A scalable neural chip with synaptic electronics using CMOS integrated memristors

International Nuclear Information System (INIS)

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

2013-01-01

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

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

Science.gov (United States)

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

2017-10-01

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

Memristor-based neural networks: Synaptic versus neuronal stochasticity

KAUST Repository

Naous, Rawan

2016-11-02

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

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

OpenAIRE

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

2015-01-01

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

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

OpenAIRE

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

2015-01-01

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

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

Science.gov (United States)

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

2018-09-01

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

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

Directory of Open Access Journals (Sweden)

Amin Mottahedin

2017-07-01

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

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

Science.gov (United States)

Hutt, Axel; Buhry, Laure

2014-12-01

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

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

Science.gov (United States)

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

2017-08-01

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

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

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Wilfredo Blanco

2017-09-01

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

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

Science.gov (United States)

Ly, Cheng; Marsat, Gary

2018-02-01

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

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

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Srinivasa, Narayan; Cho, Youngkwan

2014-01-01

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

Binocular Rivalry in a Competitive Neural Network with Synaptic Depression

KAUST Repository

Kilpatrick, Zachary P.

2010-01-01

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

Dynamic Control of Synaptic Adhesion and Organizing Molecules in Synaptic Plasticity

Energy Technology Data Exchange (ETDEWEB)

Rudenko, Gabby (Texas-MED)

2017-01-01

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

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

DEFF Research Database (Denmark)

Grinke, Eduard; Tetzlaff, Christian; Wörgötter, Florentin

2015-01-01

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

Self-organised criticality via retro-synaptic signals

Science.gov (United States)

Hernandez-Urbina, Victor; Herrmann, J. Michael

2016-12-01

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

Secreted factors as synaptic organizers.

Science.gov (United States)

Johnson-Venkatesh, Erin M; Umemori, Hisashi

2010-07-01

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

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

International Nuclear Information System (INIS)

Ichiki, Akihisa; Shiino, Masatoshi

2007-01-01

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

Presynaptic Active Zone Density during Development and Synaptic Plasticity.

Science.gov (United States)

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

2012-01-01

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

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

Directory of Open Access Journals (Sweden)

Jianmin Yang

2014-05-01

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

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

Science.gov (United States)

Harsing, Laszlo G; Matyus, Peter

2013-04-01

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

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

Science.gov (United States)

Pérez, Oswaldo; Merchant, Hugo

2018-04-03

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

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

Science.gov (United States)

Schroeder, Anna; de Wit, Joris

2018-04-09

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2015-08-15

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

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

Directory of Open Access Journals (Sweden)

Li Qiang Guo

2015-08-01

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

A Voltage Mode Memristor Bridge Synaptic Circuit with Memristor Emulators

Directory of Open Access Journals (Sweden)

Leon Chua

2012-03-01

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

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

Science.gov (United States)

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

2016-11-09

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

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

Science.gov (United States)

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

2015-09-01

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

Remodeling of the postsynaptic plasma membrane during neural development.

Science.gov (United States)

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

2016-11-07

Neuronal synapses are the fundamental units of neural signal transduction and must maintain exquisite signal fidelity while also accommodating the plasticity that underlies learning and development. To achieve these goals, the molecular composition and spatial organization of synaptic terminals must be tightly regulated; however, little is known about the regulation of lipid composition and organization in synaptic membranes. Here we quantify the comprehensive lipidome of rat synaptic membranes during postnatal development and observe dramatic developmental lipidomic remodeling during the first 60 postnatal days, including progressive accumulation of cholesterol, plasmalogens, and sphingolipids. Further analysis of membranes associated with isolated postsynaptic densities (PSDs) suggests the PSD-associated postsynaptic plasma membrane (PSD-PM) as one specific location of synaptic remodeling. We analyze the biophysical consequences of developmental remodeling in reconstituted synaptic membranes and observe remarkably stable microdomains, with the stability of domains increasing with developmental age. We rationalize the developmental accumulation of microdomain-forming lipids in synapses by proposing a mechanism by which palmitoylation of the immobilized scaffold protein PSD-95 nucleates domains at the postsynaptic plasma membrane. These results reveal developmental changes in lipid composition and palmitoylation that facilitate the formation of postsynaptic membrane microdomains, which may serve key roles in the function of the neuronal synapse. © 2016 Tulodziecka et al. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

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

Science.gov (United States)

Wei, Hui; Bu, Yijie; Dai, Dawei

2017-10-01

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

EDITORIAL: Synaptic electronics Synaptic electronics

Science.gov (United States)

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

2013-09-01

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

Synaptic control of motoneuronal excitability

DEFF Research Database (Denmark)

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

2000-01-01

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

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

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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

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

Science.gov (United States)

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

2008-01-01

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

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

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Jason Tait Sanchez Quinones

2015-01-01

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

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

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Naina Kurup

2017-06-01

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

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

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

2017-08-01

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

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

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Sengupta, Abhronil; Roy, Kaushik

2017-12-01

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

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

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

2015-12-01

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

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

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

2017-11-01

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

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

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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.

Synaptic theory of Replicator-like melioration

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Yonatan Loewenstein

2010-06-01

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

Spike timing analysis in neural networks with unsupervised synaptic plasticity

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

2013-01-01

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

Learning Structure of Sensory Inputs with Synaptic Plasticity Leads to Interference

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Joseph eChrol-Cannon

2015-08-01

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

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

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

2015-05-01

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

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

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Eduard eGrinke

2015-10-01

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

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

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

2018-01-01

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

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

Science.gov (United States)

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

2015-01-01

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

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

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

2012-01-01

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

Hopfield neural network in HEP track reconstruction

International Nuclear Information System (INIS)

Muresan, R.; Pentia, M.

1997-01-01

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

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

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Harish Babu

2009-09-01

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

An Attractive Reelin Gradient Establishes Synaptic Lamination in the Vertebrate Visual System.

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Di Donato, Vincenzo; De Santis, Flavia; Albadri, Shahad; Auer, Thomas Oliver; Duroure, Karine; Charpentier, Marine; Concordet, Jean-Paul; Gebhardt, Christoph; Del Bene, Filippo

2018-03-07

A conserved organizational and functional principle of neural networks is the segregation of axon-dendritic synaptic connections into laminae. Here we report that targeting of synaptic laminae by retinal ganglion cell (RGC) arbors in the vertebrate visual system is regulated by a signaling system relying on target-derived Reelin and VLDLR/Dab1a on the projecting neurons. Furthermore, we find that Reelin is distributed as a gradient on the target tissue and stabilized by heparan sulfate proteoglycans (HSPGs) in the extracellular matrix (ECM). Through genetic manipulations, we show that this Reelin gradient is important for laminar targeting and that it is attractive for RGC axons. Finally, we suggest a comprehensive model of synaptic lamina formation in which attractive Reelin counter-balances repulsive Slit1, thereby guiding RGC axons toward single synaptic laminae. We establish a mechanism that may represent a general principle for neural network assembly in vertebrate species and across different brain areas. Copyright © 2018 Elsevier Inc. All rights reserved.

Optogenetic Examination of Prefrontal-Amygdala Synaptic Development.

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

2017-03-15

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

Lateral regulation of synaptic transmission by astrocytes.

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Covelo, A; Araque, A

2016-05-26

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

Neuro-inspired computing using resistive synaptic devices

CERN Document Server

2017-01-01

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

Active hippocampal networks undergo spontaneous synaptic modification.

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Masako Tsukamoto-Yasui

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

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

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Paula A Garay

2010-09-01

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

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

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

2015-09-15

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

Feedforward inhibition and synaptic scaling--two sides of the same coin?

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Keck, Christian; Savin, Cristina; Lücke, Jörg

2012-01-01

Feedforward inhibition and synaptic scaling are important adaptive processes that control the total input a neuron can receive from its afferents. While often studied in isolation, the two have been reported to co-occur in various brain regions. The functional implications of their interactions remain unclear, however. Based on a probabilistic modeling approach, we show here that fast feedforward inhibition and synaptic scaling interact synergistically during unsupervised learning. In technical terms, we model the input to a neural circuit using a normalized mixture model with Poisson noise. We demonstrate analytically and numerically that, in the presence of lateral inhibition introducing competition between different neurons, Hebbian plasticity and synaptic scaling approximate the optimal maximum likelihood solutions for this model. Our results suggest that, beyond its conventional use as a mechanism to remove undesired pattern variations, input normalization can make typical neural interaction and learning rules optimal on the stimulus subspace defined through feedforward inhibition. Furthermore, learning within this subspace is more efficient in practice, as it helps avoid locally optimal solutions. Our results suggest a close connection between feedforward inhibition and synaptic scaling which may have important functional implications for general cortical processing.

Feedforward inhibition and synaptic scaling--two sides of the same coin?

Directory of Open Access Journals (Sweden)

Christian Keck

Full Text Available Feedforward inhibition and synaptic scaling are important adaptive processes that control the total input a neuron can receive from its afferents. While often studied in isolation, the two have been reported to co-occur in various brain regions. The functional implications of their interactions remain unclear, however. Based on a probabilistic modeling approach, we show here that fast feedforward inhibition and synaptic scaling interact synergistically during unsupervised learning. In technical terms, we model the input to a neural circuit using a normalized mixture model with Poisson noise. We demonstrate analytically and numerically that, in the presence of lateral inhibition introducing competition between different neurons, Hebbian plasticity and synaptic scaling approximate the optimal maximum likelihood solutions for this model. Our results suggest that, beyond its conventional use as a mechanism to remove undesired pattern variations, input normalization can make typical neural interaction and learning rules optimal on the stimulus subspace defined through feedforward inhibition. Furthermore, learning within this subspace is more efficient in practice, as it helps avoid locally optimal solutions. Our results suggest a close connection between feedforward inhibition and synaptic scaling which may have important functional implications for general cortical processing.

Genetic attack on neural cryptography.

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

2006-03-01

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

Genetic attack on neural cryptography

International Nuclear Information System (INIS)

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

2006-01-01

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

Genetic attack on neural cryptography

Science.gov (United States)

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

2006-03-01

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

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

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Gemma de Ramon Francàs

2017-08-01

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

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

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Kyung-Seok Han

2017-01-01

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

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

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

2016-10-01

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

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

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

2017-06-01

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

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

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

2012-10-03

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

Feedforward Inhibition and Synaptic Scaling – Two Sides of the Same Coin?

Science.gov (United States)

Lücke, Jörg

2012-01-01

Feedforward inhibition and synaptic scaling are important adaptive processes that control the total input a neuron can receive from its afferents. While often studied in isolation, the two have been reported to co-occur in various brain regions. The functional implications of their interactions remain unclear, however. Based on a probabilistic modeling approach, we show here that fast feedforward inhibition and synaptic scaling interact synergistically during unsupervised learning. In technical terms, we model the input to a neural circuit using a normalized mixture model with Poisson noise. We demonstrate analytically and numerically that, in the presence of lateral inhibition introducing competition between different neurons, Hebbian plasticity and synaptic scaling approximate the optimal maximum likelihood solutions for this model. Our results suggest that, beyond its conventional use as a mechanism to remove undesired pattern variations, input normalization can make typical neural interaction and learning rules optimal on the stimulus subspace defined through feedforward inhibition. Furthermore, learning within this subspace is more efficient in practice, as it helps avoid locally optimal solutions. Our results suggest a close connection between feedforward inhibition and synaptic scaling which may have important functional implications for general cortical processing. PMID:22457610

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

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Basabdatta Sen Bhattacharya

2016-11-01

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

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

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Hazem eToutounji

2014-05-01

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

Burst firing enhances neural output correlation

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Ho Ka eChan

2016-05-01

Full Text Available Neurons communicate and transmit information predominantly through spikes. Given that experimentally observed neural spike trains in a variety of brain areas can be highly correlated, it is important to investigate how neurons process correlated inputs. Most previous work in this area studied the problem of correlation transfer analytically by making significant simplifications on neural dynamics. Temporal correlation between inputs that arises from synaptic filtering, for instance, is often ignored when assuming that an input spike can at most generate one output spike. Through numerical simulations of a pair of leaky integrate-and-fire (LIF neurons receiving correlated inputs, we demonstrate that neurons in the presence of synaptic filtering by slow synapses exhibit strong output correlations. We then show that burst firing plays a central role in enhancing output correlations, which can explain the above-mentioned observation because synaptic filtering induces bursting. The observed changes of correlations are mostly on a long time scale. Our results suggest that other features affecting the prevalence of neural burst firing in biological neurons, e.g., adaptive spiking mechanisms, may play an important role in modulating the overall level of correlations in neural networks.

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

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

2011-05-19

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

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

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Dobkin Carl

2011-05-01

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

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

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Chih-Chieh Wang

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

Robust short-term memory without synaptic learning.

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Samuel Johnson

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

Robust short-term memory without synaptic learning.

Science.gov (United States)

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

2013-01-01

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

Robust Short-Term Memory without Synaptic Learning

Science.gov (United States)

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

2013-01-01

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

On optical detection of densely labeled synapses in neuropil and mapping connectivity with combinatorially multiplexed fluorescent synaptic markers.

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Yuriy Mishchenko

Full Text Available We propose a new method for mapping neural connectivity optically, by utilizing Cre/Lox system Brainbow to tag synapses of different neurons with random mixtures of different fluorophores, such as GFP, YFP, etc., and then detecting patterns of fluorophores at different synapses using light microscopy (LM. Such patterns will immediately report the pre- and post-synaptic cells at each synaptic connection, without tracing neural projections from individual synapses to corresponding cell bodies. We simulate fluorescence from a population of densely labeled synapses in a block of hippocampal neuropil, completely reconstructed from electron microscopy data, and show that high-end LM is able to detect such patterns with over 95% accuracy. We conclude, therefore, that with the described approach neural connectivity in macroscopically large neural circuits can be mapped with great accuracy, in scalable manner, using fast optical tools, and straightforward image processing. Relying on an electron microscopy dataset, we also derive and explicitly enumerate the conditions that should be met to allow synaptic connectivity studies with high-resolution optical tools.

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

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

2017-06-14

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

Synaptic integration of transplanted interneuron progenitor cells into native cortical networks.

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Howard, MacKenzie A; Baraban, Scott C

2016-08-01

Interneuron-based cell transplantation is a powerful method to modify network function in a variety of neurological disorders, including epilepsy. Whether new interneurons integrate into native neural networks in a subtype-specific manner is not well understood, and the therapeutic mechanisms underlying interneuron-based cell therapy, including the role of synaptic inhibition, are debated. In this study, we tested subtype-specific integration of transplanted interneurons using acute cortical brain slices and visualized patch-clamp recordings to measure excitatory synaptic inputs, intrinsic properties, and inhibitory synaptic outputs. Fluorescently labeled progenitor cells from the embryonic medial ganglionic eminence (MGE) were used for transplantation. At 5 wk after transplantation, MGE-derived parvalbumin-positive (PV+) interneurons received excitatory synaptic inputs, exhibited mature interneuron firing properties, and made functional synaptic inhibitory connections to native pyramidal cells that were comparable to those of native PV+ interneurons. These findings demonstrate that MGE-derived PV+ interneurons functionally integrate into subtype-appropriate physiological niches within host networks following transplantation. Copyright © 2016 the American Physiological Society.

Memristor-based neural networks

International Nuclear Information System (INIS)

Thomas, Andy

2013-01-01

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

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

Directory of Open Access Journals (Sweden)

Dmitry V. Amakhin

2016-10-01

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

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

Science.gov (United States)

Ovtscharoff, Wladimir; Helmeke, Carina; Braun, Katharina

2006-10-20

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

Emulating short-term synaptic dynamics with memristive devices

Science.gov (United States)

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

2016-01-01

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

Does autophagy work in synaptic plasticity and memory?

Science.gov (United States)

Shehata, Mohammad; Inokuchi, Kaoru

2014-01-01

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

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

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DiAntonio Aaron

2007-08-01

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

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

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Christian Tetzlaff

2013-10-01

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

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

Science.gov (United States)

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

2013-10-01

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

Neural principles of memory and a neural theory of analogical insight

Science.gov (United States)

Lawson, David I.; Lawson, Anton E.

1993-12-01

Grossberg's principles of neural modeling are reviewed and extended to provide a neural level theory to explain how analogies greatly increase the rate of learning and can, in fact, make learning and retention possible. In terms of memory, the key point is that the mind is able to recognize and recall when it is able to match sensory input from new objects, events, or situations with past memory records of similar objects, events, or situations. When a match occurs, an adaptive resonance is set up in which the synaptic strengths of neurons are increased; thus a long term record of the new input is formed in memory. Systems of neurons called outstars and instars are presumably the underlying units that enable this to occur. Analogies can greatly facilitate learning and retention because they activate the outstars (i.e., the cells that are sampling the to-be-learned pattern) and cause the neural activity to grow exponentially by forming feedback loops. This increased activity insures the boost in synaptic strengths of neurons, thus causing storage and retention in long-term memory (i.e., learning).

Modular Neural Tile Architecture for Compact Embedded Hardware Spiking Neural Network

NARCIS (Netherlands)

Pande, Sandeep; Morgan, Fearghal; Cawley, Seamus; Bruintjes, Tom; Smit, Gerardus Johannes Maria; McGinley, Brian; Carrillo, Snaider; Harkin, Jim; McDaid, Liam

2013-01-01

Biologically-inspired packet switched network on chip (NoC) based hardware spiking neural network (SNN) architectures have been proposed as an embedded computing platform for classification, estimation and control applications. Storage of large synaptic connectivity (SNN topology) information in

A neural flow estimator

DEFF Research Database (Denmark)

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

1995-01-01

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

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

Science.gov (United States)

Faugeras, Olivier; Touboul, Jonathan; Cessac, Bruno

2009-01-01

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

The epigenetic switches for neural development and psychiatric disorders.

Science.gov (United States)

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

2013-07-20

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

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

DEFF Research Database (Denmark)

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

2010-01-01

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

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

Science.gov (United States)

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

2017-06-20

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

Transformation-invariant visual representations in self-organizing spiking neural networks.

Science.gov (United States)

Evans, Benjamin D; Stringer, Simon M

2012-01-01

The ventral visual pathway achieves object and face recognition by building transformation-invariant representations from elementary visual features. In previous computer simulation studies with rate-coded neural networks, the development of transformation-invariant representations has been demonstrated using either of two biologically plausible learning mechanisms, Trace learning and Continuous Transformation (CT) learning. However, it has not previously been investigated how transformation-invariant representations may be learned in a more biologically accurate spiking neural network. A key issue is how the synaptic connection strengths in such a spiking network might self-organize through Spike-Time Dependent Plasticity (STDP) where the change in synaptic strength is dependent on the relative times of the spikes emitted by the presynaptic and postsynaptic neurons rather than simply correlated activity driving changes in synaptic efficacy. Here we present simulations with conductance-based integrate-and-fire (IF) neurons using a STDP learning rule to address these gaps in our understanding. It is demonstrated that with the appropriate selection of model parameters and training regime, the spiking network model can utilize either Trace-like or CT-like learning mechanisms to achieve transform-invariant representations.

Transform-invariant visual representations in self-organizing spiking neural networks

Directory of Open Access Journals (Sweden)

Benjamin eEvans

2012-07-01

Full Text Available The ventral visual pathway achieves object and face recognition by building transform-invariant representations from elementary visual features. In previous computer simulation studies with rate-coded neural networks, the development of transform invariant representations has been demonstrated using either of two biologically plausible learning mechanisms, Trace learning and Continuous Transformation (CT learning. However, it has not previously been investigated how transform invariant representations may be learned in a more biologically accurate spiking neural network. A key issue is how the synaptic connection strengths in such a spiking network might self-organize through Spike-Time Dependent Plasticity (STDP where the change in synaptic strength is dependent on the relative times of the spikes emitted by the pre- and postsynaptic neurons rather than simply correlated activity driving changes in synaptic efficacy. Here we present simulations with conductance-based integrate-and-fire (IF neurons using a STDP learning rule to address these gaps in our understanding. It is demonstrated that with the appropriate selection of model pa- rameters and training regime, the spiking network model can utilize either Trace-like or CT-like learning mechanisms to achieve transform-invariant representations.

Integrated neuron circuit for implementing neuromorphic system with synaptic device

Science.gov (United States)

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

2018-02-01

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

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

Directory of Open Access Journals (Sweden)

Andrea T. U. Schaefers

2010-01-01

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

Synaptic Cell Adhesion

OpenAIRE

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

2012-01-01

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

Morphological neural networks

Energy Technology Data Exchange (ETDEWEB)

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

1996-12-31

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

Neural network regulation driven by autonomous neural firings

Science.gov (United States)

Cho, Myoung Won

2016-07-01

Biological neurons naturally fire spontaneously due to the existence of a noisy current. Such autonomous firings may provide a driving force for network formation because synaptic connections can be modified due to neural firings. Here, we study the effect of autonomous firings on network formation. For the temporally asymmetric Hebbian learning, bidirectional connections lose their balance easily and become unidirectional ones. Defining the difference between reciprocal connections as new variables, we could express the learning dynamics as if Ising model spins interact with each other in magnetism. We present a theoretical method to estimate the interaction between the new variables in a neural system. We apply the method to some network systems and find some tendencies of autonomous neural network regulation.

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

Science.gov (United States)

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

2018-02-14

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

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

International Nuclear Information System (INIS)

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

2016-01-01

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

Bidirectional control of social hierarchy by synaptic efficacy in medial prefrontal cortex.

Science.gov (United States)

Wang, Fei; Zhu, Jun; Zhu, Hong; Zhang, Qi; Lin, Zhanmin; Hu, Hailan

2011-11-04

Dominance hierarchy has a profound impact on animals' survival, health, and reproductive success, but its neural circuit mechanism is virtually unknown. We found that dominance ranking in mice is transitive, relatively stable, and highly correlates among multiple behavior measures. Recording from layer V pyramidal neurons of the medial prefrontal cortex (mPFC) showed higher strength of excitatory synaptic inputs in mice with higher ranking, as compared with their subordinate cage mates. Furthermore, molecular manipulations that resulted in an increase and decrease in the synaptic efficacy in dorsal mPFC neurons caused an upward and downward movement in the social rank, respectively. These results provide direct evidence for mPFC's involvement in social hierarchy and suggest that social rank is plastic and can be tuned by altering synaptic strength in mPFC pyramidal cells.

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

Science.gov (United States)

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

2017-01-01

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

Plasticity of Hippocampal Excitatory-Inhibitory Balance: Missing the Synaptic Control in the Epileptic Brain

Directory of Open Access Journals (Sweden)

Christian Bonansco

2016-01-01

Full Text Available Synaptic plasticity is the capacity generated by experience to modify the neural function and, thereby, adapt our behaviour. Long-term plasticity of glutamatergic and GABAergic transmission occurs in a concerted manner, finely adjusting the excitatory-inhibitory (E/I balance. Imbalances of E/I function are related to several neurological diseases including epilepsy. Several evidences have demonstrated that astrocytes are able to control the synaptic plasticity, with astrocytes being active partners in synaptic physiology and E/I balance. Here, we revise molecular evidences showing the epileptic stage as an abnormal form of long-term brain plasticity and propose the possible participation of astrocytes to the abnormal increase of glutamatergic and decrease of GABAergic neurotransmission in epileptic networks.

Neuromodulation, development and synaptic plasticity.

Science.gov (United States)

Foehring, R C; Lorenzon, N M

1999-03-01

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

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

Directory of Open Access Journals (Sweden)

Margarita M. Preobrazhenskaia

2017-01-01

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

Statistical theory of synaptic connectivity in the neocortex

Science.gov (United States)

Escobar, Gina

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

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

Science.gov (United States)

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

2013-03-01

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

A framework for plasticity implementation on the SpiNNaker neural architecture.

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

2014-01-01

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

Neural plasticity of development and learning.

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Galván, Adriana

2010-06-01

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

Cocaine Promotes Coincidence Detection and Lowers Induction Threshold during Hebbian Associative Synaptic Potentiation in Prefrontal Cortex.

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Ruan, Hongyu; Yao, Wei-Dong

2017-01-25

Addictive drugs usurp neural plasticity mechanisms that normally serve reward-related learning and memory, primarily by evoking changes in glutamatergic synaptic strength in the mesocorticolimbic dopamine circuitry. Here, we show that repeated cocaine exposure in vivo does not alter synaptic strength in the mouse prefrontal cortex during an early period of withdrawal, but instead modifies a Hebbian quantitative synaptic learning rule by broadening the temporal window and lowers the induction threshold for spike-timing-dependent LTP (t-LTP). After repeated, but not single, daily cocaine injections, t-LTP in layer V pyramidal neurons is induced at +30 ms, a normally ineffective timing interval for t-LTP induction in saline-exposed mice. This cocaine-induced, extended-timing t-LTP lasts for ∼1 week after terminating cocaine and is accompanied by an increased susceptibility to potentiation by fewer pre-post spike pairs, indicating a reduced t-LTP induction threshold. Basal synaptic strength and the maximal attainable t-LTP magnitude remain unchanged after cocaine exposure. We further show that the cocaine facilitation of t-LTP induction is caused by sensitized D1-cAMP/protein kinase A dopamine signaling in pyramidal neurons, which then pathologically recruits voltage-gated l-type Ca 2+ channels that synergize with GluN2A-containing NMDA receptors to drive t-LTP at extended timing. Our results illustrate a mechanism by which cocaine, acting on a key neuromodulation pathway, modifies the coincidence detection window during Hebbian plasticity to facilitate associative synaptic potentiation in prefrontal excitatory circuits. By modifying rules that govern activity-dependent synaptic plasticity, addictive drugs can derail the experience-driven neural circuit remodeling process important for executive control of reward and addiction. It is believed that addictive drugs often render an addict's brain reward system hypersensitive, leaving the individual more susceptible to

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

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Keerthi Thirtamara Rajamani

2018-06-01

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

Spiking neural P systems with multiple channels.

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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.

Can Neural Activity Propagate by Endogenous Electrical Field?

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

2015-01-01

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

Epigenetic Basis of Neuronal and Synaptic Plasticity.

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

2017-01-01

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

Self-organized critical neural networks

International Nuclear Information System (INIS)

Bornholdt, Stefan; Roehl, Torsten

2003-01-01

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

The Roles of Cortical Slow Waves in Synaptic Plasticity and Memory Consolidation.

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Miyamoto, Daisuke; Hirai, Daichi; Murayama, Masanori

2017-01-01

Sleep plays important roles in sensory and motor memory consolidation. Sleep oscillations, reflecting neural population activity, involve the reactivation of learning-related neurons and regulate synaptic strength and, thereby affect memory consolidation. Among sleep oscillations, slow waves (0.5-4 Hz) are closely associated with memory consolidation. For example, slow-wave power is regulated in an experience-dependent manner and correlates with acquired memory. Furthermore, manipulating slow waves can enhance or impair memory consolidation. During slow wave sleep, inter-areal interactions between the cortex and hippocampus (HC) have been proposed to consolidate declarative memory; however, interactions for non-declarative (HC-independent) memory remain largely uninvestigated. We recently showed that the directional influence in a slow-wave range through a top-down cortical long-range circuit is involved in the consolidation of non-declarative memory. At the synaptic level, the average cortical synaptic strength is known to be potentiated during wakefulness and depressed during sleep. Moreover, learning causes plasticity in a subset of synapses, allocating memory to them. Sleep may help to differentiate synaptic strength between allocated and non-allocated synapses (i.e., improving the signal-to-noise ratio, which may facilitate memory consolidation). Herein, we offer perspectives on inter-areal interactions and synaptic plasticity for memory consolidation during sleep.

The Roles of Cortical Slow Waves in Synaptic Plasticity and Memory Consolidation

Directory of Open Access Journals (Sweden)

Daisuke Miyamoto

2017-11-01

Full Text Available Sleep plays important roles in sensory and motor memory consolidation. Sleep oscillations, reflecting neural population activity, involve the reactivation of learning-related neurons and regulate synaptic strength and, thereby affect memory consolidation. Among sleep oscillations, slow waves (0.5–4 Hz are closely associated with memory consolidation. For example, slow-wave power is regulated in an experience-dependent manner and correlates with acquired memory. Furthermore, manipulating slow waves can enhance or impair memory consolidation. During slow wave sleep, inter-areal interactions between the cortex and hippocampus (HC have been proposed to consolidate declarative memory; however, interactions for non-declarative (HC-independent memory remain largely uninvestigated. We recently showed that the directional influence in a slow-wave range through a top-down cortical long-range circuit is involved in the consolidation of non-declarative memory. At the synaptic level, the average cortical synaptic strength is known to be potentiated during wakefulness and depressed during sleep. Moreover, learning causes plasticity in a subset of synapses, allocating memory to them. Sleep may help to differentiate synaptic strength between allocated and non-allocated synapses (i.e., improving the signal-to-noise ratio, which may facilitate memory consolidation. Herein, we offer perspectives on inter-areal interactions and synaptic plasticity for memory consolidation during sleep.

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

Science.gov (United States)

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

2013-01-01

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

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

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Tao Tan

2018-02-01

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

Gamma Oscillations and Neural Field DCMs Can Reveal Cortical Excitability and Microstructure

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Dimitris Pinotsis

2014-05-01

Full Text Available This paper shows how gamma oscillations can be combined with neural population models and dynamic causal modeling (DCM to distinguish among alternative hypotheses regarding cortical excitability and microstructure. This approach exploits inter-subject variability and trial-specific effects associated with modulations in the peak frequency of gamma oscillations. Neural field models are used to evaluate model evidence and obtain parameter estimates using invasive and non-invasive gamma recordings. Our overview comprises two parts: in the first part, we use neural fields to simulate neural activity and distinguish the effects of post synaptic filtering on predicted responses in terms of synaptic rate constants that correspond to different timescales and distinct neurotransmitters. We focus on model predictions of conductance and convolution based field models and show that these can yield spectral responses that are sensitive to biophysical properties of local cortical circuits like synaptic kinetics and filtering; we also consider two different mechanisms for this filtering: a nonlinear mechanism involving specific conductances and a linear convolution of afferent firing rates producing post synaptic potentials. In the second part of this paper, we use neural fields quantitatively—to fit empirical data recorded during visual stimulation. We present two studies of spectral responses obtained from the visual cortex during visual perception experiments: in the first study, MEG data were acquired during a task designed to show how activity in the gamma band is related to visual perception, while in the second study, we exploited high density electrocorticographic (ECoG data to study the effect of varying stimulus contrast on cortical excitability and gamma peak frequency.

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

OpenAIRE

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

2014-01-01

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

Diversity of bilateral synaptic assemblies for binaural computation in midbrain single neurons.

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He, Na; Kong, Lingzhi; Lin, Tao; Wang, Shaohui; Liu, Xiuping; Qi, Jiyao; Yan, Jun

2017-11-01

Binaural hearing confers many beneficial functions but our understanding of its underlying neural substrates is limited. This study examines the bilateral synaptic assemblies and binaural computation (or integration) in the central nucleus of the inferior colliculus (ICc) of the auditory midbrain, a key convergent center. Using in-vivo whole-cell patch-clamp, the excitatory and inhibitory postsynaptic potentials (EPSPs/IPSPs) of single ICc neurons to contralateral, ipsilateral and bilateral stimulation were recorded. According to the contralateral and ipsilateral EPSP/IPSP, 7 types of bilateral synaptic assemblies were identified. These include EPSP-EPSP (EE), E-IPSP (EI), E-no response (EO), II, IE, IO and complex-mode (CM) neurons. The CM neurons showed frequency- and/or amplitude-dependent EPSPs/IPSPs to contralateral or ipsilateral stimulation. Bilateral stimulation induced EPSPs/IPSPs that could be larger than (facilitation), similar to (ineffectiveness) or smaller than (suppression) those induced by contralateral stimulation. Our findings have allowed our group to characterize novel neural circuitry for binaural computation in the midbrain. Copyright © 2017 Elsevier B.V. All rights reserved.

Temporal and spatial expression of Drosophila DLGS97 during neural development.

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

2008-07-01

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

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

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Bailey, Craig H; Kandel, Eric R

2008-01-01

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

Precise synaptic efficacy alignment suggests potentiation dominated learning

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Christoph eHartmann

2016-01-01

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

Designing neural networks that process mean values of random variables

International Nuclear Information System (INIS)

Barber, Michael J.; Clark, John W.

2014-01-01

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

Designing neural networks that process mean values of random variables

Energy Technology Data Exchange (ETDEWEB)

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

2014-06-13

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

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

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Lin Lin

2018-03-01

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

The super-Turing computational power of plastic recurrent neural networks.

Science.gov (United States)

Cabessa, Jérémie; Siegelmann, Hava T

2014-12-01

We study the computational capabilities of a biologically inspired neural model where the synaptic weights, the connectivity pattern, and the number of neurons can evolve over time rather than stay static. Our study focuses on the mere concept of plasticity of the model so that the nature of the updates is assumed to be not constrained. In this context, we show that the so-called plastic recurrent neural networks (RNNs) are capable of the precise super-Turing computational power--as the static analog neural networks--irrespective of whether their synaptic weights are modeled by rational or real numbers, and moreover, irrespective of whether their patterns of plasticity are restricted to bi-valued updates or expressed by any other more general form of updating. Consequently, the incorporation of only bi-valued plastic capabilities in a basic model of RNNs suffices to break the Turing barrier and achieve the super-Turing level of computation. The consideration of more general mechanisms of architectural plasticity or of real synaptic weights does not further increase the capabilities of the networks. These results support the claim that the general mechanism of plasticity is crucially involved in the computational and dynamical capabilities of biological neural networks. They further show that the super-Turing level of computation reflects in a suitable way the capabilities of brain-like models of computation.

Amine Neurotransmitter Regulation of Long-Term Synaptic Plasticity in Hippocampus.

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1987-04-27

T.H. ontrol theory applied to neural networks illuminates synaptic basis of interictal epileptiform activity. In: Basic Mechanimw of the Epilepsies...the activity of voltage-dqmxfdm* calcium dwas in hixocaupal nerone . Nature (in press). atecir.U P. A., pebeda,# F. J., a nd Jduutoni, D. 4...Annual Synposium on Networks in Brain and ompiter Arhitecture at North Texas State University in Denton. Oct. 22-25 Attended Neurdehavioral Research

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

OpenAIRE

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

2015-01-01

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

Goal-seeking neural net for recall and recognition

Science.gov (United States)

Omidvar, Omid M.

1990-07-01

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

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

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

2017-11-01

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

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

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Wei Ling Lim

2016-08-01

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

Birth order dependent growth cone segregation determines synaptic layer identity in the Drosophila visual system.

