Hebbian Wiring Plasticity Generates Efficient Network Structures for Robust Inference with Synaptic Weight Plasticity

PubMed Central

Hiratani, Naoki; Fukai, Tomoki

2016-01-01

In the adult mammalian cortex, a small fraction of spines are created and eliminated every day, and the resultant synaptic connection structure is highly nonrandom, even in local circuits. However, it remains unknown whether a particular synaptic connection structure is functionally advantageous in local circuits, and why creation and elimination of synaptic connections is necessary in addition to rich synaptic weight plasticity. To answer these questions, we studied an inference task model through theoretical and numerical analyses. We demonstrate that a robustly beneficial network structure naturally emerges by combining Hebbian-type synaptic weight plasticity and wiring plasticity. Especially in a sparsely connected network, wiring plasticity achieves reliable computation by enabling efficient information transmission. Furthermore, the proposed rule reproduces experimental observed correlation between spine dynamics and task performance. PMID:27303271

An Approximation of the Error Backpropagation Algorithm in a Predictive Coding Network with Local Hebbian Synaptic Plasticity

PubMed Central

Whittington, James C. R.; Bogacz, Rafal

2017-01-01

To efficiently learn from feedback, cortical networks need to update synaptic weights on multiple levels of cortical hierarchy. An effective and well-known algorithm for computing such changes in synaptic weights is the error backpropagation algorithm. However, in this algorithm, the change in synaptic weights is a complex function of weights and activities of neurons not directly connected with the synapse being modified, whereas the changes in biological synapses are determined only by the activity of presynaptic and postsynaptic neurons. Several models have been proposed that approximate the backpropagation algorithm with local synaptic plasticity, but these models require complex external control over the network or relatively complex plasticity rules. Here we show that a network developed in the predictive coding framework can efficiently perform supervised learning fully autonomously, employing only simple local Hebbian plasticity. Furthermore, for certain parameters, the weight change in the predictive coding model converges to that of the backpropagation algorithm. This suggests that it is possible for cortical networks with simple Hebbian synaptic plasticity to implement efficient learning algorithms in which synapses in areas on multiple levels of hierarchy are modified to minimize the error on the output. PMID:28333583

An Approximation of the Error Backpropagation Algorithm in a Predictive Coding Network with Local Hebbian Synaptic Plasticity.

PubMed

Whittington, James C R; Bogacz, Rafal

2017-05-01

To efficiently learn from feedback, cortical networks need to update synaptic weights on multiple levels of cortical hierarchy. An effective and well-known algorithm for computing such changes in synaptic weights is the error backpropagation algorithm. However, in this algorithm, the change in synaptic weights is a complex function of weights and activities of neurons not directly connected with the synapse being modified, whereas the changes in biological synapses are determined only by the activity of presynaptic and postsynaptic neurons. Several models have been proposed that approximate the backpropagation algorithm with local synaptic plasticity, but these models require complex external control over the network or relatively complex plasticity rules. Here we show that a network developed in the predictive coding framework can efficiently perform supervised learning fully autonomously, employing only simple local Hebbian plasticity. Furthermore, for certain parameters, the weight change in the predictive coding model converges to that of the backpropagation algorithm. This suggests that it is possible for cortical networks with simple Hebbian synaptic plasticity to implement efficient learning algorithms in which synapses in areas on multiple levels of hierarchy are modified to minimize the error on the output.

Origin of the computational hardness for learning with binary synapses.

PubMed

Huang, Haiping; Kabashima, Yoshiyuki

2014-11-01

Through supervised learning in a binary perceptron one is able to classify an extensive number of random patterns by a proper assignment of binary synaptic weights. However, to find such assignments in practice is quite a nontrivial task. The relation between the weight space structure and the algorithmic hardness has not yet been fully understood. To this end, we analytically derive the Franz-Parisi potential for the binary perceptron problem by starting from an equilibrium solution of weights and exploring the weight space structure around it. Our result reveals the geometrical organization of the weight space; the weight space is composed of isolated solutions, rather than clusters of exponentially many close-by solutions. The pointlike clusters far apart from each other in the weight space explain the previously observed glassy behavior of stochastic local search heuristics.

Characterization of emergent synaptic topologies in noisy neural networks

NASA Astrophysics Data System (ADS)

Miller, Aaron James

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

Event-Driven Random Back-Propagation: Enabling Neuromorphic Deep Learning Machines

PubMed Central

Neftci, Emre O.; Augustine, Charles; Paul, Somnath; Detorakis, Georgios

2017-01-01

An ongoing challenge in neuromorphic computing is to devise general and computationally efficient models of inference and learning which are compatible with the spatial and temporal constraints of the brain. One increasingly popular and successful approach is to take inspiration from inference and learning algorithms used in deep neural networks. However, the workhorse of deep learning, the gradient descent Gradient Back Propagation (BP) rule, often relies on the immediate availability of network-wide information stored with high-precision memory during learning, and precise operations that are difficult to realize in neuromorphic hardware. Remarkably, recent work showed that exact backpropagated gradients are not essential for learning deep representations. Building on these results, we demonstrate an event-driven random BP (eRBP) rule that uses an error-modulated synaptic plasticity for learning deep representations. Using a two-compartment Leaky Integrate & Fire (I&F) neuron, the rule requires only one addition and two comparisons for each synaptic weight, making it very suitable for implementation in digital or mixed-signal neuromorphic hardware. Our results show that using eRBP, deep representations are rapidly learned, achieving classification accuracies on permutation invariant datasets comparable to those obtained in artificial neural network simulations on GPUs, while being robust to neural and synaptic state quantizations during learning. PMID:28680387

Event-Driven Random Back-Propagation: Enabling Neuromorphic Deep Learning Machines.

PubMed

Neftci, Emre O; Augustine, Charles; Paul, Somnath; Detorakis, Georgios

2017-01-01

An ongoing challenge in neuromorphic computing is to devise general and computationally efficient models of inference and learning which are compatible with the spatial and temporal constraints of the brain. One increasingly popular and successful approach is to take inspiration from inference and learning algorithms used in deep neural networks. However, the workhorse of deep learning, the gradient descent Gradient Back Propagation (BP) rule, often relies on the immediate availability of network-wide information stored with high-precision memory during learning, and precise operations that are difficult to realize in neuromorphic hardware. Remarkably, recent work showed that exact backpropagated gradients are not essential for learning deep representations. Building on these results, we demonstrate an event-driven random BP (eRBP) rule that uses an error-modulated synaptic plasticity for learning deep representations. Using a two-compartment Leaky Integrate & Fire (I&F) neuron, the rule requires only one addition and two comparisons for each synaptic weight, making it very suitable for implementation in digital or mixed-signal neuromorphic hardware. Our results show that using eRBP, deep representations are rapidly learned, achieving classification accuracies on permutation invariant datasets comparable to those obtained in artificial neural network simulations on GPUs, while being robust to neural and synaptic state quantizations during learning.

From modulated Hebbian plasticity to simple behavior learning through noise and weight saturation.

PubMed

Soltoggio, Andrea; Stanley, Kenneth O

2012-10-01

Synaptic plasticity is a major mechanism for adaptation, learning, and memory. Yet current models struggle to link local synaptic changes to the acquisition of behaviors. The aim of this paper is to demonstrate a computational relationship between local Hebbian plasticity and behavior learning by exploiting two traditionally unwanted features: neural noise and synaptic weight saturation. A modulation signal is employed to arbitrate the sign of plasticity: when the modulation is positive, the synaptic weights saturate to express exploitative behavior; when it is negative, the weights converge to average values, and neural noise reconfigures the network's functionality. This process is demonstrated through simulating neural dynamics in the autonomous emergence of fearful and aggressive navigating behaviors and in the solution to reward-based problems. The neural model learns, memorizes, and modifies different behaviors that lead to positive modulation in a variety of settings. The algorithm establishes a simple relationship between local plasticity and behavior learning by demonstrating the utility of noise and weight saturation. Moreover, it provides a new tool to simulate adaptive behavior, and contributes to bridging the gap between synaptic changes and behavior in neural computation. Copyright © 2012 Elsevier Ltd. All rights reserved.

Attractor neural networks with resource-efficient synaptic connectivity

NASA Astrophysics Data System (ADS)

Pehlevan, Cengiz; Sengupta, Anirvan

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

Integrated neuron circuit for implementing neuromorphic system with synaptic device

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Energy Efficient Sparse Connectivity from Imbalanced Synaptic Plasticity Rules

PubMed Central

Sacramento, João; Wichert, Andreas; van Rossum, Mark C. W.

2015-01-01

It is believed that energy efficiency is an important constraint in brain evolution. As synaptic transmission dominates energy consumption, energy can be saved by ensuring that only a few synapses are active. It is therefore likely that the formation of sparse codes and sparse connectivity are fundamental objectives of synaptic plasticity. In this work we study how sparse connectivity can result from a synaptic learning rule of excitatory synapses. Information is maximised when potentiation and depression are balanced according to the mean presynaptic activity level and the resulting fraction of zero-weight synapses is around 50%. However, an imbalance towards depression increases the fraction of zero-weight synapses without significantly affecting performance. We show that imbalanced plasticity corresponds to imposing a regularising constraint on the L 1-norm of the synaptic weight vector, a procedure that is well-known to induce sparseness. Imbalanced plasticity is biophysically plausible and leads to more efficient synaptic configurations than a previously suggested approach that prunes synapses after learning. Our framework gives a novel interpretation to the high fraction of silent synapses found in brain regions like the cerebellum. PMID:26046817

Plasticity-Driven Self-Organization under Topological Constraints Accounts for Non-random Features of Cortical Synaptic Wiring

PubMed Central

Miner, Daniel; Triesch, Jochen

2016-01-01

Understanding the structure and dynamics of cortical connectivity is vital to understanding cortical function. Experimental data strongly suggest that local recurrent connectivity in the cortex is significantly non-random, exhibiting, for example, above-chance bidirectionality and an overrepresentation of certain triangular motifs. Additional evidence suggests a significant distance dependency to connectivity over a local scale of a few hundred microns, and particular patterns of synaptic turnover dynamics, including a heavy-tailed distribution of synaptic efficacies, a power law distribution of synaptic lifetimes, and a tendency for stronger synapses to be more stable over time. Understanding how many of these non-random features simultaneously arise would provide valuable insights into the development and function of the cortex. While previous work has modeled some of the individual features of local cortical wiring, there is no model that begins to comprehensively account for all of them. We present a spiking network model of a rodent Layer 5 cortical slice which, via the interactions of a few simple biologically motivated intrinsic, synaptic, and structural plasticity mechanisms, qualitatively reproduces these non-random effects when combined with simple topological constraints. Our model suggests that mechanisms of self-organization arising from a small number of plasticity rules provide a parsimonious explanation for numerous experimentally observed non-random features of recurrent cortical wiring. Interestingly, similar mechanisms have been shown to endow recurrent networks with powerful learning abilities, suggesting that these mechanism are central to understanding both structure and function of cortical synaptic wiring. PMID:26866369

Modeling of synchronization behavior of bursting neurons at nonlinearly coupled dynamical networks.

PubMed

Çakir, Yüksel

2016-01-01

Synchronization behaviors of bursting neurons coupled through electrical and dynamic chemical synapses are investigated. The Izhikevich model is used with random and small world network of bursting neurons. Various currents which consist of diffusive electrical and time-delayed dynamic chemical synapses are used in the simulations to investigate the influences of synaptic currents and couplings on synchronization behavior of bursting neurons. The effects of parameters, such as time delay, inhibitory synaptic strengths, and decay time on synchronization behavior are investigated. It is observed that in random networks with no delay, bursting synchrony is established with the electrical synapse alone, single spiking synchrony is observed with hybrid coupling. In small world network with no delay, periodic bursting behavior with multiple spikes is observed when only chemical and only electrical synapse exist. Single-spike and multiple-spike bursting are established with hybrid couplings. A decrease in the synchronization measure is observed with zero time delay, as the decay time is increased in random network. For synaptic delays which are above active phase period, synchronization measure increases with an increase in synaptic strength and time delay in small world network. However, in random network, it increases with only an increase in synaptic strength.

3D Ta/TaO x /TiO2/Ti synaptic array and linearity tuning of weight update for hardware neural network applications

NASA Astrophysics Data System (ADS)

Wang, I.-Ting; Chang, Chih-Cheng; Chiu, Li-Wen; Chou, Teyuh; Hou, Tuo-Hung

2016-09-01

The implementation of highly anticipated hardware neural networks (HNNs) hinges largely on the successful development of a low-power, high-density, and reliable analog electronic synaptic array. In this study, we demonstrate a two-layer Ta/TaO x /TiO2/Ti cross-point synaptic array that emulates the high-density three-dimensional network architecture of human brains. Excellent uniformity and reproducibility among intralayer and interlayer cells were realized. Moreover, at least 50 analog synaptic weight states could be precisely controlled with minimal drifting during a cycling endurance test of 5000 training pulses at an operating voltage of 3 V. We also propose a new state-independent bipolar-pulse-training scheme to improve the linearity of weight updates. The improved linearity considerably enhances the fault tolerance of HNNs, thus improving the training accuracy.

On-chip photonic synapse.

PubMed

Cheng, Zengguang; Ríos, Carlos; Pernice, Wolfram H P; Wright, C David; Bhaskaran, Harish

2017-09-01

The search for new "neuromorphic computing" architectures that mimic the brain's approach to simultaneous processing and storage of information is intense. Because, in real brains, neuronal synapses outnumber neurons by many orders of magnitude, the realization of hardware devices mimicking the functionality of a synapse is a first and essential step in such a search. We report the development of such a hardware synapse, implemented entirely in the optical domain via a photonic integrated-circuit approach. Using purely optical means brings the benefits of ultrafast operation speed, virtually unlimited bandwidth, and no electrical interconnect power losses. Our synapse uses phase-change materials combined with integrated silicon nitride waveguides. Crucially, we can randomly set the synaptic weight simply by varying the number of optical pulses sent down the waveguide, delivering an incredibly simple yet powerful approach that heralds systems with a continuously variable synaptic plasticity resembling the true analog nature of biological synapses.

A Mathematical Model for Storage and Recall of Images using Targeted Synchronization of Coupled Maps.

PubMed

Palaniyandi, P; Rangarajan, Govindan

2017-08-21

We propose a mathematical model for storage and recall of images using coupled maps. We start by theoretically investigating targeted synchronization in coupled map systems wherein only a desired (partial) subset of the maps is made to synchronize. A simple method is introduced to specify coupling coefficients such that targeted synchronization is ensured. The principle of this method is extended to storage/recall of images using coupled Rulkov maps. The process of adjusting coupling coefficients between Rulkov maps (often used to model neurons) for the purpose of storing a desired image mimics the process of adjusting synaptic strengths between neurons to store memories. Our method uses both synchronisation and synaptic weight modification, as the human brain is thought to do. The stored image can be recalled by providing an initial random pattern to the dynamical system. The storage and recall of the standard image of Lena is explicitly demonstrated.

On-chip photonic synapse

PubMed Central

Cheng, Zengguang; Ríos, Carlos; Pernice, Wolfram H. P.; Wright, C. David; Bhaskaran, Harish

2017-01-01

The search for new “neuromorphic computing” architectures that mimic the brain’s approach to simultaneous processing and storage of information is intense. Because, in real brains, neuronal synapses outnumber neurons by many orders of magnitude, the realization of hardware devices mimicking the functionality of a synapse is a first and essential step in such a search. We report the development of such a hardware synapse, implemented entirely in the optical domain via a photonic integrated-circuit approach. Using purely optical means brings the benefits of ultrafast operation speed, virtually unlimited bandwidth, and no electrical interconnect power losses. Our synapse uses phase-change materials combined with integrated silicon nitride waveguides. Crucially, we can randomly set the synaptic weight simply by varying the number of optical pulses sent down the waveguide, delivering an incredibly simple yet powerful approach that heralds systems with a continuously variable synaptic plasticity resembling the true analog nature of biological synapses. PMID:28959725

Soybean isoflavone ameliorates β-amyloid 1-42-induced learning and memory deficit in rats by protecting synaptic structure and function.

PubMed

Ding, Juan; Xi, Yuan-Di; Zhang, Dan-Di; Zhao, Xia; Liu, Jin-Meng; Li, Chao-Qun; Han, Jing; Xiao, Rong

2013-12-01

This research aims to investigate whether soybean isoflavone (SIF) could alleviate the learning and memory deficit induced by β-amyloid peptides 1-42 (Aβ 1-42) by protecting the synapses of rats. Adult male Wistar rats were randomly allocated to the following groups: (1) control group; (2) Aβ 1-42 group; (3) SIF group; (4) SIF + Aβ 1-42 group (SIF pretreatment group) according to body weight. The 80 mg/kg/day of SIF was administered orally by gavage to the rats in SIF and SIF+Aβ 1-42 groups. Aβ 1-42 was injected into the lateral cerebral ventricle of rats in Aβ 1-42 and SIF+Aβ 1-42 groups. The ability of learning and memory, ultramicrostructure of hippocampal synapses, and expression of synaptic related proteins were investigated. The Morris water maze results showed the escape latency and total distance were decreased in the rats of SIF pretreatment group compared to the rats in Aβ1-42 group. Furthermore, SIF pretreatment could alleviate the synaptic structural damage and antagonize the down-regulation expressions of below proteins induced by Aβ1-42: (1) mRNA and protein of the synaptophysin and postsynaptic density protein 95 (PSD-95); (2) protein of calmodulin (CaM), Ca(2+) /calmodulin-dependent protein kinase II (CaMK II), and cAMP response element binding protein (CREB); (3) phosphorylation levels of CaMK II and CREB (pCAMK II, pCREB). These results suggested that SIF pretreatment could ameliorate the impairment of learning and memory ability in rats induced by Aβ 1-42, and its mechanism might be associated with the protection of synaptic plasticity by improving the synaptic structure and regulating the synaptic related proteins. Copyright © 2013 Wiley Periodicals, Inc.

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

PubMed Central

Bi, Zedong; Zhou, Changsong

2016-01-01

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

Dimensionality and entropy of spontaneous and evoked rate activity

NASA Astrophysics Data System (ADS)

Engelken, Rainer; Wolf, Fred

Cortical circuits exhibit complex activity patterns both spontaneously and evoked by external stimuli. Finding low-dimensional structure in population activity is a challenge. What is the diversity of the collective neural activity and how is it affected by an external stimulus? Using concepts from ergodic theory, we calculate the attractor dimensionality and dynamical entropy production of these networks. We obtain these two canonical measures of the collective network dynamics from the full set of Lyapunov exponents. We consider a randomly-wired firing-rate network that exhibits chaotic rate fluctuations for sufficiently strong synaptic weights. We show that dynamical entropy scales logarithmically with synaptic coupling strength, while the attractor dimensionality saturates. Thus, despite the increasing uncertainty, the diversity of collective activity saturates for strong coupling. We find that a time-varying external stimulus drastically reduces both entropy and dimensionality. Finally, we analytically approximate the full Lyapunov spectrum in several limiting cases by random matrix theory. Our study opens a novel avenue to characterize the complex dynamics of rate networks and the geometric structure of the corresponding high-dimensional chaotic attractor. received funding from Evangelisches Studienwerk Villigst, DFG through CRC 889 and Volkswagen Foundation.

Synaptic behaviors of thin-film transistor with a Pt/HfO x /n-type indium-gallium-zinc oxide gate stack.

PubMed

Yang, Paul; Park, Daehoon; Beom, Keonwon; Kim, Hyung Jun; Kang, Chi Jung; Yoon, Tae-Sik

2018-07-20

We report a variety of synaptic behaviors in a thin-film transistor (TFT) with a metal-oxide-semiconductor gate stack that has a Pt/HfO x /n-type indium-gallium-zinc oxide (n-IGZO) structure. The three-terminal synaptic TFT exhibits a tunable synaptic weight with a drain current modulation upon repeated application of gate and drain voltages. The synaptic weight modulation is analog, voltage-polarity dependent reversible, and strong with a dynamic range of multiple orders of magnitude (>10 4 ). This modulation process emulates biological synaptic potentiation, depression, excitatory-postsynaptic current, paired-pulse facilitation, and short-term to long-term memory transition behaviors as a result of repeated pulsing with respect to the pulse amplitude, width, repetition number, and the interval between pulses. These synaptic behaviors are interpreted based on the changes in the capacitance of the Pt/HfO x /n-IGZO gate stack, the channel mobility, and the threshold voltage that result from the redistribution of oxygen ions by the applied gate voltage. These results demonstrate the potential of this structure for three-terminal synaptic transistor using the gate stack composed of the HfO x gate insulator and the IGZO channel layer.

Synaptic behaviors of thin-film transistor with a Pt/HfO x /n-type indium–gallium–zinc oxide gate stack

NASA Astrophysics Data System (ADS)

Yang, Paul; Park, Daehoon; Beom, Keonwon; Kim, Hyung Jun; Kang, Chi Jung; Yoon, Tae-Sik

2018-07-01

We report a variety of synaptic behaviors in a thin-film transistor (TFT) with a metal-oxide-semiconductor gate stack that has a Pt/HfO x /n-type indium–gallium–zinc oxide (n-IGZO) structure. The three-terminal synaptic TFT exhibits a tunable synaptic weight with a drain current modulation upon repeated application of gate and drain voltages. The synaptic weight modulation is analog, voltage-polarity dependent reversible, and strong with a dynamic range of multiple orders of magnitude (>104). This modulation process emulates biological synaptic potentiation, depression, excitatory-postsynaptic current, paired-pulse facilitation, and short-term to long-term memory transition behaviors as a result of repeated pulsing with respect to the pulse amplitude, width, repetition number, and the interval between pulses. These synaptic behaviors are interpreted based on the changes in the capacitance of the Pt/HfO x /n-IGZO gate stack, the channel mobility, and the threshold voltage that result from the redistribution of oxygen ions by the applied gate voltage. These results demonstrate the potential of this structure for three-terminal synaptic transistor using the gate stack composed of the HfO x gate insulator and the IGZO channel layer.

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

PubMed Central

Burbank, Kendra S.; Kreiman, Gabriel

2012-01-01

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

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

PubMed

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

2009-12-01

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

Neural network for processing both spatial and temporal data with time based back-propagation

NASA Technical Reports Server (NTRS)

Villarreal, James A. (Inventor); Shelton, Robert O. (Inventor)

1993-01-01

Neural networks are computing systems modeled after the paradigm of the biological brain. For years, researchers using various forms of neural networks have attempted to model the brain's information processing and decision-making capabilities. Neural network algorithms have impressively demonstrated the capability of modeling spatial information. On the other hand, the application of parallel distributed models to the processing of temporal data has been severely restricted. The invention introduces a novel technique which adds the dimension of time to the well known back-propagation neural network algorithm. In the space-time neural network disclosed herein, the synaptic weights between two artificial neurons (processing elements) are replaced with an adaptable-adjustable filter. Instead of a single synaptic weight, the invention provides a plurality of weights representing not only association, but also temporal dependencies. In this case, the synaptic weights are the coefficients to the adaptable digital filters. Novelty is believed to lie in the disclosure of a processing element and a network of the processing elements which are capable of processing temporal as well as spacial data.

Synaptic Tagging During Memory Allocation

PubMed Central

Rogerson, Thomas; Cai, Denise; Frank, Adam; Sano, Yoshitake; Shobe, Justin; Aranda, Manuel L.; Silva, Alcino J.

2014-01-01

There is now compelling evidence that the allocation of memory to specific neurons (neuronal allocation) and synapses (synaptic allocation) in a neurocircuit is not random and that instead specific mechanisms, such as increases in neuronal excitability and synaptic tagging and capture, determine the exact sites where memories are stored. We propose an integrated view of these processes, such that neuronal allocation, synaptic tagging and capture, spine clustering and metaplasticity reflect related aspects of memory allocation mechanisms. Importantly, the properties of these mechanisms suggest a set of rules that profoundly affect how memories are stored and recalled. PMID:24496410

Dense modifiable interconnections utilizing photorefractive volume holograms

NASA Astrophysics Data System (ADS)

Psaltis, Demetri; Qiao, Yong

1990-11-01

This report describes an experimental two-layer optical neural network built at Caltech. The system uses photorefractive volume holograms to implement dense, modifiable synaptic interconnections and liquid crystal light valves (LCVS) to perform nonlinear thresholding operations. Kanerva's Sparse, Distributed Memory was implemented using this network and its ability to recognize handwritten character-alphabet (A-Z) has been demonstrated experimentally. According to Kanerva's model, the first layer has fixed, random weights of interconnections and the second layer is trained by sum-of-outer-products rule. After training, the recognition rates of the network on the training set (104 patterns) and test set (520 patterns) are 100 and 50 percent, respectively.

Synaptic Scaling in Combination with Many Generic Plasticity Mechanisms Stabilizes Circuit Connectivity

PubMed Central

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

2011-01-01

Synaptic scaling is a slow process that modifies synapses, keeping the firing rate of neural circuits in specific regimes. Together with other processes, such as conventional synaptic plasticity in the form of long term depression and potentiation, synaptic scaling changes the synaptic patterns in a network, ensuring diverse, functionally relevant, stable, and input-dependent connectivity. How synaptic patterns are generated and stabilized, however, is largely unknown. Here we formally describe and analyze synaptic scaling based on results from experimental studies and demonstrate that the combination of different conventional plasticity mechanisms and synaptic scaling provides a powerful general framework for regulating network connectivity. In addition, we design several simple models that reproduce experimentally observed synaptic distributions as well as the observed synaptic modifications during sustained activity changes. These models predict that the combination of plasticity with scaling generates globally stable, input-controlled synaptic patterns, also in recurrent networks. Thus, in combination with other forms of plasticity, synaptic scaling can robustly yield neuronal circuits with high synaptic diversity, which potentially enables robust dynamic storage of complex activation patterns. This mechanism is even more pronounced when considering networks with a realistic degree of inhibition. Synaptic scaling combined with plasticity could thus be the basis for learning structured behavior even in initially random networks. PMID:22203799

Using Inspiration from Synaptic Plasticity Rules to Optimize Traffic Flow in Distributed Engineered Networks.

PubMed

Suen, Jonathan Y; Navlakha, Saket

2017-05-01

Controlling the flow and routing of data is a fundamental problem in many distributed networks, including transportation systems, integrated circuits, and the Internet. In the brain, synaptic plasticity rules have been discovered that regulate network activity in response to environmental inputs, which enable circuits to be stable yet flexible. Here, we develop a new neuro-inspired model for network flow control that depends only on modifying edge weights in an activity-dependent manner. We show how two fundamental plasticity rules, long-term potentiation and long-term depression, can be cast as a distributed gradient descent algorithm for regulating traffic flow in engineered networks. We then characterize, both by simulation and analytically, how different forms of edge-weight-update rules affect network routing efficiency and robustness. We find a close correspondence between certain classes of synaptic weight update rules derived experimentally in the brain and rules commonly used in engineering, suggesting common principles to both.

Pattern classification by memristive crossbar circuits using ex situ and in situ training.

PubMed

Alibart, Fabien; Zamanidoost, Elham; Strukov, Dmitri B

2013-01-01

Memristors are memory resistors that promise the efficient implementation of synaptic weights in artificial neural networks. Whereas demonstrations of the synaptic operation of memristors already exist, the implementation of even simple networks is more challenging and has yet to be reported. Here we demonstrate pattern classification using a single-layer perceptron network implemented with a memrisitive crossbar circuit and trained using the perceptron learning rule by ex situ and in situ methods. In the first case, synaptic weights, which are realized as conductances of titanium dioxide memristors, are calculated on a precursor software-based network and then imported sequentially into the crossbar circuit. In the second case, training is implemented in situ, so the weights are adjusted in parallel. Both methods work satisfactorily despite significant variations in the switching behaviour of the memristors. These results give hope for the anticipated efficient implementation of artificial neuromorphic networks and pave the way for dense, high-performance information processing systems.

Pattern classification by memristive crossbar circuits using ex situ and in situ training

NASA Astrophysics Data System (ADS)

Alibart, Fabien; Zamanidoost, Elham; Strukov, Dmitri B.

2013-06-01

Memristors are memory resistors that promise the efficient implementation of synaptic weights in artificial neural networks. Whereas demonstrations of the synaptic operation of memristors already exist, the implementation of even simple networks is more challenging and has yet to be reported. Here we demonstrate pattern classification using a single-layer perceptron network implemented with a memrisitive crossbar circuit and trained using the perceptron learning rule by ex situ and in situ methods. In the first case, synaptic weights, which are realized as conductances of titanium dioxide memristors, are calculated on a precursor software-based network and then imported sequentially into the crossbar circuit. In the second case, training is implemented in situ, so the weights are adjusted in parallel. Both methods work satisfactorily despite significant variations in the switching behaviour of the memristors. These results give hope for the anticipated efficient implementation of artificial neuromorphic networks and pave the way for dense, high-performance information processing systems.

Fully parallel write/read in resistive synaptic array for accelerating on-chip learning

NASA Astrophysics Data System (ADS)

Gao, Ligang; Wang, I.-Ting; Chen, Pai-Yu; Vrudhula, Sarma; Seo, Jae-sun; Cao, Yu; Hou, Tuo-Hung; Yu, Shimeng

2015-11-01

A neuro-inspired computing paradigm beyond the von Neumann architecture is emerging and it generally takes advantage of massive parallelism and is aimed at complex tasks that involve intelligence and learning. The cross-point array architecture with synaptic devices has been proposed for on-chip implementation of the weighted sum and weight update in the learning algorithms. In this work, forming-free, silicon-process-compatible Ta/TaO x /TiO2/Ti synaptic devices are fabricated, in which >200 levels of conductance states could be continuously tuned by identical programming pulses. In order to demonstrate the advantages of parallelism of the cross-point array architecture, a novel fully parallel write scheme is designed and experimentally demonstrated in a small-scale crossbar array to accelerate the weight update in the training process, at a speed that is independent of the array size. Compared to the conventional row-by-row write scheme, it achieves >30× speed-up and >30× improvement in energy efficiency as projected in a large-scale array. If realistic synaptic device characteristics such as device variations are taken into an array-level simulation, the proposed array architecture is able to achieve ∼95% recognition accuracy of MNIST handwritten digits, which is close to the accuracy achieved by software using the ideal sparse coding algorithm.

Face classification using electronic synapses

NASA Astrophysics Data System (ADS)

Yao, Peng; Wu, Huaqiang; Gao, Bin; Eryilmaz, Sukru Burc; Huang, Xueyao; Zhang, Wenqiang; Zhang, Qingtian; Deng, Ning; Shi, Luping; Wong, H.-S. Philip; Qian, He

2017-05-01

Conventional hardware platforms consume huge amount of energy for cognitive learning due to the data movement between the processor and the off-chip memory. Brain-inspired device technologies using analogue weight storage allow to complete cognitive tasks more efficiently. Here we present an analogue non-volatile resistive memory (an electronic synapse) with foundry friendly materials. The device shows bidirectional continuous weight modulation behaviour. Grey-scale face classification is experimentally demonstrated using an integrated 1024-cell array with parallel online training. The energy consumption within the analogue synapses for each iteration is 1,000 × (20 ×) lower compared to an implementation using Intel Xeon Phi processor with off-chip memory (with hypothetical on-chip digital resistive random access memory). The accuracy on test sets is close to the result using a central processing unit. These experimental results consolidate the feasibility of analogue synaptic array and pave the way toward building an energy efficient and large-scale neuromorphic system.

Face classification using electronic synapses.

PubMed

Yao, Peng; Wu, Huaqiang; Gao, Bin; Eryilmaz, Sukru Burc; Huang, Xueyao; Zhang, Wenqiang; Zhang, Qingtian; Deng, Ning; Shi, Luping; Wong, H-S Philip; Qian, He

2017-05-12

Conventional hardware platforms consume huge amount of energy for cognitive learning due to the data movement between the processor and the off-chip memory. Brain-inspired device technologies using analogue weight storage allow to complete cognitive tasks more efficiently. Here we present an analogue non-volatile resistive memory (an electronic synapse) with foundry friendly materials. The device shows bidirectional continuous weight modulation behaviour. Grey-scale face classification is experimentally demonstrated using an integrated 1024-cell array with parallel online training. The energy consumption within the analogue synapses for each iteration is 1,000 × (20 ×) lower compared to an implementation using Intel Xeon Phi processor with off-chip memory (with hypothetical on-chip digital resistive random access memory). The accuracy on test sets is close to the result using a central processing unit. These experimental results consolidate the feasibility of analogue synaptic array and pave the way toward building an energy efficient and large-scale neuromorphic system.

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

PubMed Central

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

2015-01-01

We present a neuromorphic implementation of multiple synaptic plasticity learning rules, which include both Spike Timing Dependent Plasticity (STDP) and Spike Timing Dependent Delay Plasticity (STDDP). We present a fully digital implementation as well as a mixed-signal implementation, both of which use a novel dynamic-assignment time-multiplexing approach and support up to 226 (64M) synaptic plasticity elements. Rather than implementing dedicated synapses for particular types of synaptic plasticity, we implemented a more generic synaptic plasticity adaptor array that is separate from the neurons in the neural network. Each adaptor performs synaptic plasticity according to the arrival times of the pre- and post-synaptic spikes assigned to it, and sends out a weighted or delayed pre-synaptic spike to the post-synaptic neuron in the neural network. This strategy provides great flexibility for building complex large-scale neural networks, as a neural network can be configured for multiple synaptic plasticity rules without changing its structure. We validate the proposed neuromorphic implementations with measurement results and illustrate that the circuits are capable of performing both STDP and STDDP. We argue that it is practical to scale the work presented here up to 236 (64G) synaptic adaptors on a current high-end FPGA platform. PMID:26041985

Retrieval Property of Attractor Network with Synaptic Depression

NASA Astrophysics Data System (ADS)

Matsumoto, Narihisa; Ide, Daisuke; Watanabe, Masataka; Okada, Masato

2007-08-01

Synaptic connections are known to change dynamically. High-frequency presynaptic inputs induce decrease of synaptic weights. This process is known as short-term synaptic depression. The synaptic depression controls a gain for presynaptic inputs. However, it remains a controversial issue what are functional roles of this gain control. We propose a new hypothesis that one of the functional roles is to enlarge basins of attraction. To verify this hypothesis, we employ a binary discrete-time associative memory model which consists of excitatory and inhibitory neurons. It is known that the excitatory-inhibitory balance controls an overall activity of the network. The synaptic depression might incorporate an activity control mechanism. Using a mean-field theory and computer simulations, we find that the synaptic depression enlarges the basins at a small loading rate while the excitatory-inhibitory balance enlarges them at a large loading rate. Furthermore the synaptic depression does not affect the steady state of the network if a threshold is set at an appropriate value. These results suggest that the synaptic depression works in addition to the effect of the excitatory-inhibitory balance, and it might improve an error-correcting ability in cortical circuits.

Generalized Adaptive Artificial Neural Networks

NASA Technical Reports Server (NTRS)

Tawel, Raoul

1993-01-01

Mathematical model of supervised learning by artificial neural network provides for simultaneous adjustments of both temperatures of neurons and synaptic weights, and includes feedback as well as feedforward synaptic connections. Extension of mathematical model described in "Adaptive Neurons For Artificial Neural Networks" (NPO-17803). Dynamics of neural network represented in new model by less-restrictive continuous formalism.

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

PubMed

Gilson, Matthieu; Fukai, Tomoki

2011-01-01

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

Emergence of low noise frustrated states in E/I balanced neural networks.

PubMed

Recio, I; Torres, J J

2016-12-01

We study emerging phenomena in binary neural networks where, with a probability c synaptic intensities are chosen according with a Hebbian prescription, and with probability (1-c) there is an extra random contribution to synaptic weights. This new term, randomly taken from a Gaussian bimodal distribution, balances the synaptic population in the network so that one has 80%-20% relation in E/I population ratio, mimicking the balance observed in mammals cortex. For some regions of the relevant parameters, our system depicts standard memory (at low temperature) and non-memory attractors (at high temperature). However, as c decreases and the level of the underlying noise also decreases below a certain temperature T t , a kind of memory-frustrated state, which resembles spin-glass behavior, sharply emerges. Contrary to what occurs in Hopfield-like neural networks, the frustrated state appears here even in the limit of the loading parameter α→0. Moreover, we observed that the frustrated state in fact corresponds to two states of non-vanishing activity uncorrelated with stored memories, associated, respectively, to a high activity or Up state and to a low activity or Down state. Using a linear stability analysis, we found regions in the space of relevant parameters for locally stable steady states and demonstrated that frustrated states coexist with memory attractors below T t . Then, multistability between memory and frustrated states is present for relatively small c, and metastability of memory attractors can emerge as c decreases even more. We studied our system using standard mean-field techniques and with Monte Carlo simulations, obtaining a perfect agreement between theory and simulations. Our study can be useful to explain the role of synapse heterogeneity on the emergence of stable Up and Down states not associated to memory attractors, and to explore the conditions to induce transitions among them, as in sleep-wake transitions. Copyright © 2016 Elsevier Ltd. All rights reserved.

Network algorithmics and the emergence of the cortical synaptic-weight distribution

NASA Astrophysics Data System (ADS)

Nathan, Andre; Barbosa, Valmir C.

2010-02-01

When a neuron fires and the resulting action potential travels down its axon toward other neurons’ dendrites, the effect on each of those neurons is mediated by the strength of the synapse that separates it from the firing neuron. This strength, in turn, is affected by the postsynaptic neuron’s response through a mechanism that is thought to underlie important processes such as learning and memory. Although of difficult quantification, cortical synaptic strengths have been found to obey a long-tailed unimodal distribution peaking near the lowest values (approximately lognormal), thus confirming some of the predictive models built previously. Most of these models are causally local, in the sense that they refer to the situation in which a number of neurons all fire directly at the same postsynaptic neuron. Consequently, they necessarily embody assumptions regarding the generation of action potentials by the presynaptic neurons that have little biological interpretability. We introduce a network model of large groups of interconnected neurons and demonstrate, making none of the assumptions that characterize the causally local models, that its long-term behavior gives rise to a distribution of synaptic weights (the mathematical surrogates of synaptic strengths) with the same properties that were experimentally observed. In our model, the action potentials that create a neuron’s input are, ultimately, the product of network-wide causal chains relating what happens at a neuron to the firings of others. Our model is then of a causally global nature and predicates the emergence of the synaptic-weight distribution on network structure and function. As such, it has the potential to become instrumental also in the study of other emergent cortical phenomena.

Operational parameters of an opto-electronic neural network employing fixed planar holographic interconnects

NASA Astrophysics Data System (ADS)

Keller, P. E.; Gmitro, A. F.

1993-07-01

A prototype neutral network system of multifaceted, planar interconnection holograms and opto-electronic neurons is analyzed. This analysis shows that a hologram fabricated with electron-beam lithography has the capacity to connect 6700 neuron outputs to 6700 neuron inputs, and that, the encoded synaptic weights have a precision of approximately 5 bits. Higher interconnection densities can be achieved by accepting a lower synaptic weight accuracy. For systems employing laser diodes at the outputs of the neurons, processing rates in the range of 45 to 720 trillion connections per second can potentially be achieved.

Real-Time Adaptive Color Segmentation by Neural Networks

NASA Technical Reports Server (NTRS)

Duong, Tuan A.

2004-01-01

Artificial neural networks that would utilize the cascade error projection (CEP) algorithm have been proposed as means of autonomous, real-time, adaptive color segmentation of images that change with time. In the original intended application, such a neural network would be used to analyze digitized color video images of terrain on a remote planet as viewed from an uninhabited spacecraft approaching the planet. During descent toward the surface of the planet, information on the segmentation of the images into differently colored areas would be updated adaptively in real time to capture changes in contrast, brightness, and resolution, all in an effort to identify a safe and scientifically productive landing site and provide control feedback to steer the spacecraft toward that site. Potential terrestrial applications include monitoring images of crops to detect insect invasions and monitoring of buildings and other facilities to detect intruders. The CEP algorithm is reliable and is well suited to implementation in very-large-scale integrated (VLSI) circuitry. It was chosen over other neural-network learning algorithms because it is better suited to realtime learning: It provides a self-evolving neural-network structure, requires fewer iterations to converge and is more tolerant to low resolution (that is, fewer bits) in the quantization of neural-network synaptic weights. Consequently, a CEP neural network learns relatively quickly, and the circuitry needed to implement it is relatively simple. Like other neural networks, a CEP neural network includes an input layer, hidden units, and output units (see figure). As in other neural networks, a CEP network is presented with a succession of input training patterns, giving rise to a set of outputs that are compared with the desired outputs. Also as in other neural networks, the synaptic weights are updated iteratively in an effort to bring the outputs closer to target values. A distinctive feature of the CEP neural network and algorithm is that each update of synaptic weights takes place in conjunction with the addition of another hidden unit, which then remains in place as still other hidden units are added on subsequent iterations. For a given training pattern, the synaptic weight between (1) the inputs and the previously added hidden units and (2) the newly added hidden unit is updated by an amount proportional to the partial derivative of a quadratic error function with respect to the synaptic weight. The synaptic weight between the newly added hidden unit and each output unit is given by a more complex function that involves the errors between the outputs and their target values, the transfer functions (hyperbolic tangents) of the neural units, and the derivatives of the transfer functions.

A synaptic organizing principle for cortical neuronal groups

PubMed Central

Perin, Rodrigo; Berger, Thomas K.; Markram, Henry

2011-01-01

Neuronal circuitry is often considered a clean slate that can be dynamically and arbitrarily molded by experience. However, when we investigated synaptic connectivity in groups of pyramidal neurons in the neocortex, we found that both connectivity and synaptic weights were surprisingly predictable. Synaptic weights follow very closely the number of connections in a group of neurons, saturating after only 20% of possible connections are formed between neurons in a group. When we examined the network topology of connectivity between neurons, we found that the neurons cluster into small world networks that are not scale-free, with less than 2 degrees of separation. We found a simple clustering rule where connectivity is directly proportional to the number of common neighbors, which accounts for these small world networks and accurately predicts the connection probability between any two neurons. This pyramidal neuron network clusters into multiple groups of a few dozen neurons each. The neurons composing each group are surprisingly distributed, typically more than 100 μm apart, allowing for multiple groups to be interlaced in the same space. In summary, we discovered a synaptic organizing principle that groups neurons in a manner that is common across animals and hence, independent of individual experiences. We speculate that these elementary neuronal groups are prescribed Lego-like building blocks of perception and that acquired memory relies more on combining these elementary assemblies into higher-order constructs. PMID:21383177

Spatiotemporal discrimination in neural networks with short-term synaptic plasticity

NASA Astrophysics Data System (ADS)

Shlaer, Benjamin; Miller, Paul

2015-03-01

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

Dynamic Observation of Brain-Like Learning in a Ferroelectric Synapse Device

NASA Astrophysics Data System (ADS)

Nishitani, Yu; Kaneko, Yukihiro; Ueda, Michihito; Fujii, Eiji; Tsujimura, Ayumu

2013-04-01

A brain-like learning function was implemented in an electronic synapse device using a ferroelectric-gate field effect transistor (FeFET). The FeFET was a bottom-gate type FET with a ZnO channel and a ferroelectric Pb(Zr,Ti)O3 (PZT) gate insulator. The synaptic weight, which is represented by the channel conductance of the FeFET, is updated by applying a gate voltage through a change in the ferroelectric polarization in the PZT. A learning function based on the symmetric spike-timing dependent synaptic plasticity was implemented in the synapse device using the multilevel weight update by applying a pulse gate voltage. The dynamic weighting and learning behavior in the synapse device was observed as a change in the membrane potential in a spiking neuron circuit.

Synaptic transistor with a reversible and analog conductance modulation using a Pt/HfOx/n-IGZO memcapacitor

NASA Astrophysics Data System (ADS)

Yang, Paul; Kim, Hyung Jun; Zheng, Hong; Beom, Geon Won; Park, Jong-Sung; Kang, Chi Jung; Yoon, Tae-Sik

2017-06-01

A synaptic transistor emulating the biological synaptic motion is demonstrated using the memcapacitance characteristics in a Pt/HfOx/n-indium-gallium-zinc-oxide (IGZO) memcapacitor. First, the metal-oxide-semiconductor (MOS) capacitor with Pt/HfOx/n-IGZO structure exhibits analog, polarity-dependent, and reversible memcapacitance in capacitance-voltage (C-V), capacitance-time (C-t), and voltage-pulse measurements. When a positive voltage is applied repeatedly to the Pt electrode, the accumulation capacitance increases gradually and sequentially. The depletion capacitance also increases consequently. The capacitances are restored by repeatedly applying a negative voltage, confirming the reversible memcapacitance. The analog and reversible memcapacitance emulates the potentiation and depression synaptic motions. The synaptic thin-film transistor (TFT) with this memcapacitor also shows the synaptic motion with gradually increasing drain current by repeatedly applying the positive gate and drain voltages and reversibly decreasing one by applying the negative voltages, representing synaptic weight modulation. The reversible and analog conductance change in the transistor at both the voltage sweep and pulse operations is obtained through the memcapacitance and threshold voltage shift at the same time. These results demonstrate the synaptic transistor operations with a MOS memcapacitor gate stack consisting of Pt/HfOx/n-IGZO.

Synaptic transistor with a reversible and analog conductance modulation using a Pt/HfOx/n-IGZO memcapacitor.

PubMed

Yang, Paul; Jun Kim, Hyung; Zheng, Hong; Won Beom, Geon; Park, Jong-Sung; Jung Kang, Chi; Yoon, Tae-Sik

2017-06-02

A synaptic transistor emulating the biological synaptic motion is demonstrated using the memcapacitance characteristics in a Pt/HfOx/n-indium-gallium-zinc-oxide (IGZO) memcapacitor. First, the metal-oxide-semiconductor (MOS) capacitor with Pt/HfOx/n-IGZO structure exhibits analog, polarity-dependent, and reversible memcapacitance in capacitance-voltage (C-V), capacitance-time (C-t), and voltage-pulse measurements. When a positive voltage is applied repeatedly to the Pt electrode, the accumulation capacitance increases gradually and sequentially. The depletion capacitance also increases consequently. The capacitances are restored by repeatedly applying a negative voltage, confirming the reversible memcapacitance. The analog and reversible memcapacitance emulates the potentiation and depression synaptic motions. The synaptic thin-film transistor (TFT) with this memcapacitor also shows the synaptic motion with gradually increasing drain current by repeatedly applying the positive gate and drain voltages and reversibly decreasing one by applying the negative voltages, representing synaptic weight modulation. The reversible and analog conductance change in the transistor at both the voltage sweep and pulse operations is obtained through the memcapacitance and threshold voltage shift at the same time. These results demonstrate the synaptic transistor operations with a MOS memcapacitor gate stack consisting of Pt/HfOx/n-IGZO.

Signaling in large-scale neural networks.

PubMed

Berg, Rune W; Hounsgaard, Jørn

2009-02-01

We examine the recent finding that neurons in spinal motor circuits enter a high conductance state during functional network activity. The underlying concomitant increase in random inhibitory and excitatory synaptic activity leads to stochastic signal processing. The possible advantages of this metabolically costly organization are analyzed by comparing with synaptically less intense networks driven by the intrinsic response properties of the network neurons.

Nonvolatile Array Of Synapses For Neural Network

NASA Technical Reports Server (NTRS)

Tawel, Raoul

1993-01-01

Elements of array programmed with help of ultraviolet light. A 32 x 32 very-large-scale integrated-circuit array of electronic synapses serves as building-block chip for analog neural-network computer. Synaptic weights stored in nonvolatile manner. Makes information content of array invulnerable to loss of power, and, by eliminating need for circuitry to refresh volatile synaptic memory, makes architecture simpler and more compact.

Hippocampal ripples down-regulate synapses.

PubMed

Norimoto, Hiroaki; Makino, Kenichi; Gao, Mengxuan; Shikano, Yu; Okamoto, Kazuki; Ishikawa, Tomoe; Sasaki, Takuya; Hioki, Hiroyuki; Fujisawa, Shigeyoshi; Ikegaya, Yuji

2018-03-30

The specific effects of sleep on synaptic plasticity remain unclear. We report that mouse hippocampal sharp-wave ripple oscillations serve as intrinsic events that trigger long-lasting synaptic depression. Silencing of sharp-wave ripples during slow-wave states prevented the spontaneous down-regulation of net synaptic weights and impaired the learning of new memories. The synaptic down-regulation was dependent on the N -methyl-d-aspartate receptor and selective for a specific input pathway. Thus, our findings are consistent with the role of slow-wave states in refining memory engrams by reducing recent memory-irrelevant neuronal activity and suggest a previously unrecognized function for sharp-wave ripples. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Neural coding using telegraphic switching of magnetic tunnel junction

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

Suh, Dong Ik; Bae, Gi Yoon; Oh, Heong Sik

2015-05-07

In this work, we present a synaptic transmission representing neural coding with spike trains by using a magnetic tunnel junction (MTJ). Telegraphic switching generates an artificial neural signal with both the applied magnetic field and the spin-transfer torque that act as conflicting inputs for modulating the number of spikes in spike trains. The spiking probability is observed to be weighted with modulation between 27.6% and 99.8% by varying the amplitude of the voltage input or the external magnetic field. With a combination of the reverse coding scheme and the synaptic characteristic of MTJ, an artificial function for the synaptic transmissionmore » is achieved.« less

Synaptic Impairment and Robustness of Excitatory Neuronal Networks with Different Topologies

PubMed Central

Mirzakhalili, Ehsan; Gourgou, Eleni; Booth, Victoria; Epureanu, Bogdan

2017-01-01

Synaptic deficiencies are a known hallmark of neurodegenerative diseases, but the diagnosis of impaired synapses on the cellular level is not an easy task. Nonetheless, changes in the system-level dynamics of neuronal networks with damaged synapses can be detected using techniques that do not require high spatial resolution. This paper investigates how the structure/topology of neuronal networks influences their dynamics when they suffer from synaptic loss. We study different neuronal network structures/topologies by specifying their degree distributions. The modes of the degree distribution can be used to construct networks that consist of rich clubs and resemble small world networks, as well. We define two dynamical metrics to compare the activity of networks with different structures: persistent activity (namely, the self-sustained activity of the network upon removal of the initial stimulus) and quality of activity (namely, percentage of neurons that participate in the persistent activity of the network). Our results show that synaptic loss affects the persistent activity of networks with bimodal degree distributions less than it affects random networks. The robustness of neuronal networks enhances when the distance between the modes of the degree distribution increases, suggesting that the rich clubs of networks with distinct modes keep the whole network active. In addition, a tradeoff is observed between the quality of activity and the persistent activity. For a range of distributions, both of these dynamical metrics are considerably high for networks with bimodal degree distribution compared to random networks. We also propose three different scenarios of synaptic impairment, which may correspond to different pathological or biological conditions. Regardless of the network structure/topology, results demonstrate that synaptic loss has more severe effects on the activity of the network when impairments are correlated with the activity of the neurons. PMID:28659765

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

PubMed

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

2014-05-09

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

Effect of CDP-choline on age-dependent modifications of energy- and glutamate-linked enzyme activities in synaptic and non-synaptic mitochondria from rat cerebral cortex.

PubMed

Villa, Roberto Federico; Ferrari, Federica; Gorini, Antonella

2012-12-01

The effect of aging and CDP-choline treatment (20 mg kg⁻¹ body weight i.p. for 28 days) on the maximal rates (V(max)) of representative mitochondrial enzyme activities related to Krebs' cycle (citrate synthase, α-ketoglutarate dehydrogenase, malate dehydrogenase), glutamate and related amino acid metabolism (glutamate dehydrogenase, glutamate-oxaloacetate- and glutamate-pyruvate transaminases) were evaluated in non-synaptic and intra-synaptic "light" and "heavy" mitochondria from frontal cerebral cortex of male Wistar rats aged 4, 12, 18 and 24 months. During aging, enzyme activities vary in a complex way respect to the type of mitochondria, i.e. non-synaptic and intra-synaptic. This micro-heterogeneity is an important factor, because energy-related mitochondrial enzyme catalytic properties cause metabolic modifications of physiopathological significance in cerebral tissue in vivo, also discriminating pre- and post-synaptic sites of action for drugs and affecting tissue responsiveness to noxious stimuli. Results show that CDP-choline in vivo treatment enhances cerebral energy metabolism selectively at 18 months, specifically modifying enzyme catalytic activities in non-synaptic and intra-synaptic "light" mitochondrial sub-populations. This confirms that the observed changes in enzyme catalytic activities during aging reflect the bioenergetic state at each single age and the corresponding energy requirements, further proving that in vivo drug treatment is able to interfere with the neuronal energy metabolism. Copyright © 2012. Published by Elsevier Ltd.

Excitement and synchronization of small-world neuronal networks with short-term synaptic plasticity.

PubMed

Han, Fang; Wiercigroch, Marian; Fang, Jian-An; Wang, Zhijie

2011-10-01

Excitement and synchronization of electrically and chemically coupled Newman-Watts (NW) small-world neuronal networks with a short-term synaptic plasticity described by a modified Oja learning rule are investigated. For each type of neuronal network, the variation properties of synaptic weights are examined first. Then the effects of the learning rate, the coupling strength and the shortcut-adding probability on excitement and synchronization of the neuronal network are studied. It is shown that the synaptic learning suppresses the over-excitement, helps synchronization for the electrically coupled network but impairs synchronization for the chemically coupled one. Both the introduction of shortcuts and the increase of the coupling strength improve synchronization and they are helpful in increasing the excitement for the chemically coupled network, but have little effect on the excitement of the electrically coupled one.

E-I balance emerges naturally from continuous Hebbian learning in autonomous neural networks.

PubMed

Trapp, Philip; Echeveste, Rodrigo; Gros, Claudius

2018-06-12

Spontaneous brain activity is characterized in part by a balanced asynchronous chaotic state. Cortical recordings show that excitatory (E) and inhibitory (I) drivings in the E-I balanced state are substantially larger than the overall input. We show that such a state arises naturally in fully adapting networks which are deterministic, autonomously active and not subject to stochastic external or internal drivings. Temporary imbalances between excitatory and inhibitory inputs lead to large but short-lived activity bursts that stabilize irregular dynamics. We simulate autonomous networks of rate-encoding neurons for which all synaptic weights are plastic and subject to a Hebbian plasticity rule, the flux rule, that can be derived from the stationarity principle of statistical learning. Moreover, the average firing rate is regulated individually via a standard homeostatic adaption of the bias of each neuron's input-output non-linear function. Additionally, networks with and without short-term plasticity are considered. E-I balance may arise only when the mean excitatory and inhibitory weights are themselves balanced, modulo the overall activity level. We show that synaptic weight balance, which has been considered hitherto as given, naturally arises in autonomous neural networks when the here considered self-limiting Hebbian synaptic plasticity rule is continuously active.

Differential Modifications of Synaptic Weights During Odor Rule Learning: Dynamics of Interaction Between the Piriform Cortex with Lower and Higher Brain Areas

PubMed Central

Cohen, Yaniv; Wilson, Donald A.; Barkai, Edi

2015-01-01

Learning of a complex olfactory discrimination (OD) task results in acquisition of rule learning after prolonged training. Previously, we demonstrated enhanced synaptic connectivity between the piriform cortex (PC) and its ascending and descending inputs from the olfactory bulb (OB) and orbitofrontal cortex (OFC) following OD rule learning. Here, using recordings of evoked field postsynaptic potentials in behaving animals, we examined the dynamics by which these synaptic pathways are modified during rule acquisition. We show profound differences in synaptic connectivity modulation between the 2 input sources. During rule acquisition, the ascending synaptic connectivity from the OB to the anterior and posterior PC is simultaneously enhanced. Furthermore, post-training stimulation of the OB enhanced learning rate dramatically. In sharp contrast, the synaptic input in the descending pathway from the OFC was significantly reduced until training completion. Once rule learning was established, the strength of synaptic connectivity in the 2 pathways resumed its pretraining values. We suggest that acquisition of olfactory rule learning requires a transient enhancement of ascending inputs to the PC, synchronized with a parallel decrease in the descending inputs. This combined short-lived modulation enables the PC network to reorganize in a manner that enables it to first acquire and then maintain the rule. PMID:23960200

Growth of neurites toward neurite- neurite contact sites increases synaptic clustering and secretion and is regulated by synaptic activity.

PubMed

Cove, Joshua; Blinder, Pablo; Abi-Jaoude, Elia; Lafrenière-Roula, Myriam; Devroye, Luc; Baranes, Danny

2006-01-01

The integrative properties of dendrites are determined by several factors, including their morphology and the spatio-temporal patterning of their synaptic inputs. One of the great challenges is to discover the interdependency of these two factors and the mechanisms which sculpt dendrites' fine morphological details. We found a novel form of neurite growth behavior in neuronal cultures of the hippocampus and cortex, when axons and dendrites grew directly toward neurite-neurite contact sites and crossed them, forming multi-neurite intersections (MNIs). MNIs were found at a frequency higher than obtained by computer simulations of randomly distributed dendrites, involved many of the dendrites and were stable for days. They were formed specifically by neurites originating from different neurons and were extremely rare among neurites of individual neurons or among astrocytic processes. Axonal terminals were clustered at MNIs and exhibited higher synaptophysin content and release capability than in those located elsewhere. MNI formation, as well as enhancement of axonal terminal clustering and secretion at MNIs, was disrupted by inhibitors of synaptic activity. Thus, convergence of axons and dendrites to form MNIs is a non-random activity-regulated wiring behavior which shapes dendritic trees and affects the location, clustering level and strength of their presynaptic inputs.

Analog hardware for learning neural networks

NASA Technical Reports Server (NTRS)

Eberhardt, Silvio P. (Inventor)

1991-01-01

This is a recurrent or feedforward analog neural network processor having a multi-level neuron array and a synaptic matrix for storing weighted analog values of synaptic connection strengths which is characterized by temporarily changing one connection strength at a time to determine its effect on system output relative to the desired target. That connection strength is then adjusted based on the effect, whereby the processor is taught the correct response to training examples connection by connection.

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

PubMed

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

2017-07-13

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

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

NASA Astrophysics Data System (ADS)

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

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

Cycles of insanity and creativity within contemplative neural systems.

PubMed

Thaler, Stephen L

2016-09-01

Random connection weight disturbances within an assembly of artificial neural networks (ANN) drive a progression of activation patterns that are tantamount to the memories and ideas nucleating within the brain's cortex. The numerical evaluation of these pattern-based notions by another, more placid system of ANNs governs the magnitude of weight disturbances administered to the former assembly, that perturbative intensity in turn controlling the novelty of the resulting ideational stream as well as the retention of newly formed concepts. In search of solution patterns to posed problems, such collaborating neural systems autonomously cycle between two extremes in mean synaptic perturbation level. The higher limit, characterized by chaos and inattentiveness to exogenous input patterns, is the regime in which ideas first form and incubate. The lower bound, marked by relative synaptic tranquility, is favorable to the reactivation and reinforcement of concepts first seeded during heightened perturbation. When considering this synthetic neural architecture as a cognitive model, the proposed source of such synaptic fluctuations is volume neurotransmitter release within cortex where both ideational and critic nets are commingled. As a result of their overlap, not only are the generative cortical networks suffused with neurotransmitters, but also those functioning in a critic role, leading to altered 'opinions' about the perturbation-driven stream of consciousness that then govern the injection of neurotransmitters into cortex. The likely effect of such chemical feedback is that the brain constantly cycles between states of idea generating chaos and perception stabilizing tranquility in much the same way that creative artificial neural systems do. Postulating that ideas are potentially useful or interesting false memories born within such turmoil, creativity appears to take place through a cyclic process consisting of alternating phases of (1) cognitive incapacitation, during which confabulatory notions incubate, and (2) synaptic calm when these incubated thoughts reemerge and reinforce themselves as they are then recognized for their value by a lucid perceptual apparatus. Extremes in such cycling, especially within the former dysfunctional phase, would be problematic from a mental health perspective. Whereas the literature is replete with findings linking creativity and various psychopathologies, the main hypothesis advanced herein is that the neurodynamics of both phenomena are the same. If vindicated, this theory may lead to advanced treatments that could potentially boost creativity as well as safeguard against the associated cognitive and psychological disorders, all through control of just one parameter, the difference between cortical concentrations of excitatory and inhibitory neurotransmitters. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

PubMed Central

Effenberger, Felix; Jost, Jürgen; Levina, Anna

2015-01-01

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

Attention Enhances Synaptic Efficacy and Signal-to-Noise in Neural Circuits

PubMed Central

Briggs, Farran; Mangun, George R.; Usrey, W. Martin

2013-01-01

Summary Attention is a critical component of perception. However, the mechanisms by which attention modulates neuronal communication to guide behavior are poorly understood. To elucidate the synaptic mechanisms of attention, we developed a sensitive assay of attentional modulation of neuronal communication. In alert monkeys performing a visual spatial attention task, we probed thalamocortical communication by electrically stimulating neurons in the lateral geniculate nucleus of the thalamus while simultaneously recording shock-evoked responses from monosynaptically connected neurons in primary visual cortex. We found that attention enhances neuronal communication by (1) increasing the efficacy of presynaptic input in driving postsynaptic responses, (2) increasing synchronous responses among ensembles of postsynaptic neurons receiving independent input, and (3) decreasing redundant signals between postsynaptic neurons receiving common input. These results demonstrate that attention finely tunes neuronal communication at the synaptic level by selectively altering synaptic weights, enabling enhanced detection of salient events in the noisy sensory milieu. PMID:23803766

Synaptic Mechanisms of Memory Consolidation during Sleep Slow Oscillations

PubMed Central

Wei, Yina; Krishnan, Giri P.

2016-01-01

Sleep is critical for regulation of synaptic efficacy, memories, and learning. However, the underlying mechanisms of how sleep rhythms contribute to consolidating memories acquired during wakefulness remain unclear. Here we studied the role of slow oscillations, 0.2–1 Hz rhythmic transitions between Up and Down states during stage 3/4 sleep, on dynamics of synaptic connectivity in the thalamocortical network model implementing spike-timing-dependent synaptic plasticity. We found that the spatiotemporal pattern of Up-state propagation determines the changes of synaptic strengths between neurons. Furthermore, an external input, mimicking hippocampal ripples, delivered to the cortical network results in input-specific changes of synaptic weights, which persisted after stimulation was removed. These synaptic changes promoted replay of specific firing sequences of the cortical neurons. Our study proposes a neuronal mechanism on how an interaction between hippocampal input, such as mediated by sharp wave-ripple events, cortical slow oscillations, and synaptic plasticity, may lead to consolidation of memories through preferential replay of cortical cell spike sequences during slow-wave sleep. SIGNIFICANCE STATEMENT Sleep is critical for memory and learning. Replay during sleep of temporally ordered spike sequences related to a recent experience was proposed to be a neuronal substrate of memory consolidation. However, specific mechanisms of replay or how spike sequence replay leads to synaptic changes that underlie memory consolidation are still poorly understood. Here we used a detailed computational model of the thalamocortical system to report that interaction between slow cortical oscillations and synaptic plasticity during deep sleep can underlie mapping hippocampal memory traces to persistent cortical representation. This study provided, for the first time, a mechanistic explanation of how slow-wave sleep may promote consolidation of recent memory events. PMID:27076422

Synaptic behaviors of a single metal-oxide-metal resistive device

NASA Astrophysics Data System (ADS)

Choi, Sang-Jun; Kim, Guk-Bae; Lee, Kyoobin; Kim, Ki-Hong; Yang, Woo-Young; Cho, Soohaeng; Bae, Hyung-Jin; Seo, Dong-Seok; Kim, Sang-Il; Lee, Kyung-Jin

2011-03-01

The mammalian brain is far superior to today's electronic circuits in intelligence and efficiency. Its functions are realized by the network of neurons connected via synapses. Much effort has been extended in finding satisfactory electronic neural networks that act like brains, i.e., especially the electronic version of synapse that is capable of the weight control and is independent of the external data storage. We demonstrate experimentally that a single metal-oxide-metal structure successfully stores the biological synaptic weight variations (synaptic plasticity) without any external storage node or circuit. Our device also demonstrates the reliability of plasticity experimentally with the model considering the time dependence of spikes. All these properties are embodied by the change of resistance level corresponding to the history of injected voltage-pulse signals. Moreover, we prove the capability of second-order learning of the multi-resistive device by applying it to the circuit composed of transistors. We anticipate our demonstration will invigorate the study of electronic neural networks using non-volatile multi-resistive device, which is simpler and superior compared to other storage devices.

The effect of soybean isoflavone on the dysregulation of NMDA receptor signaling pathway induced by β-amyloid peptides 1-42 in rats.

PubMed

Xi, Yuan-Di; Ding, Juan; Han, Jing; Zhang, Dan-Di; Liu, Jin-Meng; Feng, Ling-Li; Xiao, Rong

2015-05-01

Synaptic damage is the key factor of cognitive impairment. The purpose of this study was to understand the effect of soybean isoflavone (SIF) on synaptic damage induced by β-amyloid peptide 1-42 (Aβ1-42) in rats. Adult male Wistar rats were randomly divided into control, Aβ1-42, SIF, and SIF + Aβ1-42 (SIF pretreatment) groups according to body weight. SIF was treated orally by gavage in SIF and SIF + Aβ1-42 groups. After 14 days pretreatment with SIF or vehicle, Aβ1-42 was injected into the lateral cerebral ventricle of rats in Aβ1-42 and SIF + Aβ1-42 groups using miniosmotic pump. The level of Aβ1-42 and the expression of N-methyl-D-aspartic-acid receptor (NMDAR) were observed by immunohistochemistry. Reverse transcriptase polymerase chain reaction was used to detect the mRNA levels of NMDAR, calmodulin (CaM), calcium/CaM-dependent protein kinase II (CaMKII), cAMP-response element binding protein (CREB), and brain-derived neurotrophic factor (BDNF). The results showed that Aβ1-42 down-regulated mRNA and protein expression of the NR1 and NR2B subunits of NMDAR, SIF pretreatment could reverse these changes. The mRNA expression of CaM, CaMKII, CREB, and BDNF were down-regulated by Aβ1-42, but they were all regulated by SIF pretreatment. These results suggest that SIF pretreatment could antagonize the neuron damage in rats induced by Aβ1-42, and its mechanism might be associated with the NMDA receptor and CaM/CaMKII/CREB/BDNF signaling pathway, which are the synaptic plasticity-related molecules.

Synaptic and extrasynaptic traces of long-term memory: the ID molecule theory.

PubMed

Legéndy, Charles R

2016-08-01

It is generally assumed at the time of this writing that memories are stored in the form of synaptic weights. However, it is now also clear that the synapses are not permanent; in fact, synaptic patterns undergo significant change in a matter of hours. This means that to implement the long survival of distant memories (for several decades in humans), the brain must possess a molecular backup mechanism in some form, complete with provisions for the storage and retrieval of information. It is found below that the memory-supporting molecules need not contain a detailed description of mental entities, as had been envisioned in the 'memory molecule papers' from 50 years ago, they only need to contain unique identifiers of various entities, and that this can be achieved using relatively small molecules, using a random code ('ID molecules'). In this paper, the logistics of information flow are followed through the steps of storage and retrieval, and the conclusion reached is that the ID molecules, by carrying a sufficient amount of information (entropy), can effectively control the recreation of complex multineuronal patterns. In illustrations, it is described how ID molecules can be made to revive a selected cell assembly by waking up its synapses and how they cause a selected cell assembly to ignite by sending slow inward currents into its cells. The arrangement involves producing multiple copies of the ID molecules and distributing them at strategic locations at selected sets of synapses, then reaching them through small noncoding RNA molecules. This requires the quick creation of entropy-rich messengers and matching receptors, and it suggests that these are created from each other by small-scale transcription and reverse transcription.

Genetic attack on neural cryptography.

PubMed

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

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

Ruttor, Andreas; Kinzel, Wolfgang; Naeh, Rivka

2006-03-15

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 formore » 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.« less

Genetic attack on neural cryptography

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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.

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

PubMed Central

Panda, Priyadarshini; Roy, Kaushik

2017-01-01

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

Differential Acute and Chronic Effects of Leptin on Hypothalamic Astrocyte Morphology and Synaptic Protein Levels

PubMed Central

García-Cáceres, Cristina; Fuente-Martín, Esther; Burgos-Ramos, Emma; Granado, Miriam; Frago, Laura M.; Barrios, Vicente; Horvath, Tamas

2011-01-01

Astrocytes participate in neuroendocrine functions partially through modulation of synaptic input density in the hypothalamus. Indeed, glial ensheathing of neurons is modified by specific hormones, thus determining the availability of neuronal membrane space for synaptic inputs, with the loss of this plasticity possibly being involved in pathological processes. Leptin modulates synaptic inputs in the hypothalamus, but whether astrocytes participate in this action is unknown. Here we report that astrocyte structural proteins, such as glial fibrillary acidic protein (GFAP) and vimentin, are induced and astrocyte morphology modified by chronic leptin administration (intracerebroventricular, 2 wk), with these changes being inversely related to modifications in synaptic protein densities. Similar changes in glial structural proteins were observed in adult male rats that had increased body weight and circulating leptin levels due to neonatal overnutrition (overnutrition: four pups/litter vs. control: 12 pups/litter). However, acute leptin treatment reduced hypothalamic GFAP levels and induced synaptic protein levels 1 h after administration, with no effect on vimentin. In primary hypothalamic astrocyte cultures leptin also reduced GFAP levels at 1 h, with an induction at 24 h, indicating a possible direct effect of leptin. Hence, one mechanism by which leptin may affect metabolism is by modifying hypothalamic astrocyte morphology, which in turn could alter synaptic inputs to hypothalamic neurons. Furthermore, the responses to acute and chronic leptin exposure are inverse, raising the possibility that increased glial activation in response to chronic leptin exposure could be involved in central leptin resistance. PMID:21343257

Robust short-term memory without synaptic learning.

PubMed

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.

A Constructive Mean-Field Analysis of Multi-Population Neural Networks with Random Synaptic Weights and Stochastic Inputs

PubMed Central

Faugeras, Olivier; Touboul, Jonathan; Cessac, Bruno

2008-01-01

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. PMID:19255631

Presynaptic miniature GABAergic currents in developing interneurons.

PubMed

Trigo, Federico F; Bouhours, Brice; Rostaing, Philippe; Papageorgiou, George; Corrie, John E T; Triller, Antoine; Ogden, David; Marty, Alain

2010-04-29

Miniature synaptic currents have long been known to represent random transmitter release under resting conditions, but much remains to be learned about their nature and function in central synapses. In this work, we describe a new class of miniature currents ("preminis") that arise by the autocrine activation of axonal receptors following random vesicular release. Preminis are prominent in gabaergic synapses made by cerebellar interneurons during the development of the molecular layer. Unlike ordinary miniature postsynaptic currents in the same cells, premini frequencies are strongly enhanced by subthreshold depolarization, suggesting that the membrane depolarization they produce belongs to a feedback loop regulating neurotransmitter release. Thus, preminis could guide the formation of the interneuron network by enhancing neurotransmitter release at recently formed synaptic contacts. Copyright 2010 Elsevier Inc. All rights reserved.

Parasitoid wasp sting: a cocktail of GABA, taurine, and beta-alanine opens chloride channels for central synaptic block and transient paralysis of a cockroach host.

