[Involvement of aquaporin-4 in synaptic plasticity, learning and memory].
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.
Modeling somatic and dendritic spike mediated plasticity at the single neuron and network level.
Bono, Jacopo; Clopath, Claudia
2017-09-26
Synaptic plasticity is thought to be the principal neuronal mechanism underlying learning. Models of plastic networks typically combine point neurons with spike-timing-dependent plasticity (STDP) as the learning rule. However, a point neuron does not capture the local non-linear processing of synaptic inputs allowed for by dendrites. Furthermore, experimental evidence suggests that STDP is not the only learning rule available to neurons. By implementing biophysically realistic neuron models, we study how dendrites enable multiple synaptic plasticity mechanisms to coexist in a single cell. In these models, we compare the conditions for STDP and for synaptic strengthening by local dendritic spikes. We also explore how the connectivity between two cells is affected by these plasticity rules and by different synaptic distributions. Finally, we show that how memory retention during associative learning can be prolonged in networks of neurons by including dendrites.Synaptic plasticity is the neuronal mechanism underlying learning. Here the authors construct biophysical models of pyramidal neurons that reproduce observed plasticity gradients along the dendrite and show that dendritic spike dependent LTP which is predominant in distal sections can prolong memory retention.
Synaptic plasticity associated with a memory engram in the basolateral amygdala.
Nonaka, Ayako; Toyoda, Takeshi; Miura, Yuki; Hitora-Imamura, Natsuko; Naka, Masamitsu; Eguchi, Megumi; Yamaguchi, Shun; Ikegaya, Yuji; Matsuki, Norio; Nomura, Hiroshi
2014-07-09
Synaptic plasticity is a cellular mechanism putatively underlying learning and memory. However, it is unclear whether learning induces synaptic modification globally or only in a subset of neurons in associated brain regions. In this study, we genetically identified neurons activated during contextual fear learning and separately recorded synaptic efficacy from recruited and nonrecruited neurons in the mouse basolateral amygdala (BLA). We found that the fear learning induces presynaptic potentiation, which was reflected by an increase in the miniature EPSC frequency and by a decrease in the paired-pulse ratio. Changes occurred only in the cortical synapses targeting the BLA neurons that were recruited into the fear memory trace. Furthermore, we found that fear learning reorganizes the neuronal ensemble responsive to the conditioning context in conjunction with the synaptic plasticity. In particular, the neuronal activity during learning was associated with the neuronal recruitment into the context-responsive ensemble. These findings suggest that synaptic plasticity in a subset of BLA neurons contributes to fear memory expression through ensemble reorganization. Copyright © 2014 the authors 0270-6474/14/349305-05$15.00/0.
[Progress on metaplasticity and its role in learning and memory].
Wang, Shao-Li; Lu, Wei
2016-08-25
Long-term potentiation (LTP) and long-term depression (LTD) are two major forms of synaptic plasticity that are widely considered as important cellular models of learning and memory. Metaplasticity is defined as the plasticity of synaptic plasticity and thus is an advanced form of plasticity. The history of synaptic activity can affect the subsequent synaptic plasticity induction. Therefore, it is important to study metaplasticity to explore new mechanisms underlying various brain functions including learning and memory. Since the concept of metaplasticity was proposed, it has aroused widespread concerns and attracted numerous researchers to dig more details on this topic. These new-found experimental phenomena and cellular mechanisms have established the basis of theoretical studies on metaplasticity. In recent years, researchers have found that metaplasticity can not only affect the synaptic plasticity, but also regulate the neural network to encode specific content and enhance the learning and memory. These findings have greatly enriched our knowledge on plasticity and opened a new route to study the mechanism of learning and memory. In this review, we discuss the recent progress on metaplasticity on following three aspects: (1) the molecular mechanisms of metaplasticity; (2) the role of metaplasticity in learning and memory; and (3) the outlook of future study on metaplasticity.
Somato-dendritic Synaptic Plasticity and Error-backpropagation in Active Dendrites
Schiess, Mathieu; Urbanczik, Robert; Senn, Walter
2016-01-01
In the last decade dendrites of cortical neurons have been shown to nonlinearly combine synaptic inputs by evoking local dendritic spikes. It has been suggested that these nonlinearities raise the computational power of a single neuron, making it comparable to a 2-layer network of point neurons. But how these nonlinearities can be incorporated into the synaptic plasticity to optimally support learning remains unclear. We present a theoretically derived synaptic plasticity rule for supervised and reinforcement learning that depends on the timing of the presynaptic, the dendritic and the postsynaptic spikes. For supervised learning, the rule can be seen as a biological version of the classical error-backpropagation algorithm applied to the dendritic case. When modulated by a delayed reward signal, the same plasticity is shown to maximize the expected reward in reinforcement learning for various coding scenarios. Our framework makes specific experimental predictions and highlights the unique advantage of active dendrites for implementing powerful synaptic plasticity rules that have access to downstream information via backpropagation of action potentials. PMID:26841235
Spatial Object Recognition Enables Endogenous LTD that Curtails LTP in the Mouse Hippocampus
Goh, Jinzhong Jeremy
2013-01-01
Although synaptic plasticity is believed to comprise the cellular substrate for learning and memory, limited direct evidence exists that hippocampus-dependent learning actually triggers synaptic plasticity. It is likely, however, that long-term potentiation (LTP) works in concert with its counterpart, long-term depression (LTD) in the creation of spatial memory. It has been reported in rats that weak synaptic plasticity is facilitated into persistent plasticity if afferent stimulation is coupled with a novel spatial learning event. It is not known if this phenomenon also occurs in other species. We recorded from the hippocampal CA1 of freely behaving mice and observed that novel spatial learning triggers endogenous LTD. Specifically, we observed that LTD is enabled when test-pulse afferent stimulation is given during the learning of object constellations or during a spatial object recognition task. Intriguingly, LTP is significantly impaired by the same tasks, suggesting that LTD is the main cellular substrate for this type of learning. These data indicate that learning-facilitated plasticity is not exclusive to rats and that spatial learning leads to endogenous LTD in the hippocampus, suggesting an important role for this type of synaptic plasticity in the creation of hippocampus-dependent memory. PMID:22510536
From modulated Hebbian plasticity to simple behavior learning through noise and weight saturation.
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.
GRASP1 regulates synaptic plasticity and learning through endosomal recycling of AMPA receptors
Chiu, Shu-Ling; Diering, Graham Hugh; Ye, Bing; Takamiya, Kogo; Chen, Chih-Ming; Jiang, Yuwu; Niranjan, Tejasvi; Schwartz, Charles E.; Wang, Tao; Huganir, Richard L.
2017-01-01
Summary Learning depends on experience-dependent modification of synaptic efficacy and neuronal connectivity in the brain. We provide direct evidence for physiological roles of the recycling endosome protein GRASP1 in glutamatergic synapse function and animal behavior. Mice lacking GRASP1 showed abnormal excitatory synapse number, synaptic plasticity and hippocampal-dependent learning and memory due to a failure in learning-induced synaptic AMPAR incorporation. We identified two GRASP1 point mutations from intellectual disability (ID) patients that showed convergent disruptive effects on AMPAR recycling and glutamate uncaging-induced structural and functional plasticity. Wild-type GRASP1, but not ID mutants, rescues spine loss in hippocampal CA1 neurons of Grasp1 knockout mice. Together, these results demonstrate a requirement for normal recycling endosome function in AMPAR-dependent synaptic function and neuronal connectivity in vivo, and suggest a potential role for GRASP1 in the pathophysiology of human cognitive disorders. PMID:28285821
Pannexin 1 regulates bidirectional hippocampal synaptic plasticity in adult mice.
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
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
Toward a Neurocentric View of Learning.
Titley, Heather K; Brunel, Nicolas; Hansel, Christian
2017-07-05
Synaptic plasticity (e.g., long-term potentiation [LTP]) is considered the cellular correlate of learning. Recent optogenetic studies on memory engram formation assign a critical role in learning to suprathreshold activation of neurons and their integration into active engrams ("engram cells"). Here we review evidence that ensemble integration may result from LTP but also from cell-autonomous changes in membrane excitability. We propose that synaptic plasticity determines synaptic connectivity maps, whereas intrinsic plasticity-possibly separated in time-amplifies neuronal responsiveness and acutely drives engram integration. Our proposal marks a move away from an exclusively synaptocentric toward a non-exclusive, neurocentric view of learning. Copyright © 2017 Elsevier Inc. All rights reserved.
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
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.
Sieling, Fred; Bédécarrats, Alexis; Simmers, John; Prinz, Astrid A; Nargeot, Romuald
2014-05-05
Rewarding stimuli in associative learning can transform the irregularly and infrequently generated motor patterns underlying motivated behaviors into output for accelerated and stereotyped repetitive action. This transition to compulsive behavioral expression is associated with modified synaptic and membrane properties of central neurons, but establishing the causal relationships between cellular plasticity and motor adaptation has remained a challenge. We found previously that changes in the intrinsic excitability and electrical synapses of identified neurons in Aplysia's central pattern-generating network for feeding are correlated with a switch to compulsive-like motor output expression induced by in vivo operant conditioning. Here, we used specific computer-simulated ionic currents in vitro to selectively replicate or suppress the membrane and synaptic plasticity resulting from this learning. In naive in vitro preparations, such experimental manipulation of neuronal membrane properties alone increased the frequency but not the regularity of feeding motor output found in preparations from operantly trained animals. On the other hand, changes in synaptic strength alone switched the regularity but not the frequency of feeding output from naive to trained states. However, simultaneously imposed changes in both membrane and synaptic properties reproduced both major aspects of the motor plasticity. Conversely, in preparations from trained animals, experimental suppression of the membrane and synaptic plasticity abolished the increase in frequency and regularity of the learned motor output expression. These data establish direct causality for the contributions of distinct synaptic and nonsynaptic adaptive processes to complementary facets of a compulsive behavior resulting from operant reward learning. Copyright © 2014 Elsevier Ltd. All rights reserved.
Huang, Lianyan; Yang, Guang
2014-01-01
Background Recent studies in rodents suggest that repeated and prolonged anesthetic exposure at early stages of development leads to cognitive and behavioral impairments later in life. However, the underlying mechanism remains unknown. In this study, we tested whether exposure to general anesthesia during early development will disrupt the maturation of synaptic circuits and compromise learning-related synaptic plasticity later in life. Methods Mice received ketamine/xylazine (20/3 mg/kg) anesthesia for one or three times, starting at either early [postnatal day 14 (P14)] or late (P21) stages of development (n=105). Control mice received saline injections (n=34). At P30, mice were subjected to rotarod motor training and fear conditioning. Motor learning-induced synaptic remodeling was examined in vivo by repeatedly imaging fluorescently-labeled postsynaptic dendritic spines in the primary motor cortex before and after training using two-photon microscopy. Results Three exposures to ketamine/xylazine anesthesia between P14–18 impair the animals’ motor learning and learning-dependent dendritic spine plasticity [new spine formation, 8.4 ± 1.3% (mean ± SD) versus 13.4 ± 1.8%, P = 0.002] without affecting fear memory and cell apoptosis. One exposure at P14 or three exposures between P21–25 has no effects on the animals’ motor learning or spine plasticity. Finally, enriched motor experience ameliorates anesthesia-induced motor learning impairment and synaptic deficits. Conclusion Our study demonstrates that repeated exposures to ketamine/xylazine during early development impair motor learning and learning-dependent dendritic spine plasticity later in life. The reduction in synaptic structural plasticity may underlie anesthesia-induced behavioral impairment. PMID:25575163
Spatial features of synaptic adaptation affecting learning performance.
Berger, Damian L; de Arcangelis, Lucilla; Herrmann, Hans J
2017-09-08
Recent studies have proposed that the diffusion of messenger molecules, such as monoamines, can mediate the plastic adaptation of synapses in supervised learning of neural networks. Based on these findings we developed a model for neural learning, where the signal for plastic adaptation is assumed to propagate through the extracellular space. We investigate the conditions allowing learning of Boolean rules in a neural network. Even fully excitatory networks show very good learning performances. Moreover, the investigation of the plastic adaptation features optimizing the performance suggests that learning is very sensitive to the extent of the plastic adaptation and the spatial range of synaptic connections.
Learning of Precise Spike Times with Homeostatic Membrane Potential Dependent Synaptic Plasticity.
Albers, Christian; Westkott, Maren; Pawelzik, Klaus
2016-01-01
Precise spatio-temporal patterns of neuronal action potentials underly e.g. sensory representations and control of muscle activities. However, it is not known how the synaptic efficacies in the neuronal networks of the brain adapt such that they can reliably generate spikes at specific points in time. Existing activity-dependent plasticity rules like Spike-Timing-Dependent Plasticity are agnostic to the goal of learning spike times. On the other hand, the existing formal and supervised learning algorithms perform a temporally precise comparison of projected activity with the target, but there is no known biologically plausible implementation of this comparison. Here, we propose a simple and local unsupervised synaptic plasticity mechanism that is derived from the requirement of a balanced membrane potential. Since the relevant signal for synaptic change is the postsynaptic voltage rather than spike times, we call the plasticity rule Membrane Potential Dependent Plasticity (MPDP). Combining our plasticity mechanism with spike after-hyperpolarization causes a sensitivity of synaptic change to pre- and postsynaptic spike times which can reproduce Hebbian spike timing dependent plasticity for inhibitory synapses as was found in experiments. In addition, the sensitivity of MPDP to the time course of the voltage when generating a spike allows MPDP to distinguish between weak (spurious) and strong (teacher) spikes, which therefore provides a neuronal basis for the comparison of actual and target activity. For spatio-temporal input spike patterns our conceptually simple plasticity rule achieves a surprisingly high storage capacity for spike associations. The sensitivity of the MPDP to the subthreshold membrane potential during training allows robust memory retrieval after learning even in the presence of activity corrupted by noise. We propose that MPDP represents a biophysically plausible mechanism to learn temporal target activity patterns.
Learning of Precise Spike Times with Homeostatic Membrane Potential Dependent Synaptic Plasticity
Albers, Christian; Westkott, Maren; Pawelzik, Klaus
2016-01-01
Precise spatio-temporal patterns of neuronal action potentials underly e.g. sensory representations and control of muscle activities. However, it is not known how the synaptic efficacies in the neuronal networks of the brain adapt such that they can reliably generate spikes at specific points in time. Existing activity-dependent plasticity rules like Spike-Timing-Dependent Plasticity are agnostic to the goal of learning spike times. On the other hand, the existing formal and supervised learning algorithms perform a temporally precise comparison of projected activity with the target, but there is no known biologically plausible implementation of this comparison. Here, we propose a simple and local unsupervised synaptic plasticity mechanism that is derived from the requirement of a balanced membrane potential. Since the relevant signal for synaptic change is the postsynaptic voltage rather than spike times, we call the plasticity rule Membrane Potential Dependent Plasticity (MPDP). Combining our plasticity mechanism with spike after-hyperpolarization causes a sensitivity of synaptic change to pre- and postsynaptic spike times which can reproduce Hebbian spike timing dependent plasticity for inhibitory synapses as was found in experiments. In addition, the sensitivity of MPDP to the time course of the voltage when generating a spike allows MPDP to distinguish between weak (spurious) and strong (teacher) spikes, which therefore provides a neuronal basis for the comparison of actual and target activity. For spatio-temporal input spike patterns our conceptually simple plasticity rule achieves a surprisingly high storage capacity for spike associations. The sensitivity of the MPDP to the subthreshold membrane potential during training allows robust memory retrieval after learning even in the presence of activity corrupted by noise. We propose that MPDP represents a biophysically plausible mechanism to learn temporal target activity patterns. PMID:26900845
Implementation of a spike-based perceptron learning rule using TiO2-x memristors.
Mostafa, Hesham; Khiat, Ali; Serb, Alexander; Mayr, Christian G; Indiveri, Giacomo; Prodromakis, Themis
2015-01-01
Synaptic plasticity plays a crucial role in allowing neural networks to learn and adapt to various input environments. Neuromorphic systems need to implement plastic synapses to obtain basic "cognitive" capabilities such as learning. One promising and scalable approach for implementing neuromorphic synapses is to use nano-scale memristors as synaptic elements. In this paper we propose a hybrid CMOS-memristor system comprising CMOS neurons interconnected through TiO2-x memristors, and spike-based learning circuits that modulate the conductance of the memristive synapse elements according to a spike-based Perceptron plasticity rule. We highlight a number of advantages for using this spike-based plasticity rule as compared to other forms of spike timing dependent plasticity (STDP) rules. We provide experimental proof-of-concept results with two silicon neurons connected through a memristive synapse that show how the CMOS plasticity circuits can induce stable changes in memristor conductances, giving rise to increased synaptic strength after a potentiation episode and to decreased strength after a depression episode.
All about running: synaptic plasticity, growth factors and adult hippocampal neurogenesis.
Vivar, Carmen; Potter, Michelle C; van Praag, Henriette
2013-01-01
Accumulating evidence from animal and human research shows exercise benefits learning and memory, which may reduce the risk of neurodegenerative diseases, and could delay age-related cognitive decline. Exercise-induced improvements in learning and memory are correlated with enhanced adult hippocampal neurogenesis and increased activity-dependent synaptic plasticity. In this present chapter we will highlight the effects of physical activity on cognition in rodents, as well as on dentate gyrus (DG) neurogenesis, synaptic plasticity, spine density, neurotransmission and growth factors, in particular brain-derived nerve growth factor (BDNF).
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
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
Synaptic plasticity in drug reward circuitry.
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.
Common mechanisms of synaptic plasticity in vertebrates and invertebrates
Glanzman, David L.
2016-01-01
Until recently, the literature on learning-related synaptic plasticity in invertebrates has been dominated by models assuming plasticity is mediated by presynaptic changes, whereas the vertebrate literature has been dominated by models assuming it is mediated by postsynaptic changes. Here I will argue that this situation does not reflect a biological reality and that, in fact, invertebrate and vertebrate nervous systems share a common set of mechanisms of synaptic plasticity. PMID:20152143
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.
Barmashenko, Gleb; Buttgereit, Jens; Herring, Neil; Bader, Michael; Özcelik, Cemil; Manahan-Vaughan, Denise; Braunewell, Karl H.
2014-01-01
The second messenger cyclic GMP affects synaptic transmission and modulates synaptic plasticity and certain types of learning and memory processes. The impact of the natriuretic peptide receptor B (NPR-B) and its ligand C-type natriuretic peptide (CNP), one of several cGMP producing signaling systems, on hippocampal synaptic plasticity and learning is, however, less well understood. We have previously shown that the NPR-B ligand CNP increases the magnitude of long-term depression (LTD) in hippocampal area CA1, while reducing the induction of long-term potentiation (LTP). We have extended this line of research to show that bidirectional plasticity is affected in the opposite way in rats expressing a dominant-negative mutant of NPR-B (NSE-NPR-BΔKC) lacking the intracellular guanylyl cyclase domain under control of a promoter for neuron-specific enolase. The brain cells of these transgenic rats express functional dimers of the NPR-B receptor containing the dominant-negative NPR-BΔKC mutant, and therefore show decreased CNP-stimulated cGMP-production in brain membranes. The NPR-B transgenic rats display enhanced LTP but reduced LTD in hippocampal slices. When the frequency-dependence of synaptic modification to afferent stimulation in the range of 1–100 Hz was assessed in transgenic rats, the threshold for both, LTP and LTD induction, was shifted to lower frequencies. In parallel, NPR-BΔKC rats exhibited an enhancement in exploratory and learning behavior. These results indicate that bidirectional plasticity and learning and memory mechanism are affected in transgenic rats expressing a dominant-negative mutant of NPR-B. Our data substantiate the hypothesis that NPR-B-dependent cGMP signaling has a modulatory role for synaptic information storage and learning. PMID:25520616
Weinmann, Oliver; Kellner, Yves; Yu, Xinzhu; Vicente, Raul; Gullo, Miriam; Kasper, Hansjörg; Lussi, Karin; Ristic, Zorica; Luft, Andreas R.; Rioult-Pedotti, Mengia; Zuo, Yi; Zagrebelsky, Marta; Schwab, Martin E.
2014-01-01
The membrane protein Nogo-A is known as an inhibitor of axonal outgrowth and regeneration in the CNS. However, its physiological functions in the normal adult CNS remain incompletely understood. Here, we investigated the role of Nogo-A in cortical synaptic plasticity and motor learning in the uninjured adult rodent motor cortex. Nogo-A and its receptor NgR1 are present at cortical synapses. Acute treatment of slices with function-blocking antibodies (Abs) against Nogo-A or against NgR1 increased long-term potentiation (LTP) induced by stimulation of layer 2/3 horizontal fibers. Furthermore, anti-Nogo-A Ab treatment increased LTP saturation levels, whereas long-term depression remained unchanged, thus leading to an enlarged synaptic modification range. In vivo, intrathecal application of Nogo-A-blocking Abs resulted in a higher dendritic spine density at cortical pyramidal neurons due to an increase in spine formation as revealed by in vivo two-photon microscopy. To investigate whether these changes in synaptic plasticity correlate with motor learning, we trained rats to learn a skilled forelimb-reaching task while receiving anti-Nogo-A Abs. Learning of this cortically controlled precision movement was improved upon anti-Nogo-A Ab treatment. Our results identify Nogo-A as an influential molecular modulator of synaptic plasticity and as a regulator for learning of skilled movements in the motor cortex. PMID:24966370
Fletcher, Bonnie R; Calhoun, Michael E; Rapp, Peter R; Shapiro, Matthew L
2006-02-01
The immediate-early gene (IEG) Arc is transcribed after behavioral and physiological treatments that induce synaptic plasticity and is implicated in memory consolidation. The relative contributions of neuronal activity and learning-related plasticity to the behavioral induction of Arc remain to be defined. To differentiate the contributions of each, we assessed the induction of Arc transcription in rats with fornix lesions that impair hippocampal learning yet leave cortical connectivity and neuronal firing essentially intact. Arc expression was assessed after exploration of novel environments and performance of a novel water maze task during which normal rats learned the spatial location of an escape platform. During the same task, rats with fornix lesions learned to approach a visible platform but did not learn its spatial location. Rats with fornix lesions had normal baseline levels of hippocampal Arc mRNA, but unlike normal rats, expression was not increased in response to water maze training. The integrity of signaling pathways controlling Arc expression was demonstrated by stimulation of the medial perforant path, which induced normal synaptic potentiation and Arc in rats with fornix lesions. Together, the results demonstrate that Arc induction can be decoupled from behavior and is more likely to indicate the engagement of synaptic plasticity mechanisms than synaptic or neuronal activity per se. The results further imply that fornix lesions may impair memory in part by decoupling neuronal activity from signaling pathways required for long-lasting hippocampal synaptic plasticity.
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.
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
Mirrored STDP Implements Autoencoder Learning in a Network of Spiking Neurons.
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
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
Bouchard, Kristofer E.; Ganguli, Surya; Brainard, Michael S.
2015-01-01
The majority of distinct sensory and motor events occur as temporally ordered sequences with rich probabilistic structure. Sequences can be characterized by the probability of transitioning from the current state to upcoming states (forward probability), as well as the probability of having transitioned to the current state from previous states (backward probability). Despite the prevalence of probabilistic sequencing of both sensory and motor events, the Hebbian mechanisms that mold synapses to reflect the statistics of experienced probabilistic sequences are not well understood. Here, we show through analytic calculations and numerical simulations that Hebbian plasticity (correlation, covariance, and STDP) with pre-synaptic competition can develop synaptic weights equal to the conditional forward transition probabilities present in the input sequence. In contrast, post-synaptic competition can develop synaptic weights proportional to the conditional backward probabilities of the same input sequence. We demonstrate that to stably reflect the conditional probability of a neuron's inputs and outputs, local Hebbian plasticity requires balance between competitive learning forces that promote synaptic differentiation and homogenizing learning forces that promote synaptic stabilization. The balance between these forces dictates a prior over the distribution of learned synaptic weights, strongly influencing both the rate at which structure emerges and the entropy of the final distribution of synaptic weights. Together, these results demonstrate a simple correspondence between the biophysical organization of neurons, the site of synaptic competition, and the temporal flow of information encoded in synaptic weights by Hebbian plasticity while highlighting the utility of balancing learning forces to accurately encode probability distributions, and prior expectations over such probability distributions. PMID:26257637
Energy Efficient Sparse Connectivity from Imbalanced Synaptic Plasticity Rules
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
NASA Astrophysics Data System (ADS)
Das, Mangal; Kumar, Amitesh; Singh, Rohit; Than Htay, Myo; Mukherjee, Shaibal
2018-02-01
Single synaptic device with inherent learning and memory functions is demonstrated based on a forming-free amorphous Y2O3 (yttria) memristor fabricated by dual ion beam sputtering system. Synaptic functions such as nonlinear transmission characteristics, long-term plasticity, short-term plasticity and ‘learning behavior (LB)’ are achieved using a single synaptic device based on cost-effective metal-insulator-semiconductor (MIS) structure. An ‘LB’ function is demonstrated, for the first time in the literature, for a yttria based memristor, which bears a resemblance to certain memory functions of biological systems. The realization of key synaptic functions in a cost-effective MIS structure would promote much cheaper synapse for artificial neural network.
Nie, Jingjing; Yang, Xiaosu
2017-01-01
In recent years, rehabilitation of ischemic stroke draws more and more attention in the world, and has been linked to changes of synaptic plasticity. Exercise training improves motor function of ischemia as well as cognition which is associated with formation of learning and memory. The molecular basis of learning and memory might be synaptic plasticity. Research has therefore been conducted in an attempt to relate effects of exercise training to neuroprotection and neurogenesis adjacent to the ischemic injury brain. The present paper reviews the current literature addressing this question and discusses the possible mechanisms involved in modulation of synaptic plasticity by exercise training. This review shows the pathological process of synaptic dysfunction in ischemic roughly and then discusses the effects of exercise training on scaffold proteins and regulatory protein expression. The expression of scaffold proteins generally increased after training, but the effects on regulatory proteins were mixed. Moreover, the compositions of postsynaptic receptors were changed and the strength of synaptic transmission was enhanced after training. Finally, the recovery of cognition is critically associated with synaptic remodeling in an injured brain, and the remodeling occurs through a number of local regulations including mRNA translation, remodeling of cytoskeleton, and receptor trafficking into and out of the synapse. We do provide a comprehensive knowledge of synaptic plasticity enhancement obtained by exercise training in this review.
The Corticohippocampal Circuit, Synaptic Plasticity, and Memory
Basu, Jayeeta; Siegelbaum, Steven A.
2015-01-01
Synaptic plasticity serves as a cellular substrate for information storage in the central nervous system. The entorhinal cortex (EC) and hippocampus are interconnected brain areas supporting basic cognitive functions important for the formation and retrieval of declarative memories. Here, we discuss how information flow in the EC–hippocampal loop is organized through circuit design. We highlight recently identified corticohippocampal and intrahippocampal connections and how these long-range and local microcircuits contribute to learning. This review also describes various forms of activity-dependent mechanisms that change the strength of corticohippocampal synaptic transmission. A key point to emerge from these studies is that patterned activity and interaction of coincident inputs gives rise to associational plasticity and long-term regulation of information flow. Finally, we offer insights about how learning-related synaptic plasticity within the corticohippocampal circuit during sensory experiences may enable adaptive behaviors for encoding spatial, episodic, social, and contextual memories. PMID:26525152
Out with the old and in with the new: Synaptic mechanisms of extinction in the amygdala
Maren, Stephen
2014-01-01
Considerable research indicates that long-term synaptic plasticity in the amygdala underlies the acquisition of emotional memories, including those learned during Pavlovian fear conditioning. Much less is known about the synaptic mechanisms involved in other forms of associative learning, including extinction, that update fear memories. Extinction learning might reverse conditioning-related changes (e.g., depotentiation) or induce plasticity at inhibitory synapses (e.g., long-term potentiation) to suppress conditioned fear responses. Either mechanism must account for fear recovery phenomena after extinction, as well as savings of extinction after fear recovery. PMID:25312830
Learning to learn – intrinsic plasticity as a metaplasticity mechanism for memory formation
Sehgal, Megha; Song, Chenghui; Ehlers, Vanessa L.; Moyer, James R.
2013-01-01
“Use it or lose it” is a popular adage often associated with use-dependent enhancement of cognitive abilities. Much research has focused on understanding exactly how the brain changes as a function of experience. Such experience-dependent plasticity involves both structural and functional alterations that contribute to adaptive behaviors, such as learning and memory, as well as maladaptive behaviors, including anxiety disorders, phobias, and posttraumatic stress disorder. With the advancing age of our population, understanding how use-dependent plasticity changes across the lifespan may also help to promote healthy brain aging. A common misconception is that such experience-dependent plasticity (e.g., associative learning) is synonymous with synaptic plasticity. Other forms of plasticity also play a critical role in shaping adaptive changes within the nervous system, including intrinsic plasticity – a change in the intrinsic excitability of a neuron. Intrinsic plasticity can result from a change in the number, distribution or activity of various ion channels located throughout the neuron. Here, we review evidence that intrinsic plasticity is an important and evolutionarily conserved neural correlate of learning. Intrinsic plasticity acts as a metaplasticity mechanism by lowering the threshold for synaptic changes. Thus, learning-related intrinsic changes can facilitate future synaptic plasticity and learning. Such intrinsic changes can impact the allocation of a memory trace within a brain structure, and when compromised, can contribute to cognitive decline during the aging process. This unique role of intrinsic excitability can provide insight into how memories are formed and, more interestingly, how neurons that participate in a memory trace are selected. Most importantly, modulation of intrinsic excitability can allow for regulation of learning ability – this can prevent or provide treatment for cognitive decline not only in patients with clinical disorders but also in the aging population. PMID:23871744
Mahati, K; Bhagya, V; Christofer, T; Sneha, A; Shankaranarayana Rao, B S
2016-10-01
Severe depression compromises structural and functional integrity of the brain and results in impaired learning and memory, maladaptive synaptic plasticity as well as degenerative changes in the hippocampus and amygdala. The precise mechanisms underlying cognitive dysfunctions in depression remain largely unknown. On the other hand, enriched environment (EE) offers beneficial effects on cognitive functions, synaptic plasticity in the hippocampus. However, the effect of EE on endogenous depression associated cognitive dysfunction has not been explored. Accordingly, we have attempted to address this issue by investigating behavioural, structural and synaptic plasticity mechanisms in an animal model of endogenous depression after exposure to enriched environment. Our results demonstrate that depression is associated with impaired spatial learning and enhanced anxiety-like behaviour which is correlated with hypotrophy of the dentate gyrus and amygdalar hypertrophy. We also observed a gross reduction in the hippocampal long-term potentiation (LTP). We report a complete behavioural recovery with reduced indices of anhedonia and behavioural despair, reduced anxiety-like behaviour and improved spatial learning along with a complete restoration of dentate gyrus and amygdalar volumes in depressive rats subjected to EE. Enrichment also facilitated CA3-Schaffer collateral LTP. Our study convincingly proves that depression-induces learning deficits and impairs hippocampal synaptic plasticity. It also highlights the role of environmental stimuli in restoring depression-induced cognitive deficits which might prove vital in outlining more effective strategies to treat major depressive disorders. Copyright © 2016 Elsevier Inc. All rights reserved.
The central amygdala controls learning in the lateral amygdala
Yu, Kai; Ahrens, Sandra; Zhang, Xian; Schiff, Hillary; Ramakrishnan, Charu; Fenno, Lief; Deisseroth, Karl; Zhao, Fei; Luo, Min-Hua; Gong, Ling; He, Miao; Zhou, Pengcheng; Paninski, Liam; Li, Bo
2018-01-01
Experience-driven synaptic plasticity in the lateral amygdala (LA) is thought to underlie the formation of associations between sensory stimuli and an ensuing threat. However, how the central amygdala (CeA) participates in such learning process remains unclear. Here we show that PKC-δ-expressing CeA neurons are essential for the synaptic plasticity underlying learning in the LA, as they convey information about unconditioned stimulus to LA neurons during fear conditioning. PMID:29184202
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
Intracellular GPCRs Play Key Roles in Synaptic Plasticity.
Jong, Yuh-Jiin I; Harmon, Steven K; O'Malley, Karen L
2018-02-16
The trillions of synaptic connections within the human brain are shaped by experience and neuronal activity, both of which underlie synaptic plasticity and ultimately learning and memory. G protein-coupled receptors (GPCRs) play key roles in synaptic plasticity by strengthening or weakening synapses and/or shaping dendritic spines. While most studies of synaptic plasticity have focused on cell surface receptors and their downstream signaling partners, emerging data point to a critical new role for the very same receptors to signal from inside the cell. Intracellular receptors have been localized to the nucleus, endoplasmic reticulum, lysosome, and mitochondria. From these intracellular positions, such receptors may couple to different signaling systems, display unique desensitization patterns, and/or show distinct patterns of subcellular distribution. Intracellular GPCRs can be activated at the cell surface, endocytosed, and transported to an intracellular site or simply activated in situ by de novo ligand synthesis, diffusion of permeable ligands, or active transport of non-permeable ligands. Current findings reinforce the notion that intracellular GPCRs play a dynamic role in synaptic plasticity and learning and memory. As new intracellular GPCR roles are defined, the need to selectively tailor agonists and/or antagonists to both intracellular and cell surface receptors may lead to the development of more effective therapeutic tools.
Multi-layer network utilizing rewarded spike time dependent plasticity to learn a foraging task
2017-01-01
Neural networks with a single plastic layer employing reward modulated spike time dependent plasticity (STDP) are capable of learning simple foraging tasks. Here we demonstrate advanced pattern discrimination and continuous learning in a network of spiking neurons with multiple plastic layers. The network utilized both reward modulated and non-reward modulated STDP and implemented multiple mechanisms for homeostatic regulation of synaptic efficacy, including heterosynaptic plasticity, gain control, output balancing, activity normalization of rewarded STDP and hard limits on synaptic strength. We found that addition of a hidden layer of neurons employing non-rewarded STDP created neurons that responded to the specific combinations of inputs and thus performed basic classification of the input patterns. When combined with a following layer of neurons implementing rewarded STDP, the network was able to learn, despite the absence of labeled training data, discrimination between rewarding patterns and the patterns designated as punishing. Synaptic noise allowed for trial-and-error learning that helped to identify the goal-oriented strategies which were effective in task solving. The study predicts a critical set of properties of the spiking neuronal network with STDP that was sufficient to solve a complex foraging task involving pattern classification and decision making. PMID:28961245
Nanou, Evanthia; Scheuer, Todd; Catterall, William A
2016-11-15
Many forms of short-term synaptic plasticity rely on regulation of presynaptic voltage-gated Ca 2+ type 2.1 (Ca V 2.1) channels. However, the contribution of regulation of Ca V 2.1 channels to other forms of neuroplasticity and to learning and memory are not known. Here we have studied mice with a mutation (IM-AA) that disrupts regulation of Ca V 2.1 channels by calmodulin and related calcium sensor proteins. Surprisingly, we find that long-term potentiation (LTP) of synaptic transmission at the Schaffer collateral-CA1 synapse in the hippocampus is substantially weakened, even though this form of synaptic plasticity is thought to be primarily generated postsynaptically. LTP in response to θ-burst stimulation and to 100-Hz tetanic stimulation is much reduced. However, a normal level of LTP can be generated by repetitive 100-Hz stimulation or by depolarization of the postsynaptic cell to prevent block of NMDA-specific glutamate receptors by Mg 2+ The ratio of postsynaptic responses of NMDA-specific glutamate receptors to those of AMPA-specific glutamate receptors is decreased, but the postsynaptic current from activation of NMDA-specific glutamate receptors is progressively increased during trains of stimuli and exceeds WT by the end of 1-s trains. Strikingly, these impairments in long-term synaptic plasticity and the previously documented impairments in short-term synaptic plasticity in IM-AA mice are associated with pronounced deficits in spatial learning and memory in context-dependent fear conditioning and in the Barnes circular maze. Thus, regulation of Ca V 2.1 channels by calcium sensor proteins is required for normal short-term synaptic plasticity, LTP, and spatial learning and memory in mice.
Berger, Stefan M; Fernández-Lamo, Iván; Schönig, Kai; Fernández Moya, Sandra M; Ehses, Janina; Schieweck, Rico; Clementi, Stefano; Enkel, Thomas; Grothe, Sascha; von Bohlen Und Halbach, Oliver; Segura, Inmaculada; Delgado-García, José María; Gruart, Agnès; Kiebler, Michael A; Bartsch, Dusan
2017-11-17
Dendritic messenger RNA (mRNA) localization and subsequent local translation in dendrites critically contributes to synaptic plasticity and learning and memory. Little is known, however, about the contribution of RNA-binding proteins (RBPs) to these processes in vivo. To delineate the role of the double-stranded RBP Staufen2 (Stau2), we generate a transgenic rat model, in which Stau2 expression is conditionally silenced by Cre-inducible expression of a microRNA (miRNA) targeting Stau2 mRNA in adult forebrain neurons. Known physiological mRNA targets for Stau2, such as RhoA, Complexin 1, and Rgs4 mRNAs, are found to be dysregulated in brains of Stau2-deficient rats. In vivo electrophysiological recordings reveal synaptic strengthening upon stimulation, showing a shift in the frequency-response function of hippocampal synaptic plasticity to favor long-term potentiation and impair long-term depression in Stau2-deficient rats. These observations are accompanied by deficits in hippocampal spatial working memory, spatial novelty detection, and in tasks investigating associative learning and memory. Together, these experiments reveal a critical contribution of Stau2 to various forms of synaptic plasticity including spatial working memory and cognitive management of new environmental information. These findings might contribute to the development of treatments for conditions associated with learning and memory deficits.
A saturation hypothesis to explain both enhanced and impaired learning with enhanced plasticity
Nguyen-Vu, TD Barbara; Zhao, Grace Q; Lahiri, Subhaneil; Kimpo, Rhea R; Lee, Hanmi; Ganguli, Surya; Shatz, Carla J; Raymond, Jennifer L
2017-01-01
Across many studies, animals with enhanced synaptic plasticity exhibit either enhanced or impaired learning, raising a conceptual puzzle: how enhanced plasticity can yield opposite learning outcomes? Here, we show that the recent history of experience can determine whether mice with enhanced plasticity exhibit enhanced or impaired learning in response to the same training. Mice with enhanced cerebellar LTD, due to double knockout (DKO) of MHCI H2-Kb/H2-Db (KbDb−/−), exhibited oculomotor learning deficits. However, the same mice exhibited enhanced learning after appropriate pre-training. Theoretical analysis revealed that synapses with history-dependent learning rules could recapitulate the data, and suggested that saturation may be a key factor limiting the ability of enhanced plasticity to enhance learning. Optogenetic stimulation designed to saturate LTD produced the same impairment in WT as observed in DKO mice. Overall, our results suggest that the recent history of activity and the threshold for synaptic plasticity conspire to effect divergent learning outcomes. DOI: http://dx.doi.org/10.7554/eLife.20147.001 PMID:28234229
Fast Learning with Weak Synaptic Plasticity.
Yger, Pierre; Stimberg, Marcel; Brette, Romain
2015-09-30
New sensory stimuli can be learned with a single or a few presentations. Similarly, the responses of cortical neurons to a stimulus have been shown to increase reliably after just a few repetitions. Long-term memory is thought to be mediated by synaptic plasticity, but in vitro experiments in cortical cells typically show very small changes in synaptic strength after a pair of presynaptic and postsynaptic spikes. Thus, it is traditionally thought that fast learning requires stronger synaptic changes, possibly because of neuromodulation. Here we show theoretically that weak synaptic plasticity can, in fact, support fast learning, because of the large number of synapses N onto a cortical neuron. In the fluctuation-driven regime characteristic of cortical neurons in vivo, the size of membrane potential fluctuations grows only as √N, whereas a single output spike leads to potentiation of a number of synapses proportional to N. Therefore, the relative effect of a single spike on synaptic potentiation grows as √N. This leverage effect requires precise spike timing. Thus, the large number of synapses onto cortical neurons allows fast learning with very small synaptic changes. Significance statement: Long-term memory is thought to rely on the strengthening of coactive synapses. This physiological mechanism is generally considered to be very gradual, and yet new sensory stimuli can be learned with just a few presentations. Here we show theoretically that this apparent paradox can be solved when there is a tight balance between excitatory and inhibitory input. In this case, small synaptic modifications applied to the many synapses onto a given neuron disrupt that balance and produce a large effect even for modifications induced by a single stimulus. This effect makes fast learning possible with small synaptic changes and reconciles physiological and behavioral observations. Copyright © 2015 the authors 0270-6474/15/3513351-12$15.00/0.
Zinc transporter 3 is involved in learned fear and extinction, but not in innate fear.
Martel, Guillaume; Hevi, Charles; Friebely, Olivia; Baybutt, Trevor; Shumyatsky, Gleb P
2010-11-01
Synaptically released Zn²+ 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, highly enriched in the amygdala-associated neural circuitry, and ZnT3 KO mice lack Zn²+ in synaptic vesicles. However, earlier work reported no deficiency in fear memory in ZnT3 KO mice, which is surprising based on the effects of Zn²+ on amygdala synaptic plasticity. We therefore reexamined ZnT3 KO mice in various tasks for learned and innate fear. The mutants were deficient in a weak fear-conditioning protocol using single tone-shock pairing but showed normal memory when a stronger, five-pairing protocol was used. ZnT3 KO mice were deficient in memory when a tone was presented as complex auditory information in a discontinuous fashion. Moreover, ZnT3 KO mice showed abnormality in trace fear conditioning and in fear extinction. By contrast, ZnT3 KO mice had normal anxiety. Thus, ZnT3 is involved in associative fear memory and extinction, but not in innate fear, consistent with the role of synaptic zinc in amygdala synaptic plasticity.
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.
Reversing the Effects of Fragile X Syndrome
ERIC Educational Resources Information Center
Ogren, Marilee P.; Lombroso, Paul J.
2008-01-01
A research on how synaptic plasticity is abnormally regulated in fragile X syndrome and how this abnormality can be reversed by therapeutic interventions is presented. Fragile X syndrome is a disorder of synaptic plasticity that contributes to abnormal development and interferes with normal learning and memory.
ALTERED PHOSPHORYLATION OF MAP KINASE AFTER ACUTE EXPOSURE TO PCB153.
Long-term potentiation (LTP) is a model of synaptic plasticity believed to encompass the physiological substrate of memory. The mitogen-activated protein kinase (ERK1/2) signalling cascade contributes to synaptic plasticity and to long-term memory formation. Learning and LTP st...
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,…
Learning induces the translin/trax RNase complex to express activin receptors for persistent memory.
Park, Alan Jung; Havekes, Robbert; Fu, Xiuping; Hansen, Rolf; Tudor, Jennifer C; Peixoto, Lucia; Li, Zhi; Wu, Yen-Ching; Poplawski, Shane G; Baraban, Jay M; Abel, Ted
2017-09-20
Long-lasting forms of synaptic plasticity and memory require de novo protein synthesis. Yet, how learning triggers this process to form memory is unclear. Translin/trax is a candidate to drive this learning-induced memory mechanism by suppressing microRNA-mediated translational silencing at activated synapses. We find that mice lacking translin/trax display defects in synaptic tagging, which requires protein synthesis at activated synapses, and long-term memory. Hippocampal samples harvested from these mice following learning show increases in several disease-related microRNAs targeting the activin A receptor type 1C (ACVR1C), a component of the transforming growth factor-β receptor superfamily. Furthermore, the absence of translin/trax abolishes synaptic upregulation of ACVR1C protein after learning. Finally, synaptic tagging and long-term memory deficits in mice lacking translin/trax are mimicked by ACVR1C inhibition. Thus, we define a new memory mechanism by which learning reverses microRNA-mediated silencing of the novel plasticity protein ACVR1C via translin/trax.
Learning and Memory, Part II: Molecular Mechanisms of Synaptic Plasticity
ERIC Educational Resources Information Center
Lombroso, Paul; Ogren, Marilee
2009-01-01
The molecular events that are responsible for strengthening synaptic connections and how these are linked to memory and learning are discussed. The laboratory preparations that allow the investigation of these events are also described.
Removal of S6K1 and S6K2 Leads to Divergent Alterations in Learning, Memory, and Synaptic Plasticity
ERIC Educational Resources Information Center
Antion, Marcia D.; Merhav, Maayan; Hoeffer, Charles A.; Reis, Gerald; Kozma, Sara C.; Thomas, George; Schuman Erin M.; Rosenblum, Kobi; Klann, Eric
2008-01-01
Protein synthesis is required for the expression of enduring memories and long-lasting synaptic plasticity. During cellular proliferation and growth, S6 kinases (S6Ks) are activated and coordinate the synthesis of de novo proteins. We hypothesized that protein synthesis mediated by S6Ks is critical for the manifestation of learning, memory, and…
The Convallis Rule for Unsupervised Learning in Cortical Networks
Yger, Pierre; Harris, Kenneth D.
2013-01-01
The phenomenology and cellular mechanisms of cortical synaptic plasticity are becoming known in increasing detail, but the computational principles by which cortical plasticity enables the development of sensory representations are unclear. Here we describe a framework for cortical synaptic plasticity termed the “Convallis rule”, mathematically derived from a principle of unsupervised learning via constrained optimization. Implementation of the rule caused a recurrent cortex-like network of simulated spiking neurons to develop rate representations of real-world speech stimuli, enabling classification by a downstream linear decoder. Applied to spike patterns used in in vitro plasticity experiments, the rule reproduced multiple results including and beyond STDP. However STDP alone produced poorer learning performance. The mathematical form of the rule is consistent with a dual coincidence detector mechanism that has been suggested by experiments in several synaptic classes of juvenile neocortex. Based on this confluence of normative, phenomenological, and mechanistic evidence, we suggest that the rule may approximate a fundamental computational principle of the neocortex. PMID:24204224
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.
Synaptic Ensemble Underlying the Selection and Consolidation of Neuronal Circuits during Learning.
Hoshiba, Yoshio; Wada, Takeyoshi; Hayashi-Takagi, Akiko
2017-01-01
Memories are crucial to the cognitive essence of who we are as human beings. Accumulating evidence has suggested that memories are stored as a subset of neurons that probably fire together in the same ensemble. Such formation of cell ensembles must meet contradictory requirements of being plastic and responsive during learning, but also stable in order to maintain the memory. Although synaptic potentiation is presumed to be the cellular substrate for this process, the link between the two remains correlational. With the application of the latest optogenetic tools, it has been possible to collect direct evidence of the contributions of synaptic potentiation in the formation and consolidation of cell ensemble in a learning task specific manner. In this review, we summarize the current view of the causative role of synaptic plasticity as the cellular mechanism underlying the encoding of memory and recalling of learned memories. In particular, we will be focusing on the latest optoprobe developed for the visualization of such "synaptic ensembles." We further discuss how a new synaptic ensemble could contribute to the formation of cell ensembles during learning and memory. With the development and application of novel research tools in the future, studies on synaptic ensembles will pioneer new discoveries, eventually leading to a comprehensive understanding of how the brain works.
NASA Astrophysics Data System (ADS)
La Barbera, Selina; Vincent, Adrien F.; Vuillaume, Dominique; Querlioz, Damien; Alibart, Fabien
2016-12-01
Bio-inspired computing represents today a major challenge at different levels ranging from material science for the design of innovative devices and circuits to computer science for the understanding of the key features required for processing of natural data. In this paper, we propose a detail analysis of resistive switching dynamics in electrochemical metallization cells for synaptic plasticity implementation. We show how filament stability associated to joule effect during switching can be used to emulate key synaptic features such as short term to long term plasticity transition and spike timing dependent plasticity. Furthermore, an interplay between these different synaptic features is demonstrated for object motion detection in a spike-based neuromorphic circuit. System level simulation presents robust learning and promising synaptic operation paving the way to complex bio-inspired computing systems composed of innovative memory devices.
Dopamine Promotes Motor Cortex Plasticity and Motor Skill Learning via PLC Activation
Rioult-Pedotti, Mengia-Seraina; Pekanovic, Ana; Atiemo, Clement Osei; Marshall, John; Luft, Andreas Rüdiger
2015-01-01
Dopaminergic neurons in the ventral tegmental area, the major midbrain nucleus projecting to the motor cortex, play a key role in motor skill learning and motor cortex synaptic plasticity. Dopamine D1 and D2 receptor antagonists exert parallel effects in the motor system: they impair motor skill learning and reduce long-term potentiation. Traditionally, D1 and D2 receptor modulate adenylyl cyclase activity and cyclic adenosine monophosphate accumulation in opposite directions via different G-proteins and bidirectionally modulate protein kinase A (PKA), leading to distinct physiological and behavioral effects. Here we show that D1 and D2 receptor activity influences motor skill acquisition and long term synaptic potentiation via phospholipase C (PLC) activation in rat primary motor cortex. Learning a new forelimb reaching task is severely impaired in the presence of PLC, but not PKA-inhibitor. Similarly, long term potentiation in motor cortex, a mechanism involved in motor skill learning, is reduced when PLC is inhibited but remains unaffected by the PKA inhibitor. Skill learning deficits and reduced synaptic plasticity caused by dopamine antagonists are prevented by co-administration of a PLC agonist. These results provide evidence for a role of intracellular PLC signaling in motor skill learning and associated cortical synaptic plasticity, challenging the traditional view of bidirectional modulation of PKA by D1 and D2 receptors. These findings reveal a novel and important action of dopamine in motor cortex that might be a future target for selective therapeutic interventions to support learning and recovery of movement resulting from injury and disease. PMID:25938462
Ketamine Protects Gamma Oscillations by Inhibiting Hippocampal LTD
Huang, Lanting; Yang, Xiu-Juan; Huang, Ying; Sun, Eve Y.
2016-01-01
NMDA receptors have been widely reported to be involved in the regulation of synaptic plasticity through effects on long-term potentiation (LTP) and long-term depression (LTD). LTP and LTD have been implicated in learning and memory processes. Besides synaptic plasticity, it is known that the phenomenon of gamma oscillations is critical in cognitive functions. Synaptic plasticity has been widely studied, however it is still not clear, to what degree synaptic plasticity regulates the oscillations of neuronal networks. Two NMDA receptor antagonists, ketamine and memantine, have been shown to regulate LTP and LTD, to promote cognitive functions, and have even been reported to bring therapeutic effects in major depression and Alzheimer’s disease respectively. These compounds allow us to investigate the putative interrelationship between network oscillations and synaptic plasticity and to learn more about the mechanisms of their therapeutic effects. In the present study, we have identified that ketamine and memantine could inhibit LTD, without impairing LTP in the CA1 region of mouse hippocampus, which may underlie the mechanism of these drugs’ therapeutic effects. Our results suggest that NMDA-induced LTD caused a marked loss in the gamma power, and pretreatment with 10 μM ketamine prevented the oscillatory loss via its inhibitory effect on LTD. Our study provides a new understanding of the role of NMDA receptors on hippocampal plasticity and oscillations. PMID:27467732
Excitement and synchronization of small-world neuronal networks with short-term synaptic plasticity.
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.
The roles of protein expression in synaptic plasticity and memory consolidation
Rosenberg, Tali; Gal-Ben-Ari, Shunit; Dieterich, Daniela C.; Kreutz, Michael R.; Ziv, Noam E.; Gundelfinger, Eckart D.; Rosenblum, Kobi
2014-01-01
The amount and availability of proteins are regulated by their synthesis, degradation, and transport. These processes can specifically, locally, and temporally regulate a protein or a population of proteins, thus affecting numerous biological processes in health and disease states. Accordingly, malfunction in the processes of protein turnover and localization underlies different neuronal diseases. However, as early as a century ago, it was recognized that there is a specific need for normal macromolecular synthesis in a specific fragment of the learning process, memory consolidation, which takes place minutes to hours following acquisition. Memory consolidation is the process by which fragile short-term memory is converted into stable long-term memory. It is accepted today that synaptic plasticity is a cellular mechanism of learning and memory processes. Interestingly, similar molecular mechanisms subserve both memory and synaptic plasticity consolidation. In this review, we survey the current view on the connection between memory consolidation processes and proteostasis, i.e., maintaining the protein contents at the neuron and the synapse. In addition, we describe the technical obstacles and possible new methods to determine neuronal proteostasis of synaptic function and better explain the process of memory and synaptic plasticity consolidation. PMID:25429258
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
Garrido, Jesús A.; Luque, Niceto R.; D'Angelo, Egidio; Ros, Eduardo
2013-01-01
Adaptable gain regulation is at the core of the forward controller operation performed by the cerebro-cerebellar loops and it allows the intensity of motor acts to be finely tuned in a predictive manner. In order to learn and store information about body-object dynamics and to generate an internal model of movement, the cerebellum is thought to employ long-term synaptic plasticity. LTD at the PF-PC synapse has classically been assumed to subserve this function (Marr, 1969). However, this plasticity alone cannot account for the broad dynamic ranges and time scales of cerebellar adaptation. We therefore tested the role of plasticity distributed over multiple synaptic sites (Hansel et al., 2001; Gao et al., 2012) by generating an analog cerebellar model embedded into a control loop connected to a robotic simulator. The robot used a three-joint arm and performed repetitive fast manipulations with different masses along an 8-shape trajectory. In accordance with biological evidence, the cerebellum model was endowed with both LTD and LTP at the PF-PC, MF-DCN and PC-DCN synapses. This resulted in a network scheme whose effectiveness was extended considerably compared to one including just PF-PC synaptic plasticity. Indeed, the system including distributed plasticity reliably self-adapted to manipulate different masses and to learn the arm-object dynamics over a time course that included fast learning and consolidation, along the lines of what has been observed in behavioral tests. In particular, PF-PC plasticity operated as a time correlator between the actual input state and the system error, while MF-DCN and PC-DCN plasticity played a key role in generating the gain controller. This model suggests that distributed synaptic plasticity allows generation of the complex learning properties of the cerebellum. The incorporation of further plasticity mechanisms and of spiking signal processing will allow this concept to be extended in a more realistic computational scenario. PMID:24130518
Sleep, Plasticity and Memory from Molecules to Whole-Brain Networks
Abel, Ted; Havekes, Robbert; Saletin, Jared M.; Walker, Matthew P.
