual neurons that are the hallmark of neural information processing. Here, we overcome this limitation and present a new relationship between connectivity and activity in networks of nonlinear spiking neurons by developing a diagrammatic fluctuation expansion based on statistical field theory. We explicitly show how recurrent network structure produces pairwise and higher-order correlated activity, and how nonlinearities impact the networks' spiking activity. Our findings open new avenues to investigating how single-neuron nonlinearities-including those of different cell types-combine with connectivity to shape population activity and function.

Linking structure and activity in nonlinear spiking networks.

Science.gov (United States)

Ocker, Gabriel Koch; Josić, Krešimir; Shea-Brown, Eric; Buice, Michael A

2017-06-01

Recent experimental advances are producing an avalanche of data on both neural connectivity and neural activity. To take full advantage of these two emerging datasets we need a framework that links them, revealing how collective neural activity arises from the structure of neural connectivity and intrinsic neural dynamics. This problem of structure-driven activity has drawn major interest in computational neuroscience. Existing methods for relating activity and architecture in spiking networks rely on linearizing activity around a central operating point and thus fail to capture the nonlinear responses of individual neurons that are the hallmark of neural information processing. Here, we overcome this limitation and present a new relationship between connectivity and activity in networks of nonlinear spiking neurons by developing a diagrammatic fluctuation expansion based on statistical field theory. We explicitly show how recurrent network structure produces pairwise and higher-order correlated activity, and how nonlinearities impact the networks' spiking activity. Our findings open new avenues to investigating how single-neuron nonlinearities-including those of different cell types-combine with connectivity to shape population activity and function.

The Second Spiking Threshold: Dynamics of Laminar Network Spiking in the Visual Cortex

DEFF Research Database (Denmark)

Forsberg, Lars E.; Bonde, Lars H.; Harvey, Michael A.

2016-01-01

and moving visual stimuli from the spontaneous ongoing spiking state, in all layers and zones of areas 17 and 18 indicating that the second threshold is a property of the network. Spontaneous and evoked spiking, thus can easily be distinguished. In addition, the trajectories of spontaneous ongoing states......Most neurons have a threshold separating the silent non-spiking state and the state of producing temporal sequences of spikes. But neurons in vivo also have a second threshold, found recently in granular layer neurons of the primary visual cortex, separating spontaneous ongoing spiking from...... visually evoked spiking driven by sharp transients. Here we examine whether this second threshold exists outside the granular layer and examine details of transitions between spiking states in ferrets exposed to moving objects. We found the second threshold, separating spiking states evoked by stationary...

Size-controlled gold nanoparticles obtained from electrodeposited amidoferrocenylpoly(propyleneimine) dendrimer-templates for the electrochemical sensing of dopamine

Science.gov (United States)

Villena, Carlos; Bravo, Marta; Alonso, Beatriz; Casado, Carmen M.; Losada, José; García Armada, M. Pilar

2017-10-01

Nanometer-scale gold particles exhibit size-dependent electronic properties with important sensing and biosensing applications. In the same way, a lot of analytes show some type of surface-sensitive reaction and the electrode material has a strong influence on the catalytic activity. In this work we study the kinetics and electrochemistry of electrodes with size controlled gold nanoparticles, obtained by electrodeposited amidoferrocenylpoly(propyleneimine) dendrimers of two generations as templates, and the kinetics and the analytical response to the oxidation of dopamine. We demonstrate that the four-types of modified electrodes show good catalytic responses toward the oxidation of dopamine via different processes in relation with the absence or presence of gold nanoparticles and their size. The best response was obtained with the largest nanoparticles, obtained with the first generation dendrimer-template at 0.3 V vs. SCE, with three linear ranges (0-70, 70-600 and 600-1000 μM), with sensitivities 585.7; 466.0 and 314.3 μA/mM cm2, and limit of detection of 0.01 μM. The effect of interfering substances has been studied by differential pulse voltammetry and the developed sensor has been successfully used for the determination of dopamine in a commercial dopamine hydrochloride injection and in spiked Human urine.

TRH regulates action potential shape in cerebral cortex pyramidal neurons.

Science.gov (United States)

Rodríguez-Molina, Víctor; Patiño, Javier; Vargas, Yamili; Sánchez-Jaramillo, Edith; Joseph-Bravo, Patricia; Charli, Jean-Louis

2014-07-07

Thyrotropin releasing hormone (TRH) is a neuropeptide with a wide neural distribution and a variety of functions. It modulates neuronal electrophysiological properties, including resting membrane potential, as well as excitatory postsynaptic potential and spike frequencies. We explored, with whole-cell patch clamp, TRH effect on action potential shape in pyramidal neurons of the sensorimotor cortex. TRH reduced spike and after hyperpolarization amplitudes, and increased spike half-width. The effect varied with dose, time and cortical layer. In layer V, 0.5µM of TRH induced a small increase in spike half-width, while 1 and 5µM induced a strong but transient change in spike half-width, and amplitude; after hyperpolarization amplitude was modified at 5µM of TRH. Cortical layers III and VI neurons responded intensely to 0.5µM TRH; layer II neurons response was small. The effect of 1µM TRH on action potential shape in layer V neurons was blocked by G-protein inhibition. Inhibition of the activity of the TRH-degrading enzyme pyroglutamyl peptidase II (PPII) reproduced the effect of TRH, with enhanced spike half-width. Many cortical PPII mRNA+ cells were VGLUT1 mRNA+, and some GAD mRNA+. These data show that TRH regulates action potential shape in pyramidal cortical neurons, and are consistent with the hypothesis that PPII controls its action in this region. Copyright © 2014 Elsevier B.V. All rights reserved.

Span: spike pattern association neuron for learning spatio-temporal spike patterns.

Science.gov (United States)

Mohemmed, Ammar; Schliebs, Stefan; Matsuda, Satoshi; Kasabov, Nikola

2012-08-01

Spiking Neural Networks (SNN) were shown to be suitable tools for the processing of spatio-temporal information. However, due to their inherent complexity, the formulation of efficient supervised learning algorithms for SNN is difficult and remains an important problem in the research area. This article presents SPAN - a spiking neuron that is able to learn associations of arbitrary spike trains in a supervised fashion allowing the processing of spatio-temporal information encoded in the precise timing of spikes. The idea of the proposed algorithm is to transform spike trains during the learning phase into analog signals so that common mathematical operations can be performed on them. Using this conversion, it is possible to apply the well-known Widrow-Hoff rule directly to the transformed spike trains in order to adjust the synaptic weights and to achieve a desired input/output spike behavior of the neuron. In the presented experimental analysis, the proposed learning algorithm is evaluated regarding its learning capabilities, its memory capacity, its robustness to noisy stimuli and its classification performance. Differences and similarities of SPAN regarding two related algorithms, ReSuMe and Chronotron, are discussed.

Deep Spiking Networks

NARCIS (Netherlands)

O'Connor, P.; Welling, M.

2016-01-01

We introduce an algorithm to do backpropagation on a spiking network. Our network is "spiking" in the sense that our neurons accumulate their activation into a potential over time, and only send out a signal (a "spike") when this potential crosses a threshold and the neuron is reset. Neurons only

Differential Regulation of Action Potential Shape and Burst-Frequency Firing by BK and Kv2 Channels in Substantia Nigra Dopaminergic Neurons.

Science.gov (United States)

Kimm, Tilia; Khaliq, Zayd M; Bean, Bruce P

2015-12-16

Little is known about the voltage-dependent potassium currents underlying spike repolarization in midbrain dopaminergic neurons. Studying mouse substantia nigra pars compacta dopaminergic neurons both in brain slice and after acute dissociation, we found that BK calcium-activated potassium channels and Kv2 channels both make major contributions to the depolarization-activated potassium current. Inhibiting Kv2 or BK channels had very different effects on spike shape and evoked firing. Inhibiting Kv2 channels increased spike width and decreased the afterhyperpolarization, as expected for loss of an action potential-activated potassium conductance. BK inhibition also increased spike width but paradoxically increased the afterhyperpolarization. Kv2 channel inhibition steeply increased the slope of the frequency-current (f-I) relationship, whereas BK channel inhibition had little effect on the f-I slope or decreased it, sometimes resulting in slowed firing. Action potential clamp experiments showed that both BK and Kv2 current flow during spike repolarization but with very different kinetics, with Kv2 current activating later and deactivating more slowly. Further experiments revealed that inhibiting either BK or Kv2 alone leads to recruitment of additional current through the other channel type during the action potential as a consequence of changes in spike shape. Enhancement of slowly deactivating Kv2 current can account for the increased afterhyperpolarization produced by BK inhibition and likely underlies the very different effects on the f-I relationship. The cross-regulation of BK and Kv2 activation illustrates that the functional role of a channel cannot be defined in isolation but depends critically on the context of the other conductances in the cell. This work shows that BK calcium-activated potassium channels and Kv2 voltage-activated potassium channels both regulate action potentials in dopamine neurons of the substantia nigra pars compacta. Although both

Decoding spikes in a spiking neuronal network

Energy Technology Data Exchange (ETDEWEB)

Feng Jianfeng [Department of Informatics, University of Sussex, Brighton BN1 9QH (United Kingdom); Ding, Mingzhou [Department of Mathematics, Florida Atlantic University, Boca Raton, FL 33431 (United States)

2004-06-04

We investigate how to reliably decode the input information from the output of a spiking neuronal network. A maximum likelihood estimator of the input signal, together with its Fisher information, is rigorously calculated. The advantage of the maximum likelihood estimation over the 'brute-force rate coding' estimate is clearly demonstrated. It is pointed out that the ergodic assumption in neuroscience, i.e. a temporal average is equivalent to an ensemble average, is in general not true. Averaging over an ensemble of neurons usually gives a biased estimate of the input information. A method on how to compensate for the bias is proposed. Reconstruction of dynamical input signals with a group of spiking neurons is extensively studied and our results show that less than a spike is sufficient to accurately decode dynamical inputs.

Decoding spikes in a spiking neuronal network

International Nuclear Information System (INIS)

Feng Jianfeng; Ding, Mingzhou

2004-01-01

We investigate how to reliably decode the input information from the output of a spiking neuronal network. A maximum likelihood estimator of the input signal, together with its Fisher information, is rigorously calculated. The advantage of the maximum likelihood estimation over the 'brute-force rate coding' estimate is clearly demonstrated. It is pointed out that the ergodic assumption in neuroscience, i.e. a temporal average is equivalent to an ensemble average, is in general not true. Averaging over an ensemble of neurons usually gives a biased estimate of the input information. A method on how to compensate for the bias is proposed. Reconstruction of dynamical input signals with a group of spiking neurons is extensively studied and our results show that less than a spike is sufficient to accurately decode dynamical inputs

Methamphetamine Increases Locomotion and Dopamine Transporter Activity in Dopamine D5 Receptor-Deficient Mice

OpenAIRE

Hayashizaki, Seiji; Hirai, Shinobu; Ito, Yumi; Honda, Yoshiko; Arime, Yosefu; Sora, Ichiro; Okado, Haruo; Kodama, Tohru; Takada, Masahiko

2013-01-01

Dopamine regulates the psychomotor stimulant activities of amphetamine-like substances in the brain. The effects of dopamine are mediated through five known dopamine receptor subtypes in mammals. The functional relevance of D5 dopamine receptors in the central nervous system is not well understood. To determine the functional relevance of D5 dopamine receptors, we created D5 dopamine receptor-deficient mice and then used these mice to assess the roles of D5 dopamine receptors in the behaviora...

Differential and distributed effects of dopamine neuromodulations on resting-state network connectivity

NARCIS (Netherlands)

Cole, D.M.; Beckmann, Christian; Oei, N.Y.L.; Both, S.; van Gerven, J.M.A.; Rombouts, S.A.R.B.

2013-01-01

Dopaminergic medications, used to treat neurochemical pathology and resultant symptoms in neuropsychiatric disorders, are of mixed efficacy and regularly associated with behavioural side effects. The possibility that dopamine exerts both linear and nonlinear ('inverted U-shaped') effects on

Differential and distributed effects of dopamine neuromodulations on resting-state network connectivity

NARCIS (Netherlands)

Cole, D.M.; Beckmann, C.F.; Oei, N.Y.L.; Both, S.; van Gerven, J.M.A.; Rombouts, S.A.R.B.

Dopaminergic medications, used to treat neurochemical pathology and resultant symptoms in neuropsychiatric disorders, are of mixed efficacy and regularly associated with behavioural side effects. The possibility that dopamine exerts both linear and nonlinear ('inverted U-shaped') effects on

The dynamic relationship between cerebellar Purkinje cell simple spikes and the spikelet number of complex spikes.

Science.gov (United States)

Burroughs, Amelia; Wise, Andrew K; Xiao, Jianqiang; Houghton, Conor; Tang, Tianyu; Suh, Colleen Y; Lang, Eric J; Apps, Richard; Cerminara, Nadia L

2017-01-01

Purkinje cells are the sole output of the cerebellar cortex and fire two distinct types of action potential: simple spikes and complex spikes. Previous studies have mainly considered complex spikes as unitary events, even though the waveform is composed of varying numbers of spikelets. The extent to which differences in spikelet number affect simple spike activity (and vice versa) remains unclear. We found that complex spikes with greater numbers of spikelets are preceded by higher simple spike firing rates but, following the complex spike, simple spikes are reduced in a manner that is graded with spikelet number. This dynamic interaction has important implications for cerebellar information processing, and suggests that complex spike spikelet number may maintain Purkinje cells within their operational range. Purkinje cells are central to cerebellar function because they form the sole output of the cerebellar cortex. They exhibit two distinct types of action potential: simple spikes and complex spikes. It is widely accepted that interaction between these two types of impulse is central to cerebellar cortical information processing. Previous investigations of the interactions between simple spikes and complex spikes have mainly considered complex spikes as unitary events. However, complex spikes are composed of an initial large spike followed by a number of secondary components, termed spikelets. The number of spikelets within individual complex spikes is highly variable and the extent to which differences in complex spike spikelet number affects simple spike activity (and vice versa) remains poorly understood. In anaesthetized adult rats, we have found that Purkinje cells recorded from the posterior lobe vermis and hemisphere have high simple spike firing frequencies that precede complex spikes with greater numbers of spikelets. This finding was also evident in a small sample of Purkinje cells recorded from the posterior lobe hemisphere in awake cats. In addition

The Second Spiking Threshold: Dynamics of Laminar Network Spiking in the Visual Cortex

Science.gov (United States)

Forsberg, Lars E.; Bonde, Lars H.; Harvey, Michael A.; Roland, Per E.

2016-01-01

Most neurons have a threshold separating the silent non-spiking state and the state of producing temporal sequences of spikes. But neurons in vivo also have a second threshold, found recently in granular layer neurons of the primary visual cortex, separating spontaneous ongoing spiking from visually evoked spiking driven by sharp transients. Here we examine whether this second threshold exists outside the granular layer and examine details of transitions between spiking states in ferrets exposed to moving objects. We found the second threshold, separating spiking states evoked by stationary and moving visual stimuli from the spontaneous ongoing spiking state, in all layers and zones of areas 17 and 18 indicating that the second threshold is a property of the network. Spontaneous and evoked spiking, thus can easily be distinguished. In addition, the trajectories of spontaneous ongoing states were slow, frequently changing direction. In single trials, sharp as well as smooth and slow transients transform the trajectories to be outward directed, fast and crossing the threshold to become evoked. Although the speeds of the evolution of the evoked states differ, the same domain of the state space is explored indicating uniformity of the evoked states. All evoked states return to the spontaneous evoked spiking state as in a typical mono-stable dynamical system. In single trials, neither the original spiking rates, nor the temporal evolution in state space could distinguish simple visual scenes. PMID:27582693

Heads for learning, tails for memory: Reward, reinforcement and a role of dopamine in determining behavioural relevance across multiple timescales

Directory of Open Access Journals (Sweden)

Mathieu eBaudonnat

2013-10-01

Full Text Available Dopamine has long been tightly associated with aspects of reinforcement learning and motivation in simple situations where there are a limited number of stimuli to guide behaviour and constrained range of outcomes. In naturalistic situations, however, there are many potential cues and foraging strategies that could be adopted, and it is critical that animals determine what might be behaviourally relevant in such complex environments. This requires not only detecting discrepancies with what they have recently experienced, but also identifying similarities with past experiences stored in memory. Here, we review what role dopamine might play in determining how and when to learn about the world, and how to develop choice policies appropriate to the situation faced. We discuss evidence that dopamine is shaped by motivation and memory and in turn shapes reward-based memory formation. In particular, we suggest that hippocampal-striatal-dopamine networks may interact to determine how surprising the world is and to either inhibit or promote actions at time of behavioural uncertainty.

Automatic EEG spike detection.

Science.gov (United States)

Harner, Richard

2009-10-01

Since the 1970s advances in science and technology during each succeeding decade have renewed the expectation of efficient, reliable automatic epileptiform spike detection (AESD). But even when reinforced with better, faster tools, clinically reliable unsupervised spike detection remains beyond our reach. Expert-selected spike parameters were the first and still most widely used for AESD. Thresholds for amplitude, duration, sharpness, rise-time, fall-time, after-coming slow waves, background frequency, and more have been used. It is still unclear which of these wave parameters are essential, beyond peak-peak amplitude and duration. Wavelet parameters are very appropriate to AESD but need to be combined with other parameters to achieve desired levels of spike detection efficiency. Artificial Neural Network (ANN) and expert-system methods may have reached peak efficiency. Support Vector Machine (SVM) technology focuses on outliers rather than centroids of spike and nonspike data clusters and should improve AESD efficiency. An exemplary spike/nonspike database is suggested as a tool for assessing parameters and methods for AESD and is available in CSV or Matlab formats from the author at brainvue@gmail.com. Exploratory Data Analysis (EDA) is presented as a graphic method for finding better spike parameters and for the step-wise evaluation of the spike detection process.

SpikeTemp: An Enhanced Rank-Order-Based Learning Approach for Spiking Neural Networks With Adaptive Structure.

Science.gov (United States)

Wang, Jinling; Belatreche, Ammar; Maguire, Liam P; McGinnity, Thomas Martin

2017-01-01

This paper presents an enhanced rank-order-based learning algorithm, called SpikeTemp, for spiking neural networks (SNNs) with a dynamically adaptive structure. The trained feed-forward SNN consists of two layers of spiking neurons: 1) an encoding layer which temporally encodes real-valued features into spatio-temporal spike patterns and 2) an output layer of dynamically grown neurons which perform spatio-temporal classification. Both Gaussian receptive fields and square cosine population encoding schemes are employed to encode real-valued features into spatio-temporal spike patterns. Unlike the rank-order-based learning approach, SpikeTemp uses the precise times of the incoming spikes for adjusting the synaptic weights such that early spikes result in a large weight change and late spikes lead to a smaller weight change. This removes the need to rank all the incoming spikes and, thus, reduces the computational cost of SpikeTemp. The proposed SpikeTemp algorithm is demonstrated on several benchmark data sets and on an image recognition task. The results show that SpikeTemp can achieve better classification performance and is much faster than the existing rank-order-based learning approach. In addition, the number of output neurons is much smaller when the square cosine encoding scheme is employed. Furthermore, SpikeTemp is benchmarked against a selection of existing machine learning algorithms, and the results demonstrate the ability of SpikeTemp to classify different data sets after just one presentation of the training samples with comparable classification performance.

Dopamine Receptor-Specific Contributions to the Computation of Value.

Science.gov (United States)

Burke, Christopher J; Soutschek, Alexander; Weber, Susanna; Raja Beharelle, Anjali; Fehr, Ernst; Haker, Helene; Tobler, Philippe N

2018-05-01

Dopamine is thought to play a crucial role in value-based decision making. However, the specific contributions of different dopamine receptor subtypes to the computation of subjective value remain unknown. Here we demonstrate how the balance between D1 and D2 dopamine receptor subtypes shapes subjective value computation during risky decision making. We administered the D2 receptor antagonist amisulpride or placebo before participants made choices between risky options. Compared with placebo, D2 receptor blockade resulted in more frequent choice of higher risk and higher expected value options. Using a novel model fitting procedure, we concurrently estimated the three parameters that define individual risk attitude according to an influential theoretical account of risky decision making (prospect theory). This analysis revealed that the observed reduction in risk aversion under amisulpride was driven by increased sensitivity to reward magnitude and decreased distortion of outcome probability, resulting in more linear value coding. Our data suggest that different components that govern individual risk attitude are under dopaminergic control, such that D2 receptor blockade facilitates risk taking and expected value processing.

Automatic spike sorting using tuning information.

Science.gov (United States)

Ventura, Valérie

2009-09-01

Current spike sorting methods focus on clustering neurons' characteristic spike waveforms. The resulting spike-sorted data are typically used to estimate how covariates of interest modulate the firing rates of neurons. However, when these covariates do modulate the firing rates, they provide information about spikes' identities, which thus far have been ignored for the purpose of spike sorting. This letter describes a novel approach to spike sorting, which incorporates both waveform information and tuning information obtained from the modulation of firing rates. Because it efficiently uses all the available information, this spike sorter yields lower spike misclassification rates than traditional automatic spike sorters. This theoretical result is verified empirically on several examples. The proposed method does not require additional assumptions; only its implementation is different. It essentially consists of performing spike sorting and tuning estimation simultaneously rather than sequentially, as is currently done. We used an expectation-maximization maximum likelihood algorithm to implement the new spike sorter. We present the general form of this algorithm and provide a detailed implementable version under the assumptions that neurons are independent and spike according to Poisson processes. Finally, we uncover a systematic flaw of spike sorting based on waveform information only.

Reliability of MEG source imaging of anterior temporal spikes: analysis of an intracranially characterized spike focus.

Science.gov (United States)

Wennberg, Richard; Cheyne, Douglas

2014-05-01

To assess the reliability of MEG source imaging (MSI) of anterior temporal spikes through detailed analysis of the localization and orientation of source solutions obtained for a large number of spikes that were separately confirmed by intracranial EEG to be focally generated within a single, well-characterized spike focus. MSI was performed on 64 identical right anterior temporal spikes from an anterolateral temporal neocortical spike focus. The effects of different volume conductors (sphere and realistic head model), removal of noise with low frequency filters (LFFs) and averaging multiple spikes were assessed in terms of the reliability of the source solutions. MSI of single spikes resulted in scattered dipole source solutions that showed reasonable reliability for localization at the lobar level, but only for solutions with a goodness-of-fit exceeding 80% using a LFF of 3 Hz. Reliability at a finer level of intralobar localization was limited. Spike averaging significantly improved the reliability of source solutions and averaging 8 or more spikes reduced dependency on goodness-of-fit and data filtering. MSI performed on topographically identical individual spikes from an intracranially defined classical anterior temporal lobe spike focus was limited by low reliability (i.e., scattered source solutions) in terms of fine, sublobar localization within the ipsilateral temporal lobe. Spike averaging significantly improved reliability. MSI performed on individual anterior temporal spikes is limited by low reliability. Reduction of background noise through spike averaging significantly improves the reliability of MSI solutions. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Decoding spatiotemporal spike sequences via the finite state automata dynamics of spiking neural networks

International Nuclear Information System (INIS)

Jin, Dezhe Z

2008-01-01

Temporally complex stimuli are encoded into spatiotemporal spike sequences of neurons in many sensory areas. Here, we describe how downstream neurons with dendritic bistable plateau potentials can be connected to decode such spike sequences. Driven by feedforward inputs from the sensory neurons and controlled by feedforward inhibition and lateral excitation, the neurons transit between UP and DOWN states of the membrane potentials. The neurons spike only in the UP states. A decoding neuron spikes at the end of an input to signal the recognition of specific spike sequences. The transition dynamics is equivalent to that of a finite state automaton. A connection rule for the networks guarantees that any finite state automaton can be mapped into the transition dynamics, demonstrating the equivalence in computational power between the networks and finite state automata. The decoding mechanism is capable of recognizing an arbitrary number of spatiotemporal spike sequences, and is insensitive to the variations of the spike timings in the sequences

Dopamine-induced apoptosis in human neuronal cells: inhibition by nucleic acides antisense to the dopamine transporter

International Nuclear Information System (INIS)

Porat, S.; Gabbay, M.; Tauber, M.; Ratovitski, T.; Blinder, E.; Simantov, R.

1996-01-01

Human neuroblastoma NMB cells take up [ 3 H]dopamine in a selective manner indicating that dopamine transporters are responsible for this uptake. These cells were therefore used as a model to study dopamine neurotoxicity, and to elucidate the role of dopamine transporters in controlling cell death. Treatment with 0.05-0.4 mM dopamine changed cells' morphology within 4 h, accompanied by retraction of processes, shrinkage, apoptosis-like atrophy, accumulation of apoptotic particles, DNA fragmentation and cell death. Cycloheximide inhibited dopamine's effect, suggesting that induction of apoptosis by dopamine was dependent upon protein synthesis. Dopamine cytotoxicity, monitored morphologically by flow cytometric analysis, and by lactate dehydrogenase released, was blocked by cocaine but not by the noradrenaline and serotonin uptake blockers desimipramine and imipramine, respectively. Attempting to inhibit dopamine transport and toxicity in a drug-free and highly selective way, three 18-mer dopamine transporter antisense phosphorothioate oligonucleotides (numbers 1, 2 and 3) and a new plasmid vector expressing the entire rat dopamine transporter complementary DNA in the antisense orientation were prepared and tested. Antisense phosphorothioate oligonucleotide 3 inhibited [ 3 H]dopamine uptake in a time- and dose-dependent manner. Likewise, transient transfection of NMB cells with the plasmid expressing dopamine transporter complementary DNA in the antisense orientation partially blocked [ 3 H]dopamine uptake. Antisense phosphorothioate oligonucleotide 3 also decreased, dose-dependently, the toxic effect of dopamine and 6-hydroxydopamine. Western blot analysis with newly prepared anti-human dopamine transporter antibodies showed that antisense phosphorothioate oligonucleotide 3 decreased the transporter protein level. These studies contribute to better understand the mechanism of dopamine-induced apoptosis and neurotoxicity. (Copyright (c) 1996 Elsevier Science B

CuO nanoparticle sensor for the electrochemical determination of dopamine

International Nuclear Information System (INIS)

Reddy, Sathish; Kumara Swamy, B.E.; Jayadevappa, H.

2012-01-01

Highlights: ► The MCPE prepared from flake-shaped CuO nanoparticles exhibits good electrocatalytic activity for DA compared with MCPE prepared from rod-shaped CuO nanoparticles. ► The MCPE prepared from SDS/polyglycine/flake-shaped CuO nanoparticles strong electrocatalytic enhancement of redox peak currents for DA and large peak potential separation between E AA − E DA . ► Analysis of DA shows linearly increase in anodic peak current in presence of excess ascorbic acid. ► Ease of preparation and good analytical response supports its claim for use as a potential dopamine sensor. - Abstract: In the present work, different shaped CuO nanoparticles were synthesized using cetyl trimethyl ammonium bromide (CTAB) and sodium dodecyl sulfate (SDS) in a co-precipitation method. The CuO nanoparticles were characterized using X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), infrared absorption spectroscopy (IR) and UV–visible absorption spectroscopy (UV–vis). The prepared CuO nanoparticles were used for the preparation of modified carbon-paste electrodes (MCPE) for the electrochemical detection of dopamine (DA) at pH 6.0. The MCPE prepared from flake-shaped CuO nanoparticles exhibited an enhanced current response for DA. Electrochemical parameters, such as the surface area of the electrode, the heterogeneous rate constant (k s ) and the lower detection limit (5.5 × 10 −8 M), were calculated and compared with those of the MCPE prepared from rod-shaped CuO nanoparticles. The MCPE prepared from SDS/polyglycine/flake-shaped CuO nanoparticles exhibited a further improved current response for DA and a high selectivity (E AA − E DA = 0.28 V) for the simultaneous investigation of DA and ascorbic acid (AA) at pH 6.0. The modified carbon-paste electrochemical sensors were compared, and the MCPE prepared from SDS/polyglycine/flake-shaped CuO nanoparticles exhibited better performance than the MCPE prepared from CTAB/polyglycine/flake-shaped

Bidirectional modulation of goal-directed actions by prefrontal cortical dopamine.

Science.gov (United States)

Hitchcott, Paul K; Quinn, Jennifer J; Taylor, Jane R

2007-12-01

Instrumental actions are a vital cognitive asset that endows an organism with sensitivity to the consequences of its behavior. Response-outcome feedback allows responding to be shaped in order to maximize beneficial, and minimize detrimental, outcomes. Lesions of the medial prefrontal cortex (mPFC) result in behavior that is insensitive to changes in outcome value in animals and compulsive behavior in several human psychopathologies. Such insensitivity to changes in outcome value is a defining characteristic of instrumental habits: responses that are controlled by antecedent stimuli rather than goal expectancy. Little is known regarding the neurochemical substrates mediating this sensitivity. The present experiments used sensitivity to posttraining outcome devaluation to index the action-habit status of instrumental responding. Infusions of dopamine into the ventral mPFC (vmPFC), but not dorsal mPFC, restored outcome sensitivity bidirectionally-decreasing responding following outcome devaluation and increasing responding when the outcome was not devalued. This bidirectionality makes the possibility that these infusions nonspecifically dysregulated vmPFC dopamine transmission unlikely. VmPFC dopamine promoted instrumental responding appropriate to outcome value. Reinforcer consumption data indicated that this was not a consequence of altered sensitivity to the reinforcer itself. We suggest that vmPFC dopamine reengages attentional processes underlying goal-directed behavior.

Automatic online spike sorting with singular value decomposition and fuzzy C-mean clustering

Directory of Open Access Journals (Sweden)

Oliynyk Andriy

2012-08-01

Full Text Available Abstract Background Understanding how neurons contribute to perception, motor functions and cognition requires the reliable detection of spiking activity of individual neurons during a number of different experimental conditions. An important problem in computational neuroscience is thus to develop algorithms to automatically detect and sort the spiking activity of individual neurons from extracellular recordings. While many algorithms for spike sorting exist, the problem of accurate and fast online sorting still remains a challenging issue. Results Here we present a novel software tool, called FSPS (Fuzzy SPike Sorting, which is designed to optimize: (i fast and accurate detection, (ii offline sorting and (iii online classification of neuronal spikes with very limited or null human intervention. The method is based on a combination of Singular Value Decomposition for fast and highly accurate pre-processing of spike shapes, unsupervised Fuzzy C-mean, high-resolution alignment of extracted spike waveforms, optimal selection of the number of features to retain, automatic identification the number of clusters, and quantitative quality assessment of resulting clusters independent on their size. After being trained on a short testing data stream, the method can reliably perform supervised online classification and monitoring of single neuron activity. The generalized procedure has been implemented in our FSPS spike sorting software (available free for non-commercial academic applications at the address: http://www.spikesorting.com using LabVIEW (National Instruments, USA. We evaluated the performance of our algorithm both on benchmark simulated datasets with different levels of background noise and on real extracellular recordings from premotor cortex of Macaque monkeys. The results of these tests showed an excellent accuracy in discriminating low-amplitude and overlapping spikes under strong background noise. The performance of our method is

Automatic online spike sorting with singular value decomposition and fuzzy C-mean clustering.

Science.gov (United States)

Oliynyk, Andriy; Bonifazzi, Claudio; Montani, Fernando; Fadiga, Luciano

2012-08-08

Understanding how neurons contribute to perception, motor functions and cognition requires the reliable detection of spiking activity of individual neurons during a number of different experimental conditions. An important problem in computational neuroscience is thus to develop algorithms to automatically detect and sort the spiking activity of individual neurons from extracellular recordings. While many algorithms for spike sorting exist, the problem of accurate and fast online sorting still remains a challenging issue. Here we present a novel software tool, called FSPS (Fuzzy SPike Sorting), which is designed to optimize: (i) fast and accurate detection, (ii) offline sorting and (iii) online classification of neuronal spikes with very limited or null human intervention. The method is based on a combination of Singular Value Decomposition for fast and highly accurate pre-processing of spike shapes, unsupervised Fuzzy C-mean, high-resolution alignment of extracted spike waveforms, optimal selection of the number of features to retain, automatic identification the number of clusters, and quantitative quality assessment of resulting clusters independent on their size. After being trained on a short testing data stream, the method can reliably perform supervised online classification and monitoring of single neuron activity. The generalized procedure has been implemented in our FSPS spike sorting software (available free for non-commercial academic applications at the address: http://www.spikesorting.com) using LabVIEW (National Instruments, USA). We evaluated the performance of our algorithm both on benchmark simulated datasets with different levels of background noise and on real extracellular recordings from premotor cortex of Macaque monkeys. The results of these tests showed an excellent accuracy in discriminating low-amplitude and overlapping spikes under strong background noise. The performance of our method is competitive with respect to other robust spike

Application of cross-correlated delay shift rule in spiking neural networks for interictal spike detection.

Science.gov (United States)

Lilin Guo; Zhenzhong Wang; Cabrerizo, Mercedes; Adjouadi, Malek

2016-08-01

This study proposes a Cross-Correlated Delay Shift (CCDS) supervised learning rule to train neurons with associated spatiotemporal patterns to classify spike patterns. The objective of this study was to evaluate the feasibility of using the CCDS rule to automate the detection of interictal spikes in electroencephalogram (EEG) data on patients with epilepsy. Encoding is the initial yet essential step for spiking neurons to process EEG patterns. A new encoding method is utilized to convert the EEG signal into spike patterns. The simulation results show that the proposed algorithm identified 69 spikes out of 82 spikes, or 84% detection rate, which is quite high considering the subtleties of interictal spikes and the tediousness of monitoring long EEG records. This CCDS rule is also benchmarked by ReSuMe on the same task.

The dopamine beta-hydroxylase inhibitor nepicastat increases dopamine release and potentiates psychostimulant-induced dopamine release in the prefrontal cortex.

Science.gov (United States)

Devoto, Paola; Flore, Giovanna; Saba, Pierluigi; Bini, Valentina; Gessa, Gian Luigi

2014-07-01

The dopamine-beta-hydroxylase inhibitor nepicastat has been shown to reproduce disulfiram ability to suppress the reinstatement of cocaine seeking after extinction in rats. To clarify its mechanism of action, we examined the effect of nepicastat, given alone or in association with cocaine or amphetamine, on catecholamine release in the medial prefrontal cortex and the nucleus accumbens, two key regions involved in the reinforcing and motivational effects of cocaine and in the reinstatement of cocaine seeking. Nepicastat effect on catecholamines was evaluated by microdialysis in freely moving rats. Nepicastat reduced noradrenaline release both in the medial prefrontal cortex and in the nucleus accumbens, and increased dopamine release in the medial prefrontal cortex but not in the nucleus accumbens. Moreover, nepicastat markedly potentiated cocaine- and amphetamine-induced extracellular dopamine accumulation in the medial prefrontal cortex but not in the nucleus accumbens. Extracellular dopamine accumulation produced by nepicastat alone or by its combination with cocaine or amphetamine was suppressed by the α2 -adrenoceptor agonist clonidine. It is suggested that nepicastat, by suppressing noradrenaline synthesis and release, eliminated the α2 -adrenoceptor mediated inhibitory mechanism that constrains dopamine release and cocaine- and amphetamine-induced dopamine release from noradrenaline or dopamine terminals in the medial prefrontal cortex. © 2012 The Authors, Addiction Biology © 2012 Society for the Study of Addiction.

Dopamine D(1) receptor-mediated control of striatal acetylcholine release by endogenous dopamine.

Science.gov (United States)

Acquas, E; Di Chiara, G

1999-10-27

The role of dopamine D(1) and D(2) receptors in the control of acetylcholine release in the dorsal striatum by endogenous dopamine was investigated by monitoring with microdialysis the effect of the separate or combined administration of the dopamine D(1) receptor antagonist, SCH 39166 ¿(-)-trans-6,7,7a,8,9, 13b-exahydro-3-chloro-2-hydroxy-N-methyl-5H-benzo-[d]-nap hto-[2, 1b]-azepine hydrochloride¿ (50 microg/kg subcutaneous (s.c.)), of the dopamine D(2)/D(3) receptor agonist, quinpirole (trans-(-)-4aR, 4a,5,6,7,8,8a,9-octahydro-5-propyl-1H-pyrazolo-(3,4-g)-quinoline hydrochloride) (5 and 10 microg/kg s.c.), and of the D(3) receptor selective agonist, PD 128,907 [S(+)-(4aR,10bR)-3,4,4a, 10b-tetrahydro-4-propyl-2H,5H-[1]benzopyrano-[4,3-b]-1,4-oxazin -9-ol hydrochloride] (50 microg/kg s.c.), on in vivo dopamine and acetylcholine release. Microdialysis was performed with a Ringer containing low concentrations (0.01 microM) of the acetylcholinesterase inhibitor, neostigmine. Quinpirole (10 microg/kg s.c.) decreased striatal dopamine and acetylcholine release. Administration of PD 128,907 (50 microg/kg) decreased dopamine but failed to affect acetylcholine release. SCH 39166 (50 microg/kg s.c.) stimulated dopamine release and reduced acetylcholine release. Pretreatment with quinpirole reduced (5 microg/kg s.c.) or completely prevented (10 microg/kg s.c.) the stimulation of dopamine release elicited by SCH 39166 (50 microg/kg s.c.); on the other hand, pretreatment with quinpirole (5 and 10 microg/kg) potentiated the reduction of striatal acetylcholine release induced by SCH 39166 (50 microg/kg s.c.). Similarly, pretreatment with PD 128,907 (50 microg/kg) which prevented the increase of dopamine release induced by SCH 39166 (50 microg/kg), potentiated the reduction of striatal acetylcholine transmission elicited by SCH 39166. Thus, pretreatment with low doses of quinpirole or PD 128,907 influences in opposite manner the effect of SCH 39166 on striatal dopamine and

Dopamine treatment and cognitive functioning in individuals with Parkinson's disease: the "cognitive flexibility" hypothesis seems to work.

Science.gov (United States)

Costa, Alberto; Peppe, Antonella; Mazzù, Ilenia; Longarzo, Mariachiara; Caltagirone, Carlo; Carlesimo, Giovanni A

2014-01-01

Previous data suggest that (i) dopamine modulates the ability to implement nonroutine schemata and update operations (flexibility processes) and that (ii) dopamine-related improvement may be related to baseline dopamine levels in target pathways (inverted U-shaped hypothesis). To investigate above hypotheses in individuals with Parkinson's disease (PD). Twenty PD patients were administered tasks varying as to flexibility load in two treatment conditions: (i) "off" condition, about 18 hours after dopamine dose and (ii) "on" condition, after dopamine administration. PD patients were separated into two groups: low performers (i.e., performance on Digit Span Backward below the sample mean) and high performers (i.e., performance above the mean). Twenty healthy individuals performed the tasks in two sessions without taking drugs. Passing from the "off" to the "on" state, only low performer PD patients significantly improved their performance on high-flexibility measures (interference condition of the Stroop test; P flexibility tasks. These findings document that high-flexibility processes are sensitive to dopamine neuromodulation in the early phases of PD. This is in line with the hypothesis that striatal dopamine pathways, affected early by PD, are precociously implicated in the expression of cognitive disorders in these individuals.

Spike rate and spike timing contributions to coding taste quality information in rat periphery

Directory of Open Access Journals (Sweden)

Vernon eLawhern

2011-05-01

Full Text Available There is emerging evidence that individual sensory neurons in the rodent brain rely on temporal features of the discharge pattern to code differences in taste quality information. In contrast, in-vestigations of individual sensory neurons in the periphery have focused on analysis of spike rate and mostly disregarded spike timing as a taste quality coding mechanism. The purpose of this work was to determine the contribution of spike timing to taste quality coding by rat geniculate ganglion neurons using computational methods that have been applied successfully in other sys-tems. We recorded the discharge patterns of narrowly-tuned and broadly-tuned neurons in the rat geniculate ganglion to representatives of the five basic taste qualities. We used mutual in-formation to determine significant responses and the van Rossum metric to characterize their temporal features. While our findings show that spike timing contributes a significant part of the message, spike rate contributes the largest portion of the message relayed by afferent neurons from rat fungiform taste buds to the brain. Thus, spike rate and spike timing together are more effective than spike rate alone in coding stimulus quality information to a single basic taste in the periphery for both narrowly-tuned specialist and broadly-tuned generalist neurons.

Determination of dopamine using a glassy carbon electrode modified with a graphene and carbon nanotube hybrid decorated with molybdenum disulfide flowers

International Nuclear Information System (INIS)

Mani, Veerappan; Govindasamy, Mani; Chen, Shen-Ming; Karthik, Raj; Huang, Sheng-Tung

2016-01-01

We describe a hybrid material that consists of molybdenum sulfide flowers placed on graphene nanosheets and multiwalled carbon nanotubes (GNS-CNTs/MoS_2). It was deposited on a glassy carbon electrode (GCE) which then is well suited for sensitive and selective determination of dopamine. The GNS-CNTs/MoS_2 nanocomposite was prepared by a hydrothermal method and characterized by scanning electron and transmission emission microscopies, energy-dispersive X-ray spectroscopy, cyclic voltammetry, differential pulse voltammetry and electrochemical impedance spectroscopy. Electrochemical studies show the composite to possess excellent electrochemical properties such as a large electrochemically active surface, high capacitance current, a wide potential window, high conductivity and large porosity. The electrode displays excellent electrocatalytic ability to oxidize dopamine. The modified GCE, best operated at a working potential as low as 0.15 V (vs. Ag/AgCl), responds linearly to dopamine in the 100 nM to 100 μM concentration range. The detection limit is 50 nM, and the sensitivity is 10.81 (± 0.26) μA⋅μM"−"1⋅cm"−"2. The sensor has good selectivity, appreciable stability, repeatability and reproducibility. It was applied to the determination of dopamine in (spiked) biological and pharmaceutical samples. (author)

Nicotine-Mediated ADP to Spike Transition: Double Spiking in Septal Neurons.

Science.gov (United States)

Kodirov, Sodikdjon A; Wehrmeister, Michael; Colom, Luis

2016-04-01

The majority of neurons in lateral septum (LS) are electrically silent at resting membrane potential. Nicotine transiently excites a subset of neurons and occasionally leads to long lasting bursting activity upon longer applications. We have observed simultaneous changes in frequencies and amplitudes of spontaneous action potentials (AP) in the presence of nicotine. During the prolonged exposure, nicotine increased numbers of spikes within a burst. One of the hallmarks of nicotine effects was the occurrences of double spikes (known also as bursting). Alignment of 51 spontaneous spikes, triggered upon continuous application of nicotine, revealed that the slope of after-depolarizing potential gradually increased (1.4 vs. 3 mV/ms) and neuron fired the second AP, termed as double spiking. A transition from a single AP to double spikes increased the amplitude of after-hyperpolarizing potential. The amplitude of the second (premature) AP was smaller compared to the first one, and this correlation persisted in regard to their duration (half-width). A similar bursting activity in the presence of nicotine, to our knowledge, has not been reported previously in the septal structure in general and in LS in particular.

Comparison of degradation between indigenous and spiked bisphenol A and triclosan in a biosolids amended soil.

Science.gov (United States)

Langdon, Kate A; Warne, Michael Stj; Smernik, Ronald J; Shareef, Ali; Kookana, Rai S

2013-03-01

This study compared the degradation of indigenous bisphenol A (BPA) and triclosan (TCS) in a biosolids-amended soil, to the degradation of spiked labelled surrogates of the same compounds (BPA-d16 and TCS-(13)C12). The aim was to determine if spiking experiments accurately predict the degradation of compounds in biosolids-amended soils using two different types of biosolids, a centrifuge dried biosolids (CDB) and a lagoon dried biosolids (LDB). The rate of degradation of the compounds was examined and the results indicated that there were considerable differences between the indigenous and spiked compounds. These differences were more marked for BPA, for which the indigenous compound was detectable throughout the study, whereas the spiked compound decreased to below the detection limit prior to the study completion. The rate of degradation for the indigenous BPA was approximately 5-times slower than that of the spiked BPA-d16. The indigenous and spiked TCS were both detectable throughout the study, however, the shape of the degradation curves varied considerably, particularly in the CDB treatment. These findings show that spiking experiments may not be suitable to predict the degradation and persistence of organic compounds following land application of biosolids. Copyright © 2013 Elsevier B.V. All rights reserved.

Comparison of degradation between indigenous and spiked bisphenol A and triclosan in a biosolids amended soil

International Nuclear Information System (INIS)

Langdon, Kate A.; Warne, Michael StJ.; Smernik, Ronald J.; Shareef, Ali; Kookana, Rai S.

2013-01-01

This study compared the degradation of indigenous bisphenol A (BPA) and triclosan (TCS) in a biosolids-amended soil, to the degradation of spiked labelled surrogates of the same compounds (BPA-d 16 and TCS- 13 C 12 ). The aim was to determine if spiking experiments accurately predict the degradation of compounds in biosolids-amended soils using two different types of biosolids, a centrifuge dried biosolids (CDB) and a lagoon dried biosolids (LDB). The rate of degradation of the compounds was examined and the results indicated that there were considerable differences between the indigenous and spiked compounds. These differences were more marked for BPA, for which the indigenous compound was detectable throughout the study, whereas the spiked compound decreased to below the detection limit prior to the study completion. The rate of degradation for the indigenous BPA was approximately 5-times slower than that of the spiked BPA-d 16 . The indigenous and spiked TCS were both detectable throughout the study, however, the shape of the degradation curves varied considerably, particularly in the CDB treatment. These findings show that spiking experiments may not be suitable to predict the degradation and persistence of organic compounds following land application of biosolids. - Highlights: ► Degradation of indigenous and spiked compounds from biosolids were compared. ► Differences were observed for both the rate and pattern of degradation. ► Spiked bisphenol A entirely degraded however the indigenous compound remained. ► TCS was detectable during the experiment however the degradation patterns varied. ► Spiking experiments may not be suitable to predict degradation of organic compounds

Dopamine plasma clearance is increased in piglets compared to neonates during continuous dopamine infusion

DEFF Research Database (Denmark)

Rasmussen, Martin B; Gramsbergen, Jan Bert; Eriksen, Vibeke Ramsgaard

2018-01-01

pharmacokinetics. METHODS: Arterial blood samples were drawn from six neonates admitted to the neonatal intensive care unit of Copenhagen University Hospital and 20 newborn piglets during continuous dopamine infusion. Furthermore, to estimate the piglet plasma dopamine half-life, blood samples were drawn at 2.......5-minute intervals after the dopamine infusion was discontinued. The plasma dopamine content was analysed by high-performance liquid chromatography with electrochemical detection. RESULTS: The dopamine displayed first-order kinetics in piglets and had a half-life of 2.5 minutes, while the median plasma...

Propagation of spiking regularity and double coherence resonance in feedforward networks.

Science.gov (United States)

Men, Cong; Wang, Jiang; Qin, Ying-Mei; Deng, Bin; Tsang, Kai-Ming; Chan, Wai-Lok

2012-03-01

We investigate the propagation of spiking regularity in noisy feedforward networks (FFNs) based on FitzHugh-Nagumo neuron model systematically. It is found that noise could modulate the transmission of firing rate and spiking regularity. Noise-induced synchronization and synfire-enhanced coherence resonance are also observed when signals propagate in noisy multilayer networks. It is interesting that double coherence resonance (DCR) with the combination of synaptic input correlation and noise intensity is finally attained after the processing layer by layer in FFNs. Furthermore, inhibitory connections also play essential roles in shaping DCR phenomena. Several properties of the neuronal network such as noise intensity, correlation of synaptic inputs, and inhibitory connections can serve as control parameters in modulating both rate coding and the order of temporal coding.

A Theory of Material Spike Formation in Flow Separation

Science.gov (United States)

Serra, Mattia; Haller, George

2017-11-01

We develop a frame-invariant theory of material spike formation during flow separation over a no-slip boundary in two-dimensional flows with arbitrary time dependence. This theory identifies both fixed and moving separation, is effective also over short-time intervals, and admits a rigorous instantaneous limit. Our theory is based on topological properties of material lines, combining objectively stretching- and rotation-based kinematic quantities. The separation profile identified here serves as the theoretical backbone for the material spike from its birth to its fully developed shape, and remains hidden to existing approaches. Finally, our theory can be used to rigorously explain the perception of off-wall separation in unsteady flows, and more importantly, provide the conditions under which such a perception is justified. We illustrate our results in several examples including steady, time-periodic and unsteady analytic velocity fields with flat and curved boundaries, and an experimental dataset.

NEW DOPAMINE AGONISTS IN CARDIOVASCULAR THERAPY

NARCIS (Netherlands)

GIRBES, ARJ; VANVELDHUISEN, DJ; SMIT, AJ

1992-01-01

Dopamine, a naturally occurring catecholamine, has been extensively used in intensive care for many years. Dopamine stimulates different types of adrenergic receptors: alpha-1 and -2, beta-1 and -2, and dopamine-1 and -2. The renal effects of dopamine are the result of dopamine-1 receptor (DA1)

Impacts of stress and sex hormones on dopamine neurotransmission in the adolescent brain.

Science.gov (United States)

Sinclair, Duncan; Purves-Tyson, Tertia D; Allen, Katherine M; Weickert, Cynthia Shannon

2014-04-01

Adolescence is a developmental period of complex neurobiological change and heightened vulnerability to psychiatric illness. As a result, understanding factors such as sex and stress hormones which drive brain changes in adolescence, and how these factors may influence key neurotransmitter systems implicated in psychiatric illness, is paramount. In this review, we outline the impact of sex and stress hormones at adolescence on dopamine neurotransmission, a signaling pathway which is critical to healthy brain function and has been implicated in psychiatric illness. We review normative developmental changes in dopamine, sex hormone, and stress hormone signaling during adolescence and throughout postnatal life, then highlight the interaction of sex and stress hormones and review their impacts on dopamine neurotransmission in the adolescent brain. Adolescence is a time of increased responsiveness to sex and stress hormones, during which the maturing dopaminergic neural circuitry is profoundly influenced by these factors. Testosterone, estrogen, and glucocorticoids interact with each other and have distinct, brain region-specific impacts on dopamine neurotransmission in the adolescent brain, shaping brain maturation and cognitive function in adolescence and adulthood. Some effects of stress/sex hormones on cortical and subcortical dopamine parameters bear similarities with dopaminergic abnormalities seen in schizophrenia, suggesting a possible role for sex/stress hormones at adolescence in influencing risk for psychiatric illness via modulation of dopamine neurotransmission. Stress and sex hormones may prove useful targets in future strategies for modifying risk for psychiatric illness.

Radioiodinated ligands for dopamine receptors

International Nuclear Information System (INIS)

Kung, H.F.

1994-01-01

The dopamine receptor system is important for normal brain function; it is also the apparent action site for various neuroleptic drugs for the treatment of schizophrenia and other metal disorders. In the past few years radioiodinated ligands for single photon emission tomography (SPECT) have been successfully developed and tested in humans: [ 123 I]TISCH for D1 dopamine receptors; [ 123 I]IBZM, epidepride, IBF and FIDA2, four iodobenzamide derivatives, for D2/D3 dopamine receptors. In addition, [ 123 I]β-CIT (RTI-55) and IPT, cocaine derivatives, for the dopamine reuptake site are potentially useful for diagnosis of loss of dopamine neurons. The first iodinated ligand, (R)trans-7-OH-PIPAT, for D3 dopamine receptors, was synthesized and characterized with cloned cell lines (Spodoptera frugiperda, Sf9) expressing the D2 and D3 dopamine receptors and with rat basal forebrain membrane preparations. Most of the known iodobenzamides displayed similar potency in binding to both D2 and D3 dopamine receptors expressed in the cell lines. Initial studies appear to suggest that by fine tuning the structures it may be possible to develop agents specific for D2 and D3 dopamine receptors. It is important to investigate D2/D3 selectivity for this series of potent ligands

Dopamine induces neutrophil apoptosis through a dopamine D-1 receptor-independent mechanism.

LENUS (Irish Health Repository)

Sookhai, S

2012-02-03

BACKGROUND: For the normal resolution of an acute inflammatory response, neutrophil (PMN) apoptosis is essential to maintain immune homeostasis and to limit inappropriate host tissue damage. A delay in PMN apoptosis has been implicated in the pathogenesis of the systemic inflammatory response syndrome (SIRS). Dopamine, a biogenic amine with known cardiovascular and neurotransmitter properties, is used in patients with SIRS to maintain hemodynamic stability. We sought to determine whether dopamine may also have immunoregulatory properties capable of influencing PMN apoptosis, function, and activation state in patients with SIRS. METHODS: PMNs were isolated from healthy volunteers and patients with SIRS and treated with varying doses of dopamine and a dopamine D-1 receptor agonist, fenoldopam. PMN apoptosis was assessed every 6 hours with use of propidium iodide DNA staining and PMN function was assessed with use of respiratory burst activity, phagocytosis ability, and CD11a, CD11b, and CD18 receptor expression as functional markers. RESULTS: There was a significant delay in PMN apotosis in patients with SIRS compared with controls. Treatment of isolated PMNs from both healthy controls and patients with SIRS with 10 and 100 mumol\\/L dopamine induced apoptosis. PMN ingestive and cytocidal capacity were both decreased in patients with SIRS compared with controls. Treatment with dopamine significantly increased phagocytic function. Fenoldopam did not induce PMN apoptosis. CONCLUSION: Our data demonstrate for the first time that dopamine induces PMN apoptosis and modulates PMN function both in healthy controls and in patients with SIRS. These results indicate that dopamine may be beneficial during SIRS through a nonhemodynamic PMN-dependent proapoptotic mechanism.

Spike-timing computation properties of a feed-forward neural network model

Directory of Open Access Journals (Sweden)

Drew Benjamin Sinha

2014-01-01

Full Text Available Brain function is characterized by dynamical interactions among networks of neurons. These interactions are mediated by network topology at many scales ranging from microcircuits to brain areas. Understanding how networks operate can be aided by understanding how the transformation of inputs depends upon network connectivity patterns, e.g. serial and parallel pathways. To tractably determine how single synapses or groups of synapses in such pathways shape transformations, we modeled feed-forward networks of 7-22 neurons in which synaptic strength changed according to a spike-timing dependent plasticity rule. We investigated how activity varied when dynamics were perturbed by an activity-dependent electrical stimulation protocol (spike-triggered stimulation; STS in networks of different topologies and background input correlations. STS can successfully reorganize functional brain networks in vivo, but with a variability in effectiveness that may derive partially from the underlying network topology. In a simulated network with a single disynaptic pathway driven by uncorrelated background activity, structured spike-timing relationships between polysynaptically connected neurons were not observed. When background activity was correlated or parallel disynaptic pathways were added, however, robust polysynaptic spike timing relationships were observed, and application of STS yielded predictable changes in synaptic strengths and spike-timing relationships. These observations suggest that precise input-related or topologically induced temporal relationships in network activity are necessary for polysynaptic signal propagation. Such constraints for polysynaptic computation suggest potential roles for higher-order topological structure in network organization, such as maintaining polysynaptic correlation in the face of relatively weak synapses.