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Kulkarni, Abhishek; Ertekin, Deniz; Lee, Chi-Hon; Hummel, Thomas

2016-03-17

The precise recognition of appropriate synaptic partner neurons is a critical step during neural circuit assembly. However, little is known about the developmental context in which recognition specificity is important to establish synaptic contacts. We show that in the Drosophila visual system, sequential segregation of photoreceptor afferents, reflecting their birth order, lead to differential positioning of their growth cones in the early target region. By combining loss- and gain-of-function analyses we demonstrate that relative differences in the expression of the transcription factor Sequoia regulate R cell growth cone segregation. This initial growth cone positioning is consolidated via cell-adhesion molecule Capricious in R8 axons. Further, we show that the initial growth cone positioning determines synaptic layer selection through proximity-based axon-target interactions. Taken together, we demonstrate that birth order dependent pre-patterning of afferent growth cones is an essential pre-requisite for the identification of synaptic partner neurons during visual map formation in Drosophila.

Biophysical synaptic dynamics in an analog VLSI network of Hodgkin-Huxley neurons.

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Yu, Theodore; Cauwenberghs, Gert

2009-01-01

We study synaptic dynamics in a biophysical network of four coupled spiking neurons implemented in an analog VLSI silicon microchip. The four neurons implement a generalized Hodgkin-Huxley model with individually configurable rate-based kinetics of opening and closing of Na+ and K+ ion channels. The twelve synapses implement a rate-based first-order kinetic model of neurotransmitter and receptor dynamics, accounting for NMDA and non-NMDA type chemical synapses. The implemented models on the chip are fully configurable by 384 parameters accounting for conductances, reversal potentials, and pre/post-synaptic voltage-dependence of the channel kinetics. We describe the models and present experimental results from the chip characterizing single neuron dynamics, single synapse dynamics, and multi-neuron network dynamics showing phase-locking behavior as a function of synaptic coupling strength. The 3mm x 3mm microchip consumes 1.29 mW power making it promising for applications including neuromorphic modeling and neural prostheses.

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

Institute of Scientific and Technical Information of China (English)

Hui YU; Zhe-yu CHEN

2011-01-01

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

Evolving networks and the development of neural systems

International Nuclear Information System (INIS)

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

2010-01-01

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

Synaptic molecular imaging in spared and deprived columns of mouse barrel cortex with array tomography.

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Weiler, Nicholas C; Collman, Forrest; Vogelstein, Joshua T; Burns, Randal; Smith, Stephen J

2014-01-01

A major question in neuroscience is how diverse subsets of synaptic connections in neural circuits are affected by experience dependent plasticity to form the basis for behavioral learning and memory. Differences in protein expression patterns at individual synapses could constitute a key to understanding both synaptic diversity and the effects of plasticity at different synapse populations. Our approach to this question leverages the immunohistochemical multiplexing capability of array tomography (ATomo) and the columnar organization of mouse barrel cortex to create a dataset comprising high resolution volumetric images of spared and deprived cortical whisker barrels stained for over a dozen synaptic molecules each. These dataset has been made available through the Open Connectome Project for interactive online viewing, and may also be downloaded for offline analysis using web, Matlab, and other interfaces.

Realization of synaptic learning and memory functions in Y2O3 based memristive device fabricated by dual ion beam sputtering

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Das, Mangal; Kumar, Amitesh; Singh, Rohit; Than Htay, Myo; Mukherjee, Shaibal

2018-02-01

Single synaptic device with inherent learning and memory functions is demonstrated based on a forming-free amorphous Y2O3 (yttria) memristor fabricated by dual ion beam sputtering system. Synaptic functions such as nonlinear transmission characteristics, long-term plasticity, short-term plasticity and ‘learning behavior (LB)’ are achieved using a single synaptic device based on cost-effective metal-insulator-semiconductor (MIS) structure. An ‘LB’ function is demonstrated, for the first time in the literature, for a yttria based memristor, which bears a resemblance to certain memory functions of biological systems. The realization of key synaptic functions in a cost-effective MIS structure would promote much cheaper synapse for artificial neural network.

Bio-mimicked atomic-layer-deposited iron oxide-based memristor with synaptic potentiation and depression functions

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Wan, Xiang; Gao, Fei; Lian, Xiaojuan; Ji, Xincun; Hu, Ertao; He, Lin; Tong, Yi; Guo, Yufeng

2018-06-01

In this study, an iron oxide (FeO x )-based memristor was investigated for the realization of artificial synapses. An FeO x resistive switching layer was prepared by self-limiting atomic layer deposition (ALD). The movement of oxygen vacancies enabled the device to have history-dependent synaptic functions, which was further demonstrated by device modeling and simulation. Analog synaptic potentiation/depression in conductance was emulated by applying consecutive voltage pulses in the simulation. Our results suggest that the ALD FeO x -based memristor can be used as the basic building block for neural networks, neuromorphic systems, and brain-inspired computers.

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

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Turney, Stephen G; Lichtman, Jeff W

2012-01-01

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

Forebrain deletion of αGDI in adult mice worsens the pre-synaptic deficit at cortico-lateral amygdala synaptic connections.

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Veronica Bianchi

Full Text Available The GDI1 gene encodes αGDI, which retrieves inactive GDP-bound RAB from membranes to form a cytosolic pool awaiting vesicular release. Mutations in GDI1 are responsible for X-linked Intellectual Disability. Characterization of the Gdi1-null mice has revealed alterations in the total number and distribution of hippocampal and cortical synaptic vesicles, hippocampal short-term synaptic plasticity and specific short-term memory deficits in adult mice, which are possibly caused by alterations of different synaptic vesicle recycling pathways controlled by several RAB GTPases. However, interpretation of these studies is complicated by the complete ablation of Gdi1 in all cells in the brain throughout development. In this study, we generated conditionally gene-targeted mice in which the knockout of Gdi1 is restricted to the forebrain, hippocampus, cortex and amygdala and occurs only during postnatal development. Adult mutant mice reproduce the short-term memory deficit previously reported in Gdi1-null mice. Surprisingly, the delayed ablation of Gdi1 worsens the pre-synaptic phenotype at cortico-amygdala synaptic connections compared to Gdi1-null mice. These results suggest a pivotal role of αGDI via specific RAB GTPases acting specifically in forebrain regions at the pre-synaptic sites involved in memory formation.

Evolution of the aging brain transcriptome and synaptic regulation.

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Patrick M Loerch

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

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

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

2017-12-01

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

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

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

2014-01-01

Phrenic motor neurons receive rhythmic synaptic inputs throughout life. Since even brief disruption in phrenic neural activity is detrimental to life, on-going neural activity may play a key role in shaping phrenic motor output. To test the hypothesis that spinal mechanisms sense and respond to reduced phrenic activity, anesthetized, ventilated rats received micro-injections of procaine in the C2 ventrolateral funiculus (VLF) to transiently (~30 min) block axon conduction in bulbospinal axons from medullary respiratory neurons that innervate one phrenic motor pool; during procaine injections, contralateral phrenic neural activity was maintained. Once axon conduction resumed, a prolonged increase in phrenic burst amplitude was observed in the ipsilateral phrenic nerve, demonstrating inactivity-induced phrenic motor facilitation (iPMF). Inhibition of tumor necrosis factor alpha (TNFα) and atypical PKC (aPKC) activity in spinal segments containing the phrenic motor nucleus impaired ipsilateral iPMF, suggesting a key role for spinal TNFα and aPKC in iPMF following unilateral axon conduction block. A small phrenic burst amplitude facilitation was also observed contralateral to axon conduction block, indicating crossed spinal phrenic motor facilitation (csPMF). csPMF was independent of spinal TNFα and aPKC. Ipsilateral iPMF and csPMF following unilateral withdrawal of phrenic synaptic inputs were associated with proportional increases in phrenic responses to chemoreceptor stimulation (hypercapnia), suggesting iPMF and csPMF increase phrenic dynamic range. These data suggest that local, spinal mechanisms sense and respond to reduced synaptic inputs to phrenic motor neurons. We hypothesize that iPMF and csPMF may represent compensatory mechanisms that assure adequate motor output is maintained in a physiological system in which prolonged inactivity ends life. PMID:24681155

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

Directory of Open Access Journals (Sweden)

Stephen G Turney

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

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

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

2017-03-01

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

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

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Beier, Corinne; Palanker, Daniel; Sher, Alexander

2018-06-04

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

Fragile X mental retardation protein regulates trans-synaptic signaling in Drosophila

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Samuel H. Friedman

2013-11-01

Fragile X syndrome (FXS, the most common inherited determinant of intellectual disability and autism spectrum disorders, is caused by loss of the fragile X mental retardation 1 (FMR1 gene product (FMRP, an mRNA-binding translational repressor. A number of conserved FMRP targets have been identified in the well-characterized Drosophila FXS disease model, but FMRP is highly pleiotropic in function and the full spectrum of FMRP targets has yet to be revealed. In this study, screens for upregulated neural proteins in Drosophila fmr1 (dfmr1 null mutants reveal strong elevation of two synaptic heparan sulfate proteoglycans (HSPGs: GPI-anchored glypican Dally-like protein (Dlp and transmembrane Syndecan (Sdc. Our recent work has shown that Dlp and Sdc act as co-receptors regulating extracellular ligands upstream of intracellular signal transduction in multiple trans-synaptic pathways that drive synaptogenesis. Consistently, dfmr1 null synapses exhibit altered WNT signaling, with changes in both Wingless (Wg ligand abundance and downstream Frizzled-2 (Fz2 receptor C-terminal nuclear import. Similarly, a parallel anterograde signaling ligand, Jelly belly (Jeb, and downstream ERK phosphorylation (dpERK are depressed at dfmr1 null synapses. In contrast, the retrograde BMP ligand Glass bottom boat (Gbb and downstream signaling via phosphorylation of the transcription factor MAD (pMAD seem not to be affected. To determine whether HSPG upregulation is causative for synaptogenic defects, HSPGs were genetically reduced to control levels in the dfmr1 null background. HSPG correction restored both (1 Wg and Jeb trans-synaptic signaling, and (2 synaptic architecture and transmission strength back to wild-type levels. Taken together, these data suggest that FMRP negatively regulates HSPG co-receptors controlling trans-synaptic signaling during synaptogenesis, and that loss of this regulation causes synaptic structure and function defects characterizing the FXS disease state.

Synaptic proteome changes in the superior frontal gyrus and occipital cortex of the alcoholic brain.

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Etheridge, Naomi; Lewohl, Joanne M; Mayfield, R Dayne; Harris, R Adron; Dodd, Peter R

2009-06-24

Cognitive deficits and behavioral changes that result from chronic alcohol abuse are a consequence of neuropathological changes which alter signal transmission through the neural network. To focus on the changes that occur at the point of connection between the neural network cells, synaptosomal preparations from post-mortem human brain of six chronic alcoholics and six non-alcoholic controls were compared using 2D-DIGE. Functionally affected and spared regions (superior frontal gyrus, SFG, and occipital cortex, OC, respectively) were analyzed from both groups to further investigate the specific pathological response that alcoholism has on the brain. Forty-nine proteins were differentially regulated between the SFG of alcoholics and the SFG of controls and 94 proteins were regulated in the OC with an overlap of 23 proteins. Additionally, the SFG was compared to the OC within each group (alcoholics or controls) to identify region specific differences. A selection were identified by MALDI-TOF mass spectrometry revealing proteins involved in vesicle transport, metabolism, folding and trafficking, and signal transduction, all of which have the potential to influence synaptic activity. A number of proteins identified in this study have been previously related to alcoholism; however, the focus on synaptic proteins has also uncovered novel alcoholism-affected proteins. Further exploration of these proteins will illuminate the mechanisms altering synaptic plasticity, and thus neuronal signaling and response, in the alcoholic brain.

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

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Owen Rackham

2010-07-01

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

"The seven sins" of the Hebbian synapse: can the hypothesis of synaptic plasticity explain long-term memory consolidation?

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Arshavsky, Yuri I

2006-10-01

Memorizing new facts and events means that entering information produces specific physical changes within the brain. According to the commonly accepted view, traces of memory are stored through the structural modifications of synaptic connections, which result in changes of synaptic efficiency and, therefore, in formations of new patterns of neural activity (the hypothesis of synaptic plasticity). Most of the current knowledge on learning and initial stages of memory consolidation ("synaptic consolidation") is based on this hypothesis. However, the hypothesis of synaptic plasticity faces a number of conceptual and experimental difficulties when it deals with potentially permanent consolidation of declarative memory ("system consolidation"). These difficulties are rooted in the major intrinsic self-contradiction of the hypothesis: stable declarative memory is unlikely to be based on such a non-stable foundation as synaptic plasticity. Memory that can last throughout an entire lifespan should be "etched in stone." The only "stone-like" molecules within living cells are DNA molecules. Therefore, I advocate an alternative, genomic hypothesis of memory, which suggests that acquired information is persistently stored within individual neurons through modifications of DNA, and that these modifications serve as the carriers of elementary memory traces.

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

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Baertsch, Nathan A; Baker-Herman, Tracy L

2015-04-15

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

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

DEFF Research Database (Denmark)

Secher, Thomas; Novitskaia, V; Berezin, Vladimir

2006-01-01

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

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

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

2018-02-01

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

Metabolic Turnover of Synaptic Proteins: Kinetics, Interdependencies and Implications for Synaptic Maintenance

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Cohen, Laurie D.; Zuchman, Rina; Sorokina, Oksana; Müller, Anke; Dieterich, Daniela C.; Armstrong, J. Douglas; Ziv, Tamar; Ziv, Noam E.

2013-01-01

Chemical synapses contain multitudes of proteins, which in common with all proteins, have finite lifetimes and therefore need to be continuously replaced. Given the huge numbers of synaptic connections typical neurons form, the demand to maintain the protein contents of these connections might be expected to place considerable metabolic demands on each neuron. Moreover, synaptic proteostasis might differ according to distance from global protein synthesis sites, the availability of distributed protein synthesis facilities, trafficking rates and synaptic protein dynamics. To date, the turnover kinetics of synaptic proteins have not been studied or analyzed systematically, and thus metabolic demands or the aforementioned relationships remain largely unknown. In the current study we used dynamic Stable Isotope Labeling with Amino acids in Cell culture (SILAC), mass spectrometry (MS), Fluorescent Non–Canonical Amino acid Tagging (FUNCAT), quantitative immunohistochemistry and bioinformatics to systematically measure the metabolic half-lives of hundreds of synaptic proteins, examine how these depend on their pre/postsynaptic affiliation or their association with particular molecular complexes, and assess the metabolic load of synaptic proteostasis. We found that nearly all synaptic proteins identified here exhibited half-lifetimes in the range of 2–5 days. Unexpectedly, metabolic turnover rates were not significantly different for presynaptic and postsynaptic proteins, or for proteins for which mRNAs are consistently found in dendrites. Some functionally or structurally related proteins exhibited very similar turnover rates, indicating that their biogenesis and degradation might be coupled, a possibility further supported by bioinformatics-based analyses. The relatively low turnover rates measured here (∼0.7% of synaptic protein content per hour) are in good agreement with imaging-based studies of synaptic protein trafficking, yet indicate that the metabolic load

Optical implementation of neural learning algorithms based on cross-gain modulation in a semiconductor optical amplifier

Science.gov (United States)

Li, Qiang; Wang, Zhi; Le, Yansi; Sun, Chonghui; Song, Xiaojia; Wu, Chongqing

2016-10-01

Neuromorphic engineering has a wide range of applications in the fields of machine learning, pattern recognition, adaptive control, etc. Photonics, characterized by its high speed, wide bandwidth, low power consumption and massive parallelism, is an ideal way to realize ultrafast spiking neural networks (SNNs). Synaptic plasticity is believed to be critical for learning, memory and development in neural circuits. Experimental results have shown that changes of synapse are highly dependent on the relative timing of pre- and postsynaptic spikes. Synaptic plasticity in which presynaptic spikes preceding postsynaptic spikes results in strengthening, while the opposite timing results in weakening is called antisymmetric spike-timing-dependent plasticity (STDP) learning rule. And synaptic plasticity has the opposite effect under the same conditions is called antisymmetric anti-STDP learning rule. We proposed and experimentally demonstrated an optical implementation of neural learning algorithms, which can achieve both of antisymmetric STDP and anti-STDP learning rule, based on the cross-gain modulation (XGM) within a single semiconductor optical amplifier (SOA). The weight and height of the potentitation and depression window can be controlled by adjusting the injection current of the SOA, to mimic the biological antisymmetric STDP and anti-STDP learning rule more realistically. As the injection current increases, the width of depression and potentitation window decreases and height increases, due to the decreasing of recovery time and increasing of gain under a stronger injection current. Based on the demonstrated optical STDP circuit, ultrafast learning in optical SNNs can be realized.

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

Science.gov (United States)

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

2012-01-01

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

The Roles of Cortical Slow Waves in Synaptic Plasticity and Memory Consolidation

OpenAIRE

Miyamoto, Daisuke; Hirai, Daichi; Murayama, Masanori

2017-01-01

Sleep plays important roles in sensory and motor memory consolidation. Sleep oscillations, reflecting neural population activity, involve the reactivation of learning-related neurons and regulate synaptic strength and, thereby affect memory consolidation. Among sleep oscillations, slow waves (0.5–4 Hz) are closely associated with memory consolidation. For example, slow-wave power is regulated in an experience-dependent manner and correlates with acquired memory. Furthermore, manipulating slow...

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

Science.gov (United States)

Streeter, K A; Baker-Herman, T L

2014-06-01

Phrenic motor neurons receive rhythmic synaptic inputs throughout life. Since even brief disruption in phrenic neural activity is detrimental to life, on-going neural activity may play a key role in shaping phrenic motor output. To test the hypothesis that spinal mechanisms sense and respond to reduced phrenic activity, anesthetized, ventilated rats received micro-injections of procaine in the C2 ventrolateral funiculus (VLF) to transiently (~30min) block axon conduction in bulbospinal axons from medullary respiratory neurons that innervate one phrenic motor pool; during procaine injections, contralateral phrenic neural activity was maintained. Once axon conduction resumed, a prolonged increase in phrenic burst amplitude was observed in the ipsilateral phrenic nerve, demonstrating inactivity-induced phrenic motor facilitation (iPMF). Inhibition of tumor necrosis factor alpha (TNFα) and atypical PKC (aPKC) activity in spinal segments containing the phrenic motor nucleus impaired ipsilateral iPMF, suggesting a key role for spinal TNFα and aPKC in iPMF following unilateral axon conduction block. A small phrenic burst amplitude facilitation was also observed contralateral to axon conduction block, indicating crossed spinal phrenic motor facilitation (csPMF). csPMF was independent of spinal TNFα and aPKC. Ipsilateral iPMF and csPMF following unilateral withdrawal of phrenic synaptic inputs were associated with proportional increases in phrenic responses to chemoreceptor stimulation (hypercapnia), suggesting iPMF and csPMF increase phrenic dynamic range. These data suggest that local, spinal mechanisms sense and respond to reduced synaptic inputs to phrenic motor neurons. We hypothesize that iPMF and csPMF may represent compensatory mechanisms that assure adequate motor output is maintained in a physiological system in which prolonged inactivity ends life. Copyright © 2014 Elsevier Inc. All rights reserved.

Death and rebirth of neural activity in sparse inhibitory networks

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Angulo-Garcia, David; Luccioli, Stefano; Olmi, Simona; Torcini, Alessandro

2017-05-01

Inhibition is a key aspect of neural dynamics playing a fundamental role for the emergence of neural rhythms and the implementation of various information coding strategies. Inhibitory populations are present in several brain structures, and the comprehension of their dynamics is strategical for the understanding of neural processing. In this paper, we clarify the mechanisms underlying a general phenomenon present in pulse-coupled heterogeneous inhibitory networks: inhibition can induce not only suppression of neural activity, as expected, but can also promote neural re-activation. In particular, for globally coupled systems, the number of firing neurons monotonically reduces upon increasing the strength of inhibition (neuronal death). However, the random pruning of connections is able to reverse the action of inhibition, i.e. in a random sparse network a sufficiently strong synaptic strength can surprisingly promote, rather than depress, the activity of neurons (neuronal rebirth). Thus, the number of firing neurons reaches a minimum value at some intermediate synaptic strength. We show that this minimum signals a transition from a regime dominated by neurons with a higher firing activity to a phase where all neurons are effectively sub-threshold and their irregular firing is driven by current fluctuations. We explain the origin of the transition by deriving a mean field formulation of the problem able to provide the fraction of active neurons as well as the first two moments of their firing statistics. The introduction of a synaptic time scale does not modify the main aspects of the reported phenomenon. However, for sufficiently slow synapses the transition becomes dramatic, and the system passes from a perfectly regular evolution to irregular bursting dynamics. In this latter regime the model provides predictions consistent with experimental findings for a specific class of neurons, namely the medium spiny neurons in the striatum.

Stability of a neural network model with small-world connections

International Nuclear Information System (INIS)

Li Chunguang; Chen Guanrong

2003-01-01

Small-world networks are highly clustered networks with small distances among the nodes. There are many biological neural networks that present this kind of connection. There are no special weightings in the connections of most existing small-world network models. However, this kind of simply connected model cannot characterize biological neural networks, in which there are different weights in synaptic connections. In this paper, we present a neural network model with weighted small-world connections and further investigate the stability of this model

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

Science.gov (United States)

Gordon, Darcy G; Traniello, James F A

2018-05-29

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

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

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Kevin G. Bath

2017-12-01

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

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

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

2017-01-01

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

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

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

2015-01-21

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

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

Directory of Open Access Journals (Sweden)

Peng Wang

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

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

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Daewoo eLee

2015-08-01

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

All-optical functional synaptic connectivity mapping in acute brain slices using the calcium integrator CaMPARI.

Science.gov (United States)

Zolnik, Timothy A; Sha, Fern; Johenning, Friedrich W; Schreiter, Eric R; Looger, Loren L; Larkum, Matthew E; Sachdev, Robert N S

2017-03-01

The genetically encoded fluorescent calcium integrator calcium-modulated photoactivatable ratiobetric integrator (CaMPARI) reports calcium influx induced by synaptic and neural activity. Its fluorescence is converted from green to red in the presence of violet light and calcium. The rate of conversion - the sensitivity to activity - is tunable and depends on the intensity of violet light. Synaptic activity and action potentials can independently initiate significant CaMPARI conversion. The level of conversion by subthreshold synaptic inputs is correlated to the strength of input, enabling optical readout of relative synaptic strength. When combined with optogenetic activation of defined presynaptic neurons, CaMPARI provides an all-optical method to map synaptic connectivity. The calcium-modulated photoactivatable ratiometric integrator (CaMPARI) is a genetically encoded calcium integrator that facilitates the study of neural circuits by permanently marking cells active during user-specified temporal windows. Permanent marking enables measurement of signals from large swathes of tissue and easy correlation of activity with other structural or functional labels. One potential application of CaMPARI is labelling neurons postsynaptic to specific populations targeted for optogenetic stimulation, giving rise to all-optical functional connectivity mapping. Here, we characterized the response of CaMPARI to several common types of neuronal calcium signals in mouse acute cortical brain slices. Our experiments show that CaMPARI is effectively converted by both action potentials and subthreshold synaptic inputs, and that conversion level is correlated to synaptic strength. Importantly, we found that conversion rate can be tuned: it is linearly related to light intensity. At low photoconversion light levels CaMPARI offers a wide dynamic range due to slower conversion rate; at high light levels conversion is more rapid and more sensitive to activity. Finally, we employed Ca

Changes in neural network homeostasis trigger neuropsychiatric symptoms.

Science.gov (United States)

Winkelmann, Aline; Maggio, Nicola; Eller, Joanna; Caliskan, Gürsel; Semtner, Marcus; Häussler, Ute; Jüttner, René; Dugladze, Tamar; Smolinsky, Birthe; Kowalczyk, Sarah; Chronowska, Ewa; Schwarz, Günter; Rathjen, Fritz G; Rechavi, Gideon; Haas, Carola A; Kulik, Akos; Gloveli, Tengis; Heinemann, Uwe; Meier, Jochen C

2014-02-01

The mechanisms that regulate the strength of synaptic transmission and intrinsic neuronal excitability are well characterized; however, the mechanisms that promote disease-causing neural network dysfunction are poorly defined. We generated mice with targeted neuron type-specific expression of a gain-of-function variant of the neurotransmitter receptor for glycine (GlyR) that is found in hippocampectomies from patients with temporal lobe epilepsy. In this mouse model, targeted expression of gain-of-function GlyR in terminals of glutamatergic cells or in parvalbumin-positive interneurons persistently altered neural network excitability. The increased network excitability associated with gain-of-function GlyR expression in glutamatergic neurons resulted in recurrent epileptiform discharge, which provoked cognitive dysfunction and memory deficits without affecting bidirectional synaptic plasticity. In contrast, decreased network excitability due to gain-of-function GlyR expression in parvalbumin-positive interneurons resulted in an anxiety phenotype, but did not affect cognitive performance or discriminative associative memory. Our animal model unveils neuron type-specific effects on cognition, formation of discriminative associative memory, and emotional behavior in vivo. Furthermore, our data identify a presynaptic disease-causing molecular mechanism that impairs homeostatic regulation of neural network excitability and triggers neuropsychiatric symptoms.

Biologically plausible learning in neural networks: a lesson from bacterial chemotaxis.

Science.gov (United States)

Shimansky, Yury P

2009-12-01

Learning processes in the brain are usually associated with plastic changes made to optimize the strength of connections between neurons. Although many details related to biophysical mechanisms of synaptic plasticity have been discovered, it is unclear how the concurrent performance of adaptive modifications in a huge number of spatial locations is organized to minimize a given objective function. Since direct experimental observation of even a relatively small subset of such changes is not feasible, computational modeling is an indispensable investigation tool for solving this problem. However, the conventional method of error back-propagation (EBP) employed for optimizing synaptic weights in artificial neural networks is not biologically plausible. This study based on computational experiments demonstrated that such optimization can be performed rather efficiently using the same general method that bacteria employ for moving closer to an attractant or away from a repellent. With regard to neural network optimization, this method consists of regulating the probability of an abrupt change in the direction of synaptic weight modification according to the temporal gradient of the objective function. Neural networks utilizing this method (regulation of modification probability, RMP) can be viewed as analogous to swimming in the multidimensional space of their parameters in the flow of biochemical agents carrying information about the optimality criterion. The efficiency of RMP is comparable to that of EBP, while RMP has several important advantages. Since the biological plausibility of RMP is beyond a reasonable doubt, the RMP concept provides a constructive framework for the experimental analysis of learning in natural neural networks.

Phase Diagram of Spiking Neural Networks

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Hamed eSeyed-Allaei

2015-03-01

Full Text Available In computer simulations of spiking neural networks, often it is assumed that every two neurons of the network are connected by a probablilty of 2%, 20% of neurons are inhibitory and 80% are excitatory. These common values are based on experiments, observations. but here, I take a different perspective, inspired by evolution. I simulate many networks, each with a different set of parameters, and then I try to figure out what makes the common values desirable by nature. Networks which are configured according to the common values, have the best dynamic range in response to an impulse and their dynamic range is more robust in respect to synaptic weights. In fact, evolution has favored networks of best dynamic range. I present a phase diagram that shows the dynamic ranges of different networks of different parameteres. This phase diagram gives an insight into the space of parameters -- excitatory to inhibitory ratio, sparseness of connections and synaptic weights. It may serve as a guideline to decide about the values of parameters in a simulation of spiking neural network.

Requirement of mouse BCCIP for neural development and progenitor proliferation.

Directory of Open Access Journals (Sweden)

Yi-Yuan Huang

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

Optimal neural computations require analog processors

Energy Technology Data Exchange (ETDEWEB)

Beiu, V.

1998-12-31

This paper discusses some of the limitations of hardware implementations of neural networks. The authors start by presenting neural structures and their biological inspirations, while mentioning the simplifications leading to artificial neural networks. Further, the focus will be on hardware imposed constraints. They will present recent results for three different alternatives of parallel implementations of neural networks: digital circuits, threshold gate circuits, and analog circuits. The area and the delay will be related to the neurons` fan-in and to the precision of their synaptic weights. The main conclusion is that hardware-efficient solutions require analog computations, and suggests the following two alternatives: (i) cope with the limitations imposed by silicon, by speeding up the computation of the elementary silicon neurons; (2) investigate solutions which would allow the use of the third dimension (e.g. using optical interconnections).

Homeostatic scaling of excitability in recurrent neural networks.

NARCIS (Netherlands)

Remme, M.W.H.; Wadman, W.J.

2012-01-01

Neurons adjust their intrinsic excitability when experiencing a persistent change in synaptic drive. This process can prevent neural activity from moving into either a quiescent state or a saturated state in the face of ongoing plasticity, and is thought to promote stability of the network in which

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

Science.gov (United States)

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

2006-02-01

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

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

Science.gov (United States)

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

2015-12-01

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

Associative memory model with spontaneous neural activity

Science.gov (United States)

Kurikawa, Tomoki; Kaneko, Kunihiko

2012-05-01

We propose a novel associative memory model wherein the neural activity without an input (i.e., spontaneous activity) is modified by an input to generate a target response that is memorized for recall upon the same input. Suitable design of synaptic connections enables the model to memorize input/output (I/O) mappings equaling 70% of the total number of neurons, where the evoked activity distinguishes a target pattern from others. Spontaneous neural activity without an input shows chaotic dynamics but keeps some similarity with evoked activities, as reported in recent experimental studies.

Synaptic electronics: materials, devices and applications.

Science.gov (United States)

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

2013-09-27

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

Synaptic electronics: materials, devices and applications

International Nuclear Information System (INIS)

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

2013-01-01

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

Human embryonic stem cell-derived neurons adopt and regulate the activity of an established neural network

Science.gov (United States)

Weick, Jason P.; Liu, Yan; Zhang, Su-Chun

2011-01-01

Whether hESC-derived neurons can fully integrate with and functionally regulate an existing neural network remains unknown. Here, we demonstrate that hESC-derived neurons receive unitary postsynaptic currents both in vitro and in vivo and adopt the rhythmic firing behavior of mouse cortical networks via synaptic integration. Optical stimulation of hESC-derived neurons expressing Channelrhodopsin-2 elicited both inhibitory and excitatory postsynaptic currents and triggered network bursting in mouse neurons. Furthermore, light stimulation of hESC-derived neurons transplanted to the hippocampus of adult mice triggered postsynaptic currents in host pyramidal neurons in acute slice preparations. Thus, hESC-derived neurons can participate in and modulate neural network activity through functional synaptic integration, suggesting they are capable of contributing to neural network information processing both in vitro and in vivo. PMID:22106298

Banach Synaptic Algebras

Science.gov (United States)

Foulis, David J.; Pulmannov, Sylvia

2018-04-01

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

Nicotinic mechanisms influencing synaptic plasticity in the hippocampus

Institute of Scientific and Technical Information of China (English)

Andon Nicholas PLACZEK; Tao A ZHANG; John Anthony DANI

2009-01-01

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

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

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

2018-04-25

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

TGF-β Signaling in Dopaminergic Neurons Regulates Dendritic Growth, Excitatory-Inhibitory Synaptic Balance, and Reversal Learning

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Sarah X. Luo

2016-12-01

Full Text Available Neural circuits involving midbrain dopaminergic (DA neurons regulate reward and goal-directed behaviors. Although local GABAergic input is known to modulate DA circuits, the mechanism that controls excitatory/inhibitory synaptic balance in DA neurons remains unclear. Here, we show that DA neurons use autocrine transforming growth factor β (TGF-β signaling to promote the growth of axons and dendrites. Surprisingly, removing TGF-β type II receptor in DA neurons also disrupts the balance in TGF-β1 expression in DA neurons and neighboring GABAergic neurons, which increases inhibitory input, reduces excitatory synaptic input, and alters phasic firing patterns in DA neurons. Mice lacking TGF-β signaling in DA neurons are hyperactive and exhibit inflexibility in relinquishing learned behaviors and re-establishing new stimulus-reward associations. These results support a role for TGF-β in regulating the delicate balance of excitatory/inhibitory synaptic input in local microcircuits involving DA and GABAergic neurons and its potential contributions to neuropsychiatric disorders.

Motor unit recruitment strategies and muscle properties determine the influence of synaptic noise on force steadiness

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Dideriksen, Jakob L.; Negro, Francesco; Enoka, Roger M.

2012-01-01

Motoneurons receive synaptic inputs from tens of thousands of connections that cause membrane potential to fluctuate continuously (synaptic noise), which introduces variability in discharge times of action potentials. We hypothesized that the influence of synaptic noise on force steadiness during voluntary contractions is limited to low muscle forces. The hypothesis was examined with an analytical description of transduction of motor unit spike trains into muscle force, a computational model of motor unit recruitment and rate coding, and experimental analysis of interspike interval variability during steady contractions with the abductor digiti minimi muscle. Simulations varied contraction force, level of synaptic noise, size of motor unit population, recruitment range, twitch contraction times, and level of motor unit short-term synchronization. Consistent with the analytical derivations, simulations and experimental data showed that force variability at target forces above a threshold was primarily due to low-frequency oscillations in neural drive, whereas the influence of synaptic noise was almost completely attenuated by two low-pass filters, one related to convolution of motoneuron spike trains with motor unit twitches (temporal summation) and the other attributable to summation of single motor unit forces (spatial summation). The threshold force above which synaptic noise ceased to influence force steadiness depended on recruitment range, size of motor unit population, and muscle contractile properties. This threshold was low (motor unit recruitment and muscle properties of a typical muscle are tuned to limit the influence of synaptic noise on force steadiness to low forces and that the inability to produce a constant force during stronger contractions is mainly attributable to the common low-frequency oscillations in motoneuron discharge rates. PMID:22423000

Functional integration of grafted neural stem cell-derived dopaminergic neurons monitored by optogenetics in an in vitro Parkinson model

DEFF Research Database (Denmark)

Tønnesen, Jan; Parish, Clare L; Sørensen, Andreas T

2011-01-01

Intrastriatal grafts of stem cell-derived dopamine (DA) neurons induce behavioral recovery in animal models of Parkinson's disease (PD), but how they functionally integrate in host neural circuitries is poorly understood. Here, Wnt5a-overexpressing neural stem cells derived from embryonic ventral...... of post-synaptic currents, and functional expression of DA D₂ autoreceptors. These properties resembled those recorded from identical cells in acute slices of intrastriatal grafts in the 6-hydroxy-DA-induced mouse PD model and from DA neurons in intact substantia nigra. Optogenetic activation...... using optogenetics that ectopically grafted stem cell-derived DA neurons become functionally integrated in the DA-denervated striatum. Further optogenetic dissection of the synaptic wiring between grafted and host neurons will be crucial to clarify the cellular and synaptic mechanisms underlying...