2014-01-01
Despite the ubiquity of sleep across phylogeny, its function remains elusive. In this review, we consider one compelling candidate: brain plasticity associated with memory processing. Focusing largely on hippocampus-dependent memory in rodents and humans, we describe molecular, cellular, network, whole-brain and behavioral evidence establishing a role for sleep both in preparation for initial memory encoding, and in the subsequent offline consolidation ofmemory. Sleep and sleep deprivation bidirectionally alter molecular signaling pathways that regulate synaptic strength and control plasticity-related gene transcription and protein translation. At the cellular level, sleep deprivation impairs cellular excitability necessary for inducing synaptic potentiation and accelerates the decay of long-lasting forms of synaptic plasticity. In contrast, NREM and REM sleep enhance previously induced synaptic potentiation, although synaptic de-potentiation during sleep has also been observed. Beyond single cell dynamics, large-scale cell ensembles express coordinated replay of prior learning-related firing patterns during subsequent sleep. This occurs in the hippocampus, in the cortex, and between the hippocampus and cortex, commonly in association with specific NREM sleep oscillations. At the whole-brain level, somewhat analogous learning-associated hippocampal (re)activation during NREM sleep has been reported in humans. Moreover, the same cortical NREM oscillations associated with replay in rodents also promote human hippocampal memory consolidation, and this process can be manipulated using exogenous reactivation cues during sleep. Mirroring molecular findings in rodents, specific NREM sleep oscillations before encoding refresh human hippocampal learning capacity, while deprivation of sleep conversely impairs subsequent hippocampal activity and associated encoding. Together, these cross-descriptive level findings demonstrate that the unique neurobiology of sleep exert powerful effects on molecular, cellular and network mechanism of plasticity that govern both initial learning and subsequent long-term memory consolidation. PMID:24028961
A framework for plasticity implementation on the SpiNNaker neural architecture.
Galluppi, Francesco; Lagorce, Xavier; Stromatias, Evangelos; Pfeiffer, Michael; Plana, Luis A; Furber, Steve B; Benosman, Ryad B
2014-01-01
Many of the precise biological mechanisms of synaptic plasticity remain elusive, but simulations of neural networks have greatly enhanced our understanding of how specific global functions arise from the massively parallel computation of neurons and local Hebbian or spike-timing dependent plasticity rules. For simulating large portions of neural tissue, this has created an increasingly strong need for large scale simulations of plastic neural networks on special purpose hardware platforms, because synaptic transmissions and updates are badly matched to computing style supported by current architectures. Because of the great diversity of biological plasticity phenomena and the corresponding diversity of models, there is a great need for testing various hypotheses about plasticity before committing to one hardware implementation. Here we present a novel framework for investigating different plasticity approaches on the SpiNNaker distributed digital neural simulation platform. The key innovation of the proposed architecture is to exploit the reconfigurability of the ARM processors inside SpiNNaker, dedicating a subset of them exclusively to process synaptic plasticity updates, while the rest perform the usual neural and synaptic simulations. We demonstrate the flexibility of the proposed approach by showing the implementation of a variety of spike- and rate-based learning rules, including standard Spike-Timing dependent plasticity (STDP), voltage-dependent STDP, and the rate-based BCM rule. We analyze their performance and validate them by running classical learning experiments in real time on a 4-chip SpiNNaker board. The result is an efficient, modular, flexible and scalable framework, which provides a valuable tool for the fast and easy exploration of learning models of very different kinds on the parallel and reconfigurable SpiNNaker system.
A framework for plasticity implementation on the SpiNNaker neural architecture
Galluppi, Francesco; Lagorce, Xavier; Stromatias, Evangelos; Pfeiffer, Michael; Plana, Luis A.; Furber, Steve B.; Benosman, Ryad B.
2015-01-01
Many of the precise biological mechanisms of synaptic plasticity remain elusive, but simulations of neural networks have greatly enhanced our understanding of how specific global functions arise from the massively parallel computation of neurons and local Hebbian or spike-timing dependent plasticity rules. For simulating large portions of neural tissue, this has created an increasingly strong need for large scale simulations of plastic neural networks on special purpose hardware platforms, because synaptic transmissions and updates are badly matched to computing style supported by current architectures. Because of the great diversity of biological plasticity phenomena and the corresponding diversity of models, there is a great need for testing various hypotheses about plasticity before committing to one hardware implementation. Here we present a novel framework for investigating different plasticity approaches on the SpiNNaker distributed digital neural simulation platform. The key innovation of the proposed architecture is to exploit the reconfigurability of the ARM processors inside SpiNNaker, dedicating a subset of them exclusively to process synaptic plasticity updates, while the rest perform the usual neural and synaptic simulations. We demonstrate the flexibility of the proposed approach by showing the implementation of a variety of spike- and rate-based learning rules, including standard Spike-Timing dependent plasticity (STDP), voltage-dependent STDP, and the rate-based BCM rule. We analyze their performance and validate them by running classical learning experiments in real time on a 4-chip SpiNNaker board. The result is an efficient, modular, flexible and scalable framework, which provides a valuable tool for the fast and easy exploration of learning models of very different kinds on the parallel and reconfigurable SpiNNaker system. PMID:25653580
Havekes, Robbert; Canton, David A.; Park, Alan J.; Huang, Ted; Nie, Ting; Day, Jonathan P.; Guercio, Leonardo A.; Grimes, Quinn; Luczak, Vincent; Gelman, Irwin H.; Baillie, George S.; Scott, John D.; Abel, Ted
2012-01-01
A kinase-anchoring proteins (AKAPs) organize compartmentalized pools of Protein Kinase A (PKA) to enable localized signaling events within neurons. However, it is unclear which of the many expressed AKAPs in neurons target PKA to signaling complexes important for long-lasting forms of synaptic plasticity and memory storage. In the forebrain, the anchoring protein gravin recruits a signaling complex containing PKA, PKC, calmodulin, and PDE4D to the β2-adrenergic receptor. Here, we show that mice lacking the α-isoform of gravin have deficits in PKA-dependent long-lasting forms of hippocampal synaptic plasticity including β2-adrenergic receptor-mediated plasticity, and selective impairments of long-term memory storage. Further, both hippocampal β2-adrenergic receptor phosphorylation by PKA, and learning-induced activation of ERK, are attenuated in the CA1 region of the hippocampus in mice lacking gravin-α. We conclude that gravin compartmentalizes a significant pool of PKA that regulates learning-induced β2-adrenergic receptor signaling and ERK activation in the hippocampus in vivo, organizing molecular interactions between glutamatergic and noradrenergic signaling pathways for long-lasting synaptic plasticity, and memory storage. PMID:23238728
Spike Train Auto-Structure Impacts Post-Synaptic Firing and Timing-Based Plasticity
Scheller, Bertram; Castellano, Marta; Vicente, Raul; Pipa, Gordon
2011-01-01
Cortical neurons are typically driven by several thousand synapses. The precise spatiotemporal pattern formed by these inputs can modulate the response of a post-synaptic cell. In this work, we explore how the temporal structure of pre-synaptic inhibitory and excitatory inputs impact the post-synaptic firing of a conductance-based integrate and fire neuron. Both the excitatory and inhibitory input was modeled by renewal gamma processes with varying shape factors for modeling regular and temporally random Poisson activity. We demonstrate that the temporal structure of mutually independent inputs affects the post-synaptic firing, while the strength of the effect depends on the firing rates of both the excitatory and inhibitory inputs. In a second step, we explore the effect of temporal structure of mutually independent inputs on a simple version of Hebbian learning, i.e., hard bound spike-timing-dependent plasticity. We explore both the equilibrium weight distribution and the speed of the transient weight dynamics for different mutually independent gamma processes. We find that both the equilibrium distribution of the synaptic weights and the speed of synaptic changes are modulated by the temporal structure of the input. Finally, we highlight that the sensitivity of both the post-synaptic firing as well as the spike-timing-dependent plasticity on the auto-structure of the input of a neuron could be used to modulate the learning rate of synaptic modification. PMID:22203800
Reumann, Rebecca; Vierk, Ricardo; Zhou, Lepu; Gries, Frederice; Kraus, Vanessa; Mienert, Julia; Romswinkel, Eva; Morellini, Fabio; Ferrer, Isidre; Nicolini, Chiara; Fahnestock, Margaret; Rune, Gabriele; Glatzel, Markus; Galliciotti, Giovanna
2017-01-01
The serine protease inhibitor neuroserpin regulates the activity of tissue-type plasminogen activator (tPA) in the nervous system. Neuroserpin expression is particularly prominent at late stages of neuronal development in most regions of the central nervous system (CNS), whereas it is restricted to regions related to learning and memory in the adult brain. The physiological expression pattern of neuroserpin, its high degree of colocalization with tPA within the CNS, together with its dysregulation in neuropsychiatric disorders, suggest a role in formation and refinement of synapses. In fact, studies in cell culture and mice point to a role for neuroserpin in dendritic branching, spine morphology, and modulation of behavior. In this study, we investigated the physiological role of neuroserpin in the regulation of synaptic density, synaptic plasticity, and behavior in neuroserpin-deficient mice. In the absence of neuroserpin, mice show a significant decrease in spine-synapse density in the CA1 region of the hippocampus, while expression of the key postsynaptic scaffold protein PSD-95 is increased in this region. Neuroserpin-deficient mice show decreased synaptic potentiation, as indicated by reduced long-term potentiation (LTP), whereas presynaptic paired-pulse facilitation (PPF) is unaffected. Consistent with altered synaptic plasticity, neuroserpin-deficient mice exhibit cognitive and sociability deficits in behavioral assays. However, although synaptic dysfunction is implicated in neuropsychiatric disorders, we do not detect alterations in expression of neuroserpin in fusiform gyrus of autism patients or in dorsolateral prefrontal cortex of schizophrenia patients. Our results identify neuroserpin as a modulator of synaptic plasticity, and point to a role for neuroserpin in learning and memory. PMID:29142062
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
Loss of Cdc42 leads to defects in synaptic plasticity and remote memory recall.
Kim, Il Hwan; Wang, Hong; Soderling, Scott H; Yasuda, Ryohei
2014-07-08
Cdc42 is a signaling protein important for reorganization of actin cytoskeleton and morphogenesis of cells. However, the functional role of Cdc42 in synaptic plasticity and in behaviors such as learning and memory are not well understood. Here we report that postnatal forebrain deletion of Cdc42 leads to deficits in synaptic plasticity and in remote memory recall using conditional knockout of Cdc42. We found that deletion of Cdc42 impaired LTP in the Schaffer collateral synapses and postsynaptic structural plasticity of dendritic spines in CA1 pyramidal neurons in the hippocampus. Additionally, loss of Cdc42 did not affect memory acquisition, but instead significantly impaired remote memory recall. Together these results indicate that the postnatal functions of Cdc42 may be crucial for the synaptic plasticity in hippocampal neurons, which contribute to the capacity for remote memory recall.
Lack of Pannexin 1 Alters Synaptic GluN2 Subunit Composition and Spatial Reversal Learning in Mice.
Gajardo, Ivana; Salazar, Claudia S; Lopez-Espíndola, Daniela; Estay, Carolina; Flores-Muñoz, Carolina; Elgueta, Claudio; Gonzalez-Jamett, Arlek M; Martínez, Agustín D; Muñoz, Pablo; Ardiles, Álvaro O
2018-01-01
Long-term potentiation (LTP) and long-term depression (LTD) are two forms of synaptic plasticity that have been considered as the cellular substrate of memory formation. Although LTP has received considerable more attention, recent evidences indicate that LTD plays also important roles in the acquisition and storage of novel information in the brain. Pannexin 1 (Panx1) is a membrane protein that forms non-selective channels which have been shown to modulate the induction of hippocampal synaptic plasticity. Animals lacking Panx1 or blockade of Pannexin 1 channels precludes the induction of LTD and facilitates LTP. To evaluate if the absence of Panx1 also affects the acquisition of rapidly changing information we trained Panx1 knockout (KO) mice and wild type (WT) littermates in a visual and hidden version of the Morris water maze (MWM). We found that KO mice find the hidden platform similarly although slightly quicker than WT animals, nonetheless, when the hidden platform was located in the opposite quadrant (OQ) to the previous learned location, KO mice spent significantly more time in the previous quadrant than in the new location indicating that the absence of Panx1 affects the reversion of a previously acquired spatial memory. Consistently, we observed changes in the content of synaptic proteins critical to LTD, such as GluN2 subunits of N-methyl-D-aspartate receptors (NMDARs), which changed their contribution to synaptic plasticity in conditions of Panx1 ablation. Our findings give further support to the role of Panx1 channels on the modulation of synaptic plasticity induction, learning and memory processes.
Dynamical model of long-term synaptic plasticity
Abarbanel, Henry D. I.; Huerta, R.; Rabinovich, M. I.
2002-01-01
Long-term synaptic plasticity leading to enhancement in synaptic efficacy (long-term potentiation, LTP) or decrease in synaptic efficacy (long-term depression, LTD) is widely regarded as underlying learning and memory in nervous systems. LTP and LTD at excitatory neuronal synapses are observed to be induced by precise timing of pre- and postsynaptic events. Modification of synaptic transmission in long-term plasticity is a complex process involving many pathways; for example, it is also known that both forms of synaptic plasticity can be induced by various time courses of Ca2+ introduction into the postsynaptic cell. We present a phenomenological description of a two-component process for synaptic plasticity. Our dynamical model reproduces the spike time-dependent plasticity of excitatory synapses as a function of relative timing between pre- and postsynaptic events, as observed in recent experiments. The model accounts for LTP and LTD when the postsynaptic cell is voltage clamped and depolarized (LTP) or hyperpolarized (LTD) and no postsynaptic action potentials are evoked. We are also able to connect our model with the Bienenstock, Cooper, and Munro rule. We give model predictions for changes in synaptic strength when periodic spike trains of varying frequency and Poisson distributed spike trains with varying average frequency are presented pre- and postsynaptically. When the frequency of spike presentation exceeds ≈30–40 Hz, only LTP is induced. PMID:12114531
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.
Potjans, Wiebke; Morrison, Abigail; Diesmann, Markus
2010-01-01
A major puzzle in the field of computational neuroscience is how to relate system-level learning in higher organisms to synaptic plasticity. Recently, plasticity rules depending not only on pre- and post-synaptic activity but also on a third, non-local neuromodulatory signal have emerged as key candidates to bridge the gap between the macroscopic and the microscopic level of learning. Crucial insights into this topic are expected to be gained from simulations of neural systems, as these allow the simultaneous study of the multiple spatial and temporal scales that are involved in the problem. In particular, synaptic plasticity can be studied during the whole learning process, i.e., on a time scale of minutes to hours and across multiple brain areas. Implementing neuromodulated plasticity in large-scale network simulations where the neuromodulatory signal is dynamically generated by the network itself is challenging, because the network structure is commonly defined purely by the connectivity graph without explicit reference to the embedding of the nodes in physical space. Furthermore, the simulation of networks with realistic connectivity entails the use of distributed computing. A neuromodulated synapse must therefore be informed in an efficient way about the neuromodulatory signal, which is typically generated by a population of neurons located on different machines than either the pre- or post-synaptic neuron. Here, we develop a general framework to solve the problem of implementing neuromodulated plasticity in a time-driven distributed simulation, without reference to a particular implementation language, neuromodulator, or neuromodulated plasticity mechanism. We implement our framework in the simulator NEST and demonstrate excellent scaling up to 1024 processors for simulations of a recurrent network incorporating neuromodulated spike-timing dependent plasticity. PMID:21151370
Hagena, Hardy; Hansen, Niels; Manahan-Vaughan, Denise
2016-01-01
Noradrenaline (NA) is a key neuromodulator for the regulation of behavioral state and cognition. It supports learning by increasing arousal and vigilance, whereby new experiences are “earmarked” for encoding. Within the hippocampus, experience-dependent information storage occurs by means of synaptic plasticity. Furthermore, novel spatial, contextual, or associative learning drives changes in synaptic strength, reflected by the strengthening of long-term potentiation (LTP) or long-term depression (LTD). NA acting on β-adrenergic receptors (β-AR) is a key determinant as to whether new experiences result in persistent hippocampal synaptic plasticity. This can even dictate the direction of change of synaptic strength. The different hippocampal subfields play different roles in encoding components of a spatial representation through LTP and LTD. Strikingly, the sensitivity of synaptic plasticity in these subfields to β-adrenergic control is very distinct (dentate gyrus > CA3 > CA1). Moreover, NA released from the locus coeruleus that acts on β-AR leads to hippocampal LTD and an enhancement of LTD-related memory processing. We propose that NA acting on hippocampal β-AR, that is graded according to the novelty or saliency of the experience, determines the content and persistency of synaptic information storage in the hippocampal subfields and therefore of spatial memories. PMID:26804338
ERIC Educational Resources Information Center
Nagy, Vanja; Bozdagi, Ozlem; Huntley, George W.
2007-01-01
Matrix metalloproteinases (MMPs) are a family of extracellularly acting proteolytic enzymes with well-recognized roles in plasticity and remodeling of synaptic circuits during brain development and following brain injury. However, it is now becoming increasingly apparent that MMPs also function in normal, nonpathological synaptic plasticity of the…
Long-Term Exercise Is Needed to Enhance Synaptic Plasticity in the Hippocampus
ERIC Educational Resources Information Center
Patten, Anna R.; Sickmann, Helle; Hryciw, Brett N.; Kucharsky, Tessa; Parton, Roberta; Kernick, Aimee; Christie, Brian R.
2013-01-01
Exercise can have many benefits for the body, but it also benefits the brain by increasing neurogenesis, synaptic plasticity, and performance on learning and memory tasks. The period of exercise needed to realize the structural and functional benefits for the brain have not been well delineated, and previous studies have used periods of exercise…
Dynamic DNA Methylation Controls Glutamate Receptor Trafficking and Synaptic Scaling
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
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.
Synaptic electronics: materials, devices and applications.
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.
Cerebellar Plasticity and Motor Learning Deficits in a Copy Number Variation Mouse Model of Autism
Piochon, Claire; Kloth, Alexander D; Grasselli, Giorgio; Titley, Heather K; Nakayama, Hisako; Hashimoto, Kouichi; Wan, Vivian; Simmons, Dana H; Eissa, Tahra; Nakatani, Jin; Cherskov, Adriana; Miyazaki, Taisuke; Watanabe, Masahiko; Takumi, Toru; Kano, Masanobu; Wang, Samuel S-H; Hansel, Christian
2014-01-01
A common feature of autism spectrum disorder (ASD) is the impairment of motor control and learning, occurring in a majority of children with autism, consistent with perturbation in cerebellar function. Here we report alterations in motor behavior and cerebellar synaptic plasticity in a mouse model (patDp/+) for the human 15q11-13 duplication, one of the most frequently observed genetic aberrations in autism. These mice show ASD-resembling social behavior deficits. We find that in patDp/+ mice delay eyeblink conditioning—a form of cerebellum-dependent motor learning—is impaired, and observe deregulation of a putative cellular mechanism for motor learning, long-term depression (LTD) at parallel fiber-Purkinje cell synapses. Moreover, developmental elimination of surplus climbing fibers—a model for activity-dependent synaptic pruning—is impaired. These findings point to deficits in synaptic plasticity and pruning as potential causes for motor problems and abnormal circuit development in autism. PMID:25418414
Synaptic and nonsynaptic plasticity approximating probabilistic inference
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
Asymmetry of Neuronal Combinatorial Codes Arises from Minimizing Synaptic Weight Change.
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.
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.
An Imperfect Dopaminergic Error Signal Can Drive Temporal-Difference Learning
Potjans, Wiebke; Diesmann, Markus; Morrison, Abigail
2011-01-01
An open problem in the field of computational neuroscience is how to link synaptic plasticity to system-level learning. A promising framework in this context is temporal-difference (TD) learning. Experimental evidence that supports the hypothesis that the mammalian brain performs temporal-difference learning includes the resemblance of the phasic activity of the midbrain dopaminergic neurons to the TD error and the discovery that cortico-striatal synaptic plasticity is modulated by dopamine. However, as the phasic dopaminergic signal does not reproduce all the properties of the theoretical TD error, it is unclear whether it is capable of driving behavior adaptation in complex tasks. Here, we present a spiking temporal-difference learning model based on the actor-critic architecture. The model dynamically generates a dopaminergic signal with realistic firing rates and exploits this signal to modulate the plasticity of synapses as a third factor. The predictions of our proposed plasticity dynamics are in good agreement with experimental results with respect to dopamine, pre- and post-synaptic activity. An analytical mapping from the parameters of our proposed plasticity dynamics to those of the classical discrete-time TD algorithm reveals that the biological constraints of the dopaminergic signal entail a modified TD algorithm with self-adapting learning parameters and an adapting offset. We show that the neuronal network is able to learn a task with sparse positive rewards as fast as the corresponding classical discrete-time TD algorithm. However, the performance of the neuronal network is impaired with respect to the traditional algorithm on a task with both positive and negative rewards and breaks down entirely on a task with purely negative rewards. Our model demonstrates that the asymmetry of a realistic dopaminergic signal enables TD learning when learning is driven by positive rewards but not when driven by negative rewards. PMID:21589888
The Roles of Cortical Slow Waves in Synaptic Plasticity and Memory Consolidation.
Miyamoto, Daisuke; Hirai, Daichi; Murayama, Masanori
2017-01-01
Sleep plays important roles in sensory and motor memory consolidation. Sleep oscillations, reflecting neural population activity, involve the reactivation of learning-related neurons and regulate synaptic strength and, thereby affect memory consolidation. Among sleep oscillations, slow waves (0.5-4 Hz) are closely associated with memory consolidation. For example, slow-wave power is regulated in an experience-dependent manner and correlates with acquired memory. Furthermore, manipulating slow waves can enhance or impair memory consolidation. During slow wave sleep, inter-areal interactions between the cortex and hippocampus (HC) have been proposed to consolidate declarative memory; however, interactions for non-declarative (HC-independent) memory remain largely uninvestigated. We recently showed that the directional influence in a slow-wave range through a top-down cortical long-range circuit is involved in the consolidation of non-declarative memory. At the synaptic level, the average cortical synaptic strength is known to be potentiated during wakefulness and depressed during sleep. Moreover, learning causes plasticity in a subset of synapses, allocating memory to them. Sleep may help to differentiate synaptic strength between allocated and non-allocated synapses (i.e., improving the signal-to-noise ratio, which may facilitate memory consolidation). Herein, we offer perspectives on inter-areal interactions and synaptic plasticity for memory consolidation during sleep.
The Roles of Cortical Slow Waves in Synaptic Plasticity and Memory Consolidation
Miyamoto, Daisuke; Hirai, Daichi; Murayama, Masanori
2017-01-01
Sleep plays important roles in sensory and motor memory consolidation. Sleep oscillations, reflecting neural population activity, involve the reactivation of learning-related neurons and regulate synaptic strength and, thereby affect memory consolidation. Among sleep oscillations, slow waves (0.5–4 Hz) are closely associated with memory consolidation. For example, slow-wave power is regulated in an experience-dependent manner and correlates with acquired memory. Furthermore, manipulating slow waves can enhance or impair memory consolidation. During slow wave sleep, inter-areal interactions between the cortex and hippocampus (HC) have been proposed to consolidate declarative memory; however, interactions for non-declarative (HC-independent) memory remain largely uninvestigated. We recently showed that the directional influence in a slow-wave range through a top-down cortical long-range circuit is involved in the consolidation of non-declarative memory. At the synaptic level, the average cortical synaptic strength is known to be potentiated during wakefulness and depressed during sleep. Moreover, learning causes plasticity in a subset of synapses, allocating memory to them. Sleep may help to differentiate synaptic strength between allocated and non-allocated synapses (i.e., improving the signal-to-noise ratio, which may facilitate memory consolidation). Herein, we offer perspectives on inter-areal interactions and synaptic plasticity for memory consolidation during sleep. PMID:29213231
Li, Yan; Wang, Guo-Dong; Wang, Ming-Shan; Irwin, David M; Wu, Dong-Dong; Zhang, Ya-Ping
2014-11-05
Dogs shared a much closer relationship with humans than any other domesticated animals, probably due to their unique social cognitive capabilities, which were hypothesized to be a by-product of selection for tameness toward humans. Here, we demonstrate that genes involved in glutamate metabolism, which account partially for fear response, indeed show the greatest population differentiation by whole-genome comparison of dogs and wolves. However, the changing direction of their expression supports a role in increasing excitatory synaptic plasticity in dogs rather than reducing fear response. Because synaptic plasticity are widely believed to be cellular correlates of learning and memory, this change may alter the learning and memory abilities of ancient scavenging wolves, weaken the fear reaction toward humans, and prompt the initial interspecific contact. © The Author(s) 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.
Tononi, Giulio; Cirelli, Chiara
2014-01-01
Summary Sleep is universal, tightly regulated, and its loss impairs cognition. But why does the brain need to disconnect from the environment for hours every day? The synaptic homeostasis hypothesis (SHY) proposes that sleep is the price the brain pays for plasticity. During a waking episode, learning statistical regularities about the current environment requires strengthening connections throughout the brain. This increases cellular needs for energy and supplies, decreases signal-to-noise ratios, and saturates learning. During sleep, spontaneous activity renormalizes net synaptic strength and restores cellular homeostasis. Activity-dependent down-selection of synapses can also explain the benefits of sleep on memory acquisition, consolidation, and integration. This happens through the off-line, comprehensive sampling of statistical regularities incorporated in neuronal circuits over a lifetime. This review considers the rationale and evidence for SHY and points to open issues related to sleep and plasticity. PMID:24411729
Tononi, Giulio; Cirelli, Chiara
2014-01-08
Sleep is universal, tightly regulated, and its loss impairs cognition. But why does the brain need to disconnect from the environment for hours every day? The synaptic homeostasis hypothesis (SHY) proposes that sleep is the price the brain pays for plasticity. During a waking episode, learning statistical regularities about the current environment requires strengthening connections throughout the brain. This increases cellular needs for energy and supplies, decreases signal-to-noise ratios, and saturates learning. During sleep, spontaneous activity renormalizes net synaptic strength and restores cellular homeostasis. Activity-dependent down-selection of synapses can also explain the benefits of sleep on memory acquisition, consolidation, and integration. This happens through the offline, comprehensive sampling of statistical regularities incorporated in neuronal circuits over a lifetime. This Perspective considers the rationale and evidence for SHY and points to open issues related to sleep and plasticity. Copyright © 2014 Elsevier Inc. All rights reserved.
Gorkiewicz, Tomasz; Balcerzyk, Marcin; Kaczmarek, Leszek; Knapska, Ewelina
2015-01-01
It has been shown that matrix metalloproteinase 9 (MMP-9) is required for synaptic plasticity, learning and memory. In particular, MMP-9 involvement in long-term potentiation (LTP, the model of synaptic plasticity) in the hippocampus and prefrontal cortex has previously been demonstrated. Recent data suggest the role of MMP-9 in amygdala-dependent learning and memory. Nothing is known, however, about its physiological correlates in the specific pathways in the amygdala. In the present study we show that LTP in the basal and central but not lateral amygdala (LA) is affected by MMP-9 knock-out. The MMP-9 dependency of LTP was confirmed in brain slices treated with a specific MMP-9 inhibitor. The results suggest that MMP-9 plays different roles in synaptic plasticity in different nuclei of the amygdala.
Acute and Chronic Effects of Ethanol on Learning-Related Synaptic Plasticity
Zorumski, Charles F.; Mennerick, Steven; Izumi, Yukitoshi
2014-01-01
Alcoholism is associated with acute and long-term cognitive dysfunction including memory impairment, resulting in substantial disability and cost to society. Thus, understanding how ethanol impairs cognition is essential for developing treatment strategies to dampen its adverse impact. Memory processing is thought to involve persistent, use-dependent changes in synaptic transmission, and ethanol alters the activity of multiple signaling molecules involved in synaptic processing, including modulation of the glutamate and gamma-aminobutyric acid (GABA) transmitter systems that mediate most fast excitatory and inhibitory transmission in the brain. Effects on glutamate and GABA receptors contribute to ethanol-induced changes in long-term potentiation (LTP) and long-term depression (LTD), forms of synaptic plasticity thought to underlie memory acquisition. In this paper, we review the effects of ethanol on learning-related forms of synaptic plasticity with emphasis on changes observed in the hippocampus, a brain region that is critical for encoding contextual and episodic memories. We also include studies in other brain regions as they pertain to altered cognitive and mental function. Comparison of effects in the hippocampus to other brain regions is instructive for understanding the complexities of ethanol’s acute and long-term pharmacological consequences. PMID:24447472
Loss of Cdc42 leads to defects in synaptic plasticity and remote memory recall
Kim, Il Hwan; Wang, Hong; Soderling, Scott H; Yasuda, Ryohei
2014-01-01
Cdc42 is a signaling protein important for reorganization of actin cytoskeleton and morphogenesis of cells. However, the functional role of Cdc42 in synaptic plasticity and in behaviors such as learning and memory are not well understood. Here we report that postnatal forebrain deletion of Cdc42 leads to deficits in synaptic plasticity and in remote memory recall using conditional knockout of Cdc42. We found that deletion of Cdc42 impaired LTP in the Schaffer collateral synapses and postsynaptic structural plasticity of dendritic spines in CA1 pyramidal neurons in the hippocampus. Additionally, loss of Cdc42 did not affect memory acquisition, but instead significantly impaired remote memory recall. Together these results indicate that the postnatal functions of Cdc42 may be crucial for the synaptic plasticity in hippocampal neurons, which contribute to the capacity for remote memory recall. DOI: http://dx.doi.org/10.7554/eLife.02839.001 PMID:25006034
Matrix metalloproteinase-9 involvement in the structural plasticity of dendritic spines
Stawarski, Michal; Stefaniuk, Marzena; Wlodarczyk, Jakub
2014-01-01
Dendritic spines are the locus for excitatory synaptic transmission in the brain and thus play a major role in neuronal plasticity. The ability to alter synaptic connections includes volumetric changes in dendritic spines that are driven by scaffolds created by the extracellular matrix (ECM). Here, we review the effects of the proteolytic activity of ECM proteases in physiological and pathological structural plasticity. We use matrix metalloproteinase-9 (MMP-9) as an example of an ECM modifier that has recently emerged as a key molecule in regulating the morphology and dysmorphology of dendritic spines that underlie synaptic plasticity and neurological disorders, respectively. We summarize the influence of MMP-9 on the dynamic remodeling of the ECM via the cleavage of extracellular substrates. We discuss its role in the formation, modification, and maintenance of dendritic spines in learning and memory. Finally, we review research that implicates MMP-9 in aberrant synaptic plasticity and spine dysmorphology in neurological disorders, with a focus on morphological abnormalities of dendritic protrusions that are associated with epilepsy. PMID:25071472
Drug-Induced Alterations of Endocannabinoid-Mediated Plasticity in Brain Reward Regions.
Zlebnik, Natalie E; Cheer, Joseph F
2016-10-05
The endocannabinoid (eCB) system has emerged as one of the most important mediators of physiological and pathological reward-related synaptic plasticity. eCBs are retrograde messengers that provide feedback inhibition, resulting in the suppression of neurotransmitter release at both excitatory and inhibitory synapses, and they serve a critical role in the spatiotemporal regulation of both short- and long-term synaptic plasticity that supports adaptive learning of reward-motivated behaviors. However, mechanisms of eCB-mediated synaptic plasticity in reward areas of the brain are impaired following exposure to drugs of abuse. Because of this, it is theorized that maladaptive eCB signaling may contribute to the development and maintenance of addiction-related behavior. Here we review various forms of eCB-mediated synaptic plasticity present in regions of the brain involved in reward and reinforcement and explore the potential physiological relevance of maladaptive eCB signaling to addiction vulnerability. Copyright © 2016 the authors 0270-6474/16/3610230-09$15.00/0.
Synaptic plasticity functions in an organic electrochemical transistor
NASA Astrophysics Data System (ADS)
Gkoupidenis, Paschalis; Schaefer, Nathan; Strakosas, Xenofon; Fairfield, Jessamyn A.; Malliaras, George G.
2015-12-01
Synaptic plasticity functions play a crucial role in the transmission of neural signals in the brain. Short-term plasticity is required for the transmission, encoding, and filtering of the neural signal, whereas long-term plasticity establishes more permanent changes in neural microcircuitry and thus underlies memory and learning. The realization of bioinspired circuits that can actually mimic signal processing in the brain demands the reproduction of both short- and long-term aspects of synaptic plasticity in a single device. Here, we demonstrate the implementation of neuromorphic functions similar to biological memory, such as short- to long-term memory transition, in non-volatile organic electrochemical transistors (OECTs). Depending on the training of the OECT, the device displays either short- or long-term plasticity, therefore, exhibiting non von Neumann characteristics with merged processing and storing functionalities. These results are a first step towards the implementation of organic-based neuromorphic circuits.
Neuromodulated Spike-Timing-Dependent Plasticity, and Theory of Three-Factor Learning Rules.
Frémaux, Nicolas; Gerstner, Wulfram
2015-01-01
Classical Hebbian learning puts the emphasis on joint pre- and postsynaptic activity, but neglects the potential role of neuromodulators. Since neuromodulators convey information about novelty or reward, the influence of neuromodulators on synaptic plasticity is useful not just for action learning in classical conditioning, but also to decide "when" to create new memories in response to a flow of sensory stimuli. In this review, we focus on timing requirements for pre- and postsynaptic activity in conjunction with one or several phasic neuromodulatory signals. While the emphasis of the text is on conceptual models and mathematical theories, we also discuss some experimental evidence for neuromodulation of Spike-Timing-Dependent Plasticity. We highlight the importance of synaptic mechanisms in bridging the temporal gap between sensory stimulation and neuromodulatory signals, and develop a framework for a class of neo-Hebbian three-factor learning rules that depend on presynaptic activity, postsynaptic variables as well as the influence of neuromodulators.
JIP1-Mediated JNK Activation Negatively Regulates Synaptic Plasticity and Spatial Memory.
Morel, Caroline; Sherrin, Tessi; Kennedy, Norman J; Forest, Kelly H; Avcioglu Barutcu, Seda; Robles, Michael; Carpenter-Hyland, Ezekiel; Alfulaij, Naghum; Standen, Claire L; Nichols, Robert A; Benveniste, Morris; Davis, Roger J; Todorovic, Cedomir
2018-04-11
The c-Jun N-terminal kinase (JNK) signal transduction pathway is implicated in learning and memory. Here, we examined the role of JNK activation mediated by the JNK-interacting protein 1 (JIP1) scaffold protein. We compared male wild-type mice with a mouse model harboring a point mutation in the Jip1 gene that selectively blocks JIP1-mediated JNK activation. These male mutant mice exhibited increased NMDAR currents, increased NMDAR-mediated gene expression, and a lower threshold for induction of hippocampal long-term potentiation. The JIP1 mutant mice also displayed improved hippocampus-dependent spatial memory and enhanced associative fear conditioning. These results were confirmed using a second JIP1 mutant mouse model that suppresses JNK activity. Together, these observations establish that JIP1-mediated JNK activation contributes to the regulation of hippocampus-dependent, NMDAR-mediated synaptic plasticity and learning. SIGNIFICANCE STATEMENT The results of this study demonstrate that c-Jun N-terminal kinase (JNK) activation induced by the JNK-interacting protein 1 (JIP1) scaffold protein negatively regulates the threshold for induction of long-term synaptic plasticity through the NMDA-type glutamate receptor. This change in plasticity threshold influences learning. Indeed, mice with defects in JIP1-mediated JNK activation display enhanced memory in hippocampus-dependent tasks, such as contextual fear conditioning and Morris water maze, indicating that JIP1-JNK constrains spatial memory. This study identifies JIP1-mediated JNK activation as a novel molecular pathway that negatively regulates NMDAR-dependent synaptic plasticity and memory. Copyright © 2018 the authors 0270-6474/18/383708-21$15.00/0.
Liu, Zhiqiang; Han, Jing; Jia, Lintao; Maillet, Jean-Christian; Bai, Guang; Xu, Lin; Jia, Zhengping; Zheng, Qiaohua; Zhang, Wandong; Monette, Robert; Merali, Zul; Zhu, Zhou; Wang, Wei; Ren, Wei; Zhang, Xia
2010-01-01
Drug addiction is an association of compulsive drug use with long-term associative learning/memory. Multiple forms of learning/memory are primarily subserved by activity- or experience-dependent synaptic long-term potentiation (LTP) and long-term depression (LTD). Recent studies suggest LTP expression in locally activated glutamate synapses onto dopamine neurons (local Glu-DA synapses) of the midbrain ventral tegmental area (VTA) following a single or chronic exposure to many drugs of abuse, whereas a single exposure to cannabinoid did not significantly affect synaptic plasticity at these synapses. It is unknown whether chronic exposure of cannabis (marijuana or cannabinoids), the most commonly used illicit drug worldwide, induce LTP or LTD at these synapses. More importantly, whether such alterations in VTA synaptic plasticity causatively contribute to drug addictive behavior has not previously been addressed. Here we show in rats that chronic cannabinoid exposure activates VTA cannabinoid CB1 receptors to induce transient neurotransmission depression at VTA local Glu-DA synapses through activation of NMDA receptors and subsequent endocytosis of AMPA receptor GluR2 subunits. A GluR2-derived peptide blocks cannabinoid-induced VTA synaptic depression and conditioned place preference, i.e., learning to associate drug exposure with environmental cues. These data not only provide the first evidence, to our knowledge, that NMDA receptor-dependent synaptic depression at VTA dopamine circuitry requires GluR2 endocytosis, but also suggest an essential contribution of such synaptic depression to cannabinoid-associated addictive learning, in addition to pointing to novel pharmacological strategies for the treatment of cannabis addiction. PMID:21187978
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
Neuron-glia metabolic coupling and plasticity.
Magistretti, Pierre J
2006-06-01
The coupling between synaptic activity and glucose utilization (neurometabolic coupling) is a central physiological principle of brain function that has provided the basis for 2-deoxyglucose-based functional imaging with positron emission tomography (PET). Astrocytes play a central role in neurometabolic coupling, and the basic mechanism involves glutamate-stimulated aerobic glycolysis; the sodium-coupled reuptake of glutamate by astrocytes and the ensuing activation of the Na-K-ATPase triggers glucose uptake and processing via glycolysis, resulting in the release of lactate from astrocytes. Lactate can then contribute to the activity-dependent fuelling of the neuronal energy demands associated with synaptic transmission. An operational model, the 'astrocyte-neuron lactate shuttle', is supported experimentally by a large body of evidence, which provides a molecular and cellular basis for interpreting data obtained from functional brain imaging studies. In addition, this neuron-glia metabolic coupling undergoes plastic adaptations in parallel with adaptive mechanisms that characterize synaptic plasticity. Thus, distinct subregions of the hippocampus are metabolically active at different time points during spatial learning tasks, suggesting that a type of metabolic plasticity, involving by definition neuron-glia coupling, occurs during learning. In addition, marked variations in the expression of genes involved in glial glycogen metabolism are observed during the sleep-wake cycle, with in particular a marked induction of expression of the gene encoding for protein targeting to glycogen (PTG) following sleep deprivation. These data suggest that glial metabolic plasticity is likely to be concomitant with synaptic plasticity.
Synaptic Mechanisms of Memory Consolidation during Sleep Slow Oscillations
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
NASA Astrophysics Data System (ADS)
Wang, Lai-Guo; Zhang, Wei; Chen, Yan; Cao, Yan-Qiang; Li, Ai-Dong; Wu, Di
2017-01-01
In this work, a kind of new memristor with the simple structure of Pt/HfOx/ZnOx/TiN was fabricated completely via combination of thermal-atomic layer deposition (TALD) and plasma-enhanced ALD (PEALD). The synaptic plasticity and learning behaviors of Pt/HfOx/ZnOx/TiN memristive system have been investigated deeply. Multilevel resistance states are obtained by varying the programming voltage amplitudes during the pulse cycling. The device conductance can be continuously increased or decreased from cycle to cycle with better endurance characteristics up to about 3 × 103 cycles. Several essential synaptic functions are simultaneously achieved in such a single double-layer of HfOx/ZnOx device, including nonlinear transmission properties, such as long-term plasticity (LTP), short-term plasticity (STP), and spike-timing-dependent plasticity. The transformation from STP to LTP induced by repetitive pulse stimulation is confirmed in Pt/HfOx/ZnOx/TiN memristive device. Above all, simple structure of Pt/HfOx/ZnOx/TiN by ALD technique is a kind of promising memristor device for applications in artificial neural network.
Cellular Mechanisms of Transcranial Direct Current Stimulation
2016-07-14
32 Section 3 Electrical stimulation accelerates and boosts the capacity for synaptic learning ...................... 50 Section 4...Section 3: tDCS is thought to boost the learning of tasks or therapy applied at the same time. We provide a cellular mechanism for this. Moreover, we...show that thus “boosting” is specific to the trained task. [Aim 2] Section 4: tDCS is though to boost learning by promoting synaptic plasticity. We
Monje, Francisco J; Kim, Eun-Jung; Pollak, Daniela D; Cabatic, Maureen; Li, Lin; Baston, Arthur; Lubec, Gert
2012-01-01
The focal adhesion kinase (FAK) is a non-receptor tyrosine kinase abundantly expressed in the mammalian brain and highly enriched in neuronal growth cones. Inhibitory and facilitatory activities of FAK on neuronal growth have been reported and its role in neuritic outgrowth remains controversial. Unlike other tyrosine kinases, such as the neurotrophin receptors regulating neuronal growth and plasticity, the relevance of FAK for learning and memory in vivo has not been clearly defined yet. A comprehensive study aimed at determining the role of FAK in neuronal growth, neurotransmitter release and synaptic plasticity in hippocampal neurons and in hippocampus-dependent learning and memory was therefore undertaken using the mouse model. Gain- and loss-of-function experiments indicated that FAK is a critical regulator of hippocampal cell morphology. FAK mediated neurotrophin-induced neuritic outgrowth and FAK inhibition affected both miniature excitatory postsynaptic potentials and activity-dependent hippocampal long-term potentiation prompting us to explore the possible role of FAK in spatial learning and memory in vivo. Our data indicate that FAK has a growth-promoting effect, is importantly involved in the regulation of the synaptic function and mediates in vivo hippocampus-dependent spatial learning and memory. Copyright © 2011 S. Karger AG, Basel.
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.
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.
Nanou, Evanthia; Lee, Amy; Catterall, William A
2018-05-02
Activity-dependent regulation controls the balance of synaptic excitation to inhibition in neural circuits, and disruption of this regulation impairs learning and memory and causes many neurological disorders. The molecular mechanisms underlying short-term synaptic plasticity are incompletely understood, and their role in inhibitory synapses remains uncertain. Here we show that regulation of voltage-gated calcium (Ca 2+ ) channel type 2.1 (Ca V 2.1) by neuronal Ca 2+ sensor (CaS) proteins controls synaptic plasticity and excitation/inhibition balance in a hippocampal circuit. Prevention of CaS protein regulation by introducing the IM-AA mutation in Ca V 2.1 channels in male and female mice impairs short-term synaptic facilitation at excitatory synapses of CA3 pyramidal neurons onto parvalbumin (PV)-expressing basket cells. In sharp contrast, the IM-AA mutation abolishes rapid synaptic depression in the inhibitory synapses of PV basket cells onto CA1 pyramidal neurons. These results show that CaS protein regulation of facilitation and inactivation of Ca V 2.1 channels controls the direction of short-term plasticity at these two synapses. Deletion of the CaS protein CaBP1/caldendrin also blocks rapid depression at PV-CA1 synapses, implicating its upregulation of inactivation of Ca V 2.1 channels in control of short-term synaptic plasticity at this inhibitory synapse. Studies of local-circuit function revealed reduced inhibition of CA1 pyramidal neurons by the disynaptic pathway from CA3 pyramidal cells via PV basket cells and greatly increased excitation/inhibition ratio of the direct excitatory input versus indirect inhibitory input from CA3 pyramidal neurons to CA1 pyramidal neurons. This striking defect in local-circuit function may contribute to the dramatic impairment of spatial learning and memory in IM-AA mice. SIGNIFICANCE STATEMENT Many forms of short-term synaptic plasticity in neuronal circuits rely on regulation of presynaptic voltage-gated Ca 2+ (Ca V ) channels. Regulation of Ca V 2.1 channels by neuronal calcium sensor (CaS) proteins controls short-term synaptic plasticity. Here we demonstrate a direct link between regulation of Ca V 2.1 channels and short-term synaptic plasticity in native hippocampal excitatory and inhibitory synapses. We also identify CaBP1/caldendrin as the calcium sensor interacting with Ca V 2.1 channels to mediate rapid synaptic depression in the inhibitory hippocampal synapses of parvalbumin-expressing basket cells to CA1 pyramidal cells. Disruption of this regulation causes altered short-term plasticity and impaired balance of hippocampal excitatory to inhibitory circuits. Copyright © 2018 the authors 0270-6474/18/384430-11$15.00/0.
A Cognitive Model Based on Neuromodulated Plasticity
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
MOLECULAR MECHANISMS OF FEAR LEARNING AND MEMORY
Johansen, Joshua P.; Cain, Christopher K.; Ostroff, Linnaea E.; LeDoux, Joseph E.
2011-01-01
Pavlovian fear conditioning is a useful behavioral paradigm for exploring the molecular mechanisms of learning and memory because a well-defined response to a specific environmental stimulus is produced through associative learning processes. Synaptic plasticity in the lateral nucleus of the amygdala (LA) underlies this form of associative learning. Here we summarize the molecular mechanisms that contribute to this synaptic plasticity in the context of auditory fear conditioning, the form of fear conditioning best understood at the molecular level. We discuss the neurotransmitter systems and signaling cascades that contribute to three phases of auditory fear conditioning: acquisition, consolidation, and reconsolidation. These studies suggest that multiple intracellular signaling pathways, including those triggered by activation of Hebbian processes and neuromodulatory receptors, interact to produce neural plasticity in the LA and behavioral fear conditioning. Together, this research illustrates the power of fear conditioning as a model system for characterizing the mechanisms of learning and memory in mammals, and potentially for understanding fear related disorders, such as PTSD and phobias. PMID:22036561
Spiking neuron network Helmholtz machine.
Sountsov, Pavel; Miller, Paul
2015-01-01
An increasing amount of behavioral and neurophysiological data suggests that the brain performs optimal (or near-optimal) probabilistic inference and learning during perception and other tasks. Although many machine learning algorithms exist that perform inference and learning in an optimal way, the complete description of how one of those algorithms (or a novel algorithm) can be implemented in the brain is currently incomplete. There have been many proposed solutions that address how neurons can perform optimal inference but the question of how synaptic plasticity can implement optimal learning is rarely addressed. This paper aims to unify the two fields of probabilistic inference and synaptic plasticity by using a neuronal network of realistic model spiking neurons to implement a well-studied computational model called the Helmholtz Machine. The Helmholtz Machine is amenable to neural implementation as the algorithm it uses to learn its parameters, called the wake-sleep algorithm, uses a local delta learning rule. Our spiking-neuron network implements both the delta rule and a small example of a Helmholtz machine. This neuronal network can learn an internal model of continuous-valued training data sets without supervision. The network can also perform inference on the learned internal models. We show how various biophysical features of the neural implementation constrain the parameters of the wake-sleep algorithm, such as the duration of the wake and sleep phases of learning and the minimal sample duration. We examine the deviations from optimal performance and tie them to the properties of the synaptic plasticity rule.
Spiking neuron network Helmholtz machine
Sountsov, Pavel; Miller, Paul
2015-01-01
An increasing amount of behavioral and neurophysiological data suggests that the brain performs optimal (or near-optimal) probabilistic inference and learning during perception and other tasks. Although many machine learning algorithms exist that perform inference and learning in an optimal way, the complete description of how one of those algorithms (or a novel algorithm) can be implemented in the brain is currently incomplete. There have been many proposed solutions that address how neurons can perform optimal inference but the question of how synaptic plasticity can implement optimal learning is rarely addressed. This paper aims to unify the two fields of probabilistic inference and synaptic plasticity by using a neuronal network of realistic model spiking neurons to implement a well-studied computational model called the Helmholtz Machine. The Helmholtz Machine is amenable to neural implementation as the algorithm it uses to learn its parameters, called the wake-sleep algorithm, uses a local delta learning rule. Our spiking-neuron network implements both the delta rule and a small example of a Helmholtz machine. This neuronal network can learn an internal model of continuous-valued training data sets without supervision. The network can also perform inference on the learned internal models. We show how various biophysical features of the neural implementation constrain the parameters of the wake-sleep algorithm, such as the duration of the wake and sleep phases of learning and the minimal sample duration. We examine the deviations from optimal performance and tie them to the properties of the synaptic plasticity rule. PMID:25954191
Weng, Feng-Ju; Garcia, Rodrigo I; Lutzu, Stefano; Alviña, Karina; Zhang, Yuxiang; Dushko, Margaret; Ku, Taeyun; Zemoura, Khaled; Rich, David; Garcia-Dominguez, Dario; Hung, Matthew; Yelhekar, Tushar D; Sørensen, Andreas Toft; Xu, Weifeng; Chung, Kwanghun; Castillo, Pablo E; Lin, Yingxi
2018-03-07
Synaptic connections between hippocampal mossy fibers (MFs) and CA3 pyramidal neurons are essential for contextual memory encoding, but the molecular mechanisms regulating MF-CA3 synapses during memory formation and the exact nature of this regulation are poorly understood. Here we report that the activity-dependent transcription factor Npas4 selectively regulates the structure and strength of MF-CA3 synapses by restricting the number of their functional synaptic contacts without affecting the other synaptic inputs onto CA3 pyramidal neurons. Using an activity-dependent reporter, we identified CA3 pyramidal cells that were activated by contextual learning and found that MF inputs on these cells were selectively strengthened. Deletion of Npas4 prevented both contextual memory formation and this learning-induced synaptic modification. We further show that Npas4 regulates MF-CA3 synapses by controlling the expression of the polo-like kinase Plk2. Thus, Npas4 is a critical regulator of experience-dependent, structural, and functional plasticity at MF-CA3 synapses during contextual memory formation. Copyright © 2018 Elsevier Inc. All rights reserved.