PubMed

Moore, Eugene L; Haspel, Gal; Libersat, Frederic; Adams, Michael E

2006-07-01

The wasp Ampulex compressa injects venom directly into the prothoracic ganglion of its cockroach host to induce a transient paralysis of the front legs. To identify the biochemical basis for this paralysis, we separated venom components according to molecular size and tested fractions for inhibition of synaptic transmission at the cockroach cercal-giant synapse. Only fractions in the low molecular weight range (<2 kDa) caused synaptic block. Dabsylation of venom components and analysis by HPLC and MALDI-TOF-MS revealed high levels of GABA (25 mM), and its receptor agonists beta-alanine (18 mM), and taurine (9 mM) in the active fractions. Each component produces transient block of synaptic transmission at the cercal-giant synapse and block of efferent motor output from the prothoracic ganglion, which mimics effects produced by injection of whole venom. Whole venom evokes picrotoxin-sensitive chloride currents in cockroach central neurons, consistent with a GABAergic action. Together these data demonstrate that Ampulex utilizes GABAergic chloride channel activation as a strategy for central synaptic block to induce transient and focal leg paralysis in its host. Copyright 2006 Wiley Periodicals, Inc.

The orientating reflex: the "targeting reaction" and "searchlight of attention".

PubMed

Sokolov, E N; Nezlina, N I; Polyanskii, V B; Evtikhin, D V

2002-01-01

A concept of the orientating reflex is presented, based on the principle of vector coding of cognitive and executive processes. The orientating reflex is a complex of orientating reactions of motor, autonomic, and subjective types, accentuating new and significant stimuli. Two main systems form the orientating reflex: the "targeting reaction" and the "searchlight of attention:" In the visual system, the targeting reaction ensures that the image of the object falls onto the fovea; this is mediated by involvement of premotor neurons which are excited by saccade command neurons in the superior colliculi. The "searchlight of attention" is activated as a result of resonance within the gamma frequency range, selectively enhancing cortical detectors and involving the reticular nucleus of the thalamus. Novelty signals arise in novelty neurons of the hippocampus. The synaptic weightings of neocortical detectors for hippocampal novelty neurons is initially characterized by high efficiency, which assigns a significant level of excitation of these neurons to the new stimulus. During repeated stimulation, the synaptic weightings of all the detectors representing a given stimulus decrease, with the result that the novelty signal becomes weaker. When the stimulus changes, it acts on other detectors, whose weightings for novelty neurons remain high, which strengthens the novelty signal. Decreases in the synaptic weightings on repetition of a standard stimulus form a trace of this stimulus in the novelty neurons - this is the "neural model of the stimulus." The novelty signal is determined by the non-concordance of the new stimulus with this "neural model," which is formed under the influence of the standard stimulus. The greater the difference between the new stimulus and the previously formed neural model, the stronger the novelty signal.

Large developing receptive fields using a distributed and locally reprogrammable address-event receiver.

PubMed

Bamford, Simeon A; Murray, Alan F; Willshaw, David J

2010-02-01

A distributed and locally reprogrammable address-event receiver has been designed, in which incoming address-events are monitored simultaneously by all synapses, allowing for arbitrarily large axonal fan-out without reducing channel capacity. Synapses can change the address of their presynaptic neuron, allowing the distributed implementation of a biologically realistic learning rule, with both synapse formation and elimination (synaptic rewiring). Probabilistic synapse formation leads to topographic map development, made possible by a cross-chip current-mode calculation of Euclidean distance. As well as synaptic plasticity in rewiring, synapses change weights using a competitive Hebbian learning rule (spike-timing-dependent plasticity). The weight plasticity allows receptive fields to be modified based on spatio-temporal correlations in the inputs, and the rewiring plasticity allows these modifications to become embedded in the network topology.

Charting epilepsy by searching for intelligence in network space with the help of evolving autonomous agents.

PubMed

Ohayon, Elan L; Kalitzin, Stiliyan; Suffczynski, Piotr; Jin, Frank Y; Tsang, Paul W; Borrett, Donald S; Burnham, W McIntyre; Kwan, Hon C

2004-01-01

The problem of demarcating neural network space is formidable. A simple fully connected recurrent network of five units (binary activations, synaptic weight resolution of 10) has 3.2 *10(26) possible initial states. The problem increases drastically with scaling. Here we consider three complementary approaches to help direct the exploration to distinguish epileptic from healthy networks. [1] First, we perform a gross mapping of the space of five-unit continuous recurrent networks using randomized weights and initial activations. The majority of weight patterns (>70%) were found to result in neural assemblies exhibiting periodic limit-cycle oscillatory behavior. [2] Next we examine the activation space of non-periodic networks demonstrating that the emergence of paroxysmal activity does not require changes in connectivity. [3] The next challenge is to focus the search of network space to identify networks with more complex dynamics. Here we rely on a major available indicator critical to clinical assessment but largely ignored by epilepsy modelers, namely: behavioral states. To this end, we connected the above network layout to an external robot in which interactive states were evolved. The first random generation showed a distribution in line with approach [1]. That is, the predominate phenotypes were fixed-point or oscillatory with seizure-like motor output. As evolution progressed the profile changed markedly. Within 20 generations the entire population was able to navigate a simple environment with all individuals exhibiting multiply-stable behaviors with no cases of default locked limit-cycle oscillatory motor behavior. The resultant population may thus afford us a view of the architectural principles demarcating healthy biological networks from the pathological. The approach has an advantage over other epilepsy modeling techniques in providing a way to clarify whether observed dynamics or suggested therapies are pointing to computational viability or dead space.

Poisson-Like Spiking in Circuits with Probabilistic Synapses

PubMed Central

Moreno-Bote, Rubén

2014-01-01

Neuronal activity in cortex is variable both spontaneously and during stimulation, and it has the remarkable property that it is Poisson-like over broad ranges of firing rates covering from virtually zero to hundreds of spikes per second. The mechanisms underlying cortical-like spiking variability over such a broad continuum of rates are currently unknown. We show that neuronal networks endowed with probabilistic synaptic transmission, a well-documented source of variability in cortex, robustly generate Poisson-like variability over several orders of magnitude in their firing rate without fine-tuning of the network parameters. Other sources of variability, such as random synaptic delays or spike generation jittering, do not lead to Poisson-like variability at high rates because they cannot be sufficiently amplified by recurrent neuronal networks. We also show that probabilistic synapses predict Fano factor constancy of synaptic conductances. Our results suggest that synaptic noise is a robust and sufficient mechanism for the type of variability found in cortex. PMID:25032705

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

NASA Astrophysics Data System (ADS)

Mikkelsen, Kaare; Imparato, Alberto; Torcini, Alessandro

2013-05-01

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

Hippocampal Spike-Timing Correlations Lead to Hexagonal Grid Fields

NASA Astrophysics Data System (ADS)

Monsalve-Mercado, Mauro M.; Leibold, Christian

2017-07-01

Space is represented in the mammalian brain by the activity of hippocampal place cells, as well as in their spike-timing correlations. Here, we propose a theory for how this temporal code is transformed to spatial firing rate patterns via spike-timing-dependent synaptic plasticity. The resulting dynamics of synaptic weights resembles well-known pattern formation models in which a lateral inhibition mechanism gives rise to a Turing instability. We identify parameter regimes in which hexagonal firing patterns develop as they have been found in medial entorhinal cortex.

Effects of Lipoic Acid on High-Fat Diet-Induced Alteration of Synaptic Plasticity and Brain Glucose Metabolism: A PET/CT and 13C-NMR Study.

PubMed

Liu, Zhigang; Patil, Ishan; Sancheti, Harsh; Yin, Fei; Cadenas, Enrique

2017-07-14

High-fat diet (HFD)-induced obesity is accompanied by insulin resistance and compromised brain synaptic plasticity through the impairment of insulin-sensitive pathways regulating neuronal survival, learning, and memory. Lipoic acid is known to modulate the redox status of the cell and has insulin mimetic effects. This study was aimed at determining the effects of dietary administration of lipoic acid on a HFD-induced obesity model in terms of (a) insulin signaling, (b) brain glucose uptake and neuronal- and astrocytic metabolism, and (c) synaptic plasticity. 3-Month old C57BL/6J mice were divided into 4 groups exposed to their respective treatments for 9 weeks: (1) normal diet, (2) normal diet plus lipoic acid, (3) HFD, and (4) HFD plus lipoic acid. HFD resulted in higher body weight, development of insulin resistance, lower brain glucose uptake and glucose transporters, alterations in glycolytic and acetate metabolism in neurons and astrocytes, and ultimately synaptic plasticity loss evident by a decreased long-term potentiation (LTP). Lipoic acid treatment in mice on HFD prevented several HFD-induced metabolic changes and preserved synaptic plasticity. The metabolic and physiological changes in HFD-fed mice, including insulin resistance, brain glucose uptake and metabolism, and synaptic function, could be preserved by the insulin-like effect of lipoic acid.

Glucose rapidly induces different forms of excitatory synaptic plasticity in hypothalamic POMC neurons.

PubMed

Hu, Jun; Jiang, Lin; Low, Malcolm J; Rui, Liangyou

2014-01-01

Hypothalamic POMC neurons are required for glucose and energy homeostasis. POMC neurons have a wide synaptic connection with neurons both within and outside the hypothalamus, and their activity is controlled by a balance between excitatory and inhibitory synaptic inputs. Brain glucose-sensing plays an essential role in the maintenance of normal body weight and metabolism; however, the effect of glucose on synaptic transmission in POMC neurons is largely unknown. Here we identified three types of POMC neurons (EPSC(+), EPSC(-), and EPSC(+/-)) based on their glucose-regulated spontaneous excitatory postsynaptic currents (sEPSCs), using whole-cell patch-clamp recordings. Lowering extracellular glucose decreased the frequency of sEPSCs in EPSC(+) neurons, but increased it in EPSC(-) neurons. Unlike EPSC(+) and EPSC(-) neurons, EPSC(+/-) neurons displayed a bi-phasic sEPSC response to glucoprivation. In the first phase of glucoprivation, both the frequency and the amplitude of sEPSCs decreased, whereas in the second phase, they increased progressively to the levels above the baseline values. Accordingly, lowering glucose exerted a bi-phasic effect on spontaneous action potentials in EPSC(+/-) neurons. Glucoprivation decreased firing rates in the first phase, but increased them in the second phase. These data indicate that glucose induces distinct excitatory synaptic plasticity in different subpopulations of POMC neurons. This synaptic remodeling is likely to regulate the sensitivity of the melanocortin system to neuronal and hormonal signals.

Space-Time Neural Networks

NASA Technical Reports Server (NTRS)

Villarreal, James A.; Shelton, Robert O.

1992-01-01

Concept of space-time neural network affords distributed temporal memory enabling such network to model complicated dynamical systems mathematically and to recognize temporally varying spatial patterns. Digital filters replace synaptic-connection weights of conventional back-error-propagation neural network.

Leptin regulation of hippocampal synaptic function in health and disease

PubMed Central

Irving, Andrew J.; Harvey, Jenni

2014-01-01

The endocrine hormone leptin plays a key role in regulating food intake and body weight via its actions in the hypothalamus. However, leptin receptors are highly expressed in many extra-hypothalamic brain regions and evidence is growing that leptin influences many central processes including cognition. Indeed, recent studies indicate that leptin is a potential cognitive enhancer as it markedly facilitates the cellular events underlying hippocampal-dependent learning and memory, including effects on glutamate receptor trafficking, neuronal morphology and activity-dependent synaptic plasticity. However, the ability of leptin to regulate hippocampal synaptic function markedly declines with age and aberrant leptin function has been linked to neurodegenerative disorders such as Alzheimer's disease (AD). Here, we review the evidence supporting a cognitive enhancing role for the hormone leptin and discuss the therapeutic potential of using leptin-based agents to treat AD. PMID:24298156

Cognition and Synaptic-Plasticity Related Changes in Aged Rats Supplemented with 8- and 10-Carbon Medium Chain Triglycerides.

PubMed

Wang, Dongmei; Mitchell, Ellen S

2016-01-01

Brain glucose hypometabolism is a common feature of Alzheimer's disease (AD). Previous studies have shown that cognition is improved by providing AD patients with an alternate energy source: ketones derived from either ketogenic diet or supplementation with medium chain triglycerides (MCT). Recently, data on the neuroprotective capacity of MCT-derived medium chain fatty acids (MCFA) suggest 8-carbon and 10-carbon MCFA may have cognition-enhancing properties which are not related to ketone production. We investigated the effect of 8 week treatment with MCT8, MCT10 or sunflower oil supplementation (5% by weight of chow diet) in 21 month old Wistar rats. Both MCT diets increased ketones plasma similarly compared to control diet, but MCT diets did not increase ketones in the brain. Treatment with MCT10, but not MCT8, significantly improved novel object recognition memory compared to control diet, while social recognition increased in both MCT groups. MCT8 and MCT10 diets decreased weight compared to control diet, where MCFA plasma levels were higher in MCT10 groups than in MCT8 groups. Both MCT diets increased IRS-1 (612) phosphorylation and decreased S6K phosphorylation (240/244) but only MCT10 increased Akt phosphorylation (473). MCT8 supplementation increased synaptophysin, but not PSD-95, in contrast MCT10 had no effect on either synaptic marker. Expression of Ube3a, which controls synaptic stability, was increased by both MCT diets. Cortex transcription via qPCR showed that immediate early genes related to synaptic plasticity (arc, plk3, junb, egr2, nr4a1) were downregulated by both MCT diets while MCT8 additionally down-regulated fosb and egr1 but upregulated grin1 and gba2. These results demonstrate that treatment of 8- and 10-carbon length MCTs in aged rats have slight differential effects on synaptic stability, protein synthesis and behavior that may be independent of brain ketone levels.

Cognition and Synaptic-Plasticity Related Changes in Aged Rats Supplemented with 8- and 10-Carbon Medium Chain Triglycerides

PubMed Central

Wang, Dongmei; Mitchell, Ellen S.

2016-01-01

Brain glucose hypometabolism is a common feature of Alzheimer’s disease (AD). Previous studies have shown that cognition is improved by providing AD patients with an alternate energy source: ketones derived from either ketogenic diet or supplementation with medium chain triglycerides (MCT). Recently, data on the neuroprotective capacity of MCT-derived medium chain fatty acids (MCFA) suggest 8-carbon and 10-carbon MCFA may have cognition-enhancing properties which are not related to ketone production. We investigated the effect of 8 week treatment with MCT8, MCT10 or sunflower oil supplementation (5% by weight of chow diet) in 21 month old Wistar rats. Both MCT diets increased ketones plasma similarly compared to control diet, but MCT diets did not increase ketones in the brain. Treatment with MCT10, but not MCT8, significantly improved novel object recognition memory compared to control diet, while social recognition increased in both MCT groups. MCT8 and MCT10 diets decreased weight compared to control diet, where MCFA plasma levels were higher in MCT10 groups than in MCT8 groups. Both MCT diets increased IRS-1 (612) phosphorylation and decreased S6K phosphorylation (240/244) but only MCT10 increased Akt phosphorylation (473). MCT8 supplementation increased synaptophysin, but not PSD-95, in contrast MCT10 had no effect on either synaptic marker. Expression of Ube3a, which controls synaptic stability, was increased by both MCT diets. Cortex transcription via qPCR showed that immediate early genes related to synaptic plasticity (arc, plk3, junb, egr2, nr4a1) were downregulated by both MCT diets while MCT8 additionally down-regulated fosb and egr1 but upregulated grin1 and gba2. These results demonstrate that treatment of 8- and 10-carbon length MCTs in aged rats have slight differential effects on synaptic stability, protein synthesis and behavior that may be independent of brain ketone levels. PMID:27517611

Short-term memory of TiO2-based electrochemical capacitors: empirical analysis with adoption of a sliding threshold

NASA Astrophysics Data System (ADS)

Lim, Hyungkwang; Kim, Inho; Kim, Jin-Sang; Hwang, Cheol Seong; Jeong, Doo Seok

2013-09-01

Chemical synapses are important components of the large-scaled neural network in the hippocampus of the mammalian brain, and a change in their weight is thought to be in charge of learning and memory. Thus, the realization of artificial chemical synapses is of crucial importance in achieving artificial neural networks emulating the brain’s functionalities to some extent. This kind of research is often referred to as neuromorphic engineering. In this study, we report short-term memory behaviours of electrochemical capacitors (ECs) utilizing TiO2 mixed ionic-electronic conductor and various reactive electrode materials e.g. Ti, Ni, and Cr. By experiments, it turned out that the potentiation behaviours did not represent unlimited growth of synaptic weight. Instead, the behaviours exhibited limited synaptic weight growth that can be understood by means of an empirical equation similar to the Bienenstock-Cooper-Munro rule, employing a sliding threshold. The observed potentiation behaviours were analysed using the empirical equation and the differences between the different ECs were parameterized.

Neuronal uptake and propagation of a rare phosphorylated high-molecular-weight tau derived from Alzheimer's disease brain

PubMed Central

Takeda, Shuko; Wegmann, Susanne; Cho, Hansang; DeVos, Sarah L.; Commins, Caitlin; Roe, Allyson D.; Nicholls, Samantha B.; Carlson, George A.; Pitstick, Rose; Nobuhara, Chloe K.; Costantino, Isabel; Frosch, Matthew P.; Müller, Daniel J.; Irimia, Daniel; Hyman, Bradley T.

2015-01-01

Tau pathology is known to spread in a hierarchical pattern in Alzheimer's disease (AD) brain during disease progression, likely by trans-synaptic tau transfer between neurons. However, the tau species involved in inter-neuron propagation remains unclear. To identify tau species responsible for propagation, we examined uptake and propagation properties of different tau species derived from postmortem cortical extracts and brain interstitial fluid of tau-transgenic mice, as well as human AD cortices. Here we show that PBS-soluble phosphorylated high-molecular-weight (HMW) tau, though very low in abundance, is taken up, axonally transported, and passed on to synaptically connected neurons. Our findings suggest that a rare species of soluble phosphorylated HMW tau is the endogenous form of tau involved in propagation and could be a target for therapeutic intervention and biomarker development. PMID:26458742

Thalamic reticular cells firing modes and its dependency on the frequency and amplitude ranges of the current stimulus.

PubMed

Hernandez, Oscar; Hernandez, Lilibeth; Vera, David; Santander, Alcides; Zurek, Eduardo

2015-01-01

The neurons of the Thalamic Reticular Nucleus (TRNn) respond to inputs in two activity modes called burst and tonic firing and both can be observed in different physiological states. The functional states of the thalamus depend in part on the properties of synaptic transmission between the TRNn and the thalamocortical and corticothalamic neurons. A dendrite can receive inhibitory and excitatory postsynaptic potentials. The novelties presented in this paper can be summarized as follows: First, it shows, through a computational simulation, that the burst and tonic firings observed in the TRNn soma could be explained as a product of random synaptic inputs on the distal dendrites, the tonic firings are generated by random excitatory stimuli, and the burst firings are generated by two different types of stimuli: inhibitory random stimuli, and a combination of inhibitory (from TRNn) and excitatory (from corticothalamic and thalamocortical neurons) random stimuli; second, according to in vivo recordings, we have found that the burst observed in the TRNn soma has graduate properties that are proportional to the stimuli frequency; and third, a novel method for showing in a quantitative manner the accelerando-decelerando pattern is proposed.

Mean Field Analysis of Stochastic Neural Network Models with Synaptic Depression

NASA Astrophysics Data System (ADS)

Yasuhiko Igarashi,; Masafumi Oizumi,; Masato Okada,

2010-08-01

We investigated the effects of synaptic depression on the macroscopic behavior of stochastic neural networks. Dynamical mean field equations were derived for such networks by taking the average of two stochastic variables: a firing-state variable and a synaptic variable. In these equations, the average product of thesevariables is decoupled as the product of their averages because the two stochastic variables are independent. We proved the independence of these two stochastic variables assuming that the synaptic weight Jij is of the order of 1/N with respect to the number of neurons N. Using these equations, we derived macroscopic steady-state equations for a network with uniform connections and for a ring attractor network with Mexican hat type connectivity and investigated the stability of the steady-state solutions. An oscillatory uniform state was observed in the network with uniform connections owing to a Hopf instability. For the ring network, high-frequency perturbations were shown not to affect system stability. Two mechanisms destabilize the inhomogeneous steady state, leading to two oscillatory states. A Turing instability leads to a rotating bump state, while a Hopf instability leads to an oscillatory bump state, which was previously unreported. Various oscillatory states take place in a network with synaptic depression depending on the strength of the interneuron connections.

Synapsin I is associated with cholinergic nerve terminals in the electric organs of Torpedo, Electrophorus, and Malapterurus and copurifies with Torpedo synaptic vesicles.

PubMed

Volknandt, W; Naito, S; Ueda, T; Zimmermann, H

1987-08-01

Using an affinity-purified monospecific polyclonal antibody against bovine brain synapsin I, the distribution of antigenically related proteins was investigated in the electric organs of the three strongly electric fish Torpedo marmorata, Electrophorus electricus, Malapterurus electricus and in the rat diaphragm. On application of indirect fluorescein isothiocyanate-immunofluorescence and using alpha-bungarotoxin for identification of synaptic sites, intense and very selective staining of nerve terminals was found in all of these tissues. Immunotransfer blots of tissue homogenates revealed specific bands whose molecular weights are similar to those of synapsin Ia and synapsin Ib. Moreover, synapsin I-like proteins are still attached to the synaptic vesicles that were isolated in isotonic glycine solution from Torpedo electric organ by density gradient centrifugation and chromatography on Sephacryl-1000. Our results suggest that synapsin I-like proteins are also associated with cholinergic synaptic vesicles of electric organs and that the electric organ may be an ideal source for studying further the functional and molecular properties of synapsin.

Memristor-based cellular nonlinear/neural network: design, analysis, and applications.

PubMed

Duan, Shukai; Hu, Xiaofang; Dong, Zhekang; Wang, Lidan; Mazumder, Pinaki

2015-06-01

Cellular nonlinear/neural network (CNN) has been recognized as a powerful massively parallel architecture capable of solving complex engineering problems by performing trillions of analog operations per second. The memristor was theoretically predicted in the late seventies, but it garnered nascent research interest due to the recent much-acclaimed discovery of nanocrossbar memories by engineers at the Hewlett-Packard Laboratory. The memristor is expected to be co-integrated with nanoscale CMOS technology to revolutionize conventional von Neumann as well as neuromorphic computing. In this paper, a compact CNN model based on memristors is presented along with its performance analysis and applications. In the new CNN design, the memristor bridge circuit acts as the synaptic circuit element and substitutes the complex multiplication circuit used in traditional CNN architectures. In addition, the negative differential resistance and nonlinear current-voltage characteristics of the memristor have been leveraged to replace the linear resistor in conventional CNNs. The proposed CNN design has several merits, for example, high density, nonvolatility, and programmability of synaptic weights. The proposed memristor-based CNN design operations for implementing several image processing functions are illustrated through simulation and contrasted with conventional CNNs. Monte-Carlo simulation has been used to demonstrate the behavior of the proposed CNN due to the variations in memristor synaptic weights.

Ultralow power artificial synapses using nanotextured magnetic Josephson junctions.

PubMed

Schneider, Michael L; Donnelly, Christine A; Russek, Stephen E; Baek, Burm; Pufall, Matthew R; Hopkins, Peter F; Dresselhaus, Paul D; Benz, Samuel P; Rippard, William H

2018-01-01

Neuromorphic computing promises to markedly improve the efficiency of certain computational tasks, such as perception and decision-making. Although software and specialized hardware implementations of neural networks have made tremendous accomplishments, both implementations are still many orders of magnitude less energy efficient than the human brain. We demonstrate a new form of artificial synapse based on dynamically reconfigurable superconducting Josephson junctions with magnetic nanoclusters in the barrier. The spiking energy per pulse varies with the magnetic configuration, but in our demonstration devices, the spiking energy is always less than 1 aJ. This compares very favorably with the roughly 10 fJ per synaptic event in the human brain. Each artificial synapse is composed of a Si barrier containing Mn nanoclusters with superconducting Nb electrodes. The critical current of each synapse junction, which is analogous to the synaptic weight, can be tuned using input voltage spikes that change the spin alignment of Mn nanoclusters. We demonstrate synaptic weight training with electrical pulses as small as 3 aJ. Further, the Josephson plasma frequencies of the devices, which determine the dynamical time scales, all exceed 100 GHz. These new artificial synapses provide a significant step toward a neuromorphic platform that is faster, more energy-efficient, and thus can attain far greater complexity than has been demonstrated with other technologies.

Ultralow power artificial synapses using nanotextured magnetic Josephson junctions

PubMed Central

Schneider, Michael L.; Donnelly, Christine A.; Russek, Stephen E.; Baek, Burm; Pufall, Matthew R.; Hopkins, Peter F.; Dresselhaus, Paul D.; Benz, Samuel P.; Rippard, William H.

2018-01-01

Neuromorphic computing promises to markedly improve the efficiency of certain computational tasks, such as perception and decision-making. Although software and specialized hardware implementations of neural networks have made tremendous accomplishments, both implementations are still many orders of magnitude less energy efficient than the human brain. We demonstrate a new form of artificial synapse based on dynamically reconfigurable superconducting Josephson junctions with magnetic nanoclusters in the barrier. The spiking energy per pulse varies with the magnetic configuration, but in our demonstration devices, the spiking energy is always less than 1 aJ. This compares very favorably with the roughly 10 fJ per synaptic event in the human brain. Each artificial synapse is composed of a Si barrier containing Mn nanoclusters with superconducting Nb electrodes. The critical current of each synapse junction, which is analogous to the synaptic weight, can be tuned using input voltage spikes that change the spin alignment of Mn nanoclusters. We demonstrate synaptic weight training with electrical pulses as small as 3 aJ. Further, the Josephson plasma frequencies of the devices, which determine the dynamical time scales, all exceed 100 GHz. These new artificial synapses provide a significant step toward a neuromorphic platform that is faster, more energy-efficient, and thus can attain far greater complexity than has been demonstrated with other technologies. PMID:29387787

Glucose Rapidly Induces Different Forms of Excitatory Synaptic Plasticity in Hypothalamic POMC Neurons

PubMed Central

Hu, Jun; Jiang, Lin; Low, Malcolm J.; Rui, Liangyou

2014-01-01

Hypothalamic POMC neurons are required for glucose and energy homeostasis. POMC neurons have a wide synaptic connection with neurons both within and outside the hypothalamus, and their activity is controlled by a balance between excitatory and inhibitory synaptic inputs. Brain glucose-sensing plays an essential role in the maintenance of normal body weight and metabolism; however, the effect of glucose on synaptic transmission in POMC neurons is largely unknown. Here we identified three types of POMC neurons (EPSC(+), EPSC(−), and EPSC(+/−)) based on their glucose-regulated spontaneous excitatory postsynaptic currents (sEPSCs), using whole-cell patch-clamp recordings. Lowering extracellular glucose decreased the frequency of sEPSCs in EPSC(+) neurons, but increased it in EPSC(−) neurons. Unlike EPSC(+) and EPSC(−) neurons, EPSC(+/−) neurons displayed a bi-phasic sEPSC response to glucoprivation. In the first phase of glucoprivation, both the frequency and the amplitude of sEPSCs decreased, whereas in the second phase, they increased progressively to the levels above the baseline values. Accordingly, lowering glucose exerted a bi-phasic effect on spontaneous action potentials in EPSC(+/−) neurons. Glucoprivation decreased firing rates in the first phase, but increased them in the second phase. These data indicate that glucose induces distinct excitatory synaptic plasticity in different subpopulations of POMC neurons. This synaptic remodeling is likely to regulate the sensitivity of the melanocortin system to neuronal and hormonal signals. PMID:25127258

Survival motor neuron protein in motor neurons determines synaptic integrity in spinal muscular atrophy.

PubMed

Martinez, Tara L; Kong, Lingling; Wang, Xueyong; Osborne, Melissa A; Crowder, Melissa E; Van Meerbeke, James P; Xu, Xixi; Davis, Crystal; Wooley, Joe; Goldhamer, David J; Lutz, Cathleen M; Rich, Mark M; Sumner, Charlotte J

2012-06-20

The inherited motor neuron disease spinal muscular atrophy (SMA) is caused by deficient expression of survival motor neuron (SMN) protein and results in severe muscle weakness. In SMA mice, synaptic dysfunction of both neuromuscular junctions (NMJs) and central sensorimotor synapses precedes motor neuron cell death. To address whether this synaptic dysfunction is due to SMN deficiency in motor neurons, muscle, or both, we generated three lines of conditional SMA mice with tissue-specific increases in SMN expression. All three lines of mice showed increased survival, weights, and improved motor behavior. While increased SMN expression in motor neurons prevented synaptic dysfunction at the NMJ and restored motor neuron somal synapses, increased SMN expression in muscle did not affect synaptic function although it did improve myofiber size. Together these data indicate that both peripheral and central synaptic integrity are dependent on motor neurons in SMA, but SMN may have variable roles in the maintenance of these different synapses. At the NMJ, it functions at the presynaptic terminal in a cell-autonomous fashion, but may be necessary for retrograde trophic signaling to presynaptic inputs onto motor neurons. Importantly, SMN also appears to function in muscle growth and/or maintenance independent of motor neurons. Our data suggest that SMN plays distinct roles in muscle, NMJs, and motor neuron somal synapses and that restored function of SMN at all three sites will be necessary for full recovery of muscle power.

Three-dimensional distribution of cortical synapses: a replicated point pattern-based analysis

PubMed Central

Anton-Sanchez, Laura; Bielza, Concha; Merchán-Pérez, Angel; Rodríguez, José-Rodrigo; DeFelipe, Javier; Larrañaga, Pedro

2014-01-01

The biggest problem when analyzing the brain is that its synaptic connections are extremely complex. Generally, the billions of neurons making up the brain exchange information through two types of highly specialized structures: chemical synapses (the vast majority) and so-called gap junctions (a substrate of one class of electrical synapse). Here we are interested in exploring the three-dimensional spatial distribution of chemical synapses in the cerebral cortex. Recent research has showed that the three-dimensional spatial distribution of synapses in layer III of the neocortex can be modeled by a random sequential adsorption (RSA) point process, i.e., synapses are distributed in space almost randomly, with the only constraint that they cannot overlap. In this study we hypothesize that RSA processes can also explain the distribution of synapses in all cortical layers. We also investigate whether there are differences in both the synaptic density and spatial distribution of synapses between layers. Using combined focused ion beam milling and scanning electron microscopy (FIB/SEM), we obtained three-dimensional samples from the six layers of the rat somatosensory cortex and identified and reconstructed the synaptic junctions. A total volume of tissue of approximately 4500μm3 and around 4000 synapses from three different animals were analyzed. Different samples, layers and/or animals were aggregated and compared using RSA replicated spatial point processes. The results showed no significant differences in the synaptic distribution across the different rats used in the study. We found that RSA processes described the spatial distribution of synapses in all samples of each layer. We also found that the synaptic distribution in layers II to VI conforms to a common underlying RSA process with different densities per layer. Interestingly, the results showed that synapses in layer I had a slightly different spatial distribution from the other layers. PMID:25206325

Three-dimensional distribution of cortical synapses: a replicated point pattern-based analysis.

PubMed

Anton-Sanchez, Laura; Bielza, Concha; Merchán-Pérez, Angel; Rodríguez, José-Rodrigo; DeFelipe, Javier; Larrañaga, Pedro

2014-01-01

The biggest problem when analyzing the brain is that its synaptic connections are extremely complex. Generally, the billions of neurons making up the brain exchange information through two types of highly specialized structures: chemical synapses (the vast majority) and so-called gap junctions (a substrate of one class of electrical synapse). Here we are interested in exploring the three-dimensional spatial distribution of chemical synapses in the cerebral cortex. Recent research has showed that the three-dimensional spatial distribution of synapses in layer III of the neocortex can be modeled by a random sequential adsorption (RSA) point process, i.e., synapses are distributed in space almost randomly, with the only constraint that they cannot overlap. In this study we hypothesize that RSA processes can also explain the distribution of synapses in all cortical layers. We also investigate whether there are differences in both the synaptic density and spatial distribution of synapses between layers. Using combined focused ion beam milling and scanning electron microscopy (FIB/SEM), we obtained three-dimensional samples from the six layers of the rat somatosensory cortex and identified and reconstructed the synaptic junctions. A total volume of tissue of approximately 4500μm(3) and around 4000 synapses from three different animals were analyzed. Different samples, layers and/or animals were aggregated and compared using RSA replicated spatial point processes. The results showed no significant differences in the synaptic distribution across the different rats used in the study. We found that RSA processes described the spatial distribution of synapses in all samples of each layer. We also found that the synaptic distribution in layers II to VI conforms to a common underlying RSA process with different densities per layer. Interestingly, the results showed that synapses in layer I had a slightly different spatial distribution from the other layers.

Simple modification of Oja rule limits L1-norm of weight vector and leads to sparse connectivity.

PubMed

Aparin, Vladimir

2012-03-01

This letter describes a simple modification of the Oja learning rule, which asymptotically constrains the L1-norm of an input weight vector instead of the L2-norm as in the original rule. This constraining is local as opposed to commonly used instant normalizations, which require the knowledge of all input weights of a neuron to update each one of them individually. The proposed rule converges to a weight vector that is sparser (has more zero weights) than the vector learned by the original Oja rule with or without the zero bound, which could explain the developmental synaptic pruning.

On Using the Volatile Mem-Capacitive Effect of TiO2 Resistive Random Access Memory to Mimic the Synaptic Forgetting Process

NASA Astrophysics Data System (ADS)

Sarkar, Biplab; Mills, Steven; Lee, Bongmook; Pitts, W. Shepherd; Misra, Veena; Franzon, Paul D.

2018-02-01

In this work, we report on mimicking the synaptic forgetting process using the volatile mem-capacitive effect of a resistive random access memory (RRAM). TiO2 dielectric, which is known to show volatile memory operations due to migration of inherent oxygen vacancies, was used to achieve the volatile mem-capacitive effect. By placing the volatile RRAM candidate along with SiO2 at the gate of a MOS capacitor, a volatile capacitance change resembling the forgetting nature of a human brain is demonstrated. Furthermore, the memory operation in the MOS capacitor does not require a current flow through the gate dielectric indicating the feasibility of obtaining low power memory operations. Thus, the mem-capacitive effect of volatile RRAM candidates can be attractive to the future neuromorphic systems for implementing the forgetting process of a human brain.

Neural Synchronization and Cryptography

NASA Astrophysics Data System (ADS)

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.

Ultrafast Synaptic Events in a Chalcogenide Memristor

NASA Astrophysics Data System (ADS)

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

2013-04-01

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

Ultrafast synaptic events in a chalcogenide memristor.

PubMed

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

2013-01-01

Compact and power-efficient plastic electronic synapses are of fundamental importance to overcoming the bottlenecks of developing a neuromorphic chip. Memristor is a strong contender among the various electronic synapses in existence today. However, the speeds of synaptic events are relatively slow in most attempts at emulating synapses due to the material-related mechanism. Here we revealed the intrinsic memristance of stoichiometric crystalline Ge2Sb2Te5 that originates from the charge trapping and releasing by the defects. The device resistance states, representing synaptic weights, were precisely modulated by 30 ns potentiating/depressing electrical pulses. We demonstrated four spike-timing-dependent plasticity (STDP) forms by applying programmed pre- and postsynaptic spiking pulse pairs in different time windows ranging from 50 ms down to 500 ns, the latter of which is 10(5) times faster than the speed of STDP in human brain. This study provides new opportunities for building ultrafast neuromorphic computing systems and surpassing Von Neumann architecture.

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

NASA Astrophysics Data System (ADS)

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.

Differences in spike train variability in rat vasopressin and oxytocin neurons and their relationship to synaptic activity

PubMed Central

Li, Chunyan; Tripathi, Pradeep K; Armstrong, William E

2007-01-01

The firing pattern of magnocellular neurosecretory neurons is intimately related to hormone release, but the relative contribution of synaptic versus intrinsic factors to the temporal dispersion of spikes is unknown. In the present study, we examined the firing patterns of vasopressin (VP) and oxytocin (OT) supraoptic neurons in coronal slices from virgin female rats, with and without blockade of inhibitory and excitatory synaptic currents. Inhibitory postsynaptic currents (IPSCs) were twice as prevalent as their excitatory counterparts (EPSCs), and both were more prevalent in OT compared with VP neurons. Oxytocin neurons fired more slowly and irregularly than VP neurons near threshold. Blockade of Cl− currents (including tonic and synaptic currents) with picrotoxin reduced interspike interval (ISI) variability of continuously firing OT and VP neurons without altering input resistance or firing rate. Blockade of EPSCs did not affect firing pattern. Phasic bursting neurons (putative VP neurons) were inconsistently affected by broad synaptic blockade, suggesting that intrinsic factors may dominate the ISI distribution during this mode in the slice. Specific blockade of synaptic IPSCs with gabazine also reduced ISI variability, but only in OT neurons. In all cases, the effect of inhibitory blockade on firing pattern was independent of any consistent change in input resistance or firing rate. Since the great majority of IPSCs are randomly distributed, miniature events (mIPSCs) in the coronal slice, these findings imply that even mIPSCs can impart irregularity to the firing pattern of OT neurons in particular, and could be important in regulating spike patterning in vivo. For example, the increased firing variability that precedes bursting in OT neurons during lactation could be related to significant changes in synaptic activity. PMID:17332000

Inter-synaptic learning of combination rules in a cortical network model

PubMed Central

Lavigne, Frédéric; Avnaïm, Francis; Dumercy, Laurent

2014-01-01

Selecting responses in working memory while processing combinations of stimuli depends strongly on their relations stored in long-term memory. However, the learning of XOR-like combinations of stimuli and responses according to complex rules raises the issue of the non-linear separability of the responses within the space of stimuli. One proposed solution is to add neurons that perform a stage of non-linear processing between the stimuli and responses, at the cost of increasing the network size. Based on the non-linear integration of synaptic inputs within dendritic compartments, we propose here an inter-synaptic (IS) learning algorithm that determines the probability of potentiating/depressing each synapse as a function of the co-activity of the other synapses within the same dendrite. The IS learning is effective with random connectivity and without either a priori wiring or additional neurons. Our results show that IS learning generates efficacy values that are sufficient for the processing of XOR-like combinations, on the basis of the sole correlational structure of the stimuli and responses. We analyze the types of dendrites involved in terms of the number of synapses from pre-synaptic neurons coding for the stimuli and responses. The synaptic efficacy values obtained show that different dendrites specialize in the detection of different combinations of stimuli. The resulting behavior of the cortical network model is analyzed as a function of inter-synaptic vs. Hebbian learning. Combinatorial priming effects show that the retrospective activity of neurons coding for the stimuli trigger XOR-like combination-selective prospective activity of neurons coding for the expected response. The synergistic effects of inter-synaptic learning and of mixed-coding neurons are simulated. The results show that, although each mechanism is sufficient by itself, their combined effects improve the performance of the network. PMID:25221529

A VLSI recurrent network of integrate-and-fire neurons connected by plastic synapses with long-term memory.

PubMed

Chicca, E; Badoni, D; Dante, V; D'Andreagiovanni, M; Salina, G; Carota, L; Fusi, S; Del Giudice, P

2003-01-01

Electronic neuromorphic devices with on-chip, on-line learning should be able to modify quickly the synaptic couplings to acquire information about new patterns to be stored (synaptic plasticity) and, at the same time, preserve this information on very long time scales (synaptic stability). Here, we illustrate the electronic implementation of a simple solution to this stability-plasticity problem, recently proposed and studied in various contexts. It is based on the observation that reducing the analog depth of the synapses to the extreme (bistable synapses) does not necessarily disrupt the performance of the device as an associative memory, provided that 1) the number of neurons is large enough; 2) the transitions between stable synaptic states are stochastic; and 3) learning is slow. The drastic reduction of the analog depth of the synaptic variable also makes this solution appealing from the point of view of electronic implementation and offers a simple methodological alternative to the technological solution based on floating gates. We describe the full custom analog very large-scale integration (VLSI) realization of a small network of integrate-and-fire neurons connected by bistable deterministic plastic synapses which can implement the idea of stochastic learning. In the absence of stimuli, the memory is preserved indefinitely. During the stimulation the synapse undergoes quick temporary changes through the activities of the pre- and postsynaptic neurons; those changes stochastically result in a long-term modification of the synaptic efficacy. The intentionally disordered pattern of connectivity allows the system to generate a randomness suited to drive the stochastic selection mechanism. We check by a suitable stimulation protocol that the stochastic synaptic plasticity produces the expected pattern of potentiation and depression in the electronic network.

Investigation of the ferroelectric switching behavior of P(VDF-TrFE)-PMMA blended films for synaptic device applications

NASA Astrophysics Data System (ADS)

Kim, E. J.; Kim, K. A.; Yoon, S. M.

2016-02-01

Synaptic plasticity can be mimicked by electronic synaptic devices. By using ferroelectric thin films as gate insulator for thin-film transistors (TFT), channel conductance can be defined as the synaptic plasticity, and gradually modulated by the variations in amounts of aligned ferroelectric dipoles. Poly(vinylidene fluoride-trifluoroethylene) [P(VDF-TrFE)]-poly(methyl methacrylate) (PMMA) blended films are chosen and their switching kinetics are investigated by using the Kolmogorov-Avrami-Ishibashi model. The switching time for ferroelectric polarization is sensitively influenced by the amplitude of applied electric field and volumetric ratio of ferroelectric beta-phases in the P(VDF-TrFE)-PMMA films. The switching time of the P(VDF-TrFE) increases with decreasing the pulse amplitude and/or the ratio of ferroelectric beta-phases by incorporation of PMMA. The activation electric field is also found to increase as the increase in blended amount of PMMA. Synapse TFTs are fabricated using the P(VDF-TrFE)-PMMA as gate insulator and In-Ga-Zn-O active channels. The drain currents of the synapse TFTs gradually increased when the voltage pulse signals with given duration are repeatedly applied. This suggests that the synaptic weights can be modulated by the number of external pulse signals, and that the proposed synapse TFT can be applied for mimicking the operations of bio-synapses.

Neurobiologically realistic determinants of self-organized criticality in networks of spiking neurons.

PubMed

Rubinov, Mikail; Sporns, Olaf; Thivierge, Jean-Philippe; Breakspear, Michael

2011-06-01

Self-organized criticality refers to the spontaneous emergence of self-similar dynamics in complex systems poised between order and randomness. The presence of self-organized critical dynamics in the brain is theoretically appealing and is supported by recent neurophysiological studies. Despite this, the neurobiological determinants of these dynamics have not been previously sought. Here, we systematically examined the influence of such determinants in hierarchically modular networks of leaky integrate-and-fire neurons with spike-timing-dependent synaptic plasticity and axonal conduction delays. We characterized emergent dynamics in our networks by distributions of active neuronal ensemble modules (neuronal avalanches) and rigorously assessed these distributions for power-law scaling. We found that spike-timing-dependent synaptic plasticity enabled a rapid phase transition from random subcritical dynamics to ordered supercritical dynamics. Importantly, modular connectivity and low wiring cost broadened this transition, and enabled a regime indicative of self-organized criticality. The regime only occurred when modular connectivity, low wiring cost and synaptic plasticity were simultaneously present, and the regime was most evident when between-module connection density scaled as a power-law. The regime was robust to variations in other neurobiologically relevant parameters and favored systems with low external drive and strong internal interactions. Increases in system size and connectivity facilitated internal interactions, permitting reductions in external drive and facilitating convergence of postsynaptic-response magnitude and synaptic-plasticity learning rate parameter values towards neurobiologically realistic levels. We hence infer a novel association between self-organized critical neuronal dynamics and several neurobiologically realistic features of structural connectivity. The central role of these features in our model may reflect their importance for neuronal information processing.

Monitoring synaptic and neuronal activity in 3D with synthetic and genetic indicators using a compact acousto-optic lens two-photon microscope☆

PubMed Central

Fernández-Alfonso, Tomás; Nadella, K.M. Naga Srinivas; Iacaruso, M. Florencia; Pichler, Bruno; Roš, Hana; Kirkby, Paul A.; Silver, R. Angus

2014-01-01

Background Two-photon microscopy is widely used to study brain function, but conventional microscopes are too slow to capture the timing of neuronal signalling and imaging is restricted to one plane. Recent development of acousto-optic-deflector-based random access functional imaging has improved the temporal resolution, but the utility of these technologies for mapping 3D synaptic activity patterns and their performance at the excitation wavelengths required to image genetically encoded indicators have not been investigated. New method Here, we have used a compact acousto-optic lens (AOL) two-photon microscope to make high speed [Ca2+] measurements from spines and dendrites distributed in 3D with different excitation wavelengths (800–920 nm). Results We show simultaneous monitoring of activity from many synaptic inputs distributed over the 3D arborisation of a neuronal dendrite using both synthetic as well as genetically encoded indicators. We confirm the utility of AOL-based imaging for fast in vivo recordings by measuring, simultaneously, visually evoked responses in 100 neurons distributed over a 150 μm focal depth range. Moreover, we explore ways to improve the measurement of timing of neuronal activation by choosing specific regions within the cell soma. Comparison with existing methods These results establish that AOL-based 3D random access two-photon microscopy has a wider range of neuroscience applications than previously shown. Conclusions Our findings show that the compact AOL microscope design has the speed, spatial resolution, sensitivity and wavelength flexibility to measure 3D patterns of synaptic and neuronal activity on individual trials. PMID:24200507

Synaptic characteristics with strong analog potentiation, depression, and short-term to long-term memory transition in a Pt/CeO2/Pt crossbar array structure

NASA Astrophysics Data System (ADS)

Kim, Hyung Jun; Park, Daehoon; Yang, Paul; Beom, Keonwon; Kim, Min Ju; Shin, Chansun; Kang, Chi Jung; Yoon, Tae-Sik

2018-06-01

A crossbar array of Pt/CeO2/Pt memristors exhibited the synaptic characteristics such as analog, reversible, and strong resistance change with a ratio of ∼103, corresponding to wide dynamic range of synaptic weight modulation as potentiation and depression with respect to the voltage polarity. In addition, it presented timing-dependent responses such as paired-pulse facilitation and the short-term to long-term memory transition by increasing amplitude, width, and repetition number of voltage pulse and reducing the interval time between pulses. The memory loss with a time was fitted with a stretched exponential relaxation model, revealing the relation of memory stability with the input stimuli strength. The resistance change was further enhanced but its stability got worse as increasing measurement temperature, indicating that the resistance was changed as a result of voltage- and temperature-dependent electrical charging and discharging to alter the energy barrier for charge transport. These detailed synaptic characteristics demonstrated the potential of crossbar array of Pt/CeO2/Pt memristors as artificial synapses in highly connected neuron-synapse network.

Synaptic characteristics with strong analog potentiation, depression, and short-term to long-term memory transition in a Pt/CeO2/Pt crossbar array structure.

PubMed

Kim, Hyung Jun; Park, Daehoon; Yang, Paul; Beom, Keonwon; Kim, Min Ju; Shin, Chansun; Kang, Chi Jung; Yoon, Tae-Sik

2018-06-29

A crossbar array of Pt/CeO 2 /Pt memristors exhibited the synaptic characteristics such as analog, reversible, and strong resistance change with a ratio of ∼10 3 , corresponding to wide dynamic range of synaptic weight modulation as potentiation and depression with respect to the voltage polarity. In addition, it presented timing-dependent responses such as paired-pulse facilitation and the short-term to long-term memory transition by increasing amplitude, width, and repetition number of voltage pulse and reducing the interval time between pulses. The memory loss with a time was fitted with a stretched exponential relaxation model, revealing the relation of memory stability with the input stimuli strength. The resistance change was further enhanced but its stability got worse as increasing measurement temperature, indicating that the resistance was changed as a result of voltage- and temperature-dependent electrical charging and discharging to alter the energy barrier for charge transport. These detailed synaptic characteristics demonstrated the potential of crossbar array of Pt/CeO 2 /Pt memristors as artificial synapses in highly connected neuron-synapse network.

Asymmetry of Neuronal Combinatorial Codes Arises from Minimizing Synaptic Weight Change.

PubMed

Leibold, Christian; Monsalve-Mercado, Mauro M

2016-08-01

Synaptic change is a costly resource, particularly for brain structures that have a high demand of synaptic plasticity. For example, building memories of object positions requires efficient use of plasticity resources since objects can easily change their location in space and yet we can memorize object locations. But how should a neural circuit ideally be set up to integrate two input streams (object location and identity) in case the overall synaptic changes should be minimized during ongoing learning? This letter provides a theoretical framework on how the two input pathways should ideally be specified. Generally the model predicts that the information-rich pathway should be plastic and encoded sparsely, whereas the pathway conveying less information should be encoded densely and undergo learning only if a neuronal representation of a novel object has to be established. As an example, we consider hippocampal area CA1, which combines place and object information. The model thereby provides a normative account of hippocampal rate remapping, that is, modulations of place field activity by changes of local cues. It may as well be applicable to other brain areas (such as neocortical layer V) that learn combinatorial codes from multiple input streams.

Role of GABAA-Mediated Inhibition and Functional Assortment of Synapses onto Individual Layer 4 Neurons in Regulating Plasticity Expression in Visual Cortex.

PubMed

Saez, Ignacio; Friedlander, Michael J

2016-01-01

Layer 4 (L4) of primary visual cortex (V1) is the main recipient of thalamocortical fibers from the dorsal lateral geniculate nucleus (LGNd). Thus, it is considered the main entry point of visual information into the neocortex and the first anatomical opportunity for intracortical visual processing before information leaves L4 and reaches supra- and infragranular cortical layers. The strength of monosynaptic connections from individual L4 excitatory cells onto adjacent L4 cells (unitary connections) is highly malleable, demonstrating that the initial stage of intracortical synaptic transmission of thalamocortical information can be altered by previous activity. However, the inhibitory network within L4 of V1 may act as an internal gate for induction of excitatory synaptic plasticity, thus providing either high fidelity throughput to supragranular layers or transmittal of a modified signal subject to recent activity-dependent plasticity. To evaluate this possibility, we compared the induction of synaptic plasticity using classical extracellular stimulation protocols that recruit a combination of excitatory and inhibitory synapses with stimulation of a single excitatory neuron onto a L4 cell. In order to induce plasticity, we paired pre- and postsynaptic activity (with the onset of postsynaptic spiking leading the presynaptic activation by 10ms) using extracellular stimulation (ECS) in acute slices of primary visual cortex and comparing the outcomes with our previously published results in which an identical protocol was used to induce synaptic plasticity between individual pre- and postsynaptic L4 excitatory neurons. Our results indicate that pairing of ECS with spiking in a L4 neuron fails to induce plasticity in L4-L4 connections if synaptic inhibition is intact. However, application of a similar pairing protocol under GABAARs inhibition by bath application of 2μM bicuculline does induce robust synaptic plasticity, long term potentiation (LTP) or long term depression (LTD), similar to our results with pairing of pre- and postsynaptic activation between individual excitatory L4 neurons in which inhibitory connections are not activated. These results are consistent with the well-established observation that inhibition limits the capacity for induction of plasticity at excitatory synapses and that pre- and postsynaptic activation at a fixed time interval can result in a variable range of plasticity outcomes. However, in the current study by virtue of having two sets of experimental data, we have provided a new insight into these processes. By randomly mixing the assorting of individual L4 neurons according to the frequency distribution of the experimentally determined plasticity outcome distribution based on the calculated convergence of multiple individual L4 neurons onto a single postsynaptic L4 neuron, we were able to compare then actual ECS plasticity outcomes to those predicted by randomly mixing individual pairs of neurons. Interestingly, the observed plasticity profiles with ECS cannot account for the random assortment of plasticity behaviors of synaptic connections between individual cell pairs. These results suggest that connections impinging onto a single postsynaptic cell may be grouped according to plasticity states.

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

PubMed

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.

Stochastic Synapses Enable Efficient Brain-Inspired Learning Machines.

PubMed

Neftci, Emre O; Pedroni, Bruno U; Joshi, Siddharth; Al-Shedivat, Maruan; Cauwenberghs, Gert

2016-01-01

Recent studies have shown that synaptic unreliability is a robust and sufficient mechanism for inducing the stochasticity observed in cortex. Here, we introduce Synaptic Sampling Machines (S2Ms), a class of neural network models that uses synaptic stochasticity as a means to Monte Carlo sampling and unsupervised learning. Similar to the original formulation of Boltzmann machines, these models can be viewed as a stochastic counterpart of Hopfield networks, but where stochasticity is induced by a random mask over the connections. Synaptic stochasticity plays the dual role of an efficient mechanism for sampling, and a regularizer during learning akin to DropConnect. A local synaptic plasticity rule implementing an event-driven form of contrastive divergence enables the learning of generative models in an on-line fashion. S2Ms perform equally well using discrete-timed artificial units (as in Hopfield networks) or continuous-timed leaky integrate and fire neurons. The learned representations are remarkably sparse and robust to reductions in bit precision and synapse pruning: removal of more than 75% of the weakest connections followed by cursory re-learning causes a negligible performance loss on benchmark classification tasks. The spiking neuron-based S2Ms outperform existing spike-based unsupervised learners, while potentially offering substantial advantages in terms of power and complexity, and are thus promising models for on-line learning in brain-inspired hardware.

Stochastic Synapses Enable Efficient Brain-Inspired Learning Machines

PubMed Central

Neftci, Emre O.; Pedroni, Bruno U.; Joshi, Siddharth; Al-Shedivat, Maruan; Cauwenberghs, Gert

2016-01-01

Recent studies have shown that synaptic unreliability is a robust and sufficient mechanism for inducing the stochasticity observed in cortex. Here, we introduce Synaptic Sampling Machines (S2Ms), a class of neural network models that uses synaptic stochasticity as a means to Monte Carlo sampling and unsupervised learning. Similar to the original formulation of Boltzmann machines, these models can be viewed as a stochastic counterpart of Hopfield networks, but where stochasticity is induced by a random mask over the connections. Synaptic stochasticity plays the dual role of an efficient mechanism for sampling, and a regularizer during learning akin to DropConnect. A local synaptic plasticity rule implementing an event-driven form of contrastive divergence enables the learning of generative models in an on-line fashion. S2Ms perform equally well using discrete-timed artificial units (as in Hopfield networks) or continuous-timed leaky integrate and fire neurons. The learned representations are remarkably sparse and robust to reductions in bit precision and synapse pruning: removal of more than 75% of the weakest connections followed by cursory re-learning causes a negligible performance loss on benchmark classification tasks. The spiking neuron-based S2Ms outperform existing spike-based unsupervised learners, while potentially offering substantial advantages in terms of power and complexity, and are thus promising models for on-line learning in brain-inspired hardware. PMID:27445650

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

PubMed Central

2017-01-01

Abstract 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. PMID:28534043

Metal oxide resistive random access memory based synaptic devices for brain-inspired computing

NASA Astrophysics Data System (ADS)

Gao, Bin; Kang, Jinfeng; Zhou, Zheng; Chen, Zhe; Huang, Peng; Liu, Lifeng; Liu, Xiaoyan

2016-04-01

The traditional Boolean computing paradigm based on the von Neumann architecture is facing great challenges for future information technology applications such as big data, the Internet of Things (IoT), and wearable devices, due to the limited processing capability issues such as binary data storage and computing, non-parallel data processing, and the buses requirement between memory units and logic units. The brain-inspired neuromorphic computing paradigm is believed to be one of the promising solutions for realizing more complex functions with a lower cost. To perform such brain-inspired computing with a low cost and low power consumption, novel devices for use as electronic synapses are needed. Metal oxide resistive random access memory (ReRAM) devices have emerged as the leading candidate for electronic synapses. This paper comprehensively addresses the recent work on the design and optimization of metal oxide ReRAM-based synaptic devices. A performance enhancement methodology and optimized operation scheme to achieve analog resistive switching and low-energy training behavior are provided. A three-dimensional vertical synapse network architecture is proposed for high-density integration and low-cost fabrication. The impacts of the ReRAM synaptic device features on the performances of neuromorphic systems are also discussed on the basis of a constructed neuromorphic visual system with a pattern recognition function. Possible solutions to achieve the high recognition accuracy and efficiency of neuromorphic systems are presented.

The Physiology of Moral Maturity.

ERIC Educational Resources Information Center

Hemming, James

1991-01-01

Discusses an evolutionary approach to human morality. Emphasizes the rapid development of brain weight, neural circuits, and synaptic systems during early childhood. Concludes that the human brain has resources for generating responsible, caring behavior but must be nurtured and educated. Urges that moral training in a proper social climate be…

Three-Dimensional Spatial Distribution of Synapses in the Neocortex: A Dual-Beam Electron Microscopy Study

PubMed Central

Merchán-Pérez, Angel; Rodríguez, José-Rodrigo; González, Santiago; Robles, Víctor; DeFelipe, Javier; Larrañaga, Pedro; Bielza, Concha

2014-01-01

In the cerebral cortex, most synapses are found in the neuropil, but relatively little is known about their 3-dimensional organization. Using an automated dual-beam electron microscope that combines focused ion beam milling and scanning electron microscopy, we have been able to obtain 10 three-dimensional samples with an average volume of 180 µm3 from the neuropil of layer III of the young rat somatosensory cortex (hindlimb representation). We have used specific software tools to fully reconstruct 1695 synaptic junctions present in these samples and to accurately quantify the number of synapses per unit volume. These tools also allowed us to determine synapse position and to analyze their spatial distribution using spatial statistical methods. Our results indicate that the distribution of synaptic junctions in the neuropil is nearly random, only constrained by the fact that synapses cannot overlap in space. A theoretical model based on random sequential absorption, which closely reproduces the actual distribution of synapses, is also presented. PMID:23365213

Three-dimensional spatial distribution of synapses in the neocortex: a dual-beam electron microscopy study.

PubMed

Merchán-Pérez, Angel; Rodríguez, José-Rodrigo; González, Santiago; Robles, Víctor; Defelipe, Javier; Larrañaga, Pedro; Bielza, Concha

2014-06-01

In the cerebral cortex, most synapses are found in the neuropil, but relatively little is known about their 3-dimensional organization. Using an automated dual-beam electron microscope that combines focused ion beam milling and scanning electron microscopy, we have been able to obtain 10 three-dimensional samples with an average volume of 180 µm(3) from the neuropil of layer III of the young rat somatosensory cortex (hindlimb representation). We have used specific software tools to fully reconstruct 1695 synaptic junctions present in these samples and to accurately quantify the number of synapses per unit volume. These tools also allowed us to determine synapse position and to analyze their spatial distribution using spatial statistical methods. Our results indicate that the distribution of synaptic junctions in the neuropil is nearly random, only constrained by the fact that synapses cannot overlap in space. A theoretical model based on random sequential absorption, which closely reproduces the actual distribution of synapses, is also presented.

Mechanisms for Selective Single-Cell Reactivation during Offline Sharp-Wave Ripples and Their Distortion by Fast Ripples.

PubMed

Valero, Manuel; Averkin, Robert G; Fernandez-Lamo, Ivan; Aguilar, Juan; Lopez-Pigozzi, Diego; Brotons-Mas, Jorge R; Cid, Elena; Tamas, Gabor; Menendez de la Prida, Liset

2017-06-21

Memory traces are reactivated selectively during sharp-wave ripples. The mechanisms of selective reactivation, and how degraded reactivation affects memory, are poorly understood. We evaluated hippocampal single-cell activity during physiological and pathological sharp-wave ripples using juxtacellular and intracellular recordings in normal and epileptic rats with different memory abilities. CA1 pyramidal cells participate selectively during physiological events but fired together during epileptic fast ripples. We found that firing selectivity was dominated by an event- and cell-specific synaptic drive, modulated in single cells by changes in the excitatory/inhibitory ratio measured intracellularly. This mechanism collapses during pathological fast ripples to exacerbate and randomize neuronal firing. Acute administration of a use- and cell-type-dependent sodium channel blocker reduced neuronal collapse and randomness and improved recall in epileptic rats. We propose that cell-specific synaptic inputs govern firing selectivity of CA1 pyramidal cells during sharp-wave ripples. Copyright © 2017 Elsevier Inc. All rights reserved.

A Cognitive Model Based on Neuromodulated Plasticity

PubMed Central

Ruan, Xiaogang

2016-01-01

Associative learning, including classical conditioning and operant conditioning, is regarded as the most fundamental type of learning for animals and human beings. Many models have been proposed surrounding classical conditioning or operant conditioning. However, a unified and integrated model to explain the two types of conditioning is much less studied. Here, a model based on neuromodulated synaptic plasticity is presented. The model is bioinspired including multistored memory module and simulated VTA dopaminergic neurons to produce reward signal. The synaptic weights are modified according to the reward signal, which simulates the change of associative strengths in associative learning. The experiment results in real robots prove the suitability and validity of the proposed model. PMID:27872638

Two cell circuits of oriented adult hippocampal neurons on self-assembled monolayers for use in the study of neuronal communication in a defined system.

PubMed

Edwards, Darin; Stancescu, Maria; Molnar, Peter; Hickman, James J

2013-08-21

In this study, we demonstrate the directed formation of small circuits of electrically active, synaptically connected neurons derived from the hippocampus of adult rats through the use of engineered chemically modified culture surfaces that orient the polarity of the neuronal processes. Although synaptogenesis, synaptic communication, synaptic plasticity, and brain disease pathophysiology can be studied using brain slice or dissociated embryonic neuronal culture systems, the complex elements found in neuronal synapses makes specific studies difficult in these random cultures. The study of synaptic transmission in mature adult neurons and factors affecting synaptic transmission are generally studied in organotypic cultures, in brain slices, or in vivo. However, engineered neuronal networks would allow these studies to be performed instead on simple functional neuronal circuits derived from adult brain tissue. Photolithographic patterned self-assembled monolayers (SAMs) were used to create the two-cell "bidirectional polarity" circuit patterns. This pattern consisted of a cell permissive SAM, N-1[3-(trimethoxysilyl)propyl] diethylenetriamine (DETA), and was composed of two 25 μm somal adhesion sites connected with 5 μm lines acting as surface cues for guided axonal and dendritic regeneration. Surrounding the DETA pattern was a background of a non-cell-permissive poly(ethylene glycol) (PEG) SAM. Adult hippocampal neurons were first cultured on coverslips coated with DETA monolayers and were later passaged onto the PEG-DETA bidirectional polarity patterns in serum-free medium. These neurons followed surface cues, attaching and regenerating only along the DETA substrate to form small engineered neuronal circuits. These circuits were stable for more than 21 days in vitro (DIV), during which synaptic connectivity was evaluated using basic electrophysiological methods.

Mid-life environmental enrichment increases synaptic density in CA1 in a mouse model of Aβ-associated pathology and positively influences synaptic and cognitive health in healthy ageing.

PubMed

Stuart, Kimberley E; King, Anna E; Fernandez-Martos, Carmen M; Dittmann, Justin; Summers, Mathew J; Vickers, James C

2017-06-01

Early-life cognitive enrichment may reduce the risk of experiencing cognitive deterioration and dementia in later-life. However, an intervention to prevent or delay dementia is likely to be taken up in mid to later-life. Hence, we investigated the effects of environmental enrichment in wildtype mice and in a mouse model of Aβ neuropathology (APP SWE /PS1 dE9 ) from 6 months of age. After 6 months of housing in standard laboratory cages, APP SWE /PS1 dE9 (n = 27) and healthy wildtype (n = 21) mice were randomly assigned to either enriched or standard housing. At 12 months of age, wildtype mice showed altered synaptic protein levels and relatively superior cognitive performance afforded by environmental enrichment. Environmental enrichment was not associated with alterations to Aβ plaque pathology in the neocortex or hippocampus of APP SWE /PS1 dE9 mice. However, a significant increase in synaptophysin immunolabeled puncta in the hippocampal subregion, CA1, in APP SWE /PS1 dE9 mice was detected, with no significant synaptic density changes observed in CA3, or the Fr2 region of the prefrontal cortex. Moreover, a significant increase in hippocampal BDNF was detected in APP SWE /PS1 dE9 mice exposed to EE, however, no changes were detected in neocortex or between Wt animals. These results demonstrate that mid to later-life cognitive enrichment has the potential to promote synaptic and cognitive health in ageing, and to enhance compensatory capacity for synaptic connectivity in pathological ageing associated with Aβ deposition. © 2017 Wiley Periodicals, Inc.

Oscillations, Timing, Plasticity, and Learning in the Cerebellum.

PubMed

Cheron, G; Márquez-Ruiz, J; Dan, B

2016-04-01

The highly stereotyped, crystal-like architecture of the cerebellum has long served as a basis for hypotheses with regard to the function(s) that it subserves. Historically, most clinical observations and experimental work have focused on the involvement of the cerebellum in motor control, with particular emphasis on coordination and learning. Two main models have been suggested to account for cerebellar functioning. According to Llinás's theory, the cerebellum acts as a control machine that uses the rhythmic activity of the inferior olive to synchronize Purkinje cell populations for fine-tuning of coordination. In contrast, the Ito-Marr-Albus theory views the cerebellum as a motor learning machine that heuristically refines synaptic weights of the Purkinje cell based on error signals coming from the inferior olive. Here, we review the role of timing of neuronal events, oscillatory behavior, and synaptic and non-synaptic influences in functional plasticity that can be recorded in awake animals in various physiological and pathological models in a perspective that also includes non-motor aspects of cerebellar function. We discuss organizational levels from genes through intracellular signaling, synaptic network to system and behavior, as well as processes from signal production and processing to memory, delegation, and actual learning. We suggest an integrative concept for control and learning based on articulated oscillation templates.

Relaxation oscillator-realized artificial electronic neurons, their responses, and noise

NASA Astrophysics Data System (ADS)

Lim, Hyungkwang; Ahn, Hyung-Woo; Kornijcuk, Vladimir; Kim, Guhyun; Seok, Jun Yeong; Kim, Inho; Hwang, Cheol Seong; Jeong, Doo Seok

2016-05-01

A proof-of-concept relaxation oscillator-based leaky integrate-and-fire (ROLIF) neuron circuit is realized by using an amorphous chalcogenide-based threshold switch and non-ideal operational amplifier (op-amp). The proposed ROLIF neuron offers biologically plausible features such as analog-type encoding, signal amplification, unidirectional synaptic transmission, and Poisson noise. The synaptic transmission between pre- and postsynaptic neurons is achieved through a passive synapse (simple resistor). The synaptic resistor coupled to the non-ideal op-amp realizes excitatory postsynaptic potential (EPSP) evolution that evokes postsynaptic neuron spiking. In an attempt to generalize our proposed model, we theoretically examine ROLIF neuron circuits adopting different non-ideal op-amps having different gains and slew rates. The simulation results indicate the importance of gain in postsynaptic neuron spiking, irrespective of the slew rate (as long as the rate exceeds a particular value), providing the basis for the ROLIF neuron circuit design. Eventually, the behavior of a postsynaptic neuron in connection to multiple presynaptic neurons via synapses is highlighted in terms of EPSP evolution amid simultaneously incident asynchronous presynaptic spikes, which in fact reveals an important role of the random noise in spatial integration.A proof-of-concept relaxation oscillator-based leaky integrate-and-fire (ROLIF) neuron circuit is realized by using an amorphous chalcogenide-based threshold switch and non-ideal operational amplifier (op-amp). The proposed ROLIF neuron offers biologically plausible features such as analog-type encoding, signal amplification, unidirectional synaptic transmission, and Poisson noise. The synaptic transmission between pre- and postsynaptic neurons is achieved through a passive synapse (simple resistor). The synaptic resistor coupled to the non-ideal op-amp realizes excitatory postsynaptic potential (EPSP) evolution that evokes postsynaptic neuron spiking. In an attempt to generalize our proposed model, we theoretically examine ROLIF neuron circuits adopting different non-ideal op-amps having different gains and slew rates. The simulation results indicate the importance of gain in postsynaptic neuron spiking, irrespective of the slew rate (as long as the rate exceeds a particular value), providing the basis for the ROLIF neuron circuit design. Eventually, the behavior of a postsynaptic neuron in connection to multiple presynaptic neurons via synapses is highlighted in terms of EPSP evolution amid simultaneously incident asynchronous presynaptic spikes, which in fact reveals an important role of the random noise in spatial integration. Electronic supplementary information (ESI) available. See DOI: 10.1039/c6nr01278g

Dendrites of cerebellar granule cells correctly recognize their target axons for synaptogenesis in vitro.

PubMed

Ito, Shoko; Takeichi, Masatoshi

2009-08-04

Neural circuits are generated by precisely ordered synaptic connections among neurons, and this process is thought to rely on the ability of neurons to recognize specific partners. However, it is also known that neurons promiscuously form synapses with nonspecific partners, in particular when cultured in vitro, causing controversies about neural recognition mechanisms. Here we reexamined whether neurons can or cannot select particular partners in vitro. In the cerebellum, granule cell (GC) dendrites form synaptic connections specifically with mossy fibers, but not with climbing fibers. We cocultured GC neurons with pontine or inferior olivary axons, the major sources for mossy and climbing fibers, respectively, as well as with hippocampal axons as a control. The GC neurons formed synapses with pontine axons predominantly at the distal ends of their dendrites, reproducing the characteristic morphology of their synapses observed in vivo, whereas they failed to do so when combined with other axons. In the latter case, synaptic proteins could accumulate between axons and dendrites, but these synapses were randomly distributed throughout the contact sites, and also their synaptic vesicle recycling was anomalous. These observations suggest that GC dendrites can select their authentic partners for synaptogenesis even in vitro, forming the synapses with a GC-specific nature only with them.

Synapse Specificity of Long-Term Potentiation Breaks Down with Aging

ERIC Educational Resources Information Center

Ris, Laurence; Godaux, Emile

2007-01-01

Memory shows age-related decline. According to the current prevailing theoretical model, encoding of memories relies on modifications in the strength of the synapses connecting the different cells within a neuronal network. The selective increases in synaptic weight are thought to be biologically implemented by long-term potentiation (LTP). Here,…

Theta Coordinated Error Driven Learning in the Hippocampus (Open Access, Publisher’s Version)

DTIC Science & Technology

2013-06-06

assumed to be Hebbian in nature, where individual neurons in an engram join together with synaptic weight increases to support facilitated recall of...together as part of a memory or engram representation, e.g., in the central area CA3 of the hippocampus. With these connections strengthened, the ability

A theory for how sensorimotor skills are learned and retained in noisy and nonstationary neural circuits

PubMed Central

Ajemian, Robert; D’Ausilio, Alessandro; Moorman, Helene; Bizzi, Emilio

2013-01-01

During the process of skill learning, synaptic connections in our brains are modified to form motor memories of learned sensorimotor acts. The more plastic the adult brain is, the easier it is to learn new skills or adapt to neurological injury. However, if the brain is too plastic and the pattern of synaptic connectivity is constantly changing, new memories will overwrite old memories, and learning becomes unstable. This trade-off is known as the stability–plasticity dilemma. Here a theory of sensorimotor learning and memory is developed whereby synaptic strengths are perpetually fluctuating without causing instability in motor memory recall, as long as the underlying neural networks are sufficiently noisy and massively redundant. The theory implies two distinct stages of learning—preasymptotic and postasymptotic—because once the error drops to a level comparable to that of the noise-induced error, further error reduction requires altered network dynamics. A key behavioral prediction derived from this analysis is tested in a visuomotor adaptation experiment, and the resultant learning curves are modeled with a nonstationary neural network. Next, the theory is used to model two-photon microscopy data that show, in animals, high rates of dendritic spine turnover, even in the absence of overt behavioral learning. Finally, the theory predicts enhanced task selectivity in the responses of individual motor cortical neurons as the level of task expertise increases. From these considerations, a unique interpretation of sensorimotor memory is proposed—memories are defined not by fixed patterns of synaptic weights but, rather, by nonstationary synaptic patterns that fluctuate coherently. PMID:24324147

The role of ionotropic glutamate receptors in childhood neurodevelopmental disorders: autism spectrum disorders and fragile x syndrome.