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

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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.

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

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Melanie A Samuel

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

Nanowire FET Based Neural Element for Robotic Tactile Sensing Skin

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William Taube Navaraj

2017-09-01

Full Text Available This paper presents novel Neural Nanowire Field Effect Transistors (υ-NWFETs based hardware-implementable neural network (HNN approach for tactile data processing in electronic skin (e-skin. The viability of Si nanowires (NWs as the active material for υ-NWFETs in HNN is explored through modeling and demonstrated by fabricating the first device. Using υ-NWFETs to realize HNNs is an interesting approach as by printing NWs on large area flexible substrates it will be possible to develop a bendable tactile skin with distributed neural elements (for local data processing, as in biological skin in the backplane. The modeling and simulation of υ-NWFET based devices show that the overlapping areas between individual gates and the floating gate determines the initial synaptic weights of the neural network - thus validating the working of υ-NWFETs as the building block for HNN. The simulation has been further extended to υ-NWFET based circuits and neuronal computation system and this has been validated by interfacing it with a transparent tactile skin prototype (comprising of 6 × 6 ITO based capacitive tactile sensors array integrated on the palm of a 3D printed robotic hand. In this regard, a tactile data coding system is presented to detect touch gesture and the direction of touch. Following these simulation studies, a four-gated υ-NWFET is fabricated with Pt/Ti metal stack for gates, source and drain, Ni floating gate, and Al2O3 high-k dielectric layer. The current-voltage characteristics of fabricated υ-NWFET devices confirm the dependence of turn-off voltages on the (synaptic weight of each gate. The presented υ-NWFET approach is promising for a neuro-robotic tactile sensory system with distributed computing as well as numerous futuristic applications such as prosthetics, and electroceuticals.

Synaptic transmission modulates while non-synaptic processes govern the transition from pre-ictal to seizure activity in vitro

OpenAIRE

Jefferys, John; Fox, John; Jiruska, Premysl; Kronberg, Greg; Miranda, Dolores; Ruiz-Nuño, Ana; Bikson, Marom

2018-01-01

It is well established that non-synaptic mechanisms can generate electrographic seizures after blockade of synaptic function. We investigated the interaction of intact synaptic activity with non-synaptic mechanisms in the isolated CA1 region of rat hippocampal slices using the 'elevated-K+' model of epilepsy. Elevated K+ ictal bursts share waveform features with other models of electrographic seizures, including non-synaptic models where chemical synaptic transmission is suppressed, such as t...

Glutamatergic synaptic plasticity in the mesocorticolimbic system in addiction

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Aile evan Huijstee

2015-01-01

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

Glutamatergic synaptic plasticity in the mesocorticolimbic system in addiction

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

2015-01-01

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

Neural control of phrenic motoneuron discharge

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Lee, Kun-Ze; Fuller, David D.

2011-01-01

Phrenic motoneurons (PMNs) provide a synaptic relay between bulbospinal respiratory pathways and the diaphragm muscle. PMNs also receive propriospinal inputs, although the functional role of these interneuronal projections has not been established. Here we review the literature regarding PMN discharge patterns during breathing and the potential mechanisms that underlie PMN recruitment. Anatomical and neurophysiological studies indicate that PMNs form a heterogeneous pool, with respiratory-related PMN discharge and recruitment patterns likely determined by a balance between intrinsic MN properties and extrinsic synaptic inputs. We also review the limited literature regarding PMN bursting during respiratory plasticity. Differential recruitment or rate modulation of PMN subtypes may underlie phrenic motor plasticity following neural injury and/or respiratory stimulation; however this possibility remains relatively unexplored. PMID:21376841

Neural networks within multi-core optic fibers.

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Cohen, Eyal; Malka, Dror; Shemer, Amir; Shahmoon, Asaf; Zalevsky, Zeev; London, Michael

2016-07-07

Hardware implementation of artificial neural networks facilitates real-time parallel processing of massive data sets. Optical neural networks offer low-volume 3D connectivity together with large bandwidth and minimal heat production in contrast to electronic implementation. Here, we present a conceptual design for in-fiber optical neural networks. Neurons and synapses are realized as individual silica cores in a multi-core fiber. Optical signals are transferred transversely between cores by means of optical coupling. Pump driven amplification in erbium-doped cores mimics synaptic interactions. We simulated three-layered feed-forward neural networks and explored their capabilities. Simulations suggest that networks can differentiate between given inputs depending on specific configurations of amplification; this implies classification and learning capabilities. Finally, we tested experimentally our basic neuronal elements using fibers, couplers, and amplifiers, and demonstrated that this configuration implements a neuron-like function. Therefore, devices similar to our proposed multi-core fiber could potentially serve as building blocks for future large-scale small-volume optical artificial neural networks.

Neuromorphic implementations of neurobiological learning algorithms for spiking neural networks.

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Walter, Florian; Röhrbein, Florian; Knoll, Alois

2015-12-01

The application of biologically inspired methods in design and control has a long tradition in robotics. Unlike previous approaches in this direction, the emerging field of neurorobotics not only mimics biological mechanisms at a relatively high level of abstraction but employs highly realistic simulations of actual biological nervous systems. Even today, carrying out these simulations efficiently at appropriate timescales is challenging. Neuromorphic chip designs specially tailored to this task therefore offer an interesting perspective for neurorobotics. Unlike Von Neumann CPUs, these chips cannot be simply programmed with a standard programming language. Like real brains, their functionality is determined by the structure of neural connectivity and synaptic efficacies. Enabling higher cognitive functions for neurorobotics consequently requires the application of neurobiological learning algorithms to adjust synaptic weights in a biologically plausible way. In this paper, we therefore investigate how to program neuromorphic chips by means of learning. First, we provide an overview over selected neuromorphic chip designs and analyze them in terms of neural computation, communication systems and software infrastructure. On the theoretical side, we review neurobiological learning techniques. Based on this overview, we then examine on-die implementations of these learning algorithms on the considered neuromorphic chips. A final discussion puts the findings of this work into context and highlights how neuromorphic hardware can potentially advance the field of autonomous robot systems. The paper thus gives an in-depth overview of neuromorphic implementations of basic mechanisms of synaptic plasticity which are required to realize advanced cognitive capabilities with spiking neural networks. Copyright © 2015 Elsevier Ltd. All rights reserved.

AKT signaling displays multifaceted functions in neural crest development.

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Sittewelle, Méghane; Monsoro-Burq, Anne H

2018-05-31

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

Network-based characterization of the synaptic proteome reveals that removal of epigenetic regulator Prmt8 restricts proteins associated with synaptic maturation.

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Lee, Patrick Kia Ming; Goh, Wilson Wen Bin; Sng, Judy Chia Ghee

2017-02-01

The brain adapts to dynamic environmental conditions by altering its epigenetic state, thereby influencing neuronal transcriptional programs. An example of an epigenetic modification is protein methylation, catalyzed by protein arginine methyltransferases (PRMT). One member, Prmt8, is selectively expressed in the central nervous system during a crucial phase of early development, but little else is known regarding its function. We hypothesize Prmt8 plays a role in synaptic maturation during development. To evaluate this, we used a proteome-wide approach to characterize the synaptic proteome of Prmt8 knockout versus wild-type mice. Through comparative network-based analyses, proteins and functional clusters related to neurite development were identified to be differentially regulated between the two genotypes. One interesting protein that was differentially regulated was tenascin-R (TNR). Chromatin immunoprecipitation demonstrated binding of PRMT8 to the tenascin-r (Tnr) promoter. TNR, a component of perineuronal nets, preserves structural integrity of synaptic connections within neuronal networks during the development of visual-somatosensory cortices. On closer inspection, Prmt8 removal increased net formation and decreased inhibitory parvalbumin-positive (PV+) puncta on pyramidal neurons, thereby hindering the maturation of circuits. Consequently, visual acuity of the knockout mice was reduced. Our results demonstrated Prmt8's involvement in synaptic maturation and its prospect as an epigenetic modulator of developmental neuroplasticity by regulating structural elements such as the perineuronal nets. © 2016 International Society for Neurochemistry.

Drosophila-Cdh1 (Rap/Fzr) a regulatory subunit of APC/C is required for synaptic morphology, synaptic transmission and locomotion.

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Wise, Alexandria; Schatoff, Emma; Flores, Julian; Hua, Shao-Ying; Ueda, Atsushi; Wu, Chun-Fang; Venkatesh, Tadmiri

2013-11-01

The assembly of functional synapses requires the orchestration of the synthesis and degradation of a multitude of proteins. Protein degradation and modification by the conserved ubiquitination pathway has emerged as a key cellular regulatory mechanism during nervous system development and function (Kwabe and Brose, 2011). The anaphase promoting complex/cyclosome (APC/C) is a multi-subunit ubiquitin ligase complex primarily characterized for its role in the regulation of mitosis (Peters, 2002). In recent years, a role for APC/C in nervous system development and function has been rapidly emerging (Stegmuller and Bonni, 2005; Li et al., 2008). In the mammalian central nervous system the activator subunit, APC/C-Cdh1, has been shown to be a regulator of axon growth and dendrite morphogenesis (Konishi et al., 2004). In the Drosophila peripheral nervous system (PNS), APC2, a ligase subunit of the APC/C complex has been shown to regulate synaptic bouton size and activity (van Roessel et al., 2004). To investigate the role of APC/C-Cdh1 at the synapse we examined loss-of-function mutants of Rap/Fzr (Retina aberrant in pattern/Fizzy related), a Drosophila homolog of the mammalian Cdh1 during the development of the larval neuromuscular junction in Drosophila. Our cell biological, ultrastructural, electrophysiological, and behavioral data showed that rap/fzr loss-of-function mutations lead to changes in synaptic structure and function as well as locomotion defects. Data presented here show changes in size and morphology of synaptic boutons, and, muscle tissue organization. Electrophysiological experiments show that loss-of-function mutants exhibit increased frequency of spontaneous miniature synaptic potentials, indicating a higher rate of spontaneous synaptic vesicle fusion events. In addition, larval locomotion and peristaltic movement were also impaired. These findings suggest a role for Drosophila APC/C-Cdh1 mediated ubiquitination in regulating synaptic morphology

MAPK3 at the Autism-Linked Human 16p11.2 Locus Influences Precise Synaptic Target Selection at Drosophila Larval Neuromuscular Junctions.

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Park, Sang Mee; Park, Hae Ryoun; Lee, Ji Hye

2017-02-01

Proper synaptic function in neural circuits requires precise pairings between correct pre- and post-synaptic partners. Errors in this process may underlie development of neuropsychiatric disorders, such as autism spectrum disorder (ASD). Development of ASD can be influenced by genetic factors, including copy number variations (CNVs). In this study, we focused on a CNV occurring at the 16p11.2 locus in the human genome and investigated potential defects in synaptic connectivity caused by reduced activities of genes located in this region at Drosophila larval neuromuscular junctions, a well-established model synapse with stereotypic synaptic structures. A mutation of rolled , a Drosophila homolog of human mitogen-activated protein kinase 3 ( MAPK3 ) at the 16p11.2 locus, caused ectopic innervation of axonal branches and their abnormal defasciculation. The specificity of these phenotypes was confirmed by expression of wild-type rolled in the mutant background. Albeit to a lesser extent, we also observed ectopic innervation patterns in mutants defective in Cdk2, Gα q , and Gp93, all of which were expected to interact with Rolled MAPK3. A further genetic analysis in double heterozygous combinations revealed a synergistic interaction between rolled and Gp93 . In addition, results from RT-qPCR analyses indicated consistently reduced rolled mRNA levels in Cdk2 , Gα q , and Gp93 mutants. Taken together, these data suggest a central role of MAPK3 in regulating the precise targeting of presynaptic axons to proper postsynaptic targets, a critical step that may be altered significantly in ASD.

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

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Yuzaki, Michisuke

2018-02-10

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

The Less Things Change, the More They Are Different: Contributions of Long-Term Synaptic Plasticity and Homeostasis to Memory

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Schacher, Samuel; Hu, Jiang-Yuan

2014-01-01

An important cellular mechanism contributing to the strength and duration of memories is activity-dependent alterations in the strength of synaptic connections within the neural circuit encoding the memory. Reversal of the memory is typically correlated with a reversal of the cellular changes to levels expressed prior to the stimulation. Thus, for…

Imbalanced pattern completion vs. separation in cognitive disease: network simulations of synaptic pathologies predict a personalized therapeutics strategy

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Hanson Jesse E

2010-08-01

Full Text Available Abstract Background Diverse Mouse genetic models of neurodevelopmental, neuropsychiatric, and neurodegenerative causes of impaired cognition exhibit at least four convergent points of synaptic malfunction: 1 Strength of long-term potentiation (LTP, 2 Strength of long-term depression (LTD, 3 Relative inhibition levels (Inhibition, and 4 Excitatory connectivity levels (Connectivity. Results To test the hypothesis that pathological increases or decreases in these synaptic properties could underlie imbalances at the level of basic neural network function, we explored each type of malfunction in a simulation of autoassociative memory. These network simulations revealed that one impact of impairments or excesses in each of these synaptic properties is to shift the trade-off between pattern separation and pattern completion performance during memory storage and recall. Each type of synaptic pathology either pushed the network balance towards intolerable error in pattern separation or intolerable error in pattern completion. Imbalances caused by pathological impairments or excesses in LTP, LTD, inhibition, or connectivity, could all be exacerbated, or rescued, by the simultaneous modulation of any of the other three synaptic properties. Conclusions Because appropriate modulation of any of the synaptic properties could help re-balance network function, regardless of the origins of the imbalance, we propose a new strategy of personalized cognitive therapeutics guided by assay of pattern completion vs. pattern separation function. Simulated examples and testable predictions of this theorized approach to cognitive therapeutics are presented.

Gradient Learning in Spiking Neural Networks by Dynamic Perturbation of Conductances

International Nuclear Information System (INIS)

Fiete, Ila R.; Seung, H. Sebastian

2006-01-01

We present a method of estimating the gradient of an objective function with respect to the synaptic weights of a spiking neural network. The method works by measuring the fluctuations in the objective function in response to dynamic perturbation of the membrane conductances of the neurons. It is compatible with recurrent networks of conductance-based model neurons with dynamic synapses. The method can be interpreted as a biologically plausible synaptic learning rule, if the dynamic perturbations are generated by a special class of 'empiric' synapses driven by random spike trains from an external source

Synaptic Vesicle Endocytosis in Different Model Systems

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Quan Gan

2018-06-01

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

Glial processes at the Drosophila larval neuromuscular junction match synaptic growth.

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Deidre L Brink

Full Text Available Glia are integral participants in synaptic physiology, remodeling and maturation from blowflies to humans, yet how glial structure is coordinated with synaptic growth is unknown. To investigate the dynamics of glial development at the Drosophila larval neuromuscular junction (NMJ, we developed a live imaging system to establish the relationship between glia, neuronal boutons, and the muscle subsynaptic reticulum. Using this system we observed processes from two classes of peripheral glia present at the NMJ. Processes from the subperineurial glia formed a blood-nerve barrier around the axon proximal to the first bouton. Processes from the perineurial glial extended beyond the end of the blood-nerve barrier into the NMJ where they contacted synapses and extended across non-synaptic muscle. Growth of the glial processes was coordinated with NMJ growth and synaptic activity. Increasing synaptic size through elevated temperature or the highwire mutation increased the extent of glial processes at the NMJ and conversely blocking synaptic activity and size decreased the presence and size of glial processes. We found that elevated temperature was required during embryogenesis in order to increase glial expansion at the nmj. Therefore, in our live imaging system, glial processes at the NMJ are likely indirectly regulated by synaptic changes to ensure the coordinated growth of all components of the tripartite larval NMJ.

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

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

2010-01-01

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

Disorder generated by interacting neural networks: application to econophysics and cryptography

International Nuclear Information System (INIS)

Kinzel, Wolfgang; Kanter, Ido

2003-01-01

When neural networks are trained on their own output signals they generate disordered time series. In particular, when two neural networks are trained on their mutual output they can synchronize; they relax to a time-dependent state with identical synaptic weights. Two applications of this phenomenon are discussed for (a) econophysics and (b) cryptography. (a) When agents competing in a closed market (minority game) are using neural networks to make their decisions, the total system relaxes to a state of good performance. (b) Two partners communicating over a public channel can find a common secret key

Nonlinear dynamics analysis of a self-organizing recurrent neural network: chaos waning.

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Eser, Jürgen; Zheng, Pengsheng; Triesch, Jochen

2014-01-01

Self-organization is thought to play an important role in structuring nervous systems. It frequently arises as a consequence of plasticity mechanisms in neural networks: connectivity determines network dynamics which in turn feed back on network structure through various forms of plasticity. Recently, self-organizing recurrent neural network models (SORNs) have been shown to learn non-trivial structure in their inputs and to reproduce the experimentally observed statistics and fluctuations of synaptic connection strengths in cortex and hippocampus. However, the dynamics in these networks and how they change with network evolution are still poorly understood. Here we investigate the degree of chaos in SORNs by studying how the networks' self-organization changes their response to small perturbations. We study the effect of perturbations to the excitatory-to-excitatory weight matrix on connection strengths and on unit activities. We find that the network dynamics, characterized by an estimate of the maximum Lyapunov exponent, becomes less chaotic during its self-organization, developing into a regime where only few perturbations become amplified. We also find that due to the mixing of discrete and (quasi-)continuous variables in SORNs, small perturbations to the synaptic weights may become amplified only after a substantial delay, a phenomenon we propose to call deferred chaos.

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

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Sengupta, Abhronil; Shim, Yong; Roy, Kaushik

2016-12-01

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

Qualitative and quantitative estimation of comprehensive synaptic connectivity in short- and long-term cultured rat hippocampal neurons with new analytical methods inspired by Scatchard and Hill plots

Energy Technology Data Exchange (ETDEWEB)

Tanamoto, Ryo; Shindo, Yutaka; Niwano, Mariko [Department of Biosciences and Informatics, Faculty of Science and Technology, Keio University (Japan); Matsumoto, Yoshinori [Department of Applied Physics and Physico-Informatics, Faculty of Science and Technology, Keio University (Japan); Miki, Norihisa [Department of Mechanical Engineering, Faculty of Science and Technology, Keio University, 3-14-1 Hiyoshi, Kohoku-ku, Yokohama, Kanagawa, 223-8522 (Japan); Hotta, Kohji [Department of Biosciences and Informatics, Faculty of Science and Technology, Keio University (Japan); Oka, Kotaro, E-mail: oka@bio.keio.ac.jp [Department of Biosciences and Informatics, Faculty of Science and Technology, Keio University (Japan)

2016-03-18

To investigate comprehensive synaptic connectivity, we examined Ca{sup 2+} responses with quantitative electric current stimulation by indium-tin-oxide (ITO) glass electrode with transparent and high electro-conductivity. The number of neurons with Ca{sup 2+} responses was low during the application of stepwise increase of electric current in short-term cultured neurons (less than 17 days in-vitro (DIV)). The neurons cultured over 17 DIV showed two-type responses: S-shaped (sigmoid) and monotonous saturated responses, and Scatchard plots well illustrated the difference of these two responses. Furthermore, sigmoid like neural network responses over 17 DIV were altered to the monotonous saturated ones by the application of the mixture of AP5 and CNQX, specific blockers of NMDA and AMPA receptors, respectively. This alternation was also characterized by the change of Hill coefficients. These findings indicate that the neural network with sigmoid-like responses has strong synergetic or cooperative synaptic connectivity via excitatory glutamate synapses. - Highlights: • We succeed to evaluate the maturation of neural network by Scathard and Hill Plots. • Long-term cultured neurons showed two-type responses: sigmoid and monotonous. • The sigmoid-like increase indicates the cooperatevity of neural networks. • Excitatory glutamate synapses cause the cooperatevity of neural networks.

Age-related deficits in synaptic plasticity rescued by activating PKA or PKC in sensory neurons of Aplysia californica

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Andrew T Kempsell

2015-09-01

Full Text Available Brain aging is associated with declines in synaptic function that contribute to memory loss, including reduced postsynaptic response to neurotransmitters and decreased neuronal excitability. To understand how aging affects memory in a simple neural circuit, we studied neuronal proxies of memory for sensitization in mature versus advanced age Aplysia. Glutamate- (L-Glu- evoked excitatory currents were facilitated by the neuromodulator serotonin (5-HT in sensory neurons (SN isolated from mature but not aged animals. Activation of PKA and PKC signaling rescued facilitation of L-Glu currents in aged SN. Similarly, PKA and PKC activators restored increased excitability in aged tail SN. These results suggest that altered synaptic plasticity during aging involves defects in second messenger systems

Synaptic Plasticity and Nociception

Institute of Scientific and Technical Information of China (English)

ChenJianguo

2004-01-01

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

Supervised Learning in Spiking Neural Networks for Precise Temporal Encoding.

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Gardner, Brian; Grüning, André

2016-01-01

Precise spike timing as a means to encode information in neural networks is biologically supported, and is advantageous over frequency-based codes by processing input features on a much shorter time-scale. For these reasons, much recent attention has been focused on the development of supervised learning rules for spiking neural networks that utilise a temporal coding scheme. However, despite significant progress in this area, there still lack rules that have a theoretical basis, and yet can be considered biologically relevant. Here we examine the general conditions under which synaptic plasticity most effectively takes place to support the supervised learning of a precise temporal code. As part of our analysis we examine two spike-based learning methods: one of which relies on an instantaneous error signal to modify synaptic weights in a network (INST rule), and the other one relying on a filtered error signal for smoother synaptic weight modifications (FILT rule). We test the accuracy of the solutions provided by each rule with respect to their temporal encoding precision, and then measure the maximum number of input patterns they can learn to memorise using the precise timings of individual spikes as an indication of their storage capacity. Our results demonstrate the high performance of the FILT rule in most cases, underpinned by the rule's error-filtering mechanism, which is predicted to provide smooth convergence towards a desired solution during learning. We also find the FILT rule to be most efficient at performing input pattern memorisations, and most noticeably when patterns are identified using spikes with sub-millisecond temporal precision. In comparison with existing work, we determine the performance of the FILT rule to be consistent with that of the highly efficient E-learning Chronotron rule, but with the distinct advantage that our FILT rule is also implementable as an online method for increased biological realism.

Comparison of the dynamics of neural interactions in integrate-and-fire networks with current-based and conductance-based synapses

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Stefano eCavallari

2014-03-01

Full Text Available Models of networks of Leaky Integrate-and-Fire neurons (LIF are a widely used tool for theoretical investigations of brain function. These models have been used both with current- and conductance-based synapses. However, the differences in the dynamics expressed by these two approaches have been so far mainly studied at the single neuron level. To investigate how these synaptic models affect network activity, we compared the single-neuron and neural population dynamics of conductance-based networks (COBN and current-based networks (CUBN of LIF neurons. These networks were endowed with sparse excitatory and inhibitory recurrent connections, and were tested in conditions including both low- and high-conductance states. We developed a novel procedure to obtain comparable networks by properly tuning the synaptic parameters not shared by the models. The so defined comparable networks displayed an excellent and robust match of first order statistics (average single neuron firing rates and average frequency spectrum of network activity. However, these comparable networks showed profound differences in the second order statistics of neural population interactions and in the modulation of these properties by external inputs. The correlation between inhibitory and excitatory synaptic currents and the cross-neuron correlation between synaptic inputs, membrane potentials and spike trains were stronger and more stimulus-sensitive in the COBN. Because of these properties, the spike train correlation carried more information about the strength of the input in the COBN, although the firing rates were equally informative in both network models. Moreover, COBN showed stronger neuronal population synchronization in the gamma band, and their spectral information about the network input was higher and spread over a broader range of frequencies. These results suggest that second order properties of network dynamics depend strongly on the choice of synaptic model.

Emerging phenomena in neural networks with dynamic synapses and their computational implications

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Joaquin J. eTorres

2013-04-01

Full Text Available In this paper we review our research on the effect and computational role of dynamical synapses on feed-forward and recurrent neural networks. Among others, we report on the appearance of a new class of dynamical memories which result from the destabilisation of learned memory attractors. This has important consequences for dynamic information processing allowing the system to sequentially access the information stored in the memories under changing stimuli. Although storage capacity of stable memories also decreases, our study demonstrated the positive effect of synaptic facilitation to recover maximum storage capacity and to enlarge the capacity of the system for memory recall in noisy conditions. Possibly, the new dynamical behaviour can be associated with the voltage transitions between up and down states observed in cortical areas in the brain. We investigated the conditions for which the permanence times in the up state are power-law distributed, which is a sign for criticality, and concluded that the experimentally observed large variability of permanence times could be explained as the result of noisy dynamic synapses with large recovery times. Finally, we report how short-term synaptic processes can transmit weak signals throughout more than one frequency range in noisy neural networks, displaying a kind of stochastic multi-resonance. This effect is due to competition between activity-dependent synaptic fluctuations (due to dynamic synapses and the existence of neuron firing threshold which adapts to the incoming mean synaptic input.

Acid-sensing ion channels: trafficking and synaptic function

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Zha Xiang-ming

2013-01-01

Full Text Available Abstract Extracellular acidification occurs in the brain with elevated neural activity, increased metabolism, and neuronal injury. This reduction in pH can have profound effects on brain function because pH regulates essentially every single biochemical reaction. Therefore, it is not surprising to see that Nature evolves a family of proteins, the acid-sensing ion channels (ASICs, to sense extracellular pH reduction. ASICs are proton-gated cation channels that are mainly expressed in the nervous system. In recent years, a growing body of literature has shown that acidosis, through activating ASICs, contributes to multiple diseases, including ischemia, multiple sclerosis, and seizures. In addition, ASICs play a key role in fear and anxiety related psychiatric disorders. Several recent reviews have summarized the importance and therapeutic potential of ASICs in neurological diseases, as well as the structure-function relationship of ASICs. However, there is little focused coverage on either the basic biology of ASICs or their contribution to neural plasticity. This review will center on these topics, with an emphasis on the synaptic role of ASICs and molecular mechanisms regulating the spatial distribution and function of these ion channels.

Acid-sensing ion channels: trafficking and synaptic function.

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Zha, Xiang-ming

2013-01-02

Extracellular acidification occurs in the brain with elevated neural activity, increased metabolism, and neuronal injury. This reduction in pH can have profound effects on brain function because pH regulates essentially every single biochemical reaction. Therefore, it is not surprising to see that Nature evolves a family of proteins, the acid-sensing ion channels (ASICs), to sense extracellular pH reduction. ASICs are proton-gated cation channels that are mainly expressed in the nervous system. In recent years, a growing body of literature has shown that acidosis, through activating ASICs, contributes to multiple diseases, including ischemia, multiple sclerosis, and seizures. In addition, ASICs play a key role in fear and anxiety related psychiatric disorders. Several recent reviews have summarized the importance and therapeutic potential of ASICs in neurological diseases, as well as the structure-function relationship of ASICs. However, there is little focused coverage on either the basic biology of ASICs or their contribution to neural plasticity. This review will center on these topics, with an emphasis on the synaptic role of ASICs and molecular mechanisms regulating the spatial distribution and function of these ion channels.

Phase-response curves and synchronized neural networks.

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Smeal, Roy M; Ermentrout, G Bard; White, John A

2010-08-12

We review the principal assumptions underlying the application of phase-response curves (PRCs) to synchronization in neuronal networks. The PRC measures how much a given synaptic input perturbs spike timing in a neural oscillator. Among other applications, PRCs make explicit predictions about whether a given network of interconnected neurons will synchronize, as is often observed in cortical structures. Regarding the assumptions of the PRC theory, we conclude: (i) The assumption of noise-tolerant cellular oscillations at or near the network frequency holds in some but not all cases. (ii) Reduced models for PRC-based analysis can be formally related to more realistic models. (iii) Spike-rate adaptation limits PRC-based analysis but does not invalidate it. (iv) The dependence of PRCs on synaptic location emphasizes the importance of improving methods of synaptic stimulation. (v) New methods can distinguish between oscillations that derive from mutual connections and those arising from common drive. (vi) It is helpful to assume linear summation of effects of synaptic inputs; experiments with trains of inputs call this assumption into question. (vii) Relatively subtle changes in network structure can invalidate PRC-based predictions. (viii) Heterogeneity in the preferred frequencies of component neurons does not invalidate PRC analysis, but can annihilate synchronous activity.

Spine Calcium Transients Induced by Synaptically-Evoked Action Potentials Can Predict Synapse Location and Establish Synaptic Democracy

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Meredith, Rhiannon M.; van Ooyen, Arjen

2012-01-01

CA1 pyramidal neurons receive hundreds of synaptic inputs at different distances from the soma. Distance-dependent synaptic scaling enables distal and proximal synapses to influence the somatic membrane equally, a phenomenon called “synaptic democracy”. How this is established is unclear. The backpropagating action potential (BAP) is hypothesised to provide distance-dependent information to synapses, allowing synaptic strengths to scale accordingly. Experimental measurements show that a BAP evoked by current injection at the soma causes calcium currents in the apical shaft whose amplitudes decay with distance from the soma. However, in vivo action potentials are not induced by somatic current injection but by synaptic inputs along the dendrites, which creates a different excitable state of the dendrites. Due to technical limitations, it is not possible to study experimentally whether distance information can also be provided by synaptically-evoked BAPs. Therefore we adapted a realistic morphological and electrophysiological model to measure BAP-induced voltage and calcium signals in spines after Schaffer collateral synapse stimulation. We show that peak calcium concentration is highly correlated with soma-synapse distance under a number of physiologically-realistic suprathreshold stimulation regimes and for a range of dendritic morphologies. Peak calcium levels also predicted the attenuation of the EPSP across the dendritic tree. Furthermore, we show that peak calcium can be used to set up a synaptic democracy in a homeostatic manner, whereby synapses regulate their synaptic strength on the basis of the difference between peak calcium and a uniform target value. We conclude that information derived from synaptically-generated BAPs can indicate synapse location and can subsequently be utilised to implement a synaptic democracy. PMID:22719238

Myopic (HD-PTP, PTPN23) selectively regulates synaptic neuropeptide release.

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Bulgari, Dinara; Jha, Anupma; Deitcher, David L; Levitan, Edwin S

2018-02-13

Neurotransmission is mediated by synaptic exocytosis of neuropeptide-containing dense-core vesicles (DCVs) and small-molecule transmitter-containing small synaptic vesicles (SSVs). Exocytosis of both vesicle types depends on Ca 2+ and shared secretory proteins. Here, we show that increasing or decreasing expression of Myopic (mop, HD-PTP, PTPN23), a Bro1 domain-containing pseudophosphatase implicated in neuronal development and neuropeptide gene expression, increases synaptic neuropeptide stores at the Drosophila neuromuscular junction (NMJ). This occurs without altering DCV content or transport, but synaptic DCV number and age are increased. The effect on synaptic neuropeptide stores is accounted for by inhibition of activity-induced Ca 2+ -dependent neuropeptide release. cAMP-evoked Ca 2+ -independent synaptic neuropeptide release also requires optimal Myopic expression, showing that Myopic affects the DCV secretory machinery shared by cAMP and Ca 2+ pathways. Presynaptic Myopic is abundant at early endosomes, but interaction with the endosomal sorting complex required for transport III (ESCRT III) protein (CHMP4/Shrub) that mediates Myopic's effect on neuron pruning is not required for control of neuropeptide release. Remarkably, in contrast to the effect on DCVs, Myopic does not affect release from SSVs. Therefore, Myopic selectively regulates synaptic DCV exocytosis that mediates peptidergic transmission at the NMJ.

Alteration of synaptic transmission in the hippocampal-mPFC pathway during extinction trials of context-dependent fear memory in juvenile rat stress models.

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Koseki, Hiroyo; Matsumoto, Machiko; Togashi, Hiroko; Miura, Yoshihide; Fukushima, Kazuaki; Yoshioka, Mitsuhiro

2009-09-01

The medial prefrontal cortex (mPFC) has been proposed to be essential for extinction of fear memory, but its neural mechanism has been poorly understood. The present study examined whether synaptic transmission in the hippocampal-mPFC pathway is related to extinction of context-dependent fear memory in freely moving rats using electrophysiological approaches combined with behavioral analysis. Population spike amplitude in the mPFC was decreased during the first extinction trial by exposure to contextual fear conditioning. This synaptic inhibition was reversed by repeated extinction trials, accompanied by decreases in fear-related freezing behavior. These results suggest that alteration of synaptic transmission in the hippocampal-mPFC pathway is associated with the extinction processes of context-dependent fear memory. Further experiments were performed to elucidate whether early postnatal stress alters the synaptic response in the mPFC during extinction trials using a juvenile stress model, based on our previous findings that early postnatal stress affects the behavioral response to emotional stress. Adult rats that previously were exposed to five footshocks (FS) (shock intensity, 0.5 mA; intershock interval, 28 seconds; shock duration, 2 seconds) at postnatal day 21 to 25 (week 3; 3W-FS) exhibited impaired reversal of both inhibitory synaptic transmission and freezing behavior induced by repeated extinction trials. The neuronal and behavioral deficits observed in the 3W-FS group were prevented by pretreatment with the serotonin(1A) receptor agonist tandospirone (1 mg/kg, i.p.). These results indicate the possiblity that aversive stress exposure during the third postnatal week impaired extinction processes of context-dependent fear memory. The deficits in extinction observed in the 3W-FS group might be attributable to dysfunction of hippocampal-mPFC neural circuits involving 5-HT(1A) receptor mechanisms. 2009 Wiley-Liss, Inc.

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

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

2011-01-01

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

[Distribution of neural memory, loading factor, its regulation and optimization].

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Radchenko, A N

1999-01-01

Recording and retrieving functions of the neural memory are simulated as a control of local conformational processes in neural synaptic fields. The localization of conformational changes is related to the afferent temporal-spatial pulse pattern flow, the microstructure of connections and a plurality of temporal delays in synaptic fields and afferent pathways. The loci of conformations are described by sets of afferent addresses named address domains. Being superimposed on each other, address domains form a multilayer covering of the address space of the neuron or the ensemble. The superposition factor determines the dissemination of the conformational process, and the fuzzing of memory, and its accuracy and reliability. The engram is formed as detects in the packing of the address space and hence can be retrieved in inverse form. The accuracy of the retrieved information depends on the threshold level of conformational transitions, the distribution of conformational changes in synaptic fields of the neuronal population, and the memory loading factor. The latter is represented in the model by a slow potential. It reflects total conformational changes and displaces the membrane potential to monostable conformational regimes, by governing the exit from the recording regime, the potentiation of the neurone, and the readiness to reproduction. A relative amplitude of the slow potential and the coefficient of postconformational modification of ionic conductivity, which provides maximum reliability, accuracy, and capacity of memory, are calculated.