Feng, Jian; Zhou, Yu; Campbell, Susan L.; Le, Thuc; Li, En; Sweatt, J. David; Silva, Alcino J.; Fan, Guoping
2011-01-01
Dnmt1 and Dnmt3a, two major DNA methyltransferases, are expressed in postmitotic neurons, but their function in the central nervous system (CNS) is unclear. We generated conditional mutant mice that lack either Dnmt1, or Dnmt3a, or both exclusively in forebrain excitatory neurons and found only double knockout (DKO) mice exhibited abnormal hippocampal CA1 long-term plasticity and deficits of learning and memory. While no neuronal loss was found, the size of hippocampal neurons in DKO was smaller; furthermore, DKO neurons showed a deregulation of gene expression including class I MHC and Stat1 that are known to play a role in synaptic plasticity. In addition, we observed a significant decrease in DNA methylation in DKO neurons. We conclude that Dnmt1 and Dnmt3a are required for synaptic plasticity, learning and memory through their overlapping roles in maintaining DNA methylation and modulating neuronal gene expression in adult CNS neurons. PMID:20228804
Brzosko, Zuzanna; Zannone, Sara; Schultz, Wolfram
2017-01-01
Spike timing-dependent plasticity (STDP) is under neuromodulatory control, which is correlated with distinct behavioral states. Previously, we reported that dopamine, a reward signal, broadens the time window for synaptic potentiation and modulates the outcome of hippocampal STDP even when applied after the plasticity induction protocol (Brzosko et al., 2015). Here, we demonstrate that sequential neuromodulation of STDP by acetylcholine and dopamine offers an efficacious model of reward-based navigation. Specifically, our experimental data in mouse hippocampal slices show that acetylcholine biases STDP toward synaptic depression, whilst subsequent application of dopamine converts this depression into potentiation. Incorporating this bidirectional neuromodulation-enabled correlational synaptic learning rule into a computational model yields effective navigation toward changing reward locations, as in natural foraging behavior. Thus, temporally sequenced neuromodulation of STDP enables associations to be made between actions and outcomes and also provides a possible mechanism for aligning the time scales of cellular and behavioral learning. DOI: http://dx.doi.org/10.7554/eLife.27756.001 PMID:28691903
The penumbra of learning: a statistical theory of synaptic tagging and capture.
Gershman, Samuel J
2014-01-01
Learning in humans and animals is accompanied by a penumbra: Learning one task benefits from learning an unrelated task shortly before or after. At the cellular level, the penumbra of learning appears when weak potentiation of one synapse is amplified by strong potentiation of another synapse on the same neuron during a critical time window. Weak potentiation sets a molecular tag that enables the synapse to capture plasticity-related proteins synthesized in response to strong potentiation at another synapse. This paper describes a computational model which formalizes synaptic tagging and capture in terms of statistical learning mechanisms. According to this model, synaptic strength encodes a probabilistic inference about the dynamically changing association between pre- and post-synaptic firing rates. The rate of change is itself inferred, coupling together different synapses on the same neuron. When the inputs to one synapse change rapidly, the inferred rate of change increases, amplifying learning at other synapses.
Owen, Scott F; Berke, Joshua D; Kreitzer, Anatol C
2018-02-08
Fast-spiking interneurons (FSIs) are a prominent class of forebrain GABAergic cells implicated in two seemingly independent network functions: gain control and network plasticity. Little is known, however, about how these roles interact. Here, we use a combination of cell-type-specific ablation, optogenetics, electrophysiology, imaging, and behavior to describe a unified mechanism by which striatal FSIs control burst firing, calcium influx, and synaptic plasticity in neighboring medium spiny projection neurons (MSNs). In vivo silencing of FSIs increased bursting, calcium transients, and AMPA/NMDA ratios in MSNs. In a motor sequence task, FSI silencing increased the frequency of calcium transients but reduced the specificity with which transients aligned to individual task events. Consistent with this, ablation of FSIs disrupted the acquisition of striatum-dependent egocentric learning strategies. Together, our data support a model in which feedforward inhibition from FSIs temporally restricts MSN bursting and calcium-dependent synaptic plasticity to facilitate striatum-dependent sequence learning. Copyright © 2018 Elsevier Inc. All rights reserved.
Kassabov, Stefan R.; Choi, Yun-Beom; Karl, Kevin A.; Vishwasrao, Harshad D.; Bailey, Craig H.; Kandel, Eric R.
2014-01-01
Summary Neurotrophins control the development and adult plasticity of the vertebrate nervous system. Failure to identify invertebrate neurotrophin orthologs, however, has precluded studies in invertebrate models, limiting understanding of fundamental aspects of neurotrophin biology and function. We identified a neurotrophin (ApNT) and Trk receptor (ApTrk) in the mollusk Aplysia and find they play a central role in learning related synaptic plasticity. ApNT increases the magnitude and lowers the threshold for induction of long-term facilitation and initiates the growth of new synaptic varicosities at the monosynaptic connection between sensory and motor neurons of the gill-withdrawal reflex. Unlike vertebrate neurotrophins, ApNT has multiple coding exons and exerts distinct synaptic effects through differentially processed and secreted splice isoforms. Our findings demonstrate the existence of bona-fide neurotrophin signaling in invertebrates and reveal a novel, post-transcriptional mechanism, regulating neurotrophin processing and the release of pro- and mature neurotrophins which differentially modulate synaptic plasticity. PMID:23562154
Synaptic plasticity in sleep: learning, homeostasis, and disease
Wang, Gordon; Grone, Brian; Colas, Damien; Appelbaum, Lior; Mourrain, Philippe
2012-01-01
Sleep is a fundamental and evolutionarily conserved aspect of animal life. Recent studies have shed light on the role of sleep in synaptic plasticity. Demonstrations of memory replay and synapse homeostasis suggest that one essential role of sleep is in the consolidation and optimization of synaptic circuits to retain salient memory traces despite the noise of daily experience. Here, we review this recent evidence, and suggest that sleep creates a heightened state of plasticity, which may be essential for this optimization. Furthermore, we discuss how sleep deficits seen in diseases such as Alzheimer’s disease and autism spectrum disorders might not just reflect underlying circuit malfunction, but could also play a direct role in the progression of those disorders. PMID:21840068
Interplay between Short- and Long-Term Plasticity in Cell-Assembly Formation
Hiratani, Naoki; Fukai, Tomoki
2014-01-01
Various hippocampal and neocortical synapses of mammalian brain show both short-term plasticity and long-term plasticity, which are considered to underlie learning and memory by the brain. According to Hebb’s postulate, synaptic plasticity encodes memory traces of past experiences into cell assemblies in cortical circuits. However, it remains unclear how the various forms of long-term and short-term synaptic plasticity cooperatively create and reorganize such cell assemblies. Here, we investigate the mechanism in which the three forms of synaptic plasticity known in cortical circuits, i.e., spike-timing-dependent plasticity (STDP), short-term depression (STD) and homeostatic plasticity, cooperatively generate, retain and reorganize cell assemblies in a recurrent neuronal network model. We show that multiple cell assemblies generated by external stimuli can survive noisy spontaneous network activity for an adequate range of the strength of STD. Furthermore, our model predicts that a symmetric temporal window of STDP, such as observed in dopaminergic modulations on hippocampal neurons, is crucial for the retention and integration of multiple cell assemblies. These results may have implications for the understanding of cortical memory processes. PMID:25007209
Soulé, Jonathan; Penke, Zsuzsa; Kanhema, Tambudzai; Alme, Maria Nordheim; Laroche, Serge; Bramham, Clive R.
2008-01-01
Long-term recognition memory requires protein synthesis, but little is known about the coordinate regulation of specific genes. Here, we examined expression of the plasticity-associated immediate early genes (Arc, Zif268, and Narp) in the dentate gyrus following long-term object-place recognition learning in rats. RT-PCR analysis from dentate gyrus tissue collected shortly after training did not reveal learning-specific changes in Arc mRNA expression. In situ hybridization and immunohistochemistry were therefore used to assess possible sparse effects on gene expression. Learning about objects increased the density of granule cells expressing Arc, and to a lesser extent Narp, specifically in the dorsal blade of the dentate gyrus, while Zif268 expression was elevated across both blades. Thus, object-place recognition triggers rapid, blade-specific upregulation of plasticity-associated immediate early genes. Furthermore, Western blot analysis of dentate gyrus homogenates demonstrated concomitant upregulation of three postsynaptic density proteins (Arc, PSD-95, and α-CaMKII) with key roles in long-term synaptic plasticity and long-term memory. PMID:19190776
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.
Oscillations, Timing, Plasticity, and Learning in the Cerebellum.
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.
Super Resolution Imaging of Genetically Labeled Synapses in Drosophila Brain Tissue
Spühler, Isabelle A.; Conley, Gaurasundar M.; Scheffold, Frank; Sprecher, Simon G.
2016-01-01
Understanding synaptic connectivity and plasticity within brain circuits and their relationship to learning and behavior is a fundamental quest in neuroscience. Visualizing the fine details of synapses using optical microscopy remains however a major technical challenge. Super resolution microscopy opens the possibility to reveal molecular features of synapses beyond the diffraction limit. With direct stochastic optical reconstruction microscopy, dSTORM, we image synaptic proteins in the brain tissue of the fruit fly, Drosophila melanogaster. Super resolution imaging of brain tissue harbors difficulties due to light scattering and the density of signals. In order to reduce out of focus signal, we take advantage of the genetic tools available in the Drosophila and have fluorescently tagged synaptic proteins expressed in only a small number of neurons. These neurons form synapses within the calyx of the mushroom body, a distinct brain region involved in associative memory formation. Our results show that super resolution microscopy, in combination with genetically labeled synaptic proteins, is a powerful tool to investigate synapses in a quantitative fashion providing an entry point for studies on synaptic plasticity during learning and memory formation. PMID:27303270
Super Resolution Imaging of Genetically Labeled Synapses in Drosophila Brain Tissue.
Spühler, Isabelle A; Conley, Gaurasundar M; Scheffold, Frank; Sprecher, Simon G
2016-01-01
Understanding synaptic connectivity and plasticity within brain circuits and their relationship to learning and behavior is a fundamental quest in neuroscience. Visualizing the fine details of synapses using optical microscopy remains however a major technical challenge. Super resolution microscopy opens the possibility to reveal molecular features of synapses beyond the diffraction limit. With direct stochastic optical reconstruction microscopy, dSTORM, we image synaptic proteins in the brain tissue of the fruit fly, Drosophila melanogaster. Super resolution imaging of brain tissue harbors difficulties due to light scattering and the density of signals. In order to reduce out of focus signal, we take advantage of the genetic tools available in the Drosophila and have fluorescently tagged synaptic proteins expressed in only a small number of neurons. These neurons form synapses within the calyx of the mushroom body, a distinct brain region involved in associative memory formation. Our results show that super resolution microscopy, in combination with genetically labeled synaptic proteins, is a powerful tool to investigate synapses in a quantitative fashion providing an entry point for studies on synaptic plasticity during learning and memory formation.
Learning rules for spike timing-dependent plasticity depend on dendritic synapse location.
Letzkus, Johannes J; Kampa, Björn M; Stuart, Greg J
2006-10-11
Previous studies focusing on the temporal rules governing changes in synaptic strength during spike timing-dependent synaptic plasticity (STDP) have paid little attention to the fact that synaptic inputs are distributed across complex dendritic trees. During STDP, propagation of action potentials (APs) back to the site of synaptic input is thought to trigger plasticity. However, in pyramidal neurons, backpropagation of single APs is decremental, whereas high-frequency bursts lead to generation of distal dendritic calcium spikes. This raises the question whether STDP learning rules depend on synapse location and firing mode. Here, we investigate this issue at synapses between layer 2/3 and layer 5 pyramidal neurons in somatosensory cortex. We find that low-frequency pairing of single APs at positive times leads to a distance-dependent shift to long-term depression (LTD) at distal inputs. At proximal sites, this LTD could be converted to long-term potentiation (LTP) by dendritic depolarizations suprathreshold for BAC-firing or by high-frequency AP bursts. During AP bursts, we observed a progressive, distance-dependent shift in the timing requirements for induction of LTP and LTD, such that distal synapses display novel timing rules: they potentiate when inputs are activated after burst onset (negative timing) but depress when activated before burst onset (positive timing). These findings could be explained by distance-dependent differences in the underlying dendritic voltage waveforms driving NMDA receptor activation during STDP induction. Our results suggest that synapse location within the dendritic tree is a crucial determinant of STDP, and that synapses undergo plasticity according to local rather than global learning rules.
Neuromodulated Spike-Timing-Dependent Plasticity, and Theory of Three-Factor Learning Rules
Frémaux, Nicolas; Gerstner, Wulfram
2016-01-01
Classical Hebbian learning puts the emphasis on joint pre- and postsynaptic activity, but neglects the potential role of neuromodulators. Since neuromodulators convey information about novelty or reward, the influence of neuromodulators on synaptic plasticity is useful not just for action learning in classical conditioning, but also to decide “when” to create new memories in response to a flow of sensory stimuli. In this review, we focus on timing requirements for pre- and postsynaptic activity in conjunction with one or several phasic neuromodulatory signals. While the emphasis of the text is on conceptual models and mathematical theories, we also discuss some experimental evidence for neuromodulation of Spike-Timing-Dependent Plasticity. We highlight the importance of synaptic mechanisms in bridging the temporal gap between sensory stimulation and neuromodulatory signals, and develop a framework for a class of neo-Hebbian three-factor learning rules that depend on presynaptic activity, postsynaptic variables as well as the influence of neuromodulators. PMID:26834568
Lim, Chae-Seok; Hoang, Elizabeth T; Viar, Kenneth E; Stornetta, Ruth L; Scott, Michael M; Zhu, J Julius
2014-02-01
Fragile X syndrome, caused by the loss of Fmr1 gene function, is the most common form of inherited mental retardation, with no effective treatment. Using a tractable animal model, we investigated mechanisms of action of a few FDA-approved psychoactive drugs that modestly benefit the cognitive performance in fragile X patients. Here we report that compounds activating serotonin (5HT) subtype 2B receptors (5HT2B-Rs) or dopamine (DA) subtype 1-like receptors (D1-Rs) and/or those inhibiting 5HT2A-Rs or D2-Rs moderately enhance Ras-PI3K/PKB signaling input, GluA1-dependent synaptic plasticity, and learning in Fmr1 knockout mice. Unexpectedly, combinations of these 5HT and DA compounds at low doses synergistically stimulate Ras-PI3K/PKB signal transduction and GluA1-dependent synaptic plasticity and remarkably restore normal learning in Fmr1 knockout mice without causing anxiety-related side effects. These findings suggest that properly dosed and combined FDA-approved psychoactive drugs may effectively treat the cognitive impairment associated with fragile X syndrome.
Baez, María Verónica; Cercato, Magalí Cecilia; Jerusalinsky, Diana Alicia
2018-01-01
NMDA ionotropic glutamate receptors (NMDARs) are crucial in activity-dependent synaptic changes and in learning and memory. NMDARs are composed of two GluN1 essential subunits and two regulatory subunits which define their pharmacological and physiological profile. In CNS structures involved in cognitive functions as the hippocampus and prefrontal cortex, GluN2A and GluN2B are major regulatory subunits; their expression is dynamic and tightly regulated, but little is known about specific changes after plasticity induction or memory acquisition. Data strongly suggest that following appropriate stimulation, there is a rapid increase in surface GluN2A-NMDAR at the postsynapses, attributed to lateral receptor mobilization from adjacent locations. Whenever synaptic plasticity is induced or memory is consolidated, more GluN2A-NMDARs are assembled likely using GluN2A from a local translation and GluN1 from local ER. Later on, NMDARs are mobilized from other pools, and there are de novo syntheses at the neuron soma. Changes in GluN1 or NMDAR levels induced by synaptic plasticity and by spatial memory formation seem to occur in different waves of NMDAR transport/expression/degradation, with a net increase at the postsynaptic side and a rise in expression at both the spine and neuronal soma. This review aims to put together that information and the proposed hypotheses.
Lüscher, Christian; Huber, Kimberly M
2010-02-25
Many excitatory synapses express Group 1, or Gq coupled, metabotropic glutamate receptors (Gp1 mGluRs) at the periphery of their postsynaptic density. Activation of Gp1 mGluRs typically occurs in response to strong activity and triggers long-term plasticity of synaptic transmission in many brain regions, including the neocortex, hippocampus, midbrain, striatum, and cerebellum. Here we focus on mGluR-induced long-term synaptic depression (LTD) and review the literature that implicates Gp1 mGluRs in the plasticity of behavior, learning, and memory. Moreover, recent studies investigating the molecular mechanisms of mGluR-LTD have discovered links to mental retardation, autism, Alzheimer's disease, Parkinson's disease, and drug addiction. We discuss how mGluRs lead to plasticity of neural circuits and how the understanding of the molecular mechanisms of mGluR plasticity provides insight into brain disease.
Goh, Jinzhong J.; Manahan-Vaughan, Denise
2012-01-01
Persistent synaptic plasticity has been subjected to intense study in the decades since it was first described. Occurring in the form of long-term potentiation (LTP) and long-term depression (LTD), it shares many cellular and molecular properties with hippocampus-dependent forms of persistent memory. Recent reports of both LTP and LTD occurring endogenously under specific learning conditions provide further support that these forms of synaptic plasticity may comprise the cellular correlates of memory. Most studies of synaptic plasticity are performed using in vitro or in vivo preparations where patterned electrical stimulation of afferent fibers is implemented to induce changes in synaptic strength. This strategy has proven very effective in inducing LTP, even under in vivo conditions. LTD in vivo has proven more elusive: although LTD occurs endogenously under specific learning conditions in both rats and mice, its induction has not been successfully demonstrated with afferent electrical stimulation alone. In this study we screened a large spectrum of protocols that are known to induce LTD either in hippocampal slices or in the intact rat hippocampus, to clarify if LTD can be induced by sole afferent stimulation in the mouse CA1 region in vivo. Low frequency stimulation at 1, 2, 3, 5, 7, or 10 Hz given in the range of 100 through 1800 pulses produced, at best, short-term depression (STD) that lasted for up to 60 min. Varying the administration pattern of the stimuli (e.g., 900 pulses given twice at 5 min intervals), or changing the stimulation intensity did not improve the persistency of synaptic depression. LTD that lasts for at least 24 h occurs under learning conditions in mice. We conclude that a coincidence of factors, such as afferent activity together with neuromodulatory inputs, play a decisive role in the enablement of LTD under more naturalistic (e.g., learning) conditions. PMID:23355815
A Synaptic Basis for Memory Storage in the Cerebral Cortex
NASA Astrophysics Data System (ADS)
Bear, Mark F.
1996-11-01
A cardinal feature of neurons in the cerebral cortex is stimulus selectivity, and experience-dependent shifts in selectivity are a common correlate of memory formation. We have used a theoretical ``learning rule,'' devised to account for experience-dependent shifts in neuronal selectivity, to guide experiments on the elementary mechanisms of synaptic plasticity in hippocampus and neocortex. These experiments reveal that many synapses in hippocampus and neocortex are bidirectionally modifiable, that the modifications persist long enough to contribute to long-term memory storage, and that key variables governing the sign of synaptic plasticity are the amount of NMDA receptor activation and the recent history of cortical activity.
Habituation based synaptic plasticity and organismic learning in a quantum perovskite.
Zuo, Fan; Panda, Priyadarshini; Kotiuga, Michele; Li, Jiarui; Kang, Mingu; Mazzoli, Claudio; Zhou, Hua; Barbour, Andi; Wilkins, Stuart; Narayanan, Badri; Cherukara, Mathew; Zhang, Zhen; Sankaranarayanan, Subramanian K R S; Comin, Riccardo; Rabe, Karin M; Roy, Kaushik; Ramanathan, Shriram
2017-08-14
A central characteristic of living beings is the ability to learn from and respond to their environment leading to habit formation and decision making. This behavior, known as habituation, is universal among all forms of life with a central nervous system, and is also observed in single-cell organisms that do not possess a brain. Here, we report the discovery of habituation-based plasticity utilizing a perovskite quantum system by dynamical modulation of electron localization. Microscopic mechanisms and pathways that enable this organismic collective charge-lattice interaction are elucidated by first-principles theory, synchrotron investigations, ab initio molecular dynamics simulations, and in situ environmental breathing studies. We implement a learning algorithm inspired by the conductance relaxation behavior of perovskites that naturally incorporates habituation, and demonstrate learning to forget: a key feature of animal and human brains. Incorporating this elementary skill in learning boosts the capability of neural computing in a sequential, dynamic environment.Habituation is a learning mechanism that enables control over forgetting and learning. Zuo, Panda et al., demonstrate adaptive synaptic plasticity in SmNiO 3 perovskites to address catastrophic forgetting in a dynamic learning environment via hydrogen-induced electron localization.
Stably maintained dendritic spines are associated with lifelong memories
Yang, Guang; Pan, Feng; Gan, Wen-Biao
2016-01-01
Changes in synaptic connections are considered essential for learning and memory formation1–6. However, it is unknown how neural circuits undergo continuous synaptic changes during learning while maintaining lifelong memories. Here we show, by following postsynaptic dendritic spines over time in the mouse cortex7–8, that learning and novel sensory experience lead to spine formation and elimination by a protracted process. The extent of spine remodelling correlates with behavioural improvement after learning, suggesting a crucial role of synaptic structural plasticity in memory formation and storage. Importantly, a small fraction of new spines induced by novel experience, together with most spines formed early during development and surviving experience-dependent elimination, are preserved throughout the entire life of an animal. These studies indicate that learning and daily sensory experience leave minute but permanent marks on cortical connections and suggest that lifelong memories are stored in largely stably connected synaptic networks. PMID:19946265
ERIC Educational Resources Information Center
Hugues, Sandrine; Garcia, Rene
2007-01-01
We have previously shown that fear extinction is accompanied by an increase of synaptic efficacy in inputs from the ventral hippocampus (vHPC) and mediodorsal thalamus (MD) to the medial prefrontal cortex (mPFC) and that disrupting these changes to mPFC synaptic transmission compromises extinction processes. The aim of this study was to examine…
Circadian clocks, rhythmic synaptic plasticity and the sleep-wake cycle in zebrafish.
Elbaz, Idan; Foulkes, Nicholas S; Gothilf, Yoav; Appelbaum, Lior
2013-01-01
The circadian clock and homeostatic processes are fundamental mechanisms that regulate sleep. Surprisingly, despite decades of research, we still do not know why we sleep. Intriguing hypotheses suggest that sleep regulates synaptic plasticity and consequently has a beneficial role in learning and memory. However, direct evidence is still limited and the molecular regulatory mechanisms remain unclear. The zebrafish provides a powerful vertebrate model system that enables simple genetic manipulation, imaging of neuronal circuits and synapses in living animals, and the monitoring of behavioral performance during day and night. Thus, the zebrafish has become an attractive model to study circadian and homeostatic processes that regulate sleep. Zebrafish clock- and sleep-related genes have been cloned, neuronal circuits that exhibit circadian rhythms of activity and synaptic plasticity have been studied, and rhythmic behavioral outputs have been characterized. Integration of this data could lead to a better understanding of sleep regulation. Here, we review the progress of circadian clock and sleep studies in zebrafish with special emphasis on the genetic and neuroendocrine mechanisms that regulate rhythms of melatonin secretion, structural synaptic plasticity, locomotor activity and sleep.
Synaptic Effects of Electric Fields
NASA Astrophysics Data System (ADS)
Rahman, Asif
Learning and sensory processing in the brain relies on the effective transmission of information across synapses. The strength and efficacy of synaptic transmission is modifiable through training and can be modulated with noninvasive electrical brain stimulation. Transcranial electrical stimulation (TES), specifically, induces weak intensity and spatially diffuse electric fields in the brain. Despite being weak, electric fields modulate spiking probability and the efficacy of synaptic transmission. These effects critically depend on the direction of the electric field relative to the orientation of the neuron and on the level of endogenous synaptic activity. TES has been used to modulate a wide range of neuropsychiatric indications, for various rehabilitation applications, and cognitive performance in diverse tasks. How can a weak and diffuse electric field, which simultaneously polarizes neurons across the brain, have precise changes in brain function? Designing therapies to maximize desired outcomes and minimize undesired effects presents a challenging problem. A series of experiments and computational models are used to define the anatomical and functional factors leading to specificity of TES. Anatomical specificity derives from guiding current to targeted brain structures and taking advantage of the direction-sensitivity of neurons with respect to the electric field. Functional specificity originates from preferential modulation of neuronal networks that are already active. Diffuse electric fields may recruit connected brain networks involved in a training task and promote plasticity along active synaptic pathways. In vitro, electric fields boost endogenous synaptic plasticity and raise the ceiling for synaptic learning with repeated stimulation sessions. Synapses undergoing strong plasticity are preferentially modulated over weak synapses. Therefore, active circuits that are involved in a task could be more susceptible to stimulation than inactive circuits. Moreover, stimulation polarity has asymmetric effects on synaptic strength making it easier to enhance ongoing plasticity. These results suggest that the susceptibility of brain networks to an electric field depends on the state of synaptic activity. Combining a training task, which activates specific circuits, with TES may lead to functionally-specific effects. Given the simplicity of TES and the complexity of brain function, understanding the mechanisms leading to specificity is fundamental to the rational advancement of TES.
The A-Current Modulates Learning via NMDA Receptors Containing the NR2B Subunit
Fontán-Lozano, Ángela; Suárez-Pereira, Irene; González-Forero, David; Carrión, Ángel Manuel
2011-01-01
Synaptic plasticity involves short- and long-term events, although the molecular mechanisms that underlie these processes are not fully understood. The transient A-type K+ current (IA) controls the excitability of the dendrites from CA1 pyramidal neurons by regulating the back-propagation of action potentials and shaping synaptic input. Here, we have studied how decreases in IA affect cognitive processes and synaptic plasticity. Using wild-type mice treated with 4-AP, an IA inhibitor, and mice lacking the DREAM protein, a transcriptional repressor and modulator of the IA, we demonstrate that impairment of IA decreases the stimulation threshold for learning and the induction of early-LTP. Hippocampal electrical recordings in both models revealed alterations in basal electrical oscillatory properties toward low-theta frequencies. In addition, we demonstrated that the facilitated learning induced by decreased IA requires the activation of NMDA receptors containing the NR2B subunit. Together, these findings point to a balance between the IA and the activity of NR2B-containing NMDA receptors in the regulation of learning. PMID:21966384
Nonlinear Hebbian Learning as a Unifying Principle in Receptive Field Formation.
Brito, Carlos S N; Gerstner, Wulfram
2016-09-01
The development of sensory receptive fields has been modeled in the past by a variety of models including normative models such as sparse coding or independent component analysis and bottom-up models such as spike-timing dependent plasticity or the Bienenstock-Cooper-Munro model of synaptic plasticity. Here we show that the above variety of approaches can all be unified into a single common principle, namely nonlinear Hebbian learning. When nonlinear Hebbian learning is applied to natural images, receptive field shapes were strongly constrained by the input statistics and preprocessing, but exhibited only modest variation across different choices of nonlinearities in neuron models or synaptic plasticity rules. Neither overcompleteness nor sparse network activity are necessary for the development of localized receptive fields. The analysis of alternative sensory modalities such as auditory models or V2 development lead to the same conclusions. In all examples, receptive fields can be predicted a priori by reformulating an abstract model as nonlinear Hebbian learning. Thus nonlinear Hebbian learning and natural statistics can account for many aspects of receptive field formation across models and sensory modalities.
Nonlinear Hebbian Learning as a Unifying Principle in Receptive Field Formation
Gerstner, Wulfram
2016-01-01
The development of sensory receptive fields has been modeled in the past by a variety of models including normative models such as sparse coding or independent component analysis and bottom-up models such as spike-timing dependent plasticity or the Bienenstock-Cooper-Munro model of synaptic plasticity. Here we show that the above variety of approaches can all be unified into a single common principle, namely nonlinear Hebbian learning. When nonlinear Hebbian learning is applied to natural images, receptive field shapes were strongly constrained by the input statistics and preprocessing, but exhibited only modest variation across different choices of nonlinearities in neuron models or synaptic plasticity rules. Neither overcompleteness nor sparse network activity are necessary for the development of localized receptive fields. The analysis of alternative sensory modalities such as auditory models or V2 development lead to the same conclusions. In all examples, receptive fields can be predicted a priori by reformulating an abstract model as nonlinear Hebbian learning. Thus nonlinear Hebbian learning and natural statistics can account for many aspects of receptive field formation across models and sensory modalities. PMID:27690349
Molecular mechanisms of fear learning and memory.
Johansen, Joshua P; Cain, Christopher K; Ostroff, Linnaea E; LeDoux, Joseph E
2011-10-28
Pavlovian fear conditioning is a particularly useful behavioral paradigm for exploring the molecular mechanisms of learning and memory because a well-defined response to a specific environmental stimulus is produced through associative learning processes. Synaptic plasticity in the lateral nucleus of the amygdala (LA) underlies this form of associative learning. Here, we summarize the molecular mechanisms that contribute to this synaptic plasticity in the context of auditory fear conditioning, the form of fear conditioning best understood at the molecular level. We discuss the neurotransmitter systems and signaling cascades that contribute to three phases of auditory fear conditioning: acquisition, consolidation, and reconsolidation. These studies suggest that multiple intracellular signaling pathways, including those triggered by activation of Hebbian processes and neuromodulatory receptors, interact to produce neural plasticity in the LA and behavioral fear conditioning. Collectively, this body of research illustrates the power of fear conditioning as a model system for characterizing the mechanisms of learning and memory in mammals and potentially for understanding fear-related disorders, such as PTSD and phobias. Copyright © 2011 Elsevier Inc. All rights reserved.
Goh, Jinzhong Jeremy; Manahan-Vaughan, Denise
2013-02-01
Learning-facilitated synaptic plasticity describes the ability of hippocampal synapses to respond with persistent plasticity to afferent stimulation when coupled with a spatial learning event, whereby the afferent stimulation normally produces short-term plasticity or no change in synaptic strength if given in the absence of novel learning. Recently, it was reported that in the mouse hippocampus intrinsic long-term depression (LTD > 24 h) occurs when test-pulse afferent stimulation is coupled with a novel spatial learning. It is not known to what extent this phenomenon shares molecular properties with synaptic plasticity that is typically induced by means of patterned electrical afferent stimulation. In previous work, we showed that a novel spatial object recognition task facilitates LTD at the Schaffer collateral-CA1 synapse of freely behaving adult mice, whereas reexposure to the familiar spatial configuration ∼24 h later elicited no such facilitation. Here we report that treatment with the NMDA receptor antagonist, (±)-3-(2-Carboxypiperazin-4-yl)-propanephosphonic acid (CPP), or antagonism of metabotropic glutamate (mGlu) receptor, mGlu5, using 2-methyl-6-(phenylethynyl) pyridine (MPEP), completely prevented LTD under the novel learning conditions. Behavioral assessment during re-exposure after application of the antagonists revealed that the animals did not remember the object during novel exposure and treated them as if they were novel. Under these circumstances, where the acquisition of novel spatial information was involved, LTD was facilitated. Our data support that the endogenous LTD that is enabled through novel spatial learning in adult mice is critically dependent on the activation of both the NMDA receptors and mGlu5. Copyright © 2012 Wiley Periodicals, Inc.
Croft, Wayne; Dobson, Katharine L; Bellamy, Tomas C
2015-01-01
The capacity of synaptic networks to express activity-dependent changes in strength and connectivity is essential for learning and memory processes. In recent years, glial cells (most notably astrocytes) have been recognized as active participants in the modulation of synaptic transmission and synaptic plasticity, implicating these electrically nonexcitable cells in information processing in the brain. While the concept of bidirectional communication between neurons and glia and the mechanisms by which gliotransmission can modulate neuronal function are well established, less attention has been focussed on the computational potential of neuron-glial transmission itself. In particular, whether neuron-glial transmission is itself subject to activity-dependent plasticity and what the computational properties of such plasticity might be has not been explored in detail. In this review, we summarize current examples of plasticity in neuron-glial transmission, in many brain regions and neurotransmitter pathways. We argue that induction of glial plasticity typically requires repetitive neuronal firing over long time periods (minutes-hours) rather than the short-lived, stereotyped trigger typical of canonical long-term potentiation. We speculate that this equips glia with a mechanism for monitoring average firing rates in the synaptic network, which is suited to the longer term roles proposed for astrocytes in neurophysiology.
Induction and Consolidation of Calcium-Based Homo- and Heterosynaptic Potentiation and Depression
Li, Yinyun; Kulvicius, Tomas; Tetzlaff, Christian
2016-01-01
The adaptive mechanisms of homo- and heterosynaptic plasticity play an important role in learning and memory. In order to maintain plasticity-induced changes for longer time scales (up to several days), they have to be consolidated by transferring them from a short-lasting early-phase to a long-lasting late-phase state. The underlying processes of this synaptic consolidation are already well-known for homosynaptic plasticity, however, it is not clear whether the same processes also enable the induction and consolidation of heterosynaptic plasticity. In this study, by extending a generic calcium-based plasticity model with the processes of synaptic consolidation, we show in simulations that indeed heterosynaptic plasticity can be induced and, furthermore, consolidated by the same underlying processes as for homosynaptic plasticity. Furthermore, we show that by local diffusion processes the heterosynaptic effect can be restricted to a few synapses neighboring the homosynaptically changed ones. Taken together, this generic model reproduces many experimental results of synaptic tagging and consolidation, provides several predictions for heterosynaptic induction and consolidation, and yields insights into the complex interactions between homo- and heterosynaptic plasticity over a broad variety of time (minutes to days) and spatial scales (several micrometers). PMID:27560350
Long Term Synaptic Plasticity and Learning in Neuronal Networks
1989-01-14
Videomicroscopy and synaptic physiology of cultured hippocampal slices. Soc, Neurosci. Abstr. 14:246, 1988. Griffith, W.H., Brown, T.H. and Johnston, D...Chapman, P.F., Chang, V., and Brown, T.H. . Videomicroscopy of acute brain slices from hippocampus and amygdala. Brain Res. Bull, 21: 373-383, 1988
Neural ECM proteases in learning and synaptic plasticity.
Tsilibary, Effie; Tzinia, Athina; Radenovic, Lidija; Stamenkovic, Vera; Lebitko, Tomasz; Mucha, Mariusz; Pawlak, Robert; Frischknecht, Renato; Kaczmarek, Leszek
2014-01-01
Recent studies implicate extracellular proteases in synaptic plasticity, learning, and memory. The data are especially strong for such serine proteases as thrombin, tissue plasminogen activator, neurotrypsin, and neuropsin as well as matrix metalloproteinases, MMP-9 in particular. The role of those enzymes in the aforementioned phenomena is supported by the experimental results on the expression patterns (at the gene expression and protein and enzymatic activity levels) and functional studies, including knockout mice, specific inhibitors, etc. Counterintuitively, the studies have shown that the extracellular proteolysis is not responsible mainly for an overall degradation of the extracellular matrix (ECM) and loosening perisynaptic structures, but rather allows for releasing signaling molecules from the ECM, transsynaptic proteins, and latent form of growth factors. Notably, there are also indications implying those enzymes in the major neuropsychiatric disorders, probably by contributing to synaptic aberrations underlying such diseases as schizophrenia, bipolar, autism spectrum disorders, and drug addiction.
ERIC Educational Resources Information Center
Middei, Silvia; Roberto, Anna; Berretta, Nicola; Panico, Maria Beatrice; Lista, Simone; Bernardi, Giorgio; Mercuri, Nicola B.; Ammassari-Teule, Martine; Nistico, Robert
2010-01-01
B6-Tg/Thy1APP23Sdz (APP23) mutant mice exhibit neurohistological hallmarks of Alzheimer's disease but show intact basal hippocampal neurotransmission and synaptic plasticity. Here, we examine whether spatial learning differently modifies the structural and electrophysiological properties of hippocampal synapses in APP23 and wild-type mice. While…
Role of motor cortex NMDA receptors in learning-dependent synaptic plasticity of behaving mice
Hasan, Mazahir T.; Hernández-González, Samuel; Dogbevia, Godwin; Treviño, Mario; Bertocchi, Ilaria; Gruart, Agnès; Delgado-García, José M.
2013-01-01
The primary motor cortex has an important role in the precise execution of learned motor responses. During motor learning, synaptic efficacy between sensory and primary motor cortical neurons is enhanced, possibly involving long-term potentiation and N-methyl-D-aspartate (NMDA)-specific glutamate receptor function. To investigate whether NMDA receptor in the primary motor cortex can act as a coincidence detector for activity-dependent changes in synaptic strength and associative learning, here we generate mice with deletion of the Grin1 gene, encoding the essential NMDA receptor subunit 1 (GluN1), specifically in the primary motor cortex. The loss of NMDA receptor function impairs primary motor cortex long-term potentiation in vivo. Importantly, it impairs the synaptic efficacy between the primary somatosensory and primary motor cortices and significantly reduces classically conditioned eyeblink responses. Furthermore, compared with wild-type littermates, mice lacking primary motor cortex show slower learning in Skinner-box tasks. Thus, primary motor cortex NMDA receptors are necessary for activity-dependent synaptic strengthening and associative learning. PMID:23978820
Ruan, Hongyu; Yao, Wei-Dong
2017-01-25
Addictive drugs usurp neural plasticity mechanisms that normally serve reward-related learning and memory, primarily by evoking changes in glutamatergic synaptic strength in the mesocorticolimbic dopamine circuitry. Here, we show that repeated cocaine exposure in vivo does not alter synaptic strength in the mouse prefrontal cortex during an early period of withdrawal, but instead modifies a Hebbian quantitative synaptic learning rule by broadening the temporal window and lowers the induction threshold for spike-timing-dependent LTP (t-LTP). After repeated, but not single, daily cocaine injections, t-LTP in layer V pyramidal neurons is induced at +30 ms, a normally ineffective timing interval for t-LTP induction in saline-exposed mice. This cocaine-induced, extended-timing t-LTP lasts for ∼1 week after terminating cocaine and is accompanied by an increased susceptibility to potentiation by fewer pre-post spike pairs, indicating a reduced t-LTP induction threshold. Basal synaptic strength and the maximal attainable t-LTP magnitude remain unchanged after cocaine exposure. We further show that the cocaine facilitation of t-LTP induction is caused by sensitized D1-cAMP/protein kinase A dopamine signaling in pyramidal neurons, which then pathologically recruits voltage-gated l-type Ca 2+ channels that synergize with GluN2A-containing NMDA receptors to drive t-LTP at extended timing. Our results illustrate a mechanism by which cocaine, acting on a key neuromodulation pathway, modifies the coincidence detection window during Hebbian plasticity to facilitate associative synaptic potentiation in prefrontal excitatory circuits. By modifying rules that govern activity-dependent synaptic plasticity, addictive drugs can derail the experience-driven neural circuit remodeling process important for executive control of reward and addiction. It is believed that addictive drugs often render an addict's brain reward system hypersensitive, leaving the individual more susceptible to relapse. We found that repeated cocaine exposure alters a Hebbian associative synaptic learning rule that governs activity-dependent synaptic plasticity in the mouse prefrontal cortex, characterized by a broader temporal window and a lower threshold for spike-timing-dependent LTP (t-LTP), a cellular form of learning and memory. This rule change is caused by cocaine-exacerbated D1-cAMP/protein kinase A dopamine signaling in pyramidal neurons that in turn pathologically recruits l-type Ca 2+ channels to facilitate coincidence detection during t-LTP induction. Our study provides novel insights on how cocaine, even with only brief exposure, may prime neural circuits for subsequent experience-dependent remodeling that may underlie certain addictive behavior. Copyright © 2017 the authors 0270-6474/17/370986-12$15.00/0.
Feduccia, Allison A.; Chatterjee, Susmita; Bartlett, Selena E.
2012-01-01
Addictive drugs can activate systems involved in normal reward-related learning, creating long-lasting memories of the drug's reinforcing effects and the environmental cues surrounding the experience. These memories significantly contribute to the maintenance of compulsive drug use as well as cue-induced relapse which can occur even after long periods of abstinence. Synaptic plasticity is thought to be a prominent molecular mechanism underlying drug-induced learning and memories. Ethanol and nicotine are both widely abused drugs that share a common molecular target in the brain, the neuronal nicotinic acetylcholine receptors (nAChRs). The nAChRs are ligand-gated ion channels that are vastly distributed throughout the brain and play a key role in synaptic neurotransmission. In this review, we will delineate the role of nAChRs in the development of ethanol and nicotine addiction. We will characterize both ethanol and nicotine's effects on nAChR-mediated synaptic transmission and plasticity in several key brain areas that are important for addiction. Finally, we will discuss some of the behavioral outcomes of drug-induced synaptic plasticity in animal models. An understanding of the molecular and cellular changes that occur following administration of ethanol and nicotine will lead to better therapeutic strategies. PMID:22876217
Hamilton, Kelly A; Wang, Yue; Raefsky, Sophia M; Berkowitz, Sean; Spangler, Ryan; Suire, Caitlin N; Camandola, Simonetta; Lipsky, Robert H; Mattson, Mark P
2018-01-01
Bhlhe40 is a transcription factor that is highly expressed in the hippocampus; however, its role in neuronal function is not well understood. Here, we used Bhlhe40 null mice on a congenic C57Bl6/J background (Bhlhe40 KO) to investigate the impact of Bhlhe40 on neuronal excitability and synaptic plasticity in the hippocampus. Bhlhe40 KO CA1 neurons had increased miniature excitatory post-synaptic current amplitude and decreased inhibitory post-synaptic current amplitude, indicating CA1 neuronal hyperexcitability. Increased CA1 neuronal excitability was not associated with increased seizure severity as Bhlhe40 KO relative to +/+ (WT) control mice injected with the convulsant kainic acid. However, significant reductions in long term potentiation and long term depression at CA1 synapses were observed in Bhlhe40 KO mice, indicating impaired hippocampal synaptic plasticity. Behavioral testing for spatial learning and memory on the Morris Water Maze (MWM) revealed that while Bhlhe40 KO mice performed similarly to WT controls initially, when the hidden platform was moved to the opposite quadrant Bhlhe40 KO mice showed impairments in relearning, consistent with decreased hippocampal synaptic plasticity. To investigate possible mechanisms for increased neuronal excitability and decreased synaptic plasticity, a whole genome mRNA expression profile of Bhlhe40 KO hippocampus was performed followed by a chromatin immunoprecipitation sequencing (ChIP-Seq) screen of the validated candidate genes for Bhlhe40 protein-DNA interactions consistent with transcriptional regulation. Of the validated genes identified from mRNA expression analysis, insulin degrading enzyme (Ide) had the most significantly altered expression in hippocampus and was significantly downregulated on the RNA and protein levels; although Bhlhe40 did not occupy the Ide gene by ChIP-Seq. Together, these findings support a role for Bhlhe40 in regulating neuronal excitability and synaptic plasticity in the hippocampus and that indirect regulation of Ide transcription may be involved in these phenotypes.
The Chemokine MIP-1α/CCL3 impairs mouse hippocampal synaptic transmission, plasticity and memory.
Marciniak, Elodie; Faivre, Emilie; Dutar, Patrick; Alves Pires, Claire; Demeyer, Dominique; Caillierez, Raphaëlle; Laloux, Charlotte; Buée, Luc; Blum, David; Humez, Sandrine
2015-10-29
Chemokines are signaling molecules playing an important role in immune regulations. They are also thought to regulate brain development, neurogenesis and neuroendocrine functions. While chemokine upsurge has been associated with conditions characterized with cognitive impairments, their ability to modulate synaptic plasticity remains ill-defined. In the present study, we specifically evaluated the effects of MIP1-α/CCL3 towards hippocampal synaptic transmission, plasticity and spatial memory. We found that CCL3 (50 ng/ml) significantly reduced basal synaptic transmission at the Schaffer collateral-CA1 synapse without affecting NMDAR-mediated field potentials. This effect was ascribed to post-synaptic regulations, as CCL3 did not impact paired-pulse facilitation. While CCL3 did not modulate long-term depression (LTD), it significantly impaired long-term potentiation (LTP), an effect abolished by Maraviroc, a CCR5 specific antagonist. In addition, sub-chronic intracerebroventricular (icv) injections of CCL3 also impair LTP. In accordance with these electrophysiological findings, we demonstrated that the icv injection of CCL3 in mouse significantly impaired spatial memory abilities and long-term memory measured using the two-step Y-maze and passive avoidance tasks. These effects of CCL3 on memory were inhibited by Maraviroc. Altogether, these data suggest that the chemokine CCL3 is an hippocampal neuromodulator able to regulate synaptic plasticity mechanisms involved in learning and memory functions.
Matching tutors and students: effective strategies for information transfer between circuits
NASA Astrophysics Data System (ADS)
Tesileanu, Tiberiu; Balasubramanian, Vijay; Olveczky, Bence
Many neural circuits transfer learned information to downstream circuits: hippocampal-dependent memories are consolidated into long-term memories elsewhere; motor cortex is essential for skill learning but dispensable for execution; anterior forebrain pathway (AFP) in songbirds drives short-term improvements in song that are later consolidated in pre-motor area RA. We show how to match instructive signals from tutor circuits to synaptic plasticity rules in student circuits to achieve effective two-stage learning. We focus on learning sequential patterns where a timebase is transformed into motor commands by connectivity with a `student' area. If the sign of the synaptic change is given by the magnitude of tutor input, a good teaching strategy uses a strong (weak) tutor signal if student output is below (above) its target. If instead timing of tutor input relative to the timebase determines the sign of synaptic modifications, a good instructive signal accumulates the errors in student output as the motor program progresses. We demonstrate song learning in a biologically-plausible model of the songbird circuit given diverse plasticity rules interpolating between those described above. The model also reproduces qualitative firing statistics of RA neurons in juveniles and adults. Also affiliated to CUNY - Graduate Center.
Synaptic Scaling Enables Dynamically Distinct Short- and Long-Term Memory Formation
Tetzlaff, Christian; Kolodziejski, Christoph; Timme, Marc; Tsodyks, Misha; Wörgötter, Florentin
2013-01-01
Memory storage in the brain relies on mechanisms acting on time scales from minutes, for long-term synaptic potentiation, to days, for memory consolidation. During such processes, neural circuits distinguish synapses relevant for forming a long-term storage, which are consolidated, from synapses of short-term storage, which fade. How time scale integration and synaptic differentiation is simultaneously achieved remains unclear. Here we show that synaptic scaling – a slow process usually associated with the maintenance of activity homeostasis – combined with synaptic plasticity may simultaneously achieve both, thereby providing a natural separation of short- from long-term storage. The interaction between plasticity and scaling provides also an explanation for an established paradox where memory consolidation critically depends on the exact order of learning and recall. These results indicate that scaling may be fundamental for stabilizing memories, providing a dynamic link between early and late memory formation processes. PMID:24204240
Synaptic scaling enables dynamically distinct short- and long-term memory formation.
Tetzlaff, Christian; Kolodziejski, Christoph; Timme, Marc; Tsodyks, Misha; Wörgötter, Florentin
2013-10-01
Memory storage in the brain relies on mechanisms acting on time scales from minutes, for long-term synaptic potentiation, to days, for memory consolidation. During such processes, neural circuits distinguish synapses relevant for forming a long-term storage, which are consolidated, from synapses of short-term storage, which fade. How time scale integration and synaptic differentiation is simultaneously achieved remains unclear. Here we show that synaptic scaling - a slow process usually associated with the maintenance of activity homeostasis - combined with synaptic plasticity may simultaneously achieve both, thereby providing a natural separation of short- from long-term storage. The interaction between plasticity and scaling provides also an explanation for an established paradox where memory consolidation critically depends on the exact order of learning and recall. These results indicate that scaling may be fundamental for stabilizing memories, providing a dynamic link between early and late memory formation processes.
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
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.
Amadi, Ugwechi; Allman, Claire; Johansen-Berg, Heidi; Stagg, Charlotte J
2015-01-01
The relative timing of plasticity-induction protocols is known to be crucial. For example, anodal transcranial direct current stimulation (tDCS), which increases cortical excitability and typically enhances plasticity, can impair performance if it is applied before a motor learning task. Such timing-dependent effects have been ascribed to homeostatic plasticity, but the specific synaptic site of this interaction remains unknown. We wished to investigate the synaptic substrate, and in particular the role of inhibitory signaling, underpinning the behavioral effects of anodal tDCS in homeostatic interactions between anodal tDCS and motor learning. We used transcranial magnetic stimulation (TMS) to investigate cortical excitability and inhibitory signaling following tDCS and motor learning. Each subject participated in four experimental sessions and data were analyzed using repeated measures ANOVAs and post-hoc t-tests as appropriate. As predicted, we found that anodal tDCS prior to the motor task decreased learning rates. This worsening of learning after tDCS was accompanied by a correlated increase in GABAA activity, as measured by TMS-assessed short interval intra-cortical inhibition (SICI). This provides the first direct demonstration in humans that inhibitory synapses are the likely site for the interaction between anodal tDCS and motor learning, and further, that homeostatic plasticity at GABAA synapses has behavioral relevance in humans. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.
Tunicamycin impairs olfactory learning and synaptic plasticity in the olfactory bulb.
Tong, Jia; Okutani, Fumino; Murata, Yoshihiro; Taniguchi, Mutsuo; Namba, Toshiharu; Wang, Yu-Jie; Kaba, Hideto
2017-03-06
Tunicamycin (TM) induces endoplasmic reticulum (ER) stress and inhibits N-glycosylation in cells. ER stress is associated with neuronal death in neurodegenerative disorders, such as Parkinson's disease and Alzheimer's disease, and most patients complain of the impairment of olfactory recognition. Here we examined the effects of TM on aversive olfactory learning and the underlying synaptic plasticity in the main olfactory bulb (MOB). Behavioral experiments demonstrated that the intrabulbar infusion of TM disabled aversive olfactory learning without affecting short-term memory. Histological analyses revealed that TM infusion upregulated C/EBP homologous protein (CHOP), a marker of ER stress, in the mitral and granule cell layers of MOB. Electrophysiological data indicated that TM inhibited tetanus-induced long-term potentiation (LTP) at the dendrodendritic excitatory synapse from mitral to granule cells. A low dose of TM (250nM) abolished the late phase of LTP, and a high dose (1μM) inhibited the early and late phases of LTP. Further, high-dose, but not low-dose, TM reduced the paired-pulse facilitation ratio, suggesting that the inhibitory effects of TM on LTP are partially mediated through the presynaptic machinery. Thus, our results support the hypothesis that TM-induced ER stress impairs olfactory learning by inhibiting synaptic plasticity via presynaptic and postsynaptic mechanisms in MOB. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.
Navakkode, Sheeja; Chew, Katherine C M; Tay, Sabrina Jia Ning; Lin, Qingshu; Behnisch, Thomas; Soong, Tuck Wah
2017-11-14
Long-term potentiation (LTP) is the persistent increase in the strength of the synapses. However, the neural networks would become saturated if there is only synaptic strenghthening. Synaptic weakening could be facilitated by active processes like long-term depression (LTD). Molecular mechanisms that facilitate the weakening of synapses and thereby stabilize the synapses are also important in learning and memory. Here we show that blockade of dopaminergic D4 receptors (D4R) promoted the formation of late-LTP and transformed early-LTP into late-LTP. This effect was dependent on protein synthesis, activation of NMDA-receptors and CaMKII. We also show that GABA A -receptor mediated mechanisms are involved in the enhancement of late-LTP. We could show that short-term plasticity and baseline synaptic transmission were unaffected by D4R inhibition. On the other hand, antagonizing D4R prevented both early and late forms of LTD, showing that activation of D4Rs triggered a dual function. Synaptic tagging experiments on LTD showed that D4Rs act as plasticity related proteins rather than the setting of synaptic tags. D4R activation by PD 168077 induced a slow-onset depression that was protein synthesis, NMDAR and CaMKII dependent. The D4 receptors, thus exert a bidirectional modulation of CA1 pyramidal neurons by restricting synaptic strengthening and facilitating synaptic weakening.
Cicvaric, Ana; Yang, Jiaye; Krieger, Sigurd; Khan, Deeba; Kim, Eun-Jung; Dominguez-Rodriguez, Manuel; Cabatic, Maureen; Molz, Barbara; Acevedo Aguilar, Juan Pablo; Milicevic, Radoslav; Smani, Tarik; Breuss, Johannes M; Kerjaschki, Dontscho; Pollak, Daniela D; Uhrin, Pavel; Monje, Francisco J
2016-12-01
Podoplanin is a cell-surface glycoprotein constitutively expressed in the brain and implicated in human brain tumorigenesis. The intrinsic function of podoplanin in brain neurons remains however uncharacterized. Using an established podoplanin-knockout mouse model and electrophysiological, biochemical, and behavioral approaches, we investigated the brain neuronal role of podoplanin. Ex-vivo electrophysiology showed that podoplanin deletion impairs dentate gyrus synaptic strengthening. In vivo, podoplanin deletion selectively impaired hippocampus-dependent spatial learning and memory without affecting amygdala-dependent cued fear conditioning. In vitro, neuronal overexpression of podoplanin promoted synaptic activity and neuritic outgrowth whereas podoplanin-deficient neurons exhibited stunted outgrowth and lower levels of p-Ezrin, TrkA, and CREB in response to nerve growth factor (NGF). Surface Plasmon Resonance data further indicated a physical interaction between podoplanin and NGF. This work proposes podoplanin as a novel component of the neuronal machinery underlying neuritogenesis, synaptic plasticity, and hippocampus-dependent memory functions. The existence of a relevant cross-talk between podoplanin and the NGF/TrkA signaling pathway is also for the first time proposed here, thus providing a novel molecular complex as a target for future multidisciplinary studies of the brain function in the physiology and the pathology. Key messages Podoplanin, a protein linked to the promotion of human brain tumors, is required in vivo for proper hippocampus-dependent learning and memory functions. Deletion of podoplanin selectively impairs activity-dependent synaptic strengthening at the neurogenic dentate-gyrus and hampers neuritogenesis and phospho Ezrin, TrkA and CREB protein levels upon NGF stimulation. Surface plasmon resonance data indicates a physical interaction between podoplanin and NGF. On these grounds, a relevant cross-talk between podoplanin and NGF as well as a role for podoplanin in plasticity-related brain neuronal functions is here proposed.