PubMed

Uzunova, Genoveva; Hollander, Eric; Shepherd, Jason

2014-01-01

Autism spectrum disorder (ASD) and Fragile X syndrome (FXS) are relatively common childhood neurodevelopmental disorders with increasing incidence in recent years. They are currently accepted as disorders of the synapse with alterations in different forms of synaptic communication and neuronal network connectivity. The major excitatory neurotransmitter system in brain, the glutamatergic system, is implicated in learning and memory, synaptic plasticity, neuronal development. While much attention is attributed to the role of metabotropic glutamate receptors in ASD and FXS, studies indicate that the ionotropic glutamate receptors (iGluRs) and their regulatory proteins are also altered in several brain regions. Role of iGluRs in the neurobiology of ASD and FXS is supported by a weight of evidence that ranges from human genetics to in vitro cultured neurons. In this review we will discuss clinical, molecular, cellular and functional changes in NMDA, AMPA and kainate receptors and the synaptic proteins that regulate them in the context of ASD and FXS. We will also discuss the significance for the development of translational biomarkers and treatments for the core symptoms of ASD and FXS.

Models of Acetylcholine and Dopamine Signals Differentially Improve Neural Representations

PubMed Central

Holca-Lamarre, Raphaël; Lücke, Jörg; Obermayer, Klaus

2017-01-01

Biological and artificial neural networks (ANNs) represent input signals as patterns of neural activity. In biology, neuromodulators can trigger important reorganizations of these neural representations. For instance, pairing a stimulus with the release of either acetylcholine (ACh) or dopamine (DA) evokes long lasting increases in the responses of neurons to the paired stimulus. The functional roles of ACh and DA in rearranging representations remain largely unknown. Here, we address this question using a Hebbian-learning neural network model. Our aim is both to gain a functional understanding of ACh and DA transmission in shaping biological representations and to explore neuromodulator-inspired learning rules for ANNs. We model the effects of ACh and DA on synaptic plasticity and confirm that stimuli coinciding with greater neuromodulator activation are over represented in the network. We then simulate the physiological release schedules of ACh and DA. We measure the impact of neuromodulator release on the network's representation and on its performance on a classification task. We find that ACh and DA trigger distinct changes in neural representations that both improve performance. The putative ACh signal redistributes neural preferences so that more neurons encode stimulus classes that are challenging for the network. The putative DA signal adapts synaptic weights so that they better match the classes of the task at hand. Our model thus offers a functional explanation for the effects of ACh and DA on cortical representations. Additionally, our learning algorithm yields performances comparable to those of state-of-the-art optimisation methods in multi-layer perceptrons while requiring weaker supervision signals and interacting with synaptically-local weight updates. PMID:28690509

A Digital Liquid State Machine With Biologically Inspired Learning and Its Application to Speech Recognition.

PubMed

Zhang, Yong; Li, Peng; Jin, Yingyezhe; Choe, Yoonsuck

2015-11-01

This paper presents a bioinspired digital liquid-state machine (LSM) for low-power very-large-scale-integration (VLSI)-based machine learning applications. To the best of the authors' knowledge, this is the first work that employs a bioinspired spike-based learning algorithm for the LSM. With the proposed online learning, the LSM extracts information from input patterns on the fly without needing intermediate data storage as required in offline learning methods such as ridge regression. The proposed learning rule is local such that each synaptic weight update is based only upon the firing activities of the corresponding presynaptic and postsynaptic neurons without incurring global communications across the neural network. Compared with the backpropagation-based learning, the locality of computation in the proposed approach lends itself to efficient parallel VLSI implementation. We use subsets of the TI46 speech corpus to benchmark the bioinspired digital LSM. To reduce the complexity of the spiking neural network model without performance degradation for speech recognition, we study the impacts of synaptic models on the fading memory of the reservoir and hence the network performance. Moreover, we examine the tradeoffs between synaptic weight resolution, reservoir size, and recognition performance and present techniques to further reduce the overhead of hardware implementation. Our simulation results show that in terms of isolated word recognition evaluated using the TI46 speech corpus, the proposed digital LSM rivals the state-of-the-art hidden Markov-model-based recognizer Sphinx-4 and outperforms all other reported recognizers including the ones that are based upon the LSM or neural networks.

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

PubMed

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.

Efficient Transmission of Subthreshold Signals in Complex Networks of Spiking Neurons

PubMed Central

Torres, Joaquin J.; Elices, Irene; Marro, J.

2015-01-01

We investigate the efficient transmission and processing of weak, subthreshold signals in a realistic neural medium in the presence of different levels of the underlying noise. Assuming Hebbian weights for maximal synaptic conductances—that naturally balances the network with excitatory and inhibitory synapses—and considering short-term synaptic plasticity affecting such conductances, we found different dynamic phases in the system. This includes a memory phase where population of neurons remain synchronized, an oscillatory phase where transitions between different synchronized populations of neurons appears and an asynchronous or noisy phase. When a weak stimulus input is applied to each neuron, increasing the level of noise in the medium we found an efficient transmission of such stimuli around the transition and critical points separating different phases for well-defined different levels of stochasticity in the system. We proved that this intriguing phenomenon is quite robust, as it occurs in different situations including several types of synaptic plasticity, different type and number of stored patterns and diverse network topologies, namely, diluted networks and complex topologies such as scale-free and small-world networks. We conclude that the robustness of the phenomenon in different realistic scenarios, including spiking neurons, short-term synaptic plasticity and complex networks topologies, make very likely that it could also occur in actual neural systems as recent psycho-physical experiments suggest. PMID:25799449

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

PubMed Central

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

2014-01-01

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

Closed-loop control of a fragile network: application to seizure-like dynamics of an epilepsy model

PubMed Central

Ehrens, Daniel; Sritharan, Duluxan; Sarma, Sridevi V.

2015-01-01

It has recently been proposed that the epileptic cortex is fragile in the sense that seizures manifest through small perturbations in the synaptic connections that render the entire cortical network unstable. Closed-loop therapy could therefore entail detecting when the network goes unstable, and then stimulating with an exogenous current to stabilize the network. In this study, a non-linear stochastic model of a neuronal network was used to simulate both seizure and non-seizure activity. In particular, synaptic weights between neurons were chosen such that the network's fixed point is stable during non-seizure periods, and a subset of these connections (the most fragile) were perturbed to make the same fixed point unstable to model seizure events; and, the model randomly transitions between these two modes. The goal of this study was to measure spike train observations from this epileptic network and then apply a feedback controller that (i) detects when the network goes unstable, and then (ii) applies a state-feedback gain control input to the network to stabilize it. The stability detector is based on a 2-state (stable, unstable) hidden Markov model (HMM) of the network, and detects the transition from the stable mode to the unstable mode from using the firing rate of the most fragile node in the network (which is the output of the HMM). When the unstable mode is detected, a state-feedback gain is applied to generate a control input to the fragile node bringing the network back to the stable mode. Finally, when the network is detected as stable again, the feedback control input is switched off. High performance was achieved for the stability detector, and feedback control suppressed seizures within 2 s after onset. PMID:25784851

Biochemistry of snake venom neurotoxins and their application to the study of synapse. [Neurotoxins isolated from venom of the Formosan banded krait

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

Hanley, M.R.

1978-11-01

The crude venom of the Formosan banded krait, Bungarus multicinctus, was separated into eleven lethal protein fractions. Nine fractions were purified to final homogeneous toxins, designated ..cap alpha..-bungarotoxin, ..beta..-bungarotoxin, and toxins 7, 8, 9A, 11, 12, 13, and 14. Three of the toxins, ..cap alpha..-bungarotoxin, 7, and 8, were identified as post-synaptic curarimimetic neurotoxins. The remaining toxins were identified as pre-synaptic neurotoxins. ..cap alpha..-Bungarotoxin, toxin 7, and toxin 8 are all highly stable basic polypeptides of approx. 8000 daltons molecular weight. The pre-synaptic toxins fell into two structural groups: toxin 9A and 14 which were single basic chains of approx.more » 14,000 daltons, and ..beta..-bungarotoxin, and toxins 11 thru 13 which were composed of two chains of approx. 8000 and approx. 13,000 daltons covalently linked by disulfides. All the pre-synaptic neurotoxins were shown to have intrinsic calcium-dependent phospholipase A activities. Under certain conditions, intact synaptic membranes were hydrolyzed more rapidly than protein-free extracted synaptic-lipid liposomes which, in turn, were hydrolyzed more rapidly than any other tested liposomes. It was speculated that cell-surface arrays of phosphatidyl serine/glycolipids created high affinity target sites for ..beta..-bungarotoxin. Single-chain toxins were found to be qualitatively different from the two-chain toxins in their ability to block the functioning of acetylcholine receptors, and were quantitatively different in their enzymatic and membrane disruptive activities. ..beta..-Bungarotoxin was shown to be an extremely potent neuronal lesioning agent. There was no apparent selectivity for cholinergic over non-cholinergic neurons, nor for nerve terminals over cell bodies. It was suggested that ..beta..-bungarotoxin can be considered a useful new histological tool, which may exhibit some regional selectivity.« less

The emergence of polychronization and feature binding in a spiking neural network model of the primate ventral visual system.

PubMed

Eguchi, Akihiro; Isbister, James B; Ahmad, Nasir; Stringer, Simon

2018-07-01

We present a hierarchical neural network model, in which subpopulations of neurons develop fixed and regularly repeating temporal chains of spikes (polychronization), which respond specifically to randomized Poisson spike trains representing the input training images. The performance is improved by including top-down and lateral synaptic connections, as well as introducing multiple synaptic contacts between each pair of pre- and postsynaptic neurons, with different synaptic contacts having different axonal delays. Spike-timing-dependent plasticity thus allows the model to select the most effective axonal transmission delay between neurons. Furthermore, neurons representing the binding relationship between low-level and high-level visual features emerge through visually guided learning. This begins to provide a way forward to solving the classic feature binding problem in visual neuroscience and leads to a new hypothesis concerning how information about visual features at every spatial scale may be projected upward through successive neuronal layers. We name this hypothetical upward projection of information the "holographic principle." (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Proposed mechanism for learning and memory erasure in a white-noise-driven sleeping cortex.

PubMed

Steyn-Ross, Moira L; Steyn-Ross, D A; Sleigh, J W; Wilson, M T; Wilcocks, Lara C

2005-12-01

Understanding the structure and purpose of sleep remains one of the grand challenges of neurobiology. Here we use a mean-field linearized theory of the sleeping cortex to derive statistics for synaptic learning and memory erasure. The growth in correlated low-frequency high-amplitude voltage fluctuations during slow-wave sleep (SWS) is characterized by a probability density function that becomes broader and shallower as the transition into rapid-eye-movement (REM) sleep is approached. At transition, the Shannon information entropy of the fluctuations is maximized. If we assume Hebbian-learning rules apply to the cortex, then its correlated response to white-noise stimulation during SWS provides a natural mechanism for a synaptic weight change that will tend to shut down reverberant neural activity. In contrast, during REM sleep the weights will evolve in a direction that encourages excitatory activity. These entropy and weight-change predictions lead us to identify the final portion of deep SWS that occurs immediately prior to transition into REM sleep as a time of enhanced erasure of labile memory. We draw a link between the sleeping cortex and Landauer's dissipation theorem for irreversible computing [R. Landauer, IBM J. Res. Devel. 5, 183 (1961)], arguing that because information erasure is an irreversible computation, there is an inherent entropy cost as the cortex transits from SWS into REM sleep.

Proposed mechanism for learning and memory erasure in a white-noise-driven sleeping cortex

NASA Astrophysics Data System (ADS)

Steyn-Ross, Moira L.; Steyn-Ross, D. A.; Sleigh, J. W.; Wilson, M. T.; Wilcocks, Lara C.

2005-12-01

Understanding the structure and purpose of sleep remains one of the grand challenges of neurobiology. Here we use a mean-field linearized theory of the sleeping cortex to derive statistics for synaptic learning and memory erasure. The growth in correlated low-frequency high-amplitude voltage fluctuations during slow-wave sleep (SWS) is characterized by a probability density function that becomes broader and shallower as the transition into rapid-eye-movement (REM) sleep is approached. At transition, the Shannon information entropy of the fluctuations is maximized. If we assume Hebbian-learning rules apply to the cortex, then its correlated response to white-noise stimulation during SWS provides a natural mechanism for a synaptic weight change that will tend to shut down reverberant neural activity. In contrast, during REM sleep the weights will evolve in a direction that encourages excitatory activity. These entropy and weight-change predictions lead us to identify the final portion of deep SWS that occurs immediately prior to transition into REM sleep as a time of enhanced erasure of labile memory. We draw a link between the sleeping cortex and Landauer’s dissipation theorem for irreversible computing [R. Landauer, IBM J. Res. Devel. 5, 183 (1961)], arguing that because information erasure is an irreversible computation, there is an inherent entropy cost as the cortex transits from SWS into REM sleep.

Repeated restraint stress impairs auditory attention and GABAergic synaptic efficacy in the rat auditory cortex.

PubMed

Pérez, Miguel Ángel; Pérez-Valenzuela, Catherine; Rojas-Thomas, Felipe; Ahumada, Juan; Fuenzalida, Marco; Dagnino-Subiabre, Alexies

2013-08-29

Chronic stress induces dendritic atrophy in the rat primary auditory cortex (A1), a key brain area for auditory attention. The aim of this study was to determine whether repeated restraint stress affects auditory attention and synaptic transmission in A1. Male Sprague-Dawley rats were trained in a two-alternative choice task (2-ACT), a behavioral paradigm to study auditory attention in rats. Trained animals that reached a performance over 80% of correct trials in the 2-ACT were randomly assigned to control and restraint stress experimental groups. To analyze the effects of restraint stress on the auditory attention, trained rats of both groups were subjected to 50 2-ACT trials one day before and one day after of the stress period. A difference score was determined by subtracting the number of correct trials after from those before the stress protocol. Another set of rats was used to study the synaptic transmission in A1. Restraint stress decreased the number of correct trials by 28% compared to the performance of control animals (p < 0.001). Furthermore, stress reduced the frequency of spontaneous inhibitory postsynaptic currents (sIPSC) and miniature IPSC in A1, whereas glutamatergic efficacy was not affected. Our results demonstrate that restraint stress decreased auditory attention and GABAergic synaptic efficacy in A1. Copyright © 2013 IBRO. Published by Elsevier Ltd. All rights reserved.

Preclinical and clinical characterization of the selective 5-HT(1A) receptor antagonist DU-125530 for antidepressant treatment.

PubMed

Scorza, M C; Lladó-Pelfort, L; Oller, S; Cortés, R; Puigdemont, D; Portella, M J; Pérez-Egea, R; Alvarez, E; Celada, P; Pérez, V; Artigas, F

2012-11-01

The antidepressant efficacy of selective 5-HT reuptake inhibitors (SSRI) and other 5-HT-enhancing drugs is compromised by a negative feedback mechanism involving 5-HT(1A) autoreceptor activation by the excess 5-HT produced by these drugs in the somatodendritic region of 5-HT neurones. 5-HT(1A) receptor antagonists augment antidepressant-like effects in rodents by preventing this negative feedback, and the mixed β-adrenoceptor/5-HT(1A) receptor antagonist pindolol improves clinical antidepressant effects by preferentially interacting with 5-HT(1A) autoreceptors. However, it is unclear whether 5-HT(1A) receptor antagonists not discriminating between pre- and post-synaptic 5-HT(1A) receptors would be clinically effective. We characterized the pharmacological properties of the 5-HT(1A) receptor antagonist DU-125530 using receptor autoradiography, intracerebral microdialysis and electrophysiological recordings. Its capacity to accelerate/enhance the clinical effects of fluoxetine was assessed in a double-blind, randomized, 6 week placebo-controlled trial in 50 patients with major depression (clinicaltrials.gov identifier NCT01119430). DU-125530 showed equal (low nM) potency to displace agonist and antagonist binding to pre- and post-synaptic 5-HT(1A) receptors in rat and human brain. It antagonized suppression of 5-hydroxytryptaminergic activity evoked by 8-OH-DPAT and SSRIs in vivo. DU-125530 augmented SSRI-induced increases in extracellular 5-HT as effectively as in mice lacking 5-HT(1A) receptors, indicating a silent, maximal occupancy of pre-synaptic 5-HT(1A) receptors at the dose used. However, DU-125530 addition to fluoxetine did not accelerate nor augment its antidepressant effects. DU-125530 is an excellent pre- and post-synaptic 5-HT(1A) receptor antagonist. However, blockade of post-synaptic 5- HT(1A) receptors by DU-125530 cancels benefits obtained by enhancing pre-synaptic 5-hydroxytryptaminergic function. © 2011 The Authors. British Journal of Pharmacology © 2011 The British Pharmacological Society.

Effects of organic selenium on lead-induced impairments of spatial learning and memory as well as synaptic structural plasticity in rats.

PubMed

Han, Xiao-jie; Xiao, Yong-mei; Ai, Bao-min; Hu, Xiao-xia; Wei, Qing; Hu, Qian-sheng

2014-01-01

To study the effect of organic Se on spatial learning and memory deficits induced by Pb exposure at different developmental stages, and its relationship with alterations of synaptic structural plasticity, postnatal rat pups were randomly divided into five groups: Control; Pb (Weaned pups were exposed to Pb at postnatal day (PND) 21-42); Pb-Se (Weaned pups were exposed to Se at PND 43-63 after Pb exposure); maternal Pb (mPb) (Parents were exposed to Pb from 3 weeks before mating to the weaning of pups); mPb-Se (Parents were exposed to Pb and weaned pups were exposed to Se at PND 43-63). The spatial learning and memory of rat pups was measured by Morris water maze (MWM) on PND 63. We found that rat pups in Pb-Se group performed significantly better than those in Pb group (p<0.05). However, there was no significant difference in the ability of spatial learning and memory between the groups of mPb and mPb-Se (p>0.05). We also found that, before MWM, the numbers of neurons and synapses significantly decreased in mPb group, but not in Pb group. After MWM, the number of synapses, the thickness of postsynaptic density (PSD), the length of synaptic active zone and the synaptic curvature increased significantly in Pb-Se and mPb-Se group; while the width of synaptic cleft decreased significantly (p<0.05), compared to Pb group and mPb group, respectively. However, the number of synapses in mPb-Se group was still significantly lower than that in the control group (p<0.05). Our data demonstrated that organic Se had protective effects on the impairments of spatial learning and memory as well as synaptic structural plasticity induced by Pb exposure in rats after weaning, but not by the maternal Pb exposure which reduced the numbers of neurons and synapses in the early neural development.

Synaptic and nonsynaptic plasticity approximating probabilistic inference

PubMed Central

Tully, Philip J.; Hennig, Matthias H.; Lansner, Anders

2014-01-01

Learning and memory operations in neural circuits are believed to involve molecular cascades of synaptic and nonsynaptic changes that lead to a diverse repertoire of dynamical phenomena at higher levels of processing. Hebbian and homeostatic plasticity, neuromodulation, and intrinsic excitability all conspire to form and maintain memories. But it is still unclear how these seemingly redundant mechanisms could jointly orchestrate learning in a more unified system. To this end, a Hebbian learning rule for spiking neurons inspired by Bayesian statistics is proposed. In this model, synaptic weights and intrinsic currents are adapted on-line upon arrival of single spikes, which initiate a cascade of temporally interacting memory traces that locally estimate probabilities associated with relative neuronal activation levels. Trace dynamics enable synaptic learning to readily demonstrate a spike-timing dependence, stably return to a set-point over long time scales, and remain competitive despite this stability. Beyond unsupervised learning, linking the traces with an external plasticity-modulating signal enables spike-based reinforcement learning. At the postsynaptic neuron, the traces are represented by an activity-dependent ion channel that is shown to regulate the input received by a postsynaptic cell and generate intrinsic graded persistent firing levels. We show how spike-based Hebbian-Bayesian learning can be performed in a simulated inference task using integrate-and-fire (IAF) neurons that are Poisson-firing and background-driven, similar to the preferred regime of cortical neurons. Our results support the view that neurons can represent information in the form of probability distributions, and that probabilistic inference could be a functional by-product of coupled synaptic and nonsynaptic mechanisms operating over several timescales. The model provides a biophysical realization of Bayesian computation by reconciling several observed neural phenomena whose functional effects are only partially understood in concert. PMID:24782758

Nicotine Significantly Improves Chronic Stress-Induced Impairments of Cognition and Synaptic Plasticity in Mice.

PubMed

Shang, Xueliang; Shang, Yingchun; Fu, Jingxuan; Zhang, Tao

2017-08-01

The aim of this study was to examine if nicotine was able to improve cognition deficits in a mouse model of chronic mild stress. Twenty-four male C57BL/6 mice were divided into three groups: control, stress, and stress with nicotine treatment. The animal model was established by combining chronic unpredictable mild stress (CUMS) and isolated feeding. Mice were exposed to CUMS continued for 28 days, while nicotine (0.2 mg/kg) was also administrated for 28 days. Weight and sucrose consumption were measured during model establishing period. The anxiety and behavioral despair were analyzed using the forced swim test (FST) and open-field test (OFT). Spatial cognition was evaluated using Morris water maze (MWM) test. Following behavioral assessment, both long-term potentiation (LTP) and depotentiation (DEP) were recorded in the hippocampal dentate gyrus (DG) region. Both synaptic and Notch1 proteins were measured by Western. Nicotine increased stressed mouse's sucrose consumption. The MWM test showed that spatial learning and reversal learning in stressed animals were remarkably affected relative to controls, whereas nicotine partially rescued cognitive functions. Additionally, nicotine considerably alleviated the level of anxiety and the degree of behavioral despair in stressed mice. It effectively mitigated the depression-induced impairment of hippocampal synaptic plasticity, in which both the LTP and DEP were significantly inhibited in stressed mice. Moreover, nicotine enhanced the expression of synaptic and Notch1 proteins in stressed animals. The results suggest that nicotine ameliorates the depression-like symptoms and improves the hippocampal synaptic plasticity closely associated with activating transmembrane ion channel receptors and Notch signaling components. Graphical Abstract ᅟ.

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

PubMed

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.

[Effects of postnatal lambda-cyhalothrin exposure on synaptic proteins in ICR mouse brain].

PubMed

Bao, Xun-Di; Wang, Qu-Nan; Li, Fang-Fang; Chai, Xiao-Yu; Gao, Ye

2011-04-01

To evaluate the influence on the synaptic protein expression in different brain regions of ICR mice after lambda-cyhalothrin (LCT) exposure during postnatal period. Two male and 4 female healthy ICR mice were put in one cage. It was set as pregnancy if vaginal plug was founded. Offspring were divided into 5 groups randomly, and exposed to LCT (0.01% DMSO solution) at the doses of 0.1, 1.0 and 10.0 mg/kg by intragastric rout every other day from postnatal days (PND) 5 to PND13, control animals were treated with normal saline or DMSO by the same route. The brains were removed from pups on PND 14, the synaptic protein expression levels in cortex, hippocampus and striatum were measured by western blot. GFAP levels of cortex and hippocampus in the LCT exposure group increased with doses, as compared with control group (P < 0.05), while Tuj protein expression did not change significantly in the various brain regions of ICR mice. GAP-43 protein expression levels in the LCT exposed mouse hippocampus and in female ICR mouse cortex increased with doses, as compared with control group (P < 0.05). Presynaptic protein (Synapsin I) expression levels did not change obviously in various brain regions. However, postsynaptic density protein 95 (PSD95) expression levels of the hippocampus and striatum in male offspring of 10.0 mg/kg LCT group, of cortex of female LCT groups, and of female offspring in all exposure groups, of striatum, in 1.0 or 10.0 mg/kg LCT exposure groups significantly decreased (P < 0.05). Early postnatal exposure to LCT affects synaptic protein expression. These effects may ultimately affect the construction of synaptic connections.

A biophysical model examining the role of low-voltage-activated potassium currents in shaping the responses of vestibular ganglion neurons.

PubMed

Hight, Ariel E; Kalluri, Radha

2016-08-01

The vestibular nerve is characterized by two broad groups of neurons that differ in the timing of their interspike intervals; some fire at highly regular intervals, whereas others fire at highly irregular intervals. Heterogeneity in ion channel properties has been proposed as shaping these firing patterns (Highstein SM, Politoff AL. Brain Res 150: 182-187, 1978; Smith CE, Goldberg JM. Biol Cybern 54: 41-51, 1986). Kalluri et al. (J Neurophysiol 104: 2034-2051, 2010) proposed that regularity is controlled by the density of low-voltage-activated potassium currents (IKL). To examine the impact of IKL on spike timing regularity, we implemented a single-compartment model with three conductances known to be present in the vestibular ganglion: transient sodium (gNa), low-voltage-activated potassium (gKL), and high-voltage-activated potassium (gKH). Consistent with in vitro observations, removing gKL depolarized resting potential, increased input resistance and membrane time constant, and converted current step-evoked firing patterns from transient (1 spike at current onset) to sustained (many spikes). Modeled neurons were driven with a time-varying synaptic conductance that captured the random arrival times and amplitudes of glutamate-driven synaptic events. In the presence of gKL, spiking occurred only in response to large events with fast onsets. Models without gKL exhibited greater integration by responding to the superposition of rapidly arriving events. Three synaptic conductance were modeled, each with different kinetics to represent a variety of different synaptic processes. In response to all three types of synaptic conductance, models containing gKL produced spike trains with irregular interspike intervals. Only models lacking gKL when driven by rapidly arriving small excitatory postsynaptic currents were capable of generating regular spiking. Copyright © 2016 the American Physiological Society.

Rationale and clinical data supporting nutritional intervention in Alzheimer's disease.

PubMed

Engelborghs, S; Gilles, C; Ivanoiu, A; Vandewoude, M

2014-01-01

Adequate nutrition plays an important role in the maintenance of cognitive function, particularly during aging. Malnutrition is amongst the risk factors for developing mild cognitive impairment (MCI) and Alzheimer's disease (AD). Epidemiological studies have associated deficiencies in some nutrients with a higher risk of cognitive dysfunction and/or AD. Cognitive decline in AD is correlated with synaptic loss and many of the components required to maintain optimal synaptic function are derived from dietary sources. As synapses are part of the neuronal membrane and are continuously being remodelled, the availability of sufficient levels of nutritional precursors (mainly uridine monophosphate, choline and omega-3 fatty acids) to make the phospholipids required to build neuronal membranes may have beneficial effects on synaptic degeneration in AD. In addition, B-vitamins, phospholipids and other micronutrients act as cofactors to enhance the supply of precursors required to make neuronal membranes and synapses. Despite this, no randomized controlled trial has hitherto provided evidence that any single nutrient has a beneficial effect on cognition or lowers the risk for AD. However, a multi-target approach using combinations of (micro)nutrients might have beneficial effects on cognitive function in neurodegenerative brain disorders like AD leading to synaptic degeneration. Here we review the clinical evidence for supplementation, based on a multi-target approach with a focus on key nutrients with a proposed role in synaptic dysfunction. Based on preclinical evidence, a nutrient mixture, Souvenaid(®) (Nutricia N.V., Zoetermeer, The Netherlands) was developed. Clinical trials with Souvenaid(®) have shown improved memory performance in patients with mild AD. Further clinical trials to evaluate the effects of nutritional intervention in MCI and early dementia due to AD are on-going.

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

NASA Astrophysics Data System (ADS)

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.

The Beneficial Effects of Leptin on REM Sleep Deprivation-Induced Cognitive Deficits in Mice

ERIC Educational Resources Information Center

Chang, Hsiao-Fu; Su, Chun-Lin; Chang, Chih-Hua; Chen, Yu-Wen; Gean, Po-Wu

2013-01-01

Leptin, a 167 amino acid peptide, is synthesized predominantly in the adipose tissues and plays a key role in the regulation of food intake and body weight. Recent studies indicate that leptin receptor is expressed with high levels in many brain regions that may regulate synaptic plasticity. Here we show that deprivation of rapid eye movement…

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

PubMed Central

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

2013-01-01

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

Designing Artificial Neural Networks Using Particle Swarm Optimization Algorithms

PubMed Central

Vázquez, Roberto A.

2015-01-01

Artificial Neural Network (ANN) design is a complex task because its performance depends on the architecture, the selected transfer function, and the learning algorithm used to train the set of synaptic weights. In this paper we present a methodology that automatically designs an ANN using particle swarm optimization algorithms such as Basic Particle Swarm Optimization (PSO), Second Generation of Particle Swarm Optimization (SGPSO), and a New Model of PSO called NMPSO. The aim of these algorithms is to evolve, at the same time, the three principal components of an ANN: the set of synaptic weights, the connections or architecture, and the transfer functions for each neuron. Eight different fitness functions were proposed to evaluate the fitness of each solution and find the best design. These functions are based on the mean square error (MSE) and the classification error (CER) and implement a strategy to avoid overtraining and to reduce the number of connections in the ANN. In addition, the ANN designed with the proposed methodology is compared with those designed manually using the well-known Back-Propagation and Levenberg-Marquardt Learning Algorithms. Finally, the accuracy of the method is tested with different nonlinear pattern classification problems. PMID:26221132

Statistical characteristics of climbing fiber spikes necessary for efficient cerebellar learning.

PubMed

Kuroda, S; Yamamoto, K; Miyamoto, H; Doya, K; Kawat, M

2001-03-01

Mean firing rates (MFRs), with analogue values, have thus far been used as information carriers of neurons in most brain theories of learning. However, the neurons transmit the signal by spikes, which are discrete events. The climbing fibers (CFs), which are known to be essential for cerebellar motor learning, fire at the ultra-low firing rates (around 1 Hz), and it is not yet understood theoretically how high-frequency information can be conveyed and how learning of smooth and fast movements can be achieved. Here we address whether cerebellar learning can be achieved by CF spikes instead of conventional MFR in an eye movement task, such as the ocular following response (OFR), and an arm movement task. There are two major afferents into cerebellar Purkinje cells: parallel fiber (PF) and CF, and the synaptic weights between PFs and Purkinje cells have been shown to be modulated by the stimulation of both types of fiber. The modulation of the synaptic weights is regulated by the cerebellar synaptic plasticity. In this study we simulated cerebellar learning using CF signals as spikes instead of conventional MFR. To generate the spikes we used the following four spike generation models: (1) a Poisson model in which the spike interval probability follows a Poisson distribution, (2) a gamma model in which the spike interval probability follows the gamma distribution, (3) a max model in which a spike is generated when a synaptic input reaches maximum, and (4) a threshold model in which a spike is generated when the input crosses a certain small threshold. We found that, in an OFR task with a constant visual velocity, learning was successful with stochastic models, such as Poisson and gamma models, but not in the deterministic models, such as max and threshold models. In an OFR with a stepwise velocity change and an arm movement task, learning could be achieved only in the Poisson model. In addition, for efficient cerebellar learning, the distribution of CF spike-occurrence time after stimulus onset must capture at least the first, second and third moments of the temporal distribution of error signals.

Eigenvalue distributions for a class of covariance matrices with application to Bienenstock-Cooper-Munro neurons under noisy conditions.

PubMed

Bazzani, Armando; Castellani, Gastone C; Cooper, Leon N

2010-05-01

We analyze the effects of noise correlations in the input to, or among, Bienenstock-Cooper-Munro neurons using the Wigner semicircular law to construct random, positive-definite symmetric correlation matrices and compute their eigenvalue distributions. In the finite dimensional case, we compare our analytic results with numerical simulations and show the effects of correlations on the lifetimes of synaptic strengths in various visual environments. These correlations can be due either to correlations in the noise from the input lateral geniculate nucleus neurons, or correlations in the variability of lateral connections in a network of neurons. In particular, we find that for fixed dimensionality, a large noise variance can give rise to long lifetimes of synaptic strengths. This may be of physiological significance.

Synchrony detection and amplification by silicon neurons with STDP synapses.

PubMed

Bofill-i-petit, Adria; Murray, Alan F

2004-09-01

Spike-timing dependent synaptic plasticity (STDP) is a form of plasticity driven by precise spike-timing differences between presynaptic and postsynaptic spikes. Thus, the learning rules underlying STDP are suitable for learning neuronal temporal phenomena such as spike-timing synchrony. It is well known that weight-independent STDP creates unstable learning processes resulting in balanced bimodal weight distributions. In this paper, we present a neuromorphic analog very large scale integration (VLSI) circuit that contains a feedforward network of silicon neurons with STDP synapses. The learning rule implemented can be tuned to have a moderate level of weight dependence. This helps stabilise the learning process and still generates binary weight distributions. From on-chip learning experiments we show that the chip can detect and amplify hierarchical spike-timing synchrony structures embedded in noisy spike trains. The weight distributions of the network emerging from learning are bimodal.

AHaH computing-from metastable switches to attractors to machine learning.

PubMed

Nugent, Michael Alexander; Molter, Timothy Wesley

2014-01-01

Modern computing architecture based on the separation of memory and processing leads to a well known problem called the von Neumann bottleneck, a restrictive limit on the data bandwidth between CPU and RAM. This paper introduces a new approach to computing we call AHaH computing where memory and processing are combined. The idea is based on the attractor dynamics of volatile dissipative electronics inspired by biological systems, presenting an attractive alternative architecture that is able to adapt, self-repair, and learn from interactions with the environment. We envision that both von Neumann and AHaH computing architectures will operate together on the same machine, but that the AHaH computing processor may reduce the power consumption and processing time for certain adaptive learning tasks by orders of magnitude. The paper begins by drawing a connection between the properties of volatility, thermodynamics, and Anti-Hebbian and Hebbian (AHaH) plasticity. We show how AHaH synaptic plasticity leads to attractor states that extract the independent components of applied data streams and how they form a computationally complete set of logic functions. After introducing a general memristive device model based on collections of metastable switches, we show how adaptive synaptic weights can be formed from differential pairs of incremental memristors. We also disclose how arrays of synaptic weights can be used to build a neural node circuit operating AHaH plasticity. By configuring the attractor states of the AHaH node in different ways, high level machine learning functions are demonstrated. This includes unsupervised clustering, supervised and unsupervised classification, complex signal prediction, unsupervised robotic actuation and combinatorial optimization of procedures-all key capabilities of biological nervous systems and modern machine learning algorithms with real world application.

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

PubMed Central

Alemi, Alireza; Baldassi, Carlo; Brunel, Nicolas; Zecchina, Riccardo

2015-01-01

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 number of stored patterns. PMID:26291608

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

PubMed

Alemi, Alireza; Baldassi, Carlo; Brunel, Nicolas; Zecchina, Riccardo

2015-08-01

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 number of stored patterns.

AHaH Computing–From Metastable Switches to Attractors to Machine Learning

PubMed Central

Nugent, Michael Alexander; Molter, Timothy Wesley

2014-01-01

Modern computing architecture based on the separation of memory and processing leads to a well known problem called the von Neumann bottleneck, a restrictive limit on the data bandwidth between CPU and RAM. This paper introduces a new approach to computing we call AHaH computing where memory and processing are combined. The idea is based on the attractor dynamics of volatile dissipative electronics inspired by biological systems, presenting an attractive alternative architecture that is able to adapt, self-repair, and learn from interactions with the environment. We envision that both von Neumann and AHaH computing architectures will operate together on the same machine, but that the AHaH computing processor may reduce the power consumption and processing time for certain adaptive learning tasks by orders of magnitude. The paper begins by drawing a connection between the properties of volatility, thermodynamics, and Anti-Hebbian and Hebbian (AHaH) plasticity. We show how AHaH synaptic plasticity leads to attractor states that extract the independent components of applied data streams and how they form a computationally complete set of logic functions. After introducing a general memristive device model based on collections of metastable switches, we show how adaptive synaptic weights can be formed from differential pairs of incremental memristors. We also disclose how arrays of synaptic weights can be used to build a neural node circuit operating AHaH plasticity. By configuring the attractor states of the AHaH node in different ways, high level machine learning functions are demonstrated. This includes unsupervised clustering, supervised and unsupervised classification, complex signal prediction, unsupervised robotic actuation and combinatorial optimization of procedures–all key capabilities of biological nervous systems and modern machine learning algorithms with real world application. PMID:24520315

Errors in the estimation of the variance: implications for multiple-probability fluctuation analysis.

PubMed

Saviane, Chiara; Silver, R Angus

2006-06-15

Synapses play a crucial role in information processing in the brain. Amplitude fluctuations of synaptic responses can be used to extract information about the mechanisms underlying synaptic transmission and its modulation. In particular, multiple-probability fluctuation analysis can be used to estimate the number of functional release sites, the mean probability of release and the amplitude of the mean quantal response from fits of the relationship between the variance and mean amplitude of postsynaptic responses, recorded at different probabilities. To determine these quantal parameters, calculate their uncertainties and the goodness-of-fit of the model, it is important to weight the contribution of each data point in the fitting procedure. We therefore investigated the errors associated with measuring the variance by determining the best estimators of the variance of the variance and have used simulations of synaptic transmission to test their accuracy and reliability under different experimental conditions. For central synapses, which generally have a low number of release sites, the amplitude distribution of synaptic responses is not normal, thus the use of a theoretical variance of the variance based on the normal assumption is not a good approximation. However, appropriate estimators can be derived for the population and for limited sample sizes using a more general expression that involves higher moments and introducing unbiased estimators based on the h-statistics. Our results are likely to be relevant for various applications of fluctuation analysis when few channels or release sites are present.

Forebrain glutamatergic neurons mediate leptin action on depression-like behaviors and synaptic depression

PubMed Central

Guo, M; Lu, Y; Garza, J C; Li, Y; Chua, S C; Zhang, W; Lu, B; Lu, X-Y

2012-01-01

The glutamatergic system has been implicated in the pathophysiology of depression and the mechanism of action of antidepressants. Leptin, an adipocyte-derived hormone, has antidepressant-like properties. However, the functional role of leptin receptor (Lepr) signaling in glutamatergic neurons remains to be elucidated. In this study, we generated conditional knockout mice in which the long form of Lepr was ablated selectively in glutamatergic neurons located in the forebrain structures, including the hippocampus and prefrontal cortex (Lepr cKO). Lepr cKO mice exhibit normal growth and body weight. Behavioral characterization of Lepr cKO mice reveals depression-like behavioral deficits, including anhedonia, behavioral despair, enhanced learned helplessness and social withdrawal, with no evident signs of anxiety. In addition, loss of Lepr in forebrain glutamatergic neurons facilitates N-methyl--aspartate (NMDA)-induced hippocampal long-term synaptic depression (LTD), whereas conventional LTD or long-term potentiation (LTP) was not affected. The facilitated LTD induction requires activation of the NMDA receptor GluN2B (NR2B) subunit as it was completely blocked by a selective GluN2B antagonist. Moreover, Lepr cKO mice are highly sensitive to the antidepressant-like behavioral effects of the GluN2B antagonist but resistant to leptin. These results support important roles for Lepr signaling in glutamatergic neurons in regulating depression-related behaviors and modulating excitatory synaptic strength, suggesting a possible association between synaptic depression and behavioral manifestation of behavioral depression. PMID:22408745

Unbiased View of Synaptic and Neuronal Gene Complement in Ctenophores: Are There Pan-neuronal and Pan-synaptic Genes across Metazoa?

PubMed

Moroz, Leonid L; Kohn, Andrea B

2015-12-01

Hypotheses of origins and evolution of neurons and synapses are controversial, mostly due to limited comparative data. Here, we investigated the genome-wide distribution of the bilaterian "synaptic" and "neuronal" protein-coding genes in non-bilaterian basal metazoans (Ctenophora, Porifera, Placozoa, and Cnidaria). First, there are no recognized genes uniquely expressed in neurons across all metazoan lineages. None of the so-called pan-neuronal genes such as embryonic lethal abnormal vision (ELAV), Musashi, or Neuroglobin are expressed exclusively in neurons of the ctenophore Pleurobrachia. Second, our comparative analysis of about 200 genes encoding canonical presynaptic and postsynaptic proteins in bilaterians suggests that there are no true "pan-synaptic" genes or genes uniquely and specifically attributed to all classes of synapses. The majority of these genes encode receptive and secretory complexes in a broad spectrum of eukaryotes. Trichoplax (Placozoa) an organism without neurons and synapses has more orthologs of bilaterian synapse-related/neuron-related genes than do ctenophores-the group with well-developed neuronal and synaptic organization. Third, the majority of genes encoding ion channels and ionotropic receptors are broadly expressed in unicellular eukaryotes and non-neuronal tissues in metazoans. Therefore, they cannot be viewed as neuronal markers. Nevertheless, the co-expression of multiple types of ion channels and receptors does correlate with the presence of neural and synaptic organization. As an illustrative example, the ctenophore genomes encode a greater diversity of ion channels and ionotropic receptors compared with the genomes of the placozoan Trichoplax and the demosponge Amphimedon. Surprisingly, both placozoans and sponges have a similar number of orthologs of "synaptic" proteins as we identified in the genomes of two ctenophores. Ctenophores have a distinct synaptic organization compared with other animals. Our analysis of transcriptomes from 10 different ctenophores did not detect recognized orthologs of synthetic enzymes encoding several classical, low-molecular-weight (neuro)transmitters; glutamate signaling machinery is one of the few exceptions. Novel peptidergic signaling molecules were predicted for ctenophores, together with the diversity of putative receptors including SCNN1/amiloride-sensitive sodium channel-like channels, many of which could be examples of a lineage-specific expansion within this group. In summary, our analysis supports the hypothesis of independent evolution of neurons and, as corollary, a parallel evolution of synapses. We suggest that the formation of synaptic machinery might occur more than once over 600 million years of animal evolution. © The Author 2015. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.

Simulation of synaptic short-term plasticity using Ba(CF3SO3)2-doped polyethylene oxide electrolyte film.

PubMed

Chang, C T; Zeng, F; Li, X J; Dong, W S; Lu, S H; Gao, S; Pan, F

2016-01-07

The simulation of synaptic plasticity using new materials is critical in the study of brain-inspired computing. Devices composed of Ba(CF3SO3)2-doped polyethylene oxide (PEO) electrolyte film were fabricated and with pulse responses found to resemble the synaptic short-term plasticity (STP) of both short-term depression (STD) and short-term facilitation (STF) synapses. The values of the charge and discharge peaks of the pulse responses did not vary with input number when the pulse frequency was sufficiently low(~1 Hz). However, when the frequency was increased, the charge and discharge peaks decreased and increased, respectively, in gradual trends and approached stable values with respect to the input number. These stable values varied with the input frequency, which resulted in the depressed and potentiated weight modifications of the charge and discharge peaks, respectively. These electrical properties simulated the high and low band-pass filtering effects of STD and STF, respectively. The simulations were consistent with biological results and the corresponding biological parameters were successfully extracted. The study verified the feasibility of using organic electrolytes to mimic STP.

The Role of Ionotropic Glutamate Receptors in Childhood Neurodevelopmental Disorders: Autism Spectrum Disorders and Fragile X Syndrome

PubMed Central

Uzunova, Genoveva; Hollander, Eric; Shepherd, Jason

2014-01-01

Autism spectrum disorder (ASD) and Fragile X syndrome (FXS) are relatively common childhood neurodevelopmental disorders with increasing incidence in recent years. They are currently accepted as disorders of the synapse with alterations in different forms of synaptic communication and neuronal network connectivity. The major excitatory neurotransmitter system in brain, the glutamatergic system, is implicated in learning and memory, synaptic plasticity, neuronal development. While much attention is attributed to the role of metabotropic glutamate receptors in ASD and FXS, studies indicate that the ionotropic glutamate receptors (iGluRs) and their regulatory proteins are also altered in several brain regions. Role of iGluRs in the neurobiology of ASD and FXS is supported by a weight of evidence that ranges from human genetics to in vitro cultured neurons. In this review we will discuss clinical, molecular, cellular and functional changes in NMDA, AMPA and kainate receptors and the synaptic proteins that regulate them in the context of ASD and FXS. We will also discuss the significance for the development of translational biomarkers and treatments for the core symptoms of ASD and FXS. PMID:24533017

Simulation of synaptic short-term plasticity using Ba(CF3SO3)2-doped polyethylene oxide electrolyte film

PubMed Central

Chang, C. T.; Zeng, F.; Li, X. J.; Dong, W. S.; Lu, S. H.; Gao, S.; Pan, F.

2016-01-01

The simulation of synaptic plasticity using new materials is critical in the study of brain-inspired computing. Devices composed of Ba(CF3SO3)2-doped polyethylene oxide (PEO) electrolyte film were fabricated and with pulse responses found to resemble the synaptic short-term plasticity (STP) of both short-term depression (STD) and short-term facilitation (STF) synapses. The values of the charge and discharge peaks of the pulse responses did not vary with input number when the pulse frequency was sufficiently low(~1 Hz). However, when the frequency was increased, the charge and discharge peaks decreased and increased, respectively, in gradual trends and approached stable values with respect to the input number. These stable values varied with the input frequency, which resulted in the depressed and potentiated weight modifications of the charge and discharge peaks, respectively. These electrical properties simulated the high and low band-pass filtering effects of STD and STF, respectively. The simulations were consistent with biological results and the corresponding biological parameters were successfully extracted. The study verified the feasibility of using organic electrolytes to mimic STP. PMID:26739613

Simulation of synaptic short-term plasticity using Ba(CF3SO3)2-doped polyethylene oxide electrolyte film

NASA Astrophysics Data System (ADS)

Chang, C. T.; Zeng, F.; Li, X. J.; Dong, W. S.; Lu, S. H.; Gao, S.; Pan, F.

2016-01-01

The simulation of synaptic plasticity using new materials is critical in the study of brain-inspired computing. Devices composed of Ba(CF3SO3)2-doped polyethylene oxide (PEO) electrolyte film were fabricated and with pulse responses found to resemble the synaptic short-term plasticity (STP) of both short-term depression (STD) and short-term facilitation (STF) synapses. The values of the charge and discharge peaks of the pulse responses did not vary with input number when the pulse frequency was sufficiently low(~1 Hz). However, when the frequency was increased, the charge and discharge peaks decreased and increased, respectively, in gradual trends and approached stable values with respect to the input number. These stable values varied with the input frequency, which resulted in the depressed and potentiated weight modifications of the charge and discharge peaks, respectively. These electrical properties simulated the high and low band-pass filtering effects of STD and STF, respectively. The simulations were consistent with biological results and the corresponding biological parameters were successfully extracted. The study verified the feasibility of using organic electrolytes to mimic STP.

Ensemble stacking mitigates biases in inference of synaptic connectivity.

PubMed

Chambers, Brendan; Levy, Maayan; Dechery, Joseph B; MacLean, Jason N

2018-01-01

A promising alternative to directly measuring the anatomical connections in a neuronal population is inferring the connections from the activity. We employ simulated spiking neuronal networks to compare and contrast commonly used inference methods that identify likely excitatory synaptic connections using statistical regularities in spike timing. We find that simple adjustments to standard algorithms improve inference accuracy: A signing procedure improves the power of unsigned mutual-information-based approaches and a correction that accounts for differences in mean and variance of background timing relationships, such as those expected to be induced by heterogeneous firing rates, increases the sensitivity of frequency-based methods. We also find that different inference methods reveal distinct subsets of the synaptic network and each method exhibits different biases in the accurate detection of reciprocity and local clustering. To correct for errors and biases specific to single inference algorithms, we combine methods into an ensemble. Ensemble predictions, generated as a linear combination of multiple inference algorithms, are more sensitive than the best individual measures alone, and are more faithful to ground-truth statistics of connectivity, mitigating biases specific to single inference methods. These weightings generalize across simulated datasets, emphasizing the potential for the broad utility of ensemble-based approaches.

Oscillations and chaos in neural networks: an exactly solvable model.

PubMed Central

Wang, L P; Pichler, E E; Ross, J

1990-01-01

We consider a randomly diluted higher-order network with noise, consisting of McCulloch-Pitts neurons that interact by Hebbian-type connections. For this model, exact dynamical equations are derived and solved for both parallel and random sequential updating algorithms. For parallel dynamics, we find a rich spectrum of different behaviors including static retrieving and oscillatory and chaotic phenomena in different parts of the parameter space. The bifurcation parameters include first- and second-order neuronal interaction coefficients and a rescaled noise level, which represents the combined effects of the random synaptic dilution, interference between stored patterns, and additional background noise. We show that a marked difference in terms of the occurrence of oscillations or chaos exists between neural networks with parallel and random sequential dynamics. Images PMID:2251287

Competitive STDP Learning of Overlapping Spatial Patterns.

PubMed

Krunglevicius, Dalius

2015-08-01

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

Learning Reward Uncertainty in the Basal Ganglia

PubMed Central

Bogacz, Rafal

2016-01-01

Learning the reliability of different sources of rewards is critical for making optimal choices. However, despite the existence of detailed theory describing how the expected reward is learned in the basal ganglia, it is not known how reward uncertainty is estimated in these circuits. This paper presents a class of models that encode both the mean reward and the spread of the rewards, the former in the difference between the synaptic weights of D1 and D2 neurons, and the latter in their sum. In the models, the tendency to seek (or avoid) options with variable reward can be controlled by increasing (or decreasing) the tonic level of dopamine. The models are consistent with the physiology of and synaptic plasticity in the basal ganglia, they explain the effects of dopaminergic manipulations on choices involving risks, and they make multiple experimental predictions. PMID:27589489

Light sleep versus slow wave sleep in memory consolidation: a question of global versus local processes?

PubMed

Genzel, Lisa; Kroes, Marijn C W; Dresler, Martin; Battaglia, Francesco P

2014-01-01

Sleep is strongly involved in memory consolidation, but its role remains unclear. 'Sleep replay', the active potentiation of relevant synaptic connections via reactivation of patterns of network activity that occurred during previous experience, has received considerable attention. Alternatively, sleep has been suggested to regulate synaptic weights homeostatically and nonspecifically, thereby improving the signal:noise ratio of memory traces. Here, we reconcile these theories by highlighting the distinction between light and deep nonrapid eye movement (NREM) sleep. Specifically, we draw on recent studies to suggest a link between light NREM and active potentiation, and between deep NREM and homeostatic regulation. This framework could serve as a key for interpreting the physiology of sleep stages and reconciling inconsistencies in terminology in this field. Copyright © 2013 Elsevier Ltd. All rights reserved.

Effects of autoshaping procedures on 3H-8-OH-DPAT-labeled 5-HT1a binding and 125I-LSD-labeled 5-HT2a binding in rat brain.

PubMed

Tomie, Arthur; Di Poce, Jason; Aguado, Allison; Janes, Amy; Benjamin, Daniel; Pohorecky, Larissa

2003-06-13

Effects of experience with Pavlovian autoshaping procedures on lever-press autoshaping conditioned response (CR) performance and 3H-8-OH-DPAT-labeled binding of 5-HT(1a) receptors as well as 125I-LSD-labeled binding of 5-HT(2a) receptors were evaluated in four groups of male Long-Evans hooded rats. Two groups of rats (Group Paired High CR and Group Paired Low CR) received Pavlovian autoshaping procedures wherein the presentation of a lever (conditioned stimulus, CS) was followed by the response-independent presentation of food (unconditioned stimulus, US). Rats in Group Paired High CR (n=12) showed more rapid CR acquisition and higher asymptotic levels of lever-press autoshaping CR performance relative to rats in Group Low CR (n=12). Group Omission (n=9) received autoshaping with an omission contingency, such that performing the lever-press autoshaping CR resulted in the cancellation the food US, while Group Random (n=9) received presentations of lever CS and food US randomly with respect to one another. Though Groups Omission and Random did not differ in lever-press autoshaping CR performance, Group Omission showed significantly lower levels of 3H-8-OH-DPAT-labeled 5-HT(1a) binding in post-synaptic areas (frontal cortex, septum, caudate putamen), as well as significantly higher plasma corticosterone levels than Group Random. In addition, Group Random showed higher levels of 3H-8-OH-DPAT-labeled 5-HT(1a) binding in pre-synaptic somatodendritic autoreceptors on dorsal raphe nucleus relative to each of the other three groups. Autoradiographic analysis of 125I-LSD-labeled 5-HT(2a) receptor binding revealed no significant differences between Groups Paired High CR and Paired Low CR or between Groups Omission and Random in any brain regions.

Death and rebirth of neural activity in sparse inhibitory networks

NASA Astrophysics Data System (ADS)

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.

A single high dose of dexamethasone affects the phosphorylation state of glutamate AMPA receptors in the human limbic system

PubMed Central

Lopes, M W; Leal, R B; Guarnieri, R; Schwarzbold, M L; Hoeller, A; Diaz, A P; Boos, G L; Lin, K; Linhares, M N; Nunes, J C; Quevedo, J; Bortolotto, Z A; Markowitsch, H J; Lightman, S L; Walz, R

2016-01-01

Glucocorticoids (GC) released during stress response exert feedforward effects in the whole brain, but particularly in the limbic circuits that modulates cognition, emotion and behavior. GC are the most commonly prescribed anti-inflammatory and immunosuppressant medication worldwide and pharmacological GC treatment has been paralleled by the high incidence of acute and chronic neuropsychiatric side effects, which reinforces the brain sensitivity for GC. Synapses can be bi-directionally modifiable via potentiation (long-term potentiation, LTP) or depotentiation (long-term depression, LTD) of synaptic transmission efficacy, and the phosphorylation state of Ser831 and Ser845 sites, in the GluA1 subunit of the glutamate AMPA receptors, are a critical event for these synaptic neuroplasticity events. Through a quasi-randomized controlled study, we show that a single high dexamethasone dose significantly reduces in a dose-dependent manner the levels of GluA1-Ser831 phosphorylation in the amygdala resected during surgery for temporal lobe epilepsy. This is the first report demonstrating GC effects on key markers of synaptic neuroplasticity in the human limbic system. The results contribute to understanding how GC affects the human brain under physiologic and pharmacologic conditions. PMID:27959333

Transition to Chaos in Random Neuronal Networks

NASA Astrophysics Data System (ADS)

Kadmon, Jonathan; Sompolinsky, Haim

2015-10-01

Firing patterns in the central nervous system often exhibit strong temporal irregularity and considerable heterogeneity in time-averaged response properties. Previous studies suggested that these properties are the outcome of the intrinsic chaotic dynamics of the neural circuits. Indeed, simplified rate-based neuronal networks with synaptic connections drawn from Gaussian distribution and sigmoidal nonlinearity are known to exhibit chaotic dynamics when the synaptic gain (i.e., connection variance) is sufficiently large. In the limit of an infinitely large network, there is a sharp transition from a fixed point to chaos, as the synaptic gain reaches a critical value. Near the onset, chaotic fluctuations are slow, analogous to the ubiquitous, slow irregular fluctuations observed in the firing rates of many cortical circuits. However, the existence of a transition from a fixed point to chaos in neuronal circuit models with more realistic architectures and firing dynamics has not been established. In this work, we investigate rate-based dynamics of neuronal circuits composed of several subpopulations with randomly diluted connections. Nonzero connections are either positive for excitatory neurons or negative for inhibitory ones, while single neuron output is strictly positive with output rates rising as a power law above threshold, in line with known constraints in many biological systems. Using dynamic mean field theory, we find the phase diagram depicting the regimes of stable fixed-point, unstable-dynamic, and chaotic-rate fluctuations. We focus on the latter and characterize the properties of systems near this transition. We show that dilute excitatory-inhibitory architectures exhibit the same onset to chaos as the single population with Gaussian connectivity. In these architectures, the large mean excitatory and inhibitory inputs dynamically balance each other, amplifying the effect of the residual fluctuations. Importantly, the existence of a transition to chaos and its critical properties depend on the shape of the single-neuron nonlinear input-output transfer function, near firing threshold. In particular, for nonlinear transfer functions with a sharp rise near threshold, the transition to chaos disappears in the limit of a large network; instead, the system exhibits chaotic fluctuations even for small synaptic gain. Finally, we investigate transition to chaos in network models with spiking dynamics. We show that when synaptic time constants are slow relative to the mean inverse firing rates, the network undergoes a transition from fast spiking fluctuations with constant rates to a state where the firing rates exhibit chaotic fluctuations, similar to the transition predicted by rate-based dynamics. Systems with finite synaptic time constants and firing rates exhibit a smooth transition from a regime dominated by stationary firing rates to a regime of slow rate fluctuations. This smooth crossover obeys scaling properties, similar to crossover phenomena in statistical mechanics. The theoretical results are supported by computer simulations of several neuronal architectures and dynamics. Consequences for cortical circuit dynamics are discussed. These results advance our understanding of the properties of intrinsic dynamics in realistic neuronal networks and their functional consequences.

Recruitment and Retention for a Weight Loss Maintenance Trial Involving Weight Loss Prior to Randomization

PubMed Central

Grubber, J. M.; McVay, M. A.; Olsen, M. K.; Bolton, J.; Gierisch, J. M.; Taylor, S. S.; Maciejewski, M. L.; Yancy, W. S.

2016-01-01

Abstract Objective A weight loss maintenance trial involving weight loss prior to randomization is challenging to implement due to the potential for dropout and insufficient weight loss. We examined rates and correlates of non‐initiation, dropout, and insufficient weight loss during a weight loss maintenance trial. Methods The MAINTAIN trial involved a 16‐week weight loss program followed by randomization among participants losing at least 4 kg. Psychosocial measures were administered during a screening visit. Weight was obtained at the first group session and 16 weeks later to determine eligibility for randomization. Results Of 573 patients who screened as eligible, 69 failed to initiate the weight loss program. In adjusted analyses, failure to initiate was associated with lower age, lack of a support person, and less encouragement for making dietary changes. Among participants who initiated, 200 dropped out, 82 lost insufficient weight, and 222 lost sufficient weight for randomization. Compared to losing sufficient weight, dropping out was associated with younger age and tobacco use, whereas losing insufficient weight was associated with non‐White race and controlled motivation for physical activity. Conclusions Studies should be conducted to evaluate strategies to maximize recruitment and retention of subgroups that are less likely to initiate and be retained in weight loss maintenance trials. PMID:28090340

Neither fixed nor random: weighted least squares meta-analysis.

PubMed

Stanley, T D; Doucouliagos, Hristos

2015-06-15

This study challenges two core conventional meta-analysis methods: fixed effect and random effects. We show how and explain why an unrestricted weighted least squares estimator is superior to conventional random-effects meta-analysis when there is publication (or small-sample) bias and better than a fixed-effect weighted average if there is heterogeneity. Statistical theory and simulations of effect sizes, log odds ratios and regression coefficients demonstrate that this unrestricted weighted least squares estimator provides satisfactory estimates and confidence intervals that are comparable to random effects when there is no publication (or small-sample) bias and identical to fixed-effect meta-analysis when there is no heterogeneity. When there is publication selection bias, the unrestricted weighted least squares approach dominates random effects; when there is excess heterogeneity, it is clearly superior to fixed-effect meta-analysis. In practical applications, an unrestricted weighted least squares weighted average will often provide superior estimates to both conventional fixed and random effects. Copyright © 2015 John Wiley & Sons, Ltd.

Schaffer Collateral Inputs to CA1 Excitatory and Inhibitory Neurons Follow Different Connectivity Rules.

PubMed

Kwon, Osung; Feng, Linqing; Druckmann, Shaul; Kim, Jinhyun

2018-05-30

Neural circuits, governed by a complex interplay between excitatory and inhibitory neurons, are the substrate for information processing, and the organization of synaptic connectivity in neural network is an important determinant of circuit function. Here, we analyzed the fine structure of connectivity in hippocampal CA1 excitatory and inhibitory neurons innervated by Schaffer collaterals (SCs) using mGRASP in male mice. Our previous study revealed spatially structured synaptic connectivity between CA3 and CA1 pyramidal cells (PCs). Surprisingly, parvalbumin-positive interneurons (PVs) showed a significantly more random pattern spatial structure. Notably, application of Peters' rule for synapse prediction by random overlap between axons and dendrites enhanced structured connectivity in PCs, but, by contrast, made the connectivity pattern in PVs more random. In addition, PCs in a deep sublayer of striatum pyramidale appeared more highly structured than PCs in superficial layers, and little or no sublayer specificity was found in PVs. Our results show that CA1 excitatory PCs and inhibitory PVs innervated by the same SC inputs follow different connectivity rules. The different organizations of fine scale structured connectivity in hippocampal excitatory and inhibitory neurons provide important insights into the development and functions of neural networks. SIGNIFICANCE STATEMENT Understanding how neural circuits generate behavior is one of the central goals of neuroscience. An important component of this endeavor is the mapping of fine-scale connection patterns that underlie, and help us infer, signal processing in the brain. Here, using our recently developed synapse detection technology (mGRASP and neuTube), we provide detailed profiles of synaptic connectivity in excitatory (CA1 pyramidal) and inhibitory (CA1 parvalbumin-positive) neurons innervated by the same presynaptic inputs (CA3 Schaffer collaterals). Our results reveal that these two types of CA1 neurons follow different connectivity patterns. Our new evidence for differently structured connectivity at a fine scale in hippocampal excitatory and inhibitory neurons provides a better understanding of hippocampal networks and will guide theoretical and experimental studies. Copyright © 2018 the authors 0270-6474/18/385140-13$15.00/0.

Addiction-like synaptic impairments in diet-induced obesity

PubMed Central

Spencer, Sade; Garcia-Keller, Constanza; Spanswick, David C; Lawrence, Andrew John; Simonds, Stephanie Elise; Schwartz, Danielle Joy; Jordan, Kelsey Ann; Jhou, Thomas Clayton; Kalivas, Peter William

2016-01-01

Background There is increasing evidence that the pathological overeating underlying some forms of obesity is compulsive in nature, and therefore contains elements of an addictive disorder. However, direct physiological evidence linking obesity to synaptic plasticity akin to that occurring in addiction is lacking. We sought to establish whether the propensity to diet-induced obesity (DIO) is associated with addictive-like behavior, as well as synaptic impairments in the nucleus accumbens core (NAcore) considered hallmarks of addiction. Methods Sprague-Dawley rats were allowed free access to a palatable diet for 8 weeks then separated by weight gain into DIO prone (OP) and resistant (OR) subgroups. Access to palatable food was then restricted to daily operant self-administration sessions using fixed (FR1, 3 and 5) and progressive ratio (PR) schedules. Subsequently, NAcore brain slices were prepared and we tested for changes in the ratio between AMPA and NMDA currents (AMPA/NMDA) and the ability to exhibit long-term depression (LTD). Results We found that propensity to develop DIO is linked to deficits in the ability to induce LTD in the NAcore, as well as increased potentiation at these synapses as measured by AMPA/NMDA currents. Consistent with these impairments, we observed addictive-like behavior in OP rats, including i) heightened motivation for palatable food (ii) excessive intake and (iii) increased food-seeking when food was unavailable. Conclusions Our results show overlap between the propensity for DIO and the synaptic changes associated with facets of addictive behavior, supporting partial coincident neurological underpinnings for compulsive overeating and drug addiction. PMID:26826876

Learning and memory disabilities in IUGR babies: Functional and molecular analysis in a rat model.

PubMed

Camprubí Camprubí, Marta; Balada Caballé, Rafel; Ortega Cano, Juan A; Ortega de la Torre, Maria de Los Angeles; Duran Fernández-Feijoo, Cristina; Girabent-Farrés, Montserrat; Figueras-Aloy, Josep; Krauel, Xavier; Alcántara, Soledad

2017-03-01

1Intrauterine growth restriction (IUGR) is the failure of the fetus to achieve its inherent growth potential, and it has frequently been associated with neurodevelopmental problems in childhood. Neurological disorders are mostly associated with IUGR babies with an abnormally high cephalization index (CI) and a brain sparing effect. However, a similar correlation has never been demonstrated in an animal model. The aim of this study was to determine the correlations between CI, functional deficits in learning and memory and alterations in synaptic proteins in a rat model of IUGR. 2Utero-placental insufficiency was induced by meso-ovarian vessel cauterization (CMO) in pregnant rats at embryonic day 17 (E17). Learning performance in an aquatic learning test was evaluated 25 days after birth and during 10 days. Some synaptic proteins were analyzed (PSD95, Synaptophysin) by Western blot and immunohistochemistry. 3Placental insufficiency in CMO pups was associated with spatial memory deficits, which are correlated with a CI above the normal range. CMO pups presented altered levels of synaptic proteins PSD95 and synaptophysin in the hippocampus. 4The results of this study suggest that learning disabilities may be associated with altered development of excitatory neurotransmission and synaptic plasticity. Although interspecific differences in fetal response to placental insufficiency should be taken into account, the translation of these data to humans suggest that both IUGR babies and babies with a normal birth weight but with intrauterine Doppler alterations and abnormal CI should be closely followed to detect neurodevelopmental alterations during the postnatal period.

FPGA Implementation of Generalized Hebbian Algorithm for Texture Classification

PubMed Central

Lin, Shiow-Jyu; Hwang, Wen-Jyi; Lee, Wei-Hao

2012-01-01

This paper presents a novel hardware architecture for principal component analysis. The architecture is based on the Generalized Hebbian Algorithm (GHA) because of its simplicity and effectiveness. The architecture is separated into three portions: the weight vector updating unit, the principal computation unit and the memory unit. In the weight vector updating unit, the computation of different synaptic weight vectors shares the same circuit for reducing the area costs. To show the effectiveness of the circuit, a texture classification system based on the proposed architecture is physically implemented by Field Programmable Gate Array (FPGA). It is embedded in a System-On-Programmable-Chip (SOPC) platform for performance measurement. Experimental results show that the proposed architecture is an efficient design for attaining both high speed performance and low area costs. PMID:22778640

Asymmetric Operation of the Locomotor Central Pattern Generator in the Neonatal Mouse Spinal Cord

PubMed Central

Endo, Toshiaki; Kiehn, Ole

2008-01-01

The rhythmic voltage oscillations in motor neurons (MNs) during locomotor movements reflect the operation of the pre-MN central pattern generator (CPG) network. Recordings from MNs can thus be used as a method to deduct the organization of CPGs. Here, we use continuous conductance measurements and decomposition methods to quantitatively assess the weighting and phase tuning of synaptic inputs to different flexor and extensor MNs during locomotor-like activity in the isolated neonatal mice lumbar spinal cord preparation. Whole cell recordings were obtained from 22 flexor and 18 extensor MNs in rostral and caudal lumbar segments. In all flexor and the large majority of extensor MNs the extracted excitatory and inhibitory synaptic conductances alternate but with a predominance of inhibitory conductances, most pronounced in extensors. These conductance changes are consistent with a “push–pull” operation of locomotor CPG. The extracted excitatory and inhibitory synaptic conductances varied between 2 and 56% of the mean total conductance. Analysis of the phase tuning of the extracted synaptic conductances in flexor and extensor MNs in the rostral lumbar cord showed that the flexor-phase–related synaptic conductance changes have sharper locomotor-phase tuning than the extensor-phase–related conductances, suggesting a modular organization of premotor CPG networks consisting of reciprocally coupled, but differently composed, flexor and extensor CPG networks. There was a clear difference between phase tuning in rostral and caudal MNs, suggesting a distinct operation of CPG networks in different lumbar segments. The highly asymmetric features were preserved throughout all ranges of locomotor frequencies investigated and with different combinations of locomotor-inducing drugs. The asymmetric nature of CPG operation and phase tuning of the conductance profiles provide important clues to the organization of the rodent locomotor CPG and are compatible with a multilayered and distributed structure of the network. PMID:18829847

The morphological characteristics of corticostriatal and thalamostriatal neurons and their intrastriatal terminals in rats.

PubMed

Liu, Bingbing; Ouyang, Lisi; Mu, Shuhua; Zhu, Yaxi; Li, Keyi; Zhan, Mali; Liu, Zongwei; Jia, Yu; Lei, Wanlong

2011-11-01

The glutamatergic projection from the cerebral cortex and the thalamus extensively innervates the neostriatal neurons. However, some conflicts in the published literatures about cortical and thalamic intrastriatal synaptic terminals still need to be resolved. The present study intends to further elucidate the morphological characteristics of these two types of the terminals and their neurons. The corticostriatal and thalamostriatal terminals were immunolabeled for vesicular glutamate transporter type 1 (VGluT1) and 2 (VGluT2), respectively, and their neurons were retrograde labeled by biotinylated dextran amine 3,000 molecular weight (BDA3k) injection into the dorsolateral striatum of rats. The characteristics of the corticostriatal and thalamostriatal terminals were observed at the LM and EM levels, and the data were statistically analyzed with SPSS10.0 software. We observed that 63.53% of VGluT1+ terminals synapsed on dendritic spines, which was different from VGluT2+ terminals with the equal percentage of synapses on spines and dendrites (14.88 and 17.86%, respectively). Notably, VGluT1+ axospinous synaptic terminals were remarkably larger than VGluT2+ axospinous synaptic terminals. Terminal size-frequency distribution analysis showed that VGluT1+ terminals were within the size ranges of 0.4-0.5 and 0.8-0.9 μm, and VGluT2+ terminals were in the ranges of 0.4-0.5 and 0.6-0.7 μm. Perforated-postsynaptic densities (-PSDs) were more frequently found in VGluT1+ axospinous synaptic terminals than in VGluT2+ axospinous terminals. Furthermore, BDA3k-labeled corticostrital neurons were larger in perikaryal diameter than the thalamostriatal neurons, and they were also categorized as the two main populations based on their size-frequency distribution. The morphological characteristics of corticostriatal and thalamostriatal terminals and neurons have implications for understanding the roles of synaptic plasticity in adaptive motor control by the basal ganglia, and they have facilitations for understanding the complexities of basal ganglia function.

Myostatin-like proteins regulate synaptic function and neuronal morphology.

PubMed

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.

The modeling and simulation of visuospatial working memory

PubMed Central

Liang, Lina; Zhang, Zhikang

2010-01-01

Camperi and Wang (Comput Neurosci 5:383–405, 1998) presented a network model for working memory that combines intrinsic cellular bistability with the recurrent network architecture of the neocortex. While Fall and Rinzel (Comput Neurosci 20:97–107, 2006) replaced this intrinsic bistability with a biological mechanism-Ca2+ release subsystem. In this study, we aim to further expand the above work. We integrate the traditional firing-rate network with Ca2+ subsystem-induced bistability, amend the synaptic weights and suggest that Ca2+ concentration only increase the efficacy of synaptic input but has nothing to do with the external input for the transient cue. We found that our network model maintained the persistent activity in response to a brief transient stimulus like that of the previous two models and the working memory performance was resistant to noise and distraction stimulus if Ca2+ subsystem was tuned to be bistable. PMID:22132045

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

PubMed

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.

The cortical structure of consolidated memory: a hypothesis on the role of the cingulate-entorhinal cortical connection.

PubMed

Insel, Nathan; Takehara-Nishiuchi, Kaori

2013-11-01

Daily experiences are represented by networks of neurons distributed across the neocortex, bound together for rapid storage and later retrieval by the hippocampus. While the hippocampus is necessary for retrieving recent episode-based memory associations, over time, consolidation processes take place that enable many of these associations to be expressed independent of the hippocampus. It is generally thought that mechanisms of consolidation involve synaptic weight changes between cortical regions; or, in other words, the formation of "horizontal" cortico-cortical connections. Here, we review anatomical, behavioral, and physiological data which suggest that the connections in and between the entorhinal and cingulate cortices may be uniquely important for the long-term storage of memories that initially depend on the hippocampus. We propose that current theories of consolidation that divide memory into dual systems of hippocampus and neocortex might be improved by introducing a third, middle layer of entorhinal and cingulate allocortex, the synaptic weights within which are necessary and potentially sufficient for maintaining initially hippocampus-dependent associations over long time periods. This hypothesis makes a number of still untested predictions, and future experiments designed to address these will help to fill gaps in the current understanding of the cortical structure of consolidated memory. Copyright © 2013 Elsevier Inc. All rights reserved.