Learning by stimulation avoidance: A principle to control spiking neural networks dynamics.

Science.gov (United States)

Sinapayen, Lana; Masumori, Atsushi; Ikegami, Takashi

2017-01-01

Learning based on networks of real neurons, and learning based on biologically inspired models of neural networks, have yet to find general learning rules leading to widespread applications. In this paper, we argue for the existence of a principle allowing to steer the dynamics of a biologically inspired neural network. Using carefully timed external stimulation, the network can be driven towards a desired dynamical state. We term this principle "Learning by Stimulation Avoidance" (LSA). We demonstrate through simulation that the minimal sufficient conditions leading to LSA in artificial networks are also sufficient to reproduce learning results similar to those obtained in biological neurons by Shahaf and Marom, and in addition explains synaptic pruning. We examined the underlying mechanism by simulating a small network of 3 neurons, then scaled it up to a hundred neurons. We show that LSA has a higher explanatory power than existing hypotheses about the response of biological neural networks to external simulation, and can be used as a learning rule for an embodied application: learning of wall avoidance by a simulated robot. In other works, reinforcement learning with spiking networks can be obtained through global reward signals akin simulating the dopamine system; we believe that this is the first project demonstrating sensory-motor learning with random spiking networks through Hebbian learning relying on environmental conditions without a separate reward system.

Detection of bursts in neuronal spike trains by the mean inter-spike interval method

Institute of Scientific and Technical Information of China (English)

Lin Chen; Yong Deng; Weihua Luo; Zhen Wang; Shaoqun Zeng

2009-01-01

Bursts are electrical spikes firing with a high frequency, which are the most important property in synaptic plasticity and information processing in the central nervous system. However, bursts are difficult to identify because bursting activities or patterns vary with phys-iological conditions or external stimuli. In this paper, a simple method automatically to detect bursts in spike trains is described. This method auto-adaptively sets a parameter (mean inter-spike interval) according to intrinsic properties of the detected burst spike trains, without any arbitrary choices or any operator judgrnent. When the mean value of several successive inter-spike intervals is not larger than the parameter, a burst is identified. By this method, bursts can be automatically extracted from different bursting patterns of cultured neurons on multi-electrode arrays, as accurately as by visual inspection. Furthermore, significant changes of burst variables caused by electrical stimulus have been found in spontaneous activity of neuronal network. These suggest that the mean inter-spike interval method is robust for detecting changes in burst patterns and characteristics induced by environmental alterations.

Comparison of degradation between indigenous and spiked bisphenol A and triclosan in a biosolids amended soil

Energy Technology Data Exchange (ETDEWEB)

Langdon, Kate A., E-mail: Kate.Langdon@csiro.au [School of Agriculture, Food and Wine and Waite Research Institute, University of Adelaide, South Australia, 5005, Adelaide (Australia); Water for a Healthy Country Research Flagship, Commonwealth Scientific and Industrial Research Organisation (CSIRO), PMB 2, Glen Osmond, South Australia, 5064, Adelaide (Australia); Warne, Michael StJ. [Water for a Healthy Country Research Flagship, Commonwealth Scientific and Industrial Research Organisation (CSIRO), PMB 2, Glen Osmond, South Australia, 5064, Adelaide (Australia); Smernik, Ronald J. [School of Agriculture, Food and Wine and Waite Research Institute, University of Adelaide, South Australia, 5005, Adelaide (Australia); Shareef, Ali; Kookana, Rai S. [Water for a Healthy Country Research Flagship, Commonwealth Scientific and Industrial Research Organisation (CSIRO), PMB 2, Glen Osmond, South Australia, 5064, Adelaide (Australia)

2013-03-01

This study compared the degradation of indigenous bisphenol A (BPA) and triclosan (TCS) in a biosolids-amended soil, to the degradation of spiked labelled surrogates of the same compounds (BPA-d{sub 16} and TCS-{sup 13}C{sub 12}). The aim was to determine if spiking experiments accurately predict the degradation of compounds in biosolids-amended soils using two different types of biosolids, a centrifuge dried biosolids (CDB) and a lagoon dried biosolids (LDB). The rate of degradation of the compounds was examined and the results indicated that there were considerable differences between the indigenous and spiked compounds. These differences were more marked for BPA, for which the indigenous compound was detectable throughout the study, whereas the spiked compound decreased to below the detection limit prior to the study completion. The rate of degradation for the indigenous BPA was approximately 5-times slower than that of the spiked BPA-d{sub 16}. The indigenous and spiked TCS were both detectable throughout the study, however, the shape of the degradation curves varied considerably, particularly in the CDB treatment. These findings show that spiking experiments may not be suitable to predict the degradation and persistence of organic compounds following land application of biosolids. - Highlights: ► Degradation of indigenous and spiked compounds from biosolids were compared. ► Differences were observed for both the rate and pattern of degradation. ► Spiked bisphenol A entirely degraded however the indigenous compound remained. ► TCS was detectable during the experiment however the degradation patterns varied. ► Spiking experiments may not be suitable to predict degradation of organic compounds.

Information transmission with spiking Bayesian neurons

International Nuclear Information System (INIS)

Lochmann, Timm; Deneve, Sophie

2008-01-01

Spike trains of cortical neurons resulting from repeatedpresentations of a stimulus are variable and exhibit Poisson-like statistics. Many models of neural coding therefore assumed that sensory information is contained in instantaneous firing rates, not spike times. Here, we ask how much information about time-varying stimuli can be transmitted by spiking neurons with such input and output variability. In particular, does this variability imply spike generation to be intrinsically stochastic? We consider a model neuron that estimates optimally the current state of a time-varying binary variable (e.g. presence of a stimulus) by integrating incoming spikes. The unit signals its current estimate to other units with spikes whenever the estimate increased by a fixed amount. As shown previously, this computation results in integrate and fire dynamics with Poisson-like output spike trains. This output variability is entirely due to the stochastic input rather than noisy spike generation. As a result such a deterministic neuron can transmit most of the information about the time varying stimulus. This contrasts with a standard model of sensory neurons, the linear-nonlinear Poisson (LNP) model which assumes that most variability in output spike trains is due to stochastic spike generation. Although it yields the same firing statistics, we found that such noisy firing results in the loss of most information. Finally, we use this framework to compare potential effects of top-down attention versus bottom-up saliency on information transfer with spiking neurons

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

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Gabriel Koch Ocker

2015-08-01

Full Text Available 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.

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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.

Cellular programming and reprogramming: sculpting cell fate for the production of dopamine neurons for cell therapy.

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Aguila, Julio C; Hedlund, Eva; Sanchez-Pernaute, Rosario

2012-01-01

Pluripotent stem cells are regarded as a promising cell source to obtain human dopamine neurons in sufficient amounts and purity for cell replacement therapy. Importantly, the success of clinical applications depends on our ability to steer pluripotent stem cells towards the right neuronal identity. In Parkinson disease, the loss of dopamine neurons is more pronounced in the ventrolateral population that projects to the sensorimotor striatum. Because synapses are highly specific, only neurons with this precise identity will contribute, upon transplantation, to the synaptic reconstruction of the dorsal striatum. Thus, understanding the developmental cell program of the mesostriatal dopamine neurons is critical for the identification of the extrinsic signals and cell-intrinsic factors that instruct and, ultimately, determine cell identity. Here, we review how extrinsic signals and transcription factors act together during development to shape midbrain cell fates. Further, we discuss how these same factors can be applied in vitro to induce, select, and reprogram cells to the mesostriatal dopamine fate.

Bayesian population decoding of spiking neurons.

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Gerwinn, Sebastian; Macke, Jakob; Bethge, Matthias

2009-01-01

The timing of action potentials in spiking neurons depends on the temporal dynamics of their inputs and contains information about temporal fluctuations in the stimulus. Leaky integrate-and-fire neurons constitute a popular class of encoding models, in which spike times depend directly on the temporal structure of the inputs. However, optimal decoding rules for these models have only been studied explicitly in the noiseless case. Here, we study decoding rules for probabilistic inference of a continuous stimulus from the spike times of a population of leaky integrate-and-fire neurons with threshold noise. We derive three algorithms for approximating the posterior distribution over stimuli as a function of the observed spike trains. In addition to a reconstruction of the stimulus we thus obtain an estimate of the uncertainty as well. Furthermore, we derive a 'spike-by-spike' online decoding scheme that recursively updates the posterior with the arrival of each new spike. We use these decoding rules to reconstruct time-varying stimuli represented by a Gaussian process from spike trains of single neurons as well as neural populations.

Bayesian population decoding of spiking neurons

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Sebastian Gerwinn

2009-10-01

Full Text Available The timing of action potentials in spiking neurons depends on the temporal dynamics of their inputs and contains information about temporal fluctuations in the stimulus. Leaky integrate-and-fire neurons constitute a popular class of encoding models, in which spike times depend directly on the temporal structure of the inputs. However, optimal decoding rules for these models have only been studied explicitly in the noiseless case. Here, we study decoding rules for probabilistic inference of a continuous stimulus from the spike times of a population of leaky integrate-and-fire neurons with threshold noise. We derive three algorithms for approximating the posterior distribution over stimuli as a function of the observed spike trains. In addition to a reconstruction of the stimulus we thus obtain an estimate of the uncertainty as well. Furthermore, we derive a `spike-by-spike' online decoding scheme that recursively updates the posterior with the arrival of each new spike. We use these decoding rules to reconstruct time-varying stimuli represented by a Gaussian process from spike trains of single neurons as well as neural populations.

Heterogeneity of Purkinje cell simple spike-complex spike interactions: zebrin- and non-zebrin-related variations.

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Tang, Tianyu; Xiao, Jianqiang; Suh, Colleen Y; Burroughs, Amelia; Cerminara, Nadia L; Jia, Linjia; Marshall, Sarah P; Wise, Andrew K; Apps, Richard; Sugihara, Izumi; Lang, Eric J

2017-08-01

Cerebellar Purkinje cells (PCs) generate two types of action potentials, simple and complex spikes. Although they are generated by distinct mechanisms, interactions between the two spike types exist. Zebrin staining produces alternating positive and negative stripes of PCs across most of the cerebellar cortex. Thus, here we compared simple spike-complex spike interactions both within and across zebrin populations. Simple spike activity undergoes a complex modulation preceding and following a complex spike. The amplitudes of the pre- and post-complex spike modulation phases were correlated across PCs. On average, the modulation was larger for PCs in zebrin positive regions. Correlations between aspects of the complex spike waveform and simple spike activity were found, some of which varied between zebrin positive and negative PCs. The implications of the results are discussed with regard to hypotheses that complex spikes are triggered by rises in simple spike activity for either motor learning or homeostatic functions. Purkinje cells (PCs) generate two types of action potentials, called simple and complex spikes (SSs and CSs). We first investigated the CS-associated modulation of SS activity and its relationship to the zebrin status of the PC. The modulation pattern consisted of a pre-CS rise in SS activity, and then, following the CS, a pause, a rebound, and finally a late inhibition of SS activity for both zebrin positive (Z+) and negative (Z-) cells, though the amplitudes of the phases were larger in Z+ cells. Moreover, the amplitudes of the pre-CS rise with the late inhibitory phase of the modulation were correlated across PCs. In contrast, correlations between modulation phases across CSs of individual PCs were generally weak. Next, the relationship between CS spikelets and SS activity was investigated. The number of spikelets/CS correlated with the average SS firing rate only for Z+ cells. In contrast, correlations across CSs between spikelet numbers and the

Dopamine, reward learning, and active inference.

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FitzGerald, Thomas H B; Dolan, Raymond J; Friston, Karl

2015-01-01

Temporal difference learning models propose phasic dopamine signaling encodes reward prediction errors that drive learning. This is supported by studies where optogenetic stimulation of dopamine neurons can stand in lieu of actual reward. Nevertheless, a large body of data also shows that dopamine is not necessary for learning, and that dopamine depletion primarily affects task performance. We offer a resolution to this paradox based on an hypothesis that dopamine encodes the precision of beliefs about alternative actions, and thus controls the outcome-sensitivity of behavior. We extend an active inference scheme for solving Markov decision processes to include learning, and show that simulated dopamine dynamics strongly resemble those actually observed during instrumental conditioning. Furthermore, simulated dopamine depletion impairs performance but spares learning, while simulated excitation of dopamine neurons drives reward learning, through aberrant inference about outcome states. Our formal approach provides a novel and parsimonious reconciliation of apparently divergent experimental findings.

Pharmacological characterization of the dopamine-sensitive adenylate cyclase in cockroach brain: evidence for a distinct dopamine receptor

International Nuclear Information System (INIS)

Orr, G.L.; Gole, J.W.D.; Notman, H.J.; Downer, R.G.H.

1987-01-01

Dopamine increases cyclic AMP production in crude membrane preparations of cockroach brain with plateaus in cyclic AMP production occurring between 1-10 μM and 10 mM. Maximal production of cyclic AMP is 2.25 fold greater than that of control values. Octopamine also increases cyclic AMP production with a Ka of 1.4 μM and maximal production 3.5 fold greater than that of control. 5-Hydroxytryptamine does not increase cyclic AMP production. The effects of octopamine and dopamine are fully additive. The vertebrate dopamine agonists ADTN and epinine stimulate the dopamine-sensitive adenylate cyclase (AC) with Ka values of 4.5 and 0.6 μM respectively and with maximal effectiveness 1.7 fold greater than that of control. The selective D 2 -dopamine agonist LY-171555 stimulates cyclic AMP production to a similar extent with a Ka of 50 μM. Other dopamine agonists have no stimulatory effects. With the exception of mianserin, 3 H-piflutixol is displaced from brain membranes by dopamine antagonists with an order of potency similar to that observed for the inhibition of dopamine-sensitive AC. The results indicate that the octopamine- and dopamine-sensitive AC in cockroach brain can be distinguished pharmacologically and the dopamine receptors coupled to AC have pharmacological characteristics distinct from vertebrate D 1 - and D 2 -dopamine receptors. 33 references, 3 figures, 2 tables

Improved SpikeProp for Using Particle Swarm Optimization

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Falah Y. H. Ahmed

2013-01-01

Full Text Available A spiking neurons network encodes information in the timing of individual spike times. A novel supervised learning rule for SpikeProp is derived to overcome the discontinuities introduced by the spiking thresholding. This algorithm is based on an error-backpropagation learning rule suited for supervised learning of spiking neurons that use exact spike time coding. The SpikeProp is able to demonstrate the spiking neurons that can perform complex nonlinear classification in fast temporal coding. This study proposes enhancements of SpikeProp learning algorithm for supervised training of spiking networks which can deal with complex patterns. The proposed methods include the SpikeProp particle swarm optimization (PSO and angle driven dependency learning rate. These methods are presented to SpikeProp network for multilayer learning enhancement and weights optimization. Input and output patterns are encoded as spike trains of precisely timed spikes, and the network learns to transform the input trains into target output trains. With these enhancements, our proposed methods outperformed other conventional neural network architectures.

Dopamine, reward learning, and active inference

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Thomas eFitzgerald

2015-11-01

Full Text Available Temporal difference learning models propose phasic dopamine signalling encodes reward prediction errors that drive learning. This is supported by studies where optogenetic stimulation of dopamine neurons can stand in lieu of actual reward. Nevertheless, a large body of data also shows that dopamine is not necessary for learning, and that dopamine depletion primarily affects task performance. We offer a resolution to this paradox based on an hypothesis that dopamine encodes the precision of beliefs about alternative actions, and thus controls the outcome-sensitivity of behaviour. We extend an active inference scheme for solving Markov decision processes to include learning, and show that simulated dopamine dynamics strongly resemble those actually observed during instrumental conditioning. Furthermore, simulated dopamine depletion impairs performance but spares learning, while simulated excitation of dopamine neurons drives reward learning, through aberrant inference about outcome states. Our formal approach provides a novel and parsimonious reconciliation of apparently divergent experimental findings.

Dopamine Gene Profiling to Predict Impulse Control and Effects of Dopamine Agonist Ropinirole.

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MacDonald, Hayley J; Stinear, Cathy M; Ren, April; Coxon, James P; Kao, Justin; Macdonald, Lorraine; Snow, Barry; Cramer, Steven C; Byblow, Winston D

2016-07-01

Dopamine agonists can impair inhibitory control and cause impulse control disorders for those with Parkinson disease (PD), although mechanistically this is not well understood. In this study, we hypothesized that the extent of such drug effects on impulse control is related to specific dopamine gene polymorphisms. This double-blind, placebo-controlled study aimed to examine the effect of single doses of 0.5 and 1.0 mg of the dopamine agonist ropinirole on impulse control in healthy adults of typical age for PD onset. Impulse control was measured by stop signal RT on a response inhibition task and by an index of impulsive decision-making on the Balloon Analogue Risk Task. A dopamine genetic risk score quantified basal dopamine neurotransmission from the influence of five genes: catechol-O-methyltransferase, dopamine transporter, and those encoding receptors D1, D2, and D3. With placebo, impulse control was better for the high versus low genetic risk score groups. Ropinirole modulated impulse control in a manner dependent on genetic risk score. For the lower score group, both doses improved response inhibition (decreased stop signal RT) whereas the lower dose reduced impulsiveness in decision-making. Conversely, the higher score group showed a trend for worsened response inhibition on the lower dose whereas both doses increased impulsiveness in decision-making. The implications of the present findings are that genotyping can be used to predict impulse control and whether it will improve or worsen with the administration of dopamine agonists.

Cellular Programming and Reprogramming: Sculpting Cell Fate for the Production of Dopamine Neurons for Cell Therapy

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Julio C. Aguila

2012-01-01

success of clinical applications depends on our ability to steer pluripotent stem cells towards the right neuronal identity. In Parkinson disease, the loss of dopamine neurons is more pronounced in the ventrolateral population that projects to the sensorimotor striatum. Because synapses are highly specific, only neurons with this precise identity will contribute, upon transplantation, to the synaptic reconstruction of the dorsal striatum. Thus, understanding the developmental cell program of the mesostriatal dopamine neurons is critical for the identification of the extrinsic signals and cell-intrinsic factors that instruct and, ultimately, determine cell identity. Here, we review how extrinsic signals and transcription factors act together during development to shape midbrain cell fates. Further, we discuss how these same factors can be applied in vitro to induce, select, and reprogram cells to the mesostriatal dopamine fate.

Peripheral Dopamine in Restless Legs Syndrome

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Ulrike H. Mitchell

2018-03-01

Full Text Available Objective/BackgroundRestless Legs Syndrome (RLS is a dopamine-dependent disorder characterized by a strong urge to move. The objective of this study was to evalulate blood levels of dopamine and other catecholamines and blood D2-subtype dopamine receptors (D2Rs in RLS.Patients/MethodsDopamine levels in blood samples from age-matched unmedicated RLS subjects, medicated RLS subjects and Controls were evaluated with high performance liquid chromatography and dopamine D2R white blood cell (WBC expression levels were determined with fluorescence-activated cell sorting and immunocytochemistry.ResultsBlood plasma dopamine levels, but not norepinepherine or epinephrine levels, were significantly increased in medicated RLS subjects vs unmedicated RLS subjects and Controls. The percentage of lymphocytes and monocytes expressing D2Rs differed between Control, RLS medicated and RLS unmedicated subjects. Total D2R expression in lymphocytes, but not monocytes, differed between Control, RLS medicated and RLS unmedicated subjects. D2Rs in lymphocytes, but not monocytes, were sensitive to dopamine in Controls only.ConclusionDownregulation of WBCs D2Rs occurs in RLS. This downregulation is not reversed by medication, although commonly used RLS medications increase plasma dopamine levels. The insensitivity of monocytes to dopamine levels, but their downregulation in RLS, may reflect their utility as a biomarker for RLS and perhaps brain dopamine homeostasis.

Presence and function of dopamine transporter (DAT in stallion sperm: dopamine modulates sperm motility and acrosomal integrity.

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Javier A Urra

Full Text Available Dopamine is a catecholamine with multiple physiological functions, playing a key role in nervous system; however its participation in reproductive processes and sperm physiology is controversial. High dopamine concentrations have been reported in different portions of the feminine and masculine reproductive tract, although the role fulfilled by this catecholamine in reproductive physiology is as yet unknown. We have previously shown that dopamine type 2 receptor is functional in boar sperm, suggesting that dopamine acts as a physiological modulator of sperm viability, capacitation and motility. In the present study, using immunodetection methods, we revealed the presence of several proteins important for the dopamine uptake and signalling in mammalian sperm, specifically monoamine transporters as dopamine (DAT, serotonin (SERT and norepinephrine (NET transporters in equine sperm. We also demonstrated for the first time in equine sperm a functional dopamine transporter using 4-[4-(Dimethylaminostyryl]-N-methylpyridinium iodide (ASP(+, as substrate. In addition, we also showed that dopamine (1 mM treatment in vitro, does not affect sperm viability but decreases total and progressive sperm motility. This effect is reversed by blocking the dopamine transporter with the selective inhibitor vanoxerine (GBR12909 and non-selective inhibitors of dopamine reuptake such as nomifensine and bupropion. The effect of dopamine in sperm physiology was evaluated and we demonstrated that acrosome integrity and thyrosine phosphorylation in equine sperm is significantly reduced at high concentrations of this catecholamine. In summary, our results revealed the presence of monoamine transporter DAT, NET and SERT in equine sperm, and that the dopamine uptake by DAT can regulate sperm function, specifically acrosomal integrity and sperm motility.

Precise-spike-driven synaptic plasticity: learning hetero-association of spatiotemporal spike patterns.

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Qiang Yu

Full Text Available A new learning rule (Precise-Spike-Driven (PSD Synaptic Plasticity is proposed for processing and memorizing spatiotemporal patterns. PSD is a supervised learning rule that is analytically derived from the traditional Widrow-Hoff rule and can be used to train neurons to associate an input spatiotemporal spike pattern with a desired spike train. Synaptic adaptation is driven by the error between the desired and the actual output spikes, with positive errors causing long-term potentiation and negative errors causing long-term depression. The amount of modification is proportional to an eligibility trace that is triggered by afferent spikes. The PSD rule is both computationally efficient and biologically plausible. The properties of this learning rule are investigated extensively through experimental simulations, including its learning performance, its generality to different neuron models, its robustness against noisy conditions, its memory capacity, and the effects of its learning parameters. Experimental results show that the PSD rule is capable of spatiotemporal pattern classification, and can even outperform a well studied benchmark algorithm with the proposed relative confidence criterion. The PSD rule is further validated on a practical example of an optical character recognition problem. The results again show that it can achieve a good recognition performance with a proper encoding. Finally, a detailed discussion is provided about the PSD rule and several related algorithms including tempotron, SPAN, Chronotron and ReSuMe.

Precise-spike-driven synaptic plasticity: learning hetero-association of spatiotemporal spike patterns.

Science.gov (United States)

Yu, Qiang; Tang, Huajin; Tan, Kay Chen; Li, Haizhou

2013-01-01

A new learning rule (Precise-Spike-Driven (PSD) Synaptic Plasticity) is proposed for processing and memorizing spatiotemporal patterns. PSD is a supervised learning rule that is analytically derived from the traditional Widrow-Hoff rule and can be used to train neurons to associate an input spatiotemporal spike pattern with a desired spike train. Synaptic adaptation is driven by the error between the desired and the actual output spikes, with positive errors causing long-term potentiation and negative errors causing long-term depression. The amount of modification is proportional to an eligibility trace that is triggered by afferent spikes. The PSD rule is both computationally efficient and biologically plausible. The properties of this learning rule are investigated extensively through experimental simulations, including its learning performance, its generality to different neuron models, its robustness against noisy conditions, its memory capacity, and the effects of its learning parameters. Experimental results show that the PSD rule is capable of spatiotemporal pattern classification, and can even outperform a well studied benchmark algorithm with the proposed relative confidence criterion. The PSD rule is further validated on a practical example of an optical character recognition problem. The results again show that it can achieve a good recognition performance with a proper encoding. Finally, a detailed discussion is provided about the PSD rule and several related algorithms including tempotron, SPAN, Chronotron and ReSuMe.

Effects of Spike Anticipation on the Spiking Dynamics of Neural Networks

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Daniel ede Santos-Sierra

2015-11-01

Full Text Available Synchronization is one of the central phenomena involved in information processing in living systems. It is known that the nervous system requires the coordinated activity of both local and distant neural populations. Such an interplay allows to merge different information modalities in a whole processing supporting high-level mental skills as understanding, memory, abstraction, etc. Though the biological processes underlying synchronization in the brain are not fully understood there have been reported a variety of mechanisms supporting different types of synchronization both at theoretical and experimental level. One of the more intriguing of these phenomena is the anticipating synchronization, which has been recently reported in a pair of unidirectionally coupled artificial neurons under simple conditions cite{Pyragas}, where the slave neuron is able to anticipate in time the behaviour of the master one. In this paper we explore the effect of spike anticipation over the information processing performed by a neural network at functional and structural level. We show that the introduction of intermediary neurons in the network enhances spike anticipation and analyse how these variations in spike anticipation can significantly change the firing regime of the neural network according to its functional and structural properties. In addition we show that the interspike interval (ISI, one of the main features of the neural response associated to the information coding, can be closely related to spike anticipation by each spike, and how synaptic plasticity can be modulated through that relationship. This study has been performed through numerical simulation of a coupled system of Hindmarsh-Rose neurons.

Effects of Spike Anticipation on the Spiking Dynamics of Neural Networks.

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de Santos-Sierra, Daniel; Sanchez-Jimenez, Abel; Garcia-Vellisca, Mariano A; Navas, Adrian; Villacorta-Atienza, Jose A

2015-01-01

Synchronization is one of the central phenomena involved in information processing in living systems. It is known that the nervous system requires the coordinated activity of both local and distant neural populations. Such an interplay allows to merge different information modalities in a whole processing supporting high-level mental skills as understanding, memory, abstraction, etc. Though, the biological processes underlying synchronization in the brain are not fully understood there have been reported a variety of mechanisms supporting different types of synchronization both at theoretical and experimental level. One of the more intriguing of these phenomena is the anticipating synchronization, which has been recently reported in a pair of unidirectionally coupled artificial neurons under simple conditions (Pyragiene and Pyragas, 2013), where the slave neuron is able to anticipate in time the behavior of the master one. In this paper, we explore the effect of spike anticipation over the information processing performed by a neural network at functional and structural level. We show that the introduction of intermediary neurons in the network enhances spike anticipation and analyse how these variations in spike anticipation can significantly change the firing regime of the neural network according to its functional and structural properties. In addition we show that the interspike interval (ISI), one of the main features of the neural response associated with the information coding, can be closely related to spike anticipation by each spike, and how synaptic plasticity can be modulated through that relationship. This study has been performed through numerical simulation of a coupled system of Hindmarsh-Rose neurons.

Coronavirus spike-receptor interactions

NARCIS (Netherlands)

Mou, H.

2015-01-01

Coronaviruses cause important diseases in humans and animals. Coronavirus infection starts with the virus binding with its spike proteins to molecules present on the surface of host cells that act as receptors. This spike-receptor interaction is highly specific and determines the virus’ cell, tissue

Spike-based population coding and working memory.

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Martin Boerlin

2011-02-01

Full Text Available Compelling behavioral evidence suggests that humans can make optimal decisions despite the uncertainty inherent in perceptual or motor tasks. A key question in neuroscience is how populations of spiking neurons can implement such probabilistic computations. In this article, we develop a comprehensive framework for optimal, spike-based sensory integration and working memory in a dynamic environment. We propose that probability distributions are inferred spike-per-spike in recurrently connected networks of integrate-and-fire neurons. As a result, these networks can combine sensory cues optimally, track the state of a time-varying stimulus and memorize accumulated evidence over periods much longer than the time constant of single neurons. Importantly, we propose that population responses and persistent working memory states represent entire probability distributions and not only single stimulus values. These memories are reflected by sustained, asynchronous patterns of activity which make relevant information available to downstream neurons within their short time window of integration. Model neurons act as predictive encoders, only firing spikes which account for new information that has not yet been signaled. Thus, spike times signal deterministically a prediction error, contrary to rate codes in which spike times are considered to be random samples of an underlying firing rate. As a consequence of this coding scheme, a multitude of spike patterns can reliably encode the same information. This results in weakly correlated, Poisson-like spike trains that are sensitive to initial conditions but robust to even high levels of external neural noise. This spike train variability reproduces the one observed in cortical sensory spike trains, but cannot be equated to noise. On the contrary, it is a consequence of optimal spike-based inference. In contrast, we show that rate-based models perform poorly when implemented with stochastically spiking neurons.

Visually Evoked Spiking Evolves While Spontaneous Ongoing Dynamics Persist

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Huys, Raoul; Jirsa, Viktor K.; Darokhan, Ziauddin; Valentiniene, Sonata; Roland, Per E.

2016-01-01

Neurons in the primary visual cortex spontaneously spike even when there are no visual stimuli. It is unknown whether the spiking evoked by visual stimuli is just a modification of the spontaneous ongoing cortical spiking dynamics or whether the spontaneous spiking state disappears and is replaced by evoked spiking. This study of laminar recordings of spontaneous spiking and visually evoked spiking of neurons in the ferret primary visual cortex shows that the spiking dynamics does not change: the spontaneous spiking as well as evoked spiking is controlled by a stable and persisting fixed point attractor. Its existence guarantees that evoked spiking return to the spontaneous state. However, the spontaneous ongoing spiking state and the visual evoked spiking states are qualitatively different and are separated by a threshold (separatrix). The functional advantage of this organization is that it avoids the need for a system reorganization following visual stimulation, and impedes the transition of spontaneous spiking to evoked spiking and the propagation of spontaneous spiking from layer 4 to layers 2–3. PMID:26778982

NEUROTRANSMITTERS AND IMMUNITY: 1. DOPAMINE

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Lucian Hritcu

2007-08-01

Full Text Available Dopamine is one of the principal neurotransmitters in the central nervous system (CNC, and its neuronal pathways are involved in several key functions such as behavior (Hefco et al., 2003a,b, control of movement, endocrine regulation, immune response (Fiserova et al., 2002; Levite et al., 2001, Hritcu et al., 2006a,b,c, and cardiovascular function. Dopamine has at least five G-protein, coupled receptor subtypes, D1-D5, each arising from a different gene (Sibley et al., 1993. Traditionally, these receptors have been classified into D1-like (the D1 and D5 and D2-like (D2, D3 and D4 receptors subtypes, primarily according to their ability to stimulate or inhibit adenylate cyclase, respectively, and to their pharmacological characteristics (Seeman et al., 1993. Receptors for dopamine (particularly of D2 subclass are the primary therapeutic target in a number of neuropathological disorders including schizophrenia, Parkinson’s disease and Huntington’s chorea (Seeman et al., 1987. Neither dopamine by itself, nor dopaminergic agonists by themselves, has been shown to activate T cell function. Nevertheless, lymphocytes are most probably exposed to dopamine since the primary and secondary lymphoid organs of various mammals are markedly innervated, and contain nerve fibers which stain for tyrosine hydroxylase (Weihe et al., 1991, the enzyme responsible for dopamine synthesis. Moreover, cathecolamines and their metabolites are present in single lymphocytes and in extracts of T and B cell clones, and pharmacological inhibition of tyrosine hydroxylase reduces catecholamine levels, suggesting catecholamine synthesis by lymphocytes (Bergquist et al., 1994. The existence of putative dopamine receptors of D2, D3, D4 and D5 subtypes on immune cells has been proposed of several authors, primarily on the basis of dopaminergic ligand binding assays and specific mRNA expression as monitored by reverse transcription-PCR. Several experiments evoked the idea of a

Spike voltage topography in temporal lobe epilepsy.

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Asadi-Pooya, Ali A; Asadollahi, Marjan; Shimamoto, Shoichi; Lorenzo, Matthew; Sperling, Michael R

2016-07-15

We investigated the voltage topography of interictal spikes in patients with temporal lobe epilepsy (TLE) to see whether topography was related to etiology for TLE. Adults with TLE, who had epilepsy surgery for drug-resistant seizures from 2011 until 2014 at Jefferson Comprehensive Epilepsy Center were selected. Two groups of patients were studied: patients with mesial temporal sclerosis (MTS) on MRI and those with other MRI findings. The voltage topography maps of the interictal spikes at the peak were created using BESA software. We classified the interictal spikes as polar, basal, lateral, or others. Thirty-four patients were studied, from which the characteristics of 340 spikes were investigated. The most common type of spike orientation was others (186 spikes; 54.7%), followed by lateral (146; 42.9%), polar (5; 1.5%), and basal (3; 0.9%). Characteristics of the voltage topography maps of the spikes between the two groups of patients were somewhat different. Five spikes in patients with MTS had polar orientation, but none of the spikes in patients with other MRI findings had polar orientation (odds ratio=6.98, 95% confidence interval=0.38 to 127.38; p=0.07). Scalp topographic mapping of interictal spikes has the potential to offer different information than visual inspection alone. The present results do not allow an immediate clinical application of our findings; however, detecting a polar spike in a patient with TLE may increase the possibility of mesial temporal sclerosis as the underlying etiology. Copyright © 2016 Elsevier B.V. All rights reserved.

Cross-hemispheric dopamine projections have functional significance

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Fox, Megan E.; Mikhailova, Maria A.; Bass, Caroline E.; Takmakov, Pavel; Gainetdinov, Raul R.; Budygin, Evgeny A.; Wightman, R. Mark

2016-01-01

Dopamine signaling occurs on a subsecond timescale, and its dysregulation is implicated in pathologies ranging from drug addiction to Parkinson’s disease. Anatomic evidence suggests that some dopamine neurons have cross-hemispheric projections, but the significance of these projections is unknown. Here we report unprecedented interhemispheric communication in the midbrain dopamine system of awake and anesthetized rats. In the anesthetized rats, optogenetic and electrical stimulation of dopamine cells elicited physiologically relevant dopamine release in the contralateral striatum. Contralateral release differed between the dorsal and ventral striatum owing to differential regulation by D2-like receptors. In the freely moving animals, simultaneous bilateral measurements revealed that dopamine release synchronizes between hemispheres and intact, contralateral projections can release dopamine in the midbrain of 6-hydroxydopamine–lesioned rats. These experiments are the first, to our knowledge, to show cross-hemispheric synchronicity in dopamine signaling and support a functional role for contralateral projections. In addition, our data reveal that psychostimulants, such as amphetamine, promote the coupling of dopamine transients between hemispheres. PMID:27298371

The binding sites for cocaine and dopamine in the dopamine transporter overlap

DEFF Research Database (Denmark)

Beuming, Thijs; Kniazeff, Julie; Bergmann, Marianne L

2008-01-01

Cocaine is a widely abused substance with psychostimulant effects that are attributed to inhibition of the dopamine transporter (DAT). We present molecular models for DAT binding of cocaine and cocaine analogs constructed from the high-resolution structure of the bacterial transporter homolog Leu......T. Our models suggest that the binding site for cocaine and cocaine analogs is deeply buried between transmembrane segments 1, 3, 6 and 8, and overlaps with the binding sites for the substrates dopamine and amphetamine, as well as for benztropine-like DAT inhibitors. We validated our models by detailed...... inhibition of dopamine transport by cocaine....

Multineuronal Spike Sequences Repeat with Millisecond Precision

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Koki eMatsumoto

2013-06-01

Full Text Available Cortical microcircuits are nonrandomly wired by neurons. As a natural consequence, spikes emitted by microcircuits are also nonrandomly patterned in time and space. One of the prominent spike organizations is a repetition of fixed patterns of spike series across multiple neurons. However, several questions remain unsolved, including how precisely spike sequences repeat, how the sequences are spatially organized, how many neurons participate in sequences, and how different sequences are functionally linked. To address these questions, we monitored spontaneous spikes of hippocampal CA3 neurons ex vivo using a high-speed functional multineuron calcium imaging technique that allowed us to monitor spikes with millisecond resolution and to record the location of spiking and nonspiking neurons. Multineuronal spike sequences were overrepresented in spontaneous activity compared to the statistical chance level. Approximately 75% of neurons participated in at least one sequence during our observation period. The participants were sparsely dispersed and did not show specific spatial organization. The number of sequences relative to the chance level decreased when larger time frames were used to detect sequences. Thus, sequences were precise at the millisecond level. Sequences often shared common spikes with other sequences; parts of sequences were subsequently relayed by following sequences, generating complex chains of multiple sequences.

Computational systems analysis of dopamine metabolism.

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Zhen Qi

2008-06-01

Full Text Available A prominent feature of Parkinson's disease (PD is the loss of dopamine in the striatum, and many therapeutic interventions for the disease are aimed at restoring dopamine signaling. Dopamine signaling includes the synthesis, storage, release, and recycling of dopamine in the presynaptic terminal and activation of pre- and post-synaptic receptors and various downstream signaling cascades. As an aid that might facilitate our understanding of dopamine dynamics in the pathogenesis and treatment in PD, we have begun to merge currently available information and expert knowledge regarding presynaptic dopamine homeostasis into a computational model, following the guidelines of biochemical systems theory. After subjecting our model to mathematical diagnosis and analysis, we made direct comparisons between model predictions and experimental observations and found that the model exhibited a high degree of predictive capacity with respect to genetic and pharmacological changes in gene expression or function. Our results suggest potential approaches to restoring the dopamine imbalance and the associated generation of oxidative stress. While the proposed model of dopamine metabolism is preliminary, future extensions and refinements may eventually serve as an in silico platform for prescreening potential therapeutics, identifying immediate side effects, screening for biomarkers, and assessing the impact of risk factors of the disease.

Dopamine receptors in human gastrointestinal mucosa

International Nuclear Information System (INIS)

Hernandez, D.E.; Mason, G.A.; Walker, C.H.; Valenzuela, J.E.

1987-01-01

Dopamine is a putative enteric neurotransmitter that has been implicated in exocrine secretory and motility functions of the gastrointestinal tract of several mammalian species including man. This study was designed to determine the presence of dopamine binding sites in human gastric and duodenal mucosa and to describe certain biochemical characteristics of these enteric receptor sites. The binding assay was performed in triplicate with tissue homogenates obtained from healthy volunteers of both sexes using 3 H-dopamine as a ligand. The extent of nonspecific binding was determined in the presence of a 100-fold excess of unlabeled dopamine. Scatchard analysis performed with increasing concentrations of 3 H-dopamine (20-500 nM) revealed a single class of saturable dopamine binding sites in gastric and duodenal mucosa. The results of this report demonstrate the presence of specific dopamine receptors in human gastric and duodenal mucosa. These biochemical data suggest that molecular abnormalities of these receptor sites may be operative in the pathogenesis of important gastrointestinal disorders. 33 references, 2 figures

Developmental Vitamin D (DVD) Deficiency Reduces Nurr1 and TH Expression in Post-mitotic Dopamine Neurons in Rat Mesencephalon.

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Luan, Wei; Hammond, Luke Alexander; Cotter, Edmund; Osborne, Geoffrey William; Alexander, Suzanne Adele; Nink, Virginia; Cui, Xiaoying; Eyles, Darryl Walter

2018-03-01

Developmental vitamin D (DVD) deficiency has been proposed as an important risk factor for schizophrenia. Our previous study using Sprague Dawley rats found that DVD deficiency disrupted the ontogeny of mesencephalic dopamine neurons by decreasing the mRNA level of a crucial differentiation factor of dopamine cells, the nuclear receptor related 1 protein (Nurr1). However, it remains unknown whether this reflects a reduction in dopamine cell number or in Nurr1 expression. It is also unclear if any particular subset of developing dopamine neurons in the mesencephalon is selectively affected. In this study, we employed state-of-the-art spinning disk confocal microscopy optimized for the imaging of tissue sections and 3D segmentation to assess post-mitotic dopamine cells on a single-cell basis in the rat mesencephalon at embryonic day 15. Our results showed that DVD deficiency did not alter the number, morphology, or positioning of post-mitotic dopamine cells. However, the ratio of Nurr1+TH+ cells in the substantia nigra pars compacta (SNc) compared with the ventral tegmental area (VTA) was increased in DVD-deficient embryos. In addition, the expression of Nurr1 in immature dopamine cells and mature dopamine neurons in the VTA was decreased in DVD-deficient group. Tyrosine hydroxylase was selectively reduced in SNc of DVD-deficient mesencephalon. We conclude that DVD deficiency induced early alterations in mesencephalic dopamine development may in part explain the abnormal dopamine-related behaviors found in this model. Our findings may have broader implications for how certain environmental risk factors for schizophrenia may shape the ontogeny of dopaminergic systems and by inference increase the risk of schizophrenia.

Spiking Neural P Systems with Communication on Request.

Science.gov (United States)

Pan, Linqiang; Păun, Gheorghe; Zhang, Gexiang; Neri, Ferrante

2017-12-01

Spiking Neural [Formula: see text] Systems are Neural System models characterized by the fact that each neuron mimics a biological cell and the communication between neurons is based on spikes. In the Spiking Neural [Formula: see text] systems investigated so far, the application of evolution rules depends on the contents of a neuron (checked by means of a regular expression). In these [Formula: see text] systems, a specified number of spikes are consumed and a specified number of spikes are produced, and then sent to each of the neurons linked by a synapse to the evolving neuron. [Formula: see text]In the present work, a novel communication strategy among neurons of Spiking Neural [Formula: see text] Systems is proposed. In the resulting models, called Spiking Neural [Formula: see text] Systems with Communication on Request, the spikes are requested from neighboring neurons, depending on the contents of the neuron (still checked by means of a regular expression). Unlike the traditional Spiking Neural [Formula: see text] systems, no spikes are consumed or created: the spikes are only moved along synapses and replicated (when two or more neurons request the contents of the same neuron). [Formula: see text]The Spiking Neural [Formula: see text] Systems with Communication on Request are proved to be computationally universal, that is, equivalent with Turing machines as long as two types of spikes are used. Following this work, further research questions are listed to be open problems.

Self-control with spiking and non-spiking neural networks playing games.

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Christodoulou, Chris; Banfield, Gaye; Cleanthous, Aristodemos

2010-01-01

Self-control can be defined as choosing a large delayed reward over a small immediate reward, while precommitment is the making of a choice with the specific aim of denying oneself future choices. Humans recognise that they have self-control problems and attempt to overcome them by applying precommitment. Problems in exercising self-control, suggest a conflict between cognition and motivation, which has been linked to competition between higher and lower brain functions (representing the frontal lobes and the limbic system respectively). This premise of an internal process conflict, lead to a behavioural model being proposed, based on which, we implemented a computational model for studying and explaining self-control through precommitment behaviour. Our model consists of two neural networks, initially non-spiking and then spiking ones, representing the higher and lower brain systems viewed as cooperating for the benefit of the organism. The non-spiking neural networks are of simple feed forward multilayer type with reinforcement learning, one with selective bootstrap weight update rule, which is seen as myopic, representing the lower brain and the other with the temporal difference weight update rule, which is seen as far-sighted, representing the higher brain. The spiking neural networks are implemented with leaky integrate-and-fire neurons with learning based on stochastic synaptic transmission. The differentiating element between the two brain centres in this implementation is based on the memory of past actions determined by an eligibility trace time constant. As the structure of the self-control problem can be likened to the Iterated Prisoner's Dilemma (IPD) game in that cooperation is to defection what self-control is to impulsiveness or what compromising is to insisting, we implemented the neural networks as two players, learning simultaneously but independently, competing in the IPD game. With a technique resembling the precommitment effect, whereby the

Memristors Empower Spiking Neurons With Stochasticity

KAUST Repository

Al-Shedivat, Maruan

2015-06-01

Recent theoretical studies have shown that probabilistic spiking can be interpreted as learning and inference in cortical microcircuits. This interpretation creates new opportunities for building neuromorphic systems driven by probabilistic learning algorithms. However, such systems must have two crucial features: 1) the neurons should follow a specific behavioral model, and 2) stochastic spiking should be implemented efficiently for it to be scalable. This paper proposes a memristor-based stochastically spiking neuron that fulfills these requirements. First, the analytical model of the memristor is enhanced so it can capture the behavioral stochasticity consistent with experimentally observed phenomena. The switching behavior of the memristor model is demonstrated to be akin to the firing of the stochastic spike response neuron model, the primary building block for probabilistic algorithms in spiking neural networks. Furthermore, the paper proposes a neural soma circuit that utilizes the intrinsic nondeterminism of memristive switching for efficient spike generation. The simulations and analysis of the behavior of a single stochastic neuron and a winner-take-all network built of such neurons and trained on handwritten digits confirm that the circuit can be used for building probabilistic sampling and pattern adaptation machinery in spiking networks. The findings constitute an important step towards scalable and efficient probabilistic neuromorphic platforms. © 2011 IEEE.

Voltammetric sensing of paracetamole, dopamine and 4-aminophenol at a glassy carbon electrode coated with gold nanoparticles and an organophillic layered double hydroxide

International Nuclear Information System (INIS)

Yin, H.; Shang, K.; Meng, X.; Ai, S.

2011-01-01

A differential pulse voltammetric method was developed for the simultaneous determination of paracetamole, 4-aminophenol and dopamine at pH 7.0 using a glassy carbon electrode (GCE) coated with gold nanoparticles (AuNPs) and a layered double hydroxide sodium modified with dodecyl sulfate (SDS-LDH). The modified electrode displays excellent redox activity towards paracetamole, and the redox current is increased (and the corresponding over-potential decreased) compared to those of the bare GCE, the AuNPs-modified GCE, and the SDS-LDH-modified GCE. The modified electrode enables the determination of paracetamole in the concentration range from 0.5 to 400 μM, with a detection limit of 0.13 μM (at an S/N of 3). The sensor was successfully applied to the simultaneous determination of paracetamole and dopamine, and of paracetamole and 4-aminophenol, respectively, in pharmaceutical tablets and in spiked human serum samples. (author)

Non-orthogonally transitive G2 spike solution

International Nuclear Information System (INIS)

Lim, Woei Chet

2015-01-01

We generalize the orthogonally transitive (OT) G 2 spike solution to the non-OT G 2 case. This is achieved by applying Geroch’s transformation on a Kasner seed. The new solution contains two more parameters than the OT G 2 spike solution. Unlike the OT G 2 spike solution, the new solution always resolves its spike. (fast track communication)

Wavelet analysis of epileptic spikes

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Latka, Miroslaw; Was, Ziemowit; Kozik, Andrzej; West, Bruce J.

2003-05-01

Interictal spikes and sharp waves in human EEG are characteristic signatures of epilepsy. These potentials originate as a result of synchronous pathological discharge of many neurons. The reliable detection of such potentials has been the long standing problem in EEG analysis, especially after long-term monitoring became common in investigation of epileptic patients. The traditional definition of a spike is based on its amplitude, duration, sharpness, and emergence from its background. However, spike detection systems built solely around this definition are not reliable due to the presence of numerous transients and artifacts. We use wavelet transform to analyze the properties of EEG manifestations of epilepsy. We demonstrate that the behavior of wavelet transform of epileptic spikes across scales can constitute the foundation of a relatively simple yet effective detection algorithm.

Wavelet analysis of epileptic spikes

CERN Document Server

Latka, M; Kozik, A; West, B J; Latka, Miroslaw; Was, Ziemowit; Kozik, Andrzej; West, Bruce J.

2003-01-01

Interictal spikes and sharp waves in human EEG are characteristic signatures of epilepsy. These potentials originate as a result of synchronous, pathological discharge of many neurons. The reliable detection of such potentials has been the long standing problem in EEG analysis, especially after long-term monitoring became common in investigation of epileptic patients. The traditional definition of a spike is based on its amplitude, duration, sharpness, and emergence from its background. However, spike detection systems built solely around this definition are not reliable due to the presence of numerous transients and artifacts. We use wavelet transform to analyze the properties of EEG manifestations of epilepsy. We demonstrate that the behavior of wavelet transform of epileptic spikes across scales can constitute the foundation of a relatively simple yet effective detection algorithm.

Space-Time Dynamics of Membrane Currents Evolve to Shape Excitation, Spiking, and Inhibition in the Cortex at Small and Large Scales

DEFF Research Database (Denmark)

Roland, Per E.

2017-01-01

positions. After transition to active spiking states, larger structured zones with active spiking neurons appear, propagating through the cortical network, driving it into various forms of widespread excitation, and engaging the network from microscopic scales to whole cortical areas. At each engaged...... cortical site, the amount of excitation in the network, after a delay, becomes matched by an equal amount of space-time fine-tuned inhibition that might be instrumental in driving the dynamics toward perception and action....

Motor control by precisely timed spike patterns

DEFF Research Database (Denmark)

Srivastava, Kyle H; Holmes, Caroline M; Vellema, Michiel

2017-01-01

whether the information in spike timing actually plays a role in brain function. By examining the activity of individual motor units (the muscle fibers innervated by a single motor neuron) and manipulating patterns of activation of these neurons, we provide both correlative and causal evidence......A fundamental problem in neuroscience is understanding how sequences of action potentials ("spikes") encode information about sensory signals and motor outputs. Although traditional theories assume that this information is conveyed by the total number of spikes fired within a specified time...... interval (spike rate), recent studies have shown that additional information is carried by the millisecond-scale timing patterns of action potentials (spike timing). However, it is unknown whether or how subtle differences in spike timing drive differences in perception or behavior, leaving it unclear...

Striatal dopamine D1 and D2 receptors: widespread influences on methamphetamine-induced dopamine and serotonin neurotoxicity.

Science.gov (United States)

Gross, Noah B; Duncker, Patrick C; Marshall, John F

2011-11-01

Methamphetamine (mAMPH) is an addictive psychostimulant drug that releases monoamines through nonexocytotic mechanisms. In animals, binge mAMPH dosing regimens deplete markers for monoamine nerve terminals, for example, dopamine and serotonin transporters (DAT and SERT), in striatum and cerebral cortex. Although the precise mechanism of mAMPH-induced damage to monoaminergic nerve terminals is uncertain, both dopamine D1 and D2 receptors are known to be important. Systemic administration of dopamine D1 or D2 receptor antagonists to rodents prevents mAMPH-induced damage to striatal dopamine nerve terminals. Because these studies employed systemic antagonist administration, the specific brain regions involved remain to be elucidated. The present study examined the contribution of dopamine D1 and D2 receptors in striatum to mAMPH-induced DAT and SERT neurotoxicities. In this experiment, either the dopamine D1 antagonist, SCH23390, or the dopamine D2 receptor antagonist, sulpiride, was intrastriatally infused during a binge mAMPH regimen. Striatal DAT and cortical, hippocampal, and amygdalar SERT were assessed as markers of mAMPH-induced neurotoxicity 1 week following binge mAMPH administration. Blockade of striatal dopamine D1 or D2 receptors during an otherwise neurotoxic binge mAMPH regimen produced widespread protection against mAMPH-induced striatal DAT loss and cortical, hippocampal, and amygdalar SERT loss. This study demonstrates that (1) dopamine D1 and D2 receptors in striatum, like nigral D1 receptors, are needed for mAMPH-induced striatal DAT reductions, (2) these same receptors are needed for mAMPH-induced SERT loss, and (3) these widespread influences of striatal dopamine receptor antagonists are likely attributable to circuits connecting basal ganglia to thalamus and cortex. Copyright © 2011 Wiley-Liss, Inc.

α2A- and α2C-Adrenoceptors as Potential Targets for Dopamine and Dopamine Receptor Ligands.

Science.gov (United States)

Sánchez-Soto, Marta; Casadó-Anguera, Verònica; Yano, Hideaki; Bender, Brian Joseph; Cai, Ning-Sheng; Moreno, Estefanía; Canela, Enric I; Cortés, Antoni; Meiler, Jens; Casadó, Vicent; Ferré, Sergi

2018-03-18

The poor norepinephrine innervation and high density of Gi/o-coupled α 2A - and α 2C -adrenoceptors in the striatum and the dense striatal dopamine innervation have prompted the possibility that dopamine could be an effective adrenoceptor ligand. Nevertheless, the reported adrenoceptor agonistic properties of dopamine are still inconclusive. In this study, we analyzed the binding of norepinephrine, dopamine, and several compounds reported as selective dopamine D 2 -like receptor ligands, such as the D 3 receptor agonist 7-OH-PIPAT and the D 4 receptor agonist RO-105824, to α 2 -adrenoceptors in cortical and striatal tissue, which express α 2A -adrenoceptors and both α 2A - and α 2C -adrenoceptors, respectively. The affinity of dopamine for α 2 -adrenoceptors was found to be similar to that for D 1 -like and D 2 -like receptors. Moreover, the exogenous dopamine receptor ligands also showed high affinity for α 2A - and α 2C -adrenoceptors. Their ability to activate Gi/o proteins through α 2A - and α 2C -adrenoceptors was also analyzed in transfected cells with bioluminescent resonance energy transfer techniques. The relative ligand potencies and efficacies were dependent on the Gi/o protein subtype. Furthermore, dopamine binding to α 2 -adrenoceptors was functional, inducing changes in dynamic mass redistribution, adenylyl cyclase activity, and ERK1/2 phosphorylation. Binding events were further studied with computer modeling of ligand docking. Docking of dopamine at α 2A - and α 2C -adrenoceptors was nearly identical to its binding to the crystallized D 3 receptor. Therefore, we provide conclusive evidence that α 2A - and α 2C -adrenoceptors are functional receptors for norepinephrine, dopamine, and other previously assumed selective D 2 -like receptor ligands, which calls for revisiting previous studies with those ligands.

Dopamine versus noradrenaline in septic shock

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Bo Xu

2011-10-01

Full Text Available BackgroundThe ‘Surviving Sepsis’ Campaign guidelines recommend theuse of dopamine or noradrenaline as the first vasopressor inseptic shock. However, information that guides clinicians inchoosing between dopamine and noradrenaline as the firstvasopressor in patients with septic shock is limited.ObjectiveThis article presents a review of the literature regarding theuse of dopamine versus noradrenaline in patients with septicshock.ResultsTwo randomised controlled trials (RCT and two largeprospective cohort studies were analysed. RCT data showeddopamine was associated with increased arrhythmic events.One cohort study found dopamine was associated with higher30-day mortality. The other cohort study found noradrenalinewas associated with higher 28-day mortality.DiscussionData on the use of dopamine versus noradrenaline in patientswith septic shock is limited. Following the recent SOAP IIstudy, there is now strong evidence that the use of dopaminein septic shock is associated with significantly morecardiovascular adverse events, compared tonoradrenaline.ConclusionNoradrenaline should be used as the initial vasopressor inseptic shock to avoid the arrhythmic events associatedwith dopamine.