NASA Astrophysics Data System (ADS)
Yang, Rui; Terabe, Kazuya; Yao, Yiping; Tsuruoka, Tohru; Hasegawa, Tsuyoshi; Gimzewski, James K.; Aono, Masakazu
2013-09-01
A compact neuromorphic nanodevice with inherent learning and memory properties emulating those of biological synapses is the key to developing artificial neural networks rivaling their biological counterparts. Experimental results showed that memorization with a wide time scale from volatile to permanent can be achieved in a WO3-x-based nanoionics device and can be precisely and cumulatively controlled by adjusting the device’s resistance state and input pulse parameters such as the amplitude, interval, and number. This control is analogous to biological synaptic plasticity including short-term plasticity, long-term potentiation, transition from short-term memory to long-term memory, forgetting processes for short- and long-term memory, learning speed, and learning history. A compact WO3-x-based nanoionics device with a simple stacked layer structure should thus be a promising candidate for use as an inorganic synapse in artificial neural networks due to its striking resemblance to the biological synapse.
Le Barillier, Léa; Léger, Lucienne; Luppi, Pierre-Hervé; Fort, Patrice; Malleret, Gaël; Salin, Paul-Antoine
2015-11-01
The cognitive role of melanin-concentrating hormone (MCH) neurons, a neuronal population located in the mammalian postero-lateral hypothalamus sending projections to all cortical areas, remains poorly understood. Mainly activated during paradoxical sleep (PS), MCH neurons have been implicated in sleep regulation. The genetic deletion of the only known MCH receptor in rodent leads to an impairment of hippocampal dependent forms of memory and to an alteration of hippocampal long-term synaptic plasticity. By using MCH/ataxin3 mice, a genetic model characterized by a selective deletion of MCH neurons in the adult, we investigated the role of MCH neurons in hippocampal synaptic plasticity and hippocampal-dependent forms of memory. MCH/ataxin3 mice exhibited a deficit in the early part of both long-term potentiation and depression in the CA1 area of the hippocampus. Post-tetanic potentiation (PTP) was diminished while synaptic depression induced by repetitive stimulation was enhanced suggesting an alteration of pre-synaptic forms of short-term plasticity in these mice. Behaviorally, MCH/ataxin3 mice spent more time and showed a higher level of hesitation as compared to their controls in performing a short-term memory T-maze task, displayed retardation in acquiring a reference memory task in a Morris water maze, and showed a habituation deficit in an open field task. Deletion of MCH neurons could thus alter spatial short-term memory by impairing short-term plasticity in the hippocampus. Altogether, these findings could provide a cellular mechanism by which PS may facilitate memory encoding. Via MCH neuron activation, PS could prepare the day's learning by increasing and modulating short-term synaptic plasticity in the hippocampus. © 2015 Wiley Periodicals, Inc.
The Demise of the Synapse As the Locus of Memory: A Looming Paradigm Shift?
Trettenbrein, Patrick C
2016-01-01
Synaptic plasticity is widely considered to be the neurobiological basis of learning and memory by neuroscientists and researchers in adjacent fields, though diverging opinions are increasingly being recognized. From the perspective of what we might call "classical cognitive science" it has always been understood that the mind/brain is to be considered a computational-representational system. Proponents of the information-processing approach to cognitive science have long been critical of connectionist or network approaches to (neuro-)cognitive architecture, pointing to the shortcomings of the associative psychology that underlies Hebbian learning as well as to the fact that synapses are practically unfit to implement symbols. Recent work on memory has been adding fuel to the fire and current findings in neuroscience now provide first tentative neurobiological evidence for the cognitive scientists' doubts about the synapse as the (sole) locus of memory in the brain. This paper briefly considers the history and appeal of synaptic plasticity as a memory mechanism, followed by a summary of the cognitive scientists' objections regarding these assertions. Next, a variety of tentative neuroscientific evidence that appears to substantiate questioning the idea of the synapse as the locus of memory is presented. On this basis, a novel way of thinking about the role of synaptic plasticity in learning and memory is proposed.
Zanutto, B. Silvano
2017-01-01
Animals are proposed to learn the latent rules governing their environment in order to maximize their chances of survival. However, rules may change without notice, forcing animals to keep a memory of which one is currently at work. Rule switching can lead to situations in which the same stimulus/response pairing is positively and negatively rewarded in the long run, depending on variables that are not accessible to the animal. This fact raises questions on how neural systems are capable of reinforcement learning in environments where the reinforcement is inconsistent. Here we address this issue by asking about which aspects of connectivity, neural excitability and synaptic plasticity are key for a very general, stochastic spiking neural network model to solve a task in which rules change without being cued, taking the serial reversal task (SRT) as paradigm. Contrary to what could be expected, we found strong limitations for biologically plausible networks to solve the SRT. Especially, we proved that no network of neurons can learn a SRT if it is a single neural population that integrates stimuli information and at the same time is responsible of choosing the behavioural response. This limitation is independent of the number of neurons, neuronal dynamics or plasticity rules, and arises from the fact that plasticity is locally computed at each synapse, and that synaptic changes and neuronal activity are mutually dependent processes. We propose and characterize a spiking neural network model that solves the SRT, which relies on separating the functions of stimuli integration and response selection. The model suggests that experimental efforts to understand neural function should focus on the characterization of neural circuits according to their connectivity, neural dynamics, and the degree of modulation of synaptic plasticity with reward. PMID:29077735
Fole, A; Martin, M; Morales, L; Del Olmo, N
2015-09-01
The use of Lewis (LEW) together with Fischer-344 (F344) rats has been proposed as an addiction model because of the addiction behavior differences of these two strains. We have previously suggested that these differences could be related to learning and memory processes and that they depend on the genetic background of these two strains of rats. Adolescence is a period of active synaptic remodeling, plasticity and particular vulnerability to the effects of environmental insults such as drugs of abuse. We have evaluated spatial memory using novel location recognition in LEW and F344 adult rats undergoing a chronic treatment with cocaine during adolescence or adulthood. In order to study whether synaptic plasticity mechanisms were involved in the possible changes in learning after chronic cocaine treatment, we carried out electrophysiological experiments in hippocampal slices from treated animals. Our results showed that, in LEW cocaine-treated rats, hippocampal memory was only significantly impaired when the drug was administered during adolescence whereas adult administration did not produce any detrimental effect in spatial memory measured in this protocol. Moreover, F344 rats showed clear difficulties carrying out the protocol even in standard conditions, confirming the spatial memory problems observed in previous reports and demonstrating the genetic differences in spatial learning and memory. Our experiments show that the effects in behavioral experiments are related to synaptic plasticity mechanisms. Long-term depression induced by the glutamate agonist NMDA (LTD-NMDA) is partially abolished in cocaine-treated animals in hippocampal slices from LEW rats. Hippocampal LTD-NMDA is partially inhibited in F344 animals regardless of whether saline or cocaine administration, suggesting the lack of plasticity of this strain that could be related to the inability of these animals to carry out the novel object location protocol. Copyright © 2015 Elsevier Inc. All rights reserved.
E-I balance emerges naturally from continuous Hebbian learning in autonomous neural networks.
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.
Lüscher, Christian; Huber, Kimberly M.
2010-01-01
Many excitatory synapses express Group 1, or Gq coupled, metabotropic glutamate receptors (Gp1 mGluRs) at the periphery of their postsynaptic density. Activation of Gp1 mGluRs typically occurs in response to strong activity and triggers long-term plasticity of synaptic transmission in many brain regions including the neocortex, hippocampus, midbrain, striatum and cerebellum. Here we focus on mGluR-induced long-term synaptic depression (LTD) and review the literature that implicates Gp1 mGluRs in the plasticity of behavior, learning and memory. Moreover, recent studies investigating the molecular mechanisms of mGluR-LTD have discovered links to mental retardation, autism, Alzheimer’s disease, Parkinson’s disease and drug addiction. We discuss how mGluRs lead to plasticity of neural circuits and how the understanding of the molecular mechanisms of mGluR plasticity provides insight into brain disease. PMID:20188650
de Hoz, Livia; Gierej, Dorota; Lioudyno, Victoria; Jaworski, Jacek; Blazejczyk, Magda; Cruces-Solís, Hugo; Beroun, Anna; Lebitko, Tomasz; Nikolaev, Tomasz; Knapska, Ewelina; Nelken, Israel; Kaczmarek, Leszek
2018-05-01
The behavioral changes that comprise operant learning are associated with plasticity in early sensory cortices as well as with modulation of gene expression, but the connection between the behavioral, electrophysiological, and molecular changes is only partially understood. We specifically manipulated c-Fos expression, a hallmark of learning-induced synaptic plasticity, in auditory cortex of adult mice using a novel approach based on RNA interference. Locally blocking c-Fos expression caused a specific behavioral deficit in a sound discrimination task, in parallel with decreased cortical experience-dependent plasticity, without affecting baseline excitability or basic auditory processing. Thus, c-Fos-dependent experience-dependent cortical plasticity is necessary for frequency discrimination in an operant behavioral task. Our results connect behavioral, molecular and physiological changes and demonstrate a role of c-Fos in experience-dependent plasticity and learning.
Impaired associative learning in schizophrenia: behavioral and computational studies
Diwadkar, Vaibhav A.; Flaugher, Brad; Jones, Trevor; Zalányi, László; Ujfalussy, Balázs; Keshavan, Matcheri S.
2008-01-01
Associative learning is a central building block of human cognition and in large part depends on mechanisms of synaptic plasticity, memory capacity and fronto–hippocampal interactions. A disorder like schizophrenia is thought to be characterized by altered plasticity, and impaired frontal and hippocampal function. Understanding the expression of this dysfunction through appropriate experimental studies, and understanding the processes that may give rise to impaired behavior through biologically plausible computational models will help clarify the nature of these deficits. We present a preliminary computational model designed to capture learning dynamics in healthy control and schizophrenia subjects. Experimental data was collected on a spatial-object paired-associate learning task. The task evinces classic patterns of negatively accelerated learning in both healthy control subjects and patients, with patients demonstrating lower rates of learning than controls. Our rudimentary computational model of the task was based on biologically plausible assumptions, including the separation of dorsal/spatial and ventral/object visual streams, implementation of rules of learning, the explicit parameterization of learning rates (a plausible surrogate for synaptic plasticity), and learning capacity (a plausible surrogate for memory capacity). Reductions in learning dynamics in schizophrenia were well-modeled by reductions in learning rate and learning capacity. The synergy between experimental research and a detailed computational model of performance provides a framework within which to infer plausible biological bases of impaired learning dynamics in schizophrenia. PMID:19003486
Aβ Damages Learning and Memory in Alzheimer's Disease Rats with Kidney-Yang Deficiency
Qi, Dongmei; Qiao, Yongfa; Zhang, Xin; Yu, Huijuan; Cheng, Bin; Qiao, Haifa
2012-01-01
Previous studies demonstrated that Alzheimer's disease was considered as the consequence produced by deficiency of Kidney essence. However, the mechanism underlying the symptoms also remains elusive. Here we report that spatial learning and memory, escape, and swimming capacities were damaged significantly in Kidney-yang deficiency rats. Indeed, both hippocampal Aβ 40 and 42 increases in Kidney-yang deficiency contribute to the learning and memory impairments. Specifically, damage of synaptic plasticity is involved in the learning and memory impairment of Kidney-yang deficiency rats. We determined that the learning and memory damage in Kidney-yang deficiency due to synaptic plasticity impairment and increases of Aβ 40 and 42 was not caused via NMDA receptor internalization induced by Aβ increase. β-Adrenergic receptor agonist can rescue the impaired long-term potential (LTP) in Kidney-yang rats. Taken together, our results suggest that spatial learning and memory inhibited in Kidney-yang deficiency might be induced by Aβ increase and the decrease of β 2 receptor function in glia. PMID:22645624
Ramsey, Mary E.; Vu, Wendy; Cummings, Molly E.
2014-01-01
Social behaviours such as mate choice require context-specific responses, often with evolutionary consequences. Increasing evidence indicates that the behavioural plasticity associated with mate choice involves learning. For example, poeciliids show age-dependent changes in female preference functions and express synaptic-plasticity-associated molecular markers during mate choice. Here, we test whether social cognition is necessary for female preference behaviour by blocking the central player in synaptic plasticity, NMDAR (N-methyl d-aspartate receptor), in a poeciliid fish, Xiphophorus nigrensis. After subchronic exposure to NMDAR antagonist MK-801, female preference behaviours towards males were dramatically reduced. Overall activity levels were unaffected, but there was a directional shift from ‘social’ behaviours towards neutral activity. Multivariate gene expression patterns significantly discriminated between females with normal versus disrupted plasticity processes and correlated with preference behaviours—not general activity. Furthermore, molecular patterns support a distinction between ‘preference’ (e.g. neuroserpin, neuroligin-3, NMDAR) and ‘sociality’ (isotocin and vasotocin) gene clusters, highlighting a possible conservation between NMDAR disruption and nonapeptides in modulating behaviour. Our results suggest that mate preference may involve greater social memory processing than overall sociality, and that poeciliid preference functions integrate synaptic-plasticity-oriented ‘preference’ pathways with overall sociality to invoke dynamic, context-specific responses towards favoured males and away from unfavoured males. PMID:24807251
Weiler, Nicholas C; Collman, Forrest; Vogelstein, Joshua T; Burns, Randal; Smith, Stephen J
2014-01-01
A major question in neuroscience is how diverse subsets of synaptic connections in neural circuits are affected by experience dependent plasticity to form the basis for behavioral learning and memory. Differences in protein expression patterns at individual synapses could constitute a key to understanding both synaptic diversity and the effects of plasticity at different synapse populations. Our approach to this question leverages the immunohistochemical multiplexing capability of array tomography (ATomo) and the columnar organization of mouse barrel cortex to create a dataset comprising high resolution volumetric images of spared and deprived cortical whisker barrels stained for over a dozen synaptic molecules each. These dataset has been made available through the Open Connectome Project for interactive online viewing, and may also be downloaded for offline analysis using web, Matlab, and other interfaces. PMID:25977797
Weiler, Nicholas C; Collman, Forrest; Vogelstein, Joshua T; Burns, Randal; Smith, Stephen J
2014-01-01
A major question in neuroscience is how diverse subsets of synaptic connections in neural circuits are affected by experience dependent plasticity to form the basis for behavioral learning and memory. Differences in protein expression patterns at individual synapses could constitute a key to understanding both synaptic diversity and the effects of plasticity at different synapse populations. Our approach to this question leverages the immunohistochemical multiplexing capability of array tomography (ATomo) and the columnar organization of mouse barrel cortex to create a dataset comprising high resolution volumetric images of spared and deprived cortical whisker barrels stained for over a dozen synaptic molecules each. These dataset has been made available through the Open Connectome Project for interactive online viewing, and may also be downloaded for offline analysis using web, Matlab, and other interfaces.
Calmodulin-regulated adenylyl cyclases and neuromodulation.
Xia, Z; Storm, D R
1997-06-01
Coincidence detection and crosstalk between signal transduction systems play very important regulatory roles in the nervous system, particularly in the regulation of transcription. Coupling of the Ca2+ and cAMP regulatory systems by calmodulin-regulated adenylyl cyclases is hypothesized to be important for some forms of synaptic plasticity, neuroendocrine function, and olfactory detection. Recent studies of a mutant mouse deficient in type I calmodulin-sensitive adenylyl cyclase have provided the first evidence that adenylyl cyclases are important for synaptic plasticity, as well as for learning and memory in vertebrates.
Spontaneous neuronal activity as a self-organized critical phenomenon
NASA Astrophysics Data System (ADS)
de Arcangelis, L.; Herrmann, H. J.
2013-01-01
Neuronal avalanches are a novel mode of activity in neuronal networks, experimentally found in vitro and in vivo, and exhibit a robust critical behaviour. Avalanche activity can be modelled within the self-organized criticality framework, including threshold firing, refractory period and activity-dependent synaptic plasticity. The size and duration distributions confirm that the system acts in a critical state, whose scaling behaviour is very robust. Next, we discuss the temporal organization of neuronal avalanches. This is given by the alternation between states of high and low activity, named up and down states, leading to a balance between excitation and inhibition controlled by a single parameter. During these periods both the single neuron state and the network excitability level, keeping memory of past activity, are tuned by homeostatic mechanisms. Finally, we verify if a system with no characteristic response can ever learn in a controlled and reproducible way. Learning in the model occurs via plastic adaptation of synaptic strengths by a non-uniform negative feedback mechanism. Learning is a truly collective process and the learning dynamics exhibits universal features. Even complex rules can be learned provided that the plastic adaptation is sufficiently slow.
Cuthbert, Peter C; Stanford, Lianne E; Coba, Marcelo P; Ainge, James A; Fink, Ann E; Opazo, Patricio; Delgado, Jary Y; Komiyama, Noboru H; O'Dell, Thomas J; Grant, Seth G N
2007-03-07
Understanding the mechanisms whereby information encoded within patterns of action potentials is deciphered by neurons is central to cognitive psychology. The multiprotein complexes formed by NMDA receptors linked to synaptic membrane-associated guanylate kinase (MAGUK) proteins including synapse-associated protein 102 (SAP102) and other associated proteins are instrumental in these processes. Although humans with mutations in SAP102 show mental retardation, the physiological and biochemical mechanisms involved are unknown. Using SAP102 knock-out mice, we found specific impairments in synaptic plasticity induced by selective frequencies of stimulation that also required extracellular signal-regulated kinase signaling. This was paralleled by inflexibility and impairment in spatial learning. Improvement in spatial learning performance occurred with extra training despite continued use of a suboptimal search strategy, and, in a separate nonspatial task, the mutants again deployed a different strategy. Double-mutant analysis of postsynaptic density-95 and SAP102 mutants indicate overlapping and specific functions of the two MAGUKs. These in vivo data support the model that specific MAGUK proteins couple the NMDA receptor to distinct downstream signaling pathways. This provides a mechanism for discriminating patterns of synaptic activity that lead to long-lasting changes in synaptic strength as well as distinct aspects of cognition in the mammalian nervous system.
Convergent evidence for abnormal striatal synaptic plasticity in dystonia
Peterson, David A.; Sejnowski, Terrence J.; Poizner, Howard
2010-01-01
Dystonia is a functionally disabling movement disorder characterized by abnormal movements and postures. Although substantial recent progress has been made in identifying genetic factors, the pathophysiology of the disease remains a mystery. A provocative suggestion gaining broader acceptance is that some aspect of neural plasticity may be abnormal. There is also evidence that, at least in some forms of dystonia, sensorimotor “use” may be a contributing factor. Most empirical evidence of abnormal plasticity in dystonia comes from measures of sensorimotor cortical organization and physiology. However, the basal ganglia also play a critical role in sensorimotor function. Furthermore, the basal ganglia are prominently implicated in traditional models of dystonia, are the primary targets of stereotactic neurosurgical interventions, and provide a neural substrate for sensorimotor learning influenced by neuromodulators. Our working hypothesis is that abnormal plasticity in the basal ganglia is a critical link between the etiology and pathophysiology of dystonia. In this review we set up the background for this hypothesis by integrating a large body of disparate indirect evidence that dystonia may involve abnormalities in synaptic plasticity in the striatum. After reviewing evidence implicating the striatum in dystonia, we focus on the influence of two neuromodulatory systems: dopamine and acetylcholine. For both of these neuromodulators, we first describe the evidence for abnormalities in dystonia and then the means by which it may influence striatal synaptic plasticity. Collectively, the evidence suggests that many different forms of dystonia may involve abnormal plasticity in the striatum. An improved understanding of these altered plastic processes would help inform our understanding of the pathophysiology of dystonia, and, given the role of the striatum in sensorimotor learning, provide a principled basis for designing therapies aimed at the dynamic processes linking etiology to pathophysiology of the disease. PMID:20005952
ERIC Educational Resources Information Center
Pu, Lu; Kopec, Ashley M.; Boyle, Heather D.; Carew, Thomas J.
2014-01-01
Neurotrophins are critically involved in developmental processes such as neuronal cell survival, growth, and differentiation, as well as in adult synaptic plasticity contributing to learning and memory. Our previous studies examining neurotrophins and memory formation in "Aplysia" showed that a TrkB ligand is required for MAPK…
Bian, Chen; Huang, Yan; Zhu, Haitao; Zhao, Yangang; Zhao, Jikai; Zhang, Jiqiang
2018-05-01
Steroids have been demonstrated to play profound roles in the regulation of hippocampal function by acting on their receptors, which need coactivators for their transcriptional activities. Previous studies have shown that steroid receptor coactivator-1 (SRC-1) is the predominant coactivator in the hippocampus, but its exact role and the underlying mechanisms remain unclear. In this study, we constructed SRC-1 RNA interference (RNAi) lentiviruses, injected them into the hippocampus of male mice, and then examined the changes in the expression of selected synaptic proteins, CA1 synapse density, postsynaptic density (PSD) thickness, and in vivo long-term potentiation (LTP). Spatial learning and memory behavior changes were investigated using the Morris water maze. We then transfected the lentiviruses into cultured hippocampal cells and examined the changes in synaptic protein and phospho-cyclic AMP response element-binding protein (pCREB) expression. The in vivo results showed that SRC-1 knockdown significantly decreased the expression of synaptic proteins and CA1 synapse density as well as PSD thickness; SRC-1 knockdown also significantly impaired in vivo LTP and disrupted spatial learning and memory. The in vitro results showed that while the expression of synaptic proteins was significantly decreased by SRC-1 knockdown, pCREB expression was also significantly decreased. The above results suggest a pivotal role of SRC-1 in the regulation of hippocampal synaptic plasticity and spatial learning and memory, strongly indicating SRC-1 may serve as a novel therapeutic target for hippocampus-dependent memory disorders. Copyright © 2018 IBRO. Published by Elsevier Ltd. All rights reserved.
More than synaptic plasticity: Role of nonsynaptic plasticity in learning and memory
Mozzachiodi, Riccardo; Byrne, John H.
2009-01-01
Decades of research on the cellular mechanisms of memory have led to the widely-held view that memories are stored as modifications of synaptic strength. These changes involve presynaptic processes, such as direct modulation of the release machinery, or postsynaptic processes, such as modulation of receptor properties. Parallel studies have revealed that memories may also be stored by nonsynaptic processes, such as modulation of voltage-dependent membrane conductances, which are expressed as changes in neuronal excitability. Although in some cases nonsynaptic changes may function as part of the engram itself, they may also serve as mechanisms through which a neural circuit is set to a permissive state to facilitate synaptic modifications that are necessary for memory storage. PMID:19889466
Valcarcel-Ares, Marta Noa; Tucsek, Zsuzsanna; Kiss, Tamas; Giles, Cory B; Tarantini, Stefano; Yabluchanskiy, Andriy; Balasubramanian, Priya; Gautam, Tripti; Galvan, Veronica; Ballabh, Praveen; Richardson, Arlan; Freeman, Willard M; Wren, Jonathan D; Deak, Ferenc; Ungvari, Zoltan; Csiszar, Anna
2018-06-08
There is strong evidence that obesity has deleterious effects on cognitive function of older adults. Previous preclinical studies demonstrate that obesity in aging is associated with a heightened state of systemic inflammation, which exacerbates blood brain barrier disruption, promoting neuroinflammation and oxidative stress. To test the hypothesis that synergistic effects of obesity and aging on inflammatory processes exert deleterious effects on hippocampal function, young and aged C57BL/6 mice were rendered obese by chronic feeding of a high fat diet followed by assessment of learning and memory function, measurement of hippocampal long-term potentiation (LTP), assessment of changes in hippocampal expression of genes relevant for synaptic function and determination of synaptic density. Because there is increasing evidence that altered production of lipid mediators modulate LTP, neuroinflammation and neurovascular coupling responses, the effects of obesity on hippocampal levels of relevant eicosanoid mediators were also assessed. We found that aging exacerbates obesity-induced microglia activation, which is associated with deficits in hippocampal-dependent learning and memory tests, impaired LTP, decreased synaptic density and dysregulation of genes involved in regulation of synaptic plasticity. Obesity in aging also resulted in an altered hippocampal eicosanoid profile, including decreases in vasodilator and pro-LTP epoxy-eicosatrienoic acids (EETs). Collectively, our results taken together with previous findings suggest that obesity in aging promotes hippocampal inflammation, which in turn may contribute to synaptic dysfunction and cognitive impairment.
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
The schizophrenia risk gene product miR-137 alters presynaptic plasticity
Siegert, Sandra; Seo, Jinsoo; Kwon, Ester J.; Rudenko, Andrii; Cho, Sukhee; Wang, Wenyuan; Flood, Zachary; Martorell, Anthony J.; Ericsson, Maria; Mungenast, Alison E.; Tsai, Li-Huei
2015-01-01
Non-coding variants in the human MIR137 gene locus increase schizophrenia risk at a genome-wide significance level. However, the functional consequence of these risk alleles is unknown. Here, we examined induced human neurons harboring the minor alleles of four disease-associated single nucleotide polymorphisms (SNPs) in MIR137, and observed increased MIR137 levels compared to major allele-carrying cells. We found that miR-137 gain-of-function causes downregulation of the presynaptic target genes, Complexin-1 (Cplx1), Nsf, and Synaptotagmin-1 (Syt1), leading to impaired vesicle release. In vivo, miR-137 gain-of-function results in changes in synaptic vesicle pool distribution, impaired mossy fiber-LTP induction and deficits in hippocampus-dependent learning and memory. By sequestering endogenous miR-137, we were able to ameliorate the synaptic phenotypes. Moreover, reinstatement of Syt1 expression partially restored synaptic plasticity, demonstrating the importance of Syt1 as a miR-137 target. Our data provide new insight into the mechanism by which miR-137 dysregulation can impair synaptic plasticity in the hippocampus. PMID:26005852
Butts, Daniel A; Kanold, Patrick O; Shatz, Carla J
2007-01-01
Patterned spontaneous activity in the developing retina is necessary to drive synaptic refinement in the lateral geniculate nucleus (LGN). Using perforated patch recordings from neurons in LGN slices during the period of eye segregation, we examine how such burst-based activity can instruct this refinement. Retinogeniculate synapses have a novel learning rule that depends on the latencies between pre- and postsynaptic bursts on the order of one second: coincident bursts produce long-lasting synaptic enhancement, whereas non-overlapping bursts produce mild synaptic weakening. It is consistent with “Hebbian” development thought to exist at this synapse, and we demonstrate computationally that such a rule can robustly use retinal waves to drive eye segregation and retinotopic refinement. Thus, by measuring plasticity induced by natural activity patterns, synaptic learning rules can be linked directly to their larger role in instructing the patterning of neural connectivity. PMID:17341130
Bowling, Heather; Bhattacharya, Aditi; Klann, Eric; Chao, Moses V
2016-03-01
Brain-derived neurotrophic factor (BDNF) plays an important role in neurodevelopment, synaptic plasticity, learning and memory, and in preventing neurodegeneration. Despite decades of investigations into downstream signaling cascades and changes in cellular processes, the mechanisms of how BDNF reshapes circuits in vivo remain unclear. This informational gap partly arises from the fact that the bulk of studies into the molecular actions of BDNF have been performed in dissociated neuronal cultures, while the majority of studies on synaptic plasticity, learning and memory were performed in acute brain slices or in vivo. A recent study by Bowling-Bhattacharya et al., measured the proteomic changes in acute adult hippocampal slices following treatment and reported changes in proteins of neuronal and non-neuronal origin that may in concert modulate synaptic release and secretion in the slice. In this paper, we place these findings into the context of existing literature and discuss how they impact our understanding of how BDNF can reshape the brain.
Spinal Plasticity and Behavior: BDNF-Induced Neuromodulation in Uninjured and Injured Spinal Cord
Huie, J. Russell
2016-01-01
Brain-derived neurotrophic factor (BDNF) is a member of the neurotrophic factor family of signaling molecules. Since its discovery over three decades ago, BDNF has been identified as an important regulator of neuronal development, synaptic transmission, and cellular and synaptic plasticity and has been shown to function in the formation and maintenance of certain forms of memory. Neural plasticity that underlies learning and memory in the hippocampus shares distinct characteristics with spinal cord nociceptive plasticity. Research examining the role BDNF plays in spinal nociception and pain overwhelmingly suggests that BDNF promotes pronociceptive effects. BDNF induces synaptic facilitation and engages central sensitization-like mechanisms. Also, peripheral injury-induced neuropathic pain is often accompanied with increased spinal expression of BDNF. Research has extended to examine how spinal cord injury (SCI) influences BDNF plasticity and the effects BDNF has on sensory and motor functions after SCI. Functional recovery and adaptive plasticity after SCI are typically associated with upregulation of BDNF. Although neuropathic pain is a common consequence of SCI, the relation between BDNF and pain after SCI remains elusive. This article reviews recent literature and discusses the diverse actions of BDNF. We also highlight similarities and differences in BDNF-induced nociceptive plasticity in naïve and SCI conditions. PMID:27721996
McKinstry, Jeffrey L; Edelman, Gerald M
2013-01-01
Animal behavior often involves a temporally ordered sequence of actions learned from experience. Here we describe simulations of interconnected networks of spiking neurons that learn to generate patterns of activity in correct temporal order. The simulation consists of large-scale networks of thousands of excitatory and inhibitory neurons that exhibit short-term synaptic plasticity and spike-timing dependent synaptic plasticity. The neural architecture within each area is arranged to evoke winner-take-all (WTA) patterns of neural activity that persist for tens of milliseconds. In order to generate and switch between consecutive firing patterns in correct temporal order, a reentrant exchange of signals between these areas was necessary. To demonstrate the capacity of this arrangement, we used the simulation to train a brain-based device responding to visual input by autonomously generating temporal sequences of motor actions.
Liu, Yuqiang; Chen, Cui; Liu, Yunlong; Li, Wei; Wang, Zhihong; Sun, Qifeng; Zhou, Hang; Chen, Xiangjun; Yu, Yongchun; Wang, Yun; Abumaria, Nashat
2018-06-19
The TRPM7 chanzyme contributes to several biological and pathological processes in different tissues. However, its role in the CNS under physiological conditions remains unclear. Here, we show that TRPM7 knockdown in hippocampal neurons reduces structural synapse density. The synapse density is rescued by the α-kinase domain in the C terminus but not by the ion channel region of TRPM7 or by increasing extracellular concentrations of Mg 2+ or Zn 2+ . Early postnatal conditional knockout of TRPM7 in mice impairs learning and memory and reduces synapse density and plasticity. TRPM7 knockdown in the hippocampus of adult rats also impairs learning and memory and reduces synapse density and synaptic plasticity. In knockout mice, restoring expression of the α-kinase domain in the brain rescues synapse density/plasticity and memory, probably by interacting with and phosphorylating cofilin. These results suggest that brain TRPM7 is important for having normal synaptic and cognitive functions under physiological, non-pathological conditions. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.
Modulating STDP Balance Impacts the Dendritic Mosaic
Iannella, Nicolangelo; Launey, Thomas
2017-01-01
The ability for cortical neurons to adapt their input/output characteristics and information processing capabilities ultimately relies on the interplay between synaptic plasticity, synapse location, and the nonlinear properties of the dendrite. Collectively, they shape both the strengths and spatial arrangements of convergent afferent inputs to neuronal dendrites. Recent experimental and theoretical studies support a clustered plasticity model, a view that synaptic plasticity promotes the formation of clusters or hotspots of synapses sharing similar properties. We have previously shown that spike timing-dependent plasticity (STDP) can lead to synaptic efficacies being arranged into spatially segregated clusters. This effectively partitions the dendritic tree into a tessellated imprint which we have called a dendritic mosaic. Here, using a biophysically detailed neuron model of a reconstructed layer 2/3 pyramidal cell and STDP learning, we investigated the impact of altered STDP balance on forming such a spatial organization. We show that cluster formation and extend depend on several factors, including the balance between potentiation and depression, the afferents' mean firing rate and crucially on the dendritic morphology. We find that STDP balance has an important role to play for this emergent mode of spatial organization since any imbalances lead to severe degradation- and in some case even destruction- of the mosaic. Our model suggests that, over a broad range of of STDP parameters, synaptic plasticity shapes the spatial arrangement of synapses, favoring the formation of clustered efficacy engrams. PMID:28649195
Minatohara, Keiichiro; Akiyoshi, Mika; Okuno, Hiroyuki
2016-01-01
In the brain, neuronal gene expression is dynamically changed in response to neuronal activity. In particular, the expression of immediate-early genes (IEGs) such as egr-1, c-fos, and Arc is rapidly and selectively upregulated in subsets of neurons in specific brain regions associated with learning and memory formation. IEG expression has therefore been widely used as a molecular marker for neuronal populations that undergo plastic changes underlying formation of long-term memory. In recent years, optogenetic and pharmacogenetic studies of neurons expressing c-fos or Arc have revealed that, during learning, IEG-positive neurons encode and store information that is required for memory recall, suggesting that they may be involved in formation of the memory trace. However, despite accumulating evidence for the role of IEGs in synaptic plasticity, the molecular and cellular mechanisms associated with this process remain unclear. In this review, we first summarize recent literature concerning the role of IEG-expressing neuronal ensembles in organizing the memory trace. We then focus on the physiological significance of IEGs, especially Arc, in synaptic plasticity, and describe our hypotheses about the importance of Arc expression in various types of input-specific circuit reorganization. Finally, we offer perspectives on Arc function that would unveil the role of IEG-expressing neurons in the formation of memory traces in the hippocampus and other brain areas. PMID:26778955
Srinivasa, Narayan; Jiang, Qin
2013-01-01
This study describes a spiking model that self-organizes for stable formation and maintenance of orientation and ocular dominance maps in the visual cortex (V1). This self-organization process simulates three development phases: an early experience-independent phase, a late experience-independent phase and a subsequent refinement phase during which experience acts to shape the map properties. The ocular dominance maps that emerge accommodate the two sets of monocular inputs that arise from the lateral geniculate nucleus (LGN) to layer 4 of V1. The orientation selectivity maps that emerge feature well-developed iso-orientation domains and fractures. During the last two phases of development the orientation preferences at some locations appear to rotate continuously through ±180° along circular paths and referred to as pinwheel-like patterns but without any corresponding point discontinuities in the orientation gradient maps. The formation of these functional maps is driven by balanced excitatory and inhibitory currents that are established via synaptic plasticity based on spike timing for both excitatory and inhibitory synapses. The stability and maintenance of the formed maps with continuous synaptic plasticity is enabled by homeostasis caused by inhibitory plasticity. However, a prolonged exposure to repeated stimuli does alter the formed maps over time due to plasticity. The results from this study suggest that continuous synaptic plasticity in both excitatory neurons and interneurons could play a critical role in the formation, stability, and maintenance of functional maps in the cortex. PMID:23450808
Yu, Qiang; Tang, Huajin; Tan, Kay Chen; Li, Haizhou
2013-01-01
A new learning rule (Precise-Spike-Driven (PSD) Synaptic Plasticity) is proposed for processing and memorizing spatiotemporal patterns. PSD is a supervised learning rule that is analytically derived from the traditional Widrow-Hoff rule and can be used to train neurons to associate an input spatiotemporal spike pattern with a desired spike train. Synaptic adaptation is driven by the error between the desired and the actual output spikes, with positive errors causing long-term potentiation and negative errors causing long-term depression. The amount of modification is proportional to an eligibility trace that is triggered by afferent spikes. The PSD rule is both computationally efficient and biologically plausible. The properties of this learning rule are investigated extensively through experimental simulations, including its learning performance, its generality to different neuron models, its robustness against noisy conditions, its memory capacity, and the effects of its learning parameters. Experimental results show that the PSD rule is capable of spatiotemporal pattern classification, and can even outperform a well studied benchmark algorithm with the proposed relative confidence criterion. The PSD rule is further validated on a practical example of an optical character recognition problem. The results again show that it can achieve a good recognition performance with a proper encoding. Finally, a detailed discussion is provided about the PSD rule and several related algorithms including tempotron, SPAN, Chronotron and ReSuMe.
Yu, Qiang; Tang, Huajin; Tan, Kay Chen; Li, Haizhou
2013-01-01
A new learning rule (Precise-Spike-Driven (PSD) Synaptic Plasticity) is proposed for processing and memorizing spatiotemporal patterns. PSD is a supervised learning rule that is analytically derived from the traditional Widrow-Hoff rule and can be used to train neurons to associate an input spatiotemporal spike pattern with a desired spike train. Synaptic adaptation is driven by the error between the desired and the actual output spikes, with positive errors causing long-term potentiation and negative errors causing long-term depression. The amount of modification is proportional to an eligibility trace that is triggered by afferent spikes. The PSD rule is both computationally efficient and biologically plausible. The properties of this learning rule are investigated extensively through experimental simulations, including its learning performance, its generality to different neuron models, its robustness against noisy conditions, its memory capacity, and the effects of its learning parameters. Experimental results show that the PSD rule is capable of spatiotemporal pattern classification, and can even outperform a well studied benchmark algorithm with the proposed relative confidence criterion. The PSD rule is further validated on a practical example of an optical character recognition problem. The results again show that it can achieve a good recognition performance with a proper encoding. Finally, a detailed discussion is provided about the PSD rule and several related algorithms including tempotron, SPAN, Chronotron and ReSuMe. PMID:24223789
ERIC Educational Resources Information Center
Zheng, Fei; Zhang, Ming; Ding, Qi; Sethna, Ferzin; Yan, Lily; Moon, Changjong; Yang, Miyoung; Wang, Hongbing
2016-01-01
Mental health and cognitive functions are influenced by both genetic and environmental factors. Although having active lifestyle with physical exercise improves learning and memory, how it interacts with the specific key molecular regulators of synaptic plasticity is largely unknown. Here, we examined the effects of voluntary running on long-term…
Contributions of Bcl-xL to acute and long term changes in bioenergetics during neuronal plasticity.
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.
Synaptic Plasticity, Dementia and Alzheimer Disease.
Skaper, Stephen D; Facci, Laura; Zusso, Morena; Giusti, Pietro
2017-01-01
Neuroplasticity is not only shaped by learning and memory but is also a mediator of responses to neuron attrition and injury (compensatory plasticity). As an ongoing process it reacts to neuronal cell activity and injury, death, and genesis, which encompasses the modulation of structural and functional processes of axons, dendrites, and synapses. The range of structural elements that comprise plasticity includes long-term potentiation (a cellular correlate of learning and memory), synaptic efficacy and remodelling, synaptogenesis, axonal sprouting and dendritic remodelling, and neurogenesis and recruitment. Degenerative diseases of the human brain continue to pose one of biomedicine's most intractable problems. Research on human neurodegeneration is now moving from descriptive to mechanistic analyses. At the same time, it is increasing apparently that morphological lesions traditionally used by neuropathologists to confirm post-mortem clinical diagnosis might furnish us with an experimentally tractable handle to understand causative pathways. Consider the aging-dependent neurodegenerative disorder Alzheimer's disease (AD) which is characterised at the neuropathological level by deposits of insoluble amyloid β-peptide (Aβ) in extracellular plaques and aggregated tau protein, which is found largely in the intracellular neurofibrillary tangles. We now appreciate that mild cognitive impairment in early AD may be due to synaptic dysfunction caused by accumulation of non-fibrillar, oligomeric Aβ, occurring well in advance of evident widespread synaptic loss and neurodegeneration. Soluble Aβ oligomers can adversely affect synaptic structure and plasticity at extremely low concentrations, although the molecular substrates by which synaptic memory mechanisms are disrupted remain to be fully elucidated. The dendritic spine constitutes a primary locus of excitatory synaptic transmission in the mammalian central nervous system. These structures protruding from dendritic shafts undergo dynamic changes in number, size and shape in response to variations in hormonal status, developmental stage, and changes in afferent input. It is perhaps not unexpected that loss of spine density may be linked to cognitive and memory impairment in AD, although the underlying mechanism(s) remain uncertain. This article aims to present a critical overview of current knowledge on the bases of synaptic dysfunction in neurodegenerative diseases, with a focus on AD, and will cover amyloid- and nonamyloid- driven mechanisms. We will consider also emerging data dealing with potential therapeutic approaches for ameliorating the cognitive and memory deficits associated with these disorders. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.
A Presynaptic Role for FMRP during Protein Synthesis-Dependent Long-Term Plasticity in "Aplysia"
ERIC Educational Resources Information Center
Till, Sally M.; Li, Hsiu-Ling; Miniaci, Maria Concetta; Kandel, Eric R.; Choi, Yun-Beom
2011-01-01
Loss of the Fragile X mental retardation protein (FMRP) is associated with presumed postsynaptic deficits in mouse models of Fragile X syndrome. However, the possible presynaptic roles of FMRP in learning-related plasticity have received little attention. As a result, the mechanisms whereby FMRP influences synaptic function remain poorly…
Zhang, Zhan-Chi; Luan, Feng; Xie, Chun-Yan; Geng, Dan-Dan; Wang, Yan-Yong; Ma, Jun
2015-06-01
In the aging brain, cognitive function gradually declines and causes a progressive reduction in the structural and functional plasticity of the hippocampus. Transcranial magnetic stimulation is an emerging and novel neurological and psychiatric tool used to investigate the neurobiology of cognitive function. Recent studies have demonstrated that low-frequency transcranial magnetic stimulation (≤1 Hz) ameliorates synaptic plasticity and spatial cognitive deficits in learning-impaired mice. However, the mechanisms by which this treatment improves these deficits during normal aging are still unknown. Therefore, the current study investigated the effects of transcranial magnetic stimulation on the brain-derived neurotrophic factor signal pathway, synaptic protein markers, and spatial memory behavior in the hippocampus of normal aged mice. The study also investigated the downstream regulator, Fyn kinase, and the downstream effectors, synaptophysin and growth-associated protein 43 (both synaptic markers), to determine the possible mechanisms by which transcranial magnetic stimulation regulates cognitive capacity. Transcranial magnetic stimulation with low intensity (110% average resting motor threshold intensity, 1 Hz) increased mRNA and protein levels of brain-derived neurotrophic factor, tropomyosin receptor kinase B, and Fyn in the hippocampus of aged mice. The treatment also upregulated the mRNA and protein expression of synaptophysin and growth-associated protein 43 in the hippocampus of these mice. In conclusion, brain-derived neurotrophic factor signaling may play an important role in sustaining and regulating structural synaptic plasticity induced by transcranial magnetic stimulation in the hippocampus of aging mice, and Fyn may be critical during this regulation. These responses may change the structural plasticity of the aging hippocampus, thereby improving cognitive function.
Stampanoni Bassi, Mario; Garofalo, Sara; Marfia, Girolama A; Gilio, Luana; Simonelli, Ilaria; Finardi, Annamaria; Furlan, Roberto; Sancesario, Giulia M; Di Giandomenico, Jonny; Storto, Marianna; Mori, Francesco; Centonze, Diego; Iezzi, Ennio
2017-01-01
Cognitive deficits are frequently observed in multiple sclerosis (MS), mainly involving processing speed and episodic memory. Both demyelination and gray matter atrophy can contribute to cognitive deficits in MS. In recent years, neuroinflammation is emerging as a new factor influencing clinical course in MS. Inflammatory cytokines induce synaptic dysfunction in MS. Synaptic plasticity occurring within hippocampal structures is considered as one of the basic physiological mechanisms of learning and memory. In experimental models of MS, hippocampal plasticity is profoundly altered by proinflammatory cytokines. Although mechanisms of inflammation-induced hippocampal pathology in MS are not completely understood, alteration of Amyloid-β (Aβ) metabolism is emerging as a key factor linking together inflammation, synaptic plasticity and neurodegeneration in different neurological diseases. We explored the correlation between concentrations of Aβ 1-42 and the levels of some proinflammatory and anti-inflammatory cytokines (interleukin-1β (IL-1β), IL1-ra, IL-8, IL-10, IL-12, tumor necrosis factor α (TNFα), interferon γ (IFNγ)) in the cerebrospinal fluid (CSF) of 103 remitting MS patients. CSF levels of Aβ 1-42 were negatively correlated with the proinflammatory cytokine IL-8 and positively correlated with the anti-inflammatory molecules IL-10 and interleukin-1 receptor antagonist (IL-1ra). Other correlations, although noticeable, were either borderline or not significant. Our data show that an imbalance between proinflammatory and anti-inflammatory cytokines may lead to altered Aβ homeostasis, representing a key factor linking together inflammation, synaptic plasticity and cognitive dysfunction in MS. This could be relevant to identify novel therapeutic approaches to hinder the progression of cognitive dysfunction in MS.
Bin, Na-Ryum; Ma, Ke; Harada, Hidekiyo; Tien, Chi-Wei; Bergin, Fiona; Sugita, Kyoko; Luyben, Thomas T; Narimatsu, Masahiro; Jia, Zhengping; Wrana, Jeffrey L; Monnier, Philippe P; Zhang, Liang; Okamoto, Kenichi; Sugita, Shuzo
2018-06-05
Trafficking of neurotransmitter receptors on postsynaptic membranes is critical for basal neurotransmission and synaptic plasticity, yet the underlying mechanisms remain elusive. Here, we investigated the role of syntaxin 4 in postsynaptic hippocampal CA1 neurons by analyzing conditional knockout (syntaxin 4 cKO) mice. We show that syntaxin 4 cKO resulted in reduction of basal neurotransmission without changes in paired-pulse ratios. Both α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) and N-methyl-d-aspartic acid (NMDA) receptor-mediated charge transfers were diminished. Patch-clamp experiments revealed that amplitudes, but not frequencies, of spontaneous excitatory postsynaptic currents are reduced. Syntaxin 4 knockout (KO) caused drastic reduction in expression of surface α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) and N-methyl-d-aspartic acid (NMDA) receptors in cultured hippocampal neurons. Furthermore, cKO caused defects in theta-burst stimulation induced long-term potentiation and spatial learning as assessed by a water maze task, indicating that synaptic plasticity was altered. Our data reveal a crucial role of syntaxin 4 in trafficking of ionotropic glutamate receptors that are essential for basal neurotransmission, synaptic plasticity, and spatial memory. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.
Elbaz, Idan; Lerer-Goldshtein, Tali; Okamoto, Hitoshi; Appelbaum, Lior
2015-04-01
Neuronal-activity-regulated pentraxin (NARP/NPTX2/NP2) is a secreted synaptic protein that regulates the trafficking of glutamate receptors and mediates learning, memory, and drug addiction. The role of NPTX2 in regulating structural synaptic plasticity and behavior in a developing vertebrate is indefinite. We characterized the expression of nptx2a in larvae and adult zebrafish and established a transcription activator-like effector nuclease (TALEN)-mediated nptx2a mutant (nptx2a(-/-)) to study the role of Nptx2a in regulating structural synaptic plasticity and behavior. Similar to mammals, the zebrafish nptx2a was expressed in excitatory neurons in the brain and spinal cord. Its expression was induced in response to a mechanosensory stimulus but did not change during day and night. Behavioral assays showed that loss of Nptx2a results in reduced locomotor response to light-to-dark transition states and to a sound stimulus. Live imaging of synapses using the transgenic nptx2a:GAL4VP16 zebrafish and a fluorescent presynaptic synaptophysin (SYP) marker revealed reduced synaptic density in the axons of the spinal motor neurons and the anterodorsal lateral-line ganglion (gAD), which regulate locomotor activity and locomotor response to mechanosensory stimuli, respectively. These results suggest that Nptx2a affects locomotor response to external stimuli by mediating structural synaptic plasticity in excitatory neuronal circuits. © FASEB.
Age-Dependent Deficits in Fear Learning in Heterozygous BDNF Knock-Out Mice
ERIC Educational Resources Information Center
Endres, Thomas; Lessmann, Volkmar
2012-01-01
Beyond its trophic function, the neurotrophin BDNF (brain-derived neurotrophic factor) is well known to crucially mediate synaptic plasticity and memory formation. Whereas recent studies suggested that acute BDNF/TrkB signaling regulates amygdala-dependent fear learning, no impairments of cued fear learning were reported in heterozygous BDNF…
Chambers, R. Andrew; Conroy, Susan K.
2010-01-01
Apoptotic and neurogenic events in the adult hippocampus are hypothesized to play a role in cognitive responses to new contexts. Corticosteroid-mediated stress responses and other neural processes invoked by substantially novel contextual changes may regulate these processes. Using elementary three-layer neural networks that learn by incremental synaptic plasticity, we explored whether the cognitive effects of differential regimens of neuronal turnover depend on the environmental context in terms of the degree of novelty in the new information to be learned. In “adult” networks that had achieved mature synaptic connectivity upon prior learning of the Roman alphabet, imposition of apoptosis/neurogenesis before learning increasingly novel information (alternate Roman < Russian < Hebrew) reveals optimality of informatic cost benefits when rates of turnover are geared in proportion to the degree of novelty. These findings predict that flexible control of rates of apoptosis–neurogenesis within plastic, mature neural systems optimizes learning attributes under varying degrees of contextual change, and that failures in this regulation may define a role for adult hippocampal neurogenesis in novelty- and stress-responsive psychiatric disorders. PMID:17214558
Chambers, R Andrew; Conroy, Susan K
2007-01-01
Apoptotic and neurogenic events in the adult hippocampus are hypothesized to play a role in cognitive responses to new contexts. Corticosteroid-mediated stress responses and other neural processes invoked by substantially novel contextual changes may regulate these processes. Using elementary three-layer neural networks that learn by incremental synaptic plasticity, we explored whether the cognitive effects of differential regimens of neuronal turnover depend on the environmental context in terms of the degree of novelty in the new information to be learned. In "adult" networks that had achieved mature synaptic connectivity upon prior learning of the Roman alphabet, imposition of apoptosis/neurogenesis before learning increasingly novel information (alternate Roman < Russian < Hebrew) reveals optimality of informatic cost benefits when rates of turnover are geared in proportion to the degree of novelty. These findings predict that flexible control of rates of apoptosis-neurogenesis within plastic, mature neural systems optimizes learning attributes under varying degrees of contextual change, and that failures in this regulation may define a role for adult hippocampal neurogenesis in novelty- and stress-responsive psychiatric disorders.
Cicvaric, Ana; Yang, Jiaye; Krieger, Sigurd; Khan, Deeba; Kim, Eun-Jung; Dominguez-Rodriguez, Manuel; Cabatic, Maureen; Molz, Barbara; Acevedo Aguilar, Juan Pablo; Milicevic, Radoslav; Smani, Tarik; Breuss, Johannes M.; Kerjaschki, Dontscho; Pollak, Daniela D.; Uhrin, Pavel; Monje, Francisco J.
2016-01-01
Abstract Introduction: Podoplanin is a cell-surface glycoprotein constitutively expressed in the brain and implicated in human brain tumorigenesis. The intrinsic function of podoplanin in brain neurons remains however uncharacterized. Materials and methods: Using an established podoplanin-knockout mouse model and electrophysiological, biochemical, and behavioral approaches, we investigated the brain neuronal role of podoplanin. Results: Ex-vivo electrophysiology showed that podoplanin deletion impairs dentate gyrus synaptic strengthening. In vivo, podoplanin deletion selectively impaired hippocampus-dependent spatial learning and memory without affecting amygdala-dependent cued fear conditioning. In vitro, neuronal overexpression of podoplanin promoted synaptic activity and neuritic outgrowth whereas podoplanin-deficient neurons exhibited stunted outgrowth and lower levels of p-Ezrin, TrkA, and CREB in response to nerve growth factor (NGF). Surface Plasmon Resonance data further indicated a physical interaction between podoplanin and NGF. Discussion: This work proposes podoplanin as a novel component of the neuronal machinery underlying neuritogenesis, synaptic plasticity, and hippocampus-dependent memory functions. The existence of a relevant cross-talk between podoplanin and the NGF/TrkA signaling pathway is also for the first time proposed here, thus providing a novel molecular complex as a target for future multidisciplinary studies of the brain function in the physiology and the pathology.Key messagesPodoplanin, a protein linked to the promotion of human brain tumors, is required in vivo for proper hippocampus-dependent learning and memory functions.Deletion of podoplanin selectively impairs activity-dependent synaptic strengthening at the neurogenic dentate-gyrus and hampers neuritogenesis and phospho Ezrin, TrkA and CREB protein levels upon NGF stimulation.Surface plasmon resonance data indicates a physical interaction between podoplanin and NGF. On these grounds, a relevant cross-talk between podoplanin and NGF as well as a role for podoplanin in plasticity-related brain neuronal functions is here proposed. PMID:27558977
Berlucchi, Giovanni
2002-09-01
The Italian psychiatrist Ernesto Lugaro can be regarded as responsible for introducing the term plasticity into the neurosciences as early as 1906. By this term he meant that throughout life the anatomo-functional relations between neurons can change in an adaptive fashion to enable psychic maturation, learning, and even functional recovery after brain damage. Lugaro's concept of plasticity was strongly inspired by a neural hypothesis of learning and memory put forward in 1893 by his teacher Eugenio Tanzi. Tanzi postulated that practice and experience promote neuronal growth and shorten the minute spatial gaps between functionally associated neurons, thus facilitating their interactions. In addition to discovering the cerebellar cells known by his name and advancing profound speculations about the functions of the glia, Lugaro lucidly foresaw the chemical nature of synaptic transmission in the central nervous system, and was the first to propose the usage of the terms "nervous conduction" and "nervous transmission" in their currently accepted meaning.