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

PubMed

Hoshino, Osamu

2015-06-01

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

Autism-Associated Insertion Mutation (InsG) of Shank3 Exon 21 Causes Impaired Synaptic Transmission and Behavioral Deficits

PubMed Central

Speed, Haley E.; Kouser, Mehreen; Xuan, Zhong; Reimers, Jeremy M.; Ochoa, Christine F.; Gupta, Natasha; Liu, Shunan

2015-01-01

SHANK3 (also known as PROSAP2) is a postsynaptic scaffolding protein at excitatory synapses in which mutations and deletions have been implicated in patients with idiopathic autism, Phelan–McDermid (aka 22q13 microdeletion) syndrome, and other neuropsychiatric disorders. In this study, we have created a novel mouse model of human autism caused by the insertion of a single guanine nucleotide into exon 21 (Shank3G). The resulting frameshift causes a premature STOP codon and loss of major higher molecular weight Shank3 isoforms at the synapse. Shank3G/G mice exhibit deficits in hippocampus-dependent spatial learning, impaired motor coordination, altered response to novelty, and sensory processing deficits. At the cellular level, Shank3G/G mice also exhibit impaired hippocampal excitatory transmission and plasticity as well as changes in baseline NMDA receptor-mediated synaptic responses. This work identifies clear alterations in synaptic function and behavior in a novel, genetically accurate mouse model of autism mimicking an autism-associated insertion mutation. Furthermore, these findings lay the foundation for future studies aimed to validate and study region-selective and temporally selective genetic reversal studies in the Shank3G/G mouse that was engineered with such future experiments in mind. PMID:26134648

Effect of canola oil consumption on memory, synapse and neuropathology in the triple transgenic mouse model of Alzheimer's disease.

PubMed

Lauretti, Elisabetta; Praticò, Domenico

2017-12-07

In recent years consumption of canola oil has increased due to lower cost compared with olive oil and the perception that it shares its health benefits. However, no data are available on the effect of canola oil intake on Alzheimer's disease (AD) pathogenesis. Herein, we investigated the effect of chronic daily consumption of canola oil on the phenotype of a mouse model of AD that develops both plaques and tangles (3xTg). To this end mice received either regular chow or a chow diet supplemented with canola oil for 6 months. At this time point we found that chronic exposure to the canola-rich diet resulted in a significant increase in body weight and impairments in their working memory together with decrease levels of post-synaptic density protein-95, a marker of synaptic integrity, and an increase in the ratio of insoluble Aβ 42/40. No significant changes were observed in tau phosphorylation and neuroinflammation. Taken together, our findings do not support a beneficial effect of chronic canola oil consumption on two important aspects of AD pathophysiology which includes memory impairments as well as synaptic integrity. While more studies are needed, our data do not justify the current trend aimed at replacing olive oil with canola oil.

SUMO1 Affects Synaptic Function, Spine Density and Memory

PubMed Central

Matsuzaki, Shinsuke; Lee, Linda; Knock, Erin; Srikumar, Tharan; Sakurai, Mikako; Hazrati, Lili-Naz; Katayama, Taiichi; Staniszewski, Agnieszka; Raught, Brian; Arancio, Ottavio; Fraser, Paul E.

2015-01-01

Small ubiquitin-like modifier-1 (SUMO1) plays a number of roles in cellular events and recent evidence has given momentum for its contributions to neuronal development and function. Here, we have generated a SUMO1 transgenic mouse model with exclusive overexpression in neurons in an effort to identify in vivo conjugation targets and the functional consequences of their SUMOylation. A high-expressing line was examined which displayed elevated levels of mono-SUMO1 and increased high molecular weight conjugates in all brain regions. Immunoprecipitation of SUMOylated proteins from total brain extract and proteomic analysis revealed ~95 candidate proteins from a variety of functional classes, including a number of synaptic and cytoskeletal proteins. SUMO1 modification of synaptotagmin-1 was found to be elevated as compared to non-transgenic mice. This observation was associated with an age-dependent reduction in basal synaptic transmission and impaired presynaptic function as shown by altered paired pulse facilitation, as well as a decrease in spine density. The changes in neuronal function and morphology were also associated with a specific impairment in learning and memory while other behavioral features remained unchanged. These findings point to a significant contribution of SUMO1 modification on neuronal function which may have implications for mechanisms involved in mental retardation and neurodegeneration. PMID:26022678

Specific multi-nutrient enriched diet enhances hippocampal cholinergic transmission in aged rats.

PubMed

Cansev, Mehmet; van Wijk, Nick; Turkyilmaz, Mesut; Orhan, Fulya; Sijben, John W C; Broersen, Laus M

2015-01-01

Fortasyn Connect (FC) is a specific nutrient combination designed to target synaptic dysfunction in Alzheimer's disease by providing neuronal membrane precursors and other supportive nutrients. The aim of the present study was to investigate the effects of FC on hippocampal cholinergic neurotransmission in association with its effects on synaptic membrane formation in aged rats. Eighteen-month-old male Wistar rats were randomized to receive a control diet for 4 weeks or an FC-enriched diet for 4 or 6 weeks. At the end of the dietary treatments, acetylcholine (ACh) release was investigated by in vivo microdialysis in the right hippocampi. On completion of microdialysis studies, the rats were sacrificed, and the left hippocampi were obtained to determine the levels of choline, ACh, membrane phospholipids, synaptic proteins, and choline acetyltransferase. Our results revealed that supplementation with FC diet for 4 or 6 weeks, significantly enhanced basal and stimulated hippocampal ACh release and ACh tissue levels, along with levels of phospholipids. Feeding rats the FC diet for 6 weeks significantly increased the levels of choline acetyltransferase, the presynaptic marker Synapsin-1, and the postsynaptic marker PSD-95, but decreased levels of Nogo-A, a neurite outgrowth inhibitor. These data show that the FC diet enhances hippocampal cholinergic neurotransmission in aged rats and suggest that this effect is mediated by enhanced synaptic membrane formation. These data provide further insight into cellular and molecular mechanisms by which FC may support memory processes in Alzheimer's disease. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

D2 receptor genotype and striatal dopamine signaling predict motor cortical activity and behavior in humans.

PubMed

Fazio, Leonardo; Blasi, Giuseppe; Taurisano, Paolo; Papazacharias, Apostolos; Romano, Raffaella; Gelao, Barbara; Ursini, Gianluca; Quarto, Tiziana; Lo Bianco, Luciana; Di Giorgio, Annabella; Mancini, Marina; Popolizio, Teresa; Rubini, Giuseppe; Bertolino, Alessandro

2011-02-14

Pre-synaptic D2 receptors regulate striatal dopamine release and DAT activity, key factors for modulation of motor pathways. A functional SNP of DRD2 (rs1076560 G>T) is associated with alternative splicing such that the relative expression of D2S (mainly pre-synaptic) vs. D2L (mainly post-synaptic) receptor isoforms is decreased in subjects with the T allele with a putative increase of striatal dopamine levels. To evaluate how DRD2 genotype and striatal dopamine signaling predict motor cortical activity and behavior in humans, we have investigated the association of rs1076560 with BOLD fMRI activity during a motor task. To further evaluate the relationship of this circuitry with dopamine signaling, we also explored the correlation between genotype based differences in motor brain activity and pre-synaptic striatal DAT binding measured with [(123)I] FP-CIT SPECT. Fifty healthy subjects, genotyped for DRD2 rs1076560 were studied with BOLD-fMRI at 3T while performing a visually paced motor task with their right hand; eleven of these subjects also underwent [(123)I]FP-CIT SPECT. SPM5 random-effects models were used for statistical analyses. Subjects carrying the T allele had greater BOLD responses in left basal ganglia, thalamus, supplementary motor area, and primary motor cortex, whose activity was also negatively correlated with reaction time at the task. Moreover, left striatal DAT binding and activity of left supplementary motor area were negatively correlated. The present results suggest that DRD2 genetic variation was associated with focusing of responses in the whole motor network, in which activity of predictable nodes was correlated with reaction time and with striatal pre-synaptic dopamine signaling. Our results in humans may help shed light on genetic risk for neurobiological mechanisms involved in the pathophysiology of disorders with dysregulation of striatal dopamine like Parkinson's disease. Copyright © 2010 Elsevier Inc. All rights reserved.

Effects of exercise intensity on spatial memory performance and hippocampal synaptic plasticity in transient brain ischemic rats.

PubMed

Shih, Pei-Cheng; Yang, Yea-Ru; Wang, Ray-Yau

2013-01-01

Memory impairment is commonly noted in stroke survivors, and can lead to delay of functional recovery. Exercise has been proved to improve memory in adult healthy subjects. Such beneficial effects are often suggested to relate to hippocampal synaptic plasticity, which is important for memory processing. Previous evidence showed that in normal rats, low intensity exercise can improve synaptic plasticity better than high intensity exercise. However, the effects of exercise intensities on hippocampal synaptic plasticity and spatial memory after brain ischemia remain unclear. In this study, we investigated such effects in brain ischemic rats. The middle cerebral artery occlusion (MCAO) procedure was used to induce brain ischemia. After the MCAO procedure, rats were randomly assigned to sedentary (Sed), low-intensity exercise (Low-Ex), or high-intensity exercise (High-Ex) group. Treadmill training began from the second day post MCAO procedure, 30 min/day for 14 consecutive days for the exercise groups. The Low-Ex group was trained at the speed of 8 m/min, while the High-Ex group at the speed of 20 m/min. The spatial memory, hippocampal brain-derived neurotrophic factor (BDNF), synapsin-I, postsynaptic density protein 95 (PSD-95), and dendritic structures were examined to document the effects. Serum corticosterone level was also quantified as stress marker. Our results showed the Low-Ex group, but not the High-Ex group, demonstrated better spatial memory performance than the Sed group. Dendritic complexity and the levels of BDNF and PSD-95 increased significantly only in the Low-Ex group as compared with the Sed group in bilateral hippocampus. Notably, increased level of corticosterone was found in the High-Ex group, implicating higher stress response. In conclusion, after brain ischemia, low intensity exercise may result in better synaptic plasticity and spatial memory performance than high intensity exercise; therefore, the intensity is suggested to be considered during exercise training.

Understanding the gradual reset in Pt/Al2O3/Ni RRAM for synaptic applications

NASA Astrophysics Data System (ADS)

Sarkar, Biplab; Lee, Bongmook; Misra, Veena

2015-10-01

In this work, a study has been performed to understand the gradual reset in Al2O3 resistive random-access memory (RRAM). Concentration of vacancies created during the forming or set operation is found to play a major role in the reset mechanism. The reset was observed to be gradual when a significantly higher number of vacancies are created in the dielectric during the set event. The vacancy concentration inside the dielectric was increased using a multi-step forming method which resulted in a diffusion-dominated gradual filament dissolution during the reset in Al2O3 RRAM. The gradual dissolution of the filament allows one to control the conductance of the dielectric during the reset. RRAM devices with gradual reset show excellent endurance and retention for multi-bit storage. Finally, the conductance modulation characteristics realizing synaptic learning are also confirmed in the RRAM.

Memory replay in balanced recurrent networks

PubMed Central

Chenkov, Nikolay; Sprekeler, Henning; Kempter, Richard

2017-01-01

Complex patterns of neural activity appear during up-states in the neocortex and sharp waves in the hippocampus, including sequences that resemble those during prior behavioral experience. The mechanisms underlying this replay are not well understood. How can small synaptic footprints engraved by experience control large-scale network activity during memory retrieval and consolidation? We hypothesize that sparse and weak synaptic connectivity between Hebbian assemblies are boosted by pre-existing recurrent connectivity within them. To investigate this idea, we connect sequences of assemblies in randomly connected spiking neuronal networks with a balance of excitation and inhibition. Simulations and analytical calculations show that recurrent connections within assemblies allow for a fast amplification of signals that indeed reduces the required number of inter-assembly connections. Replay can be evoked by small sensory-like cues or emerge spontaneously by activity fluctuations. Global—potentially neuromodulatory—alterations of neuronal excitability can switch between network states that favor retrieval and consolidation. PMID:28135266

Souvenaid reduces behavioral deficits and improves social cognition skills in frontotemporal dementia: a proof-of-concept study.

PubMed

Pardini, Matteo; Serrati, Carlo; Guida, Silvia; Mattei, Chiara; Abate, Lucia; Massucco, Davide; Sassos, Davide; Amore, Mario; Krueger, Frank; Cocito, Leonardo; Emberti Gialloreti, Leonardo

2015-01-01

Souvenaid™ is a nutraceutical compound thought to positively enhance synaptic function. In line with this mechanism of action, Souvenaid™ has been shown to improve cognitive function in subjects with mild Alzheimer's disease in randomized clinical trials. To date, however, the potential of Souvenaid™ to improve cognitive functioning in subjects with other neurodegenerative conditions also characterized by synaptic loss has not been explored. To evaluate the impact of Souvenaid™ on executive functions, social cognition and behavioral disturbances in subjects with the behavioral variant of frontotemporal dementia (bv-FTD). Twenty-six subjects with bv-FTD were enrolled in the study and randomized to Souvenaid™ (125 ml/day) or placebo groups. After 12 weeks, subjects were switched between the two groups. All subjects, blinded to treatment, underwent clinical and cognitive evaluations at enrollment, after 12 weeks and after 24 weeks. Treatment with Souvenaid™ was associated with a significant reduction of behavioral symptoms and an increase in Theory of Mind skills compared to placebo, which both returned to baseline when Souvenaid™ was discontinued. Souvenaid™ did not have an effect on executive functions. Our results provide evidence of the potential of Souvenaid™ therapy for the treatment of behavioral disturbances and social cognition skills in FTD. © 2015 S. Karger AG, Basel.

Non-random nature of spontaneous mIPSCs in mouse auditory brainstem neurons revealed by recurrence quantification analysis

PubMed Central

Leao, Richardson N; Leao, Fabricio N; Walmsley, Bruce

2005-01-01

A change in the spontaneous release of neurotransmitter is a useful indicator of processes occurring within presynaptic terminals. Linear techniques (e.g. Fourier transform) have been used to analyse spontaneous synaptic events in previous studies, but such methods are inappropriate if the timing pattern is complex. We have investigated spontaneous glycinergic miniature synaptic currents (mIPSCs) in principal cells of the medial nucleus of the trapezoid body. The random versus deterministic (or periodic) nature of mIPSCs was assessed using recurrence quantification analysis. Nonlinear methods were then used to quantify any detected determinism in spontaneous release, and to test for chaotic or fractal patterns. Modelling demonstrated that this procedure is much more sensitive in detecting periodicities than conventional techniques. mIPSCs were found to exhibit periodicities that were abolished by blockade of internal calcium stores with ryanodine, suggesting calcium oscillations in the presynaptic inhibitory terminals. Analysis indicated that mIPSC occurrences were chaotic in nature. Furthermore, periodicities were less evident in congenitally deaf mice than in normal mice, indicating that appropriate neural activity during development is necessary for the expression of deterministic chaos in mIPSC patterns. We suggest that chaotic oscillations of mIPSC occurrences play a physiological role in signal processing in the auditory brainstem. PMID:16271982

Promoting Healthy Weight with "Stability Skills First": A Randomized Trial

ERIC Educational Resources Information Center

Kiernan, Michaela; Brown, Susan D.; Schoffman, Danielle E.; Lee, Katherine; King, Abby C.; Taylor, C. Barr; Schleicher, Nina C.; Perri, Michael G.

2013-01-01

Objective: Although behavioral weight-loss interventions produce short-term weight loss, long-term maintenance remains elusive. This randomized trial examined whether learning a novel set of "stability skills" before losing weight improved long-term weight management. Stability skills were designed to optimize individuals' current…

Cascaded VLSI Chips Help Neural Network To Learn

NASA Technical Reports Server (NTRS)

Duong, Tuan A.; Daud, Taher; Thakoor, Anilkumar P.

1993-01-01

Cascading provides 12-bit resolution needed for learning. Using conventional silicon chip fabrication technology of VLSI, fully connected architecture consisting of 32 wide-range, variable gain, sigmoidal neurons along one diagonal and 7-bit resolution, electrically programmable, synaptic 32 x 31 weight matrix implemented on neuron-synapse chip. To increase weight nominally from 7 to 13 bits, synapses on chip individually cascaded with respective synapses on another 32 x 32 matrix chip with 7-bit resolution synapses only (without neurons). Cascade correlation algorithm varies number of layers effectively connected into network; adds hidden layers one at a time during learning process in such way as to optimize overall number of neurons and complexity and configuration of network.

Weight maintenance and additional weight loss with liraglutide after low-calorie-diet-induced weight loss: the SCALE Maintenance randomized study.

PubMed

Wadden, T A; Hollander, P; Klein, S; Niswender, K; Woo, V; Hale, P M; Aronne, L

2013-11-01

Liraglutide, a once-daily human glucagon-like peptide-1 analog, induced clinically meaningful weight loss in a phase 2 study in obese individuals without diabetes. The present randomized phase 3 trial assessed the efficacy of liraglutide in maintaining weight loss achieved with a low-calorie diet (LCD). Obese/overweight participants (≥18 years, body mass index ≥30 kg m(-2) or ≥27 kg m(-2) with comorbidities) who lost ≥5% of initial weight during a LCD run-in were randomly assigned to liraglutide 3.0 mg per day or placebo (subcutaneous administration) for 56 weeks. Diet and exercise counseling were provided throughout the trial. Co-primary end points were percentage weight change from randomization, the proportion of participants that maintained the initial ≥5% weight loss, and the proportion that lost ≥5% of randomization weight (intention-to-treat analysis). ClinicalTrials.gov identifier: NCT00781937. Participants (n=422) lost a mean 6.0% (s.d. 0.9) of screening weight during run-in. From randomization to week 56, weight decreased an additional mean 6.2% (s.d. 7.3) with liraglutide and 0.2% (s.d. 7.0) with placebo (estimated difference -6.1% (95% class intervals -7.5 to -4.6), P<0.0001). More participants receiving liraglutide (81.4%) maintained the ≥5% run-in weight loss, compared with those receiving placebo (48.9%) (estimated odds ratio 4.8 (3.0; 7.7), P<0.0001), and 50.5% versus 21.8% of participants lost ≥5% of randomization weight (estimated odds ratio 3.9 (2.4; 6.1), P<0.0001). Liraglutide produced small but statistically significant improvements in several cardiometabolic risk factors compared with placebo. Gastrointestinal (GI) disorders were reported more frequently with liraglutide than placebo, but most events were transient, and mild or moderate in severity. Liraglutide, with diet and exercise, maintained weight loss achieved by caloric restriction and induced further weight loss over 56 weeks. Improvements in some cardiovascular disease-risk factors were also observed. Liraglutide, prescribed as 3.0 mg per day, holds promise for improving the maintenance of lost weight.

Short-Term Memory Trace in Rapidly Adapting Synapses of Inferior Temporal Cortex

PubMed Central

Sugase-Miyamoto, Yasuko; Liu, Zheng; Wiener, Matthew C.; Optican, Lance M.; Richmond, Barry J.

2008-01-01

Visual short-term memory tasks depend upon both the inferior temporal cortex (ITC) and the prefrontal cortex (PFC). Activity in some neurons persists after the first (sample) stimulus is shown. This delay-period activity has been proposed as an important mechanism for working memory. In ITC neurons, intervening (nonmatching) stimuli wipe out the delay-period activity; hence, the role of ITC in memory must depend upon a different mechanism. Here, we look for a possible mechanism by contrasting memory effects in two architectonically different parts of ITC: area TE and the perirhinal cortex. We found that a large proportion (80%) of stimulus-selective neurons in area TE of macaque ITCs exhibit a memory effect during the stimulus interval. During a sequential delayed matching-to-sample task (DMS), the noise in the neuronal response to the test image was correlated with the noise in the neuronal response to the sample image. Neurons in perirhinal cortex did not show this correlation. These results led us to hypothesize that area TE contributes to short-term memory by acting as a matched filter. When the sample image appears, each TE neuron captures a static copy of its inputs by rapidly adjusting its synaptic weights to match the strength of their individual inputs. Input signals from subsequent images are multiplied by those synaptic weights, thereby computing a measure of the correlation between the past and present inputs. The total activity in area TE is sufficient to quantify the similarity between the two images. This matched filter theory provides an explanation of what is remembered, where the trace is stored, and how comparison is done across time, all without requiring delay period activity. Simulations of a matched filter model match the experimental results, suggesting that area TE neurons store a synaptic memory trace during short-term visual memory. PMID:18464917

Supervised Learning in Spiking Neural Networks for Precise Temporal Encoding

PubMed Central

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. PMID:27532262

Supervised Learning in Spiking Neural Networks for Precise Temporal Encoding.

PubMed

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.

Addiction-like Synaptic Impairments in Diet-Induced Obesity.

PubMed

Brown, Robyn Mary; Kupchik, Yonatan Michael; Spencer, Sade; Garcia-Keller, Constanza; Spanswick, David C; Lawrence, Andrew John; Simonds, Stephanie Elise; Schwartz, Danielle Joy; Jordan, Kelsey Ann; Jhou, Thomas Clayton; Kalivas, Peter William

2017-05-01

There is increasing evidence that the pathological overeating underlying some forms of obesity is compulsive in nature and therefore contains elements of an addictive disorder. However, direct physiological evidence linking obesity to synaptic plasticity akin to that occurring in addiction is lacking. We sought to establish whether the propensity to diet-induced obesity (DIO) is associated with addictive-like behavior, as well as synaptic impairments in the nucleus accumbens core considered hallmarks of addiction. Sprague Dawley rats were allowed free access to a palatable diet for 8 weeks then separated by weight gain into DIO-prone and DIO-resistant subgroups. Access to palatable food was then restricted to daily operant self-administration sessions using fixed ratio 1, 3, and 5 and progressive ratio schedules. Subsequently, nucleus accumbens brain slices were prepared, and we tested for changes in the ratio between α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid (AMPA) and N-methyl-D-aspartate currents and the ability to exhibit long-term depression. We found that propensity to develop DIO is linked to deficits in the ability to induce long-term depression in the nucleus accumbens, as well as increased potentiation at these synapses as measured by AMPA/N-methyl-D-aspartate currents. Consistent with these impairments, we observed addictive-like behavior in DIO-prone rats, including 1) heightened motivation for palatable food; 2) excessive intake; and 3) increased food seeking when food was unavailable. Our results show overlap between the propensity for DIO and the synaptic changes associated with facets of addictive behavior, supporting partial coincident neurological underpinnings for compulsive overeating and drug addiction. Copyright © 2016 Society of Biological Psychiatry. All rights reserved.

NR2A- and NR2B-NMDA receptors and drebrin within postsynaptic spines of the hippocampus correlate with hunger-evoked exercise.

PubMed

Chen, Yi-Wen; Actor-Engel, Hannah; Sherpa, Ang Doma; Klingensmith, Lauren; Chowdhury, Tara G; Aoki, Chiye

2017-07-01

Hunger evokes foraging. This innate response can be quantified as voluntary wheel running following food restriction (FR). Paradoxically, imposing severe FR evokes voluntary FR, as some animals choose to run rather than eat, even during limited periods of food availability. This phenomenon, called activity-based anorexia (ABA), has been used to identify brain changes associated with FR and excessive exercise (EX), two core symptoms of anorexia nervosa (AN), and to explore neurobiological bases of AN vulnerability. Previously, we showed a strong positive correlation between suppression of FR-evoked hyperactivity, i.e., ABA resilience, and levels of extra-synaptic GABA receptors in stratum radiatum (SR) of hippocampal CA1. Here, we tested for the converse: whether animals with enhanced expression of NMDA receptors (NMDARs) exhibit greater levels of FR-evoked hyperactivity, i.e., ABA vulnerability. Four groups of animals were assessed for NMDAR levels at CA1 spines: (1) ABA, in which 4 days of FR was combined with wheel access to allow voluntary EX; (2) FR only; (3) EX only; and (4) control (CON) that experienced neither EX nor FR. Electron microscopy revealed that synaptic NR2A-NMDARs and NR2B-NMDARs levels are significantly elevated, relative to CONs'. Individuals' ABA severity, based on weight loss, correlated with synaptic NR2B-NMDAR levels. ABA resilience, quantified as suppression of hyperactivity, correlated strongly with reserve pools of NR2A-NMDARs in spine cytoplasm. NR2A- and NR2B-NMDAR measurements correlated with spinous prevalence of an F-actin binding protein, drebrin, suggesting that drebrin enables insertion of NR2B-NMDAR to and retention of NR2A-NMDARs away from synaptic membranes, together influencing ABA vulnerability.

Mirrored STDP Implements Autoencoder Learning in a Network of Spiking Neurons.

PubMed

Burbank, Kendra S

2015-12-01

The autoencoder algorithm is a simple but powerful unsupervised method for training neural networks. Autoencoder networks can learn sparse distributed codes similar to those seen in cortical sensory areas such as visual area V1, but they can also be stacked to learn increasingly abstract representations. Several computational neuroscience models of sensory areas, including Olshausen & Field's Sparse Coding algorithm, can be seen as autoencoder variants, and autoencoders have seen extensive use in the machine learning community. Despite their power and versatility, autoencoders have been difficult to implement in a biologically realistic fashion. The challenges include their need to calculate differences between two neuronal activities and their requirement for learning rules which lead to identical changes at feedforward and feedback connections. Here, we study a biologically realistic network of integrate-and-fire neurons with anatomical connectivity and synaptic plasticity that closely matches that observed in cortical sensory areas. Our choice of synaptic plasticity rules is inspired by recent experimental and theoretical results suggesting that learning at feedback connections may have a different form from learning at feedforward connections, and our results depend critically on this novel choice of plasticity rules. Specifically, we propose that plasticity rules at feedforward versus feedback connections are temporally opposed versions of spike-timing dependent plasticity (STDP), leading to a symmetric combined rule we call Mirrored STDP (mSTDP). We show that with mSTDP, our network follows a learning rule that approximately minimizes an autoencoder loss function. When trained with whitened natural image patches, the learned synaptic weights resemble the receptive fields seen in V1. Our results use realistic synaptic plasticity rules to show that the powerful autoencoder learning algorithm could be within the reach of real biological networks.

Mirrored STDP Implements Autoencoder Learning in a Network of Spiking Neurons

PubMed Central

Burbank, Kendra S.

2015-01-01

The autoencoder algorithm is a simple but powerful unsupervised method for training neural networks. Autoencoder networks can learn sparse distributed codes similar to those seen in cortical sensory areas such as visual area V1, but they can also be stacked to learn increasingly abstract representations. Several computational neuroscience models of sensory areas, including Olshausen & Field’s Sparse Coding algorithm, can be seen as autoencoder variants, and autoencoders have seen extensive use in the machine learning community. Despite their power and versatility, autoencoders have been difficult to implement in a biologically realistic fashion. The challenges include their need to calculate differences between two neuronal activities and their requirement for learning rules which lead to identical changes at feedforward and feedback connections. Here, we study a biologically realistic network of integrate-and-fire neurons with anatomical connectivity and synaptic plasticity that closely matches that observed in cortical sensory areas. Our choice of synaptic plasticity rules is inspired by recent experimental and theoretical results suggesting that learning at feedback connections may have a different form from learning at feedforward connections, and our results depend critically on this novel choice of plasticity rules. Specifically, we propose that plasticity rules at feedforward versus feedback connections are temporally opposed versions of spike-timing dependent plasticity (STDP), leading to a symmetric combined rule we call Mirrored STDP (mSTDP). We show that with mSTDP, our network follows a learning rule that approximately minimizes an autoencoder loss function. When trained with whitened natural image patches, the learned synaptic weights resemble the receptive fields seen in V1. Our results use realistic synaptic plasticity rules to show that the powerful autoencoder learning algorithm could be within the reach of real biological networks. PMID:26633645

Social stress alters inhibitory synaptic input to distinct subpopulations of raphe serotonin neurons.

PubMed

Crawford, LaTasha K; Rahman, Shumaia F; Beck, Sheryl G

2013-01-16

Anxiety disorders are among the most prevalent psychiatric disorders, yet much is unknown about the underlying mechanisms. The dorsal raphe (DR) is at the crux of the anxiety-inducing effects of uncontrollable stress, a key component of models of anxiety. Though DR serotonin (5-HT) neurons play a prominent role, anxiety-associated changes in the physiology of 5-HT neurons remain poorly understood. A 5-day social defeat model of anxiety produced a multifaceted, anxious phenotype in intruder mice that included increased avoidance behavior in the open field test, increased stress-evoked grooming, and increased bladder and heart weights when compared to control mice. Intruders were further compared to controls using electrophysiology recordings conducted in midbrain slices wherein recordings targeted 5-HT neurons of the ventromedial (vmDR) and lateral wing (lwDR) subfields of the DR. Though defining membrane characteristics of 5-HT neurons were unchanged, γ-aminobutyric-acid-mediated (GABAergic) synaptic regulation of 5-HT neurons was altered in a topographically specific way. In the vmDR of intruders, there was a decrease in the frequency and amplitude of GABAergic spontaneous inhibitory postsynaptic currents (sIPSCs). However, in the lwDR, there was an increase in the strength of inhibitory signals due to slower sIPSC kinetics. Synaptic changes were selective for GABAergic input, as glutamatergic synaptic input was unchanged in intruders. The distinct inhibitory regulation of DR subfields provides a mechanism for increased 5-HT output in vmDR target regions and decreased 5-HT output in lwDR target regions, divergent responses to uncontrollable stress that have been reported in the literature but were previously poorly understood.

Role of presynaptic inputs to proprioceptive afferents in tuning sensorimotor pathways of an insect joint control network.

PubMed

Sauer, A E; Büschges, A; Stein, W

1997-04-01

The femur-tibia (FT) joint of insects is governed by a neuronal network that controls activity in tibial motoneurons by processing sensory information about tibial position and movement provided by afferents of the femoral chordotonal organ (fCO). We show that central arborizations of fCO afferents receive presynaptic depolarizing synaptic inputs. With an average resting potential of -71.9 +/- 3.72 mV (n = 10), the reversal potential of these potentials is on average -62.8 +/- 2.3 mV (n = 5). These synaptic potentials occur either spontaneously or are related to movements at the fCO. They are thus induced by signals from other fCO afferents. Therefore, the synaptic inputs to fCO afferents are specific and depend on the sensitivity of the individual afferent affected. These potentials reduce the amplitude of concurrent afferent action potentials. Bath application of picrotoxin, a noncompetitive blocker of chloride ion channels, blocks these potentials, which indicates that they are mediated by chloride ions. From these results, it is concluded that these are inhibitory synaptic potentials generated in the central terminals of fCO afferents. Pharmacologic removal of these potentials affects the tuning of the complete FT control system. Following removal, the dependence of the FT control loop on the tibia position increases relative to the dependency on the velocity of tibia movements. This is due to changes in the relative weighting of the position and velocity signals in the parallel interneuronal pathways from the fCO onto tibial motoneurons. Consequently, the FT joint is no longer able to perform twig mimesis (i.e., catalepsy), which is known to rely on a low position compared to the high-velocity dependency of the FT control system.

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

PubMed Central

Srinivasa, Narayan; Cho, Youngkwan

2014-01-01

A spiking neural network model is described for learning to discriminate among spatial patterns in an unsupervised manner. The network anatomy consists of source neurons that are activated by external inputs, a reservoir that resembles a generic cortical layer with an excitatory-inhibitory (EI) network and a sink layer of neurons for readout. Synaptic plasticity in the form of STDP is imposed on all the excitatory and inhibitory synapses at all times. While long-term excitatory STDP enables sparse and efficient learning of the salient features in inputs, inhibitory STDP enables this learning to be stable by establishing a balance between excitatory and inhibitory currents at each neuron in the network. The synaptic weights between source and reservoir neurons form a basis set for the input patterns. The neural trajectories generated in the reservoir due to input stimulation and lateral connections between reservoir neurons can be readout by the sink layer neurons. This activity is used for adaptation of synapses between reservoir and sink layer neurons. A new measure called the discriminability index (DI) is introduced to compute if the network can discriminate between old patterns already presented in an initial training session. The DI is also used to compute if the network adapts to new patterns without losing its ability to discriminate among old patterns. The final outcome is that the network is able to correctly discriminate between all patterns—both old and new. This result holds as long as inhibitory synapses employ STDP to continuously enable current balance in the network. The results suggest a possible direction for future investigation into how spiking neural networks could address the stability-plasticity question despite having continuous synaptic plasticity. PMID:25566045

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

PubMed

Srinivasa, Narayan; Cho, Youngkwan

2014-01-01

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

Emerging feed-forward inhibition allows the robust formation of direction selectivity in the developing ferret visual cortex

PubMed Central

Escobar, Gina M.; Maffei, Arianna; Miller, Paul

2014-01-01

The computation of direction selectivity requires that a cell respond to joint spatial and temporal characteristics of the stimulus that cannot be separated into independent components. Direction selectivity in ferret visual cortex is not present at the time of eye opening but instead develops in the days and weeks following eye opening in a process that requires visual experience with moving stimuli. Classic Hebbian or spike timing-dependent modification of excitatory feed-forward synaptic inputs is unable to produce direction-selective cells from unselective or weakly directionally biased initial conditions because inputs eventually grow so strong that they can independently drive cortical neurons, violating the joint spatial-temporal activation requirement. Furthermore, without some form of synaptic competition, cells cannot develop direction selectivity in response to training with bidirectional stimulation, as cells in ferret visual cortex do. We show that imposing a maximum lateral geniculate nucleus (LGN)-to-cortex synaptic weight allows neurons to develop direction-selective responses that maintain the requirement for joint spatial and temporal activation. We demonstrate that a novel form of inhibitory plasticity, postsynaptic activity-dependent long-term potentiation of inhibition (POSD-LTPi), which operates in the developing cortex at the time of eye opening, can provide synaptic competition and enables robust development of direction-selective receptive fields with unidirectional or bidirectional stimulation. We propose a general model of the development of spatiotemporal receptive fields that consists of two phases: an experience-independent establishment of initial biases, followed by an experience-dependent amplification or modification of these biases via correlation-based plasticity of excitatory inputs that compete against gradually increasing feed-forward inhibition. PMID:24598528

Genetic predictors of antipsychotic response to lurasidone identified in a genome wide association study and by schizophrenia risk genes.

PubMed

Li, Jiang; Yoshikawa, Akane; Brennan, Mark D; Ramsey, Timothy L; Meltzer, Herbert Y

2018-02-01

Biomarkers which predict response to atypical antipsychotic drugs (AAPDs) increases their benefit/risk ratio. We sought to identify common variants in genes which predict response to lurasidone, an AAPD, by associating genome-wide association study (GWAS) data and changes (Δ) in Positive And Negative Syndrome Scale (PANSS) scores from two 6-week randomized, placebo-controlled trials of lurasidone in schizophrenia (SCZ) patients. We also included SCZ risk SNPs identified by the Psychiatric Genomics Consortium using a polygenic risk analysis. The top genomic loci, with uncorrected p<10 -4 , include: 1) synaptic adhesion (PTPRD, LRRC4C, NRXN1, ILIRAPL1, SLITRK1) and scaffolding (MAGI1, MAGI2, NBEA) genes, both essential for synaptic function; 2) other synaptic plasticity-related genes (NRG1/3 and KALRN); 3) the neuron-specific RNA splicing regulator, RBFOX1; and 4) ion channel genes, e.g. KCNA10, KCNAB1, KCNK9 and CACNA2D3). Some genes predicted response for patients with both European and African Ancestries. We replicated some SNPs reported to predict response to other atypical APDs in other GWAS. Although none of the biomarkers reached genome-wide significance, many of the genes and associated pathways have previously been linked to SCZ. Two polygenic modeling approaches, GCTA-GREML and PLINK-Polygenic Risk Score, demonstrated that some risk genes related to neurodevelopment, synaptic biology, immune response, and histones, also contributed to prediction of response. The top hits predicting response to lurasidone did not predict improvement with placebo. This is the first evidence from clinical trials that SCZ risk SNPs are related to clinical response to an AAPD. These results need to be replicated in an independent sample. Copyright © 2017. Published by Elsevier B.V.

Emergence of synchronization and regularity in firing patterns in time-varying neural hypernetworks

NASA Astrophysics Data System (ADS)

Rakshit, Sarbendu; Bera, Bidesh K.; Ghosh, Dibakar; Sinha, Sudeshna

2018-05-01

We study synchronization of dynamical systems coupled in time-varying network architectures, composed of two or more network topologies, corresponding to different interaction schemes. As a representative example of this class of time-varying hypernetworks, we consider coupled Hindmarsh-Rose neurons, involving two distinct types of networks, mimicking interactions that occur through the electrical gap junctions and the chemical synapses. Specifically, we consider the connections corresponding to the electrical gap junctions to form a small-world network, while the chemical synaptic interactions form a unidirectional random network. Further, all the connections in the hypernetwork are allowed to change in time, modeling a more realistic neurobiological scenario. We model this time variation by rewiring the links stochastically with a characteristic rewiring frequency f . We find that the coupling strength necessary to achieve complete neuronal synchrony is lower when the links are switched rapidly. Further, the average time required to reach the synchronized state decreases as synaptic coupling strength and/or rewiring frequency increases. To quantify the local stability of complete synchronous state we use the Master Stability Function approach, and for global stability we employ the concept of basin stability. The analytically derived necessary condition for synchrony is in excellent agreement with numerical results. Further we investigate the resilience of the synchronous states with respect to increasing network size, and we find that synchrony can be maintained up to larger network sizes by increasing either synaptic strength or rewiring frequency. Last, we find that time-varying links not only promote complete synchronization, but also have the capacity to change the local dynamics of each single neuron. Specifically, in a window of rewiring frequency and synaptic coupling strength, we observe that the spiking behavior becomes more regular.

Medium-Chain Fatty Acids Improve Cognitive Function in Intensively Treated Type 1 Diabetic Patients and Support In Vitro Synaptic Transmission During Acute Hypoglycemia

PubMed Central

Page, Kathleen A.; Williamson, Anne; Yu, Namyi; McNay, Ewan C.; Dzuira, James; McCrimmon, Rory J.; Sherwin, Robert S.

2009-01-01

OBJECTIVE We examined whether ingestion of medium-chain triglycerides could improve cognition during hypoglycemia in subjects with intensively treated type 1 diabetes and assessed potential underlying mechanisms by testing the effect of β-hydroxybutyrate and octanoate on rat hippocampal synaptic transmission during exposure to low glucose. RESEARCH DESIGN AND METHODS A total of 11 intensively treated type 1 diabetic subjects participated in stepped hyperinsulinemic- (2 mU · kg−1 · min−1) euglycemic- (glucose ∼5.5 mmol/l) hypoglycemic (glucose ∼2.8 mmol/l) clamp studies. During two separate sessions, they randomly received either medium-chain triglycerides or placebo drinks and performed a battery of cognitive tests. In vitro rat hippocampal slice preparations were used to assess the ability of β-hydroxybutyrate and octanoate to support neuronal activity when glucose levels are reduced. RESULTS Hypoglycemia impaired cognitive performance in tests of verbal memory, digit symbol coding, digit span backwards, and map searching. Ingestion of medium-chain triglycerides reversed these effects. Medium-chain triglycerides also produced higher free fatty acids and β-hydroxybutyrate levels compared with placebo. However, the increase in catecholamines and symptoms during hypoglycemia was not altered. In hippocampal slices β-hydroxybutyrate supported synaptic transmission under low-glucose conditions, whereas octanoate could not. Nevertheless, octanoate improved the rate of recovery of synaptic function upon restoration of control glucose concentrations. CONCLUSIONS Medium-chain triglyceride ingestion improves cognition without adversely affecting adrenergic or symptomatic responses to hypoglycemia in intensively treated type 1 diabetic subjects. Medium-chain triglycerides offer the therapeutic advantage of preserving brain function under hypoglycemic conditions without causing deleterious hyperglycemia. PMID:19223595

Python scripting in the nengo simulator.

PubMed

Stewart, Terrence C; Tripp, Bryan; Eliasmith, Chris

2009-01-01

Nengo (http://nengo.ca) is an open-source neural simulator that has been greatly enhanced by the recent addition of a Python script interface. Nengo provides a wide range of features that are useful for physiological simulations, including unique features that facilitate development of population-coding models using the neural engineering framework (NEF). This framework uses information theory, signal processing, and control theory to formalize the development of large-scale neural circuit models. Notably, it can also be used to determine the synaptic weights that underlie observed network dynamics and transformations of represented variables. Nengo provides rich NEF support, and includes customizable models of spike generation, muscle dynamics, synaptic plasticity, and synaptic integration, as well as an intuitive graphical user interface. All aspects of Nengo models are accessible via the Python interface, allowing for programmatic creation of models, inspection and modification of neural parameters, and automation of model evaluation. Since Nengo combines Python and Java, it can also be integrated with any existing Java or 100% Python code libraries. Current work includes connecting neural models in Nengo with existing symbolic cognitive models, creating hybrid systems that combine detailed neural models of specific brain regions with higher-level models of remaining brain areas. Such hybrid models can provide (1) more realistic boundary conditions for the neural components, and (2) more realistic sub-components for the larger cognitive models.

Synergistic Gating of Electro-Iono-Photoactive 2D Chalcogenide Neuristors: Coexistence of Hebbian and Homeostatic Synaptic Metaplasticity.

PubMed

John, Rohit Abraham; Liu, Fucai; Chien, Nguyen Anh; Kulkarni, Mohit R; Zhu, Chao; Fu, Qundong; Basu, Arindam; Liu, Zheng; Mathews, Nripan

2018-06-01

Emulation of brain-like signal processing with thin-film devices can lay the foundation for building artificially intelligent learning circuitry in future. Encompassing higher functionalities into single artificial neural elements will allow the development of robust neuromorphic circuitry emulating biological adaptation mechanisms with drastically lesser neural elements, mitigating strict process challenges and high circuit density requirements necessary to match the computational complexity of the human brain. Here, 2D transition metal di-chalcogenide (MoS 2 ) neuristors are designed to mimic intracellular ion endocytosis-exocytosis dynamics/neurotransmitter-release in chemical synapses using three approaches: (i) electronic-mode: a defect modulation approach where the traps at the semiconductor-dielectric interface are perturbed; (ii) ionotronic-mode: where electronic responses are modulated via ionic gating; and (iii) photoactive-mode: harnessing persistent photoconductivity or trap-assisted slow recombination mechanisms. Exploiting a novel multigated architecture incorporating electrical and optical biases, this incarnation not only addresses different charge-trapping probabilities to finely modulate the synaptic weights, but also amalgamates neuromodulation schemes to achieve "plasticity of plasticity-metaplasticity" via dynamic control of Hebbian spike-time dependent plasticity and homeostatic regulation. Coexistence of such multiple forms of synaptic plasticity increases the efficacy of memory storage and processing capacity of artificial neuristors, enabling design of highly efficient novel neural architectures. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Autism-Associated Insertion Mutation (InsG) of Shank3 Exon 21 Causes Impaired Synaptic Transmission and Behavioral Deficits.

PubMed

Speed, Haley E; Kouser, Mehreen; Xuan, Zhong; Reimers, Jeremy M; Ochoa, Christine F; Gupta, Natasha; Liu, Shunan; Powell, Craig M

2015-07-01

SHANK3 (also known as PROSAP2) is a postsynaptic scaffolding protein at excitatory synapses in which mutations and deletions have been implicated in patients with idiopathic autism, Phelan-McDermid (aka 22q13 microdeletion) syndrome, and other neuropsychiatric disorders. In this study, we have created a novel mouse model of human autism caused by the insertion of a single guanine nucleotide into exon 21 (Shank3(G)). The resulting frameshift causes a premature STOP codon and loss of major higher molecular weight Shank3 isoforms at the synapse. Shank3(G/G) mice exhibit deficits in hippocampus-dependent spatial learning, impaired motor coordination, altered response to novelty, and sensory processing deficits. At the cellular level, Shank3(G/G) mice also exhibit impaired hippocampal excitatory transmission and plasticity as well as changes in baseline NMDA receptor-mediated synaptic responses. This work identifies clear alterations in synaptic function and behavior in a novel, genetically accurate mouse model of autism mimicking an autism-associated insertion mutation. Furthermore, these findings lay the foundation for future studies aimed to validate and study region-selective and temporally selective genetic reversal studies in the Shank3(G/G) mouse that was engineered with such future experiments in mind. Copyright © 2015 the authors 0270-6474/15/359648-18$15.00/0.

Python Scripting in the Nengo Simulator

PubMed Central

Stewart, Terrence C.; Tripp, Bryan; Eliasmith, Chris

2008-01-01

Nengo (http://nengo.ca) is an open-source neural simulator that has been greatly enhanced by the recent addition of a Python script interface. Nengo provides a wide range of features that are useful for physiological simulations, including unique features that facilitate development of population-coding models using the neural engineering framework (NEF). This framework uses information theory, signal processing, and control theory to formalize the development of large-scale neural circuit models. Notably, it can also be used to determine the synaptic weights that underlie observed network dynamics and transformations of represented variables. Nengo provides rich NEF support, and includes customizable models of spike generation, muscle dynamics, synaptic plasticity, and synaptic integration, as well as an intuitive graphical user interface. All aspects of Nengo models are accessible via the Python interface, allowing for programmatic creation of models, inspection and modification of neural parameters, and automation of model evaluation. Since Nengo combines Python and Java, it can also be integrated with any existing Java or 100% Python code libraries. Current work includes connecting neural models in Nengo with existing symbolic cognitive models, creating hybrid systems that combine detailed neural models of specific brain regions with higher-level models of remaining brain areas. Such hybrid models can provide (1) more realistic boundary conditions for the neural components, and (2) more realistic sub-components for the larger cognitive models. PMID:19352442

Gating of Long-Term Potentiation by Nicotinic Acetylcholine Receptors at the Cerebellum Input Stage

PubMed Central

Prestori, Francesca; Bonardi, Claudia; Mapelli, Lisa; Lombardo, Paola; Goselink, Rianne; De Stefano, Maria Egle; Gandolfi, Daniela; Mapelli, Jonathan; Bertrand, Daniel; Schonewille, Martijn; De Zeeuw, Chris; D’Angelo, Egidio

2013-01-01

The brain needs mechanisms able to correlate plastic changes with local circuit activity and internal functional states. At the cerebellum input stage, uncontrolled induction of long-term potentiation or depression (LTP or LTD) between mossy fibres and granule cells can saturate synaptic capacity and impair cerebellar functioning, which suggests that neuromodulators are required to gate plasticity processes. Cholinergic systems innervating the cerebellum are thought to enhance procedural learning and memory. Here we show that a specific subtype of acetylcholine receptors, the α7-nAChRs, are distributed both in cerebellar mossy fibre terminals and granule cell dendrites and contribute substantially to synaptic regulation. Selective α7-nAChR activation enhances the postsynaptic calcium increase, allowing weak mossy fibre bursts, which would otherwise cause LTD, to generate robust LTP. The local microperfusion of α7-nAChR agonists could also lead to in vivo switching of LTD to LTP following sensory stimulation of the whisker pad. In the cerebellar flocculus, α7-nAChR pharmacological activation impaired vestibulo-ocular-reflex adaptation, probably because LTP was saturated, preventing the fine adjustment of synaptic weights. These results show that gating mechanisms mediated by specific subtypes of nicotinic receptors are required to control the LTD/LTP balance at the mossy fibre-granule cell relay in order to regulate cerebellar plasticity and behavioural adaptation. PMID:23741401

Enhanced AMPA receptor trafficking mediates the anorexigenic effect of endogenous glucagon like peptide-1 in the paraventricular hypothalamus

PubMed Central

Liu, Ji; Conde, Kristie; Zhang, Peng; Lilascharoen, Varoth; Xu, Zihui; Lim, Byung Kook; Seeley, Randy J.; Zhu, Julius J.; Scott, Michael M.; Pang, Zhiping P.

2017-01-01

SUMMARY Glucagon Like Peptide 1 (GLP-1)-expressing neurons in the hindbrain send robust projections to the paraventricular nucleus of the hypothalamus (PVN), which is involved in the regulation of food intake. Here, we describe that stimulation of GLP-1 afferent fibers within the PVN is sufficient to suppress food intake independent of glutamate release. We also show that GLP-1 receptor (GLP-1R) activation augments excitatory synaptic strength in PVN corticotropin-releasing hormone (CRH) neurons, with GLP-1R activation promoting a protein kinase A (PKA) dependent signaling cascade leading to phosphorylation of serine S845 on GluA1 AMPA receptors and their trafficking to the plasma membrane. Finally, we show that postnatal depletion of GLP-1R in the PVN increases food intake and causes obesity. This study provides a comprehensive multi-level (circuit, synaptic, and molecular) explanation of how food intake behavior and body weight are regulated by endogenous central GLP-1. PMID:29056294

Synaptic electronics: materials, devices and applications.

PubMed

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 Efficacy as a Function of Ionotropic Receptor Distribution: A Computational Study

PubMed Central

Allam, Sushmita L.; Bouteiller, Jean-Marie C.; Hu, Eric Y.; Ambert, Nicolas; Greget, Renaud; Bischoff, Serge; Baudry, Michel; Berger, Theodore W.

2015-01-01

Glutamatergic synapses are the most prevalent functional elements of information processing in the brain. Changes in pre-synaptic activity and in the function of various post-synaptic elements contribute to generate a large variety of synaptic responses. Previous studies have explored postsynaptic factors responsible for regulating synaptic strength variations, but have given far less importance to synaptic geometry, and more specifically to the subcellular distribution of ionotropic receptors. We analyzed the functional effects resulting from changing the subsynaptic localization of ionotropic receptors by using a hippocampal synaptic computational framework. The present study was performed using the EONS (Elementary Objects of the Nervous System) synaptic modeling platform, which was specifically developed to explore the roles of subsynaptic elements as well as their interactions, and that of synaptic geometry. More specifically, we determined the effects of changing the localization of ionotropic receptors relative to the presynaptic glutamate release site, on synaptic efficacy and its variations following single pulse and paired-pulse stimulation protocols. The results indicate that changes in synaptic geometry do have consequences on synaptic efficacy and its dynamics. PMID:26480028

Synaptic Efficacy as a Function of Ionotropic Receptor Distribution: A Computational Study.

PubMed

Allam, Sushmita L; Bouteiller, Jean-Marie C; Hu, Eric Y; Ambert, Nicolas; Greget, Renaud; Bischoff, Serge; Baudry, Michel; Berger, Theodore W

2015-01-01

Glutamatergic synapses are the most prevalent functional elements of information processing in the brain. Changes in pre-synaptic activity and in the function of various post-synaptic elements contribute to generate a large variety of synaptic responses. Previous studies have explored postsynaptic factors responsible for regulating synaptic strength variations, but have given far less importance to synaptic geometry, and more specifically to the subcellular distribution of ionotropic receptors. We analyzed the functional effects resulting from changing the subsynaptic localization of ionotropic receptors by using a hippocampal synaptic computational framework. The present study was performed using the EONS (Elementary Objects of the Nervous System) synaptic modeling platform, which was specifically developed to explore the roles of subsynaptic elements as well as their interactions, and that of synaptic geometry. More specifically, we determined the effects of changing the localization of ionotropic receptors relative to the presynaptic glutamate release site, on synaptic efficacy and its variations following single pulse and paired-pulse stimulation protocols. The results indicate that changes in synaptic geometry do have consequences on synaptic efficacy and its dynamics.

The distribution of early recombination nodules on zygotene bivalents from plants.

PubMed Central

Anderson, L K; Hooker, K D; Stack, S M

2001-01-01

Early recombination nodules (ENs) are protein complexes approximately 100 nm in diameter that are associated with forming synaptonemal complexes (SCs) during leptotene and zygotene of meiosis. Although their functions are not yet clear, ENs may have roles in synapsis and recombination. Here we report on the frequency and distribution of ENs in zygotene SC spreads from six plant species that include one lower vascular plant, two dicots, and three monocots. For each species, the number of ENs per unit length is higher for SC segments than for (asynapsed) axial elements (AEs). In addition, EN number is strongly correlated with SC segment length. There are statistically significant differences in EN frequencies on SCs between species, but these differences are not related to genome size, number of chromosomes, or phylogenetic class. There is no difference in the frequency of ENs per unit length of SC from early to late zygotene. The distribution of distances between adjacent ENs on SC segments is random for all six species, but ENs are found at synaptic forks more often than expected for a random distribution of ENs on SCs. From these observations, we conclude that in plants: (1) some ENs bind to AEs prior to synapsis, (2) most ENs bind to forming SCs at synaptic forks, and (3) ENs do not bind to already formed SCs. PMID:11729167

Network recruitment to coherent oscillations in a hippocampal computer model

PubMed Central

Krieger, Abba; Litt, Brian

2011-01-01

Coherent neural oscillations represent transient synchronization of local neuronal populations in both normal and pathological brain activity. These oscillations occur at or above gamma frequencies (>30 Hz) and often are propagated to neighboring tissue under circumstances that are both normal and abnormal, such as gamma binding or seizures. The mechanisms that generate and propagate these oscillations are poorly understood. In the present study we demonstrate, via a detailed computational model, a mechanism whereby physiological noise and coupling initiate oscillations and then recruit neighboring tissue, in a manner well described by a combination of stochastic resonance and coherence resonance. We develop a novel statistical method to quantify recruitment using several measures of network synchrony. This measurement demonstrates that oscillations spread via preexisting network connections such as interneuronal connections, recurrent synapses, and gap junctions, provided that neighboring cells also receive sufficient inputs in the form of random synaptic noise. “Epileptic” high-frequency oscillations (HFOs), produced by pathologies such as increased synaptic activity and recurrent connections, were superior at recruiting neighboring tissue. “Normal” HFOs, associated with fast firing of inhibitory cells and sparse pyramidal cell firing, tended to suppress surrounding cells and showed very limited ability to recruit. These findings point to synaptic noise and physiological coupling as important targets for understanding the generation and propagation of both normal and pathological HFOs, suggesting potential new diagnostic and therapeutic approaches to human disorders such as epilepsy. PMID:21273309

Calibration of neural networks using genetic algorithms, with application to optimal path planning

NASA Technical Reports Server (NTRS)

Smith, Terence R.; Pitney, Gilbert A.; Greenwood, Daniel

1987-01-01

Genetic algorithms (GA) are used to search the synaptic weight space of artificial neural systems (ANS) for weight vectors that optimize some network performance function. GAs do not suffer from some of the architectural constraints involved with other techniques and it is straightforward to incorporate terms into the performance function concerning the metastructure of the ANS. Hence GAs offer a remarkably general approach to calibrating ANS. GAs are applied to the problem of calibrating an ANS that finds optimal paths over a given surface. This problem involves training an ANS on a relatively small set of paths and then examining whether the calibrated ANS is able to find good paths between arbitrary start and end points on the surface.

Three-dimensional weight-accumulation algorithm for generating multiple excitation spots in fast optical stimulation

NASA Astrophysics Data System (ADS)

Takiguchi, Yu; Toyoda, Haruyoshi

2017-11-01

We report here an algorithm for calculating a hologram to be employed in a high-access speed microscope for observing sensory-driven synaptic activity across all inputs to single living neurons in an intact cerebral cortex. The system is based on holographic multi-beam generation using a two-dimensional phase-only spatial light modulator to excite multiple locations in three dimensions with a single hologram. The hologram was calculated with a three-dimensional weighted iterative Fourier transform method using the Ewald sphere restriction to increase the calculation speed. Our algorithm achieved good uniformity of three dimensionally generated excitation spots; the standard deviation of the spot intensities was reduced by a factor of two compared with a conventional algorithm.

Three-dimensional weight-accumulation algorithm for generating multiple excitation spots in fast optical stimulation

NASA Astrophysics Data System (ADS)

Takiguchi, Yu; Toyoda, Haruyoshi

2018-06-01

We report here an algorithm for calculating a hologram to be employed in a high-access speed microscope for observing sensory-driven synaptic activity across all inputs to single living neurons in an intact cerebral cortex. The system is based on holographic multi-beam generation using a two-dimensional phase-only spatial light modulator to excite multiple locations in three dimensions with a single hologram. The hologram was calculated with a three-dimensional weighted iterative Fourier transform method using the Ewald sphere restriction to increase the calculation speed. Our algorithm achieved good uniformity of three dimensionally generated excitation spots; the standard deviation of the spot intensities was reduced by a factor of two compared with a conventional algorithm.

USAF 1990 Research Initiation Program. Volume 3

DTIC Science & Technology

1992-06-25

the reinforcement outward, both on the entrance and exit sides. The reinforcement was bent outward like a membrane under internal prressure. This led...potential of a neuron. C: cell capacitance. R: membrane resistance. w: synaptic weight. h(x): sigmoidal function describing the firing rate. y: external...Proof: The uncertain closed loop plant may be written as x(t)=(A+AA)x(t)+(Ao+ AAo )x(t-T) (B+AB)F(C AC)x(t) =(A+BFC)x(t)+(AA+ABFC+BFAC+ABFAC)x(t)+(Ao+Ao)X(t

Bit-serial neuroprocessor architecture

NASA Technical Reports Server (NTRS)

Tawel, Raoul (Inventor)

2001-01-01

A neuroprocessor architecture employs a combination of bit-serial and serial-parallel techniques for implementing the neurons of the neuroprocessor. The neuroprocessor architecture includes a neural module containing a pool of neurons, a global controller, a sigmoid activation ROM look-up-table, a plurality of neuron state registers, and a synaptic weight RAM. The neuroprocessor reduces the number of neurons required to perform the task by time multiplexing groups of neurons from a fixed pool of neurons to achieve the successive hidden layers of a recurrent network topology.

Higher-order neural networks, Polyà polynomials, and Fermi cluster diagrams

NASA Astrophysics Data System (ADS)

Kürten, K. E.; Clark, J. W.

2003-09-01

The problem of controlling higher-order interactions in neural networks is addressed with techniques commonly applied in the cluster analysis of quantum many-particle systems. For multineuron synaptic weights chosen according to a straightforward extension of the standard Hebbian learning rule, we show that higher-order contributions to the stimulus felt by a given neuron can be readily evaluated via Polyà’s combinatoric group-theoretical approach or equivalently by exploiting a precise formal analogy with fermion diagrammatics.

Multi-component access to a commercially available weight loss program: A randomized controlled trial

USDA-ARS?s Scientific Manuscript database

This study examined weight loss between a community-based, intensive behavioral counseling program (Weight Watchers PointsPlus that included three treatment access modes and a self-help condition. A total of 292 participants were randomized to a Weight Watchers (WW; n=147) or a self-help condition (...

Flexible Proton-Gated Oxide Synaptic Transistors on Si Membrane.

PubMed

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.

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

PubMed

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.

Spiking Neural Networks Based on OxRAM Synapses for Real-Time Unsupervised Spike Sorting.

PubMed

Werner, Thilo; Vianello, Elisa; Bichler, Olivier; Garbin, Daniele; Cattaert, Daniel; Yvert, Blaise; De Salvo, Barbara; Perniola, Luca

2016-01-01

In this paper, we present an alternative approach to perform spike sorting of complex brain signals based on spiking neural networks (SNN). The proposed architecture is suitable for hardware implementation by using resistive random access memory (RRAM) technology for the implementation of synapses whose low latency (<1μs) enables real-time spike sorting. This offers promising advantages to conventional spike sorting techniques for brain-computer interfaces (BCI) and neural prosthesis applications. Moreover, the ultra-low power consumption of the RRAM synapses of the spiking neural network (nW range) may enable the design of autonomous implantable devices for rehabilitation purposes. We demonstrate an original methodology to use Oxide based RRAM (OxRAM) as easy to program and low energy (<75 pJ) synapses. Synaptic weights are modulated through the application of an online learning strategy inspired by biological Spike Timing Dependent Plasticity. Real spiking data have been recorded both intra- and extracellularly from an in-vitro preparation of the Crayfish sensory-motor system and used for validation of the proposed OxRAM based SNN. This artificial SNN is able to identify, learn, recognize and distinguish between different spike shapes in the input signal with a recognition rate about 90% without any supervision.

Electrocortical changes associated with minocycline treatment in fragile X syndrome.

PubMed

Schneider, Andrea; Leigh, Mary Jacena; Adams, Patrick; Nanakul, Rawi; Chechi, Tasleem; Olichney, John; Hagerman, Randi; Hessl, David

2013-10-01

Minocycline normalizes synaptic connections and behavior in the knockout mouse model of fragile X syndrome (FXS). Human-targeted treatment trials with minocycline have shown benefits in behavioral measures and parent reports. Event-related potentials (ERPs) may provide a sensitive method of monitoring treatment response and changes in coordinated brain activity. Measurement of electrocortical changes due to minocycline was done in a double-blind, placebo-controlled crossover treatment trial in children with FXS. Children with FXS (Meanage 10.5 years) were randomized to minocycline or placebo treatment for 3 months then changed to the other treatment for 3 months. The minocycline dosage ranged from 25-100 mg daily, based on weight. Twelve individuals with FXS (eight male, four female) completed ERP studies using a passive auditory oddball paradigm. Current source density (CSD) and ERP analysis at baseline showed high-amplitude, long-latency components over temporal regions. After 3 months of treatment with minocycline, the temporal N1 and P2 amplitudes were significantly reduced compared with placebo. There was a significant amplitude increase of the central P2 component on minocycline. Electrocortical habituation to auditory stimuli improved with minocycline treatment. Our study demonstrated improvements of the ERP in children with FXS treated with minocycline, and the potential feasibility and sensitivity of ERPs as a cognitive biomarker in FXS treatment trials.

Lorcaserin plus lifestyle modification for weight loss maintenance: Rationale and design for a randomized controlled trial.

PubMed

Tronieri, Jena Shaw; Alfaris, Nasreen; Chao, Ariana M; Pearl, Rebecca L; Alamuddin, Naji; Bakizada, Zayna M; Berkowitz, Robert I; Wadden, Thomas A

2017-08-01

Few studies have examined the efficacy of recently approved medications for chronic weight management in facilitating the maintenance of lost weight. This paper provides an overview of the design and rationale for a trial investigating whether lorcaserin, when combined with behavioral weight loss maintenance sessions (WLM), will facilitate the maintenance of losses of ≥5% of initial weight. In this two-phase trial, participants with obesity will enroll in a 14-week run-in diet program consisting of weekly group lifestyle modification sessions and a 1000-1200kcal/d meal replacement diet. Participants who complete this weight induction phase and lose at least 5% of initial weight will then be randomized to 52weeks of WLM plus lorcaserin or WLM plus placebo. We hypothesize that at 52weeks post randomization, participants assigned to WLM plus lorcaserin will achieve significantly better maintenance of the prior 5% weight loss. We will recruit 182 adults with obesity to participate in the diet run-in, 136 of whom (75%) are expected to become eligible for the randomized controlled trial. Co-primary outcomes include the percentage of participants who maintain a loss of at least 5% of initial weight at week 52 and change in weight (kg) from randomization to week 52. This two-phase design will allow us to determine the potential efficacy of chronic weight management using lorcaserin for maintaining initial losses of at least 5% body weight, induced by the use of a structured meal-replacement diet. This combined approach holds promise of achieving larger long-term weight losses. NCT02388568 on ClinicalTrials.gov. Copyright © 2017 Elsevier Inc. All rights reserved.

Formulation and Application of the Hierarchical Generalized Random-Situation Random-Weight MIRID

ERIC Educational Resources Information Center

Hung, Lai-Fa

2011-01-01

The process-component approach has become quite popular for examining many psychological concepts. A typical example is the model with internal restrictions on item difficulty (MIRID) described by Butter (1994) and Butter, De Boeck, and Verhelst (1998). This study proposes a hierarchical generalized random-situation random-weight MIRID. The…

Correlations induced by depressing synapses in critically self-organized networks with quenched dynamics

NASA Astrophysics Data System (ADS)

Campos, João Guilherme Ferreira; Costa, Ariadne de Andrade; Copelli, Mauro; Kinouchi, Osame

2017-04-01

In a recent work, mean-field analysis and computer simulations were employed to analyze critical self-organization in networks of excitable cellular automata where randomly chosen synapses in the network were depressed after each spike (the so-called annealed dynamics). Calculations agree with simulations of the annealed version, showing that the nominal branching ratio σ converges to unity in the thermodynamic limit, as expected of a self-organized critical system. However, the question remains whether the same results apply to the biological case where only the synapses of firing neurons are depressed (the so-called quenched dynamics). We show that simulations of the quenched model yield significant deviations from σ =1 due to spatial correlations. However, the model is shown to be critical, as the largest eigenvalue of the synaptic matrix approaches unity in the thermodynamic limit, that is, λc=1 . We also study the finite size effects near the critical state as a function of the parameters of the synaptic dynamics.

The slippery slope: prediction of successful weight maintenance in anorexia nervosa

PubMed Central

Kaplan, A. S.; Walsh, B. T.; Olmsted, M.; Attia, E.; Carter, J. C.; Devlin, M. J.; Pike, K. M.; Woodside, B.; Rockert, W.; Roberto, C. A.; Parides, M.

2015-01-01

Background Previous research has found that many patients with anorexia nervosa (AN) are unable to maintain normal weight after weight restoration. The objective of this study was to identify variables that predicted successful weight maintenance among weight-restored AN patients. Method Ninety-three patients with AN treated at two sites (Toronto and New York) through in-patient or partial hospitalization achieved a minimally normal weight and were then randomly assigned to receive fluoxetine or placebo along with cognitive behavioral therapy (CBT) for 1 year. Clinical, demographic and psychometric variables were assessed after weight restoration prior to randomization and putative predictors of successful weight maintenance at 6 and 12 months were examined. Results The most powerful predictors of weight maintenance at 6 and 12 months following weight restoration were pre-randomization body mass index (BMI) and the rate of weight loss in the first 28 days following randomization. Higher BMI and lower rate of weight loss were associated with greater likelihood of maintaining a normal BMI at 6 and 12 months. An additional predictor of weight maintenance was site; patients in Toronto fared better than those in New York. Conclusions This study found that the best predictors of weight maintenance in weight-restored AN patients over 6 and 12 months were the level of weight restoration at the conclusion of acute treatment and the avoidance of weight loss immediately following intensive treatment. These results suggest that outcome might be improved by achieving a higher BMI during structured treatment programs and on preventing weight loss immediately following discharge from such programs. PMID:18845008

Efficacy of Souvenaid in mild Alzheimer's disease: results from a randomized, controlled trial.

PubMed

Scheltens, Philip; Twisk, Jos W R; Blesa, Rafael; Scarpini, Elio; von Arnim, Christine A F; Bongers, Anke; Harrison, John; Swinkels, Sophie H N; Stam, Cornelis J; de Waal, Hanneke; Wurtman, Richard J; Wieggers, Rico L; Vellas, Bruno; Kamphuis, Patrick J G H

2012-01-01

Souvenaid aims to improve synapse formation and function. An earlier study in patients with Alzheimer's disease (AD) showed that Souvenaid increased memory performance after 12 weeks in drug-naïve patients with mild AD. The Souvenir II study was a 24-week, randomized, controlled, double-blind, parallel-group, multi-country trial to confirm and extend previous findings in drug-naïve patients with mild AD. Patients were randomized 1:1 to receive Souvenaid or an iso-caloric control product once daily for 24 weeks. The primary outcome was the memory function domain Z-score of the Neuropsychological Test Battery (NTB) over 24 weeks. Electroencephalography (EEG) measures served as secondary outcomes as marker for synaptic connectivity. Assessments were done at baseline, 12, and 24 weeks. The NTB memory domain Z-score was significantly increased in the active versus the control group over the 24-week intervention period (p = 0.023; Cohen's d = 0.21; 95% confidence interval [-0.06]-[0.49]). A trend for an effect was observed on the NTB total composite z-score (p = 0.053). EEG measures of functional connectivity in the delta band were significantly different between study groups during 24 weeks in favor of the active group. Compliance was very high (96.6% [control] and 97.1% [active]). No difference between study groups in the occurrence of (serious) adverse events. This study demonstrates that Souvenaid is well tolerated and improves memory performance in drug-naïve patients with mild AD. EEG outcomes suggest that Souvenaid has an effect on brain functional connectivity, supporting the underlying hypothesis of changed synaptic activity.

Short- and Long-Term Changes in Health-Related Quality of Life with Weight Loss: Results from a Randomized Controlled Trial.

PubMed

Pearl, Rebecca L; Wadden, Thomas A; Tronieri, Jena Shaw; Berkowitz, Robert I; Chao, Ariana M; Alamuddin, Naji; Leonard, Sharon M; Carvajal, Raymond; Bakizada, Zayna M; Pinkasavage, Emilie; Gruber, Kathryn A; Walsh, Olivia A; Alfaris, Nasreen

2018-06-01

The objective of this study was to determine the effects of weight loss and weight loss maintenance (WLM) on weight-specific health-related quality of life in a 66-week trial. Adults with obesity (N = 137, 86.1% female, 68.6% black, mean age = 46.1 years) who had lost ≥ 5% of initial weight in a 14-week intensive lifestyle intervention/low-calorie diet (LCD) program were randomly assigned to lorcaserin or placebo for an additional 52-week WLM program. The Impact of Weight on Quality of Life-Lite (IWQOL-Lite) scale (including five subscales), Patient Health Questionnaire-9 (depression), and Perceived Stress Scale were administered at the start of the 14-week LCD program, randomization, and week 52 of the randomized controlled trial (i.e., 66 weeks total). Significant improvements in all outcomes, except weight-related public distress, were found following the 14-week LCD program (P values < 0.05). Improvements were largely maintained during the 52-week randomized controlled trial, despite weight regain of 2.0 to 2.5 kg across treatment groups. Participants who lost ≥ 10% of initial weight achieved greater improvements in physical function, self-esteem, sexual life, and the IWQOL-Lite total score than those who lost < 5% and did not differ from those who lost 5% to 9.9%. Improvements in weight-specific health-related quality of life were achieved with moderate weight loss and were sustained during WLM. © 2018 The Obesity Society.

APP is cleaved by Bace1 in pre-synaptic vesicles and establishes a pre-synaptic interactome, via its intracellular domain, with molecular complexes that regulate pre-synaptic vesicles functions.

PubMed

Del Prete, Dolores; Lombino, Franco; Liu, Xinran; D'Adamio, Luciano

2014-01-01

Amyloid Precursor Protein (APP) is a type I membrane protein that undergoes extensive processing by secretases, including BACE1. Although mutations in APP and genes that regulate processing of APP, such as PSENs and BRI2/ITM2B, cause dementias, the normal function of APP in synaptic transmission, synaptic plasticity and memory formation is poorly understood. To grasp the biochemical mechanisms underlying the function of APP in the central nervous system, it is important to first define the sub-cellular localization of APP in synapses and the synaptic interactome of APP. Using biochemical and electron microscopy approaches, we have found that APP is localized in pre-synaptic vesicles, where it is processed by Bace1. By means of a proteomic approach, we have characterized the synaptic interactome of the APP intracellular domain. We focused on this region of APP because in vivo data underline the central functional and pathological role of the intracellular domain of APP. Consistent with the expression of APP in pre-synaptic vesicles, the synaptic APP intracellular domain interactome is predominantly constituted by pre-synaptic, rather than post-synaptic, proteins. This pre-synaptic interactome of the APP intracellular domain includes proteins expressed on pre-synaptic vesicles such as the vesicular SNARE Vamp2/Vamp1 and the Ca2+ sensors Synaptotagmin-1/Synaptotagmin-2, and non-vesicular pre-synaptic proteins that regulate exocytosis, endocytosis and recycling of pre-synaptic vesicles, such as target-membrane-SNAREs (Syntaxin-1b, Syntaxin-1a, Snap25 and Snap47), Munc-18, Nsf, α/β/γ-Snaps and complexin. These data are consistent with a functional role for APP, via its carboxyl-terminal domain, in exocytosis, endocytosis and/or recycling of pre-synaptic vesicles.