Optogenetic stimulation of VTA dopamine neurons reveals that tonic but not phasic patterns of dopamine transmission reduce ethanol self-administration

Directory of Open Access Journals (Sweden)

Caroline E Bass

2013-11-01

Full Text Available There is compelling evidence that acute ethanol exposure stimulates ventral tegmental area (VTA dopamine cell activity and that VTA-dependent dopamine release in terminal fields within the nucleus accumbens plays an integral role in the regulation of ethanol drinking behaviors. Unfortunately, due to technical limitations, the specific temporal dynamics linking VTA dopamine cell activation and ethanol self-administration are not known. In fact, establishing a causal link between specific patterns of dopamine transmission and ethanol drinking behaviors has proven elusive. Here, we sought to address these gaps in our knowledge using a newly developed viral-mediated gene delivery strategy to selectively express Channelrhodopsin-2 (ChR2 on dopamine cells in the VTA of wild-type rats. We then used this approach to precisely control VTA dopamine transmission during voluntary ethanol drinking sessions. The results confirmed that ChR2 was selectively expressed on VTA dopamine cells and delivery of blue light pulses to the VTA induced dopamine release in accumbal terminal fields with very high temporal and spatial precision. Brief high frequency VTA stimulation induced phasic patterns of dopamine release in the nucleus accumbens. Lower frequency stimulation, applied for longer periods mimicked tonic increases in accumbal dopamine. Notably, using this optogenetic approach in rats engaged in an intermittent ethanol drinking procedure, we found that tonic, but not phasic, stimulation of VTA dopamine cells selectively attenuated ethanol drinking behaviors. Collectively, these data demonstrate the effectiveness of a novel viral targeting strategy that can be used to restrict opsin expression to dopamine cells in standard outbred animals and provide the first causal evidence demonstrating that tonic activation of VTA dopamine neurons selectively decreases ethanol self-administration behaviors.

Generalized activity equations for spiking neural network dynamics

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Michael A Buice

2013-11-01

Full Text Available Much progress has been made in uncovering the computational capabilities of spiking neural networks. However, spiking neurons will always be more expensive to simulate compared to rate neurons because of the inherent disparity in time scales - the spike duration time is much shorter than the inter-spike time, which is much shorter than any learning time scale. In numerical analysis, this is a classic stiff problem. Spiking neurons are also much more difficult to study analytically. One possible approach to making spiking networks more tractable is to augment mean field activity models with some information about spiking correlations. For example, such a generalized activity model could carry information about spiking rates and correlations between spikes self-consistently. Here, we will show how this can be accomplished by constructing a complete formal probabilistic description of the network and then expanding around a small parameter such as the inverse of the number of neurons in the network. The mean field theory of the system gives a rate-like description. The first order terms in the perturbation expansion keep track of covariances.

Dopamine reward prediction error responses reflect marginal utility.

Science.gov (United States)

Stauffer, William R; Lak, Armin; Schultz, Wolfram

2014-11-03

Optimal choices require an accurate neuronal representation of economic value. In economics, utility functions are mathematical representations of subjective value that can be constructed from choices under risk. Utility usually exhibits a nonlinear relationship to physical reward value that corresponds to risk attitudes and reflects the increasing or decreasing marginal utility obtained with each additional unit of reward. Accordingly, neuronal reward responses coding utility should robustly reflect this nonlinearity. In two monkeys, we measured utility as a function of physical reward value from meaningful choices under risk (that adhered to first- and second-order stochastic dominance). The resulting nonlinear utility functions predicted the certainty equivalents for new gambles, indicating that the functions' shapes were meaningful. The monkeys were risk seeking (convex utility function) for low reward and risk avoiding (concave utility function) with higher amounts. Critically, the dopamine prediction error responses at the time of reward itself reflected the nonlinear utility functions measured at the time of choices. In particular, the reward response magnitude depended on the first derivative of the utility function and thus reflected the marginal utility. Furthermore, dopamine responses recorded outside of the task reflected the marginal utility of unpredicted reward. Accordingly, these responses were sufficient to train reinforcement learning models to predict the behaviorally defined expected utility of gambles. These data suggest a neuronal manifestation of marginal utility in dopamine neurons and indicate a common neuronal basis for fundamental explanatory constructs in animal learning theory (prediction error) and economic decision theory (marginal utility). Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

How the modified method of orbit quality assessment works for Oort spike comets?

Science.gov (United States)

Królikowska, Małgorzata; Dybczyński, Piotr A.

2018-03-01

We present a brief overview of the effectiveness of the modified method of a quality of orbit estimation proposed by us a few years ago. Having now a complete sample of 100 Oort spike comets with large-perihelion distances, we show that it was justified to introduce more restricted conditions separating the individual quality classes as well as introducing a new quality class containing orbits of the excellent quality, marked by us as 1a+. To enrich the perception, we provided a complete collection of visual time-distributions of positional data sets used by us for an orbit determination (see Appendix). We show that modern positional measurements of large-perihelion Oort spike comets should be carried out for at least three years around perihelion (three-four oppositions) to be almost certain that the derived orbit will be of the highest quality (1a+ class). Our results strongly support an expectation that in a near future it will be possible to study a shape of 1/aori-distribution of the Oort spike comets in a great detail basing only on the highest quality orbits, having 1/aori-uncertainties well below 5 . 10-6 au-1.

Epileptiform spike detection via convolutional neural networks

DEFF Research Database (Denmark)

Johansen, Alexander Rosenberg; Jin, Jing; Maszczyk, Tomasz

2016-01-01

The EEG of epileptic patients often contains sharp waveforms called "spikes", occurring between seizures. Detecting such spikes is crucial for diagnosing epilepsy. In this paper, we develop a convolutional neural network (CNN) for detecting spikes in EEG of epileptic patients in an automated...

Interaction of structural analogs of dopamine, chlorpromazine and sulpiride with striatal dopamine receptors

International Nuclear Information System (INIS)

Wallace, R.A.

1987-01-01

The objectives of these studies were to determine if the nitrogen atom of dopaminergic agonists and antagonists drugs is required for interaction with the D-1 and D-2 dopamine receptors and whether the positively charged or uncharged molecular species interacts with these receptors. To address these issues, permanently charged analogs of dopamine, chlorpromazine and sulpiride were synthesized in which a dimethylsulfonium, dimethylselenonium or quaternary ammonium group replaced the amine group. Permanently uncharged analogs which contained a methylsulfide, methylselenide and sulfoxide group instead of an amine group were also synthesized. The interactions of these compounds with striatal dopamine receptors were studied. We found that the permanently charged dopamine analogs bound to the D-2 receptor of striatal membranes like conventional dopaminergic agonists and displayed agonist activity at the D-2 receptor regulating potassium-evoked [ 3 H] acetylcholine release. In contrast, the permanently uncharged analogs bound only to the high affinity state of the D-2 receptor and had neither agonist or antagonist activity

PRESYNAPTIC DOPAMINE MODULATION BY STIMULANT SELF ADMINISTRATION

Science.gov (United States)

España, Rodrigo A.; Jones, Sara R.

2013-01-01

The mesolimbic dopamine system is an essential participant in the initiation and modulation of various forms of goal-directed behavior, including drug reinforcement and addiction processes. Dopamine neurotransmission is increased by acute administration of all drugs of abuse, including the stimulants cocaine and amphetamine. Chronic exposure to these drugs via voluntary self-administration provides a model of stimulant abuse that is useful in evaluating potential behavioral and neurochemical adaptations that occur during addiction. This review describes commonly used methodologies to measure dopamine and baseline parameters of presynaptic dopamine regulation, including exocytotic release and reuptake through the dopamine transporter in the nucleus accumbens core, as well as dramatic adaptations in dopamine neurotransmission and drug sensitivity that occur with acute non-contingent and chronic, contingent self-administration of cocaine and amphetamine. PMID:23277050

Learning Universal Computations with Spikes

Science.gov (United States)

Thalmeier, Dominik; Uhlmann, Marvin; Kappen, Hilbert J.; Memmesheimer, Raoul-Martin

2016-01-01

Providing the neurobiological basis of information processing in higher animals, spiking neural networks must be able to learn a variety of complicated computations, including the generation of appropriate, possibly delayed reactions to inputs and the self-sustained generation of complex activity patterns, e.g. for locomotion. Many such computations require previous building of intrinsic world models. Here we show how spiking neural networks may solve these different tasks. Firstly, we derive constraints under which classes of spiking neural networks lend themselves to substrates of powerful general purpose computing. The networks contain dendritic or synaptic nonlinearities and have a constrained connectivity. We then combine such networks with learning rules for outputs or recurrent connections. We show that this allows to learn even difficult benchmark tasks such as the self-sustained generation of desired low-dimensional chaotic dynamics or memory-dependent computations. Furthermore, we show how spiking networks can build models of external world systems and use the acquired knowledge to control them. PMID:27309381

Spiking Neurons for Analysis of Patterns

Science.gov (United States)

Huntsberger, Terrance

2008-01-01

Artificial neural networks comprising spiking neurons of a novel type have been conceived as improved pattern-analysis and pattern-recognition computational systems. These neurons are represented by a mathematical model denoted the state-variable model (SVM), which among other things, exploits a computational parallelism inherent in spiking-neuron geometry. Networks of SVM neurons offer advantages of speed and computational efficiency, relative to traditional artificial neural networks. The SVM also overcomes some of the limitations of prior spiking-neuron models. There are numerous potential pattern-recognition, tracking, and data-reduction (data preprocessing) applications for these SVM neural networks on Earth and in exploration of remote planets. Spiking neurons imitate biological neurons more closely than do the neurons of traditional artificial neural networks. A spiking neuron includes a central cell body (soma) surrounded by a tree-like interconnection network (dendrites). Spiking neurons are so named because they generate trains of output pulses (spikes) in response to inputs received from sensors or from other neurons. They gain their speed advantage over traditional neural networks by using the timing of individual spikes for computation, whereas traditional artificial neurons use averages of activity levels over time. Moreover, spiking neurons use the delays inherent in dendritic processing in order to efficiently encode the information content of incoming signals. Because traditional artificial neurons fail to capture this encoding, they have less processing capability, and so it is necessary to use more gates when implementing traditional artificial neurons in electronic circuitry. Such higher-order functions as dynamic tasking are effected by use of pools (collections) of spiking neurons interconnected by spike-transmitting fibers. The SVM includes adaptive thresholds and submodels of transport of ions (in imitation of such transport in biological

The Omega-Infinity Limit of Single Spikes

CERN Document Server

Axenides, Minos; Linardopoulos, Georgios

A new infinite-size limit of strings in RxS2 is presented. The limit is obtained from single spike strings by letting their angular velocity omega become infinite. We derive the energy-momenta relation of omega-infinity single spikes as their linear velocity v-->1 and their angular momentum J-->1. Generally, the v-->1, J-->1 limit of single spikes is singular and has to be excluded from the spectrum and be studied separately. We discover that the dispersion relation of omega-infinity single spikes contains logarithms in the limit J-->1. This result is somewhat surprising, since the logarithmic behavior in the string spectra is typically associated with their motion in non-compact spaces such as AdS. Omega-infinity single spikes seem to completely cover the surface of the 2-sphere they occupy, so that they may essentially be viewed as some sort of "brany strings". A proof of the sphere-filling property of omega-infinity single spikes is given in the appendix.

Intranasal dopamine reduces in vivo [123I]FP-CIT binding to striatal dopamine transporter: correlation with behavioral changes and evidence for Pavlovian conditioned dopamine response

OpenAIRE

Maria A de Souza Silva; C. eMattern; C. eMattern; C.I. eDecheva; Joseph P. Huston; A. eSadile; M. eBeu; H.W. eMüller; Susanne eNikolaus

2016-01-01

Purpose: Dopamine (DA), which does not cross the blood-brain barrier, has central and behavioral effects when administered via the nasal route. Neither the mechanisms of central action of intranasal dopamine (IN-DA), nor its mechanisms of diffusion and transport into the brain are well understood. We here examined whether IN-DA application influences dopamine transporter (DAT) binding in the dorsal striatum and assessed the extent of binding in relation to motor and exploratory behaviors. We ...

Stress-Induced Impairment of a Working Memory Task: Role of Spiking Rate and Spiking History Predicted Discharge

Science.gov (United States)

Devilbiss, David M.; Jenison, Rick L.; Berridge, Craig W.

2012-01-01

Stress, pervasive in society, contributes to over half of all work place accidents a year and over time can contribute to a variety of psychiatric disorders including depression, schizophrenia, and post-traumatic stress disorder. Stress impairs higher cognitive processes, dependent on the prefrontal cortex (PFC) and that involve maintenance and integration of information over extended periods, including working memory and attention. Substantial evidence has demonstrated a relationship between patterns of PFC neuron spiking activity (action-potential discharge) and components of delayed-response tasks used to probe PFC-dependent cognitive function in rats and monkeys. During delay periods of these tasks, persistent spiking activity is posited to be essential for the maintenance of information for working memory and attention. However, the degree to which stress-induced impairment in PFC-dependent cognition involves changes in task-related spiking rates or the ability for PFC neurons to retain information over time remains unknown. In the current study, spiking activity was recorded from the medial PFC of rats performing a delayed-response task of working memory during acute noise stress (93 db). Spike history-predicted discharge (SHPD) for PFC neurons was quantified as a measure of the degree to which ongoing neuronal discharge can be predicted by past spiking activity and reflects the degree to which past information is retained by these neurons over time. We found that PFC neuron discharge is predicted by their past spiking patterns for nearly one second. Acute stress impaired SHPD, selectively during delay intervals of the task, and simultaneously impaired task performance. Despite the reduction in delay-related SHPD, stress increased delay-related spiking rates. These findings suggest that neural codes utilizing SHPD within PFC networks likely reflects an additional important neurophysiological mechanism for maintenance of past information over time. Stress

Spikes and matter inhomogeneities in massless scalar field models

International Nuclear Information System (INIS)

Coley, A A; Lim, W C

2016-01-01

We shall discuss the general relativistic generation of spikes in a massless scalar field or stiff perfect fluid model. We first investigate orthogonally transitive (OT) G 2 stiff fluid spike models both heuristically and numerically, and give a new exact OT G 2 stiff fluid spike solution. We then present a new two-parameter family of non-OT G 2 stiff fluid spike solutions, obtained by the generalization of non-OT G 2 vacuum spike solutions to the stiff fluid case by applying Geroch’s transformation on a Jacobs seed. The dynamics of these new stiff fluid spike solutions is qualitatively different from that of the vacuum spike solutions in that the matter (stiff fluid) feels the spike directly and the stiff fluid spike solution can end up with a permanent spike. We then derive the evolution equations of non-OT G 2 stiff fluid models, including a second perfect fluid, in full generality, and briefly discuss some of their qualitative properties and their potential numerical analysis. Finally, we discuss how a fluid, and especially a stiff fluid or massless scalar field, affects the physics of the generation of spikes. (paper)

Spiking neural P systems with multiple channels.

Science.gov (United States)

Peng, Hong; Yang, Jinyu; Wang, Jun; Wang, Tao; Sun, Zhang; Song, Xiaoxiao; Luo, Xiaohui; Huang, Xiangnian

2017-11-01

Spiking neural P systems (SNP systems, in short) are a class of distributed parallel computing systems inspired from the neurophysiological behavior of biological spiking neurons. In this paper, we investigate a new variant of SNP systems in which each neuron has one or more synaptic channels, called spiking neural P systems with multiple channels (SNP-MC systems, in short). The spiking rules with channel label are introduced to handle the firing mechanism of neurons, where the channel labels indicate synaptic channels of transmitting the generated spikes. The computation power of SNP-MC systems is investigated. Specifically, we prove that SNP-MC systems are Turing universal as both number generating and number accepting devices. Copyright © 2017 Elsevier Ltd. All rights reserved.

Dopamine and anorexia nervosa.

Science.gov (United States)

Södersten, P; Bergh, C; Leon, M; Zandian, M

2016-01-01

We have suggested that reduced food intake increases the risk for anorexia nervosa by engaging mesolimbic dopamine neurons, thereby initially rewarding dieting. Recent fMRI studies have confirmed that dopamine neurons are activated in anorexia nervosa, but it is not clear whether this response is due to the disorder or to its resulting nutritional deficit. When the body senses the shortage of nutrients, it rapidly shifts behavior toward foraging for food as a normal physiological response and the mesolimbic dopamine neurons may be involved in that process. On the other hand, the altered dopamine status of anorexics has been suggested to result from a brain abnormality that underlies their complex emotional disorder. We suggest that the outcomes of the treatments that emerge from that perspective remain poor because they target the mental symptoms that are actually the consequences of the food deprivation that accompanies anorexia. On the other hand, a method that normalizes the disordered eating behavior of anorexics results in much better physiological, behavioral, and emotional outcomes. Copyright © 2015 Elsevier Ltd. All rights reserved.

Feature extraction using extrema sampling of discrete derivatives for spike sorting in implantable upper-limb neural prostheses.

Science.gov (United States)

Zamani, Majid; Demosthenous, Andreas

2014-07-01

Next generation neural interfaces for upper-limb (and other) prostheses aim to develop implantable interfaces for one or more nerves, each interface having many neural signal channels that work reliably in the stump without harming the nerves. To achieve real-time multi-channel processing it is important to integrate spike sorting on-chip to overcome limitations in transmission bandwidth. This requires computationally efficient algorithms for feature extraction and clustering suitable for low-power hardware implementation. This paper describes a new feature extraction method for real-time spike sorting based on extrema analysis (namely positive peaks and negative peaks) of spike shapes and their discrete derivatives at different frequency bands. Employing simulation across different datasets, the accuracy and computational complexity of the proposed method are assessed and compared with other methods. The average classification accuracy of the proposed method in conjunction with online sorting (O-Sort) is 91.6%, outperforming all the other methods tested with the O-Sort clustering algorithm. The proposed method offers a better tradeoff between classification error and computational complexity, making it a particularly strong choice for on-chip spike sorting.

Geomagnetic spikes on the core-mantle boundary

Science.gov (United States)

Davies, C. J.; Constable, C.

2017-12-01

Extreme variations of Earth's magnetic field occurred in the Levantine region around 1000 BC, where the field intensity rose and fell by a factor of 2-3 over a short time and confined spatial region. There is presently no coherent link between this intensity spike and the generating processes in Earth's liquid core. Here we test the attribution of a surface spike to a flux patch visible on the core-mantle boundary (CMB), calculating geometric and energetic bounds on resulting surface geomagnetic features. We show that the Levantine intensity high must span at least 60 degrees in longitude. Models providing the best trade-off between matching surface spike intensity, minimizing L1 and L2 misfit to the available data and satisfying core energy constraints produce CMB spikes 8-22 degrees wide with peak values of O(100) mT. We propose that the Levantine spike grew in place before migrating northward and westward, contributing to the growth of the axial dipole field seen in Holocene field models. Estimates of Ohmic dissipation suggest that diffusive processes, which are often neglected, likely govern the ultimate decay of geomagnetic spikes. Using these results, we search for the presence of spike-like features in geodynamo simulations.

Dopamine D1 and D2 receptor immunoreactivities in the arcuate-median eminence complex and their link to the tubero-infundibular dopamine neurons

Directory of Open Access Journals (Sweden)

W. Romero-Fernandez

2014-07-01

Full Text Available Dopamine D1 and D2 receptor immunohistochemistry and Golgi techniques were used to study the structure of the adult rat arcuate-median eminence complex, and determine the distribution of the dopamine D1 and D2 receptor immunoreactivities therein, particularly in relation to the tubero-infundibular dopamine neurons. Punctate dopamine D1 and D2 receptor immunoreactivities, likely located on nerve terminals, were enriched in the lateral palisade zone built up of nerve terminals, while the densities were low to modest in the medial palisade zone. A codistribution of dopamine D1 receptor or dopamine D2 receptor immunoreactive puncta with tyrosine hydroxylase immunoreactive nerve terminals was demonstrated in the external layer. Dopamine D1 receptor but not dopamine D2 receptor immnunoreactivites nerve cell bodies were found in the ventromedial part of the arcuate nucleus and in the lateral part of the internal layer of the median eminence forming a continuous cell mass presumably representing neuropeptide Y immunoreactive nerve cell bodies. The major arcuate dopamine/ tyrosine hydroxylase nerve cell group was found in the dorsomedial part. A large number of tyrosine hydroxylase immunoreactive nerve cell bodies in this region demonstrated punctate dopamine D1 receptor immunoreactivity but only a few presented dopamine D2 receptor immunoreactivity which were mainly found in a substantial number of tyrosine hydroxylase cell bodies of the ventral periventricular hypothalamic nucleus, also belonging to the tubero-infundibular dopamine neurons. Structural evidence for projections of the arcuate nerve cells into the median eminence was also obtained. Distal axons formed horizontal axons in the internal layer issuing a variable number of collaterals classified into single or multiple strands located in the external layer increasing our understanding of the dopamine nerve terminal networks in this region.  Dopamine D1 and D2 receptors may therefore directly

Contribution of vesicular and cytosolic dopamine to the increased striatal dopamine efflux elicited by intrastriatal injection of SKF38393.

NARCIS (Netherlands)

Saigusa, T.; Aono, Y.; Sekino, R.; Uchida, T.; Takada, K.; Oi, Y.; Koshikawa, N.; Cools, A.R.

2009-01-01

Like dexamphetamine, SKF38393 induces an increase in striatal dopamine efflux which is insensitive for tetrodotoxin, Ca(2+) independent and prevented by a dopamine transporter inhibitor. The dexamphetamine-induced striatal dopamine efflux originates from both the reserpine-sensitive vesicular

Goal-Directed Decision Making with Spiking Neurons.

Science.gov (United States)

Friedrich, Johannes; Lengyel, Máté

2016-02-03

Behavioral and neuroscientific data on reward-based decision making point to a fundamental distinction between habitual and goal-directed action selection. The formation of habits, which requires simple updating of cached values, has been studied in great detail, and the reward prediction error theory of dopamine function has enjoyed prominent success in accounting for its neural bases. In contrast, the neural circuit mechanisms of goal-directed decision making, requiring extended iterative computations to estimate values online, are still unknown. Here we present a spiking neural network that provably solves the difficult online value estimation problem underlying goal-directed decision making in a near-optimal way and reproduces behavioral as well as neurophysiological experimental data on tasks ranging from simple binary choice to sequential decision making. Our model uses local plasticity rules to learn the synaptic weights of a simple neural network to achieve optimal performance and solves one-step decision-making tasks, commonly considered in neuroeconomics, as well as more challenging sequential decision-making tasks within 1 s. These decision times, and their parametric dependence on task parameters, as well as the final choice probabilities match behavioral data, whereas the evolution of neural activities in the network closely mimics neural responses recorded in frontal cortices during the execution of such tasks. Our theory provides a principled framework to understand the neural underpinning of goal-directed decision making and makes novel predictions for sequential decision-making tasks with multiple rewards. Goal-directed actions requiring prospective planning pervade decision making, but their circuit-level mechanisms remain elusive. We show how a model circuit of biologically realistic spiking neurons can solve this computationally challenging problem in a novel way. The synaptic weights of our network can be learned using local plasticity rules

Bursts generate a non-reducible spike-pattern code

Directory of Open Access Journals (Sweden)

Hugo G Eyherabide

2009-05-01

Full Text Available On the single-neuron level, precisely timed spikes can either constitute firing-rate codes or spike-pattern codes that utilize the relative timing between consecutive spikes. There has been little experimental support for the hypothesis that such temporal patterns contribute substantially to information transmission. Using grasshopper auditory receptors as a model system, we show that correlations between spikes can be used to represent behaviorally relevant stimuli. The correlations reflect the inner structure of the spike train: a succession of burst-like patterns. We demonstrate that bursts with different spike counts encode different stimulus features, such that about 20% of the transmitted information corresponds to discriminating between different features, and the remaining 80% is used to allocate these features in time. In this spike-pattern code, the "what" and the "when" of the stimuli are encoded in the duration of each burst and the time of burst onset, respectively. Given the ubiquity of burst firing, we expect similar findings also for other neural systems.

Stochastic Variational Learning in Recurrent Spiking Networks

Directory of Open Access Journals (Sweden)

Danilo eJimenez Rezende

2014-04-01

Full Text Available The ability to learn and perform statistical inference with biologically plausible recurrent network of spiking neurons is an important step towards understanding perception and reasoning. Here we derive and investigate a new learning rule for recurrent spiking networks with hidden neurons, combining principles from variational learning and reinforcement learning. Our network defines a generative model over spike train histories and the derived learning rule has the form of a local Spike Timing Dependent Plasticity rule modulated by global factors (neuromodulators conveying information about ``novelty on a statistically rigorous ground.Simulations show that our model is able to learn bothstationary and non-stationary patterns of spike trains.We also propose one experiment that could potentially be performed with animals in order to test the dynamics of the predicted novelty signal.

Stochastic variational learning in recurrent spiking networks.

Science.gov (United States)

Jimenez Rezende, Danilo; Gerstner, Wulfram

2014-01-01

The ability to learn and perform statistical inference with biologically plausible recurrent networks of spiking neurons is an important step toward understanding perception and reasoning. Here we derive and investigate a new learning rule for recurrent spiking networks with hidden neurons, combining principles from variational learning and reinforcement learning. Our network defines a generative model over spike train histories and the derived learning rule has the form of a local Spike Timing Dependent Plasticity rule modulated by global factors (neuromodulators) conveying information about "novelty" on a statistically rigorous ground. Simulations show that our model is able to learn both stationary and non-stationary patterns of spike trains. We also propose one experiment that could potentially be performed with animals in order to test the dynamics of the predicted novelty signal.

Inferring oscillatory modulation in neural spike trains.

Science.gov (United States)

Arai, Kensuke; Kass, Robert E

2017-10-01

Oscillations are observed at various frequency bands in continuous-valued neural recordings like the electroencephalogram (EEG) and local field potential (LFP) in bulk brain matter, and analysis of spike-field coherence reveals that spiking of single neurons often occurs at certain phases of the global oscillation. Oscillatory modulation has been examined in relation to continuous-valued oscillatory signals, and independently from the spike train alone, but behavior or stimulus triggered firing-rate modulation, spiking sparseness, presence of slow modulation not locked to stimuli and irregular oscillations with large variability in oscillatory periods, present challenges to searching for temporal structures present in the spike train. In order to study oscillatory modulation in real data collected under a variety of experimental conditions, we describe a flexible point-process framework we call the Latent Oscillatory Spike Train (LOST) model to decompose the instantaneous firing rate in biologically and behaviorally relevant factors: spiking refractoriness, event-locked firing rate non-stationarity, and trial-to-trial variability accounted for by baseline offset and a stochastic oscillatory modulation. We also extend the LOST model to accommodate changes in the modulatory structure over the duration of the experiment, and thereby discover trial-to-trial variability in the spike-field coherence of a rat primary motor cortical neuron to the LFP theta rhythm. Because LOST incorporates a latent stochastic auto-regressive term, LOST is able to detect oscillations when the firing rate is low, the modulation is weak, and when the modulating oscillation has a broad spectral peak.

Bursting as a source of non-linear determinism in the firing patterns of nigral dopamine neurons.

Science.gov (United States)

Jeong, Jaeseung; Shi, Wei-Xing; Hoffman, Ralph; Oh, Jihoon; Gore, John C; Bunney, Benjamin S; Peterson, Bradley S

2012-11-01

Nigral dopamine (DA) neurons in vivo exhibit complex firing patterns consisting of tonic single-spikes and phasic bursts that encode information for certain types of reward-related learning and behavior. Non-linear dynamical analysis has previously demonstrated the presence of a non-linear deterministic structure in complex firing patterns of DA neurons, yet the origin of this non-linear determinism remains unknown. In this study, we hypothesized that bursting activity is the primary source of non-linear determinism in the firing patterns of DA neurons. To test this hypothesis, we investigated the dimension complexity of inter-spike interval data recorded in vivo from bursting and non-bursting DA neurons in the chloral hydrate-anesthetized rat substantia nigra. We found that bursting DA neurons exhibited non-linear determinism in their firing patterns, whereas non-bursting DA neurons showed truly stochastic firing patterns. Determinism was also detected in the isolated burst and inter-burst interval data extracted from firing patterns of bursting neurons. Moreover, less bursting DA neurons in halothane-anesthetized rats exhibited higher dimensional spiking dynamics than do more bursting DA neurons in chloral hydrate-anesthetized rats. These results strongly indicate that bursting activity is the main source of low-dimensional, non-linear determinism in the firing patterns of DA neurons. This finding furthermore suggests that bursts are the likely carriers of meaningful information in the firing activities of DA neurons. © 2012 The Authors. European Journal of Neuroscience © 2012 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

Dopamine-signalled reward predictions generated by competitive excitation and inhibition in a spiking neural network model

Directory of Open Access Journals (Sweden)

Paul eChorley

2011-05-01

Full Text Available Dopaminergic neurons in the mammalian substantia nigra displaycharacteristic phasic responses to stimuli which reliably predict thereceipt of primary rewards. These responses have been suggested toencode reward prediction-errors similar to those used in reinforcementlearning. Here, we propose a model of dopaminergic activity in whichprediction error signals are generated by the joint action ofshort-latency excitation and long-latency inhibition, in a networkundergoing dopaminergic neuromodulation of both spike-timing dependentsynaptic plasticity and neuronal excitability. In contrast toprevious models, sensitivity to recent events is maintained by theselective modification of specific striatal synapses, efferent tocortical neurons exhibiting stimulus-specific, temporally extendedactivity patterns. Our model shows, in the presence of significantbackground activity, (i a shift in dopaminergic response from rewardto reward predicting stimuli, (ii preservation of a response tounexpected rewards, and (iii a precisely-timed below-baseline dip inactivity observed when expected rewards are omitted.

Stereoselectivity of presynaptic autoreceptors modulating dopamine release

International Nuclear Information System (INIS)

Arbilla, S.; Langer, S.Z.

1981-01-01

The effects of the (R)- and (S)-enantiomers of sulpiride and butaclamol were studied on the spontaneous and field stimulation-evoked release of total radioactivity from slices of rabbit caudate nucleus prelabelled with [ 3 H]dopamine. (S)-Sulpiride in concentrations ranging from 0.01-1μM enhanced the electrically evoked release of [ 3 H]dopamine while (R)-sulpiride was 10 times less potent than (S)-sulpiride. Exposure to (S)-butaclamol (0.1-1 μM) but not to (R)-butaclamol (0.1-10μM) enhanced the field-stimulated release of [ 3 H]dopamine. The facilitatory effects of (S)- and (R)-sulpiride and (S)-butaclamol on the stimulated release of the labelled neurotransmitter were observed under conditions in which these drugs did not modify the spontaneous outflow of radioactivity. Only the active enantiomers of sulpiride and butaclamol antagonized the inhibition by apomorphine (1μM) of the stimulated release of [ 3 H]dopamine. Our results indicate that the presynaptic inhibitory dopamine autoreceptors modulating the stimulation-evoked release of [ 3 H]dopamine in the caudate nucleus are, like the classical postsynaptic dopamine receptors, chemically stereoselective. (Auth.)

6-hydroxydopamine-induced degeneration of nigral dopamine neurons: differential effect on nigral and striatal D-1 dopamine receptors

International Nuclear Information System (INIS)

Porceddu, M.L.; Giorgi, O.; De Montis, G.; Mele, S.; Cocco, L.; Ongini, E.; Biggio, G.

1987-01-01

Dopamine-sensitive adenylate cyclase and 3 H-SCH 23390 binding parameters were measured in the rat substantia nigra and striatum 15 days after the injection of 6-hydroxydopamine into the medial forebrain bundle. The activity of nigral dopamine-sensitive adenylate cyclase and the binding of 3 H-SCH 23390 to rat nigral D-1 dopamine receptors were markedly decreased after the lesion. On the contrary, 6-hydroxydopamine-induced degeneration of the nigrostriatal dopamine pathway enhanced both adenylate cyclase activity and the density of 3 H-SCH 23390 binding sites in striatal membrane preparations. The changes in 3 H-SCH 23390 binding found in both nigral and striatal membrane preparations were associated with changes in the total number of binding sites with no modifications in their apparent affinity. The results indicate that: a) within the substantia nigra a fraction (30%) of D-1 dopamine receptors coupled to the adenylate cyclase is located on cell bodies and and/or dendrites of dopaminergic neurons; b) striatal D-1 dopamine receptors are tonically innervated by nigrostriatal afferent fibers. 24 references, 1 figure, 1 table

Dopamine reward prediction error coding.

Science.gov (United States)

Schultz, Wolfram

2016-03-01

Reward prediction errors consist of the differences between received and predicted rewards. They are crucial for basic forms of learning about rewards and make us strive for more rewards-an evolutionary beneficial trait. Most dopamine neurons in the midbrain of humans, monkeys, and rodents signal a reward prediction error; they are activated by more reward than predicted (positive prediction error), remain at baseline activity for fully predicted rewards, and show depressed activity with less reward than predicted (negative prediction error). The dopamine signal increases nonlinearly with reward value and codes formal economic utility. Drugs of addiction generate, hijack, and amplify the dopamine reward signal and induce exaggerated, uncontrolled dopamine effects on neuronal plasticity. The striatum, amygdala, and frontal cortex also show reward prediction error coding, but only in subpopulations of neurons. Thus, the important concept of reward prediction errors is implemented in neuronal hardware.

The local field potential reflects surplus spike synchrony

DEFF Research Database (Denmark)

Denker, Michael; Roux, Sébastien; Lindén, Henrik

2011-01-01

While oscillations of the local field potential (LFP) are commonly attributed to the synchronization of neuronal firing rate on the same time scale, their relationship to coincident spiking in the millisecond range is unknown. Here, we present experimental evidence to reconcile the notions...... of synchrony at the level of spiking and at the mesoscopic scale. We demonstrate that only in time intervals of significant spike synchrony that cannot be explained on the basis of firing rates, coincident spikes are better phase locked to the LFP than predicted by the locking of the individual spikes....... This effect is enhanced in periods of large LFP amplitudes. A quantitative model explains the LFP dynamics by the orchestrated spiking activity in neuronal groups that contribute the observed surplus synchrony. From the correlation analysis, we infer that neurons participate in different constellations...

Supervised Learning Based on Temporal Coding in Spiking Neural Networks.

Science.gov (United States)

Mostafa, Hesham

2017-08-01

Gradient descent training techniques are remarkably successful in training analog-valued artificial neural networks (ANNs). Such training techniques, however, do not transfer easily to spiking networks due to the spike generation hard nonlinearity and the discrete nature of spike communication. We show that in a feedforward spiking network that uses a temporal coding scheme where information is encoded in spike times instead of spike rates, the network input-output relation is differentiable almost everywhere. Moreover, this relation is piecewise linear after a transformation of variables. Methods for training ANNs thus carry directly to the training of such spiking networks as we show when training on the permutation invariant MNIST task. In contrast to rate-based spiking networks that are often used to approximate the behavior of ANNs, the networks we present spike much more sparsely and their behavior cannot be directly approximated by conventional ANNs. Our results highlight a new approach for controlling the behavior of spiking networks with realistic temporal dynamics, opening up the potential for using these networks to process spike patterns with complex temporal information.

Membrane permeable C-terminal dopamine transporter peptides attenuate amphetamine-evoked dopamine release

DEFF Research Database (Denmark)

Rickhag, Karl Mattias; Owens, WA; Winkler, Marie-Therese

2013-01-01

The dopamine transporter (DAT) is responsible for sequestration of extracellular dopamine (DA). The psychostimulant amphetamine (AMPH) is a DAT substrate, which is actively transported into the nerve terminal, eliciting vesicular depletion and reversal of DA transport via DAT. Here, we investigate......-terminal protein-protein interactions are critical for AMPH-evoked DA efflux and suggest that it may be possible to target protein-protein interactions to modulate transporter function and interfere with psychostimulant effects....

Linking investment spikes and productivity growth

NARCIS (Netherlands)

Geylani, P.C.; Stefanou, S.E.

2013-01-01

We investigate the relationship between productivity growth and investment spikes using Census Bureau’s plant-level dataset for the U.S. food manufacturing industry. There are differences in productivity growth and investment spike patterns across different sub-industries and food manufacturing

Cerebral vascular effects of hypovolemia and dopamine infusions

DEFF Research Database (Denmark)

Holst Hahn, Gitte; Heiring, Christian; Pryds, Ole

2012-01-01

Despite widespread use, effects of volume boluses and dopamine in hypotensive newborn infants remain controversial. We aimed to elucidate if hypovolemia alone impairs cerebral autoregulation (CA) and if dopamine affects cerebral vasculature.......Despite widespread use, effects of volume boluses and dopamine in hypotensive newborn infants remain controversial. We aimed to elucidate if hypovolemia alone impairs cerebral autoregulation (CA) and if dopamine affects cerebral vasculature....

A new supervised learning algorithm for spiking neurons.

Science.gov (United States)

Xu, Yan; Zeng, Xiaoqin; Zhong, Shuiming

2013-06-01

The purpose of supervised learning with temporal encoding for spiking neurons is to make the neurons emit a specific spike train encoded by the precise firing times of spikes. If only running time is considered, the supervised learning for a spiking neuron is equivalent to distinguishing the times of desired output spikes and the other time during the running process of the neuron through adjusting synaptic weights, which can be regarded as a classification problem. Based on this idea, this letter proposes a new supervised learning method for spiking neurons with temporal encoding; it first transforms the supervised learning into a classification problem and then solves the problem by using the perceptron learning rule. The experiment results show that the proposed method has higher learning accuracy and efficiency over the existing learning methods, so it is more powerful for solving complex and real-time problems.

Surfing a spike wave down the ventral stream.

Science.gov (United States)

VanRullen, Rufin; Thorpe, Simon J

2002-10-01

Numerous theories of neural processing, often motivated by experimental observations, have explored the computational properties of neural codes based on the absolute or relative timing of spikes in spike trains. Spiking neuron models and theories however, as well as their experimental counterparts, have generally been limited to the simulation or observation of isolated neurons, isolated spike trains, or reduced neural populations. Such theories would therefore seem inappropriate to capture the properties of a neural code relying on temporal spike patterns distributed across large neuronal populations. Here we report a range of computer simulations and theoretical considerations that were designed to explore the possibilities of one such code and its relevance for visual processing. In a unified framework where the relation between stimulus saliency and spike relative timing plays the central role, we describe how the ventral stream of the visual system could process natural input scenes and extract meaningful information, both rapidly and reliably. The first wave of spikes generated in the retina in response to a visual stimulation carries information explicitly in its spatio-temporal structure: the most salient information is represented by the first spikes over the population. This spike wave, propagating through a hierarchy of visual areas, is regenerated at each processing stage, where its temporal structure can be modified by (i). the selectivity of the cortical neurons, (ii). lateral interactions and (iii). top-down attentional influences from higher order cortical areas. The resulting model could account for the remarkable efficiency and rapidity of processing observed in the primate visual system.

Serotonin-S2 and dopamine-D2 receptors are the same size in membranes

International Nuclear Information System (INIS)

Brann, M.R.

1985-01-01

Target size analysis was used to compare the sizes of serotonin-S2 and dopamine-D2 receptors in rat brain membranes. The sizes of these receptors were standardized by comparison with the muscarinic receptor, a receptor of known size. The number of serotonin-S2 receptors labeled with (3H)ketanserin or (3H)spiperone in frontal cortex decreased as an exponential function of radiation dose, and receptor affinity was not affected. The number of dopamine-D2 receptors labeled with (3H)spiperone in striatum also decreased as an exponential function of radiation dose, and D2 and S2 receptors were equally sensitive to radiation. In both striatum and frontal cortex, the number of muscarinic receptors labeled with (3H)QNB decreased as an exponential function of radiation dose, and were much less sensitive to radiation than S2 and D2 receptors. These data indicate that in rat brain membranes, S2 and D2 receptors are of similar size, and both molecules are much larger than the muscarinic receptor

Olfactory bulb short axon cell release of GABA and dopamine produces a temporally biphasic inhibition-excitation response in external tufted cells.

Science.gov (United States)

Liu, Shaolin; Plachez, Celine; Shao, Zuoyi; Puche, Adam; Shipley, Michael T

2013-02-13

Evidence for coexpression of two or more classic neurotransmitters in neurons has increased, but less is known about cotransmission. Ventral tegmental area (VTA) neurons corelease dopamine (DA), the excitatory transmitter glutamate, and the inhibitory transmitter GABA onto target cells in the striatum. Olfactory bulb (OB) short axon cells (SACs) form interglomerular connections and coexpress markers for DA and GABA. Using an optogenetic approach, we provide evidence that mouse OB SACs release both GABA and DA onto external tufted cells (ETCs) in other glomeruli. Optical activation of channelrhodopsin specifically expressed in DAergic SACs produced a GABA(A) receptor-mediated monosynaptic inhibitory response, followed by DA-D(1)-like receptor-mediated excitatory response in ETCs. The GABA(A) receptor-mediated hyperpolarization activates I(h) current in ETCs; synaptically released DA increases I(h), which enhances postinhibitory rebound spiking. Thus, the opposing actions of synaptically released GABA and DA are functionally integrated by I(h) to generate an inhibition-to-excitation "switch" in ETCs. Consistent with the established role of I(h) in ETC burst firing, we show that endogenous DA release increases ETC spontaneous bursting frequency. ETCs transmit sensory signals to mitral/tufted output neurons and drive intraglomerular inhibition to shape glomerulus output to downstream olfactory networks. GABA and DA cotransmission from SACs to ETCs may play a key role in regulating output coding across the glomerular array.

Spike timing precision of neuronal circuits.

Science.gov (United States)

Kilinc, Deniz; Demir, Alper

2018-04-17

Spike timing is believed to be a key factor in sensory information encoding and computations performed by the neurons and neuronal circuits. However, the considerable noise and variability, arising from the inherently stochastic mechanisms that exist in the neurons and the synapses, degrade spike timing precision. Computational modeling can help decipher the mechanisms utilized by the neuronal circuits in order to regulate timing precision. In this paper, we utilize semi-analytical techniques, which were adapted from previously developed methods for electronic circuits, for the stochastic characterization of neuronal circuits. These techniques, which are orders of magnitude faster than traditional Monte Carlo type simulations, can be used to directly compute the spike timing jitter variance, power spectral densities, correlation functions, and other stochastic characterizations of neuronal circuit operation. We consider three distinct neuronal circuit motifs: Feedback inhibition, synaptic integration, and synaptic coupling. First, we show that both the spike timing precision and the energy efficiency of a spiking neuron are improved with feedback inhibition. We unveil the underlying mechanism through which this is achieved. Then, we demonstrate that a neuron can improve on the timing precision of its synaptic inputs, coming from multiple sources, via synaptic integration: The phase of the output spikes of the integrator neuron has the same variance as that of the sample average of the phases of its inputs. Finally, we reveal that weak synaptic coupling among neurons, in a fully connected network, enables them to behave like a single neuron with a larger membrane area, resulting in an improvement in the timing precision through cooperation.

Causal Inference and Explaining Away in a Spiking Network

Science.gov (United States)

Moreno-Bote, Rubén; Drugowitsch, Jan

2015-01-01

While the brain uses spiking neurons for communication, theoretical research on brain computations has mostly focused on non-spiking networks. The nature of spike-based algorithms that achieve complex computations, such as object probabilistic inference, is largely unknown. Here we demonstrate that a family of high-dimensional quadratic optimization problems with non-negativity constraints can be solved exactly and efficiently by a network of spiking neurons. The network naturally imposes the non-negativity of causal contributions that is fundamental to causal inference, and uses simple operations, such as linear synapses with realistic time constants, and neural spike generation and reset non-linearities. The network infers the set of most likely causes from an observation using explaining away, which is dynamically implemented by spike-based, tuned inhibition. The algorithm performs remarkably well even when the network intrinsically generates variable spike trains, the timing of spikes is scrambled by external sources of noise, or the network is mistuned. This type of network might underlie tasks such as odor identification and classification. PMID:26621426

Neuro-Inspired Spike-Based Motion: From Dynamic Vision Sensor to Robot Motor Open-Loop Control through Spike-VITE

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Fernando Perez-Peña

2013-11-01

Full Text Available In this paper we present a complete spike-based architecture: from a Dynamic Vision Sensor (retina to a stereo head robotic platform. The aim of this research is to reproduce intended movements performed by humans taking into account as many features as possible from the biological point of view. This paper fills the gap between current spike silicon sensors and robotic actuators by applying a spike processing strategy to the data flows in real time. The architecture is divided into layers: the retina, visual information processing, the trajectory generator layer which uses a neuroinspired algorithm (SVITE that can be replicated into as many times as DoF the robot has; and finally the actuation layer to supply the spikes to the robot (using PFM. All the layers do their tasks in a spike-processing mode, and they communicate each other through the neuro-inspired AER protocol. The open-loop controller is implemented on FPGA using AER interfaces developed by RTC Lab. Experimental results reveal the viability of this spike-based controller. Two main advantages are: low hardware resources (2% of a Xilinx Spartan 6 and power requirements (3.4 W to control a robot with a high number of DoF (up to 100 for a Xilinx Spartan 6. It also evidences the suitable use of AER as a communication protocol between processing and actuation.

Neuro-Inspired Spike-Based Motion: From Dynamic Vision Sensor to Robot Motor Open-Loop Control through Spike-VITE

Science.gov (United States)

Perez-Peña, Fernando; Morgado-Estevez, Arturo; Linares-Barranco, Alejandro; Jimenez-Fernandez, Angel; Gomez-Rodriguez, Francisco; Jimenez-Moreno, Gabriel; Lopez-Coronado, Juan

2013-01-01

In this paper we present a complete spike-based architecture: from a Dynamic Vision Sensor (retina) to a stereo head robotic platform. The aim of this research is to reproduce intended movements performed by humans taking into account as many features as possible from the biological point of view. This paper fills the gap between current spike silicon sensors and robotic actuators by applying a spike processing strategy to the data flows in real time. The architecture is divided into layers: the retina, visual information processing, the trajectory generator layer which uses a neuroinspired algorithm (SVITE) that can be replicated into as many times as DoF the robot has; and finally the actuation layer to supply the spikes to the robot (using PFM). All the layers do their tasks in a spike-processing mode, and they communicate each other through the neuro-inspired AER protocol. The open-loop controller is implemented on FPGA using AER interfaces developed by RTC Lab. Experimental results reveal the viability of this spike-based controller. Two main advantages are: low hardware resources (2% of a Xilinx Spartan 6) and power requirements (3.4 W) to control a robot with a high number of DoF (up to 100 for a Xilinx Spartan 6). It also evidences the suitable use of AER as a communication protocol between processing and actuation. PMID:24264330

Retinal dopamine mediates multiple dimensions of light-adapted vision.

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Jackson, Chad R; Ruan, Guo-Xiang; Aseem, Fazila; Abey, Jane; Gamble, Karen; Stanwood, Greg; Palmiter, Richard D; Iuvone, P Michael; McMahon, Douglas G

2012-07-04

Dopamine is a key neuromodulator in the retina and brain that supports motor, cognitive, and visual function. Here, we developed a mouse model on a C57 background in which expression of the rate-limiting enzyme for dopamine synthesis, tyrosine hydroxylase, is specifically disrupted in the retina. This model enabled assessment of the overall role of retinal dopamine in vision using electrophysiological (electroretinogram), psychophysical (optokinetic tracking), and pharmacological techniques. Significant disruptions were observed in high-resolution, light-adapted vision caused by specific deficits in light responses, contrast sensitivity, acuity, and circadian rhythms in this retinal dopamine-depleted mouse model. These global effects of retinal dopamine on vision are driven by the differential actions of dopamine D1 and D4 receptors on specific retinal functions and appear to be due to the ongoing bioavailability of dopamine rather than developmental effects. Together, our data indicate that dopamine is necessary for the circadian nature of light-adapted vision as well as optimal contrast detection and acuity.

Free and conjugated dopamine in human ventricular fluid

International Nuclear Information System (INIS)

Sharpless, N.S.; Thal, L.J.; Wolfson, L.I.; Tabaddor, K.; Tyce, G.M.; Waltz, J.M.

1981-01-01

Free dopamine and an acid hydrolyzable conjugate of dopamine were measured in human ventricular fluid specimens with a radioenzymatic assay and by high performance liquid chromatography (HPLC) with electrochemical detection. Only trace amounts of free norepinephrine and dopamine were detected in ventricular fluid from patients with movement disorders. When the ventricular fluid was hydrolyzed by heating in HClO 4 or by lyophilization in dilute HClO 4 , however, a substantial amount of free dopamine was released. Values for free plus conjugated dopamine in ventricular fluid from patients who had never taken L-DOPA ranged from 139 to 340 pg/ml when determined by HPLC and from 223 to 428 pg/ml when measured radioenzymatically. The correlation coefficient for values obtained by the two methods in the same sample of CSF was 0.94 (P<0.001). Patients who had been treated with L-DOPA had higher levels of conjugated dopamine in their ventricular CSF which correlated inversely with the time between the last dose of L-DOPA and withdrawal of the ventricular fluid. Additionally, one patient with acute cerebral trauma had elevated levels of free norepinephrine and both free and conjugated dopamine in his ventricular fluid. Conjugation may be an important inactivation pathway for released dopamine in man. (Auth.)

Antagonism of presynaptic dopamine receptors by phenothiazine drug metabolites

International Nuclear Information System (INIS)

Nowak, J.Z.; Arbilla, S.; Langer, S.Z.; Dahl, S.G.

1990-01-01

Electrically evoked release of dopamine from the caudate nucleus is reduced by the dopamine receptor agonists, apomorphine and bromocriptine, and facilitated by neuroleptic drugs, which act as dopamine autoreceptor antagonists. The potencies of chlorpromazine, fluphenazine, levomepromazine and their hydroxy-metabolites in modulating electrically evoked release of dopamine were examined by superfusion of rabbit caudate nucleus slices pre-incubated with 3 H-dopamine. O-Desmethyl levomepromazine, 3-hydroxy- and 7-hydroxy metabolites of chlorpromazine and levomepromazine facilitated electrically evoked release of 3 H-dopamine, having potencies similar to that of the parent compounds. 7-Hydroxy fluphenazine was less active than fluphenazine in this system. These results indicate that phenolic metabolites of chlorpromazine and levomepromazine, but not of fluphenazine, may contribute to effects of the drugs mediated by presynaptic dopamine receptors

The multiplicity of the D-1 dopamine receptor

International Nuclear Information System (INIS)

Mailman, R.B.; Klits, C.D.; Lewis, M.H.; Rollema, H.; Schulz, D.W.; Wyrick, S.

1986-01-01

The authors have sought to address two questions of some neuropharmacological importance in this chapter. First, they examine the nature of mechanisms by which dopamine initiates many psychopharmacological effects and, second, they study the possibility of designing highly specific drugs targeted only at a selected subpopulation of dopamine receptors. Effects of SCH23390 and haloperidol on concentrations of dopamine, DOPAC, and HVA in various rat brain regions are shown. In addition, the effects of SCH23390 on the in vivo binding of dipropyl-5, 6-ADTN are shown. Differential distribution of a dopamine sensitive adenylate cyclase and ( 3 H)-SCH23390 binding sites are examined. A model is presented of D 1 dopamine receptors in membrane, illustrating the lack of identity of some of the ( 3 H)-SCH23390 binding sites with the dopamine receptor linked to stimulation of cAMP synthesis

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

Directory of Open Access Journals (Sweden)

Zedong Bi

2016-08-01

Full Text Available 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.

Joint Probability-Based Neuronal Spike Train Classification

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Yan Chen

2009-01-01

Full Text Available Neuronal spike trains are used by the nervous system to encode and transmit information. Euclidean distance-based methods (EDBMs have been applied to quantify the similarity between temporally-discretized spike trains and model responses. In this study, using the same discretization procedure, we developed and applied a joint probability-based method (JPBM to classify individual spike trains of slowly adapting pulmonary stretch receptors (SARs. The activity of individual SARs was recorded in anaesthetized, paralysed adult male rabbits, which were artificially-ventilated at constant rate and one of three different volumes. Two-thirds of the responses to the 600 stimuli presented at each volume were used to construct three response models (one for each stimulus volume consisting of a series of time bins, each with spike probabilities. The remaining one-third of the responses where used as test responses to be classified into one of the three model responses. This was done by computing the joint probability of observing the same series of events (spikes or no spikes, dictated by the test response in a given model and determining which probability of the three was highest. The JPBM generally produced better classification accuracy than the EDBM, and both performed well above chance. Both methods were similarly affected by variations in discretization parameters, response epoch duration, and two different response alignment strategies. Increasing bin widths increased classification accuracy, which also improved with increased observation time, but primarily during periods of increasing lung inflation. Thus, the JPBM is a simple and effective method performing spike train classification.

Fitting neuron models to spike trains

Directory of Open Access Journals (Sweden)

Cyrille eRossant

2011-02-01

Full Text Available Computational modeling is increasingly used to understand the function of neural circuitsin systems neuroscience.These studies require models of individual neurons with realisticinput-output properties.Recently, it was found that spiking models can accurately predict theprecisely timed spike trains produced by cortical neurons in response tosomatically injected currents,if properly fitted. This requires fitting techniques that are efficientand flexible enough to easily test different candidate models.We present a generic solution, based on the Brian simulator(a neural network simulator in Python, which allowsthe user to define and fit arbitrary neuron models to electrophysiological recordings.It relies on vectorization and parallel computing techniques toachieve efficiency.We demonstrate its use on neural recordings in the barrel cortex andin the auditory brainstem, and confirm that simple adaptive spiking modelscan accurately predict the response of cortical neurons. Finally, we show how a complexmulticompartmental model can be reduced to a simple effective spiking model.

Detection and Evaluation of Spatio-Temporal Spike Patterns in Massively Parallel Spike Train Data with SPADE

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Pietro Quaglio

2017-05-01

Full Text Available Repeated, precise sequences of spikes are largely considered a signature of activation of cell assemblies. These repeated sequences are commonly known under the name of spatio-temporal patterns (STPs. STPs are hypothesized to play a role in the communication of information in the computational process operated by the cerebral cortex. A variety of statistical methods for the detection of STPs have been developed and applied to electrophysiological recordings, but such methods scale poorly with the current size of available parallel spike train recordings (more than 100 neurons. In this work, we introduce a novel method capable of overcoming the computational and statistical limits of existing analysis techniques in detecting repeating STPs within massively parallel spike trains (MPST. We employ advanced data mining techniques to efficiently extract repeating sequences of spikes from the data. Then, we introduce and compare two alternative approaches to distinguish statistically significant patterns from chance sequences. The first approach uses a measure known as conceptual stability, of which we investigate a computationally cheap approximation for applications to such large data sets. The second approach is based on the evaluation of pattern statistical significance. In particular, we provide an extension to STPs of a method we recently introduced for the evaluation of statistical significance of synchronous spike patterns. The performance of the two approaches is evaluated in terms of computational load and statistical power on a variety of artificial data sets that replicate specific features of experimental data. Both methods provide an effective and robust procedure for detection of STPs in MPST data. The method based on significance evaluation shows the best overall performance, although at a higher computational cost. We name the novel procedure the spatio-temporal Spike PAttern Detection and Evaluation (SPADE analysis.