Unified pre- and postsynaptic long-term plasticity enables reliable and flexible learning.
Costa, Rui Ponte; Froemke, Robert C; Sjöström, P Jesper; van Rossum, Mark Cw
2015-08-26
Although it is well known that long-term synaptic plasticity can be expressed both pre- and postsynaptically, the functional consequences of this arrangement have remained elusive. We show that spike-timing-dependent plasticity with both pre- and postsynaptic expression develops receptive fields with reduced variability and improved discriminability compared to postsynaptic plasticity alone. These long-term modifications in receptive field statistics match recent sensory perception experiments. Moreover, learning with this form of plasticity leaves a hidden postsynaptic memory trace that enables fast relearning of previously stored information, providing a cellular substrate for memory savings. Our results reveal essential roles for presynaptic plasticity that are missed when only postsynaptic expression of long-term plasticity is considered, and suggest an experience-dependent distribution of pre- and postsynaptic strength changes.
Cooke, Sam F.; Bear, Mark F.
2014-01-01
Donald Hebb chose visual learning in primary visual cortex (V1) of the rodent to exemplify his theories of how the brain stores information through long-lasting homosynaptic plasticity. Here, we revisit V1 to consider roles for bidirectional ‘Hebbian’ plasticity in the modification of vision through experience. First, we discuss the consequences of monocular deprivation (MD) in the mouse, which have been studied by many laboratories over many years, and the evidence that synaptic depression of excitatory input from the thalamus is a primary contributor to the loss of visual cortical responsiveness to stimuli viewed through the deprived eye. Second, we describe a less studied, but no less interesting form of plasticity in the visual cortex known as stimulus-selective response potentiation (SRP). SRP results in increases in the response of V1 to a visual stimulus through repeated viewing and bears all the hallmarks of perceptual learning. We describe evidence implicating an important role for potentiation of thalamo-cortical synapses in SRP. In addition, we present new data indicating that there are some features of this form of plasticity that cannot be fully accounted for by such feed-forward Hebbian plasticity, suggesting contributions from intra-cortical circuit components. PMID:24298166
Ataei, Negar; Sabzghabaee, Ali Mohammad; Movahedian, Ahmad
2015-01-01
Background: Long-term memory is based on synaptic plasticity, a series of biochemical mechanisms include changes in structure and proteins of brain's neurons. In this article, we systematically reviewed the studies that indicate calcium/calmodulin kinase II (CaMKII) is a ubiquitous molecule among different enzymes involved in human long-term memory and the main downstream signaling pathway of long-term memory. Methods: All of the observational, case–control and review studies were considered and evaluated by the search engines PubMed, Cochrane Central Register of Controlled Trials and ScienceDirect Scopus between 1990 and February 2015. We did not carry out meta-analysis. Results: At the first search, it was fined 1015 articles which included “synaptic plasticity” OR “neuronal plasticity” OR “synaptic density” AND memory AND “molecular mechanism” AND “calcium/calmodulin-dependent protein kinase II” OR CaMKII as the keywords. A total of 335 articles were duplicates in the databases and eliminated. A total of 680 title articles were evaluated. Finally, 40 articles were selected as reference. Conclusions: The studies have shown the most important intracellular signal of long-term memory is calcium-dependent signals. Calcium linked calmodulin can activate CaMKII. After receiving information for learning and memory, CaMKII is activated by Glutamate, the most important neurotransmitter for memory-related plasticity. Glutamate activates CaMKII and it plays some important roles in synaptic plasticity modification and long-term memory. PMID:26445635
Novel plasticity rule can explain the development of sensorimotor intelligence
Der, Ralf; Martius, Georg
2015-01-01
Grounding autonomous behavior in the nervous system is a fundamental challenge for neuroscience. In particular, self-organized behavioral development provides more questions than answers. Are there special functional units for curiosity, motivation, and creativity? This paper argues that these features can be grounded in synaptic plasticity itself, without requiring any higher-level constructs. We propose differential extrinsic plasticity (DEP) as a new synaptic rule for self-learning systems and apply it to a number of complex robotic systems as a test case. Without specifying any purpose or goal, seemingly purposeful and adaptive rhythmic behavior is developed, displaying a certain level of sensorimotor intelligence. These surprising results require no system-specific modifications of the DEP rule. They rather arise from the underlying mechanism of spontaneous symmetry breaking, which is due to the tight brain body environment coupling. The new synaptic rule is biologically plausible and would be an interesting target for neurobiological investigation. We also argue that this neuronal mechanism may have been a catalyst in natural evolution. PMID:26504200
Strekalova, Tatyana; Sun, Mu; Sibbe, Mirjam; Evers, Matthias; Dityatev, Alexander; Gass, Peter; Schachner, Melitta
2002-09-01
The extracellular matrix molecule tenascin-C (TN-C) has been shown to be involved in hippocampal synaptic plasticity in vitro. Here, we describe a deficit in hippocampus-dependent contextual memory in TN-C-deficient mice using the step-down avoidance paradigm. We further show that a fragment of TN-C containing the fibronectin type-III repeats 6-8 (FN6-8), but not a fragment containing repeats 3-5, bound to pyramidal and granule cell somata in the hippocampal formation of C57BL/6J mice and repelled axons of pyramidal neurons when presented as a border in vitro. Injection of the FN6-8 fragment into the hippocampus inhibited retention of memory in the step-down paradigm and reduced levels of long-term potentiation in the CA1 region of the hippocampus. In summary, our data show that TN-C is involved in hippocampus-dependent contextual memory and synaptic plasticity and identify the FN6-8 domain as one of molecular determinants mediating these functions.
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.
ERIC Educational Resources Information Center
Zhang, Xiaoqun; Yao, Ning; Chergui, Karima
2016-01-01
Several forms of long-term depression (LTD) of glutamatergic synaptic transmission have been identified in the dorsal striatum and in the nucleus accumbens (NAc). Such experience-dependent synaptic plasticity might play important roles in reward-related learning. The GABA[subscript A] receptor agonist muscimol was recently found to trigger a…
Yang, Kechun; Broussard, John I; Levine, Amber T; Jenson, Daniel; Arenkiel, Benjamin R; Dani, John A
2017-01-01
Physiological and behavioral evidence supports that dopamine (DA) receptor signaling influences hippocampal function. While several recent studies examined how DA influences CA1 plasticity and learning, there are fewer studies investigating the influence of DA signaling to the dentate gyrus. The dentate gyrus receives convergent cortical input through the perforant path fiber tracts and has been conceptualized to detect novelty in spatial memory tasks. To test whether DA-receptor activity influences novelty-detection, we used a novel object recognition (NOR) task where mice remember previously presented objects as an indication of learning. Although DA innervation arises from other sources and the main DA signaling may be from those sources, our molecular approaches verified that midbrain dopaminergic fibers also sparsely innervate the dentate gyrus. During the NOR task, wild-type mice spent significantly more time investigating novel objects rather than previously observed objects. Dentate granule cells in slices cut from those mice showed an increased AMPA/NMDA-receptor current ratio indicative of potentiated synaptic transmission. Post-training injection of a D1-like receptor antagonist not only effectively blocked the preference for the novel objects, but also prevented the increased AMPA/NMDA ratio. Consistent with that finding, neither NOR learning nor the increase in the AMPA/NMDA ratio were observed in DA-receptor KO mice under the same experimental conditions. The results indicate that DA-receptor signaling contributes to the successful completion of the NOR task and to the associated synaptic plasticity of the dentate gyrus that likely contributes to the learning. © 2016 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.
AHaH computing-from metastable switches to attractors to machine learning.
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.
AHaH Computing–From Metastable Switches to Attractors to Machine Learning
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
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.
Almaguer-Melian, William; Bergado-Rosado, Jorge; Pavón-Fuentes, Nancy; Alberti-Amador, Esteban; Mercerón-Martínez, Daymara; Frey, Julietta U
2012-01-17
Novelty processing can transform short-term into long-term memory. We propose that this memory-reinforcing effect of novelty could be explained by mechanisms outlined in the "synaptic tagging hypothesis." Initial short-term memory is sustained by a transient plasticity change at activated synapses and sets synaptic tags. These tags are later able to capture and process the plasticity-related proteins (PRPs), which are required to transform a short-term synaptic change into a long-term one. Novelty is involved in inducing the synthesis of PRPs [Moncada D, et al. (2011) Proc Natl Acad Sci USA 108:12937-12936], which are then captured by the tagged synapses, consolidating memory. In contrast to novelty, stress can impair learning, memory, and synaptic plasticity. Here, we address questions as to whether novelty-induced PRPs are able to prevent the loss of memory caused by stress and if the latter would not interact with the tag-setting process. We used water-maze (WM) training as a spatial learning paradigm to test our hypothesis. Stress was induced by a strong foot shock (FS; 5 × 1 mA, 2 s) applied 5 min after WM training. Our data show that FS reduced long-term but not short-term memory in the WM paradigm. This negative effect on memory consolidation was time- and training-dependent. Interestingly, novelty exposure prevented the stress-induced memory loss of the spatial task and increased BDNF and Arc expression. This rescuing effect was blocked by anisomycin, suggesting that WM-tagged synapses were not reset by FS and were thus able to capture the novelty-induced PRPs, re-establishing FS-impaired long-term memory.
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
ERIC Educational Resources Information Center
Aceves, Jose J.; Rueda-Orozco, Pavel E.; Hernandez-Martinez, Ricardo; Galarraga, Elvira; Bargas, Jose
2011-01-01
There is no hypothesis to explain how direct and indirect basal ganglia (BG) pathways interact to reach a balance during the learning of motor procedures. Both pathways converge in the substantia nigra pars reticulata (SNr) carrying the result of striatal processing. Unfortunately, the mechanisms that regulate synaptic plasticity in striatonigral…
Sandi, Carmen; Davies, Heather A; Cordero, M Isabel; Rodriguez, Jose J; Popov, Victor I; Stewart, Michael G
2003-06-01
The impact was examined of exposing rats to two life experiences of a very different nature (stress and learning) on synaptic structures in hippocampal area CA3. Rats were subjected to either (i) chronic restraint stress for 21 days, and/or (ii) spatial training in a Morris water maze. At the behavioural level, restraint stress induced an impairment of acquisition of the spatial response. Moreover, restraint stress and water maze training had contrasting impacts on CA3 synaptic morphometry. Chronic stress induced a loss of simple asymmetric synapses [those with an unperforated postsynaptic density (PSD)], whilst water maze learning reversed this effect, promoting a rapid recovery of stress-induced synaptic loss within 2-3 days following stress. In addition, in unstressed animals a correlation was found between learning efficiency and the density of synapses with an unperforated PSD: the better the performance in the water maze, the lower the synaptic density. Water maze training increased the number of perforated synapses (those with a segmented PSD) in CA3, both in stressed and, more notably, in unstressed rats. The distinct effects of stress and learning on CA3 synapses reported here provide a neuroanatomical basis for the reported divergent effects of these experiences on hippocampal synaptic activity, i.e. stress as a suppressor and learning as a promoter of synaptic plasticity.
Tissue Plasminogen Activator Induction in Purkinje Neurons After Cerebellar Motor Learning
NASA Astrophysics Data System (ADS)
Seeds, Nicholas W.; Williams, Brian L.; Bickford, Paula C.
1995-12-01
The cerebellar cortex is implicated in the learning of complex motor skills. This learning may require synaptic remodeling of Purkinje cell inputs. An extracellular serine protease, tissue plasminogen activator (tPA), is involved in remodeling various nonneural tissues and is associated with developing and regenerating neurons. In situ hybridization showed that expression of tPA messenger RNA was increased in the Purkinje neurons of rats within an hour of their being trained for a complex motor task. Antibody to tPA also showed the induction of tPA protein associated with cerebellar Purkinje cells. Thus, the induction of tPA during motor learning may play a role in activity-dependent synaptic plasticity.
Impaired Discrimination Learning in Mice Lacking the NMDA Receptor NR2A Subunit
ERIC Educational Resources Information Center
Brigman, Jonathan L.; Feyder, Michael; Saksida, Lisa M.; Bussey, Timothy J.; Mishina, Masayoshi; Holmes, Andrew
2008-01-01
N-Methyl-D-aspartate receptors (NMDARs) mediate certain forms of synaptic plasticity and learning. We used a touchscreen system to assess NR2A subunit knockout mice (KO) for (1) pairwise visual discrimination and reversal learning and (2) acquisition and extinction of an instrumental response requiring no pairwise discrimination. NR2A KO mice…
Stochastic Synapses Enable Efficient Brain-Inspired Learning Machines.
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
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
Kiyota, Tomomi; Morrison, Christine M; Tu, Guihua; Dyavarshetty, Bhagyalaxmi; Weir, Robert A; Zhang, Gang; Xiong, Huangui; Gendelman, Howard E
2015-01-01
Aberrations in hippocampal neurogenesis are associated with learning and memory, synaptic plasticity and neurodegeneration in Alzheimer’s disease (AD). However, the linkage between them, β-amyloidosis and neuroinflammation is not well understood. To this end, we generated a mouse overexpressing familial AD (FAD) mutant human presenilin-1 (PS1) crossed with a knockout (KO) of the CC-chemokine ligand 2 (CCL2) gene. The PS1/CCL2KO mice developed robust age-dependent deficits in hippocampal neurogenesis associated with impairments in learning and memory, synaptic plasticity and long-term potentiation. Neurogliogenesis gene profiling supported β-amyloid independent pathways for FAD-associated deficits in hippocampal neurogenesis. We conclude that these PS1/CCL2KO mice are suitable for studies linking host genetics, immunity and hippocampal function. PMID:26112421
Dendritic Learning as a Paradigm Shift in Brain Learning.
Sardi, Shira; Vardi, Roni; Goldental, Amir; Tugendhaft, Yael; Uzan, Herut; Kanter, Ido
2018-06-20
Experimental and theoretical results reveal a new underlying mechanism for fast brain learning process, dendritic learning, as opposed to the misdirected research in neuroscience over decades, which is based solely on slow synaptic plasticity. The presented paradigm indicates that learning occurs in closer proximity to the neuron, the computational unit, dendritic strengths are self-oscillating, and weak synapses, which comprise the majority of our brain and previously were assumed to be insignificant, play a key role in plasticity. The new learning sites of the brain call for a reevaluation of current treatments for disordered brain functionality and for a better understanding of proper chemical drugs and biological mechanisms to maintain, control and enhance learning.
Stampanoni Bassi, Mario; Garofalo, Sara; Marfia, Girolama A.; Gilio, Luana; Simonelli, Ilaria; Finardi, Annamaria; Furlan, Roberto; Sancesario, Giulia M.; Di Giandomenico, Jonny; Storto, Marianna; Mori, Francesco; Centonze, Diego; Iezzi, Ennio
2017-01-01
Cognitive deficits are frequently observed in multiple sclerosis (MS), mainly involving processing speed and episodic memory. Both demyelination and gray matter atrophy can contribute to cognitive deficits in MS. In recent years, neuroinflammation is emerging as a new factor influencing clinical course in MS. Inflammatory cytokines induce synaptic dysfunction in MS. Synaptic plasticity occurring within hippocampal structures is considered as one of the basic physiological mechanisms of learning and memory. In experimental models of MS, hippocampal plasticity is profoundly altered by proinflammatory cytokines. Although mechanisms of inflammation-induced hippocampal pathology in MS are not completely understood, alteration of Amyloid-β (Aβ) metabolism is emerging as a key factor linking together inflammation, synaptic plasticity and neurodegeneration in different neurological diseases. We explored the correlation between concentrations of Aβ1–42 and the levels of some proinflammatory and anti-inflammatory cytokines (interleukin-1β (IL-1β), IL1-ra, IL-8, IL-10, IL-12, tumor necrosis factor α (TNFα), interferon γ (IFNγ)) in the cerebrospinal fluid (CSF) of 103 remitting MS patients. CSF levels of Aβ1–42 were negatively correlated with the proinflammatory cytokine IL-8 and positively correlated with the anti-inflammatory molecules IL-10 and interleukin-1 receptor antagonist (IL-1ra). Other correlations, although noticeable, were either borderline or not significant. Our data show that an imbalance between proinflammatory and anti-inflammatory cytokines may lead to altered Aβ homeostasis, representing a key factor linking together inflammation, synaptic plasticity and cognitive dysfunction in MS. This could be relevant to identify novel therapeutic approaches to hinder the progression of cognitive dysfunction in MS. PMID:29209169
Memory Maintenance in Synapses with Calcium-Based Plasticity in the Presence of Background Activity
Higgins, David; Graupner, Michael; Brunel, Nicolas
2014-01-01
Most models of learning and memory assume that memories are maintained in neuronal circuits by persistent synaptic modifications induced by specific patterns of pre- and postsynaptic activity. For this scenario to be viable, synaptic modifications must survive the ubiquitous ongoing activity present in neural circuits in vivo. In this paper, we investigate the time scales of memory maintenance in a calcium-based synaptic plasticity model that has been shown recently to be able to fit different experimental data-sets from hippocampal and neocortical preparations. We find that in the presence of background activity on the order of 1 Hz parameters that fit pyramidal layer 5 neocortical data lead to a very fast decay of synaptic efficacy, with time scales of minutes. We then identify two ways in which this memory time scale can be extended: (i) the extracellular calcium concentration in the experiments used to fit the model are larger than estimated concentrations in vivo. Lowering extracellular calcium concentration to in vivo levels leads to an increase in memory time scales of several orders of magnitude; (ii) adding a bistability mechanism so that each synapse has two stable states at sufficiently low background activity leads to a further boost in memory time scale, since memory decay is no longer described by an exponential decay from an initial state, but by an escape from a potential well. We argue that both features are expected to be present in synapses in vivo. These results are obtained first in a single synapse connecting two independent Poisson neurons, and then in simulations of a large network of excitatory and inhibitory integrate-and-fire neurons. Our results emphasise the need for studying plasticity at physiological extracellular calcium concentration, and highlight the role of synaptic bi- or multistability in the stability of learned synaptic structures. PMID:25275319
Synaptic Plasticity in Cardiac Innervation and Its Potential Role in Atrial Fibrillation
Ashton, Jesse L.; Burton, Rebecca A. B.; Bub, Gil; Smaill, Bruce H.; Montgomery, Johanna M.
2018-01-01
Synaptic plasticity is defined as the ability of synapses to change their strength of transmission. Plasticity of synaptic connections in the brain is a major focus of neuroscience research, as it is the primary mechanism underpinning learning and memory. Beyond the brain however, plasticity in peripheral neurons is less well understood, particularly in the neurons innervating the heart. The atria receive rich innervation from the autonomic branch of the peripheral nervous system. Sympathetic neurons are clustered in stellate and cervical ganglia alongside the spinal cord and extend fibers to the heart directly innervating the myocardium. These neurons are major drivers of hyperactive sympathetic activity observed in heart disease, ventricular arrhythmias, and sudden cardiac death. Both pre- and postsynaptic changes have been observed to occur at synapses formed by sympathetic ganglion neurons, suggesting that plasticity at sympathetic neuro-cardiac synapses is a major contributor to arrhythmias. Less is known about the plasticity in parasympathetic neurons located in clusters on the heart surface. These neuronal clusters, termed ganglionated plexi, or “little brains,” can independently modulate neural control of the heart and stimulation that enhances their excitability can induce arrhythmia such as atrial fibrillation. The ability of these neurons to alter parasympathetic activity suggests that plasticity may indeed occur at the synapses formed on and by ganglionated plexi neurons. Such changes may not only fine-tune autonomic innervation of the heart, but could also be a source of maladaptive plasticity during atrial fibrillation. PMID:29615932
Optimal structure of metaplasticity for adaptive learning
2017-01-01
Learning from reward feedback in a changing environment requires a high degree of adaptability, yet the precise estimation of reward information demands slow updates. In the framework of estimating reward probability, here we investigated how this tradeoff between adaptability and precision can be mitigated via metaplasticity, i.e. synaptic changes that do not always alter synaptic efficacy. Using the mean-field and Monte Carlo simulations we identified ‘superior’ metaplastic models that can substantially overcome the adaptability-precision tradeoff. These models can achieve both adaptability and precision by forming two separate sets of meta-states: reservoirs and buffers. Synapses in reservoir meta-states do not change their efficacy upon reward feedback, whereas those in buffer meta-states can change their efficacy. Rapid changes in efficacy are limited to synapses occupying buffers, creating a bottleneck that reduces noise without significantly decreasing adaptability. In contrast, more-populated reservoirs can generate a strong signal without manifesting any observable plasticity. By comparing the behavior of our model and a few competing models during a dynamic probability estimation task, we found that superior metaplastic models perform close to optimally for a wider range of model parameters. Finally, we found that metaplastic models are robust to changes in model parameters and that metaplastic transitions are crucial for adaptive learning since replacing them with graded plastic transitions (transitions that change synaptic efficacy) reduces the ability to overcome the adaptability-precision tradeoff. Overall, our results suggest that ubiquitous unreliability of synaptic changes evinces metaplasticity that can provide a robust mechanism for mitigating the tradeoff between adaptability and precision and thus adaptive learning. PMID:28658247
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
Wade, John J.; McDaid, Liam J.; Harkin, Jim; Crunelli, Vincenzo; Kelso, J. A. Scott
2011-01-01
In recent years research suggests that astrocyte networks, in addition to nutrient and waste processing functions, regulate both structural and synaptic plasticity. To understand the biological mechanisms that underpin such plasticity requires the development of cell level models that capture the mutual interaction between astrocytes and neurons. This paper presents a detailed model of bidirectional signaling between astrocytes and neurons (the astrocyte-neuron model or AN model) which yields new insights into the computational role of astrocyte-neuronal coupling. From a set of modeling studies we demonstrate two significant findings. Firstly, that spatial signaling via astrocytes can relay a “learning signal” to remote synaptic sites. Results show that slow inward currents cause synchronized postsynaptic activity in remote neurons and subsequently allow Spike-Timing-Dependent Plasticity based learning to occur at the associated synapses. Secondly, that bidirectional communication between neurons and astrocytes underpins dynamic coordination between neuron clusters. Although our composite AN model is presently applied to simplified neural structures and limited to coordination between localized neurons, the principle (which embodies structural, functional and dynamic complexity), and the modeling strategy may be extended to coordination among remote neuron clusters. PMID:22242121
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.
The organization of plasticity in the cerebellar cortex: from synapses to control.
D'Angelo, Egidio
2014-01-01
The cerebellum is thought to play a critical role in procedural learning, but the relationship between this function and the underlying cellular and synaptic mechanisms remains largely speculative. At present, at least nine forms of long-term synaptic and nonsynaptic plasticity (some of which are bidirectional) have been reported in the cerebellar cortex and deep cerebellar nuclei. These include long-term potentiation (LTP) and long-term depression at the mossy fiber-granule cell synapse, at the synapses formed by parallel fibers, climbing fibers, and molecular layer interneurons on Purkinje cells, and at the synapses formed by mossy fibers and Purkinje cells on deep cerebellar nuclear cells, as well as LTP of intrinsic excitability in granule cells, Purkinje cells, and deep cerebellar nuclear cells. It is suggested that the complex properties of cerebellar learning would emerge from the distribution of plasticity in the network and from its dynamic remodeling during the different phases of learning. Intrinsic and extrinsic factors may hold the key to explain how the different forms of plasticity cooperate to select specific transmission channels and to regulate the signal-to-noise ratio through the cerebellar cortex. These factors include regulation of neuronal excitation by local inhibitory networks, engagement of specific molecular mechanisms by spike bursts and theta-frequency oscillations, and gating by external neuromodulators. Therefore, a new and more complex view of cerebellar plasticity is emerging with respect to that predicted by the original "Motor Learning Theory," opening issues that will require experimental and computational testing. © 2014 Elsevier B.V. All rights reserved.
Dynamic Hebbian Cross-Correlation Learning Resolves the Spike Timing Dependent Plasticity Conundrum.
Olde Scheper, Tjeerd V; Meredith, Rhiannon M; Mansvelder, Huibert D; van Pelt, Jaap; van Ooyen, Arjen
2017-01-01
Spike Timing-Dependent Plasticity has been found to assume many different forms. The classic STDP curve, with one potentiating and one depressing window, is only one of many possible curves that describe synaptic learning using the STDP mechanism. It has been shown experimentally that STDP curves may contain multiple LTP and LTD windows of variable width, and even inverted windows. The underlying STDP mechanism that is capable of producing such an extensive, and apparently incompatible, range of learning curves is still under investigation. In this paper, it is shown that STDP originates from a combination of two dynamic Hebbian cross-correlations of local activity at the synapse. The correlation of the presynaptic activity with the local postsynaptic activity is a robust and reliable indicator of the discrepancy between the presynaptic neuron and the postsynaptic neuron's activity. The second correlation is between the local postsynaptic activity with dendritic activity which is a good indicator of matching local synaptic and dendritic activity. We show that this simple time-independent learning rule can give rise to many forms of the STDP learning curve. The rule regulates synaptic strength without the need for spike matching or other supervisory learning mechanisms. Local differences in dendritic activity at the synapse greatly affect the cross-correlation difference which determines the relative contributions of different neural activity sources. Dendritic activity due to nearby synapses, action potentials, both forward and back-propagating, as well as inhibitory synapses will dynamically modify the local activity at the synapse, and the resulting STDP learning rule. The dynamic Hebbian learning rule ensures furthermore, that the resulting synaptic strength is dynamically stable, and that interactions between synapses do not result in local instabilities. The rule clearly demonstrates that synapses function as independent localized computational entities, each contributing to the global activity, not in a simply linear fashion, but in a manner that is appropriate to achieve local and global stability of the neuron and the entire dendritic structure.
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
Dynamic Re-wiring of Neural Circuits in the Motor Cortex in Mouse Models of Parkinson's Disease
Lalchandani, Rupa R.; Cui, Yuting; Shu, Yu; Xu, Tonghui; Ding, Jun B.
2015-01-01
SUMMARY Dynamic adaptations in synaptic plasticity are critical for learning new motor skills and maintaining memory throughout life, which rapidly decline with Parkinson's disease (PD). Plasticity in the motor cortex is important for acquisition and maintenance of novel motor skills, but how the loss of dopamine in PD leads to disrupted structural and functional plasticity in the motor cortex is not well understood. Here, we utilized mouse models of PD and 2-photon imaging to show that dopamine depletion resulted in structural changes in the motor cortex. We further discovered that dopamine D1 and D2 receptor signaling were linked to selectively and distinctly regulating these aberrant changes in structural and functional plasticity. Our findings suggest that both D1 and D2 receptor signaling regulate motor cortex plasticity, and loss of dopamine results in atypical synaptic adaptations that may contribute to the impairment of motor performance and motor memory observed in PD. PMID:26237365
Mhaouty-Kodja, Sakina; Belzunces, Luc P; Canivenc, Marie-Chantal; Schroeder, Henri; Chevrier, Cécile; Pasquier, Elodie
2018-03-29
Many rodent studies and a few non-human primate data report impairments of spatial and non-spatial memory induced by exposure to bisphenol A (BPA), which are associated with neural modifications, particularly in processes involved in synaptic plasticity. BPA-induced alterations involve disruption of the estrogenic pathway as established by reversal of BPA-induced effects with estrogenic receptor antagonist or by interference of BPA with administered estradiol in ovariectomized animals. Sex differences in hormonal impregnation during critical periods of development and their influence on maturation of learning and memory processes may explain the sexual dimorphism observed in BPA-induced effects in some studies. Altogether, these data highly support the plausibility that alteration of learning and memory and synaptic plasticity by BPA is essentially mediated by disturbance of the estrogenic pathways. As memory function in humans involves similar signaling pathways, this mode of action of BPA has the potential to alter human cognitive abilities. Copyright © 2018. Published by Elsevier B.V.
The Temporal Dynamics of Arc Expression Regulate Cognitive Flexibility.
Wall, Mark J; Collins, Dawn R; Chery, Samantha L; Allen, Zachary D; Pastuzyn, Elissa D; George, Arlene J; Nikolova, Viktoriya D; Moy, Sheryl S; Philpot, Benjamin D; Shepherd, Jason D; Müller, Jürgen; Ehlers, Michael D; Mabb, Angela M; Corrêa, Sonia A L
2018-06-27
Neuronal activity regulates the transcription and translation of the immediate-early gene Arc/Arg3.1, a key mediator of synaptic plasticity. Proteasome-dependent degradation of Arc tightly limits its temporal expression, yet the significance of this regulation remains unknown. We disrupted the temporal control of Arc degradation by creating an Arc knockin mouse (ArcKR) where the predominant Arc ubiquitination sites were mutated. ArcKR mice had intact spatial learning but showed specific deficits in selecting an optimal strategy during reversal learning. This cognitive inflexibility was coupled to changes in Arc mRNA and protein expression resulting in a reduced threshold to induce mGluR-LTD and enhanced mGluR-LTD amplitude. These findings show that the abnormal persistence of Arc protein limits the dynamic range of Arc signaling pathways specifically during reversal learning. Our work illuminates how the precise temporal control of activity-dependent molecules, such as Arc, regulates synaptic plasticity and is crucial for cognition. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.
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.
Sleep and protein synthesis-dependent synaptic plasticity: impacts of sleep loss and stress
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
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.
Xiao, Min-Yi; Gustafsson, Bengt; Niu, Yin-Ping
2006-01-01
The trafficking of ionotropic glutamate (AMPA, NMDA and kainate) and GABAA receptors in and out of, or laterally along, the postsynaptic membrane has recently emerged as an important mechanism in the regulation of synaptic function, both under physiological and pathological conditions, such as information processing, learning and memory formation, neuronal development, and neurodegenerative diseases. Non-ionotropic glutamate receptors, primarily group I metabotropic glutamate receptors (mGluRs), co-exist with the postsynaptic ionotropic glutamate and GABAA receptors. The ability of mGluRs to regulate postsynaptic phosphorylation and Ca2+ concentration, as well as their interactions with postsynaptic scaffolding/signaling proteins, makes them well suited to influence the trafficking of ionotropic glutamate and GABAA receptors. Recent studies have provided insights into how mGluRs may impose such an influence at central synapses, and thus how they may affect synaptic signaling and the maintenance of long-term synaptic plasticity. In this review we will discuss some of the recent progress in this area: i) long-term synaptic plasticity and the involvement of mGluRs; ii) ionotropic glutamate receptor trafficking and long-term synaptic plasticity; iii) the involvement of postsynaptic group I mGluRs in regulating ionotropic glutamate receptor trafficking; iv) involvement of postsynaptic group I mGluRs in regulating GABAA receptor trafficking; v) and the trafficking of postsynaptic group I mGluRs themselves. PMID:18615134
Xiao, Min-Yi; Gustafsson, Bengt; Niu, Yin-Ping
2006-01-01
The trafficking of ionotropic glutamate (AMPA, NMDA and kainate) and GABA(A) receptors in and out of, or laterally along, the postsynaptic membrane has recently emerged as an important mechanism in the regulation of synaptic function, both under physiological and pathological conditions, such as information processing, learning and memory formation, neuronal development, and neurodegenerative diseases. Non-ionotropic glutamate receptors, primarily group I metabotropic glutamate receptors (mGluRs), co-exist with the postsynaptic ionotropic glutamate and GABA(A) receptors. The ability of mGluRs to regulate postsynaptic phosphorylation and Ca(2+) concentration, as well as their interactions with postsynaptic scaffolding/signaling proteins, makes them well suited to influence the trafficking of ionotropic glutamate and GABA(A) receptors. Recent studies have provided insights into how mGluRs may impose such an influence at central synapses, and thus how they may affect synaptic signaling and the maintenance of long-term synaptic plasticity. In this review we will discuss some of the recent progress in this area: i) long-term synaptic plasticity and the involvement of mGluRs; ii) ionotropic glutamate receptor trafficking and long-term synaptic plasticity; iii) the involvement of postsynaptic group I mGluRs in regulating ionotropic glutamate receptor trafficking; iv) involvement of postsynaptic group I mGluRs in regulating GABA(A) receptor trafficking; v) and the trafficking of postsynaptic group I mGluRs themselves.
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
Nothing can be coincidence: synaptic inhibition and plasticity in the cerebellar nuclei
Pugh, Jason R.; Raman, Indira M.
2009-01-01
Many cerebellar neurons fire spontaneously, generating 10–100 action potentials per second even without synaptic input. This high basal activity correlates with information-coding mechanisms that differ from those of cells that are quiescent until excited synaptically. For example, in the deep cerebellar nuclei, Hebbian patterns of coincident synaptic excitation and postsynaptic firing fail to induce long-term increases in the strength of excitatory inputs. Instead, excitatory synaptic currents are potentiated by combinations of inhibition and excitation that resemble the activity of Purkinje and mossy fiber afferents that is predicted to occur during cerebellar associative learning tasks. Such results indicate that circuits with intrinsically active neurons have rules for information transfer and storage that distinguish them from other brain regions. PMID:19178955
A correlated nickelate synaptic transistor.
Shi, Jian; Ha, Sieu D; Zhou, You; Schoofs, Frank; Ramanathan, Shriram
2013-01-01
Inspired by biological neural systems, neuromorphic devices may open up new computing paradigms to explore cognition, learning and limits of parallel computation. Here we report the demonstration of a synaptic transistor with SmNiO₃, a correlated electron system with insulator-metal transition temperature at 130°C in bulk form. Non-volatile resistance and synaptic multilevel analogue states are demonstrated by control over composition in ionic liquid-gated devices on silicon platforms. The extent of the resistance modulation can be dramatically controlled by the film microstructure. By simulating the time difference between postneuron and preneuron spikes as the input parameter of a gate bias voltage pulse, synaptic spike-timing-dependent plasticity learning behaviour is realized. The extreme sensitivity of electrical properties to defects in correlated oxides may make them a particularly suitable class of materials to realize artificial biological circuits that can be operated at and above room temperature and seamlessly integrated into conventional electronic circuits.
Learning and memory: Steroids and epigenetics.
Colciago, Alessandra; Casati, Lavinia; Negri-Cesi, Paola; Celotti, Fabio
2015-06-01
Memory formation and utilization is a complex process involving several brain structures in conjunction as the hippocampus, the amygdala and the adjacent cortical areas, usually defined as medial temporal lobe structures (MTL). The memory processes depend on the formation and modulation of synaptic connectivity affecting synaptic strength, synaptic plasticity and synaptic consolidation. The basic neurocognitive mechanisms of learning and memory are shortly recalled in the initial section of this paper. The effect of sex hormones (estrogens, androgens and progesterone) and of adrenocortical steroids on several aspects of memory processes are then analyzed on the basis of animal and human studies. A specific attention has been devoted to the different types of steroid receptors (membrane or nuclear) involved and on local metabolic transformations when required. The review is concluded by a short excursus on the steroid activated epigenetic mechanisms involved in memory formation. Copyright © 2015 Elsevier Ltd. All rights reserved.
Dynamics of Hippocampal Protein Expression During Long-term Spatial Memory Formation*
Borovok, Natalia; Nesher, Elimelech; Levin, Yishai; Reichenstein, Michal; Pinhasov, Albert
2016-01-01
Spatial memory depends on the hippocampus, which is particularly vulnerable to aging. This vulnerability has implications for the impairment of navigation capacities in older people, who may show a marked drop in performance of spatial tasks with advancing age. Contemporary understanding of long-term memory formation relies on molecular mechanisms underlying long-term synaptic plasticity. With memory acquisition, activity-dependent changes occurring in synapses initiate multiple signal transduction pathways enhancing protein turnover. This enhancement facilitates de novo synthesis of plasticity related proteins, crucial factors for establishing persistent long-term synaptic plasticity and forming memory engrams. Extensive studies have been performed to elucidate molecular mechanisms of memory traces formation; however, the identity of plasticity related proteins is still evasive. In this study, we investigated protein turnover in mouse hippocampus during long-term spatial memory formation using the reference memory version of radial arm maze (RAM) paradigm. We identified 1592 proteins, which exhibited a complex picture of expression changes during spatial memory formation. Variable linear decomposition reduced significantly data dimensionality and enriched three principal factors responsible for variance of memory-related protein levels at (1) the initial phase of memory acquisition (165 proteins), (2) during the steep learning improvement (148 proteins), and (3) the final phase of the learning curve (123 proteins). Gene ontology and signaling pathways analysis revealed a clear correlation between memory improvement and learning phase-curbed expression profiles of proteins belonging to specific functional categories. We found differential enrichment of (1) neurotrophic factors signaling pathways, proteins regulating synaptic transmission, and actin microfilament during the first day of the learning curve; (2) transcription and translation machinery, protein trafficking, enhancement of metabolic activity, and Wnt signaling pathway during the steep phase of memory formation; and (3) cytoskeleton organization proteins. Taken together, this study clearly demonstrates dynamic assembly and disassembly of protein-protein interaction networks depending on the stage of memory formation engrams. PMID:26598641
Chau, Lily S.; Prakapenka, Alesia V.; Zendeli, Liridon; Davis, Ashley S.; Galvez, Roberto
2014-01-01
Studies utilizing general learning and memory tasks have suggested the importance of neocortical structural plasticity for memory consolidation. However, these learning tasks typically result in learning of multiple different tasks over several days of training, making it difficult to determine the synaptic time course mediating each learning event. The current study used trace-eyeblink conditioning to determine the time course for neocortical spine modification during learning. With eyeblink conditioning, subjects are presented with a neutral, conditioned stimulus (CS) paired with a salient, unconditioned stimulus (US) to elicit an unconditioned response (UR). With multiple CS-US pairings, subjects learn to associate the CS with the US and exhibit a conditioned response (CR) when presented with the CS. Trace conditioning is when there is a stimulus free interval between the CS and the US. Utilizing trace-eyeblink conditioning with whisker stimulation as the CS (whisker-trace-eyeblink: WTEB), previous findings have shown that primary somatosensory (barrel) cortex is required for both acquisition and retention of the trace-association. Additionally, prior findings demonstrated that WTEB acquisition results in an expansion of the cytochrome oxidase whisker representation and synaptic modification in layer IV of barrel cortex. To further explore these findings and determine the time course for neocortical learning-induced spine modification, the present study utilized WTEB conditioning to examine Golgi-Cox stained neurons in layer IV of barrel cortex. Findings from this study demonstrated a training-dependent spine proliferation in layer IV of barrel cortex during trace associative learning. Furthermore, findings from this study showing that filopodia-like spines exhibited a similar pattern to the overall spine density further suggests that reorganization of synaptic contacts set the foundation for learning-induced neocortical modifications through the different neocortical layers. PMID:24760074
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.
Yang, Ying; Wang, Zhi-Hao; Jin, Sen; Gao, Di; Liu, Nan; Chen, Shan-Ping; Zhang, Sinan; Liu, Qing; Liu, Enjie; Wang, Xin; Liang, Xiao; Wei, Pengfei; Li, Xiaoguang; Li, Yin; Yue, Chenyu; Li, Hong-lian; Wang, Ya-Li; Wang, Qun; Ke, Dan; Xie, Qingguo; Xu, Fuqiang; Wang, Liping; Wang, Jian-Zhi
2016-01-01
Different emotional states lead to distinct behavioural consequences even when faced with the same challenging events. Emotions affect learning and memory capacities, but the underlying neurobiological mechanisms remain elusive. Here we establish models of learned helplessness (LHL) and learned hopefulness (LHF) by exposing animals to inescapable foot shocks or with anticipated avoidance trainings. The LHF animals show spatial memory potentiation with excitatory monosynaptic upscaling between posterior basolateral amygdale (BLP) and ventral hippocampal CA1 (vCA1), whereas the LHL show memory deficits with an attenuated BLP–vCA1 connection. Optogenetic disruption of BLP–vCA1 inputs abolishes the effects of LHF and impairs synaptic plasticity. By contrast, targeted BLP–vCA1 stimulation rescues the LHL-induced memory deficits and mimics the effects of LHF. BLP–vCA1 stimulation increases synaptic transmission and dendritic plasticity with the upregulation of CREB and intrasynaptic AMPA receptors in CA1. These findings indicate that opposite excitatory monosynaptic scaling of BLP–vCA1 controls LHF- and LHL-modulated spatial memory, revealing circuit-specific mechanisms linking emotions to memory. PMID:27411738
Yang, Ying; Wang, Zhi-Hao; Jin, Sen; Gao, Di; Liu, Nan; Chen, Shan-Ping; Zhang, Sinan; Liu, Qing; Liu, Enjie; Wang, Xin; Liang, Xiao; Wei, Pengfei; Li, Xiaoguang; Li, Yin; Yue, Chenyu; Li, Hong-Lian; Wang, Ya-Li; Wang, Qun; Ke, Dan; Xie, Qingguo; Xu, Fuqiang; Wang, Liping; Wang, Jian-Zhi
2016-07-14
Different emotional states lead to distinct behavioural consequences even when faced with the same challenging events. Emotions affect learning and memory capacities, but the underlying neurobiological mechanisms remain elusive. Here we establish models of learned helplessness (LHL) and learned hopefulness (LHF) by exposing animals to inescapable foot shocks or with anticipated avoidance trainings. The LHF animals show spatial memory potentiation with excitatory monosynaptic upscaling between posterior basolateral amygdale (BLP) and ventral hippocampal CA1 (vCA1), whereas the LHL show memory deficits with an attenuated BLP-vCA1 connection. Optogenetic disruption of BLP-vCA1 inputs abolishes the effects of LHF and impairs synaptic plasticity. By contrast, targeted BLP-vCA1 stimulation rescues the LHL-induced memory deficits and mimics the effects of LHF. BLP-vCA1 stimulation increases synaptic transmission and dendritic plasticity with the upregulation of CREB and intrasynaptic AMPA receptors in CA1. These findings indicate that opposite excitatory monosynaptic scaling of BLP-vCA1 controls LHF- and LHL-modulated spatial memory, revealing circuit-specific mechanisms linking emotions to memory.
Distributed Cerebellar Motor Learning: A Spike-Timing-Dependent Plasticity Model
Luque, Niceto R.; Garrido, Jesús A.; Naveros, Francisco; Carrillo, Richard R.; D'Angelo, Egidio; Ros, Eduardo
2016-01-01
Deep cerebellar nuclei neurons receive both inhibitory (GABAergic) synaptic currents from Purkinje cells (within the cerebellar cortex) and excitatory (glutamatergic) synaptic currents from mossy fibers. Those two deep cerebellar nucleus inputs are thought to be also adaptive, embedding interesting properties in the framework of accurate movements. We show that distributed spike-timing-dependent plasticity mechanisms (STDP) located at different cerebellar sites (parallel fibers to Purkinje cells, mossy fibers to deep cerebellar nucleus cells, and Purkinje cells to deep cerebellar nucleus cells) in close-loop simulations provide an explanation for the complex learning properties of the cerebellum in motor learning. Concretely, we propose a new mechanistic cerebellar spiking model. In this new model, deep cerebellar nuclei embed a dual functionality: deep cerebellar nuclei acting as a gain adaptation mechanism and as a facilitator for the slow memory consolidation at mossy fibers to deep cerebellar nucleus synapses. Equipping the cerebellum with excitatory (e-STDP) and inhibitory (i-STDP) mechanisms at deep cerebellar nuclei afferents allows the accommodation of synaptic memories that were formed at parallel fibers to Purkinje cells synapses and then transferred to mossy fibers to deep cerebellar nucleus synapses. These adaptive mechanisms also contribute to modulate the deep-cerebellar-nucleus-output firing rate (output gain modulation toward optimizing its working range). PMID:26973504
A Three-Threshold Learning Rule Approaches the Maximal Capacity of Recurrent Neural Networks
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.
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.
Operant conditioning of synaptic and spiking activity patterns in single hippocampal neurons.
Ishikawa, Daisuke; Matsumoto, Nobuyoshi; Sakaguchi, Tetsuya; Matsuki, Norio; Ikegaya, Yuji
2014-04-02
Learning is a process of plastic adaptation through which a neural circuit generates a more preferable outcome; however, at a microscopic level, little is known about how synaptic activity is patterned into a desired configuration. Here, we report that animals can generate a specific form of synaptic activity in a given neuron in the hippocampus. In awake, head-restricted mice, we applied electrical stimulation to the lateral hypothalamus, a reward-associated brain region, when whole-cell patch-clamped CA1 neurons exhibited spontaneous synaptic activity that met preset criteria. Within 15 min, the mice learned to generate frequently the excitatory synaptic input pattern that satisfied the criteria. This reinforcement learning of synaptic activity was not observed for inhibitory input patterns. When a burst unit activity pattern was conditioned in paired and nonpaired paradigms, the frequency of burst-spiking events increased and decreased, respectively. The burst reinforcement occurred in the conditioned neuron but not in other adjacent neurons; however, ripple field oscillations were concomitantly reinforced. Neural conditioning depended on activation of NMDA receptors and dopamine D1 receptors. Acutely stressed mice and depression model mice that were subjected to forced swimming failed to exhibit the neural conditioning. This learning deficit was rescued by repetitive treatment with fluoxetine, an antidepressant. Therefore, internally motivated animals are capable of routing an ongoing action potential series into a specific neural pathway of the hippocampal network.
Morphological elucidation of basal ganglia circuits contributing reward prediction
Fujiyama, Fumino; Takahashi, Susumu; Karube, Fuyuki
2015-01-01
Electrophysiological studies in monkeys have shown that dopaminergic neurons respond to the reward prediction error. In addition, striatal neurons alter their responsiveness to cortical or thalamic inputs in response to the dopamine signal, via the mechanism of dopamine-regulated synaptic plasticity. These findings have led to the hypothesis that the striatum exhibits synaptic plasticity under the influence of the reward prediction error and conduct reinforcement learning throughout the basal ganglia circuits. The reinforcement learning model is useful; however, the mechanism by which such a process emerges in the basal ganglia needs to be anatomically explained. The actor–critic model has been previously proposed and extended by the existence of role sharing within the striatum, focusing on the striosome/matrix compartments. However, this hypothesis has been difficult to confirm morphologically, partly because of the complex structure of the striosome/matrix compartments. Here, we review recent morphological studies that elucidate the input/output organization of the striatal compartments. PMID:25698913
Network evolution induced by asynchronous stimuli through spike-timing-dependent plasticity.
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.
Acetylcholine-modulated plasticity in reward-driven navigation: a computational study.
Zannone, Sara; Brzosko, Zuzanna; Paulsen, Ole; Clopath, Claudia
2018-06-21
Neuromodulation plays a fundamental role in the acquisition of new behaviours. In previous experimental work, we showed that acetylcholine biases hippocampal synaptic plasticity towards depression, and the subsequent application of dopamine can retroactively convert depression into potentiation. We also demonstrated that incorporating this sequentially neuromodulated Spike-Timing-Dependent Plasticity (STDP) rule in a network model of navigation yields effective learning of changing reward locations. Here, we employ computational modelling to further characterize the effects of cholinergic depression on behaviour. We find that acetylcholine, by allowing learning from negative outcomes, enhances exploration over the action space. We show that this results in a variety of effects, depending on the structure of the model, the environment and the task. Interestingly, sequentially neuromodulated STDP also yields flexible learning, surpassing the performance of other reward-modulated plasticity rules.
Hao, Lijie; Yang, Zhuoqin; Lei, Jinzhi
2018-01-01
Long-term potentiation (LTP) is a specific form of activity-dependent synaptic plasticity that is a leading mechanism of learning and memory in mammals. The properties of cooperativity, input specificity, and associativity are essential for LTP; however, the underlying mechanisms are unclear. Here, based on experimentally observed phenomena, we introduce a computational model of synaptic plasticity in a pyramidal cell to explore the mechanisms responsible for the cooperativity, input specificity, and associativity of LTP. The model is based on molecular processes involved in synaptic plasticity and integrates gene expression involved in the regulation of neuronal activity. In the model, we introduce a local positive feedback loop of protein synthesis at each synapse, which is essential for bimodal response and synapse specificity. Bifurcation analysis of the local positive feedback loop of brain-derived neurotrophic factor (BDNF) signaling illustrates the existence of bistability, which is the basis of LTP induction. The local bifurcation diagram provides guidance for the realization of LTP, and the projection of whole system trajectories onto the two-parameter bifurcation diagram confirms the predictions obtained from bifurcation analysis. Moreover, model analysis shows that pre- and postsynaptic components are required to achieve the three properties of LTP. This study provides insights into the mechanisms underlying the cooperativity, input specificity, and associativity of LTP, and the further construction of neural networks for learning and memory.
Optimal degrees of synaptic connectivity
Litwin-Kumar, Ashok; Harris, Kameron Decker; Axel, Richard; Sompolinsky, Haim; Abbott, L. F.
2017-01-01
Summary Synaptic connectivity varies widely across neuronal types. Cerebellar granule cells receive five orders of magnitude fewer inputs than the Purkinje cells they innervate, and cerebellum-like circuits including the insect mushroom body also exhibit large divergences in connectivity. In contrast, the number of inputs per neuron in cerebral cortex is more uniform and large. We investigate how the dimension of a representation formed by a population of neurons depends on how many inputs they each receive and what this implies for learning associations. Our theory predicts that the dimensions of the cerebellar granule-cell and Drosophila Kenyon-cell representations are maximized at degrees of synaptic connectivity that match those observed anatomically, showing that sparse connectivity is sometimes superior to dense connectivity. When input synapses are subject to supervised plasticity, however, dense wiring becomes advantageous, suggesting that the type of plasticity exhibited by a set of synapses is a major determinant of connection density. PMID:28215558
Verhoog, Matthijs B; Mansvelder, Huibert D
2011-01-01
Throughout life, activity-dependent changes in neuronal connection strength enable the brain to refine neural circuits and learn based on experience. In line with predictions made by Hebb, synapse strength can be modified depending on the millisecond timing of action potential firing (STDP). The sign of synaptic plasticity depends on the spike order of presynaptic and postsynaptic neurons. Ionotropic neurotransmitter receptors, such as NMDA receptors and nicotinic acetylcholine receptors, are intimately involved in setting the rules for synaptic strengthening and weakening. In addition, timing rules for STDP within synapses are not fixed. They can be altered by activation of ionotropic receptors located at, or close to, synapses. Here, we will highlight studies that uncovered how network actions control and modulate timing rules for STDP by activating presynaptic ionotropic receptors. Furthermore, we will discuss how interaction between different types of ionotropic receptors may create "timing" windows during which particular timing rules lead to synaptic changes.
Emergence of small-world structure in networks of spiking neurons through STDP plasticity.
Basalyga, Gleb; Gleiser, Pablo M; Wennekers, Thomas
2011-01-01
In this work, we use a complex network approach to investigate how a neural network structure changes under synaptic plasticity. In particular, we consider a network of conductance-based, single-compartment integrate-and-fire excitatory and inhibitory neurons. Initially the neurons are connected randomly with uniformly distributed synaptic weights. The weights of excitatory connections can be strengthened or weakened during spiking activity by the mechanism known as spike-timing-dependent plasticity (STDP). We extract a binary directed connection matrix by thresholding the weights of the excitatory connections at every simulation step and calculate its major topological characteristics such as the network clustering coefficient, characteristic path length and small-world index. We numerically demonstrate that, under certain conditions, a nontrivial small-world structure can emerge from a random initial network subject to STDP learning.
Neuronal DNA Methyltransferases: Epigenetic Mediators between Synaptic Activity and Gene Expression?
Bayraktar, Gonca; Kreutz, Michael R.