Efficacy of a group-based dietary intervention for limiting gestational weight gain among obese women: a randomized trial

PubMed Central

Vesco, Kimberly K.; Karanja, Njeri; King, Janet C.; Gillman, Matthew W.; Leo, Michael C.; Perrin, Nancy; McEvoy, Cindy T.; Eckhardt, Cara L.; Smith, K. Sabina; Stevens, Victor J.

2014-01-01

Objective Observational studies suggest that minimal gestational weight gain (GWG) may optimize pregnancy outcomes for obese women. This trial tested the efficacy of a group-based weight management intervention for limiting GWG among obese women. Methods We randomized 114 obese women (BMI [mean±SD] 36.7±4.9 kg/m2) between 7–21 weeks’ (14.9±2.6) gestation to intervention (n=56) or usual care control conditions (n=58). The intervention included individualized calorie goals, advice to maintain weight within 3% of randomization and follow the Dietary Approaches to Stop Hypertension dietary pattern without sodium restriction, and attendance at weekly group meetings until delivery. Control participants received one-time dietary advice. Our three main outcomes were maternal weight change from randomization to 2 weeks postpartum and from randomization to 34 weeks gestation, and newborn large-for-gestational age (birth weight >90th percentile, LGA). Results Intervention participants gained less weight from randomization to 34 weeks gestation (5.0 vs 8.4 kg, mean difference=−3.4 kg, 95% CI [−5.1, −1.8]), and from randomization to 2 weeks postpartum (−2.6 vs +1.2 kg, mean difference=−3.8 kg, 95% CI [−5.9, −1.7]). They also had a lower proportion of LGA babies (9% vs. 26%, odds ratio=0.28, 95% CI [0.09, 0.84]). Conclusions The intervention resulted in lower GWG and lower prevalence of LGA newborns. PMID:25164259

Correlating Fluorescence and High-Resolution Scanning Electron Microscopy (HRSEM) for the study of GABAA receptor clustering induced by inhibitory synaptic plasticity.

PubMed

Orlando, Marta; Ravasenga, Tiziana; Petrini, Enrica Maria; Falqui, Andrea; Marotta, Roberto; Barberis, Andrea

2017-10-23

Both excitatory and inhibitory synaptic contacts display activity dependent dynamic changes in their efficacy that are globally termed synaptic plasticity. Although the molecular mechanisms underlying glutamatergic synaptic plasticity have been extensively investigated and described, those responsible for inhibitory synaptic plasticity are only beginning to be unveiled. In this framework, the ultrastructural changes of the inhibitory synapses during plasticity have been poorly investigated. Here we combined confocal fluorescence microscopy (CFM) with high resolution scanning electron microscopy (HRSEM) to characterize the fine structural rearrangements of post-synaptic GABA A Receptors (GABA A Rs) at the nanometric scale during the induction of inhibitory long-term potentiation (iLTP). Additional electron tomography (ET) experiments on immunolabelled hippocampal neurons allowed the visualization of synaptic contacts and confirmed the reorganization of post-synaptic GABA A R clusters in response to chemical iLTP inducing protocol. Altogether, these approaches revealed that, following the induction of inhibitory synaptic potentiation, GABA A R clusters increase in size and number at the post-synaptic membrane with no other major structural changes of the pre- and post-synaptic elements.

Quantitative proteomics of synaptic and nonsynaptic mitochondria: insights for synaptic mitochondrial vulnerability.

PubMed

Stauch, Kelly L; Purnell, Phillip R; Fox, Howard S

2014-05-02

Synaptic mitochondria are essential for maintaining calcium homeostasis and producing ATP, processes vital for neuronal integrity and synaptic transmission. Synaptic mitochondria exhibit increased oxidative damage during aging and are more vulnerable to calcium insult than nonsynaptic mitochondria. Why synaptic mitochondria are specifically more susceptible to cumulative damage remains to be determined. In this study, the generation of a super-SILAC mix that served as an appropriate internal standard for mouse brain mitochondria mass spectrometry based analysis allowed for the quantification of the proteomic differences between synaptic and nonsynaptic mitochondria isolated from 10-month-old mice. We identified a total of 2260 common proteins between synaptic and nonsynaptic mitochondria of which 1629 were annotated as mitochondrial. Quantitative proteomic analysis of the proteins common between synaptic and nonsynaptic mitochondria revealed significant differential expression of 522 proteins involved in several pathways including oxidative phosphorylation, mitochondrial fission/fusion, calcium transport, and mitochondrial DNA replication and maintenance. In comparison to nonsynaptic mitochondria, synaptic mitochondria exhibited increased age-associated mitochondrial DNA deletions and decreased bioenergetic function. These findings provide insights into synaptic mitochondrial susceptibility to damage.

Quantitative Proteomics of Synaptic and Nonsynaptic Mitochondria: Insights for Synaptic Mitochondrial Vulnerability

PubMed Central

2015-01-01

Synaptic mitochondria are essential for maintaining calcium homeostasis and producing ATP, processes vital for neuronal integrity and synaptic transmission. Synaptic mitochondria exhibit increased oxidative damage during aging and are more vulnerable to calcium insult than nonsynaptic mitochondria. Why synaptic mitochondria are specifically more susceptible to cumulative damage remains to be determined. In this study, the generation of a super-SILAC mix that served as an appropriate internal standard for mouse brain mitochondria mass spectrometry based analysis allowed for the quantification of the proteomic differences between synaptic and nonsynaptic mitochondria isolated from 10-month-old mice. We identified a total of 2260 common proteins between synaptic and nonsynaptic mitochondria of which 1629 were annotated as mitochondrial. Quantitative proteomic analysis of the proteins common between synaptic and nonsynaptic mitochondria revealed significant differential expression of 522 proteins involved in several pathways including oxidative phosphorylation, mitochondrial fission/fusion, calcium transport, and mitochondrial DNA replication and maintenance. In comparison to nonsynaptic mitochondria, synaptic mitochondria exhibited increased age-associated mitochondrial DNA deletions and decreased bioenergetic function. These findings provide insights into synaptic mitochondrial susceptibility to damage. PMID:24708184

Unbiased View of Synaptic and Neuronal Gene Complement in Ctenophores: Are There Pan-neuronal and Pan-synaptic Genes across Metazoa?

PubMed Central

Moroz, Leonid L.; Kohn, Andrea B.

2015-01-01

Hypotheses of origins and evolution of neurons and synapses are controversial, mostly due to limited comparative data. Here, we investigated the genome-wide distribution of the bilaterian “synaptic” and “neuronal” protein-coding genes in non-bilaterian basal metazoans (Ctenophora, Porifera, Placozoa, and Cnidaria). First, there are no recognized genes uniquely expressed in neurons across all metazoan lineages. None of the so-called pan-neuronal genes such as embryonic lethal abnormal vision (ELAV), Musashi, or Neuroglobin are expressed exclusively in neurons of the ctenophore Pleurobrachia. Second, our comparative analysis of about 200 genes encoding canonical presynaptic and postsynaptic proteins in bilaterians suggests that there are no true “pan-synaptic” genes or genes uniquely and specifically attributed to all classes of synapses. The majority of these genes encode receptive and secretory complexes in a broad spectrum of eukaryotes. Trichoplax (Placozoa) an organism without neurons and synapses has more orthologs of bilaterian synapse-related/neuron-related genes than do ctenophores—the group with well-developed neuronal and synaptic organization. Third, the majority of genes encoding ion channels and ionotropic receptors are broadly expressed in unicellular eukaryotes and non-neuronal tissues in metazoans. Therefore, they cannot be viewed as neuronal markers. Nevertheless, the co-expression of multiple types of ion channels and receptors does correlate with the presence of neural and synaptic organization. As an illustrative example, the ctenophore genomes encode a greater diversity of ion channels and ionotropic receptors compared with the genomes of the placozoan Trichoplax and the demosponge Amphimedon. Surprisingly, both placozoans and sponges have a similar number of orthologs of “synaptic” proteins as we identified in the genomes of two ctenophores. Ctenophores have a distinct synaptic organization compared with other animals. Our analysis of transcriptomes from 10 different ctenophores did not detect recognized orthologs of synthetic enzymes encoding several classical, low-molecular-weight (neuro)transmitters; glutamate signaling machinery is one of the few exceptions. Novel peptidergic signaling molecules were predicted for ctenophores, together with the diversity of putative receptors including SCNN1/amiloride-sensitive sodium channel-like channels, many of which could be examples of a lineage-specific expansion within this group. In summary, our analysis supports the hypothesis of independent evolution of neurons and, as corollary, a parallel evolution of synapses. We suggest that the formation of synaptic machinery might occur more than once over 600 million years of animal evolution. PMID:26454853

Fuzzy logic and neural networks in artificial intelligence and pattern recognition

NASA Astrophysics Data System (ADS)

Sanchez, Elie

1991-10-01

With the use of fuzzy logic techniques, neural computing can be integrated in symbolic reasoning to solve complex real world problems. In fact, artificial neural networks, expert systems, and fuzzy logic systems, in the context of approximate reasoning, share common features and techniques. A model of Fuzzy Connectionist Expert System is introduced, in which an artificial neural network is designed to construct the knowledge base of an expert system from, training examples (this model can also be used for specifications of rules in fuzzy logic control). Two types of weights are associated with the synaptic connections in an AND-OR structure: primary linguistic weights, interpreted as labels of fuzzy sets, and secondary numerical weights. Cell activation is computed through min-max fuzzy equations of the weights. Learning consists in finding the (numerical) weights and the network topology. This feedforward network is described and first illustrated in a biomedical application (medical diagnosis assistance from inflammatory-syndromes/proteins profiles). Then, it is shown how this methodology can be utilized for handwritten pattern recognition (characters play the role of diagnoses): in a fuzzy neuron describing a number for example, the linguistic weights represent fuzzy sets on cross-detecting lines and the numerical weights reflect the importance (or weakness) of connections between cross-detecting lines and characters.

Oxide-based synaptic transistors gated by solution-processed gelatin electrolytes

NASA Astrophysics Data System (ADS)

He, Yinke; Sun, Jia; Qian, Chuan; Kong, Ling-An; Gou, Guangyang; Li, Hongjian

2017-04-01

In human brain, a large number of neurons are connected via synapses. Simulation of the synaptic behaviors using electronic devices is the most important step for neuromorphic systems. In this paper, proton conducting gelatin electrolyte-gated oxide field-effect transistors (FETs) were used for emulating synaptic functions, in which the gate electrode is regarded as pre-synaptic neuron and the channel layer as the post-synaptic neuron. In analogy to the biological synapse, a potential spike can be applied at the gate electrode and trigger ionic motion in the gelatin electrolyte, which in turn generates excitatory post-synaptic current (EPSC) in the channel layer. Basic synaptic behaviors including spike time-dependent EPSC, paired-pulse facilitation (PPF), self-adaptation, and frequency-dependent synaptic transmission were successfully mimicked. Such ionic/electronic hybrid devices are beneficial for synaptic electronics and brain-inspired neuromorphic systems.

Random Boolean networks for autoassociative memory: Optimization and sequential learning

NASA Astrophysics Data System (ADS)

Sherrington, D.; Wong, K. Y. M.

Conventional neural networks are based on synaptic storage of information, even when the neural states are discrete and bounded. In general, the set of potential local operations is much greater. Here we discuss some aspects of the properties of networks of binary neurons with more general Boolean functions controlling the local dynamics. Two specific aspects are emphasised; (i) optimization in the presence of noise and (ii) a simple model for short-term memory exhibiting primacy and recency in the recall of sequentially taught patterns.

Structural Synaptic Plasticity Has High Memory Capacity and Can Explain Graded Amnesia, Catastrophic Forgetting, and the Spacing Effect

PubMed Central

Knoblauch, Andreas; Körner, Edgar; Körner, Ursula; Sommer, Friedrich T.

2014-01-01

Although already William James and, more explicitly, Donald Hebb's theory of cell assemblies have suggested that activity-dependent rewiring of neuronal networks is the substrate of learning and memory, over the last six decades most theoretical work on memory has focused on plasticity of existing synapses in prewired networks. Research in the last decade has emphasized that structural modification of synaptic connectivity is common in the adult brain and tightly correlated with learning and memory. Here we present a parsimonious computational model for learning by structural plasticity. The basic modeling units are “potential synapses” defined as locations in the network where synapses can potentially grow to connect two neurons. This model generalizes well-known previous models for associative learning based on weight plasticity. Therefore, existing theory can be applied to analyze how many memories and how much information structural plasticity can store in a synapse. Surprisingly, we find that structural plasticity largely outperforms weight plasticity and can achieve a much higher storage capacity per synapse. The effect of structural plasticity on the structure of sparsely connected networks is quite intuitive: Structural plasticity increases the “effectual network connectivity”, that is, the network wiring that specifically supports storage and recall of the memories. Further, this model of structural plasticity produces gradients of effectual connectivity in the course of learning, thereby explaining various cognitive phenomena including graded amnesia, catastrophic forgetting, and the spacing effect. PMID:24858841

Antidepressant-like effects and possible mechanisms of amantadine on cognitive and synaptic deficits in a rat model of chronic stress.

PubMed

Yu, Mei; Zhang, Yuan; Chen, Xiaoyu; Zhang, Tao

2016-01-01

The aim of this study was to examine whether amantadine (AMA), as a low-affinity noncompetitive N-methyl-d-aspartate (NMDA) receptor antagonist, is able to improve cognitive deficits caused by chronic stress in rats. Male Wistar rats were divided into four groups: control, control + AMA, stress and stress + AMA groups. The chronic stress model combined chronic unpredictable stress (CUS) with isolated feeding. Animals were exposed to CUS continued for 21 days. AMA (25 mg/kg) was administrated p.o. for 20 days from the 4th day of CUS to the 23rd. Weight and sucrose consumption were measured during model establishing period. Spatial memory was evaluated using the Morris water maze (MWM) test. Following MWM testing, both long-term potentiation (LTP) and depotentiation were recorded in the hippocampal CA1 region. NR2B and postsynaptic density protein 95 (PSD-95) proteins were measured by Western-blot analysis. AMA increased weight and sucrose consumption of stressed rats. Spatial memory and reversal learning in stressed rats were impaired relative to controls, whereas AMA significantly attenuated cognitive impairment. AMA also mitigated the chronic stress-induced impairment of hippocampal synaptic plasticity, in which both the LTP and depotentiation were significantly inhibited in stressed rats. Moreover, AMA enhanced the expression of hippocampal NR2B and PSD-95 in stressed rats. The data suggest that AMA may be an effective therapeutic agent for depression-like symptoms and associated cognitive disturbances.

On the correlation between reservoir metrics and performance for time series classification under the influence of synaptic plasticity.

PubMed

Chrol-Cannon, Joseph; Jin, Yaochu

2014-01-01

Reservoir computing provides a simpler paradigm of training recurrent networks by initialising and adapting the recurrent connections separately to a supervised linear readout. This creates a problem, though. As the recurrent weights and topology are now separated from adapting to the task, there is a burden on the reservoir designer to construct an effective network that happens to produce state vectors that can be mapped linearly into the desired outputs. Guidance in forming a reservoir can be through the use of some established metrics which link a number of theoretical properties of the reservoir computing paradigm to quantitative measures that can be used to evaluate the effectiveness of a given design. We provide a comprehensive empirical study of four metrics; class separation, kernel quality, Lyapunov's exponent and spectral radius. These metrics are each compared over a number of repeated runs, for different reservoir computing set-ups that include three types of network topology and three mechanisms of weight adaptation through synaptic plasticity. Each combination of these methods is tested on two time-series classification problems. We find that the two metrics that correlate most strongly with the classification performance are Lyapunov's exponent and kernel quality. It is also evident in the comparisons that these two metrics both measure a similar property of the reservoir dynamics. We also find that class separation and spectral radius are both less reliable and less effective in predicting performance.

Palisade pattern of mormyrid Purkinje cells: a correlated light and electron microscopic study.

PubMed

Meek, J; Nieuwenhuys, R

1991-04-01

The present study is devoted to a detailed analysis of the structural and synaptic organization of mormyrid Purkinje cells in order to evaluate the possible functional significance of their dendritic palisade pattern. For this purpose, the properties of Golgi-impregnated as well as unimpregnated Purkinje cells in lobe C1 and C3 of the cerebellum of Gnathonemus petersii were light and electron microscopically analyzed, quantified, reconstructed, and mutually compared. Special attention was paid to the degree of regularity of their dendritic trees, their relations with Bergmann glia, and the distribution and numerical properties of their synaptic connections with parallel fibers, stellate cells, "climbing" fibers, and Purkinje axonal boutons. The highest degree of palisade specialization was encountered in lobe C1, where Purkinje cells have on average 50 palisade dendrites with a very regular distribution in a sagittal plane. Their spine density decreases from superficial to deep (from 14 to 6 per micron dendritic length), a gradient correlated with a decreasing parallel fiber density but an increasing parallel fiber diameter. Each Purkinje cell makes on average 75,000 synaptic contacts with parallel fibers, some of which are rather coarse (0.45 microns), and provided with numerous short collaterals. Climbing fibers do not climb, since their synaptic contacts are restricted to the ganglionic layer (i.e., the layer of Purkinje and eurydendroid projection cells), where they make about 130 synaptic contacts per cell with 2 or 3 clusters of thorns on the proximal dendrites. These clusters contain also a type of "shunting" elements that make desmosome-like junctions with both the climbing fiber boutons and the necks of the thorns. The axons of Purkinje cells in lobe C1 make small terminal arborizations, with about 20 boutons, that may be substantially (up to 500 microns) displaced rostrally or caudally with respect to the soma. Purkinje axonal boutons were observed to make synaptic contacts with eurydendroid projection cells and with the proximal dendritic and somatic receptive surface of Purkinje cells, where about 15 randomly distributed boutons per neuron occur. The organization of Purkinje cells in lobe C3 differs markedly from that in C1 and seems to be less regular and specialized, although the overall palisade pattern is even more regular than in lobe C1 because of the absence of large eurydendroid neurons. However, individual neurons have a less regular dendritic tree, there is no apical-basal gradient in spine density or parallel fiber density and diameter, and there are no "shunting" elements in the climbing fiber glomeruli.(ABSTRACT TRUNCATED AT 400 WORDS)

A Model of Bidirectional Synaptic Plasticity: From Signaling Network to Channel Conductance

ERIC Educational Resources Information Center

Castellani, Gastone C.; Quinlan, Elizabeth M.; Bersani, Ferdinando; Cooper, Leon N.; Shouval, Harel Z.

2005-01-01

In many regions of the brain, including the mammalian cortex, the strength of synaptic transmission can be bidirectionally regulated by cortical activity (synaptic plasticity). One line of evidence indicates that long-term synaptic potentiation (LTP) and long-term synaptic depression (LTD), correlate with the phosphorylation/dephosphorylation of…

Ca2+ Dependence of Synaptic Vesicle Endocytosis.

PubMed

Leitz, Jeremy; Kavalali, Ege T

2016-10-01

Ca(2+)-dependent synaptic vesicle recycling is essential for structural homeostasis of synapses and maintenance of neurotransmission. Although, the executive role of intrasynaptic Ca(2+) transients in synaptic vesicle exocytosis is well established, identifying the exact role of Ca(2+) in endocytosis has been difficult. In some studies, Ca(2+) has been suggested as an essential trigger required to initiate synaptic vesicle retrieval, whereas others manipulating synaptic Ca(2+) concentrations reported a modulatory role for Ca(2+) leading to inhibition or acceleration of endocytosis. Molecular studies of synaptic vesicle endocytosis, on the other hand, have consistently focused on the roles of Ca(2+)-calmodulin dependent phosphatase calcineurin and synaptic vesicle protein synaptotagmin as potential Ca(2+) sensors for endocytosis. Most studies probing the role of Ca(2+) in endocytosis have relied on measurements of synaptic vesicle retrieval after strong stimulation. Strong stimulation paradigms elicit fusion and retrieval of multiple synaptic vesicles and therefore can be affected by several factors besides the kinetics and duration of Ca(2+) signals that include the number of exocytosed vesicles and accumulation of released neurotransmitters thus altering fusion and retrieval processes indirectly via retrograde signaling. Studies monitoring single synaptic vesicle endocytosis may help resolve this conundrum as in these settings the impact of Ca(2+) on synaptic fusion probability can be uncoupled from its putative role on synaptic vesicle retrieval. Future experiments using these single vesicle approaches will help dissect the specific role(s) of Ca(2+) and its sensors in synaptic vesicle endocytosis. © The Author(s) 2015.

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

NASA Astrophysics Data System (ADS)

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.

Episodic sucrose intake during food restriction increases synaptic abundance of AMPA receptors in nucleus accumbens and augments intake of sucrose following restoration of ad libitum feeding.

PubMed

Peng, X-X; Lister, A; Rabinowitsch, A; Kolaric, R; Cabeza de Vaca, S; Ziff, E B; Carr, K D

2015-06-04

Weight-loss dieting often leads to loss of control, rebound weight gain, and is a risk factor for binge pathology. Based on findings that food restriction (FR) upregulates sucrose-induced trafficking of glutamatergic AMPA receptors to the nucleus accumbens (NAc) postsynaptic density (PSD), this study was an initial test of the hypothesis that episodic "breakthrough" intake of forbidden food during dieting interacts with upregulated mechanisms of synaptic plasticity to increase reward-driven feeding. Ad libitum (AL) fed and FR subjects consumed a limited amount of 10% sucrose, or had access to water, every other day for 10 occasions. Beginning three weeks after return of FR rats to AL feeding, when 24-h chow intake and rate of body weight gain had normalized, subjects with a history of sucrose intake during FR consumed more sucrose during a four week intermittent access protocol than the two AL groups and the group that had access to water during FR. In an experiment that substituted noncontingent administration of d-amphetamine for sucrose, FR subjects displayed an enhanced locomotor response during active FR but a blunted response, relative to AL subjects, during recovery from FR. This result suggests that the enduring increase in sucrose consumption is unlikely to be explained by residual enhancing effects of FR on dopamine signaling. In a biochemical experiment which paralleled the sucrose behavioral experiment, rats with a history of sucrose intake during FR displayed increased abundance of pSer845-GluA1, GluA2, and GluA3 in the NAc PSD relative to rats with a history of FR without sucrose access and rats that had been AL throughout, whether they had a history of episodic sucrose intake or not. A history of FR, with or without a history of sucrose intake, was associated with increased abundance of GluA1. A terminal 15-min bout of sucrose intake produced a further increase in pSer845-GluA1 and GluA2 in subjects with a history of sucrose intake during FR. Generally, neither a history of sucrose intake nor a terminal bout of sucrose intake affected AMPA receptor abundance in the NAc PSD of AL subjects. Together, these results are consistent with the hypothesis, but the functional contribution of increased synaptic incorporation of AMPA receptors remains to be established. Copyright © 2015 IBRO. Published by Elsevier Ltd. All rights reserved.

Extrasynaptic exocytosis and its mechanisms: a source of molecules mediating volume transmission in the nervous system.

PubMed

Trueta, Citlali; De-Miguel, Francisco F

2012-01-01

We review the evidence of exocytosis from extrasynaptic sites in the soma, dendrites, and axonal varicosities of central and peripheral neurons of vertebrates and invertebrates, with emphasis on somatic exocytosis, and how it contributes to signaling in the nervous system. The finding of secretory vesicles in extrasynaptic sites of neurons, the presence of signaling molecules (namely transmitters or peptides) in the extracellular space outside synaptic clefts, and the mismatch between exocytosis sites and the location of receptors for these molecules in neurons and glial cells, have long suggested that in addition to synaptic communication, transmitters are released, and act extrasynaptically. The catalog of these molecules includes low molecular weight transmitters such as monoamines, acetylcholine, glutamate, gama-aminobutiric acid (GABA), adenosine-5-triphosphate (ATP), and a list of peptides including substance P, brain-derived neurotrophic factor (BDNF), and oxytocin. By comparing the mechanisms of extrasynaptic exocytosis of different signaling molecules by various neuron types we show that it is a widespread mechanism for communication in the nervous system that uses certain common mechanisms, which are different from those of synaptic exocytosis but similar to those of exocytosis from excitable endocrine cells. Somatic exocytosis has been measured directly in different neuron types. It starts after high-frequency electrical activity or long experimental depolarizations and may continue for several minutes after the end of stimulation. Activation of L-type calcium channels, calcium release from intracellular stores and vesicle transport towards the plasma membrane couple excitation and exocytosis from small clear or large dense core vesicles in release sites lacking postsynaptic counterparts. The presence of synaptic and extrasynaptic exocytosis endows individual neurons with a wide variety of time- and space-dependent communication possibilities. Extrasynaptic exocytosis may be the major source of signaling molecules producing volume transmission and by doing so may be part of a long duration signaling mode in the nervous system.

Prenatal caffeine intake differently affects synaptic proteins during fetal brain development.

PubMed

Mioranzza, Sabrina; Nunes, Fernanda; Marques, Daniela M; Fioreze, Gabriela T; Rocha, Andréia S; Botton, Paulo Henrique S; Costa, Marcelo S; Porciúncula, Lisiane O

2014-08-01

Caffeine is the psychostimulant most consumed worldwide. However, little is known about its effects during fetal brain development. In this study, adult female Wistar rats received caffeine in drinking water (0.1, 0.3 and 1.0 g/L) during the active cycle in weekdays, two weeks before mating and throughout pregnancy. Cerebral cortex and hippocampus from embryonic stages 18 or 20 (E18 or E20, respectively) were collected for immunodetection of the following synaptic proteins: brain-derived neurotrophic factor (BDNF), TrkB receptor, Sonic Hedgehog (Shh), Growth Associated Protein 43 (GAP-43) and Synaptosomal-associated Protein 25 (SNAP-25). Besides, the estimation of NeuN-stained nuclei (mature neurons) and non-neuronal nuclei was verified in both brain regions and embryonic periods. Caffeine (1.0 g/L) decreased the body weight of embryos at E20. Cortical BDNF at E18 was decreased by caffeine (1.0 g/L), while it increased at E20, with no major effects on TrkB receptors. In the hippocampus, caffeine decreased TrkB receptor only at E18, with no effects on BDNF. Moderate and high doses of caffeine promoted an increase in Shh in both brain regions at E18, and in the hippocampus at E20. Caffeine (0.3g/L) decreased GAP-43 only in the hippocampus at E18. The NeuN-stained nuclei increased in the cortex at E20 by lower dose and in the hippocampus at E18 by moderate dose. Our data revealed that caffeine transitorily affect synaptic proteins during fetal brain development. The increased number of NeuN-stained nuclei by prenatal caffeine suggests a possible acceleration of the telencephalon maturation. Although some modifications in the synaptic proteins were transient, our data suggest that caffeine even in lower doses may alter the fetal brain development. Copyright © 2014 ISDN. Published by Elsevier Ltd. All rights reserved.

Rivastigmine Lowers Aβ and Increases sAPPα Levels, Which Parallel Elevated Synaptic Markers and Metabolic Activity in Degenerating Primary Rat Neurons

PubMed Central

Bailey, Jason A.; Ray, Balmiki; Greig, Nigel H.; Lahiri, Debomoy K.

2011-01-01

Overproduction of amyloid-β (Aβ) protein in the brain has been hypothesized as the primary toxic insult that, via numerous mechanisms, produces cognitive deficits in Alzheimer's disease (AD). Cholinesterase inhibition is a primary strategy for treatment of AD, and specific compounds of this class have previously been demonstrated to influence Aβ precursor protein (APP) processing and Aβ production. However, little information is available on the effects of rivastigmine, a dual acetylcholinesterase and butyrylcholinesterase inhibitor, on APP processing. As this drug is currently used to treat AD, characterization of its various activities is important to optimize its clinical utility. We have previously shown that rivastigmine can preserve or enhance neuronal and synaptic terminal markers in degenerating primary embryonic cerebrocortical cultures. Given previous reports on the effects of APP and Aβ on synapses, regulation of APP processing represents a plausible mechanism for the synaptic effects of rivastigmine. To test this hypothesis, we treated degenerating primary cultures with rivastigmine and measured secreted APP (sAPP) and Aβ. Rivastigmine treatment increased metabolic activity in these cultured cells, and elevated APP secretion. Analysis of the two major forms of APP secreted by these cultures, attributed to neurons or glia based on molecular weight showed that rivastigmine treatment significantly increased neuronal relative to glial secreted APP. Furthermore, rivastigmine treatment increased α-secretase cleaved sAPPα and decreased Aβ secretion, suggesting a therapeutic mechanism wherein rivastigmine alters the relative activities of the secretase pathways. Assessment of sAPP levels in rodent CSF following once daily rivastigmine administration for 21 days confirmed that elevated levels of APP in cell culture translated in vivo. Taken together, rivastigmine treatment enhances neuronal sAPP and shifts APP processing toward the α-secretase pathway in degenerating neuronal cultures, which mirrors the trend of synaptic proteins, and metabolic activity. PMID:21799757

Weighted Scaling in Non-growth Random Networks

NASA Astrophysics Data System (ADS)

Chen, Guang; Yang, Xu-Hua; Xu, Xin-Li

2012-09-01

We propose a weighted model to explain the self-organizing formation of scale-free phenomenon in non-growth random networks. In this model, we use multiple-edges to represent the connections between vertices and define the weight of a multiple-edge as the total weights of all single-edges within it and the strength of a vertex as the sum of weights for those multiple-edges attached to it. The network evolves according to a vertex strength preferential selection mechanism. During the evolution process, the network always holds its total number of vertices and its total number of single-edges constantly. We show analytically and numerically that a network will form steady scale-free distributions with our model. The results show that a weighted non-growth random network can evolve into scale-free state. It is interesting that the network also obtains the character of an exponential edge weight distribution. Namely, coexistence of scale-free distribution and exponential distribution emerges.

Weighted re-randomization tests for minimization with unbalanced allocation.

PubMed

Han, Baoguang; Yu, Menggang; McEntegart, Damian

2013-01-01

Re-randomization test has been considered as a robust alternative to the traditional population model-based methods for analyzing randomized clinical trials. This is especially so when the clinical trials are randomized according to minimization, which is a popular covariate-adaptive randomization method for ensuring balance among prognostic factors. Among various re-randomization tests, fixed-entry-order re-randomization is advocated as an effective strategy when a temporal trend is suspected. Yet when the minimization is applied to trials with unequal allocation, fixed-entry-order re-randomization test is biased and thus compromised in power. We find that the bias is due to non-uniform re-allocation probabilities incurred by the re-randomization in this case. We therefore propose a weighted fixed-entry-order re-randomization test to overcome the bias. The performance of the new test was investigated in simulation studies that mimic the settings of a real clinical trial. The weighted re-randomization test was found to work well in the scenarios investigated including the presence of a strong temporal trend. Copyright © 2013 John Wiley & Sons, Ltd.

Preparation of synaptic plasma membrane and postsynaptic density proteins using a discontinuous sucrose gradient.

PubMed

Bermejo, Marie Kristel; Milenkovic, Marija; Salahpour, Ali; Ramsey, Amy J

2014-09-03

Neuronal subcellular fractionation techniques allow the quantification of proteins that are trafficked to and from the synapse. As originally described in the late 1960's, proteins associated with the synaptic plasma membrane can be isolated by ultracentrifugation on a sucrose density gradient. Once synaptic membranes are isolated, the macromolecular complex known as the post-synaptic density can be subsequently isolated due to its detergent insolubility. The techniques used to isolate synaptic plasma membranes and post-synaptic density proteins remain essentially the same after 40 years, and are widely used in current neuroscience research. This article details the fractionation of proteins associated with the synaptic plasma membrane and post-synaptic density using a discontinuous sucrose gradient. Resulting protein preparations are suitable for western blotting or 2D DIGE analysis.

Diversity of neuropsin (KLK8)-dependent synaptic associativity in the hippocampal pyramidal neuron

PubMed Central

Ishikawa, Yasuyuki; Tamura, Hideki; Shiosaka, Sadao

2011-01-01

Abstract Hippocampal early (E-) long-term potentiation (LTP) and long-term depression (LTD) elicited by a weak stimulus normally fades within 90 min. Late (L-) LTP and LTD elicited by strong stimuli continue for >180 min and require new protein synthesis to persist. If a strong tetanus is applied once to synaptic inputs, even a weak tetanus applied to another synaptic input can evoke persistent LTP. A synaptic tag is hypothesized to enable the capture of newly synthesized synaptic molecules. This process, referred to as synaptic tagging, is found between not only the same processes (i.e. E- and L-LTP; E- and L-LTD) but also between different processes (i.e. E-LTP and L-LTD; E-LTD and L-LTP) induced at two independent synaptic inputs (cross-tagging). However, the mechanisms of synaptic tag setting remain unclear. In our previous study, we found that synaptic associativity in the hippocampal Schaffer collateral pathway depended on neuropsin (kallikrein-related peptidase 8 or KLK8), a plasticity-related extracellular protease. In the present study, we investigated how neuropsin participates in synaptic tagging and cross-tagging. We report that neuropsin is involved in synaptic tagging during LTP at basal and apical dendritic inputs. Moreover, neuropsin is involved in synaptic tagging and cross-tagging during LTP at apical dendritic inputs via integrin β1 and calcium/calmodulin-dependent protein kinase II signalling. Thus, neuropsin is a candidate molecule for the LTP-specific tag setting and regulates the transformation of E- to L-LTP during both synaptic tagging and cross-tagging. PMID:21646406

Healthy Moms, a randomized trial to promote and evaluate weight maintenance among obese pregnant women: study design and rationale

PubMed Central

Vesco, Kimberly K.; Karanja, Njeri; King, Janet C.; Gillman, Matthew W.; Perrin, Nancy; McEvoy, Cindy; Eckhardt, Cara; Smith, K. Sabina; Stevens, Victor J.

2012-01-01

Background Obesity and excessive weight gain during pregnancy are associated with adverse pregnancy outcomes. Observational studies suggest that minimal or no gestational weight gain (GWG) may minimize the risk of adverse pregnancy outcomes for obese women. Objective This report describes the design of Healthy Moms, a randomized trial testing a weekly, group-based, weight management intervention designed to help limit GWG to 3% of weight (measured at the time of randomization) among obese pregnant women (BMI ≥30 kg/m2). Participants are randomized at 10–20 weeks gestation to either the intervention or a single dietary advice control condition. Primary Outcomes The study is powered for the primary outcome of total GWG, yielding a target sample size of 160 women. Additional secondary outcomes include weight change between randomization and one-year postpartum and proportion of infants with birth weight > 90th percentile for gestational age. Statistical analyses will be based on intention-to-treat. Methods Following randomization, all participants receive a 45-minute dietary consultation. They are encouraged to follow the Dietary Approaches to Stop Hypertension diet without sodium restriction. Intervention group participants receive an individualized calorie intake goal, a second individual counseling session and attend weekly group meetings until they give birth. Research staff assess all participants at 34-weeks gestation and at 2-weeks and one-year postpartum with their infants. Summary The Healthy Moms study is testing weight management techniques that have been used with non-pregnant adults. We aim to help obese women limit GWG to improve their long-term health and the health of their offspring. PMID:22465256

A weighted ℓ{sub 1}-minimization approach for sparse polynomial chaos expansions

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

Peng, Ji; Hampton, Jerrad; Doostan, Alireza, E-mail: alireza.doostan@colorado.edu

2014-06-15

This work proposes a method for sparse polynomial chaos (PC) approximation of high-dimensional stochastic functions based on non-adapted random sampling. We modify the standard ℓ{sub 1}-minimization algorithm, originally proposed in the context of compressive sampling, using a priori information about the decay of the PC coefficients, when available, and refer to the resulting algorithm as weightedℓ{sub 1}-minimization. We provide conditions under which we may guarantee recovery using this weighted scheme. Numerical tests are used to compare the weighted and non-weighted methods for the recovery of solutions to two differential equations with high-dimensional random inputs: a boundary value problem with amore » random elliptic operator and a 2-D thermally driven cavity flow with random boundary condition.« less

Social patterns revealed through random matrix theory

NASA Astrophysics Data System (ADS)

Sarkar, Camellia; Jalan, Sarika

2014-11-01

Despite the tremendous advancements in the field of network theory, very few studies have taken weights in the interactions into consideration that emerge naturally in all real-world systems. Using random matrix analysis of a weighted social network, we demonstrate the profound impact of weights in interactions on emerging structural properties. The analysis reveals that randomness existing in particular time frame affects the decisions of individuals rendering them more freedom of choice in situations of financial security. While the structural organization of networks remains the same throughout all datasets, random matrix theory provides insight into the interaction pattern of individuals of the society in situations of crisis. It has also been contemplated that individual accountability in terms of weighted interactions remains as a key to success unless segregation of tasks comes into play.

Design and methods for a randomized clinical trial treating comorbid obesity and major depressive disorder

PubMed Central

Schneider, Kristin L; Bodenlos, Jamie S; Ma, Yunsheng; Olendzki, Barbara; Oleski, Jessica; Merriam, Philip; Crawford, Sybil; Ockene, Ira S; Pagoto, Sherry L

2008-01-01

Background Obesity is often comorbid with depression and individuals with this comorbidity fare worse in behavioral weight loss treatment. Treating depression directly prior to behavioral weight loss treatment might bolster weight loss outcomes in this population, but this has not yet been tested in a randomized clinical trial. Methods and design This randomized clinical trial will examine whether behavior therapy for depression administered prior to standard weight loss treatment produces greater weight loss than standard weight loss treatment alone. Obese women with major depressive disorder (N = 174) will be recruited from primary care clinics and the community and randomly assigned to one of the two treatment conditions. Treatment will last 2 years, and will include a 6-month intensive treatment phase followed by an 18-month maintenance phase. Follow-up assessment will occur at 6-months and 1- and 2 years following randomization. The primary outcome is weight loss. The study was designed to provide 90% power for detecting a weight change difference between conditions of 3.1 kg (standard deviation of 5.5 kg) at 1-year assuming a 25% rate of loss to follow-up. Secondary outcomes include depression, physical activity, dietary intake, psychosocial variables and cardiovascular risk factors. Potential mediators (e.g., adherence, depression, physical activity and caloric intake) of the intervention effect on weight change will also be examined. Discussion Treating depression before administering intensive health behavior interventions could potentially boost the impact on both mental and physical health outcomes. Trial registration NCT00572520 PMID:18793398

Non-synaptic receptors and transporters involved in brain functions and targets of drug treatment.

PubMed

Vizi, E S; Fekete, A; Karoly, R; Mike, A

2010-06-01

Beyond direct synaptic communication, neurons are able to talk to each other without making synapses. They are able to send chemical messages by means of diffusion to target cells via the extracellular space, provided that the target neurons are equipped with high-affinity receptors. While synaptic transmission is responsible for the 'what' of brain function, the 'how' of brain function (mood, attention, level of arousal, general excitability, etc.) is mainly controlled non-synaptically using the extracellular space as communication channel. It is principally the 'how' that can be modulated by medicine. In this paper, we discuss different forms of non-synaptic transmission, localized spillover of synaptic transmitters, local presynaptic modulation and tonic influence of ambient transmitter levels on the activity of vast neuronal populations. We consider different aspects of non-synaptic transmission, such as synaptic-extrasynaptic receptor trafficking, neuron-glia communication and retrograde signalling. We review structural and functional aspects of non-synaptic transmission, including (i) anatomical arrangement of non-synaptic release sites, receptors and transporters, (ii) intravesicular, intra- and extracellular concentrations of neurotransmitters, as well as the spatiotemporal pattern of transmitter diffusion. We propose that an effective general strategy for efficient pharmacological intervention could include the identification of specific non-synaptic targets and the subsequent development of selective pharmacological tools to influence them.

Input clustering in the normal and learned circuits of adult barn owls.

PubMed

McBride, Thomas J; DeBello, William M

2015-05-01

Experience-dependent formation of synaptic input clusters can occur in juvenile brains. Whether this also occurs in adults is largely unknown. We previously reconstructed the normal and learned circuits of prism-adapted barn owls and found that changes in clustering of axo-dendritic contacts (putative synapses) predicted functional circuit strength. Here we asked whether comparable changes occurred in normal and prism-removed adults. Across all anatomical zones, no systematic differences in the primary metrics for within-branch or between-branch clustering were observed: 95-99% of contacts resided within clusters (<10-20 μm from nearest neighbor) regardless of circuit strength. Bouton volumes, a proxy measure of synaptic strength, were on average larger in the functionally strong zones, indicating that changes in synaptic efficacy contributed to the differences in circuit strength. Bootstrap analysis showed that the distribution of inter-contact distances strongly deviated from random not in the functionally strong zones but in those that had been strong during the sensitive period (60-250 d), indicating that clusters formed early in life were preserved regardless of current value. While cluster formation in juveniles appeared to require the production of new synapses, cluster formation in adults did not. In total, these results support a model in which high cluster dynamics in juveniles sculpt a potential connectivity map that is refined in adulthood. We propose that preservation of clusters in functionally weak adult circuits provides a storage mechanism for disused but potentially useful pathways. Copyright © 2015 Elsevier Inc. All rights reserved.

The effectiveness of breakfast recommendations on weight loss: a randomized controlled trial123

PubMed Central

Dhurandhar, Emily J; Dawson, John; Alcorn, Amy; Larsen, Lesli H; Thomas, Elizabeth A; Cardel, Michelle; Bourland, Ashley C; Astrup, Arne; St-Onge, Marie-Pierre; Hill, James O; Apovian, Caroline M; Shikany, James M; Allison, David B

2014-01-01

Background: Breakfast is associated with lower body weight in observational studies. Public health authorities commonly recommend breakfast consumption to reduce obesity, but the effectiveness of adopting these recommendations for reducing body weight is unknown. Objective: We tested the relative effectiveness of a recommendation to eat or skip breakfast on weight loss in adults trying to lose weight in a free-living setting. Design: We conducted a multisite, 16-wk, 3-parallel-arm randomized controlled trial in otherwise healthy overweight and obese adults [body mass index (in kg/m2) between 25 and 40] aged 20–65 y. Our primary outcome was weight change. We compared weight change in a control group with weight loss in experimental groups told to eat breakfast or to skip breakfast [no breakfast (NB)]. Randomization was stratified by prerandomization breakfast eating habits. A total of 309 participants were randomly assigned. Results: A total of 283 of the 309 participants who were randomly assigned completed the intervention. Treatment assignment did not have a significant effect on weight loss, and there was no interaction between initial breakfast eating status and treatment. Among skippers, mean (±SD) baseline weight-, age-, sex-, site-, and race-adjusted weight changes were −0.71 ± 1.16, −0.76 ± 1.26, and −0.61 ± 1.18 kg for the control, breakfast, and NB groups, respectively. Among breakfast consumers, mean (±SD) baseline weight-, age-, sex-, site-, and race-adjusted weight changes were −0.53 ± 1.16, −0.59 ± 1.06, and −0.71 ± 1.17 kg for the control, breakfast, and NB groups, respectively. Self-reported compliance with the recommendation was 93.6% for the breakfast group and 92.4% for the NB group. Conclusions: A recommendation to eat or skip breakfast for weight loss was effective at changing self-reported breakfast eating habits, but contrary to widely espoused views this had no discernable effect on weight loss in free-living adults who were attempting to lose weight. This trial was registered at clinicaltrails.gov as NCT01781780. PMID:24898236

Cell-specific gain modulation by synaptically released zinc in cortical circuits of audition.

PubMed

Anderson, Charles T; Kumar, Manoj; Xiong, Shanshan; Tzounopoulos, Thanos

2017-09-09

In many excitatory synapses, mobile zinc is found within glutamatergic vesicles and is coreleased with glutamate. Ex vivo studies established that synaptically released (synaptic) zinc inhibits excitatory neurotransmission at lower frequencies of synaptic activity but enhances steady state synaptic responses during higher frequencies of activity. However, it remains unknown how synaptic zinc affects neuronal processing in vivo. Here, we imaged the sound-evoked neuronal activity of the primary auditory cortex in awake mice. We discovered that synaptic zinc enhanced the gain of sound-evoked responses in CaMKII-expressing principal neurons, but it reduced the gain of parvalbumin- and somatostatin-expressing interneurons. This modulation was sound intensity-dependent and, in part, NMDA receptor-independent. By establishing a previously unknown link between synaptic zinc and gain control of auditory cortical processing, our findings advance understanding about cortical synaptic mechanisms and create a new framework for approaching and interpreting the role of the auditory cortex in sound processing.

[Effect of electroacupuncture on cellular structure of hippocampus in splenic asthenia pedo-rats].

PubMed

Yang, Zhuo-xin; Zhuo, Yuan-yuan; Yu, Hai-bo; Wang, Ning

2010-02-01

To observe the effect of electroacupuncture (EA) on hippocampal structure in splenic asthenia pedo-rats. A total of 15 SD male rats were randomly assigned to normal control group (n=5), model group (n=5) and EA group (n=5). Splenic asthenic syndrome model was established by intragastric administration of rhubarb and intraperitoneal injection of Reserpine for 14 d. EA (1 mA, 3 Hz/iS Hz) was applied to bilateral "Zusanli" (ST 36) and "Sanyinjiao" (SP 6) for 20 mm, once a day for 14 days. The cellular structure of hippocampus was observed by light microscope and transmission electron microscope. Optical microscopic observation showed that in normal control group, the cellular nucleus was distinct, and the granular cell layer well-arranged and tight. In model group, the intracellular space was widened, and the granular cell layer was out of order in the arrangement. In EA group, the celluldr nucleus and the granular cell layer were nearly normal. Results of the electronic microscope showed that cells in model group had a karyopyknosis with irregular appearance and clear incisure, and some of them presented dissolving and necrotic phenomena; and those in EA group were milder in injury, had nearly-normal nucleus with visible nucleoli and relatively-intact nuclear membrane. Regarding the cellular plasma, in comparison with rich normal organelles of control group, the mitochondria in model group were swelling, with vague, dissolved and broken cristae, while in EA group, majority of the organelles were well-kept, and slightly dissolved mitochondrial cristae found. In regard to the synaptic structure, in comparison with control group, synaptic apomorphosis and swelling mitochondria were found in model group While in EA group, milder swelling and hydropic degeneration were seen. Different from the distinct pre- and post-synaptic membrane and synaptic vesicles of control group, while those in EA group were nearly-normal. electroacupunture can effectively relieve splenasthenic syndrome induced pathohistological changes of neurons of the hippocampus in the rat.

Phasic Firing in Vasopressin Cells: Understanding Its Functional Significance through Computational Models

PubMed Central

MacGregor, Duncan J.; Leng, Gareth

2012-01-01

Vasopressin neurons, responding to input generated by osmotic pressure, use an intrinsic mechanism to shift from slow irregular firing to a distinct phasic pattern, consisting of long bursts and silences lasting tens of seconds. With increased input, bursts lengthen, eventually shifting to continuous firing. The phasic activity remains asynchronous across the cells and is not reflected in the population output signal. Here we have used a computational vasopressin neuron model to investigate the functional significance of the phasic firing pattern. We generated a concise model of the synaptic input driven spike firing mechanism that gives a close quantitative match to vasopressin neuron spike activity recorded in vivo, tested against endogenous activity and experimental interventions. The integrate-and-fire based model provides a simple physiological explanation of the phasic firing mechanism involving an activity-dependent slow depolarising afterpotential (DAP) generated by a calcium-inactivated potassium leak current. This is modulated by the slower, opposing, action of activity-dependent dendritic dynorphin release, which inactivates the DAP, the opposing effects generating successive periods of bursting and silence. Model cells are not spontaneously active, but fire when perturbed by random perturbations mimicking synaptic input. We constructed one population of such phasic neurons, and another population of similar cells but which lacked the ability to fire phasically. We then studied how these two populations differed in the way that they encoded changes in afferent inputs. By comparison with the non-phasic population, the phasic population responds linearly to increases in tonic synaptic input. Non-phasic cells respond to transient elevations in synaptic input in a way that strongly depends on background activity levels, phasic cells in a way that is independent of background levels, and show a similar strong linearization of the response. These findings show large differences in information coding between the populations, and apparent functional advantages of asynchronous phasic firing. PMID:23093929

Supervised learning of probability distributions by neural networks

NASA Technical Reports Server (NTRS)

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.

Enhanced AMPA Receptor Trafficking Mediates the Anorexigenic Effect of Endogenous Glucagon-like Peptide-1 in the Paraventricular Hypothalamus.

PubMed

Liu, Ji; Conde, Kristie; Zhang, Peng; Lilascharoen, Varoth; Xu, Zihui; Lim, Byung Kook; Seeley, Randy J; Zhu, J Julius; Scott, Michael M; Pang, Zhiping P

2017-11-15

Glucagon-like Peptide 1 (GLP-1)-expressing neurons in the hindbrain send robust projections to the paraventricular nucleus of the hypothalamus (PVN), which is involved in the regulation of food intake. Here, we describe that stimulation of GLP-1 afferent fibers within the PVN is sufficient to suppress food intake independent of glutamate release. We also show that GLP-1 receptor (GLP-1R) activation augments excitatory synaptic strength in PVN corticotropin-releasing hormone (CRH) neurons, with GLP-1R activation promoting a protein kinase A (PKA)-dependent signaling cascade leading to phosphorylation of serine S845 on GluA1 AMPA receptors and their trafficking to the plasma membrane. Finally, we show that postnatal depletion of GLP-1R in the PVN increases food intake and causes obesity. This study provides a comprehensive multi-level (circuit, synaptic, and molecular) explanation of how food intake behavior and body weight are regulated by endogenous central GLP-1. VIDEO ABSTRACT. Copyright © 2017 Elsevier Inc. All rights reserved.

Development of a Highly Automated and Multiplexed Targeted Proteome Pipeline and Assay for 112 Rat Brain Synaptic Proteins

PubMed Central

Colangelo, Christopher M.; Ivosev, Gordana; Chung, Lisa; Abbott, Thomas; Shifman, Mark; Sakaue, Fumika; Cox, David; Kitchen, Rob R.; Burton, Lyle; Tate, Stephen A; Gulcicek, Erol; Bonner, Ron; Rinehart, Jesse; Nairn, Angus C.; Williams, Kenneth R.

2015-01-01

We present a comprehensive workflow for large scale (>1000 transitions/run) label-free LC-MRM proteome assays. Innovations include automated MRM transition selection, intelligent retention time scheduling (xMRM) that improves Signal/Noise by >2-fold, and automatic peak modeling. Improvements to data analysis include a novel Q/C metric, Normalized Group Area Ratio (NGAR), MLR normalization, weighted regression analysis, and data dissemination through the Yale Protein Expression Database. As a proof of principle we developed a robust 90 minute LC-MRM assay for Mouse/Rat Post-Synaptic Density (PSD) fractions which resulted in the routine quantification of 337 peptides from 112 proteins based on 15 observations per protein. Parallel analyses with stable isotope dilution peptide standards (SIS), demonstrate very high correlation in retention time (1.0) and protein fold change (0.94) between the label-free and SIS analyses. Overall, our first method achieved a technical CV of 11.4% with >97.5% of the 1697 transitions being quantified without user intervention, resulting in a highly efficient, robust, and single injection LC-MRM assay. PMID:25476245

Self-Organized Near-Zero-Lag Synchronization Induced by Spike-Timing Dependent Plasticity in Cortical Populations

PubMed Central

Matias, Fernanda S.; Carelli, Pedro V.; Mirasso, Claudio R.; Copelli, Mauro

2015-01-01

Several cognitive tasks related to learning and memory exhibit synchronization of macroscopic cortical areas together with synaptic plasticity at neuronal level. Therefore, there is a growing effort among computational neuroscientists to understand the underlying mechanisms relating synchrony and plasticity in the brain. Here we numerically study the interplay between spike-timing dependent plasticity (STDP) and anticipated synchronization (AS). AS emerges when a dominant flux of information from one area to another is accompanied by a negative time lag (or phase). This means that the receiver region pulses before the sender does. In this paper we study the interplay between different synchronization regimes and STDP at the level of three-neuron microcircuits as well as cortical populations. We show that STDP can promote auto-organized zero-lag synchronization in unidirectionally coupled neuronal populations. We also find synchronization regimes with negative phase difference (AS) that are stable against plasticity. Finally, we show that the interplay between negative phase difference and STDP provides limited synaptic weight distribution without the need of imposing artificial boundaries. PMID:26474165

An On-Chip Learning Neuromorphic Autoencoder With Current-Mode Transposable Memory Read and Virtual Lookup Table.

PubMed

Cho, Hwasuk; Son, Hyunwoo; Seong, Kihwan; Kim, Byungsub; Park, Hong-June; Sim, Jae-Yoon

2018-02-01

This paper presents an IC implementation of on-chip learning neuromorphic autoencoder unit in a form of rate-based spiking neural network. With a current-mode signaling scheme embedded in a 500 × 500 6b SRAM-based memory, the proposed architecture achieves simultaneous processing of multiplications and accumulations. In addition, a transposable memory read for both forward and backward propagations and a virtual lookup table are also proposed to perform an unsupervised learning of restricted Boltzmann machine. The IC is fabricated using 28-nm CMOS process and is verified in a three-layer network of encoder-decoder pair for training and recovery of images with two-dimensional pixels. With a dataset of 50 digits, the IC shows a normalized root mean square error of 0.078. Measured energy efficiencies are 4.46 pJ per synaptic operation for inference and 19.26 pJ per synaptic weight update for learning, respectively. The learning performance is also estimated by simulations if the proposed hardware architecture is extended to apply to a batch training of 60 000 MNIST datasets.

Genetic removal of p70 S6 kinase 1 corrects molecular, synaptic, and behavioral phenotypes in fragile X syndrome mice.

PubMed

Bhattacharya, Aditi; Kaphzan, Hanoch; Alvarez-Dieppa, Amanda C; Murphy, Jaclyn P; Pierre, Philippe; Klann, Eric

2012-10-18

Fragile X syndrome (FXS) is the leading inherited cause of autism and intellectual disability. Aberrant synaptic translation has been implicated in the etiology of FXS, but most lines of research on therapeutic strategies have targeted protein synthesis indirectly, far upstream of the translation machinery. We sought to perturb p70 ribosomal S6 kinase 1 (S6K1), a key translation initiation and elongation regulator, in FXS model mice. We found that genetic reduction of S6K1 prevented elevated phosphorylation of translational control molecules, exaggerated protein synthesis, enhanced mGluR-dependent long-term depression (LTD), weight gain, and macro-orchidism in FXS model mice. In addition, S6K1 deletion prevented immature dendritic spine morphology and multiple behavioral phenotypes, including social interaction deficits, impaired novel object recognition, and behavioral inflexibility. Our results support the model that dysregulated protein synthesis is the key causal factor in FXS and that restoration of normal translation can stabilize peripheral and neurological function in FXS. Copyright © 2012 Elsevier Inc. All rights reserved.

Balanced excitation and inhibition are required for high-capacity, noise-robust neuronal selectivity

PubMed Central

Abbott, L. F.; Sompolinsky, Haim

2017-01-01

Neurons and networks in the cerebral cortex must operate reliably despite multiple sources of noise. To evaluate the impact of both input and output noise, we determine the robustness of single-neuron stimulus selective responses, as well as the robustness of attractor states of networks of neurons performing memory tasks. We find that robustness to output noise requires synaptic connections to be in a balanced regime in which excitation and inhibition are strong and largely cancel each other. We evaluate the conditions required for this regime to exist and determine the properties of networks operating within it. A plausible synaptic plasticity rule for learning that balances weight configurations is presented. Our theory predicts an optimal ratio of the number of excitatory and inhibitory synapses for maximizing the encoding capacity of balanced networks for given statistics of afferent activations. Previous work has shown that balanced networks amplify spatiotemporal variability and account for observed asynchronous irregular states. Here we present a distinct type of balanced network that amplifies small changes in the impinging signals and emerges automatically from learning to perform neuronal and network functions robustly. PMID:29042519

Mixed protonic and electronic conductors hybrid oxide synaptic transistors

NASA Astrophysics Data System (ADS)

Fu, Yang Ming; Zhu, Li Qiang; Wen, Juan; Xiao, Hui; Liu, Rui

2017-05-01

Mixed ionic and electronic conductor hybrid devices have attracted widespread attention in the field of brain-inspired neuromorphic systems. Here, mixed protonic and electronic conductor (MPEC) hybrid indium-tungsten-oxide (IWO) synaptic transistors gated by nanogranular phosphorosilicate glass (PSG) based electrolytes were obtained. Unique field-configurable proton self-modulation behaviors were observed on the MPEC hybrid transistor with extremely strong interfacial electric-double-layer effects. Temporally coupled synaptic plasticities were demonstrated on the MPEC hybrid IWO synaptic transistor, including depolarization/hyperpolarization, synaptic facilitation and depression, facilitation-stead/depression-stead behaviors, spiking rate dependent plasticity, and high-pass/low-pass synaptic filtering behaviors. MPEC hybrid synaptic transistors may find potential applications in neuron-inspired platforms.

Presynaptic establishment of the synaptic cleft extracellular matrix is required for post-synaptic differentiation

PubMed Central

Rohrbough, Jeffrey; Rushton, Emma; Woodruff, Elvin; Fergestad, Tim; Vigneswaran, Krishanthan; Broadie, Kendal

2007-01-01

Formation and regulation of excitatory glutamatergic synapses is essential for shaping neural circuits throughout development. In a Drosophila genetic screen for synaptogenesis mutants, we identified mind the gap (mtg), which encodes a secreted, extracellular N-glycosaminoglycan-binding protein. MTG is expressed neuronally and detected in the synaptic cleft, and is required to form the specialized transsynaptic matrix that links the presynaptic active zone with the post-synaptic glutamate receptor (GluR) domain. Null mtg embryonic mutant synapses exhibit greatly reduced GluR function, and a corresponding loss of localized GluR domains. All known post-synaptic signaling/scaffold proteins functioning upstream of GluR localization are also grossly reduced or mislocalized in mtg mutants, including the dPix–dPak–Dock cascade and the Dlg/PSD-95 scaffold. Ubiquitous or neuronally targeted mtg RNA interference (RNAi) similarly reduce post-synaptic assembly, whereas post-synaptically targeted RNAi has no effect, indicating that presynaptic MTG induces and maintains the post-synaptic pathways driving GluR domain formation. These findings suggest that MTG is secreted from the presynaptic terminal to shape the extracellular synaptic cleft domain, and that the cleft domain functions to mediate transsynaptic signals required for post-synaptic development. PMID:17901219

Activity-Induced Synaptic Structural Modifications by an Activator of Integrin Signaling at the Drosophila Neuromuscular Junction.

PubMed

Lee, Joo Yeun; Geng, Junhua; Lee, Juhyun; Wang, Andrew R; Chang, Karen T

2017-03-22

Activity-induced synaptic structural modification is crucial for neural development and synaptic plasticity, but the molecular players involved in this process are not well defined. Here, we report that a protein named Shriveled (Shv) regulates synaptic growth and activity-dependent synaptic remodeling at the Drosophila neuromuscular junction. Depletion of Shv causes synaptic overgrowth and an accumulation of immature boutons. We find that Shv physically and genetically interacts with βPS integrin. Furthermore, Shv is secreted during intense, but not mild, neuronal activity to acutely activate integrin signaling, induce synaptic bouton enlargement, and increase postsynaptic glutamate receptor abundance. Consequently, loss of Shv prevents activity-induced synapse maturation and abolishes post-tetanic potentiation, a form of synaptic plasticity. Our data identify Shv as a novel trans-synaptic signal secreted upon intense neuronal activity to promote synapse remodeling through integrin receptor signaling. SIGNIFICANCE STATEMENT The ability of neurons to rapidly modify synaptic structure in response to neuronal activity, a process called activity-induced structural remodeling, is crucial for neuronal development and complex brain functions. The molecular players that are important for this fundamental biological process are not well understood. Here we show that the Shriveled (Shv) protein is required during development to maintain normal synaptic growth. We further demonstrate that Shv is selectively released during intense neuronal activity, but not mild neuronal activity, to acutely activate integrin signaling and trigger structural modifications at the Drosophila neuromuscular junction. This work identifies Shv as a key modulator of activity-induced structural remodeling and suggests that neurons use distinct molecular cues to differentially modulate synaptic growth and remodeling to meet synaptic demand. Copyright © 2017 the authors 0270-6474/17/373246-18$15.00/0.

PSD-95 and PSD-93 Play Critical but Distinct Roles in Synaptic Scaling Up and Down

PubMed Central

Sun, Qian; Turrigiano, Gina G.

2011-01-01

Synaptic scaling stabilizes neuronal firing through the homeostatic regulation of postsynaptic strength, but the mechanisms by which chronic changes in activity lead to bidirectional adjustments in synaptic AMPAR abundance are incompletely understood. Further, it remains unclear to what extent scaling up and scaling down utilize distinct molecular machinery. PSD-95 is a scaffold protein proposed to serve as a binding “slot” that determines synaptic AMPAR content, and synaptic PSD-95 abundance is regulated by activity, raising the possibility that activity-dependent changes in the synaptic abundance of PSD-95 or other MAGUKs drives the bidirectional changes in AMPAR accumulation during synaptic scaling. We found that synaptic PSD-95 and SAP102 (but not PSD-93) abundance were bidirectionally regulated by activity, but these changes were not sufficient to drive homeostatic changes in synaptic strength. Although not sufficient, the PSD-95-MAGUKs were necessary for synaptic scaling, but scaling up and down were differentially dependent on PSD-95 and PSD-93. Scaling down was completely blocked by reduced or enhanced PSD-95, through a mechanism that depended on the PDZ1/2 domains. In contrast scaling up could be supported by either PSD-95 or PSD-93 in a manner that depended on neuronal age, and was unaffected by a superabundance of PSD-95. Taken together, our data suggest that scaling up and down of quantal amplitude is not driven by changes in synaptic abundance of PSD-95-MAGUKs, but rather that the PSD-95 MAGUKs serve as critical synaptic organizers that utilize distinct protein-protein interactions to mediate homeostatic accumulation and loss of synaptic AMPAR. PMID:21543610

Mean convergence theorems and weak laws of large numbers for weighted sums of random variables under a condition of weighted integrability

NASA Astrophysics Data System (ADS)

Ordóñez Cabrera, Manuel; Volodin, Andrei I.

2005-05-01

From the classical notion of uniform integrability of a sequence of random variables, a new concept of integrability (called h-integrability) is introduced for an array of random variables, concerning an array of constantsE We prove that this concept is weaker than other previous related notions of integrability, such as Cesàro uniform integrability [Chandra, Sankhya Ser. A 51 (1989) 309-317], uniform integrability concerning the weights [Ordóñez Cabrera, Collect. Math. 45 (1994) 121-132] and Cesàro [alpha]-integrability [Chandra and Goswami, J. Theoret. ProbabE 16 (2003) 655-669]. Under this condition of integrability and appropriate conditions on the array of weights, mean convergence theorems and weak laws of large numbers for weighted sums of an array of random variables are obtained when the random variables are subject to some special kinds of dependence: (a) rowwise pairwise negative dependence, (b) rowwise pairwise non-positive correlation, (c) when the sequence of random variables in every row is [phi]-mixing. Finally, we consider the general weak law of large numbers in the sense of Gut [Statist. Probab. Lett. 14 (1992) 49-52] under this new condition of integrability for a Banach space setting.

DL-ReSuMe: A Delay Learning-Based Remote Supervised Method for Spiking Neurons.

PubMed

Taherkhani, Aboozar; Belatreche, Ammar; Li, Yuhua; Maguire, Liam P

2015-12-01

Recent research has shown the potential capability of spiking neural networks (SNNs) to model complex information processing in the brain. There is biological evidence to prove the use of the precise timing of spikes for information coding. However, the exact learning mechanism in which the neuron is trained to fire at precise times remains an open problem. The majority of the existing learning methods for SNNs are based on weight adjustment. However, there is also biological evidence that the synaptic delay is not constant. In this paper, a learning method for spiking neurons, called delay learning remote supervised method (DL-ReSuMe), is proposed to merge the delay shift approach and ReSuMe-based weight adjustment to enhance the learning performance. DL-ReSuMe uses more biologically plausible properties, such as delay learning, and needs less weight adjustment than ReSuMe. Simulation results have shown that the proposed DL-ReSuMe approach achieves learning accuracy and learning speed improvements compared with ReSuMe.

Weight distributions for turbo codes using random and nonrandom permutations

NASA Technical Reports Server (NTRS)

Dolinar, S.; Divsalar, D.

1995-01-01

This article takes a preliminary look at the weight distributions achievable for turbo codes using random, nonrandom, and semirandom permutations. Due to the recursiveness of the encoders, it is important to distinguish between self-terminating and non-self-terminating input sequences. The non-self-terminating sequences have little effect on decoder performance, because they accumulate high encoded weight until they are artificially terminated at the end of the block. From probabilistic arguments based on selecting the permutations randomly, it is concluded that the self-terminating weight-2 data sequences are the most important consideration in the design of constituent codes; higher-weight self-terminating sequences have successively decreasing importance. Also, increasing the number of codes and, correspondingly, the number of permutations makes it more and more likely that the bad input sequences will be broken up by one or more of the permuters. It is possible to design nonrandom permutations that ensure that the minimum distance due to weight-2 input sequences grows roughly as the square root of (2N), where N is the block length. However, these nonrandom permutations amplify the bad effects of higher-weight inputs, and as a result they are inferior in performance to randomly selected permutations. But there are 'semirandom' permutations that perform nearly as well as the designed nonrandom permutations with respect to weight-2 input sequences and are not as susceptible to being foiled by higher-weight inputs.

Multiple vesicle recycling pathways in central synapses and their impact on neurotransmission

PubMed Central

Kavalali, Ege T

2007-01-01

Short-term synaptic depression during repetitive activity is a common property of most synapses. Multiple mechanisms contribute to this rapid depression in neurotransmission including a decrease in vesicle fusion probability, inactivation of voltage-gated Ca2+ channels or use-dependent inhibition of release machinery by presynaptic receptors. In addition, synaptic depression can arise from a rapid reduction in the number of vesicles available for release. This reduction can be countered by two sources. One source is replenishment from a set of reserve vesicles. The second source is the reuse of vesicles that have undergone exocytosis and endocytosis. If the synaptic vesicle reuse is fast enough then it can replenish vesicles during a brief burst of action potentials and play a substantial role in regulating the rate of synaptic depression. In the last 5 years, we have examined the impact of synaptic vesicle reuse on neurotransmission using fluorescence imaging of synaptic vesicle trafficking in combination with electrophysiological detection of short-term synaptic plasticity. These studies have revealed that synaptic vesicle reuse shapes the kinetics of short-term synaptic depression in a frequency-dependent manner. In addition, synaptic vesicle recycling helps maintain the level of neurotransmission at steady state. Moreover, our studies showed that synaptic vesicle reuse is a highly plastic process as it varies widely among synapses and can adapt to changes in chronic activity levels. PMID:17690145

Influence of Synaptic Depression on Memory Storage Capacity

NASA Astrophysics Data System (ADS)

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.

Synaptic Vesicle Endocytosis

PubMed Central

Saheki, Yasunori; De Camilli, Pietro

2012-01-01

Neurons can sustain high rates of synaptic transmission without exhausting their supply of synaptic vesicles. This property relies on a highly efficient local endocytic recycling of synaptic vesicle membranes, which can be reused for hundreds, possibly thousands, of exo-endocytic cycles. Morphological, physiological, molecular, and genetic studies over the last four decades have provided insight into the membrane traffic reactions that govern this recycling and its regulation. These studies have shown that synaptic vesicle endocytosis capitalizes on fundamental and general endocytic mechanisms but also involves neuron-specific adaptations of such mechanisms. Thus, investigations of these processes have advanced not only the field of synaptic transmission but also, more generally, the field of endocytosis. This article summarizes current information on synaptic vesicle endocytosis with an emphasis on the underlying molecular mechanisms and with a special focus on clathrin-mediated endocytosis, the predominant pathway of synaptic vesicle protein internalization. PMID:22763746

Motivation for Participating in a Weight Loss Program and Financial Incentives: An Analysis from a Randomized Trial

PubMed Central

Crane, Melissa M.; Tate, Deborah F.; Finkelstein, Eric A.; Linnan, Laura A.

2012-01-01

This analysis investigated if changes in autonomous or controlled motivation for participation in a weight loss program differed between individuals offered a financial incentive for weight loss compared to individuals not offered an incentive. Additionally, the same relationships were tested among those who lost weight and either received or did not receive an incentive. This analysis used data from a year-long randomized worksite weight loss program that randomly assigned employees in each worksite to either a low-intensity weight loss program or the same program plus small financial incentives for weight loss ($5.00 per percentage of initial weight lost). There were no differences in changes between groups on motivation during the study, however, increases in autonomous motivation were consistently associated with greater weight losses. This suggests that the small incentives used in this program did not lead to increases in controlled motivation nor did they undermine autonomous motivation. Future studies are needed to evaluate the magnitude and timing of incentives to more fully understand the relationship between incentives and motivation. PMID:22577524

Role of DHA in aging-related changes in mouse brain synaptic plasma membrane proteome.

PubMed

Sidhu, Vishaldeep K; Huang, Bill X; Desai, Abhishek; Kevala, Karl; Kim, Hee-Yong

2016-05-01

Aging has been related to diminished cognitive function, which could be a result of ineffective synaptic function. We have previously shown that synaptic plasma membrane proteins supporting synaptic integrity and neurotransmission were downregulated in docosahexaenoic acid (DHA)-deprived brains, suggesting an important role of DHA in synaptic function. In this study, we demonstrate aging-induced synaptic proteome changes and DHA-dependent mitigation of such changes using mass spectrometry-based protein quantitation combined with western blot or messenger RNA analysis. We found significant reduction of 15 synaptic plasma membrane proteins in aging brains including fodrin-α, synaptopodin, postsynaptic density protein 95, synaptic vesicle glycoprotein 2B, synaptosomal-associated protein 25, synaptosomal-associated protein-α, N-methyl-D-aspartate receptor subunit epsilon-2 precursor, AMPA2, AP2, VGluT1, munc18-1, dynamin-1, vesicle-associated membrane protein 2, rab3A, and EAAT1, most of which are involved in synaptic transmission. Notably, the first 9 proteins were further reduced when brain DHA was depleted by diet, indicating that DHA plays an important role in sustaining these synaptic proteins downregulated during aging. Reduction of 2 of these proteins was reversed by raising the brain DHA level by supplementing aged animals with an omega-3 fatty acid sufficient diet for 2 months. The recognition memory compromised in DHA-depleted animals was also improved. Our results suggest a potential role of DHA in alleviating aging-associated cognitive decline by offsetting the loss of neurotransmission-regulating synaptic proteins involved in synaptic function. Published by Elsevier Inc.