Increased brain dopamine and dopamine receptors in schizophrenia

International Nuclear Information System (INIS)

Mackay, A.V.; Iversen, L.L.; Rossor, M.; Spokes, E.; Bird, E.; Arregui, A.; Creese, I.; Synder, S.H.

1982-01-01

In postmortem samples of caudate nucleus and nucleus accumbens from 48 schizophrenic patients, there were significant increases in both the maximum number of binding sites (Bmax) and the apparent dissociation constant (KD) for tritiated spiperone. The increase in apparent KD probably reflects the presence of residual neuroleptic drugs, but changes in Bmax for tritiated spiperone reflect genuine changes in receptor numbers. The increases in receptors were seen only in patients in whom neuroleptic medication had been maintained until the time of death, indicating that they may be entirely iatrogenic. Dopamine measurements for a larger series of schizophrenic and control cases (n greater than 60) show significantly increased concentrations in both the nucleus accumbens and caudate nucleus. The changes in dopamine were not obviously related to neuroleptic medication and, unlike the receptor changes, were most severe in younger patients

Constructing Precisely Computing Networks with Biophysical Spiking Neurons.

Science.gov (United States)

Schwemmer, Michael A; Fairhall, Adrienne L; Denéve, Sophie; Shea-Brown, Eric T

2015-07-15

While spike timing has been shown to carry detailed stimulus information at the sensory periphery, its possible role in network computation is less clear. Most models of computation by neural networks are based on population firing rates. In equivalent spiking implementations, firing is assumed to be random such that averaging across populations of neurons recovers the rate-based approach. Recently, however, Denéve and colleagues have suggested that the spiking behavior of neurons may be fundamental to how neuronal networks compute, with precise spike timing determined by each neuron's contribution to producing the desired output (Boerlin and Denéve, 2011; Boerlin et al., 2013). By postulating that each neuron fires to reduce the error in the network's output, it was demonstrated that linear computations can be performed by networks of integrate-and-fire neurons that communicate through instantaneous synapses. This left open, however, the possibility that realistic networks, with conductance-based neurons with subthreshold nonlinearity and the slower timescales of biophysical synapses, may not fit into this framework. Here, we show how the spike-based approach can be extended to biophysically plausible networks. We then show that our network reproduces a number of key features of cortical networks including irregular and Poisson-like spike times and a tight balance between excitation and inhibition. Lastly, we discuss how the behavior of our model scales with network size or with the number of neurons "recorded" from a larger computing network. These results significantly increase the biological plausibility of the spike-based approach to network computation. We derive a network of neurons with standard spike-generating currents and synapses with realistic timescales that computes based upon the principle that the precise timing of each spike is important for the computation. We then show that our network reproduces a number of key features of cortical networks

Spatial Frequency Selectivity Is Impaired in Dopamine D2 Receptor Knockout Mice

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Souza, Bruno Oliveira Ferreira; Abou Rjeili, Mira; Quintana, Clémentine; Beaulieu, Jean M.; Casanova, Christian

2018-01-01

Dopamine is a neurotransmitter implicated in several brain functions, including vision. In the present study, we investigated the impacts of the lack of D2 dopamine receptors on the structure and function of the primary visual cortex (V1) of D2-KO mice using optical imaging of intrinsic signals. Retinotopic maps were generated in order to measure anatomo-functional parameters such as V1 shape, cortical magnification factor, scatter, and ocular dominance. Contrast sensitivity and spatial frequency selectivity (SF) functions were computed from responses to drifting gratings. When compared to control mice, none of the parameters of the retinotopic maps were affected by D2 receptor loss of function. While the contrast sensitivity function of D2-KO mice did not differ from their wild-type counterparts, SF selectivity function was significantly affected as the optimal SF and the high cut-off frequency (p D2-KO than in WT mice. These findings show that the lack of function of D2 dopamine receptors had no influence on cortical structure whereas it had a significant impact on the spatial frequency selectivity and high cut-off. Taken together, our results suggest that D2 receptors play a specific role on the processing of spatial features in early visual cortex while they do not seem to participate in its development. PMID:29379422

A Simple Deep Learning Method for Neuronal Spike Sorting

Science.gov (United States)

Yang, Kai; Wu, Haifeng; Zeng, Yu

2017-10-01

Spike sorting is one of key technique to understand brain activity. With the development of modern electrophysiology technology, some recent multi-electrode technologies have been able to record the activity of thousands of neuronal spikes simultaneously. The spike sorting in this case will increase the computational complexity of conventional sorting algorithms. In this paper, we will focus spike sorting on how to reduce the complexity, and introduce a deep learning algorithm, principal component analysis network (PCANet) to spike sorting. The introduced method starts from a conventional model and establish a Toeplitz matrix. Through the column vectors in the matrix, we trains a PCANet, where some eigenvalue vectors of spikes could be extracted. Finally, support vector machine (SVM) is used to sort spikes. In experiments, we choose two groups of simulated data from public databases availably and compare this introduced method with conventional methods. The results indicate that the introduced method indeed has lower complexity with the same sorting errors as the conventional methods.

Human dopamine receptor and its uses

Energy Technology Data Exchange (ETDEWEB)

Civelli, Olivier (Portland, OR); Van Tol, Hubert Henri-Marie (Toronto, CA)

1999-01-01

The present invention is directed toward the isolation, characterization and pharmacological use of the human D4 dopamine receptor. The nucleotide sequence of the gene corresponding to this receptor and alleleic variant thereof are provided by the invention. The invention also includes recombinant eukaryotic expression constructs capable of expressing the human D4 dopamine receptor in cultures of transformed eukaryotic cells. The invention provides cultures of transformed eukaryotic cells which synthesize the human D4 dopamine receptor, and methods for characterizing novel psychotropic compounds using such cultures.

Recent progress in multi-electrode spike sorting methods.

Science.gov (United States)

Lefebvre, Baptiste; Yger, Pierre; Marre, Olivier

2016-11-01

In recent years, arrays of extracellular electrodes have been developed and manufactured to record simultaneously from hundreds of electrodes packed with a high density. These recordings should allow neuroscientists to reconstruct the individual activity of the neurons spiking in the vicinity of these electrodes, with the help of signal processing algorithms. Algorithms need to solve a source separation problem, also known as spike sorting. However, these new devices challenge the classical way to do spike sorting. Here we review different methods that have been developed to sort spikes from these large-scale recordings. We describe the common properties of these algorithms, as well as their main differences. Finally, we outline the issues that remain to be solved by future spike sorting algorithms. Copyright © 2017 Elsevier Ltd. All rights reserved.

CRYSTAL STRUCTURE OF HUMAN DOPAMINE BETA-HYDROXYLASE

DEFF Research Database (Denmark)

2017-01-01

A crystalline form of dopamine β-hydroxylase is provided. X-ray crystallography reveals the space group and cell dimensions, as well as the atomic coordinates. The information can be used for identifying one or more modulators of dopamine β-hydroxylase, which can then be chemically synthesised...... and used in treatment. A process for preparing the crystalline form of human dopamine β-hydroxylase is also provided....

Multineuron spike train analysis with R-convolution linear combination kernel.

Science.gov (United States)

Tezuka, Taro

2018-06-01

A spike train kernel provides an effective way of decoding information represented by a spike train. Some spike train kernels have been extended to multineuron spike trains, which are simultaneously recorded spike trains obtained from multiple neurons. However, most of these multineuron extensions were carried out in a kernel-specific manner. In this paper, a general framework is proposed for extending any single-neuron spike train kernel to multineuron spike trains, based on the R-convolution kernel. Special subclasses of the proposed R-convolution linear combination kernel are explored. These subclasses have a smaller number of parameters and make optimization tractable when the size of data is limited. The proposed kernel was evaluated using Gaussian process regression for multineuron spike trains recorded from an animal brain. It was compared with the sum kernel and the population Spikernel, which are existing ways of decoding multineuron spike trains using kernels. The results showed that the proposed approach performs better than these kernels and also other commonly used neural decoding methods. Copyright © 2018 Elsevier Ltd. All rights reserved.

Flipped Phenyl Ring Orientations of Dopamine Binding with Human and Drosophila Dopamine Transporters: Remarkable Role of Three Nonconserved Residues.

Science.gov (United States)

Yuan, Yaxia; Zhu, Jun; Zhan, Chang-Guo

2018-03-09

Molecular modeling and molecular dynamics simulations were performed in the present study to examine the modes of dopamine binding with human and Drosophila dopamine transporters (hDAT and dDAT). The computational data revealed flipped binding orientations of dopamine in hDAT and dDAT due to the major differences in three key residues (S149, G153, and A423 of hDAT vs A117, D121, and S422 of dDAT) in the binding pocket. These three residues dictate the binding orientation of dopamine in the binding pocket, as the aromatic ring of dopamine tends to take an orientation with both the para- and meta-hydroxyl groups being close to polar residues and away from nonpolar residues of the protein. The flipped binding orientations of dopamine in hDAT and dDAT clearly demonstrate a generally valuable insight concerning how the species difference could drastically affect the protein-ligand binding modes, demonstrating that the species difference, which is a factor rarely considered in early drug design stage, must be accounted for throughout the ligand/drug design and discovery processes in general.

Decreased prefrontal cortical dopamine transmission in alcoholism.

Science.gov (United States)

Narendran, Rajesh; Mason, Neale Scott; Paris, Jennifer; Himes, Michael L; Douaihy, Antoine B; Frankle, W Gordon

2014-08-01

Basic studies have demonstrated that optimal levels of prefrontal cortical dopamine are critical to various executive functions such as working memory, attention, inhibitory control, and risk/reward decisions, all of which are impaired in addictive disorders such as alcoholism. Based on this and imaging studies of alcoholism that have demonstrated less dopamine in the striatum, the authors hypothesized decreased dopamine transmission in the prefrontal cortex in persons with alcohol dependence. To test this hypothesis, amphetamine and [11C]FLB 457 positron emission tomography were used to measure cortical dopamine transmission in 21 recently abstinent persons with alcohol dependence and 21 matched healthy comparison subjects. [11C]FLB 457 binding potential, specific compared to nondisplaceable uptake (BPND), was measured in subjects with kinetic analysis using the arterial input function both before and after 0.5 mg kg-1 of d-amphetamine. Amphetamine-induced displacement of [11C]FLB 457 binding potential (ΔBPND) was significantly smaller in the cortical regions in the alcohol-dependent group compared with the healthy comparison group. Cortical regions that demonstrated lower dopamine transmission in the alcohol-dependent group included the dorsolateral prefrontal cortex, medial prefrontal cortex, orbital frontal cortex, temporal cortex, and medial temporal lobe. The results of this study, for the first time, unambiguously demonstrate decreased dopamine transmission in the cortex in alcoholism. Further research is necessary to understand the clinical relevance of decreased cortical dopamine as to whether it is related to impaired executive function, relapse, and outcome in alcoholism.

Dopamine, T cells and multiple sclerosis (MS).

Science.gov (United States)

Levite, Mia; Marino, Franca; Cosentino, Marco

2017-05-01

Dopamine is a key neurotransmitter that induces critical effects in the nervous system and in many peripheral organs, via 5 dopamine receptors (DRs): D1R-D5R. Dopamine also induces many direct and very potent effects on many DR-expressing immune cells, primarily T cells and dendritic cells. In this review, we focus only on dopamine receptors, effects and production in T cells. Dopamine by itself (at an optimal concentration of~0.1 nM) induces multiple function of resting normal human T cells, among them: T cell adhesion, chemotactic migration, homing, cytokine secretion and others. Interestingly, dopamine activates resting effector T cells (Teffs), but suppresses regulatory T cells (Tregs), and both effects lead eventually to Teff activation. Dopamine-induced effects on T cells are dynamic, context-sensitive and determined by the: T cell activation state, T cell type, DR type, and dopamine concentration. Dopamine itself, and also few dopaminergic molecules/ drugs that are in clinical use for cardiac, neurological and other non-immune indications, have direct effects on human T cells (summarized in this review). These dopaminergic drugs include: dopamine = intropin, L-DOPA, bromocriptine, pramipexole, pergolide, haloperidol, pimozide, and amantadine. Other dopaminergic drugs were not yet tested for their direct effects on T cells. Extensive evidence in multiple sclerosis (MS) and experimental autoimmune encephalomyelitis (EAE) show dopaminergic dysregulations in T cells in these diseases: D1-like DRs are decreased in Teffs of MS patients, and dopamine does not affect these cells. In contrast, D1-like DRs are increased in Tregs of MS patients, possibly causing functional Treg impairment in MS. Treatment of MS patients with interferon β (IFN-β) increases D1-like DRs and decreases D2-like DRs in Teffs, decreases D1-like DRs in Tregs, and most important: restores responsiveness of patient's Teffs to dopamine. DR agonists and antagonists confer some benefits in

Comparison of electrodialytic removal of Cu from spiked kaolinite, spiked soil and industrially polluted soil

DEFF Research Database (Denmark)

Ottosen, Lisbeth M.; Lepkova, Katarina; Kubal, Martin

2006-01-01

Electrokinetic remediation methods for removal of heavy metals from polluted soils have been subjected for quite intense research during the past years since these methods are well suitable for fine-grained soils where other remediation methods fail. Electrodialytic remediation is an electrokinetic...... remediation method which is based on applying an electric DC field and the use of ion exchange membranes that ensures the main transport of heavy metals to be out of the pollutes soil. An experimental investigation was made with electrodialytic removal of Cu from spiked kaolinite, spiked soil and industrially...... polluted soil under the same operational conditions (constant current density 0.2 mA/cm2 and duration 28 days). The results of the present paper show that caution must be taken when generalising results obtained in spiked kaolinite to remediation of industrially polluted soils, as it was shown...

Toxicity of nickel-spiked freshwater sediments to benthic invertebrates-Spiking methodology, species sensitivity, and nickel bioavailability

Science.gov (United States)

Besser, John M.; Brumbaugh, William G.; Kemble, Nile E.; Ivey, Chris D.; Kunz, James L.; Ingersoll, Christopher G.; Rudel, David

2011-01-01

This report summarizes data from studies of the toxicity and bioavailability of nickel in nickel-spiked freshwater sediments. The goal of these studies was to generate toxicity and chemistry data to support development of broadly applicable sediment quality guidelines for nickel. The studies were conducted as three tasks, which are presented here as three chapters: Task 1, Development of methods for preparation and toxicity testing of nickel-spiked freshwater sediments; Task 2, Sensitivity of benthic invertebrates to toxicity of nickel-spiked freshwater sediments; and Task 3, Effect of sediment characteristics on nickel bioavailability. Appendices with additional methodological details and raw chemistry and toxicity data for the three tasks are available online at http://pubs.usgs.gov/sir/2011/5225/downloads/.

Frequency-Dependent Modulation of Dopamine Release by Nicotine and Dopamine D1 Receptor Ligands: An In Vitro Fast Cyclic Voltammetry Study in Rat Striatum.

Science.gov (United States)

Goutier, W; Lowry, J P; McCreary, A C; O'Connor, J J

2016-05-01

Nicotine is a highly addictive drug and exerts this effect partially through the modulation of dopamine release and increasing extracellular dopamine in regions such as the brain reward systems. Nicotine acts in these regions on nicotinic acetylcholine receptors. The effect of nicotine on the frequency dependent modulation of dopamine release is well established and the purpose of this study was to investigate whether dopamine D1 receptor (D1R) ligands have an influence on this. Using fast cyclic voltammetry and rat corticostriatal slices, we show that D1R ligands are able to modulate the effect of nicotine on dopamine release. Nicotine (500 nM) induced a decrease in dopamine efflux at low frequency (single pulse or five pulses at 10 Hz) and an increase at high frequency (100 Hz) electrical field stimulation. The D1R agonist SKF-38393, whilst having no effect on dopamine release on its own or on the effect of nicotine upon multiple pulse evoked dopamine release, did significantly prevent and reverse the effect of nicotine on single pulse dopamine release. Interestingly similar results were obtained with the D1R antagonist SCH-23390. In this study we have demonstrated that the modulation of dopamine release by nicotine can be altered by D1R ligands, but only when evoked by single pulse stimulation, and are likely working via cholinergic interneuron driven dopamine release.

Dopamine D2 receptors photolabeled by iodo-azido-clebopride.

Science.gov (United States)

Niznik, H B; Dumbrille-Ross, A; Guan, J H; Neumeyer, J L; Seeman, P

1985-04-19

Iodo-azido-clebopride, a photoaffinity compound for dopamine D2 receptors, had high affinity for canine brain striatal dopamine D2 receptors with a dissociation constant (Kd) of 14 nM. Irradiation of striatal homogenate with iodo-azido-clebopride irreversibly inactivated 50% of dopamine D2 receptors at 20 nM (as indicated by subsequent [3H]spiperone binding). Dopamine agonists and antagonists prevented this photo-inactivation with the appropriate rank-order of potency. Striatal dopamine D1, serotonin (S2), alpha 1- and beta-adrenoceptors were not significantly inactivated following irradiation with iodo-azido-clebopride. Thus, iodo-azido-clebopride is a selective photoaffinity probe for dopamine D2 receptors, the radiolabelled form of which may aid in the molecular characterization of these proteins.

ILLICIT DOPAMINE TRANSIENTS: RECONCILING ACTIONS OF ABUSED DRUGS

Science.gov (United States)

Covey, Dan P.; Roitman, Mitchell F.; Garris, Paul A.

2014-01-01

Phasic increases in brain dopamine are required for cue-directed reward seeking. While compelling within the framework of appetitive behavior, the view that illicit drugs hijack reward circuits by hyper-activating these dopamine transients is inconsistent with established psychostimulant pharmacology. However, recent work reclassifying amphetamine (AMPH), cocaine, and other addictive dopamine-transporter inhibitors (DAT-Is) supports transient hyper-activation as a unifying hypothesis of abused drugs. We argue here that reclassification also identifies generating burst firing by dopamine neurons as a keystone action. Unlike natural rewards, which are processed by sensory systems, drugs act directly on the brain. Consequently, to mimic natural reward and exploit reward circuits, dopamine transients must be elicited de novo. Of available drug targets, only burst firing achieves this essential outcome. PMID:24656971

Dopamine agonist withdrawal syndrome: implications for patient care.

Science.gov (United States)

Nirenberg, Melissa J

2013-08-01

Dopamine agonists are effective treatments for a variety of indications, including Parkinson's disease and restless legs syndrome, but may have serious side effects, such as orthostatic hypotension, hallucinations, and impulse control disorders (including pathological gambling, compulsive eating, compulsive shopping/buying, and hypersexuality). The most effective way to alleviate these side effects is to taper or discontinue dopamine agonist therapy. A subset of patients who taper a dopamine agonist, however, develop dopamine agonist withdrawal syndrome (DAWS), which has been defined as a severe, stereotyped cluster of physical and psychological symptoms that correlate with dopamine agonist withdrawal in a dose-dependent manner, cause clinically significant distress or social/occupational dysfunction, are refractory to levodopa and other dopaminergic medications, and cannot be accounted for by other clinical factors. The symptoms of DAWS include anxiety, panic attacks, dysphoria, depression, agitation, irritability, suicidal ideation, fatigue, orthostatic hypotension, nausea, vomiting, diaphoresis, generalized pain, and drug cravings. The severity and prognosis of DAWS is highly variable. While some patients have transient symptoms and make a full recovery, others have a protracted withdrawal syndrome lasting for months to years, and therefore may be unwilling or unable to discontinue DA therapy. Impulse control disorders appear to be a major risk factor for DAWS, and are present in virtually all affected patients. Thus, patients who are unable to discontinue dopamine agonist therapy may experience chronic impulse control disorders. At the current time, there are no known effective treatments for DAWS. For this reason, providers are urged to use dopamine agonists judiciously, warn patients about the risks of DAWS prior to the initiation of dopamine agonist therapy, and follow patients closely for withdrawal symptoms during dopamine agonist taper.

ViSAPy: a Python tool for biophysics-based generation of virtual spiking activity for evaluation of spike-sorting algorithms.

Science.gov (United States)

Hagen, Espen; Ness, Torbjørn V; Khosrowshahi, Amir; Sørensen, Christina; Fyhn, Marianne; Hafting, Torkel; Franke, Felix; Einevoll, Gaute T

2015-04-30

New, silicon-based multielectrodes comprising hundreds or more electrode contacts offer the possibility to record spike trains from thousands of neurons simultaneously. This potential cannot be realized unless accurate, reliable automated methods for spike sorting are developed, in turn requiring benchmarking data sets with known ground-truth spike times. We here present a general simulation tool for computing benchmarking data for evaluation of spike-sorting algorithms entitled ViSAPy (Virtual Spiking Activity in Python). The tool is based on a well-established biophysical forward-modeling scheme and is implemented as a Python package built on top of the neuronal simulator NEURON and the Python tool LFPy. ViSAPy allows for arbitrary combinations of multicompartmental neuron models and geometries of recording multielectrodes. Three example benchmarking data sets are generated, i.e., tetrode and polytrode data mimicking in vivo cortical recordings and microelectrode array (MEA) recordings of in vitro activity in salamander retinas. The synthesized example benchmarking data mimics salient features of typical experimental recordings, for example, spike waveforms depending on interspike interval. ViSAPy goes beyond existing methods as it includes biologically realistic model noise, synaptic activation by recurrent spiking networks, finite-sized electrode contacts, and allows for inhomogeneous electrical conductivities. ViSAPy is optimized to allow for generation of long time series of benchmarking data, spanning minutes of biological time, by parallel execution on multi-core computers. ViSAPy is an open-ended tool as it can be generalized to produce benchmarking data or arbitrary recording-electrode geometries and with various levels of complexity. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Systemic effects of low-dose dopamine during administration of cytarabine.

Science.gov (United States)

Connelly, James; Benani, Dina J; Newman, Matthew; Burton, Bradley; Crow, Jessica; Levis, Mark

2017-09-01

Purpose Low-dose dopamine has been utilized to improve renal blood flow, urine output, and reduce drug-induced nephrotoxicity. The purpose of this study was to assess changes in renal function, cardiovascular adverse events, and neurologic toxicity in patients receiving cytarabine with or without low-dose dopamine. Methods A retrospective, single-center, cohort study of patients receiving cytarabine at 667 mg/m 2 /dose or greater, with or without dopamine at ≤5 mcg/kg/min. Cohorts were based upon initiation or absence of low-dose dopamine; cytarabine only, cytarabine + pre- and day of low-dose dopamine, and cytarabine + post-low-dose dopamine. Renal outcomes (urine output, serum creatinine, and creatinine clearance) were compared with baseline and between cohorts. Safety endpoints (arrhythmias, tachycardia, and neurotoxicity) were compared between cohorts based on low-dose dopamine exposure. Results There was no difference in urine output from baseline in all cohorts. Comparing cytarabine only and pre- and day of low-dose dopamine cohorts, there was no difference in urine output. In those receiving low-dose dopamine, there was no difference in serum creatinine and creatinine clearance from baseline. No arrhythmias were documented during the study period, and there was no difference in the incidence of tachycardia between groups (P = 0.66). Neurotoxicity was reported in three patients who were on low-dose dopamine. Conclusion Though variation existed in individual patients administered low-dose dopamine, the use of low-dose dopamine did not significantly impact renal function in this small sample at a single institution. In addition, low-dose dopamine did not negatively impact cardiovascular function.

Dopamine induces soluble α-synuclein oligomers and nigrostriatal degeneration.

Science.gov (United States)

Mor, Danielle E; Tsika, Elpida; Mazzulli, Joseph R; Gould, Neal S; Kim, Hanna; Daniels, Malcolm J; Doshi, Shachee; Gupta, Preetika; Grossman, Jennifer L; Tan, Victor X; Kalb, Robert G; Caldwell, Kim A; Caldwell, Guy A; Wolfe, John H; Ischiropoulos, Harry

2017-11-01

Parkinson's disease (PD) is defined by the loss of dopaminergic neurons in the substantia nigra and the formation of Lewy body inclusions containing aggregated α-synuclein. Efforts to explain dopamine neuron vulnerability are hindered by the lack of dopaminergic cell death in α-synuclein transgenic mice. To address this, we manipulated both dopamine levels and α-synuclein expression. Nigrally targeted expression of mutant tyrosine hydroxylase with enhanced catalytic activity increased dopamine levels without damaging neurons in non-transgenic mice. In contrast, raising dopamine levels in mice expressing human A53T mutant α-synuclein induced progressive nigrostriatal degeneration and reduced locomotion. Dopamine elevation in A53T mice increased levels of potentially toxic α-synuclein oligomers, resulting in conformationally and functionally modified species. Moreover, in genetically tractable Caenorhabditis elegans models, expression of α-synuclein mutated at the site of interaction with dopamine prevented dopamine-induced toxicity. These data suggest that a unique mechanism links two cardinal features of PD: dopaminergic cell death and α-synuclein aggregation.

Regulation of Dopamine Uptake by Vasoactive Peptides in the Kidney

Directory of Open Access Journals (Sweden)

N. L. Rukavina Mikusic

2016-01-01

Full Text Available Considering the key role of renal dopamine in tubular sodium handling, we hypothesized that c-type natriuretic peptide (CNP and Ang-(1-7 may regulate renal dopamine availability in tubular cells, contributing to Na+, K+-ATPase inhibition. Present results show that CNP did not affect either 3H-dopamine uptake in renal tissue or Na+, K+-ATPase activity; meanwhile, Ang-(1-7 was able to increase 3H-dopamine uptake and decreased Na+, K+-ATPase activity in renal cortex. Ang-(1-7 and dopamine together decreased further Na+, K+-ATPase activity showing an additive effect on the sodium pump. In addition, hydrocortisone reversed Ang-(1-7-dopamine overinhibition on the enzyme, suggesting that this inhibition is closely related to Ang-(1-7 stimulation on renal dopamine uptake. Both anantin and cANP (4-23-amide did not modify CNP effects on 3H-dopamine uptake by tubular cells. The Mas receptor antagonist, A-779, blocked the increase elicited by Ang-(1-7 on 3H-dopamine uptake. The stimulatory uptake induced by Ang-(1-7 was even more pronounced in the presence of losartan, suggesting an inhibitory effect of Ang-(1-7 on AT1 receptors on 3H-dopamine uptake. By increasing dopamine bioavailability in tubular cells, Ang-(1-7 enhances Na+, K+-ATPase activity inhibition, contributing to its natriuretic and diuretic effects.

Layered reward signalling through octopamine and dopamine in Drosophila.

Science.gov (United States)

Burke, Christopher J; Huetteroth, Wolf; Owald, David; Perisse, Emmanuel; Krashes, Michael J; Das, Gaurav; Gohl, Daryl; Silies, Marion; Certel, Sarah; Waddell, Scott

2012-12-20

Dopamine is synonymous with reward and motivation in mammals. However, only recently has dopamine been linked to motivated behaviour and rewarding reinforcement in fruitflies. Instead, octopamine has historically been considered to be the signal for reward in insects. Here we show, using temporal control of neural function in Drosophila, that only short-term appetitive memory is reinforced by octopamine. Moreover, octopamine-dependent memory formation requires signalling through dopamine neurons. Part of the octopamine signal requires the α-adrenergic-like OAMB receptor in an identified subset of mushroom-body-targeted dopamine neurons. Octopamine triggers an increase in intracellular calcium in these dopamine neurons, and their direct activation can substitute for sugar to form appetitive memory, even in flies lacking octopamine. Analysis of the β-adrenergic-like OCTβ2R receptor reveals that octopamine-dependent reinforcement also requires an interaction with dopamine neurons that control appetitive motivation. These data indicate that sweet taste engages a distributed octopamine signal that reinforces memory through discrete subsets of mushroom-body-targeted dopamine neurons. In addition, they reconcile previous findings with octopamine and dopamine and suggest that reinforcement systems in flies are more similar to mammals than previously thought.

Homeostatic mechanisms in dopamine synthesis and release: a mathematical model

Directory of Open Access Journals (Sweden)

Nijhout H Frederik

2009-09-01

Full Text Available Abstract Background Dopamine is a catecholamine that is used as a neurotransmitter both in the periphery and in the central nervous system. Dysfunction in various dopaminergic systems is known to be associated with various disorders, including schizophrenia, Parkinson's disease, and Tourette's syndrome. Furthermore, microdialysis studies have shown that addictive drugs increase extracellular dopamine and brain imaging has shown a correlation between euphoria and psycho-stimulant-induced increases in extracellular dopamine 1. These consequences of dopamine dysfunction indicate the importance of maintaining dopamine functionality through homeostatic mechanisms that have been attributed to the delicate balance between synthesis, storage, release, metabolism, and reuptake. Methods We construct a mathematical model of dopamine synthesis, release, and reuptake and use it to study homeostasis in single dopaminergic neuron terminals. We investigate the substrate inhibition of tyrosine hydroxylase by tyrosine, the consequences of the rapid uptake of extracellular dopamine by the dopamine transporters, and the effects of the autoreceoptors on dopaminergic function. The main focus is to understand the regulation and control of synthesis and release and to explicate and interpret experimental findings. Results We show that the substrate inhibition of tyrosine hydroxylase by tyrosine stabilizes cytosolic and vesicular dopamine against changes in tyrosine availability due to meals. We find that the autoreceptors dampen the fluctuations in extracellular dopamine caused by changes in tyrosine hydroxylase expression and changes in the rate of firing. We show that short bursts of action potentials create significant dopamine signals against the background of tonic firing. We explain the observed time courses of extracellular dopamine responses to stimulation in wild type mice and mice that have genetically altered dopamine transporter densities and the observed

Visually Evoked Spiking Evolves While Spontaneous Ongoing Dynamics Persist

DEFF Research Database (Denmark)

Huys, Raoul; Jirsa, Viktor K; Darokhan, Ziauddin

2016-01-01

attractor. Its existence guarantees that evoked spiking return to the spontaneous state. However, the spontaneous ongoing spiking state and the visual evoked spiking states are qualitatively different and are separated by a threshold (separatrix). The functional advantage of this organization...

Multichannel interictal spike activity detection using time-frequency entropy measure.

Science.gov (United States)

Thanaraj, Palani; Parvathavarthini, B

2017-06-01

Localization of interictal spikes is an important clinical step in the pre-surgical assessment of pharmacoresistant epileptic patients. The manual selection of interictal spike periods is cumbersome and involves a considerable amount of analysis workload for the physician. The primary focus of this paper is to automate the detection of interictal spikes for clinical applications in epilepsy localization. The epilepsy localization procedure involves detection of spikes in a multichannel EEG epoch. Therefore, a multichannel Time-Frequency (T-F) entropy measure is proposed to extract features related to the interictal spike activity. Least squares support vector machine is used to train the proposed feature to classify the EEG epochs as either normal or interictal spike period. The proposed T-F entropy measure, when validated with epilepsy dataset of 15 patients, shows an interictal spike classification accuracy of 91.20%, sensitivity of 100% and specificity of 84.23%. Moreover, the area under the curve of Receiver Operating Characteristics plot of 0.9339 shows the superior classification performance of the proposed T-F entropy measure. The results of this paper show a good spike detection accuracy without any prior information about the spike morphology.

Temporal Profiles Dissociate Regional Extracellular Ethanol versus Dopamine Concentrations

Science.gov (United States)

2015-01-01

In vivo monitoring of dopamine via microdialysis has demonstrated that acute, systemic ethanol increases extracellular dopamine in regions innervated by dopaminergic neurons originating in the ventral tegmental area and substantia nigra. Simultaneous measurement of dialysate dopamine and ethanol allows comparison of the time courses of their extracellular concentrations. Early studies demonstrated dissociations between the time courses of brain ethanol concentrations and dopaminergic responses in the nucleus accumbens (NAc) elicited by acute ethanol administration. Both brain ethanol and extracellular dopamine levels peak during the first 5 min following systemic ethanol administration, but the dopamine response returns to baseline while brain ethanol concentrations remain elevated. Post hoc analyses examined ratios of the dopamine response (represented as a percent above baseline) to tissue concentrations of ethanol at different time points within the first 25–30 min in the prefrontal cortex, NAc core and shell, and dorsomedial striatum following a single intravenous infusion of ethanol (1 g/kg). The temporal patterns of these “response ratios” differed across brain regions, possibly due to regional differences in the mechanisms underlying the decline of the dopamine signal associated with acute intravenous ethanol administration and/or to the differential effects of acute ethanol on the properties of subpopulations of midbrain dopamine neurons. This Review draws on neurochemical, physiological, and molecular studies to summarize the effects of acute ethanol administration on dopamine activity in the prefrontal cortex and striatal regions, to explore the potential reasons for the regional differences observed in the decline of ethanol-induced dopamine signals, and to suggest directions for future research. PMID:25537116

Central actions of a novel and selective dopamine antagonist

International Nuclear Information System (INIS)

Schulz, D.W.

1985-01-01

Receptors for the neurotransmitter dopamine traditionally have been divided into two subgroups: the D 1 class, which is linked to the stimulation of adenylate cyclase-activity, and the D 2 class which is not. There is much evidence suggesting that it is the D 2 class which is not. There is much evidence suggesting that it is the D 2 dopamine receptor that mediates the physiological and behavioral actions of dopamine in the intact animal. However, the benzazepine SCH23390 is a dopamine antagonist which has potent behavioral actions while displaying apparent neurochemical selectivity for the D 1 class of dopamine receptors. The purpose of this dissertation was to (1) confirm and characterize this selectivity, and (2) test certain hypothesis related to possible modes of action of SCH233390. The inhibition of adenylate cyclase by SCH23390 occurred via an action at the dopamine receptor only. A radiolabeled analog of SCH23390 displayed the receptor binding properties of a specific high-affinity ligand, and regional receptor densities were highly correlated with dopamine levels. The subcellular distribution of [ 3 H]-SCH23390 binding did not correspond completely with that of dopamine-stimulated adenylate cyclase. The neurochemical potency of SCH23390 as a D 1 receptor antagonist was preserved following parental administration. A variety of dopamine agonists and antagonists displayed a high correlation between their abilities to compete for [ 3 H]-SCH23390 binding in vitro and to act at an adenylate cyclase-linked receptor. Finally, the relative affinities of dopamine and SCH23390 for both D 1 receptors and [ 3 H]-SCH23390 binding sites were comparable. It is concluded that the behavioral effects of SCH23390 are mediated by actions at D 1 dopamine receptors only, and that the physiological importance of this class of receptors should be reevaluated

Training Deep Spiking Neural Networks Using Backpropagation.

Science.gov (United States)

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

2016-01-01

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

The thermal-spike model description of the ion-irradiated polyimide

International Nuclear Information System (INIS)

Sun Youmei; Zhang Chonghong; Zhu Zhiyong; Wang Zhiguang; Jin Yunfan; Liu Jie; Wang Ying

2004-01-01

To describe the role of electronic energy loss (dE/dX) e for chemical modification of polyimide (PI), multi-layer stacks (corresponding to different dE/dX) were irradiated by different swift heavy ions (1.158 GeV Fe 56 and 1.755 GeV Xe 136 ) under vacuum and at room temperature. Chemical changes of modified PI films were studied by Fourier transform infrared (FTIR) spectroscopy. The chain disruption rate of PI was investigated in the fluence range from 1 x 10 11 to 6 x 10 12 ions/cm 2 and a wider energy stopping power range (2.2-5.1 keV/nm for Fe 56 ions and 8.6-11.5 keV/nm for Xe 136 ions). Alkyne formation was observed over the electronic energy loss range of interest. By applying the saturated track model assumption (the damage process only occur in a cylinder of area σ), the mean degradation and alkyne formation radii in tracks were induced for Fe and Xe ion irradiation, respectively. The results were validated by the thermal-spike model. The analysis of the irradiated PI films shows that the predictions of the thermal-spike model of Szenes are in qualitative agreement with the curve shape of experimental results

Grain price spikes and beggar-thy-neighbor policy responses

DEFF Research Database (Denmark)

Jensen, Hans Grinsted; Anderson, Kym

2017-01-01

When prices spike in international grain markets, national governments often reduce the extent to which that spike affects their domestic food markets. Those actions exacerbate the price spike and international welfare transfer associated with that terms of trade change. Several recent analyses...

Molecular Mechanisms of Dopamine Receptor Mediated Neuroprotection

National Research Council Canada - National Science Library

Sealfon, Stuart

2000-01-01

... of the cellular changes characteristic of this process. Evidence from our laboratory and others suggest that activation of dopamine receptors can oppose the induction of apoptosis in dopamine neurons...

Dopamine and dopamine receptor D1 associated with decreased social interaction.

Science.gov (United States)

Liu, Qiang; Shi, Jieyun; Lin, Rongfei; Wen, Tieqiao

2017-05-01

Deficits in social interaction are hallmarks of neurological and psychiatric disorders. However, its underlying mechanism is still unclear. Here, we show that the loss of dendritic cell factor 1 (Dcf1) in the nervous system of mice induces social interaction deficiency, autism-like behaviour, and influences social interaction via the dopamine system. Dopamine receptor D1 agonist rescues this social cognition phenotype, and improves short-term plasticity. Together, this study presents a new genetic mechanism that affects social interaction and may provide a new way to improve positive social interaction and treat autism spectrum disorders. Copyright © 2017 Elsevier B.V. All rights reserved.

Illicit dopamine transients: reconciling actions of abused drugs.

Science.gov (United States)

Covey, Dan P; Roitman, Mitchell F; Garris, Paul A

2014-04-01

Phasic increases in brain dopamine are required for cue-directed reward seeking. Although compelling within the framework of appetitive behavior, the view that illicit drugs hijack reward circuits by hyperactivating these dopamine transients is inconsistent with established psychostimulant pharmacology. However, recent work reclassifying amphetamine (AMPH), cocaine, and other addictive dopamine-transporter inhibitors (DAT-Is) supports transient hyperactivation as a unifying hypothesis of abused drugs. We argue here that reclassification also identifies generating burst firing by dopamine neurons as a keystone action. Unlike natural rewards, which are processed by sensory systems, drugs act directly on the brain. Consequently, to mimic natural rewards and exploit reward circuits, dopamine transients must be elicited de novo. Of available drug targets, only burst firing achieves this essential outcome. Copyright © 2014 Elsevier Ltd. All rights reserved.

Introduction to spiking neural networks: Information processing, learning and applications.

Science.gov (United States)

Ponulak, Filip; Kasinski, Andrzej

2011-01-01

The concept that neural information is encoded in the firing rate of neurons has been the dominant paradigm in neurobiology for many years. This paradigm has also been adopted by the theory of artificial neural networks. Recent physiological experiments demonstrate, however, that in many parts of the nervous system, neural code is founded on the timing of individual action potentials. This finding has given rise to the emergence of a new class of neural models, called spiking neural networks. In this paper we summarize basic properties of spiking neurons and spiking networks. Our focus is, specifically, on models of spike-based information coding, synaptic plasticity and learning. We also survey real-life applications of spiking models. The paper is meant to be an introduction to spiking neural networks for scientists from various disciplines interested in spike-based neural processing.

Neuronal spike sorting based on radial basis function neural networks

Directory of Open Access Journals (Sweden)

Taghavi Kani M

2011-02-01

Full Text Available "nBackground: Studying the behavior of a society of neurons, extracting the communication mechanisms of brain with other tissues, finding treatment for some nervous system diseases and designing neuroprosthetic devices, require an algorithm to sort neuralspikes automatically. However, sorting neural spikes is a challenging task because of the low signal to noise ratio (SNR of the spikes. The main purpose of this study was to design an automatic algorithm for classifying neuronal spikes that are emitted from a specific region of the nervous system."n "nMethods: The spike sorting process usually consists of three stages: detection, feature extraction and sorting. We initially used signal statistics to detect neural spikes. Then, we chose a limited number of typical spikes as features and finally used them to train a radial basis function (RBF neural network to sort the spikes. In most spike sorting devices, these signals are not linearly discriminative. In order to solve this problem, the aforesaid RBF neural network was used."n "nResults: After the learning process, our proposed algorithm classified any arbitrary spike. The obtained results showed that even though the proposed Radial Basis Spike Sorter (RBSS reached to the same error as the previous methods, however, the computational costs were much lower compared to other algorithms. Moreover, the competitive points of the proposed algorithm were its good speed and low computational complexity."n "nConclusion: Regarding the results of this study, the proposed algorithm seems to serve the purpose of procedures that require real-time processing and spike sorting.

Spiking irregularity and frequency modulate the behavioral report of single-neuron stimulation.

Science.gov (United States)

Doron, Guy; von Heimendahl, Moritz; Schlattmann, Peter; Houweling, Arthur R; Brecht, Michael

2014-02-05

The action potential activity of single cortical neurons can evoke measurable sensory effects, but it is not known how spiking parameters and neuronal subtypes affect the evoked sensations. Here, we examined the effects of spike train irregularity, spike frequency, and spike number on the detectability of single-neuron stimulation in rat somatosensory cortex. For regular-spiking, putative excitatory neurons, detectability increased with spike train irregularity and decreasing spike frequencies but was not affected by spike number. Stimulation of single, fast-spiking, putative inhibitory neurons led to a larger sensory effect compared to regular-spiking neurons, and the effect size depended only on spike irregularity. An ideal-observer analysis suggests that, under our experimental conditions, rats were using integration windows of a few hundred milliseconds or more. Our data imply that the behaving animal is sensitive to single neurons' spikes and even to their temporal patterning. Copyright © 2014 Elsevier Inc. All rights reserved.

Error-backpropagation in temporally encoded networks of spiking neurons

NARCIS (Netherlands)

S.M. Bohte (Sander); J.A. La Poutré (Han); J.N. Kok (Joost)

2000-01-01

textabstractFor a network of spiking neurons that encodes information in the timing of individual spike-times, we derive a supervised learning rule, emph{SpikeProp, akin to traditional error-backpropagation and show how to overcome the discontinuities introduced by thresholding. With this algorithm,

Converging effects of Ginkgo biloba extract at the level of transmitter release, NMDA and sodium currents and dendritic spikes.

Science.gov (United States)

Szasz, Bernadett K; Lenkey, Nora; Barth, Albert M; Mike, Arpad; Somogyvari, Zsolt; Farkas, Orsolya; Lendvai, Balazs

2008-08-01

In this study, an attempt was made to integrate the effects of GINKGO BILOBA extract (GBE) in different experimental systems (IN VITRO cochlea, brain slice preparations and cortical cell culture) to elucidate whether these processes converge to promote neuroprotection or interfere with normal neural function. GBE increased the release of dopamine in the cochlea. NMDA-evoked currents were dose-dependently inhibited by rapid GBE application in cultured cortical cells. GBE moderately inhibited Na+ channels at depolarised holding potential in cortical cells. These inhibitory effects by GBE may sufficiently contribute to the prevention of excitotoxic damage in neurons. However, these channels also interact with memory formation at the cellular level. The lack of effect by GBE on dendritic spike initiation in neocortical layer 5 pyramidal neurons indicates that the integrative functions may remain intact during the inhibitory actions of GBE.

Successful treatment of dopamine dysregulation syndrome with dopamine D2 partial agonist antipsychotic drug

Directory of Open Access Journals (Sweden)

Mizushima Jin

2012-07-01

Full Text Available Abstract Dopamine dysregulation syndrome (DDS consists of a series of complications such as compulsive use of dopaminergic medications, aggressive or hypomanic behaviors during excessive use, and withdrawal states characterized by dysphoria and anxiety, caused by long-term dopaminergic treatment in patients with Parkinson’s disease (PD. Although several ways to manage DDS have been suggested, there has been no established treatment that can manage DDS without deterioration of motor symptoms. In this article, we present a case of PD in whom the administration of the dopamine D2 partial agonistic antipsychotic drug aripiprazole improved DDS symptoms such as craving and compulsive behavior without worsening of motor symptoms. Considering the profile of this drug as a partial agonist at D2 receptors, it is possible that it exerts its therapeutic effect on DDS by modulating the dysfunctional dopamine system.

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

Directory of Open Access Journals (Sweden)

Zedong eBi

2016-02-01

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

Mimickers of generalized spike and wave discharges.

Science.gov (United States)

Azzam, Raed; Bhatt, Amar B

2014-06-01

Overinterpretation of benign EEG variants is a common problem that can lead to the misdiagnosis of epilepsy. We review four normal patterns that mimic generalized spike and wave discharges: phantom spike-and-wave, hyperventilation hypersynchrony, hypnagogic/ hypnopompic hypersynchrony, and mitten patterns.

Detection of dopamine neurotransmission in 'real time'

Directory of Open Access Journals (Sweden)

Rajendra D Badgaiyan

2013-07-01

Full Text Available Current imaging techniques have limited ability to detect neurotransmitters released during brain processing. It is a critical limitation because neurotransmitters have significant control over the brain activity. In this context, recent development of single-scan dynamic molecular imaging technique is important because it allows detection, mapping, and measurement of dopamine released in the brain during task performance. The technique exploits the competition between endogenously released dopamine and its receptor ligand for occupancy of receptor sites. Dopamine released during task performance is detected by dynamically measuring concentration of intravenously injected radiolabeled ligand using a positron emission tomography camera. Based on the ligand concentration, values of receptor kinetic parameters are estimated. These estimates allow detection of dopamine released in the human brain during task performance.

A Cross-Correlated Delay Shift Supervised Learning Method for Spiking Neurons with Application to Interictal Spike Detection in Epilepsy.

Science.gov (United States)

Guo, Lilin; Wang, Zhenzhong; Cabrerizo, Mercedes; Adjouadi, Malek

2017-05-01

This study introduces a novel learning algorithm for spiking neurons, called CCDS, which is able to learn and reproduce arbitrary spike patterns in a supervised fashion allowing the processing of spatiotemporal information encoded in the precise timing of spikes. Unlike the Remote Supervised Method (ReSuMe), synapse delays and axonal delays in CCDS are variants which are modulated together with weights during learning. The CCDS rule is both biologically plausible and computationally efficient. The properties of this learning rule are investigated extensively through experimental evaluations in terms of reliability, adaptive learning performance, generality to different neuron models, learning in the presence of noise, effects of its learning parameters and classification performance. Results presented show that the CCDS learning method achieves learning accuracy and learning speed comparable with ReSuMe, but improves classification accuracy when compared to both the Spike Pattern Association Neuron (SPAN) learning rule and the Tempotron learning rule. The merit of CCDS rule is further validated on a practical example involving the automated detection of interictal spikes in EEG records of patients with epilepsy. Results again show that with proper encoding, the CCDS rule achieves good recognition performance.

Prefrontal Dopamine in Associative Learning and Memory

Science.gov (United States)

Puig, M. Victoria; Antzoulatos, Evan G.; Miller, Earl K.

2014-01-01

Learning to associate specific objects or actions with rewards and remembering the associations are everyday tasks crucial for our flexible adaptation to the environment. These higher-order cognitive processes depend on the prefrontal cortex (PFC) and frontostriatal circuits that connect areas in the frontal lobe with the striatum in the basal ganglia. Both structures are densely innervated by dopamine (DA) afferents that originate in the midbrain. Although the activity of DA neurons is thought to be important for learning, the exact role of DA transmission in frontostriatal circuits during learning-related tasks is still unresolved. Moreover, the neural substrates of this modulation are poorly understood. Here, we review our recent work in monkeys utilizing local pharmacology of DA agents in the PFC to investigate the cellular mechanisms of DA modulation of associative learning and memory. We show that blocking both D1 and D2 receptors in the lateral PFC impairs learning of new stimulus-response associations and cognitive flexibility, but not the memory of highly familiar associations. In addition, D2 receptors may also contribute to motivation. The learning deficits correlated with reductions of neural information about the associations in PFC neurons, alterations in global excitability and spike synchronization, and exaggerated alpha and beta neural oscillations. Our findings provide new insights into how DA transmission modulate associative learning and memory processes in frontostriatal systems. PMID:25241063

Cellular and circuit mechanisms maintain low spike co-variability and enhance population coding in somatosensory cortex

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Cheng eLy

2012-03-01

Full Text Available The responses of cortical neurons are highly variable across repeated presentations of a stimulus. Understanding this variability is critical for theories of both sensory and motor processing, since response variance affects the accuracy of neural codes. Despite this influence, the cellular and circuit mechanisms that shape the trial-to-trial variability of population responses remain poorly understood. We used a combination of experimental and computational techniques to uncover the mechanisms underlying response variability of populations of pyramidal (E cells in layer 2/3 of rat whisker barrel cortex. Spike trains recorded from pairs of E-cells during either spontaneous activity or whisker deflected responses show similarly low levels of spiking co-variability, despite large differences in network activation between the two states. We developed network models that show how spike threshold nonlinearities dilutes E-cell spiking co-variability during spontaneous activity and low velocity whisker deflections. In contrast, during high velocity whisker deflections, cancelation mechanisms mediated by feedforward inhibition maintain low E-cell pairwise co-variability. Thus, the combination of these two mechanisms ensure low E-cell population variability over a wide range of whisker deflection velocities. Finally, we show how this active decorrelation of population variability leads to a drastic increase in the population information about whisker velocity. The canonical cellular and circuit components of our study suggest that low network variability over a broad range of neural states may generalize across the nervous system.

Evidence for distinct sodium-, dopamine-, and cocaine-dependent conformational changes in transmembrane segments 7 and 8 of the dopamine transporter

DEFF Research Database (Denmark)

Norregaard, Lene; Loland, Claus Juul; Gether, Ulrik

2003-01-01

. Inhibitors such as cocaine did not alter the effect of MTSET in M371C. The protection of M371C inactivation by dopamine required Na+. Because dopamine binding is believed to be Na+-independent, this suggests that dopamine induces a transport-associated conformational change that decreases the reactivity of M......371C with MTSET. In contrast to M371C, cocaine decreased the reaction rate of A399C with MTSET, whereas dopamine had no effect. The protection by cocaine can either reflect that Ala-399 lines the cocaine binding crevice or that cocaine induces a conformational change that decreases the reactivity of A...

Dopamine receptors in the guinea-pig heart. A binding study

International Nuclear Information System (INIS)

Sandrini, M.; Benelli, A.; Baraldi, M.

1984-01-01

The binding of dopaminergic agonists and antagonists to guinea-pig myocardial membrane preparations was studied using 3 H-dopamine and 3 H-spiperone as radioligand. 3 H-Dopamine bound specifically to heart membranes while 3 H-spiperone did not. A Scatchard analysis of 3 H-dopamine binding showed a curvilinear plot indicating the presence of two dopamine receptor populations that we have termed high- (K/sub d/ = 1.2 nM, B/sub mx/ = 52.9 fmol/mg prot.) and low- (K/sub d/ = 11.8 nM, B/sub mx/ = 267.3 fmol/gm prot.) affinity binding sites, respectively. The charactization of the high-affinity component of 3 H-dopamine binding indicated that the binding is rapid, saturable, stereospecific, pH- and temperature-dependent, and displaced by dopaminergic agonists and antagonists known to act similarly in vivo. The finding that pretreatment with dibenamine (which has been described as an α-adrenoceptor irreversible blocker) did not affect the binding of dopamine to cardiac membrane preparations suggests that α-adrenoceptors and dopamine receptors have separate recognition sites in the heart. It is concluded that 3 H-dopamine binds to specific dopamine receptors in the heart of guinea-pigs

Noncovalent Interactions between Dopamine and Regular and Defective Graphene.

Science.gov (United States)

Fernández, Ana C Rossi; Castellani, Norberto J

2017-08-05

The role of noncovalent interactions in the adsorption of biological molecules on graphene is a subject of fundamental interest regarding the use of graphene as a material for sensing and drug delivery. The adsorption of dopamine on regular graphene and graphene with monovacancies (GV) is theoretically studied within the framework of density functional theory. Several adsorption modes are considered, and notably those in which the dopamine molecule is oriented parallel or quasi-parallel to the surface are the more stable. The adsorption of dopamine on graphene implies an attractive interaction of a dispersive nature that competes with Pauli repulsion between the occupied π orbitals of the dopamine ring and the π orbitals of graphene. If dopamine adsorbs at the monovacancy in the A-B stacking mode, a hydrogen bond is produced between one of the dopamine hydroxy groups and one carbon atom around the vacancy. The electronic charge redistribution due to adsorption is consistent with an electronic drift from the graphene or GV surface to the dopamine molecule. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Unsupervised spike sorting based on discriminative subspace learning.

Science.gov (United States)

Keshtkaran, Mohammad Reza; Yang, Zhi

2014-01-01

Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. In this paper, we present two unsupervised spike sorting algorithms based on discriminative subspace learning. The first algorithm simultaneously learns the discriminative feature subspace and performs clustering. It uses histogram of features in the most discriminative projection to detect the number of neurons. The second algorithm performs hierarchical divisive clustering that learns a discriminative 1-dimensional subspace for clustering in each level of the hierarchy until achieving almost unimodal distribution in the subspace. The algorithms are tested on synthetic and in-vivo data, and are compared against two widely used spike sorting methods. The comparative results demonstrate that our spike sorting methods can achieve substantially higher accuracy in lower dimensional feature space, and they are highly robust to noise. Moreover, they provide significantly better cluster separability in the learned subspace than in the subspace obtained by principal component analysis or wavelet transform.

Multiplexed Spike Coding and Adaptation in the Thalamus

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Rebecca A. Mease

2017-05-01

Full Text Available High-frequency “burst” clusters of spikes are a generic output pattern of many neurons. While bursting is a ubiquitous computational feature of different nervous systems across animal species, the encoding of synaptic inputs by bursts is not well understood. We find that bursting neurons in the rodent thalamus employ “multiplexing” to differentially encode low- and high-frequency stimulus features associated with either T-type calcium “low-threshold” or fast sodium spiking events, respectively, and these events adapt differently. Thus, thalamic bursts encode disparate information in three channels: (1 burst size, (2 burst onset time, and (3 precise spike timing within bursts. Strikingly, this latter “intraburst” encoding channel shows millisecond-level feature selectivity and adapts across statistical contexts to maintain stable information encoded per spike. Consequently, calcium events both encode low-frequency stimuli and, in parallel, gate a transient window for high-frequency, adaptive stimulus encoding by sodium spike timing, allowing bursts to efficiently convey fine-scale temporal information.

Physiological Ripples (± 100 Hz) in Spike-Free Scalp EEGs of Children With and Without Epilepsy.