Neural Synchronization and Cryptography

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Ruttor, Andreas

2007-11-01

Neural networks can synchronize by learning from each other. In the case of discrete weights full synchronization is achieved in a finite number of steps. Additional networks can be trained by using the inputs and outputs generated during this process as examples. Several learning rules for both tasks are presented and analyzed. In the case of Tree Parity Machines synchronization is much faster than learning. Scaling laws for the number of steps needed for full synchronization and successful learning are derived using analytical models. They indicate that the difference between both processes can be controlled by changing the synaptic depth. In the case of bidirectional interaction the synchronization time increases proportional to the square of this parameter, but it grows exponentially, if information is transmitted in one direction only. Because of this effect neural synchronization can be used to construct a cryptographic key-exchange protocol. Here the partners benefit from mutual interaction, so that a passive attacker is usually unable to learn the generated key in time. The success probabilities of different attack methods are determined by numerical simulations and scaling laws are derived from the data. They show that the partners can reach any desired level of security by just increasing the synaptic depth. Then the complexity of a successful attack grows exponentially, but there is only a polynomial increase of the effort needed to generate a key. Further improvements of security are possible by replacing the random inputs with queries generated by the partners.

Synaptic Correlates of Low-Level Perception in V1.

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Gerard-Mercier, Florian; Carelli, Pedro V; Pananceau, Marc; Troncoso, Xoana G; Frégnac, Yves

2016-04-06

The computational role of primary visual cortex (V1) in low-level perception remains largely debated. A dominant view assumes the prevalence of higher cortical areas and top-down processes in binding information across the visual field. Here, we investigated the role of long-distance intracortical connections in form and motion processing by measuring, with intracellular recordings, their synaptic impact on neurons in area 17 (V1) of the anesthetized cat. By systematically mapping synaptic responses to stimuli presented in the nonspiking surround of V1 receptive fields, we provide the first quantitative characterization of the lateral functional connectivity kernel of V1 neurons. Our results revealed at the population level two structural-functional biases in the synaptic integration and dynamic association properties of V1 neurons. First, subthreshold responses to oriented stimuli flashed in isolation in the nonspiking surround exhibited a geometric organization around the preferred orientation axis mirroring the psychophysical "association field" for collinear contour perception. Second, apparent motion stimuli, for which horizontal and feedforward synaptic inputs summed in-phase, evoked dominantly facilitatory nonlinear interactions, specifically during centripetal collinear activation along the preferred orientation axis, at saccadic-like speeds. This spatiotemporal integration property, which could constitute the neural correlate of a human perceptual bias in speed detection, suggests that local (orientation) and global (motion) information is already linked within V1. We propose the existence of a "dynamic association field" in V1 neurons, whose spatial extent and anisotropy are transiently updated and reshaped as a function of changes in the retinal flow statistics imposed during natural oculomotor exploration. The computational role of primary visual cortex in low-level perception remains debated. The expression of this "pop-out" perception is often assumed

pH during non-synaptic epileptiform activity—computational simulations

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Márcio Rodrigues, Antônio; Canton Santos, Luiz Eduardo; Covolan, Luciene; Hamani, Clement; Guimarães de Almeida, Antônio-Carlos

2015-10-01

The excitability of neuronal networks is strongly modulated by changes in pH. The origin of these changes, however, is still under debate. The high complexity of neural systems justifies the use of computational simulation to investigate mechanisms that are possibly involved. Simulated neuronal activity includes non-synaptic epileptiform events (NEA) induced in hippocampal slices perfused with high-K+ and zero-Ca2+, therefore in the absence of the synaptic circuitry. A network of functional units composes the NEA model. Each functional unit represents one interface of neuronal/extracellular space/glial segments. Each interface contains transmembrane ionic transports, such as ionic channels, cotransporters, exchangers and pumps. Neuronal interconnections are mediated by gap-junctions, electric field effects and extracellular ionic fluctuations modulated by extracellular electrodiffusion. Mechanisms investigated are those that change intracellular and extracellular ionic concentrations and are able to affect [H+]. Our simulations suggest that the intense fluctuations in intra and extracellular concentrations of Na+, K+ and Cl- that accompany NEA are able to affect the combined action of the Na+/H+ exchanger (NHE), {{{HCO}}}3-/Cl- exchanger (HCE), H+ pump and the catalytic activity of intra and extracellular carbonic anhydrase. Cellular volume changes and extracellular electrodiffusion are responsible for modulating pH.

Evaluation of therapeutic effectiveness of neural transplantation using PET imaging technique

International Nuclear Information System (INIS)

Inaji, Motoki

2004-01-01

Neural transplantation is expected as an eradicative treatment of intractable central neural disease. In addition to behavioral observations, the recent development of the in vivo imaging technique also enabled to assess functions of neural graft in living subjects. Then we performed the PET scans using the unilateral 6-OHDA-lesioned rats in order to assess the pre- and post-synaptic functions in the striatum after transplantation of fetal dopaminergic neurons. As a result of PET scan, the images of [11C]PE2I, tracer of dopamine transporter, showed increased accumulation in the region which corresponded to the transplanted site after the graft. Because dopamine transporter exists on the cytoplasma membrane of axonal terminal, the accumulation of [11C]PE2I was regarded as a market of survival and maturation of transplanted cells. Also the images of [11C]raclopride, tracer of dopamine D2 receptor, revealed that up-regulation of D2 receptors normalized 4 weeks after transplantation. [11C]Raclopride was considered a marker of change of secondary dopaminergic environment. We believed that assessments with PET bring us much information, and it will increasingly contribute to a development of the regenerative medicine. (author)

Neural Development Under Conditions of Spaceflight

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

2003-01-01

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

Synaptic consolidation across multiple timescales

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Lorric Ziegler

2014-03-01

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

The backbone of the post-synaptic density originated in a unicellular ancestor of choanoflagellates and metazoans

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Manuel Michaël

2010-02-01

Full Text Available Abstract Background Comparative genomics of the early diverging metazoan lineages and of their unicellular sister-groups opens new window to reconstructing the genetic changes which preceded or accompanied the evolution of multicellular body plans. A recent analysis found that the genome of the nerve-less sponges encodes the homologues of most vertebrate post-synaptic proteins. In vertebrate excitatory synapses, these proteins assemble to form the post-synaptic density, a complex molecular platform linking membrane receptors, components of their signalling pathways, and the cytoskeleton. Newly available genomes from Monosiga brevicollis (a member of Choanoflagellata, the closest unicellular relatives of animals and Trichoplax adhaerens (a member of Placozoa: besides sponges, the only nerve-less metazoans offer an opportunity to refine our understanding of post-synaptic protein evolution. Results Searches for orthologous proteins and reconstruction of gene gains/losses based on the taxon phylogeny indicate that post-synaptic proteins originated in two main steps. The backbone scaffold proteins (Shank, Homer, DLG and some of their partners were acquired in a unicellular ancestor of choanoflagellates and metazoans. A substantial additional set appeared in an exclusive ancestor of the Metazoa. The placozoan genome contains most post-synaptic genes but lacks some of them. Notably, the master-scaffold protein Shank might have been lost secondarily in the placozoan lineage. Conclusions The time of origination of most post-synaptic proteins was not concomitant with the acquisition of synapses or neural-like cells. The backbone of the scaffold emerged in a unicellular context and was probably not involved in cell-cell communication. Based on the reconstructed protein composition and potential interactions, its ancestral function could have been to link calcium signalling and cytoskeleton regulation. The complex later became integrated into the evolving

Towards building hybrid biological/in silico neural networks for motor neuroprosthetic control

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Mehmet eKocaturk

2015-08-01

Full Text Available In this article, we introduce the Bioinspired Neuroprosthetic Design Environment (BNDE as a practical platform for the development of novel brain machine interface (BMI controllers which are based on spiking model neurons. We built the BNDE around a hard real-time system so that it is capable of creating simulated synapses from extracellularly recorded neurons to model neurons. In order to evaluate the practicality of the BNDE for neuroprosthetic control experiments, a novel, adaptive BMI controller was developed and tested using real-time closed-loop simulations. The present controller consists of two in silico medium spiny neurons which receive simulated synaptic inputs from recorded motor cortical neurons. In the closed-loop simulations, the recordings from the cortical neurons were imitated using an external, hardware-based neural signal synthesizer. By implementing a reward-modulated spike timing-dependent plasticity rule, the controller achieved perfect target reach accuracy for a two target reaching task in one dimensional space. The BNDE combines the flexibility of software-based spiking neural network (SNN simulations with powerful online data visualization tools and is a low-cost, PC-based and all-in-one solution for developing neurally-inspired BMI controllers. We believe the BNDE is the first implementation which is capable of creating hybrid biological/in silico neural networks for motor neuroprosthetic control and utilizes multiple CPU cores for computationally intensive real-time SNN simulations.

Age-related deficits in synaptic plasticity rescued by activating PKA or PKC in sensory neurons of Aplysia californica.

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Kempsell, Andrew T; Fieber, Lynne A

2015-01-01

Brain aging is associated with declines in synaptic function that contribute to memory loss, including reduced postsynaptic response to neurotransmitters and decreased neuronal excitability. To understand how aging affects memory in a simple neural circuit, we studied neuronal proxies of memory for sensitization in mature vs. advanced age Aplysia californica (Aplysia). L-Glutamate- (L-Glu-) evoked excitatory currents were facilitated by the neuromodulator serotonin (5-HT) in sensory neurons (SN) isolated from mature but not aged animals. Activation of protein kinase A (PKA) and protein kinase C (PKC) signaling rescued facilitation of L-Glu currents in aged SN. Similarly, PKA and PKC activators restored increased excitability in aged tail SN. These results suggest that altered synaptic plasticity during aging involves defects in second messenger systems.

Diacylglycerol kinases in the coordination of synaptic plasticity

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Dongwon Lee

2016-08-01

Full Text Available Synaptic plasticity is activity-dependent modification of the efficacy of synaptic transmission. Although detailed mechanisms underlying synaptic plasticity are diverse and vary at different types of synapses, diacylglycerol (DAG-associated signaling has been considered as an important regulator of many forms of synaptic plasticity, including long-term potentiation (LTP and long-term depression (LTD. Recent evidence indicate that DAG kinases (DGKs, which phosphorylate DAG to phosphatidic acid to terminate DAG signaling, are important regulators of LTP and LTD, as supported by the results from mice lacking specific DGK isoforms. This review will summarize these studies and discuss how specific DGK isoforms distinctly regulate different forms of synaptic plasticity at pre- and postsynaptic sites. In addition, we propose a general role of DGKs as coordinators of synaptic plasticity that make local synaptic environments more permissive for synaptic plasticity by regulating DAG concentration and interacting with other synaptic proteins.

Novel Mutations in Synaptic Transmission Genes Suppress Neuronal Hyperexcitation in Caenorhabditis elegans

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Katherine A. McCulloch

2017-07-01

Full Text Available Acetylcholine (ACh receptors (AChR regulate neural circuit activity in multiple contexts. In humans, mutations in ionotropic acetylcholine receptor (iAChR genes can cause neurological disorders, including myasthenia gravis and epilepsy. In Caenorhabditis elegans, iAChRs play multiple roles in the locomotor circuit. The cholinergic motor neurons express an ACR-2-containing pentameric AChR (ACR-2R comprised of ACR-2, ACR-3, ACR-12, UNC-38, and UNC-63 subunits. A gain-of-function mutation in the non-α subunit gene acr-2 [acr-2(gf] causes defective locomotion as well as spontaneous convulsions. Previous studies of genetic suppressors of acr-2(gf have provided insights into ACR-2R composition and assembly. Here, to further understand how the ACR-2R regulates neuronal activity, we expanded the suppressor screen for acr-2(gf-induced convulsions. The majority of these suppressor mutations affect genes that play critical roles in synaptic transmission, including two novel mutations in the vesicular ACh transporter unc-17. In addition, we identified a role for a conserved major facilitator superfamily domain (MFSD protein, mfsd-6, in regulating neural circuit activity. We further defined a role for the sphingosine (SPH kinase (Sphk sphk-1 in cholinergic neuron activity, independent of previously known signaling pathways. Overall, the genes identified in our study suggest that optimal modulation of synaptic activity is balanced by the differential activities of multiple pathways, and the novel alleles provide valuable reagents to further dissect neuronal mechanisms regulating the locomotor circuit.

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

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Bridget T Jacques-Fricke

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

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

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Mikkelsen, Kaare; Imparato, Alberto; Torcini, Alessandro

2013-05-01

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

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

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

2010-04-05

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

Neuronal cytoskeleton in synaptic plasticity and regeneration.

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Gordon-Weeks, Phillip R; Fournier, Alyson E

2014-04-01

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

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

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

2017-12-01

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

Random noise effects in pulse-mode digital multilayer neural networks.

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Kim, Y C; Shanblatt, M A

1995-01-01

A pulse-mode digital multilayer neural network (DMNN) based on stochastic computing techniques is implemented with simple logic gates as basic computing elements. The pulse-mode signal representation and the use of simple logic gates for neural operations lead to a massively parallel yet compact and flexible network architecture, well suited for VLSI implementation. Algebraic neural operations are replaced by stochastic processes using pseudorandom pulse sequences. The distributions of the results from the stochastic processes are approximated using the hypergeometric distribution. Synaptic weights and neuron states are represented as probabilities and estimated as average pulse occurrence rates in corresponding pulse sequences. A statistical model of the noise (error) is developed to estimate the relative accuracy associated with stochastic computing in terms of mean and variance. Computational differences are then explained by comparison to deterministic neural computations. DMNN feedforward architectures are modeled in VHDL using character recognition problems as testbeds. Computational accuracy is analyzed, and the results of the statistical model are compared with the actual simulation results. Experiments show that the calculations performed in the DMNN are more accurate than those anticipated when Bernoulli sequences are assumed, as is common in the literature. Furthermore, the statistical model successfully predicts the accuracy of the operations performed in the DMNN.

Compensating for Thalamocortical Synaptic Loss in Alzheimer’s Disease

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Kamal eAbuhassan

2014-06-01

Full Text Available The study presents a thalamocortical network model which oscillates within the alpha frequency band (8-13 Hz as recorded in the wakeful relaxed state with closed eyes to study the neural causes of abnormal oscillatory activity in Alzheimer’s disease (AD. Incorporated within the model are various types of cortical excitatory and inhibitory neurons, recurrently connected to thalamic and reticular thalamic regions with the ratios and distances derived from the mammalian thalamocortical system. The model is utilized to study the impacts of four types of connectivity loss on the model’s spectral dynamics. The study focuses on investigating degeneration of corticocortical, thalamocortical, corticothalamic and corticoreticular couplings, with an emphasis on the influence of each modelled case on the spectral output of the model. Synaptic compensation has been included in each model to examine the interplay between synaptic deletion and compensation mechanisms, and the oscillatory activity of the network. The results of power spectra and event related desynchronisation/synchronisation (ERD/S analyses show that the dynamics of the thalamic and cortical oscillations are significantly influenced by corticocortical synaptic loss. Interestingly, the patterns of changes in thalamic spectral activity are correlated with those in the cortical model. Similarly, the thalamic oscillatory activity is diminished after partial corticothalamic denervation. The results suggest that thalamic atrophy is a secondary pathology to cortical shrinkage in Alzheimer’s disease. In addition, this study finds that the inhibition from neurons in the thalamic reticular nucleus (RTN to thalamic relay (TCR neurons plays a key role in regulating thalamic oscillations; disinhibition disrupts thalamic oscillatory activity even though TCR neurons are more depolarized after being released from RTN inhibition. This study provides information that can be explored experimentally to

Modulation of synaptic plasticity by stress hormone associates with plastic alteration of synaptic NMDA receptor in the adult hippocampus.

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Yiu Chung Tse

Full Text Available Stress exerts a profound impact on learning and memory, in part, through the actions of adrenal corticosterone (CORT on synaptic plasticity, a cellular model of learning and memory. Increasing findings suggest that CORT exerts its impact on synaptic plasticity by altering the functional properties of glutamate receptors, which include changes in the motility and function of α-amino-3-hydroxy-5-methylisoxazole-4-propionic acid subtype of glutamate receptor (AMPAR that are responsible for the expression of synaptic plasticity. Here we provide evidence that CORT could also regulate synaptic plasticity by modulating the function of synaptic N-methyl-D-aspartate receptors (NMDARs, which mediate the induction of synaptic plasticity. We found that stress level CORT applied to adult rat hippocampal slices potentiated evoked NMDAR-mediated synaptic responses within 30 min. Surprisingly, following this fast-onset change, we observed a slow-onset (>1 hour after termination of CORT exposure increase in synaptic expression of GluN2A-containing NMDARs. To investigate the consequences of the distinct fast- and slow-onset modulation of NMDARs for synaptic plasticity, we examined the formation of long-term potentiation (LTP and long-term depression (LTD within relevant time windows. Paralleling the increased NMDAR function, both LTP and LTD were facilitated during CORT treatment. However, 1-2 hours after CORT treatment when synaptic expression of GluN2A-containing NMDARs is increased, bidirectional plasticity was no longer facilitated. Our findings reveal the remarkable plasticity of NMDARs in the adult hippocampus in response to CORT. CORT-mediated slow-onset increase in GluN2A in hippocampal synapses could be a homeostatic mechanism to normalize synaptic plasticity following fast-onset stress-induced facilitation.

Synaptic heterogeneity and stimulus-induced modulation of depression in central synapses.

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Hunter, J D; Milton, J G

2001-08-01

Short-term plasticity is a pervasive feature of synapses. Synapses exhibit many forms of plasticity operating over a range of time scales. We develop an optimization method that allows rapid characterization of synapses with multiple time scales of facilitation and depression. Investigation of paired neurons that are postsynaptic to the same identified interneuron in the buccal ganglion of Aplysia reveals that the responses of the two neurons differ in the magnitude of synaptic depression. Also, for single neurons, prolonged stimulation of the presynaptic neuron causes stimulus-induced increases in the early phase of synaptic depression. These observations can be described by a model that incorporates two availability factors, e.g., depletable vesicle pools or desensitizing receptor populations, with different time courses of recovery, and a single facilitation component. This model accurately predicts the responses to novel stimuli. The source of synaptic heterogeneity is identified with variations in the relative sizes of the two availability factors, and the stimulus-induced decrement in the early synaptic response is explained by a slowing of the recovery rate of one of the availability factors. The synaptic heterogeneity and stimulus-induced modifications in synaptic depression observed here emphasize that synaptic efficacy depends on both the individual properties of synapses and their past history.

Xenopus reduced folate carrier regulates neural crest development epigenetically.

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Jiejing Li

Full Text Available Folic acid deficiency during pregnancy causes birth neurocristopathic malformations resulting from aberrant development of neural crest cells. The Reduced folate carrier (RFC is a membrane-bound receptor for facilitating transfer of reduced folate into the cells. RFC knockout mice are embryonic lethal and develop multiple malformations, including neurocristopathies. Here we show that XRFC is specifically expressed in neural crest tissues in Xenopus embryos and knockdown of XRFC by specific morpholino results in severe neurocristopathies. Inhibition of RFC blocked the expression of a series of neural crest marker genes while overexpression of RFC or injection of 5-methyltetrahydrofolate expanded the neural crest territories. In animal cap assays, knockdown of RFC dramatically reduced the mono- and trimethyl-Histone3-K4 levels and co-injection of the lysine methyltransferase hMLL1 largely rescued the XRFC morpholino phenotype. Our data revealed that the RFC mediated folate metabolic pathway likely potentiates neural crest gene expression through epigenetic modifications.

Enrichment of conserved synaptic activity-responsive element in neuronal genes predicts a coordinated response of MEF2, CREB and SRF.

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Fernanda M Rodríguez-Tornos

Full Text Available A unique synaptic activity-responsive element (SARE sequence, composed of the consensus binding sites for SRF, MEF2 and CREB, is necessary for control of transcriptional upregulation of the Arc gene in response to synaptic activity. We hypothesize that this sequence is a broad mechanism that regulates gene expression in response to synaptic activation and during plasticity; and that analysis of SARE-containing genes could identify molecular mechanisms involved in brain disorders. To search for conserved SARE sequences in the mammalian genome, we used the SynoR in silico tool, and found the SARE cluster predominantly in the regulatory regions of genes expressed specifically in the nervous system; most were related to neural development and homeostatic maintenance. Two of these SARE sequences were tested in luciferase assays and proved to promote transcription in response to neuronal activation. Supporting the predictive capacity of our candidate list, up-regulation of several SARE containing genes in response to neuronal activity was validated using external data and also experimentally using primary cortical neurons and quantitative real time RT-PCR. The list of SARE-containing genes includes several linked to mental retardation and cognitive disorders, and is significantly enriched in genes that encode mRNA targeted by FMRP (fragile X mental retardation protein. Our study thus supports the idea that SARE sequences are relevant transcriptional regulatory elements that participate in plasticity. In addition, it offers a comprehensive view of how activity-responsive transcription factors coordinate their actions and increase the selectivity of their targets. Our data suggest that analysis of SARE-containing genes will reveal yet-undescribed pathways of synaptic plasticity and additional candidate genes disrupted in mental disease.

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

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Jimenez-Romero, Cristian; Johnson, Jeffrey

2017-01-01

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

Typology of nonlinear activity waves in a layered neural continuum.

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Koch, Paul; Leisman, Gerry

2006-04-01

Neural tissue, a medium containing electro-chemical energy, can amplify small increments in cellular activity. The growing disturbance, measured as the fraction of active cells, manifests as propagating waves. In a layered geometry with a time delay in synaptic signals between the layers, the delay is instrumental in determining the amplified wavelengths. The growth of the waves is limited by the finite number of neural cells in a given region of the continuum. As wave growth saturates, the resulting activity patterns in space and time show a variety of forms, ranging from regular monochromatic waves to highly irregular mixtures of different spatial frequencies. The type of wave configuration is determined by a number of parameters, including alertness and synaptic conditioning as well as delay. For all cases studied, using numerical solution of the nonlinear Wilson-Cowan (1973) equations, there is an interval in delay in which the wave mixing occurs. As delay increases through this interval, during a series of consecutive waves propagating through a continuum region, the activity within that region changes from a single-frequency to a multiple-frequency pattern and back again. The diverse spatio-temporal patterns give a more concrete form to several metaphors advanced over the years to attempt an explanation of cognitive phenomena: Activity waves embody the "holographic memory" (Pribram, 1991); wave mixing provides a plausible cause of the competition called "neural Darwinism" (Edelman, 1988); finally the consecutive generation of growing neural waves can explain the discontinuousness of "psychological time" (Stroud, 1955).

Synaptic plasticity in drug reward circuitry.

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Winder, Danny G; Egli, Regula E; Schramm, Nicole L; Matthews, Robert T

2002-11-01

Drug addiction is a major public health issue worldwide. The persistence of drug craving coupled with the known recruitment of learning and memory centers in the brain has led investigators to hypothesize that the alterations in glutamatergic synaptic efficacy brought on by synaptic plasticity may play key roles in the addiction process. Here we review the present literature, examining the properties of synaptic plasticity within drug reward circuitry, and the effects that drugs of abuse have on these forms of plasticity. Interestingly, multiple forms of synaptic plasticity can be induced at glutamatergic synapses within the dorsal striatum, its ventral extension the nucleus accumbens, and the ventral tegmental area, and at least some of these forms of plasticity are regulated by behaviorally meaningful administration of cocaine and/or amphetamine. Thus, the present data suggest that regulation of synaptic plasticity in reward circuits is a tractable candidate mechanism underlying aspects of addiction.

Hardwiring of fine synaptic layers in the zebrafish visual pathway

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Taylor Michael R

2008-12-01

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

Artificial neural networks in the nuclear engineering (Part 2)

International Nuclear Information System (INIS)

Baptista Filho, Benedito Dias

2002-01-01

The field of Artificial Neural Networks (ANN), one of the branches of Artificial Intelligence has been waking up a lot of interest in the Nuclear Engineering (NE). ANN can be used to solve problems of difficult modeling, when the data are fail or incomplete and in high complexity problems of control. The first part of this work began a discussion with feed-forward neural networks in back-propagation. In this part of the work, the Multi-synaptic neural networks is applied to control problems. Also, the self-organized maps is presented in a typical pattern classification problem: transients classification. The main purpose of the work is to show that ANN can be successfully used in NE if a carefully choice of its type is done: the application sets this choice. (author)

Synaptic Effects of Electric Fields

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Rahman, Asif

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

Optimal multiple-information integration inherent in a ring neural network

International Nuclear Information System (INIS)

Takiyama, Ken

2017-01-01

Although several behavioral experiments have suggested that our neural system integrates multiple sources of information based on the certainty of each type of information in the manner of maximum-likelihood estimation, it is unclear how the maximum-likelihood estimation is implemented in our neural system. Here, I investigate the relationship between maximum-likelihood estimation and a widely used ring-type neural network model that is used as a model of visual, motor, or prefrontal cortices. Without any approximation or ansatz, I analytically demonstrate that the equilibrium of an order parameter in the neural network model exactly corresponds to the maximum-likelihood estimation when the strength of the symmetrical recurrent synaptic connectivity within a neural population is appropriately stronger than that of asymmetrical connectivity, that of local and external inputs, and that of symmetrical or asymmetrical connectivity between different neural populations. In this case, strengths of local and external inputs or those of symmetrical connectivity between different neural populations exactly correspond to the input certainty in maximum-likelihood estimation. Thus, my analysis suggests appropriately strong symmetrical recurrent connectivity as a possible candidate for implementing the maximum-likelihood estimation within our neural system. (paper)

An optimally evolved connective ratio of neural networks that maximizes the occurrence of synchronized bursting behavior

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2012-01-01

Background Synchronized bursting activity (SBA) is a remarkable dynamical behavior in both ex vivo and in vivo neural networks. Investigations of the underlying structural characteristics associated with SBA are crucial to understanding the system-level regulatory mechanism of neural network behaviors. Results In this study, artificial pulsed neural networks were established using spike response models to capture fundamental dynamics of large scale ex vivo cortical networks. Network simulations with synaptic parameter perturbations showed the following two findings. (i) In a network with an excitatory ratio (ER) of 80-90%, its connective ratio (CR) was within a range of 10-30% when the occurrence of SBA reached the highest expectation. This result was consistent with the experimental observation in ex vivo neuronal networks, which were reported to possess a matured inhibitory synaptic ratio of 10-20% and a CR of 10-30%. (ii) No SBA occurred when a network does not contain any all-positive-interaction feedback loop (APFL) motif. In a neural network containing APFLs, the number of APFLs presented an optimal range corresponding to the maximal occurrence of SBA, which was very similar to the optimal CR. Conclusions In a neural network, the evolutionarily selected CR (10-30%) optimizes the occurrence of SBA, and APFL serves a pivotal network motif required to maximize the occurrence of SBA. PMID:22462685

Functional integration of grafted neural stem cell-derived dopaminergic neurons monitored by optogenetics in an in vitro Parkinson model.

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Jan Tønnesen

Full Text Available Intrastriatal grafts of stem cell-derived dopamine (DA neurons induce behavioral recovery in animal models of Parkinson's disease (PD, but how they functionally integrate in host neural circuitries is poorly understood. Here, Wnt5a-overexpressing neural stem cells derived from embryonic ventral mesencephalon of tyrosine hydroxylase-GFP transgenic mice were expanded as neurospheres and transplanted into organotypic cultures of wild type mouse striatum. Differentiated GFP-labeled DA neurons in the grafts exhibited mature neuronal properties, including spontaneous firing of action potentials, presence of post-synaptic currents, and functional expression of DA D₂ autoreceptors. These properties resembled those recorded from identical cells in acute slices of intrastriatal grafts in the 6-hydroxy-DA-induced mouse PD model and from DA neurons in intact substantia nigra. Optogenetic activation or inhibition of grafted cells and host neurons using channelrhodopsin-2 (ChR2 and halorhodopsin (NpHR, respectively, revealed complex, bi-directional synaptic interactions between grafted cells and host neurons and extensive synaptic connectivity within the graft. Our data demonstrate for the first time using optogenetics that ectopically grafted stem cell-derived DA neurons become functionally integrated in the DA-denervated striatum. Further optogenetic dissection of the synaptic wiring between grafted and host neurons will be crucial to clarify the cellular and synaptic mechanisms underlying behavioral recovery as well as adverse effects following stem cell-based DA cell replacement strategies in PD.

GABA type a receptor trafficking and the architecture of synaptic inhibition.

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Lorenz-Guertin, Joshua M; Jacob, Tija C

2018-03-01

Ubiquitous expression of GABA type A receptors (GABA A R) in the central nervous system establishes their central role in coordinating most aspects of neural function and development. Dysregulation of GABAergic neurotransmission manifests in a number of human health disorders and conditions that in certain cases can be alleviated by drugs targeting these receptors. Precise changes in the quantity or activity of GABA A Rs localized at the cell surface and at GABAergic postsynaptic sites directly impact the strength of inhibition. The molecular mechanisms constituting receptor trafficking to and from these compartments therefore dictate the efficacy of GABA A R function. Here we review the current understanding of how GABA A Rs traffic through biogenesis, plasma membrane transport, and degradation. Emphasis is placed on discussing novel GABAergic synaptic proteins, receptor and scaffolding post-translational modifications, activity-dependent changes in GABA A R confinement, and neuropeptide and neurosteroid mediated changes. We further highlight modern techniques currently advancing the knowledge of GABA A R trafficking and clinically relevant neurodevelopmental diseases connected to GABAergic dysfunction. © 2017 Wiley Periodicals, Inc. Develop Neurobiol 78: 238-270, 2018. © 2017 Wiley Periodicals, Inc.

Flexible Proton-Gated Oxide Synaptic Transistors on Si Membrane.

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Zhu, Li Qiang; Wan, Chang Jin; Gao, Ping Qi; Liu, Yang Hui; Xiao, Hui; Ye, Ji Chun; Wan, Qing

2016-08-24

Ion-conducting materials have received considerable attention for their applications in fuel cells, electrochemical devices, and sensors. Here, flexible indium zinc oxide (InZnO) synaptic transistors with multiple presynaptic inputs gated by proton-conducting phosphorosilicate glass-based electrolyte films are fabricated on ultrathin Si membranes. Transient characteristics of the proton gated InZnO synaptic transistors are investigated, indicating stable proton-gating behaviors. Short-term synaptic plasticities are mimicked on the proposed proton-gated synaptic transistors. Furthermore, synaptic integration regulations are mimicked on the proposed synaptic transistor networks. Spiking logic modulations are realized based on the transition between superlinear and sublinear synaptic integration. The multigates coupled flexible proton-gated oxide synaptic transistors may be interesting for neuroinspired platforms with sophisticated spatiotemporal information processing.

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

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Godwin Sokpor

2017-08-01

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

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

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

2017-01-01

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

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

Science.gov (United States)

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

2017-01-01

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

Advances in Artificial Neural Networks – Methodological Development and Application

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Yanbo Huang

2009-08-01

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

Single-Iteration Learning Algorithm for Feed-Forward Neural Networks

Energy Technology Data Exchange (ETDEWEB)

Barhen, J.; Cogswell, R.; Protopopescu, V.

1999-07-31

A new methodology for neural learning is presented, whereby only a single iteration is required to train a feed-forward network with near-optimal results. To this aim, a virtual input layer is added to the multi-layer architecture. The virtual input layer is connected to the nominal input layer by a specird nonlinear transfer function, and to the fwst hidden layer by regular (linear) synapses. A sequence of alternating direction singular vrdue decompositions is then used to determine precisely the inter-layer synaptic weights. This algorithm exploits the known separability of the linear (inter-layer propagation) and nonlinear (neuron activation) aspects of information &ansfer within a neural network.

Non-linear feedback neural networks VLSI implementations and applications

CERN Document Server

Ansari, Mohd Samar

2014-01-01

This book aims to present a viable alternative to the Hopfield Neural Network (HNN) model for analog computation. It is well known that the standard HNN suffers from problems of convergence to local minima, and requirement of a large number of neurons and synaptic weights. Therefore, improved solutions are needed. The non-linear synapse neural network (NoSyNN) is one such possibility and is discussed in detail in this book. This book also discusses the applications in computationally intensive tasks like graph coloring, ranking, and linear as well as quadratic programming. The material in the book is useful to students, researchers and academician working in the area of analog computation.

Storage capacity of attractor neural networks with depressing synapses

International Nuclear Information System (INIS)

Torres, Joaquin J.; Pantic, Lovorka; Kappen, Hilbert J.

2002-01-01

We compute the capacity of a binary neural network with dynamic depressing synapses to store and retrieve an infinite number of patterns. We use a biologically motivated model of synaptic depression and a standard mean-field approach. We find that at T=0 the critical storage capacity decreases with the degree of the depression. We confirm the validity of our main mean-field results with numerical simulations

Neuromimetic Circuits with Synaptic Devices Based on Strongly Correlated Electron Systems

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Ha, Sieu D.; Shi, Jian; Meroz, Yasmine; Mahadevan, L.; Ramanathan, Shriram

2014-12-01

Strongly correlated electron systems such as the rare-earth nickelates (R NiO3 , R denotes a rare-earth element) can exhibit synapselike continuous long-term potentiation and depression when gated with ionic liquids; exploiting the extreme sensitivity of coupled charge, spin, orbital, and lattice degrees of freedom to stoichiometry. We present experimental real-time, device-level classical conditioning and unlearning using nickelate-based synaptic devices in an electronic circuit compatible with both excitatory and inhibitory neurons. We establish a physical model for the device behavior based on electric-field-driven coupled ionic-electronic diffusion that can be utilized for design of more complex systems. We use the model to simulate a variety of associate and nonassociative learning mechanisms, as well as a feedforward recurrent network for storing memory. Our circuit intuitively parallels biological neural architectures, and it can be readily generalized to other forms of cellular learning and extinction. The simulation of neural function with electronic device analogs may provide insight into biological processes such as decision making, learning, and adaptation, while facilitating advanced parallel information processing in hardware.

Presynaptic protein synthesis required for NT-3-induced long-term synaptic modulation

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Je H

2011-01-01

Full Text Available Abstract Background Neurotrophins elicit both acute and long-term modulation of synaptic transmission and plasticity. Previously, we demonstrated that the long-term synaptic modulation requires the endocytosis of neurotrophin-receptor complex, the activation of PI3K and Akt, and mTOR mediated protein synthesis. However, it is unclear whether the long-term synaptic modulation by neurotrophins depends on protein synthesis in pre- or post-synaptic cells. Results Here we have developed an inducible protein translation blocker, in which the kinase domain of protein kinase R (PKR is fused with bacterial gyrase B domain (GyrB-PKR, which could be dimerized upon treatment with a cell permeable drug, coumermycin. By genetically targeting GyrB-PKR to specific cell types, we show that NT-3 induced long-term synaptic modulation requires presynaptic, but not postsynaptic protein synthesis. Conclusions Our results provide mechanistic insights into the cell-specific requirement for protein synthesis in the long-term synaptic modulation by neurotrophins. The GyrB-PKR system may be useful tool to study protein synthesis in a cell-specific manner.