A Weighted Configuration Model and Inhomogeneous Epidemics

NASA Astrophysics Data System (ADS)

Britton, Tom; Deijfen, Maria; Liljeros, Fredrik

2011-12-01

A random graph model with prescribed degree distribution and degree dependent edge weights is introduced. Each vertex is independently equipped with a random number of half-edges and each half-edge is assigned an integer valued weight according to a distribution that is allowed to depend on the degree of its vertex. Half-edges with the same weight are then paired randomly to create edges. An expression for the threshold for the appearance of a giant component in the resulting graph is derived using results on multi-type branching processes. The same technique also gives an expression for the basic reproduction number for an epidemic on the graph where the probability that a certain edge is used for transmission is a function of the edge weight (reflecting how closely `connected' the corresponding vertices are). It is demonstrated that, if vertices with large degree tend to have large (small) weights on their edges and if the transmission probability increases with the edge weight, then it is easier (harder) for the epidemic to take off compared to a randomized epidemic with the same degree and weight distribution. A recipe for calculating the probability of a large outbreak in the epidemic and the size of such an outbreak is also given. Finally, the model is fitted to three empirical weighted networks of importance for the spread of contagious diseases and it is shown that R 0 can be substantially over- or underestimated if the correlation between degree and weight is not taken into account.

Evidence for recycling of synaptic vesicle membrane during transmitter release at the frog neuromuscular junction.

PubMed

Heuser, J E; Reese, T S

1973-05-01

When the nerves of isolated frog sartorius muscles were stimulated at 10 Hz, synaptic vesicles in the motor nerve terminals became transiently depleted. This depletion apparently resulted from a redistribution rather than disappearance of synaptic vesicle membrane, since the total amount of membrane comprising these nerve terminals remained constant during stimulation. At 1 min of stimulation, the 30% depletion in synaptic vesicle membrane was nearly balanced by an increase in plasma membrane, suggesting that vesicle membrane rapidly moved to the surface as it might if vesicles released their content of transmitter by exocytosis. After 15 min of stimulation, the 60% depletion of synaptic vesicle membrane was largely balanced by the appearance of numerous irregular membrane-walled cisternae inside the terminals, suggesting that vesicle membrane was retrieved from the surface as cisternae. When muscles were rested after 15 min of stimulation, cisternae disappeared and synaptic vesicles reappeared, suggesting that cisternae divided to form new synaptic vesicles so that the original vesicle membrane was now recycled into new synaptic vesicles. When muscles were soaked in horseradish peroxidase (HRP), this tracerfirst entered the cisternae which formed during stimulation and then entered a large proportion of the synaptic vesicles which reappeared during rest, strengthening the idea that synaptic vesicle membrane added to the surface was retrieved as cisternae which subsequently divided to form new vesicles. When muscles containing HRP in synaptic vesicles were washed to remove extracellular HRP and restimulated, HRP disappeared from vesicles without appearing in the new cisternae formed during the second stimulation, confirming that a one-way recycling of synaptic membrane, from the surface through cisternae to new vesicles, was occurring. Coated vesicles apparently represented the actual mechanism for retrieval of synaptic vesicle membrane from the plasma membrane, because during nerve stimulation they proliferated at regions of the nerve terminals covered by Schwann processes, took up peroxidase, and appeared in various stages of coalescence with cisternae. In contrast, synaptic vesicles did not appear to return directly from the surface to form cisternae, and cisternae themselves never appeared directly connected to the surface. Thus, during stimulation the intracellular compartments of this synapse change shape and take up extracellular protein in a manner which indicates that synaptic vesicle membrane added to the surface during exocytosis is retrieved by coated vesicles and recycled into new synaptic vesicles by way of intermediate cisternae.

EVIDENCE FOR RECYCLING OF SYNAPTIC VESICLE MEMBRANE DURING TRANSMITTER RELEASE AT THE FROG NEUROMUSCULAR JUNCTION

PubMed Central

Heuser, J. E.; Reese, T. S.

1973-01-01

When the nerves of isolated frog sartorius muscles were stimulated at 10 Hz, synaptic vesicles in the motor nerve terminals became transiently depleted. This depletion apparently resulted from a redistribution rather than disappearance of synaptic vesicle membrane, since the total amount of membrane comprising these nerve terminals remained constant during stimulation. At 1 min of stimulation, the 30% depletion in synaptic vesicle membrane was nearly balanced by an increase in plasma membrane, suggesting that vesicle membrane rapidly moved to the surface as it might if vesicles released their content of transmitter by exocytosis. After 15 min of stimulation, the 60% depletion of synaptic vesicle membrane was largely balanced by the appearance of numerous irregular membrane-walled cisternae inside the terminals, suggesting that vesicle membrane was retrieved from the surface as cisternae. When muscles were rested after 15 min of stimulation, cisternae disappeared and synaptic vesicles reappeared, suggesting that cisternae divided to form new synaptic vesicles so that the original vesicle membrane was now recycled into new synaptic vesicles. When muscles were soaked in horseradish peroxidase (HRP), this tracerfirst entered the cisternae which formed during stimulation and then entered a large proportion of the synaptic vesicles which reappeared during rest, strengthening the idea that synaptic vesicle membrane added to the surface was retrieved as cisternae which subsequently divided to form new vesicles. When muscles containing HRP in synaptic vesicles were washed to remove extracellular HRP and restimulated, HRP disappeared from vesicles without appearing in the new cisternae formed during the second stimulation, confirming that a one-way recycling of synaptic membrane, from the surface through cisternae to new vesicles, was occurring. Coated vesicles apparently represented the actual mechanism for retrieval of synaptic vesicle membrane from the plasma membrane, because during nerve stimulation they proliferated at regions of the nerve terminals covered by Schwann processes, took up peroxidase, and appeared in various stages of coalescence with cisternae. In contrast, synaptic vesicles did not appear to return directly from the surface to form cisternae, and cisternae themselves never appeared directly connected to the surface. Thus, during stimulation the intracellular compartments of this synapse change shape and take up extracellular protein in a manner which indicates that synaptic vesicle membrane added to the surface during exocytosis is retrieved by coated vesicles and recycled into new synaptic vesicles by way of intermediate cisternae. PMID:4348786

Deciphering the contribution of intrinsic and synaptic currents to the effects of transient synaptic inputs on human motor unit discharge

PubMed Central

Powers, Randall K.; Türker, Kemal S.

2010-01-01

The amplitude and time course of synaptic potentials in human motoneurons can be estimated in tonically discharging motor units by measuring stimulus-evoked changes in the rate and probability of motor unit action potentials. However, in spite of the fact that some of these techniques have been used for over thirty years, there is still no consensus on the best way to estimate the characteristics of synaptic potentials or on the accuracy of these estimates. In this review, we compare different techniques for estimating synaptic potentials from human motor unit discharge and also discuss relevant animal models in which estimated synaptic potentials can be compared to those directly measured from intracellular recordings. We also review the experimental evidence on how synaptic noise and intrinsic motoneuron properties influence their responses to synaptic inputs. Finally, we consider to what extent recordings of single motor unit discharge in humans can be used to distinguish the contribution of changes in synaptic inputs versus changes in intrinsic motoneuron properties to altered motoneuron responses following CNS injury. PMID:20427230

Forced neuronal interactions cause poor communication.

PubMed

Krzisch, Marine; Toni, Nicolas

2017-01-01

Post-natal hippocampal neurogenesis plays a role in hippocampal function, and neurons born post-natally participate to spatial memory and mood control. However, a great proportion of granule neurons generated in the post-natal hippocampus are eliminated during the first 3 weeks of their maturation, a mechanism that depends on their synaptic integration. In a recent study, we examined the possibility of enhancing the synaptic integration of neurons born post-natally, by specifically overexpressing synaptic cell adhesion molecules in these cells. Synaptic cell adhesion molecules are transmembrane proteins mediating the physical connection between pre- and post-synaptic neurons at the synapse, and their overexpression enhances synapse formation. Accordingly, we found that overexpressing synaptic adhesion molecules increased the synaptic integration and survival of newborn neurons. Surprisingly, the synaptic adhesion molecule with the strongest effect on new neurons' survival, Neuroligin-2A, decreased memory performances in a water maze task. We present here hypotheses explaining these surprising results, in the light of the current knowledge of the mechanisms of synaptic integration of new neurons in the post-natal hippocampus.

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

PubMed

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

2018-03-21

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

Genetic analysis of body weights of individually fed beef bulls in South Africa using random regression models.

PubMed

Selapa, N W; Nephawe, K A; Maiwashe, A; Norris, D

2012-02-08

The aim of this study was to estimate genetic parameters for body weights of individually fed beef bulls measured at centralized testing stations in South Africa using random regression models. Weekly body weights of Bonsmara bulls (N = 2919) tested between 1999 and 2003 were available for the analyses. The model included a fixed regression of the body weights on fourth-order orthogonal Legendre polynomials of the actual days on test (7, 14, 21, 28, 35, 42, 49, 56, 63, 70, 77, and 84) for starting age and contemporary group effects. Random regressions on fourth-order orthogonal Legendre polynomials of the actual days on test were included for additive genetic effects and additional uncorrelated random effects of the weaning-herd-year and the permanent environment of the animal. Residual effects were assumed to be independently distributed with heterogeneous variance for each test day. Variance ratios for additive genetic, permanent environment and weaning-herd-year for weekly body weights at different test days ranged from 0.26 to 0.29, 0.37 to 0.44 and 0.26 to 0.34, respectively. The weaning-herd-year was found to have a significant effect on the variation of body weights of bulls despite a 28-day adjustment period. Genetic correlations amongst body weights at different test days were high, ranging from 0.89 to 1.00. Heritability estimates were comparable to literature using multivariate models. Therefore, random regression model could be applied in the genetic evaluation of body weight of individually fed beef bulls in South Africa.

The Evaluation of Bias of the Weighted Random Effects Model Estimators. Research Report. ETS RR-11-13

ERIC Educational Resources Information Center

Jia, Yue; Stokes, Lynne; Harris, Ian; Wang, Yan

2011-01-01

Estimation of parameters of random effects models from samples collected via complex multistage designs is considered. One way to reduce estimation bias due to unequal probabilities of selection is to incorporate sampling weights. Many researchers have been proposed various weighting methods (Korn, & Graubard, 2003; Pfeffermann, Skinner,…

The Tracking Study: Description of a randomized controlled trial of variations on weight tracking frequency in a behavioral weight loss program

PubMed Central

Linde, Jennifer A.; Jeffery, Robert W.; Crow, Scott J.; Brelje, Kerrin L.; Pacanowski, Carly R.; Gavin, Kara L.; Smolenski, Derek J.

2014-01-01

Observational evidence from behavioral weight control trials and community studies suggests that greater frequency of weighing oneself, or tracking weight, is associated with better weight outcomes. Conversely, it has also been suggested that frequent weight tracking may have a negative impact on mental health and outcomes during weight loss, but there are minimal experimental data that address this concern in the context of an active weight loss program. To achieve the long-term goal of strengthening behavioral weight loss programs, the purpose of this randomized controlled trial (the Tracking Study) is to test variations on frequency of self-weighing during a behavioral weight loss program, and to examine psychosocial and mental health correlates of weight tracking and weight loss outcomes. Three hundred thirty-nine overweight and obese adults were recruited and randomized to one of three variations on weight tracking frequency during a 12-month weight loss program with a 12-month follow-up: daily weight tracking, weekly weight tracking, or no weight tracking. The primary outcome is weight in kilograms at 24 months. The weight loss program integrates each weight tracking instruction with standard behavioral weight loss techniques (goal setting, self-monitoring, stimulus control, dietary and physical activity enhancements, lifestyle modifications); participants in weight tracking conditions were provided with wireless Internet technology (Wi-Fi-enabled digital scales and touchscreen personal devices) to facilitate weight tracking during the study. This paper describes the study design, intervention features, recruitment, and baseline characteristics of participants enrolled in the Tracking Study. PMID:25533727

Anterograde Jelly belly ligand to Alk receptor signaling at developing synapses is regulated by Mind the gap.

PubMed

Rohrbough, Jeffrey; Broadie, Kendal

2010-10-01

Bidirectional trans-synaptic signals induce synaptogenesis and regulate subsequent synaptic maturation. Presynaptically secreted Mind the gap (Mtg) molds the synaptic cleft extracellular matrix, leading us to hypothesize that Mtg functions to generate the intercellular environment required for efficient signaling. We show in Drosophila that secreted Jelly belly (Jeb) and its receptor tyrosine kinase Anaplastic lymphoma kinase (Alk) are localized to developing synapses. Jeb localizes to punctate aggregates in central synaptic neuropil and neuromuscular junction (NMJ) presynaptic terminals. Secreted Jeb and Mtg accumulate and colocalize extracellularly in surrounding synaptic boutons. Alk concentrates in postsynaptic domains, consistent with an anterograde, trans-synaptic Jeb-Alk signaling pathway at developing synapses. Jeb synaptic expression is increased in Alk mutants, consistent with a requirement for Alk receptor function in Jeb uptake. In mtg null mutants, Alk NMJ synaptic levels are reduced and Jeb expression is dramatically increased. NMJ synapse morphology and molecular assembly appear largely normal in jeb and Alk mutants, but larvae exhibit greatly reduced movement, suggesting impaired functional synaptic development. jeb mutant movement is significantly rescued by neuronal Jeb expression. jeb and Alk mutants display normal NMJ postsynaptic responses, but a near loss of patterned, activity-dependent NMJ transmission driven by central excitatory output. We conclude that Jeb-Alk expression and anterograde trans-synaptic signaling are modulated by Mtg and play a key role in establishing functional synaptic connectivity in the developing motor circuit.

An analog neural hardware implementation using charge-injection multipliers and neutron-specific gain control.

PubMed

Massengill, L W; Mundie, D B

1992-01-01

A neural network IC based on a dynamic charge injection is described. The hardware design is space and power efficient, and achieves massive parallelism of analog inner products via charge-based multipliers and spatially distributed summing buses. Basic synaptic cells are constructed of exponential pulse-decay modulation (EPDM) dynamic injection multipliers operating sequentially on propagating signal vectors and locally stored analog weights. Individually adjustable gain controls on each neutron reduce the effects of limited weight dynamic range. A hardware simulator/trainer has been developed which incorporates the physical (nonideal) characteristics of actual circuit components into the training process, thus absorbing nonlinearities and parametric deviations into the macroscopic performance of the network. Results show that charge-based techniques may achieve a high degree of neural density and throughput using standard CMOS processes.

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

PubMed Central

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

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

PubMed Central

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 synaptic protein turnover places on individual neurons is very substantial. PMID:23658807

Comparing development of synaptic proteins in rat visual, somatosensory, and frontal cortex.

PubMed

Pinto, Joshua G A; Jones, David G; Murphy, Kathryn M

2013-01-01

Two theories have influenced our understanding of cortical development: the integrated network theory, where synaptic development is coordinated across areas; and the cascade theory, where the cortex develops in a wave-like manner from sensory to non-sensory areas. These different views on cortical development raise challenges for current studies aimed at comparing detailed maturation of the connectome among cortical areas. We have taken a different approach to compare synaptic development in rat visual, somatosensory, and frontal cortex by measuring expression of pre-synaptic (synapsin and synaptophysin) proteins that regulate vesicle cycling, and post-synaptic density (PSD-95 and Gephyrin) proteins that anchor excitatory or inhibitory (E-I) receptors. We also compared development of the balances between the pairs of pre- or post-synaptic proteins, and the overall pre- to post-synaptic balance, to address functional maturation and emergence of the E-I balance. We found that development of the individual proteins and the post-synaptic index overlapped among the three cortical areas, but the pre-synaptic index matured later in frontal cortex. Finally, we applied a neuroinformatics approach using principal component analysis and found that three components captured development of the synaptic proteins. The first component accounted for 64% of the variance in protein expression and reflected total protein expression, which overlapped among the three cortical areas. The second component was gephyrin and the E-I balance, it emerged as sequential waves starting in somatosensory, then frontal, and finally visual cortex. The third component was the balance between pre- and post-synaptic proteins, and this followed a different developmental trajectory in somatosensory cortex. Together, these results give the most support to an integrated network of synaptic development, but also highlight more complex patterns of development that vary in timing and end point among the cortical areas.

Spontaneously emerging direction selectivity maps in visual cortex through STDP.

PubMed

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

2005-10-01

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

Forebrain CRHR1 deficiency attenuates chronic stress-induced cognitive deficits and dendritic remodeling

PubMed Central

Wang, Xiao-Dong; Chen, Yuncai; Wolf, Miriam; Wagner, Klaus V.; Liebl, Claudia; Scharf, Sebastian H.; Harbich, Daniela; Mayer, Bianca; Wurst, Wolfgang; Holsboer, Florian; Deussing, Jan M.; Baram, Tallie Z.; Müller, Marianne B.; Schmidt, Mathias V.

2011-01-01

Chronic stress evokes profound structural and molecular changes in the hippocampus, which may underlie spatial memory deficits. Corticotropin-releasing hormone (CRH) and CRH receptor 1 (CRHR1) mediate some of the rapid effects of stress on dendritic spine morphology and modulate learning and memory, thus providing a potential molecular basis for impaired synaptic plasticity and spatial memory by repeated stress exposure. Using adult male mice with CRHR1 conditionally inactivated in the forebrain regions, we investigated the role of CRH-CRHR1 signaling in the effects of chronic social defeat stress on spatial memory, the dendritic morphology of hippocampal CA3 pyramidal neurons, and the hippocampal expression of nectin-3, a synaptic cell adhesion molecule important in synaptic remodeling. In chronically stressed wild-type mice, spatial memory was disrupted, and the complexity of apical dendrites of CA3 neurons reduced. In contrast, stressed mice with forebrain CRHR1 deficiency exhibited normal dendritic morphology of CA3 neurons and mild impairments in spatial memory. Additionally, we showed that the expression of nectin-3 in the CA3 area was regulated by chronic stress in a CRHR1-dependent fashion and associated with spatial memory and dendritic complexity. Moreover, forebrain CRHR1 deficiency prevented the down-regulation of hippocampal glucocorticoid receptor expression by chronic stress but induced increased body weight gain during persistent stress exposure. These findings underscore the important role of forebrain CRH-CRHR1 signaling in modulating chronic stress-induced cognitive, structural and molecular adaptations, with implications for stress-related psychiatric disorders. PMID:21296667

Neuromorphic implementations of neurobiological learning algorithms for spiking neural networks.

PubMed

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.

AMPA receptor desensitization mutation results in severe developmental phenotypes and early postnatal lethality

PubMed Central

Christie, Louisa A.; Russell, Theron A.; Xu, Jian; Wood, Lydia; Shepherd, Gordon M. G.; Contractor, Anis

2010-01-01

AMPA (α-amino-3-hydroxy-5-methyl-4-isoxazole-propionate) recep-tors desensitize rapidly and completely in the continued presence of their endogenous ligand glutamate; however, it is not clear what role AMPA receptor desensitization plays in the brain. We generated a knock-in mouse in which a single amino acid residue, which controls desensitization, was mutated in the GluA2 (GluR2) receptor subunit (GluA2L483Y). This mutation was homozygous lethal. However, mice carrying a single mutated allele, GluA2L483Y/wt, survived past birth, but displayed severe and progressive neurological deficits including seizures and, ultimately, increased mortality. The expression of the AMPA receptor subunits GluA1 and GluA2 was decreased, whereas NMDA receptor protein expression was increased in GluA2L483Y/wt mice. Despite this, basal synaptic transmission and plasticity in the hippocampus were largely unaffected, suggesting that neurons preferentially target receptors to synapses to normalize synaptic weight. We found no gross neuroanatomical alterations in GluA2L483Y/wt mice. Moreover, there was no accumulation of AMPA receptor subunits in intracellular compartments, suggesting that folding and assembly of AMPA receptors are not affected by this mutation. Interestingly, EPSC paired pulse ratios in the CA1 were enhanced without a change in synaptic release probability, demonstrating that postsynaptic receptor properties can contribute to facilitation. The dramatic phenotype observed in this study by the introduction of a single amino acid change demonstrates an essential role in vivo for AMPA receptor desensitization. PMID:20439731

Vitamin D status and weight loss: a systematic review and meta-analysis of randomized and nonrandomized controlled weight-loss trials.

PubMed

Mallard, Simonette R; Howe, Anna S; Houghton, Lisa A

2016-10-01

Obesity is associated with lower concentrations of serum 25-hydroxyvitamin D; however, uncertainty exists as to the direction of causation. To date, meta-analyses of randomized controlled vitamin D-supplementation trials have shown no effect of raising circulating vitamin D on body weight, although several weight-loss-intervention trials have reported an increase in circulating vitamin D after weight reduction. We undertook a systematic review and meta-analysis of randomized and nonrandomized controlled trials to determine whether weight loss compared with weight maintenance leads to an increase in serum 25-hydroxyvitamin D. A systematic search for controlled weight-loss-intervention studies published up to 31 March 2016 was performed. Studies that included participants of any age with changes in adiposity and serum 25-hydroxyvitamin D as primary or secondary outcomes were considered eligible. We identified 4 randomized controlled trials (n = 2554) and 11 nonrandomized controlled trials (n = 917) for inclusion in the meta-analysis. Random assignment to weight loss compared with weight maintenance resulted in a greater increase in serum 25-hydroxyvitamin D with a mean difference of 3.11 nmol/L (95% CI: 1.38, 4.84 nmol/L) between groups, whereas a mean difference of 4.85 nmol/L (95% CI: 2.59, 7.12 nmol/L) was observed in nonrandomized trials. No evidence for a dose-response effect of weight loss on the change in serum 25-hydroxyvitamin D was shown overall. Our results indicate that vitamin D status may be marginally improved with weight loss in comparison with weight maintenance under similar conditions of supplemental vitamin D intake. Although additional studies in unsupplemented individuals are needed to confirm these findings, our results support the view that the association between obesity and lower serum 25-hydroxyvitamin D may be due to reversed causation with increased adiposity leading to suboptimal concentrations of circulating vitamin D. This trial was registered at www.crd.york.ac.uk/PROSPERO/ as CRD42015023836. © 2016 American Society for Nutrition.

Spatial cognition and sexually dimorphic synaptic plasticity balance impairment in rats with chronic prenatal ethanol exposure.

PubMed

An, Lei; Zhang, Tao

2013-11-01

Prenatal ethanol exposure can lead to long-lasting impairments in the ability of rats to process spatial information, as well as produce long-lasting deficits in long-term potentiation (LTP), a biological model of learning and memory processing. The present study aimed to examine the sexually dimorphic effects of chronic prenatal ethanol exposure (CPEE) on behavior cognition and synaptic plasticity balance (SPB), and tried to understand a possible mechanism by evaluating the alternation of SPB. The animal model was produced by ethanol exposure throughout gestational period with 4 g/kg bodyweight. Offspring of both male and female were selected and studied on postnatal days 36. Subsequently, the data showed that chronic ethanol exposure resulted in birth weight reduction, losing bodyweight gain, microcephaly and hippocampus weight retardation. In Morris water maze (MWM) test, escape latencies were significantly higher in CPEE-treated rats than that in control ones. They also spent much less time in the target quadrant compared to that of control animals in the probe phase. In addition, it was found that there was a more severe impairment in females than that in males after CPEE treatment. Electrophysiological studies showed that CPEE considerably inhibited hippocampal LTP and facilitated depotentiation in males, while significantly enhanced LTP and suppressed depotentiation in females. A novel index, developed by us, showed that the action of CPEE on SPB was more sensitive in females than that in males, suggesting that it might be an effective index to distinguish the difference of SPB impairment between males and females. Copyright © 2013 Elsevier B.V. All rights reserved.

Robot-Applied Resistance Augments the Effects of Body Weight-Supported Treadmill Training on Stepping and Synaptic Plasticity in a Rodent Model of Spinal Cord Injury.

PubMed

Hinahon, Erika; Estrada, Christina; Tong, Lin; Won, Deborah S; de Leon, Ray D

2017-08-01

The application of resistive forces has been used during body weight-supported treadmill training (BWSTT) to improve walking function after spinal cord injury (SCI). Whether this form of training actually augments the effects of BWSTT is not yet known. To determine if robotic-applied resistance augments the effects of BWSTT using a controlled experimental design in a rodent model of SCI. Spinally contused rats were treadmill trained using robotic resistance against horizontal (n = 9) or vertical (n = 8) hind limb movements. Hind limb stepping was tested before and after 6 weeks of training. Two control groups, one receiving standard training (ie, without resistance; n = 9) and one untrained (n = 8), were also tested. At the terminal experiment, the spinal cords were prepared for immunohistochemical analysis of synaptophysin. Six weeks of training with horizontal resistance increased step length, whereas training with vertical resistance enhanced step height and movement velocity. None of these changes occurred in the group that received standard (ie, no resistance) training or in the untrained group. Only standard training increased the number of step cycles and shortened cycle period toward normal values. Synaptophysin expression in the ventral horn was highest in rats trained with horizontal resistance and in untrained rats and was positively correlated with step length. Adding robotic-applied resistance to BWSTT produced gains in locomotor function over BWSTT alone. The impact of resistive forces on spinal connections may depend on the nature of the resistive forces and the synaptic milieu that is present after SCI.

[Exploration of common biological pathways for attention deficit hyperactivity disorder and low birth weight].

PubMed

Xiang, Bo; Yu, Minglan; Liang, Xuemei; Lei, Wei; Huang, Chaohua; Chen, Jing; He, Wenying; Zhang, Tao; Li, Tao; Liu, Kezhi

2017-12-10

To explore common biological pathways for attention deficit hyperactivity disorder (ADHD) and low birth weight (LBW). Thei-Gsea4GwasV2 software was used to analyze the result of genome-wide association analysis (GWAS) for LBW (pathways were derived from Reactome), and nominally significant (P< 0.05, FDR< 0.25) pathways were tested for replication in ADHD.Significant pathways were analyzed with DAPPLE and Reatome FI software to identify genes involved in such pathways, with each cluster enriched with the gene ontology (GO). The Centiscape2.0 software was used to calculate the degree of genetic networks and the betweenness value to explore the core node (gene). Weighed gene co-expression network analysis (WGCNA) was then used to explore the co-expression of genes in these pathways.With gene expression data derived from BrainSpan, GO enrichment was carried out for each gene module. Eleven significant biological pathways was identified in association with LBW, among which two (Selenoamino acid metabolism and Diseases associated with glycosaminoglycan metabolism) were replicated during subsequent ADHD analysis. Network analysis of 130 genes in these pathways revealed that some of the sub-networksare related with morphology of cerebellum, development of hippocampus, and plasticity of synaptic structure. Upon co-expression network analysis, 120 genes passed the quality control and were found to express in 3 gene modules. These modules are mainly related to the regulation of synaptic structure and activity regulation. ADHD and LBW share some biological regulation processes. Anomalies of such proces sesmay predispose to ADHD.

Cascade Back-Propagation Learning in Neural Networks

NASA Technical Reports Server (NTRS)

Duong, Tuan A.

2003-01-01

The cascade back-propagation (CBP) algorithm is the basis of a conceptual design for accelerating learning in artificial neural networks. The neural networks would be implemented as analog very-large-scale integrated (VLSI) circuits, and circuits to implement the CBP algorithm would be fabricated on the same VLSI circuit chips with the neural networks. Heretofore, artificial neural networks have learned slowly because it has been necessary to train them via software, for lack of a good on-chip learning technique. The CBP algorithm is an on-chip technique that provides for continuous learning in real time. Artificial neural networks are trained by example: A network is presented with training inputs for which the correct outputs are known, and the algorithm strives to adjust the weights of synaptic connections in the network to make the actual outputs approach the correct outputs. The input data are generally divided into three parts. Two of the parts, called the "training" and "cross-validation" sets, respectively, must be such that the corresponding input/output pairs are known. During training, the cross-validation set enables verification of the status of the input-to-output transformation learned by the network to avoid over-learning. The third part of the data, termed the "test" set, consists of the inputs that are required to be transformed into outputs; this set may or may not include the training set and/or the cross-validation set. Proposed neural-network circuitry for on-chip learning would be divided into two distinct networks; one for training and one for validation. Both networks would share the same synaptic weights.

Behavioral Weight Loss for the Management of Menopausal Hot Flashes: A Pilot Study

PubMed Central

Thurston, Rebecca C.; Ewing, Linda J.; Low, Carissa A.; Christie, Aimee J.; Levine, Michele D.

2014-01-01

Objective Although adiposity has been considered protective against hot flashes, newer data suggest positive relations between flashes and adiposity. No studies have been specifically designed to test whether weight loss reduces hot flashes. This pilot study aimed to evaluate the feasibility, acceptability, and initial efficacy of behavioral weight loss to reduce hot flashes. Methods Forty overweight/obese women with hot flashes (≥4/day) were randomized to a behavioral weight loss intervention or to wait list control. Hot flashes were assessed pre- and post-intervention via physiologic monitor, diary, and questionnaire. Comparisons of changes in hot flashes and anthropometrics between conditions were tested via Wilcoxon tests. Results Study retention (83%) and intervention satisfaction (93.8%) were high. Most women (74.1%) reported that hot flash reduction was a main motivator to lose weight. Women randomized to the weight loss intervention lost more weight (-8.86 kg) than did women randomized to control (+0.23 kg, p<.0001). Women randomized to weight loss also showed greater reductions in questionnaire-reported hot flashes (2-week hot flashes: −63.0) than did women in the control (−28.0, p=.03), a difference not demonstrated in other hot flash measures. Reductions in weight and hot flashes were significantly correlated (e.g., r=.47, p=.006). Conclusions This pilot study showed a behavioral weight loss program to be feasible, acceptable, and effective in producing weight loss among overweight/obese women with hot flashes. Findings indicate the importance of a larger study designed to test behavioral weight loss for hot flash reduction. Hot flash management could motivate women to engage in this health-promoting behavior. PMID:24977456

Behavioral weight loss for the management of menopausal hot flashes: a pilot study.

PubMed

Thurston, Rebecca C; Ewing, Linda J; Low, Carissa A; Christie, Aimee J; Levine, Michele D

2015-01-01

Although adiposity has been considered to be protective against hot flashes, newer data suggest positive relationships between hot flashes and adiposity. No studies have been specifically designed to test whether weight loss reduces hot flashes. This pilot study aimed to evaluate the feasibility, acceptability, and initial efficacy of behavioral weight loss in reducing hot flashes. Forty overweight or obese women with hot flashes (≥ 4 hot flashes/d) were randomized to either behavioral weight loss intervention or wait-list control. Hot flashes were assessed before and after intervention via physiologic monitoring, diary, and questionnaire. Comparisons of changes in hot flashes and anthropometrics between conditions were performed via Wilcoxon tests. Study retention (83%) and intervention satisfaction (93.8%) were high. Most women (74.1%) reported that hot flash reduction was a major motivator for losing weight. Women randomized to the weight loss intervention lost more weight (-8.86 kg) than did women randomized to control (+0.23 kg; P < 0.0001). Women randomized to weight loss also showed greater reductions in questionnaire-reported hot flashes (2-wk hot flashes, -63.0) than did women in the control group (-28.0; P = 0.03)-a difference not demonstrated in other hot flash measures. Reductions in weight and hot flashes were significantly correlated (eg, r = 0.47, P = 0.006). This pilot study shows a behavioral weight loss program that is feasible, acceptable, and effective in producing weight loss among overweight or obese women with hot flashes. Findings indicate the importance of a larger study designed to test behavioral weight loss for hot flash reduction. Hot flash management could motivate women to engage in this health-promoting behavior.

Breeding value accuracy estimates for growth traits using random regression and multi-trait models in Nelore cattle.

PubMed

Boligon, A A; Baldi, F; Mercadante, M E Z; Lobo, R B; Pereira, R J; Albuquerque, L G

2011-06-28

We quantified the potential increase in accuracy of expected breeding value for weights of Nelore cattle, from birth to mature age, using multi-trait and random regression models on Legendre polynomials and B-spline functions. A total of 87,712 weight records from 8144 females were used, recorded every three months from birth to mature age from the Nelore Brazil Program. For random regression analyses, all female weight records from birth to eight years of age (data set I) were considered. From this general data set, a subset was created (data set II), which included only nine weight records: at birth, weaning, 365 and 550 days of age, and 2, 3, 4, 5, and 6 years of age. Data set II was analyzed using random regression and multi-trait models. The model of analysis included the contemporary group as fixed effects and age of dam as a linear and quadratic covariable. In the random regression analyses, average growth trends were modeled using a cubic regression on orthogonal polynomials of age. Residual variances were modeled by a step function with five classes. Legendre polynomials of fourth and sixth order were utilized to model the direct genetic and animal permanent environmental effects, respectively, while third-order Legendre polynomials were considered for maternal genetic and maternal permanent environmental effects. Quadratic polynomials were applied to model all random effects in random regression models on B-spline functions. Direct genetic and animal permanent environmental effects were modeled using three segments or five coefficients, and genetic maternal and maternal permanent environmental effects were modeled with one segment or three coefficients in the random regression models on B-spline functions. For both data sets (I and II), animals ranked differently according to expected breeding value obtained by random regression or multi-trait models. With random regression models, the highest gains in accuracy were obtained at ages with a low number of weight records. The results indicate that random regression models provide more accurate expected breeding values than the traditionally finite multi-trait models. Thus, higher genetic responses are expected for beef cattle growth traits by replacing a multi-trait model with random regression models for genetic evaluation. B-spline functions could be applied as an alternative to Legendre polynomials to model covariance functions for weights from birth to mature age.

A Bayesian context fear learning algorithm/automaton

PubMed Central

Krasne, Franklin B.; Cushman, Jesse D.; Fanselow, Michael S.

2015-01-01

Contextual fear conditioning is thought to involve the synaptic plasticity-dependent establishment in hippocampus of representations of to-be-conditioned contexts which can then become associated with USs in the amygdala. A conceptual and computational model of this process is proposed in which contextual attributes are assumed to be sampled serially and randomly during contextual exposures. Given this assumption, moment-to-moment information about such attributes will often be quite different from one exposure to another and, in particular, between exposures during which representations are created, exposures during which conditioning occurs, and during recall sessions. This presents challenges to current conceptual models of hippocampal function. In order to meet these challenges, our model's hippocampus was made to operate in different modes during representation creation and recall, and non-hippocampal machinery was constructed that controlled these hippocampal modes. This machinery uses a comparison between contextual information currently observed and information associated with existing hippocampal representations of familiar contexts to compute the Bayesian Weight of Evidence that the current context is (or is not) a known one, and it uses this value to assess the appropriateness of creation or recall modes. The model predicts a number of known phenomena such as the immediate shock deficit, spurious fear conditioning to contexts that are absent but similar to actually present ones, and modulation of conditioning by pre-familiarization with contexts. It also predicts a number of as yet unknown phenomena. PMID:26074792

The interplay between neuronal activity and actin dynamics mimic the setting of an LTD synaptic tag

PubMed Central

Szabó, Eszter C.; Manguinhas, Rita; Fonseca, Rosalina

2016-01-01

Persistent forms of plasticity, such as long-term depression (LTD), are dependent on the interplay between activity-dependent synaptic tags and the capture of plasticity-related proteins. We propose that the synaptic tag represents a structural alteration that turns synapses permissive to change. We found that modulation of actin dynamics has different roles in the induction and maintenance of LTD. Inhibition of either actin depolymerisation or polymerization blocks LTD induction whereas only the inhibition of actin depolymerisation blocks LTD maintenance. Interestingly, we found that actin depolymerisation and CaMKII activation are involved in LTD synaptic-tagging and capture. Moreover, inhibition of actin polymerisation mimics the setting of a synaptic tag, in an activity-dependent manner, allowing the expression of LTD in non-stimulated synapses. Suspending synaptic activation also restricts the time window of synaptic capture, which can be restored by inhibiting actin polymerization. Our results support our hypothesis that modulation of the actin cytoskeleton provides an input-specific signal for synaptic protein capture. PMID:27650071

Efficacy of Continuing Education in Improving Pharmacists' Competencies for Providing Weight Management Service: Three-Arm Randomized Controlled Trial

ERIC Educational Resources Information Center

Sarayani, Amir; Rashidian, Arash; Gholami, Kheirollah; Torkamandi, Hassan; Javadi, Mohammadreza

2012-01-01

Introduction: Weight management is a new public health role for community pharmacists in many countries. Lack of expertise is one of the key barriers to counseling obese patients. We evaluated the comparative efficacy of three alternative continuing education (CE) meetings on weight management. Methods: We designed a randomized controlled trial…

Complete convergence of randomly weighted END sequences and its application.

PubMed

Li, Penghua; Li, Xiaoqin; Wu, Kehan

2017-01-01

We investigate the complete convergence of partial sums of randomly weighted extended negatively dependent (END) random variables. Some results of complete moment convergence, complete convergence and the strong law of large numbers for this dependent structure are obtained. As an application, we study the convergence of the state observers of linear-time-invariant systems. Our results extend the corresponding earlier ones.

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

PubMed Central

Crabtree, Gregg W.; Gogos, Joseph A.

2014-01-01

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

Non-synaptic receptors and transporters involved in brain functions and targets of drug treatment

PubMed Central

Vizi, ES; Fekete, A; Karoly, R; Mike, A

2010-01-01

Beyond direct synaptic communication, neurons are able to talk to each other without making synapses. They are able to send chemical messages by means of diffusion to target cells via the extracellular space, provided that the target neurons are equipped with high-affinity receptors. While synaptic transmission is responsible for the ‘what’ of brain function, the ‘how’ of brain function (mood, attention, level of arousal, general excitability, etc.) is mainly controlled non-synaptically using the extracellular space as communication channel. It is principally the ‘how’ that can be modulated by medicine. In this paper, we discuss different forms of non-synaptic transmission, localized spillover of synaptic transmitters, local presynaptic modulation and tonic influence of ambient transmitter levels on the activity of vast neuronal populations. We consider different aspects of non-synaptic transmission, such as synaptic–extrasynaptic receptor trafficking, neuron–glia communication and retrograde signalling. We review structural and functional aspects of non-synaptic transmission, including (i) anatomical arrangement of non-synaptic release sites, receptors and transporters, (ii) intravesicular, intra- and extracellular concentrations of neurotransmitters, as well as the spatiotemporal pattern of transmitter diffusion. We propose that an effective general strategy for efficient pharmacological intervention could include the identification of specific non-synaptic targets and the subsequent development of selective pharmacological tools to influence them. PMID:20136842

Effects of chronic weight perturbation on energy homeostasis and brain structure in mice

PubMed Central

Ravussin, Y.; Gutman, R.; Diano, S.; Shanabrough, M.; Borok, E.; Sarman, B.; Lehmann, A.; LeDuc, C. A.; Rosenbaum, M.; Horvath, T. L.

2011-01-01

Maintenance of reduced body weight in lean and obese human subjects results in the persistent decrease in energy expenditure below what can be accounted for by changes in body mass and composition. Genetic and developmental factors may determine a central nervous system (CNS)-mediated minimum threshold of somatic energy stores below which behavioral and metabolic compensations for weight loss are invoked. A critical question is whether this threshold can be altered by environmental influences and by what mechanisms such alterations might be achieved. We examined the bioenergetic, behavioral, and CNS structural responses to weight reduction of diet-induced obese (DIO) and never-obese (CON) C57BL/6J male mice. We found that weight-reduced (WR) DIO-WR and CON-WR animals showed reductions in energy expenditure, adjusted for body mass and composition, comparable (−10–15%) to those seen in human subjects. The proportion of excitatory synapses on arcuate nucleus proopiomelanocortin neurons was decreased by ∼50% in both DIO-WR and CON-WR mice. These data suggest that prolonged maintenance of an elevated body weight (fat) alters energy homeostatic systems to defend a higher level of body fat. The synaptic changes could provide a neural substrate for the disproportionate decline in energy expenditure in weight-reduced individuals. This response to chronic weight elevation may also occur in humans. The mouse model described here could help to identify the molecular/cellular mechanisms underlying both the defense mechanisms against sustained weight loss and the upward resetting of those mechanisms following sustained weight gain. PMID:21411766

Commercial programs' online weight loss claims as compared to results from randomized controlled trials

PubMed Central

Vakil, Rachit M.; Chaudhry, Zoobia W.; Doshi, Ruchi S.; Clark, Jeanne M.; Gudzune, Kimberly A.

2017-01-01

Objective To characterize weight-loss claims and disclaimers present on websites for commercial weight-loss programs and compare them to results from published randomized controlled trials (RCT). Methods We performed a content analysis of all homepages and testimonials available on the websites of 24 randomly selected programs. Two team members independently reviewed each page and abstracted information from text and images to capture relevant content including demographics, weight loss, and disclaimers. We performed a systematic review to evaluate the efficacy of these programs by searching MEDLINE and Cochrane Database of Systematic Reviews, and abstracted mean weight change from each included RCT. Results Overall, the amount of weight loss portrayed in the testimonials was extreme across all programs examined (range median weight loss 10.7 to 49.5 kg). Only 10 out of the 24 programs had eligible RCTs. Median weight losses reported in testimonials exceeded that achieved by trial participants. Most programs with RCTs (78%) provided disclaimers stating that the testimonial's results were non-typical and/or giving a range of typical weight loss. Conclusion Weight loss claims within testimonials were higher than results from RCTs. Future studies should examine whether commercial programs' advertising practices influence patients' expectations or satisfaction with modest weight loss results. PMID:28865085

Stochastic lattice model of synaptic membrane protein domains.

PubMed

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.

Prenatal choline supplementation attenuates spatial learning deficits of offspring rats exposed to low-protein diet during fetal period.

PubMed

Zhu, Cui-Hong; Wu, Ting; Jin, Yu; Huang, Bi-Xia; Zhou, Rui-Fen; Wang, Yi-Qin; Luo, Xiao-Lin; Zhu, Hui-Lian

2016-06-01

Prenatal intake of choline has been reported to lead to enhanced cognitive function in offspring, but little is known about the effects on spatial learning deficits. The present study examined the effects of prenatal choline supplementation on developmental low-protein exposure and its potential mechanisms. Pregnant female rats were fed either a normal or low-protein diet containing sufficient choline (1.1g/kg choline chloride) or supplemented choline (5.0g/kg choline chloride) until delivery. The Barnes maze test was performed at postnatal days 31-37. Choline and its metabolites, the synaptic structural parameters of the CA1 region in the brain of the newborn rat, were measured. The Barnes maze test demonstrated that prenatal low-protein pups had significantly greater error scale values, hole deviation scores, strategy scores and spatial search strategy and had lesser random search strategy values than normal protein pups (all P<.05). These alterations were significantly reversed by choline supplementation. Choline supplementation increased the brain levels of choline, betaine, phosphatidylethanolamine and phosphatidylcholine of newborns by 51.35% (P<.05), 33.33% (P<.001), 28.68% (P<.01) and 23.58% (P<.05), respectively, compared with the LPD group. Prenatal choline supplementation reversed the increased width of the synaptic cleft (P<.05) and decreased the curvature of the synaptic interface (P<.05) induced by a low-protein diet. Prenatal choline supplementation could attenuate the spatial learning deficits caused by prenatal protein malnutrition by increasing brain choline, betaine and phospholipids and by influencing the hippocampus structure. Copyright © 2016 Elsevier Inc. All rights reserved.

Nonvolatile programmable neural network synaptic array

NASA Technical Reports Server (NTRS)

Tawel, Raoul (Inventor)

1994-01-01

A floating-gate metal oxide semiconductor (MOS) transistor is implemented for use as a nonvolatile analog storage element of a synaptic cell used to implement an array of processing synaptic cells. These cells are based on a four-quadrant analog multiplier requiring both X and Y differential inputs, where one Y input is UV programmable. These nonvolatile synaptic cells are disclosed fully connected in a 32 x 32 synaptic cell array using standard very large scale integration (VLSI) complementary MOS (CMOS) technology.

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

PubMed Central

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

2014-01-01

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

A randomized, double-blind, placebo-controlled clinical trial of megestrol acetate as an appetite stimulant in children with weight loss due to cancer and/or cancer therapy.

PubMed

Cuvelier, Geoff D E; Baker, Tina J; Peddie, Elaine F; Casey, Linda M; Lambert, Pascal J; Distefano, Dianne S; Wardle, Marlene G; Mychajlunow, Beth A; Romanick, Marcel A; Dix, David B; Wilson, Beverly A

2014-04-01

Megestrol acetate (MA) is an appetite stimulant with efficacy in promoting weight gain in adults with cancer-associated anorexia-cachexia. Studies documenting MA efficacy in children, however, are limited. We present the first randomized, double-blind, placebo-controlled clinical trial of MA versus placebo in children with cancer and weight loss. Subjects <18 years of age with weight loss (minimum 5% from highest previous weight; or %ideal body weight <90%) due to cancer and/or cancer therapy were randomized to either MA (7.5 mg/kg/day) or placebo for a planned study duration of 90 days. Primary outcome was the difference between groups in mean percent weight change from beginning to end of the study period. Secondary outcomes included effects on anthropometrics, body composition, need for tube feeding or parenteral nutrition, and toxicities. Twenty-six patients were randomly assigned (13 MA, 13 placebo). The MA group experienced a mean weight gain of +19.7% compared to a mean weight loss of -1.2% in the placebo group, for a difference of +20.9% (95%CI: +11.3% to +30.5%, P = 0.003) in favor of MA over placebo. MA subjects experienced significant increases in weight for age z-scores, body mass index z-scores, and mid upper arm circumference compared to placebo. DXA scanning suggested disproportionate increases in fat accrual. Adrenal suppression was the main toxicity of MA. In children with high-risk malignancies, MA resulted in significant increases in mean percent weight change compared to placebo. Further studies of MA should be pursued to better delineate the effect on nutritional status. © 2013 Wiley Periodicals, Inc.

Maintained intentional weight loss reduces cardiovascular outcomes: results from the Sibutramine Cardiovascular OUTcomes (SCOUT) trial.

PubMed

Caterson, I D; Finer, N; Coutinho, W; Van Gaal, L F; Maggioni, A P; Torp-Pedersen, C; Sharma, A M; Legler, U F; Shepherd, G M; Rode, R A; Perdok, R J; Renz, C L; James, W P T

2012-06-01

The Sibutramine Cardiovascular OUTcomes trial showed that sibutramine produced greater mean weight loss than placebo but increased cardiovascular morbidity but not mortality. The relationship between 12-month weight loss and subsequent cardiovascular outcomes is explored. Overweight/obese subjects (N = 10 744), ≥55 years with cardiovascular disease and/or type 2 diabetes mellitus, received sibutramine plus weight management during a 6-week Lead-in Period before randomization to continue sibutramine (N = 4906) or to receive placebo (N = 4898). The primary endpoint was the time from randomization to first occurrence of a primary outcome event (non-fatal myocardial infarction, non-fatal stroke, resuscitated cardiac arrest or cardiovascular death). For the total population, mean weight change during Lead-in Period (sibutramine) was -2.54 kg. Post-randomization, mean total weight change to Month 12 was -4.18 kg (sibutramine) or -1.87 kg (placebo). Degree of weight loss during Lead-in Period or through Month 12 was associated with a progressive reduction in risk for the total population in primary outcome events and cardiovascular mortality over the 5-year assessment. Although more events occurred in the randomized sibutramine group, on an average, a modest weight loss of approximately 3 kg achieved in the Lead-in Period appeared to offset this increased event rate. Moderate weight loss (3-10 kg) reduced cardiovascular deaths in those with severe, moderate or mild cardiovascular disease. Modest weight loss over short-term (6 weeks) and longer-term (6-12 months) periods is associated with reduction in subsequent cardiovascular mortality for the following 4-5 years even in those with pre-existing cardiovascular disease. While the sibutramine group experienced more primary outcome events than the placebo group, greater weight loss reduced overall risk of these occurring in both groups. © 2011 Blackwell Publishing Ltd.

Sparsely-synchronized brain rhythm in a small-world neural network

NASA Astrophysics Data System (ADS)

Kim, Sang-Yoon; Lim, Woochang

2013-07-01

Sparsely-synchronized cortical rhythms, associated with diverse cognitive functions, have been observed in electric recordings of brain activity. At the population level, cortical rhythms exhibit small-amplitude fast oscillations while at the cellular level, individual neurons show stochastic firings sparsely at a much lower rate than the population rate. We study the effect of network architecture on sparse synchronization in an inhibitory population of subthreshold Morris-Lecar neurons (which cannot fire spontaneously without noise). Previously, sparse synchronization was found to occur for cases of both global coupling ( i.e., regular all-to-all coupling) and random coupling. However, a real neural network is known to be non-regular and non-random. Here, we consider sparse Watts-Strogatz small-world networks which interpolate between a regular lattice and a random graph via rewiring. We start from a regular lattice with only short-range connections and then investigate the emergence of sparse synchronization by increasing the rewiring probability p for the short-range connections. For p = 0, the average synaptic path length between pairs of neurons becomes long; hence, only an unsynchronized population state exists because the global efficiency of information transfer is low. However, as p is increased, long-range connections begin to appear, and global effective communication between distant neurons may be available via shorter synaptic paths. Consequently, as p passes a threshold p th (}~ 0.044), sparsely-synchronized population rhythms emerge. However, with increasing p, longer axon wirings become expensive because of their material and energy costs. At an optimal value p* DE (}~ 0.24) of the rewiring probability, the ratio of the synchrony degree to the wiring cost is found to become maximal. In this way, an optimal sparse synchronization is found to occur at a minimal wiring cost in an economic small-world network through trade-off between synchrony and wiring cost.

Self-consistent determination of the spike-train power spectrum in a neural network with sparse connectivity.

PubMed

Dummer, Benjamin; Wieland, Stefan; Lindner, Benjamin

2014-01-01

A major source of random variability in cortical networks is the quasi-random arrival of presynaptic action potentials from many other cells. In network studies as well as in the study of the response properties of single cells embedded in a network, synaptic background input is often approximated by Poissonian spike trains. However, the output statistics of the cells is in most cases far from being Poisson. This is inconsistent with the assumption of similar spike-train statistics for pre- and postsynaptic cells in a recurrent network. Here we tackle this problem for the popular class of integrate-and-fire neurons and study a self-consistent statistics of input and output spectra of neural spike trains. Instead of actually using a large network, we use an iterative scheme, in which we simulate a single neuron over several generations. In each of these generations, the neuron is stimulated with surrogate stochastic input that has a similar statistics as the output of the previous generation. For the surrogate input, we employ two distinct approximations: (i) a superposition of renewal spike trains with the same interspike interval density as observed in the previous generation and (ii) a Gaussian current with a power spectrum proportional to that observed in the previous generation. For input parameters that correspond to balanced input in the network, both the renewal and the Gaussian iteration procedure converge quickly and yield comparable results for the self-consistent spike-train power spectrum. We compare our results to large-scale simulations of a random sparsely connected network of leaky integrate-and-fire neurons (Brunel, 2000) and show that in the asynchronous regime close to a state of balanced synaptic input from the network, our iterative schemes provide an excellent approximations to the autocorrelation of spike trains in the recurrent network.

Synaptic vesicle exocytosis in hippocampal synaptosomes correlates directly with total mitochondrial volume

PubMed Central

Ivannikov, Maxim V.; Sugimori, Mutsuyuki; Llinás, Rodolfo R.

2012-01-01

Synaptic plasticity in many regions of the central nervous system leads to the continuous adjustment of synaptic strength, which is essential for learning and memory. In this study, we show by visualizing synaptic vesicle release in mouse hippocampal synaptosomes that presynaptic mitochondria and specifically, their capacities for ATP production are essential determinants of synaptic vesicle exocytosis and its magnitude. Total internal reflection microscopy of FM1-43 loaded hippocampal synaptosomes showed that inhibition of mitochondrial oxidative phosphorylation reduces evoked synaptic release. This reduction was accompanied by a substantial drop in synaptosomal ATP levels. However, cytosolic calcium influx was not affected. Structural characterization of stimulated hippocampal synaptosomes revealed that higher total presynaptic mitochondrial volumes were consistently associated with higher levels of exocytosis. Thus, synaptic vesicle release is linked to the presynaptic ability to regenerate ATP, which itself is a utility of mitochondrial density and activity. PMID:22772899

On the Teneurin track: a new synaptic organization molecule emerges

PubMed Central

Mosca, Timothy J.

2015-01-01

To achieve proper synaptic development and function, coordinated signals must pass between the pre- and postsynaptic membranes. Such transsynaptic signals can be comprised of receptors and secreted ligands, membrane associated receptors, and also pairs of synaptic cell adhesion molecules. A critical open question bridging neuroscience, developmental biology, and cell biology involves identifying those signals and elucidating how they function. Recent work in Drosophila and vertebrate systems has implicated a family of proteins, the Teneurins, as a new transsynaptic signal in both the peripheral and central nervous systems. The Teneurins have established roles in neuronal wiring, but studies now show their involvement in regulating synaptic connections between neurons and bridging the synaptic membrane and the cytoskeleton. This review will examine the Teneurins as synaptic cell adhesion molecules, explore how they regulate synaptic organization, and consider how some consequences of human Teneurin mutations may have synaptopathic origins. PMID:26074772

Interneuron- and GABAA receptor-specific inhibitory synaptic plasticity in cerebellar Purkinje cells

NASA Astrophysics Data System (ADS)

He, Qionger; Duguid, Ian; Clark, Beverley; Panzanelli, Patrizia; Patel, Bijal; Thomas, Philip; Fritschy, Jean-Marc; Smart, Trevor G.

2015-07-01

Inhibitory synaptic plasticity is important for shaping both neuronal excitability and network activity. Here we investigate the input and GABAA receptor subunit specificity of inhibitory synaptic plasticity by studying cerebellar interneuron-Purkinje cell (PC) synapses. Depolarizing PCs initiated a long-lasting increase in GABA-mediated synaptic currents. By stimulating individual interneurons, this plasticity was observed at somatodendritic basket cell synapses, but not at distal dendritic stellate cell synapses. Basket cell synapses predominantly express β2-subunit-containing GABAA receptors; deletion of the β2-subunit ablates this plasticity, demonstrating its reliance on GABAA receptor subunit composition. The increase in synaptic currents is dependent upon an increase in newly synthesized cell surface synaptic GABAA receptors and is abolished by preventing CaMKII phosphorylation of GABAA receptors. Our results reveal a novel GABAA receptor subunit- and input-specific form of inhibitory synaptic plasticity that regulates the temporal firing pattern of the principal output cells of the cerebellum.

Archaerhodopsin Selectively and Reversibly Silences Synaptic Transmission through Altered pH.

PubMed

El-Gaby, Mohamady; Zhang, Yu; Wolf, Konstantin; Schwiening, Christof J; Paulsen, Ole; Shipton, Olivia A

2016-08-23

Tools that allow acute and selective silencing of synaptic transmission in vivo would be invaluable for understanding the synaptic basis of specific behaviors. Here, we show that presynaptic expression of the proton pump archaerhodopsin enables robust, selective, and reversible optogenetic synaptic silencing with rapid onset and offset. Two-photon fluorescence imaging revealed that this effect is accompanied by a transient increase in pH restricted to archaerhodopsin-expressing boutons. Crucially, clamping intracellular pH abolished synaptic silencing without affecting the archaerhodopsin-mediated hyperpolarizing current, indicating that changes in pH mediate the synaptic silencing effect. To verify the utility of this technique, we used trial-limited, archaerhodopsin-mediated silencing to uncover a requirement for CA3-CA1 synapses whose afferents originate from the left CA3, but not those from the right CA3, for performance on a long-term memory task. These results highlight optogenetic, pH-mediated silencing of synaptic transmission as a spatiotemporally selective approach to dissecting synaptic function in behaving animals. Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.

Synaptic vesicle recycling: steps and principles.

PubMed

Rizzoli, Silvio O

2014-04-16

Synaptic vesicle recycling is one of the best-studied cellular pathways. Many of the proteins involved are known, and their interactions are becoming increasingly clear. However, as for many other pathways, it is still difficult to understand synaptic vesicle recycling as a whole. While it is generally possible to point out how synaptic reactions take place, it is not always easy to understand what triggers or controls them. Also, it is often difficult to understand how the availability of the reaction partners is controlled: how the reaction partners manage to find each other in the right place, at the right time. I present here an overview of synaptic vesicle recycling, discussing the mechanisms that trigger different reactions, and those that ensure the availability of reaction partners. A central argument is that synaptic vesicles bind soluble cofactor proteins, with low affinity, and thus control their availability in the synapse, forming a buffer for cofactor proteins. The availability of cofactor proteins, in turn, regulates the different synaptic reactions. Similar mechanisms, in which one of the reaction partners buffers another, may apply to many other processes, from the biogenesis to the degradation of the synaptic vesicle.

Sharing is Caring: The Role of Actin/Myosin-V in Synaptic Vesicle Transport between Synapses in vivo

NASA Astrophysics Data System (ADS)

Gramlich, Michael

Inter-synaptic vesicle sharing is an important but not well understood process of pre-synaptic function. Further, the molecular mechanisms that underlie this inter-synaptic exchange are not well known, and whether this inter-synaptic vesicle sharing is regulated by neural activity remains largely unexplored. I address these questions by studying CA1/CA3 Hippocampal neurons at the single synaptic vesicle level. Using high-resolution tracking of individual vesicles that have recently undergone endocytosis, I observe long-distance axonal transport of synaptic vesicles is partly mediated by the actin network. Further, the actin-dependent transport is predominantly carried out by Myosin-V. I develop a correlated-motion analysis to characterize the mechanics of how actin and Myosin-V affect vesicle transport. Lastly, I also observe that vesicle exit rates from the synapse to the axon and long-distance vesicle transport are both regulated by activity, but Myosin-V does not appear to mediate the activity dependence. These observations highlight the roles of the axonal actin network, and Myosin-V in particular, in regulating inter-synaptic vesicle exchange.

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

PubMed

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

2015-10-16

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

Abnormal Mitochondrial Dynamics and Synaptic Degeneration as Early Events in Alzheimer’s Disease: Implications to Mitochondria-Targeted Antioxidant Therapeutics

PubMed Central

Reddy, P. Hemachandra; Tripathy, Raghav; Troung, Quang; Thirumala, Karuna; Reddy, Tejaswini P.; Anekonda, Vishwanath; Shirendeb, Ulziibat P.; Calkins, Marcus J.; Reddy, Arubala P.; Mao, Peizhong; Manczak, Maria

2011-01-01

Synaptic pathology and mitochondrial oxidative damage are early events in Alzheimer’s disease (AD) progression. Loss of synapses and synaptic damage are the best correlate of cognitive deficits found in AD patients. Recent research on amyloid bet (Aβ) and mitochondria in AD revealed that Aβ accumulates in synapses and synaptic mitochondria, leading to abnormal mitochondrial dynamics and synaptic degeneration in AD neurons. Further, recent studies using live-cell imaging and primary neurons from amyloid beta precursor protein (AβPP) transgenic mice revealed that reduced mitochondrial mass, defective axonal transport of mitochondria and synaptic degeneration, indicating that Aβ is responsible for mitochondrial and synaptic deficiencies. Tremendous progress has been made in studying antioxidant approaches in mouse models of AD and clinical trials of AD patients. This article highlights the recent developments made in Aβ-induced abnormal mitochondrial dynamics, defective mitochondrial biogenesis, impaired axonal transport and synaptic deficiencies in AD. This article also focuses on mitochondrial approaches in treating AD, and also discusses latest research on mitochondria-targeted antioxidants in AD. PMID:22037588

Restraint of presynaptic protein levels by Wnd/DLK signaling mediates synaptic defects associated with the kinesin-3 motor Unc-104

PubMed Central

Asghari Adib, Elham; Stanchev, Doychin T; Xiong, Xin; Klinedinst, Susan; Soppina, Pushpanjali; Jahn, Thomas Robert; Hume, Richard I

2017-01-01

The kinesin-3 family member Unc-104/KIF1A is required for axonal transport of many presynaptic components to synapses, and mutation of this gene results in synaptic dysfunction in mice, flies and worms. Our studies at the Drosophila neuromuscular junction indicate that many synaptic defects in unc-104-null mutants are mediated independently of Unc-104’s transport function, via the Wallenda (Wnd)/DLK MAP kinase axonal damage signaling pathway. Wnd signaling becomes activated when Unc-104’s function is disrupted, and leads to impairment of synaptic structure and function by restraining the expression level of active zone (AZ) and synaptic vesicle (SV) components. This action concomitantly suppresses the buildup of synaptic proteins in neuronal cell bodies, hence may play an adaptive role to stresses that impair axonal transport. Wnd signaling also becomes activated when pre-synaptic proteins are over-expressed, suggesting the existence of a feedback circuit to match synaptic protein levels to the transport capacity of the axon. PMID:28925357

Prevalence and elimination of sibling neurite convergence in motor units supplying neonatal and adult mouse skeletal muscle.

PubMed

Teriakidis, Adrianna; Willshaw, David J; Ribchester, Richard R

2012-10-01

During development, neurons form supernumerary synapses, most of which are selectively pruned leading to stereotyped patterns of innervation. During the development of skeletal muscle innervation, or its regeneration after nerve injury, each muscle fiber is transiently innervated by multiple motor axon branches but eventually by a single branch. The selective elimination of all but one branch is the result of competition between the converging arbors. It is thought that motor neurons initially innervate muscle fibers randomly, but that axon branches from the same neuron (sibling branches) do not converge to innervate the same muscle fiber. However, random innervation would result in many neonatal endplates that are co-innervated by sibling branches. To investigate whether this occurs we examined neonatal levator auris longus (LAL) and 4th deep lumbrical (4DL) muscles, as well as adult reinnervated deep lumbrical muscles (1-4) in transgenic mice expressing yellow fluorescent protein (YFP) as a reporter. We provide direct evidence of convergence of sibling neurites within single fluorescent motor units, both during development and during regeneration after nerve crush. The incidence of sibling neurite convergence was 40% lower in regeneration and at least 75% lower during development than expected by chance. Therefore, there must be a mechanism that decreases the probability of its occurrence. As sibling neurite convergence is not seen in normal adults, or at later timepoints in regeneration, synapse elimination must also remove convergent synaptic inputs derived from the same motor neuron. Mechanistic theories of synaptic competition should now accommodate this form of isoaxonal plasticity. Copyright © 2012 Wiley Periodicals, Inc.

Glutamatergic synaptic plasticity in the mesocorticolimbic system in addiction

PubMed Central

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

Neurogranin restores amyloid β-mediated synaptic transmission and long-term potentiation deficits.

PubMed

Kaleka, Kanwardeep Singh; Gerges, Nashaat Z

2016-03-01

Amyloid β (Aβ) is widely considered one of the early causes of cognitive deficits observed in Alzheimer's disease. Many of the deficits caused by Aβ are attributed to its disruption of synaptic function represented by its blockade of long-term potentiation (LTP) and its induction of synaptic depression. Identifying pathways that reverse these synaptic deficits may open the door to new therapeutic targets. In this study, we explored the possibility that Neurogranin (Ng)-a postsynaptic calmodulin (CaM) targeting protein that enhances synaptic function-may rescue Aβ-mediated deficits in synaptic function. Our results show that Ng is able to reverse synaptic depression and LTP deficits induced by Aβ. Furthermore, Ng's restoration of synaptic transmission is through the insertion of GluA1-containing α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid glutamate receptors (AMPARs). These restorative effects of Ng are dependent on the interaction of Ng and CaM and CaM-dependent activation of CaMKII. Overall, this study identifies a novel mechanism to rescue synaptic deficits induced by Aβ oligomers. It also suggests Ng and CaM signaling as potential therapeutic targets for Alzheimer's disease as well as important tools to further explore the pathophysiology underlying the disease. Copyright © 2015 Elsevier Inc. All rights reserved.

Increased expression of the Drosophila vesicular glutamate transporter leads to excess glutamate release and a compensatory decrease in quantal content.

PubMed

Daniels, Richard W; Collins, Catherine A; Gelfand, Maria V; Dant, Jaime; Brooks, Elizabeth S; Krantz, David E; DiAntonio, Aaron

2004-11-17

Quantal size is a fundamental parameter controlling the strength of synaptic transmission. The transmitter content of synaptic vesicles is one mechanism that can affect the physiological response to the release of a single vesicle. At glutamatergic synapses, vesicular glutamate transporters (VGLUTs) are responsible for filling synaptic vesicles with glutamate. To investigate how VGLUT expression can regulate synaptic strength in vivo, we have identified the Drosophila vesicular glutamate transporter, which we name DVGLUT. DVGLUT mRNA is expressed in glutamatergic motoneurons and a large number of interneurons in the Drosophila CNS. DVGLUT protein resides on synaptic vesicles and localizes to the presynaptic terminals of all known glutamatergic neuromuscular junctions as well as to synapses throughout the CNS neuropil. Increasing the expression of DVGLUT in motoneurons leads to an increase in quantal size that is accompanied by an increase in synaptic vesicle volume. At synapses confronted with increased glutamate release from each vesicle, there is a compensatory decrease in the number of synaptic vesicles released that maintains normal levels of synaptic excitation. These results demonstrate that (1) expression of DVGLUT determines the size and glutamate content of synaptic vesicles and (2) homeostatic mechanisms exist to attenuate the excitatory effects of excess glutamate release.

Improved Neural Networks with Random Weights for Short-Term Load Forecasting

PubMed Central

Lang, Kun; Zhang, Mingyuan; Yuan, Yongbo

2015-01-01

An effective forecasting model for short-term load plays a significant role in promoting the management efficiency of an electric power system. This paper proposes a new forecasting model based on the improved neural networks with random weights (INNRW). The key is to introduce a weighting technique to the inputs of the model and use a novel neural network to forecast the daily maximum load. Eight factors are selected as the inputs. A mutual information weighting algorithm is then used to allocate different weights to the inputs. The neural networks with random weights and kernels (KNNRW) is applied to approximate the nonlinear function between the selected inputs and the daily maximum load due to the fast learning speed and good generalization performance. In the application of the daily load in Dalian, the result of the proposed INNRW is compared with several previously developed forecasting models. The simulation experiment shows that the proposed model performs the best overall in short-term load forecasting. PMID:26629825

Improved Neural Networks with Random Weights for Short-Term Load Forecasting.

PubMed

Lang, Kun; Zhang, Mingyuan; Yuan, Yongbo

2015-01-01

An effective forecasting model for short-term load plays a significant role in promoting the management efficiency of an electric power system. This paper proposes a new forecasting model based on the improved neural networks with random weights (INNRW). The key is to introduce a weighting technique to the inputs of the model and use a novel neural network to forecast the daily maximum load. Eight factors are selected as the inputs. A mutual information weighting algorithm is then used to allocate different weights to the inputs. The neural networks with random weights and kernels (KNNRW) is applied to approximate the nonlinear function between the selected inputs and the daily maximum load due to the fast learning speed and good generalization performance. In the application of the daily load in Dalian, the result of the proposed INNRW is compared with several previously developed forecasting models. The simulation experiment shows that the proposed model performs the best overall in short-term load forecasting.

Calcium responses to synaptically activated bursts of action potentials and their synapse-independent replay in cultured networks of hippocampal neurons.

PubMed

Bengtson, C Peter; Kaiser, Martin; Obermayer, Joshua; Bading, Hilmar

2013-07-01

Both synaptic N-methyl-d-aspartate (NMDA) receptors and voltage-operated calcium channels (VOCCs) have been shown to be critical for nuclear calcium signals associated with transcriptional responses to bursts of synaptic input. However the direct contribution to nuclear calcium signals from calcium influx through NMDA receptors and VOCCs has been obscured by their concurrent roles in action potential generation and synaptic transmission. Here we compare calcium responses to synaptically induced bursts of action potentials with identical bursts devoid of any synaptic contribution generated using the pre-recorded burst as the voltage clamp command input to replay the burst in the presence of blockers of action potentials or ionotropic glutamate receptors. Synapse independent replays of bursts produced nuclear calcium responses with amplitudes around 70% of their original synaptically generated signals and were abolished by the L-type VOCC blocker, verapamil. These results identify a major direct source of nuclear calcium from local L-type VOCCs whose activation is boosted by NMDA receptor dependent depolarization. The residual component of synaptically induced nuclear calcium signals which was both VOCC independent and NMDA receptor dependent showed delayed kinetics consistent with a more distal source such as synaptic NMDA receptors or internal stores. The dual requirement of NMDA receptors and L-type VOCCs for synaptic activity-induced nuclear calcium dependent transcriptional responses most likely reflects a direct somatic calcium influx from VOCCs whose activation is amplified by synaptic NMDA receptor-mediated depolarization and whose calcium signal is boosted by a delayed input from distal calcium sources mostly likely entry through NMDA receptors and release from internal stores. This article is part of a Special Issue entitled: 12th European Symposium on Calcium. Copyright © 2013 Elsevier B.V. All rights reserved.

Alteration of synaptic connectivity of oligodendrocyte precursor cells following demyelination

PubMed Central

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

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

PubMed Central

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

2015-01-01

Although many potential neuroplasticity based therapies have been developed in the lab, few have translated into established clinical treatments for human neurologic or neuropsychiatric diseases. Animal models, especially of the visual system, have shaped our understanding of neuroplasticity by characterizing the mechanisms that promote neural changes and defining timing of the sensitive period. The lack of knowledge about development of synaptic plasticity mechanisms in human cortex, and about alignment of synaptic age between animals and humans, has limited translation of neuroplasticity therapies. In this study, we quantified expression of a set of highly conserved pre- and post-synaptic proteins (Synapsin, Synaptophysin, PSD-95, Gephyrin) and found that synaptic development in human primary visual cortex (V1) continues into late childhood. Indeed, this is many years longer than suggested by neuroanatomical studies and points to a prolonged sensitive period for plasticity in human sensory cortex. In addition, during childhood we found waves of inter-individual variability that are different for the four proteins and include a stage during early development (<1 year) when only Gephyrin has high inter-individual variability. We also found that pre- and post-synaptic protein balances develop quickly, suggesting that maturation of certain synaptic functions happens within the 1 year or 2 of life. A multidimensional analysis (principle component analysis) showed that most of the variance was captured by the sum of the four synaptic proteins. We used that sum to compare development of human and rat visual cortex and identified a simple linear equation that provides robust alignment of synaptic age between humans and rats. Alignment of synaptic ages is important for age-appropriate targeting and effective translation of neuroplasticity therapies from the lab to the clinic. PMID:25729353

Limited tryptic proteolysis of the benzodiazepine binding proteins in different species reveals structural homologies.

PubMed

Friedl, W; Lentes, K U; Schmitz, E; Propping, P; Hebebrand, J

1988-12-01

Peptide mapping can be used to elucidate further the structural similarities of the benzodiazepine binding proteins in different vertebrate species. Crude synaptic membrane preparations were photoaffinity-labeled with [3H]flunitrazepam and subsequently degraded with various concentrations of trypsin. Sodium dodecyl sulfate-polyacrylamide gel electrophoresis followed by fluorography allowed a comparison of the molecular weights of photolabeled peptides in different species. Tryptic degradation led to a common peptide of 40K in all species investigated, a finding indicating that the benzodiazepine binding proteins are structurally homologous in higher bony fishes and tetrapods.

Supervised spike-timing-dependent plasticity: a spatiotemporal neuronal learning rule for function approximation and decisions.

PubMed

Franosch, Jan-Moritz P; Urban, Sebastian; van Hemmen, J Leo

2013-12-01

How can an animal learn from experience? How can it train sensors, such as the auditory or tactile system, based on other sensory input such as the visual system? Supervised spike-timing-dependent plasticity (supervised STDP) is a possible answer. Supervised STDP trains one modality using input from another one as "supervisor." Quite complex time-dependent relationships between the senses can be learned. Here we prove that under very general conditions, supervised STDP converges to a stable configuration of synaptic weights leading to a reconstruction of primary sensory input.

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

NASA Astrophysics Data System (ADS)

Kinzel, Wolfgang; Kanter, Ido

2003-10-01

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.

Cell phone intervention for you (CITY): A randomized, controlled trial of behavioral weight loss intervention for young adults using mobile technology.