Science.gov (United States)

Mooij, Anne H; Raijmann, Renee C M A; Jansen, Floor E; Braun, Kees P J; Zijlmans, Maeike

2017-11-01

Pathological high frequency oscillations (HFOs, >80 Hz) are considered new biomarkers for epilepsy. They have mostly been recorded invasively, but pathological ripples (80-250 Hz) can also be found in scalp EEGs with frequent epileptiform spikes. Physiological HFOs also exist. They have been recorded invasively in hippocampus and neocortex. There are no reports of spontaneously occurring physiological HFOs recorded with scalp EEG. We aimed to study ripples in spike-free scalp EEGs. We included 23 children (6 with, 17 without epilepsy) who had an EEG without interictal epileptiform spikes recorded during sleep. We differentiated true ripples from spurious ripples such as filtering effects of sharp artifacts and high frequency components of muscle artifacts by viewing ripples simultaneously in bipolar and average montage and double-checking the unfiltered signal. We calculated mean frequency, duration and root mean square amplitude of the ripples, and studied their shape and distribution. We found ripples in EEGs of 20 out of 23 children (4 with, 16 without epilepsy). Ripples had a regular shape and occurred mostly on central and midline channels. Mean frequency was 102 Hz, mean duration 70 ms, mean root mean square amplitude 0.95 µV. Ripples occurring in normal EEGs of children without epilepsy were considered physiological; the similarity in appearance suggested that the ripples occurring in normal EEGs of children with epilepsy were also physiological. The finding that it is possible to study physiological neocortical ripples in scalp EEG paves the way for investigating their occurrence during brain development and their relation with cognitive functioning.

Dopamine Receptor Activation Increases HIV Entry into Primary Human Macrophages

Science.gov (United States)

Gaskill, Peter J.; Yano, Hideaki H.; Kalpana, Ganjam V.; Javitch, Jonathan A.; Berman, Joan W.

2014-01-01

Macrophages are the primary cell type infected with HIV in the central nervous system, and infection of these cells is a major component in the development of neuropathogenesis and HIV-associated neurocognitive disorders. Within the brains of drug abusers, macrophages are exposed to increased levels of dopamine, a neurotransmitter that mediates the addictive and reinforcing effects of drugs of abuse such as cocaine and methamphetamine. In this study we examined the effects of dopamine on HIV entry into primary human macrophages. Exposure to dopamine during infection increased the entry of R5 tropic HIV into macrophages, irrespective of the concentration of the viral inoculum. The entry pathway affected was CCR5 dependent, as antagonizing CCR5 with the small molecule inhibitor TAK779 completely blocked entry. The effect was dose-dependent and had a steep threshold, only occurring above 108 M dopamine. The dopamine-mediated increase in entry required dopamine receptor activation, as it was abrogated by the pan-dopamine receptor antagonist flupenthixol, and could be mediated through both subtypes of dopamine receptors. These findings indicate that the effects of dopamine on macrophages may have a significant impact on HIV pathogenesis. They also suggest that drug-induced increases in CNS dopamine may be a common mechanism by which drugs of abuse with distinct modes of action exacerbate neuroinflammation and contribute to HIV-associated neurocognitive disorders in infected drug abusers. PMID:25268786

Effects of alkylating agents on dopamine D(3) receptors in rat brain: selective protection by dopamine.

Science.gov (United States)

Zhang, K; Weiss, N T; Tarazi, F I; Kula, N S; Baldessarini, R J

1999-11-13

Dopamine D(3) receptors are structurally highly homologous to other D(2)-like dopamine receptors, but differ from them pharmacologically. D(3) receptors are notably resistant to alkylation by 1-ethoxycarbonyl-2-ethoxy-1,2-dihydroquinoline (EEDQ), which readily alkylates D(2) receptors. We compared EEDQ with N-(p-isothiocyanatophenethyl)spiperone (NIPS), a selective D(2)-like receptor alkylating agent, for effects on D(3) and D(2) receptors in rat brain using autoradiographic analysis. Neither agent occluded D(3) receptors in vivo at doses that produced substantial blockade of D(2) receptors, even after catecholamine-depleting pretreatments. In vitro, however, D(3) receptors were readily alkylated by both NIPS (IC(50)=40 nM) and EEDQ (IC(50)=12 microM). These effects on D(3) sites were blocked by nM concentrations of dopamine, whereas microM concentrations were required to protect D(2) receptors from the alkylating agents. The findings are consistent with the view that alkylation of D(3) receptors in vivo is prevented by its high affinity for even minor concentrations of endogenous dopamine.

Effect of heavy metals on pH buffering capacity and solubility of Ca, Mg, K, and P in non-spiked and heavy metal-spiked soils.

Science.gov (United States)

Najafi, Sarvenaz; Jalali, Mohsen

2016-06-01

In many parts of the world, soil acidification and heavy metal contamination has become a serious concern due to the adverse effects on chemical properties of soil and crop yield. The aim of this study was to investigate the effect of pH (in the range of 1 to 3 units above and below the native pH of soils) on calcium (Ca), magnesium (Mg), potassium (K), and phosphorus (P) solubility in non-spiked and heavy metal-spiked soil samples. Spiked samples were prepared by cadmium (Cd), copper (Cu), nickel (Ni), and zinc (Zn) as chloride salts and incubating soils for 40 days. The pH buffering capacity (pHBC) of each sample was determined by plotting the amount of H(+) or OH(-) added (mmol kg(-1)) versus the related pH value. The pHBC of soils ranged from 47.1 to 1302.5 mmol kg(-1) for non-spiked samples and from 45.0 to 1187.4 mmol kg(-1) for spiked soil samples. The pHBC values were higher in soil 2 (non-spiked and spiked) which had higher calcium carbonate content. The results indicated the presence of heavy metals in soils generally decreased the solution pH and pHBC values in spiked samples. In general, solubility of Ca, Mg, and K decreased with increasing equilibrium pH of non-spiked and spiked soil samples. In the case of P, increasing the pH to about 7, decreased the solubility in all soils but further increase of pH from 7, enhanced P solubility. The solubility trends and values for Ca, Mg, and K did not differed significantly in non-spiked and spiked samples. But in the case of P, a reduction in solubility was observed in heavy metal-spiked soils. The information obtained in this study can be useful to make better estimation of the effects of soil pollutants on anion and cation solubility from agricultural and environmental viewpoints.

ORAL IBOPAMINE SUBSTITUTION IN PATIENTS WITH INTRAVENOUS DOPAMINE DEPENDENCE

NARCIS (Netherlands)

GIRBES, ARJ; MILNER, AR; MCCLOSKEY, BV; ZWAVELING, JH; VANVELDHUISEN, DJ; ZIJLSTRA, JG; LIE, KI

1995-01-01

In a prospective open study we evaluated whether intravenous dopamine infusions can be safely switched to enterally administered ibopamine in dopamine-dependent patients. Six patients defined as being clinically stable, normovolaemic, but dopamine dependent, i.e. with repeated inability to stop

The Mutation Frequency in Different Spike Categories in Barley

DEFF Research Database (Denmark)

Frydenberg, O.; Doll, Hans; Sandfær, J.

1964-01-01

After gamma irradiation of barley seeds, a comparison has been made between the chlorophyll-mutant frequencies in X1 spikes that had multicellular bud meristems in the seeds at the time of treatment (denoted as pre-formed spikes) and X1 spikes having no recognizable meristems at the time...

Dopamine hypothesis of mania

OpenAIRE

Cookson, John

2014-01-01

s­of­the­Speakers­/­Konuşmacı­leriThe discovery of dopamine and its pathwaysDopamine (DA) was first synthesized in 1910 from 3,4-dihydroxy phenyl alanine (DOPA) by Barger and Ewens at Wellcome Laboratories in London. It is a cathecholamine and in the 1940s Blaschko in Cambridge proposed that DA was a precursor in synthesis of the cat-echolamine neurotransmitters noradrenaline (norepinephrine) and adrenaline (epinephrine). In 1957 it was shown to be present in the brain with other catecholamin...

The neurotropic parasite Toxoplasma gondii increases dopamine metabolism.

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Emese Prandovszky

Full Text Available The highly prevalent parasite Toxoplasma gondii manipulates its host's behavior. In infected rodents, the behavioral changes increase the likelihood that the parasite will be transmitted back to its definitive cat host, an essential step in completion of the parasite's life cycle. The mechanism(s responsible for behavioral changes in the host is unknown but two lines of published evidence suggest that the parasite alters neurotransmitter signal transduction: the disruption of the parasite-induced behavioral changes with medications used to treat psychiatric disease (specifically dopamine antagonists and identification of a tyrosine hydroxylase encoded in the parasite genome. In this study, infection of mammalian dopaminergic cells with T. gondii enhanced the levels of K+-induced release of dopamine several-fold, with a direct correlation between the number of infected cells and the quantity of dopamine released. Immunostaining brain sections of infected mice with dopamine antibody showed intense staining of encysted parasites. Based on these analyses, T. gondii orchestrates a significant increase in dopamine metabolism in neural cells. Tyrosine hydroxylase, the rate-limiting enzyme for dopamine synthesis, was also found in intracellular tissue cysts in brain tissue with antibodies specific for the parasite-encoded tyrosine hydroxylase. These observations provide a mechanism for parasite-induced behavioral changes. The observed effects on dopamine metabolism could also be relevant in interpreting reports of psychobehavioral changes in toxoplasmosis-infected humans.

Independent component analysis separates spikes of different origin in the EEG.

Science.gov (United States)

Urrestarazu, Elena; Iriarte, Jorge; Artieda, Julio; Alegre, Manuel; Valencia, Miguel; Viteri, César

2006-02-01

Independent component analysis (ICA) is a novel system that finds independent sources in recorded signals. Its usefulness in separating epileptiform activity of different origin has not been determined. The goal of this study was to demonstrate that ICA is useful for separating different spikes using samples of EEG of patients with focal epilepsy. Digital EEG samples from four patients with focal epilepsy were included. The patients had temporal (n = 2), centrotemporal (n = 1) or frontal spikes (n = 1). Twenty-six samples with two (or more) spikes from two different patients were created. The selection of the two spikes for each mixed EEG was performed randomly, trying to have all the different combinations and rejecting the mixture of two spikes from the same patient. Two different examiners studied the EEGs using ICA with JADE paradigm in Matlab platform, trying to separate and to identify the spikes. They agreed in the correct separation of the spikes in 24 of the 26 samples, classifying the spikes as frontal, temporal or centrotemporal, left or right sided. The demonstration of the possibility of detecting different artificially mixed spikes confirms that ICA may be useful in separating spikes or other elements in real EEGs.

Spiking and bursting patterns of fractional-order Izhikevich model

Science.gov (United States)

Teka, Wondimu W.; Upadhyay, Ranjit Kumar; Mondal, Argha

2018-03-01

Bursting and spiking oscillations play major roles in processing and transmitting information in the brain through cortical neurons that respond differently to the same signal. These oscillations display complex dynamics that might be produced by using neuronal models and varying many model parameters. Recent studies have shown that models with fractional order can produce several types of history-dependent neuronal activities without the adjustment of several parameters. We studied the fractional-order Izhikevich model and analyzed different kinds of oscillations that emerge from the fractional dynamics. The model produces a wide range of neuronal spike responses, including regular spiking, fast spiking, intrinsic bursting, mixed mode oscillations, regular bursting and chattering, by adjusting only the fractional order. Both the active and silent phase of the burst increase when the fractional-order model further deviates from the classical model. For smaller fractional order, the model produces memory dependent spiking activity after the pulse signal turned off. This special spiking activity and other properties of the fractional-order model are caused by the memory trace that emerges from the fractional-order dynamics and integrates all the past activities of the neuron. On the network level, the response of the neuronal network shifts from random to scale-free spiking. Our results suggest that the complex dynamics of spiking and bursting can be the result of the long-term dependence and interaction of intracellular and extracellular ionic currents.

Spike Bursts from an Excitable Optical System

Science.gov (United States)

Rios Leite, Jose R.; Rosero, Edison J.; Barbosa, Wendson A. S.; Tredicce, Jorge R.

Diode Lasers with double optical feedback are shown to present power drop spikes with statistical distribution controllable by the ratio of the two feedback times. The average time between spikes and the variance within long time series are studied. The system is shown to be excitable and present bursting of spikes created with specific feedback time ratios and strength. A rate equation model, extending the Lang-Kobayashi single feedback for semiconductor lasers proves to match the experimental observations. Potential applications to construct network to mimic neural systems having controlled bursting properties in each unit will be discussed. Brazilian Agency CNPQ.

Pulse shaping and energy storage capabilities of angularly multiplexed KrF laser fusion drivers

Science.gov (United States)

Lehmberg, R. H.; Giuliani, J. L.; Schmitt, A. J.

2009-07-01

This paper describes a rep-rated multibeam KrF laser driver design for the 500kJ Inertial Fusion test Facility (FTF) recently proposed by NRL, then models its optical pulse shaping capabilities using the ORESTES laser kinetics code. It describes a stable and reliable iteration technique for calculating the required precompensated input pulse shape that will achieve the desired output shape, even when the amplifiers are heavily saturated. It also describes how this precompensation technique could be experimentally implemented in real time on a reprated laser system. The simulations show that this multibeam system can achieve a high fidelity pulse shaping capability, even for a high gain shock ignition pulse whose final spike requires output intensities much higher than the ˜4MW/cm2 saturation levels associated with quasi-cw operation; i.e., they show that KrF can act as a storage medium even for pulsewidths of ˜1ns. For the chosen pulse, which gives a predicted fusion energy gain of ˜120, the simulations predict the FTF can deliver a total on-target energy of 428kJ, a peak spike power of 385TW, and amplified spontaneous emission prepulse contrast ratios IASE/Ilaser.

Acute phenylalanine/tyrosine depletion of phasic dopamine in the rat brain.

Science.gov (United States)

Shnitko, Tatiana A; Taylor, Sarah C; Stringfield, Sierra J; Zandy, Shannon L; Cofresí, Roberto U; Doherty, James M; Lynch, William B; Boettiger, Charlotte A; Gonzales, Rueben A; Robinson, Donita L

2016-06-01

Dopamine plays a critical role in striatal and cortical function, and depletion of the dopamine precursors phenylalanine and tyrosine is used in humans to temporarily reduce dopamine and probe the role of dopamine in behavior. This method has been shown to alter addiction-related behaviors and cognitive functioning presumably by reducing dopamine transmission, but it is unclear what specific aspects of dopamine transmission are altered. We performed this study to confirm that administration of an amino acid mixture omitting phenylalanine and tyrosine (Phe/Tyr[-]) reduces tyrosine tissue content in the prefrontal cortex (PFC) and nucleus accumbens (NAc), and to test the hypothesis that Phe/Tyr[-] administration reduces phasic dopamine release in the NAc. Rats were injected with a Phe/Tyr[-] amino acid mixture, a control amino acid mixture, or saline. High-performance liquid chromatography was used to determine the concentration of tyrosine, dopamine, or norepinephrine in tissue punches from the PFC and ventral striatum. In a separate group of rats, phasic dopamine release was measured with fast-scan cyclic voltammetry in the NAc core after injection with either the Phe/Tyr[-] mixture or the control amino acid solution. Phe/Tyr[-] reduced tyrosine content in the PFC and NAc, but dopamine and norepinephrine tissue content were not reduced. Moreover, Phe/Tyr[-] decreased the frequency of dopamine transients, but not their amplitude, in freely moving rats. These results indicate that depletion of tyrosine via Phe/Tyr[-] decreases phasic dopamine transmission, providing insight into the mechanism by which this method modifies dopamine-dependent behaviors in human imaging studies.

A photoaffinity ligand for dopamine D2 receptors: azidoclebopride.

Science.gov (United States)

Niznik, H B; Guan, J H; Neumeyer, J L; Seeman, P

1985-02-01

In order to label D2 dopamine receptors selectively and covalently by means of a photosensitive compound, azidoclebopride was synthesized directly from clebopride. The dissociation constant (KD) of clebopride for the D2 dopamine receptor (canine brain striatum) was 1.5 nM, while that for azidoclebopride was 21 nM. The affinities of both clebopride and azidoclebopride were markedly reduced in the absence of sodium chloride. In the presence of ultraviolet light, azidoclebopride inactivated D2 dopamine receptors irreversibly, as indicated by the inability of the receptors to bind [3H]spiperone. Maximal photoinactivation of about 60% of the D2 dopamine receptors occurred at 1 microM azidoclebopride; 30% of the receptors were inactivated at 80 nM azidoclebopride (pseudo-IC50). Dopamine agonists selectively protected the D2 receptors from being inactivated by azidoclebopride, the order of potency being (-)-N-n-propylnorapomorphine greater than apomorphine greater than (+/-)-6,7-dihydroxy-2-aminotetralin greater than (+)-N-n-propylnorapomorphine greater than dopamine greater than noradrenaline greater than serotonin. Similarly, dopaminergic antagonists prevented the photoinactivation of D2 receptors by azidoclebopride with the following order of potency: spiperone greater than (+)-butaclamol greater than haloperidol greater than clebopride greater than (-)-sulpiride greater than (-)-butaclamol. The degree of D2 dopamine receptor photoinduced inactivation by azidoclebopride was not significantly affected by scavengers such as p-aminobenzoic acid and dithiothreitol. Furthermore, irradiation of striatal membranes with a concentration of azidoclebopride sufficient to inactivate dopamine D2 receptors by 60% did not significantly reduce dopamine D1, serotonin (S2), benzodiazepine, alpha 1- or beta-noradrenergic receptors. This study describes the use of a novel and selective photoaffinity ligand for brain dopamine D2 receptors. The molecule, in radiolabeled form, may aid in the

Blockade of dopamine D1-family receptors attenuates the mania-like hyperactive, risk-preferring, and high motivation behavioral profile of mice with low dopamine transporter levels.

Science.gov (United States)

Milienne-Petiot, Morgane; Groenink, Lucianne; Minassian, Arpi; Young, Jared W

2017-10-01

Patients with bipolar disorder mania exhibit poor cognition, impulsivity, risk-taking, and goal-directed activity that negatively impact their quality of life. To date, existing treatments for bipolar disorder do not adequately remediate cognitive dysfunction. Reducing dopamine transporter expression recreates many bipolar disorder mania-relevant behaviors (i.e. hyperactivity and risk-taking). The current study investigated whether dopamine D 1 -family receptor blockade would attenuate the risk-taking, hypermotivation, and hyperactivity of dopamine transporter knockdown mice. Dopamine transporter knockdown and wild-type littermate mice were tested in mouse versions of the Iowa Gambling Task (risk-taking), Progressive Ratio Breakpoint Test (effortful motivation), and Behavioral Pattern Monitor (activity). Prior to testing, the mice were treated with the dopamine D 1 -family receptor antagonist SCH 23390 hydrochloride (0.03, 0.1, or 0.3 mg/kg), or vehicle. Dopamine transporter knockdown mice exhibited hyperactivity and hyperexploration, hypermotivation, and risk-taking preference compared with wild-type littermates. SCH 23390 hydrochloride treatment decreased premature responding in dopamine transporter knockdown mice and attenuated their hypermotivation. SCH 23390 hydrochloride flattened the safe/risk preference, while reducing activity and exploratory levels of both genotypes similarly. Dopamine transporter knockdown mice exhibited mania-relevant behavior compared to wild-type mice. Systemic dopamine D 1 -family receptor antagonism attenuated these behaviors in dopamine transporter knockdown, but not all effects were specific to only the knockdown mice. The normalization of behavior via blockade of dopamine D 1 -family receptors supports the hypothesis that D 1 and/or D 5 receptors could contribute to the mania-relevant behaviors of dopamine transporter knockdown mice.

Dopamine receptor activation increases HIV entry into primary human macrophages.

Directory of Open Access Journals (Sweden)

Peter J Gaskill

Full Text Available Macrophages are the primary cell type infected with HIV in the central nervous system, and infection of these cells is a major component in the development of neuropathogenesis and HIV-associated neurocognitive disorders. Within the brains of drug abusers, macrophages are exposed to increased levels of dopamine, a neurotransmitter that mediates the addictive and reinforcing effects of drugs of abuse such as cocaine and methamphetamine. In this study we examined the effects of dopamine on HIV entry into primary human macrophages. Exposure to dopamine during infection increased the entry of R5 tropic HIV into macrophages, irrespective of the concentration of the viral inoculum. The entry pathway affected was CCR5 dependent, as antagonizing CCR5 with the small molecule inhibitor TAK779 completely blocked entry. The effect was dose-dependent and had a steep threshold, only occurring above 108 M dopamine. The dopamine-mediated increase in entry required dopamine receptor activation, as it was abrogated by the pan-dopamine receptor antagonist flupenthixol, and could be mediated through both subtypes of dopamine receptors. These findings indicate that the effects of dopamine on macrophages may have a significant impact on HIV pathogenesis. They also suggest that drug-induced increases in CNS dopamine may be a common mechanism by which drugs of abuse with distinct modes of action exacerbate neuroinflammation and contribute to HIV-associated neurocognitive disorders in infected drug abusers.

Development of the SPIKE code for analysis of the sodium-water reaction

Energy Technology Data Exchange (ETDEWEB)

Hwang, Sung Tai; Park, Jin Ho; Choi, Jong Hyeun; Kim, Tae Joon [Korea Atomic Energy Research Institute, Taejon (Korea)

1998-08-01

In the secondary loop of liquid metal reactors, including SG, water leak into sodium causes the sudden increase of pressure by the H{sub 2} and heat generated from reaction. At few miliseconds after leak, a sharp and short-lived increase of pressure is generated and its propagation depends on the acoustic constraint characteristics of secondary loop. As increasing leak amount of water, another pressure increase is caused by H{sub 2} and its transients depends on the resistance of pressure opening system, such as rupture disc. For prediction of the transients of initial spike pressure, a code of SPIKE was developed. The code was based on the following simplifications and assumptions: combination of total and half release of H{sub 2} rate, spherical shape of H{sub 2} bubble, compressible and Newtonian fluid for sodium. The program was built in FOTRAN language and consisted of 5 modules. Several sample calculations were performed to test the code and to determine the scale down factor of experimental facilities for experimental verification of the code: parameter study of the variables in chemical reaction model, comparison study with results calculated by superposition methods for simple piping structures, comparison study with results calculated by previous researchers, and calculation for KALIMER models of various size. With these calculation results, the generally predicted phenomena of sodium water reaction can be explained and the calculated ones by SPIKE code were well agreed with the previous study. And the scale down factor can be determined. (author). 88 refs., 99 figs., 39 tabs.

ILLICIT DOPAMINE TRANSIENTS: RECONCILING ACTIONS OF ABUSED DRUGS

OpenAIRE

Covey, Dan P.; Roitman, Mitchell F.; Garris, Paul A.

2014-01-01

Phasic increases in brain dopamine are required for cue-directed reward seeking. While compelling within the framework of appetitive behavior, the view that illicit drugs hijack reward circuits by hyper-activating these dopamine transients is inconsistent with established psychostimulant pharmacology. However, recent work reclassifying amphetamine (AMPH), cocaine, and other addictive dopamine-transporter inhibitors (DAT-Is) supports transient hyper-activation as a unifying hypothesis of abuse...

Comparison of Classifier Architectures for Online Neural Spike Sorting.

Science.gov (United States)

Saeed, Maryam; Khan, Amir Ali; Kamboh, Awais Mehmood

2017-04-01

High-density, intracranial recordings from micro-electrode arrays need to undergo Spike Sorting in order to associate the recorded neuronal spikes to particular neurons. This involves spike detection, feature extraction, and classification. To reduce the data transmission and power requirements, on-chip real-time processing is becoming very popular. However, high computational resources are required for classifiers in on-chip spike-sorters, making scalability a great challenge. In this review paper, we analyze several popular classifiers to propose five new hardware architectures using the off-chip training with on-chip classification approach. These include support vector classification, fuzzy C-means classification, self-organizing maps classification, moving-centroid K-means classification, and Cosine distance classification. The performance of these architectures is analyzed in terms of accuracy and resource requirement. We establish that the neural networks based Self-Organizing Maps classifier offers the most viable solution. A spike sorter based on the Self-Organizing Maps classifier, requires only 7.83% of computational resources of the best-reported spike sorter, hierarchical adaptive means, while offering a 3% better accuracy at 7 dB SNR.

Automatic fitting of spiking neuron models to electrophysiological recordings

Directory of Open Access Journals (Sweden)

Cyrille Rossant

2010-03-01

Full Text Available Spiking models can accurately predict the spike trains produced by cortical neurons in response to somatically injected currents. Since the specific characteristics of the model depend on the neuron, a computational method is required to fit models to electrophysiological recordings. The fitting procedure can be very time consuming both in terms of computer simulations and in terms of code writing. We present algorithms to fit spiking models to electrophysiological data (time-varying input and spike trains that can run in parallel on graphics processing units (GPUs. The model fitting library is interfaced with Brian, a neural network simulator in Python. If a GPU is present it uses just-in-time compilation to translate model equations into optimized code. Arbitrary models can then be defined at script level and run on the graphics card. This tool can be used to obtain empirically validated spiking models of neurons in various systems. We demonstrate its use on public data from the INCF Quantitative Single-Neuron Modeling 2009 competition by comparing the performance of a number of neuron spiking models.

Scaling of spiking and humping in keyhole welding

Energy Technology Data Exchange (ETDEWEB)

Wei, P S; Chuang, K C [Department of Mechanical and Electro-Mechanical Engineering, National Sun Yat-Sen University, Kaohsiung, Taiwan (China); DebRoy, T [Department of Materials Science and Engineering, The Pennsylvania State University, University Park, PA 16802 (United States); Ku, J S, E-mail: pswei@mail.nsysu.edu.tw, E-mail: cielo.zhuang@gmail.com, E-mail: rtd1@psu.edu, E-mail: jsku@mail.nsysu.edu.tw [Institute of Materials Science and Engineering, National Sun Yat-Sen University, Kaohsiung, Taiwan (China)

2011-06-22

Spiking, rippling and humping seriously reduce the strength of welds. The effects of beam focusing, volatile alloying element concentration and welding velocity on spiking, coarse rippling and humping in keyhole mode electron-beam welding are examined through scale analysis. Although these defects have been studied in the past, the mechanisms for their formation are not fully understood. This work relates the average amplitudes of spikes to fusion zone depth for the welding of Al 6061, SS 304 and carbon steel, and Al 5083. The scale analysis introduces welding and melting efficiencies and an appropriate power distribution to account for the focusing effects, and the energy which is reflected and escapes through the keyhole opening to the surroundings. The frequency of humping and spiking can also be predicted from the scale analysis. The analysis also reveals the interrelation between coarse rippling and humping. The data and the mechanistic findings reported in this study are useful for understanding and preventing spiking and humping during keyhole mode electron and laser beam welding.

Behavioural effects of chemogenetic dopamine neuron activation

NARCIS (Netherlands)

Boekhoudt, L

2016-01-01

Various psychiatric disorders, including schizophrenia, attention-deficit/hyperactivity disorder (ADHD) and major depressive disorder, have been associated with altered dopamine signalling in the brain. However, it remains unclear which specific changes in dopamine activity are related to specific

Enhanced striatal dopamine release during food stimulation in binge eating disorder

Energy Technology Data Exchange (ETDEWEB)

Wang, g.j.; Wang, G.-J.; Geliebter, A.; Volkow, N.D.; Telang, F.W.; Logan, Jaynbe, M.C.; Galanti, K.; Selig, P.A.; Han, H.; Zhu, W.; Wong, C.T.; Fowler, J.S.

2011-01-13

Subjects with binge eating disorder (BED) regularly consume large amounts of food in short time periods. The neurobiology of BED is poorly understood. Brain dopamine, which regulates motivation for food intake, is likely to be involved. We assessed the involvement of brain dopamine in the motivation for food consumption in binge eaters. Positron emission tomography (PET) scans with [{sup 11}C]raclopride were done in 10 obese BED and 8 obese subjects without BED. Changes in extracellular dopamine in the striatum in response to food stimulation in food-deprived subjects were evaluated after placebo and after oral methylphenidate (MPH), a drug that blocks the dopamine reuptake transporter and thus amplifies dopamine signals. Neither the neutral stimuli (with or without MPH) nor the food stimuli when given with placebo increased extracellular dopamine. The food stimuli when given with MPH significantly increased dopamine in the caudate and putamen in the binge eaters but not in the nonbinge eaters. Dopamine increases in the caudate were significantly correlated with the binge eating scores but not with BMI. These results identify dopamine neurotransmission in the caudate as being of relevance to the neurobiology of BED. The lack of correlation between BMI and dopamine changes suggests that dopamine release per se does not predict BMI within a group of obese individuals but that it predicts binge eating.

Enhanced striatal dopamine release during food stimulation in binge eating disorder

International Nuclear Information System (INIS)

Wang, G.-J.; Geliebter, A.; Volkow, N.D.; Telang, F.W.; Logan, J.; Jaynbe, M.C.; Galanti, K.; Selig, P.A.; Han, H.; Zhu, W.; Wong, C.T.; Fowler, J.S.

2011-01-01

Subjects with binge eating disorder (BED) regularly consume large amounts of food in short time periods. The neurobiology of BED is poorly understood. Brain dopamine, which regulates motivation for food intake, is likely to be involved. We assessed the involvement of brain dopamine in the motivation for food consumption in binge eaters. Positron emission tomography (PET) scans with [ 11 C]raclopride were done in 10 obese BED and 8 obese subjects without BED. Changes in extracellular dopamine in the striatum in response to food stimulation in food-deprived subjects were evaluated after placebo and after oral methylphenidate (MPH), a drug that blocks the dopamine reuptake transporter and thus amplifies dopamine signals. Neither the neutral stimuli (with or without MPH) nor the food stimuli when given with placebo increased extracellular dopamine. The food stimuli when given with MPH significantly increased dopamine in the caudate and putamen in the binge eaters but not in the nonbinge eaters. Dopamine increases in the caudate were significantly correlated with the binge eating scores but not with BMI. These results identify dopamine neurotransmission in the caudate as being of relevance to the neurobiology of BED. The lack of correlation between BMI and dopamine changes suggests that dopamine release per se does not predict BMI within a group of obese individuals but that it predicts binge eating.

A metric space approach to the information capacity of spike trains

OpenAIRE

HOUGHTON, CONOR JAMES; GILLESPIE, JAMES

2010-01-01

PUBLISHED Classical information theory can be either discrete or continuous, corresponding to discrete or continuous random variables. However, although spike times in a spike train are described by continuous variables, the information content is usually calculated using discrete information theory. This is because the number of spikes, and hence, the number of variables, varies from spike train to spike train, making the continuous theory difficult to apply.It is possible to avoid ...

Clustering predicts memory performance in networks of spiking and non-spiking neurons

Directory of Open Access Journals (Sweden)

Weiliang eChen

2011-03-01

Full Text Available The problem we address in this paper is that of finding effective and parsimonious patterns of connectivity in sparse associative memories. This problem must be addressed in real neuronal systems, so that results in artificial systems could throw light on real systems. We show that there are efficient patterns of connectivity and that these patterns are effective in models with either spiking or non-spiking neurons. This suggests that there may be some underlying general principles governing good connectivity in such networks. We also show that the clustering of the network, measured by Clustering Coefficient, has a strong linear correlation to the performance of associative memory. This result is important since a purely static measure of network connectivity appears to determine an important dynamic property of the network.

Voltage-spike analysis for a free-running parallel inverter

Science.gov (United States)

Lee, F. C. Y.; Wilson, T. G.

1974-01-01

Unwanted and sometimes damaging high-amplitude voltage spikes occur during each half cycle in many transistor saturable-core inverters at the moment when the core saturates and the transistors switch. The analysis shows that spikes are an intrinsic characteristic of certain types of inverters even with negligible leakage inductance and purely resistive load. The small but unavoidable after-saturation inductance of the saturable-core transformer plays an essential role in creating these undesired thigh-voltage spikes. State-plane analysis provides insight into the complex interaction between core and transistors, and shows the circuit parameters upon which the magnitude of these spikes depends.

In-reactor creep of zirconium alloys by thermal spikes

International Nuclear Information System (INIS)

Ibrahim, E.F.

1975-01-01

The size and duration of thermal spikes from fast neutrons have been calculated for zirconium alloys, showing that spikes up to 1.8 nm radius may exist for 2 x 10 -11 s at greater than melting point, at 570K ambient temperature. Creep rates have been calculated assuming that the elastic strain from the applied stress relaxes in the volume of the spikes (by preferential loop alignment or modification of an existing dislocation network). The calculated rates are consistent with strain rates observed in long term tests-in-reactor, if spike lifetimes are 2 to 2.5 x 10 -11 s. (Auth.)

Automated spike preparation system for Isotope Dilution Mass Spectrometry (IDMS)

International Nuclear Information System (INIS)

Maxwell, S.L. III; Clark, J.P.

1990-01-01

Isotope Dilution Mass Spectrometry (IDMS) is a method frequently employed to measure dissolved, irradiated nuclear materials. A known quantity of a unique isotope of the element to be measured (referred to as the ''spike'') is added to the solution containing the analyte. The resulting solution is chemically purified then analyzed by mass spectrometry. By measuring the magnitude of the response for each isotope and the response for the ''unique spike'' then relating this to the known quantity of the ''spike'', the quantity of the nuclear material can be determined. An automated spike preparation system was developed at the Savannah River Site (SRS) to dispense spikes for use in IDMS analytical methods. Prior to this development, technicians weighed each individual spike manually to achieve the accuracy required. This procedure was time-consuming and subjected the master stock solution to evaporation. The new system employs a high precision SMI Model 300 Unipump dispenser interfaced with an electronic balance and a portable Epson HX-20 notebook computer to automate spike preparation

Spike-threshold adaptation predicted by membrane potential dynamics in vivo.

Directory of Open Access Journals (Sweden)

Bertrand Fontaine

2014-04-01

Full Text Available Neurons encode information in sequences of spikes, which are triggered when their membrane potential crosses a threshold. In vivo, the spiking threshold displays large variability suggesting that threshold dynamics have a profound influence on how the combined input of a neuron is encoded in the spiking. Threshold variability could be explained by adaptation to the membrane potential. However, it could also be the case that most threshold variability reflects noise and processes other than threshold adaptation. Here, we investigated threshold variation in auditory neurons responses recorded in vivo in barn owls. We found that spike threshold is quantitatively predicted by a model in which the threshold adapts, tracking the membrane potential at a short timescale. As a result, in these neurons, slow voltage fluctuations do not contribute to spiking because they are filtered by threshold adaptation. More importantly, these neurons can only respond to input spikes arriving together on a millisecond timescale. These results demonstrate that fast adaptation to the membrane potential captures spike threshold variability in vivo.

An Overview of Bayesian Methods for Neural Spike Train Analysis

Directory of Open Access Journals (Sweden)

Zhe Chen

2013-01-01

Full Text Available Neural spike train analysis is an important task in computational neuroscience which aims to understand neural mechanisms and gain insights into neural circuits. With the advancement of multielectrode recording and imaging technologies, it has become increasingly demanding to develop statistical tools for analyzing large neuronal ensemble spike activity. Here we present a tutorial overview of Bayesian methods and their representative applications in neural spike train analysis, at both single neuron and population levels. On the theoretical side, we focus on various approximate Bayesian inference techniques as applied to latent state and parameter estimation. On the application side, the topics include spike sorting, tuning curve estimation, neural encoding and decoding, deconvolution of spike trains from calcium imaging signals, and inference of neuronal functional connectivity and synchrony. Some research challenges and opportunities for neural spike train analysis are discussed.

Genetically determined interaction between the dopamine transporter and the D2 receptor on prefronto-striatal activity and volume in humans.

Science.gov (United States)

Bertolino, Alessandro; Fazio, Leonardo; Di Giorgio, Annabella; Blasi, Giuseppe; Romano, Raffaella; Taurisano, Paolo; Caforio, Grazia; Sinibaldi, Lorenzo; Ursini, Gianluca; Popolizio, Teresa; Tirotta, Emanuele; Papp, Audrey; Dallapiccola, Bruno; Borrelli, Emiliana; Sadee, Wolfgang

2009-01-28

Dopamine modulation of neuronal activity during memory tasks identifies a nonlinear inverted-U shaped function. Both the dopamine transporter (DAT) and dopamine D(2) receptors (encoded by DRD(2)) critically regulate dopamine signaling in the striatum and in prefrontal cortex during memory. Moreover, in vitro studies have demonstrated that DAT and D(2) proteins reciprocally regulate each other presynaptically. Therefore, we have evaluated the genetic interaction between a DRD(2) polymorphism (rs1076560) causing reduced presynaptic D(2) receptor expression and the DAT 3'-VNTR variant (affecting DAT expression) in a large sample of healthy subjects undergoing blood oxygenation level-dependent (BOLD)-functional magnetic resonance imaging (MRI) during memory tasks and structural MRI. Results indicated a significant DRD(2)/DAT interaction in prefrontal cortex and striatum BOLD activity during both working memory and encoding of recognition memory. The differential effect on BOLD activity of the DAT variant was mostly manifest in the context of the DRD(2) allele associated with lower presynaptic expression. Similar results were also evident for gray matter volume in caudate. These interactions describe a nonlinear relationship between compound genotypes and brain activity or gray matter volume. Complementary data from striatal protein extracts from wild-type and D(2) knock-out animals (D2R(-/-)) indicate that DAT and D(2) proteins interact in vivo. Together, our results demonstrate that the interaction between genetic variants in DRD(2) and DAT critically modulates the nonlinear relationship between dopamine and neuronal activity during memory processing.

Dopamine and glucose, obesity and Reward Deficiency Syndrome

Directory of Open Access Journals (Sweden)

Kenneth eBlum

2014-09-01

Full Text Available Obesity and many well described eating disorders are accurately considered a global epidemic. The consequences of Reward Deficiency Syndrome, a genetic and epigenetic phenomena that involves the interactions of powerful neurotransmitters, are impairments of brain reward circuitry, hypodopaminergic function and abnormal craving behavior. Numerous sound neurochemical and genetic studies provide strong evidence that food addiction is similar to psychoactive drug addiction. Important facts which could translate to potential therapeutic targets espoused in this review include: 1 brain dopamine (DA production and use is stimulated by consumption of alcohol in large quantities or carbohydrates bingeing; 2 in the mesolimbic system the enkephalinergic neurons are in close proximity, to glucose receptors; 3 highly concentrated glucose activates the calcium channel to stimulate dopamine release from P12 cells; 4 blood glucose and cerebrospinal fluid concentrations of homovanillic acid, the dopamine metabolite, are significantly correlated and 5 2-deoxyglucose the glucose analogue, in pharmacological doses associates with enhanced dopamine turnover and causes acute glucoprivation. Evidence from animal studies and human fMRI support the hypothesis that multiple, but similar brain circuits are disrupted in obesity and drug dependence and DA-modulated reward circuits are involved in pathologic eating behaviors. Treatment for addiction to glucose and drugs alike, based on a consensus of neuroscience research, should incorporate dopamine agonist therapy, in contrast to current theories and practices that use dopamine antagonists. Until now, powerful dopamine-D2 agonists have failed clinically, due to chronic down regulation of D2 receptors instead, consideration of novel less powerful D2 agonists that up-regulate D2 receptors seems prudent. We encourage new strategies targeted at improving DA function in the treatment and prevention of obesity a subtype of

Self-Consistent Scheme for Spike-Train Power Spectra in Heterogeneous Sparse Networks.

Science.gov (United States)

Pena, Rodrigo F O; Vellmer, Sebastian; Bernardi, Davide; Roque, Antonio C; Lindner, Benjamin

2018-01-01

Recurrent networks of spiking neurons can be in an asynchronous state characterized by low or absent cross-correlations and spike statistics which resemble those of cortical neurons. Although spatial correlations are negligible in this state, neurons can show pronounced temporal correlations in their spike trains that can be quantified by the autocorrelation function or the spike-train power spectrum. Depending on cellular and network parameters, correlations display diverse patterns (ranging from simple refractory-period effects and stochastic oscillations to slow fluctuations) and it is generally not well-understood how these dependencies come about. Previous work has explored how the single-cell correlations in a homogeneous network (excitatory and inhibitory integrate-and-fire neurons with nearly balanced mean recurrent input) can be determined numerically from an iterative single-neuron simulation. Such a scheme is based on the fact that every neuron is driven by the network noise (i.e., the input currents from all its presynaptic partners) but also contributes to the network noise, leading to a self-consistency condition for the input and output spectra. Here we first extend this scheme to homogeneous networks with strong recurrent inhibition and a synaptic filter, in which instabilities of the previous scheme are avoided by an averaging procedure. We then extend the scheme to heterogeneous networks in which (i) different neural subpopulations (e.g., excitatory and inhibitory neurons) have different cellular or connectivity parameters; (ii) the number and strength of the input connections are random (Erdős-Rényi topology) and thus different among neurons. In all heterogeneous cases, neurons are lumped in different classes each of which is represented by a single neuron in the iterative scheme; in addition, we make a Gaussian approximation of the input current to the neuron. These approximations seem to be justified over a broad range of parameters as

Self-Consistent Scheme for Spike-Train Power Spectra in Heterogeneous Sparse Networks

Directory of Open Access Journals (Sweden)

Rodrigo F. O. Pena

2018-03-01

Full Text Available Recurrent networks of spiking neurons can be in an asynchronous state characterized by low or absent cross-correlations and spike statistics which resemble those of cortical neurons. Although spatial correlations are negligible in this state, neurons can show pronounced temporal correlations in their spike trains that can be quantified by the autocorrelation function or the spike-train power spectrum. Depending on cellular and network parameters, correlations display diverse patterns (ranging from simple refractory-period effects and stochastic oscillations to slow fluctuations and it is generally not well-understood how these dependencies come about. Previous work has explored how the single-cell correlations in a homogeneous network (excitatory and inhibitory integrate-and-fire neurons with nearly balanced mean recurrent input can be determined numerically from an iterative single-neuron simulation. Such a scheme is based on the fact that every neuron is driven by the network noise (i.e., the input currents from all its presynaptic partners but also contributes to the network noise, leading to a self-consistency condition for the input and output spectra. Here we first extend this scheme to homogeneous networks with strong recurrent inhibition and a synaptic filter, in which instabilities of the previous scheme are avoided by an averaging procedure. We then extend the scheme to heterogeneous networks in which (i different neural subpopulations (e.g., excitatory and inhibitory neurons have different cellular or connectivity parameters; (ii the number and strength of the input connections are random (Erdős-Rényi topology and thus different among neurons. In all heterogeneous cases, neurons are lumped in different classes each of which is represented by a single neuron in the iterative scheme; in addition, we make a Gaussian approximation of the input current to the neuron. These approximations seem to be justified over a broad range of

Multiple enhancement of luminol electrochemiluminescence using electrodes functionalized with titania nanotubes and platinum black: ultrasensitive determination of hydrogen peroxide, resveratrol, and dopamine

International Nuclear Information System (INIS)

Ming, Liang; Peng, Tingting; Tu, Yifeng

2016-01-01

We describe a substantial improvement of the electrochemiluminescence (ECL) of luminol which is widely used in flow injection analysis (FIA). It is based on synchronous dual sensitization of ECL by using titania nanotubes (TiNTs) and platinum black (PB). A piece of indium tin oxide (ITO) glass functionalized with TiNTs acts as the first working electrode, and a PB-modified platinum plate serves as the second one. By applying two constant potentials to the two electrodes, strong and consecutive ECL emission of luminol is obtained. The system works well in assays as shown for the successful quantitation of hydrogen peroxide (H 2 O 2 ), of the antioxidant resveratrol, and of the neutrotransmitter dopamine (DA) in spiked human serum samples. The detection limits for these three species (at a signal-to-noise ratio of 3) are as low as 66 pM (H 2 O 2 ), 22 nM (resveratrol), and 30 nM (DA). Recoveries in assays of DA in spiked serum range from 97.3 to 105.4 %. In our perception, the technique of dual sensitization represents a substantial improvement of the detection limits of ECL assays. (author)

Emergent dynamics of spiking neurons with fluctuating threshold

Science.gov (United States)

Bhattacharjee, Anindita; Das, M. K.

2017-05-01

Role of fluctuating threshold on neuronal dynamics is investigated. The threshold function is assumed to follow a normal probability distribution. Standard deviation of inter-spike interval of the response is computed as an indicator of irregularity in spike emission. It has been observed that, the irregularity in spiking is more if the threshold variation is more. A significant change in modal characteristics of Inter Spike Intervals (ISI) is seen to occur as a function of fluctuation parameter. Investigation is further carried out for coupled system of neurons. Cooperative dynamics of coupled neurons are discussed in view of synchronization. Total and partial synchronization regimes are depicted with the help of contour plots of synchrony measure under various conditions. Results of this investigation may provide a basis for exploring the complexities of neural communication and brain functioning.

Single-trial estimation of stimulus and spike-history effects on time-varying ensemble spiking activity of multiple neurons: a simulation study

International Nuclear Information System (INIS)

Shimazaki, Hideaki

2013-01-01

Neurons in cortical circuits exhibit coordinated spiking activity, and can produce correlated synchronous spikes during behavior and cognition. We recently developed a method for estimating the dynamics of correlated ensemble activity by combining a model of simultaneous neuronal interactions (e.g., a spin-glass model) with a state-space method (Shimazaki et al. 2012 PLoS Comput Biol 8 e1002385). This method allows us to estimate stimulus-evoked dynamics of neuronal interactions which is reproducible in repeated trials under identical experimental conditions. However, the method may not be suitable for detecting stimulus responses if the neuronal dynamics exhibits significant variability across trials. In addition, the previous model does not include effects of past spiking activity of the neurons on the current state of ensemble activity. In this study, we develop a parametric method for simultaneously estimating the stimulus and spike-history effects on the ensemble activity from single-trial data even if the neurons exhibit dynamics that is largely unrelated to these effects. For this goal, we model ensemble neuronal activity as a latent process and include the stimulus and spike-history effects as exogenous inputs to the latent process. We develop an expectation-maximization algorithm that simultaneously achieves estimation of the latent process, stimulus responses, and spike-history effects. The proposed method is useful to analyze an interaction of internal cortical states and sensory evoked activity

The electric potential of tripolar spikes

Energy Technology Data Exchange (ETDEWEB)

Nocera, L. [Theoretical Plasma Physics, IPCF-CNR, Via Moruzzi 1, I-56124 Pisa (Italy)

2010-02-22

We present an analytical formula for the waveform of the electric potential associated with a tripolar spike in a plasma. This formula is based on the construction and on the subsequent solution of a differential equation for the waveform. We work out this equation as a direct consequence of the morphological and functional properties of the observed waveform, without making any reference to the velocity distributions of the electrons and of the ions which sustain the spike. In the approximation of small potential amplitudes, we solve this equation by quadrature. In particular, in the second order approximation, the solution of this equation is given in terms of elementary functions. This analytical solution is able to reproduce the potential waveforms associated with electron holes, ion holes, monotonic and nonmonotonic double layers and tripolar spikes, in excellent agreement with observations.

The electric potential of tripolar spikes

International Nuclear Information System (INIS)

Nocera, L.

2010-01-01

We present an analytical formula for the waveform of the electric potential associated with a tripolar spike in a plasma. This formula is based on the construction and on the subsequent solution of a differential equation for the waveform. We work out this equation as a direct consequence of the morphological and functional properties of the observed waveform, without making any reference to the velocity distributions of the electrons and of the ions which sustain the spike. In the approximation of small potential amplitudes, we solve this equation by quadrature. In particular, in the second order approximation, the solution of this equation is given in terms of elementary functions. This analytical solution is able to reproduce the potential waveforms associated with electron holes, ion holes, monotonic and nonmonotonic double layers and tripolar spikes, in excellent agreement with observations.

Poly(dopamine) coating to biodegradable polymers for bone tissue engineering.

Science.gov (United States)

Tsai, Wei-Bor; Chen, Wen-Tung; Chien, Hsiu-Wen; Kuo, Wei-Hsuan; Wang, Meng-Jiy

2014-02-01

In this study, a technique based on poly(dopamine) deposition to promote cell adhesion was investigated for the application in bone tissue engineering. The adhesion and proliferation of rat osteoblasts were evaluated on poly(dopamine)-coated biodegradable polymer films, such as polycaprolactone, poly(l-lactide) and poly(lactic-co-glycolic acid), which are commonly used biodegradable polymers in tissue engineering. Cell adhesion was significantly increased to a plateau by merely 15 s of dopamine incubation, 2.2-4.0-folds of increase compared to the corresponding untreated substrates. Cell proliferation was also greatly enhanced by poly(dopamine) deposition, indicated by shortened cell doubling time. Mineralization was also increased on the poly(dopamine)-deposited surfaces. The potential of poly(dopamine) deposition in bone tissue engineering is demonstrated in this study.

Demonstration of conjugated dopamine in monkey CSF by gas chromatography-mass spectrometry

Energy Technology Data Exchange (ETDEWEB)

Elchisak, M A; Powers, K H; Ebert, M H

1982-09-01

A method for measuring unconjugated and conjugated dopamine in body tissues and fluids is described. Conjugated dopamine was hydrolyzed in acid to unconjugated dopamine, separated from the sample matrix by alumina chromatography, and assayed by gas chromatography-mass spectrometry. Conjugated dopamine was detected in greater concentrations than unconjugated dopamine in CSF taken from lateral ventricle or thecal sac of the Rhesus monkey. Haloperidol administration did not increase the levels of conjugated dopamine in lumbar CSF.

Phasic dopamine release drives rapid activation of striatal D2-receptors

Science.gov (United States)

Marcott, Pamela F; Mamaligas, Aphroditi A; Ford, Christopher P

2014-01-01

Summary Striatal dopamine transmission underlies numerous goal-directed behaviors. Medium spiny neurons (MSNs) are a major target of dopamine in the striatum. However, as dopamine does not directly evoke a synaptic event in MSNs, the time course of dopamine signaling in these cells remains unclear. To examine how dopamine release activates D2-receptors on MSNs, G-protein activated inwardly rectifying potassium (GIRK2; Kir 3.2) channels were virally overexpressed in the striatum and the resulting outward currents were used as a sensor of D2-receptor activation. Electrical and optogenetic stimulation of dopamine terminals evoked robust D2-receptor inhibitory post-synaptic currents (IPSCs) in GIRK2-expressing MSNs that occurred in under a second. Evoked D2-IPSCs could be driven by repetitive stimulation and were not occluded by background dopamine tone. Together, the results indicate that D2-receptors on MSNs exhibit functional low affinity and suggest that striatal D2-receptors can encode both tonic and phasic dopamine signals. PMID:25242218

Photoaffinity ligand for dopamine D2 receptors: azidoclebopride

International Nuclear Information System (INIS)

Niznik, H.B.; Guan, J.H.; Neumeyer, J.L.; Seeman, P.

1985-01-01

In order to label D2 dopamine receptors selectively and covalently by means of a photosensitive compound, azidoclebopride was synthesized directly from clebopride. The dissociation constant (KD) of clebopride for the D2 dopamine receptor (canine brain striatum) was 1.5 nM, while that for azidoclebopride was 21 nM. The affinities of both clebopride and azidoclebopride were markedly reduced in the absence of sodium chloride. In the presence of ultraviolet light, azidoclebopride inactivated D2 dopamine receptors irreversibly, as indicated by the inability of the receptors to bind [ 3 H]spiperone. Maximal photoinactivation of about 60% of the D2 dopamine receptors occurred at 1 microM azidoclebopride; 30% of the receptors were inactivated at 80 nM azidoclebopride (pseudo-IC50). Dopamine agonists selectively protected the D2 receptors from being inactivated by azidoclebopride, the order of potency being (-)-N-n-propylnorapomorphine greater than apomorphine greater than (+/-)-6,7-dihydroxy-2-aminotetralin greater than (+)-N-n-propylnorapomorphine greater than dopamine greater than noradrenaline greater than serotonin. Similarly, dopaminergic antagonists prevented the photoinactivation of D2 receptors by azidoclebopride with the following order of potency: spiperone greater than (+)-butaclamol greater than haloperidol greater than clebopride greater than (-)-sulpiride greater than (-)-butaclamol

Noisy Spiking in Visual Area V2 of Amblyopic Monkeys.

Science.gov (United States)

Wang, Ye; Zhang, Bin; Tao, Xiaofeng; Wensveen, Janice M; Smith, Earl L; Chino, Yuzo M

2017-01-25

Interocular decorrelation of input signals in developing visual cortex can cause impaired binocular vision and amblyopia. Although increased intrinsic noise is thought to be responsible for a range of perceptual deficits in amblyopic humans, the neural basis for the elevated perceptual noise in amblyopic primates is not known. Here, we tested the idea that perceptual noise is linked to the neuronal spiking noise (variability) resulting from developmental alterations in cortical circuitry. To assess spiking noise, we analyzed the contrast-dependent dynamics of spike counts and spiking irregularity by calculating the square of the coefficient of variation in interspike intervals (CV 2 ) and the trial-to-trial fluctuations in spiking, or mean matched Fano factor (m-FF) in visual area V2 of monkeys reared with chronic monocular defocus. In amblyopic neurons, the contrast versus response functions and the spike count dynamics exhibited significant deviations from comparable data for normal monkeys. The CV 2 was pronounced in amblyopic neurons for high-contrast stimuli and the m-FF was abnormally high in amblyopic neurons for low-contrast gratings. The spike count, CV 2 , and m-FF of spontaneous activity were also elevated in amblyopic neurons. These contrast-dependent spiking irregularities were correlated with the level of binocular suppression in these V2 neurons and with the severity of perceptual loss for individual monkeys. Our results suggest that the developmental alterations in normalization mechanisms resulting from early binocular suppression can explain much of these contrast-dependent spiking abnormalities in V2 neurons and the perceptual performance of our amblyopic monkeys. Amblyopia is a common developmental vision disorder in humans. Despite the extensive animal studies on how amblyopia emerges, we know surprisingly little about the neural basis of amblyopia in humans and nonhuman primates. Although the vision of amblyopic humans is often described as

A stochastic-field description of finite-size spiking neural networks.

Science.gov (United States)

Dumont, Grégory; Payeur, Alexandre; Longtin, André

2017-08-01

Neural network dynamics are governed by the interaction of spiking neurons. Stochastic aspects of single-neuron dynamics propagate up to the network level and shape the dynamical and informational properties of the population. Mean-field models of population activity disregard the finite-size stochastic fluctuations of network dynamics and thus offer a deterministic description of the system. Here, we derive a stochastic partial differential equation (SPDE) describing the temporal evolution of the finite-size refractory density, which represents the proportion of neurons in a given refractory state at any given time. The population activity-the density of active neurons per unit time-is easily extracted from this refractory density. The SPDE includes finite-size effects through a two-dimensional Gaussian white noise that acts both in time and along the refractory dimension. For an infinite number of neurons the standard mean-field theory is recovered. A discretization of the SPDE along its characteristic curves allows direct simulations of the activity of large but finite spiking networks; this constitutes the main advantage of our approach. Linearizing the SPDE with respect to the deterministic asynchronous state allows the theoretical investigation of finite-size activity fluctuations. In particular, analytical expressions for the power spectrum and autocorrelation of activity fluctuations are obtained. Moreover, our approach can be adapted to incorporate multiple interacting populations and quasi-renewal single-neuron dynamics.