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

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Ueda, Atsushi; Wu, Chun-Fang

2012-01-01

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

Phase diagram of spiking neural networks.

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Seyed-Allaei, Hamed

2015-01-01

In computer simulations of spiking neural networks, often it is assumed that every two neurons of the network are connected by a probability of 2%, 20% of neurons are inhibitory and 80% are excitatory. These common values are based on experiments, observations, and trials and errors, but here, I take a different perspective, inspired by evolution, I systematically simulate many networks, each with a different set of parameters, and then I try to figure out what makes the common values desirable. I stimulate networks with pulses and then measure their: dynamic range, dominant frequency of population activities, total duration of activities, maximum rate of population and the occurrence time of maximum rate. The results are organized in phase diagram. This phase diagram gives an insight into the space of parameters - excitatory to inhibitory ratio, sparseness of connections and synaptic weights. This phase diagram can be used to decide the parameters of a model. The phase diagrams show that networks which are configured according to the common values, have a good dynamic range in response to an impulse and their dynamic range is robust in respect to synaptic weights, and for some synaptic weights they oscillates in α or β frequencies, independent of external stimuli.

Influence of Synaptic Depression on Memory Storage Capacity

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

2011-08-01

Synaptic efficacy between neurons is known to change within a short time scale dynamically. Neurophysiological experiments show that high-frequency presynaptic inputs decrease synaptic efficacy between neurons. This phenomenon is called synaptic depression, a short term synaptic plasticity. Many researchers have investigated how the synaptic depression affects the memory storage capacity. However, the noise has not been taken into consideration in their analysis. By introducing ``temperature'', which controls the level of the noise, into an update rule of neurons, we investigate the effects of synaptic depression on the memory storage capacity in the presence of the noise. We analytically compute the storage capacity by using a statistical mechanics technique called Self Consistent Signal to Noise Analysis (SCSNA). We find that the synaptic depression decreases the storage capacity in the case of finite temperature in contrast to the case of the low temperature limit, where the storage capacity does not change.

Limited distal organelles and synaptic function in extensive monoaminergic innervation.

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

2017-08-01

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

Long-term relationships between cholinergic tone, synchronous bursting and synaptic remodeling.

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Maya Kaufman

Full Text Available Cholinergic neuromodulation plays key roles in the regulation of neuronal excitability, network activity, arousal, and behavior. On longer time scales, cholinergic systems play essential roles in cortical development, maturation, and plasticity. Presumably, these processes are associated with substantial synaptic remodeling, yet to date, long-term relationships between cholinergic tone and synaptic remodeling remain largely unknown. Here we used automated microscopy combined with multielectrode array recordings to study long-term relationships between cholinergic tone, excitatory synapse remodeling, and network activity characteristics in networks of cortical neurons grown on multielectrode array substrates. Experimental elevations of cholinergic tone led to the abrupt suppression of episodic synchronous bursting activity (but not of general activity, followed by a gradual growth of excitatory synapses over hours. Subsequent blockage of cholinergic receptors led to an immediate restoration of synchronous bursting and the gradual reversal of synaptic growth. Neither synaptic growth nor downsizing was governed by multiplicative scaling rules. Instead, these occurred in a subset of synapses, irrespective of initial synaptic size. Synaptic growth seemed to depend on intrinsic network activity, but not on the degree to which bursting was suppressed. Intriguingly, sustained elevations of cholinergic tone were associated with a gradual recovery of synchronous bursting but not with a reversal of synaptic growth. These findings show that cholinergic tone can strongly affect synaptic remodeling and synchronous bursting activity, but do not support a strict coupling between the two. Finally, the reemergence of synchronous bursting in the presence of elevated cholinergic tone indicates that the capacity of cholinergic neuromodulation to indefinitely suppress synchronous bursting might be inherently limited.

Long-term Relationships between Cholinergic Tone, Synchronous Bursting and Synaptic Remodeling

Science.gov (United States)

Kaufman, Maya; Corner, Michael A.; Ziv, Noam E.

2012-01-01

Cholinergic neuromodulation plays key roles in the regulation of neuronal excitability, network activity, arousal, and behavior. On longer time scales, cholinergic systems play essential roles in cortical development, maturation, and plasticity. Presumably, these processes are associated with substantial synaptic remodeling, yet to date, long-term relationships between cholinergic tone and synaptic remodeling remain largely unknown. Here we used automated microscopy combined with multielectrode array recordings to study long-term relationships between cholinergic tone, excitatory synapse remodeling, and network activity characteristics in networks of cortical neurons grown on multielectrode array substrates. Experimental elevations of cholinergic tone led to the abrupt suppression of episodic synchronous bursting activity (but not of general activity), followed by a gradual growth of excitatory synapses over hours. Subsequent blockage of cholinergic receptors led to an immediate restoration of synchronous bursting and the gradual reversal of synaptic growth. Neither synaptic growth nor downsizing was governed by multiplicative scaling rules. Instead, these occurred in a subset of synapses, irrespective of initial synaptic size. Synaptic growth seemed to depend on intrinsic network activity, but not on the degree to which bursting was suppressed. Intriguingly, sustained elevations of cholinergic tone were associated with a gradual recovery of synchronous bursting but not with a reversal of synaptic growth. These findings show that cholinergic tone can strongly affect synaptic remodeling and synchronous bursting activity, but do not support a strict coupling between the two. Finally, the reemergence of synchronous bursting in the presence of elevated cholinergic tone indicates that the capacity of cholinergic neuromodulation to indefinitely suppress synchronous bursting might be inherently limited. PMID:22911726

Long-term relationships between cholinergic tone, synchronous bursting and synaptic remodeling.

Science.gov (United States)

Kaufman, Maya; Corner, Michael A; Ziv, Noam E

2012-01-01

Cholinergic neuromodulation plays key roles in the regulation of neuronal excitability, network activity, arousal, and behavior. On longer time scales, cholinergic systems play essential roles in cortical development, maturation, and plasticity. Presumably, these processes are associated with substantial synaptic remodeling, yet to date, long-term relationships between cholinergic tone and synaptic remodeling remain largely unknown. Here we used automated microscopy combined with multielectrode array recordings to study long-term relationships between cholinergic tone, excitatory synapse remodeling, and network activity characteristics in networks of cortical neurons grown on multielectrode array substrates. Experimental elevations of cholinergic tone led to the abrupt suppression of episodic synchronous bursting activity (but not of general activity), followed by a gradual growth of excitatory synapses over hours. Subsequent blockage of cholinergic receptors led to an immediate restoration of synchronous bursting and the gradual reversal of synaptic growth. Neither synaptic growth nor downsizing was governed by multiplicative scaling rules. Instead, these occurred in a subset of synapses, irrespective of initial synaptic size. Synaptic growth seemed to depend on intrinsic network activity, but not on the degree to which bursting was suppressed. Intriguingly, sustained elevations of cholinergic tone were associated with a gradual recovery of synchronous bursting but not with a reversal of synaptic growth. These findings show that cholinergic tone can strongly affect synaptic remodeling and synchronous bursting activity, but do not support a strict coupling between the two. Finally, the reemergence of synchronous bursting in the presence of elevated cholinergic tone indicates that the capacity of cholinergic neuromodulation to indefinitely suppress synchronous bursting might be inherently limited.

MPTP-meditated hippocampal dopamine deprivation modulates synaptic transmission and activity-dependent synaptic plasticity

International Nuclear Information System (INIS)

Zhu Guoqi; Chen Ying; Huang Yuying; Li Qinglin; Behnisch, Thomas

2011-01-01

Parkinson's disease (PD)-like symptoms including learning deficits are inducible by 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP). Therefore, it is possible that MPTP may disturb hippocampal memory processing by modulation of dopamine (DA)- and activity-dependent synaptic plasticity. We demonstrate here that intraperitoneal (i.p.) MPTP injection reduces the number of tyrosine hydroxylase (TH)-positive neurons in the substantia nigra (SN) within 7 days. Subsequently, the TH expression level in SN and hippocampus and the amount of DA and its metabolite DOPAC in striatum and hippocampus decrease. DA depletion does not alter basal synaptic transmission and changes pair-pulse facilitation (PPF) of field excitatory postsynaptic potentials (fEPSPs) only at the 30 ms inter-pulse interval. In addition, the induction of long-term potentiation (LTP) is impaired whereas the duration of long-term depression (LTD) becomes prolonged. Since both LTP and LTD depend critically on activation of NMDA and DA receptors, we also tested the effect of DA depletion on NMDA receptor-mediated synaptic transmission. Seven days after MPTP injection, the NMDA receptor-mediated fEPSPs are decreased by about 23%. Blocking the NMDA receptor-mediated fEPSP does not mimic the MPTP-LTP. Only co-application of D1/D5 and NMDA receptor antagonists during tetanization resembled the time course of fEPSP potentiation as observed 7 days after i.p. MPTP injection. Together, our data demonstrate that MPTP-induced degeneration of DA neurons and the subsequent hippocampal DA depletion alter NMDA receptor-mediated synaptic transmission and activity-dependent synaptic plasticity. - Highlights: → I.p. MPTP-injection mediates death of dopaminergic neurons. → I.p. MPTP-injection depletes DA and DOPAC in striatum and hippocampus. → I.p. MPTP-injection does not alter basal synaptic transmission. → Reduction of LTP and enhancement of LTD after i.p. MPTP-injection. → Attenuation of NMDA-receptors mediated

Emergence of Functional Specificity in Balanced Networks with Synaptic Plasticity.

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Sadra Sadeh

2015-06-01

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

Advances in Artificial Neural Networks - Methodological Development and Application

Science.gov (United States)

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

Spontaneous Vesicle Recycling in the Synaptic Bouton

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Sven eTruckenbrodt

2014-12-01

Full Text Available The trigger for synaptic vesicle exocytosis is Ca2+, which enters the synaptic bouton following action potential stimulation. However, spontaneous release of neurotransmitter also occurs in the absence of stimulation in virtually all synaptic boutons. It has long been thought that this represents exocytosis driven by fluctuations in local Ca2+ levels. The vesicles responding to these fluctuations are thought to be the same ones that release upon stimulation, albeit potentially triggered by different Ca2+ sensors. This view has been challenged by several recent works, which have suggested that spontaneous release is driven by a separate pool of synaptic vesicles. Numerous articles appeared during the last few years in support of each of these hypotheses, and it has been challenging to bring them into accord. We speculate here on the origins of this controversy, and propose a solution that is related to developmental effects. Constitutive membrane traffic, needed for the biogenesis of vesicles and synapses, is responsible for high levels of spontaneous membrane fusion in young neurons, probably independent of Ca2+. The vesicles releasing spontaneously in such neurons are not related to other synaptic vesicle pools and may represent constitutively releasing vesicles (CRVs rather than bona fide synaptic vesicles. In mature neurons, constitutive traffic is much dampened, and the few remaining spontaneous release events probably represent bona fide spontaneously releasing synaptic vesicles (SRSVs responding to Ca2+ fluctuations, along with a handful of CRVs that participate in synaptic vesicle turnover.

Plasticity resembling spike-timing dependent synaptic plasticity: the evidence in human cortex

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Florian Müller-Dahlhaus

2010-07-01

Full Text Available Spike-timing dependent plasticity (STDP has been studied extensively in a variety of animal models during the past decade but whether it can be studied at the systems level of the human cortex has been a matter of debate. Only recently newly developed non-invasive brain stimulation techniques such as transcranial magnetic stimulation (TMS have made it possible to induce and assess timing dependent plasticity in conscious human subjects. This review will present a critical synopsis of these experiments, which suggest that several of the principal characteristics and molecular mechanisms of TMS-induced plasticity correspond to those of STDP as studied at a cellular level. TMS combined with a second phasic stimulation modality can induce bidirectional long-lasting changes in the excitability of the stimulated cortex, whose polarity depends on the order of the associated stimulus-evoked events within a critical time window of tens of milliseconds. Pharmacological evidence suggests an NMDA receptor mediated form of synaptic plasticity. Studies in human motor cortex demonstrated that motor learning significantly modulates TMS-induced timing dependent plasticity, and, conversely, may be modulated bidirectionally by prior TMS-induced plasticity, providing circumstantial evidence that long-term potentiation-like mechanisms may be involved in motor learning. In summary, convergent evidence is being accumulated for the contention that it is now possible to induce STDP-like changes in the intact human central nervous system by means of TMS to study and interfere with synaptic plasticity in neural circuits in the context of behaviour such as learning and memory.

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

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Panda, Priyadarshini; Roy, Kaushik

2017-01-01

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

Possible relationship between the stress-induced synaptic response and metaplasticity in the hippocampal CA1 field of freely moving rats.

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Hirata, Riki; Matsumoto, Machiko; Judo, Chika; Yamaguchi, Taku; Izumi, Takeshi; Yoshioka, Mitsuhiro; Togashi, Hiroko

2009-07-01

Hippocampal long-term potentiation (LTP) is suppressed not only by stress paradigms but also by low frequency stimulation (LFS) prior to LTP-inducing high frequency stimulation (HFS; tetanus), termed metaplasticity. These synaptic responses are dependent on N-methyl-D-aspartate receptors, leading to speculations about the possible relationship between metaplasticity and stress-induced LTP impairment. However, the functional significance of metaplasticity has been unclear. The present study elucidated the electrophysiological and neurochemical profiles of metaplasticity in the hippocampal CA1 field, with a focus on the synaptic response induced by the emotional stress, contextual fear conditioning (CFC). The population spike amplitude in the CA1 field was decreased during exposure to CFC, and LTP induction was suppressed after CFC in conscious rats. The synaptic response induced by CFC was mimicked by LFS, i.e., LFS impaired the synaptic transmission and subsequent LTP. Plasma corticosterone levels were increased by both CFC and LFS. Extracellular levels of gamma-aminobutyric acid (GABA), but not glutamate, in the hippocampus increased during exposure to CFC or LFS. Furthermore, electrical stimulation of the medial prefrontal cortex (mPFC), which caused decreases in freezing behavior during exposure to CFC, counteracted the LTP impairment induced by LFS. These findings suggest that metaplasticity in the rat hippocampal CA1 field is related to the neural basis of stress experience-dependent fear memory, and that hippocampal synaptic response associated stress-related processes is under mPFC regulation.

Convergent synaptic and circuit substrates underlying autism genetic risks.

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McGee, Aaron; Li, Guohui; Lu, Zhongming; Qiu, Shenfeng

2014-02-01

There has been a surge of diagnosis of autism spectrum disorders (ASD) over the past decade. While large, high powered genome screening studies of children with ASD have identified numerous genetic risk factors, research efforts to understanding how each of these risk factors contributes to the development autism has met with limited success. Revealing the mechanisms by which these genetic risk factors affect brain development and predispose a child to autism requires mechanistic understanding of the neurobiological changes underlying this devastating group of developmental disorders at multifaceted molecular, cellular and system levels. It has been increasingly clear that the normal trajectory of neurodevelopment is compromised in autism, in multiple domains as much as aberrant neuronal production, growth, functional maturation, patterned connectivity, and balanced excitation and inhibition of brain networks. Many autism risk factors identified in humans have been now reconstituted in experimental mouse models to allow mechanistic interrogation of the biological role of the risk gene. Studies utilizing these mouse models have revealed that underlying the enormous heterogeneity of perturbed cellular events, mechanisms directing synaptic and circuit assembly may provide a unifying explanation for the pathophysiological changes and behavioral endophenotypes seen in autism, although synaptic perturbations are far from being the only alterations relevant for ASD. In this review, we discuss synaptic and circuit abnormalities obtained from several prevalent mouse models, particularly those reflecting syndromic forms of ASD that are caused by single gene perturbations. These compiled results reveal that ASD risk genes contribute to proper signaling of the developing gene networks that maintain synaptic and circuit homeostasis, which is fundamental to normal brain development.

Autonomous dynamics in neural networks: the dHAN concept and associative thought processes

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Gros, Claudius

2007-02-01

The neural activity of the human brain is dominated by self-sustained activities. External sensory stimuli influence this autonomous activity but they do not drive the brain directly. Most standard artificial neural network models are however input driven and do not show spontaneous activities. It constitutes a challenge to develop organizational principles for controlled, self-sustained activity in artificial neural networks. Here we propose and examine the dHAN concept for autonomous associative thought processes in dense and homogeneous associative networks. An associative thought-process is characterized, within this approach, by a time-series of transient attractors. Each transient state corresponds to a stored information, a memory. The subsequent transient states are characterized by large associative overlaps, which are identical to acquired patterns. Memory states, the acquired patterns, have such a dual functionality. In this approach the self-sustained neural activity has a central functional role. The network acquires a discrimination capability, as external stimuli need to compete with the autonomous activity. Noise in the input is readily filtered-out. Hebbian learning of external patterns occurs coinstantaneous with the ongoing associative thought process. The autonomous dynamics needs a long-term working-point optimization which acquires within the dHAN concept a dual functionality: It stabilizes the time development of the associative thought process and limits runaway synaptic growth, which generically occurs otherwise in neural networks with self-induced activities and Hebbian-type learning rules.

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

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Fruzsina Soltész

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

Insights into neural crest development from studies of avian embryos

OpenAIRE

Gandhi, Shashank; Bronner, Marianne E.

2018-01-01

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

Stochastic lattice model of synaptic membrane protein domains.

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Li, Yiwei; Kahraman, Osman; Haselwandter, Christoph A

2017-05-01

Neurotransmitter receptor molecules, concentrated in synaptic membrane domains along with scaffolds and other kinds of proteins, are crucial for signal transmission across chemical synapses. In common with other membrane protein domains, synaptic domains are characterized by low protein copy numbers and protein crowding, with rapid stochastic turnover of individual molecules. We study here in detail a stochastic lattice model of the receptor-scaffold reaction-diffusion dynamics at synaptic domains that was found previously to capture, at the mean-field level, the self-assembly, stability, and characteristic size of synaptic domains observed in experiments. We show that our stochastic lattice model yields quantitative agreement with mean-field models of nonlinear diffusion in crowded membranes. Through a combination of analytic and numerical solutions of the master equation governing the reaction dynamics at synaptic domains, together with kinetic Monte Carlo simulations, we find substantial discrepancies between mean-field and stochastic models for the reaction dynamics at synaptic domains. Based on the reaction and diffusion properties of synaptic receptors and scaffolds suggested by previous experiments and mean-field calculations, we show that the stochastic reaction-diffusion dynamics of synaptic receptors and scaffolds provide a simple physical mechanism for collective fluctuations in synaptic domains, the molecular turnover observed at synaptic domains, key features of the observed single-molecule trajectories, and spatial heterogeneity in the effective rates at which receptors and scaffolds are recycled at the cell membrane. Our work sheds light on the physical mechanisms and principles linking the collective properties of membrane protein domains to the stochastic dynamics that rule their molecular components.

Synaptic pathology in the cerebellar dentate nucleus in chronic multiple sclerosis.

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Albert, Monika; Barrantes-Freer, Alonso; Lohrberg, Melanie; Antel, Jack P; Prineas, John W; Palkovits, Miklós; Wolff, Joachim R; Brück, Wolfgang; Stadelmann, Christine

2017-11-01

In multiple sclerosis, cerebellar symptoms are associated with clinical impairment and an increased likelihood of progressive course. Cortical atrophy and synaptic dysfunction play a prominent role in cerebellar pathology and although the dentate nucleus is a predilection site for lesion development, structural synaptic changes in this region remain largely unexplored. Moreover, the mechanisms leading to synaptic dysfunction have not yet been investigated at an ultrastructural level in multiple sclerosis. Here, we report on synaptic changes of dentate nuclei in post-mortem cerebella of 16 multiple sclerosis patients and eight controls at the histological level as well as an electron microscopy evaluation of afferent synapses of the cerebellar dentate and pontine nuclei of one multiple sclerosis patient and one control. We found a significant reduction of afferent dentate synapses in multiple sclerosis, irrespective of the presence of demyelination, and a close relationship between glial processes and dentate synapses. Ultrastructurally, we show autophagosomes containing degradation products of synaptic vesicles within dendrites, residual bodies within intact-appearing axons and free postsynaptic densities opposed to astrocytic appendages. Our study demonstrates loss of dentate afferent synapses and provides, for the first time, ultrastructural evidence pointing towards neuron-autonomous and neuroglia-mediated mechanisms of synaptic degradation in chronic multiple sclerosis. © 2016 International Society of Neuropathology.

Natural lecithin promotes neural network complexity and activity

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Latifi, Shahrzad; Tamayol, Ali; Habibey, Rouhollah; Sabzevari, Reza; Kahn, Cyril; Geny, David; Eftekharpour, Eftekhar; Annabi, Nasim; Blau, Axel; Linder, Michel; Arab-Tehrany, Elmira

2016-01-01

Phospholipids in the brain cell membranes contain different polyunsaturated fatty acids (PUFAs), which are critical to nervous system function and structure. In particular, brain function critically depends on the uptake of the so-called “essential” fatty acids such as omega-3 (n-3) and omega-6 (n-6) PUFAs that cannot be readily synthesized by the human body. We extracted natural lecithin rich in various PUFAs from a marine source and transformed it into nanoliposomes. These nanoliposomes increased neurite outgrowth, network complexity and neural activity of cortical rat neurons in vitro. We also observed an upregulation of synapsin I (SYN1), which supports the positive role of lecithin in synaptogenesis, synaptic development and maturation. These findings suggest that lecithin nanoliposomes enhance neuronal development, which may have an impact on devising new lecithin delivery strategies for therapeutic applications. PMID:27228907

Natural lecithin promotes neural network complexity and activity.

Science.gov (United States)

Latifi, Shahrzad; Tamayol, Ali; Habibey, Rouhollah; Sabzevari, Reza; Kahn, Cyril; Geny, David; Eftekharpour, Eftekhar; Annabi, Nasim; Blau, Axel; Linder, Michel; Arab-Tehrany, Elmira

2016-05-27

Phospholipids in the brain cell membranes contain different polyunsaturated fatty acids (PUFAs), which are critical to nervous system function and structure. In particular, brain function critically depends on the uptake of the so-called "essential" fatty acids such as omega-3 (n-3) and omega-6 (n-6) PUFAs that cannot be readily synthesized by the human body. We extracted natural lecithin rich in various PUFAs from a marine source and transformed it into nanoliposomes. These nanoliposomes increased neurite outgrowth, network complexity and neural activity of cortical rat neurons in vitro. We also observed an upregulation of synapsin I (SYN1), which supports the positive role of lecithin in synaptogenesis, synaptic development and maturation. These findings suggest that lecithin nanoliposomes enhance neuronal development, which may have an impact on devising new lecithin delivery strategies for therapeutic applications.

Decreased expression of vesicular glutamate transporter 1 and complexin II mRNAs in schizophrenia: further evidence for a synaptic pathology affecting glutamate neurons.

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Eastwood, S L; Harrison, P J

2005-03-01

Synaptic protein gene expression is altered in schizophrenia. In the hippocampal formation there may be particular involvement of glutamatergic neurons and their synapses, but overall the profile remains unclear. In this in situ hybridization histochemistry (ISHH) study, we examined four informative synaptic protein transcripts: vesicular glutamate transporter (VGLUT) 1, VGLUT2, complexin I, and complexin II, in dorsolateral prefrontal cortex (DPFC), superior temporal cortex (STC), and hippocampal formation, in 13 subjects with schizophrenia and 18 controls. In these areas, VGLUT1 and complexin II are expressed primarily by excitatory neurons, whereas complexin I is mainly expressed by inhibitory neurons. In schizophrenia, VGLUT1 mRNA was decreased in hippocampal formation and DPFC, complexin II mRNA was reduced in DPFC and STC, and complexin I mRNA decreased in STC. Hippocampal VGLUT1 mRNA declined with age selectively in the schizophrenia group. VGLUT2 mRNA was not quantifiable due to its low level. The data provide additional evidence for a synaptic pathology in schizophrenia, in terms of a reduced expression of three synaptic protein genes. In the hippocampus, the loss of VGLUT1 mRNA supports data indicating that glutamatergic presynaptic deficits are prominent, whereas the pattern of results in temporal and frontal cortex suggests broadly similar changes may affect inhibitory and excitatory neurons. The impairment of synaptic transmission implied by the synaptic protein reductions may contribute to the dysfunction of cortical neural circuits that characterises the disorder.

Design principles of electrical synaptic plasticity.

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O'Brien, John

2017-09-08

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

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

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Shruti eMuralidhar

2014-01-01

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

Quantum neural networks: Current status and prospects for development

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

2014-11-01

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

Neuronal medium that supports basic synaptic functions and activity of human neurons in vitro.

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Bardy, Cedric; van den Hurk, Mark; Eames, Tameji; Marchand, Cynthia; Hernandez, Ruben V; Kellogg, Mariko; Gorris, Mark; Galet, Ben; Palomares, Vanessa; Brown, Joshua; Bang, Anne G; Mertens, Jerome; Böhnke, Lena; Boyer, Leah; Simon, Suzanne; Gage, Fred H

2015-05-19

Human cell reprogramming technologies offer access to live human neurons from patients and provide a new alternative for modeling neurological disorders in vitro. Neural electrical activity is the essence of nervous system function in vivo. Therefore, we examined neuronal activity in media widely used to culture neurons. We found that classic basal media, as well as serum, impair action potential generation and synaptic communication. To overcome this problem, we designed a new neuronal medium (BrainPhys basal + serum-free supplements) in which we adjusted the concentrations of inorganic salts, neuroactive amino acids, and energetic substrates. We then tested that this medium adequately supports neuronal activity and survival of human neurons in culture. Long-term exposure to this physiological medium also improved the proportion of neurons that were synaptically active. The medium was designed to culture human neurons but also proved adequate for rodent neurons. The improvement in BrainPhys basal medium to support neurophysiological activity is an important step toward reducing the gap between brain physiological conditions in vivo and neuronal models in vitro.

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.

Development and application of deep convolutional neural network in target detection

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Jiang, Xiaowei; Wang, Chunping; Fu, Qiang

2018-04-01

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

Synaptic proteins and receptors defects in autism spectrum disorders

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Jianling eChen

2014-09-01

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

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

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

2015-01-01

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

Synaptic conditions for auto-associative memory storage and pattern completion in Jensen et al.'s model of hippocampal area CA3.

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Cheu, Eng Yeow; Yu, Jiali; Tan, Chin Hiong; Tang, Huajin

2012-12-01

Jensen et al. (Learn Memory 3(2-3):243-256, 1996b) proposed an auto-associative memory model using an integrated short-term memory (STM) and long-term memory (LTM) spiking neural network. Their model requires that distinct pyramidal cells encoding different STM patterns are fired in different high-frequency gamma subcycles within each low-frequency theta oscillation. Auto-associative LTM is formed by modifying the recurrent synaptic efficacy between pyramidal cells. In order to store auto-associative LTM correctly, the recurrent synaptic efficacy must be bounded. The synaptic efficacy must be upper bounded to prevent re-firing of pyramidal cells in subsequent gamma subcycles. If cells encoding one memory item were to re-fire synchronously with other cells encoding another item in subsequent gamma subcycle, LTM stored via modifiable recurrent synapses would be corrupted. The synaptic efficacy must also be lower bounded so that memory pattern completion can be performed correctly. This paper uses the original model by Jensen et al. as the basis to illustrate the following points. Firstly, the importance of coordinated long-term memory (LTM) synaptic modification. Secondly, the use of a generic mathematical formulation (spiking response model) that can theoretically extend the results to other spiking network utilizing threshold-fire spiking neuron model. Thirdly, the interaction of long-term and short-term memory networks that possibly explains the asymmetric distribution of spike density in theta cycle through the merger of STM patterns with interaction of LTM network.

Convergence analysis of stochastic hybrid bidirectional associative memory neural networks with delays

International Nuclear Information System (INIS)

Wan Li; Zhou Qinghua

2007-01-01

The stability property of stochastic hybrid bidirectional associate memory (BAM) neural networks with discrete delays is considered. Without assuming the symmetry of synaptic connection weights and the monotonicity and differentiability of activation functions, the delay-independent sufficient conditions to guarantee the exponential stability of the equilibrium solution for such networks are given by using the nonnegative semimartingale convergence theorem

Convergence analysis of stochastic hybrid bidirectional associative memory neural networks with delays

Science.gov (United States)

Wan, Li; Zhou, Qinghua

2007-10-01

The stability property of stochastic hybrid bidirectional associate memory (BAM) neural networks with discrete delays is considered. Without assuming the symmetry of synaptic connection weights and the monotonicity and differentiability of activation functions, the delay-independent sufficient conditions to guarantee the exponential stability of the equilibrium solution for such networks are given by using the nonnegative semimartingale convergence theorem.

Development of target-tracking algorithms using neural network

Energy Technology Data Exchange (ETDEWEB)

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

1998-04-01

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

Effects of stevia on synaptic plasticity and NADPH oxidase level of CNS in conditions of metabolic disorders caused by fructose.

Science.gov (United States)

Chavushyan, V A; Simonyan, K V; Simonyan, R M; Isoyan, A S; Simonyan, G M; Babakhanyan, M A; Hovhannisyian, L E; Nahapetyan, Kh H; Avetisyan, L G; Simonyan, M A

2017-12-19

Excess dietary fructose intake associated with metabolic syndrome and insulin resistance and increased risk of developing type 2 diabetes. Previous animal studies have reported that diabetic animals have significantly impaired behavioural and cognitive functions, pathological synaptic function and impaired expression of glutamate receptors. Correction of the antioxidant status of laboratory rodents largely prevents the development of fructose-induced plurimetabolic changes in the nervous system. We suggest a novel concept of efficiency of Stevia leaves for treatment of central diabetic neuropathy. By in vivo extracellular studies induced spike activity of hippocampal neurons during high frequency stimulation of entorhinal cortex, as well as neurons of basolateral amygdala to high-frequency stimulation of the hippocampus effects of Stevia rebaudiana Bertoni plant evaluated in synaptic activity in the brain of fructose-enriched diet rats. In the conditions of metabolic disorders caused by fructose, antioxidant activity of Stevia rebaudiana was assessed by measuring the NOX activity of the hippocampus, amygdala and spinal cord. In this study, the characteristic features of the metabolic effects of dietary fructose on synaptic plasticity in hippocampal neurons and basolateral amygdala and the state of the NADPH oxidase (NOX) oxidative system of these brain formations are revealed, as well as the prospects for development of multitarget and polyfunctional phytopreparations (with adaptogenic, antioxidant, antidiabetic, nootropic activity) from native raw material of Stevia rebaudiana. Stevia modulates degree of expressiveness of potentiation/depression (approaches but fails to achieve the norm) by shifting the percentage balance in favor of depressor type of responses during high-frequency stimulation, indicating its adaptogenic role in plasticity of neural networks. Under the action of fructose an increase (3-5 times) in specific quantity of total fraction of NOX

Synaptic plasticity and memory functions achieved in a WO3−x-based nanoionics device by using the principle of atomic switch operation

International Nuclear Information System (INIS)

Yang, Rui; Terabe, Kazuya; Yao, Yiping; Tsuruoka, Tohru; Hasegawa, Tsuyoshi; Gimzewski, James K; Aono, Masakazu

2013-01-01

A compact neuromorphic nanodevice with inherent learning and memory properties emulating those of biological synapses is the key to developing artificial neural networks rivaling their biological counterparts. Experimental results showed that memorization with a wide time scale from volatile to permanent can be achieved in a WO 3−x -based nanoionics device and can be precisely and cumulatively controlled by adjusting the device’s resistance state and input pulse parameters such as the amplitude, interval, and number. This control is analogous to biological synaptic plasticity including short-term plasticity, long-term potentiation, transition from short-term memory to long-term memory, forgetting processes for short- and long-term memory, learning speed, and learning history. A compact WO 3−x -based nanoionics device with a simple stacked layer structure should thus be a promising candidate for use as an inorganic synapse in artificial neural networks due to its striking resemblance to the biological synapse. (paper)

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

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Brian R. Christie

2013-07-01

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

Fine-tuning and the stability of recurrent neural networks.

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David MacNeil

Full Text Available A central criticism of standard theoretical approaches to constructing stable, recurrent model networks is that the synaptic connection weights need to be finely-tuned. This criticism is severe because proposed rules for learning these weights have been shown to have various limitations to their biological plausibility. Hence it is unlikely that such rules are used to continuously fine-tune the network in vivo. We describe a learning rule that is able to tune synaptic weights in a biologically plausible manner. We demonstrate and test this rule in the context of the oculomotor integrator, showing that only known neural signals are needed to tune the weights. We demonstrate that the rule appropriately accounts for a wide variety of experimental results, and is robust under several kinds of perturbation. Furthermore, we show that the rule is able to achieve stability as good as or better than that provided by the linearly optimal weights often used in recurrent models of the integrator. Finally, we discuss how this rule can be generalized to tune a wide variety of recurrent attractor networks, such as those found in head direction and path integration systems, suggesting that it may be used to tune a wide variety of stable neural systems.

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

International Nuclear Information System (INIS)

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

2007-01-01

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

Synaptic Mechanisms Generating Orientation Selectivity in the ON Pathway of the Rabbit Retina.

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Venkataramani, Sowmya; Taylor, W Rowland

2016-03-16

Neurons that signal the orientation of edges within the visual field have been widely studied in primary visual cortex. Much less is known about the mechanisms of orientation selectivity that arise earlier in the visual stream. Here we examine the synaptic and morphological properties of a subtype of orientation-selective ganglion cell in the rabbit retina. The receptive field has an excitatory ON center, flanked by excitatory OFF regions, a structure similar to simple cell receptive fields in primary visual cortex. Examination of the light-evoked postsynaptic currents in these ON-type orientation-selective ganglion cells (ON-OSGCs) reveals that synaptic input is mediated almost exclusively through the ON pathway. Orientation selectivity is generated by larger excitation for preferred relative to orthogonal stimuli, and conversely larger inhibition for orthogonal relative to preferred stimuli. Excitatory orientation selectivity arises in part from the morphology of the dendritic arbors. Blocking GABAA receptors reduces orientation selectivity of the inhibitory synaptic inputs and the spiking responses. Negative contrast stimuli in the flanking regions produce orientation-selective excitation in part by disinhibition of a tonic NMDA receptor-mediated input arising from ON bipolar cells. Comparison with earlier studies of OFF-type OSGCs indicates that diverse synaptic circuits have evolved in the retina to detect the orientation of edges in the visual input. A core goal for visual neuroscientists is to understand how neural circuits at each stage of the visual system extract and encode features from the visual scene. This study documents a novel type of orientation-selective ganglion cell in the retina and shows that the receptive field structure is remarkably similar to that of simple cells in primary visual cortex. However, the data indicate that, unlike in the cortex, orientation selectivity in the retina depends on the activity of inhibitory interneurons. The

Reduced Synaptic Vesicle Recycling during Hypoxia in Cultured Cortical Neurons

OpenAIRE

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

2017-01-01

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

Decreased astrocytic thrombospondin-1 secretion after chronic ammonia treatment reduces the level of synaptic proteins: in vitro and in vivo studies.