PubMed

Svetkey, Laura P; Batch, Bryan C; Lin, Pao-Hwa; Intille, Stephen S; Corsino, Leonor; Tyson, Crystal C; Bosworth, Hayden B; Grambow, Steven C; Voils, Corrine; Loria, Catherine; Gallis, John A; Schwager, Jenifer; Bennett, Gary G; Bennett, Gary B

2015-11-01

To determine the effect on weight of two mobile technology-based (mHealth) behavioral weight loss interventions in young adults. Randomized, controlled comparative effectiveness trial in 18- to 35-year-olds with BMI ≥ 25 kg/m(2) (overweight/obese), with participants randomized to 24 months of mHealth intervention delivered by interactive smartphone application on a cell phone (CP); personal coaching enhanced by smartphone self-monitoring (PC); or Control. The 365 randomized participants had mean baseline BMI of 35 kg/m(2) . Final weight was measured in 86% of participants. CP was not superior to Control at any measurement point. PC participants lost significantly more weight than Controls at 6 months (net effect -1.92 kg [CI -3.17, -0.67], P = 0.003), but not at 12 and 24 months. Despite high intervention engagement and study retention, the inclusion of behavioral principles and tools in both interventions, and weight loss in all treatment groups, CP did not lead to weight loss, and PC did not lead to sustained weight loss relative to Control. Although mHealth solutions offer broad dissemination and scalability, the CITY results sound a cautionary note concerning intervention delivery by mobile applications. Effective intervention may require the efficiency of mobile technology, the social support and human interaction of personal coaching, and an adaptive approach to intervention design. © 2015 The Obesity Society.

Firing rate of noisy integrate-and-fire neurons with synaptic current dynamics

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

Andrieux, David; Monnai, Takaaki; Department of Applied Physics, Waseda University, 3-4-1 Okubo, Shinjuku-ku, Tokyo 169-8555

2009-08-15

We derive analytical formulas for the firing rate of integrate-and-fire neurons endowed with realistic synaptic dynamics. In particular, we include the possibility of multiple synaptic inputs as well as the effect of an absolute refractory period into the description. The latter affects the firing rate through its interaction with the synaptic dynamics.

The Role of Short Term Synaptic Plasticity in Temporal Coding of Neuronal Networks

ERIC Educational Resources Information Center

Chandrasekaran, Lakshmi

2008-01-01

Short term synaptic plasticity is a phenomenon which is commonly found in the central nervous system. It could contribute to functions of signal processing namely, temporal integration and coincidence detection by modulating the input synaptic strength. This dissertation has two parts. First, we study the effects of short term synaptic plasticity…

Metformin for treatment of antipsychotic-induced weight gain: a randomized, placebo-controlled study.

PubMed

Wang, Man; Tong, Jian-hua; Zhu, Gang; Liang, Guang-ming; Yan, Hong-fei; Wang, Xiu-zhen

2012-06-01

To evaluate the efficacy of metformin for treatment of antipsychotic-induced weight gain. Seventy-two patients with first-episode schizophrenia who gained more than 7% of their predrug weight were randomly assigned to receive 1000 mg/d of metformin or placebo in addition to their ongoing treatment for 12 weeks using a double-blind study design. The primary outcome was change in body weight. The secondary outcomes included changes in body mass index, fasting glucose and insulin, and insulin resistance index. Of the 72 patients who were randomly assigned, 66 (91.6%) completed treatments. The body weight, body mass index, fasting insulin and insulin resistance index decreased significantly in the metformin group, but increased in the placebo group during the 12-week follow-up period. Significantly more patients in the metformin group lost their baseline weight by more than 7%, which was the cutoff for clinically meaningful weight loss. Metformin was tolerated well by majority patients. Metformin was effective and safe in attenuating antipsychotic-induced weight gain and insulin resistance in first-episode schizophrenia patients. Patients displayed good adherence to metformin. Copyright © 2012 Elsevier B.V. All rights reserved.

Intervening on spontaneous physical activity to prevent weight regain in older adults: design of a randomized, clinical trial.

PubMed

Nicklas, Barbara J; Gaukstern, Jill E; Legault, Claudine; Leng, Iris; Rejeski, W Jack

2012-03-01

There is a need to identify evidenced-based obesity treatments that are effective in maintaining lost weight. Weight loss results in reductions in energy expenditure, including spontaneous physical activity (SPA) which is defined as energy expenditure resulting primarily from unstructured mobility-related activities that occur during daily life. To date, there is little research, especially randomized, controlled trials, testing strategies that can be adopted and sustained to prevent declines in SPA that occur with weight loss. Self-monitoring is a successful behavioral strategy to facilitate behavior change, so a provocative question is whether monitoring SPA-related energy expenditure would override these reductions in SPA, and slow weight regain. This study is a randomized trial in older, obese men and women designed to test the hypothesis that adding a self-regulatory intervention (SRI), focused around self-monitoring of SPA, to a weight loss intervention will result in less weight and fat mass regain following weight loss than a comparable intervention that lacks this self-regulatory behavioral strategy. Participants (n=72) are randomized to a 5-month weight loss intervention with or without the addition of a behavioral component that includes an innovative approach to promoting increased SPA. Both groups then transition to self-selected diet and exercise behavior for a 5-month follow-up. Throughout the 10-month period, the SRI group is provided with an intervention designed to promote a SPA level that is equal to or greater than each individual's baseline SPA level, allowing us to isolate the effects of the SPA self-regulatory intervention component on weight and fat mass regain. Copyright © 2011 Elsevier Inc. All rights reserved.

Comparing Weight Loss-Maintenance Outcomes of a Worksite-Based Lifestyle Program Delivered via DVD and Face-to-Face: A Randomized Trial.

PubMed

Ing, Claire Townsend; Miyamoto, Robin E S; Fang, Rui; Antonio, Mapuana; Paloma, Diane; Braun, Kathryn L; Kaholokula, Joseph Keawe'aimoku

2018-03-01

Native Hawaiians and other Pacific Islanders have high rates of overweight and obesity compared with other ethnic groups in Hawai'i. Effective weight loss and weight loss-maintenance programs are needed to address obesity and obesity-related health inequities for this group. Compare the effectiveness of a 9-month, worksite-based, weight loss-maintenance intervention delivered via DVD versus face-to-face in continued weight reduction and weight loss maintenance beyond the initial weight loss phase. We tested DVD versus face-to-face delivery of the PILI@Work Program's 9-month, weight loss-maintenance phase in Native Hawaiian-serving organizations. After completing the 3-month weight loss phase, participants ( n = 217) were randomized to receive the weight loss-maintenance phase delivered via trained peer facilitators or DVDs. Participant assessments at randomization and postintervention included weight, height, blood pressure, physical functioning, exercise frequency, and fat intake. Eighty-three face-to-face participants were retained at 12 months (74.1%) compared with 73 DVD participants (69.5%). There was no significant difference between groups in weight loss or weight loss maintenance. The number of lessons attended in Phase 1 of the intervention (β = 0.358, p = .022) and baseline systolic blood pressure (β = -0.038, p = .048) predicted percent weight loss at 12 months. Weight loss maintenance was similar across groups. This suggests that low-cost delivery methods for worksite-based interventions targeting at-risk populations can help address obesity and obesity-related disparities. Additionally, attendance during the weight loss phase and lower baseline systolic blood pressure predicted greater percent weight loss during the weight loss-maintenance phase, suggesting that early engagement and initial physical functioning improve long-term weight loss outcomes.

Greater weight loss among men participating in a commercial weight loss program: a pooled analysis of 2 randomized controlled trials.

PubMed

Barraj, Leila M; Murphy, Mary M; Heshka, Stanley; Katz, David L

2014-02-01

Being overweight and obese are significant health concerns for men and women, yet despite comparable needs for effective weight loss and maintenance strategies, little is known about the success of commercial weight loss programs in men. This study tests the hypothesis that men participating in a commercial weight loss program (Weight Watchers) had significantly greater weight loss than men receiving limited support from health professionals for weight loss (controls). A pooled analysis of weight loss and related physiologic parameter data from 2 randomized clinical trials was conducted. After 12 months, analysis of covariance tests showed that men in the commercial program group (n = 85) lost significantly more weight (P < .01) than men in the control group (n = 84); similar significant differences were observed for body mass index and waist circumference. These results suggest that participation in a commercial weight loss program may be a more effective means to lose weight and maintain weight loss. Published by Elsevier Inc.

One-year postpartum outcomes following a weight management intervention in pregnant women with obesity

PubMed Central

Vesco, Kimberly K.; Leo, Michael C.; Karanja, Njeri; Gillman, Matthew W.; McEvoy, Cindy T.; King, Janet C.; Eckhardt, Cara L.; Smith, K. Sabina; Perrin, Nancy; Stevens, Victor J.

2016-01-01

Objective This analysis focuses on 1-year maternal and infant follow-up of a randomized trial that tested a weight management intervention conducted during pregnancy. Methods We randomly assigned 114 women with obesity (mean BMI 36.7 kg/m2) at a mean of 15 weeks’ gestation to a weight management intervention or usual care control condition. The intervention ended at delivery and resulted in less gestational weight gain and a lower proportion of large-for-gestational age newborns among intervention compared to control participants. The primary outcome at 12 months postpartum was maternal weight. Secondary outcomes included infant weight-for-age and weight-for-length z-scores. Results At 1 year, mothers in the intervention group weighed 96.3±18.6 kg, and in the control group, 99.7±19.2 kg. There was no significant difference between groups in change in weight from randomization to 1-year postpartum (b=-0.47, 95% CI [-4.03, 3.08]. There was a significant main effect of group for infant weight-for-age z-score (b=-0.40, 95% CI [-0.75,-0.05]) but not infant weight-for-length z-scores (b=-0.20, 95% CI [-0.59,0.20]. Conclusions A gestational weight management intervention did not influence maternal weight or infant weight-for-length at 1-year postpartum. Future studies may be warranted to determine if extending prenatal interventions into the postpartum period would be beneficial for maternal and infant outcomes. PMID:27670399

Neuronal modelling of baroreflex response to orthostatic stress

NASA Astrophysics Data System (ADS)

Samin, Azfar

The accelerations experienced in aerial combat can cause pilot loss of consciousness (GLOC) due to a critical reduction in cerebral blood circulation. The development of smart protective equipment requires understanding of how the brain processes blood pressure (BP) information in response to acceleration. We present a biologically plausible model of the Baroreflex to investigate the neural correlates of short-term BP control under acceleration or orthostatic stress. The neuronal network model, which employs an integrate-and-fire representation of a biological neuron, comprises the sensory, motor, and the central neural processing areas that form the Baroreflex. Our modelling strategy is to test hypotheses relating to the encoding mechanisms of multiple sensory inputs to the nucleus tractus solitarius (NTS), the site of central neural processing. The goal is to run simulations and reproduce model responses that are consistent with the variety of available experimental data. Model construction and connectivity are inspired by the available anatomical and neurophysiological evidence that points to a barotopic organization in the NTS, and the presence of frequency-dependent synaptic depression, which provides a mechanism for generating non-linear local responses in NTS neurons that result in quantifiable dynamic global baroreflex responses. The entire physiological range of BP and rate of change of BP variables is encoded in a palisade of NTS neurons in that the spike responses approximate Gaussian 'tuning' curves. An adapting weighted-average decoding scheme computes the motor responses and a compensatory signal regulates the heart rate (HR). Model simulations suggest that: (1) the NTS neurons can encode the hydrostatic pressure difference between two vertically separated sensory receptor regions at +Gz, and use changes in that difference for the regulation of HR; (2) even though NTS neurons do not fire with a cardiac rhythm seen in the afferents, pulse-rhythmic activity is regained downstream provided the input phase information in preserved centrally; (3) frequency-dependent synaptic depression, which causes temporal variations in synaptic strength due to changes in input frequency, is a possible mechanism of non-linear dynamic baroreflex gain control. Synaptic depression enables the NTS neuron to encode dBP/dt but to lose information about the steady state firing of the afferents.

The histone acetyltransferase MOF activates hypothalamic polysialylation to prevent diet-induced obesity in mice

PubMed Central

Brenachot, Xavier; Rigault, Caroline; Nédélec, Emmanuelle; Laderrière, Amélie; Khanam, Tasneem; Gouazé, Alexandra; Chaudy, Sylvie; Lemoine, Aleth; Datiche, Frédérique; Gascuel, Jean; Pénicaud, Luc; Benani, Alexandre

2014-01-01

Overfeeding causes rapid synaptic remodeling in hypothalamus feeding circuits. Polysialylation of cell surface molecules is a key step in this neuronal rewiring and allows normalization of food intake. Here we examined the role of hypothalamic polysialylation in the long-term maintenance of body weight, and deciphered the molecular sequence underlying its nutritional regulation. We found that upon high fat diet (HFD), reduced hypothalamic polysialylation exacerbated the diet-induced obese phenotype in mice. Upon HFD, the histone acetyltransferase MOF was rapidly recruited on the St8sia4 polysialyltransferase-encoding gene. Mof silencing in the mediobasal hypothalamus of adult mice prevented activation of the St8sia4 gene transcription, reduced polysialylation, altered the acute homeostatic feeding response to HFD and increased the body weight gain. These findings indicate that impaired hypothalamic polysialylation contribute to the development of obesity, and establish a role for MOF in the brain control of energy balance. PMID:25161885

Adaptive WTA with an analog VLSI neuromorphic learning chip.

PubMed

Häfliger, Philipp

2007-03-01

In this paper, we demonstrate how a particular spike-based learning rule (where exact temporal relations between input and output spikes of a spiking model neuron determine the changes of the synaptic weights) can be tuned to express rate-based classical Hebbian learning behavior (where the average input and output spike rates are sufficient to describe the synaptic changes). This shift in behavior is controlled by the input statistic and by a single time constant. The learning rule has been implemented in a neuromorphic very large scale integration (VLSI) chip as part of a neurally inspired spike signal image processing system. The latter is the result of the European Union research project Convolution AER Vision Architecture for Real-Time (CAVIAR). Since it is implemented as a spike-based learning rule (which is most convenient in the overall spike-based system), even if it is tuned to show rate behavior, no explicit long-term average signals are computed on the chip. We show the rule's rate-based Hebbian learning ability in a classification task in both simulation and chip experiment, first with artificial stimuli and then with sensor input from the CAVIAR system.

The Brain as an Efficient and Robust Adaptive Learner.

PubMed

Denève, Sophie; Alemi, Alireza; Bourdoukan, Ralph

2017-06-07

Understanding how the brain learns to compute functions reliably, efficiently, and robustly with noisy spiking activity is a fundamental challenge in neuroscience. Most sensory and motor tasks can be described as dynamical systems and could presumably be learned by adjusting connection weights in a recurrent biological neural network. However, this is greatly complicated by the credit assignment problem for learning in recurrent networks, e.g., the contribution of each connection to the global output error cannot be determined based only on locally accessible quantities to the synapse. Combining tools from adaptive control theory and efficient coding theories, we propose that neural circuits can indeed learn complex dynamic tasks with local synaptic plasticity rules as long as they associate two experimentally established neural mechanisms. First, they should receive top-down feedbacks driving both their activity and their synaptic plasticity. Second, inhibitory interneurons should maintain a tight balance between excitation and inhibition in the circuit. The resulting networks could learn arbitrary dynamical systems and produce irregular spike trains as variable as those observed experimentally. Yet, this variability in single neurons may hide an extremely efficient and robust computation at the population level. Copyright © 2017 Elsevier Inc. All rights reserved.

A Reward-Maximizing Spiking Neuron as a Bounded Rational Decision Maker.

PubMed

Leibfried, Felix; Braun, Daniel A

2015-08-01

Rate distortion theory describes how to communicate relevant information most efficiently over a channel with limited capacity. One of the many applications of rate distortion theory is bounded rational decision making, where decision makers are modeled as information channels that transform sensory input into motor output under the constraint that their channel capacity is limited. Such a bounded rational decision maker can be thought to optimize an objective function that trades off the decision maker's utility or cumulative reward against the information processing cost measured by the mutual information between sensory input and motor output. In this study, we interpret a spiking neuron as a bounded rational decision maker that aims to maximize its expected reward under the computational constraint that the mutual information between the neuron's input and output is upper bounded. This abstract computational constraint translates into a penalization of the deviation between the neuron's instantaneous and average firing behavior. We derive a synaptic weight update rule for such a rate distortion optimizing neuron and show in simulations that the neuron efficiently extracts reward-relevant information from the input by trading off its synaptic strengths against the collected reward.

Fast convergence of learning requires plasticity between inferior olive and deep cerebellar nuclei in a manipulation task: a closed-loop robotic simulation

PubMed Central

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

2014-01-01

The cerebellum is known to play a critical role in learning relevant patterns of activity for adaptive motor control, but the underlying network mechanisms are only partly understood. The classical long-term synaptic plasticity between parallel fibers (PFs) and Purkinje cells (PCs), which is driven by the inferior olive (IO), can only account for limited aspects of learning. Recently, the role of additional forms of plasticity in the granular layer, molecular layer and deep cerebellar nuclei (DCN) has been considered. In particular, learning at DCN synapses allows for generalization, but convergence to a stable state requires hundreds of repetitions. In this paper we have explored the putative role of the IO-DCN connection by endowing it with adaptable weights and exploring its implications in a closed-loop robotic manipulation task. Our results show that IO-DCN plasticity accelerates convergence of learning by up to two orders of magnitude without conflicting with the generalization properties conferred by DCN plasticity. Thus, this model suggests that multiple distributed learning mechanisms provide a key for explaining the complex properties of procedural learning and open up new experimental questions for synaptic plasticity in the cerebellar network. PMID:25177290

Mitochondrial ROS cause motor deficits induced by synaptic inactivity: Implications for synapse pruning.

PubMed

Sidlauskaite, Eva; Gibson, Jack W; Megson, Ian L; Whitfield, Philip D; Tovmasyan, Artak; Batinic-Haberle, Ines; Murphy, Michael P; Moult, Peter R; Cobley, James N

2018-06-01

Developmental synapse pruning refines burgeoning connectomes. The basic mechanisms of mitochondrial reactive oxygen species (ROS) production suggest they select inactive synapses for pruning: whether they do so is unknown. To begin to unravel whether mitochondrial ROS regulate pruning, we made the local consequences of neuromuscular junction (NMJ) pruning detectable as motor deficits by using disparate exogenous and endogenous models to induce synaptic inactivity en masse in developing Xenopus laevis tadpoles. We resolved whether: (1) synaptic inactivity increases mitochondrial ROS; and (2) chemically heterogeneous antioxidants rescue synaptic inactivity induced motor deficits. Regardless of whether it was achieved with muscle (α-bungarotoxin), nerve (α-latrotoxin) targeted neurotoxins or an endogenous pruning cue (SPARC), synaptic inactivity increased mitochondrial ROS in vivo. The manganese porphyrins MnTE-2-PyP 5+ and/or MnTnBuOE-2-PyP 5+ blocked mitochondrial ROS to significantly reduce neurotoxin and endogenous pruning cue induced motor deficits. Selectively inducing mitochondrial ROS-using mitochondria-targeted Paraquat (MitoPQ)-recapitulated synaptic inactivity induced motor deficits; which were significantly reduced by blocking mitochondrial ROS with MnTnBuOE-2-PyP 5+ . We unveil mitochondrial ROS as synaptic activity sentinels that regulate the phenotypical consequences of forced synaptic inactivity at the NMJ. Our novel results are relevant to pruning because synaptic inactivity is one of its defining features. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Mover Is a Homomeric Phospho-Protein Present on Synaptic Vesicles

PubMed Central

Kremer, Thomas; Hoeber, Jan; Kiran Akula, Asha; Urlaub, Henning; Islinger, Markus; Kirsch, Joachim; Dean, Camin; Dresbach, Thomas

2013-01-01

With remarkably few exceptions, the molecules mediating synaptic vesicle exocytosis at active zones are structurally and functionally conserved between vertebrates and invertebrates. Mover was found in a yeast-2-hybrid assay using the vertebrate-specific active zone scaffolding protein bassoon as a bait. Peptides of Mover have been reported in proteomics screens for self-interacting proteins, phosphorylated proteins, and synaptic vesicle proteins, respectively. Here, we tested the predictions arising from these screens. Using flotation assays, carbonate stripping of peripheral membrane proteins, mass spectrometry, immunogold labelling of purified synaptic vesicles, and immuno-organelle isolation, we found that Mover is indeed a peripheral synaptic vesicle membrane protein. In addition, by generating an antibody against phosphorylated Mover and Western blot analysis of fractionated rat brain, we found that Mover is a bona fide phospho-protein. The localization of Mover to synaptic vesicles is phosphorylation dependent; treatment with a phosphatase caused Mover to dissociate from synaptic vesicles. A yeast-2-hybrid screen, co-immunoprecipitation and cell-based optical assays of homomerization revealed that Mover undergoes homophilic interaction, and regions within both the N- and C- terminus of the protein are required for this interaction. Deleting a region required for homomeric interaction abolished presynaptic targeting of recombinant Mover in cultured neurons. Together, these data prove that Mover is associated with synaptic vesicles, and implicate phosphorylation and multimerization in targeting of Mover to synaptic vesicles and presynaptic sites. PMID:23723986

Electron microscopic immunocytochemical study of somatostatin neurons in the periventricular nucleus of the rat hypothalamus with special reference to their relationships with homologous neuronal processes.

PubMed

Alonso, G; Tapia-Arancibia, L; Assenmacher, I

1985-10-01

The neurons containing somatostatin in the rat periventricular nucleus were studied by using a modified electron microscopic immunocytochemical technique that improves both the penetration of immunoreagents into unembedded immunostained tissues and the preservation of ultrastructural morphology. Inside perikarya and dendrites, immunostaining was not only associated with neurosecretory granules but also with ribosomes and saccules of the cis face of the Golgi apparatus. In the axonal profiles found in this region the labeling was observed both on neurosecretory granule cores and on the limiting membrane of small synaptic-like vesicles. Throughout the periventricular nucleus, both non-synaptic and synaptic relationships were shown between labeled neurons. Non-synaptic relationships mainly consisted of direct apposition of the membranes of neighboring neurons by dendrosomatic, somasomatic or dendrodendritic contacts. These labeled perikarya and dendrites were also synaptically contacted by labeled axonal endings containing numerous aggregated synaptic-like vesicles. The physiological significance of the synaptic and non-synaptic relationships between somatostatinergic neurons is discussed in terms of possible synchronization between homologous neurons of the somatostatin neuroendocrine system and control of these neurons by a central ultra-short loop feedback mechanism.

Dynamic DNA Methylation Controls Glutamate Receptor Trafficking and Synaptic Scaling

PubMed Central

Sweatt, J. David

2016-01-01

Hebbian plasticity, including LTP and LTD, has long been regarded as important for local circuit refinement in the context of memory formation and stabilization. However, circuit development and stabilization additionally relies on non-Hebbian, homoeostatic, forms of plasticity such as synaptic scaling. Synaptic scaling is induced by chronic increases or decreases in neuronal activity. Synaptic scaling is associated with cell-wide adjustments in postsynaptic receptor density, and can occur in a multiplicative manner resulting in preservation of relative synaptic strengths across the entire neuron's population of synapses. Both active DNA methylation and de-methylation have been validated as crucial regulators of gene transcription during learning, and synaptic scaling is known to be transcriptionally dependent. However, it has been unclear whether homeostatic forms of plasticity such as synaptic scaling are regulated via epigenetic mechanisms. This review describes exciting recent work that has demonstrated a role for active changes in neuronal DNA methylation and demethylation as a controller of synaptic scaling and glutamate receptor trafficking. These findings bring together three major categories of memory-associated mechanisms that were previously largely considered separately: DNA methylation, homeostatic plasticity, and glutamate receptor trafficking. PMID:26849493

LRRK2 kinase activity regulates synaptic vesicle trafficking and neurotransmitter release through modulation of LRRK2 macro-molecular complex

PubMed Central

Cirnaru, Maria D.; Marte, Antonella; Belluzzi, Elisa; Russo, Isabella; Gabrielli, Martina; Longo, Francesco; Arcuri, Ludovico; Murru, Luca; Bubacco, Luigi; Matteoli, Michela; Fedele, Ernesto; Sala, Carlo; Passafaro, Maria; Morari, Michele; Greggio, Elisa; Onofri, Franco; Piccoli, Giovanni

2014-01-01

Mutations in Leucine-rich repeat kinase 2 gene (LRRK2) are associated with familial and sporadic Parkinson's disease (PD). LRRK2 is a complex protein that consists of multiple domains executing several functions, including GTP hydrolysis, kinase activity, and protein binding. Robust evidence suggests that LRRK2 acts at the synaptic site as a molecular hub connecting synaptic vesicles to cytoskeletal elements via a complex panel of protein-protein interactions. Here we investigated the impact of pharmacological inhibition of LRRK2 kinase activity on synaptic function. Acute treatment with LRRK2 inhibitors reduced the frequency of spontaneous currents, the rate of synaptic vesicle trafficking and the release of neurotransmitter from isolated synaptosomes. The investigation of complementary models lacking LRRK2 expression allowed us to exclude potential off-side effects of kinase inhibitors on synaptic functions. Next we studied whether kinase inhibition affects LRRK2 heterologous interactions. We found that the binding among LRRK2, presynaptic proteins and synaptic vesicles is affected by kinase inhibition. Our results suggest that LRRK2 kinase activity influences synaptic vesicle release via modulation of LRRK2 macro-molecular complex. PMID:24904275

Reduced synaptic vesicle protein degradation at lysosomes curbs TBC1D24/sky-induced neurodegeneration.

PubMed

Fernandes, Ana Clara; Uytterhoeven, Valerie; Kuenen, Sabine; Wang, Yu-Chun; Slabbaert, Jan R; Swerts, Jef; Kasprowicz, Jaroslaw; Aerts, Stein; Verstreken, Patrik

2014-11-24

Synaptic demise and accumulation of dysfunctional proteins are thought of as common features in neurodegeneration. However, the mechanisms by which synaptic proteins turn over remain elusive. In this paper, we study Drosophila melanogaster lacking active TBC1D24/Skywalker (Sky), a protein that in humans causes severe neurodegeneration, epilepsy, and DOOR (deafness, onychdystrophy, osteodystrophy, and mental retardation) syndrome, and identify endosome-to-lysosome trafficking as a mechanism for degradation of synaptic vesicle-associated proteins. In fly sky mutants, synaptic vesicles traveled excessively to endosomes. Using chimeric fluorescent timers, we show that synaptic vesicle-associated proteins were younger on average, suggesting that older proteins are more efficiently degraded. Using a genetic screen, we find that reducing endosomal-to-lysosomal trafficking, controlled by the homotypic fusion and vacuole protein sorting (HOPS) complex, rescued the neurotransmission and neurodegeneration defects in sky mutants. Consistently, synaptic vesicle proteins were older in HOPS complex mutants, and these mutants also showed reduced neurotransmission. Our findings define a mechanism in which synaptic transmission is facilitated by efficient protein turnover at lysosomes and identify a potential strategy to suppress defects arising from TBC1D24 mutations in humans. © 2014 Fernandes et al.

Measuring Synaptic Vesicle Endocytosis in Cultured Hippocampal Neurons.

PubMed

Villarreal, Seth; Lee, Sung Hoon; Wu, Ling-Gang

2017-09-04

During endocytosis, fused synaptic vesicles are retrieved at nerve terminals, allowing for vesicle recycling and thus the maintenance of synaptic transmission during repetitive nerve firing. Impaired endocytosis in pathological conditions leads to decreases in synaptic strength and brain functions. Here, we describe methods used to measure synaptic vesicle endocytosis at the mammalian hippocampal synapse in neuronal culture. We monitored synaptic vesicle protein endocytosis by fusing a synaptic vesicular membrane protein, including synaptophysin and VAMP2/synaptobrevin, at the vesicular lumenal side, with pHluorin, a pH-sensitive green fluorescent protein that increases its fluorescence intensity as the pH increases. During exocytosis, vesicular lumen pH increases, whereas during endocytosis vesicular lumen pH is re-acidified. Thus, an increase of pHluorin fluorescence intensity indicates fusion, whereas a decrease indicates endocytosis of the labelled synaptic vesicle protein. In addition to using the pHluorin imaging method to record endocytosis, we monitored vesicular membrane endocytosis by electron microscopy (EM) measurements of Horseradish peroxidase (HRP) uptake by vesicles. Finally, we monitored the formation of nerve terminal membrane pits at various times after high potassium-induced depolarization. The time course of HRP uptake and membrane pit formation indicates the time course of endocytosis.

Synaptic vesicle recycling: steps and principles

PubMed Central

Rizzoli, Silvio O

2014-01-01

Synaptic vesicle recycling is one of the best-studied cellular pathways. Many of the proteins involved are known, and their interactions are becoming increasingly clear. However, as for many other pathways, it is still difficult to understand synaptic vesicle recycling as a whole. While it is generally possible to point out how synaptic reactions take place, it is not always easy to understand what triggers or controls them. Also, it is often difficult to understand how the availability of the reaction partners is controlled: how the reaction partners manage to find each other in the right place, at the right time. I present here an overview of synaptic vesicle recycling, discussing the mechanisms that trigger different reactions, and those that ensure the availability of reaction partners. A central argument is that synaptic vesicles bind soluble cofactor proteins, with low affinity, and thus control their availability in the synapse, forming a buffer for cofactor proteins. The availability of cofactor proteins, in turn, regulates the different synaptic reactions. Similar mechanisms, in which one of the reaction partners buffers another, may apply to many other processes, from the biogenesis to the degradation of the synaptic vesicle. PMID:24596248

Effect of Allowing Choice of Diet on Weight Loss: A Randomized Trial.

PubMed

Yancy, William S; Mayer, Stephanie B; Coffman, Cynthia J; Smith, Valerie A; Kolotkin, Ronette L; Geiselman, Paula J; McVay, Megan A; Oddone, Eugene Z; Voils, Corrine I

2015-06-16

Choosing a diet rather than being prescribed one could improve weight loss. To examine whether offering choice of diet improves weight loss. Double-randomized preference trial of choice between 2 diets (choice) versus random assignment to a diet (comparator) over 48 weeks. (ClinicalTrials.gov: NCT01152359). Outpatient clinic at a Veterans Affairs medical center. Outpatients with a body mass index of at least 30 kg/m2. Choice participants received information about their food preferences and 2 diet options (low-carbohydrate diet [LCD] or low-fat diet [LFD]) before choosing and were allowed to switch diets at 12 weeks. Comparator participants were randomly assigned to 1 diet for 48 weeks. Both groups received group and telephone counseling for 48 weeks. The primary outcome was weight at 48 weeks. Of 105 choice participants, 61 (58%) chose the LCD and 44 (42%) chose the LFD; 5 (3 on the LCD and 2 on the LFD) switched diets at 12 weeks, and 87 (83%) completed measurements at 48 weeks. Of 102 comparator participants, 53 (52%) were randomly assigned to the LCD and 49 (48%) were assigned to the LFD; 88 (86%) completed measurements. At 48 weeks, estimated mean weight loss was 5.7 kg (95% CI, 4.3 to 7.0 kg) in the choice group and 6.7 kg (CI, 5.4 to 8.0 kg) in the comparator group (mean difference, -1.1 kg [CI, -2.9 to 0.8 kg]; P = 0.26). Secondary outcomes of dietary adherence, physical activity, and weight-related quality of life were similar between groups at 48 weeks. Only 2 diet options were provided. Results from this sample of older veterans might not be generalizable to other populations. Contrary to expectations, the opportunity to choose a diet did not improve weight loss.

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

PubMed

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.

Self-organised criticality via retro-synaptic signals

NASA Astrophysics Data System (ADS)

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.

Differentiated effect of ageing on the enzymes of Krebs' cycle, electron transfer complexes and glutamate metabolism of non-synaptic and intra-synaptic mitochondria from cerebral cortex.

PubMed

Villa, R F; Gorini, A; Hoyer, S

2006-11-01

The effect of ageing on the activity of enzymes linked to Krebs' cycle, electron transfer chain and glutamate metabolism was studied in three different types of mitochondria of cerebral cortex of 1-year old and 2-year old male Wistar rats. We assessed the maximum rate (V(max)) of the mitochondrial enzyme activities in non-synaptic perikaryal mitochondria, and in two populations of intra-synaptic mitochondria. The results indicated that: (i) in normal, steady-state cerebral cortex the values of the catalytic activities of the enzymes markedly differed in the various populations of mitochondria; (ii) in intra-synaptic mitochondria, ageing affected the catalytic properties of the enzymes linked to Krebs' cycle, electron transfer chain and glutamate metabolism; (iii) these changes were more evident in intra-synaptic "heavy" than "light" mitochondria. These results indicate a different age-related vulnerability of subpopulations of mitochondria in vivo located into synapses than non-synaptic ones.

SYNAPTIC DEPRESSION IN DEEP NEURAL NETWORKS FOR SPEECH PROCESSING.

PubMed

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

2016-03-01

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

The interplay between inflammatory cytokines and the endocannabinoid system in the regulation of synaptic transmission.

PubMed

Rossi, Silvia; Motta, Caterina; Musella, Alessandra; Centonze, Diego

2015-09-01

Excessive glutamate-mediated synaptic transmission and secondary excitotoxicity have been proposed as key determinants of neurodegeneration in many neurological diseases. Soluble mediators of inflammation have recently gained attention owing to their ability to enhance glutamate transmission and affect synaptic sensitivity to neurotransmitters. In the complex crosstalk between soluble immunoactive molecules and synapses, the endocannabinoid system (ECS) plays a central role, exerting an indirect neuroprotective action by inhibiting cytokine-dependent synaptic alterations, and a direct neuroprotective effect by limiting glutamate transmission and excitotoxic damage. On the other hand, the endocannabinoid (eCB)-mediated control of synaptic transmission is altered by proinflammatory cytokines with consequent effects in central nervous system (CNS) disorders. In this review, we summarize the interactions, at the pre- and postsynaptic level, between major inflammatory cytokines and the ECS. In addition, the behavioral and clinical consequences of the modulation of synaptic transmission during neuroinflammation are discussed. This article is part of a Special Issue entitled 'Neuroimmunology and Synaptic Function'. Copyright © 2014 Elsevier Ltd. All rights reserved.

Radixin regulates synaptic GABAA receptor density and is essential for reversal learning and short-term memory

PubMed Central

Hausrat, Torben J.; Muhia, Mary; Gerrow, Kimberly; Thomas, Philip; Hirdes, Wiebke; Tsukita, Sachiko; Heisler, Frank F.; Herich, Lena; Dubroqua, Sylvain; Breiden, Petra; Feldon, Joram; Schwarz, Jürgen R; Yee, Benjamin K.; Smart, Trevor G.; Triller, Antoine; Kneussel, Matthias

2015-01-01

Neurotransmitter receptor density is a major variable in regulating synaptic strength. Receptors rapidly exchange between synapses and intracellular storage pools through endocytic recycling. In addition, lateral diffusion and confinement exchanges surface membrane receptors between synaptic and extrasynaptic sites. However, the signals that regulate this transition are currently unknown. GABAA receptors containing α5-subunits (GABAAR-α5) concentrate extrasynaptically through radixin (Rdx)-mediated anchorage at the actin cytoskeleton. Here we report a novel mechanism that regulates adjustable plasma membrane receptor pools in the control of synaptic receptor density. RhoA/ROCK signalling regulates an activity-dependent Rdx phosphorylation switch that uncouples GABAAR-α5 from its extrasynaptic anchor, thereby enriching synaptic receptor numbers. Thus, the unphosphorylated form of Rdx alters mIPSCs. Rdx gene knockout impairs reversal learning and short-term memory, and Rdx phosphorylation in wild-type mice exhibits experience-dependent changes when exposed to novel environments. Our data suggest an additional mode of synaptic plasticity, in which extrasynaptic receptor reservoirs supply synaptic GABAARs. PMID:25891999

Diverse modes of synaptic signaling, regulation, and plasticity distinguish two classes of C. elegans glutamatergic neurons.

PubMed

Ventimiglia, Donovan; Bargmann, Cornelia I

2017-11-21

Synaptic vesicle release properties vary between neuronal cell types, but in most cases the molecular basis of this heterogeneity is unknown. Here, we compare in vivo synaptic properties of two neuronal classes in the C. elegans central nervous system, using VGLUT-pHluorin to monitor synaptic vesicle exocytosis and retrieval in intact animals. We show that the glutamatergic sensory neurons AWC ON and ASH have distinct synaptic dynamics associated with tonic and phasic synaptic properties, respectively. Exocytosis in ASH and AWC ON is differentially affected by SNARE-complex regulators that are present in both neurons: phasic ASH release is strongly dependent on UNC-13, whereas tonic AWC ON release relies upon UNC-18 and on the protein kinase C homolog PKC-1. Strong stimuli that elicit high calcium levels increase exocytosis and retrieval rates in AWC ON , generating distinct tonic and evoked synaptic modes. These results highlight the differential deployment of shared presynaptic proteins in neuronal cell type-specific functions.

Diverse modes of synaptic signaling, regulation, and plasticity distinguish two classes of C. elegans glutamatergic neurons

PubMed Central

Ventimiglia, Donovan

2017-01-01

Synaptic vesicle release properties vary between neuronal cell types, but in most cases the molecular basis of this heterogeneity is unknown. Here, we compare in vivo synaptic properties of two neuronal classes in the C. elegans central nervous system, using VGLUT-pHluorin to monitor synaptic vesicle exocytosis and retrieval in intact animals. We show that the glutamatergic sensory neurons AWCON and ASH have distinct synaptic dynamics associated with tonic and phasic synaptic properties, respectively. Exocytosis in ASH and AWCON is differentially affected by SNARE-complex regulators that are present in both neurons: phasic ASH release is strongly dependent on UNC-13, whereas tonic AWCON release relies upon UNC-18 and on the protein kinase C homolog PKC-1. Strong stimuli that elicit high calcium levels increase exocytosis and retrieval rates in AWCON, generating distinct tonic and evoked synaptic modes. These results highlight the differential deployment of shared presynaptic proteins in neuronal cell type-specific functions. PMID:29160768

Synaptic transmission block by presynaptic injection of oligomeric amyloid beta

PubMed Central

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

Short-Term Synaptic Plasticity Regulation in Solution-Gated Indium-Gallium-Zinc-Oxide Electric-Double-Layer Transistors.

PubMed

Wan, Chang Jin; Liu, Yang Hui; Zhu, Li Qiang; Feng, Ping; Shi, Yi; Wan, Qing

2016-04-20

In the biological nervous system, synaptic plasticity regulation is based on the modulation of ionic fluxes, and such regulation was regarded as the fundamental mechanism underlying memory and learning. Inspired by such biological strategies, indium-gallium-zinc-oxide (IGZO) electric-double-layer (EDL) transistors gated by aqueous solutions were proposed for synaptic behavior emulations. Short-term synaptic plasticity, such as paired-pulse facilitation, high-pass filtering, and orientation tuning, was experimentally emulated in these EDL transistors. Most importantly, we found that such short-term synaptic plasticity can be effectively regulated by alcohol (ethyl alcohol) and salt (potassium chloride) additives. Our results suggest that solution gated oxide-based EDL transistors could act as the platforms for short-term synaptic plasticity emulation.

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

PubMed

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

2014-06-01

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

Experimental implementation of a biometric laser synaptic sensor.

PubMed

Pisarchik, Alexander N; Sevilla-Escoboza, Ricardo; Jaimes-Reátegui, Rider; Huerta-Cuellar, Guillermo; García-Lopez, J Hugo; Kazantsev, Victor B

2013-12-16

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.

Time-dependent decreases in nucleus accumbens AMPA/NMDA ratio and incubation of sucrose craving in adolescent and adult rats.

PubMed

Counotte, Danielle S; Schiefer, Christopher; Shaham, Yavin; O'Donnell, Patricio

2014-04-01

There is evidence that cue-induced sucrose seeking progressively increases after cessation of oral sucrose self-administration (incubation of sucrose craving) in both adolescent and adult rats. The synaptic plasticity changes associated with this incubation at different age groups are unknown. We assessed whether incubation of sucrose craving in rats trained to self-administer sucrose as young adolescents, adolescents, or adults is associated with changes in 2-amino-3-(3-hydroxy-5-methyl-isoxazol-4-yl)propanoic acid (AMPA)/N-methyl-D-aspartate (NMDA) ratio (a measure of postsynaptic changes in synaptic strength) in nucleus accumbens. Three age groups initiated oral sucrose self-administration training (10 days) on postnatal day (P) 35 (young adolescents), P42 (adolescents), or P70 (adults). They were then tested for cue-induced sucrose seeking (assessed in an extinction test) on abstinence days 1 and 21. Separate groups of rats were trained to self-administer sucrose or water (a control condition), and assessed for AMPA/NMDA ratio in nucleus accumbens on abstinence days 1-3 and 21. Adult rats earned more sucrose rewards, but sucrose intake per body weight was higher in young adolescent rats. Time-dependent increases in cue-induced sucrose seeking (incubation of sucrose craving) were more pronounced in adult rats, less pronounced in adolescents, and not detected in young adolescents. On abstinence day 21, but not days 1-3, AMPA/NMDA ratio in nucleus accumbens were decreased in rats that self-administered sucrose as adults and adolescents, but not young adolescents. Our data demonstrate age-dependent changes in magnitude of incubation of sucrose craving and nucleus accumbens synaptic plasticity after cessation of sucrose self-administration.

Network evolution induced by asynchronous stimuli through spike-timing-dependent plasticity.

PubMed

Yuan, Wu-Jie; Zhou, Jian-Fang; Zhou, Changsong

2013-01-01

In sensory neural system, external asynchronous stimuli play an important role in perceptual learning, associative memory and map development. However, the organization of structure and dynamics of neural networks induced by external asynchronous stimuli are not well understood. Spike-timing-dependent plasticity (STDP) is a typical synaptic plasticity that has been extensively found in the sensory systems and that has received much theoretical attention. This synaptic plasticity is highly sensitive to correlations between pre- and postsynaptic firings. Thus, STDP is expected to play an important role in response to external asynchronous stimuli, which can induce segregative pre- and postsynaptic firings. In this paper, we study the impact of external asynchronous stimuli on the organization of structure and dynamics of neural networks through STDP. We construct a two-dimensional spatial neural network model with local connectivity and sparseness, and use external currents to stimulate alternately on different spatial layers. The adopted external currents imposed alternately on spatial layers can be here regarded as external asynchronous stimuli. Through extensive numerical simulations, we focus on the effects of stimulus number and inter-stimulus timing on synaptic connecting weights and the property of propagation dynamics in the resulting network structure. Interestingly, the resulting feedforward structure induced by stimulus-dependent asynchronous firings and its propagation dynamics reflect both the underlying property of STDP. The results imply a possible important role of STDP in generating feedforward structure and collective propagation activity required for experience-dependent map plasticity in developing in vivo sensory pathways and cortices. The relevance of the results to cue-triggered recall of learned temporal sequences, an important cognitive function, is briefly discussed as well. Furthermore, this finding suggests a potential application for examining STDP by measuring neural population activity in a cultured neural network.

Rescuing effects of RXR agonist bexarotene on aging-related synapse loss depend on neuronal LRP1.

PubMed

Tachibana, Masaya; Shinohara, Mitsuru; Yamazaki, Yu; Liu, Chia-Chen; Rogers, Justin; Bu, Guojun; Kanekiyo, Takahisa

2016-03-01

Apolipoprotein E (apoE) plays a critical role in maintaining synaptic integrity by transporting cholesterol to neurons through the low-density lipoprotein receptor related protein-1 (LRP1). Bexarotene, a retinoid X receptor (RXR) agonist, has been reported to have potential beneficial effects on cognition by increasing brain apoE levels and lipidation. To investigate the effects of bexarotene on aging-related synapse loss and the contribution of neuronal LRP1 to the pathway, forebrain neuron-specific LRP1 knockout (nLrp1(-/-)) and littermate control mice were administered with bexarotene-formulated diet (100mg/kg/day) or control diet at the age of 20-24 months for 8 weeks. Upon bexarotene treatment, levels of brain apoE and ATP-binding cassette sub-family A member 1 (ABCA1) were significantly increased in both mice. While levels of PSD95, glutamate receptor 1 (GluR1), and N-methyl-d-aspartate receptor NR1 subunit (NR1), which are key postsynaptic proteins that regulate synaptic plasticity, were decreased with aging, they were restored by bexarotene treatment in the brains of control but not nLrp1(-/-) mice. These results indicate that the beneficial effects of bexarotene on synaptic integrity depend on the presence of neuronal LRP1. However, we also found that bexarotene treatment led to the activation of glial cells, weight loss and hepatomegaly, which are likely due to hepatic failure. Taken together, our results demonstrate that apoE-targeted treatment through the RXR pathway has a potential beneficial effect on synapses during aging; however, the therapeutic application of bexarotene requires extreme caution due to its toxic side effects. Copyright © 2015 Elsevier Inc. All rights reserved.

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

PubMed Central

Bill, Johannes; Legenstein, Robert

2014-01-01

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

Purification of a post-synaptic neurotoxic phospholipase A2 from Naja naja venom and its inhibition by a glycoprotein from Withania somnifera.

PubMed

Machiah, Deepa K; Gowda, T Veerabasappa

2006-06-01

A post-synaptic neurotoxic phospholipase A(2) (PLA(2)) has been purified from Indian cobra Naja naja venom. It was associated with a peptide in the venom. The association was disrupted using 8 M urea. It is denoted to be a basic protein by its behavior on both ion exchange chromatography and electrophoresis. It is toxic to mice, LD(50) 1.9 mg/kg body weight (ip). It is proved to be post-synaptic PLA(2) by chymographic experiment using frog nerve-muscle preparation. A glycoprotein, (WSG) was isolated from a folk medicinal plant Withania somnifera. The WSG inhibited the phospholipase A(2) activity of NN-XIa-PLA(2,) isolated from the cobra venom, completely at a mole-to-mole ratio of 1:2 (NN-XIa-PLA(2): WSG) but failed to neutralize the toxicity of the molecule. However, it reduced the toxicity as well as prolonged the death time of the experimental mice approximately 10 times when compared to venom alone. The WSG also inhibited several other PLA(2) isoforms from the venom to varying extent. The interaction of the WSG with the PLA(2) is confirmed by fluorescence quenching and gel-permeation chromatography. Chemical modification of the active histidine residue of PLA(2) using p-brophenacyl bromide resulted in the loss of both catalytic activity as well as neurotoxicity of the molecule. These findings suggest that the venom PLA(2) has multiple sites on it; perhaps some of them are overlapping. Application of the plant extract on snakebite wound confirms the medicinal value associated with the plant.

Financial incentive strategies for maintenance of weight loss: results from an internet-based randomized controlled trial.

PubMed

Yancy, William S; Shaw, Pamela A; Wesby, Lisa; Hilbert, Victoria; Yang, Lin; Zhu, Jingsan; Troxel, Andrea; Huffman, David; Foster, Gary D; Wojtanowski, Alexis C; Volpp, Kevin G

2018-05-25

Financial incentives can improve initial weight loss; we examined whether financial incentives can improve weight loss maintenance. Participants aged 30-80 years who lost at least 5 kg during the first 4-6 months in a nationally available commercial weight loss program were recruited via the internet into a three-arm randomized trial of two types of financial incentives versus active control during months 1-6 (Phase I) followed by passive monitoring during months 7-12 (Phase II). Interventions were daily self-weighing and text messaging feedback alone (control) or combined with a lottery-based incentive or a direct incentive. The primary outcome was weight change 6 months after initial weight loss. Secondary outcomes included weight change 12 months after initial weight loss (6 months after cessation of maintenance intervention), and self-reported physical activity and eating behaviors. Of 191 participants randomized, the mean age was 49.0 (SD = 10.5) years and weight loss prior to randomization was 11.4 (4.7) kg; 92% were women and 89% were White. Mean weight changes during the next 6 months (Phase I) were: lottery -3.0 (5.8) kg; direct -2.8 (5.8) kg; and control -1.4 (5.8) kg (all pairwise comparisons p > 0.1). Weight changes through the end of 12 months post-weight loss (Phase II) were: lottery -1.8 (10.5) kg; direct -0.7 (10.7) kg; and control -0.3 (9.4) kg (all pairwise comparisons p > 0.1). The percentages of participants who maintained their weight loss (defined as gaining ≤1.36 kg) were: lottery 79%, direct 76%, and control 67% at 6 months and lottery 66%, direct 62%, and control 59% at 12 months (all pairwise comparisons p > 0.1). At 6 and 12 months after initial weight loss, changes in self-reported physical activity or eating behaviors did not differ across arms. Compared with the active control of daily texting based on daily home weighing, lottery-based and direct monetary incentives provided no additional benefit for weight loss maintenance.

Zinc Transporter 3 Is Involved in Learned Fear and Extinction, but Not in Innate Fear

ERIC Educational Resources Information Center

Martel, Guillaume; Hevi, Charles; Friebely, Olivia; Baybutt, Trevor; Shumyatsky, Gleb P.

2010-01-01

Synaptically released Zn[superscript 2+] is a potential modulator of neurotransmission and synaptic plasticity in fear-conditioning pathways. Zinc transporter 3 (ZnT3) knock-out (KO) mice are well suited to test the role of zinc in learned fear, because ZnT3 is colocalized with synaptic zinc, responsible for its transport to synaptic vesicles,…

Spontaneous Release Regulates Synaptic Scaling in the Embryonic Spinal Network In Vivo

PubMed Central

Garcia-Bereguiain, Miguel Angel; Gonzalez-Islas, Carlos; Lindsly, Casie

2016-01-01

Homeostatic plasticity mechanisms maintain cellular or network spiking activity within a physiologically functional range through compensatory changes in synaptic strength or intrinsic cellular excitability. Synaptic scaling is one form of homeostatic plasticity that is triggered after blockade of spiking or neurotransmission in which the strengths of all synaptic inputs to a cell are multiplicatively scaled upward or downward in a compensatory fashion. We have shown previously that synaptic upscaling could be triggered in chick embryo spinal motoneurons by complete blockade of spiking or GABAA receptor (GABAAR) activation for 2 d in vivo. Here, we alter GABAAR activation in a more physiologically relevant manner by chronically adjusting presynaptic GABA release in vivo using nicotinic modulators or an mGluR2 agonist. Manipulating GABAAR activation in this way triggered scaling in a mechanistically similar manner to scaling induced by complete blockade of GABAARs. Remarkably, we find that altering action-potential (AP)-independent spontaneous release was able to fully account for the observed bidirectional scaling, whereas dramatic changes in spiking activity associated with spontaneous network activity had little effect on quantal amplitude. The reliance of scaling on an AP-independent process challenges the plasticity's relatedness to spiking in the living embryonic spinal network. Our findings have implications for the trigger and function of synaptic scaling and suggest that spontaneous release functions to regulate synaptic strength homeostatically in vivo. SIGNIFICANCE STATEMENT Homeostatic synaptic scaling is thought to prevent inappropriate levels of spiking activity through compensatory adjustments in the strength of synaptic inputs. Therefore, it is thought that perturbations in spike rate trigger scaling. Here, we find that dramatic changes in spiking activity in the embryonic spinal cord have little effect on synaptic scaling; conversely, alterations in GABAA receptor activation due to action-potential-independent GABA vesicle release can trigger scaling. The findings suggest that scaling in the living embryonic spinal cord functions to maintain synaptic strength and challenge the view that scaling acts to regulate spiking activity homeostatically. Finally, the results indicate that fetal exposure to drugs that influence GABA spontaneous release, such as nicotine, could profoundly affect synaptic maturation. PMID:27383600

Nanowire FET Based Neural Element for Robotic Tactile Sensing Skin

PubMed Central

Taube Navaraj, William; García Núñez, Carlos; Shakthivel, Dhayalan; Vinciguerra, Vincenzo; Labeau, Fabrice; Gregory, Duncan H.; Dahiya, Ravinder

2017-01-01

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. PMID:28979183

Effect of Wearable Technology Combined With a Lifestyle Intervention on Long-term Weight Loss: The IDEA Randomized Clinical Trial.

PubMed

Jakicic, John M; Davis, Kelliann K; Rogers, Renee J; King, Wendy C; Marcus, Marsha D; Helsel, Diane; Rickman, Amy D; Wahed, Abdus S; Belle, Steven H

2016-09-20

Effective long-term treatments are needed to address the obesity epidemic. Numerous wearable technologies specific to physical activity and diet are available, but it is unclear if these are effective at improving weight loss. To test the hypothesis that, compared with a standard behavioral weight loss intervention (standard intervention), a technology-enhanced weight loss intervention (enhanced intervention) would result in greater weight loss. Randomized clinical trial conducted at the University of Pittsburgh and enrolling 471 adult participants between October 2010 and October 2012, with data collection completed by December 2014. Participants were placed on a low-calorie diet, prescribed increases in physical activity, and had group counseling sessions. At 6 months, the interventions added telephone counseling sessions, text message prompts, and access to study materials on a website. At 6 months, participants randomized to the standard intervention group initiated self-monitoring of diet and physical activity using a website, and those randomized to the enhanced intervention group were provided with a wearable device and accompanying web interface to monitor diet and physical activity. The primary outcome of weight was measured over 24 months at 6-month intervals, and the primary hypothesis tested the change in weight between 2 groups at 24 months. Secondary outcomes included body composition, fitness, physical activity, and dietary intake. Among the 471 participants randomized (body mass index [BMI], 25 to <40; age range, 18-35 years; 28.9% nonwhite, 77.2% women), 470 (233 in the standard intervention group, 237 in the enhanced intervention group) initiated the interventions as randomized, and 74.5% completed the study. For the enhanced intervention group, mean base line weight was 96.3 kg (95% CI, 94.2-98.5) and 24-month weight 92.8 kg (95% CI, 90.6- 95.0) [corrected]. For the standard intervention group, mean baseline weight was 95.2kg (95%CI,93.0-97.3)and24-month weight was 89.3 kg (95%CI, 87.1-91.5) [corrected]. Weight change at 24 months differed significantly by intervention group (estimated mean weight loss, 3.5 kg [95% CI, 2.6-4.5} in the enhanced intervention group and 5.9 kg [95% CI, 5.0-6.8] in the standard intervention group; difference, 2.4 kg [95% CI, 1.0-3.7]; P = .002). Both groups had significant improvements in body composition, fitness, physical activity, and diet, with no significant difference between groups. Among young adults with a BMI between 25 and less than 40, the addition of a wearable technology device to a standard behavioral intervention resulted in less weight loss over 24 months. Devices that monitor and provide feedback on physical activity may not offer an advantage over standard behavioral weight loss approaches. clinicaltrials.gov Identifier: NCT01131871.

Anabolic steroids for the treatment of weight loss in HIV-infected individuals.

PubMed

Johns, K; Beddall, M J; Corrin, R C

2005-10-19

Individuals with HIV infection often lose weight during the course of their disease. Furthermore, low serum concentrations of testosterone are common in individuals with HIV infection, particularly those with weight loss. Treatment of weight loss with anabolic steroids in HIV-infected individuals may be beneficial. Our objectives were to assess the efficacy and safety of anabolic steroids for the treatment of weight loss in adults with HIV infection. We searched the following databases: Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, AIDSLINE, AIDSearch, EMBASE, CINAHL, Current Contents, and the National Library of Medicine Gateway Abstracts for controlled trials up to April 2005. We also searched the bibliographies of the identified studies and review the articles. In addition, pharmaceutical manufacturers of anabolic steroids were contacted. Randomized controlled trials that compared the use of an anabolic steroid to placebo to treat weight loss in adults with HIV were included. Randomized controlled trials that compared the use of anabolic steroids to placebo for the treatment of weight loss in adults with HIV were selected. Change from baseline in lean body mass or in body weight was reported as on outcome measure. Two reviewers independently assessed the trials for quality of randomization, blinding, withdrawals, and adequacy of allocation concealment. For continuous data, weighted mean differences (WMD) were calculated. For dichotomous outcomes, risk differences, were calculated. Because of uncertainty as to whether consistent true effects exist in such different populations and treatments, the authors decided a priori to use random effects models for all outcomes. Thirteen trials met the inclusion criteria. Two hundred ninety-four individuals randomized to anabolic steroid therapy and 238 individuals randomized to placebo were included in the analysis of efficacy for change from baseline in lean body mass. Three hundred forty-three individuals randomized to anabolic steroid and 286 randomized to placebo were included in the analysis of efficacy for change from baseline in body weight. The mean methodologic quality of the included studies was 4.1, of a maximum 5 points. Although significant heterogeneity was present for both outcomes, the average change in lean body mass was 1.3 kg (95% CI: 0.6, 2.0), while the average change in total body weight was 1.1 kg (95% CI: 0.3, 2.0). A total of eight deaths occurred during the treatment period; four in the anabolic steroid treatment groups and four in the placebo-treatment groups (risk difference 0.00, 95% CI -0.03, 0.03). The risk difference for withdrawals or discontinuations of study medication due to adverse events was 0.00 (95% CI: -0.02, 0.03). Although the results of the trials were heterogeneous, on average, the administration of anabolic steroids appeared to result in a small increase in both lean body mass and body weight as compared with placebo. While these results suggest that anabolic steroids may be useful in the treatment of weight loss in HIV infected individuals, due to limitations, treatment recommendations cannot be made. Further information is required regarding the long-term benefit and adverse effects of anabolic steroid use, the specific populations for which anabolic steroid therapy may be most beneficial, and the optimal regime. In addition, the correlation of improvement in lean body mass with more clinically relevant endpoints, such as physical functioning and survival, needs to be determined.

Cell phone Intervention for You (CITY): A randomized, controlled trial of behavioral weight loss intervention for young adults using mobile technology

PubMed Central

Svetkey, LP; Batch, BC; Lin, P-H; Intille, SS; Corsino, L; Tyson, CC; Bosworth, HB; Grambow, SC; Voils, C; Loria, C; Gallis, JA; Schwager, J; Bennett, GB

2015-01-01

Objectives To determine the effect on weight of two Mobile technology-based (mHealth) behavioral weight loss interventions in young adults. Methods Randomized, controlled comparative effectiveness trial in 18–35 year olds with BMI ≥ 25 kg/m2 (overweight/obese), with participants randomized to 24 months of mHealth intervention delivered by interactive smartphone application on a cell phone (CP); personal coaching enhanced by smartphone self-monitoring (PC); or Control. Results The 365 randomized participants had mean baseline BMI of 35 kg/m2. Final weight was measured in 86% of participants. CP was not superior to Control at any measurement point. PC participants lost significantly more weight than Controls at 6 months (net effect −1.92 kg [CI −3.17, −0.67], p=0.003), but not at 12 and 24 months. Conclusions Despite high intervention engagement and study retention, the inclusion of behavioral principles and tools in both interventions, and weight loss in all treatment groups, CP did not lead to weight loss and PC did not lead to sustained weight loss relative to control. Although mHealth solutions offer broad dissemination and scalability, the CITY results sound a cautionary note concerning intervention delivery by mobile applications. Effective intervention may require the efficiency of mobile technology, the social support and human interaction of personal coaching, and an adaptive approach to intervention design. Trial Registration ClinicalTrials.gov Identifier NCT01092364. https://clinicaltrials.gov/ct2/show/NCT01092364?term=Cell+phone+intervention+for+you&rank=3 PMID:26530929

Shank3 Is Part of a Zinc-Sensitive Signaling System That Regulates Excitatory Synaptic Strength.

PubMed

Arons, Magali H; Lee, Kevin; Thynne, Charlotte J; Kim, Sally A; Schob, Claudia; Kindler, Stefan; Montgomery, Johanna M; Garner, Craig C

2016-08-31

Shank3 is a multidomain scaffold protein localized to the postsynaptic density of excitatory synapses. Functional studies in vivo and in vitro support the concept that Shank3 is critical for synaptic plasticity and the trans-synaptic coupling between the reliability of presynaptic neurotransmitter release and postsynaptic responsiveness. However, how Shank3 regulates synaptic strength remains unclear. The C terminus of Shank3 contains a sterile alpha motif (SAM) domain that is essential for its postsynaptic localization and also binds zinc, thus raising the possibility that changing zinc levels modulate Shank3 function in dendritic spines. In support of this hypothesis, we find that zinc is a potent regulator of Shank3 activation and dynamics in rat hippocampal neurons. Moreover, we show that zinc modulation of synaptic transmission is Shank3 dependent. Interestingly, an autism spectrum disorder (ASD)-associated variant of Shank3 (Shank3(R87C)) retains its zinc sensitivity and supports zinc-dependent activation of AMPAR-mediated synaptic transmission. However, elevated zinc was unable to rescue defects in trans-synaptic signaling caused by the R87C mutation, implying that trans-synaptic increases in neurotransmitter release are not necessary for the postsynaptic effects of zinc. Together, these data suggest that Shank3 is a key component of a zinc-sensitive signaling system, regulating synaptic strength that may be impaired in ASD. Shank3 is a postsynaptic protein associated with neurodevelopmental disorders such as autism and schizophrenia. In this study, we show that Shank3 is a key component of a zinc-sensitive signaling system that regulates excitatory synaptic transmission. Intriguingly, an autism-associated mutation in Shank3 partially impairs this signaling system. Therefore, perturbation of zinc homeostasis may impair, not only synaptic functionality and plasticity, but also may lead to cognitive and behavioral abnormalities seen in patients with psychiatric disorders. Copyright © 2016 the authors 0270-6474/16/369124-11$15.00/0.

Aβ-Induced Synaptic Alterations Require the E3 Ubiquitin Ligase Nedd4-1.

PubMed

Rodrigues, Elizabeth M; Scudder, Samantha L; Goo, Marisa S; Patrick, Gentry N

2016-02-03

Alzheimer's disease (AD) is a neurodegenerative disease in which patients experience progressive cognitive decline. A wealth of evidence suggests that this cognitive impairment results from synaptic dysfunction in affected brain regions caused by cleavage of amyloid precursor protein into the pathogenic peptide amyloid-β (Aβ). Specifically, it has been shown that Aβ decreases surface AMPARs, dendritic spine density, and synaptic strength, and also alters synaptic plasticity. The precise molecular mechanisms by which this occurs remain unclear. Here we demonstrate a role for ubiquitination in Aβ-induced synaptic dysfunction in cultured rat neurons. We find that Aβ promotes the ubiquitination of AMPARs, as well as the redistribution and recruitment of Nedd4-1, a HECT E3 ubiquitin ligase we previously demonstrated to target AMPARs for ubiquitination and degradation. Strikingly, we show that Nedd4-1 is required for Aβ-induced reductions in surface AMPARs, synaptic strength, and dendritic spine density. Our findings, therefore, indicate an important role for Nedd4-1 and ubiquitin in the synaptic alterations induced by Aβ. Synaptic changes in Alzheimer's disease (AD) include surface AMPAR loss, which can weaken synapses. In a cell culture model of AD, we found that AMPAR loss correlates with increased AMPAR ubiquitination. In addition, the ubiquitin ligase Nedd4-1, known to ubiquitinate AMPARs, is recruited to synapses in response to Aβ. Strikingly, reducing Nedd4-1 levels in this model prevented surface AMPAR loss and synaptic weakening. These findings suggest that, in AD, Nedd4-1 may ubiquitinate AMPARs to promote their internalization and weaken synaptic strength, similar to what occurs in Nedd4-1's established role in homeostatic synaptic scaling. This is the first demonstration of Aβ-mediated control of a ubiquitin ligase to regulate surface AMPAR expression. Copyright © 2016 the authors 0270-6474/16/361590-06$15.00/0.

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

PubMed

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 Society for Neurochemistry.

Shank3 Is Part of a Zinc-Sensitive Signaling System That Regulates Excitatory Synaptic Strength

PubMed Central

Arons, Magali H.; Lee, Kevin; Thynne, Charlotte J.; Kim, Sally A.; Schob, Claudia; Kindler, Stefan

2016-01-01

Shank3 is a multidomain scaffold protein localized to the postsynaptic density of excitatory synapses. Functional studies in vivo and in vitro support the concept that Shank3 is critical for synaptic plasticity and the trans-synaptic coupling between the reliability of presynaptic neurotransmitter release and postsynaptic responsiveness. However, how Shank3 regulates synaptic strength remains unclear. The C terminus of Shank3 contains a sterile alpha motif (SAM) domain that is essential for its postsynaptic localization and also binds zinc, thus raising the possibility that changing zinc levels modulate Shank3 function in dendritic spines. In support of this hypothesis, we find that zinc is a potent regulator of Shank3 activation and dynamics in rat hippocampal neurons. Moreover, we show that zinc modulation of synaptic transmission is Shank3 dependent. Interestingly, an autism spectrum disorder (ASD)-associated variant of Shank3 (Shank3R87C) retains its zinc sensitivity and supports zinc-dependent activation of AMPAR-mediated synaptic transmission. However, elevated zinc was unable to rescue defects in trans-synaptic signaling caused by the R87C mutation, implying that trans-synaptic increases in neurotransmitter release are not necessary for the postsynaptic effects of zinc. Together, these data suggest that Shank3 is a key component of a zinc-sensitive signaling system, regulating synaptic strength that may be impaired in ASD. SIGNIFICANCE STATEMENT Shank3 is a postsynaptic protein associated with neurodevelopmental disorders such as autism and schizophrenia. In this study, we show that Shank3 is a key component of a zinc-sensitive signaling system that regulates excitatory synaptic transmission. Intriguingly, an autism-associated mutation in Shank3 partially impairs this signaling system. Therefore, perturbation of zinc homeostasis may impair, not only synaptic functionality and plasticity, but also may lead to cognitive and behavioral abnormalities seen in patients with psychiatric disorders. PMID:27581454

Longitudinal evidence for anterograde trans-synaptic degeneration after optic neuritis

PubMed Central

Goodkin, Olivia; Altmann, Daniel R.; Jenkins, Thomas M.; Miszkiel, Katherine; Mirigliani, Alessia; Fini, Camilla; Gandini Wheeler-Kingshott, Claudia A. M.; Thompson, Alan J.; Ciccarelli, Olga; Toosy, Ahmed T.

2016-01-01

Abstract In multiple sclerosis, microstructural damage of normal-appearing brain tissue is an important feature of its pathology. Understanding these mechanisms is vital to help develop neuroprotective strategies. The visual pathway is a key model to study mechanisms of damage and recovery in demyelination. Anterograde trans-synaptic degeneration across the lateral geniculate nuclei has been suggested as a mechanism of tissue damage to explain optic radiation abnormalities seen in association with demyelinating disease and optic neuritis, although evidence for this has relied solely on cross-sectional studies. We therefore aimed to assess: (i) longitudinal changes in the diffusion properties of optic radiations after optic neuritis suggesting trans-synaptic degeneration; (ii) the predictive value of early optic nerve magnetic resonance imaging measures for late optic radiations changes; and (iii) the impact on visual outcome of both optic nerve and brain post-optic neuritis changes. Twenty-eight consecutive patients with acute optic neuritis and eight healthy controls were assessed visually (logMAR, colour vision, and Sloan 1.25%, 5%, 25%) and by magnetic resonance imaging, at baseline, 3, 6, and 12 months. Magnetic resonance imaging sequences performed (and metrics obtained) were: (i) optic nerve fluid-attenuated inversion-recovery (optic nerve cross-sectional area); (ii) optic nerve proton density fast spin-echo (optic nerve proton density-lesion length); (iii) optic nerve post-gadolinium T 1 -weighted (Gd-enhanced lesion length); and (iv) brain diffusion-weighted imaging (to derive optic radiation fractional anisotropy, radial diffusivity, and axial diffusivity). Mixed-effects and multivariate regression models were performed, adjusting for age, gender, and optic radiation lesion load. These identified changes over time and associations between early optic nerve measures and 1-year global optic radiation/clinical measures. The fractional anisotropy in patients’ optic radiations decreased ( P = 0.018) and radial diffusivity increased ( P = 0.002) over 1 year following optic neuritis, whereas optic radiation measures were unchanged in controls. Also, smaller cross-sectional areas of affected optic nerves at 3 months post-optic neuritis predicted lower fractional anisotropy and higher radial diffusivity at 1 year ( P = 0.007) in the optic radiations, whereas none of the inflammatory measures of the optic nerve predicted changes in optic radiations. Finally, greater Gd-enhanced lesion length at baseline and greater optic nerve proton density-lesion length at 1 year were associated with worse visual function at 1 year ( P = 0.034 for both). Neither the cross-sectional area of the affected optic nerve after optic neuritis nor the damage in optic radiations was associated with 1-year visual outcome. Our longitudinal study shows that, after optic neuritis, there is progressive damage to the optic radiations, greater in patients with early residual optic nerve atrophy, even after adjusting for optic radiation lesions. These findings provide evidence for trans-synaptic degeneration. PMID:26912640

Dissonance and Healthy Weight Eating Disorder Prevention Programs: A Randomized Efficacy Trial

ERIC Educational Resources Information Center

Stice, Eric; Shaw, Heather; Burton, Emily; Wade, Emily

2006-01-01

In this trial, adolescent girls with body dissatisfaction (N = 481, M age = 17 years) were randomized to an eating disorder prevention program involving dissonance-inducing activities that reduce thin-ideal internalization, a prevention program promoting healthy weight management, an expressive writing control condition, or an assessment-only…

Contributions of Bcl-xL to acute and long term changes in bioenergetics during neuronal plasticity.

PubMed

Jonas, Elizabeth A

2014-08-01

Mitochondria manufacture and release metabolites and manage calcium during neuronal activity and synaptic transmission, but whether long term alterations in mitochondrial function contribute to the neuronal plasticity underlying changes in organism behavior patterns is still poorly understood. Although normal neuronal plasticity may determine learning, in contrast a persistent decline in synaptic strength or neuronal excitability may portend neurite retraction and eventual somatic death. Anti-death proteins such as Bcl-xL not only provide neuroprotection at the neuronal soma during cell death stimuli, but also appear to enhance neurotransmitter release and synaptic growth and development. It is proposed that Bcl-xL performs these functions through its ability to regulate mitochondrial release of bioenergetic metabolites and calcium, and through its ability to rapidly alter mitochondrial positioning and morphology. Bcl-xL also interacts with proteins that directly alter synaptic vesicle recycling. Bcl-xL translocates acutely to sub-cellular membranes during neuronal activity to achieve changes in synaptic efficacy. After stressful stimuli, pro-apoptotic cleaved delta N Bcl-xL (ΔN Bcl-xL) induces mitochondrial ion channel activity leading to synaptic depression and this is regulated by caspase activation. During physiological states of decreased synaptic stimulation, loss of mitochondrial Bcl-xL and low level caspase activation occur prior to the onset of long term decline in synaptic efficacy. The degree to which Bcl-xL changes mitochondrial membrane permeability may control the direction of change in synaptic strength. The small molecule Bcl-xL inhibitor ABT-737 has been useful in defining the role of Bcl-xL in synaptic processes. Bcl-xL is crucial to the normal health of neurons and synapses and its malfunction may contribute to neurodegenerative disease. Copyright © 2013. Published by Elsevier B.V.