2017-01-01
DNMT3A and 3B are the main de novo DNA methyltransferases (DNMTs) in the brain that introduce new methylation marks to non-methylated DNA in postmitotic neurons. DNA methylation is a key epigenetic mark that is known to regulate important cellular processes in neuronal development and brain plasticity. Accumulating evidence disclosed rapid and dynamic changes in DNA methylation of plasticity-relevant genes that are important for learning and memory formation. To understand how DNMTs contribute to brain function and how they are regulated by neuronal activity is a prerequisite for a deeper appreciation of activity-dependent gene expression in health and disease. This review discusses the functional role of de novo methyltransferases and in particular DNMT3A1 in the adult brain with special emphasis on synaptic plasticity, memory formation, and brain disorders. PMID:28513272
Protons are a neurotransmitter that regulates synaptic plasticity in the lateral amygdala.
Du, Jianyang; Reznikov, Leah R; Price, Margaret P; Zha, Xiang-ming; Lu, Yuan; Moninger, Thomas O; Wemmie, John A; Welsh, Michael J
2014-06-17
Stimulating presynaptic terminals can increase the proton concentration in synapses. Potential receptors for protons are acid-sensing ion channels (ASICs), Na(+)- and Ca(2+)-permeable channels that are activated by extracellular acidosis. Those observations suggest that protons might be a neurotransmitter. We found that presynaptic stimulation transiently reduced extracellular pH in the amygdala. The protons activated ASICs in lateral amygdala pyramidal neurons, generating excitatory postsynaptic currents. Moreover, both protons and ASICs were required for synaptic plasticity in lateral amygdala neurons. The results identify protons as a neurotransmitter, and they establish ASICs as the postsynaptic receptor. They also indicate that protons and ASICs are a neurotransmitter/receptor pair critical for amygdala-dependent learning and memory.
Ostrovskaya, Olga; Xie, Keqiang; Masuho, Ikuo; Fajardo-Serrano, Ana; Lujan, Rafael; Wickman, Kevin; Martemyanov, Kirill A
2014-01-01
In the hippocampus, the inhibitory neurotransmitter GABA shapes the activity of the output pyramidal neurons and plays important role in cognition. Most of its inhibitory effects are mediated by signaling from GABAB receptor to the G protein-gated Inwardly-rectifying K+ (GIRK) channels. Here, we show that RGS7, in cooperation with its binding partner R7BP, regulates GABABR-GIRK signaling in hippocampal pyramidal neurons. Deletion of RGS7 in mice dramatically sensitizes GIRK responses to GABAB receptor stimulation and markedly slows channel deactivation kinetics. Enhanced activity of this signaling pathway leads to decreased neuronal excitability and selective disruption of inhibitory forms of synaptic plasticity. As a result, mice lacking RGS7 exhibit deficits in learning and memory. We further report that RGS7 is selectively modulated by its membrane anchoring subunit R7BP, which sets the dynamic range of GIRK responses. Together, these results demonstrate a novel role of RGS7 in hippocampal synaptic plasticity and memory formation. DOI: http://dx.doi.org/10.7554/eLife.02053.001 PMID:24755289
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
Feedforward Inhibition and Synaptic Scaling – Two Sides of the Same Coin?
Lücke, Jörg
2012-01-01
Feedforward inhibition and synaptic scaling are important adaptive processes that control the total input a neuron can receive from its afferents. While often studied in isolation, the two have been reported to co-occur in various brain regions. The functional implications of their interactions remain unclear, however. Based on a probabilistic modeling approach, we show here that fast feedforward inhibition and synaptic scaling interact synergistically during unsupervised learning. In technical terms, we model the input to a neural circuit using a normalized mixture model with Poisson noise. We demonstrate analytically and numerically that, in the presence of lateral inhibition introducing competition between different neurons, Hebbian plasticity and synaptic scaling approximate the optimal maximum likelihood solutions for this model. Our results suggest that, beyond its conventional use as a mechanism to remove undesired pattern variations, input normalization can make typical neural interaction and learning rules optimal on the stimulus subspace defined through feedforward inhibition. Furthermore, learning within this subspace is more efficient in practice, as it helps avoid locally optimal solutions. Our results suggest a close connection between feedforward inhibition and synaptic scaling which may have important functional implications for general cortical processing. PMID:22457610
Feedforward inhibition and synaptic scaling--two sides of the same coin?
Keck, Christian; Savin, Cristina; Lücke, Jörg
2012-01-01
Feedforward inhibition and synaptic scaling are important adaptive processes that control the total input a neuron can receive from its afferents. While often studied in isolation, the two have been reported to co-occur in various brain regions. The functional implications of their interactions remain unclear, however. Based on a probabilistic modeling approach, we show here that fast feedforward inhibition and synaptic scaling interact synergistically during unsupervised learning. In technical terms, we model the input to a neural circuit using a normalized mixture model with Poisson noise. We demonstrate analytically and numerically that, in the presence of lateral inhibition introducing competition between different neurons, Hebbian plasticity and synaptic scaling approximate the optimal maximum likelihood solutions for this model. Our results suggest that, beyond its conventional use as a mechanism to remove undesired pattern variations, input normalization can make typical neural interaction and learning rules optimal on the stimulus subspace defined through feedforward inhibition. Furthermore, learning within this subspace is more efficient in practice, as it helps avoid locally optimal solutions. Our results suggest a close connection between feedforward inhibition and synaptic scaling which may have important functional implications for general cortical processing.
T-type calcium channels in synaptic plasticity
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
Bisphenol A Impairs Synaptic Plasticity by Both Pre‐ and Postsynaptic Mechanisms
Li, Tingting; Gong, Huarui; Chen, Zhi; Jin, Yan; Xu, Guangwei
2017-01-01
Bisphenol A (BPA), an environmental xenoestrogen, has been reported to induce learning and memory impairments in rodent animals. However, effects of BPA exposure on synaptic plasticity and the underlying physiological mechanisms remain elusive. Our behavioral and electrophysiological analyses show that BPA obviously perturbs hippocampal spatial memory of juvenile Sprague–Dawley rats after four weeks exposure, with significantly impaired long‐term potentiation (LTP) in the hippocampus. These effects involve decreased spine density of pyramidal neurons, especially the apical dendritic spine. Further presynaptic findings show an overt inhibition of pulse‐paired facilitation during electrophysiological recording, which suggest the decrease of presynaptic transmitter release and is consistent with reduced production of presynaptic glutamate after BPA exposure. Meanwhile, LTP‐related glutamate receptors, NMDA receptor 2A (NR2A) and AMPA receptor 1 (GluR1), are significantly downregulated in BPA‐exposed rats. Excitatory postsynaptic currents (EPSCs) results also show that EPSCNMDA, but not EPSCAMPA, is declined by 40% compared to the baseline in BPA‐perfused brain slices. Taken together, these findings reveal that juvenile BPA exposure has negative effects on synaptic plasticity, which result from decreases in dendritic spine density and excitatory synaptic transmission. Importantly, this study also provides new insights into the dynamics of BPA‐induced memory deterioration during the whole life of rats. PMID:28852612
Parrini, Martina; Ghezzi, Diego; Deidda, Gabriele; Medrihan, Lucian; Castroflorio, Enrico; Alberti, Micol; Baldelli, Pietro; Cancedda, Laura; Contestabile, Andrea
2017-12-04
Down syndrome (DS) is caused by the triplication of human chromosome 21 and represents the most frequent genetic cause of intellectual disability. The trisomic Ts65Dn mouse model of DS shows synaptic deficits and reproduces the essential cognitive disabilities of the human syndrome. Aerobic exercise improved various neurophysiological dysfunctions in Ts65Dn mice, including hippocampal synaptic deficits, by promoting synaptogenesis and neurotransmission at glutamatergic terminals. Most importantly, the same intervention also prompted the recovery of hippocampal adult neurogenesis and synaptic plasticity and restored cognitive performance in trisomic mice. Additionally, the expression of brain-derived neurotrophic factor (BDNF) was markedly decreased in the hippocampus of patients with DS. Since the positive effect of exercise was paralleled by increased BDNF expression in trisomic mice, we investigated the effectiveness of a BDNF-mimetic treatment with 7,8-dihydroxyflavone at alleviating intellectual disabilities in the DS model. Pharmacological stimulation of BDNF signaling rescued synaptic plasticity and memory deficits in Ts65Dn mice. Based on our findings, Ts65Dn mice benefit from interventions aimed at promoting brain plasticity, and we provide evidence that BDNF signaling represents a potentially new pharmacological target for treatments aimed at rescuing cognitive disabilities in patients with DS.
Wu, Qian; Sun, Miao; Bernard, Laura P; Zhang, Huaye
2017-09-29
Postsynaptic density 95 (PSD-95) is a major synaptic scaffolding protein that plays a key role in bidirectional synaptic plasticity, which is a process important for learning and memory. It is known that PSD-95 shows increased dynamics upon induction of plasticity. However, the underlying structural and functional changes in PSD-95 that mediate its role in plasticity remain unclear. Here we show that phosphorylation of PSD-95 at Ser-561 in its guanylate kinase (GK) domain, which is mediated by the partitioning-defective 1 (Par1) kinases, regulates a conformational switch and is important for bidirectional plasticity. Using a fluorescence resonance energy transfer (FRET) biosensor, we show that a phosphomimetic mutation of Ser-561 promotes an intramolecular interaction between GK and the nearby Src homology 3 (SH3) domain, leading to a closed conformation, whereas a non-phosphorylatable S561A mutation or inhibition of Par1 kinase activity decreases SH3-GK interaction, causing PSD-95 to adopt an open conformation. In addition, S561A mutation facilitates the interaction between PSD-95 and its binding partners. Fluorescence recovery after photobleaching imaging reveals that the S561A mutant shows increased stability, whereas the phosphomimetic S561D mutation increases PSD-95 dynamics at the synapse. Moreover, molecular replacement of endogenous PSD-95 with the S561A mutant blocks dendritic spine structural plasticity during chemical long-term potentiation and long-term depression. Endogenous Ser-561 phosphorylation is induced by synaptic NMDA receptor activation, and the SH3-GK domains exhibit a Ser-561 phosphorylation-dependent switch to a closed conformation during synaptic plasticity. Our results provide novel mechanistic insight into the regulation of PSD-95 in dendritic spine structural plasticity through phosphorylation-mediated regulation of protein dynamics and conformation. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.
Network Supervision of Adult Experience and Learning Dependent Sensory Cortical Plasticity.
Blake, David T
2017-06-18
The brain is capable of remodeling throughout life. The sensory cortices provide a useful preparation for studying neuroplasticity both during development and thereafter. In adulthood, sensory cortices change in the cortical area activated by behaviorally relevant stimuli, by the strength of response within that activated area, and by the temporal profiles of those responses. Evidence supports forms of unsupervised, reinforcement, and fully supervised network learning rules. Studies on experience-dependent plasticity have mostly not controlled for learning, and they find support for unsupervised learning mechanisms. Changes occur with greatest ease in neurons containing α-CamKII, which are pyramidal neurons in layers II/III and layers V/VI. These changes use synaptic mechanisms including long term depression. Synaptic strengthening at NMDA-containing synapses does occur, but its weak association with activity suggests other factors also initiate changes. Studies that control learning find support of reinforcement learning rules and limited evidence of other forms of supervised learning. Behaviorally associating a stimulus with reinforcement leads to a strengthening of cortical response strength and enlarging of response area with poor selectivity. Associating a stimulus with omission of reinforcement leads to a selective weakening of responses. In some preparations in which these associations are not as clearly made, neurons with the most informative discharges are relatively stronger after training. Studies analyzing the temporal profile of responses associated with omission of reward, or of plasticity in studies with different discriminanda but statistically matched stimuli, support the existence of limited supervised network learning. © 2017 American Physiological Society. Compr Physiol 7:977-1008, 2017. Copyright © 2017 John Wiley & Sons, Inc.
The Brain as an Efficient and Robust Adaptive Learner.
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.
Competitive STDP Learning of Overlapping Spatial Patterns.
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.
Diaz-Ruiz, Oscar; Zhang, Yajun; Shan, Lufei; Malik, Nasir; Hoffman, Alexander F; Ladenheim, Bruce; Cadet, Jean Lud; Lupica, Carl R; Tagliaferro, Adriana; Brusco, Alicia; Bäckman, Cristina M
2012-07-20
In the present study, we analyzed mice with a targeted deletion of β-catenin in DA neurons (DA-βcat KO mice) to address the functional significance of this molecule in the shaping of synaptic responses associated with motor learning and following exposure to drugs of abuse. Relative to controls, DA-βcat KO mice showed significant deficits in their ability to form long-term memories and displayed reduced expression of methamphetamine-induced behavioral sensitization after subsequent challenge doses with this drug, suggesting that motor learning and drug-induced learning plasticity are altered in these mice. Morphological analyses showed no changes in the number or distribution of tyrosine hydroxylase-labeled neurons in the ventral midbrain. While electrochemical measurements in the striatum determined no changes in acute DA release and uptake, a small but significant decrease in DA release was detected in mutant animals after prolonged repetitive stimulation, suggesting a possible deficit in the DA neurotransmitter vesicle reserve pool. However, electron microscopy analyses did not reveal significant differences in the content of synaptic vesicles per terminal, and striatal DA levels were unchanged in DA-βcat KO animals. In contrast, striatal mRNA levels for several markers known to regulate synaptic plasticity and DA neurotransmission were altered in DA-βcat KO mice. This study demonstrates that ablation of β-catenin in DA neurons leads to alterations of motor and reward-associated memories and to adaptations of the DA neurotransmitter system and suggests that β-catenin signaling in DA neurons is required to facilitate the synaptic remodeling underlying the consolidation of long-term memories.
Cantarero, Gabriela; Lloyd, Ashley
2013-01-01
Plasticity of synaptic connections in the primary motor cortex (M1) is thought to play an essential role in learning and memory. Human and animal studies have shown that motor learning results in long-term potentiation (LTP)-like plasticity processes, namely potentiation of M1 and a temporary occlusion of additional LTP-like plasticity. Moreover, biochemical processes essential for LTP are also crucial for certain types of motor learning and memory. Thus, it has been speculated that the occlusion of LTP-like plasticity after learning, indicative of how much LTP was used to learn, is essential for retention. Here we provide supporting evidence of it in humans. Induction of LTP-like plasticity can be abolished using a depotentiation protocol (DePo) consisting of brief continuous theta burst stimulation. We used transcranial magnetic stimulation to assess whether application of DePo over M1 after motor learning affected (1) occlusion of LTP-like plasticity and (2) retention of motor skill learning. We found that the magnitude of motor memory retention is proportional to the magnitude of occlusion of LTP-like plasticity. Moreover, DePo stimulation over M1, but not over a control site, reversed the occlusion of LTP-like plasticity induced by motor learning and disrupted skill retention relative to control subjects. Altogether, these results provide evidence of a link between occlusion of LTP-like plasticity and retention and that this measure could be used as a biomarker to predict retention. Importantly, attempts to reverse the occlusion of LTP-like plasticity after motor learning comes with the cost of reducing retention of motor learning. PMID:23904621
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.
The Cellular Mechanisms of Memory Are Modified by Experience
ERIC Educational Resources Information Center
Wiltgen, Brian J.; Wood, Alynda N.; Levy, Brynne
2011-01-01
The N-methyl-D-aspartate receptor (NMDAR) is thought to be essential for synaptic plasticity and learning. However, recent work indicates that the role of this receptor depends on the prior history of the research subject. For example, animals trained on a hippocampus-dependent learning task are subsequently able to acquire new information in the…
Depression-Biased Reverse Plasticity Rule Is Required for Stable Learning at Top-Down Connections
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
Learning through ferroelectric domain dynamics in solid-state synapses
NASA Astrophysics Data System (ADS)
Boyn, Sören; Grollier, Julie; Lecerf, Gwendal; Xu, Bin; Locatelli, Nicolas; Fusil, Stéphane; Girod, Stéphanie; Carrétéro, Cécile; Garcia, Karin; Xavier, Stéphane; Tomas, Jean; Bellaiche, Laurent; Bibes, Manuel; Barthélémy, Agnès; Saïghi, Sylvain; Garcia, Vincent
2017-04-01
In the brain, learning is achieved through the ability of synapses to reconfigure the strength by which they connect neurons (synaptic plasticity). In promising solid-state synapses called memristors, conductance can be finely tuned by voltage pulses and set to evolve according to a biological learning rule called spike-timing-dependent plasticity (STDP). Future neuromorphic architectures will comprise billions of such nanosynapses, which require a clear understanding of the physical mechanisms responsible for plasticity. Here we report on synapses based on ferroelectric tunnel junctions and show that STDP can be harnessed from inhomogeneous polarization switching. Through combined scanning probe imaging, electrical transport and atomic-scale molecular dynamics, we demonstrate that conductance variations can be modelled by the nucleation-dominated reversal of domains. Based on this physical model, our simulations show that arrays of ferroelectric nanosynapses can autonomously learn to recognize patterns in a predictable way, opening the path towards unsupervised learning in spiking neural networks.
Cerebellar learning mechanisms
Freeman, John H.
2014-01-01
The mechanisms underlying cerebellar learning are reviewed with an emphasis on old arguments and new perspectives on eyeblink conditioning. Eyeblink conditioning has been used for decades a model system for elucidating cerebellar learning mechanisms. The standard model of the mechanisms underlying eyeblink conditioning is that there two synaptic plasticity processes within the cerebellum that are necessary for acquisition of the conditioned response: 1) long-term depression (LTD) at parallel fiber-Purkinje cell synapses and 2) long-term potentiation (LTP) at mossy fiber-interpositus nucleus synapses. Additional Purkinje cell plasticity mechanisms may also contribute to eyeblink conditioning including LTP, excitability, and entrainment of deep nucleus activity. Recent analyses of the sensory input pathways necessary for eyeblink conditioning indicate that the cerebellum regulates its inputs to facilitate learning and maintain plasticity. Cerebellar learning during eyeblink conditioning is therefore a dynamic interactive process which maximizes responding to significant stimuli and suppresses responding to irrelevant or redundant stimuli. PMID:25289586
Real time unsupervised learning of visual stimuli in neuromorphic VLSI systems
NASA Astrophysics Data System (ADS)
Giulioni, Massimiliano; Corradi, Federico; Dante, Vittorio; Del Giudice, Paolo
2015-10-01
Neuromorphic chips embody computational principles operating in the nervous system, into microelectronic devices. In this domain it is important to identify computational primitives that theory and experiments suggest as generic and reusable cognitive elements. One such element is provided by attractor dynamics in recurrent networks. Point attractors are equilibrium states of the dynamics (up to fluctuations), determined by the synaptic structure of the network; a ‘basin’ of attraction comprises all initial states leading to a given attractor upon relaxation, hence making attractor dynamics suitable to implement robust associative memory. The initial network state is dictated by the stimulus, and relaxation to the attractor state implements the retrieval of the corresponding memorized prototypical pattern. In a previous work we demonstrated that a neuromorphic recurrent network of spiking neurons and suitably chosen, fixed synapses supports attractor dynamics. Here we focus on learning: activating on-chip synaptic plasticity and using a theory-driven strategy for choosing network parameters, we show that autonomous learning, following repeated presentation of simple visual stimuli, shapes a synaptic connectivity supporting stimulus-selective attractors. Associative memory develops on chip as the result of the coupled stimulus-driven neural activity and ensuing synaptic dynamics, with no artificial separation between learning and retrieval phases.
Real time unsupervised learning of visual stimuli in neuromorphic VLSI systems.
Giulioni, Massimiliano; Corradi, Federico; Dante, Vittorio; del Giudice, Paolo
2015-10-14
Neuromorphic chips embody computational principles operating in the nervous system, into microelectronic devices. In this domain it is important to identify computational primitives that theory and experiments suggest as generic and reusable cognitive elements. One such element is provided by attractor dynamics in recurrent networks. Point attractors are equilibrium states of the dynamics (up to fluctuations), determined by the synaptic structure of the network; a 'basin' of attraction comprises all initial states leading to a given attractor upon relaxation, hence making attractor dynamics suitable to implement robust associative memory. The initial network state is dictated by the stimulus, and relaxation to the attractor state implements the retrieval of the corresponding memorized prototypical pattern. In a previous work we demonstrated that a neuromorphic recurrent network of spiking neurons and suitably chosen, fixed synapses supports attractor dynamics. Here we focus on learning: activating on-chip synaptic plasticity and using a theory-driven strategy for choosing network parameters, we show that autonomous learning, following repeated presentation of simple visual stimuli, shapes a synaptic connectivity supporting stimulus-selective attractors. Associative memory develops on chip as the result of the coupled stimulus-driven neural activity and ensuing synaptic dynamics, with no artificial separation between learning and retrieval phases.
NgR1: A Tunable Sensor Regulating Memory Formation, Synaptic, and Dendritic Plasticity.
Karlsson, Tobias E; Smedfors, Gabriella; Brodin, Alvin T S; Åberg, Elin; Mattsson, Anna; Högbeck, Isabelle; Wellfelt, Katrin; Josephson, Anna; Brené, Stefan; Olson, Lars
2016-04-01
Nogo receptor 1 (NgR1) is expressed in forebrain neurons and mediates nerve growth inhibition in response to Nogo and other ligands. Neuronal activity downregulates NgR1 and the inability to downregulate NgR1 impairs long-term memory. We investigated behavior in a serial behavioral paradigm in mice that overexpress or lack NgR1, finding impaired locomotor behavior and recognition memory in mice lacking NgR1 and impaired sequential spatial learning in NgR1 overexpressing mice. We also investigated a role for NgR1 in drug-mediated sensitization and found that repeated cocaine exposure caused stronger locomotor responses but limited development of stereotypies in NgR1 overexpressing mice. This suggests that NgR1-regulated synaptic plasticity is needed to develop stereotypies. Ex vivo magnetic resonance imaging and diffusion tensor imaging analyses of NgR1 overexpressing brains did not reveal any major alterations. NgR1 overexpression resulted in significantly reduced density of mature spines and dendritic complexity. NgR1 overexpression also altered cocaine-induced effects on spine plasticity. Our results show that NgR1 is a negative regulator of both structural synaptic plasticity and dendritic complexity in a brain region-specific manner, and highlight anterior cingulate cortex as a key area for memory-related plasticity. © The Author 2016. Published by Oxford University Press.
NgR1: A Tunable Sensor Regulating Memory Formation, Synaptic, and Dendritic Plasticity
Karlsson, Tobias E.; Smedfors, Gabriella; Brodin, Alvin T. S.; Åberg, Elin; Mattsson, Anna; Högbeck, Isabelle; Wellfelt, Katrin; Josephson, Anna; Brené, Stefan; Olson, Lars
2016-01-01
Nogo receptor 1 (NgR1) is expressed in forebrain neurons and mediates nerve growth inhibition in response to Nogo and other ligands. Neuronal activity downregulates NgR1 and the inability to downregulate NgR1 impairs long-term memory. We investigated behavior in a serial behavioral paradigm in mice that overexpress or lack NgR1, finding impaired locomotor behavior and recognition memory in mice lacking NgR1 and impaired sequential spatial learning in NgR1 overexpressing mice. We also investigated a role for NgR1 in drug-mediated sensitization and found that repeated cocaine exposure caused stronger locomotor responses but limited development of stereotypies in NgR1 overexpressing mice. This suggests that NgR1-regulated synaptic plasticity is needed to develop stereotypies. Ex vivo magnetic resonance imaging and diffusion tensor imaging analyses of NgR1 overexpressing brains did not reveal any major alterations. NgR1 overexpression resulted in significantly reduced density of mature spines and dendritic complexity. NgR1 overexpression also altered cocaine-induced effects on spine plasticity. Our results show that NgR1 is a negative regulator of both structural synaptic plasticity and dendritic complexity in a brain region-specific manner, and highlight anterior cingulate cortex as a key area for memory-related plasticity. PMID:26838771
Spectrotemporal dynamics of auditory cortical synaptic receptive field plasticity.
Froemke, Robert C; Martins, Ana Raquel O
2011-09-01
The nervous system must dynamically represent sensory information in order for animals to perceive and operate within a complex, changing environment. Receptive field plasticity in the auditory cortex allows cortical networks to organize around salient features of the sensory environment during postnatal development, and then subsequently refine these representations depending on behavioral context later in life. Here we review the major features of auditory cortical receptive field plasticity in young and adult animals, focusing on modifications to frequency tuning of synaptic inputs. Alteration in the patterns of acoustic input, including sensory deprivation and tonal exposure, leads to rapid adjustments of excitatory and inhibitory strengths that collectively determine the suprathreshold tuning curves of cortical neurons. Long-term cortical plasticity also requires co-activation of subcortical neuromodulatory control nuclei such as the cholinergic nucleus basalis, particularly in adults. Regardless of developmental stage, regulation of inhibition seems to be a general mechanism by which changes in sensory experience and neuromodulatory state can remodel cortical receptive fields. We discuss recent findings suggesting that the microdynamics of synaptic receptive field plasticity unfold as a multi-phase set of distinct phenomena, initiated by disrupting the balance between excitation and inhibition, and eventually leading to wide-scale changes to many synapses throughout the cortex. These changes are coordinated to enhance the representations of newly-significant stimuli, possibly for improved signal processing and language learning in humans. Copyright © 2011 Elsevier B.V. All rights reserved.
Spectrotemporal Dynamics of Auditory Cortical Synaptic Receptive Field Plasticity
Froemke, Robert C.; Martins, Ana Raquel O.
2011-01-01
The nervous system must dynamically represent sensory information in order for animals to perceive and operate within a complex, changing environment. Receptive field plasticity in the auditory cortex allows cortical networks to organize around salient features of the sensory environment during postnatal development, and then subsequently refine these representations depending on behavioral context later in life. Here we review the major features of auditory cortical receptive field plasticity in young and adult animals, focusing on modifications to frequency tuning of synaptic inputs. Alteration in the patterns of acoustic input, including sensory deprivation and tonal exposure, leads to rapid adjustments of excitatory and inhibitory strengths that collectively determine the suprathreshold tuning curves of cortical neurons. Long-term cortical plasticity also requires co-activation of subcortical neuromodulatory control nuclei such as the cholinergic nucleus basalis, particularly in adults. Regardless of developmental stage, regulation of inhibition seems to be a general mechanism by which changes in sensory experience and neuromodulatory state can remodel cortical receptive fields. We discuss recent findings suggesting that the microdynamics of synaptic receptive field plasticity unfold as a multi-phase set of distinct phenomena, initiated by disrupting the balance between excitation and inhibition, and eventually leading to wide-scale changes to many synapses throughout the cortex. These changes are coordinated to enhance the representations of newly-significant stimuli, possibly for improved signal processing and language learning in humans. PMID:21426927
Gong, Wei-Gang; Wang, Yan-Juan; Zhou, Hong; Li, Xiao-Li; Bai, Feng; Ren, Qing-Guo; Zhang, Zhi-Jun
2017-04-01
Our previous experiments demonstrated that social isolation (SI) caused AD-like tau hyperphosphorylation and spatial memory deficits in middle-aged rats. However, the underlying mechanisms of SI-induced spatial memory deficits remain elusive. Middle-aged rats (10 months) were group or isolation reared for 8 weeks. Following the initial 4-week period of rearing, citalopram (10 mg/kg i.p.) was administered for 28 days. Then, pathophysiological changes were assessed by performing behavioral, biochemical, and pathological analyses. We found that SI could cause cognitive dysfunction and decrease synaptic protein (synaptophysin or PSD93) expression in different brain regions associated with cognition, such as the prefrontal cortex, dorsal hippocampus, ventral hippocampus, amygdala, and caudal putamen, but not in the entorhinal cortex or posterior cingulate. Citalopram could significantly improve learning and memory and partially restore synaptophysin or PSD93 expression in the prefrontal cortex, hippocampus, and amygdala in SI rats. Moreover, SI decreased the number of dendritic spines in the prefrontal cortex, dorsal hippocampus, and ventral hippocampus, which could be reversed by citalopram. Furthermore, SI reduced the levels of BDNF, serine-473-phosphorylated Akt (active form), and serine-9-phosphorylated GSK-3β (inactive form) with no significant changes in the levels of total GSK-3β and Akt in the dorsal hippocampus, but not in the posterior cingulate. Our results suggest that decreased synaptic plasticity in cognition-associated regions might contribute to SI-induced cognitive deficits, and citalopram could ameliorate these deficits by promoting synaptic plasticity mainly in the prefrontal cortex, dorsal hippocampus, and ventral hippocampus. The BDNF/Akt/GSK-3β pathway plays an important role in regulating synaptic plasticity in SI rats.
Mancini, Maria; Ghiglieri, Veronica; Bagetta, Vincenza; Pendolino, Valentina; Vannelli, Anna; Cacace, Fabrizio; Mineo, Desireé; Calabresi, Paolo; Picconi, Barbara
2016-02-01
Memantine is an open channel blocker that antagonizes NMDA receptors reducing the inappropriate calcium (Ca(2+)) influx occurring in presence of moderately increased glutamate levels. At the same time, memantine has the ability to preserve the transient physiological activation of NMDA receptor, essential for learning and memory formation at synaptic level. In the present study we investigated the effects exerted by memantine on striatal synaptic plasticity in rat striatal spiny projection neurons (SPNs). In vitro application of memantine in striatal slices elicited a disruption of long-term potentiation (LTP) induction and maintenance, and revealed, in the majority of the recorded neurons, a long-term depression (LTD), whose amplitude was concentration-dependent (0.3-10 μM). Interestingly, preincubation with the dopamine (DA) D2 receptor antagonist sulpiride (10 μM) prevented memantine-induced LTD and restored LTP. Moreover, the DA D2 agonist quinpirole (10 μM), similarly to memantine, induced LTD in a subgroup of SPNs. In addition, memantine-induced LTD was also prevented by the CB1 endocannabinoid receptor antagonist AM 251 (1 μM). These results suggest that the actions exerted by memantine on striatal synaptic plasticity, and in particular the induction of LTD observed in SPNs, could be attributed to its ability to activate DA D2 receptors. By contrast, blockade of NMDA receptor is not involved in memantine-induced LTD since APV (30 μM) and MK801 (10 μM), two NMDA receptor antagonists, failed to induce this form of synaptic plasticity. Our data indicate that memantine could be used as treatment of neurological disorders in which DA D2 receptor represents a possible therapeutic target. Copyright © 2015 Elsevier Ltd. All rights reserved.
ERIC Educational Resources Information Center
Liu, Yan; Sun, Jiandong; Wang, Yubin; Lopez, Dulce; Tran, Jennifer; Bi, Xiaoning; Baudry, Michel
2016-01-01
Calpain-1 (CANP1) has been shown to play a critical role in synaptic plasticity and learning and memory, as its deletion in mice results in impairment in theta-burst stimulation (TBS)-induced LTP and various forms of learning and memory. Likewise, PHLPP1 (aka SCOP) has also been found to participate in learning and memory, as PHLPP1 overexpression…
Biologically Inspired SNN for Robot Control.
Nichols, Eric; McDaid, Liam J; Siddique, Nazmul
2013-02-01
This paper proposes a spiking-neural-network-based robot controller inspired by the control structures of biological systems. Information is routed through the network using facilitating dynamic synapses with short-term plasticity. Learning occurs through long-term synaptic plasticity which is implemented using the temporal difference learning rule to enable the robot to learn to associate the correct movement with the appropriate input conditions. The network self-organizes to provide memories of environments that the robot encounters. A Pioneer robot simulator with laser and sonar proximity sensors is used to verify the performance of the network with a wall-following task, and the results are presented.
Noack, Marko; Partzsch, Johannes; Mayr, Christian G; Hänzsche, Stefan; Scholze, Stefan; Höppner, Sebastian; Ellguth, Georg; Schüffny, Rene
2015-01-01
Synaptic dynamics, such as long- and short-term plasticity, play an important role in the complexity and biological realism achievable when running neural networks on a neuromorphic IC. For example, they endow the IC with an ability to adapt and learn from its environment. In order to achieve the millisecond to second time constants required for these synaptic dynamics, analog subthreshold circuits are usually employed. However, due to process variation and leakage problems, it is almost impossible to port these types of circuits to modern sub-100nm technologies. In contrast, we present a neuromorphic system in a 28 nm CMOS process that employs switched capacitor (SC) circuits to implement 128 short term plasticity presynapses as well as 8192 stop-learning synapses. The neuromorphic system consumes an area of 0.36 mm(2) and runs at a power consumption of 1.9 mW. The circuit makes use of a technique for minimizing leakage effects allowing for real-time operation with time constants up to several seconds. Since we rely on SC techniques for all calculations, the system is composed of only generic mixed-signal building blocks. These generic building blocks make the system easy to port between technologies and the large digital circuit part inherent in an SC system benefits fully from technology scaling.
Hippocampal LTP and contextual learning require surface diffusion of AMPA receptors.
Penn, A C; Zhang, C L; Georges, F; Royer, L; Breillat, C; Hosy, E; Petersen, J D; Humeau, Y; Choquet, D
2017-09-21
Long-term potentiation (LTP) of excitatory synaptic transmission has long been considered a cellular correlate for learning and memory. Early LTP (less than 1 h) had initially been explained either by presynaptic increases in glutamate release or by direct modification of postsynaptic AMPA (α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid) receptor function. Compelling models have more recently proposed that synaptic potentiation can occur by the recruitment of additional postsynaptic AMPA receptors (AMPARs), sourced either from an intracellular reserve pool by exocytosis or from nearby extra-synaptic receptors pre-existing on the neuronal surface. However, the exact mechanism through which synapses can rapidly recruit new AMPARs during early LTP remains unknown. In particular, direct evidence for a pivotal role of AMPAR surface diffusion as a trafficking mechanism in synaptic plasticity is still lacking. Here, using AMPAR immobilization approaches, we show that interfering with AMPAR surface diffusion markedly impairs synaptic potentiation of Schaffer collaterals and commissural inputs to the CA1 area of the mouse hippocampus in cultured slices, acute slices and in vivo. Our data also identify distinct contributions of various AMPAR trafficking routes to the temporal profile of synaptic potentiation. In addition, AMPAR immobilization in vivo in the dorsal hippocampus inhibited fear conditioning, indicating that AMPAR diffusion is important for the early phase of contextual learning. Therefore, our results provide a direct demonstration that the recruitment of new receptors to synapses by surface diffusion is a critical mechanism for the expression of LTP and hippocampal learning. Since AMPAR surface diffusion is dictated by weak Brownian forces that are readily perturbed by protein-protein interactions, we anticipate that this fundamental trafficking mechanism will be a key target for modulating synaptic potentiation and learning.
A Spiking Working Memory Model Based on Hebbian Short-Term Potentiation.
Fiebig, Florian; Lansner, Anders
2017-01-04
A dominant theory of working memory (WM), referred to as the persistent activity hypothesis, holds that recurrently connected neural networks, presumably located in the prefrontal cortex, encode and maintain WM memory items through sustained elevated activity. Reexamination of experimental data has shown that prefrontal cortex activity in single units during delay periods is much more variable than predicted by such a theory and associated computational models. Alternative models of WM maintenance based on synaptic plasticity, such as short-term nonassociative (non-Hebbian) synaptic facilitation, have been suggested but cannot account for encoding of novel associations. Here we test the hypothesis that a recently identified fast-expressing form of Hebbian synaptic plasticity (associative short-term potentiation) is a possible mechanism for WM encoding and maintenance. Our simulations using a spiking neural network model of cortex reproduce a range of cognitive memory effects in the classical multi-item WM task of encoding and immediate free recall of word lists. Memory reactivation in the model occurs in discrete oscillatory bursts rather than as sustained activity. We relate dynamic network activity as well as key synaptic characteristics to electrophysiological measurements. Our findings support the hypothesis that fast Hebbian short-term potentiation is a key WM mechanism. Working memory (WM) is a key component of cognition. Hypotheses about the neural mechanism behind WM are currently under revision. Reflecting recent findings of fast Hebbian synaptic plasticity in cortex, we test whether a cortical spiking neural network model with such a mechanism can learn a multi-item WM task (word list learning). We show that our model can reproduce human cognitive phenomena and achieve comparable memory performance in both free and cued recall while being simultaneously compatible with experimental data on structure, connectivity, and neurophysiology of the underlying cortical tissue. These findings are directly relevant to the ongoing paradigm shift in the WM field. Copyright © 2017 Fiebig and Lansner.
A Spiking Working Memory Model Based on Hebbian Short-Term Potentiation
Fiebig, Florian
2017-01-01
A dominant theory of working memory (WM), referred to as the persistent activity hypothesis, holds that recurrently connected neural networks, presumably located in the prefrontal cortex, encode and maintain WM memory items through sustained elevated activity. Reexamination of experimental data has shown that prefrontal cortex activity in single units during delay periods is much more variable than predicted by such a theory and associated computational models. Alternative models of WM maintenance based on synaptic plasticity, such as short-term nonassociative (non-Hebbian) synaptic facilitation, have been suggested but cannot account for encoding of novel associations. Here we test the hypothesis that a recently identified fast-expressing form of Hebbian synaptic plasticity (associative short-term potentiation) is a possible mechanism for WM encoding and maintenance. Our simulations using a spiking neural network model of cortex reproduce a range of cognitive memory effects in the classical multi-item WM task of encoding and immediate free recall of word lists. Memory reactivation in the model occurs in discrete oscillatory bursts rather than as sustained activity. We relate dynamic network activity as well as key synaptic characteristics to electrophysiological measurements. Our findings support the hypothesis that fast Hebbian short-term potentiation is a key WM mechanism. SIGNIFICANCE STATEMENT Working memory (WM) is a key component of cognition. Hypotheses about the neural mechanism behind WM are currently under revision. Reflecting recent findings of fast Hebbian synaptic plasticity in cortex, we test whether a cortical spiking neural network model with such a mechanism can learn a multi-item WM task (word list learning). We show that our model can reproduce human cognitive phenomena and achieve comparable memory performance in both free and cued recall while being simultaneously compatible with experimental data on structure, connectivity, and neurophysiology of the underlying cortical tissue. These findings are directly relevant to the ongoing paradigm shift in the WM field. PMID:28053032
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.
Functional requirements for reward-modulated spike-timing-dependent plasticity.
Frémaux, Nicolas; Sprekeler, Henning; Gerstner, Wulfram
2010-10-06
Recent experiments have shown that spike-timing-dependent plasticity is influenced by neuromodulation. We derive theoretical conditions for successful learning of reward-related behavior for a large class of learning rules where Hebbian synaptic plasticity is conditioned on a global modulatory factor signaling reward. We show that all learning rules in this class can be separated into a term that captures the covariance of neuronal firing and reward and a second term that presents the influence of unsupervised learning. The unsupervised term, which is, in general, detrimental for reward-based learning, can be suppressed if the neuromodulatory signal encodes the difference between the reward and the expected reward-but only if the expected reward is calculated for each task and stimulus separately. If several tasks are to be learned simultaneously, the nervous system needs an internal critic that is able to predict the expected reward for arbitrary stimuli. We show that, with a critic, reward-modulated spike-timing-dependent plasticity is capable of learning motor trajectories with a temporal resolution of tens of milliseconds. The relation to temporal difference learning, the relevance of block-based learning paradigms, and the limitations of learning with a critic are discussed.
Synaptic plasticity and oscillation at zinc tin oxide/silver oxide interfaces
NASA Astrophysics Data System (ADS)
Murdoch, Billy J.; McCulloch, Dougal G.; Partridge, James G.
2017-02-01
Short-term plasticity, long-term potentiation, and pulse interval dependent plasticity learning/memory functions have been observed in junctions between amorphous zinc-tin-oxide and silver-oxide. The same junctions exhibited current-controlled negative differential resistance and when connected in an appropriate circuit, they behaved as relaxation oscillators. These oscillators produced voltage pulses suitable for device programming. Transmission electron microscopy, energy dispersive X-ray spectroscopy, and electrical measurements suggest that the characteristics of these junctions arise from Ag+/O- electromigration across a highly resistive interface layer. With memory/learning functions and programming spikes provided in a single device structure, arrays of similar devices could be used to form transistor-free neuromorphic circuits.
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…
NASA Astrophysics Data System (ADS)
Sengupta, Abhronil; Roy, Kaushik
2016-02-01
Synaptic memory is considered to be the main element responsible for learning and cognition in humans. Although traditionally nonvolatile long-term plasticity changes are implemented in nanoelectronic synapses for neuromorphic applications, recent studies in neuroscience reveal that biological synapses undergo metastable volatile strengthening followed by a long-term strengthening provided that the frequency of the input stimulus is sufficiently high. Such "memory strengthening" and "memory decay" functionalities can potentially lead to adaptive neuromorphic architectures. In this paper, we demonstrate the close resemblance of the magnetization dynamics of a magnetic tunnel junction (MTJ) to short-term plasticity and long-term potentiation observed in biological synapses. We illustrate that, in addition to the magnitude and duration of the input stimulus, the frequency of the stimulus plays a critical role in determining long-term potentiation of the MTJ. Such MTJ synaptic memory arrays can be utilized to create compact, ultrafast, and low-power intelligent neural systems.
Spike-timing dependent plasticity in primate corticospinal connections induced during free behavior
Nishimura, Yukio; Perlmutter, Steve I.; Eaton, Ryan W.; Fetz, Eberhard E.
2014-01-01
Motor learning and functional recovery from brain damage involve changes in the strength of synaptic connections between neurons. Relevant in vivo evidence on the underlying cellular mechanisms remains limited and indirect. We found that the strength of neural connections between motor cortex and spinal cord in monkeys can be modified with an autonomous recurrent neural interface that delivers electrical stimuli in the spinal cord triggered by action potentials of corticospinal cells during free behavior. The activity-dependent stimulation modified the strength of the terminal connections of single corticomotoneuronal cells, consistent with a bidirectional spike-timing dependent plasticity rule previously derived from in vitro experiments. For some cells the changes lasted for days after the end of conditioning, but most effects eventually reverted to preconditioning levels. These results provide the first direct evidence of corticospinal synaptic plasticity in vivo at the level of single neurons induced by normal firing patterns during free behavior. PMID:24210907
Genes and signaling pathways involved in memory enhancement in mutant mice
2014-01-01
Mutant mice have been used successfully as a tool for investigating the mechanisms of memory at multiple levels, from genes to behavior. In most cases, manipulating a gene expressed in the brain impairs cognitive functions such as memory and their underlying cellular mechanisms, including synaptic plasticity. However, a remarkable number of mutations have been shown to enhance memory in mice. Understanding how to improve a system provides valuable insights into how the system works under normal conditions, because this involves understanding what the crucial components are. Therefore, more can be learned about the basic mechanisms of memory by studying mutant mice with enhanced memory. This review will summarize the genes and signaling pathways that are altered in the mutants with enhanced memory, as well as their roles in synaptic plasticity. Finally, I will discuss how knowledge of memory-enhancing mechanisms could be used to develop treatments for cognitive disorders associated with impaired plasticity. PMID:24894914
[Physical activity: positive impact on brain plasticity].
Achiron, Anat; Kalron, Alon
2008-03-01
The central nervous system has a unique capability of plasticity that enables a single neuron or a group of neurons to undergo functional and constructional changes that are important to learning processes and for compensation of brain damage. The current review aims to summarize recent data related to the effects of physical activity on brain plasticity. In the last decade it was reported that physical activity can affect and manipulate neuronal connections, synaptic activity and adaptation to new neuronal environment following brain injury. One of the most significant neurotrophic factors that is critical for synaptic re-organization and is influenced by physical activity is brain-derived neurotrophic factor (BDNF). The frequency of physical activity and the intensity of exercises are of importance to brain remodeling, support neuronal survival and positively affect rehabilitation therapy. Physical activity should be employed as a tool to improve neural function in healthy subjects and in patients suffering from neurological damage.
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
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.
Motor learning induces plastic changes in Purkinje cell dendritic spines in the rat cerebellum.
González-Tapia, D; González-Ramírez, M M; Vázquez-Hernández, N; González-Burgos, I
2017-12-14
The paramedian lobule of the cerebellum is involved in learning to correctly perform motor skills through practice. Dendritic spines are dynamic structures that regulate excitatory synaptic stimulation. We studied plastic changes occurring in the dendritic spines of Purkinje cells from the paramedian lobule of rats during motor learning. Adult male rats were trained over a 6-day period using an acrobatic motor learning paradigm; the density and type of dendritic spines were determined every day during the study period using a modified version of the Golgi method. The learning curve reflected a considerable decrease in the number of errors made by rats as the training period progressed. We observed more dendritic spines on days 2 and 6, particularly more thin spines on days 1, 3, and 6, fewer mushroom spines on day 3, fewer stubby spines on day 1, and more thick spines on days 4 and 6. The initial stage of motor learning may be associated with fast processing of the underlying synaptic information combined with an apparent "silencing" of memory consolidation processes, based on the regulation of the neuronal excitability. Copyright © 2017 Sociedad Española de Neurología. Publicado por Elsevier España, S.L.U. All rights reserved.
Origin of the spike-timing-dependent plasticity rule
NASA Astrophysics Data System (ADS)
Cho, Myoung Won; Choi, M. Y.
2016-08-01
A biological synapse changes its efficacy depending on the difference between pre- and post-synaptic spike timings. Formulating spike-timing-dependent interactions in terms of the path integral, we establish a neural-network model, which makes it possible to predict relevant quantities rigorously by means of standard methods in statistical mechanics and field theory. In particular, the biological synaptic plasticity rule is shown to emerge as the optimal form for minimizing the free energy. It is further revealed that maximization of the entropy of neural activities gives rise to the competitive behavior of biological learning. This demonstrates that statistical mechanics helps to understand rigorously key characteristic behaviors of a neural network, thus providing the possibility of physics serving as a useful and relevant framework for probing life.
Protons are a neurotransmitter that regulates synaptic plasticity in the lateral amygdala
Du, Jianyang; Reznikov, Leah R.; Price, Margaret P.; Zha, Xiang-ming; Lu, Yuan; Moninger, Thomas O.; Wemmie, John A.; Welsh, Michael J.
2014-01-01
Stimulating presynaptic terminals can increase the proton concentration in synapses. Potential receptors for protons are acid-sensing ion channels (ASICs), Na+- and Ca2+-permeable channels that are activated by extracellular acidosis. Those observations suggest that protons might be a neurotransmitter. We found that presynaptic stimulation transiently reduced extracellular pH in the amygdala. The protons activated ASICs in lateral amygdala pyramidal neurons, generating excitatory postsynaptic currents. Moreover, both protons and ASICs were required for synaptic plasticity in lateral amygdala neurons. The results identify protons as a neurotransmitter, and they establish ASICs as the postsynaptic receptor. They also indicate that protons and ASICs are a neurotransmitter/receptor pair critical for amygdala-dependent learning and memory. PMID:24889629
Del Giudice, Paolo; Fusi, Stefano; Mattia, Maurizio
2003-01-01
In this paper we review a series of works concerning models of spiking neurons interacting via spike-driven, plastic, Hebbian synapses, meant to implement stimulus driven, unsupervised formation of working memory (WM) states. Starting from a summary of the experimental evidence emerging from delayed matching to sample (DMS) experiments, we briefly review the attractor picture proposed to underlie WM states. We then describe a general framework for a theoretical approach to learning with synapses subject to realistic constraints and outline some general requirements to be met by a mechanism of Hebbian synaptic structuring. We argue that a stochastic selection of the synapses to be updated allows for optimal memory storage, even if the number of stable synaptic states is reduced to the extreme (bistable synapses). A description follows of models of spike-driven synapses that implement the stochastic selection by exploiting the high irregularity in the pre- and post-synaptic activity. Reasons are listed why dynamic learning, that is the process by which the synaptic structure develops under the only guidance of neural activities, driven in turn by stimuli, is hard to accomplish. We provide a 'feasibility proof' of dynamic formation of WM states in this context the beneficial role of short-term depression (STD) is illustrated. by showing how an initially unstructured network autonomously develops a synaptic structure supporting simultaneously stable spontaneous and WM states in this context the beneficial role of short-term depression (STD) is illustrated. After summarizing heuristic indications emerging from the study performed, we conclude by briefly discussing open problems and critical issues still to be clarified.
Circadian glucocorticoid oscillations promote learning-dependent synapse formation and maintenance
Liston, Conor; Cichon, Joseph M; Jeanneteau, Freddy; Jia, Zhengping; Chao, Moses V; Gan, Wen-Biao
2013-01-01
Excessive glucocorticoid exposure during chronic stress causes synapse loss and learning impairment. Under normal physiological conditions, glucocorticoid activity oscillates in synchrony with the circadian rhythm. Whether and how endogenous glucocorticoid oscillations modulate synaptic plasticity and learning is unknown. Here we show that circadian glucocorticoid peaks promote postsynaptic dendritic spine formation in the mouse cortex after motor skill learning, whereas troughs are required for stabilizing newly formed spines that are important for long-term memory retention. Conversely, chronic and excessive exposure to glucocorticoids eliminates learning-associated new spines and disrupts previously acquired memories. Furthermore, we show that glucocorticoids promote rapid spine formation through a non-transcriptional mechanism by means of the LIM kinase–cofilin pathway and increase spine elimination through transcriptional mechanisms involving mineralocorticoid receptor activation. Together, these findings indicate that tightly regulated circadian glucocorticoid oscillations are important for learning-dependent synaptic formation and maintenance. They also delineate a new signaling mechanism underlying these effects. PMID:23624512
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhu Guoqi; Chen Ying; Huang Yuying
2011-08-01
Parkinson's disease (PD)-like symptoms including learning deficits are inducible by 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP). Therefore, it is possible that MPTP may disturb hippocampal memory processing by modulation of dopamine (DA)- and activity-dependent synaptic plasticity. We demonstrate here that intraperitoneal (i.p.) MPTP injection reduces the number of tyrosine hydroxylase (TH)-positive neurons in the substantia nigra (SN) within 7 days. Subsequently, the TH expression level in SN and hippocampus and the amount of DA and its metabolite DOPAC in striatum and hippocampus decrease. DA depletion does not alter basal synaptic transmission and changes pair-pulse facilitation (PPF) of field excitatory postsynaptic potentials (fEPSPs) only atmore » the 30 ms inter-pulse interval. In addition, the induction of long-term potentiation (LTP) is impaired whereas the duration of long-term depression (LTD) becomes prolonged. Since both LTP and LTD depend critically on activation of NMDA and DA receptors, we also tested the effect of DA depletion on NMDA receptor-mediated synaptic transmission. Seven days after MPTP injection, the NMDA receptor-mediated fEPSPs are decreased by about 23%. Blocking the NMDA receptor-mediated fEPSP does not mimic the MPTP-LTP. Only co-application of D1/D5 and NMDA receptor antagonists during tetanization resembled the time course of fEPSP potentiation as observed 7 days after i.p. MPTP injection. Together, our data demonstrate that MPTP-induced degeneration of DA neurons and the subsequent hippocampal DA depletion alter NMDA receptor-mediated synaptic transmission and activity-dependent synaptic plasticity. - Highlights: > I.p. MPTP-injection mediates death of dopaminergic neurons. > I.p. MPTP-injection depletes DA and DOPAC in striatum and hippocampus. > I.p. MPTP-injection does not alter basal synaptic transmission. > Reduction of LTP and enhancement of LTD after i.p. MPTP-injection. > Attenuation of NMDA-receptors mediated fEPSPs after i.p. MPTP-injection.« less
Fourneau, Julie; Canu, Marie-Hélène; Cieniewski-Bernard, Caroline; Bastide, Bruno; Dupont, Erwan
2018-05-28
In human, a chronic sensorimotor perturbation (SMP) through prolonged body immobilization alters motor task performance through a combination of peripheral and central factors. Studies performed on a rat model of SMP have shown biomolecular changes and a reorganization of sensorimotor cortex through events such as morphological modifications of dendritic spines (number, length, functionality). However, underlying mechanisms are still unclear. It is well known that phosphorylation regulates a wide field of synaptic activity leading to neuroplasticity. Another post-translational modification that interplays with phosphorylation is O-GlcNAcylation. This atypical glycosylation, reversible and dynamic, is involved in essential cellular and physiological processes such as synaptic activity, neuronal morphogenesis, learning and memory. We examined potential roles of phosphorylation/O-GlcNAcylation interplay in synaptic plasticity within rat sensorimotor cortex after a SMP period. For this purpose, sensorimotor cortex synaptosomes were separated by sucrose gradient, in order to isolate a subcellular compartment enriched in proteins involved in synaptic functions. A period of SMP induced plastic changes at the pre- and postsynaptic levels, characterized by a reduction of phosphorylation (synapsin1, AMPAR GluA2) and expression (synaptophysin, PSD-95, AMPAR GluA2) of synaptic proteins, as well as a decrease in MAPK/ERK42 activation. Expression levels of OGT/OGA enzymes was unchanged but we observed a specific reduction of synapsin1 O-GlcNAcylation in sensorimotor cortex synaptosomes. The synergistic regulation of synapsin1 phosphorylation/O-GlcNAcylation could affect presynaptic neurotransmitter release. Associated with other pre- and postsynaptic changes, synaptic efficacy could be impaired in somatosensory cortex of SMP rat. Thus, synapsin1 O-GlcNAcylation/phosphorylation interplay also appears to be involved in this synaptic plasticity by finely regulating neural activity. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.