The dopamine theory of addiction: 40 years of highs and lows.

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Nutt, David J; Lingford-Hughes, Anne; Erritzoe, David; Stokes, Paul R A

2015-05-01

For several decades, addiction has come to be viewed as a disorder of the dopamine neurotransmitter system; however, this view has not led to new treatments. In this Opinion article, we review the origins of the dopamine theory of addiction and discuss the ability of addictive drugs to elicit the release of dopamine in the human striatum. There is robust evidence that stimulants increase striatal dopamine levels and some evidence that alcohol may have such an effect, but little evidence, if any, that cannabis and opiates increase dopamine levels. Moreover, there is good evidence that striatal dopamine receptor availability and dopamine release are diminished in individuals with stimulant or alcohol dependence but not in individuals with opiate, nicotine or cannabis dependence. These observations have implications for understanding reward and treatment responses in various addictions.

Structural and Functional Effect of an Oscillating Electric Field on the Dopamine-D3 Receptor: A Molecular Dynamics Simulation Study.

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Zohreh Fallah

Full Text Available Dopamine as a neurotransmitter plays a critical role in the functioning of the central nervous system. The structure of D3 receptor as a member of class A G-protein coupled receptors (GPCRs has been reported. We used MD simulation to investigate the effect of an oscillating electric field, with frequencies in the range 0.6-800 GHz applied along the z-direction, on the dopamine-D3R complex. The simulations showed that at some frequencies, the application of an external oscillating electric field along the z-direction has a considerable effect on the dopamine-D3R. However, there is no enough evidence for prediction of changes in specific frequency, implying that there is no order in changes. Computing the correlation coefficient parameter showed that increasing the field frequency can weaken the interaction between dopamine and D3R and may decrease the Arg128{3.50}-Glu324{6.30} distance. Because of high stability of α helices along the z-direction, applying an oscillating electric field in this direction with an amplitude 10-time higher did not have a considerable effect. However, applying the oscillating field at the frequency of 0.6 GHz along other directions, such as X-Y and Y-Z planes, could change the energy between the dopamine and the D3R, and the number of internal hydrogen bonds of the protein. This can be due to the effect of the direction of the electric field vis-à-vis the ligands orientation and the interaction of the oscillating electric field with the dipole moment of the protein.

Functional Connectome Analysis of Dopamine Neuron Glutamatergic Connections in Forebrain Regions.

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Mingote, Susana; Chuhma, Nao; Kusnoor, Sheila V; Field, Bianca; Deutch, Ariel Y; Rayport, Stephen

2015-12-09

In the ventral tegmental area (VTA), a subpopulation of dopamine neurons express vesicular glutamate transporter 2 and make glutamatergic connections to nucleus accumbens (NAc) and olfactory tubercle (OT) neurons. However, their glutamatergic connections across the forebrain have not been explored systematically. To visualize dopamine neuron forebrain projections and to enable photostimulation of their axons independent of transmitter status, we virally transfected VTA neurons with channelrhodopsin-2 fused to enhanced yellow fluorescent protein (ChR2-EYFP) and used DAT(IREScre) mice to restrict expression to dopamine neurons. ChR2-EYFP-expressing neurons almost invariably stained for tyrosine hydroxylase, identifying them as dopaminergic. Dopamine neuron axons visualized by ChR2-EYFP fluorescence projected most densely to the striatum, moderately to the amygdala and entorhinal cortex (ERC), sparsely to prefrontal and cingulate cortices, and rarely to the hippocampus. Guided by ChR2-EYFP fluorescence, we recorded systematically from putative principal neurons in target areas and determined the incidence and strength of glutamatergic connections by activating all dopamine neuron terminals impinging on recorded neurons with wide-field photostimulation. This revealed strong glutamatergic connections in the NAc, OT, and ERC; moderate strength connections in the central amygdala; and weak connections in the cingulate cortex. No glutamatergic connections were found in the dorsal striatum, hippocampus, basolateral amygdala, or prefrontal cortex. These results indicate that VTA dopamine neurons elicit widespread, but regionally distinct, glutamatergic signals in the forebrain and begin to define the dopamine neuron excitatory functional connectome. Dopamine neurons are important for the control of motivated behavior and are involved in the pathophysiology of several major neuropsychiatric disorders. Recent studies have shown that some ventral midbrain dopamine neurons are

Synchronous spikes are necessary but not sufficient for a synchrony code in populations of spiking neurons.

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Grewe, Jan; Kruscha, Alexandra; Lindner, Benjamin; Benda, Jan

2017-03-07

Synchronous activity in populations of neurons potentially encodes special stimulus features. Selective readout of either synchronous or asynchronous activity allows formation of two streams of information processing. Theoretical work predicts that such a synchrony code is a fundamental feature of populations of spiking neurons if they operate in specific noise and stimulus regimes. Here we experimentally test the theoretical predictions by quantifying and comparing neuronal response properties in tuberous and ampullary electroreceptor afferents of the weakly electric fish Apteronotus leptorhynchus These related systems show similar levels of synchronous activity, but only in the more irregularly firing tuberous afferents a synchrony code is established, whereas in the more regularly firing ampullary afferents it is not. The mere existence of synchronous activity is thus not sufficient for a synchrony code. Single-cell features such as the irregularity of spiking and the frequency dependence of the neuron's transfer function determine whether synchronous spikes possess a distinct meaning for the encoding of time-dependent signals.

Voltage spikes in Nb3Sn and NbTi strands

International Nuclear Information System (INIS)

Bordini, B.; Ambrosio, G.; Barzi, E.; Carcagno, R.; Feher, S.; Kashikhin, V.V.; Lamm, M.J.; Orris, D.; Tartaglia, M.; Tompkins, J.C.; Turrioni, D.; Yamada, R.; Zlobin, A.V.; Fermilab

2005-01-01

As part of the High Field Magnet program at Fermilab several NbTi and Nb 3 Sn strands were tested with particular emphasis on the study of voltage spikes and their relationship to superconductor instabilities. The voltage spikes were detected under various experimental conditions using voltage-current (V-I) and voltage-field (V-H) methods. Two types of spikes, designated ''magnetization'' and ''transport current'' spikes, have been identified. Their origin is most likely related to magnetization flux jump and transport current redistribution, respectively. Many of the signals observed appear to be a combination of these two types of spikes; the combination of these two instability mechanisms should play a dominant role in determining the minimum quench current

A supervised learning rule for classification of spatiotemporal spike patterns.

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Lilin Guo; Zhenzhong Wang; Adjouadi, Malek

2016-08-01

This study introduces a novel supervised algorithm for spiking neurons that take into consideration synapse delays and axonal delays associated with weights. It can be utilized for both classification and association and uses several biologically influenced properties, such as axonal and synaptic delays. This algorithm also takes into consideration spike-timing-dependent plasticity as in Remote Supervised Method (ReSuMe). This paper focuses on the classification aspect alone. Spiked neurons trained according to this proposed learning rule are capable of classifying different categories by the associated sequences of precisely timed spikes. Simulation results have shown that the proposed learning method greatly improves classification accuracy when compared to the Spike Pattern Association Neuron (SPAN) and the Tempotron learning rule.

Intranasal dopamine reduces in vivo [123I]FP-CIT binding to striatal dopamine transporter: correlation with behavioral changes and evidence for Pavlovian conditioned dopamine response

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Maria A de Souza Silva

2016-04-01

Full Text Available Purpose: Dopamine (DA, which does not cross the blood-brain barrier, has central and behavioral effects when administered via the nasal route. Neither the mechanisms of central action of intranasal dopamine (IN-DA, nor its mechanisms of diffusion and transport into the brain are well understood. We here examined whether IN-DA application influences dopamine transporter (DAT binding in the dorsal striatum and assessed the extent of binding in relation to motor and exploratory behaviors. We hypothesized that, based on the finding of increased extracellular DA in the striatum induced by application of IN-DA, binding of [123I]FP-CIT to the DAT should be decreased due to competition at the receptor.Methods: Rats were administered intranasal application of 3 mg/kg IN-DA and vehicle (VEH, with IN-DA injection either preceding or following VEH. Then motor and exploratory behaviors (traveled distance, velocity, center time, sitting, rearing, head-shoulder motility, grooming were assessed for 30 min in an open field prior to administration of [123I]FP-CIT. DAT binding after IN-DA and VEH was measured with small animal SPECT two hours following administration of the radioligand. Results: 1 After IN-DA application, striatal DAT binding was significantly lower as compared to VEH, indicating that the nasally delivered dopamine had central action and increased DA levels comparable to that found previously with L-DOPA administration. 2 DAT binding in response to intranasal VEH was lower when IN-DA application preceded VEH treatment. This finding is suggestive of Pavlovian conditioning of DA at the level of the DAT, since the DA treatment modified (decreased the binding in response to the subsequent VEH treatment. VEH treatment also reduced motor and exploratory behaviors more when applied before, as compared to when it followed IN-DA application, also indicative of behavioral Pavlovian conditioning akin to that found upon application of various psychostimulant

A Visual Guide to Sorting Electrophysiological Recordings Using 'SpikeSorter'.

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Swindale, Nicholas V; Mitelut, Catalin; Murphy, Timothy H; Spacek, Martin A

2017-02-10

Few stand-alone software applications are available for sorting spikes from recordings made with multi-electrode arrays. Ideally, an application should be user friendly with a graphical user interface, able to read data files in a variety of formats, and provide users with a flexible set of tools giving them the ability to detect and sort extracellular voltage waveforms from different units with some degree of reliability. Previously published spike sorting methods are now available in a software program, SpikeSorter, intended to provide electrophysiologists with a complete set of tools for sorting, starting from raw recorded data file and ending with the export of sorted spikes times. Procedures are automated to the extent this is currently possible. The article explains and illustrates the use of the program. A representative data file is opened, extracellular traces are filtered, events are detected and then clustered. A number of problems that commonly occur during sorting are illustrated, including the artefactual over-splitting of units due to the tendency of some units to fire spikes in pairs where the second spike is significantly smaller than the first, and over-splitting caused by slow variation in spike height over time encountered in some units. The accuracy of SpikeSorter's performance has been tested with surrogate ground truth data and found to be comparable to that of other algorithms in current development.

A Markovian event-based framework for stochastic spiking neural networks.

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Touboul, Jonathan D; Faugeras, Olivier D

2011-11-01

In spiking neural networks, the information is conveyed by the spike times, that depend on the intrinsic dynamics of each neuron, the input they receive and on the connections between neurons. In this article we study the Markovian nature of the sequence of spike times in stochastic neural networks, and in particular the ability to deduce from a spike train the next spike time, and therefore produce a description of the network activity only based on the spike times regardless of the membrane potential process. To study this question in a rigorous manner, we introduce and study an event-based description of networks of noisy integrate-and-fire neurons, i.e. that is based on the computation of the spike times. We show that the firing times of the neurons in the networks constitute a Markov chain, whose transition probability is related to the probability distribution of the interspike interval of the neurons in the network. In the cases where the Markovian model can be developed, the transition probability is explicitly derived in such classical cases of neural networks as the linear integrate-and-fire neuron models with excitatory and inhibitory interactions, for different types of synapses, possibly featuring noisy synaptic integration, transmission delays and absolute and relative refractory period. This covers most of the cases that have been investigated in the event-based description of spiking deterministic neural networks.

Fast convergence of spike sequences to periodic patterns in recurrent networks

International Nuclear Information System (INIS)

Jin, Dezhe Z.

2002-01-01

The dynamical attractors are thought to underlie many biological functions of recurrent neural networks. Here we show that stable periodic spike sequences with precise timings are the attractors of the spiking dynamics of recurrent neural networks with global inhibition. Almost all spike sequences converge within a finite number of transient spikes to these attractors. The convergence is fast, especially when the global inhibition is strong. These results support the possibility that precise spatiotemporal sequences of spikes are useful for information encoding and processing in biological neural networks

The role of dopamine receptors in the neurotoxicity of methamphetamine.

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Ares-Santos, S; Granado, N; Moratalla, R

2013-05-01

Methamphetamine is a synthetic drug consumed by millions of users despite its neurotoxic effects in the brain, leading to loss of dopaminergic fibres and cell bodies. Moreover, clinical reports suggest that methamphetamine abusers are predisposed to Parkinson's disease. Therefore, it is important to elucidate the mechanisms involved in methamphetamine-induced neurotoxicity. Dopamine receptors may be a plausible target to prevent this neurotoxicity. Genetic inactivation of dopamine D1 or D2 receptors protects against the loss of dopaminergic fibres in the striatum and loss of dopaminergic neurons in the substantia nigra. Protection by D1 receptor inactivation is due to blockade of hypothermia, reduced dopamine content and turnover and increased stored vesicular dopamine in D1R(-/-) mice. However, the neuroprotective impact of D2 receptor inactivation is partially dependent on an effect on body temperature, as well as on the blockade of dopamine reuptake by decreased dopamine transporter activity, which results in reduced intracytosolic dopamine levels in D2R(-/-) mice. © 2013 The Association for the Publication of the Journal of Internal Medicine.

Learning Touch Preferences with a Tactile Robot Using Dopamine Modulated STDP in a Model of Insular Cortex

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Ting-Shuo eChou

2015-07-01

Full Text Available 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, the plasticity (i.e., STDP in primary somatosensory cortex and insular cortex 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.

Functional characterization of dopamine transporter in vivo using Drosophila melanogaster behavioral analysis.

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Taro eUeno

2014-09-01

Full Text Available Dopamine mediates diverse functions such as motivation, reward, attention, learning/memory and sleep/arousal. Recent studies using model organisms including the fruit fly, have elucidated various physiological functions of dopamine, and identified specific neural circuits for these functions. Flies with mutations in the Drosophila dopamine transporter (dDAT gene show enhanced dopamine signaling, and short sleep and memory impairment phenotypes. However, understanding the mechanism by which dopamine signaling causes these phenotypes requires an understanding of the dynamics of dopamine release. Here we report the effects of dDAT expression on behavioral traits. We show that dDAT expression in a subset of dopaminergic neurons is sufficient for normal sleep. dDAT expression in other cell types such as Kenyon cells and glial cells can also rescue the short sleep phenotype of dDAT mutants. dDAT mutants also show a down-regulation of the D1-like dopamine receptor dDA1, and this phenotype is rescued when dDAT is expressed in the same cell types in which it rescues sleep. On the other hand, dDAT overexpression in mushroom bodies, which are the target of memory forming dopamine neurons, abolishes olfactory aversive memory. Our data demonstrate that expression of extrasynaptic dopamine transporters can rescue some aspects of dopamine signaling in dopamine transporter mutants. These results provide novel insights into regulatory systems that modulate dopamine signaling.

Noise-enhanced coding in phasic neuron spike trains.

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Ly, Cheng; Doiron, Brent

2017-01-01

The stochastic nature of neuronal response has lead to conjectures about the impact of input fluctuations on the neural coding. For the most part, low pass membrane integration and spike threshold dynamics have been the primary features assumed in the transfer from synaptic input to output spiking. Phasic neurons are a common, but understudied, neuron class that are characterized by a subthreshold negative feedback that suppresses spike train responses to low frequency signals. Past work has shown that when a low frequency signal is accompanied by moderate intensity broadband noise, phasic neurons spike trains are well locked to the signal. We extend these results with a simple, reduced model of phasic activity that demonstrates that a non-Markovian spike train structure caused by the negative feedback produces a noise-enhanced coding. Further, this enhancement is sensitive to the timescales, as opposed to the intensity, of a driving signal. Reduced hazard function models show that noise-enhanced phasic codes are both novel and separate from classical stochastic resonance reported in non-phasic neurons. The general features of our theory suggest that noise-enhanced codes in excitable systems with subthreshold negative feedback are a particularly rich framework to study.

Financial time series prediction using spiking neural networks.

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Reid, David; Hussain, Abir Jaafar; Tawfik, Hissam

2014-01-01

In this paper a novel application of a particular type of spiking neural network, a Polychronous Spiking Network, was used for financial time series prediction. It is argued that the inherent temporal capabilities of this type of network are suited to non-stationary data such as this. The performance of the spiking neural network was benchmarked against three systems: two "traditional", rate-encoded, neural networks; a Multi-Layer Perceptron neural network and a Dynamic Ridge Polynomial neural network, and a standard Linear Predictor Coefficients model. For this comparison three non-stationary and noisy time series were used: IBM stock data; US/Euro exchange rate data, and the price of Brent crude oil. The experiments demonstrated favourable prediction results for the Spiking Neural Network in terms of Annualised Return and prediction error for 5-Step ahead predictions. These results were also supported by other relevant metrics such as Maximum Drawdown and Signal-To-Noise ratio. This work demonstrated the applicability of the Polychronous Spiking Network to financial data forecasting and this in turn indicates the potential of using such networks over traditional systems in difficult to manage non-stationary environments.

Dopamine synthesis and dopamine receptor expression are disturbed in recurrent miscarriages.

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Gratz, Michael J; Stavrou, Stavroula; Kuhn, Christina; Hofmann, Simone; Hermelink, Kerstin; Heidegger, Helene; Hutter, Stefan; Mayr, Doris; Mahner, Sven; Jeschke, Udo; Vattai, Aurelia

2018-05-01

l-dopa decarboxylase (DDC) is responsible for the synthesis of dopamine. Dopamine, which binds to the D 2 -dopamine receptor (D2R), plays an important role in the maintenance of pregnancy. Aim of our study was the analysis of DDC and D2R expression in placentas of spontaneous miscarriages (SMs) and recurrent miscarriages (RMs) in comparison to healthy controls. Patients with SM (n = 15) and RM (n = 15) were compared with patients from healthy pregnancies (n = 15) (pregnancy weeks 7-13 each). Placental tissue has been collected from SMs and RMs from the first trimester (Department of Gynaecology and Obstetrics, LMU Munich) and from abruptions (private practice, Munich). Placental cell lines, BeWo- and JEG-3 cells, were stimulated with the trace amines T 0 AM and T 1 AM in vitro . Levels of DDC and D2R in trophoblasts and the decidua were lower in RMs in comparison to healthy controls. Stimulation of BeWo cells with T 1 AM significantly reduced DDC mRNA and protein levels. Via double-immunofluorescence, a DDC-positive cell type beneath decidual stromal cells and foetal EVT in the decidua could be detected. Downregulation of DDC and D2R in trophoblasts of RMs reflects a reduced signal cascade of catecholamines on the foetal side. © 2018 The authors.

Genes with a spike expression are clustered in chromosome (sub)bands and spike (sub)bands have a powerful prognostic value in patients with multiple myeloma

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Kassambara, Alboukadel; Hose, Dirk; Moreaux, Jérôme; Walker, Brian A.; Protopopov, Alexei; Reme, Thierry; Pellestor, Franck; Pantesco, Véronique; Jauch, Anna; Morgan, Gareth; Goldschmidt, Hartmut; Klein, Bernard

2012-01-01

Background Genetic abnormalities are common in patients with multiple myeloma, and may deregulate gene products involved in tumor survival, proliferation, metabolism and drug resistance. In particular, translocations may result in a high expression of targeted genes (termed spike expression) in tumor cells. We identified spike genes in multiple myeloma cells of patients with newly-diagnosed myeloma and investigated their prognostic value. Design and Methods Genes with a spike expression in multiple myeloma cells were picked up using box plot probe set signal distribution and two selection filters. Results In a cohort of 206 newly diagnosed patients with multiple myeloma, 2587 genes/expressed sequence tags with a spike expression were identified. Some spike genes were associated with some transcription factors such as MAF or MMSET and with known recurrent translocations as expected. Spike genes were not associated with increased DNA copy number and for a majority of them, involved unknown mechanisms. Of spiked genes, 36.7% clustered significantly in 149 out of 862 documented chromosome (sub)bands, of which 53 had prognostic value (35 bad, 18 good). Their prognostic value was summarized with a spike band score that delineated 23.8% of patients with a poor median overall survival (27.4 months versus not reached, Pband score was independent of other gene expression profiling-based risk scores, t(4;14), or del17p in an independent validation cohort of 345 patients. Conclusions We present a new approach to identify spike genes and their relationship to patients’ survival. PMID:22102711

Predictive coding of dynamical variables in balanced spiking networks.

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Boerlin, Martin; Machens, Christian K; Denève, Sophie

2013-01-01

Two observations about the cortex have puzzled neuroscientists for a long time. First, neural responses are highly variable. Second, the level of excitation and inhibition received by each neuron is tightly balanced at all times. Here, we demonstrate that both properties are necessary consequences of neural networks that represent information efficiently in their spikes. We illustrate this insight with spiking networks that represent dynamical variables. Our approach is based on two assumptions: We assume that information about dynamical variables can be read out linearly from neural spike trains, and we assume that neurons only fire a spike if that improves the representation of the dynamical variables. Based on these assumptions, we derive a network of leaky integrate-and-fire neurons that is able to implement arbitrary linear dynamical systems. We show that the membrane voltage of the neurons is equivalent to a prediction error about a common population-level signal. Among other things, our approach allows us to construct an integrator network of spiking neurons that is robust against many perturbations. Most importantly, neural variability in our networks cannot be equated to noise. Despite exhibiting the same single unit properties as widely used population code models (e.g. tuning curves, Poisson distributed spike trains), balanced networks are orders of magnitudes more reliable. Our approach suggests that spikes do matter when considering how the brain computes, and that the reliability of cortical representations could have been strongly underestimated.

A method for decoding the neurophysiological spike-response transform.

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Stern, Estee; García-Crescioni, Keyla; Miller, Mark W; Peskin, Charles S; Brezina, Vladimir

2009-11-15

Many physiological responses elicited by neuronal spikes-intracellular calcium transients, synaptic potentials, muscle contractions-are built up of discrete, elementary responses to each spike. However, the spikes occur in trains of arbitrary temporal complexity, and each elementary response not only sums with previous ones, but can itself be modified by the previous history of the activity. A basic goal in system identification is to characterize the spike-response transform in terms of a small number of functions-the elementary response kernel and additional kernels or functions that describe the dependence on previous history-that will predict the response to any arbitrary spike train. Here we do this by developing further and generalizing the "synaptic decoding" approach of Sen et al. (1996). Given the spike times in a train and the observed overall response, we use least-squares minimization to construct the best estimated response and at the same time best estimates of the elementary response kernel and the other functions that characterize the spike-response transform. We avoid the need for any specific initial assumptions about these functions by using techniques of mathematical analysis and linear algebra that allow us to solve simultaneously for all of the numerical function values treated as independent parameters. The functions are such that they may be interpreted mechanistically. We examine the performance of the method as applied to synthetic data. We then use the method to decode real synaptic and muscle contraction transforms.

Antibodies to dopamine: radioimmunological study of specificity in relation to immunocytochemistry

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Geffard, M.; Kah, O.; Onteniente, B.; Seguela, P.; Le Moal, M.; Delaage, M.

1984-06-01

Two classes of anti-3,4- dihydroxyphenylethylamine (dopamine) antibodies were raised in rabbits using dopamine conjugated to albumin either via formaldehyde or via glutaraldehyde. Each was usable for immunohistochemical detection of dopamine neurons provided that the tissue was fixed by the homologous cross-linking agent. However, anti-dopamine-glutaraldehyde antibodies turned out to be of more general use because of the better fixative properties of glutaraldehyde which fixed dopamine in rat and in teleost, whereas formaldehyde only worked in lower vertebrates (such as goldfish) and not in rat brain. The specificity of anti-dopamine-glutaraldehyde antibodies was firmly established by competition experiments in equilibrium dialysis, using an immunoreactive tritiated derivative synthesized by coupling dopamine to N-alpha-acetyl-L-lysine N-methylamide via glutaraldehyde. Specificity studies in vitro and immunohistological results demonstrating the specific staining of dopaminergic neurons were found to correlate well.

Small heat-shock proteins and leaf cooling capacity account for the unusual heat tolerance of the central spike leaves in Agave tequilana var. Weber.

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Luján, Rosario; Lledías, Fernando; Martínez, Luz María; Barreto, Rita; Cassab, Gladys I; Nieto-Sotelo, Jorge

2009-12-01

Agaves are perennial crassulacean acid metabolism (CAM) plants distributed in tropical and subtropical arid environments, features that are attractive for studying the heat-shock response. In agaves, the stress response can be analysed easily during leaf development, as they form a spirally shaped rosette, having the meristem surrounded by folded leaves in the centre (spike) and the unfolded and more mature leaves in the periphery. Here, we report that the spike of Agave tequilana is the most thermotolerant part of the rosette withstanding shocks of up to 55 degrees C. This finding was inconsistent with the patterns of heat-shock protein (Hsp) gene expression, as maximal accumulation of Hsp transcripts was at 44 degrees C in all sectors (spike, inner, middle and outer). However, levels of small HSP (sHSP)-CI and sHSP-CII proteins were conspicuously higher in spike leaves at all temperatures correlating with their thermotolerance. In addition, spike leaves showed a higher stomatal density and abated more efficiently their temperature several degrees below that of air. We propose that the greater capacity for leaf cooling during the day in response to heat stress, and the elevated levels of sHSPs, constitute part of a set of strategies that protect the SAM and folded leaves of A. tequilana from high temperatures.

A spiking neuron circuit based on a carbon nanotube transistor

International Nuclear Information System (INIS)

Chen, C-L; Kim, K; Truong, Q; Shen, A; Li, Z; Chen, Y

2012-01-01

A spiking neuron circuit based on a carbon nanotube (CNT) transistor is presented in this paper. The spiking neuron circuit has a crossbar architecture in which the transistor gates are connected to its row electrodes and the transistor sources are connected to its column electrodes. An electrochemical cell is incorporated in the gate of the transistor by sandwiching a hydrogen-doped poly(ethylene glycol)methyl ether (PEG) electrolyte between the CNT channel and the top gate electrode. An input spike applied to the gate triggers a dynamic drift of the hydrogen ions in the PEG electrolyte, resulting in a post-synaptic current (PSC) through the CNT channel. Spikes input into the rows trigger PSCs through multiple CNT transistors, and PSCs cumulate in the columns and integrate into a ‘soma’ circuit to trigger output spikes based on an integrate-and-fire mechanism. The spiking neuron circuit can potentially emulate biological neuron networks and their intelligent functions. (paper)

An online supervised learning method based on gradient descent for spiking neurons.

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Xu, Yan; Yang, Jing; Zhong, Shuiming

2017-09-01

The purpose of supervised learning with temporal encoding for spiking neurons is to make the neurons emit a specific spike train encoded by precise firing times of spikes. The gradient-descent-based (GDB) learning methods are widely used and verified in the current research. Although the existing GDB multi-spike learning (or spike sequence learning) methods have good performance, they work in an offline manner and still have some limitations. This paper proposes an online GDB spike sequence learning method for spiking neurons that is based on the online adjustment mechanism of real biological neuron synapses. The method constructs error function and calculates the adjustment of synaptic weights as soon as the neurons emit a spike during their running process. We analyze and synthesize desired and actual output spikes to select appropriate input spikes in the calculation of weight adjustment in this paper. The experimental results show that our method obviously improves learning performance compared with the offline learning manner and has certain advantage on learning accuracy compared with other learning methods. Stronger learning ability determines that the method has large pattern storage capacity. Copyright © 2017 Elsevier Ltd. All rights reserved.

Cutaneous synergistic analgesia of bupivacaine in combination with dopamine in rats.

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Tzeng, Jann-Inn; Wang, Jieh-Neng; Wang, Jhi-Joung; Chen, Yu-Wen; Hung, Ching-Hsia

2016-05-04

The main goal of the study was to investigate the interaction between bupivacaine and dopamine on local analgesia. After the blockade of the cutaneous trunci muscle reflex (CTMR) responses, which occurred following the drugs were subcutaneously injected in rats, the cutaneous analgesic effect of dopamine in a dosage-dependent fashion was compared to that of bupivacaine. Drug-drug interactions were evaluated by isobolographic methods. We showed the dose-dependent effects of dopamine on infiltrative cutaneous analgesia. On the 50% effective dose (ED50) basis, the rank of drug potency was bupivacaine (1.99 [1.92-2.09] μmol/kg) greater than dopamine (190 [181-203] μmol/kg) (Pbupivacaine. The addition of dopamine to the bupivacaine solution exhibited a synergistic effect. Our pre-clinical data showed that dopamine produced a dose-dependent effect in producing cutaneous analgesia. When compared with bupivacaine, dopamine produced a lesser potency with a similar duration of cutaneous analgesia. Dopamine added to the bupivacaine preparation resulted in a synergistic analgesic effect. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Bistability induces episodic spike communication by inhibitory neurons in neuronal networks.

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Kazantsev, V B; Asatryan, S Yu

2011-09-01

Bistability is one of the important features of nonlinear dynamical systems. In neurodynamics, bistability has been found in basic Hodgkin-Huxley equations describing the cell membrane dynamics. When the neuron is clamped near its threshold, the stable rest potential may coexist with the stable limit cycle describing periodic spiking. However, this effect is often neglected in network computations where the neurons are typically reduced to threshold firing units (e.g., integrate-and-fire models). We found that the bistability may induce spike communication by inhibitory coupled neurons in the spiking network. The communication is realized in the form of episodic discharges with synchronous (correlated) spikes during the episodes. A spiking phase map is constructed to describe the synchronization and to estimate basic spike phase locking modes.

Voltage spikes in Nb3Sn and NbTi strands

Energy Technology Data Exchange (ETDEWEB)

Bordini, B.; Ambrosio, G.; Barzi, E.; Carcagno, R.; Feher, S.; Kashikhin, V.V.; Lamm, M.J.; Orris, D.; Tartaglia, M.; Tompkins, J.C.; Turrioni, D.; Yamada, R.; Zlobin,; /Fermilab

2005-09-01

As part of the High Field Magnet program at Fermilab several NbTi and Nb{sub 3}Sn strands were tested with particular emphasis on the study of voltage spikes and their relationship to superconductor instabilities. The voltage spikes were detected under various experimental conditions using voltage-current (V-I) and voltage-field (V-H) methods. Two types of spikes, designated ''magnetization'' and ''transport current'' spikes, have been identified. Their origin is most likely related to magnetization flux jump and transport current redistribution, respectively. Many of the signals observed appear to be a combination of these two types of spikes; the combination of these two instability mechanisms should play a dominant role in determining the minimum quench current.

Pressurized water reactor iodine spiking behavior under power transient conditions

International Nuclear Information System (INIS)

Ho, J.C.

1992-01-01

The most accepted theory explaining the cause of pressurized water reactor iodine spiking is steam formation and condensation in damaged fuel rods. The phase transformation of the primary coolant from water to steam and back again is believed to cause the iodine spiking phenomenon. But due to the complex nature of the phenomenon, a comprehensive model of the behavior has not yet been successfully developed. This paper presents a new model based on an empirical approach, which gives a first-order estimation of the peak iodine spiking magnitude. Based on the proposed iodine spiking model, it is apparent that it is feasible to derive a correlation using the plant operating data base to monitor and control the peak iodine spiking magnitude

Dopamine synthesis in alcohol drinking-prone and -resistant mouse strains

Science.gov (United States)

Siciliano, Cody A.; Locke, Jason L.; Mathews, Tiffany A.; Lopez, Marcelo F.; Becker, Howard C.; Jones, Sara R.

2017-01-01

Alcoholism is a prevalent and debilitating neuropsychiatric disease, and much effort has been aimed at elucidating the neurobiological mechanisms underlying maladaptive alcohol drinking in an effort to design rational treatment strategies. In preclinical literature, the use of inbred mouse lines has allowed for the examination of ethanol effects across vulnerable and resistant phenotypes. C57BL/6J mice consistently show higher rates of ethanol drinking compared to most mouse strains. Conversely, DBA/2J mice display low rates of ethanol consumption. Given that the reinforcing and rewarding effects of ethanol are thought to be in part mediated by its actions on dopamine neurotransmission, we hypothesized that alcohol-preferring C57BL/6J and alcohol-avoiding DBA/2J mice would display basal differences in dopamine system function. By administering an L-aromatic acid decarboxylase inhibitor and measuring L-Dopa accumulation via high-performance liquid chromatography as a measure of tyrosine hydroxylase activity, we found no difference in dopamine synthesis between mouse strains in the midbrain, dorsal striatum, or ventral striatum. However, we did find that quinpirole-induced inhibition of dopamine synthesis was greater in the ventral striatum of C57BL/6J mice, suggesting increased presynaptic D2-type dopamine autoreceptor sensitivity. To determine whether dopamine synthesis or autoreceptor sensitivity was altered by a history of ethanol, we exposed C57BL/6J mice to one or two weekly cycles of chronic intermittent ethanol (CIE) exposure and withdrawal. We found that there was an attenuation of baseline dopamine synthesis in the ventral striatum after two cycles of CIE. Finally, we examined tissue content of dopamine and dopamine metabolites across recombinant inbred mice bred from a C57BL/6J × DBA/2J cross (BXD). We found that low dopaminergic activity, as indicated by high dopamine/metabolite ratios, was positively correlated with drinking. Together, these findings

A sensitive electrochemical sensor for paracetamole based on a glassy carbon electrode modified with multiwalled carbon nanotubes and dopamine nanospheres functionalized with gold nanoparticles

International Nuclear Information System (INIS)

Liu, Xue; Wang, Ling-Ling; Wang, Ya-Ya; Zhang, Xiao-Yan

2014-01-01

We describe an electrochemical sensor for paracetamole that is based on a glassy carbon electrode modified with multiwalled carbon nanotubes and dopamine nanospheres functionalized with gold nanoparticles. The functionalized nanospheres were prepared by a chemical route and characterized by scanning electron microscopy. The well-dispersed gold nanoparticles were anchored on the dopamine nanosphere via a chemical reduction of the gold precursor. The stepwise fabrication of the modified electrode and its electrochemical response to paracetamole were evaluated using electrochemical impedance spectroscopy and cyclic voltammetry. The modified electrode displayed improved electrocatalytic activity towards paracetamole, a lower oxidation potential (371 mV), and a larger peak current when compared to a bare electrode or other modified electrodes. The kinetic parameters governing the electro-oxidation of paracetamole were studied, and the analytical conditions were optimized. The peak current was linearly related to the concentration of paracetamole in 0.8–400 μM range, and the detection limit was 50 nM (at an SNR of 3). The method was successfully applied to the determination of paracetamole in spiked human urine samples and gave recoveries between 95.3 and 105.2 %. (author)

Contamination spike simulation and measurement in a clean metal vapor laser

International Nuclear Information System (INIS)

Lin, C.E.; Yang, C.Y.

1990-01-01

This paper describes a new method for the generation of contamination-induced voltage spikes in a clean metal vapor laser. The method facilitates the study of the characteristics of this troublesome phenomenon in laser systems. Analysis of these artificially generated dirt spikes shows that the breakdown time of the laser tube is increased when these spike appear. The concept of a Townsend discharge is used to identify the parameter which changes the breakdown time of the discharges. The residual ionization control method is proposed to generate dirt spikes in a clean laser. Experimental results show that a wide range of dirt spike magnitudes can be obtained by using the proposed method. The method provides easy and accurate control of the magnitude of the dirt spike, and the laser tube does not become polluted. Results based on the measurements can be used in actual laser systems to monitor the appearance of dirt spikes and thus avoid the danger of thyratron failure

Dopamine en overmatig alcoholgebruik: genen in interactie met hun omgeving [Dopamine and excessive alcohol consumption: how genes interact with their environment

OpenAIRE

Schellekens, A.F.A.; Scholte, R.H.J.; Engels, R.C.M.E.; Verkes, R.J.

2013-01-01

background Hereditary factors account for approximately 50% of the risk of developing alcohol dependence. Genes that affect the dopamine function in the brain have been extensively studied as candidate genes. aim To present the results of recent Dutch studies on the interaction between genes and their environment in relation to dopamine function and excessive alcohol use. method Two large scale research projects were recently carried out in order to study the relation between dopamine genes a...

Prefrontal dopamine in associative learning and memory.

Science.gov (United States)

Puig, M V; Antzoulatos, E G; Miller, E K

2014-12-12

Learning to associate specific objects or actions with rewards and remembering the associations are everyday tasks crucial for our flexible adaptation to the environment. These higher-order cognitive processes depend on the prefrontal cortex (PFC) and frontostriatal circuits that connect areas in the frontal lobe with the striatum in the basal ganglia. Both structures are densely innervated by dopamine (DA) afferents that originate in the midbrain. Although the activity of DA neurons is thought to be important for learning, the exact role of DA transmission in frontostriatal circuits during learning-related tasks is still unresolved. Moreover, the neural substrates of this modulation are poorly understood. Here, we review our recent work in monkeys utilizing local pharmacology of DA agents in the PFC to investigate the cellular mechanisms of DA modulation of associative learning and memory. We show that blocking both D1 and D2 receptors in the lateral PFC impairs learning of new stimulus-response associations and cognitive flexibility, but not the memory of highly familiar associations. In addition, D2 receptors may also contribute to motivation. The learning deficits correlated with reductions of neural information about the associations in PFC neurons, alterations in global excitability and spike synchronization, and exaggerated alpha and beta neural oscillations. Our findings provide new insights into how DA transmission modulates associative learning and memory processes in frontostriatal systems. Copyright © 2014 IBRO. Published by Elsevier Ltd. All rights reserved.

Dopamine regulation of [3H]acetylcholine release from guinea-pig stomach

International Nuclear Information System (INIS)

Kusunoki, M.; Taniyama, K.; Tanaka, C.

1985-01-01

The involvement of dopamine receptors in cholinergic transmission of guinea-pig stomach was investigated by analyzing the effects of dopamine receptor agonists and antagonists on acetylcholine (ACh) release from this organ. Electrical stimulation (1-20 Hz) of strips of guinea-pig stomach preloaded with [ 3 H] choline induced a [ 3 H]ACh release that was calcium dependent and tetrodotoxin sensitive. Dopamine inhibited this transmural stimulation-induced [ 3 H]ACh release in a concentration-dependent manner (10(-8)-10(-4) M). This effect of dopamine was not altered by 10(-5) M hexamethonium, thereby suggesting that the major dopamine receptors are located on the postganglionic cholinergic neurons. Concentration-response curves for dopamine on [ 3 H]ACh release were inhibited by haloperidol, sulpiride and domperidone but not by prazosin, yohimbine, propranolol and ketanserin. LY 171555, an agonist for the D2 dopamine receptor, but not SKF 38-393, an agonist for the D1 dopamine receptor, to some extent decreased the release of [ 3 H]ACh induced by transmural stimulation. In view of the results, the release of ACh from postganglionic cholinergic neurons is probably required through dopamine receptors antagonized by D2 antagonists but not by adrenergic or serotonin receptor antagonists

Spike and burst coding in thalamocortical relay cells.

Directory of Open Access Journals (Sweden)

Fleur Zeldenrust

2018-02-01

Full Text Available Mammalian thalamocortical relay (TCR neurons switch their firing activity between a tonic spiking and a bursting regime. In a combined experimental and computational study, we investigated the features in the input signal that single spikes and bursts in the output spike train represent and how this code is influenced by the membrane voltage state of the neuron. Identical frozen Gaussian noise current traces were injected into TCR neurons in rat brain slices as well as in a validated three-compartment TCR model cell. The resulting membrane voltage traces and spike trains were analyzed by calculating the coherence and impedance. Reverse correlation techniques gave the Event-Triggered Average (ETA and the Event-Triggered Covariance (ETC. This demonstrated that the feature selectivity started relatively long before the events (up to 300 ms and showed a clear distinction between spikes (selective for fluctuations and bursts (selective for integration. The model cell was fine-tuned to mimic the frozen noise initiated spike and burst responses to within experimental accuracy, especially for the mixed mode regimes. The information content carried by the various types of events in the signal as well as by the whole signal was calculated. Bursts phase-lock to and transfer information at lower frequencies than single spikes. On depolarization the neuron transits smoothly from the predominantly bursting regime to a spiking regime, in which it is more sensitive to high-frequency fluctuations. The model was then used to elucidate properties that could not be assessed experimentally, in particular the role of two important subthreshold voltage-dependent currents: the low threshold activated calcium current (IT and the cyclic nucleotide modulated h current (Ih. The ETAs of those currents and their underlying activation/inactivation states not only explained the state dependence of the firing regime but also the long-lasting concerted dynamic action of the two

Dopamine and extinction: a convergence of theory with fear and reward circuitry.

Science.gov (United States)

Abraham, Antony D; Neve, Kim A; Lattal, K Matthew

2014-02-01

Research on dopamine lies at the intersection of sophisticated theoretical and neurobiological approaches to learning and memory. Dopamine has been shown to be critical for many processes that drive learning and memory, including motivation, prediction error, incentive salience, memory consolidation, and response output. Theories of dopamine's function in these processes have, for the most part, been developed from behavioral approaches that examine learning mechanisms in reward-related tasks. A parallel and growing literature indicates that dopamine is involved in fear conditioning and extinction. These studies are consistent with long-standing ideas about appetitive-aversive interactions in learning theory and they speak to the general nature of cellular and molecular processes that underlie behavior. We review the behavioral and neurobiological literature showing a role for dopamine in fear conditioning and extinction. At a cellular level, we review dopamine signaling and receptor pharmacology, cellular and molecular events that follow dopamine receptor activation, and brain systems in which dopamine functions. At a behavioral level, we describe theories of learning and dopamine function that could describe the fundamental rules underlying how dopamine modulates different aspects of learning and memory processes. Copyright © 2013 Elsevier Inc. All rights reserved.

The role of dopamine in human addiction: from reward to motivated attention.

Science.gov (United States)

Franken, Ingmar H A; Booij, Jan; van den Brink, Wim

2005-12-05

There is general consensus among preclinical researchers that dopamine plays an important role in the development and persistence of addiction. However, the precise role of dopamine in addictive behaviors is far from clear and only a few clinical studies on the role of dopamine in human addiction have been conducted so far. The present paper reviews studies addressing the role of dopamine in humans. There is substantial and consistent evidence that dopamine is involved in the experience of drug reward in humans. Dopamine may also be involved in motivational processes such as drug craving. However, given the inconsistent findings of studies using dopamine receptor (ant)agonists, the role of dopamine in the experience of craving is far from resolved. Recent theories claiming that dopamine signals salience and makes the brain paying attention to biological relevant stimuli may provide an interesting framework for explaining addictive behaviors. There is accumulating evidence that patients with drug and alcohol addiction have an aberrant focus on drug-related stimuli. Although there is some preliminary support for the role of dopamine in these attention processes, more studies have to be carried out in order to test the validity of these theories in human subjects.

Striatal dopamine D2 receptor binding and dopamine release during cue-elicited craving in recently abstinent opiate-dependent males

NARCIS (Netherlands)

Zijlstra, Fleur; Booij, Jan; van den Brink, Wim; Franken, Ingmar H. A.

2008-01-01

Opiate addiction is a chronic disorder characterized by relapse behaviour, often preceded by craving and anhedonia. Chronic craving and anhedonia have been associated with low availability of dopamine D2 receptors (D2Rs) and cue-elicited craving has been linked with endogenous dopamine release. We

Dopamine does double duty in motivating cognitive effort

Science.gov (United States)

Westbrook, Andrew; Braver, Todd S.

2015-01-01

Cognitive control is subjectively costly, suggesting that engagement is modulated in relationship to incentive state. Dopamine appears to play key roles. In particular, dopamine may mediate cognitive effort by two broad classes of functions: 1) modulating the functional parameters of working memory circuits subserving effortful cognition, and 2) mediating value-learning and decision-making about effortful cognitive action. Here we tie together these two lines of research, proposing how dopamine serves “double duty”, translating incentive information into cognitive motivation. PMID:26889810

Stochastic optimal control of single neuron spike trains

DEFF Research Database (Denmark)

Iolov, Alexandre; Ditlevsen, Susanne; Longtin, Andrë

2014-01-01

stimulation of a neuron to achieve a target spike train under the physiological constraint to not damage tissue. Approach. We pose a stochastic optimal control problem to precisely specify the spike times in a leaky integrate-and-fire (LIF) model of a neuron with noise assumed to be of intrinsic or synaptic...... origin. In particular, we allow for the noise to be of arbitrary intensity. The optimal control problem is solved using dynamic programming when the controller has access to the voltage (closed-loop control), and using a maximum principle for the transition density when the controller only has access...... to the spike times (open-loop control). Main results. We have developed a stochastic optimal control algorithm to obtain precise spike times. It is applicable in both the supra-threshold and sub-threshold regimes, under open-loop and closed-loop conditions and with an arbitrary noise intensity; the accuracy...

Anticipating Activity in Social Media Spikes

OpenAIRE

Higham, Desmond J.; Grindrod, Peter; Mantzaris, Alexander V.; Otley, Amanda; Laflin, Peter

2014-01-01

We propose a novel mathematical model for the activity of microbloggers during an external, event-driven spike. The model leads to a testable prediction of who would become most active if a spike were to take place. This type of information is of great interest to commercial organisations, governments and charities, as it identifies key players who can be targeted with information in real time when the network is most receptive. The model takes account of the fact that dynamic interactions ev...

Reward-based hypertension control by a synthetic brain-dopamine interface.

Science.gov (United States)

Rössger, Katrin; Charpin-El Hamri, Ghislaine; Fussenegger, Martin

2013-11-05

Synthetic biology has significantly advanced the design of synthetic trigger-controlled devices that can reprogram mammalian cells to interface with complex metabolic activities. In the brain, the neurotransmitter dopamine coordinates communication with target neurons via a set of dopamine receptors that control behavior associated with reward-driven learning. This dopamine transmission has recently been suggested to increase central sympathetic outflow, resulting in plasma dopamine levels that correlate with corresponding brain activities. By functionally rewiring the human dopamine receptor D1 (DRD1) via the second messenger cyclic adenosine monophosphate (cAMP) to synthetic promoters containing cAMP response element-binding protein 1(CREB1)-specific cAMP-responsive operator modules, we have designed a synthetic dopamine-sensitive transcription controller that reversibly fine-tunes specific target gene expression at physiologically relevant brain-derived plasma dopamine levels. Following implantation of circuit-transgenic human cell lines insulated by semipermeable immunoprotective microcontainers into mice, the designer device interfaced with dopamine-specific brain activities and produced a systemic expression response when the animal's reward system was stimulated by food, sexual arousal, or addictive drugs. Reward-triggered brain activities were able to remotely program peripheral therapeutic implants to produce sufficient amounts of the atrial natriuretic peptide, which reduced the blood pressure of hypertensive mice to the normal physiologic range. Seamless control of therapeutic transgenes by subconscious behavior may provide opportunities for treatment strategies of the future.

Multimodal imaging of spike propagation: a technical case report.

Science.gov (United States)

Tanaka, N; Grant, P E; Suzuki, N; Madsen, J R; Bergin, A M; Hämäläinen, M S; Stufflebeam, S M

2012-06-01

We report an 11-year-old boy with intractable epilepsy, who had cortical dysplasia in the right superior frontal gyrus. Spatiotemporal source analysis of MEG and EEG spikes demonstrated a similar time course of spike propagation from the superior to inferior frontal gyri, as observed on intracranial EEG. The tractography reconstructed from DTI showed a fiber connection between these areas. Our multimodal approach demonstrates spike propagation and a white matter tract guiding the propagation.

Stronger Dopamine D1 Receptor-Mediated Neurotransmission in Dyskinesia.

Science.gov (United States)

Farré, Daniel; Muñoz, Ana; Moreno, Estefanía; Reyes-Resina, Irene; Canet-Pons, Júlia; Dopeso-Reyes, Iria G; Rico, Alberto J; Lluís, Carme; Mallol, Josefa; Navarro, Gemma; Canela, Enric I; Cortés, Antonio; Labandeira-García, José L; Casadó, Vicent; Lanciego, José L; Franco, Rafael

2015-12-01

Radioligand binding assays to rat striatal dopamine D1 receptors showed that brain lateralization of the dopaminergic system were not due to changes in expression but in agonist affinity. D1 receptor-mediated striatal imbalance resulted from a significantly higher agonist affinity in the left striatum. D1 receptors heteromerize with dopamine D3 receptors, which are considered therapeutic targets for dyskinesia in parkinsonian patients. Expression of both D3 and D1-D3 receptor heteromers were increased in samples from 6-hydroxy-dopamine-hemilesioned rats rendered dyskinetic by treatment with 3, 4-dihydroxyphenyl-L-alanine (L-DOPA). Similar findings were obtained using striatal samples from primates. Radioligand binding studies in the presence of a D3 agonist led in dyskinetic, but not in lesioned or L-DOPA-treated rats, to a higher dopamine sensitivity. Upon D3-receptor activation, the affinity of agonists for binding to the right striatal D1 receptor increased. Excess dopamine coming from L-DOPA medication likely activates D3 receptors thus making right and left striatal D1 receptors equally responsive to dopamine. These results show that dyskinesia occurs concurrently with a right/left striatal balance in D1 receptor-mediated neurotransmission.

Demonstration of specific dopamine receptors on human pituitary adenomas

Energy Technology Data Exchange (ETDEWEB)

Koga, Masafumi; Nakao, Haruyoshi; Arao, Masayo; Sato, Bunzo; Noma, Keizo; Morimoto, Yasuhiko; Kishimoto, Susumu; Mori, Shintaro; Uozumi, Toru

1987-01-01

Dopamine receptors on human pituitary adenoma membranes were characterized using (/sup 3/H)spiperone as the radioligand. The specific (/sup 3/H)spiperone binding sites on prolactin (PRL)-secreting adenoma membranes were recognized as a dopamine receptor, based upon the data showing high affinity binding, saturability, specificity, temperature dependence, and reversibility. All of 14 PRL-secreting adenomas had high affinity dopamine receptors, with a dissociation constant (Kd) of 0.85 +- 0.11 nmol/l (mean+-SEM) and a maximal binding capacity (Bmax) of 428 +- 48.6 fmol/mg protein. Among 14 growth hormone (GH)-secreting adenomas examined, 8 (57%) had dopamine receptors with a Kd of 1.90 +- 0.47 nmol/l and a Bmax of 131 +- 36.9 fmol/mg protein. Furthermore, 15 of 24 (58%) nonsecreting pituitary adenomas also had dopamine receptors with a Kd of 1.86 +- 0.37 nmol/l and a Bmax of 162 +- 26.0 fmol/mg protein. These results indicate that some GH-secreting adenomas as well as some nonsecreting pituitary adenomas contain dopamine receptors. But their affinity and number of binding sites are significantly lower (P<0.05) and fewer (P<0.001) respectively, than those in PRL-secreting adenomas.

The Analysis and Suppression of the spike noise in vibrator record

Science.gov (United States)

Jia, H.; Jiang, T.; Xu, X.; Ge, L.; Lin, J.; Yang, Z.

2013-12-01

During the seismic exploration with vibrator, seismic recording systems have often been affected by random spike noise in the background, which leads to strong data distortions as a result of the cross-correlation processing of the vibrator method. Partial or total loss of the desired seismic information is possible if no automatic spike reduction is available in the field prior to correlation of the field record. Generally speaking, original record of vibrator is uncorrelated data, in which the signal is non-wavelet form. In order to obtain the seismic record similar to explosive source, the signal of uncorrelated data needs to use the correlation algorithm to compress into wavelet form. The correlation process results in that the interference of spike in correlated data is not only being suppressed, but also being expanded. So the spike noise suppression of vibrator is indispensable. According to numerical simulation results, the effect of spike in the vibrator record is mainly affected by the amplitude and proportional points in the uncorrelated record. When the spike noise ratio in uncorrelated record reaches 1.5% and the average amplitude exceeds 200, it will make the SNR(signal-to-noise ratio) of the correlated record lower than 0dB, so that it is difficult to separate the signal. While the amplitude and ratio is determined by the intensity of background noise. Therefore, when the noise level is strong, in order to improve SNR of the seismic data, the uncorrelated record of vibrator need to take necessary steps to suppress spike noise. For the sake of reducing the influence of the spike noise, we need to make the detection and suppression of spike noise process for the uncorrelated record. Because vibrator works by inputting sweep signal into the underground long time, ideally, the peak and valley values of each trace have little change. On the basis of the peak and valley values, we can get a reference amplitude value. Then the spike can be detected and

Dopamine Signaling Regulates Fat Content through β-Oxidation in Caenorhabditis elegans

Science.gov (United States)

Barros, Alexandre Guimarães de Almeida; Bridi, Jessika Cristina; de Souza, Bruno Rezende; de Castro Júnior, Célio; de Lima Torres, Karen Cecília; Malard, Leandro; Jorio, Ado; de Miranda, Débora Marques; Ashrafi, Kaveh; Romano-Silva, Marco Aurélio

2014-01-01

The regulation of energy balance involves an intricate interplay between neural mechanisms that respond to internal and external cues of energy demand and food availability. Compelling data have implicated the neurotransmitter dopamine as an important part of body weight regulation. However, the precise mechanisms through which dopamine regulates energy homeostasis remain poorly understood. Here, we investigate mechanisms through which dopamine modulates energy storage. We showed that dopamine signaling regulates fat reservoirs in Caenorhabditis elegans. We found that the fat reducing effects of dopamine were dependent on dopaminergic receptors and a set of fat oxidation enzymes. Our findings reveal an ancient role for dopaminergic regulation of fat and suggest that dopamine signaling elicits this outcome through cascades that ultimately mobilize peripheral fat depots. PMID:24465759

Quantum chemical study of TiO2/dopamine-DNA triads

International Nuclear Information System (INIS)

Vega-Arroyo, Manuel; LeBreton, Pierre R.; Zapol, Peter; Curtiss, Larry A.; Rajh, Tijana

2007-01-01

Photoinduced charge separation in triads of DNA covalently linked to an anatase nanoparticle via a dopamine bridge was studied by ab initio calculations of the oxidation potentials of carboxyl-DNA trimers and the TiO 2 /dopamine complex. Conjugation of dopamine to the TiO 2 surface results in a lower oxidation potential of the complex relative to the surface and in localization of photogenerated holes on dopamine, while photogenerated electrons are excited into the conduction band of TiO 2 . Linking dopamine to the DNA trimers at the 5' end of the oligonucleotide may lead to further hole migration to the DNA. Calculations show that for several different sequences hole migration is favorable in double stranded DNA and unfavorable in single-stranded DNA. This extended charge separation was shown to follow from the redox properties of DNA sequence rather than from the modification of DNA's electron donating properties by the dopamine linker, which explains experimental observations

Neuronal Depolarization Drives Increased Dopamine Synaptic Vesicle Loading via VGLUT.