Natural Firing Patterns Imply Low Sensitivity of Synaptic Plasticity to Spike Timing Compared with Firing Rate

PubMed Central

Wallisch, Pascal; Ostojic, Srdjan

2016-01-01

Synaptic plasticity is sensitive to the rate and the timing of presynaptic and postsynaptic action potentials. In experimental protocols inducing plasticity, the imposed spike trains are typically regular and the relative timing between every presynaptic and postsynaptic spike is fixed. This is at odds with firing patterns observed in the cortex of intact animals, where cells fire irregularly and the timing between presynaptic and postsynaptic spikes varies. To investigate synaptic changes elicited by in vivo-like firing, we used numerical simulations and mathematical analysis of synaptic plasticity models. We found that the influence of spike timing on plasticity is weaker than expected from regular stimulation protocols. Moreover, when neurons fire irregularly, synaptic changes induced by precise spike timing can be equivalently induced by a modest firing rate variation. Our findings bridge the gap between existing results on synaptic plasticity and plasticity occurring in vivo, and challenge the dominant role of spike timing in plasticity. SIGNIFICANCE STATEMENT Synaptic plasticity, the change in efficacy of connections between neurons, is thought to underlie learning and memory. The dominant paradigm posits that the precise timing of neural action potentials (APs) is central for plasticity induction. This concept is based on experiments using highly regular and stereotyped patterns of APs, in stark contrast with natural neuronal activity. Using synaptic plasticity models, we investigated how irregular, in vivo-like activity shapes synaptic plasticity. We found that synaptic changes induced by precise timing of APs are much weaker than suggested by regular stimulation protocols, and can be equivalently induced by modest variations of the AP rate alone. Our results call into question the dominant role of precise AP timing for plasticity in natural conditions. PMID:27807166

Free radical production and antioxidant status in brain cortex non-synaptic mitochondria and synaptosomes at alcohol hangover onset.

PubMed

Karadayian, Analía G; Malanga, Gabriela; Czerniczyniec, Analía; Lombardi, Paulina; Bustamante, Juanita; Lores-Arnaiz, Silvia

2017-07-01

Alcohol hangover (AH) is the pathophysiological state after a binge-like drinking. We have previously demonstrated that AH induced bioenergetics impairments in a total fresh mitochondrial fraction in brain cortex and cerebellum. The aim of this work was to determine free radical production and antioxidant systems in non-synaptic mitochondria and synaptosomes in control and hangover animals. Superoxide production was not modified in non-synaptic mitochondria while a 17.5% increase was observed in synaptosomes. A similar response was observed for cardiolipin content as no changes were evidenced in non-synaptic mitochondria while a 55% decrease in cardiolipin content was found in synaptosomes. Hydrogen peroxide production was 3-fold increased in non-synaptic mitochondria and 4-fold increased in synaptosomes. In the presence of deprenyl, synaptosomal H 2 O 2 production was 67% decreased in the AH condition. Hydrogen peroxide generation was not affected by deprenyl addition in non-synaptic mitochondria from AH mice. MAO activity was 57% increased in non-synaptic mitochondria and 3-fold increased in synaptosomes. Catalase activity was 40% and 50% decreased in non-synaptic mitochondria and synaptosomes, respectively. Superoxide dismutase was 60% decreased in non-synaptic mitochondria and 80% increased in synaptosomal fractions. On the other hand, GSH (glutathione) content was 43% and 17% decreased in synaptosomes and cytosol. GSH-related enzymes were mostly affected in synaptosomes fractions by AH condition. Acetylcholinesterase activity in synaptosomes was 11% increased due to AH. The present work reveals that AH provokes an imbalance in the cellular redox homeostasis mainly affecting mitochondria present in synaptic terminals. Copyright © 2017 Elsevier Inc. All rights reserved.

Structural versus dynamical origins of mean-field behavior in a self-organized critical model of neuronal avalanches

NASA Astrophysics Data System (ADS)

Moosavi, S. Amin; Montakhab, Afshin

2015-11-01

Critical dynamics of cortical neurons have been intensively studied over the past decade. Neuronal avalanches provide the main experimental as well as theoretical tools to consider criticality in such systems. Experimental studies show that critical neuronal avalanches show mean-field behavior. There are structural as well as recently proposed [Phys. Rev. E 89, 052139 (2014), 10.1103/PhysRevE.89.052139] dynamical mechanisms that can lead to mean-field behavior. In this work we consider a simple model of neuronal dynamics based on threshold self-organized critical models with synaptic noise. We investigate the role of high-average connectivity, random long-range connections, as well as synaptic noise in achieving mean-field behavior. We employ finite-size scaling in order to extract critical exponents with good accuracy. We conclude that relevant structural mechanisms responsible for mean-field behavior cannot be justified in realistic models of the cortex. However, strong dynamical noise, which can have realistic justifications, always leads to mean-field behavior regardless of the underlying structure. Our work provides a different (dynamical) origin than the conventionally accepted (structural) mechanisms for mean-field behavior in neuronal avalanches.

Cholinergic synaptic transmissions were altered after single sevoflurane exposure in Drosophila pupa.

PubMed

Chen, Rongfa; Zhang, Tao; Kuang, Liting; Chen, Zhen; Ran, Dongzhi; Niu, Yang; Xu, Kangqing; Gu, Huaiyu

2015-01-01

. Sevoflurane, one of the most used general anesthetics, is widely used in clinical practice all over the world. Previous studies indicated that sevoflurane could induce neuron apoptosis and neural deficit causing query in the safety of anesthesia using sevoflurane. The present study was designed to investigate the effects of sevoflurane on electrophysiology in Drosophila pupa whose excitatory neurotransmitter is acetylcholine early after sevoflurane exposure using whole brain recording technique. Wide types of Drosophila (canton-s flies) were allocated to control and sevoflurane groups randomly. Sevoflurane groups (1% sevoflurane; 2% sevoflurane; 3% sevoflurane) were exposed to sevoflurane and the exposure lasted 5 hours, respectively. All flies were subjected to electrophysiology experiment using patch clamp 24 hours after exposure. The results showed that, 24 hours after sevoflurane exposure, frequency but not the amplitude of miniature excitatory postsynaptic currents (mEPSCs) was significantly reduced (P < 0.05). Furthermore, we explored the underlying mechanism and found that calcium currents density, which partially regulated the frequency of mEPSCs, was significantly reduced after sevoflurane exposure (P < 0.05). All these suggested that sevoflurane could alter the mEPSCs that are related to synaptic plasticity partially through modulating calcium channel early after sevoflurane exposure.

Biological conservation law as an emerging functionality in dynamical neuronal networks.

PubMed

Podobnik, Boris; Jusup, Marko; Tiganj, Zoran; Wang, Wen-Xu; Buldú, Javier M; Stanley, H Eugene

2017-11-07

Scientists strive to understand how functionalities, such as conservation laws, emerge in complex systems. Living complex systems in particular create high-ordered functionalities by pairing up low-ordered complementary processes, e.g., one process to build and the other to correct. We propose a network mechanism that demonstrates how collective statistical laws can emerge at a macro (i.e., whole-network) level even when they do not exist at a unit (i.e., network-node) level. Drawing inspiration from neuroscience, we model a highly stylized dynamical neuronal network in which neurons fire either randomly or in response to the firing of neighboring neurons. A synapse connecting two neighboring neurons strengthens when both of these neurons are excited and weakens otherwise. We demonstrate that during this interplay between the synaptic and neuronal dynamics, when the network is near a critical point, both recurrent spontaneous and stimulated phase transitions enable the phase-dependent processes to replace each other and spontaneously generate a statistical conservation law-the conservation of synaptic strength. This conservation law is an emerging functionality selected by evolution and is thus a form of biological self-organized criticality in which the key dynamical modes are collective.

Effects of lacosamide and carbamazepine on human motor cortex excitability: a double-blind, placebo-controlled transcranial magnetic stimulation study.

PubMed

Lang, Nicolas; Rothkegel, Holger; Peckolt, Hannes; Deuschl, Günther

2013-11-01

Lacosamide (LCM) and carbamazepine (CBZ) are antiepileptic drugs both acting on neuronal voltage-gated sodium channels. Patch-clamp studies demonstrated significant differences in how LCM and CBZ affect neuronal membrane excitability. Despite valuable information patch-clamp studies provide, they also comprise some constraints. For example, little is known about effects of LCM on intracortical synaptic excitability. In contrast, transcranial magnetic stimulation (TMS) can describe drug-induced changes at the system level of the human cerebral cortex. The present study was designed to explore dose-depended effects of LCM and effects of CBZ on motor cortex excitability with TMS in a randomized, double-blind, placebo-controlled crossover trial in healthy human subjects. Subjects received 600 mg CBZ, 200 mg LCM, 400 mg LCM or placebo preceding TMS measurements. Compared to placebo, TMS motor thresholds were significantly increased after carbamazepine and lacosamide, with a trend for a dose dependent effect of lacosamide. Both, carbamazepine and lacosamide did not affect TMS parameters of intracortical synaptic excitability. TMS measurements suggest that lacosamide and carbamazepine predominantly act on neuronal membrane excitability. Copyright © 2013 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Parecoxib mitigates spatial memory impairment induced by sevoflurane anesthesia in aged rats.

PubMed

Gong, M; Chen, G; Zhang, X M; Xu, L H; Wang, H M; Yan, M

2012-05-01

Inflammation in brain plays a critical role in the pathogenesis of cognitive impairment. Anti-inflammatory therapy may thus constitute a novel approach for associated cognitive dysfunction. The present study investigated the effects of parecoxib in the prevention of cognitive impairments induced by sevoflurane in aged rats. Sixty-six aged rats were divided randomly into three groups: control group (n = 22, sham anesthesia), sevoflurane group (n = 22, received 2% sevoflurane for 5 h) and parecoxib group (n = 22, received intraperitoneal injections of 10 mg/kg parecoxib and then exposed to 2% sevoflurane for 5 h). Spatial learning performance was tested by Morris water maze. The expression of cyclooxygenase-2 protein and ultrastructure of synapse in hippocampus were measured. Sevoflurane anesthesia impaired the spatial learning and memory in aged rats. Compared with sevoflurane group, parecoxib group showed shorter escape latency and more number of crossings over the previous platform area. Furthermore, parecoxib treatment also significantly prevented the synaptic changes induced by sevoflurane. Parecoxib mitigates spatial memory impairment induced by sevoflurane anesthesia in aged rats. The synaptic morphometry change may be one of the mechanisms involved in learning and memory deficit. © 2012 The Authors. Acta Anaesthesiologica Scandinavica © 2012 The Acta Anaesthesiologica Scandinavica Foundation.

Biological conservation law as an emerging functionality in dynamical neuronal networks

PubMed Central

Podobnik, Boris; Tiganj, Zoran; Wang, Wen-Xu; Buldú, Javier M.

2017-01-01

Scientists strive to understand how functionalities, such as conservation laws, emerge in complex systems. Living complex systems in particular create high-ordered functionalities by pairing up low-ordered complementary processes, e.g., one process to build and the other to correct. We propose a network mechanism that demonstrates how collective statistical laws can emerge at a macro (i.e., whole-network) level even when they do not exist at a unit (i.e., network-node) level. Drawing inspiration from neuroscience, we model a highly stylized dynamical neuronal network in which neurons fire either randomly or in response to the firing of neighboring neurons. A synapse connecting two neighboring neurons strengthens when both of these neurons are excited and weakens otherwise. We demonstrate that during this interplay between the synaptic and neuronal dynamics, when the network is near a critical point, both recurrent spontaneous and stimulated phase transitions enable the phase-dependent processes to replace each other and spontaneously generate a statistical conservation law—the conservation of synaptic strength. This conservation law is an emerging functionality selected by evolution and is thus a form of biological self-organized criticality in which the key dynamical modes are collective. PMID:29078286

Cholesterol asymmetry in synaptic plasma membranes.

PubMed

Wood, W Gibson; Igbavboa, Urule; Müller, Walter E; Eckert, Gunter P

2011-03-01

Lipids are essential for the structural and functional integrity of membranes. Membrane lipids are not randomly distributed but are localized in different domains. A common characteristic of these membrane domains is their association with cholesterol. Lipid rafts and caveolae are examples of cholesterol enriched domains, which have attracted keen interest. However, two other important cholesterol domains are the exofacial and cytofacial leaflets of the plasma membrane. The two leaflets that make up the bilayer differ in their fluidity, electrical charge, lipid distribution, and active sites of certain proteins. The synaptic plasma membrane (SPM) cytofacial leaflet contains over 85% of the total SPM cholesterol as compared with the exofacial leaflet. This asymmetric distribution of cholesterol is not fixed or immobile but can be modified by different conditions in vivo: (i) chronic ethanol consumption; (ii) statins; (iii) aging; and (iv) apoE isoform. Several potential candidates have been proposed as mechanisms involved in regulation of SPM cholesterol asymmetry: apoE, low-density lipoprotein receptor, sterol carrier protein-2, fatty acid binding proteins, polyunsaturated fatty acids, P-glycoprotein and caveolin-1. This review examines cholesterol asymmetry in SPM, potential mechanisms of regulation and impact on membrane structure and function. © 2011 The Authors. Journal of Neurochemistry © 2011 International Society for Neurochemistry.

Sugar-sweetened beverages and weight gain in children and adults: a systematic review and meta-analysis123

PubMed Central

Pan, An; Willett, Walter C; Hu, Frank B

2013-01-01

Background: The relation between sugar-sweetened beverages (SSBs) and body weight remains controversial. Objective: We conducted a systematic review and meta-analysis to summarize the evidence in children and adults. Design: We searched PubMed, EMBASE, and Cochrane databases through March 2013 for prospective cohort studies and randomized controlled trials (RCTs) that evaluated the SSB-weight relation. Separate meta-analyses were conducted in children and adults and for cohorts and RCTs by using random- and fixed-effects models. Results: Thirty-two original articles were included in our meta-analyses: 20 in children (15 cohort studies, n = 25,745; 5 trials, n = 2772) and 12 in adults (7 cohort studies, n = 174,252; 5 trials, n = 292). In cohort studies, one daily serving increment of SSBs was associated with a 0.06 (95% CI: 0.02, 0.10) and 0.05 (95% CI: 0.03, 0.07)-unit increase in BMI in children and 0.22 kg (95% CI: 0.09, 0.34 kg) and 0.12 kg (95% CI: 0.10, 0.14 kg) weight gain in adults over 1 y in random- and fixed-effects models, respectively. RCTs in children showed reductions in BMI gain when SSBs were reduced [random and fixed effects: −0.17 (95% CI: −0.39, 0.05) and −0.12 (95% CI: −0.22, −0.2)], whereas RCTs in adults showed increases in body weight when SSBs were added (random and fixed effects: 0.85 kg; 95% CI: 0.50, 1.20 kg). Sensitivity analyses of RCTs in children showed more pronounced benefits in preventing weight gain in SSB substitution trials (compared with school-based educational programs) and among overweight children (compared with normal-weight children). Conclusion: Our systematic review and meta-analysis of prospective cohort studies and RCTs provides evidence that SSB consumption promotes weight gain in children and adults. PMID:23966427

Influence of maternal factors on the successful outcome of kangaroo mother care in low birth-weight infants: A randomized controlled trial.

PubMed

Lumbanraja, S N

2016-01-01

Kangaroo mother care (KMC) is associated with positive neonatal outcomes. Studies demonstrated significant influence of maternal factors on the success of applying KMC. To determine maternal factors that influence on anthropometric parameters in low birth weight babies that received kangaroo mother care. This is a randomized controlled study that involved low birth weight newborns. We randomly assigned newborns into two groups; a group who received KMC and a group who received conventional care. Maternal factors were recorded. We followed weight, length, and head circumferences of newborns for thirty days. A total of 40 newborns were included. Weight parameters were significantly higher in the KMC group than the conventional group. From maternal characteristics, only gestational age was found to influence increased head circumference in KMC group (p = 0.035); however, it did not affect the increase in weight or length. Maternal age, parity, education, mode of delivery, fetal sex, and initial Apgar score did not influence growth parameters in either groups. KMC was associated with increased weight gain in LBW infants. Gestational age influences head growth in infants who received KMC.

Programmable synaptic chip for electronic neural networks

NASA Technical Reports Server (NTRS)

Moopenn, A.; Langenbacher, H.; Thakoor, A. P.; Khanna, S. K.

1988-01-01

A binary synaptic matrix chip has been developed for electronic neural networks. The matrix chip contains a programmable 32X32 array of 'long channel' NMOSFET binary connection elements implemented in a 3-micron bulk CMOS process. Since the neurons are kept off-chip, the synaptic chip serves as a 'cascadable' building block for a multi-chip synaptic network as large as 512X512 in size. As an alternative to the programmable NMOSFET (long channel) connection elements, tailored thin film resistors are deposited, in series with FET switches, on some CMOS test chips, to obtain the weak synaptic connections. Although deposition and patterning of the resistors require additional processing steps, they promise substantial savings in silicon area. The performance of synaptic chip in a 32-neuron breadboard system in an associative memory test application is discussed.

Phosphodiesterase Inhibition to Target the Synaptic Dysfunction in Alzheimer's Disease

NASA Astrophysics Data System (ADS)

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.

Enduring medial perforant path short-term synaptic depression at high pressure.

PubMed

Talpalar, Adolfo E; Giugliano, Michele; Grossman, Yoram

2010-01-01

The high pressure neurological syndrome develops during deep-diving (>1.1 MPa) involving impairment of cognitive functions, alteration of synaptic transmission and increased excitability in cortico-hippocampal areas. The medial perforant path (MPP), connecting entorhinal cortex with the hippocampal formation, displays synaptic frequency-dependent-depression (FDD) under normal conditions. Synaptic FDD is essential for specific functions of various neuronal networks. We used rat cortico-hippocampal slices and computer simulations for studying the effects of pressure and its interaction with extracellular Ca(2+) ([Ca(2+)](o)) on FDD at the MPP synapses. At atmospheric pressure, high [Ca(2+)](o) (4-6 mM) saturated single MPP field EPSP (fEPSP) and increased FDD in response to short trains at 50 Hz. High pressure (HP; 10.1 MPa) depressed single fEPSPs by 50%. Increasing [Ca(2+)](o) to 4 mM at HP saturated synaptic response at a subnormal level (only 20% recovery of single fEPSPs), but generated a FDD similar to atmospheric pressure. Mathematical model analysis of the fractions of synaptic resources used by each fEPSP during trains (normalized to their maximum) and the total fraction utilized within a train indicate that HP depresses synaptic activity also by reducing synaptic resources. This data suggest that MPP synapses may be modulated, in addition to depression of single events, by reduction of synaptic resources and then may have the ability to conserve their dynamic properties under different conditions.

Enduring Medial Perforant Path Short-Term Synaptic Depression at High Pressure

PubMed Central

Talpalar, Adolfo E.; Giugliano, Michele; Grossman, Yoram

2010-01-01

The high pressure neurological syndrome develops during deep-diving (>1.1 MPa) involving impairment of cognitive functions, alteration of synaptic transmission and increased excitability in cortico-hippocampal areas. The medial perforant path (MPP), connecting entorhinal cortex with the hippocampal formation, displays synaptic frequency-dependent-depression (FDD) under normal conditions. Synaptic FDD is essential for specific functions of various neuronal networks. We used rat cortico-hippocampal slices and computer simulations for studying the effects of pressure and its interaction with extracellular Ca2+ ([Ca2+]o) on FDD at the MPP synapses. At atmospheric pressure, high [Ca2+]o (4–6 mM) saturated single MPP field EPSP (fEPSP) and increased FDD in response to short trains at 50 Hz. High pressure (HP; 10.1 MPa) depressed single fEPSPs by 50%. Increasing [Ca2+]o to 4 mM at HP saturated synaptic response at a subnormal level (only 20% recovery of single fEPSPs), but generated a FDD similar to atmospheric pressure. Mathematical model analysis of the fractions of synaptic resources used by each fEPSP during trains (normalized to their maximum) and the total fraction utilized within a train indicate that HP depresses synaptic activity also by reducing synaptic resources. This data suggest that MPP synapses may be modulated, in addition to depression of single events, by reduction of synaptic resources and then may have the ability to conserve their dynamic properties under different conditions. PMID:21048901

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

PubMed Central

Wu, Chunlai; Daniels, Richard W; DiAntonio, Aaron

2007-01-01

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. PMID:17697379

Weight management program for treatment-emergent weight gain in olanzapine-treated patients with schizophrenia or schizoaffective disorder: A 12-week randomized controlled clinical trial.

PubMed

Kwon, Jun Soo; Choi, Jung-Seok; Bahk, Won-Myoung; Yoon Kim, Chang; Hyung Kim, Chan; Chul Shin, Young; Park, Byung-Joo; Geun Oh, Chang

2006-04-01

The main objective was to assess the efficacy of a weight management program designed for outpatients taking olanzapine for schizophrenia or schizoaffective disorder and to compare these patients with a randomized control group. The effects of the weight management program were also assessed with regard to safety and quality of life. Forty-eight patients were enrolled in a 12-week, randomized, multicenter weight management study. Thirty-three patients were randomly allocated to an intervention group in which they received olanzapine within a weight management program. Fifteen patients were allocated to a control group in which they were given olanzapine treatment as usual outpatients. Weight, body mass index (BMI), and measurements of safety and quality of life were evaluated. The study was conducted from January 7, 2003, to September 16, 2003. Thirty-six patients (75%) completed this study. We found significant differences in weight (-3.94 +/- 3.63 kg vs. -1.48 +/- 1.88 kg, p = .006) and BMI (-1.50 +/- 1.34 vs. -0.59 +/- 0.73, p = .007) change from baseline to endpoint between the intervention and control groups, respectively. Significant differences in weight reduction were initially observed at week 8 (p = .040). No significant differences were found with regard to the safety outcomes. When the ratio of low-density lipoproteins to high-density lipoproteins was calculated, change from baseline was greater in the intervention group than the control group (-0.19 vs. -0.04), but the difference was not statistically significant (p = .556). After the completion of the weight management program, there was a trend toward statistical difference in the physical health score changes between the weight management and control groups (1.12 in the intervention group vs. -0.93 in the control group, p = .067). The weight management program was effective in terms of weight reduction in patients with schizophrenia or schizoaffective disorder taking olanzapine and was also found to be safe in terms of psychiatric symptoms, vital signs, and laboratory data. In addition, such a weight management program might improve quality of life in patients with schizophrenia or schizoaffective disorder with respect to their physical well-being.

Evaluation of Metabolic and Synaptic Dysfunction Hypotheses of Alzheimer’s Disease (AD): A Meta-Analysis of CSF Markers

PubMed Central

Manyevitch, Roni; Protas, Matthew; Scarpiello, Sean; Deliso, Marisa; Bass, Brittany; Nanajian, Anthony; Chang, Matthew; Thompson, Stefani M.; Khoury, Neil; Gonnella, Rachel; Trotz, Margit; Moore, D. Blaine; Harms, Emily; Perry, George; Clunes, Lucy; Ortiz, Angélica; Friedrich, Jan O.; Murray, Ian V.J.

2018-01-01

Background: Alzheimer’s disease (AD) is currently incurable and a majority of investigational drugs have failed clinical trials. One explanation for this failure may be the invalidity of hypotheses focus-ing on amyloid to explain AD pathogenesis. Recently, hypotheses which are centered on synaptic and met-abolic dysfunction are increasingly implicated in AD. Objective: Evaluate AD hypotheses by comparing neurotransmitter and metabolite marker concentrations in normal versus AD CSF. Methods: Meta-analysis allows for statistical comparison of pooled, existing cerebrospinal fluid (CSF) marker data extracted from multiple publications, to obtain a more reliable estimate of concentrations. This method also provides a unique opportunity to rapidly validate AD hypotheses using the resulting CSF con-centration data. Hubmed, Pubmed and Google Scholar were comprehensively searched for published Eng-lish articles, without date restrictions, for the keywords “AD”, “CSF”, and “human” plus markers selected for synaptic and metabolic pathways. Synaptic markers were acetylcholine, gamma-aminobutyric acid (GABA), glutamine, and glycine. Metabolic markers were glutathione, glucose, lactate, pyruvate, and 8 other amino acids. Only studies that measured markers in AD and controls (Ctl), provided means, standard er-rors/deviation, and subject numbers were included. Data were extracted by six authors and reviewed by two others for accuracy. Data were pooled using ratio of means (RoM of AD/Ctl) and random effects meta-analysis using Cochrane Collaboration’s Review Manager software. Results: Of the 435 identified publications, after exclusion and removal of duplicates, 35 articles were in-cluded comprising a total of 605 AD patients and 585 controls. The following markers of synaptic and met-abolic pathways were significantly changed in AD/controls: acetylcholine (RoM 0.36, 95% CI 0.24-0.53, p<0.00001), GABA (0.74, 0.58-0.94, p<0.01), pyruvate (0.48, 0.24-0.94, p=0.03), glutathione (1.11, 1.01-1.21, p=0.03), alanine (1.10, 0.98-1.23, p=0.09), and lower levels of significance for lactate (1.2, 1.00-1.47, p=0.05). Of note, CSF glucose and glutamate levels in AD were not significantly different than that of the controls. Conclusion: This study provides proof of concept for the use of meta-analysis validation of AD hypothe-ses, specifically via robust evidence for the cholinergic hypothesis of AD. Our data disagree with the other synaptic hypotheses of glutamate excitotoxicity and GABAergic resistance to neurodegeneration, given ob-served unchanged glutamate levels and decreased GABA levels. With regards to metabolic hypotheses, the data supported upregulation of anaerobic glycolysis, pentose phosphate pathway (glutathione), and anaple-rosis of the tricarboxylic acid cycle using glutamate. Future applications of meta-analysis indicate the pos-sibility of further in silico evaluation and generation of novel hypotheses in the AD field. PMID:28933272

Evaluation of Metabolic and Synaptic Dysfunction Hypotheses of Alzheimer's Disease (AD): A Meta-Analysis of CSF Markers.

PubMed

Manyevitch, Roni; Protas, Matthew; Scarpiello, Sean; Deliso, Marisa; Bass, Brittany; Nanajian, Anthony; Chang, Matthew; Thompson, Stefani M; Khoury, Neil; Gonnella, Rachel; Trotz, Margit; Moore, D Blaine; Harms, Emily; Perry, George; Clunes, Lucy; Ortiz, Angelica; Friedrich, Jan O; Murray, Ian V J

2018-01-01

Alzheimer's disease (AD) is currently incurable and a majority of investigational drugs have failed clinical trials. One explanation for this failure may be the invalidity of hypotheses focusing on amyloid to explain AD pathogenesis. Recently, hypotheses which are centered on synaptic and metabolic dysfunction are increasingly implicated in AD. Evaluate AD hypotheses by comparing neurotransmitter and metabolite marker concentrations in normal versus AD CSF. Meta-analysis allows for statistical comparison of pooled, existing cerebrospinal fluid (CSF) marker data extracted from multiple publications, to obtain a more reliable estimate of concentrations. This method also provides a unique opportunity to rapidly validate AD hypotheses using the resulting CSF concentration data. Hubmed, Pubmed and Google Scholar were comprehensively searched for published English articles, without date restrictions, for the keywords "AD", "CSF", and "human" plus markers selected for synaptic and metabolic pathways. Synaptic markers were acetylcholine, gamma-aminobutyric acid (GABA), glutamine, and glycine. Metabolic markers were glutathione, glucose, lactate, pyruvate, and 8 other amino acids. Only studies that measured markers in AD and controls (Ctl), provided means, standard errors/deviation, and subject numbers were included. Data were extracted by six authors and reviewed by two others for accuracy. Data were pooled using ratio of means (RoM of AD/Ctl) and random effects meta-analysis using Cochrane Collaboration's Review Manager software. Of the 435 identified publications, after exclusion and removal of duplicates, 35 articles were included comprising a total of 605 AD patients and 585 controls. The following markers of synaptic and metabolic pathways were significantly changed in AD/controls: acetylcholine (RoM 0.36, 95% CI 0.24-0.53, p<0.00001), GABA (0.74, 0.58-0.94, p<0.01), pyruvate (0.48, 0.24-0.94, p=0.03), glutathione (1.11, 1.01- 1.21, p=0.03), alanine (1.10, 0.98-1.23, p=0.09), and lower levels of significance for lactate (1.2, 1.00-1.47, p=0.05). Of note, CSF glucose and glutamate levels in AD were not significantly different than that of the controls. This study provides proof of concept for the use of meta-analysis validation of AD hypotheses, specifically via robust evidence for the cholinergic hypothesis of AD. Our data disagree with the other synaptic hypotheses of glutamate excitotoxicity and GABAergic resistance to neurodegeneration, given observed unchanged glutamate levels and decreased GABA levels. With regards to metabolic hypotheses, the data supported upregulation of anaerobic glycolysis, pentose phosphate pathway (glutathione), and anaplerosis of the tricarboxylic acid cycle using glutamate. Future applications of meta-analysis indicate the possibility of further in silico evaluation and generation of novel hypotheses in the AD field. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

The influence of synaptic size on AMPA receptor activation: a Monte Carlo model.

PubMed

Montes, Jesus; Peña, Jose M; DeFelipe, Javier; Herreras, Oscar; Merchan-Perez, Angel

2015-01-01

Physiological and electron microscope studies have shown that synapses are functionally and morphologically heterogeneous and that variations in size of synaptic junctions are related to characteristics such as release probability and density of postsynaptic AMPA receptors. The present article focuses on how these morphological variations impact synaptic transmission. We based our study on Monte Carlo computational simulations of simplified model synapses whose morphological features have been extracted from hundreds of actual synaptic junctions reconstructed by three-dimensional electron microscopy. We have examined the effects that parameters such as synaptic size or density of AMPA receptors have on the number of receptors that open after release of a single synaptic vesicle. Our results indicate that the maximum number of receptors that will open after the release of a single synaptic vesicle may show a ten-fold variation in the whole population of synapses. When individual synapses are considered, there is also a stochastical variability that is maximal in small synapses with low numbers of receptors. The number of postsynaptic receptors and the size of the synaptic junction are the most influential parameters, while the packing density of receptors or the concentration of extrasynaptic transporters have little or no influence on the opening of AMPA receptors.

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

PubMed

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.

Estimating synaptic parameters from mean, variance, and covariance in trains of synaptic responses.

PubMed

Scheuss, V; Neher, E

2001-10-01

Fluctuation analysis of synaptic transmission using the variance-mean approach has been restricted in the past to steady-state responses. Here we extend this method to short repetitive trains of synaptic responses, during which the response amplitudes are not stationary. We consider intervals between trains, long enough so that the system is in the same average state at the beginning of each train. This allows analysis of ensemble means and variances for each response in a train separately. Thus, modifications in synaptic efficacy during short-term plasticity can be attributed to changes in synaptic parameters. In addition, we provide practical guidelines for the analysis of the covariance between successive responses in trains. Explicit algorithms to estimate synaptic parameters are derived and tested by Monte Carlo simulations on the basis of a binomial model of synaptic transmission, allowing for quantal variability, heterogeneity in the release probability, and postsynaptic receptor saturation and desensitization. We find that the combined analysis of variance and covariance is advantageous in yielding an estimate for the number of release sites, which is independent of heterogeneity in the release probability under certain conditions. Furthermore, it allows one to calculate the apparent quantal size for each response in a sequence of stimuli.

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

PubMed

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.

Differential Roles of Postsynaptic Density-93 Isoforms in Regulating Synaptic Transmission

PubMed Central

Krüger, Juliane M.; Favaro, Plinio D.; Liu, Mingna; Kitlińska, Agata; Huang, Xiaojie; Raabe, Monika; Akad, Derya S.; Liu, Yanling; Urlaub, Henning; Dong, Yan; Xu, Weifeng

2013-01-01

In the postsynaptic density of glutamatergic synapses, the discs large (DLG)-membrane-associated guanylate kinase (MAGUK) family of scaffolding proteins coordinates a multiplicity of signaling pathways to maintain and regulate synaptic transmission. Postsynaptic density-93 (PSD-93) is the most variable paralog in this family; it exists in six different N-terminal isoforms. Probably because of the structural and functional variability of these isoforms, the synaptic role of PSD-93 remains controversial. To accurately characterize the synaptic role of PSD-93, we quantified the expression of all six isoforms in the mouse hippocampus and examined them individually in hippocampal synapses. Using molecular manipulations, including overexpression, gene knockdown, PSD-93 knock-out mice combined with biochemical assays, and slice electrophysiology both in rat and mice, we demonstrate that PSD-93 is required at different developmental synaptic states to maintain the strength of excitatory synaptic transmission. This strength is differentially regulated by the six isoforms of PSD-93, including regulations of α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid (AMPA) receptor-active and inactive synapses, and activity-dependent modulations. Collectively, these results demonstrate that alternative combinations of N-terminal PSD-93 isoforms and DLG-MAGUK paralogs can fine-tune signaling scaffolds to adjust synaptic needs to regulate synaptic transmission. PMID:24068818

PSD-95 regulates synaptic kainate receptors at mouse hippocampal mossy fiber-CA3 synapses.

PubMed

Suzuki, Etsuko; Kamiya, Haruyuki

2016-06-01

Kainate-type glutamate receptors (KARs) are the third class of ionotropic glutamate receptors whose activation leads to the unique roles in regulating synaptic transmission and circuit functions. In contrast to AMPA receptors (AMPARs), little is known about the mechanism of synaptic localization of KARs. PSD-95, a major scaffold protein of the postsynaptic density, is a candidate molecule that regulates the synaptic KARs. Although PSD-95 was shown to bind directly to KARs subunits, it has not been tested whether PSD-95 regulates synaptic KARs in intact synapses. Using PSD-95 knockout mice, we directly investigated the role of PSD-95 in the KARs-mediated components of synaptic transmission at hippocampal mossy fiber-CA3 synapse, one of the synapses with the highest density of KARs. Mossy fiber EPSCs consist of AMPA receptor (AMPAR)-mediated fast component and KAR-mediated slower component, and the ratio was significantly reduced in PSD-95 knockout mice. The size of KARs-mediated field EPSP reduced in comparison with the size of the fiber volley. Analysis of KARs-mediated miniature EPSCs also suggested reduced synaptic KARs. All the evidence supports critical roles of PSD-95 in regulating synaptic KARs. Copyright © 2015 Elsevier Ireland Ltd and Japan Neuroscience Society. All rights reserved.

Pannexin 1 regulates bidirectional hippocampal synaptic plasticity in adult mice.

PubMed

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

2014-01-01

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

Pannexin 1 regulates bidirectional hippocampal synaptic plasticity in adult mice

PubMed Central

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

2014-01-01

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

Blocking Effects of Human Tau on Squid Giant Synapse Transmission and Its Prevention by T-817 MA

PubMed Central

Moreno, Herman; Choi, Soonwook; Yu, Eunah; Brusco, Janaina; Avila, Jesus; Moreira, Jorge E.; Sugimori, Mutsuyuki; Llinás, Rodolfo R.

2011-01-01

Filamentous tau inclusions are hallmarks of Alzheimer's disease and related neurodegenerative tauopathies, but the molecular mechanisms involved in tau-mediated changes in neuronal function and their possible effects on synaptic transmission are unknown. We have evaluated the effects of human tau protein injected directly into the presynaptic terminal axon of the squid giant synapse, which affords functional, structural, and biochemical analysis of its action on the synaptic release process. Indeed, we have found that at physiological concentration recombinant human tau (h-tau42) becomes phosphorylated, produces a rapid synaptic transmission block, and induces the formation of clusters of aggregated synaptic vesicles in the vicinity of the active zone. Presynaptic voltage clamp recordings demonstrate that h-tau42 does not modify the presynaptic calcium current amplitude or kinetics. Analysis of synaptic noise at the post-synaptic axon following presynaptic h-tau42 microinjection revealed an initial phase of increase spontaneous transmitter release followed by a marked reduction in noise. Finally, systemic administration of T-817MA, a proposed neuro-protective agent, rescued tau-induced synaptic abnormalities. Our results show novel mechanisms of h-tau42 mediated synaptic transmission failure and identify a potential therapeutic agent to treat tau-related neurotoxicity. PMID:21629767

The Influence of Synaptic Size on AMPA Receptor Activation: A Monte Carlo Model

PubMed Central

Montes, Jesus; Peña, Jose M.; DeFelipe, Javier; Herreras, Oscar; Merchan-Perez, Angel

2015-01-01

Physiological and electron microscope studies have shown that synapses are functionally and morphologically heterogeneous and that variations in size of synaptic junctions are related to characteristics such as release probability and density of postsynaptic AMPA receptors. The present article focuses on how these morphological variations impact synaptic transmission. We based our study on Monte Carlo computational simulations of simplified model synapses whose morphological features have been extracted from hundreds of actual synaptic junctions reconstructed by three-dimensional electron microscopy. We have examined the effects that parameters such as synaptic size or density of AMPA receptors have on the number of receptors that open after release of a single synaptic vesicle. Our results indicate that the maximum number of receptors that will open after the release of a single synaptic vesicle may show a ten-fold variation in the whole population of synapses. When individual synapses are considered, there is also a stochastical variability that is maximal in small synapses with low numbers of receptors. The number of postsynaptic receptors and the size of the synaptic junction are the most influential parameters, while the packing density of receptors or the concentration of extrasynaptic transporters have little or no influence on the opening of AMPA receptors. PMID:26107874

Synaptic Vesicle-Recycling Machinery Components as Potential Therapeutic Targets

PubMed Central

Li, Ying C.

2017-01-01

Presynaptic nerve terminals are highly specialized vesicle-trafficking machines. Neurotransmitter release from these terminals is sustained by constant local recycling of synaptic vesicles independent from the neuronal cell body. This independence places significant constraints on maintenance of synaptic protein complexes and scaffolds. Key events during the synaptic vesicle cycle—such as exocytosis and endocytosis—require formation and disassembly of protein complexes. This extremely dynamic environment poses unique challenges for proteostasis at synaptic terminals. Therefore, it is not surprising that subtle alterations in synaptic vesicle cycle-associated proteins directly or indirectly contribute to pathophysiology seen in several neurologic and psychiatric diseases. In contrast to the increasing number of examples in which presynaptic dysfunction causes neurologic symptoms or cognitive deficits associated with multiple brain disorders, synaptic vesicle-recycling machinery remains an underexplored drug target. In addition, irrespective of the involvement of presynaptic function in the disease process, presynaptic machinery may also prove to be a viable therapeutic target because subtle alterations in the neurotransmitter release may counter disease mechanisms, correct, or compensate for synaptic communication deficits without the need to interfere with postsynaptic receptor signaling. In this article, we will overview critical properties of presynaptic release machinery to help elucidate novel presynaptic avenues for the development of therapeutic strategies against neurologic and neuropsychiatric disorders. PMID:28265000

Weight loss increases follicle stimulating hormone in overweight postmenopausal women [corrected].

PubMed

Kim, Catherine; Randolph, John F; Golden, Sherita H; Labrie, Fernand; Kong, Shengchun; Nan, Bin; Barrett-Connor, Elizabeth

2015-01-01

To examine the impact of a weight loss intervention upon follicle stimulating hormone (FSH) levels in postmenopause. Participants were postmenopausal, overweight, glucose-intolerant women not using exogenous estrogen (n = 382) in the Diabetes Prevention Program. Women were randomized to intensive lifestyle change (ILS) with the goals of weight reduction of at least 7% of initial weight and 150 min per week of moderate-intensity exercise, metformin 850 mg twice a day, or placebo administered twice a day. Randomization to ILS led to small increases in FSH between baseline and 1-year follow-up vs. placebo (2.3 IU/l vs. -0.81 IU/l, P < 0.01). Increases in FSH were correlated with decreases in weight (r = -0.165, P < 0.01) and estradiol (E2) (r = -0.464, P < 0.0001) after adjustment for age, race/ethnicity, and randomization arm. Changes in FSH were still significantly associated with changes in weight even after adjustment for E2 levels. Metformin users had reductions in weight but non-significant changes in FSH and E2 levels vs. placebo. Weight loss leads to small increases in FSH among overweight, postmenopausal women, potentially through pathways mediated by endogenous estrogen as well as other pathways. © 2014 The Obesity Society.

Motor skills training promotes motor functional recovery and induces synaptogenesis in the motor cortex and striatum after intracerebral hemorrhage in rats.

PubMed

Tamakoshi, Keigo; Ishida, Akimasa; Takamatsu, Yasuyuki; Hamakawa, Michiru; Nakashima, Hiroki; Shimada, Haruka; Ishida, Kazuto

2014-03-01

We investigated the effects of motor skills training on several types of motor function and synaptic plasticity following intracerebral hemorrhage (ICH) in rats. Male Wistar rats were injected with collagenase into the left striatum to induce ICH, and they were randomly assigned to the ICH or sham groups. Each group was divided into the motor skills training (acrobatic training) and control (no exercise) groups. The acrobatic group performed acrobatic training from 4 to 28 days after surgery. Motor functions were assessed by motor deficit score, the horizontal ladder test and the wide or narrow beam walking test at several time points after ICH. The number of ΔFosB-positive cells was counted using immunohistochemistry to examine neuronal activation, and the PSD95 protein levels were analyzed by Western blotting to examine synaptic plasticity in the bilateral sensorimotor cortices and striata at 14 and 29 days after ICH. Motor skills training following ICH significantly improved gross motor function in the early phase after ICH and skilled motor coordinated function in the late phase. The number of ΔFosB-positive cells in the contralateral sensorimotor cortex in the acrobatic group significantly increased compared to the control group. PSD95 protein expression in the motor cortex significantly increased in the late phase, and in the striatum, the protein level significantly increased in the early phase by motor skills training after ICH compared to no training after ICH. We demonstrated that motor skills training improved motor function after ICH in rats and enhanced the neural activity and synaptic plasticity in the striatum and sensorimotor cortex. Copyright © 2013 Elsevier B.V. All rights reserved.

Chronic intermittent hypoxia affects endogenous serotonergic inputs and expression of synaptic proteins in rat hypoglossal nucleus

PubMed Central

Wu, Xu; Lu, Huan; Hu, Lijuan; Gong, Wankun; Wang, Juan; Fu, Cuiping; Liu, Zilong; Li, Shanqun

2017-01-01

Evidence has shown that hypoxic episodes elicit hypoglossal neuroplasticity which depends on elevated serotonin (5-HT), in contrast to the rationale of obstructive sleep apnea (OSA) that deficient serotonergic input to HMs fails to keep airway patency. Therefore, understanding of the 5-HT dynamic changes at hypoglossal nucleus (HN) during chronic intermittent hypoxia (CIH) will be essential to central pathogenic mechanism and pharmacological therapy of OSA. Moreover, the effect of CIH on BDNF-TrkB signaling proteins was quantified in an attempt to elucidate cellular cascades/synaptic mechanisms following 5-HT alteration. Male rats were randomly exposed to normal air (control), intermittent hypoxia of 3 weeks (IH3) and 5 weeks (IH5) groups. Through electrical stimulation of dorsal raphe nuclei (DRN), we conducted amperometric technique with carbon fiber electrode in vivo to measure the real time release of 5-HT at XII nucleus. 5-HT2A receptors immunostaining measured by intensity and c-Fos quantified visually were both determined by immunohistochemistry. CIH significantly reduced endogenous serotonergic inputs from DRN to XII nucleus, shown as decreased peak value of 5-HT signals both in IH3 and IH5groups, whereas time to peak and half-life period of 5-HT were unaffected. Neither 5-HT2A receptors nor c-Fos expression in HN were significantly altered by CIH. Except for marked increase in phosphorylation of ERK in IH5 rats, BDNF-TrkB signaling and synaptophys consistently demonstrated downregulated levels. These results suggest that the deficiency of 5-HT and BDNF-dependent synaptic proteins in our CIH protocol contribute to the decompensated mechanism of OSA. PMID:28337282

Chronic intermittent hypoxia affects endogenous serotonergic inputs and expression of synaptic proteins in rat hypoglossal nucleus.

PubMed

Wu, Xu; Lu, Huan; Hu, Lijuan; Gong, Wankun; Wang, Juan; Fu, Cuiping; Liu, Zilong; Li, Shanqun

2017-01-01

Evidence has shown that hypoxic episodes elicit hypoglossal neuroplasticity which depends on elevated serotonin (5-HT), in contrast to the rationale of obstructive sleep apnea (OSA) that deficient serotonergic input to HMs fails to keep airway patency. Therefore, understanding of the 5-HT dynamic changes at hypoglossal nucleus (HN) during chronic intermittent hypoxia (CIH) will be essential to central pathogenic mechanism and pharmacological therapy of OSA. Moreover, the effect of CIH on BDNF-TrkB signaling proteins was quantified in an attempt to elucidate cellular cascades/synaptic mechanisms following 5-HT alteration. Male rats were randomly exposed to normal air (control), intermittent hypoxia of 3 weeks (IH3) and 5 weeks (IH5) groups. Through electrical stimulation of dorsal raphe nuclei (DRN), we conducted amperometric technique with carbon fiber electrode in vivo to measure the real time release of 5-HT at XII nucleus. 5-HT 2A receptors immunostaining measured by intensity and c-Fos quantified visually were both determined by immunohistochemistry. CIH significantly reduced endogenous serotonergic inputs from DRN to XII nucleus, shown as decreased peak value of 5-HT signals both in IH3 and IH5groups, whereas time to peak and half-life period of 5-HT were unaffected. Neither 5-HT 2A receptors nor c-Fos expression in HN were significantly altered by CIH. Except for marked increase in phosphorylation of ERK in IH5 rats, BDNF-TrkB signaling and synaptophys consistently demonstrated downregulated levels. These results suggest that the deficiency of 5-HT and BDNF-dependent synaptic proteins in our CIH protocol contribute to the decompensated mechanism of OSA.

Oleanolic Acid Ameliorates Aβ25-35 Injection-induced Spatial Learning and Memory Deficit in Alzheimer's Disease Model Rats.

PubMed

Wang, Kai; Sun, Weiming; Zhang, Linlin; Guo, Wei; Xu, Jiachun; Liu, Shuang; Zhou, Zhen; Zhang, Yulian

2018-05-24

Abnormal amyloid β (Aβ) accumulation and deposition in hippocampus is an essential process in Alzheimer's disease (AD). To investigate whether Oleanolic acid (OA) could improve learning and memory deficit and its possible mechanism. Forty-five SD rats were randomly divided into sham operation group, model group, and OA group. AD models by injection of Aβ25-35 were built. Morris water maze (MWM) was applied to investigate learning and memory, transmission electron microscope (TEM) to observe the ultrastructure of synapse, western blot to the key targets of synapse, electrophysiology for long-term potentiation (LTP), and Ca2+ concentration in synapse was also measured. The latency time in model group was significantly longer than that in sham operation group (P=0.0001<0.05); while it was significantly shorter in the OA group than that in model group (P=0.0001<0.05); compared with model group, the times of cross-platform in OA group significantly increased (P = 0.0001 <0.05). TEM results showed OA couldalleviate neuron damage and synapses changes induced by Aβ25-35. The expression of CaMKII, PKC, NMDAR2B, BDNF, TrkB, and CREB protein were significantly improved by OA; the concentration of Ca2+ were significantly lower and the slope and amplitude of f-EPSP increased in OA group. OA could ameliorate Aβ-induced spatial learning and memory loss of AD rats, and the mechanism might be involved with maintaining synaptic integrity to restore synaptic plasticity and increasing the NMDAR2B protein, CaMKII and PKC protein in postsynaptic density (PSD), reducing synaptic Ca2+ concentration, enhancing LTP by up-regulating BDNF, TrkB, CREB proteins. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Synaptophysin regulates the kinetics of synaptic vesicle endocytosis in central neurons

PubMed Central

Kwon, Sung E.; Chapman, Edwin R.

2011-01-01

Summary Despite being the most abundant synaptic vesicle membrane protein, the function of synaptophysin remains enigmatic. For example, synaptic transmission was reported to be completely normal in synaptophysin knockout mice; however, direct experiments to monitor the synaptic vesicle cycle have not been carried out. Here, using optical imaging and electrophysiological experiments, we demonstrate that synaptophysin is required for kinetically efficient endocytosis of synaptic vesicles in cultured hippocampal neurons. Truncation analysis revealed that distinct structural elements of synaptophysin differentially regulate vesicle retrieval during and after stimulation. Thus, synaptophysin regulates at least two phases of endocytosis to ensure vesicle availability during and after sustained neuronal activity. PMID:21658579

A mathematical analysis of the effects of Hebbian learning rules on the dynamics and structure of discrete-time random recurrent neural networks.

PubMed

Siri, Benoît; Berry, Hugues; Cessac, Bruno; Delord, Bruno; Quoy, Mathias

2008-12-01

We present a mathematical analysis of the effects of Hebbian learning in random recurrent neural networks, with a generic Hebbian learning rule, including passive forgetting and different timescales, for neuronal activity and learning dynamics. Previous numerical work has reported that Hebbian learning drives the system from chaos to a steady state through a sequence of bifurcations. Here, we interpret these results mathematically and show that these effects, involving a complex coupling between neuronal dynamics and synaptic graph structure, can be analyzed using Jacobian matrices, which introduce both a structural and a dynamical point of view on neural network evolution. Furthermore, we show that sensitivity to a learned pattern is maximal when the largest Lyapunov exponent is close to 0. We discuss how neural networks may take advantage of this regime of high functional interest.

Neural Mechanism for Stochastic Behavior During a Competitive Game

PubMed Central

Soltani, Alireza; Lee, Daeyeol; Wang, Xiao-Jing

2006-01-01

Previous studies have shown that non-human primates can generate highly stochastic choice behavior, especially when this is required during a competitive interaction with another agent. To understand the neural mechanism of such dynamic choice behavior, we propose a biologically plausible model of decision making endowed with synaptic plasticity that follows a reward-dependent stochastic Hebbian learning rule. This model constitutes a biophysical implementation of reinforcement learning, and it reproduces salient features of behavioral data from an experiment with monkeys playing a matching pennies game. Due to interaction with an opponent and learning dynamics, the model generates quasi-random behavior robustly in spite of intrinsic biases. Furthermore, non-random choice behavior can also emerge when the model plays against a non-interactive opponent, as observed in the monkey experiment. Finally, when combined with a meta-learning algorithm, our model accounts for the slow drift in the animal’s strategy based on a process of reward maximization. PMID:17015181

On a phase diagram for random neural networks with embedded spike timing dependent plasticity.

PubMed

Turova, Tatyana S; Villa, Alessandro E P

2007-01-01

This paper presents an original mathematical framework based on graph theory which is a first attempt to investigate the dynamics of a model of neural networks with embedded spike timing dependent plasticity. The neurons correspond to integrate-and-fire units located at the vertices of a finite subset of 2D lattice. There are two types of vertices, corresponding to the inhibitory and the excitatory neurons. The edges are directed and labelled by the discrete values of the synaptic strength. We assume that there is an initial firing pattern corresponding to a subset of units that generate a spike. The number of activated externally vertices is a small fraction of the entire network. The model presented here describes how such pattern propagates throughout the network as a random walk on graph. Several results are compared with computational simulations and new data are presented for identifying critical parameters of the model.

Heterotopic synaptic bodies in the auditory hair cells of adult lizards.

PubMed

Miller, M R; Beck, J

1987-07-01

The auditory hair cells of adults of eight species of lizards (three gekkonids: Coleonyx variegatus, Gekko gecko, and Cosymbotus platyurus; two teiids: Ameiva ameiva and Cnemidophorus tigris; one anguid: Celestus costatus; one lacertid: Podarcis (Lacerta) sicula; and one iguanid: Crotaphytus wislizeni) were studied by transmission electron microscopy. Heterotopic synaptic bodies were found in some of the auditory hair cells of all of the above species, occurring frequently in the gekkonids but infrequently in other species. The groups of heterotopic synaptic bodies occurred mainly in the infranuclear cytoplasm between the hair cell nucleus and the hair cell plasma membrane. The groups of synaptic bodies that were close to the hair cell nucleus were usually associated with specialized arrays of rough and smooth endoplasmic reticulum. The numbers of heterotopic synaptic bodies were greatest in the gekkonid species and were especially large in Coleonyx variegatus, where an average of 36.8 synaptic bodies occur in one group. The functional significance of the presence of heterotopic synaptic bodies in the auditory hair cells of adults animals is not known.

The structure and function of presynaptic endosomes

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

Jähne, Sebastian, E-mail: sebastian.jaehne1@stud.uni-goettingen.de; International Max Planck Research School for Neurosciences, 37077 Göttingen; Rizzoli, Silvio O.

The function of endosomes and of endosome-like structures in the presynaptic compartment is still controversial. This is in part due to the absence of a consensus on definitions and markers for these compartments. Synaptic endosomes are sometimes seen as stable organelles, permanently present in the synapse. Alternatively, they are seen as short-lived intermediates in synaptic vesicle recycling, arising from the endocytosis of large vesicles from the plasma membrane, or from homotypic fusion of small vesicles. In addition, the potential function of the endosome is largely unknown in the synapse. Some groups have proposed that the endosome is involved in themore » sorting of synaptic vesicle proteins, albeit others have produced data that deny this possibility. In this review, we present the existing evidence for synaptic endosomes, we discuss their potential functions, and we highlight frequent technical pitfalls in the analysis of this elusive compartment. We also sketch a roadmap to definitely determine the role of synaptic endosomes for the synaptic vesicle cycle. Finally, we propose a common definition of synaptic endosome-like structures.« less

Synaptic genes are extensively downregulated across multiple brain regions in normal human aging and Alzheimer’s disease

PubMed Central

Berchtold, Nicole C.; Coleman, Paul D.; Cribbs, David H.; Rogers, Joseph; Gillen, Daniel L.; Cotman, Carl W.

2014-01-01

Synapses are essential for transmitting, processing, and storing information, all of which decline in aging and Alzheimer’s disease (AD). Because synapse loss only partially accounts for the cognitive declines seen in aging and AD, we hypothesized that existing synapses might undergo molecular changes that reduce their functional capacity. Microarrays were used to evaluate expression profiles of 340 synaptic genes in aging (20–99 years) and AD across 4 brain regions from 81 cases. The analysis revealed an unexpectedly large number of significant expression changes in synapse-related genes in aging, with many undergoing progressive downregulation across aging and AD. Functional classification of the genes showing altered expression revealed that multiple aspects of synaptic function are affected, notably synaptic vesicle trafficking and release, neurotransmitter receptors and receptor trafficking, postsynaptic density scaffolding, cell adhesion regulating synaptic stability, and neuromodulatory systems. The widespread declines in synaptic gene expression in normal aging suggests that function of existing synapses might be impaired, and that a common set of synaptic genes are vulnerable to change in aging and AD. PMID:23273601

Mitochondrial Aspects of Synaptic Dysfunction in Alzheimer’s Disease

PubMed Central

Cai, Qian; Tammineni, Prasad

2016-01-01

Alzheimer’s disease (AD) is characterized by brain deposition of amyloid plaques and tau neurofibrillary tangles along with steady cognitive decline. Synaptic damage, an early pathological event, correlates strongly with cognitive deficits and memory loss. Mitochondria are essential organelles for synaptic function. Neurons utilize specialized mechanisms to drive mitochondrial trafficking to synapses in which mitochondria buffer Ca2+ and serve as local energy sources by supplying ATP to sustain neurotransmitter release. Mitochondrial abnormalities are one of the earliest and prominent features in AD patient brains. Amyloid-β (Aβ) and tau both trigger mitochondrial alterations. Accumulating evidence suggests that mitochondrial perturbation acts as a key factor that is involved in synaptic failure and degeneration in AD. The importance of mitochondria in supporting synaptic function has made them a promising target of new therapeutic strategy for AD. Here, we review the molecular mechanisms regulating mitochondrial function at synapses, highlight recent findings on the disturbance of mitochondrial dynamics and transport in AD, and discuss how these alterations impact synaptic vesicle release and thus contribute to synaptic pathology associated with AD. PMID:27767992

Synaptic UNC13A protein variant causes increased neurotransmission and dyskinetic movement disorder.

PubMed

Lipstein, Noa; Verhoeven-Duif, Nanda M; Michelassi, Francesco E; Calloway, Nathaniel; van Hasselt, Peter M; Pienkowska, Katarzyna; van Haaften, Gijs; van Haelst, Mieke M; van Empelen, Ron; Cuppen, Inge; van Teeseling, Heleen C; Evelein, Annemieke M V; Vorstman, Jacob A; Thoms, Sven; Jahn, Olaf; Duran, Karen J; Monroe, Glen R; Ryan, Timothy A; Taschenberger, Holger; Dittman, Jeremy S; Rhee, Jeong-Seop; Visser, Gepke; Jans, Judith J; Brose, Nils

2017-03-01

Munc13 proteins are essential regulators of neurotransmitter release at nerve cell synapses. They mediate the priming step that renders synaptic vesicles fusion-competent, and their genetic elimination causes a complete block of synaptic transmission. Here we have described a patient displaying a disorder characterized by a dyskinetic movement disorder, developmental delay, and autism. Using whole-exome sequencing, we have shown that this condition is associated with a rare, de novo Pro814Leu variant in the major human Munc13 paralog UNC13A (also known as Munc13-1). Electrophysiological studies in murine neuronal cultures and functional analyses in Caenorhabditis elegans revealed that the UNC13A variant causes a distinct dominant gain of function that is characterized by increased fusion propensity of synaptic vesicles, which leads to increased initial synaptic vesicle release probability and abnormal short-term synaptic plasticity. Our study underscores the critical importance of fine-tuned presynaptic control in normal brain function. Further, it adds the neuronal Munc13 proteins and the synaptic vesicle priming process that they control to the known etiological mechanisms of psychiatric and neurological synaptopathies.

Synaptic UNC13A protein variant causes increased neurotransmission and dyskinetic movement disorder

PubMed Central

Lipstein, Noa; Verhoeven-Duif, Nanda M.; Calloway, Nathaniel; van Hasselt, Peter M.; Pienkowska, Katarzyna; van Haelst, Mieke M.; van Empelen, Ron; Cuppen, Inge; van Teeseling, Heleen C.; Evelein, Annemieke M.V.; Vorstman, Jacob A.; Jahn, Olaf; Duran, Karen J.; Monroe, Glen R.; Ryan, Timothy A.; Taschenberger, Holger; Rhee, Jeong-Seop; Visser, Gepke; Jans, Judith J.

2017-01-01

Munc13 proteins are essential regulators of neurotransmitter release at nerve cell synapses. They mediate the priming step that renders synaptic vesicles fusion-competent, and their genetic elimination causes a complete block of synaptic transmission. Here we have described a patient displaying a disorder characterized by a dyskinetic movement disorder, developmental delay, and autism. Using whole-exome sequencing, we have shown that this condition is associated with a rare, de novo Pro814Leu variant in the major human Munc13 paralog UNC13A (also known as Munc13-1). Electrophysiological studies in murine neuronal cultures and functional analyses in Caenorhabditis elegans revealed that the UNC13A variant causes a distinct dominant gain of function that is characterized by increased fusion propensity of synaptic vesicles, which leads to increased initial synaptic vesicle release probability and abnormal short-term synaptic plasticity. Our study underscores the critical importance of fine-tuned presynaptic control in normal brain function. Further, it adds the neuronal Munc13 proteins and the synaptic vesicle priming process that they control to the known etiological mechanisms of psychiatric and neurological synaptopathies. PMID:28192369

Adjunctive α-lipoic acid reduces weight gain compared with placebo at 12 weeks in schizophrenic patients treated with atypical antipsychotics: a double-blind randomized placebo-controlled study.

PubMed

Kim, Nam Wook; Song, Yul-Mai; Kim, Eosu; Cho, Hyun-Sang; Cheon, Keun-Ah; Kim, Su Jin; Park, Jin Young

2016-09-01

α-Lipoic acid (ALA) has been reported to be effective in reducing body weight in rodents and obese patients. Our previous open trial showed that ALA may play a role in reducing weight gain in patients with schizophrenia on atypical antipsychotics. The present study evaluated the efficacy of ALA in reducing weight and BMI in patients with schizophrenia who had experienced significant weight gain since taking atypical antipsychotics. In a 12-week, double-blind randomized placebo-controlled study, 22 overweight and clinically stable patients with schizophrenia were randomly assigned to receive ALA or placebo. ALA was administered at 600-1800 mg, as tolerated. Weight, BMI, abdomen fat area measured by computed tomography, and metabolic values were determined. Adverse effects were also assessed to examine safety. Overall, 15 patients completed 12 weeks of treatment. There was significant weight loss and decreased visceral fat levels in the ALA group compared with the placebo group. There were no instances of psychopathologic aggravation or severe ALA-associated adverse effects. ALA was effective in reducing weight and abdominal obesity in patients with schizophrenia who had experienced significant weight gain since beginning an atypical antipsychotic regimen. Moreover, ALA was well tolerated throughout this study. ALA might play an important role as an adjunctive treatment in decreasing obesity in patients who take atypical antipsychotics.

Fragile X Syndrome: Keys to the Molecular Genetics of Synaptic Plasticity

ERIC Educational Resources Information Center

Lombroso, Paul J.; Ogren, Marilee P.

2008-01-01

Fragile X syndrome, the most common form of inherited mental retardation is discussed. The relationship between specific impairments in synaptic plasticity and Fragile X syndrome is investigated as it strengthens synaptic contacts between neurons.

A light-stimulated synaptic transistor with synaptic plasticity and memory functions based on InGaZnO{sub x}–Al{sub 2}O{sub 3} thin film structure

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

Li, H. K.; Chen, T. P., E-mail: echentp@ntu.edu.sg; Liu, P.

In this work, a synaptic transistor based on the indium gallium zinc oxide (IGZO)–aluminum oxide (Al{sub 2}O{sub 3}) thin film structure, which uses ultraviolet (UV) light pulses as the pre-synaptic stimulus, has been demonstrated. The synaptic transistor exhibits the behavior of synaptic plasticity like the paired-pulse facilitation. In addition, it also shows the brain's memory behaviors including the transition from short-term memory to long-term memory and the Ebbinghaus forgetting curve. The synapse-like behavior and memory behaviors of the transistor are due to the trapping and detrapping processes of the holes, which are generated by the UV pulses, at the IGZO/Al{submore » 2}O{sub 3} interface and/or in the Al{sub 2}O{sub 3} layer.« less

Synaptic plasticity in drug reward circuitry.

PubMed

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.

Tau mislocalization to dendritic spines mediates synaptic dysfunction independently of neurodegeneration

PubMed Central

Hoover, Brian R.; Reed, Miranda N.; Su, Jianjun; Penrod, Rachel D.; Kotilinek, Linda A.; Grant, Marianne K.; Pitstick, Rose; Carlson, George A.; Lanier, Lorene M.; Yuan, Li-Lian; Ashe, Karen H.; Liao, Dezhi

2010-01-01

The microtubule-associated protein tau accumulates in Alzheimer’s and other fatal dementias, which manifest when forebrain neurons die. Recent advances in understanding these disorders indicate that brain dysfunction precedes neurodegeneration, but the role of tau is unclear. Here, we show that early tau-related deficits develop not from the loss of synapses or neurons, but rather as a result of synaptic abnormalities caused by the accumulation of hyperphosphorylated tau within intact dendritic spines, where it disrupts synaptic function by impairing glutamate receptor trafficking or synaptic anchoring. Mutagenesis of 14 disease-associated serine and threonine amino acid residues to create pseudohyperphosphorylated tau caused tau mislocalization while creation of phosphorylation-deficient tau blocked the mis-targeting of tau to dendritic spines. Thus, tau phosphorylation plays a critical role in mediating tau mislocalization and subsequent synaptic impairment. These data establish that the locus of early synaptic malfunction caused by tau resides in dendritic spines. PMID:21172610

Acute suppression of spontaneous neurotransmission drives synaptic potentiation.

PubMed

Nosyreva, Elena; Szabla, Kristen; Autry, Anita E; Ryazanov, Alexey G; Monteggia, Lisa M; Kavalali, Ege T

2013-04-17

The impact of spontaneous neurotransmission on neuronal plasticity remains poorly understood. Here, we show that acute suppression of spontaneous NMDA receptor-mediated (NMDAR-mediated) neurotransmission potentiates synaptic responses in the CA1 regions of rat and mouse hippocampus. This potentiation requires protein synthesis, brain-derived neurotrophic factor expression, eukaryotic elongation factor-2 kinase function, and increased surface expression of AMPA receptors. Our behavioral studies link this same synaptic signaling pathway to the fast-acting antidepressant responses elicited by ketamine. We also show that selective neurotransmitter depletion from spontaneously recycling vesicles triggers synaptic potentiation via the same pathway as NMDAR blockade, demonstrating that presynaptic impairment of spontaneous release, without manipulation of evoked neurotransmission, is sufficient to elicit postsynaptic plasticity. These findings uncover an unexpectedly dynamic impact of spontaneous glutamate release on synaptic efficacy and provide new insight into a key synaptic substrate for rapid antidepressant action.

Characterization and Modeling of Nonfilamentary Ta/TaOx/TiO2/Ti Analog Synaptic Device

PubMed Central

Wang, Yu-Fen; Lin, Yen-Chuan; Wang, I-Ting; Lin, Tzu-Ping; Hou, Tuo-Hung

2015-01-01

A two-terminal analog synaptic device that precisely emulates biological synaptic features is expected to be a critical component for future hardware-based neuromorphic computing. Typical synaptic devices based on filamentary resistive switching face severe limitations on the implementation of concurrent inhibitory and excitatory synapses with low conductance and state fluctuation. For overcoming these limitations, we propose a Ta/TaOx/TiO2/Ti device with superior analog synaptic features. A physical simulation based on the homogeneous (nonfilamentary) barrier modulation induced by oxygen ion migration accurately reproduces various DC and AC evolutions of synaptic states, including the spike-timing-dependent plasticity and paired-pulse facilitation. Furthermore, a physics-based compact model for facilitating circuit-level design is proposed on the basis of the general definition of memristor devices. This comprehensive experimental and theoretical study of the promising electronic synapse can facilitate realizing large-scale neuromorphic systems. PMID:25955658

T-type calcium channels in synaptic plasticity

PubMed Central

Lambert, Régis C.

2017-01-01

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

The role of microglia in synaptic stripping and synaptic degeneration: a revised perspective

PubMed Central

Hugh Perry, V; O'Connor, Vincent

2010-01-01

Chronic neurodegenerative diseases of the CNS (central nervous system) are characterized by the loss of neurons. There is, however, growing evidence to show that an early stage of this process involves degeneration of presynaptic terminals prior to the loss of the cell body. Synaptic plasticity in CNS pathology has been associated with microglia and the phenomenon of synaptic stripping. We review here the evidence for the involvement of microglia in synaptic stripping and synapse degeneration and we conclude that this is a case of guilt by association. In disease models of chronic neurodegeneration, there is no evidence that microglia play an active role in either synaptic stripping or synapse degeneration, but the degeneration of the synapse and the envelopment of a degenerating terminal appears to be a neuron autonomous event. We highlight here some of the gaps in our understanding of synapse degeneration in chronic neurodegenerative disease. PMID:20967131

[Involvement of aquaporin-4 in synaptic plasticity, learning and memory].

PubMed

Wu, Xin; Gao, Jian-Feng

2017-06-25

Aquaporin-4 (AQP-4) is the predominant water channel in the central nervous system (CNS) and primarily expressed in astrocytes. Astrocytes have been generally believed to play important roles in regulating synaptic plasticity and information processing. However, the role of AQP-4 in regulating synaptic plasticity, learning and memory, cognitive function is only beginning to be investigated. It is well known that synaptic plasticity is the prime candidate for mediating of learning and memory. Long term potentiation (LTP) and long term depression (LTD) are two forms of synaptic plasticity, and they share some but not all the properties and mechanisms. Hippocampus is a part of limbic system that is particularly important in regulation of learning and memory. This article is to review some research progresses of the function of AQP-4 in synaptic plasticity, learning and memory, and propose the possible role of AQP-4 as a new target in the treatment of cognitive dysfunction.

Adult-born neurons modify excitatory synaptic transmission to existing neurons

PubMed Central

Adlaf, Elena W; Vaden, Ryan J; Niver, Anastasia J; Manuel, Allison F; Onyilo, Vincent C; Araujo, Matheus T; Dieni, Cristina V; Vo, Hai T; King, Gwendalyn D; Wadiche, Jacques I; Overstreet-Wadiche, Linda

2017-01-01

Adult-born neurons are continually produced in the dentate gyrus but it is unclear whether synaptic integration of new neurons affects the pre-existing circuit. Here we investigated how manipulating neurogenesis in adult mice alters excitatory synaptic transmission to mature dentate neurons. Enhancing neurogenesis by conditional deletion of the pro-apoptotic gene Bax in stem cells reduced excitatory postsynaptic currents (EPSCs) and spine density in mature neurons, whereas genetic ablation of neurogenesis increased EPSCs in mature neurons. Unexpectedly, we found that Bax deletion in developing and mature dentate neurons increased EPSCs and prevented neurogenesis-induced synaptic suppression. Together these results show that neurogenesis modifies synaptic transmission to mature neurons in a manner consistent with a redistribution of pre-existing synapses to newly integrating neurons and that a non-apoptotic function of the Bax signaling pathway contributes to ongoing synaptic refinement within the dentate circuit. DOI: http://dx.doi.org/10.7554/eLife.19886.001 PMID:28135190

A network of autism linked genes stabilizes two pools of synaptic GABAA receptors

PubMed Central

Tong, Xia-Jing; Hu, Zhitao; Liu, Yu; Anderson, Dorian; Kaplan, Joshua M

2015-01-01

Changing receptor abundance at synapses is an important mechanism for regulating synaptic strength. Synapses contain two pools of receptors, immobilized and diffusing receptors, both of which are confined to post-synaptic elements. Here we show that immobile and diffusing GABAA receptors are stabilized by distinct synaptic scaffolds at C. elegans neuromuscular junctions. Immobilized GABAA receptors are stabilized by binding to FRM-3/EPB4.1 and LIN-2A/CASK. Diffusing GABAA receptors are stabilized by the synaptic adhesion molecules Neurexin and Neuroligin. Inhibitory post-synaptic currents are eliminated in double mutants lacking both scaffolds. Neurexin, Neuroligin, and CASK mutations are all linked to Autism Spectrum Disorders (ASD). Our results suggest that these mutations may directly alter inhibitory transmission, which could contribute to the developmental and cognitive deficits observed in ASD. DOI: http://dx.doi.org/10.7554/eLife.09648.001 PMID:26575289

A Hebbian learning rule gives rise to mirror neurons and links them to control theoretic inverse models.

PubMed

Hanuschkin, A; Ganguli, S; Hahnloser, R H R

2013-01-01

Mirror neurons are neurons whose responses to the observation of a motor act resemble responses measured during production of that act. Computationally, mirror neurons have been viewed as evidence for the existence of internal inverse models. Such models, rooted within control theory, map-desired sensory targets onto the motor commands required to generate those targets. To jointly explore both the formation of mirrored responses and their functional contribution to inverse models, we develop a correlation-based theory of interactions between a sensory and a motor area. We show that a simple eligibility-weighted Hebbian learning rule, operating within a sensorimotor loop during motor explorations and stabilized by heterosynaptic competition, naturally gives rise to mirror neurons as well as control theoretic inverse models encoded in the synaptic weights from sensory to motor neurons. Crucially, we find that the correlational structure or stereotypy of the neural code underlying motor explorations determines the nature of the learned inverse model: random motor codes lead to causal inverses that map sensory activity patterns to their motor causes; such inverses are maximally useful, by allowing the imitation of arbitrary sensory target sequences. By contrast, stereotyped motor codes lead to less useful predictive inverses that map sensory activity to future motor actions. Our theory generalizes previous work on inverse models by showing that such models can be learned in a simple Hebbian framework without the need for error signals or backpropagation, and it makes new conceptual connections between the causal nature of inverse models, the statistical structure of motor variability, and the time-lag between sensory and motor responses of mirror neurons. Applied to bird song learning, our theory can account for puzzling aspects of the song system, including necessity of sensorimotor gating and selectivity of auditory responses to bird's own song (BOS) stimuli.