Science.gov (United States)

Jayakumar, Arumugam R; Tong, Xiao Y; Curtis, Kevin M; Ruiz-Cordero, Roberto; Shamaladevi, Nagarajarao; Abuzamel, Missa; Johnstone, Joshua; Gaidosh, Gabriel; Rama Rao, Kakulavarapu V; Norenberg, Michael D

2014-11-01

Chronic hepatic encephalopathy (CHE) is a major complication in patients with severe liver disease. Elevated blood and brain ammonia levels have been implicated in its pathogenesis, and astrocytes are the principal neural cells involved in this disorder. Since defective synthesis and release of astrocytic factors have been shown to impair synaptic integrity in other neurological conditions, we examined whether thrombospondin-1 (TSP-1), an astrocytic factor involved in the maintenance of synaptic integrity, is also altered in CHE. Cultured astrocytes were exposed to ammonia (NH₄Cl, 0.5-2.5 mM) for 1-10 days, and TSP-1 content was measured in cell extracts and culture media. Astrocytes exposed to ammonia exhibited a reduction in intra- and extracellular TSP-1 levels. Exposure of cultured neurons to conditioned media from ammonia-treated astrocytes showed a decrease in synaptophysin, PSD95, and synaptotagmin levels. Conditioned media from TSP-1 over-expressing astrocytes that were treated with ammonia, when added to cultured neurons, reversed the decline in synaptic proteins. Recombinant TSP-1 similarly reversed the decrease in synaptic proteins. Metformin, an agent known to increase TSP-1 synthesis in other cell types, also reversed the ammonia-induced TSP-1 reduction. Likewise, we found a significant decline in TSP-1 level in cortical astrocytes, as well as a reduction in synaptophysin content in vivo in a rat model of CHE. These findings suggest that TSP-1 may represent an important therapeutic target for CHE. Defective release of astrocytic factors may impair synaptic integrity in chronic hepatic encephalopathy. We found a reduction in the release of the astrocytic matricellular proteins thrombospondin-1 (TSP-1) in ammonia-treated astrocytes; such reduction was associated with a decrease in synaptic proteins caused by conditioned media from ammonia-treated astrocytes. Exposure of neurons to CM from ammonia-treated astrocytes, in which TSP-1 is over

msh/Msx gene family in neural development.

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Ramos, Casto; Robert, Benoît

2005-11-01

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

A Three-Threshold Learning Rule Approaches the Maximal Capacity of Recurrent Neural Networks.

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Alireza Alemi

2015-08-01

Full Text Available Understanding the theoretical foundations of how memories are encoded and retrieved in neural populations is a central challenge in neuroscience. A popular theoretical scenario for modeling memory function is the attractor neural network scenario, whose prototype is the Hopfield model. The model simplicity and the locality of the synaptic update rules come at the cost of a poor storage capacity, compared with the capacity achieved with perceptron learning algorithms. Here, by transforming the perceptron learning rule, we present an online learning rule for a recurrent neural network that achieves near-maximal storage capacity without an explicit supervisory error signal, relying only upon locally accessible information. The fully-connected network consists of excitatory binary neurons with plastic recurrent connections and non-plastic inhibitory feedback stabilizing the network dynamics; the memory patterns to be memorized are presented online as strong afferent currents, producing a bimodal distribution for the neuron synaptic inputs. Synapses corresponding to active inputs are modified as a function of the value of the local fields with respect to three thresholds. Above the highest threshold, and below the lowest threshold, no plasticity occurs. In between these two thresholds, potentiation/depression occurs when the local field is above/below an intermediate threshold. We simulated and analyzed a network of binary neurons implementing this rule and measured its storage capacity for different sizes of the basins of attraction. The storage capacity obtained through numerical simulations is shown to be close to the value predicted by analytical calculations. We also measured the dependence of capacity on the strength of external inputs. Finally, we quantified the statistics of the resulting synaptic connectivity matrix, and found that both the fraction of zero weight synapses and the degree of symmetry of the weight matrix increase with the

Synaptic protein changes after a chronic period of sensorimotor perturbation in adult rats: a potential role of phosphorylation/O-GlcNAcylation interplay.

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Fourneau, Julie; Canu, Marie-Hélène; Cieniewski-Bernard, Caroline; Bastide, Bruno; Dupont, Erwan

2018-05-28

In human, a chronic sensorimotor perturbation (SMP) through prolonged body immobilization alters motor task performance through a combination of peripheral and central factors. Studies performed on a rat model of SMP have shown biomolecular changes and a reorganization of sensorimotor cortex through events such as morphological modifications of dendritic spines (number, length, functionality). However, underlying mechanisms are still unclear. It is well known that phosphorylation regulates a wide field of synaptic activity leading to neuroplasticity. Another post-translational modification that interplays with phosphorylation is O-GlcNAcylation. This atypical glycosylation, reversible and dynamic, is involved in essential cellular and physiological processes such as synaptic activity, neuronal morphogenesis, learning and memory. We examined potential roles of phosphorylation/O-GlcNAcylation interplay in synaptic plasticity within rat sensorimotor cortex after a SMP period. For this purpose, sensorimotor cortex synaptosomes were separated by sucrose gradient, in order to isolate a subcellular compartment enriched in proteins involved in synaptic functions. A period of SMP induced plastic changes at the pre- and postsynaptic levels, characterized by a reduction of phosphorylation (synapsin1, AMPAR GluA2) and expression (synaptophysin, PSD-95, AMPAR GluA2) of synaptic proteins, as well as a decrease in MAPK/ERK42 activation. Expression levels of OGT/OGA enzymes was unchanged but we observed a specific reduction of synapsin1 O-GlcNAcylation in sensorimotor cortex synaptosomes. The synergistic regulation of synapsin1 phosphorylation/O-GlcNAcylation could affect presynaptic neurotransmitter release. Associated with other pre- and postsynaptic changes, synaptic efficacy could be impaired in somatosensory cortex of SMP rat. Thus, synapsin1 O-GlcNAcylation/phosphorylation interplay also appears to be involved in this synaptic plasticity by finely regulating neural activity

Age-related changes in the hippocampus (loss of synaptophysin and glial-synaptic interaction) are modified by systemic treatment with an NCAM-derived peptide, FGL.

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Ojo, Bunmi; Rezaie, Payam; Gabbott, Paul L; Davies, Heather; Colyer, Frances; Cowley, Thelma R; Lynch, Marina; Stewart, Michael G

2012-07-01

Altered synaptic morphology, progressive loss of synapses and glial (astrocyte and microglial) cell activation are considered as characteristic hallmarks of aging. Recent evidence suggests that there is a concomitant age-related decrease in expression of the presynaptic protein, synaptophysin, and the neuronal glycoprotein CD200, which, by interacting with its receptor, plays a role in maintaining microglia in a quiescent state. These age-related changes may be indicative of reduced neuroglial support of synapses. FG Loop (FGL) peptide synthesized from the second fibronectin type III module of neural cell adhesion molecule (NCAM), has previously been shown to attenuate age-related glial cell activation, and to 'restore' cognitive function in aged rats. The mechanisms by which FGL exerts these neuroprotective effects remain unclear, but could involve regulation of CD200, modifying glial-synaptic interactions (affecting neuroglial 'support' at synapses), or impacting directly on synaptic function. Light and electron microscopic (EM) analyses were undertaken to investigate whether systemic treatment with FGL (i) alters CD200, synaptophysin (presynaptic) and PSD-95 (postsynaptic) immunohistochemical expression levels, (ii) affects synaptic number, or (iii) exerts any effects on glial-synaptic interactions within young (4 month-old) and aged (22 month-old) rat hippocampus. Treatment with FGL attenuated the age-related loss of synaptophysin immunoreactivity (-ir) within CA3 and hilus (with no major effect on PSD-95-ir), and of CD200-ir specifically in the CA3 region. Ultrastructural morphometric analyses showed that FGL treatment (i) prevented age-related loss in astrocyte-synaptic contacts, (ii) reduced microglia-synaptic contacts in the CA3 stratum radiatum, but (iii) had no effect on the mean number of synapses in this region. These data suggest that FGL mediates its neuroprotective effects by regulating glial-synaptic interaction. Copyright © 2011 Elsevier Inc. All

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

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Sakyasingha eDasgupta

2015-09-01

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

Comprehensive quantitative comparison of the membrane proteome and PTM-ome of human embryonic stem cells and neural stem cells

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Braga, Marcella Nunes de Melo; Schulz, Melanie; Jakobsen, Lene

Introduction: Human embryonic stem cells (hESCs) can differentiate into all three germ layers and self-renew. Due to its ability to differentiate in vitro into human neural stem cells (hNSCs), which can further be differentiated into motor neurons and dopaminergic neurons, these cells are potential...... identified phosphorylated and SA glycosylated proteins, respectively. This study allowed us to identify several significantly regulated proteins during the differentiation process, including proteins involved in the early embryonic development as well as in the neural development. In the latter group...... of proteins we could identify a number of proteins associated with synaptic vesicles, which are vesicles that store neurotransmitters in the nerve-terminals. An example of an upregulated protein in hESCs is the gap junction alpha 1 (GJA1), a phosphorylated protein which plays a crucial role in embryonic...

Abnormal frontoparietal synaptic gain mediating the P300 in patients with psychotic disorder and their unaffected relatives.

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Díez, Álvaro; Ranlund, Siri; Pinotsis, Dimitris; Calafato, Stella; Shaikh, Madiha; Hall, Mei-Hua; Walshe, Muriel; Nevado, Ángel; Friston, Karl J; Adams, Rick A; Bramon, Elvira

2017-06-01

The "dysconnection hypothesis" of psychosis suggests that a disruption of functional integration underlies cognitive deficits and clinical symptoms. Impairments in the P300 potential are well documented in psychosis. Intrinsic (self-)connectivity in a frontoparietal cortical hierarchy during a P300 experiment was investigated. Dynamic Causal Modeling was used to estimate how evoked activity results from the dynamics of coupled neural populations and how neural coupling changes with the experimental factors. Twenty-four patients with psychotic disorder, twenty-four unaffected relatives, and twenty-five controls underwent EEG recordings during an auditory oddball paradigm. Sixteen frontoparietal network models (including primary auditory, superior parietal, and superior frontal sources) were analyzed and an optimal model of neural coupling, explaining diagnosis and genetic risk effects, as well as their interactions with task condition were identified. The winning model included changes in connectivity at all three hierarchical levels. Patients showed decreased self-inhibition-that is, increased cortical excitability-in left superior frontal gyrus across task conditions, compared with unaffected participants. Relatives had similar increases in excitability in left superior frontal and right superior parietal sources, and a reversal of the normal synaptic gain changes in response to targets relative to standard tones. It was confirmed that both subjects with psychotic disorder and their relatives show a context-independent loss of synaptic gain control at the highest hierarchy levels. The relatives also showed abnormal gain modulation responses to task-relevant stimuli. These may be caused by NMDA-receptor and/or GABAergic pathologies that change the excitability of superficial pyramidal cells and may be a potential biological marker for psychosis. Hum Brain Mapp 38:3262-3276, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Statistical Physics of Neural Systems with Nonadditive Dendritic Coupling

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David Breuer

2014-03-01

Full Text Available How neurons process their inputs crucially determines the dynamics of biological and artificial neural networks. In such neural and neural-like systems, synaptic input is typically considered to be merely transmitted linearly or sublinearly by the dendritic compartments. Yet, single-neuron experiments report pronounced supralinear dendritic summation of sufficiently synchronous and spatially close-by inputs. Here, we provide a statistical physics approach to study the impact of such nonadditive dendritic processing on single-neuron responses and the performance of associative-memory tasks in artificial neural networks. First, we compute the effect of random input to a neuron incorporating nonlinear dendrites. This approach is independent of the details of the neuronal dynamics. Second, we use those results to study the impact of dendritic nonlinearities on the network dynamics in a paradigmatic model for associative memory, both numerically and analytically. We find that dendritic nonlinearities maintain network convergence and increase the robustness of memory performance against noise. Interestingly, an intermediate number of dendritic branches is optimal for memory functionality.

Artificial neural networks for prediction of quality in resistance spot welding

International Nuclear Information System (INIS)

Martin, O.; Lopez, M.; Martin, F.

2006-01-01

An artificial neural network is proposed as a tool for predicting from three parameters (weld time, current intensity and electrode sort) if the quality of a resistance spot weld reaches a certain level or not. The quality id determined by cross tension testing. The fact of reaching this quality level or not is the desired output that goes with each input of the artificial neural network during its supervised learning. The available data set is made up of input/desired output pairs and is split randomly into a training subset (to update synaptic weight values) and a validation subset (to avoid overfitting phenomenon by means of cross validation). (Author) 44 refs

Synapse geometry and receptor dynamics modulate synaptic strength.

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Dominik Freche

Full Text Available Synaptic transmission relies on several processes, such as the location of a released vesicle, the number and type of receptors, trafficking between the postsynaptic density (PSD and extrasynaptic compartment, as well as the synapse organization. To study the impact of these parameters on excitatory synaptic transmission, we present a computational model for the fast AMPA-receptor mediated synaptic current. We show that in addition to the vesicular release probability, due to variations in their release locations and the AMPAR distribution, the postsynaptic current amplitude has a large variance, making a synapse an intrinsic unreliable device. We use our model to examine our experimental data recorded from CA1 mice hippocampal slices to study the differences between mEPSC and evoked EPSC variance. The synaptic current but not the coefficient of variation is maximal when the active zone where vesicles are released is apposed to the PSD. Moreover, we find that for certain type of synapses, receptor trafficking can affect the magnitude of synaptic depression. Finally, we demonstrate that perisynaptic microdomains located outside the PSD impacts synaptic transmission by regulating the number of desensitized receptors and their trafficking to the PSD. We conclude that geometrical modifications, reorganization of the PSD or perisynaptic microdomains modulate synaptic strength, as the mechanisms underlying long-term plasticity.

Structural Components of Synaptic Plasticity and Memory Consolidation

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Bailey, Craig H.; Kandel, Eric R.; Harris, Kristen M.

2015-01-01

Consolidation of implicit memory in the invertebrate Aplysia and explicit memory in the mammalian hippocampus are associated with remodeling and growth of preexisting synapses and the formation of new synapses. Here, we compare and contrast structural components of the synaptic plasticity that underlies these two distinct forms of memory. In both cases, the structural changes involve time-dependent processes. Thus, some modifications are transient and may contribute to early formative stages of long-term memory, whereas others are more stable, longer lasting, and likely to confer persistence to memory storage. In addition, we explore the possibility that trans-synaptic signaling mechanisms governing de novo synapse formation during development can be reused in the adult for the purposes of structural synaptic plasticity and memory storage. Finally, we discuss how these mechanisms set in motion structural rearrangements that prepare a synapse to strengthen the same memory and, perhaps, to allow it to take part in other memories as a basis for understanding how their anatomical representation results in the enhanced expression and storage of memories in the brain. PMID:26134321

Potential Mechanisms and Functions of Intermittent Neural Synchronization

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Sungwoo Ahn

2017-05-01

Full Text Available Neural synchronization is believed to play an important role in different brain functions. Synchrony in cortical and subcortical circuits is frequently variable in time and not perfect. Few long intervals of desynchronized dynamics may be functionally different from many short desynchronized intervals although the average synchrony may be the same. Recent analysis of imperfect synchrony in different neural systems reported one common feature: neural oscillations may go out of synchrony frequently, but primarily for a short time interval. This study explores potential mechanisms and functional advantages of this short desynchronizations dynamics using computational neuroscience techniques. We show that short desynchronizations are exhibited in coupled neurons if their delayed rectifier potassium current has relatively large values of the voltage-dependent activation time-constant. The delayed activation of potassium current is associated with generation of quickly-rising action potential. This “spikiness” is a very general property of neurons. This may explain why very different neural systems exhibit short desynchronization dynamics. We also show how the distribution of desynchronization durations may be independent of the synchronization strength. Finally, we show that short desynchronization dynamics requires weaker synaptic input to reach a pre-set synchrony level. Thus, this dynamics allows for efficient regulation of synchrony and may promote efficient formation of synchronous neural assemblies.

Synaptic vesicle distribution by conveyor belt.

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Moughamian, Armen J; Holzbaur, Erika L F

2012-03-02

The equal distribution of synaptic vesicles among synapses along the axon is critical for robust neurotransmission. Wong et al. show that the continuous circulation of synaptic vesicles throughout the axon driven by molecular motors ultimately yields this even distribution. Copyright © 2012 Elsevier Inc. All rights reserved.

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

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Ueda, Atsushi; Wu, Chun-Fang

2012-03-01

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

Interregional synaptic maps among engram cells underlie memory formation.

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

2018-04-27

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

Memory and pattern storage in neural networks with activity dependent synapses

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Mejias, J. F.; Torres, J. J.

2009-01-01

We present recently obtained results on the influence of the interplay between several activity dependent synaptic mechanisms, such as short-term depression and facilitation, on the maximum memory storage capacity in an attractor neural network [1]. In contrast with the case of synaptic depression, which drastically reduces the capacity of the network to store and retrieve activity patterns [2], synaptic facilitation is able to enhance the memory capacity in different situations. In particular, we find that a convenient balance between depression and facilitation can enhance the memory capacity, reaching maximal values similar to those obtained with static synapses, that is, without activity-dependent processes. We also argue, employing simple arguments, that this level of balance is compatible with experimental data recorded from some cortical areas, where depression and facilitation may play an important role for both memory-oriented tasks and information processing. We conclude that depressing synapses with a certain level of facilitation allow to recover the good retrieval properties of networks with static synapses while maintaining the nonlinear properties of dynamic synapses, convenient for information processing and coding.

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

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

2017-10-01

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

The mouse that roared: neural mechanisms of social hierarchy.

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Wang, Fei; Kessels, Helmut W; Hu, Hailan

2014-11-01

Hierarchical social status greatly influences behavior and health. Human and animal studies have begun to identify the brain regions that are activated during the formation of social hierarchies. They point towards the prefrontal cortex (PFC) as a central regulator, with brain areas upstream of the PFC conveying information about social status, and downstream brain regions executing dominance behavior. This review summarizes our current knowledge on the neural circuits that control social status. We discuss how the neural mechanisms for various types of dominance behavior can be studied in laboratory rodents by selective manipulation of neuronal activity or synaptic plasticity. These studies may help in finding the cause of social stress-related mental and physical health problems. Copyright © 2014 Elsevier Ltd. All rights reserved.

PRRT2: from Paroxysmal Disorders to Regulation of Synaptic Function.

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

2016-10-01

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

A robust and scalable neuromorphic communication system by combining synaptic time multiplexing and MIMO-OFDM.

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Srinivasa, Narayan; Zhang, Deying; Grigorian, Beayna

2014-03-01

This paper describes a novel architecture for enabling robust and efficient neuromorphic communication. The architecture combines two concepts: 1) synaptic time multiplexing (STM) that trades space for speed of processing to create an intragroup communication approach that is firing rate independent and offers more flexibility in connectivity than cross-bar architectures and 2) a wired multiple input multiple output (MIMO) communication with orthogonal frequency division multiplexing (OFDM) techniques to enable a robust and efficient intergroup communication for neuromorphic systems. The MIMO-OFDM concept for the proposed architecture was analyzed by simulating large-scale spiking neural network architecture. Analysis shows that the neuromorphic system with MIMO-OFDM exhibits robust and efficient communication while operating in real time with a high bit rate. Through combining STM with MIMO-OFDM techniques, the resulting system offers a flexible and scalable connectivity as well as a power and area efficient solution for the implementation of very large-scale spiking neural architectures in hardware.

Bumps, breathers, and waves in a neural network with spike frequency adaptation

International Nuclear Information System (INIS)

Coombes, S.; Owen, M.R.

2005-01-01

We introduce a continuum model of neural tissue that includes the effects of spike frequency adaptation (SFA). The basic model is an integral equation for synaptic activity that depends upon nonlocal network connectivity, synaptic response, and the firing rate of a single neuron. We consider a phenomenological model of SFA via a simple state-dependent threshold firing rate function. As without SFA, Mexican-hat connectivity allows for the existence of spatially localized states (bumps). Importantly recent Evans function techniques are used to show that bumps may destabilize leading to the emergence of breathers and traveling waves. Moreover, a similar analysis for traveling pulses leads to the conditions necessary to observe a stable traveling breather. Simulations confirm our theoretical predictions and illustrate the rich behavior of this model

Evolving RBF neural networks for adaptive soft-sensor design.

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Alexandridis, Alex

2013-12-01

This work presents an adaptive framework for building soft-sensors based on radial basis function (RBF) neural network models. The adaptive fuzzy means algorithm is utilized in order to evolve an RBF network, which approximates the unknown system based on input-output data from it. The methodology gradually builds the RBF network model, based on two separate levels of adaptation: On the first level, the structure of the hidden layer is modified by adding or deleting RBF centers, while on the second level, the synaptic weights are adjusted with the recursive least squares with exponential forgetting algorithm. The proposed approach is tested on two different systems, namely a simulated nonlinear DC Motor and a real industrial reactor. The results show that the produced soft-sensors can be successfully applied to model the two nonlinear systems. A comparison with two different adaptive modeling techniques, namely a dynamic evolving neural-fuzzy inference system (DENFIS) and neural networks trained with online backpropagation, highlights the advantages of the proposed methodology.

Using strategic movement to calibrate a neural compass: a spiking network for tracking head direction in rats and robots.

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Peter Stratton

Full Text Available The head direction (HD system in mammals contains neurons that fire to represent the direction the animal is facing in its environment. The ability of these cells to reliably track head direction even after the removal of external sensory cues implies that the HD system is calibrated to function effectively using just internal (proprioceptive and vestibular inputs. Rat pups and other infant mammals display stereotypical warm-up movements prior to locomotion in novel environments, and similar warm-up movements are seen in adult mammals with certain brain lesion-induced motor impairments. In this study we propose that synaptic learning mechanisms, in conjunction with appropriate movement strategies based on warm-up movements, can calibrate the HD system so that it functions effectively even in darkness. To examine the link between physical embodiment and neural control, and to determine that the system is robust to real-world phenomena, we implemented the synaptic mechanisms in a spiking neural network and tested it on a mobile robot platform. Results show that the combination of the synaptic learning mechanisms and warm-up movements are able to reliably calibrate the HD system so that it accurately tracks real-world head direction, and that calibration breaks down in systematic ways if certain movements are omitted. This work confirms that targeted, embodied behaviour can be used to calibrate neural systems, demonstrates that 'grounding' of modelled biological processes in the real world can reveal underlying functional principles (supporting the importance of robotics to biology, and proposes a functional role for stereotypical behaviours seen in infant mammals and those animals with certain motor deficits. We conjecture that these calibration principles may extend to the calibration of other neural systems involved in motion tracking and the representation of space, such as grid cells in entorhinal cortex.

Using strategic movement to calibrate a neural compass: a spiking network for tracking head direction in rats and robots.

Science.gov (United States)

Stratton, Peter; Milford, Michael; Wyeth, Gordon; Wiles, Janet

2011-01-01

The head direction (HD) system in mammals contains neurons that fire to represent the direction the animal is facing in its environment. The ability of these cells to reliably track head direction even after the removal of external sensory cues implies that the HD system is calibrated to function effectively using just internal (proprioceptive and vestibular) inputs. Rat pups and other infant mammals display stereotypical warm-up movements prior to locomotion in novel environments, and similar warm-up movements are seen in adult mammals with certain brain lesion-induced motor impairments. In this study we propose that synaptic learning mechanisms, in conjunction with appropriate movement strategies based on warm-up movements, can calibrate the HD system so that it functions effectively even in darkness. To examine the link between physical embodiment and neural control, and to determine that the system is robust to real-world phenomena, we implemented the synaptic mechanisms in a spiking neural network and tested it on a mobile robot platform. Results show that the combination of the synaptic learning mechanisms and warm-up movements are able to reliably calibrate the HD system so that it accurately tracks real-world head direction, and that calibration breaks down in systematic ways if certain movements are omitted. This work confirms that targeted, embodied behaviour can be used to calibrate neural systems, demonstrates that 'grounding' of modelled biological processes in the real world can reveal underlying functional principles (supporting the importance of robotics to biology), and proposes a functional role for stereotypical behaviours seen in infant mammals and those animals with certain motor deficits. We conjecture that these calibration principles may extend to the calibration of other neural systems involved in motion tracking and the representation of space, such as grid cells in entorhinal cortex.

Real-time cerebellar neuroprosthetic system based on a spiking neural network model of motor learning.

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Xu, Tao; Xiao, Na; Zhai, Xiaolong; Kwan Chan, Pak; Tin, Chung

2018-02-01

Damage to the brain, as a result of various medical conditions, impacts the everyday life of patients and there is still no complete cure to neurological disorders. Neuroprostheses that can functionally replace the damaged neural circuit have recently emerged as a possible solution to these problems. Here we describe the development of a real-time cerebellar neuroprosthetic system to substitute neural function in cerebellar circuitry for learning delay eyeblink conditioning (DEC). The system was empowered by a biologically realistic spiking neural network (SNN) model of the cerebellar neural circuit, which considers the neuronal population and anatomical connectivity of the network. The model simulated synaptic plasticity critical for learning DEC. This SNN model was carefully implemented on a field programmable gate array (FPGA) platform for real-time simulation. This hardware system was interfaced in in vivo experiments with anesthetized rats and it used neural spikes recorded online from the animal to learn and trigger conditioned eyeblink in the animal during training. This rat-FPGA hybrid system was able to process neuronal spikes in real-time with an embedded cerebellum model of ~10 000 neurons and reproduce learning of DEC with different inter-stimulus intervals. Our results validated that the system performance is physiologically relevant at both the neural (firing pattern) and behavioral (eyeblink pattern) levels. This integrated system provides the sufficient computation power for mimicking the cerebellar circuit in real-time. The system interacts with the biological system naturally at the spike level and can be generalized for including other neural components (neuron types and plasticity) and neural functions for potential neuroprosthetic applications.

Brief environmental enrichment elicits metaplasticity of hippocampal synaptic potentiation in vivo

Directory of Open Access Journals (Sweden)

Denise eManahan-Vaughan

2012-12-01

Full Text Available Long-term environmental enrichment (EE elicits enduring effects on the adult brain, including altered synaptic plasticity. Synaptic plasticity may underlie memory formation and includes robust (>24h and weak (<2h forms of long-term potentiation (LTP and long-term depression (LTD. Most studies of the effect of EE on synaptic efficacy have examined the consequences of very prolonged EE-exposure. It is unclear whether brief exposure to EE can alter synaptic plasticity. Clarifying this issue could help develop strategies to address cognitive deficits arising from neglect in children or adults.We assessed whether short-term EE elicits alterations in hippocampal synaptic plasticity and if social context may play a role. Adult mice were exposed to EE for 14 consecutive days. We found that robust late-LTP (>24h and short-term depression (<2h at Schaffer-collateral-CA1 synapses in freely behaving mice were unaltered, whereas early-LTP (E-LTP, <2h was significantly enhanced by EE. Effects were transient: E-LTP returned to control levels 1 week after cessation of EE. Six weeks later animals were re-exposed to EE for 14d. Under these conditions, E-LTP was facilitated into L-LTP (>24h, suggesting that metaplasticity was induced during the first EE experience and that EE-mediated modifications are cumulative. Effects were absent in mice that underwent solitary enrichment or were group-housed without EE. These data suggest that EE in naïve animals strengthens E-LTP, and also promotes L-LTP in animals that underwent EE in the past. This indicates that brief exposure to EE, particularly under social conditions can elicit lasting positive effects on synaptic strength that may have beneficial consequences for cognition that depends on synaptic plasticity.

New numerical approximation for solving fractional delay differential equations of variable order using artificial neural networks

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Zúñiga-Aguilar, C. J.; Coronel-Escamilla, A.; Gómez-Aguilar, J. F.; Alvarado-Martínez, V. M.; Romero-Ugalde, H. M.

2018-02-01

In this paper, we approximate the solution of fractional differential equations with delay using a new approach based on artificial neural networks. We consider fractional differential equations of variable order with the Mittag-Leffler kernel in the Liouville-Caputo sense. With this new neural network approach, an approximate solution of the fractional delay differential equation is obtained. Synaptic weights are optimized using the Levenberg-Marquardt algorithm. The neural network effectiveness and applicability were validated by solving different types of fractional delay differential equations, linear systems with delay, nonlinear systems with delay and a system of differential equations, for instance, the Newton-Leipnik oscillator. The solution of the neural network was compared with the analytical solutions and the numerical simulations obtained through the Adams-Bashforth-Moulton method. To show the effectiveness of the proposed neural network, different performance indices were calculated.

Autism as an adaptive common variant pathway for human brain development

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Mark H. Johnson

2017-06-01

Full Text Available While research on focal perinatal lesions has provided evidence for recovery of function, much less is known about processes of brain adaptation resulting from mild but widespread disturbances to neural processing over the early years (such as alterations in synaptic efficiency. Rather than being viewed as a direct behavioral consequence of life-long neural dysfunction, I propose that autism is best viewed as the end result of engaging adaptive processes during a sensitive period. From this perspective, autism is not appropriately described as a disorder of neurodevelopment, but rather as an adaptive common variant pathway of human functional brain development.

Experimental Implementation of a Biometric Laser Synaptic Sensor

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Alexander N. Pisarchik

2013-12-01

Full Text Available We fabricate a biometric laser fiber synaptic sensor to transmit information from one neuron cell to the other by an optical way. The optical synapse is constructed on the base of an erbium-doped fiber laser, whose pumped diode current is driven by a pre-synaptic FitzHugh–Nagumo electronic neuron, and the laser output controls a post-synaptic FitzHugh–Nagumo electronic neuron. The implemented laser synapse displays very rich dynamics, including fixed points, periodic orbits with different frequency-locking ratios and chaos. These regimes can be beneficial for efficient biorobotics, where behavioral flexibility subserved by synaptic connectivity is a challenge.

Energy-efficient neural information processing in individual neurons and neuronal networks.

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Yu, Lianchun; Yu, Yuguo

2017-11-01

Brains are composed of networks of an enormous number of neurons interconnected with synapses. Neural information is carried by the electrical signals within neurons and the chemical signals among neurons. Generating these electrical and chemical signals is metabolically expensive. The fundamental issue raised here is whether brains have evolved efficient ways of developing an energy-efficient neural code from the molecular level to the circuit level. Here, we summarize the factors and biophysical mechanisms that could contribute to the energy-efficient neural code for processing input signals. The factors range from ion channel kinetics, body temperature, axonal propagation of action potentials, low-probability release of synaptic neurotransmitters, optimal input and noise, the size of neurons and neuronal clusters, excitation/inhibition balance, coding strategy, cortical wiring, and the organization of functional connectivity. Both experimental and computational evidence suggests that neural systems may use these factors to maximize the efficiency of energy consumption in processing neural signals. Studies indicate that efficient energy utilization may be universal in neuronal systems as an evolutionary consequence of the pressure of limited energy. As a result, neuronal connections may be wired in a highly economical manner to lower energy costs and space. Individual neurons within a network may encode independent stimulus components to allow a minimal number of neurons to represent whole stimulus characteristics efficiently. This basic principle may fundamentally change our view of how billions of neurons organize themselves into complex circuits to operate and generate the most powerful intelligent cognition in nature. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Molecular mechanisms of synaptic remodeling in alcoholism.

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Kyzar, Evan J; Pandey, Subhash C

2015-08-05

Alcohol use and alcohol addiction represent dysfunctional brain circuits resulting from neuroadaptive changes during protracted alcohol exposure and its withdrawal. Alcohol exerts a potent effect on synaptic plasticity and dendritic spine formation in specific brain regions, providing a neuroanatomical substrate for the pathophysiology of alcoholism. Epigenetics has recently emerged as a critical regulator of gene expression and synaptic plasticity-related events in the brain. Alcohol exposure and withdrawal induce changes in crucial epigenetic processes in the emotional brain circuitry (amygdala) that may be relevant to the negative affective state defined as the "dark side" of addiction. Here, we review the literature concerning synaptic plasticity and epigenetics, with a particular focus on molecular events related to dendritic remodeling during alcohol abuse and alcoholism. Targeting epigenetic processes that modulate synaptic plasticity may yield novel treatments for alcoholism. Published by Elsevier Ireland Ltd.

Adaptive competitive learning neural networks

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Ahmed R. Abas

2013-11-01

Full Text Available In this paper, the adaptive competitive learning (ACL neural network algorithm is proposed. This neural network not only groups similar input feature vectors together but also determines the appropriate number of groups of these vectors. This algorithm uses a new proposed criterion referred to as the ACL criterion. This criterion evaluates different clustering structures produced by the ACL neural network for an input data set. Then, it selects the best clustering structure and the corresponding network architecture for this data set. The selected structure is composed of the minimum number of clusters that are compact and balanced in their sizes. The selected network architecture is efficient, in terms of its complexity, as it contains the minimum number of neurons. Synaptic weight vectors of these neurons represent well-separated, compact and balanced clusters in the input data set. The performance of the ACL algorithm is evaluated and compared with the performance of a recently proposed algorithm in the literature in clustering an input data set and determining its number of clusters. Results show that the ACL algorithm is more accurate and robust in both determining the number of clusters and allocating input feature vectors into these clusters than the other algorithm especially with data sets that are sparsely distributed.

Prenatal Nicotine Exposure Disrupts Infant Neural Markers of Orienting.