ERIC Educational Resources Information Center
Reumann, Rebecca; Vierk, Ricardo; Zhou, Lepu; Gries, Frederice; Kraus, Vanessa; Mienert, Julia; Romswinkel, Eva; Morellini, Fabio; Ferrer, Isidre; Nicolini, Chiara; Fahnestock, Margaret; Rune, Gabriele; Glatzel, Markus; Galliciotti, Giovanna
2017-01-01
The serine protease inhibitor neuroserpin regulates the activity of tissue-type plasminogen activator (tPA) in the nervous system. Neuroserpin expression is particularly prominent at late stages of neuronal development in most regions of the central nervous system (CNS), whereas it is restricted to regions related to learning and memory in the…
ERIC Educational Resources Information Center
Kimura, Ryoichi; Silva, Alcino J.; Ohno, Masuo
2008-01-01
Accumulating evidence indicates the key role of [alpha]-calcium/calmodulin-dependent protein kinase II ([alpha]CaMKII) in synaptic plasticity and learning, but it remains unclear how this kinase participates in the processing of memory extinction. Here, we investigated the mechanism by which [alpha]CaMKII may mediate extinction by using…
Learning and memory deficits in mice lacking protease activated receptor-1
Almonte, Antoine G.; Hamill, Cecily E.; Chhatwal, Jasmeer P.; Wingo, Thomas S.; Barber, Jeremy A.; Lyuboslavsky, Polina N.; Sweatt, J. David; Ressler, Kerry J.; White, David A.; Traynelis, Stephen F.
2007-01-01
The roles of serine proteases and protease activated receptors have been extensively studied in coagulation, wound healing, inflammation, and neurodegeneration. More recently, serine proteases have been suggested to influence synaptic plasticity. In this context, we examined the role of protease activated receptor 1 (PAR1), which is activated following proteolytic cleavage by thrombin and plasmin, in emotionally-motivated learning. We were particularly interested in PAR1 because its activation enhances the function of NMDA receptors, which are required for some forms of synaptic plasticity. We examined several baseline behavioral measures, including locomotor activity, expression of anxiety-like behavior, motor task acquisition, nociceptive responses, and startle responses in C57Bl/6 mice in which the PAR1 receptor has been genetically deleted. In addition, we evaluated learning and memory in these mice using two memory tasks, passive avoidance and cued fear-conditioning. Whereas locomotion, pain response, startle, and measures of baseline anxiety were largely unaffected by PAR1 removal, PAR1−/− animals showed significant deficits in a passive avoidance task and in cued fear conditioning. These data suggest that PAR1 may play an important role in emotionally-motivated learning. PMID:17544303
SPIN90 Modulates Long-Term Depression and Behavioral Flexibility in the Hippocampus
Kim, Dae Hwan; Kang, Minkyung; Kim, Chong-Hyun; Huh, Yun Hyun; Cho, In Ha; Ryu, Hyun-Hee; Chung, Kyung Hwun; Park, Chul-Seung; Rhee, Sangmyung; Lee, Yong-Seok; Song, Woo Keun
2017-01-01
The importance of actin-binding proteins (ABPs) in the regulation of synapse morphology and plasticity has been well established. SH3 protein interacting with Nck, 90 kDa (SPIN90), an Nck-interacting protein highly expressed in synapses, is essential for actin remodeling and dendritic spine morphology. Synaptic targeting of SPIN90 to spine heads or dendritic shafts depends on its phosphorylation state, leading to blockage of cofilin-mediated actin depolymerization and spine shrinkage. However, the physiological role of SPIN90 in long-term plasticity, learning and memory are largely unknown. In this study, we demonstrate that Spin90-knockout (KO) mice exhibit substantial deficits in synaptic plasticity and behavioral flexibility. We found that loss of SPIN90 disrupted dendritic spine density in CA1 neurons of the hippocampus and significantly impaired long-term depression (LTD), leaving basal synaptic transmission and long-term potentiation (LTP) intact. These impairments were due in part to deficits in AMPA receptor endocytosis and its pre-requisites, GluA1 dephosphorylation and postsynaptic density (PSD) 95 phosphorylation, but also by an intrinsic activation of Akt-GSK3β signaling as a result of Spin90-KO. In accordance with these defects, mice lacking SPIN90 were found to carry significant deficits in object-recognition and behavioral flexibility, while learning ability was largely unaffected. Collectively, these findings demonstrate a novel modulatory role for SPIN90 in hippocampal LTD and behavioral flexibility. PMID:28979184
He, Hongbo; Mahnke, Amanda H.; Doyle, Sukhjeevan; Fan, Ni; Wang, Chih-Chieh; Hall, Benjamin J.; Tang, Ya-Ping; Inglis, Fiona M.; Chen, Chu; Erickson, Jeffrey D.
2012-01-01
The level and integrity of glutamate transmission during critical periods of postnatal development plays an important role in the refinement of pyramidal neuron dendritic arbor, synaptic plasticity, and cognition. Presently, it is not clear how excitatory transmission via the two predominant isoforms of the vesicular glutamate transporter (VGLUT1 and VGLUT2) participate in this process. To assess a neurodevelopmental role for VGLUT2 in pyramidal neuron maturation we have generated recombinant VGLUT2 knockout mice and inactivated VGLUT2 throughout development using Emx1-Cre+/+ knockin mice. We show that VGLUT2-deficiency in cortico-limbic circuits results in reduced evoked glutamate transmission, release probability, and LTD at hippocampal CA3-CA1 synapses during a formative developmental period (postnatal days 11–14). In adults, we find a marked reduction in the amount of dendritic arbor across the span of the dendritic tree of CA1 pyramidal neurons, reduced LTP and levels of synaptic markers spinophilin and VGLUT1. Loss of dendritic arbor is accompanied by corresponding reductions in the number of dendritic spines, suggesting widespread alterations in synaptic connectivity. Conditional VGLUT2 knockout mice exhibit increased open-field exploratory activity, yet impaired spatial learning and memory; endophenotypes similar to NMDA receptor knockdown mice. Remarkably, the impairment in learning can be partially restored selectively increasing NMDA-receptor mediated glutamate transmission in adult mice by prolonged treatment with D-serine and a D-amino acid oxidase inhibitor. Our data indicate that VGLUT2 expression is pivotal to the proper development of mature pyramidal neuronal architecture and plasticity, and that such glutamatergic deficiency leads to cognitive malfunction as observed in several neurodevelopmental psychiatric disorders. PMID:23136427
He, Hongbo; Mahnke, Amanda H; Doyle, Sukhjeevan; Fan, Ni; Wang, Chih-Chieh; Hall, Benjamin J; Tang, Ya-Ping; Inglis, Fiona M; Chen, Chu; Erickson, Jeffrey D
2012-11-07
The level and integrity of glutamate transmission during critical periods of postnatal development plays an important role in the refinement of pyramidal neuron dendritic arbor, synaptic plasticity, and cognition. Presently, it is not clear how excitatory transmission via the two predominant isoforms of the vesicular glutamate transporter (VGLUT1 and VGLUT2) participate in this process. To assess a neurodevelopmental role for VGLUT2 in pyramidal neuron maturation, we generated recombinant VGLUT2 knock-out mice and inactivated VGLUT2 throughout development using Emx1-Cre(+/+) knock-in mice. We show that VGLUT2 deficiency in corticolimbic circuits results in reduced evoked glutamate transmission, release probability, and LTD at hippocampal CA3-CA1 synapses during a formative developmental period (postnatal days 11-14). In adults, we find a marked reduction in the amount of dendritic arbor across the span of the dendritic tree of CA1 pyramidal neurons and reduced long-term potentiation and levels of synaptic markers spinophilin and VGLUT1. Loss of dendritic arbor is accompanied by corresponding reductions in the number of dendritic spines, suggesting widespread alterations in synaptic connectivity. Conditional VGLUT2 knock-out mice exhibit increased open-field exploratory activity yet impaired spatial learning and memory, endophenotypes similar to those of NMDA receptor knock-down mice. Remarkably, the impairment in learning can be partially restored by selectively increasing NMDA receptor-mediated glutamate transmission in adult mice by prolonged treatment with d-serine and a d-amino acid oxidase inhibitor. Our data indicate that VGLUT2 expression is pivotal to the proper development of mature pyramidal neuronal architecture and plasticity, and that such glutamatergic deficiency leads to cognitive malfunction as observed in several neurodevelopmental psychiatric disorders.
Reelin Supplementation Enhances Cognitive Ability, Synaptic Plasticity, and Dendritic Spine Density
ERIC Educational Resources Information Center
Rogers, Justin T.; Rusiana, Ian; Trotter, Justin; Zhao, Lisa; Donaldson, Erika; Pak, Daniel T.S.; Babus, Lenard W.; Peters, Melinda; Banko, Jessica L.; Chavis, Pascale; Rebeck, G. William; Hoe, Hyang-Sook; Weeber, Edwin J.
2011-01-01
Apolipoprotein receptors belong to an evolutionarily conserved surface receptor family that has intimate roles in the modulation of synaptic plasticity and is necessary for proper hippocampal-dependent memory formation. The known lipoprotein receptor ligand Reelin is important for normal synaptic plasticity, dendritic morphology, and cognitive…
Matrix Metalloproteinase-9 as a Novel Player in Synaptic Plasticity and Schizophrenia
Lepeta, Katarzyna; Kaczmarek, Leszek
2015-01-01
Recent findings implicate alterations in glutamate signaling, leading to aberrant synaptic plasticity, in schizophrenia. Matrix metalloproteinase-9 (MMP-9) has been shown to regulate glutamate receptors, be regulated by glutamate at excitatory synapses, and modulate physiological and morphological synaptic plasticity. By means of functional gene polymorphism, gene responsiveness to antipsychotics and blood plasma levels MMP-9 has recently been implicated in schizophrenia. This commentary critically reviews these findings based on the hypothesis that MMP-9 contributes to pathological synaptic plasticity in schizophrenia. PMID:25837304
Adenosine Kinase Deficiency in the Brain Results in Maladaptive Synaptic Plasticity.
Sandau, Ursula S; Colino-Oliveira, Mariana; Jones, Abbie; Saleumvong, Bounmy; Coffman, Shayla Q; Liu, Long; Miranda-Lourenço, Catarina; Palminha, Cátia; Batalha, Vânia L; Xu, Yiming; Huo, Yuqing; Diógenes, Maria J; Sebastião, Ana M; Boison, Detlev
2016-11-30
Adenosine kinase (ADK) deficiency in human patients (OMIM:614300) disrupts the methionine cycle and triggers hypermethioninemia, hepatic encephalopathy, cognitive impairment, and seizures. To identify whether this neurological phenotype is intrinsically based on ADK deficiency in the brain or if it is secondary to liver dysfunction, we generated a mouse model with a brain-wide deletion of ADK by introducing a Nestin-Cre transgene into a line of conditional ADK deficient Adk fl/fl mice. These Adk Δbrain mice developed a progressive stress-induced seizure phenotype associated with spontaneous convulsive seizures and profound deficits in hippocampus-dependent learning and memory. Pharmacological, biochemical, and electrophysiological studies suggest enhanced adenosine levels around synapses resulting in an enhanced adenosine A 1 receptor (A 1 R)-dependent protective tone despite lower expression levels of the receptor. Theta-burst-induced LTP was enhanced in the mutants and this was dependent on adenosine A 2A receptor (A 2A R) and tropomyosin-related kinase B signaling, suggesting increased activation of these receptors in synaptic plasticity phenomena. Accordingly, reducing adenosine A 2A receptor activity in Adk Δbrain mice restored normal associative learning and contextual memory and attenuated seizure risk. We conclude that ADK deficiency in the brain triggers neuronal adaptation processes that lead to dysregulated synaptic plasticity, cognitive deficits, and increased seizure risk. Therefore, ADK mutations have an intrinsic effect on brain physiology and may present a genetic risk factor for the development of seizures and learning impairments. Furthermore, our data show that blocking A 2A R activity therapeutically can attenuate neurological symptoms in ADK deficiency. A novel human genetic condition (OMIM #614300) that is based on mutations in the adenosine kinase (Adk) gene has been discovered recently. Affected patients develop hepatic encephalopathy, seizures, and severe cognitive impairment. To model and understand the neurological phenotype of the human mutation, we generated a new conditional knock-out mouse with a brain-specific deletion of Adk (Adk Δbrain ). Similar to ADK-deficient patients, Adk Δbrain mice develop seizures and cognitive deficits. We identified increased basal synaptic transmission and enhanced adenosine A 2A receptor (A 2A R)-dependent synaptic plasticity as the underlying mechanisms that govern these phenotypes. Our data show that neurological phenotypes in ADK-deficient patients are intrinsic to ADK deficiency in the brain and that blocking A 2A R activity therapeutically can attenuate neurological symptoms in ADK deficiency. Copyright © 2016 the authors 0270-6474/16/3612118-12$15.00/0.
Berthet, Pierre; Hellgren-Kotaleski, Jeanette; Lansner, Anders
2012-01-01
Several studies have shown a strong involvement of the basal ganglia (BG) in action selection and dopamine dependent learning. The dopaminergic signal to striatum, the input stage of the BG, has been commonly described as coding a reward prediction error (RPE), i.e., the difference between the predicted and actual reward. The RPE has been hypothesized to be critical in the modulation of the synaptic plasticity in cortico-striatal synapses in the direct and indirect pathway. We developed an abstract computational model of the BG, with a dual pathway structure functionally corresponding to the direct and indirect pathways, and compared its behavior to biological data as well as other reinforcement learning models. The computations in our model are inspired by Bayesian inference, and the synaptic plasticity changes depend on a three factor Hebbian–Bayesian learning rule based on co-activation of pre- and post-synaptic units and on the value of the RPE. The model builds on a modified Actor-Critic architecture and implements the direct (Go) and the indirect (NoGo) pathway, as well as the reward prediction (RP) system, acting in a complementary fashion. We investigated the performance of the model system when different configurations of the Go, NoGo, and RP system were utilized, e.g., using only the Go, NoGo, or RP system, or combinations of those. Learning performance was investigated in several types of learning paradigms, such as learning-relearning, successive learning, stochastic learning, reversal learning and a two-choice task. The RPE and the activity of the model during learning were similar to monkey electrophysiological and behavioral data. Our results, however, show that there is not a unique best way to configure this BG model to handle well all the learning paradigms tested. We thus suggest that an agent might dynamically configure its action selection mode, possibly depending on task characteristics and also on how much time is available. PMID:23060764
Restoring synaptic plasticity and memory in mouse models of Alzheimer's disease by PKR inhibition.
Hwang, Kyoung-Doo; Bak, Myeong Seong; Kim, Sang Jeong; Rhee, Sangmyung; Lee, Yong-Seok
2017-12-13
Alzheimer's disease (AD) is a neurodegenerative disorder associated with deficits in cognition and synaptic plasticity. While accumulation of amyloid β (Aβ) and hyper-phosphorylation of tau are parts of the etiology, AD can be caused by a large number of different genetic mutations and other unknown factors. Considering such a heterogeneous nature of AD, it would be desirable to develop treatment strategies that can improve memory irrespective of the individual causes. Reducing the phosphorylation of eukaryotic translation initiation factor 2α (eIF2α) was shown to enhance long-term memory and synaptic plasticity in naïve mice. Moreover, hyper-phosphorylation of eIF2α is observed in the brains of postmortem AD patients. Therefore, regulating eIF2α phosphorylation can be a plausible candidate for restoring memory in AD by targeting memory-enhancing mechanism. In this study, we examined whether PKR inhibition can rescue synaptic and learning deficits in two different AD mouse models; 5XFAD transgenic and Aβ 1-42 -injected mice. We found that the acute treatment of PKR inhibitor (PKRi) can restore the deficits in long-term memory and long-term potentiation (LTP) in both mouse models without affecting the Aβ load in the hippocampus. Our results prove the principle that targeting memory enhancing mechanisms can be a valid candidate for developing AD treatment.
Neuronal cytoskeleton in synaptic plasticity and regeneration.
Gordon-Weeks, Phillip R; Fournier, Alyson E
2014-04-01
During development, dynamic changes in the axonal growth cone and dendrite are necessary for exploratory movements underlying initial axo-dendritic contact and ultimately the formation of a functional synapse. In the adult central nervous system, an impressive degree of plasticity is retained through morphological and molecular rearrangements in the pre- and post-synaptic compartments that underlie the strengthening or weakening of synaptic pathways. Plasticity is regulated by the interplay of permissive and inhibitory extracellular cues, which signal through receptors at the synapse to regulate the closure of critical periods of developmental plasticity as well as by acute changes in plasticity in response to experience and activity in the adult. The molecular underpinnings of synaptic plasticity are actively studied and it is clear that the cytoskeleton is a key substrate for many cues that affect plasticity. Many of the cues that restrict synaptic plasticity exhibit residual activity in the injured adult CNS and restrict regenerative growth by targeting the cytoskeleton. Here, we review some of the latest insights into how cytoskeletal remodeling affects neuronal plasticity and discuss how the cytoskeleton is being targeted in an effort to promote plasticity and repair following traumatic injury in the central nervous system. © 2013 International Society for Neurochemistry.
Glial Cells in the Genesis and Regulation of Circadian Rhythms
Chi-Castañeda, Donají; Ortega, Arturo
2018-01-01
Circadian rhythms are biological oscillations with a period of ~24 h. These rhythms are orchestrated by a circadian timekeeper in the suprachiasmatic nucleus of the hypothalamus, the circadian “master clock,” which exactly adjusts clock outputs to solar time via photic synchronization. At the molecular level, circadian rhythms are generated by the interaction of positive and negative feedback loops of transcriptional and translational processes of the so-called “clock genes.” A large number of clock genes encode numerous proteins that regulate their own transcription and that of other genes, collectively known as “clock-controlled genes.” In addition to the sleep/wake cycle, many cellular processes are regulated by circadian rhythms, including synaptic plasticity in which an exquisite interplay between neurons and glial cells takes place. In particular, there is compelling evidence suggesting that glial cells participate in and regulate synaptic plasticity in a circadian fashion, possibly representing the missing cellular and physiological link between circadian rhythms with learning and cognition processes. Here we review recent studies in support of this hypothesis, focusing on the interplay between glial cells, synaptic plasticity, and circadian rhythmogenesis. PMID:29483880
Does Spike-Timing-Dependent Synaptic Plasticity Couple or Decouple Neurons Firing in Synchrony?
Knoblauch, Andreas; Hauser, Florian; Gewaltig, Marc-Oliver; Körner, Edgar; Palm, Günther
2012-01-01
Spike synchronization is thought to have a constructive role for feature integration, attention, associative learning, and the formation of bidirectionally connected Hebbian cell assemblies. By contrast, theoretical studies on spike-timing-dependent plasticity (STDP) report an inherently decoupling influence of spike synchronization on synaptic connections of coactivated neurons. For example, bidirectional synaptic connections as found in cortical areas could be reproduced only by assuming realistic models of STDP and rate coding. We resolve this conflict by theoretical analysis and simulation of various simple and realistic STDP models that provide a more complete characterization of conditions when STDP leads to either coupling or decoupling of neurons firing in synchrony. In particular, we show that STDP consistently couples synchronized neurons if key model parameters are matched to physiological data: First, synaptic potentiation must be significantly stronger than synaptic depression for small (positive or negative) time lags between presynaptic and postsynaptic spikes. Second, spike synchronization must be sufficiently imprecise, for example, within a time window of 5–10 ms instead of 1 ms. Third, axonal propagation delays should not be much larger than dendritic delays. Under these assumptions synchronized neurons will be strongly coupled leading to a dominance of bidirectional synaptic connections even for simple STDP models and low mean firing rates at the level of spontaneous activity. PMID:22936909
LRP8-Reelin-regulated Neuronal (LRN) Enhancer Signature Underlying Learning and Memory Formation
Telese, Francesca; Ma, Qi; Perez, Patricia Montilla; Notani, Dimple; Oh, Soohwan; Li, Wenbo; Comoletti, Davide; Ohgi, Kenneth A.; Taylor, Havilah; Rosenfeld, Michael G.
2015-01-01
Summary One of the exceptional properties of the brain is its ability to acquire new knowledge through learning and to store that information through memory. The epigenetic mechanisms linking changes in neuronal transcriptional programs to behavioral plasticity remain largely unknown. Here, we identify the epigenetic signature of the neuronal enhancers required for transcriptional regulation of synaptic plasticity genes during memory formation, linking this to Reelin signaling. The binding of Reelin to its receptor, LRP8, triggers activation of this cohort of LRP8-Reelin-regulated-Neuronal (LRN) enhancers that serve as the ultimate convergence point of a novel synapse-to-nucleus pathway. Reelin simultaneously regulates NMDA-receptor transmission, which reciprocally permits the required, γ-secretase-dependent cleavage of LRP8, revealing an unprecedented role for its intracellular domain in the regulation of synaptically generated signals. These results uncover an in vivo enhancer code serving as a critical molecular component of cognition and relevant to psychiatric disorders linked to defects in Reelin signaling. PMID:25892301
CaM Kinases: From Memories to Addiction.
Müller, Christian P; Quednow, Boris B; Lourdusamy, Anbarasu; Kornhuber, Johannes; Schumann, Gunter; Giese, K Peter
2016-02-01
Drug addiction is a major psychiatric disorder with a neurobiological basis that is still insufficiently understood. Initially, non-addicted, controlled drug consumption and drug instrumentalization are established. They comprise highly systematic behaviours acquired by learning and the establishment of drug memories. Ca(2+)/calmodulin-dependent protein kinases (CaMKs) are important Ca(2+) sensors translating glutamatergic activation into synaptic plasticity during learning and memory formation. Here we review the role of CaMKs in the establishment of drug-related behaviours in animal models and in humans. Converging evidence now shows that CaMKs are a crucial mechanism of how addictive drugs induce synaptic plasticity and establish various types of drug memories. Thereby, CaMKs are not only molecular relays for glutamatergic activity but they also directly control dopaminergic and serotonergic activity in the mesolimbic reward system. They can now be considered as major molecular pathways translating normal memory formation into establishment of drug memories and possibly transition to drug addiction. Copyright © 2015 Elsevier Ltd. All rights reserved.
Experience-dependent modification of a central amygdala fear circuit
Li, Haohong; Penzo, Mario A.; Taniguchi, Hiroki; Kopec, Charles D.; Huang, Z. Josh; Li, Bo
2013-01-01
The amygdala is essential for fear learning and expression. The central amygdala (CeA), once viewed as a passive relay between the amygdala complex and downstream fear effectors, has emerged as an active participant in fear conditioning. However, how CeA contributes to the learning and expression of fear is unclear. Here we show in mice that fear conditioning induces robust plasticity of excitatory synapses onto inhibitory neurons in the lateral subdivision of CeA (CeL). This experience-dependent plasticity is cell-specific, bidirectional, and expressed presynaptically by inputs from the lateral amygdala. In particular, preventing synaptic potentiation onto somatostatin-positive neurons impairs fear memory formation. Furthermore, activation of these neurons is necessary for fear memory recall and sufficient to drive fear responses. Our findings support a model in which the fear conditioning-induced synaptic modifications in CeL favor the activation of somatostatin-positive neurons, which inhibit CeL output thereby disinhibiting the medial subdivision of CeA and releasing fear expression. PMID:23354330
Modulating Hippocampal Plasticity with In Vivo Brain Stimulation
2015-09-16
persists in the Schaffer collateral–CA1 region of the hippocampus . NMDA-dependent LTP has been shown to be essential for learning and memory ...S114 –S121. CrossRef Medline Neves G, Cooke SF, Bliss TV (2008) Synaptic plasticity, memory and the hippocampus : a neural network approach to causality...and memory . Understanding such molecular effects will lead to a better understanding of the mechanisms by which brain stimulation produces its effects
Event-Driven Random Back-Propagation: Enabling Neuromorphic Deep Learning Machines
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.
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.
Pan, Enhui; Zhang, Xiao-an; Huang, Zhen; Krezel, Artur; Zhao, Min; Tin-berg, Christine E.; Lippard, Stephen J.; McNamara, James O.
2011-01-01
The presence of zinc in glutamatergic synaptic vesicles of excitatory neurons of mammalian cerebral cortex suggests that zinc might regulate plasticity of synapses formed by these neurons. Long term potentiation (LTP) is a form of synaptic plasticity that may underlie learning and memory. We tested the hypothesis that zinc within vesicles of mossy fibers (mf) contributes to mf-LTP, a classical form of presynaptic LTP. We synthesized an extracellular zinc chelator with selectivity and kinetic properties suitable for study of the large transient of zinc in the synaptic cleft induced by mf stimulation. We found that vesicular zinc is required for presynaptic mf-LTP. Unexpectedly, vesicular zinc also inhibits a novel form of postsynaptic mf-LTP. Because the mf-CA3 synapse provides a major source of excitatory input to the hippocampus, regulating its efficacy by these dual actions of vesicular zinc is critical to proper function of hippocampal circuitry in health and disease. PMID:21943607
Verhoog, Matthijs B.; Mansvelder, Huibert D.
2011-01-01
Throughout life, activity-dependent changes in neuronal connection strength enable the brain to refine neural circuits and learn based on experience. In line with predictions made by Hebb, synapse strength can be modified depending on the millisecond timing of action potential firing (STDP). The sign of synaptic plasticity depends on the spike order of presynaptic and postsynaptic neurons. Ionotropic neurotransmitter receptors, such as NMDA receptors and nicotinic acetylcholine receptors, are intimately involved in setting the rules for synaptic strengthening and weakening. In addition, timing rules for STDP within synapses are not fixed. They can be altered by activation of ionotropic receptors located at, or close to, synapses. Here, we will highlight studies that uncovered how network actions control and modulate timing rules for STDP by activating presynaptic ionotropic receptors. Furthermore, we will discuss how interaction between different types of ionotropic receptors may create “timing” windows during which particular timing rules lead to synaptic changes. PMID:21941664
Minge, Daniel; Senkov, Oleg; Kaushik, Rahul; Herde, Michel K.; Tikhobrazova, Olga; Wulff, Andreas B.; Mironov, Andrey; van Kuppevelt, Toin H.; Oosterhof, Arie; Kochlamazashvili, Gaga
2017-01-01
Abstract Heparan sulfate (HS) proteoglycans represent a major component of the extracellular matrix and are critical for brain development. However, their function in the mature brain remains to be characterized. Here, acute enzymatic digestion of HS side chains was used to uncover how HSs support hippocampal function in vitro and in vivo. We found that long-term potentiation (LTP) of synaptic transmission at CA3–CA1 Schaffer collateral synapses was impaired after removal of highly sulfated HSs with heparinase 1. This reduction was associated with decreased Ca2+ influx during LTP induction, which was the consequence of a reduced excitability of CA1 pyramidal neurons. At the subcellular level, heparinase treatment resulted in reorganization of the distal axon initial segment, as detected by a reduction in ankyrin G expression. In vivo, digestion of HSs impaired context discrimination in a fear conditioning paradigm and oscillatory network activity in the low theta band after fear conditioning. Thus, HSs maintain neuronal excitability and, as a consequence, support synaptic plasticity and learning. PMID:28119345
Spike-Based Bayesian-Hebbian Learning of Temporal Sequences
Lindén, Henrik; Lansner, Anders
2016-01-01
Many cognitive and motor functions are enabled by the temporal representation and processing of stimuli, but it remains an open issue how neocortical microcircuits can reliably encode and replay such sequences of information. To better understand this, a modular attractor memory network is proposed in which meta-stable sequential attractor transitions are learned through changes to synaptic weights and intrinsic excitabilities via the spike-based Bayesian Confidence Propagation Neural Network (BCPNN) learning rule. We find that the formation of distributed memories, embodied by increased periods of firing in pools of excitatory neurons, together with asymmetrical associations between these distinct network states, can be acquired through plasticity. The model’s feasibility is demonstrated using simulations of adaptive exponential integrate-and-fire model neurons (AdEx). We show that the learning and speed of sequence replay depends on a confluence of biophysically relevant parameters including stimulus duration, level of background noise, ratio of synaptic currents, and strengths of short-term depression and adaptation. Moreover, sequence elements are shown to flexibly participate multiple times in the sequence, suggesting that spiking attractor networks of this type can support an efficient combinatorial code. The model provides a principled approach towards understanding how multiple interacting plasticity mechanisms can coordinate hetero-associative learning in unison. PMID:27213810
Lovinger, David M.; Kash, Thomas L.
2015-01-01
Long-lasting changes in synaptic function (i.e., synaptic plasticity) have long been thought to contribute to information storage in the nervous system. Although synaptic plasticity mainly has adaptive functions that allow the organism to function in complex environments, it is now clear that certain events or exposure to various substances can produce plasticity that has negative consequences for organisms. Exposure to drugs of abuse, in particular ethanol, is a life experience that can activate or alter synaptic plasticity, often resulting in increased drug seeking and taking and in many cases addiction. Two brain regions subject to alcohol’s effects on synaptic plasticity are the striatum and bed nucleus of the stria terminalis (BNST), both of which have key roles in alcohol’s actions and control of intake. The specific effects depend on both the brain region analyzed (e.g., specific subregions of the striatum and BNST) and the duration of ethanol exposure (i.e., acute vs. chronic). Plastic changes in synaptic transmission in these two brain regions following prolonged ethanol exposure are thought to contribute to excessive alcohol drinking and relapse to drinking. Understanding the mechanisms underlying this plasticity may lead to new therapies for treatment of these and other aspects of alcohol use disorder. PMID:26259092
Enabling an Integrated Rate-temporal Learning Scheme on Memristor
NASA Astrophysics Data System (ADS)
He, Wei; Huang, Kejie; Ning, Ning; Ramanathan, Kiruthika; Li, Guoqi; Jiang, Yu; Sze, Jiayin; Shi, Luping; Zhao, Rong; Pei, Jing
2014-04-01
Learning scheme is the key to the utilization of spike-based computation and the emulation of neural/synaptic behaviors toward realization of cognition. The biological observations reveal an integrated spike time- and spike rate-dependent plasticity as a function of presynaptic firing frequency. However, this integrated rate-temporal learning scheme has not been realized on any nano devices. In this paper, such scheme is successfully demonstrated on a memristor. Great robustness against the spiking rate fluctuation is achieved by waveform engineering with the aid of good analog properties exhibited by the iron oxide-based memristor. The spike-time-dependence plasticity (STDP) occurs at moderate presynaptic firing frequencies and spike-rate-dependence plasticity (SRDP) dominates other regions. This demonstration provides a novel approach in neural coding implementation, which facilitates the development of bio-inspired computing systems.
Human θ burst stimulation enhances subsequent motor learning and increases performance variability.
Teo, James T H; Swayne, Orlando B C; Cheeran, Binith; Greenwood, Richard J; Rothwell, John C
2011-07-01
Intermittent theta burst stimulation (iTBS) transiently increases motor cortex excitability in healthy humans by a process thought to involve synaptic long-term potentiation (LTP), and this is enhanced by nicotine. Acquisition of a ballistic motor task is likewise accompanied by increased excitability and presumed intracortical LTP. Here, we test how iTBS and nicotine influences subsequent motor learning. Ten healthy subjects participated in a double-blinded placebo-controlled trial testing the effects of iTBS and nicotine. iTBS alone increased the rate of learning but this increase was blocked by nicotine. We then investigated factors other than synaptic strengthening that may play a role. Behavioral analysis and modeling suggested that iTBS increased performance variability, which correlated with learning outcome. A control experiment confirmed the increase in motor output variability by showing that iTBS increased the dispersion of involuntary transcranial magnetic stimulation-evoked thumb movements. We suggest that in addition to the effect on synaptic plasticity, iTBS may have facilitated performance by increasing motor output variability; nicotine negated this effect on variability perhaps via increasing the signal-to-noise ratio in cerebral cortex.
Precise Synaptic Efficacy Alignment Suggests Potentiation Dominated Learning.
Hartmann, Christoph; Miner, Daniel C; Triesch, Jochen
2015-01-01
Recent evidence suggests that parallel synapses from the same axonal branch onto the same dendritic branch have almost identical strength. It has been proposed that this alignment is only possible through learning rules that integrate activity over long time spans. However, learning mechanisms such as spike-timing-dependent plasticity (STDP) are commonly assumed to be temporally local. Here, we propose that the combination of temporally local STDP and a multiplicative synaptic normalization mechanism is sufficient to explain the alignment of parallel synapses. To address this issue, we introduce three increasingly complex models: First, we model the idealized interaction of STDP and synaptic normalization in a single neuron as a simple stochastic process and derive analytically that the alignment effect can be described by a so-called Kesten process. From this we can derive that synaptic efficacy alignment requires potentiation-dominated learning regimes. We verify these conditions in a single-neuron model with independent spiking activities but more realistic synapses. As expected, we only observe synaptic efficacy alignment for long-term potentiation-biased STDP. Finally, we explore how well the findings transfer to recurrent neural networks where the learning mechanisms interact with the correlated activity of the network. We find that due to the self-reinforcing correlations in recurrent circuits under STDP, alignment occurs for both long-term potentiation- and depression-biased STDP, because the learning will be potentiation dominated in both cases due to the potentiating events induced by correlated activity. This is in line with recent results demonstrating a dominance of potentiation over depression during waking and normalization during sleep. This leads us to predict that individual spine pairs will be more similar after sleep compared to after sleep deprivation. In conclusion, we show that synaptic normalization in conjunction with coordinated potentiation--in this case, from STDP in the presence of correlated pre- and post-synaptic activity--naturally leads to an alignment of parallel synapses.
Real time unsupervised learning of visual stimuli in neuromorphic VLSI systems
Giulioni, Massimiliano; Corradi, Federico; Dante, Vittorio; del Giudice, Paolo
2015-01-01
Neuromorphic chips embody computational principles operating in the nervous system, into microelectronic devices. In this domain it is important to identify computational primitives that theory and experiments suggest as generic and reusable cognitive elements. One such element is provided by attractor dynamics in recurrent networks. Point attractors are equilibrium states of the dynamics (up to fluctuations), determined by the synaptic structure of the network; a ‘basin’ of attraction comprises all initial states leading to a given attractor upon relaxation, hence making attractor dynamics suitable to implement robust associative memory. The initial network state is dictated by the stimulus, and relaxation to the attractor state implements the retrieval of the corresponding memorized prototypical pattern. In a previous work we demonstrated that a neuromorphic recurrent network of spiking neurons and suitably chosen, fixed synapses supports attractor dynamics. Here we focus on learning: activating on-chip synaptic plasticity and using a theory-driven strategy for choosing network parameters, we show that autonomous learning, following repeated presentation of simple visual stimuli, shapes a synaptic connectivity supporting stimulus-selective attractors. Associative memory develops on chip as the result of the coupled stimulus-driven neural activity and ensuing synaptic dynamics, with no artificial separation between learning and retrieval phases. PMID:26463272
Emergent spatial synaptic structure from diffusive plasticity.
Sweeney, Yann; Clopath, Claudia
2017-04-01
Some neurotransmitters can diffuse freely across cell membranes, influencing neighbouring neurons regardless of their synaptic coupling. This provides a means of neural communication, alternative to synaptic transmission, which can influence the way in which neural networks process information. Here, we ask whether diffusive neurotransmission can also influence the structure of synaptic connectivity in a network undergoing plasticity. We propose a form of Hebbian synaptic plasticity which is mediated by a diffusive neurotransmitter. Whenever a synapse is modified at an individual neuron through our proposed mechanism, similar but smaller modifications occur in synapses connecting to neighbouring neurons. The effects of this diffusive plasticity are explored in networks of rate-based neurons. This leads to the emergence of spatial structure in the synaptic connectivity of the network. We show that this spatial structure can coexist with other forms of structure in the synaptic connectivity, such as with groups of strongly interconnected neurons that form in response to correlated external drive. Finally, we explore diffusive plasticity in a simple feedforward network model of receptive field development. We show that, as widely observed across sensory cortex, the preferred stimulus identity of neurons in our network become spatially correlated due to diffusion. Our proposed mechanism of diffusive plasticity provides an efficient mechanism for generating these spatial correlations in stimulus preference which can flexibly interact with other forms of synaptic organisation. © 2016 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.
NASA Astrophysics Data System (ADS)
Srinivasan, Gopalakrishnan; Sengupta, Abhronil; Roy, Kaushik
2016-07-01
Spiking Neural Networks (SNNs) have emerged as a powerful neuromorphic computing paradigm to carry out classification and recognition tasks. Nevertheless, the general purpose computing platforms and the custom hardware architectures implemented using standard CMOS technology, have been unable to rival the power efficiency of the human brain. Hence, there is a need for novel nanoelectronic devices that can efficiently model the neurons and synapses constituting an SNN. In this work, we propose a heterostructure composed of a Magnetic Tunnel Junction (MTJ) and a heavy metal as a stochastic binary synapse. Synaptic plasticity is achieved by the stochastic switching of the MTJ conductance states, based on the temporal correlation between the spiking activities of the interconnecting neurons. Additionally, we present a significance driven long-term short-term stochastic synapse comprising two unique binary synaptic elements, in order to improve the synaptic learning efficiency. We demonstrate the efficacy of the proposed synaptic configurations and the stochastic learning algorithm on an SNN trained to classify handwritten digits from the MNIST dataset, using a device to system-level simulation framework. The power efficiency of the proposed neuromorphic system stems from the ultra-low programming energy of the spintronic synapses.
Srinivasan, Gopalakrishnan; Sengupta, Abhronil; Roy, Kaushik
2016-07-13
Spiking Neural Networks (SNNs) have emerged as a powerful neuromorphic computing paradigm to carry out classification and recognition tasks. Nevertheless, the general purpose computing platforms and the custom hardware architectures implemented using standard CMOS technology, have been unable to rival the power efficiency of the human brain. Hence, there is a need for novel nanoelectronic devices that can efficiently model the neurons and synapses constituting an SNN. In this work, we propose a heterostructure composed of a Magnetic Tunnel Junction (MTJ) and a heavy metal as a stochastic binary synapse. Synaptic plasticity is achieved by the stochastic switching of the MTJ conductance states, based on the temporal correlation between the spiking activities of the interconnecting neurons. Additionally, we present a significance driven long-term short-term stochastic synapse comprising two unique binary synaptic elements, in order to improve the synaptic learning efficiency. We demonstrate the efficacy of the proposed synaptic configurations and the stochastic learning algorithm on an SNN trained to classify handwritten digits from the MNIST dataset, using a device to system-level simulation framework. The power efficiency of the proposed neuromorphic system stems from the ultra-low programming energy of the spintronic synapses.
Hippocampal ripples down-regulate synapses.
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.
Ultrastructural evidence for synaptic scaling across the wake/sleep cycle.
de Vivo, Luisa; Bellesi, Michele; Marshall, William; Bushong, Eric A; Ellisman, Mark H; Tononi, Giulio; Cirelli, Chiara
2017-02-03
It is assumed that synaptic strengthening and weakening balance throughout learning to avoid runaway potentiation and memory interference. However, energetic and informational considerations suggest that potentiation should occur primarily during wake, when animals learn, and depression should occur during sleep. We measured 6920 synapses in mouse motor and sensory cortices using three-dimensional electron microscopy. The axon-spine interface (ASI) decreased ~18% after sleep compared with wake. This decrease was proportional to ASI size, which is indicative of scaling. Scaling was selective, sparing synapses that were large and lacked recycling endosomes. Similar scaling occurred for spine head volume, suggesting a distinction between weaker, more plastic synapses (~80%) and stronger, more stable synapses. These results support the hypothesis that a core function of sleep is to renormalize overall synaptic strength increased by wake. Copyright © 2017, American Association for the Advancement of Science.
Histone Deacetylase Inhibition Facilitates Massed Pattern-Induced Synaptic Plasticity and Memory
ERIC Educational Resources Information Center
Pandey, Kiran; Sharma, Kaushik P.; Sharma, Shiv K.
2015-01-01
Massed training is less effective for long-term memory formation than the spaced training. The role of acetylation in synaptic plasticity and memory is now well established. However, the role of this important protein modification in synaptic plasticity induced by massed pattern of stimulation or memory induced by massed training is not well…
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.
Synaptic Plasticity and Memory: New Insights from Hippocampal Left-Right Asymmetries.
El-Gaby, Mohamady; Shipton, Olivia A; Paulsen, Ole
2015-10-01
All synapses are not the same. They differ in their morphology, molecular constituents, and malleability. A striking left-right asymmetry in the distribution of different types of synapse was recently uncovered at the CA3-CA1 projection in the mouse hippocampus, whereby afferents from the CA3 in the left hemisphere innervate small, highly plastic synapses on the apical dendrites of CA1 pyramidal neurons, whereas those originating from the right CA3 target larger, more stable synapses. Activity-dependent modification of these synapses is thought to participate in circuit formation and remodeling during development, and further plastic changes may support memory encoding in adulthood. Therefore, exploiting the CA3-CA1 asymmetry provides a promising opportunity to investigate the roles that different types of synapse play in these fundamental properties of the CNS. Here we describe the discovery of these segregated synaptic populations in the mouse hippocampus, and discuss what we have already learnt about synaptic plasticity from this asymmetric arrangement. We then propose models for how the asymmetry could be generated during development, and how the adult hippocampus might use these distinct populations of synapses differentially during learning and memory. Finally, we outline the potential implications of this left-right asymmetry for human hippocampal function, as well as dysfunction in memory disorders such as Alzheimer's disease. © The Author(s) 2014.
Bhagya, Venkanna Rao; Srikumar, Bettadapura N; Veena, Jayagopalan; Shankaranarayana Rao, Byrathnahalli S
2017-08-01
Exposure to prolonged stress results in structural and functional alterations in the hippocampus including reduced long-term potentiation (LTP), neurogenesis, spatial learning and working memory impairments, and enhanced anxiety-like behavior. On the other hand, enriched environment (EE) has beneficial effects on hippocampal structure and function, such as improved memory, increased hippocampal neurogenesis, and progressive synaptic plasticity. It is unclear whether exposure to short-term EE for 10 days can overcome restraint stress-induced cognitive deficits and impaired hippocampal plasticity. Consequently, the present study explored the beneficial effects of short-term EE on chronic stress-induced impaired LTP, working memory, and anxiety-like behavior. Male Wistar rats were subjected to chronic restraint stress (6 hr/day) over a period of 21 days, and then they were exposed to EE (6 hr/day) for 10 days. Restraint stress reduced hippocampal CA1-LTP, increased anxiety-like symptoms in elevated plus maze, and impaired working memory in T-maze task. Remarkably, EE facilitated hippocampal LTP, improved working memory performance, and completely overcame the effect of chronic stress on anxiety behavior. In conclusion, exposure to EE can bring out positive effects on synaptic plasticity in the hippocampus and thereby elicit its beneficial effects on cognitive functions. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
Noack, Marko; Partzsch, Johannes; Mayr, Christian G.; Hänzsche, Stefan; Scholze, Stefan; Höppner, Sebastian; Ellguth, Georg; Schüffny, Rene
2015-01-01
Synaptic dynamics, such as long- and short-term plasticity, play an important role in the complexity and biological realism achievable when running neural networks on a neuromorphic IC. For example, they endow the IC with an ability to adapt and learn from its environment. In order to achieve the millisecond to second time constants required for these synaptic dynamics, analog subthreshold circuits are usually employed. However, due to process variation and leakage problems, it is almost impossible to port these types of circuits to modern sub-100nm technologies. In contrast, we present a neuromorphic system in a 28 nm CMOS process that employs switched capacitor (SC) circuits to implement 128 short term plasticity presynapses as well as 8192 stop-learning synapses. The neuromorphic system consumes an area of 0.36 mm2 and runs at a power consumption of 1.9 mW. The circuit makes use of a technique for minimizing leakage effects allowing for real-time operation with time constants up to several seconds. Since we rely on SC techniques for all calculations, the system is composed of only generic mixed-signal building blocks. These generic building blocks make the system easy to port between technologies and the large digital circuit part inherent in an SC system benefits fully from technology scaling. PMID:25698914
Fructose consumption reduces hippocampal synaptic plasticity underlying cognitive performance
Cisternas, Pedro; Salazar, Paulina; Serrano, Felipe G.; Montecinos-Oliva, Carla; Arredondo, Sebastián B.; Varela-Nallar, Lorena; Barja, Salesa; Vio, Carlos P.; Gomez-Pinilla, Fernando; Inestrosa, Nibaldo C.
2017-01-01
Metabolic syndrome (MetS) is a global epidemic, which involves a spectrum of metabolic disorders comprising diabetes and obesity. The impact of MetS on the brain is becoming to be a concern, however, the poor understanding of mechanisms involved has limited the development of therapeutic strategies. We induced a MetS-like condition by exposing mice to fructose feeding for 7 weeks. There was a dramatic deterioration in the capacity of the hippocampus to sustain synaptic plasticity in the forms of long-term potentiation (LTP) and long-term depression (LTD). Mice exposed to fructose showed a reduction in the number of contact zones and the size of postsynaptic densities (PSDs) in the hippocampus, as well as a decrease in hippocampal neurogenesis. There was an increase in lipid peroxidation likely associated with a deficiency in plasma membrane excitability. Consistent with an overall hippocampal dysfunction, there was a subsequent decrease in hippocampal dependent learning and memory performance, i.e., spatial learning and episodic memory. Most of the pathological sequel of MetS in the brain was reversed three month after discontinue fructose feeding. These results are novel to show that MetS triggers a cascade of molecular events, which disrupt hippocampal functional plasticity, and specific aspects of learning and memory function. The overall information raises concerns about the risk imposed by excessive fructose consumption on the pathology of neurological disorders. PMID:26300486
Learning through ferroelectric domain dynamics in solid-state synapses
DOE Office of Scientific and Technical Information (OSTI.GOV)
Boyn, Soren; Grollier, Julie; Lecerf, Gwendal
In the brain, learning is achieved through the ability of synapses to reconfigure the strength by which they connect neurons (synaptic plasticity). In promising solid-state synapses called memristors, conductance can be finely tuned by voltage pulses and set to evolve according to a biological learning rule called spike-timing-dependent plasticity (STDP). Future neuromorphic architectures will comprise billions of such nanosynapses, which require a clear understanding of the physical mechanisms responsible for plasticity. Here we report on synapses based on ferroelectric tunnel junctions and show that STDP can be harnessed from inhomogeneous polarization switching. Through combined scanning probe imaging, electrical transport andmore » atomic-scale molecular dynamics, we demonstrate that conductance variations can be modelled by the nucleation-dominated reversal of domains. Finally, based on this physical model, our simulations show that arrays of ferroelectric nanosynapses can autonomously learn to recognize patterns in a predictable way, opening the path towards unsupervised learning in spiking neural networks.« less
Learning through ferroelectric domain dynamics in solid-state synapses
Boyn, Soren; Grollier, Julie; Lecerf, Gwendal; ...
2017-04-03
In the brain, learning is achieved through the ability of synapses to reconfigure the strength by which they connect neurons (synaptic plasticity). In promising solid-state synapses called memristors, conductance can be finely tuned by voltage pulses and set to evolve according to a biological learning rule called spike-timing-dependent plasticity (STDP). Future neuromorphic architectures will comprise billions of such nanosynapses, which require a clear understanding of the physical mechanisms responsible for plasticity. Here we report on synapses based on ferroelectric tunnel junctions and show that STDP can be harnessed from inhomogeneous polarization switching. Through combined scanning probe imaging, electrical transport andmore » atomic-scale molecular dynamics, we demonstrate that conductance variations can be modelled by the nucleation-dominated reversal of domains. Finally, based on this physical model, our simulations show that arrays of ferroelectric nanosynapses can autonomously learn to recognize patterns in a predictable way, opening the path towards unsupervised learning in spiking neural networks.« less
Kleschevnikov, Alexander M.; Belichenko, Pavel V.; Gall, Jessica; George, Lizzy; Nosheny, Rachel; Maloney, Michael T.; Salehi, Ahmad; Mobley, William C.
2011-01-01
Cognitive impairment in Down syndrome (DS) involves the hippocampus. In the Ts65Dn mouse model of DS, deficits in hippocampus-dependent learning and synaptic plasticity were linked to enhanced inhibition. However, the mechanistic basis of changes in inhibitory efficiency remains largely unexplored, and efficiency of the GABAergic synaptic neurotransmission has not yet been investigated in direct electrophysiological experiments. To investigate this important feature of neurobiology of DS, we examined synaptic and molecular properties of the GABAergic system in the dentate gyrus (DG) of adult Ts65Dn mice. Both GABAA and GABAB receptor-mediated components of evoked inhibitory postsynaptic currents (IPSCs) were significantly increased in Ts65Dn vs. control (2N) DG granule cells. These changes were unaccompanied by alterations in hippocampal levels of GABAA (α1, α2, α3, α5 and γ2) or GABAB (Gbr1a and Gbr1b) receptor subunits. Immunoreactivity for GAD65, a marker for GABAergic terminals, was also unchanged. In contrast, there was a marked change in functional parameters of GABAergic synapses. Paired stimulations showed reduced paired-pulse ratios of both GABAA and GABAB receptor-mediated IPSC components (IPSC2/IPSC1), suggesting an increase in presynaptic release of GABA. Consistent with increased gene dose, the level of the Kir3.2 subunit of potassium channels, effectors for postsynaptic GABAB receptors, was increased. This change was associated with enhanced postsynaptic GABAB/Kir3.2 signaling following application of the GABAB receptor agonist baclofen. Thus, both GABAA and GABAB receptor-mediated synaptic efficiency is increased in the Ts65Dn DG, thus likely contributing to deficient synaptic plasticity and poor learning in DS. PMID:22062771
2017-09-01
water maze hippocampus neurogenesis synaptic plasticity neurotrophins corticosterone priming inflammatory mediators gene expression...remaining studies conducted on the project at the University of Illinois at Chicago. The Morris water maze was the initial behavioral test of spatial...experience with this paradigm. In this test a mouse must learn the location of an escape platform by swimming in a pool of water at room temperature
Spike timing analysis in neural networks with unsupervised synaptic plasticity
NASA Astrophysics Data System (ADS)
Mizusaki, B. E. P.; Agnes, E. J.; Brunnet, L. G.; Erichsen, R., Jr.
2013-01-01
The synaptic plasticity rules that sculpt a neural network architecture are key elements to understand cortical processing, as they may explain the emergence of stable, functional activity, while avoiding runaway excitation. For an associative memory framework, they should be built in a way as to enable the network to reproduce a robust spatio-temporal trajectory in response to an external stimulus. Still, how these rules may be implemented in recurrent networks and the way they relate to their capacity of pattern recognition remains unclear. We studied the effects of three phenomenological unsupervised rules in sparsely connected recurrent networks for associative memory: spike-timing-dependent-plasticity, short-term-plasticity and an homeostatic scaling. The system stability is monitored during the learning process of the network, as the mean firing rate converges to a value determined by the homeostatic scaling. Afterwards, it is possible to measure the recovery efficiency of the activity following each initial stimulus. This is evaluated by a measure of the correlation between spike fire timings, and we analysed the full memory separation capacity and limitations of this system.
Tessadori, Jacopo; Ghirardi, Mirella
2015-01-01
Brain functions are strictly dependent on neural connections formed during development and modified during life. The cellular and molecular mechanisms underlying synaptogenesis and plastic changes involved in learning and memory have been analyzed in detail in simple animals such as invertebrates and in circuits of mammalian brains mainly by intracellular recordings of neuronal activity. In the last decades, the evolution of techniques such as microelectrode arrays (MEAs) that allow simultaneous, long-lasting, noninvasive, extracellular recordings from a large number of neurons has proven very useful to study long-term processes in neuronal networks in vivo and in vitro. In this work, we start off by briefly reviewing the microelectrode array technology and the optimization of the coupling between neurons and microtransducers to detect subthreshold synaptic signals. Then, we report MEA studies of circuit formation and activity in invertebrate models such as Lymnaea, Aplysia, and Helix. In the following sections, we analyze plasticity and connectivity in cultures of mammalian dissociated neurons, focusing on spontaneous activity and electrical stimulation. We conclude by discussing plasticity in closed-loop experiments. PMID:25866681
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.