Science.gov (United States)

Aguilar, Jenny I; Dunn, Matthew; Mingote, Susana; Karam, Caline S; Farino, Zachary J; Sonders, Mark S; Choi, Se Joon; Grygoruk, Anna; Zhang, Yuchao; Cela, Carolina; Choi, Ben Jiwon; Flores, Jorge; Freyberg, Robin J; McCabe, Brian D; Mosharov, Eugene V; Krantz, David E; Javitch, Jonathan A; Sulzer, David; Sames, Dalibor; Rayport, Stephen; Freyberg, Zachary

2017-08-30

The ability of presynaptic dopamine terminals to tune neurotransmitter release to meet the demands of neuronal activity is critical to neurotransmission. Although vesicle content has been assumed to be static, in vitro data increasingly suggest that cell activity modulates vesicle content. Here, we use a coordinated genetic, pharmacological, and imaging approach in Drosophila to study the presynaptic machinery responsible for these vesicular processes in vivo. We show that cell depolarization increases synaptic vesicle dopamine content prior to release via vesicular hyperacidification. This depolarization-induced hyperacidification is mediated by the vesicular glutamate transporter (VGLUT). Remarkably, both depolarization-induced dopamine vesicle hyperacidification and its dependence on VGLUT2 are seen in ventral midbrain dopamine neurons in the mouse. Together, these data suggest that in response to depolarization, dopamine vesicles utilize a cascade of vesicular transporters to dynamically increase the vesicular pH gradient, thereby increasing dopamine vesicle content. Copyright © 2017 Elsevier Inc. All rights reserved.

The dopamine transporter: role in neurotoxicity and human disease

International Nuclear Information System (INIS)

Bannon, Michael J.

2005-01-01

The dopamine transporter (DAT) is a plasma membrane transport protein expressed exclusively within a small subset of CNS neurons. It plays a crucial role in controlling dopamine-mediated neurotransmission and a number of associated behaviors. This review focuses on recent data elucidating the role of the dopamine transporter in neurotoxicity and a number of CNS disorders, including Parkinson disease, drug abuse, and attention deficit hyperactivity disorder (ADHD)

The dopamine transporter: role in neurotoxicity and human disease

Energy Technology Data Exchange (ETDEWEB)

Bannon, Michael J [Department of Psychiatry and Behavioral Neuroscience, Pharmacology, and Molecular Medicine and Genetics, Wayne State University School of Medicine, Detroit, MI 48201 (United States)

2005-05-01

The dopamine transporter (DAT) is a plasma membrane transport protein expressed exclusively within a small subset of CNS neurons. It plays a crucial role in controlling dopamine-mediated neurotransmission and a number of associated behaviors. This review focuses on recent data elucidating the role of the dopamine transporter in neurotoxicity and a number of CNS disorders, including Parkinson disease, drug abuse, and attention deficit hyperactivity disorder (ADHD)

Sub-second changes in accumbal dopamine during sexual behavior in male rats.

Science.gov (United States)

Robinson, D L; Phillips, P E; Budygin, E A; Trafton, B J; Garris, P A; Wightman, R M

2001-08-08

Transient (200--900 ms), high concentrations (200--500 nM) of dopamine, measured using fast-scan cyclic voltammetry, occurred in the nucleus accumbens core of male rats at the presentation of a receptive female. Additional dopamine signals were observed during subsequent approach behavior. Background-subtracted cyclic voltammograms of the naturally-evoked signals matched those of electrically-evoked dopamine measured at the same recording sites. Administration of nomifensine amplified natural and evoked dopamine release, and increased the frequency of detectable signals. While gradual changes in dopamine concentration during sexual behavior have been well established, these findings dramatically improve the time resolution. The observed dopamine transients, probably resulting from neuronal burst firing, represent the first direct correlation of dopamine with sexual behavior on a sub-second time scale.

Tyrosinase-Based Biosensors for Selective Dopamine Detection

Directory of Open Access Journals (Sweden)

Monica Florescu

2017-06-01

Full Text Available A novel tyrosinase-based biosensor was developed for the detection of dopamine (DA. For increased selectivity, gold electrodes were previously modified with cobalt (II-porphyrin (CoP film with electrocatalytic activity, to act both as an electrochemical mediator and an enzyme support, upon which the enzyme tyrosinase (Tyr was cross-linked. Differential pulse voltammetry was used for electrochemical detection and the reduction current of dopamine-quinone was measured as a function of dopamine concentration. Our experiments demonstrated that the presence of CoP improves the selectivity of the electrode towards dopamine in the presence of ascorbic acid (AA, with a linear trend of concentration dependence in the range of 2–30 µM. By optimizing the conditioning parameters, a separation of 130 mV between the peak potentials for ascorbic acid AA and DA was obtained, allowing the selective detection of DA. The biosensor had a sensitivity of 1.22 ± 0.02 µA·cm−2·µM−1 and a detection limit of 0.43 µM. Biosensor performances were tested in the presence of dopamine medication, with satisfactory results in terms of recovery (96%, and relative standard deviation values below 5%. These results confirmed the applicability of the biosensors in real samples such as human urine and blood serum.

Cytoplasmic tail of coronavirus spike protein has intracellular

Indian Academy of Sciences (India)

https://www.ias.ac.in/article/fulltext/jbsc/042/02/0231-0244. Keywords. Coronavirus spike protein trafficking; cytoplasmic tail signal; endoplasmic reticulum–Golgi intermediate complex; lysosome. Abstract. Intracellular trafficking and localization studies of spike protein from SARS and OC43 showed that SARS spikeprotein is ...

Thorndike’s Law 2.0: Dopamine and the regulation of thrift

Directory of Open Access Journals (Sweden)

Jeff A Beeler

2012-08-01

Full Text Available Dopamine is widely associated with reward, motivation and reinforcement learning. Research on dopamine has emphasized its contribution to compulsive behaviors, such as addiction and overeating, with less examination of its potential role in behavioral flexibility in normal, non-pathological states. In the study reviewed here, we investigated the effect of increased tonic dopamine in a two-lever homecage operant paradigm where the relative value of the levers was dynamic, requiring the mice to constantly monitor reward outcome and adapt their behavior. The data were fit to a temporal difference learning model that showed that mice with elevated dopamine exhibited less coupling between reward history and behavioral choice. This work suggests a way to integrate motivational and learning theories of dopamine into a single formal model where tonic dopamine regulates the expression of prior reward learning by controlling the degree to which learned reward values bias behavioral choice. Here I place these results in a broader context of dopamine’s role in instrumental learning and suggest a novel hypothesis that tonic dopamine regulates thrift, the degree to which an animal needs to exploit its prior reward learning to maximize return on energy expenditure. Our data suggest that increased dopamine decreases thriftiness, facilitating energy expenditure and permitting greater exploration. Conversely, this implies that decreased dopamine increases thriftiness, favoring the exploitation of prior reward learning and diminishing exploration. This perspective provides a different window onto the role dopamine may play in behavioral flexibility and its failure, compulsive behavior.

Reduced dopamine transporter binding predates impulse control disorders in Parkinson's disease.

Science.gov (United States)

Vriend, Chris; Nordbeck, Anna H; Booij, Jan; van der Werf, Ysbrand D; Pattij, Tommy; Voorn, Pieter; Raijmakers, Pieter; Foncke, Elisabeth M J; van de Giessen, Elsmarieke; Berendse, Henk W; van den Heuvel, Odile A

2014-06-01

Impulse control disorders (ICD) are relatively common in Parkinson's disease (PD) and generally are regarded as adverse effects of dopamine replacement therapy, although certain demographic and clinical risk factors are also involved. Previous single-photon emission computed tomography (SPECT) studies showed reduced ventral striatal dopamine transporter binding in Parkinson patients with ICD compared with patients without. Nevertheless, these studies were performed in patients with preexisting impulse control impairments, which impedes clear-cut interpretation of these findings. We retrospectively procured follow-up data from 31 medication-naïve PD patients who underwent dopamine transporter SPECT imaging at baseline and were subsequently treated with dopamine replacement therapy. We used questionnaires and a telephone interview to assess medication status and ICD symptom development during the follow-up period (31.5 ± 12.0 months). Eleven patients developed ICD symptoms during the follow-up period, eight of which were taking dopamine agonists. The PD patients with ICD symptoms at follow-up had higher baseline depressive scores and lower baseline dopamine transporter availability in the right ventral striatum, anterior-dorsal striatum, and posterior putamen compared with PD patients without ICD symptoms. No baseline between-group differences in age and disease stage or duration were found. The ICD symptom severity correlated negatively with baseline dopamine transporter availability in the right ventral and anterior-dorsal striatum. The results of this preliminary study show that reduced striatal dopamine transporter availability predates the development of ICD symptoms after dopamine replacement therapy and may constitute a neurobiological risk factor related to a lower premorbid dopamine transporter availability or a more pronounced dopamine denervation in PD patients susceptible to ICD. © 2014 International Parkinson and Movement Disorder Society.

SPIKY: a graphical user interface for monitoring spike train synchrony.

Science.gov (United States)

Kreuz, Thomas; Mulansky, Mario; Bozanic, Nebojsa

2015-05-01

Techniques for recording large-scale neuronal spiking activity are developing very fast. This leads to an increasing demand for algorithms capable of analyzing large amounts of experimental spike train data. One of the most crucial and demanding tasks is the identification of similarity patterns with a very high temporal resolution and across different spatial scales. To address this task, in recent years three time-resolved measures of spike train synchrony have been proposed, the ISI-distance, the SPIKE-distance, and event synchronization. The Matlab source codes for calculating and visualizing these measures have been made publicly available. However, due to the many different possible representations of the results the use of these codes is rather complicated and their application requires some basic knowledge of Matlab. Thus it became desirable to provide a more user-friendly and interactive interface. Here we address this need and present SPIKY, a graphical user interface that facilitates the application of time-resolved measures of spike train synchrony to both simulated and real data. SPIKY includes implementations of the ISI-distance, the SPIKE-distance, and the SPIKE-synchronization (an improved and simplified extension of event synchronization) that have been optimized with respect to computation speed and memory demand. It also comprises a spike train generator and an event detector that makes it capable of analyzing continuous data. Finally, the SPIKY package includes additional complementary programs aimed at the analysis of large numbers of datasets and the estimation of significance levels. Copyright © 2015 the American Physiological Society.

Regenerative, Highly-Sensitive, Non-Enzymatic Dopamine Sensor and Impact of Different Buffer Systems in Dopamine Sensing

Directory of Open Access Journals (Sweden)

Saumya Joshi

2018-01-01

Full Text Available Carbon nanotube field-effect transistors are used extensively in ultra-sensitive biomolecule sensing applications. Along with high sensitivity, the possibility of regeneration is highly desired in bio-sensors. An important constituent of such bio-sensing systems is the buffer used to maintain pH and provide an ionic conducting medium, among its other properties. In this work, we demonstrate highly-sensitive regenerative dopamine sensors and the impact of varying buffer composition and type on the electrolyte gated field effect sensors. The role of the buffer system is an often ignored condition in the electrical characterization of sensors. Non-enzymatic dopamine sensors are fabricated and regenerated in hydrochloric acid (HCl solution. The sensors are finally measured against four different buffer solutions. The impact of the nature and chemical structure of buffer molecules on the dopamine sensors is shown, and the appropriate buffer systems are demonstrated.

Femtosecond laser fabricated spike structures for selective control of cellular behavior.

Science.gov (United States)

Schlie, Sabrina; Fadeeva, Elena; Koch, Jürgen; Ngezahayo, Anaclet; Chichkov, Boris N

2010-09-01

In this study we investigate the potential of femtosecond laser generated micrometer sized spike structures as functional surfaces for selective cell controlling. The spike dimensions as well as the average spike to spike distance can be easily tuned by varying the process parameters. Moreover, negative replications in soft materials such as silicone elastomer can be produced. This allows tailoring of wetting properties of the spike structures and their negative replicas representing a reduced surface contact area. Furthermore, we investigated material effects on cellular behavior. By comparing human fibroblasts and SH-SY5Y neuroblastoma cells we found that the influence of the material was cell specific. The cells not only changed their morphology, but also the cell growth was affected. Whereas, neuroblastoma cells proliferated at the same rate on the spike structures as on the control surfaces, the proliferation of fibroblasts was reduced by the spike structures. These effects can result from the cell specific adhesion patterns as shown in this work. These findings show a possibility to design defined surface microstructures, which could control cellular behavior in a cell specific manner.

Dopamine D1 and D2 dopamine receptors regulate immobilization stress-induced activation of the hypothalamus-pituitary-adrenal axis.

Science.gov (United States)

Belda, Xavier; Armario, Antonio

2009-10-01

Whereas the role of most biogenic amines in the control of the hypothalamus-pituitary-adrenal (HPA) response to stress has been extensively studied, the role of dopamine has not. We studied the effect of different dopamine receptor antagonists on HPA response to a severe stressor (immobilization, IMO) in adult male Sprague-Dawley rats. Haloperidol administration reduced adrenocorticotropin hormone and corticosterone responses to acute IMO, particularly during the post-IMO period. This effect cannot be explained by a role of dopamine to maintain a sustained activation of the HPA axis as haloperidol did not modify the response to prolonged (up to 6 h) IMO. Administration of more selective D1 and D2 receptor antagonists (SCH23390 and eticlopride, respectively) also resulted in lower and/or shorter lasting HPA response to IMO. Dopamine, acting through both D1 and D2 receptors, exerts a stimulatory role on the activation of the HPA axis in response to a severe stressor. The finding that dopamine is involved in the maintenance of post-stress activation of the HPA axis is potentially important because the actual pathological impact of HPA activation is likely to be related to the area under the curve of plasma glucocorticoid levels, which is critically dependent on how long after stress high levels of glucocorticoid are maintained.

Progress of study on the dopamine D4 receptor imaging agent

International Nuclear Information System (INIS)

Tian Haibin; Zhang Lan; Zhang Chunfu; Li Junling; Yin Duanzhi

2001-01-01

Dopamine receptors were originally classified into five receptors subtypes, the dopamine D 4 receptor was included. Schizophrenic pathophysiology may be associated with expression and function of the dopamine D 4 receptor; it is of great importance to study the imaging agent of dopamine D 4 receptor. The study on radioactivity distribution and metabolize of radioligand remains hampered by the lack radioligand for the D 4 receptor which can be labeled using suitable nuclei. This paper reviews the progress of study on the dopamine D 4 receptor imaging agent, with particular emphasis vary nuclei, for example 11 C, 18 F, 123 I, labeled D 4 receptor ligands, antagonists and analogs as PET or SPECT imaging agents. Authors estimated affinity and selectivity of radioligands for the dopamine D 4 receptor in laboratory animal tests

An Investigation of the Stoichiometry of Na+ Cotransport with Dopamine in Rat and Human Dopamine Transporters Expressed in Human Embryonic Kidney Cells

National Research Council Canada - National Science Library

Schumacher, Paul

2001-01-01

The neuronal membrane transporter for dopamine (DAT) is a member of the Na+ and Cl dependent family of transporters and concentrates dopamine intracellularly up to 106 fold over extracellular levels...

Google Searches for "Cheap Cigarettes" Spike at Tax Increases: Evidence from an Algorithm to Detect Spikes in Time Series Data.

Science.gov (United States)

Caputi, Theodore L

2018-05-03

Online cigarette dealers have lower prices than brick-and-mortar retailers and advertise tax-free status.1-8 Previous studies show smokers search out these online alternatives at the time of a cigarette tax increase.9,10 However, these studies rely upon researchers' decision to consider a specific date and preclude the possibility that researchers focus on the wrong date. The purpose of this study is to introduce an unbiased methodology to the field of observing search patterns and to use this methodology to determine whether smokers search Google for "cheap cigarettes" at cigarette tax increases and, if so, whether the increased level of searches persists. Publicly available data from Google Trends is used to observe standardized search volumes for the term, "cheap cigarettes". Seasonal Hybrid Extreme Studentized Deviate and E-Divisive with Means tests were performed to observe spikes and mean level shifts in search volume. Of the twelve cigarette tax increases studied, ten showed spikes in searches for "cheap cigarettes" within two weeks of the tax increase. However, the mean level shifts did not occur for any cigarette tax increase. Searches for "cheap cigarettes" spike around the time of a cigarette tax increase, but the mean level of searches does not shift in response to a tax increase. The SHESD and EDM tests are unbiased methodologies that can be used to identify spikes and mean level shifts in time series data without an a priori date to be studied. SHESD and EDM affirm spikes in interest are related to tax increases. • Applies improved statistical techniques (SHESD and EDM) to Google search data related to cigarettes, reducing bias and increasing power • Contributes to the body of evidence that state and federal tax increases are associated with spikes in searches for cheap cigarettes and may be good dates for increased online health messaging related to tobacco.

Spike-timing theory of working memory.

Directory of Open Access Journals (Sweden)

Botond Szatmáry

Full Text Available Working memory (WM is the part of the brain's memory system that provides temporary storage and manipulation of information necessary for cognition. Although WM has limited capacity at any given time, it has vast memory content in the sense that it acts on the brain's nearly infinite repertoire of lifetime long-term memories. Using simulations, we show that large memory content and WM functionality emerge spontaneously if we take the spike-timing nature of neuronal processing into account. Here, memories are represented by extensively overlapping groups of neurons that exhibit stereotypical time-locked spatiotemporal spike-timing patterns, called polychronous patterns; and synapses forming such polychronous neuronal groups (PNGs are subject to associative synaptic plasticity in the form of both long-term and short-term spike-timing dependent plasticity. While long-term potentiation is essential in PNG formation, we show how short-term plasticity can temporarily strengthen the synapses of selected PNGs and lead to an increase in the spontaneous reactivation rate of these PNGs. This increased reactivation rate, consistent with in vivo recordings during WM tasks, results in high interspike interval variability and irregular, yet systematically changing, elevated firing rate profiles within the neurons of the selected PNGs. Additionally, our theory explains the relationship between such slowly changing firing rates and precisely timed spikes, and it reveals a novel relationship between WM and the perception of time on the order of seconds.

Putting Desire on a Budget: Dopamine and Energy Expenditure, Reconciling Reward and Resources

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Jeff A Beeler

2012-07-01

Full Text Available Accumulating evidence indicates integration of dopamine function with metabolic signals, highlighting a potential role for dopamine in energy balance, frequently construed as modulating reward in response to homeostatic state. Though its precise role remains controversial, the reward perspective of dopamine has dominated investigation of motivational disorders, including obesity. In the hypothesis outlined here, we suggest instead that the primary role of dopamine in behavior is to modulate activity to adapt behavioral energy expenditure to the prevailing environmental energy conditions, with the role of dopamine in reward and motivated behaviors derived from its primary role in energy balance. Dopamine has long been known to modulate activity, exemplified by psychostimulants that act via dopamine. More recently, there has been nascent investigation into the role of dopamine in modulating voluntary activity, with some investigators suggesting that dopamine may serve as a final common pathway that couples energy sensing to regulated voluntary energy expenditure. We suggest that interposed between input from both the internal and external world, dopamine modulates behavioral energy expenditure along two axes: a conserve-expend axis that regulates generalized activity and an explore-exploit axes that regulates the degree to which reward value biases the distribution of activity. In this view, increased dopamine does not promote consumption of tasty food. Instead increased dopamine promotes energy expenditure and exploration while decreased dopamine favors energy conservation and exploitation. This hypothesis provides a mechanistic interpretation to an apparent paradox: the well-established role of dopamine in food seeking and the findings that low dopaminergic functions are associated with obesity. Our hypothesis provides an alternative perspective on the role of dopamine in obesity and reinterprets the ‘reward deficiency hypothesis’ as a

Dual roles for spike signaling in cortical neural populations

Directory of Open Access Journals (Sweden)

Dana eBallard

2011-06-01

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

Dopamine and extinction: A convergence of theory with fear and reward circuitry

Science.gov (United States)

Abraham, Antony D.; Neve, Kim A.; Lattal, K. Matthew

2014-01-01

Research on dopamine lies at the intersection of sophisticated theoretical and neurobiological approaches to learning and memory. Dopamine has been shown to be critical for many processes that drive learning and memory, including motivation, prediction error, incentive salience, memory consolidation, and response output. Theories of dopamine’s function in these processes have, for the most part, been developed from behavioral approaches that examine learning mechanisms in reward-related tasks. A parallel and growing literature indicates that dopamine is involved in fear conditioning and extinction. These studies are consistent with long-standing ideas about appetitive-aversive interactions in learning theory and they speak to the general nature of cellular and molecular processes that underlie behavior. We review the behavioral and neurobiological literature showing a role for dopamine in fear conditioning and extinction. At a cellular level, we review dopamine signaling and receptor pharmacology, cellular and molecular events that follow dopamine receptor activation, and brain systems in which dopamine functions. At a behavioral level, we describe theories of learning and dopamine function that could describe the fundamental rules underlying how dopamine modulates different aspects of learning and memory processes. PMID:24269353

New detection of brain dopamine receptors with [3H]dihydroergocryptine

International Nuclear Information System (INIS)

Tittler, M.; Weinreich, P.; Seeman, P.

1977-01-01

Because dihydroergocryptine (DHE) and closely related ergots are dopamine-mimetic agonists, we tested [ 3 H]DHE as a possible ligand for [ 3 H]dopamine receptors in the calf caudate. In order to avoid [ 3 H]DHE from tagging α-adrenergic receptors, an excess of 500 nM phentolamine was used to block these sites, permitting the dopamine receptors to be measured separately. Specific binding of [ 3 H]DHE was defined as total binding minus that occurring in the presence of 1 μM (+)-butaclamol. Excess phentolamine reduced the specific binding of [ 3 H]DHE from 328 down to 138 fmol/mg, the difference presumably representing α-receptors. The K/sub D/ for [ 3 H]DHE was 0.55 nM (with or without phentolamine), and this high affinity site was blocked (in the presence of phentolamine) by 250 nM apomorphine, 650 nM dopamine, and 1200 nM (-)-norepinephrine, indicating that [ 3 H]DHE was binding to dopamine receptors. All neuroleptics blocked specific [ 3 H]DHE binding in direct relation to the clinical potency of the neuroleptic. The displacement of specific [ 3 H]DHE binding by dopamine or by norepinephrine (in the presence of phentolamine) revealed two subsets of dopamine receptors

Measures of spike train synchrony for data with multiple time scales

NARCIS (Netherlands)

Satuvuori, Eero; Mulansky, Mario; Bozanic, Nebojsa; Malvestio, Irene; Zeldenrust, Fleur; Lenk, Kerstin; Kreuz, Thomas

2017-01-01

Background Measures of spike train synchrony are widely used in both experimental and computational neuroscience. Time-scale independent and parameter-free measures, such as the ISI-distance, the SPIKE-distance and SPIKE-synchronization, are preferable to time scale parametric measures, since by

Demonstration of specific dopamine receptors on human pituitary adenomas

International Nuclear Information System (INIS)

Koga, Masafumi; Nakao, Haruyoshi; Arao, Masayo; Sato, Bunzo; Noma, Keizo; Morimoto, Yasuhiko; Kishimoto, Susumu; Mori, Shintaro; Uozumi, Toru

1987-01-01

Dopamine receptors on human pituitary adenoma membranes were characterized using [ 3 H]spiperone as the radioligand. The specific [ 3 H]spiperone binding sites on prolactin (PRL)-secreting adenoma membranes were recognized as a dopamine receptor, based upon the data showing high affinity binding, saturability, specificity, temperature dependence, and reversibility. All of 14 PRL-secreting adenomas had high affinity dopamine receptors, with a dissociation constant (Kd) of 0.85±0.11 nmol/l (mean±SEM) and a maximal binding capacity (Bmax) of 428±48.6 fmol/mg protein. Among 14 growth hormone (GH)-secreting adenomas examined, 8 (57%) had dopamine receptors with a Kd of 1.90±0.47 nmol/l and a Bmax of 131±36.9 fmol/mg protein. Furthermore, 15 of 24 (58%) nonsecreting pituitary adenomas also had dopamine receptors with a Kd of 1.86±0.37 nmol/l and a Bmax of 162±26.0 fmol/mg protein. These results indicate that some GH-secreting adenomas as well as some nonsecreting pituitary adenomas contain dopamine receptors. But their affinity and number of binding sites are significantly lower (P<0.05) and fewer (P<0.001) respectively, than those in PRL-secreting adenomas. (author)

Development of specific dopamine D-1 agonists and antagonists

International Nuclear Information System (INIS)

Sakolchai, S.

1987-01-01

To develop potentially selective dopamine D-1 agonists and to investigate on the structural requirement for D-1 activity, the derivatives of dibenzocycloheptadiene are synthesized and pharmacologically evaluated. The target compounds are 5-aminomethyl-10,11-dihydro-1,2-dihydroxy-5H-dibenzo[a,d]cycloheptene hydrobromide 10 and 9,10-dihydroxy-1,2,3,7,8,12b-hexahydrobenzo[1,2]cyclohepta[3,4,5d,e]isoquinoline hydrobromide 11. In a dopamine-sensitive rat retinal adenylate cyclase assay, a model for D-1 activity, compound 10 is essentially inert for both agonist and antagonist activity. In contrast, compound 11 is approximately equipotent to dopamine in activation of the D-1 receptor. Based on radioligand and binding data, IC 50 of compound 11 for displacement of 3 H-SCH 23390, a D-1 ligand, is about 7 fold less than that for displacement of 3 H-spiperone, a D-2 ligand. These data indicate that compound 11 is a potent selective dopamine D-1 agonist. This study provides a new structural class of dopamine D-1 acting agent: dihydroxy-benzocycloheptadiene analog which can serve as a lead compound for further drug development and as a probe for investigation on the nature of dopamine D-1 receptor

A novel unsupervised spike sorting algorithm for intracranial EEG.

Science.gov (United States)

Yadav, R; Shah, A K; Loeb, J A; Swamy, M N S; Agarwal, R

2011-01-01

This paper presents a novel, unsupervised spike classification algorithm for intracranial EEG. The method combines template matching and principal component analysis (PCA) for building a dynamic patient-specific codebook without a priori knowledge of the spike waveforms. The problem of misclassification due to overlapping classes is resolved by identifying similar classes in the codebook using hierarchical clustering. Cluster quality is visually assessed by projecting inter- and intra-clusters onto a 3D plot. Intracranial EEG from 5 patients was utilized to optimize the algorithm. The resulting codebook retains 82.1% of the detected spikes in non-overlapping and disjoint clusters. Initial results suggest a definite role of this method for both rapid review and quantitation of interictal spikes that could enhance both clinical treatment and research studies on epileptic patients.

No WIMP mini-spikes in dwarf spheroidal galaxies

NARCIS (Netherlands)

Wanders, M.; Bertone, G.; Volonteri, M.; Weniger, C.

2015-01-01

The formation of black holes inevitably affects the distribution of dark and baryonic matter in their vicinity, leading to an enhancement of the dark matter density, called spike, and if dark matter is made of WIMPs, to a strong enhancement of the dark matter annihilation rate. Spikes at the center

The Mechanisms of Repetitive Spike Generation in an Axonless Retinal Interneuron

Directory of Open Access Journals (Sweden)

Mark S. Cembrowski

2012-02-01

Full Text Available Several types of retinal interneurons exhibit spikes but lack axons. One such neuron is the AII amacrine cell, in which spikes recorded at the soma exhibit small amplitudes (5 ms. Here, we used electrophysiological recordings and computational analysis to examine the mechanisms underlying this atypical spiking. We found that somatic spikes likely represent large, brief action potential-like events initiated in a single, electrotonically distal dendritic compartment. In this same compartment, spiking undergoes slow modulation, likely by an M-type K conductance. The structural correlate of this compartment is a thin neurite that extends from the primary dendritic tree: local application of TTX to this neurite, or excision of it, eliminates spiking. Thus, the physiology of the axonless AII is much more complex than would be anticipated from morphological descriptions and somatic recordings; in particular, the AII possesses a single dendritic structure that controls its firing pattern.

Building functional networks of spiking model neurons.

Science.gov (United States)

Abbott, L F; DePasquale, Brian; Memmesheimer, Raoul-Martin

2016-03-01

Most of the networks used by computer scientists and many of those studied by modelers in neuroscience represent unit activities as continuous variables. Neurons, however, communicate primarily through discontinuous spiking. We review methods for transferring our ability to construct interesting networks that perform relevant tasks from the artificial continuous domain to more realistic spiking network models. These methods raise a number of issues that warrant further theoretical and experimental study.

D1 dopamine receptor is involved in shell formation in larvae of Pacific oyster Crassostrea gigas.

Science.gov (United States)

Liu, Zhaoqun; Wang, Lingling; Yan, Yunchen; Zheng, Yan; Ge, Wenjing; Li, Meijia; Wang, Weilin; Song, Xiaorui; Song, Linsheng

2018-07-01

Dopamine (DA), a significant member of catecholamines, is reported to induce biomineralization of calcium carbonate vaterite microspheres via dopamine receptor (DR) in bivalves, implying the modulation of dopaminergic system on shell formation during larval development. In this research, a homologue of D1 type DR (CgD1DR-1) was identified from oyster Crassostrea gigas, whose full length cDNA was 1197 bp. It was widely expressed in various tissues of C. gigas, with the significantly higher levels in hepatopancreas, mantle, muscle and gill. During developmental stages, the mRNA transcripts of CgD1DR-1 in D-shape larvae were obviously higher (p < 0.05) than those in trochophore and umbo larvae, and CO 2 exposure could inhibit the synthesis of DA and mRNA expression of CgD1DR-1. After cell transfection and DA treatment, intracellular cAMP in cells with the expression of CgD1DR-1 increased significantly (p < 0.05). Furthermore, the incubation with SCH 23390 for the blockage of CgD1DR-1 significantly restrained the expressions of six shell formation-related genes including CgTyrosinase-1, CgTyrosinase-3, CgChitinaseLP, CgAMC, CgBMP and CgBMPR in trochophore and D-shape larvae. These results jointly suggested that DA together with its receptor CgD1DR-1 might be involved in shell formation during oyster larval development from trochophore to D-shape larvae, and CO 2 -induced ocean acidification (OA) might influence marine bivalves by inhibiting the DA-D1DR pathway to prohibit their shell formation. Copyright © 2018 Elsevier Ltd. All rights reserved.

Characterization of D1 dopamine receptors in the central nervous system

International Nuclear Information System (INIS)

Hess, E.J.

1987-01-01

Several lines of evidence suggest an association of central nervous system dopaminergic systems in the etiology of the schizophrenia. Interest in the role of D 1 dopamine receptors has revived with the advent of selective drugs for this dopamine receptor, particularly the D 1 dopamine receptor antagonists, SCH23390. [ 3 H]SCH23390 represents a superior radioligand for labeling the two-state striatal D 1 dopamine receptor in that its high percent specific binding makes it especially suitable for detailed mechanistic studies of this receptor. Striatal D 1 dopamine receptors have been shown to mediate the stimulation of adenylate cyclase activity via a guanine nucleotide regulatory subunit. Forskolin acts in a synergistic manner with dopamine agonists, guanine nucleotides or sodium fluoride to potentiate the stimulation of rat striatal adenylate cyclase activity mediated by these reagents. By using the aforementioned reagents and the irreversible receptor modifying reagent N-ethoxycarbonyl-2-ethoxy-1,2,-dihydroquinoline, we demonstrated that the D 1 dopamine receptor population in rat striatum is not a stoichiometrically-limiting factor in agonist stimulation of adenylate cyclase activity

A peptide disrupting the D2R-DAT interaction protects against dopamine neurotoxicity.

Science.gov (United States)

Su, Ping; Liu, Fang

2017-09-01

Dopamine reuptake from extracellular space to cytosol leads to accumulation of dopamine, which triggers neurotoxicity in dopaminergic neurons. Previous studies have shown that both dopamine D2 receptor (D2R) and dopamine transporter (DAT) are involved in dopamine neurotoxicity. However, blockade of either D2R or DAT causes side effects due to antagonism of other physiological functions of these two proteins. We previously found that DAT can form a protein complex with D2R and its cell surface expression is facilitated via D2R-DAT interaction, which regulates dopamine reuptake and intracellular dopamine levels. Here we found that an interfering peptide (DAT-S1) disrupting the D2R-DAT interaction protects neurons against dopamine neurotoxicity, and this effect is mediated by inhibiting DAT cell surface expression and inhibiting both caspase-3 and PARP-1 cleavage. This study demonstrates the role of the D2R-DAT complex in dopamine neurotoxicity and investigated the potential mechanisms, which might help better understand the mechanisms of dopamine neurotoxicity. The peptide may provide some insights to improve treatments for dopamine neurotoxicity and related diseases, such as Parkinson's disease, as well as methamphetamine- and 3,4-methsylenedioxy methamphetamine-induced neurotoxicity. Copyright © 2017. Published by Elsevier Inc.

Spike morphology in blast-wave-driven instability experiments

International Nuclear Information System (INIS)

Kuranz, C. C.; Drake, R. P.; Grosskopf, M. J.; Fryxell, B.; Budde, A.; Hansen, J. F.; Miles, A. R.; Plewa, T.; Hearn, N.; Knauer, J.

2010-01-01

The laboratory experiments described in the present paper observe the blast-wave-driven Rayleigh-Taylor instability with three-dimensional (3D) initial conditions. About 5 kJ of energy from the Omega laser creates conditions similar to those of the He-H interface during the explosion phase of a supernova. The experimental target is a 150 μm thick plastic disk followed by a low-density foam. The plastic piece has an embedded, 3D perturbation. The basic structure of the pattern is two orthogonal sine waves where each sine wave has an amplitude of 2.5 μm and a wavelength of 71 μm. In some experiments, an additional wavelength is added to explore the interaction of modes. In experiments with 3D initial conditions the spike morphology differs from what has been observed in other Rayleigh-Taylor experiments and simulations. Under certain conditions, experimental radiographs show some mass extending from the interface to the shock front. Current simulations show neither the spike morphology nor the spike penetration observed in the experiments. The amount of mass reaching the shock front is analyzed and potential causes for the spike morphology and the spikes reaching the shock are discussed. One such hypothesis is that these phenomena may be caused by magnetic pressure, generated by an azimuthal magnetic field produced by the plasma dynamics.

In vivo neurochemical characterization of clothianidin induced striatal dopamine release.

Science.gov (United States)

Faro, L R F; Oliveira, I M; Durán, R; Alfonso, M

2012-12-16

Clothianidin (CLO) is a neonicotinoid insecticide with selective action on nicotinic acetylcholine receptors. The aim of this study was to determine the neurochemical basis for CLO-induced striatal dopamine release using the microdialysis technique in freely moving and conscious rats. Intrastriatal administration of CLO (3.5mM), produced an increase in both spontaneous (2462 ± 627% with respect to basal values) and KCl-evoked (4672 ± 706% with respect to basal values) dopamine release. This effect was attenuated in Ca(2+)-free medium, and was prevented in reserpine pre-treated animals or in presence of tetrodotoxin (TTX). To investigate the involvement of dopamine transporter (DAT), the effect of CLO was observed in presence of nomifensine. The coadministration of CLO and nomifensine produced an additive effect on striatal dopamine release. The results suggest that the effect of CLO on striatal dopamine release is predominantly mediated by an exocytotic mechanism, Ca(2+), vesicular and TTX-dependent and not by a mechanism mediated by dopamine transporter. Published by Elsevier Ireland Ltd.

Striatal dopamine in Parkinson disease: A meta-analysis of imaging studies.

Science.gov (United States)

Kaasinen, Valtteri; Vahlberg, Tero

2017-12-01

A meta-analysis of 142 positron emission tomography and single photon emission computed tomography studies that have investigated striatal presynaptic dopamine function in Parkinson disease (PD) was performed. Subregional estimates of striatal dopamine metabolism are presented. The aromatic L-amino-acid decarboxylase (AADC) defect appears to be consistently smaller than the dopamine transporter and vesicular monoamine transporter 2 defects, suggesting upregulation of AADC function in PD. The correlation between disease severity and dopamine loss appears linear, but the majority of longitudinal studies point to a negative exponential progression pattern of dopamine loss in PD. Ann Neurol 2017;82:873-882. © 2017 American Neurological Association.

Fast and Efficient Asynchronous Neural Computation with Adapting Spiking Neural Networks

NARCIS (Netherlands)

D. Zambrano (Davide); S.M. Bohte (Sander)

2016-01-01

textabstractBiological neurons communicate with a sparing exchange of pulses - spikes. It is an open question how real spiking neurons produce the kind of powerful neural computation that is possible with deep artificial neural networks, using only so very few spikes to communicate. Building on

Coincidence Detection Using Spiking Neurons with Application to Face Recognition

Directory of Open Access Journals (Sweden)

Fadhlan Kamaruzaman

2015-01-01

Full Text Available We elucidate the practical implementation of Spiking Neural Network (SNN as local ensembles of classifiers. Synaptic time constant τs is used as learning parameter in representing the variations learned from a set of training data at classifier level. This classifier uses coincidence detection (CD strategy trained in supervised manner using a novel supervised learning method called τs Prediction which adjusts the precise timing of output spikes towards the desired spike timing through iterative adaptation of τs. This paper also discusses the approximation of spike timing in Spike Response Model (SRM for the purpose of coincidence detection. This process significantly speeds up the whole process of learning and classification. Performance evaluations with face datasets such as AR, FERET, JAFFE, and CK+ datasets show that the proposed method delivers better face classification performance than the network trained with Supervised Synaptic-Time Dependent Plasticity (STDP. We also found that the proposed method delivers better classification accuracy than k nearest neighbor, ensembles of kNN, and Support Vector Machines. Evaluation on several types of spike codings also reveals that latency coding delivers the best result for face classification as well as for classification of other multivariate datasets.

Adaptive coupling optimized spiking coherence and synchronization in Newman-Watts neuronal networks.

Science.gov (United States)

Gong, Yubing; Xu, Bo; Wu, Ya'nan

2013-09-01

In this paper, we have numerically studied the effect of adaptive coupling on the temporal coherence and synchronization of spiking activity in Newman-Watts Hodgkin-Huxley neuronal networks. It is found that random shortcuts can enhance the spiking synchronization more rapidly when the increment speed of adaptive coupling is increased and can optimize the temporal coherence of spikes only when the increment speed of adaptive coupling is appropriate. It is also found that adaptive coupling strength can enhance the synchronization of spikes and can optimize the temporal coherence of spikes when random shortcuts are appropriate. These results show that adaptive coupling has a big influence on random shortcuts related spiking activity and can enhance and optimize the temporal coherence and synchronization of spiking activity of the network. These findings can help better understand the roles of adaptive coupling for improving the information processing and transmission in neural systems.

Forskolin suppresses delayed-rectifier K+ currents and enhances spike frequency-dependent adaptation of sympathetic neurons.

Science.gov (United States)

Angel-Chavez, Luis I; Acosta-Gómez, Eduardo I; Morales-Avalos, Mario; Castro, Elena; Cruzblanca, Humberto

2015-01-01

In signal transduction research natural or synthetic molecules are commonly used to target a great variety of signaling proteins. For instance, forskolin, a diterpene activator of adenylate cyclase, has been widely used in cellular preparations to increase the intracellular cAMP level. However, it has been shown that forskolin directly inhibits some cloned K+ channels, which in excitable cells set up the resting membrane potential, the shape of action potential and regulate repetitive firing. Despite the growing evidence indicating that K+ channels are blocked by forskolin, there are no studies yet assessing the impact of this mechanism of action on neuron excitability and firing patterns. In sympathetic neurons, we find that forskolin and its derivative 1,9-Dideoxyforskolin, reversibly suppress the delayed rectifier K+ current (IKV). Besides, forskolin reduced the spike afterhyperpolarization and enhanced the spike frequency-dependent adaptation. Given that IKV is mostly generated by Kv2.1 channels, HEK-293 cells were transfected with cDNA encoding for the Kv2.1 α subunit, to characterize the mechanism of forskolin action. Both drugs reversible suppressed the Kv2.1-mediated K+ currents. Forskolin inhibited Kv2.1 currents and IKV with an IC50 of ~32 μM and ~24 µM, respectively. Besides, the drug induced an apparent current inactivation and slowed-down current deactivation. We suggest that forskolin reduces the excitability of sympathetic neurons by enhancing the spike frequency-dependent adaptation, partially through a direct block of their native Kv2.1 channels.

A matched-filter algorithm to detect amperometric spikes resulting from quantal secretion.

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Balaji Ramachandran, Supriya; Gillis, Kevin D

2018-01-01

Electrochemical microelectrodes located immediately adjacent to the cell surface can detect spikes of amperometric current during exocytosis as the transmitter released from a single vesicle is oxidized on the electrode surface. Automated techniques to detect spikes are needed in order to quantify the spike rate as a measure of the rate of exocytosis. We have developed a Matched Filter (MF) detection algorithm that scans the data set with a library of prototype spike templates while performing a least-squares fit to determine the amplitude and standard error. The ratio of the fit amplitude to the standard error constitutes a criterion score that is assigned for each time point and for each template. A spike is detected when the criterion score exceeds a threshold and the highest-scoring template and the time of peak score is identified. The search for the next spike commences only after the score falls below a second, lower threshold to reduce false positives. The approach was extended to detect spikes with double-exponential decays with the sum of two templates. Receiver Operating Characteristic plots (ROCs) demonstrate that the algorithm detects >95% of manually identified spikes with a false-positive rate of ∼2%. ROCs demonstrate that the MF algorithm performs better than algorithms that detect spikes based on a derivative-threshold approach. The MF approach performs well and leads into approaches to identify spike parameters. Copyright © 2017 Elsevier B.V. All rights reserved.

Dopamins renale virkninger

DEFF Research Database (Denmark)

Olsen, Niels Vidiendal

1990-01-01

is frequently employed in cases of acute oliguric renal failure but the results available concerning the therapeutic effect are frequently retrospective and uncontrolled. The results suggest that early treatment with 1-3 micrograms/kg/min dopamine combined with furosemide can postpone or possibly render...

Pyrethroid pesticide-induced alterations in dopamine transporter function

International Nuclear Information System (INIS)

Elwan, Mohamed A.; Richardson, Jason R.; Guillot, Thomas S.; Caudle, W. Michael; Miller, Gary W.

2006-01-01

Parkinson's disease (PD) is a progressive neurodegenerative disease affecting the nigrostriatal dopaminergic pathway. Several epidemiological studies have demonstrated an association between pesticide exposure and the incidence of PD. Studies from our laboratory and others have demonstrated that certain pesticides increase levels of the dopamine transporter (DAT), an integral component of dopaminergic neurotransmission and a gateway for dopaminergic neurotoxins. Here, we report that repeated exposure (3 injections over 2 weeks) of mice to two commonly used pyrethroid pesticides, deltamethrin (3 mg/kg) and permethrin (0.8 mg/kg), increases DAT-mediated dopamine uptake by 31 and 28%, respectively. Using cells stably expressing DAT, we determined that exposure (10 min) to deltamethrin and permethrin (1 nM-100 μM) had no effect on DAT-mediated dopamine uptake. Extending exposures to both pesticides for 30 min (10 μM) or 24 h (1, 5, and 10 μM) resulted in significant decrease in dopamine uptake. This reduction was not the result of competitive inhibition, loss of DAT protein, or cytotoxicity. However, there was an increase in DNA fragmentation, an index of apoptosis, in cells exhibiting reduced uptake at 30 min and 24 h. These data suggest that up-regulation of DAT by in vivo pyrethroid exposure is an indirect effect and that longer-term exposure of cells results in apoptosis. Since DAT can greatly affect the vulnerability of dopamine neurons to neurotoxicants, up-regulation of DAT by deltamethrin and permethrin may increase the susceptibility of dopamine neurons to toxic insult, which may provide insight into the association between pesticide exposure and PD

Serotonin 2B Receptors in Mesoaccumbens Dopamine Pathway Regulate Cocaine Responses.

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Doly, Stéphane; Quentin, Emily; Eddine, Raphaël; Tolu, Stefania; Fernandez, Sebastian P; Bertran-Gonzalez, Jesus; Valjent, Emmanuel; Belmer, Arnauld; Viñals, Xavier; Callebert, Jacques; Faure, Philippe; Meye, Frank J; Hervé, Denis; Robledo, Patricia; Mameli, Manuel; Launay, Jean-Marie; Maldonado, Rafael; Maroteaux, Luc

2017-10-25

Addiction is a maladaptive pattern of behavior following repeated use of reinforcing drugs in predisposed individuals, leading to lifelong changes. Common among these changes are alterations of neurons releasing dopamine in the ventral and dorsal territories of the striatum. The serotonin 5-HT 2B receptor has been involved in various behaviors, including impulsivity, response to antidepressants, and response to psychostimulants, pointing toward putative interactions with the dopamine system. Despite these findings, it remains unknown whether 5-HT 2B receptors directly modulate dopaminergic activity and the possible mechanisms involved. To answer these questions, we investigated the contribution of 5-HT 2B receptors to cocaine-dependent behavioral responses. Male mice permanently lacking 5-HT 2B receptors, even restricted to dopamine neurons, developed heightened cocaine-induced locomotor responses. Retrograde tracing combined with single-cell mRNA amplification indicated that 5-HT 2B receptors are expressed by mesolimbic dopamine neurons. In vivo and ex vivo electrophysiological recordings showed that 5-HT 2B -receptor inactivation in dopamine neurons affects their neuronal activity and increases AMPA-mediated over NMDA-mediated excitatory synaptic currents. These changes are associated with lower ventral striatum dopamine activity and blunted cocaine self-administration. These data identify the 5-HT 2B receptor as a pharmacological intermediate and provide mechanistic insight into attenuated dopamine tone following exposure to drugs of abuse. SIGNIFICANCE STATEMENT Here we report that mice lacking 5-HT 2B receptors totally or exclusively in dopamine neurons exhibit heightened cocaine-induced locomotor responses. Despite the sensitized state of these mice, we found that associated changes include lower ventral striatum dopamine activity and lower cocaine operant self-administration. We described the selective expression of 5-HT 2B receptors in a subpopulation of

Dopamine Modulates Option Generation for Behavior.

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Ang, Yuen-Siang; Manohar, Sanjay; Plant, Olivia; Kienast, Annika; Le Heron, Campbell; Muhammed, Kinan; Hu, Michele; Husain, Masud

2018-05-21

Animals make innumerable decisions every day, each of which involves evaluating potential options for action. But how are options generated? Although much is now known about decision making when a fixed set of potential options is provided, surprisingly little progress has been made on self-generated options. Some researchers have proposed that such abilities might be modulated by dopamine. Here, we used a new measure of option generation that is quantitative, objective, and culture fair to investigate how humans generate different behavioral options. Participants were asked to draw as many different paths (options) as they could between two points within a fixed time. Healthy individuals (n = 96) exhibited a trade-off between uniqueness (how individually different their options were) and fluency (number of options), generating either many similar or few unique options. To assess influence of dopamine, we first examined patients with Parkinson's disease (n = 35) ON and OFF their dopaminergic medication and compared them to elderly healthy controls (n = 34). Then we conducted a double-blind, placebo-controlled crossover study of the D2 agonist cabergoline in healthy older people (n = 29). Across both studies, dopamine increased fluency but diminished overall uniqueness of options generated, due to the effect of fluency trading off with uniqueness. Crucially, however, when this trade-off was corrected for, dopamine was found to increase uniqueness for any given fluency. Three carefully designed control studies showed that performance on our option-generation task was not related to executing movements, planning actions, or selecting between generated options. These findings show that dopamine plays an important role in modulating option generation. Copyright © 2018 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Dopamine release in ventral striatum of pathological gamblers losing money

DEFF Research Database (Denmark)

Linnet, J; Peterson, E; Doudet, D J

2010-01-01

Linnet J, Peterson E, Doudet DJ, Gjedde A, Møller A. Dopamine release in ventral striatum of pathological gamblers losing money. Objective: To investigate dopaminergic neurotransmission in relation to monetary reward and punishment in pathological gambling. Pathological gamblers (PG) often continue...... gambling despite losses, known as 'chasing one's losses'. We therefore hypothesized that losing money would be associated with increased dopamine release in the ventral striatum of PG compared with healthy controls (HC). Method: We used Positron Emission Tomography (PET) with [(11)C]raclopride to measure...... dopamine release in the ventral striatum of 16 PG and 15 HC playing the Iowa Gambling Task (IGT). Results: PG who lost money had significantly increased dopamine release in the left ventral striatum compared with HC. PG and HC who won money did not differ in dopamine release. Conclusion: Our findings...

A kinetic model of dopamine- and calcium-dependent striatal synaptic plasticity.

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Takashi Nakano

2010-02-01

Full Text Available Corticostriatal synapse plasticity of medium spiny neurons is regulated by glutamate input from the cortex and dopamine input from the substantia nigra. While cortical stimulation alone results in long-term depression (LTD, the combination with dopamine switches LTD to long-term potentiation (LTP, which is known as dopamine-dependent plasticity. LTP is also induced by cortical stimulation in magnesium-free solution, which leads to massive calcium influx through NMDA-type receptors and is regarded as calcium-dependent plasticity. Signaling cascades in the corticostriatal spines are currently under investigation. However, because of the existence of multiple excitatory and inhibitory pathways with loops, the mechanisms regulating the two types of plasticity remain poorly understood. A signaling pathway model of spines that express D1-type dopamine receptors was constructed to analyze the dynamic mechanisms of dopamine- and calcium-dependent plasticity. The model incorporated all major signaling molecules, including dopamine- and cyclic AMP-regulated phosphoprotein with a molecular weight of 32 kDa (DARPP32, as well as AMPA receptor trafficking in the post-synaptic membrane. Simulations with dopamine and calcium inputs reproduced dopamine- and calcium-dependent plasticity. Further in silico experiments revealed that the positive feedback loop consisted of protein kinase A (PKA, protein phosphatase 2A (PP2A, and the phosphorylation site at threonine 75 of DARPP-32 (Thr75 served as the major switch for inducing LTD and LTP. Calcium input modulated this loop through the PP2B (phosphatase 2B-CK1 (casein kinase 1-Cdk5 (cyclin-dependent kinase 5-Thr75 pathway and PP2A, whereas calcium and dopamine input activated the loop via PKA activation by cyclic AMP (cAMP. The positive feedback loop displayed robust bi-stable responses following changes in the reaction parameters. Increased basal dopamine levels disrupted this dopamine-dependent plasticity. The

Dopamine and oxytocin interactions underlying behaviors: potential contributions to behavioral disorders.

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Baskerville, Tracey A; Douglas, Alison J

2010-06-01

Dopamine is an important neuromodulator that exerts widespread effects on the central nervous system (CNS) function. Disruption in dopaminergic neurotransmission can have profound effects on mood and behavior and as such is known to be implicated in various neuropsychiatric behavioral disorders including autism and depression. The subsequent effects on other neurocircuitries due to dysregulated dopamine function have yet to be fully explored. Due to the marked social deficits observed in psychiatric patients, the neuropeptide, oxytocin is emerging as one particular neural substrate that may be influenced by the altered dopamine levels subserving neuropathologic-related behavioral diseases. Oxytocin has a substantial role in social attachment, affiliation and sexual behavior. More recently, it has emerged that disturbances in peripheral and central oxytocin levels have been detected in some patients with dopamine-dependent disorders. Thus, oxytocin is proposed to be a key neural substrate that interacts with central dopamine systems. In addition to psychosocial improvement, oxytocin has recently been implicated in mediating mesolimbic dopamine pathways during drug addiction and withdrawal. This bi-directional role of dopamine has also been implicated during some components of sexual behavior. This review will discuss evidence for the existence dopamine/oxytocin positive interaction in social behavioral paradigms and associated disorders such as sexual dysfunction, autism, addiction, anorexia/bulimia, and depression. Preliminary findings suggest that whilst further rigorous testing has to be conducted to establish a dopamine/oxytocin link in human disorders, animal models seem to indicate the existence of broad and integrated brain circuits where dopamine and oxytocin interactions at least in part mediate socio-affiliative behaviors. A profound disruption to these pathways is likely to underpin associated behavioral disorders. Central oxytocin pathways may serve as a

Thermal spike analysis of highly charged ion tracks

International Nuclear Information System (INIS)

Karlušić, M.; Jakšić, M.

2012-01-01

The irradiation of material using swift heavy ion or highly charged ion causes excitation of the electron subsystem at nanometer scale along the ion trajectory. According to the thermal spike model, energy deposited into the electron subsystem leads to temperature increase due to electron–phonon coupling. If ion-induced excitation is sufficiently intensive, then melting of the material can occur, and permanent damage (i.e., ion track) can be formed upon rapid cooling. We present an extension of the analytical thermal spike model of Szenes for the analysis of surface ion track produced after the impact of highly charged ion. By applying the model to existing experimental data, more than 60% of the potential energy of the highly charged ion was shown to be retained in the material during the impact and transformed into the energy of the thermal spike. This value is much higher than 20–40% of the transferred energy into the thermal spike by swift heavy ion. Thresholds for formation of highly charged ion track in different materials show uniform behavior depending only on few material parameters.

Ascorbic acid enables reversible dopamine receptor 3H-agonist binding

International Nuclear Information System (INIS)

Leff, S.; Sibley, D.R.; Hamblin, M.; Creese, I.

1981-01-01

The effects of ascorbic acid on dopaminergic 3 H-agonist receptor binding were studied in membrane homogenates of bovine anterior pituitary and caudate, and rat striatum. In all tissues virtually no stereospecific binding (defined using 1uM (+)butaclamol) of the 3 H-agonists N-propylnorapomorphine (NPA), apomorphine, or dopamine could be demonstrated in the absence of ascorbic acid. Although levels of total 3 H-agonist binding were three to five times greater in the absence than in the presence of 0.1% ascorbic acid, the increased binding was entirely non-stereospecific. Greater amounts of dopamine-inhibitable 3 H-NPA binding could be demonstrated in the absence of 0.1% ascorbic acid, but this measure of ''specific binding'' was demonstrated not to represent dopamine receptor binding since several other catecholamines and catechol were equipotent with dopamine and more potent than the dopamine agonist (+/-)amino-6,7-dihydroxy-1,2,3,4-tetrahydronapthalene (ADTN) in inhibiting this binding. High levels of dopamine-displaceable 3 H-agonist binding were detected in fresh and boiled homogenates of cerebellum, an area of brain which receives no dopaminergic innervation, further demonstrating the non-specific nature of 3 H-agonist binding in the absence of ascorbic acid. These studies emphasize that under typical assay conditions ascorbic acid is required in order to demonstrate reversible and specific 3 H-agonist binding to dopamine receptors

Dopamine modulates metabolic rate and temperature sensitivity in Drosophila melanogaster.