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King, Erin; Campbell, Alana; Belger, Aysenil; Grewen, Karen

2017-08-17

Prenatal nicotine exposure (PNE) from maternal cigarette-smoking is linked to developmental deficits, including impaired auditory processing, language, generalized intelligence, attention and sleep. Fetal brain undergoes massive growth, organization and connectivity during gestation, making it particularly vulnerable to neurotoxic insult. Nicotine binds to nicotinic acetylcholine receptors, which are extensively involved in growth, connectivity and function of developing neural circuitry and neurotransmitter systems. Thus, PNE may have long-term impact on neurobehavioral development. The purpose of this study was to compare the auditory K-complex, an event-related potential reflective of auditory gating, sleep preservation and memory consolidation during sleep, in infants with and without PNE and to relate these neural correlates to neurobehavioral development. We compared brain responses to an auditory paired-click paradigm in 3 to 5-month-old infants during Stage 2 sleep, when the K-complex is best observed. We measured component amplitude and delta activity during the K-complex. PNE may impair auditory sensory gating, which may contribute to disrupted sleep and to reduced auditory discrimination and learning, attention re-orienting and/or arousal during wakefulness reported in other studies. Links between PNE and reduced K-complex amplitude and delta power may represent altered cholinergic and GABAergic synaptic programming, and possibly reflect early neural bases for PNE-linked disruptions in sleep quality and auditory processing. These may pose significant disadvantage for language acquisition, attention, and social interaction necessary for academic and social success. © The Author 2017. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

A neural model for temporal order judgments and their active recalibration: a common mechanism for space and time?

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Mingbo eCai

2012-11-01

Full Text Available When observers experience a constant delay between their motor actions and sensory feedback, their perception of the temporal order between actions and sensations adapt (Stetson et al., 2006a. We present here a novel neural model that can explain temporal order judgments (TOJs and their recalibration. Our model employs three ubiquitous features of neural systems: 1 information pooling, 2 opponent processing, and 3 synaptic scaling. Specifically, the model proposes that different populations of neurons encode different delays between motor-sensory events, the outputs of these populations feed into rivaling neural populations (encoding before and after, and the activity difference between these populations determines the perceptual judgment. As a consequence of synaptic scaling of input weights, motor acts which are consistently followed by delayed sensory feedback will cause the network to recalibrate its point of subjective simultaneity. The structure of our model raises the possibility that recalibration of TOJs is a temporal analogue to the motion aftereffect. In other words, identical neural mechanisms may be used to make perceptual determinations about both space and time. Our model captures behavioral recalibration results for different numbers of adapting trials and different adapting delays. In line with predictions of the model, we additionally demonstrate that temporal recalibration can last through time, in analogy to storage of the motion aftereffect.

Synaptic Contacts Enhance Cell-to-Cell Tau Pathology Propagation

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Sara Calafate

2015-05-01

Full Text Available Accumulation of insoluble Tau protein aggregates and stereotypical propagation of Tau pathology through the brain are common hallmarks of tauopathies, including Alzheimer’s disease (AD. Propagation of Tau pathology appears to occur along connected neurons, but whether synaptic contacts between neurons are facilitating propagation has not been demonstrated. Using quantitative in vitro models, we demonstrate that, in parallel to non-synaptic mechanisms, synapses, but not merely the close distance between the cells, enhance the propagation of Tau pathology between acceptor hippocampal neurons and Tau donor cells. Similarly, in an artificial neuronal network using microfluidic devices, synapses and synaptic activity are promoting neuronal Tau pathology propagation in parallel to the non-synaptic mechanisms. Our work indicates that the physical presence of synaptic contacts between neurons facilitate Tau pathology propagation. These findings can have implications for synaptic repair therapies, which may turn out to have adverse effects by promoting propagation of Tau pathology.

Synaptic Contacts Enhance Cell-to-Cell Tau Pathology Propagation.

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Calafate, Sara; Buist, Arjan; Miskiewicz, Katarzyna; Vijayan, Vinoy; Daneels, Guy; de Strooper, Bart; de Wit, Joris; Verstreken, Patrik; Moechars, Diederik

2015-05-26

Accumulation of insoluble Tau protein aggregates and stereotypical propagation of Tau pathology through the brain are common hallmarks of tauopathies, including Alzheimer's disease (AD). Propagation of Tau pathology appears to occur along connected neurons, but whether synaptic contacts between neurons are facilitating propagation has not been demonstrated. Using quantitative in vitro models, we demonstrate that, in parallel to non-synaptic mechanisms, synapses, but not merely the close distance between the cells, enhance the propagation of Tau pathology between acceptor hippocampal neurons and Tau donor cells. Similarly, in an artificial neuronal network using microfluidic devices, synapses and synaptic activity are promoting neuronal Tau pathology propagation in parallel to the non-synaptic mechanisms. Our work indicates that the physical presence of synaptic contacts between neurons facilitate Tau pathology propagation. These findings can have implications for synaptic repair therapies, which may turn out to have adverse effects by promoting propagation of Tau pathology. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Firing rate dynamics in recurrent spiking neural networks with intrinsic and network heterogeneity.

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Ly, Cheng

2015-12-01

Heterogeneity of neural attributes has recently gained a lot of attention and is increasing recognized as a crucial feature in neural processing. Despite its importance, this physiological feature has traditionally been neglected in theoretical studies of cortical neural networks. Thus, there is still a lot unknown about the consequences of cellular and circuit heterogeneity in spiking neural networks. In particular, combining network or synaptic heterogeneity and intrinsic heterogeneity has yet to be considered systematically despite the fact that both are known to exist and likely have significant roles in neural network dynamics. In a canonical recurrent spiking neural network model, we study how these two forms of heterogeneity lead to different distributions of excitatory firing rates. To analytically characterize how these types of heterogeneities affect the network, we employ a dimension reduction method that relies on a combination of Monte Carlo simulations and probability density function equations. We find that the relationship between intrinsic and network heterogeneity has a strong effect on the overall level of heterogeneity of the firing rates. Specifically, this relationship can lead to amplification or attenuation of firing rate heterogeneity, and these effects depend on whether the recurrent network is firing asynchronously or rhythmically firing. These observations are captured with the aforementioned reduction method, and furthermore simpler analytic descriptions based on this dimension reduction method are developed. The final analytic descriptions provide compact and descriptive formulas for how the relationship between intrinsic and network heterogeneity determines the firing rate heterogeneity dynamics in various settings.

Defective Glycinergic Synaptic Transmission in Zebrafish Motility Mutants

OpenAIRE

Hirata, Hiromi; Carta, Eloisa; Yamanaka, Iori; Harvey, Robert J.; Kuwada, John Y.

2010-01-01

Glycine is a major inhibitory neurotransmitter in the spinal cord and brainstem. Recently, in vivo analysis of glycinergic synaptic transmission has been pursued in zebrafish using molecular genetics. An ENU mutagenesis screen identified two behavioral mutants that are defective in glycinergic synaptic transmission. Zebrafish bandoneon (beo) mutants have a defect in glrbb, one of the duplicated glycine receptor (GlyR) β subunit genes. These mutants exhibit a loss of glycinergic synaptic ...

Myostatin-like proteins regulate synaptic function and neuronal morphology.

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Augustin, Hrvoje; McGourty, Kieran; Steinert, Joern R; Cochemé, Helena M; Adcott, Jennifer; Cabecinha, Melissa; Vincent, Alec; Halff, Els F; Kittler, Josef T; Boucrot, Emmanuel; Partridge, Linda

2017-07-01

Growth factors of the TGFβ superfamily play key roles in regulating neuronal and muscle function. Myostatin (or GDF8) and GDF11 are potent negative regulators of skeletal muscle mass. However, expression of myostatin and its cognate receptors in other tissues, including brain and peripheral nerves, suggests a potential wider biological role. Here, we show that Myoglianin (MYO), the Drosophila homolog of myostatin and GDF11, regulates not only body weight and muscle size, but also inhibits neuromuscular synapse strength and composition in a Smad2-dependent manner. Both myostatin and GDF11 affected synapse formation in isolated rat cortical neuron cultures, suggesting an effect on synaptogenesis beyond neuromuscular junctions. We also show that MYO acts in vivo to inhibit synaptic transmission between neurons in the escape response neural circuit of adult flies. Thus, these anti-myogenic proteins act as important inhibitors of synapse function and neuronal growth. © 2017. Published by The Company of Biologists Ltd.

Synaptic Correlates of Working Memory Capacity.

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Mi, Yuanyuan; Katkov, Mikhail; Tsodyks, Misha

2017-01-18

Psychological studies indicate that human ability to keep information in readily accessible working memory is limited to four items for most people. This extremely low capacity severely limits execution of many cognitive tasks, but its neuronal underpinnings remain unclear. Here we show that in the framework of synaptic theory of working memory, capacity can be analytically estimated to scale with characteristic time of short-term synaptic depression relative to synaptic current time constant. The number of items in working memory can be regulated by external excitation, enabling the system to be tuned to the desired load and to clear the working memory of currently held items to make room for new ones. Copyright © 2017 Elsevier Inc. All rights reserved.

Neural networks for feedback feedforward nonlinear control systems.

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Parisini, T; Zoppoli, R

1994-01-01

This paper deals with the problem of designing feedback feedforward control strategies to drive the state of a dynamic system (in general, nonlinear) so as to track any desired trajectory joining the points of given compact sets, while minimizing a certain cost function (in general, nonquadratic). Due to the generality of the problem, conventional methods are difficult to apply. Thus, an approximate solution is sought by constraining control strategies to take on the structure of multilayer feedforward neural networks. After discussing the approximation properties of neural control strategies, a particular neural architecture is presented, which is based on what has been called the "linear-structure preserving principle". The original functional problem is then reduced to a nonlinear programming one, and backpropagation is applied to derive the optimal values of the synaptic weights. Recursive equations to compute the gradient components are presented, which generalize the classical adjoint system equations of N-stage optimal control theory. Simulation results related to nonlinear nonquadratic problems show the effectiveness of the proposed method.

Bioelectrochemical control of neural cell development on conducting polymers.

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

2010-12-01

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

Depression as a Glial-Based Synaptic Dysfunction

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Daniel eRial

2016-01-01

Full Text Available Recent studies combining pharmacological, behavioral, electrophysiological and molecular approaches indicate that depression results from maladaptive neuroplastic processing occurring in defined frontolimbic circuits responsible for emotional processing such as the prefrontal cortex, hippocampus, amygdala and ventral striatum. However, the exact mechanisms controlling synaptic plasticity that are disrupted to trigger depressive conditions have not been elucidated. Since glial cells (astrocytes and microglia tightly and dynamically interact with synapses, engaging a bi-directional communication critical for the processing of synaptic information, we now revisit the role of glial cells in the etiology of depression focusing on a dysfunction of the ‘quad-partite’ synapse. This interest is supported by the observations that depressive-like conditions are associated with a decreased density and hypofunction of astrocytes and with an increase microglia ‘activation’ in frontolimbic regions, which is expected to contribute for the synaptic dysfunction present in depression. Furthermore, the traditional culprits of depression (glucocorticoids, biogenic amines, BDNF affect glia functioning, whereas antidepressant treatments (SSRIs, electroshock, deep brain stimulation recover glia functioning. In this context of a quad-partite synapse, systems modulating glia-synapse bidirectional communication - such as the purinergic neuromodulation system operated by ATP and adenosine - emerge as promising candidates to re-normalize synaptic function by combining direct synaptic effects with an ability to also control astrocyte and microglia function. This proposed triple action of purines to control aberrant synaptic function illustrates the rationale to consider the interference with glia dysfunction as a mechanism of action driving the design of future pharmacological tools to manage depression.

Process for forming synapses in neural networks and resistor therefor

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Fu, Chi Y.

1996-01-01

Customizable neural network in which one or more resistors form each synapse. All the resistors in the synaptic array are identical, thus simplifying the processing issues. Highly doped, amorphous silicon is used as the resistor material, to create extremely high resistances occupying very small spaces. Connected in series with each resistor in the array is at least one severable conductor whose uppermost layer has a lower reflectivity of laser energy than typical metal conductors at a desired laser wavelength.

Early life stress accelerates behavioral and neural maturation of the hippocampus in male mice.

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Bath, K; Manzano-Nieves, G; Goodwill, H

2016-06-01

Early life stress (ELS) increases the risk for later cognitive and emotional dysfunction. ELS is known to truncate neural development through effects on suppressing cell birth, increasing cell death, and altering neuronal morphology, effects that have been associated with behavioral profiles indicative of precocious maturation. However, how earlier silencing of growth drives accelerated behavioral maturation has remained puzzling. Here, we test the novel hypothesis that, ELS drives a switch from growth to maturation to accelerate neural and behavioral development. To test this, we used a mouse model of ELS, fragmented maternal care, and a cross-sectional dense sampling approach focusing on hippocampus and measured effects of ELS on the ontogeny of behavioral development and biomarkers of neural maturation. Consistent with previous work, ELS was associated with an earlier developmental decline in expression of markers of cell proliferation (Ki-67) and differentiation (doublecortin). However, ELS also led to a precocious arrival of Parvalbumin-positive cells, led to an earlier switch in NMDA receptor subunit expression (marker of synaptic maturity), and was associated with an earlier rise in myelin basic protein expression (key component of the myelin sheath). In addition, in a contextual fear-conditioning task, ELS accelerated the timed developmental suppression of contextual fear. Together, these data provide support for the hypothesis that ELS serves to switch neurodevelopment from processes of growth to maturation and promotes accelerated development of some forms of emotional learning. Copyright © 2016 Elsevier Inc. All rights reserved.

Synaptic Conversion of Chloride-Dependent Synapses in Spinal Nociceptive Circuits: Roles in Neuropathic Pain

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Mark S. Cooper

2011-01-01

Full Text Available Electrophysiological conversion of chloride-dependent synapses from inhibitory to excitatory function, as a result of aberrant neuronal chloride homeostasis, is a known mechanism for the genesis of neuropathic pain. This paper examines theoretically how this type of synaptic conversion can disrupt circuit logic in spinal nociceptive circuits. First, a mathematical scaling factor is developed to represent local aberration in chloride electrochemical driving potential. Using this mathematical scaling factor, electrophysiological symbols are developed to represent the magnitude of synaptic conversion within nociceptive circuits. When inserted into a nociceptive circuit diagram, these symbols assist in understanding the generation of neuropathic pain associated with the collapse of transmembrane chloride gradients. A more generalized scaling factor is also derived to represent the interplay of chloride and bicarbonate driving potentials on the function of GABAergic and glycinergic synapses. These mathematical and symbolic representations of synaptic conversion help illustrate the critical role that anion driving potentials play in the transduction of pain. Using these representations, we discuss ramifications of glial-mediated synaptic conversion in the genesis, and treatment, of neuropathic pain.

Neural plasticity and behavior - sixty years of conceptual advances.

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Sweatt, J David

2016-10-01

This brief review summarizes 60 years of conceptual advances that have demonstrated a role for active changes in neuronal connectivity as a controller of behavior and behavioral change. Seminal studies in the first phase of the six-decade span of this review firmly established the cellular basis of behavior - a concept that we take for granted now, but which was an open question at the time. Hebbian plasticity, including long-term potentiation and long-term depression, was then discovered as being important for local circuit refinement in the context of memory formation and behavioral change and stabilization in the mammalian central nervous system. Direct demonstration of plasticity of neuronal circuit function in vivo, for example, hippocampal neurons forming place cell firing patterns, extended this concept. However, additional neurophysiologic and computational studies demonstrated that circuit development and stabilization additionally relies on non-Hebbian, homoeostatic, forms of plasticity, such as synaptic scaling and control of membrane intrinsic properties. Activity-dependent neurodevelopment was found to be associated with cell-wide adjustments in post-synaptic receptor density, and found to occur in conjunction with synaptic pruning. Pioneering cellular neurophysiologic studies demonstrated the critical roles of transmembrane signal transduction, NMDA receptor regulation, regulation of neural membrane biophysical properties, and back-propagating action potential in critical time-dependent coincidence detection in behavior-modifying circuits. Concerning the molecular mechanisms underlying these processes, regulation of gene transcription was found to serve as a bridge between experience and behavioral change, closing the 'nature versus nurture' divide. Both active DNA (de)methylation and regulation of chromatin structure have been validated as crucial regulators of gene transcription during learning. The discovery of protein synthesis dependence on the

Role of the origin of glutamatergic synaptic inputs in controlling synaptic plasticity and its modulation by alcohol in mice nucleus accumbens

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Gilles Erwann Martin

2015-07-01

Full Text Available It is widely accepted that long-lasting changes of synaptic strength in the nucleus accumbens, a brain region involved in drug reward, mediate acute and chronic effects of alcohol. However, our understanding of the mechanisms underlying the effects of alcohol on synaptic plasticity is limited by the fact that the nucleus accumbens receives glutamatergic inputs from distinct brain regions (e.g. the prefrontal cortex, the amygdala and the hippocampus, each region providing different information (e.g. spatial, emotional and cognitive. Combining whole-cell patch-clamp recordings and the optogenetic technique, we examined synaptic plasticity, and its regulation by alcohol, at cortical, hippocampal and amygdala inputs in fresh slices of mouse tissue. We showed that the origin of synaptic inputs determines the basic properties of glutamatergic synaptic transmission, the expression of spike-timing dependent long-term depression (tLTD and long-term potentiation (tLTP and their regulation by alcohol. While we observed both tLTP and tLTD at amygadala and hippocampal synapses, we showed that cortical inputs only undergo tLTD. Functionally, we provide evidence that acute EtOH has little effects on higher order information coming from the prefrontal cortex (PFCx, while severely impacting the ability of emotional and contextual information to induce long-lasting changes of synaptic strength.

Dysregulation of autism-associated synaptic proteins by psychoactive pharmaceuticals at environmental concentrations.

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Kaushik, Gaurav; Xia, Yu; Pfau, Jean C; Thomas, Michael A

2017-11-20

Autism Spectrum Disorders (ASD) are complex neurological disorders for which the prevalence in the U.S. is currently estimated to be 1 in 50 children. A majority of cases of idiopathic autism in children likely result from unknown environmental triggers in genetically susceptible individuals. These triggers may include maternal exposure of a developing embryo to environmentally relevant minute concentrations of psychoactive pharmaceuticals through ineffectively purified drinking water. Previous studies in our lab examined the extent to which gene sets associated with neuronal development were up- and down-regulated (enriched) in the brains of fathead minnows treated with psychoactive pharmaceuticals at environmental concentrations. The aim of this study was to determine whether similar treatments would alter in vitro expression of ASD-associated synaptic proteins on differentiated human neuronal cells. Human SK-N-SH neuroblastoma cells were differentiated for two weeks with 10μM retinoic acid (RA) and treated with environmentally relevant concentrations of fluoxetine, carbamazepine or venlafaxine, and flow cytometry technique was used to analyze expression of ASD-associated synaptic proteins. Data showed that carbamazepine individually, venlafaxine individually and mixture treatment at environmental concentrations significantly altered the expression of key synaptic proteins (NMDAR1, PSD95, SV2A, HTR1B, HTR2C and OXTR). Data indicated that psychoactive pharmaceuticals at extremely low concentrations altered the in vitro expression of key synaptic proteins that may potentially contribute to neurological disorders like ASD by disrupting neuronal development. Copyright © 2017 Elsevier B.V. All rights reserved.

Supervised learning of probability distributions by neural networks

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Baum, Eric B.; Wilczek, Frank

1988-01-01

Supervised learning algorithms for feedforward neural networks are investigated analytically. The back-propagation algorithm described by Werbos (1974), Parker (1985), and Rumelhart et al. (1986) is generalized by redefining the values of the input and output neurons as probabilities. The synaptic weights are then varied to follow gradients in the logarithm of likelihood rather than in the error. This modification is shown to provide a more rigorous theoretical basis for the algorithm and to permit more accurate predictions. A typical application involving a medical-diagnosis expert system is discussed.

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

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Elliott, Terry; Kramer, Jörg

2002-10-01

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

PRED-CLASS: cascading neural networks for generalized protein classification and genome-wide applications

OpenAIRE

Pasquier, Claude; Promponas, Vasilis; Hamodrakas, Stavros

2009-01-01

International audience; A cascading system of hierarchical, artificial neural networks (named PRED-CLASS) is presented for the generalized classification of proteins into four distinct classes-transmembrane, fibrous, globular, and mixed-from information solely encoded in their amino acid sequences. The architecture of the individual component networks is kept very simple, reducing the number of free parameters (network synaptic weights) for faster training, improved generalization, and the av...

Chelation of hippocampal zinc enhances long-term potentiation and synaptic tagging/capture in CA1 pyramidal neurons of aged rats: implications to aging and memory.

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Shetty, Mahesh Shivarama; Sharma, Mahima; Sajikumar, Sreedharan

2017-02-01

Aging is associated with decline in cognitive functions, prominently in the memory consolidation and association capabilities. Hippocampus plays a crucial role in the formation and maintenance of long-term associative memories, and a significant body of evidence shows that impairments in hippocampal function correlate with aging-related memory loss. A number of studies have implicated alterations in hippocampal synaptic plasticity, such as long-term potentiation (LTP), in age-related cognitive decline although exact mechanisms underlying are not completely clear. Zinc deficiency and the resultant adverse effects on cognition have been well studied. However, the role of excess of zinc in synaptic plasticity, especially in aging, is not addressed well. Here, we have investigated the hippocampal zinc levels and the impairments in synaptic plasticity, such as LTP and synaptic tagging and capture (STC), in the CA1 region of acute hippocampal slices from 82- to 84-week-old male Wistar rats. We report increased zinc levels in the hippocampus of aged rats and also deficits in the tetani-induced and dopaminergic agonist-induced late-LTP and STC. The observed deficits in synaptic plasticity were restored upon chelation of zinc using a cell-permeable chelator. These data suggest that functional plasticity and associativity can be successfully established in aged neural networks by chelating zinc with cell-permeable chelating agents. © 2016 The Authors. Aging Cell published by the Anatomical Society and John Wiley & Sons Ltd.

Alteration of synaptic connectivity of oligodendrocyte precursor cells following demyelination

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Sahel, Aurélia; Ortiz, Fernando C.; Kerninon, Christophe; Maldonado, Paloma P.; Angulo, María Cecilia; Nait-Oumesmar, Brahim

2015-01-01

Oligodendrocyte precursor cells (OPCs) are a major source of remyelinating oligodendrocytes in demyelinating diseases such as Multiple Sclerosis (MS). While OPCs are innervated by unmyelinated axons in the normal brain, the fate of such synaptic contacts after demyelination is still unclear. By combining electrophysiology and immunostainings in different transgenic mice expressing fluorescent reporters, we studied the synaptic innervation of OPCs in the model of lysolecithin (LPC)-induced demyelination of corpus callosum. Synaptic innervation of reactivated OPCs in the lesion was revealed by the presence of AMPA receptor-mediated synaptic currents, VGluT1+ axon-OPC contacts in 3D confocal reconstructions and synaptic junctions observed by electron microscopy. Moreover, 3D confocal reconstructions of VGluT1 and NG2 immunolabeling showed the existence of glutamatergic axon-OPC contacts in post-mortem MS lesions. Interestingly, patch-clamp recordings in LPC-induced lesions demonstrated a drastic decrease in spontaneous synaptic activity of OPCs early after demyelination that was not caused by an impaired conduction of compound action potentials. A reduction in synaptic connectivity was confirmed by the lack of VGluT1+ axon-OPC contacts in virtually all rapidly proliferating OPCs stained with EdU (50-ethynyl-20-deoxyuridine). At the end of the massive proliferation phase in lesions, the proportion of innervated OPCs rapidly recovers, although the frequency of spontaneous synaptic currents did not reach control levels. In conclusion, our results demonstrate that newly-generated OPCs do not receive synaptic inputs during their active proliferation after demyelination, but gain synapses during the remyelination process. Hence, glutamatergic synaptic inputs may contribute to inhibit OPC proliferation and might have a physiopathological relevance in demyelinating disorders. PMID:25852473

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

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

1999-02-01

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

A Computational Model to Investigate Astrocytic Glutamate Uptake Influence on Synaptic Transmission and Neuronal Spiking

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Sushmita Lakshmi Allam

2012-10-01

Full Text Available Over the past decades, our view of astrocytes has switched from passive support cells to active processing elements in the brain. The current view is that astrocytes shape neuronal communication and also play an important role in many neurodegenerative diseases. Despite the growing awareness of the importance of astrocytes, the exact mechanisms underlying neuron-astrocyte communication and the physiological consequences of astrocytic-neuronal interactions remain largely unclear. In this work, we define a modeling framework that will permit to address unanswered questions regarding the role of astrocytes. Our computational model of a detailed glutamatergic synapse facilitates the analysis of neural system responses to various stimuli and conditions that are otherwise difficult to obtain experimentally, in particular the readouts at the sub-cellular level. In this paper, we extend a detailed glutamatergic synaptic model, to include astrocytic glutamate transporters. We demonstrate how these glial transporters, responsible for the majority of glutamate uptake, modulate synaptic transmission mediated by ionotropic AMPA and NMDA receptors at glutamatergic synapses. Furthermore, we investigate how these local signaling effects at the synaptic level are translated into varying spatio-temporal patterns of neuron firing. Paired pulse stimulation results reveal that the effect of astrocytic glutamate uptake is more apparent when the input inter-spike interval is sufficiently long to allow the receptors to recover from desensitization. These results suggest an important functional role of astrocytes in spike timing dependent processes and demand further investigation of the molecular basis of certain neurological diseases specifically related to alterations in astrocytic glutamate uptake, such as epilepsy.

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

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

2013-05-01

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

Synchronization of map-based neurons with memory and synaptic delay

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Sausedo-Solorio, J.M. [Universidad Autónoma del Estado de Hidalgo, Carretera Pachuca-Tulancingo Km. 4.5, 42074 Pachuca, Hidalgo (Mexico); Pisarchik, A.N., E-mail: apisarch@cio.mx [Centro de Investigaciones en Optica, Loma del Bosque 115, Lomas del Campestre, 37150 Leon, Guanajuato (Mexico); Centre for Biomedical Technology, Technical University of Madrid, Campus Montegancedo, 28223 Pozuelo de Alarcon, Madrid (Spain)

2014-06-13

Synchronization of two synaptically coupled neurons with memory and synaptic delay is studied using the Rulkov map, one of the simplest neuron models which displays specific features inherent to bursting dynamics. We demonstrate a transition from lag to anticipated synchronization as the relationship between the memory duration and the synaptic delay time changes. The neuron maps synchronize either with anticipation, if the memory is longer than the synaptic delay time, or with lag otherwise. The mean anticipation time is equal to the difference between the memory and synaptic delay independently of the coupling strength. Frequency entrainment and phase-locking phenomena as well as a transition from regular spikes to chaos are demonstrated with respect to the coupling strength. - Highlights: • We study synchronization of neurons with memory and synaptic delay in the map model. • Neurons synchronize either with anticipation or with lag depending on delay time. • Mean anticipation time is equal to the difference between memory and synaptic delay. • Frequency entrainment and phase locking are studied with respect to the coupling.

Synaptic Plasticity, Dementia and Alzheimer Disease.

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Skaper, Stephen D; Facci, Laura; Zusso, Morena; Giusti, Pietro

2017-01-01

Neuroplasticity is not only shaped by learning and memory but is also a mediator of responses to neuron attrition and injury (compensatory plasticity). As an ongoing process it reacts to neuronal cell activity and injury, death, and genesis, which encompasses the modulation of structural and functional processes of axons, dendrites, and synapses. The range of structural elements that comprise plasticity includes long-term potentiation (a cellular correlate of learning and memory), synaptic efficacy and remodelling, synaptogenesis, axonal sprouting and dendritic remodelling, and neurogenesis and recruitment. Degenerative diseases of the human brain continue to pose one of biomedicine's most intractable problems. Research on human neurodegeneration is now moving from descriptive to mechanistic analyses. At the same time, it is increasing apparently that morphological lesions traditionally used by neuropathologists to confirm post-mortem clinical diagnosis might furnish us with an experimentally tractable handle to understand causative pathways. Consider the aging-dependent neurodegenerative disorder Alzheimer's disease (AD) which is characterised at the neuropathological level by deposits of insoluble amyloid β-peptide (Aβ) in extracellular plaques and aggregated tau protein, which is found largely in the intracellular neurofibrillary tangles. We now appreciate that mild cognitive impairment in early AD may be due to synaptic dysfunction caused by accumulation of non-fibrillar, oligomeric Aβ, occurring well in advance of evident widespread synaptic loss and neurodegeneration. Soluble Aβ oligomers can adversely affect synaptic structure and plasticity at extremely low concentrations, although the molecular substrates by which synaptic memory mechanisms are disrupted remain to be fully elucidated. The dendritic spine constitutes a primary locus of excitatory synaptic transmission in the mammalian central nervous system. These structures protruding from dendritic

Glutamatergic synaptic plasticity in the mesocorticolimbic system in addiction.

NARCIS (Netherlands)

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

2015-01-01

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

A pivotal role of GSK-3 in synaptic plasticity

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Clarrisa A Bradley

2012-02-01

Full Text Available Glycogen synthase kinase-3 (GSK-3 has many cellular functions. Recent evidence suggests that it plays a key role in certain types of synaptic plasticity, in particular a form of long-term depression (LTD that is induced by the synaptic activation of N-methyl-D-aspartate (NMDA receptors. In the present article we summarise what is currently known concerning the roles of GSK-3 in synaptic plasticity at both glutamatergic and GABAergic synapses. We summarise its role in cognition and speculate on how alterations in the synaptic functioning of GSK-3 may be a major factor in certain neurodegenerative disorders.

Early-life seizures alter synaptic calcium-permeable AMPA receptor function and plasticity

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Lippman-Bell, Jocelyn J.; Zhou, Chengwen; Sun, Hongyu; Feske, Joel S.; Jensen, Frances E.

2016-01-01

Calcium (Ca2+)-mediated1 signaling pathways are critical to synaptic plasticity. In adults, the NMDA glutamate receptor (NMDAR) represents a major route for activity-dependent synaptic Ca2+ entry. However, during neonatal development, when synaptic plasticity is high, many AMPA glutamate receptors (AMPARs) are also permeable to Ca2+ (CP-AMPAR) due to low GluA2 subunit expression, providing an additional route for activity- and glutamate-dependent Ca2+ influx and subsequent signaling. Therefore, altered hippocampal Ca2+ signaling may represent an age-specific pathogenic mechanism. We thus aimed to assess Ca2+ responses 48 hours after hypoxia-induced neonatal seizures (HS) in postnatal day (P)10 rats, a post-seizure time point at which we previously reported LTP attenuation. We found that Ca2+ responses were higher in brain slices from post-HS rats than in controls and this increase was CP-AMPAR-dependent. To determine whether synaptic CP-AMPAR expression was also altered post-HS, we assessed the expression of GluA2 at hippocampal synapses and the expression of long-term depression (LTD), which has been linked to the presence of synaptic GluA2. Here we report a decrease 48 hours after HS in synaptic GluA2 expression at synapses and LTD in hippocampal CA1. Given the potentially critical role of AMPAR trafficking in disease progression, we aimed to establish whether post-seizure in vivo AMPAR antagonist treatment prevented the enhanced Ca2+ responses, changes in GluA2 synaptic expression, and diminished LTD. We found that NBQX treatment prevents all three of these post-seizure consequences, further supporting a critical role for AMPARs as an age-specific therapeutic target. PMID:27521497

BDNF-induced local protein synthesis and synaptic plasticity.

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Leal, Graciano; Comprido, Diogo; Duarte, Carlos B

2014-01-01

Brain-derived neurotrophic factor (BDNF) is an important regulator of synaptic transmission and long-term potentiation (LTP) in the hippocampus and in other brain regions, playing a role in the formation of certain forms of memory. The effects of BDNF in LTP are mediated by TrkB (tropomyosin-related kinase B) receptors, which are known to be coupled to the activation of the Ras/ERK, phosphatidylinositol 3-kinase/Akt and phospholipase C-γ (PLC-γ) pathways. The role of BDNF in LTP is best studied in the hippocampus, where the neurotrophin acts at pre- and post-synaptic levels. Recent studies have shown that BDNF regulates the transport of mRNAs along dendrites and their translation at the synapse, by modulating the initiation and elongation phases of protein synthesis, and by acting on specific miRNAs. Furthermore, the effect of BDNF on transcription regulation may further contribute to long-term changes in the synaptic proteome. In this review we discuss the recent progress in understanding the mechanisms contributing to the short- and long-term regulation of the synaptic proteome by BDNF, and the role in synaptic plasticity, which is likely to influence learning and memory formation. This article is part of the Special Issue entitled 'BDNF Regulation of Synaptic Structure, Function, and Plasticity'. Copyright © 2013 Elsevier Ltd. All rights reserved.

Synaptic learning rules and sparse coding in a model sensory system.

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Luca A Finelli

2008-04-01

Full Text Available Neural circuits exploit numerous strategies for encoding information. Although the functional significance of individual coding mechanisms has been investigated, ways in which multiple mechanisms interact and integrate are not well understood. The locust olfactory system, in which dense, transiently synchronized spike trains across ensembles of antenna lobe (AL neurons are transformed into a sparse representation in the mushroom body (MB; a region associated with memory, provides a well-studied preparation for investigating the interaction of multiple coding mechanisms. Recordings made in vivo from the insect MB demonstrated highly specific responses to odors in Kenyon cells (KCs. Typically, only a few KCs from the recorded population of neurons responded reliably when a specific odor was presented. Different odors induced responses in different KCs. Here, we explored with a biologically plausible model the possibility that a form of plasticity may control and tune synaptic weights of inputs to the mushroom body to ensure the specificity of KCs' responses to familiar or meaningful odors. We found that plasticity at the synapses between the AL and the MB efficiently regulated the delicate tuning necessary to selectively filter the intense AL oscillatory output and condense it to a sparse representation in the MB. Activity-dependent plasticity drove the observed specificity, reliability, and expected persistence of odor representations, suggesting a role for plasticity in information processing and making a testable prediction about synaptic plasticity at AL-MB synapses.

Real-time cerebellar neuroprosthetic system based on a spiking neural network model of motor learning

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Xu, Tao; Xiao, Na; Zhai, Xiaolong; Chan, Pak Kwan; Tin, Chung

2018-02-01

Objective. Damage to the brain, as a result of various medical conditions, impacts the everyday life of patients and there is still no complete cure to neurological disorders. Neuroprostheses that can functionally replace the damaged neural circuit have recently emerged as a possible solution to these problems. Here we describe the development of a real-time cerebellar neuroprosthetic system to substitute neural function in cerebellar circuitry for learning delay eyeblink conditioning (DEC). Approach. The system was empowered by a biologically realistic spiking neural network (SNN) model of the cerebellar neural circuit, which considers the neuronal population and anatomical connectivity of the network. The model simulated synaptic plasticity critical for learning DEC. This SNN model was carefully implemented on a field programmable gate array (FPGA) platform for real-time simulation. This hardware system was interfaced in in vivo experiments with anesthetized rats and it used neural spikes recorded online from the animal to learn and trigger conditioned eyeblink in the animal during training. Main results. This rat-FPGA hybrid system was able to process neuronal spikes in real-time with an embedded cerebellum model of ~10 000 neurons and reproduce learning of DEC with different inter-stimulus intervals. Our results validated that the system performance is physiologically relevant at both the neural (firing pattern) and behavioral (eyeblink pattern) levels. Significance. This integrated system provides the sufficient computation power for mimicking the cerebellar circuit in real-time. The system interacts with the biological system naturally at the spike level and can be generalized for including other neural components (neuron types and plasticity) and neural functions for potential neuroprosthetic applications.

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

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Son, Esther Y; Crabtree, Gerald R

2014-09-01

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

SAD-B kinase regulates pre-synaptic vesicular dynamics at hippocampal Schaffer collateral synapses and affects contextual fear memory.

Science.gov (United States)

Watabe, Ayako M; Nagase, Masashi; Hagiwara, Akari; Hida, Yamato; Tsuji, Megumi; Ochiai, Toshitaka; Kato, Fusao; Ohtsuka, Toshihisa

2016-01-01

Synapses of amphids defective (SAD)-A/B kinases control various steps in neuronal development and differentiation, such as axon specifications and maturation in central and peripheral nervous systems. At mature pre-synaptic terminals, SAD-B is associated with synaptic vesicles and the active zone cytomatrix; however, how SAD-B regulates neurotransmission and synaptic plasticity in vivo remains unclear. Thus, we used SAD-B knockout (KO) mice to study the function of this pre-synaptic kinase in the brain. We found that the paired-pulse ratio was significantly enhanced at Shaffer collateral synapses in the hippocampal CA1 region in SAD-B KO mice compared with wild-type littermates. We also found that the frequency of the miniature excitatory post-synaptic current was decreased in SAD-B KO mice. Moreover, synaptic depression following prolonged low-frequency synaptic stimulation was significantly enhanced in SAD-B KO mice. These results suggest that SAD-B kinase regulates vesicular release probability at pre-synaptic terminals and is involved in vesicular trafficking and/or regulation of the readily releasable pool size. Finally, we found that hippocampus-dependent contextual fear learning was significantly impaired in SAD-B KO mice. These observations suggest that SAD-B kinase plays pivotal roles in controlling vesicular release properties and regulating hippocampal function in the mature brain. Synapses of amphids defective (SAD)-A/B kinases control various steps in neuronal development and differentiation, but their roles in mature brains were only partially known. Here, we demonstrated, at mature pre-synaptic terminals, that SAD-B regulates vesicular release probability and synaptic plasticity. Moreover, hippocampus-dependent contextual fear learning was significantly impaired in SAD-B KO mice, suggesting that SAD-B kinase plays pivotal roles in controlling vesicular release properties and regulating hippocampal function in the mature brain. © 2015 International

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

Science.gov (United States)

2009-01-01

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

Influence of sex and estrous cycle on synaptic responses of the medial vestibular nuclei in rats: role of circulating 17β-estradiol.

Science.gov (United States)

Grassi, Silvarosa; Frondaroli, Adele; Scarduzio, Mariangela; Dieni, Cristina V; Brecchia, Gabriele; Boiti, Cristiano; Pettorossi, Vito E

2012-02-10

We investigated the possible influence of sex and estrous cycle on the synaptic responses of neurons in the medial vestibular nucleus (MVN) and their long-term modifications. In brain stem slices of male and female rats during proestrus (PE) and diestrus (DE), we evaluated the field potential evoked in the MVN by vestibular afferent stimulation. Here we find that in PE females the field potential had a lower threshold and higher amplitude than in DE females and in males and also that the stimulus-response curve was shifted to the left. Such difference is related to the level and cyclic fluctuation of circulating 17β-estradiol (E(2)). This is supported by the exogenous administration of E(2) in DE females and males, with low levels of circulating E(2) that enhanced the field potential amplitude to values close to those of PE females. Sex and estrous cycle also influence the MVN synaptic plasticity. This has been shown by investigating the effect of testosterone (T) on the induction of long-term effects, since T is the precursor for the neural synthesis of E(2) (estrogenic pathway), which is involved in the induction of fast long-term potentiation (LTP), or of 5α-dihydrotestosterone (DHT, androgenic pathway) which mediates slow LTP and long-term depression (LTD). We found that T mostly induced LTD in PE females and no effect in DE females, while it only provoked fast LTP in males. We suggest that high level of circulating E(2) may interfere with the conversion of T, by inhibiting the neural estrogenic pathway and facilitating the androgenic one. On the whole these results demonstrate an influence of circulating E(2) on vestibular synaptic transmission and plasticity that in some cases may contribute to the sex and menstrual cycle dependence of symptoms in human vestibular pathology. Copyright © 2011 Elsevier Inc. All rights reserved.

PET measures of pre- and post-synaptic cardiac beta adrenergic function

Energy Technology Data Exchange (ETDEWEB)

Link, Jeanne M.; Stratton, John R.; Levy, Wayne; Poole, Jeanne E.; Shoner, Steven C.; Stuetzle, Werner; Caldwell, James H. E-mail: jcald@u.washington.edu

2003-11-01

Positron Emission Tomography was used to measure global and regional cardiac {beta}-adrenergic function in 19 normal subjects and 9 congestive heart failure patients. [{sup 11}C]-meta-hydroxyephedrine was used to image norepinephrine transporter function as an indicator of pre-synaptic function and [{sup 11}C]-CGP12177 was used to measure cell surface {beta}-receptor density as an indicator of post-synaptic function. Pre-synaptic, but not post-synaptic, function was significantly different between normals and CHF patients. Pre-synaptic function was well matched to post-synaptic function in the normal hearts but significantly different and poorly matched in the CHF patients studied. This imaging technique can help us understand regional sympathetic function in cardiac disease.

Role for a Novel Usher Protein Complex in Hair Cell Synaptic Maturation

Science.gov (United States)

Zallocchi, Marisa; Meehan, Daniel T.; Delimont, Duane; Rutledge, Joseph; Gratton, Michael Anne; Flannery, John; Cosgrove, Dominic

2012-01-01

The molecular mechanisms underlying hair cell synaptic maturation are not well understood. Cadherin-23 (CDH23), protocadherin-15 (PCDH15) and the very large G-protein coupled receptor 1 (VLGR1) have been implicated in the development of cochlear hair cell stereocilia, while clarin-1 has been suggested to also play a role in synaptogenesis. Mutations in CDH23, PCDH15, VLGR1 and clarin-1 cause Usher syndrome, characterized by congenital deafness, vestibular dysfunction and retinitis pigmentosa. Here we show developmental expression of these Usher proteins in afferent spiral ganglion neurons and hair cell synapses. We identify a novel synaptic Usher complex comprised of clarin-1 and specific isoforms of CDH23, PCDH15 and VLGR1. To establish the in vivo relevance of this complex, we performed morphological and quantitative analysis of the neuronal fibers and their synapses in the Clrn1−/− mouse, which was generated by incomplete deletion of the gene. These mice showed a delay in neuronal/synaptic maturation by both immunostaining and electron microscopy. Analysis of the ribbon synapses in Ames waltzerav3J mice also suggests a delay in hair cell synaptogenesis. Collectively, these results show that, in addition to the well documented role for Usher proteins in stereocilia development, Usher protein complexes comprised of specific protein isoforms likely function in synaptic maturation as well. PMID:22363448

Role for a novel Usher protein complex in hair cell synaptic maturation.

Directory of Open Access Journals (Sweden)

Marisa Zallocchi

Full Text Available The molecular mechanisms underlying hair cell synaptic maturation are not well understood. Cadherin-23 (CDH23, protocadherin-15 (PCDH15 and the very large G-protein coupled receptor 1 (VLGR1 have been implicated in the development of cochlear hair cell stereocilia, while clarin-1 has been suggested to also play a role in synaptogenesis. Mutations in CDH23, PCDH15, VLGR1 and clarin-1 cause Usher syndrome, characterized by congenital deafness, vestibular dysfunction and retinitis pigmentosa. Here we show developmental expression of these Usher proteins in afferent spiral ganglion neurons and hair cell synapses. We identify a novel synaptic Usher complex comprised of clarin-1 and specific isoforms of CDH23, PCDH15 and VLGR1. To establish the in vivo relevance of this complex, we performed morphological and quantitative analysis of the neuronal fibers and their synapses in the Clrn1-/- mouse, which was generated by incomplete deletion of the gene. These mice showed a delay in neuronal/synaptic maturation by both immunostaining and electron microscopy. Analysis of the ribbon synapses in Ames waltzer(av3J mice also suggests a delay in hair cell synaptogenesis. Collectively, these results show that, in addition to the well documented role for Usher proteins in stereocilia development, Usher protein complexes comprised of specific protein isoforms likely function in synaptic maturation as well.

Spiking neural networks for handwritten digit recognition-Supervised learning and network optimization.

Science.gov (United States)

Kulkarni, Shruti R; Rajendran, Bipin

2018-07-01

We demonstrate supervised learning in Spiking Neural Networks (SNNs) for the problem of handwritten digit recognition using the spike triggered Normalized Approximate Descent (NormAD) algorithm. Our network that employs neurons operating at sparse biological spike rates below 300Hz achieves a classification accuracy of 98.17% on the MNIST test database with four times fewer parameters compared to the state-of-the-art. We present several insights from extensive numerical experiments regarding optimization of learning parameters and network configuration to improve its accuracy. We also describe a number of strategies to optimize the SNN for implementation in memory and energy constrained hardware, including approximations in computing the neuronal dynamics and reduced precision in storing the synaptic weights. Experiments reveal that even with 3-bit synaptic weights, the classification accuracy of the designed SNN does not degrade beyond 1% as compared to the floating-point baseline. Further, the proposed SNN, which is trained based on the precise spike timing information outperforms an equivalent non-spiking artificial neural network (ANN) trained using back propagation, especially at low bit precision. Thus, our study shows the potential for realizing efficient neuromorphic systems that use spike based information encoding and learning for real-world applications. Copyright © 2018 Elsevier Ltd. All rights reserved.

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

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

2016-03-01

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

A presynaptic role for PKA in synaptic tagging and memory.

Science.gov (United States)

Park, Alan Jung; Havekes, Robbert; Choi, Jennifer Hk; Luczak, Vince; Nie, Ting; Huang, Ted; Abel, Ted

2014-10-01

Protein kinase A (PKA) and other signaling molecules are spatially restricted within neurons by A-kinase anchoring proteins (AKAPs). Although studies on compartmentalized PKA signaling have focused on postsynaptic mechanisms, presynaptically anchored PKA may contribute to synaptic plasticity and memory because PKA also regulates presynaptic transmitter release. Here, we examine this issue using genetic and pharmacological application of Ht31, a PKA anchoring disrupting peptide. At the hippocampal Schaffer collateral CA3-CA1 synapse, Ht31 treatment elicits a rapid decay of synaptic responses to repetitive stimuli, indicating a fast depletion of the readily releasable pool of synaptic vesicles. The interaction between PKA and proteins involved in producing this pool of synaptic vesicles is supported by biochemical assays showing that synaptic vesicle protein 2 (SV2), Rim1, and SNAP25 are components of a complex that interacts with cAMP. Moreover, acute treatment with Ht31 reduces the levels of SV2. Finally, experiments with transgenic mouse lines, which express Ht31 in excitatory neurons at the Schaffer collateral CA3-CA1 synapse, highlight a requirement for presynaptically anchored PKA in pathway-specific synaptic tagging and long-term contextual fear memory. These results suggest that a presynaptically compartmentalized PKA is critical for synaptic plasticity and memory by regulating the readily releasable pool of synaptic vesicles. Copyright © 2014 Elsevier Inc. All rights reserved.

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

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

2018-06-06

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

Effects of salicylate on the inflammatory genes expression and synaptic ultrastructure in the cochlear nucleus of rats.

Science.gov (United States)

Hu, Shou-Sen; Mei, Ling; Chen, Jian-Yong; Huang, Zhi-Wu; Wu, Hao

2014-04-01

Aspirin (salicylate), as a common drug that is frequently used for long-term treatment in a clinical setting, has the potential to cause reversible tinnitus. However, few reports have examined the inflammatory cytokines expression and alteration of synaptic ultrastructure in the cochlear nucleus (CN) in a rat model of tinnitus. The tinnitus-like behavior of rats were detected by the gap prepulse inhibition of acoustic startle (GPIAS) paradigm. We investigated the expression levels of the tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), N-methyl D-aspartate receptor subunit 2A (NR2A) mRNA and protein in the CN and compared synapses ultrastructure in the CN of tinnitus rats with normal ones. GPIAS showed that rats with long-term administration of salicylate were experiencing tinnitus, and the mRNA and protein expression levels of TNF-α and NR2A were up-regulated in chronic treatment groups, and they returned to baseline 14 days after cessation of treatment. Furthermore, compared to normal rats, repetitive salicylate-treated rats showed a greater number of presynaptic vesicles, thicker and longer postsynaptic densities, increased synaptic interface curvature. These data revealed that chronic salicylate administration markedly, but reversibly, induces tinnitus possibly via augmentation of the expression of TNF-α and NR2A and cause changes in synaptic ultrastructure in the CN. Long-term administration of salicylate causes neural plasticity changes at the CN level.

GABAA Receptor-Mediated Bidirectional Control of Synaptic Activity, Intracellular Ca2+, Cerebral Blood Flow, and Oxygen Consumption in Mouse Somatosensory Cortex In Vivo

DEFF Research Database (Denmark)

Jessen, Sanne Barsballe; Brazhe, Alexey; Lind, Barbara Lykke

2015-01-01

Neural activity regulates local increases in cerebral blood flow (ΔCBF) and the cortical metabolic rate of oxygen (ΔCMRO2) that constitutes the basis of BOLD functional neuroimaging signals. Glutamate signaling plays a key role in brain vascular and metabolic control; however, the modulatory effect...... of GABA is incompletely understood. Here we performed in vivo studies in mice to investigate how THIP (which tonically activates extrasynaptic GABAARs) and Zolpidem (a positive allosteric modulator of synaptic GABAARs) impact stimulation-induced ΔCBF, ΔCMRO2, local field potentials (LFPs), and fluorescent...... cytosolic Ca2+ transients in neurons and astrocytes. Low concentrations of THIP increased ΔCBF and ΔCMRO2 at low stimulation frequencies. These responses were coupled to increased synaptic activity as indicated by LFP responses, and to Ca2+ activities in neurons and astrocytes. Intermediate and high...

Development of nuclear power plant diagnosis technique using neural networks

International Nuclear Information System (INIS)

Horiguchi, Masahiro; Fukawa, Naohiro; Nishimura, Kazuo

1991-01-01

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

Artificial Astrocytes Improve Neural Network Performance

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Porto-Pazos, Ana B.; Veiguela, Noha; Mesejo, Pablo; Navarrete, Marta; Alvarellos, Alberto; Ibáñez, Oscar; Pazos, Alejandro; Araque, Alfonso

2011-01-01

Compelling evidence indicates the existence of bidirectional communication between astrocytes and neurons. Astrocytes, a type of glial cells classically considered to be passive supportive cells, have been recently demonstrated to be actively involved in the processing and regulation of synaptic information, suggesting that brain function arises from the activity of neuron-glia networks. However, the actual impact of astrocytes in neural network function is largely unknown and its application in artificial intelligence remains untested. We have investigated the consequences of including artificial astrocytes, which present the biologically defined properties involved in astrocyte-neuron communication, on artificial neural network performance. Using connectionist systems and evolutionary algorithms, we have compared the performance of artificial neural networks (NN) and artificial neuron-glia networks (NGN) to solve classification problems. We show that the degree of success of NGN is superior to NN. Analysis of performances of NN with different number of neurons or different architectures indicate that the effects of NGN cannot be accounted for an increased number of network elements, but rather they are specifically due to astrocytes. Furthermore, the relative efficacy of NGN vs. NN increases as the complexity of the network increases. These results indicate that artificial astrocytes improve neural network performance, and established the concept of Artificial Neuron-Glia Networks, which represents a novel concept in Artificial Intelligence with implications in computational science as well as in the understanding of brain function. PMID:21526157

Artificial astrocytes improve neural network performance.

Directory of Open Access Journals (Sweden)

Ana B Porto-Pazos

Full Text Available Compelling evidence indicates the existence of bidirectional communication between astrocytes and neurons. Astrocytes, a type of glial cells classically considered to be passive supportive cells, have been recently demonstrated to be actively involved in the processing and regulation of synaptic information, suggesting that brain function arises from the activity of neuron-glia networks. However, the actual impact of astrocytes in neural network function is largely unknown and its application in artificial intelligence remains untested. We have investigated the consequences of including artificial astrocytes, which present the biologically defined properties involved in astrocyte-neuron communication, on artificial neural network performance. Using connectionist systems and evolutionary algorithms, we have compared the performance of artificial neural networks (NN and artificial neuron-glia networks (NGN to solve classification problems. We show that the degree of success of NGN is superior to NN. Analysis of performances of NN with different number of neurons or different architectures indicate that the effects of NGN cannot be accounted for an increased number of network elements, but rather they are specifically due to astrocytes. Furthermore, the relative efficacy of NGN vs. NN increases as the complexity of the network increases. These results indicate that artificial astrocytes improve neural network performance, and established the concept of Artificial Neuron-Glia Networks, which represents a novel concept in Artificial Intelligence with implications in computational science as well as in the understanding of brain function.

Artificial astrocytes improve neural network performance.

Science.gov (United States)

Porto-Pazos, Ana B; Veiguela, Noha; Mesejo, Pablo; Navarrete, Marta; Alvarellos, Alberto; Ibáñez, Oscar; Pazos, Alejandro; Araque, Alfonso

2011-04-19

Compelling evidence indicates the existence of bidirectional communication between astrocytes and neurons. Astrocytes, a type of glial cells classically considered to be passive supportive cells, have been recently demonstrated to be actively involved in the processing and regulation of synaptic information, suggesting that brain function arises from the activity of neuron-glia networks. However, the actual impact of astrocytes in neural network function is largely unknown and its application in artificial intelligence remains untested. We have investigated the consequences of including artificial astrocytes, which present the biologically defined properties involved in astrocyte-neuron communication, on artificial neural network performance. Using connectionist systems and evolutionary algorithms, we have compared the performance of artificial neural networks (NN) and artificial neuron-glia networks (NGN) to solve classification problems. We show that the degree of success of NGN is superior to NN. Analysis of performances of NN with different number of neurons or different architectures indicate that the effects of NGN cannot be accounted for an increased number of network elements, but rather they are specifically due to astrocytes. Furthermore, the relative efficacy of NGN vs. NN increases as the complexity of the network increases. These results indicate that artificial astrocytes improve neural network performance, and established the concept of Artificial Neuron-Glia Networks, which represents a novel concept in Artificial Intelligence with implications in computational science as well as in the understanding of brain function.

A Pruning Neural Network Model in Credit Classification Analysis

Directory of Open Access Journals (Sweden)

Yajiao Tang

2018-01-01

Full Text Available Nowadays, credit classification models are widely applied because they can help financial decision-makers to handle credit classification issues. Among them, artificial neural networks (ANNs have been widely accepted as the convincing methods in the credit industry. In this paper, we propose a pruning neural network (PNN and apply it to solve credit classification problem by adopting the well-known Australian and Japanese credit datasets. The model is inspired by synaptic nonlinearity of a dendritic tree in a biological neural model. And it is trained by an error back-propagation algorithm. The model is capable of realizing a neuronal pruning function by removing the superfluous synapses and useless dendrites and forms a tidy dendritic morphology at the end of learning. Furthermore, we utilize logic circuits (LCs to simulate the dendritic structures successfully which makes PNN be implemented on the hardware effectively. The statistical results of our experiments have verified that PNN obtains superior performance in comparison with other classical algorithms in terms of accuracy and computational efficiency.

NEURAL NETWORKS AS A CLASSIFICATION TOOL BIOTECHNOLOGICAL SYSTEMS (FOR EXAMPLE FLOUR PRODUCTION

Directory of Open Access Journals (Sweden)

V. K. Bitykov

2015-01-01

Full Text Available Summary. To date, artificial intelligence systems are the most common type to classify objects of different quality. The proposed modeling technology to predict the quality of flour products by using artificial neural networks allows to solve problems of analysis of the factors determining the quality of the products. Interest in artificial neural networks has grown due to the fact that they can change their behavior depending on external environment. This factor more than any other responsible for the interest that they cause. After the presentation of input signals (possibly together with the desired outputs, they self-configurable to provide the desired reaction. We developed a set of training algorithms, each with their own strengths and weaknesses. The solution to the problem of classification is one of the most important applications of neural networks, which represents a problem of attributing the sample to one of several non-intersecting sets. To solve this problem developed algorithms for synthesis of NA with the use of nonlinear activation functions, the algorithms for training the network. Training the NS involves determining the weights of layers of neurons. Training the NA occurs with the teacher, that is, the network must meet the values of both input and desired output signals, and it is according to some internal algorithm adjusts the weights of their synaptic connections. The work was built an artificial neural network, multilayer perceptron example. With the help of correlation analysis in total sample revealed that the traits are correlated at the significance level of 0.01 with grade quality bread. The classification accuracy exceeds 90%.

Sequential estimation of intrinsic activity and synaptic input in single neurons by particle filtering with optimal importance density

Science.gov (United States)

Closas, Pau; Guillamon, Antoni

2017-12-01

This paper deals with the problem of inferring the signals and parameters that cause neural activity to occur. The ultimate challenge being to unveil brain's connectivity, here we focus on a microscopic vision of the problem, where single neurons (potentially connected to a network of peers) are at the core of our study. The sole observation available are noisy, sampled voltage traces obtained from intracellular recordings. We design algorithms and inference methods using the tools provided by stochastic filtering that allow a probabilistic interpretation and treatment of the problem. Using particle filtering, we are able to reconstruct traces of voltages and estimate the time course of auxiliary variables. By extending the algorithm, through PMCMC methodology, we are able to estimate hidden physiological parameters as well, like intrinsic conductances or reversal potentials. Last, but not least, the method is applied to estimate synaptic conductances arriving at a target cell, thus reconstructing the synaptic excitatory/inhibitory input traces. Notably, the performance of these estimations achieve the theoretical lower bounds even in spiking regimes.

Electric Dipole Theory of Chemical Synaptic Transmission

Science.gov (United States)

Wei, Ling Y.

1968-01-01

In this paper we propose that chemicals such as acetylcholine are electric dipoles which when oriented and arranged in a large array could produce an electric field strong enough to drive positive ions over the junction barrier of the post-synaptic membrane and thus initiate excitation or produce depolarization. This theory is able to explain a great number of facts such as cleft size, synaptic delay, nonregeneration, subthreshold integration, facilitation with repetition, and the calcium and magnesium effects. It also shows why and how acetylcholine could act as excitatory or inhibitory transmitters under different circumstances. Our conclusion is that the nature of synaptic transmission is essentially electrical, be it mediated by electrical or chemical transmitters. PMID:4296121

Astroglial Metabolic Networks Sustain Hippocampal Synaptic Transmission

Science.gov (United States)

Rouach, Nathalie; Koulakoff, Annette; Abudara, Veronica; Willecke, Klaus; Giaume, Christian

2008-12-01

Astrocytes provide metabolic substrates to neurons in an activity-dependent manner. However, the molecular mechanisms involved in this function, as well as its role in synaptic transmission, remain unclear. Here, we show that the gap-junction subunit proteins connexin 43 and 30 allow intercellular trafficking of glucose and its metabolites through astroglial networks. This trafficking is regulated by glutamatergic synaptic activity mediated by AMPA receptors. In the absence of extracellular glucose, the delivery of glucose or lactate to astrocytes sustains glutamatergic synaptic transmission and epileptiform activity only when they are connected by gap junctions. These results indicate that astroglial gap junctions provide an activity-dependent intercellular pathway for the delivery of energetic metabolites from blood vessels to distal neurons.

Astroglial metabolic networks sustain hippocampal synaptic transmission.

Science.gov (United States)

Rouach, Nathalie; Koulakoff, Annette; Abudara, Veronica; Willecke, Klaus; Giaume, Christian

2008-12-05

Astrocytes provide metabolic substrates to neurons in an activity-dependent manner. However, the molecular mechanisms involved in this function, as well as its role in synaptic transmission, remain unclear. Here, we show that the gap-junction subunit proteins connexin 43 and 30 allow intercellular trafficking of glucose and its metabolites through astroglial networks. This trafficking is regulated by glutamatergic synaptic activity mediated by AMPA receptors. In the absence of extracellular glucose, the delivery of glucose or lactate to astrocytes sustains glutamatergic synaptic transmission and epileptiform activity only when they are connected by gap junctions. These results indicate that astroglial gap junctions provide an activity-dependent intercellular pathway for the delivery of energetic metabolites from blood vessels to distal neurons.

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

Science.gov (United States)

Rieger, Sandra; Wang, Fang; Sagasti, Alvaro

2011-07-01

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

Synaptic transmission block by presynaptic injection of oligomeric amyloid beta

Science.gov (United States)

Moreno, Herman; Yu, Eunah; Pigino, Gustavo; Hernandez, Alejandro I.; Kim, Natalia; Moreira, Jorge E.; Sugimori, Mutsuyuki; Llinás, Rodolfo R.

2009-01-01

Early Alzheimer's disease (AD) pathophysiology is characterized by synaptic changes induced by degradation products of amyloid precursor protein (APP). The exact mechanisms of such modulation are unknown. Here, we report that nanomolar concentrations of intraaxonal oligomeric (o)Aβ42, but not oAβ40 or extracellular oAβ42, acutely inhibited synaptic transmission at the squid giant synapse. Further characterization of this phenotype demonstrated that presynaptic calcium currents were unaffected. However, electron microscopy experiments revealed diminished docked synaptic vesicles in oAβ42-microinjected terminals, without affecting clathrin-coated vesicles. The molecular events of this modulation involved casein kinase 2 and the synaptic vesicle rapid endocytosis pathway. These findings open the possibility of a new therapeutic target aimed at ameliorating synaptic dysfunction in AD. PMID:19304802

Ultrafast Synaptic Events in a Chalcogenide Memristor

Science.gov (United States)

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

2013-04-01

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

Deletion of OTX2 in neural ectoderm delays anterior pituitary development

Science.gov (United States)

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

2015-01-01

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

Stability of bumps in piecewise smooth neural fields with nonlinear adaptation

KAUST Repository

Kilpatrick, Zachary P.

2010-06-01

We study the linear stability of stationary bumps in piecewise smooth neural fields with local negative feedback in the form of synaptic depression or spike frequency adaptation. The continuum dynamics is described in terms of a nonlocal integrodifferential equation, in which the integral kernel represents the spatial distribution of synaptic weights between populations of neurons whose mean firing rate is taken to be a Heaviside function of local activity. Discontinuities in the adaptation variable associated with a bump solution means that bump stability cannot be analyzed by constructing the Evans function for a network with a sigmoidal gain function and then taking the high-gain limit. In the case of synaptic depression, we show that linear stability can be formulated in terms of solutions to a system of pseudo-linear equations. We thus establish that sufficiently strong synaptic depression can destabilize a bump that is stable in the absence of depression. These instabilities are dominated by shift perturbations that evolve into traveling pulses. In the case of spike frequency adaptation, we show that for a wide class of perturbations the activity and adaptation variables decouple in the linear regime, thus allowing us to explicitly determine stability in terms of the spectrum of a smooth linear operator. We find that bumps are always unstable with respect to this class of perturbations, and destabilization of a bump can result in either a traveling pulse or a spatially localized breather. © 2010 Elsevier B.V. All rights reserved.

Phosphodiesterase Inhibition to Target the Synaptic Dysfunction in Alzheimer's Disease

Science.gov (United States)

Bales, Kelly R.; Plath, Niels; Svenstrup, Niels; Menniti, Frank S.

Alzheimer's Disease (AD) is a disease of synaptic dysfunction that ultimately proceeds to neuronal death. There is a wealth of evidence that indicates the final common mediator of this neurotoxic process is the formation and actions on synaptotoxic b-amyloid (Aβ). The premise in this review is that synaptic dysfunction may also be an initiating factor in for AD and promote synaptotoxic Aβ formation. This latter hypothesis is consistent with the fact that the most common risk factors for AD, apolipoprotein E (ApoE) allele status, age, education, and fitness, encompass suboptimal synaptic function. Thus, the synaptic dysfunction in AD may be both cause and effect, and remediating synaptic dysfunction in AD may have acute effects on the symptoms present at the initiation of therapy and also slow disease progression. The cyclic nucleotide (cAMP and cGMP) signaling systems are intimately involved in the regulation of synaptic homeostasis. The phosphodiesterases (PDEs) are a superfamily of enzymes that critically regulate spatial and temporal aspects of cyclic nucleotide signaling through metabolic inactivation of cAMP and cGMP. Thus, targeting the PDEs to promote improved synaptic function, or 'synaptic resilience', may be an effective and facile approach to new symptomatic and disease modifying therapies for AD. There continues to be a significant drug discovery effort aimed at discovering PDE inhibitors to treat a variety of neuropsychiatric disorders. Here we review the current status of those efforts as they relate to potential new therapies for AD.

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

Directory of Open Access Journals (Sweden)

Sethuraman Swaminathan

2009-11-01

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

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

Science.gov (United States)

Graupner, Michael; Reyes, Alex D

2013-09-18

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

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

Science.gov (United States)

Sears, James C.; Broadie, Kendal

2018-01-01

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

Status Epilepticus Impairs Synaptic Plasticity in Rat Hippocampus and Is Followed by Changes in Expression of NMDA Receptors.

Science.gov (United States)

Postnikova, T Y; Zubareva, O E; Kovalenko, A A; Kim, K K; Magazanik, L G; Zaitsev, A V

2017-03-01

Cognitive deficits and memory loss are frequent in patients with temporal lobe epilepsy. Persistent changes in synaptic efficacy are considered as a cellular substrate underlying memory processes. Electrophysiological studies have shown that the properties of short-term and long-term synaptic plasticity in the cortex and hippocampus may undergo substantial changes after seizures. However, the neural mechanisms responsible for these changes are not clear. In this study, we investigated the properties of short-term and long-term synaptic plasticity in rat hippocampal slices 24 h after pentylenetetrazole (PTZ)-induced status epilepticus. We found that the induction of long-term potentiation (LTP) in CA1 pyramidal cells is reduced compared to the control, while short-term facilitation is increased. The experimental results do not support the hypothesis that status epilepticus leads to background potentiation of hippocampal synapses and further LTP induction becomes weaker due to occlusion, as the dependence of synaptic responses on the strength of input stimulation was not different in the control and experimental animals. The decrease in LTP can be caused by impairment of molecular mechanisms of neuronal plasticity, including those associated with NMDA receptors and/or changes in their subunit composition. Real-time PCR demonstrated significant increases in the expression of GluN1 and GluN2A subunits 3 h after PTZ-induced status epilepticus. The overexpression of obligate GluN1 subunit suggests an increase in the total number of NMDA receptors in the hippocampus. A 3-fold increase in the expression of the GluN2B subunit observed 24 h after PTZ-induced status epilepticus might be indicative of an increase in the proportion of GluN2B-containing NMDA receptors. Increased expression of the GluN2B subunit may be a cause for reducing the magnitude of LTP at hippocampal synapses after status epilepticus.

Functional properties and synaptic integration of genetically labelled dopaminergic neurons in intrastriatal grafts

DEFF Research Database (Denmark)

Sørensen, Andreas Toft; Thompson, Lachlan; Kirik, Deniz

2005-01-01

in the dopamine-depleted striatum than of those in the intact striatum. Our findings define specific electrophysiological characteristics of transplanted fetal dopaminergic neurons, and we provide the first direct evidence of functional synaptic integration of these neurons into host neural circuitries......., the electrophysiological properties grafted cells need to have in order to induce substantial functional recovery are poorly defined. It has not been possible to prospectively identify and record from dopaminergic neurons in fetal transplants. Here we used transgenic mice expressing green fluorescent protein under control...... of the rat tyrosine hydroxylase promoter for whole-cell patch-clamp recordings of endogenous and grafted dopaminergic neurons. We transplanted ventral mesencephalic tissue from E12.5 transgenic mice into striatum of neonatal rats with or without lesions of the nigrostriatal dopamine system. The transplanted...

A computational study of astrocytic glutamate influence on post-synaptic neuronal excitability.

Directory of Open Access Journals (Sweden)

Bronac Flanagan

2018-04-01

Full Text Available The ability of astrocytes to rapidly clear synaptic glutamate and purposefully release the excitatory transmitter is critical in the functioning of synapses and neuronal circuits. Dysfunctions of these homeostatic functions have been implicated in the pathology of brain disorders such as mesial temporal lobe epilepsy. However, the reasons for these dysfunctions are not clear from experimental data and computational models have been developed to provide further understanding of the implications of glutamate clearance from the extracellular space, as a result of EAAT2 downregulation: although they only partially account for the glutamate clearance process. In this work, we develop an explicit model of the astrocytic glutamate transporters, providing a more complete description of the glutamate chemical potential across the astrocytic membrane and its contribution to glutamate transporter driving force based on thermodynamic principles and experimental data. Analysis of our model demonstrates that increased astrocytic glutamate content due to glutamine synthetase downregulation also results in increased postsynaptic quantal size due to gliotransmission. Moreover, the proposed model demonstrates that increased astrocytic glutamate could prolong the time course of glutamate in the synaptic cleft and enhances astrocyte-induced slow inward currents, causing a disruption to the clarity of synaptic signalling and the occurrence of intervals of higher frequency postsynaptic firing. Overall, our work distilled the necessity of a low astrocytic glutamate concentration for reliable synaptic transmission of information and the possible implications of enhanced glutamate levels as in epilepsy.

Neural cell adhesion molecule-180-mediated homophilic binding induces epidermal growth factor receptor (EGFR) down-regulation and uncouples the inhibitory function of EGFR in neurite outgrowth

DEFF Research Database (Denmark)

Povlsen, Gro Klitgaard; Berezin, Vladimir; Bock, Elisabeth

2008-01-01

The neural cell adhesion molecule (NCAM) plays important roles in neuronal development, regeneration, and synaptic plasticity. NCAM homophilic binding mediates cell adhesion and induces intracellular signals, in which the fibroblast growth factor receptor plays a prominent role. Recent studies...... this NCAM-180-induced EGFR down-regulation involves increased EGFR ubiquitination and lysosomal EGFR degradation. Furthermore, NCAM-180-mediated EGFR down-regulation requires NCAM homophilic binding and interactions of the cytoplasmic domain of NCAM-180 with intracellular interaction partners, but does...

Synaptic Plasticity in Cardiac Innervation and Its Potential Role in Atrial Fibrillation

Directory of Open Access Journals (Sweden)

Jesse L. Ashton

2018-03-01