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Taro Ueno

Full Text Available Homeothermal animals, such as mammals, maintain their body temperature by heat generation and heat dissipation, while poikilothermal animals, such as insects, accomplish it by relocating to an environment of their favored temperature. Catecholamines are known to regulate thermogenesis and metabolic rate in mammals, but their roles in other animals are poorly understood. The fruit fly, Drosophila melanogaster, has been used as a model system for the genetic studies of temperature preference behavior. Here, we demonstrate that metabolic rate and temperature sensitivity of some temperature sensitive behaviors are regulated by dopamine in Drosophila. Temperature-sensitive molecules like dTrpA1 and shi(ts induce temperature-dependent behavioral changes, and the temperature at which the changes are induced were lowered in the dopamine transporter-defective mutant, fumin. The mutant also displays a preference for lower temperatures. This thermophobic phenotype was rescued by the genetic recovery of the dopamine transporter in dopamine neurons. Flies fed with a dopamine biosynthesis inhibitor (3-iodo-L-tyrosine, which diminishes dopamine signaling, exhibited preference for a higher temperature. Furthermore, we found that the metabolic rate is up-regulated in the fumin mutant. Taken together, dopamine has functions in the temperature sensitivity of behavioral changes and metabolic rate regulation in Drosophila, as well as its previously reported functions in arousal/sleep regulation.

A model-based spike sorting algorithm for removing correlation artifacts in multi-neuron recordings.

Science.gov (United States)

Pillow, Jonathan W; Shlens, Jonathon; Chichilnisky, E J; Simoncelli, Eero P

2013-01-01

We examine the problem of estimating the spike trains of multiple neurons from voltage traces recorded on one or more extracellular electrodes. Traditional spike-sorting methods rely on thresholding or clustering of recorded signals to identify spikes. While these methods can detect a large fraction of the spikes from a recording, they generally fail to identify synchronous or near-synchronous spikes: cases in which multiple spikes overlap. Here we investigate the geometry of failures in traditional sorting algorithms, and document the prevalence of such errors in multi-electrode recordings from primate retina. We then develop a method for multi-neuron spike sorting using a model that explicitly accounts for the superposition of spike waveforms. We model the recorded voltage traces as a linear combination of spike waveforms plus a stochastic background component of correlated Gaussian noise. Combining this measurement model with a Bernoulli prior over binary spike trains yields a posterior distribution for spikes given the recorded data. We introduce a greedy algorithm to maximize this posterior that we call "binary pursuit". The algorithm allows modest variability in spike waveforms and recovers spike times with higher precision than the voltage sampling rate. This method substantially corrects cross-correlation artifacts that arise with conventional methods, and substantially outperforms clustering methods on both real and simulated data. Finally, we develop diagnostic tools that can be used to assess errors in spike sorting in the absence of ground truth.

Graphitic carbon nitride nanosheets doped graphene oxide for electrochemical simultaneous determination of ascorbic acid, dopamine and uric acid

International Nuclear Information System (INIS)

Zhang, Hanqiang; Huang, Qitong; Huang, Yihong; Li, Feiming; Zhang, Wuxiang; Wei, Chan; Chen, Jianhua; Dai, Pingwang; Huang, Lizhang; Huang, Zhouyi; Kang, Lianping; Hu, Shirong; Hao, Aiyou

2014-01-01

Graphical abstract: Schematic drawing of electrochemical oxidize AA, DA and UA on graphitic carbon nitride nanosheets-graphene oxide composite modified electrode. - Highlights: • Synthesize g-C 3 N 4 , GO and CNNS-GO composite. • CNNS-GO composite was the first time for simultaneous determination of AA, DA and UA. • CNNS-GO/GCE displays fantastic selectivity and sensitivity for AA, DA and UA. • CNNS-GO/GCE was applied to detect real sample with satisfactory results. - Abstract: Graphitic carbon nitride nanosheets with a graphite-like structure have strong covalent bonds between carbon and nitride atoms, and nitrogen atoms in the carbon architecture can accelerate the electron transfer and enhance electrical properties effectually. The graphitic carbon nitride nanosheets-graphene oxide composite was synthesized. And the electrochemical performance of the composite was investigated by cyclic voltammetry and differential pulse voltammetry ulteriorly. Due to the synergistic effects of layer-by-layer structures by π-π stacking or charge-transfer interactions, graphitic carbon nitride nanosheets-graphene oxide composite can improved conductivity, electro-catalytic and selective oxidation performance. The proposed graphitic carbon nitride nanosheets-graphene oxide composite modified electrode was employed for simultaneous determination of ascorbic acid, dopamine and uric acid in their mixture solution, it exhibited distinguished sensitivity, wide linear range and low detection limit. Moreover, the modified electrode was applied to detect urine and dopamine injection sample, and then the samples were spiked with certain concentration of three substances with satisfactory recovery results

Simultaneous detection of ascorbic acid, dopamine, uric acid and tryptophan with Azure A-interlinked multi-walled carbon nanotube/gold nanoparticles composite modified electrode

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Hayati Filik

2016-05-01

Full Text Available In this paper, multi-walled carbon nanotube/Azure A/gold nanoparticle composites (Nafion/AuNPs/AzA/MWCNTs were prepared by binding gold nanoparticles to the surfaces of Azure A-coated carbon nanotubes. Nafion/AuNPs/AzA/MWCNTs based electrochemical sensor was fabricated for the simultaneous determination of ascorbic acid, dopamine, uric acid, and tryptophan. Cyclic voltammetry and electrochemical impedance spectroscopy were used to characterize the electrochemical properties of the modified electrodes. The modified electrode showed excellent electrocatalytic activity toward ascorbic acid, dopamine, uric acid, and tryptophan (pH 7.0. The experiment results showed that the linear response range for simultaneous detection of AA, DA, UA and Trp were 300–10,000 μM, 0.5–50 μM, 0.5–50 μM and 1.0–100 μM, respectively, and the detection limits were 16 μM, 0.014 μM, 0.028 μM and 0.56 μM (S/N = 3. The proposed method offers promise for simple, rapid, selective and cost-effective analysis of small biomolecules. The procedure was also applied to the determination of tryptophan in spiked milk samples.

Dopamine release dynamics change during adolescence and after voluntary alcohol intake.

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Sara Palm

Full Text Available Adolescence is associated with high impulsivity and risk taking, making adolescent individuals more inclined to use drugs. Early drug use is correlated to increased risk for substance use disorders later in life but the neurobiological basis is unclear. The brain undergoes extensive development during adolescence and disturbances at this time are hypothesized to contribute to increased vulnerability. The transition from controlled to compulsive drug use and addiction involve long-lasting changes in neural networks including a shift from the nucleus accumbens, mediating acute reinforcing effects, to recruitment of the dorsal striatum and habit formation. This study aimed to test the hypothesis of increased dopamine release after a pharmacological challenge in adolescent rats. Potassium-evoked dopamine release and uptake was investigated using chronoamperometric dopamine recordings in combination with a challenge by amphetamine in early and late adolescent rats and in adult rats. In addition, the consequences of voluntary alcohol intake during adolescence on these effects were investigated. The data show a gradual increase of evoked dopamine release with age, supporting previous studies suggesting that the pool of releasable dopamine increases with age. In contrast, a gradual decrease in evoked release with age was seen in response to amphetamine, supporting a proportionally larger storage pool of dopamine in younger animals. Dopamine measures after voluntary alcohol intake resulted in lower release amplitudes in response to potassium-chloride, indicating that alcohol affects the releasable pool of dopamine and this may have implications for vulnerability to addiction and other psychiatric diagnoses involving dopamine in the dorsal striatum.

Increased dopamine tone during meditation-induced change of consciousness

DEFF Research Database (Denmark)

Kjaer, Troels W; Bertelsen, Camilla; Piccini, Paola

2002-01-01

This is the first in vivo demonstration of an association between endogenous neurotransmitter release and conscious experience. Using 11C-raclopride PET we demonstrated increased endogenous dopamine release in the ventral striatum during Yoga Nidra meditation. Yoga Nidra is characterized by a dep......This is the first in vivo demonstration of an association between endogenous neurotransmitter release and conscious experience. Using 11C-raclopride PET we demonstrated increased endogenous dopamine release in the ventral striatum during Yoga Nidra meditation. Yoga Nidra is characterized...... the frontal cortex to striatal neurons, which in turn project back to the frontal cortex via the pallidum and ventral thalamus. The present study was designed to investigate whether endogenous dopamine release increases during loss of executive control in meditation. Participants underwent two 11C......-raclopride PET scans: one while attending to speech with eyes closed, and one during active meditation. The tracer competes with endogenous dopamine for access to dopamine D2 receptors predominantly found in the basal ganglia. During meditation, 11C-raclopride binding in ventral striatum decreased by 7...

Inherently stochastic spiking neurons for probabilistic neural computation

KAUST Repository

Al-Shedivat, Maruan

2015-04-01

Neuromorphic engineering aims to design hardware that efficiently mimics neural circuitry and provides the means for emulating and studying neural systems. In this paper, we propose a new memristor-based neuron circuit that uniquely complements the scope of neuron implementations and follows the stochastic spike response model (SRM), which plays a cornerstone role in spike-based probabilistic algorithms. We demonstrate that the switching of the memristor is akin to the stochastic firing of the SRM. Our analysis and simulations show that the proposed neuron circuit satisfies a neural computability condition that enables probabilistic neural sampling and spike-based Bayesian learning and inference. Our findings constitute an important step towards memristive, scalable and efficient stochastic neuromorphic platforms. © 2015 IEEE.

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

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Christian Albers

Full Text Available 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.

Science.gov (United States)

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.

Correlations decrease with propagation of spiking activity in the mouse barrel cortex

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Gayathri Nattar Ranganathan

2011-05-01

Full Text Available Propagation of suprathreshold spiking activity through neuronal populations is important for the function of the central nervous system. Neural correlations have an impact on cortical function particularly on the signaling of information and propagation of spiking activity. Therefore we measured the change in correlations as suprathreshold spiking activity propagated between recurrent neuronal networks of the mammalian cerebral cortex. Using optical methods we recorded spiking activity from large samples of neurons from two neural populations simultaneously. The results indicate that correlations decreased as spiking activity propagated from layer 4 to layer 2/3 in the rodent barrel cortex.

Spike timing-dependent plasticity as the origin of the formation of clustered synaptic efficacy engrams

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Nicolangelo L Iannella

2010-07-01

Full Text Available Synapse location, dendritic active properties and synaptic plasticity are all known to play some role in shaping the different input streams impinging onto a neuron. It remains unclear however, how the magnitude and spatial distribution of synaptic efficacies emerge from this interplay. Here, we investigate this interplay using a biophysically detailed neuron model of a reconstructed layer 2/3 pyramidal cell and spike timing-dependent plasticity (STDP. Specifically, we focus on the issue of how the efficacy of synapses contributed by different input streams are spatially represented in dendrites after STDP learning. We construct a simple feed forward network where a detailed model neuron receives synaptic inputs independently from multiple yet equally sized groups of afferent fibres with correlated activity, mimicking the spike activity from different neuronal populations encoding, for example, different sensory modalities. Interestingly, ensuing STDP learning, we observe that for all afferent groups, STDP leads to synaptic efficacies arranged into spatially segregated clusters effectively partitioning the dendritic tree. These segregated clusters possess a characteristic global organisation in space, where they form a tessellation in which each group dominates mutually exclusive regions of the dendrite.Put simply, the dendritic imprint from different input streams left after STDP learning effectively forms what we term a dendritic efficacy mosaic. Furthermore, we show how variations of the inputs and STDP rule affect such an organization. Our model suggests that STDP may be an important mechanism for creating a clustered plasticity engram, which shapes how different input streams are spatially represented in dendrite.

The treatment of Parkinson's disease with dopamine agonists

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Frank, Wilhelm

2008-06-01

Full Text Available Parkinson’s disease is a chronic degenerative organic disease with unknown causes. A disappearance of cells with melanin in the substantia nigra is considered as biological artefact of the disease, which causes a degenerative loss of neurons in the corpus striatum of mesencephalon. This structure produces also the transmitter substance dopamine. Due to this disappearance of cells dopamine is not produced in a sufficient quantity which is needed for movement of the body. The questions of this report are concerned the efficiency and safety of a treatment with dopamine agonists. Furthermore the cost-effectiveness is investigated as well as ethic questions. The goal is to give recommendation for the use of dopamine agonists to the German health system. A systematic literature search was done. The identified studies have different methodological quality and investigate different hypothesis and different outcome criteria. Therefore a qualitative method of information synthesis was chosen. Since the introduction of L-Dopa in the 1960´s it is considered as the most effective substance to reduce all the cardinal symptoms of Parkinson disease. This substance was improved in the course of time. Firstly some additional substances were given (decarbonxylase inhibitors, catechol-o-transferase inhibitors (COMT-inhibitors, monoaminoxydase-inhibitors (MAO-inhibitors and NMDA-antagonists (N-Methyl-d-aspartat-antagonists. In the practical therapy of Parkinson dopamine agonists play an important role, because they directly use the dopamine receptors. The monotherapy of Parkinson disease is basically possible and is used in early stages of the disease. Clinical practise has shown, that an add on therapy with dopamine agonists can led to a reduction of the dose of L-dopa and a reduction of following dyskinesia. The studies for effectiveness include studies for the initial therapy, monotherapy and add-on-therapy. Basically there is a good effectiveness of dopamine

Dopamine neurons projecting to the posterior striatum form an anatomically distinct subclass

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Menegas, William; Bergan, Joseph F; Ogawa, Sachie K; Isogai, Yoh; Umadevi Venkataraju, Kannan; Osten, Pavel; Uchida, Naoshige; Watabe-Uchida, Mitsuko

2015-01-01

Combining rabies-virus tracing, optical clearing (CLARITY), and whole-brain light-sheet imaging, we mapped the monosynaptic inputs to midbrain dopamine neurons projecting to different targets (different parts of the striatum, cortex, amygdala, etc) in mice. We found that most populations of dopamine neurons receive a similar set of inputs rather than forming strong reciprocal connections with their target areas. A common feature among most populations of dopamine neurons was the existence of dense ‘clusters’ of inputs within the ventral striatum. However, we found that dopamine neurons projecting to the posterior striatum were outliers, receiving relatively few inputs from the ventral striatum and instead receiving more inputs from the globus pallidus, subthalamic nucleus, and zona incerta. These results lay a foundation for understanding the input/output structure of the midbrain dopamine circuit and demonstrate that dopamine neurons projecting to the posterior striatum constitute a unique class of dopamine neurons regulated by different inputs. DOI: http://dx.doi.org/10.7554/eLife.10032.001 PMID:26322384

Diet-induced obesity: dopamine transporter function, impulsivity and motivation.

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Narayanaswami, V; Thompson, A C; Cassis, L A; Bardo, M T; Dwoskin, L P

2013-08-01

A rat model of diet-induced obesity (DIO) was used to determine dopamine transporter (DAT) function, impulsivity and motivation as neurobehavioral outcomes and predictors of obesity. To evaluate neurobehavioral alterations following the development of DIO induced by an 8-week high-fat diet (HF) exposure, striatal D2-receptor density, DAT function and expression, extracellular dopamine concentrations, impulsivity, and motivation for high- and low-fat reinforcers were determined. To determine predictors of DIO, neurobehavioral antecedents including impulsivity, motivation for high-fat reinforcers, DAT function and extracellular dopamine were evaluated before the 8-week HF exposure. Striatal D2-receptor density was determined by in vitro kinetic analysis of [(3)H]raclopride binding. DAT function was determined using in vitro kinetic analysis of [(3)H]dopamine uptake, methamphetamine-evoked [(3)H]dopamine overflow and no-net flux in vivo microdialysis. DAT cell-surface expression was determined using biotinylation and western blotting. Impulsivity and food-motivated behavior were determined using a delay discounting task and progressive ratio schedule, respectively. Relative to obesity-resistant (OR) rats, obesity-prone (OP) rats exhibited 18% greater body weight following an 8-week HF-diet exposure, 42% lower striatal D2-receptor density, 30% lower total DAT expression, 40% lower in vitro and in vivo DAT function, 45% greater extracellular dopamine and twofold greater methamphetamine-evoked [(3)H]dopamine overflow. OP rats exhibited higher motivation for food, and surprisingly, were less impulsive relative to OR rats. Impulsivity, in vivo DAT function and extracellular dopamine concentration did not predict DIO. Importantly, motivation for high-fat reinforcers predicted the development of DIO. Human studies are limited by their ability to determine if impulsivity, motivation and DAT function are causes or consequences of DIO. The current animal model shows that

Could dopamine agonists aid in drug development for anorexia nervosa?

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Frank, Guido K W

2014-01-01

Anorexia nervosa is a severe psychiatric disorder most commonly starting during the teenage-years and associated with food refusal and low body weight. Typically there is a loss of menses, intense fear of gaining weight, and an often delusional quality of altered body perception. Anorexia nervosa is also associated with a pattern of high cognitive rigidity, which may contribute to treatment resistance and relapse. The complex interplay of state and trait biological, psychological, and social factors has complicated identifying neurobiological mechanisms that contribute to the illness. The dopamine D1 and D2 neurotransmitter receptors are involved in motivational aspects of food approach, fear extinction, and cognitive flexibility. They could therefore be important targets to improve core and associated behaviors in anorexia nervosa. Treatment with dopamine antagonists has shown little benefit, and it is possible that antagonists over time increase an already hypersensitive dopamine pathway activity in anorexia nervosa. On the contrary, application of dopamine receptor agonists could reduce circuit responsiveness, facilitate fear extinction, and improve cognitive flexibility in anorexia nervosa, as they may be particularly effective during underweight and low gonadal hormone states. This article provides evidence that the dopamine receptor system could be a key factor in the pathophysiology of anorexia nervosa and dopamine agonists could be helpful in reducing core symptoms of the disorder. This review is a theoretical approach that primarily focuses on dopamine receptor function as this system has been mechanistically better described than other neurotransmitters that are altered in anorexia nervosa. However, those proposed dopamine mechanisms in anorexia nervosa also warrant further study with respect to their interaction with other neurotransmitter systems, such as serotonin pathways.

Could Dopamine Agonists Aid in Drug Development for Anorexia Nervosa?

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Guido eFrank

2014-11-01

Full Text Available Anorexia nervosa is a severe psychiatric disorder most commonly starting during the teenage years and associated with food refusal and low body weight. Typically there is a loss of menses, intense fear of gaining weight and an often delusional quality of altered body perception. Anorexia nervosa is also associated with a pattern of high cognitive rigidity, which may contribute to treatment resistance and relapse. The complex interplay of state and trait biological, psychological and social factors has complicated identifying neurobiological mechanisms that contribute to the illness. The dopamine D1 and D2 neurotransmitter receptors are involved in motivational aspects of food approach, fear extinction and cognitive flexibility. They could therefore be important targets to improve core and associated behaviors in anorexia nervosa. Treatment with dopamine antagonists has shown little benefit, and it is possible that antagonists over time increase an already hypersensitive dopamine pathway activity in anorexia nervosa. On the contrary, application of dopamine receptor agonists could reduce circuit responsiveness, facilitate fear extinction and improve cognitive flexibility in anorexia nervosa, as they may be particularly effective during underweight and low gonadal hormone states. This article provides evidence that the dopamine receptor system could be a key factor in the pathophysiology of anorexia nervosa and dopamine agonists could be helpful in reducing core symptoms of the disorder. This review is a theoretical approach that primarily focuses on dopamine receptor function as this system has been mechanistically better described than other neurotransmitters that are altered in anorexia nervosa. However, those proposed dopamine mechanisms in anorexia nervosa also warrant further study with respect to their interaction with other neurotransmitter systems, such as serotonin pathways.

Could Dopamine Agonists Aid in Drug Development for Anorexia Nervosa?

Science.gov (United States)

Frank, Guido K. W.

2014-01-01

Anorexia nervosa is a severe psychiatric disorder most commonly starting during the teenage-years and associated with food refusal and low body weight. Typically there is a loss of menses, intense fear of gaining weight, and an often delusional quality of altered body perception. Anorexia nervosa is also associated with a pattern of high cognitive rigidity, which may contribute to treatment resistance and relapse. The complex interplay of state and trait biological, psychological, and social factors has complicated identifying neurobiological mechanisms that contribute to the illness. The dopamine D1 and D2 neurotransmitter receptors are involved in motivational aspects of food approach, fear extinction, and cognitive flexibility. They could therefore be important targets to improve core and associated behaviors in anorexia nervosa. Treatment with dopamine antagonists has shown little benefit, and it is possible that antagonists over time increase an already hypersensitive dopamine pathway activity in anorexia nervosa. On the contrary, application of dopamine receptor agonists could reduce circuit responsiveness, facilitate fear extinction, and improve cognitive flexibility in anorexia nervosa, as they may be particularly effective during underweight and low gonadal hormone states. This article provides evidence that the dopamine receptor system could be a key factor in the pathophysiology of anorexia nervosa and dopamine agonists could be helpful in reducing core symptoms of the disorder. This review is a theoretical approach that primarily focuses on dopamine receptor function as this system has been mechanistically better described than other neurotransmitters that are altered in anorexia nervosa. However, those proposed dopamine mechanisms in anorexia nervosa also warrant further study with respect to their interaction with other neurotransmitter systems, such as serotonin pathways. PMID:25988121

Developmental changes in human dopamine neurotransmission: cortical receptors and terminators

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Rothmond Debora A

2012-02-01

Full Text Available Abstract Background Dopamine is integral to cognition, learning and memory, and dysfunctions of the frontal cortical dopamine system have been implicated in several developmental neuropsychiatric disorders. The dorsolateral prefrontal cortex (DLPFC is critical for working memory which does not fully mature until the third decade of life. Few studies have reported on the normal development of the dopamine system in human DLPFC during postnatal life. We assessed pre- and postsynaptic components of the dopamine system including tyrosine hydroxylase, the dopamine receptors (D1, D2 short and D2 long isoforms, D4, D5, catechol-O-methyltransferase, and monoamine oxidase (A and B in the developing human DLPFC (6 weeks -50 years. Results Gene expression was first analysed by microarray and then by quantitative real-time PCR. Protein expression was analysed by western blot. Protein levels for tyrosine hydroxylase peaked during the first year of life (p O-methyltransferase (p = 0.024 were significantly higher in neonates and infants as was catechol-O-methyltransferase protein (32 kDa, p = 0.027. In contrast, dopamine D1 receptor mRNA correlated positively with age (p = 0.002 and dopamine D1 receptor protein expression increased throughout development (p Conclusions We find distinct developmental changes in key components of the dopamine system in DLPFC over postnatal life. Those genes that are highly expressed during the first year of postnatal life may influence and orchestrate the early development of cortical neural circuitry while genes portraying a pattern of increasing expression with age may indicate a role in DLPFC maturation and attainment of adult levels of cognitive function.

Absolute Ca Isotopic Measurement Using an Improved Double Spike Technique

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Jason Jiun-San Shen

2009-01-01

Full Text Available A new vector analytical method has been developed in order to obtain the true isotopic composition of the 42Ca-48Ca double spike. This is achieved by using two different sample-spike mixtures combined with the double spike and natural Ca data. Be cause the natural sample (two mixtures and the spike should all lie on a single mixing line, we are able to con strain the true isotopic composition of our double spike using this new approach. Once the isotopic composition of the Ca double spike is established, we are able to obtain the true Ca isotopic composition of the NIST Ca standard SRM915a, 40Ca/44Ca = 46.537 ± 2 (2sm, n = 55, 42Ca/44Ca = 0.31031 ± 1, 43Ca/44Ca = 0.06474 ± 1, and 48Ca/44Ca = 0.08956 ± 1. De spite an off set of 1.3% in 40Ca/44Ca between our result and the previously re ported value (Russell et al. 1978, our data indicate an off set of 1.89__in 40Ca/44Ca between SRM915a and seawater, entirely consistent with the published results.

Ventral tegmental area dopamine revisited: effects of acute and repeated stress

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Holly, Elizabeth N.; Miczek, Klaus A.

2015-01-01

Aversive events rapidly and potently excite certain dopamine neurons in the ventral tegmental area (VTA), promoting phasic increases in the medial prefrontal cortex and nucleus accumbens. This is in apparent contradiction to a wealth of literature demonstrating that most VTA dopamine neurons are strongly activated by reward and reward-predictive cues while inhibited by aversive stimuli. How can these divergent processes both be mediated by VTA dopamine neurons? The answer may lie within the functional and anatomical heterogeneity of the VTA. We focus on VTA heterogeneity in anatomy, neurochemistry, electrophysiology, and afferent/efferent connectivity. Second, recent evidence for a critical role of VTA dopamine neurons in response to both acute and repeated stress will be discussed. Understanding which dopamine neurons are activated by stress, the neural mechanisms driving the activation, and where these neurons project will provide valuable insight into how stress can promote psychiatric disorders associated with the dopamine system, such as addiction and depression. PMID:26676983

Dopamine-independent locomotor actions of amphetamines in a novel acute mouse model of Parkinson disease.

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2005-08-01

Full Text Available Brain dopamine is critically involved in movement control, and its deficiency is the primary cause of motor symptoms in Parkinson disease. Here we report development of an animal model of acute severe dopamine deficiency by using mice lacking the dopamine transporter. In the absence of transporter-mediated recycling mechanisms, dopamine levels become entirely dependent on de novo synthesis. Acute pharmacological inhibition of dopamine synthesis in these mice induces transient elimination of striatal dopamine accompanied by the development of a striking behavioral phenotype manifested as severe akinesia, rigidity, tremor, and ptosis. This phenotype can be reversed by administration of the dopamine precursor, L-DOPA, or by nonselective dopamine agonists. Surprisingly, several amphetamine derivatives were also effective in reversing these behavioral abnormalities in a dopamine-independent manner. Identification of dopamine transporter- and dopamine-independent locomotor actions of amphetamines suggests a novel paradigm in the search for prospective anti-Parkinsonian drugs.

Introducing Thermal Wave Transport Analysis (TWTA): A Thermal Technique for Dopamine Detection by Screen-Printed Electrodes Functionalized with Molecularly Imprinted Polymer (MIP) Particles.

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Peeters, Marloes M; van Grinsven, Bart; Foster, Christopher W; Cleij, Thomas J; Banks, Craig E

2016-04-26

A novel procedure is developed for producing bulk modified Molecularly Imprinted Polymer (MIP) screen-printed electrodes (SPEs), which involves the direct mixing of the polymer particles within the screen-printed ink. This allowed reduction of the sample preparation time from 45 min to 1 min, and resulted in higher reproducibility of the electrodes. The samples are measured with a novel detection method, namely, thermal wave transport analysis (TWTA), relying on the analysis of thermal waves through a functional interface. As a first proof-of-principle, MIPs for dopamine are developed and successfully incorporated within a bulk modified MIP SPE. The detection limits of dopamine within buffer solutions for the MIP SPEs are determined via three independent techniques. With cyclic voltammetry this was determined to be 4.7 × 10(-6) M, whereas by using the heat-transfer method (HTM) 0.35 × 10(-6) M was obtained, and with the novel TWTA concept 0.26 × 10(-6) M is possible. This TWTA technique is measured simultaneously with HTM and has the benefits of reducing measurement time to less than 5 min and increasing effect size by nearly a factor of two. The two thermal methods are able to enhance dopamine detection by one order of magnitude compared to the electrochemical method. In previous research, it was not possible to measure neurotransmitters in complex samples with HTM, but with the improved signal-to-noise of TWTA for the first time, spiked dopamine concentrations were determined in a relevant food sample. In summary, novel concepts are presented for both the sensor functionalization side by employing screen-printing technology, and on the sensing side, the novel TWTA thermal technique is reported. The developed bio-sensing platform is cost-effective and suitable for mass-production due to the nature of screen-printing technology, which makes it very interesting for neurotransmitter detection in clinical diagnostic applications.

Effect of dopamine, dopamine D-1 and D-2 receptor modulation on ACTH and cortisol levels in normal men and women

DEFF Research Database (Denmark)

Boesgaard, S; Hagen, C; Andersen, A N

1990-01-01

The regulation of the hypothalamic-pituitary-adrenal axis by dopamine is not fully understood. Therefore, we have studied the effect of dopamine, metoclopramide, a D-2 receptor antagonist, and fenoldopam, a specific D-1 receptor agonist, on ACTH and cortisol levels in normal subjects. Normal women...

The Nature of Power Spikes: a regime-switch approach

NARCIS (Netherlands)

C.M. de Jong (Cyriel)

2005-01-01

textabstractDue to its non-storable nature, electricity is a commodity with probably the most volatile spot prices, exemplified by occasional spikes. Appropriate pricing, portfolio, and risk management models have to incorporate these characteristics, and the spikes in particular. We investigate the

A Dopamine Hypothesis of Autism Spectrum Disorder.

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Pavăl, Denis

2017-01-01

Autism spectrum disorder (ASD) comprises a group of neurodevelopmental disorders characterized by social deficits and stereotyped behaviors. While several theories have emerged, the pathogenesis of ASD remains unknown. Although studies report dopamine signaling abnormalities in autistic patients, a coherent dopamine hypothesis which could link neurobiology to behavior in ASD is currently lacking. In this paper, we present such a hypothesis by proposing that autistic behavior arises from dysfunctions in the midbrain dopaminergic system. We hypothesize that a dysfunction of the mesocorticolimbic circuit leads to social deficits, while a dysfunction of the nigrostriatal circuit leads to stereotyped behaviors. Furthermore, we discuss 2 key predictions of our hypothesis, with emphasis on clinical and therapeutic aspects. First, we argue that dopaminergic dysfunctions in the same circuits should associate with autistic-like behavior in nonautistic subjects. Concerning this, we discuss the case of PANDAS (pediatric autoimmune neuropsychiatric disorder associated with streptococcal infections) which displays behaviors similar to those of ASD, presumed to arise from dopaminergic dysfunctions. Second, we argue that providing dopamine modulators to autistic subjects should lead to a behavioral improvement. Regarding this, we present clinical studies of dopamine antagonists which seem to have improving effects on autistic behavior. Furthermore, we explore the means of testing our hypothesis by using neuroreceptor imaging, which could provide comprehensive evidence for dopamine signaling dysfunctions in autistic subjects. Lastly, we discuss the limitations of our hypothesis. Along these lines, we aim to provide a dopaminergic model of ASD which might lead to a better understanding of the ASD pathogenesis. © 2017 S. Karger AG, Basel.

Dopamine therapy does not affect cerebral autoregulation during hypotension in newborn piglets.

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Vibeke Ramsgaard Eriksen

Full Text Available Hypotensive neonates who have been treated with dopamine have poorer neurodevelopmental outcome than those who have not been treated with dopamine. We speculate that dopamine stimulates adrenoceptors on cerebral arteries causing cerebral vasoconstriction. This vasoconstriction might lead to a rightward shift of the cerebral autoregulatory curve; consequently, infants treated with dopamine would have a higher risk of low cerebral blood flow at a blood pressure that is otherwise considered "safe".In anaesthetized piglets, perfusion of the brain, monitored with laser-doppler flowmetry, and cerebral venous saturation was measured at different levels of hypotension. Each piglet was studied in two phases: a phase with stepwise decreases in MAP and a phase with stepwise increases in MAP. We randomized the order of the two phases, whether dopamine was given in the first or second phase, and the infusion rate of dopamine (10, 25, or 40 μg/kg/min. In/deflation of a balloon catheter, placed in vena cava, induced different levels of hypotension. At each level of hypotension, fluctuations in MAP were induced by in/deflations of a balloon catheter in descending aorta.During measurements, PaCO2 and arterial saturation were stable. MAP levels ranged between 14 and 82 mmHg. Cerebral autoregulation (CA capacity was calculated as the ratio between %-change in cerebrovascular resistance and %-change in MAP induced by the in/deflation of the arterial balloon. A breakpoint in CA capacity was identified at a MAP of 38±18 mmHg without dopamine and at 44±18, 31±14, and 24±14 mmHg with dopamine infusion rates of 10, 25, and 40 μg/kg/min (p = 0.057. Neither the index of steady-state cerebral perfusion nor cerebral venous saturation were affected by dopamine infusion.Dopamine infusion tended to improve CA capacity at low blood pressures while an index of steady-state cerebral blood flow and cerebral venous saturation were unaffected by dopamine infusion. Thus

Transcriptome Analysis for Abnormal Spike Development of the Wheat Mutant dms.

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Zhu, Xin-Xin; Li, Qiao-Yun; Shen, Chun-Cai; Duan, Zong-Biao; Yu, Dong-Yan; Niu, Ji-Shan; Ni, Yong-Jing; Jiang, Yu-Mei

2016-01-01

Wheat (Triticum aestivum L.) spike development is the foundation for grain yield. We obtained a novel wheat mutant, dms, characterized as dwarf, multi-pistil and sterility. Although the genetic changes are not clear, the heredity of traits suggests that a recessive gene locus controls the two traits of multi-pistil and sterility in self-pollinating populations of the medium plants (M), such that the dwarf genotype (D) and tall genotype (T) in the progeny of the mutant are ideal lines for studies regarding wheat spike development. The objective of this study was to explore the molecular basis for spike abnormalities of dwarf genotype. Four unigene libraries were assembled by sequencing the mRNAs of the super-bulked differentiating spikes and stem tips of the D and T plants. Using integrative analysis, we identified 419 genes highly expressed in spikes, including nine typical homeotic genes of the MADS-box family and the genes TaAP2, TaFL and TaDL. We also identified 143 genes that were significantly different between young spikes of T and D, and 26 genes that were putatively involved in spike differentiation. The result showed that the expression levels of TaAP1-2, TaAP2, and other genes involved in the majority of biological processes such as transcription, translation, cell division, photosynthesis, carbohydrate transport and metabolism, and energy production and conversion were significantly lower in D than in T. We identified a set of genes related to wheat floral organ differentiation, including typical homeotic genes. Our results showed that the major causal factors resulting in the spike abnormalities of dms were the lower expression homeotic genes, hormonal imbalance, repressed biological processes, and deficiency of construction materials and energy. We performed a series of studies on the homeotic genes, however the other three causal factors for spike abnormal phenotype of dms need further study.

Axonal propagation of simple and complex spikes in cerebellar Purkinje neurons.

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Khaliq, Zayd M; Raman, Indira M

2005-01-12

In cerebellar Purkinje neurons, the reliability of propagation of high-frequency simple spikes and spikelets of complex spikes is likely to regulate inhibition of Purkinje target neurons. To test the extent to which a one-to-one correspondence exists between somatic and axonal spikes, we made dual somatic and axonal recordings from Purkinje neurons in mouse cerebellar slices. Somatic action potentials were recorded with a whole-cell pipette, and the corresponding axonal signals were recorded extracellularly with a loose-patch pipette. Propagation of spontaneous and evoked simple spikes was highly reliable. At somatic firing rates of approximately 200 spikes/sec, 375 Hz during somatic hyperpolarizations that silenced spontaneous firing to approximately 150 Hz during spontaneous activity. The probability of propagation of individual spikelets could be described quantitatively as a saturating function of spikelet amplitude, rate of rise, or preceding interspike interval. The results suggest that ion channels of Purkinje axons are adapted to produce extremely short refractory periods and that brief bursts of forward-propagating action potentials generated by complex spikes may contribute transiently to inhibition of postsynaptic neurons.

Fluid-thermal analysis of aerodynamic heating over spiked blunt body configurations

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Qin, Qihao; Xu, Jinglei; Guo, Shuai

2017-03-01

When flying at hypersonic speeds, the spiked blunt body is constantly subjected to severe aerodynamic heating. To illustrate the thermal response of different configurations and the relevant flow field variation, a loosely-coupled fluid-thermal analysis is performed in this paper. The Mesh-based parallel Code Coupling Interface (MpCCI) is adopted to implement the data exchange between the fluid solver and the thermal solver. The results indicate that increases in spike diameter and length will result in a sharp decline of the wall temperature along the spike, and the overall heat flux is remarkably reduced to less than 300 W/cm2 with the aerodome mounted at the spike tip. Moreover, the presence and evolution of small vortices within the recirculation zone are observed and proved to be induced by the stagnation effect of reattachment points on the spike. In addition, the drag coefficient of the configuration with a doubled spike length presents a maximum drop of 4.59% due to the elevated wall temperature. And the growing difference of the drag coefficient is further increased during the accelerating process.

The chronotron: a neuron that learns to fire temporally precise spike patterns.

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Răzvan V Florian

Full Text Available In many cases, neurons process information carried by the precise timings of spikes. Here we show how neurons can learn to generate specific temporally precise output spikes in response to input patterns of spikes having precise timings, thus processing and memorizing information that is entirely temporally coded, both as input and as output. We introduce two new supervised learning rules for spiking neurons with temporal coding of information (chronotrons, one that provides high memory capacity (E-learning, and one that has a higher biological plausibility (I-learning. With I-learning, the neuron learns to fire the target spike trains through synaptic changes that are proportional to the synaptic currents at the timings of real and target output spikes. We study these learning rules in computer simulations where we train integrate-and-fire neurons. Both learning rules allow neurons to fire at the desired timings, with sub-millisecond precision. We show how chronotrons can learn to classify their inputs, by firing identical, temporally precise spike trains for different inputs belonging to the same class. When the input is noisy, the classification also leads to noise reduction. We compute lower bounds for the memory capacity of chronotrons and explore the influence of various parameters on chronotrons' performance. The chronotrons can model neurons that encode information in the time of the first spike relative to the onset of salient stimuli or neurons in oscillatory networks that encode information in the phases of spikes relative to the background oscillation. Our results show that firing one spike per cycle optimizes memory capacity in neurons encoding information in the phase of firing relative to a background rhythm.

Accelerated spike resampling for accurate multiple testing controls.

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Harrison, Matthew T

2013-02-01

Controlling for multiple hypothesis tests using standard spike resampling techniques often requires prohibitive amounts of computation. Importance sampling techniques can be used to accelerate the computation. The general theory is presented, along with specific examples for testing differences across conditions using permutation tests and for testing pairwise synchrony and precise lagged-correlation between many simultaneously recorded spike trains using interval jitter.

Preparation of (7,8-3H) dopamine

International Nuclear Information System (INIS)

Shen Qiyuan; Tang Guozhong; Guo Zili

1986-01-01

Dopamine is a neurotransmitter in the central nervous system. (7,8- 3 H) dopamine is an important tracer for the study of physiological functions and metabolic processes. It was prepared by catalytic reduction of 3-hydroxy-4-methoxy-8-nitro-styrene with tritium gas. At the end of reaction, hydrobromic acid was added and heated to remove the methoxyl group. The crude product was purified by paper chromatography. The purity of (7,8- 3 H) dopamine was identified by IR, UV, PC and 3 H-NMR spectra. The radiochemical purity was over 95% and the specific activity was 1.26 x 10 12 Bq/mmol (34 Ci/mmol). The distribution of labelled tritium in molecule was shown as follows: 55.4% at position 7 and 44.6% at position 8

An electrochemical dopamine sensor based on the ZnO/CuO nanohybrid structures.

Science.gov (United States)

Khun, K; Ibupoto, Z H; Liu, X; Mansor, N A; Turner, A P F; Beni, V; Willander, M

2014-09-01

The selective detection of dopamine (DA) is of great importance in the modern medicine because dopamine is one of the main regulators in human behaviour. In this study, ZnO/CuO nanohybrid structures, grown on the gold coated glass substrate, have been investigated as a novel electrode material for the electrochemical detection of dopamine. Scanning electron microscopy (SEM), X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS) techniques were used for the material characterization and the obtained results are in good agreement. The selective determination of dopamine was demonstrated by cyclic voltammetry (CV) and amperometric experiments. The amperometric response was linear for dopamine concentrations between 1.0 x 10(-3) and 8.0 mM with a sensitivity of 90.9 μA mM(-1) cm(-2). The proposed dopamine biosensor is very stable, selective over common interferents as glucose, uric acid and ascorbic acid, and also good reproducibility was observed for seven electrodes. Moreover, the dopamine sensor exhibited a fast response time of less than 10 s. The wide range and acceptable sensitivity of the presented dopamine sensor provide the possible application in analysing the dopamine from the real samples.

Perceptron learning rule derived from spike-frequency adaptation and spike-time-dependent plasticity.

Science.gov (United States)

D'Souza, Prashanth; Liu, Shih-Chii; Hahnloser, Richard H R

2010-03-09

It is widely believed that sensory and motor processing in the brain is based on simple computational primitives rooted in cellular and synaptic physiology. However, many gaps remain in our understanding of the connections between neural computations and biophysical properties of neurons. Here, we show that synaptic spike-time-dependent plasticity (STDP) combined with spike-frequency adaptation (SFA) in a single neuron together approximate the well-known perceptron learning rule. Our calculations and integrate-and-fire simulations reveal that delayed inputs to a neuron endowed with STDP and SFA precisely instruct neural responses to earlier arriving inputs. We demonstrate this mechanism on a developmental example of auditory map formation guided by visual inputs, as observed in the external nucleus of the inferior colliculus (ICX) of barn owls. The interplay of SFA and STDP in model ICX neurons precisely transfers the tuning curve from the visual modality onto the auditory modality, demonstrating a useful computation for multimodal and sensory-guided processing.

Real-time computing platform for spiking neurons (RT-spike).

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Ros, Eduardo; Ortigosa, Eva M; Agís, Rodrigo; Carrillo, Richard; Arnold, Michael

2006-07-01

A computing platform is described for simulating arbitrary networks of spiking neurons in real time. A hybrid computing scheme is adopted that uses both software and hardware components to manage the tradeoff between flexibility and computational power; the neuron model is implemented in hardware and the network model and the learning are implemented in software. The incremental transition of the software components into hardware is supported. We focus on a spike response model (SRM) for a neuron where the synapses are modeled as input-driven conductances. The temporal dynamics of the synaptic integration process are modeled with a synaptic time constant that results in a gradual injection of charge. This type of model is computationally expensive and is not easily amenable to existing software-based event-driven approaches. As an alternative we have designed an efficient time-based computing architecture in hardware, where the different stages of the neuron model are processed in parallel. Further improvements occur by computing multiple neurons in parallel using multiple processing units. This design is tested using reconfigurable hardware and its scalability and performance evaluated. Our overall goal is to investigate biologically realistic models for the real-time control of robots operating within closed action-perception loops, and so we evaluate the performance of the system on simulating a model of the cerebellum where the emulation of the temporal dynamics of the synaptic integration process is important.

The Dopamine D2 Receptor Gene in Lamprey, Its Expression in the Striatum and Cellular Effects of D2 Receptor Activation

Science.gov (United States)

Robertson, Brita; Huerta-Ocampo, Icnelia; Ericsson, Jesper; Stephenson-Jones, Marcus; Pérez-Fernández, Juan; Bolam, J. Paul; Diaz-Heijtz, Rochellys; Grillner, Sten

2012-01-01

All basal ganglia subnuclei have recently been identified in lampreys, the phylogenetically oldest group of vertebrates. Furthermore, the interconnectivity of these nuclei is similar to mammals and tyrosine hydroxylase-positive (dopaminergic) fibers have been detected within the input layer, the striatum. Striatal processing is critically dependent on the interplay with the dopamine system, and we explore here whether D2 receptors are expressed in the lamprey striatum and their potential role. We have identified a cDNA encoding the dopamine D2 receptor from the lamprey brain and the deduced protein sequence showed close phylogenetic relationship with other vertebrate D2 receptors, and an almost 100% identity within the transmembrane domains containing the amino acids essential for dopamine binding. There was a strong and distinct expression of D2 receptor mRNA in a subpopulation of striatal neurons, and in the same region tyrosine hydroxylase-immunoreactive synaptic terminals were identified at the ultrastructural level. The synaptic incidence of tyrosine hydroxylase-immunoreactive boutons was highest in a region ventrolateral to the compact layer of striatal neurons, a region where most striatal dendrites arborise. Application of a D2 receptor agonist modulates striatal neurons by causing a reduced spike discharge and a diminished post-inhibitory rebound. We conclude that the D2 receptor gene had already evolved in the earliest group of vertebrates, cyclostomes, when they diverged from the main vertebrate line of evolution (560 mya), and that it is expressed in striatum where it exerts similar cellular effects to that in other vertebrates. These results together with our previous published data (Stephenson-Jones et al. 2011, 2012) further emphasize the high degree of conservation of the basal ganglia, also with regard to the indirect loop, and its role as a basic mechanism for action selection in all vertebrates. PMID:22563388

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

Science.gov (United States)

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

2014-04-02

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

SPAN: spike pattern association neuron for learning spatio-temporal sequences

OpenAIRE

Mohemmed, A; Schliebs, S; Matsuda, S; Kasabov, N

2012-01-01

Spiking Neural Networks (SNN) were shown to be suitable tools for the processing of spatio-temporal information. However, due to their inherent complexity, the formulation of efficient supervised learning algorithms for SNN is difficult and remains an important problem in the research area. This article presents SPAN — a spiking neuron that is able to learn associations of arbitrary spike trains in a supervised fashion allowing the processing of spatio-temporal information encoded in the prec...

A causal link between prediction errors, dopamine neurons and learning.

Science.gov (United States)

Steinberg, Elizabeth E; Keiflin, Ronald; Boivin, Josiah R; Witten, Ilana B; Deisseroth, Karl; Janak, Patricia H

2013-07-01

Situations in which rewards are unexpectedly obtained or withheld represent opportunities for new learning. Often, this learning includes identifying cues that predict reward availability. Unexpected rewards strongly activate midbrain dopamine neurons. This phasic signal is proposed to support learning about antecedent cues by signaling discrepancies between actual and expected outcomes, termed a reward prediction error. However, it is unknown whether dopamine neuron prediction error signaling and cue-reward learning are causally linked. To test this hypothesis, we manipulated dopamine neuron activity in rats in two behavioral procedures, associative blocking and extinction, that illustrate the essential function of prediction errors in learning. We observed that optogenetic activation of dopamine neurons concurrent with reward delivery, mimicking a prediction error, was sufficient to cause long-lasting increases in cue-elicited reward-seeking behavior. Our findings establish a causal role for temporally precise dopamine neuron signaling in cue-reward learning, bridging a critical gap between experimental evidence and influential theoretical frameworks.

Socially isolated rats exhibit changes in dopamine homeostasis pertinent to schizophrenia

DEFF Research Database (Denmark)

Fabricius, Katrine; Steiniger-Brach, Björn; Helboe, Lone

2011-01-01

Post-weaning social isolation of rats produces an array of behavioral and neurochemical changes indicative of altered dopamine function. It has therefore been suggested that post-weaning social isolation mimics some aspects of schizophrenia. Here we replicate and extent these findings to include...... dopamine levels in the nucleus accumbens, it did cause a significant reduction of basal dopamine release in the prefrontal cortex. In addition, social isolation lead to a significantly larger dopamine response to an amphetamine challenge, in both the nucleus accumbens and the prefrontal cortex compared...

Dopamine in the medial amygdala network mediates human bonding.

Science.gov (United States)

Atzil, Shir; Touroutoglou, Alexandra; Rudy, Tali; Salcedo, Stephanie; Feldman, Ruth; Hooker, Jacob M; Dickerson, Bradford C; Catana, Ciprian; Barrett, Lisa Feldman

2017-02-28

Research in humans and nonhuman animals indicates that social affiliation, and particularly maternal bonding, depends on reward circuitry. Although numerous mechanistic studies in rodents demonstrated that maternal bonding depends on striatal dopamine transmission, the neurochemistry supporting maternal behavior in humans has not been described so far. In this study, we tested the role of central dopamine in human bonding. We applied a combined functional MRI-PET scanner to simultaneously probe mothers' dopamine responses to their infants and the connectivity between the nucleus accumbens (NAcc), the amygdala, and the medial prefrontal cortex (mPFC), which form an intrinsic network (referred to as the "medial amygdala network") that supports social functioning. We also measured the mothers' behavioral synchrony with their infants and plasma oxytocin. The results of this study suggest that synchronous maternal behavior is associated with increased dopamine responses to the mother's infant and stronger intrinsic connectivity within the medial amygdala network. Moreover, stronger network connectivity is associated with increased dopamine responses within the network and decreased plasma oxytocin. Together, these data indicate that dopamine is involved in human bonding. Compared with other mammals, humans have an unusually complex social life. The complexity of human bonding cannot be fully captured in nonhuman animal models, particularly in pathological bonding, such as that in autistic spectrum disorder or postpartum depression. Thus, investigations of the neurochemistry of social bonding in humans, for which this study provides initial evidence, are warranted.

Impact of substance P on the correlation of spike train evoked by electro acupuncture

International Nuclear Information System (INIS)

Jin, Chen; Zhang, Xuan; Wang, Jiang; Guo, Yi; Zhao, Xue; Guo, Yong-Ming

2016-01-01

Highlights: • We analyze spike trains induced by EA before and after inhibiting SP in PC6 area. • Inhibiting SP leads to an increase of spiking rate of median nerve. • SP may modulate membrane potential to affect the spiking rate. • SP has an influence on long-range correlation of spike train evoked by EA. • SP play an important role in EA-induced neural spiking and encoding. - Abstract: Substance P (SP) participates in the neural signal transmission evoked by electro-acupuncture (EA). This paper investigates the impact of SP on the correlation of spike train in the median nerve evoked by EA at 'Neiguan' acupoint (PC6). It shows that the spiking rate and interspike interval (ISI) distribution change obviously after inhibiting SP. This variation of spiking activity indicates that SP affects the temporal structure of spike train through modulating the action potential on median nerve filaments. Furtherly, the correlation coefficient and scaling exponent are considered to measure the correlation of spike train. Scaled Windowed Variance (SWV) method is applied to calculate scaling exponent which quantifies the long-range correlation of the neural electrical signals. It is found that the correlation coefficients of ISI increase after inhibiting SP released. In addition, the scaling exponents of neuronal spike train have significant differences between before and after inhibiting SP. These findings demonstrate that SP has an influence on the long-range correlation of spike train. Our results indicate that SP may play an important role in EA-induced neural spiking and encoding.

Dynamic mesolimbic dopamine signaling during action sequence learning and expectation violation

Science.gov (United States)

Collins, Anne L.; Greenfield, Venuz Y.; Bye, Jeffrey K.; Linker, Kay E.; Wang, Alice S.; Wassum, Kate M.

2016-01-01

Prolonged mesolimbic dopamine concentration changes have been detected during spatial navigation, but little is known about the conditions that engender this signaling profile or how it develops with learning. To address this, we monitored dopamine concentration changes in the nucleus accumbens core of rats throughout acquisition and performance of an instrumental action sequence task. Prolonged dopamine concentration changes were detected that ramped up as rats executed each action sequence and declined after earned reward collection. With learning, dopamine concentration began to rise increasingly earlier in the execution of the sequence and ultimately backpropagated away from stereotyped sequence actions, becoming only transiently elevated by the most distal and unexpected reward predictor. Action sequence-related dopamine signaling was reactivated in well-trained rats if they became disengaged in the task and in response to an unexpected change in the value, but not identity of the earned reward. Throughout training and test, dopamine signaling correlated with sequence performance. These results suggest that action sequences can engender a prolonged mode of dopamine signaling in the nucleus accumbens core and that such signaling relates to elements of the motivation underlying sequence execution and is dynamic with learning, overtraining and violations in reward expectation. PMID:26869075

Plasma functionalized surface of commodity polymers for dopamine detection

Energy Technology Data Exchange (ETDEWEB)

Fabregat, Georgina [Departament d’Enginyeria Química, E.T.S. d’Enginyeria Industrial de Barcelona, Universitat Politècnica de Catalunya, Diagonal 647, 08028, Barcelona (Spain); Center for Research in Nano-Engineering, Universitat Politècnica de Catalunya, Campus Sud, Edifici C’, C/Pasqual i Vila s/n, Barcelona, E-08028 (Spain); Osorio, Joaquin [Departament d’Enginyeria Química, E.T.S. d’Enginyeria Industrial de Barcelona, Universitat Politècnica de Catalunya, Diagonal 647, 08028, Barcelona (Spain); Castedo, Alejandra [Center for Research in Nano-Engineering, Universitat Politècnica de Catalunya, Campus Sud, Edifici C’, C/Pasqual i Vila s/n, Barcelona, E-08028 (Spain); Institut de Tècniques Energètiques, E.T.S. d’Enginyeria Industrial de Barcelona, Universitat Politècnica de Catalunya, Diagonal 647, 08028, Barcelona (Spain); Armelin, Elaine [Departament d’Enginyeria Química, E.T.S. d’Enginyeria Industrial de Barcelona, Universitat Politècnica de Catalunya, Diagonal 647, 08028, Barcelona (Spain); Center for Research in Nano-Engineering, Universitat Politècnica de Catalunya, Campus Sud, Edifici C’, C/Pasqual i Vila s/n, Barcelona, E-08028 (Spain); and others

2017-03-31

Highlights: • Electrochemically inert polymers become electroactive after plasma functionalization. • Selective dopamine detection has been achieved functionalizing polymers with plasma. • Plasma-functionalized polymers are sensitive dopamine detectors. • XPS analyses reflect the transformation of inert polymers into electrosensors. - Abstract: We have fabricated potentially generalizable sensors based on polymeric-modified electrodes for the electrochemical detection of dopamine. Sensitive and selective sensors have been successfully obtained by applying a cold-plasma treatment during 1–2 min not only to conducting polymers but also to electrochemically inert polymers, such as polyethylene, polypropylene, polyvinylpyrrolidone, polycaprolactone and polystyrene. The effects of the plasma in the electrode surface activation, which is an essential requirement for the dopamine detection when inert polymers are used, have been investigated using X-ray photoelectron spectroscopy. Results indicate that exposure of polymer-modified electrodes to cold-plasma produces the formation of a large variety of reactive species adsorbed on the electrode surface, which catalyse the dopamine oxidation. With this technology, which is based on the application of a very simple physical functionalization, we have defined a paradox-based paradigm for the fabrication of electrochemical sensors by using inert and cheap plastics.

Robust spike sorting of retinal ganglion cells tuned to spot stimuli.

Science.gov (United States)

Ghahari, Alireza; Badea, Tudor C

2016-08-01

We propose an automatic spike sorting approach for the data recorded from a microelectrode array during visual stimulation of wild type retinas with tiled spot stimuli. The approach first detects individual spikes per electrode by their signature local minima. With the mixture probability distribution of the local minima estimated afterwards, it applies a minimum-squared-error clustering algorithm to sort the spikes into different clusters. A template waveform for each cluster per electrode is defined, and a number of reliability tests are performed on it and its corresponding spikes. Finally, a divisive hierarchical clustering algorithm is used to deal with the correlated templates per cluster type across all the electrodes. According to the measures of performance of the spike sorting approach, it is robust even in the cases of recordings with low signal-to-noise ratio.