Lange, Maren D; Jüngling, Kay; Paulukat, Linda; Vieler, Marc; Gaburro, Stefano; Sosulina, Ludmila; Blaesse, Peter; Sreepathi, Hari K; Ferraguti, Francesco; Pape, Hans-Christian
2014-08-01
An imbalance of the gamma-aminobutyric acid (GABA) system is considered a major neurobiological pathomechanism of anxiety, and the amygdala is a key brain region involved. Reduced GABA levels have been found in anxiety patients, and genetic variations of glutamic acid decarboxylase (GAD), the rate-limiting enzyme of GABA synthesis, have been associated with anxiety phenotypes in both humans and mice. These findings prompted us to hypothesize that a deficiency of GAD65, the GAD isoform controlling the availability of GABA as a transmitter, affects synaptic transmission and plasticity in the lateral amygdala (LA), and thereby interferes with fear responsiveness. Results indicate that genetically determined GAD65 deficiency in mice is associated with (1) increased synaptic length and release at GABAergic connections, (2) impaired efficacy of GABAergic synaptic transmission and plasticity, and (3) reduced spillover of GABA to presynaptic GABAB receptors, resulting in a loss of the associative nature of long-term synaptic plasticity at cortical inputs to LA principal neurons. (4) In addition, training with high shock intensities in wild-type mice mimicked the phenotype of GAD65 deficiency at both the behavioral and synaptic level, indicated by generalization of conditioned fear and a loss of the associative nature of synaptic plasticity in the LA. In conclusion, GAD65 is required for efficient GABAergic synaptic transmission and plasticity, and for maintaining extracellular GABA at a level needed for associative plasticity at cortical inputs in the LA, which, if disturbed, results in an impairment of the cue specificity of conditioned fear responses typifying anxiety disorders.
Lange, Maren D; Jüngling, Kay; Paulukat, Linda; Vieler, Marc; Gaburro, Stefano; Sosulina, Ludmila; Blaesse, Peter; Sreepathi, Hari K; Ferraguti, Francesco; Pape, Hans-Christian
2014-01-01
An imbalance of the gamma-aminobutyric acid (GABA) system is considered a major neurobiological pathomechanism of anxiety, and the amygdala is a key brain region involved. Reduced GABA levels have been found in anxiety patients, and genetic variations of glutamic acid decarboxylase (GAD), the rate-limiting enzyme of GABA synthesis, have been associated with anxiety phenotypes in both humans and mice. These findings prompted us to hypothesize that a deficiency of GAD65, the GAD isoform controlling the availability of GABA as a transmitter, affects synaptic transmission and plasticity in the lateral amygdala (LA), and thereby interferes with fear responsiveness. Results indicate that genetically determined GAD65 deficiency in mice is associated with (1) increased synaptic length and release at GABAergic connections, (2) impaired efficacy of GABAergic synaptic transmission and plasticity, and (3) reduced spillover of GABA to presynaptic GABAB receptors, resulting in a loss of the associative nature of long-term synaptic plasticity at cortical inputs to LA principal neurons. (4) In addition, training with high shock intensities in wild-type mice mimicked the phenotype of GAD65 deficiency at both the behavioral and synaptic level, indicated by generalization of conditioned fear and a loss of the associative nature of synaptic plasticity in the LA. In conclusion, GAD65 is required for efficient GABAergic synaptic transmission and plasticity, and for maintaining extracellular GABA at a level needed for associative plasticity at cortical inputs in the LA, which, if disturbed, results in an impairment of the cue specificity of conditioned fear responses typifying anxiety disorders. PMID:24663011
Bichler, Olivier; Querlioz, Damien; Thorpe, Simon J; Bourgoin, Jean-Philippe; Gamrat, Christian
2012-08-01
A biologically inspired approach to learning temporally correlated patterns from a spiking silicon retina is presented. Spikes are generated from the retina in response to relative changes in illumination at the pixel level and transmitted to a feed-forward spiking neural network. Neurons become sensitive to patterns of pixels with correlated activation times, in a fully unsupervised scheme. This is achieved using a special form of Spike-Timing-Dependent Plasticity which depresses synapses that did not recently contribute to the post-synaptic spike activation, regardless of their activation time. Competitive learning is implemented with lateral inhibition. When tested with real-life data, the system is able to extract complex and overlapping temporally correlated features such as car trajectories on a freeway, after only 10 min of traffic learning. Complete trajectories can be learned with a 98% detection rate using a second layer, still with unsupervised learning, and the system may be used as a car counter. The proposed neural network is extremely robust to noise and it can tolerate a high degree of synaptic and neuronal variability with little impact on performance. Such results show that a simple biologically inspired unsupervised learning scheme is capable of generating selectivity to complex meaningful events on the basis of relatively little sensory experience. Copyright © 2012 Elsevier Ltd. All rights reserved.
Bonansco, Christian; Fuenzalida, Marco
2016-01-01
Synaptic plasticity is the capacity generated by experience to modify the neural function and, thereby, adapt our behaviour. Long-term plasticity of glutamatergic and GABAergic transmission occurs in a concerted manner, finely adjusting the excitatory-inhibitory (E/I) balance. Imbalances of E/I function are related to several neurological diseases including epilepsy. Several evidences have demonstrated that astrocytes are able to control the synaptic plasticity, with astrocytes being active partners in synaptic physiology and E/I balance. Here, we revise molecular evidences showing the epileptic stage as an abnormal form of long-term brain plasticity and propose the possible participation of astrocytes to the abnormal increase of glutamatergic and decrease of GABAergic neurotransmission in epileptic networks.
Bonansco, Christian; Fuenzalida, Marco
2016-01-01
Synaptic plasticity is the capacity generated by experience to modify the neural function and, thereby, adapt our behaviour. Long-term plasticity of glutamatergic and GABAergic transmission occurs in a concerted manner, finely adjusting the excitatory-inhibitory (E/I) balance. Imbalances of E/I function are related to several neurological diseases including epilepsy. Several evidences have demonstrated that astrocytes are able to control the synaptic plasticity, with astrocytes being active partners in synaptic physiology and E/I balance. Here, we revise molecular evidences showing the epileptic stage as an abnormal form of long-term brain plasticity and propose the possible participation of astrocytes to the abnormal increase of glutamatergic and decrease of GABAergic neurotransmission in epileptic networks. PMID:27006834
Cerebellar supervised learning revisited: biophysical modeling and degrees-of-freedom control.
Kawato, Mitsuo; Kuroda, Shinya; Schweighofer, Nicolas
2011-10-01
The biophysical models of spike-timing-dependent plasticity have explored dynamics with molecular basis for such computational concepts as coincidence detection, synaptic eligibility trace, and Hebbian learning. They overall support different learning algorithms in different brain areas, especially supervised learning in the cerebellum. Because a single spine is physically very small, chemical reactions at it are essentially stochastic, and thus sensitivity-longevity dilemma exists in the synaptic memory. Here, the cascade of excitable and bistable dynamics is proposed to overcome this difficulty. All kinds of learning algorithms in different brain regions confront with difficult generalization problems. For resolution of this issue, the control of the degrees-of-freedom can be realized by changing synchronicity of neural firing. Especially, for cerebellar supervised learning, the triangle closed-loop circuit consisting of Purkinje cells, the inferior olive nucleus, and the cerebellar nucleus is proposed as a circuit to optimally control synchronous firing and degrees-of-freedom in learning. Copyright © 2011 Elsevier Ltd. All rights reserved.
Lithium rescues synaptic plasticity and memory in Down syndrome mice
Contestabile, Andrea; Greco, Barbara; Ghezzi, Diego; Tucci, Valter; Benfenati, Fabio; Gasparini, Laura
2012-01-01
Down syndrome (DS) patients exhibit abnormalities of hippocampal-dependent explicit memory, a feature that is replicated in relevant mouse models of the disease. Adult hippocampal neurogenesis, which is impaired in DS and other neuropsychiatric diseases, plays a key role in hippocampal circuit plasticity and has been implicated in learning and memory. However, it remains unknown whether increasing adult neurogenesis improves hippocampal plasticity and behavioral performance in the multifactorial context of DS. We report that, in the Ts65Dn mouse model of DS, chronic administration of lithium, a clinically used mood stabilizer, promoted the proliferation of neuronal precursor cells through the pharmacological activation of the Wnt/β-catenin pathway and restored adult neurogenesis in the hippocampal dentate gyrus (DG) to physiological levels. The restoration of adult neurogenesis completely rescued the synaptic plasticity of newborn neurons in the DG and led to the full recovery of behavioral performance in fear conditioning, object location, and novel object recognition tests. These findings indicate that reestablishing a functional population of hippocampal newborn neurons in adult DS mice rescues hippocampal plasticity and memory and implicate adult neurogenesis as a promising therapeutic target to alleviate cognitive deficits in DS patients. PMID:23202733
Liu, Yong; Yang, Ying; Dong, Hui; Cutler, Roy G; Strong, Randy; Mattson, Mark P
2016-01-01
A high calorie diet (HCD) can impair hippocampal synaptic plasticity and cognitive function in animal models. Mitochondrial thioredoxin 2 (TRX-2) is critical for maintaining intracellular redox status, but whether it can protect against HCD-induced impairment of synaptic plasticity is unknown. We found that levels of TRX-2 are reduced in the hippocampus of wild type mice maintained for 8 months on a HCD, and that the mice on the HCD exhibit impaired hippocampal synaptic plasticity (long-term potentiation at CA1 synapses) and cognitive function (novel object recognition). Transgenic mice overexpressing human TRX-2 (hTRX-2) exhibit increased resistance to diquat-induced oxidative stress in peripheral tissues. However, neither the HCD nor hTRX-2 overexpression affected levels of lipid peroxidation products (F2 isoprostanes) in the hippocampus, and hTRX-2 transgenic mice were not protected against the adverse effects of the HCD on hippocampal synaptic plasticity and cognitive function. Our findings indicate that TRX-2 overexpression does not mitigate adverse effects of a HCD on synaptic plasticity, and also suggest that oxidative stress may not be a pivotal factor in the impairment of synaptic plasticity and cognitive function caused by HCDs. Published by Elsevier Inc.
Although severe developmental hypothyroidism leads to stunted growth, alterations in hippocampal structure, and impaired performance on a variety of behavioral learning tasks, the impact of milder forms of hypothyroidism has not been adequately assessed. Preliminary reports of ...
Separate Functional Properties of NMDARs Regulate Distinct Aspects of Spatial Cognition
ERIC Educational Resources Information Center
Sanders, Erin M.; Nyarko-Odoom, Akua O.; Zhao, Kevin; Nguyen, Michael; Liao, Hong Hong Liao; Keith, Matthew; Pyon, Jane; Kozma, Alyssa; Sanyal, Mohima; McHail, Daniel G.; Dumas, Theodore C.
2018-01-01
N-methyl-D-aspartate receptors (NMDARs) at excitatory synapses are central to activity-dependent synaptic plasticity and learning and memory. NMDARs act as ionotropic and metabotropic receptors by elevating postsynaptic calcium concentrations and by direct intracellular protein signaling. In the forebrain, these properties are controlled largely…
Nicotinic modulation of hippocampal cell signaling and associated effects on learning and memory.
Kutlu, Munir Gunes; Gould, Thomas J
2016-03-01
The hippocampus is a key brain structure involved in synaptic plasticity associated with long-term declarative memory formation. Importantly, nicotine and activation of nicotinic acetylcholine receptors (nAChRs) can alter hippocampal plasticity and these changes may occur through modulation of hippocampal kinases and transcription factors. Hippocampal kinases such as cAMP-dependent protein kinase (PKA), calcium/calmodulin-dependent protein kinases (CAMKs), extracellular signal-regulated kinases 1 and 2 (ERK1/2), and c-jun N-terminal kinase 1 (JNK1), and the transcription factor cAMP-response element-binding protein (CREB) that are activated either directly or indirectly by nicotine may modulate hippocampal plasticity and in parallel hippocampus-dependent learning and memory. Evidence suggests that nicotine may alter hippocampus-dependent learning by changing the time and magnitude of activation of kinases and transcription factors normally involved in learning and by recruiting additional cell signaling molecules. Understanding how nicotine alters learning and memory will advance basic understanding of the neural substrates of learning and aid in understanding mental disorders that involve cognitive and learning deficits. Copyright © 2015 Elsevier Inc. All rights reserved.
Endocannabinoid signaling and memory dynamics: A synaptic perspective.
Drumond, Ana; Madeira, Natália; Fonseca, Rosalina
2017-02-01
Memory acquisition is a key brain feature in which our human nature relies on. Memories evolve over time. Initially after learning, memories are labile and sensitive to disruption by the interference of concurrent events. Later on, after consolidation, memories are resistant to disruption. However, reactivation of previously consolidated memories renders them again in an unstable state and therefore susceptible to perturbation. Additionally, and depending on the characteristics of the stimuli, a parallel process may be initiated which ultimately leads to the extinction of the previously acquired response. This dynamic aspect of memory maintenance opens the possibility for an updating of previously acquired memories but it also creates several conceptual challenges. What is the time window for memory updating? What determines whether reconsolidation or extinction is triggered? In this review, we tried to re-examine the relationship between consolidation, reconsolidation and extinction, aiming for a unifying view of memory dynamics. Since cellular models of memory share common principles, we present the evidence that similar rules apply to the maintenance of synaptic plasticity. Recently, a new function of the endocannabinoid (eCB) signaling system has been described for associative forms of synaptic plasticity in amygdala synapses. The eCB system has emerged as a key modulator of memory dynamics by adjusting the outcome to stimuli intensity. We propose a key function of eCB in discriminative forms of learning by restricting associative plasticity in amygdala synapses. Since many neuropsychiatric disorders are associated with a dysregulation in memory dynamics, understanding the rules underlying memory maintenance paves the path to better clinical interventions. Copyright © 2016 Elsevier Inc. All rights reserved.
Nitric Oxide Is an Activity-Dependent Regulator of Target Neuron Intrinsic Excitability
Steinert, Joern R.; Robinson, Susan W.; Tong, Huaxia; Haustein, Martin D.; Kopp-Scheinpflug, Cornelia; Forsythe, Ian D.
2011-01-01
Summary Activity-dependent changes in synaptic strength are well established as mediating long-term plasticity underlying learning and memory, but modulation of target neuron excitability could complement changes in synaptic strength and regulate network activity. It is thought that homeostatic mechanisms match intrinsic excitability to the incoming synaptic drive, but evidence for involvement of voltage-gated conductances is sparse. Here, we show that glutamatergic synaptic activity modulates target neuron excitability and switches the basis of action potential repolarization from Kv3 to Kv2 potassium channel dominance, thereby adjusting neuronal signaling between low and high activity states, respectively. This nitric oxide-mediated signaling dramatically increases Kv2 currents in both the auditory brain stem and hippocampus (>3-fold) transforming synaptic integration and information transmission but with only modest changes in action potential waveform. We conclude that nitric oxide is a homeostatic regulator, tuning neuronal excitability to the recent history of excitatory synaptic inputs over intervals of minutes to hours. PMID:21791288
Synchrony detection and amplification by silicon neurons with STDP synapses.
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.
Ahmad Ganai, Shabir; Ramadoss, Mahalakshmi; Mahadevan, Vijayalakshmi
2016-01-01
Epigenetic regulation of neuronal signalling through histone acetylation dictates transcription programs that govern neuronal memory, plasticity and learning paradigms. Histone Acetyl Transferases (HATs) and Histone Deacetylases (HDACs) are antagonistic enzymes that regulate gene expression through acetylation and deacetylation of histone proteins around which DNA is wrapped inside a eukaryotic cell nucleus. The epigenetic control of HDACs and the cellular imbalance between HATs and HDACs dictate disease states and have been implicated in muscular dystrophy, loss of memory, neurodegeneration and autistic disorders. Altering gene expression profiles through inhibition of HDACs is now emerging as a powerful technique in therapy. This review presents evolving applications of HDAC inhibitors as potential drugs in neurological research and therapy. Mechanisms that govern their expression profiles in neuronal signalling, plasticity and learning will be covered. Promising and exciting possibilities of HDAC inhibitors in memory formation, fear conditioning, ischemic stroke and neural regeneration have been detailed. PMID:26487502
Ganai, Shabir Ahmad; Ramadoss, Mahalakshmi; Mahadevan, Vijayalakshmi
2016-01-01
Epigenetic regulation of neuronal signalling through histone acetylation dictates transcription programs that govern neuronal memory, plasticity and learning paradigms. Histone Acetyl Transferases (HATs) and Histone Deacetylases (HDACs) are antagonistic enzymes that regulate gene expression through acetylation and deacetylation of histone proteins around which DNA is wrapped inside a eukaryotic cell nucleus. The epigenetic control of HDACs and the cellular imbalance between HATs and HDACs dictate disease states and have been implicated in muscular dystrophy, loss of memory, neurodegeneration and autistic disorders. Altering gene expression profiles through inhibition of HDACs is now emerging as a powerful technique in therapy. This review presents evolving applications of HDAC inhibitors as potential drugs in neurological research and therapy. Mechanisms that govern their expression profiles in neuronal signalling, plasticity and learning will be covered. Promising and exciting possibilities of HDAC inhibitors in memory formation, fear conditioning, ischemic stroke and neural regeneration have been detailed.
A Model of In vitro Plasticity at the Parallel Fiber—Molecular Layer Interneuron Synapses
Lennon, William; Yamazaki, Tadashi; Hecht-Nielsen, Robert
2015-01-01
Theoretical and computational models of the cerebellum typically focus on the role of parallel fiber (PF)—Purkinje cell (PKJ) synapses for learned behavior, but few emphasize the role of the molecular layer interneurons (MLIs)—the stellate and basket cells. A number of recent experimental results suggest the role of MLIs is more important than previous models put forth. We investigate learning at PF—MLI synapses and propose a mathematical model to describe plasticity at this synapse. We perform computer simulations with this form of learning using a spiking neuron model of the MLI and show that it reproduces six in vitro experimental results in addition to simulating four novel protocols. Further, we show how this plasticity model can predict the results of other experimental protocols that are not simulated. Finally, we hypothesize what the biological mechanisms are for changes in synaptic efficacy that embody the phenomenological model proposed here. PMID:26733856
H2-K(b) and H2-D(b) regulate cerebellar long-term depression and limit motor learning.
McConnell, Michael J; Huang, Yanhua H; Datwani, Akash; Shatz, Carla J
2009-04-21
There are more than 50 class I MHC (MHCI) molecules in the mouse genome, some of which are now known to be expressed in neurons; however, the role of classical MHCI molecules in synaptic plasticity is unknown. We report that the classical MHCI molecules, H2-K(b) and H2-D(b), are co-expressed by Purkinje cells (PCs). In the cerebellum of mice deficient for both H2-K(b) and H2-D(b) (K(b)D(b-/-)), there is a lower threshold for induction of long-term depression (LTD) at parallel fiber to PC synapses. This change may be a result of additional glutamate release observed at K(b)D(b-/-) CF to PC synapses, which are thought to "train" the cerebellar circuit. A behavioral correlate of cerebellar LTD is motor learning; acquisition and retention of a Rotarod behavioral task is significantly better in K(b)D(b-/-) mice than in WT cohorts. These physiological and behavioral phenotypes in K(b)D(b-/-) mice reveal a surprising role for classical MHCI molecules in synaptic plasticity and motor learning.
Balschun, Detlef; Moechars, Diederik; Callaerts-Vegh, Zsuzsanna; Vermaercke, Ben; Van Acker, Nathalie; Andries, Luc; D'Hooge, Rudi
2010-03-01
Vesicular glutamate transporters 1 and 2 (VGLUT1, VGLUT2) show largely complementary distribution in the mature rodent brain and tend to segregate to synapses with different physiological properties. In the hippocampus, VGLUT1 is the dominate subtype in adult animals, whereas VGLUT2 is transiently expressed during early postnatal development. We generated and characterized VGLUT1 knockout mice in order to examine the functional contribution of this transporter to hippocampal synaptic plasticity and hippocampus-dependent spatial learning. Because complete deletion of VGLUT1 resulted in postnatal lethality, we used heterozygous animals for analysis. Here, we report that deletion of VGLUT1 resulted in impaired hippocampal long-term potentiation (LTP) in the CA1 region in vitro. In contrast, heterozygous VGLUT2 mice that were investigated for comparison did not show any changes in LTP. The reduced ability of VGLUT1-deficient mice to express LTP was accompanied by a specific deficit in spatial reversal learning in the water maze. Our data suggest a functional role of VGLUT1 in forms of hippocampal synaptic plasticity that are required to adapt and modify acquired spatial maps to external stimuli and changes.
Astrocytic Activation Generates De Novo Neuronal Potentiation and Memory Enhancement.
Adamsky, Adar; Kol, Adi; Kreisel, Tirzah; Doron, Adi; Ozeri-Engelhard, Nofar; Melcer, Talia; Refaeli, Ron; Horn, Henrike; Regev, Limor; Groysman, Maya; London, Michael; Goshen, Inbal
2018-05-18
Astrocytes respond to neuronal activity and were shown to be necessary for plasticity and memory. To test whether astrocytic activity is also sufficient to generate synaptic potentiation and enhance memory, we expressed the Gq-coupled receptor hM3Dq in CA1 astrocytes, allowing their activation by a designer drug. We discovered that astrocytic activation is not only necessary for synaptic plasticity, but also sufficient to induce NMDA-dependent de novo long-term potentiation in the hippocampus that persisted after astrocytic activation ceased. In vivo, astrocytic activation enhanced memory allocation; i.e., it increased neuronal activity in a task-specific way only when coupled with learning, but not in home-caged mice. Furthermore, astrocytic activation using either a chemogenetic or an optogenetic tool during acquisition resulted in memory recall enhancement on the following day. Conversely, directly increasing neuronal activity resulted in dramatic memory impairment. Our findings that astrocytes induce plasticity and enhance memory may have important clinical implications for cognitive augmentation treatments. Copyright © 2018 Elsevier Inc. All rights reserved.
Learning place cells, grid cells and invariances with excitatory and inhibitory plasticity
2018-01-01
Neurons in the hippocampus and adjacent brain areas show a large diversity in their tuning to location and head direction, and the underlying circuit mechanisms are not yet resolved. In particular, it is unclear why certain cell types are selective to one spatial variable, but invariant to another. For example, place cells are typically invariant to head direction. We propose that all observed spatial tuning patterns – in both their selectivity and their invariance – arise from the same mechanism: Excitatory and inhibitory synaptic plasticity driven by the spatial tuning statistics of synaptic inputs. Using simulations and a mathematical analysis, we show that combined excitatory and inhibitory plasticity can lead to localized, grid-like or invariant activity. Combinations of different input statistics along different spatial dimensions reproduce all major spatial tuning patterns observed in rodents. Our proposed model is robust to changes in parameters, develops patterns on behavioral timescales and makes distinctive experimental predictions. PMID:29465399
Prince, Toni-Moi; Wimmer, Mathieu; Choi, Jennifer; Havekes, Robbert; Aton, Sara; Abel, Ted
2014-01-01
Sleep deprivation disrupts hippocampal function and plasticity. In particular, long-term memory consolidation is impaired by sleep deprivation, suggesting that a specific critical period exists following learning during which sleep is necessary. To elucidate the impact of sleep deprivation on long-term memory consolidation and synaptic plasticity, long-term memory was assessed when mice were sleep deprived following training in the hippocampus-dependent object place recognition task. We found that 3 hours of sleep deprivation significantly impaired memory when deprivation began 1 hour after training. In contrast, 3 hours of deprivation beginning immediately post-training did not impair spatial memory. Furthermore, a 3-hour sleep deprivation beginning 1 hour after training impaired hippocampal long-term potentiation (LTP), whereas sleep deprivation immediately after training did not affect LTP. Together, our findings define a specific 3-hour critical period, extending from 1 to 4 hours after training, during which sleep deprivation impairs hippocampal function. PMID:24380868
Transmission, Development, and Plasticity of Synapses
Harris, Kathryn P.
2015-01-01
Chemical synapses are sites of contact and information transfer between a neuron and its partner cell. Each synapse is a specialized junction, where the presynaptic cell assembles machinery for the release of neurotransmitter, and the postsynaptic cell assembles components to receive and integrate this signal. Synapses also exhibit plasticity, during which synaptic function and/or structure are modified in response to activity. With a robust panel of genetic, imaging, and electrophysiology approaches, and strong evolutionary conservation of molecular components, Drosophila has emerged as an essential model system for investigating the mechanisms underlying synaptic assembly, function, and plasticity. We will discuss techniques for studying synapses in Drosophila, with a focus on the larval neuromuscular junction (NMJ), a well-established model glutamatergic synapse. Vesicle fusion, which underlies synaptic release of neurotransmitters, has been well characterized at this synapse. In addition, studies of synaptic assembly and organization of active zones and postsynaptic densities have revealed pathways that coordinate those events across the synaptic cleft. We will also review modes of synaptic growth and plasticity at the fly NMJ, and discuss how pre- and postsynaptic cells communicate to regulate plasticity in response to activity. PMID:26447126
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…
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.
Fortress, Ashley M; Smith, Ian M; Pang, Kevin C H
2018-05-08
Anxiety disorders and posttraumatic stress disorder (PTSD) share a common feature of pathological avoidance behavior. The Wistar Kyoto (WKY) rat has been used as a model of anxiety vulnerability, expressing a behaviorally inhibited temperament, acquiring avoidance behavior more rapidly and displaying extinction-resistant avoidance compared to Sprague Dawley (SD) rats. Subanesthetic levels of ketamine have gained attention as a rapid antidepressant in treatment-resistant depression. While traditional antidepressants are commonly used to treat anxiety disorders and PTSD, the therapeutic utility of ketamine for these disorders is much less understood. The hippocampus is critical for the actions of antidepressants, is a structure of implicated in anxiety disorders and PTSD, and is necessary for extinction of avoidance in SD rats. WKY rats have impaired hippocampal long-term potentiation (LTP), suggesting that persistent avoidance in WKY rats may be due to deficient hippocampal synaptic plasticity. In the present study, we hypothesized that ketamine would facilitate extinction of avoidance learning in WKY rats, and do so by enhancing hippocampal synaptic plasticity. As predicted, ketamine facilitated extinction of avoidance behavior in a subset of WKY rats (responders), with effects lasting at least three weeks. Additionally, LTP in these rats was enhanced by ketamine. Ketamine was not effective in facilitating avoidance extinction or in modifying LTP in WKY non-responders. The results suggest that subanesthetic levels of ketamine may be useful for treating anxiety disorders by reducing avoidance behaviors when combined with extinction conditions. Moreover, ketamine may have its long-lasting behavioral effects through enhancing hippocampal synaptic plasticity. Copyright © 2018. Published by Elsevier Ltd.
Anglada-Huguet, Marta; Vidal-Sancho, Laura; Giralt, Albert; García-Díaz Barriga, Gerardo; Xifró, Xavier; Alberch, Jordi
2016-11-01
Huntington's disease (HD) patients and mouse models show learning and memory impairment even before the onset of motor symptoms. Deficits in hippocampal synaptic plasticity have been involved in the HD memory impairment. Several studies show that prostaglandin E2 (PGE2) EP2 receptor stimulates synaptic plasticity and memory formation. However, this role was not explored in neurodegenerative diseases. Here, we investigated the capacity of PGE2 EP2 receptor to promote synaptic plasticity and memory improvements in a model of HD, the R6/1 mice, by administration of the agonist misoprostol. We found that misoprostol increases dendritic branching in cultured hippocampal neurons in a brain-derived neurotrophic factor (BDNF)-dependent manner. Then, we implanted an osmotic mini-pump system to chronically administrate misoprostol to R6/1 mice from 14 to 18weeks of age. We observed that misoprostol treatment ameliorates the R6/1 long-term memory deficits as analyzed by the T-maze spontaneous alternation task and the novel object recognition test. Importantly, administration of misoprostol promoted the expression of hippocampal BDNF. Moreover, the treatment with misoprostol in R6/1 mice blocked the reduction in the number of PSD-95 and VGluT-1 positive particles observed in hippocampus of vehicle-R6/1 mice. In addition, we observed an increase of cAMP levels in the dentate ` of WT and R6/1 mice treated with misoprostol. Accordingly, we showed a reduction in the number of mutant huntingtin nuclear inclusions in the dentate gyrus of R6/1 mice. Altogether, these results suggest a putative therapeutic effect of PGE2 EP2 receptor in reducing cognitive deficits in HD. Copyright © 2016. Published by Elsevier Inc.
Reelin protects against amyloid β toxicity in vivo
Lane-Donovan, Courtney; Philips, Gary T.; Wasser, Catherine R.; Durakoglugil, Murat S.; Masiulis, Irene; Upadhaya, Ajeet; Pohlkamp, Theresa; Coskun, Cagil; Kotti, Tiina; Steller, Laura; Hammer, Robert E.; Frotscher, Michael; Bock, Hans H.; Herz, Joachim
2015-01-01
Alzheimer's disease (AD) is a currently incurable neurodegenerative disorder and the most common form of dementia in people over the age of 65. The predominant genetic risk factor for AD is the ε4 allele encoding apolipoprotein E (ApoE4). The secreted glycoprotein Reelin, which is a physiological ligand for the multifunctional ApoE receptors Apolipoprotein E receptor 2 (Apoer2) and very low-density lipoprotein receptor (Vldlr), enhances synaptic plasticity. We have previously shown that the presence of ApoE4 renders neurons unresponsive to Reelin by impairing the recycling of the receptors, thereby decreasing its protective effects against amyloid β (Aβ) oligomer-induced synaptic toxicity in vitro. Here, we show that when Reelin was knocked out in adult mice, these mice behaved normally without overt learning or memory deficits. However, they were strikingly sensitive to amyloid-induced synaptic suppression, and had profound memory and learning disabilities at very low amounts of amyloid deposition. Our findings highlight the physiological importance of Reelin in protecting the brain against Aβ-induced synaptic dysfunction and memory impairment. PMID:26152694
Synaptic tagging, evaluation of memories, and the distal reward problem.
Päpper, Marc; Kempter, Richard; Leibold, Christian
2011-01-01
Long-term synaptic plasticity exhibits distinct phases. The synaptic tagging hypothesis suggests an early phase in which synapses are prepared, or "tagged," for protein capture, and a late phase in which those proteins are integrated into the synapses to achieve memory consolidation. The synapse specificity of the tags is consistent with conventional neural network models of associative memory. Memory consolidation through protein synthesis, however, is neuron specific, and its functional role in those models has not been assessed. Here, using a theoretical network model, we test the tagging hypothesis on its potential to prolong memory lifetimes in an online-learning paradigm. We find that protein synthesis, though not synapse specific, prolongs memory lifetimes if it is used to evaluate memory items on a cellular level. In our model we assume that only "important" memory items evoke protein synthesis such that these become more stable than "unimportant" items, which do not evoke protein synthesis. The network model comprises an equilibrium distribution of synaptic states that is very susceptible to the storage of new items: Most synapses are in a state in which they are plastic and can be changed easily, whereas only those synapses that are essential for the retrieval of the important memory items are in the stable late phase. The model can solve the distal reward problem, where the initial exposure of a memory item and its evaluation are temporally separated. Synaptic tagging hence provides a viable mechanism to consolidate and evaluate memories on a synaptic basis.
Statistical theory of synaptic connectivity in the neocortex
NASA Astrophysics Data System (ADS)
Escobar, Gina
Learning and long-term memory rely on plasticity of neural circuits. In adult cerebral cortex plasticity can be mediated by modulation of existing synapses and structural reorganization of circuits through growth and retraction of dendritic spines. In the first part of this thesis, we describe a theoretical framework for the analysis of spine remodeling plasticity. New synaptic contacts appear in the neuropil where gaps between axonal and dendritic branches can be bridged by dendritic spines. Such sites are termed potential synapses. We derive expressions for the densities of potential synapses in the neuropil. We calculate the ratio of actual to potential synapses, called the connectivity fraction, and use it to find the number of structurally different circuits attainable with spine remodeling. These parameters are calculated in four systems: mouse occipital cortex, rat hippocampal area CA1, monkey primary visual (V1), and human temporal cortex. The neurogeometric results indicate that a dendritic spine can choose among an average of 4-7 potential targets in rodents, while in primates it can choose from 10-20 potential targets. The potential of the neuropil to undergo circuit remodeling is found to be highest in rat CA1 (4.9-6.0 nats/mum 3) and lowest in monkey V1 (0.9-1.0 nats/mum3). We evaluate the lower bound of neuron selectivity in the choice of synaptic partners and find that post-synaptic excitatory neurons in rodents make synaptic contacts with more than 21-30% of pre-synaptic axons encountered with new spine growth. Primate neurons appear to be more selective, making synaptic connections with more than 7-15% of encountered axons. Another plasticity mechanism is included in the second part of this work: long-term potentiation and depression of excitatory synaptic connections. Because synaptic strength is correlated with the size of the synapse, the former can be inferred from the distribution of spine head volumes. To this end we analyze and compare 166 distributions of spine head volumes and spine lengths from mouse, rat, monkey, and human brains. We develope a statistical theory in which the equilibrium distribution of dendritic spine shapes is governed by the principle of synaptic entropy maximization under a "generalized cost" constraint. We find the generalized cost of dendritic spines and show that it universally depends on the spine shape, i.e. the dependence is the same in all the considered systems. We show that the modulatory and structural plasticity mechanisms in adults are in a statistical equilibrium with each other, the numbers of dendritic spines in different cortical areas are nearly optimally chosen for memory storage, and the distribution of spine shapes is governed by a single parameter -- the effective temperature. Our results suggest that the effective temperature of a cortical area may be viewed as a measure of longevity of stored memories. Finally, we test the hypothesis that the number of spines in the neuropil is chosen to optimize its storage information capacity.
Mean-field theory of a plastic network of integrate-and-fire neurons.
Chen, Chun-Chung; Jasnow, David
2010-01-01
We consider a noise-driven network of integrate-and-fire neurons. The network evolves as result of the activities of the neurons following spike-timing-dependent plasticity rules. We apply a self-consistent mean-field theory to the system to obtain the mean activity level for the system as a function of the mean synaptic weight, which predicts a first-order transition and hysteresis between a noise-dominated regime and a regime of persistent neural activity. Assuming Poisson firing statistics for the neurons, the plasticity dynamics of a synapse under the influence of the mean-field environment can be mapped to the dynamics of an asymmetric random walk in synaptic-weight space. Using a master equation for small steps, we predict a narrow distribution of synaptic weights that scales with the square root of the plasticity rate for the stationary state of the system given plausible physiological parameter values describing neural transmission and plasticity. The dependence of the distribution on the synaptic weight of the mean-field environment allows us to determine the mean synaptic weight self-consistently. The effect of fluctuations in the total synaptic conductance and plasticity step sizes are also considered. Such fluctuations result in a smoothing of the first-order transition for low number of afferent synapses per neuron and a broadening of the synaptic-weight distribution, respectively.
Experience-Dependent Induction of Hippocampal ΔFosB Controls Learning.
Eagle, Andrew L; Gajewski, Paula A; Yang, Miyoung; Kechner, Megan E; Al Masraf, Basma S; Kennedy, Pamela J; Wang, Hongbing; Mazei-Robison, Michelle S; Robison, Alfred J
2015-10-07
The hippocampus (HPC) is known to play an important role in learning, a process dependent on synaptic plasticity; however, the molecular mechanisms underlying this are poorly understood. ΔFosB is a transcription factor that is induced throughout the brain by chronic exposure to drugs, stress, and variety of other stimuli and regulates synaptic plasticity and behavior in other brain regions, including the nucleus accumbens. We show here that ΔFosB is also induced in HPC CA1 and DG subfields by spatial learning and novel environmental exposure. The goal of the current study was to examine the role of ΔFosB in hippocampal-dependent learning and memory and the structural plasticity of HPC synapses. Using viral-mediated gene transfer to silence ΔFosB transcriptional activity by expressing ΔJunD (a negative modulator of ΔFosB transcriptional function) or to overexpress ΔFosB, we demonstrate that HPC ΔFosB regulates learning and memory. Specifically, ΔJunD expression in HPC impaired learning and memory on a battery of hippocampal-dependent tasks in mice. Similarly, general ΔFosB overexpression also impaired learning. ΔJunD expression in HPC did not affect anxiety or natural reward, but ΔFosB overexpression induced anxiogenic behaviors, suggesting that ΔFosB may mediate attentional gating in addition to learning. Finally, we found that overexpression of ΔFosB increases immature dendritic spines on CA1 pyramidal cells, whereas ΔJunD reduced the number of immature and mature spine types, indicating that ΔFosB may exert its behavioral effects through modulation of HPC synaptic function. Together, these results suggest collectively that ΔFosB plays a significant role in HPC cellular morphology and HPC-dependent learning and memory. Consolidation of our explicit memories occurs within the hippocampus, and it is in this brain region that the molecular and cellular processes of learning have been most closely studied. We know that connections between hippocampal neurons are formed, eliminated, enhanced, and weakened during learning, and we know that some stages of this process involve alterations in the transcription of specific genes. However, the specific transcription factors involved in this process are not fully understood. Here, we demonstrate that the transcription factor ΔFosB is induced in the hippocampus by learning, regulates the shape of hippocampal synapses, and is required for memory formation, opening up a host of new possibilities for hippocampal transcriptional regulation. Copyright © 2015 the authors 0270-6474/15/3513773-11$15.00/0.
In search of the motor engram: motor map plasticity as a mechanism for encoding motor experience.
Monfils, Marie-H; Plautz, Erik J; Kleim, Jeffrey A
2005-10-01
Motor skill acquisition occurs through modification and organization of muscle synergies into effective movement sequences. The learning process is reflected neurophysiologically as a reorganization of movement representations within the primary motor cortex, suggesting that the motor map is a motor engram. However, the specific neural mechanisms underlying map plasticity are unknown. Here the authors review evidence that 1) motor map topography reflects the capacity for skilled movement, 2) motor skill learning induces reorganization of motor maps in a manner that reflects the kinematics of acquired skilled movement, 3) map plasticity is supported by a reorganization of cortical microcircuitry involving changes in synaptic efficacy, and 4) motor map integrity and topography are influenced by various neurochemical signals that coordinate changes in cortical circuitry to encode motor experience. Finally, the role of motor map plasticity in recovery of motor function after brain damage is discussed.
Neural Protein Synthesis during Aging: Effects on Plasticity and Memory
Schimanski, Lesley A.; Barnes, Carol A.
2010-01-01
During aging, many experience a decline in cognitive function that includes memory loss. The encoding of long-term memories depends on new protein synthesis, and this is also reduced during aging. Thus, it is possible that changes in the regulation of protein synthesis contribute to the memory impairments observed in older animals. Several lines of evidence support this hypothesis. For instance, protein synthesis is required for a longer period following learning to establish long-term memory in aged rodents. Also, under some conditions, synaptic activity or pharmacological activation can induce de novo protein synthesis and lasting changes in synaptic transmission in aged, but not young, rodents; the opposite results can be observed in other conditions. These changes in plasticity likely play a role in manifesting the altered place field properties observed in awake and behaving aged rats. The collective evidence suggests a link between memory loss and the regulation of protein synthesis in senescence. In fact, pharmaceuticals that target the signaling pathways required for induction of protein synthesis have improved memory, synaptic plasticity, and place cell properties in aged animals. We suggest that a better understanding of the mechanisms that lead to different protein expression patterns in the neural circuits that change as a function of age will enable the development of more effective therapeutic treatments for memory loss. PMID:20802800
Ciranna, Lucia; Catania, Maria Vincenza
2014-01-01
Serotonin type 7 receptors (5-HT7) are expressed in several brain areas, regulate brain development, synaptic transmission and plasticity, and therefore are involved in various brain functions such as learning and memory. A number of studies suggest that 5-HT7 receptors could be potential pharmacotherapeutic target for cognitive disorders. Several abnormalities of serotonergic system have been described in patients with autism spectrum disorder (ASD), including abnormal activity of 5-HT transporter, altered blood and brain 5-HT levels, reduced 5-HT synthesis and altered expression of 5-HT receptors in the brain. A specific role for 5-HT7 receptors in ASD has not yet been demonstrated but some evidence implicates their possible involvement. We have recently shown that 5-HT7 receptor activation rescues hippocampal synaptic plasticity in a mouse model of Fragile X Syndrome, a monogenic cause of autism. Several other studies have shown that 5-HT7 receptors modulate behavioral flexibility, exploratory behavior, mood disorders and epilepsy, which include core and co-morbid symptoms of ASD. These findings further suggest an involvement of 5-HT7 receptors in ASD. Here, we review the physiological roles of 5-HT7 receptors and their implications in Fragile X Syndrome and other ASD. PMID:25221471
Treating a novel plasticity defect rescues episodic memory in Fragile X model mice
Wang, Weisheng; Cox, Brittney M.; Jia, Yousheng; Le, Aliza A.; Cox, Conor D.; Jung, Kwang M.; Hou, Bowen; Piomelli, Daniele; Gall, Christine M.; Lynch, Gary
2017-01-01
Episodic memory, a fundamental component of human cognition, is significantly impaired in autism. We report the first evidence for this problem in the Fmr1-knockout (KO) mouse model of Fragile X syndrome and describe potentially treatable underlying causes. The hippocampus is critical for the formation and use of episodes, with semantic (cue identity) information relayed to the structure via the lateral perforant path (LPP). The unusual form of synaptic plasticity expressed by the LPP (lppLTP) was profoundly impaired in Fmr1-KOs relative to wild type mice. Two factors contributed to this defect: i) reduced GluN1 subunit levels in synaptic NMDA receptors and related currents, and ii) impaired retrograde synaptic signaling by the endocannabinoid 2-archadonolglycerol (2-AG). Studies using a novel serial cue paradigm showed that episodic encoding is dependent on both the LPP and the endocannabinoid receptor CB1, and is strikingly impaired in Fmr1-KOs. Enhancing 2-AG signaling rescued both lppLTP and learning in the mutants. Thus, two consequences of the Fragile-X mutation converge on plasticity at one site in hippocampus to prevent encoding of a basic element of cognitive memory. Collectively, the results suggest a clinically plausible approach to treatment. PMID:29133950
Zanca, Roseanna M.; Braren, Stephen H.; Maloney, Brigid; Schrott, Lisa M.; Luine, Victoria N.; Serrano, Peter A.
2015-01-01
Environmental enrichment (EE) housing paradigms have long been shown beneficial for brain function involving neural growth and activity, learning and memory capacity, and for developing stress resiliency. The expression of the α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor subunit GluA2, which is important for synaptic plasticity and memory, is increased with corticosterone (CORT), undermining synaptic plasticity and memory. Thus, we determined the effect of EE and stress on modulating GluA2 expression in Sprague-Dawley male rats. Several markers were evaluated which include: plasma CORT, the glucocorticoid receptor (GR), GluA2, and the atypical protein kinase M zeta (PKMζ). For 1 week standard-(ST) or EE-housed animals were treated with one of the following four conditions: (1) no stress; (2) acute stress (forced swim test, FST; on day 7); (3) chronic restraint stress (6 h/day for 7 days); and (4) chronic + acute stress (restraint stress 6 h/day for 7 days + FST on day 7). Hippocampi were collected on day 7. Our results show that EE animals had reduced time immobile on the FST across all conditions. After chronic + acute stress EE animals showed increased GR levels with no change in synaptic GluA2/PKMζ. ST-housed animals showed the reverse pattern with decreased GR levels and a significant increase in synaptic GluA2/PKMζ. These results suggest that EE produces an adaptive response to chronic stress allowing for increased GR levels, which lowers neuronal excitability reducing GluA2/PKMζ trafficking. We discuss this EE adaptive response to stress as a potential underlying mechanism that is protective for retaining synaptic plasticity and memory function. PMID:26617502
Learning Reward Uncertainty in the Basal Ganglia
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
Arc expression identifies the lateral amygdala fear memory trace
Gouty-Colomer, L A; Hosseini, B; Marcelo, I M; Schreiber, J; Slump, D E; Yamaguchi, S; Houweling, A R; Jaarsma, D; Elgersma, Y; Kushner, S A
2016-01-01
Memories are encoded within sparsely distributed neuronal ensembles. However, the defining cellular properties of neurons within a memory trace remain incompletely understood. Using a fluorescence-based Arc reporter, we were able to visually identify the distinct subset of lateral amygdala (LA) neurons activated during auditory fear conditioning. We found that Arc-expressing neurons have enhanced intrinsic excitability and are preferentially recruited into newly encoded memory traces. Furthermore, synaptic potentiation of thalamic inputs to the LA during fear conditioning is learning-specific, postsynaptically mediated and highly localized to Arc-expressing neurons. Taken together, our findings validate the immediate-early gene Arc as a molecular marker for the LA neuronal ensemble recruited during fear learning. Moreover, these results establish a model of fear memory formation in which intrinsic excitability determines neuronal selection, whereas learning-related encoding is governed by synaptic plasticity. PMID:25802982
Molecular mechanisms of synaptic remodeling in alcoholism
Kyzar, Evan J.; Pandey, Subhash C.
2015-01-01
Alcohol use and alcohol addiction represent dysfunctional brain circuits resulting from neuroadaptive changes during protracted alcohol exposure and its withdrawal. Alcohol exerts a potent effect on synaptic plasticity and dendritic spine formation in specific brain regions, providing a neuroanatomical substrate for the pathophysiology of alcoholism. Epigenetics has recently emerged as a critical regulator of gene expression and synaptic plasticity-related events in the brain. Alcohol exposure and withdrawal induce changes in crucial epigenetic processes in the emotional brain circuitry (amygdala) that may be relevant to the negative affective state defined as the “dark side” of addiction. Here, we review the literature concerning synaptic plasticity and epigenetics, with a particular focus on molecular events related to dendritic remodeling during alcohol abuse and alcoholism. Targeting epigenetic processes that modulate synaptic plasticity may yield novel treatments for alcoholism. PMID:25623036
Molecular mechanisms of synaptic remodeling in alcoholism.
Kyzar, Evan J; Pandey, Subhash C
2015-08-05
Alcohol use and alcohol addiction represent dysfunctional brain circuits resulting from neuroadaptive changes during protracted alcohol exposure and its withdrawal. Alcohol exerts a potent effect on synaptic plasticity and dendritic spine formation in specific brain regions, providing a neuroanatomical substrate for the pathophysiology of alcoholism. Epigenetics has recently emerged as a critical regulator of gene expression and synaptic plasticity-related events in the brain. Alcohol exposure and withdrawal induce changes in crucial epigenetic processes in the emotional brain circuitry (amygdala) that may be relevant to the negative affective state defined as the "dark side" of addiction. Here, we review the literature concerning synaptic plasticity and epigenetics, with a particular focus on molecular events related to dendritic remodeling during alcohol abuse and alcoholism. Targeting epigenetic processes that modulate synaptic plasticity may yield novel treatments for alcoholism. Published by Elsevier Ireland Ltd.
Learning complex temporal patterns with resource-dependent spike timing-dependent plasticity.
Hunzinger, Jason F; Chan, Victor H; Froemke, Robert C
2012-07-01
Studies of spike timing-dependent plasticity (STDP) have revealed that long-term changes in the strength of a synapse may be modulated substantially by temporal relationships between multiple presynaptic and postsynaptic spikes. Whereas long-term potentiation (LTP) and long-term depression (LTD) of synaptic strength have been modeled as distinct or separate functional mechanisms, here, we propose a new shared resource model. A functional consequence of our model is fast, stable, and diverse unsupervised learning of temporal multispike patterns with a biologically consistent spiking neural network. Due to interdependencies between LTP and LTD, dendritic delays, and proactive homeostatic aspects of the model, neurons are equipped to learn to decode temporally coded information within spike bursts. Moreover, neurons learn spike timing with few exposures in substantial noise and jitter. Surprisingly, despite having only one parameter, the model also accurately predicts in vitro observations of STDP in more complex multispike trains, as well as rate-dependent effects. We discuss candidate commonalities in natural long-term plasticity mechanisms.
Plasticity in the Interoceptive System.
Torrealba, Fernando; Madrid, Carlos; Contreras, Marco; Gómez, Karina
2017-01-01
The most outstanding manifestations of the plastic capacities of brain circuits and their neuronal and synaptic components in the adult CNS are learning and memory. A reduced number of basic plastic mechanisms underlie learning capacities at many levels and regions of the brain. The interoceptive system is no exception, and some of the most studied behavioral changes that involve learning and memory engage the interoceptive pathways at many levels of their anatomical and functional organization.In this chapter, we will review four examples of learning, mostly in rats, where the interoceptive system has a role. In the case of conditioned taste aversion, the interoceptive system is of outstanding importance. In drug addiction, the role of the insular cortex - the highest level of the interoceptive system- is unusual and complex, as many forebrain regions are engaged by the process of addiction. In the third example, neophobia, the gustatory region of the insular cortex plays a major role. Finally, the role of different areas of the insular cortex in different processes of aversive memory, particularly fear conditioning, will be reviewed.
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.
Chronic cocaine disrupts mesocortical learning mechanisms
Buchta, William C.; Riegel, Arthur C.
2016-01-01
The addictive power of drugs of abuse such as cocaine comes from their ability to hijack natural reward and plasticity mechanisms mediated by dopamine signaling in the brain. Reward learning involves burst firing of midbrain dopamine neurons in response to rewards and cues predictive of reward. The resulting release of dopamine in terminal regions is thought to act as a teaching signaling to areas such as the prefrontal cortex and striatum. In this review, we posit that a pool of extrasynaptic dopaminergic D1-like receptors activated in response to dopamine neuron burst firing serve to enable synaptic plasticity in the prefrontal cortex in response to rewards and their cues. We propose that disruptions in these mechanisms following chronic cocaine use contribute to addiction pathology, in part due to the unique architecture of the mesocortical pathway. By blocking dopamine reuptake in the cortex, cocaine elevates dopamine signaling at these extra-synaptic receptors, prolonging D1-receptor activation and the subsequent activation of intracellular signaling cascades, and thus inducing long-lasting maladaptive plasticity. These cellular adaptations may account for many of the changes in cortical function observed in drug addicts, including an enduring vulnerability to relapse. Therefore, understanding and targeting these neuroadaptations may provide cognitive benefits and help prevent relapse in human drug addicts. PMID:25704202
Kerr, Robert R.; Grayden, David B.; Thomas, Doreen A.; Gilson, Matthieu; Burkitt, Anthony N.
2014-01-01
A fundamental goal of neuroscience is to understand how cognitive processes, such as operant conditioning, are performed by the brain. Typical and well studied examples of operant conditioning, in which the firing rates of individual cortical neurons in monkeys are increased using rewards, provide an opportunity for insight into this. Studies of reward-modulated spike-timing-dependent plasticity (RSTDP), and of other models such as R-max, have reproduced this learning behavior, but they have assumed that no unsupervised learning is present (i.e., no learning occurs without, or independent of, rewards). We show that these models cannot elicit firing rate reinforcement while exhibiting both reward learning and ongoing, stable unsupervised learning. To fix this issue, we propose a new RSTDP model of synaptic plasticity based upon the observed effects that dopamine has on long-term potentiation and depression (LTP and LTD). We show, both analytically and through simulations, that our new model can exhibit unsupervised learning and lead to firing rate reinforcement. This requires that the strengthening of LTP by the reward signal is greater than the strengthening of LTD and that the reinforced neuron exhibits irregular firing. We show the robustness of our findings to spike-timing correlations, to the synaptic weight dependence that is assumed, and to changes in the mean reward. We also consider our model in the differential reinforcement of two nearby neurons. Our model aligns more strongly with experimental studies than previous models and makes testable predictions for future experiments. PMID:24475240
John, Rohit Abraham; Ko, Jieun; Kulkarni, Mohit R; Tiwari, Naveen; Chien, Nguyen Anh; Ing, Ng Geok; Leong, Wei Lin; Mathews, Nripan
2017-08-01
Emulation of biological synapses is necessary for future brain-inspired neuromorphic computational systems that could look beyond the standard von Neuman architecture. Here, artificial synapses based on ionic-electronic hybrid oxide-based transistors on rigid and flexible substrates are demonstrated. The flexible transistors reported here depict a high field-effect mobility of ≈9 cm 2 V -1 s -1 with good mechanical performance. Comprehensive learning abilities/synaptic rules like paired-pulse facilitation, excitatory and inhibitory postsynaptic currents, spike-time-dependent plasticity, consolidation, superlinear amplification, and dynamic logic are successfully established depicting concurrent processing and memory functionalities with spatiotemporal correlation. The results present a fully solution processable approach to fabricate artificial synapses for next-generation transparent neural circuits. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Bozdagi, Ozlem; Rich, Erin; Tronel, Sophie; Sadahiro, Masato; Patterson, Kamara; Shapiro, Matthew L; Alberini, Cristina M; Huntley, George W; Salton, Stephen R J
2008-09-24
VGF is a neurotrophin-inducible, activity-regulated gene product that is expressed in CNS and PNS neurons, in which it is processed into peptides and secreted. VGF synthesis is stimulated by BDNF, a critical regulator of hippocampal development and function, and two VGF C-terminal peptides increase synaptic activity in cultured hippocampal neurons. To assess VGF function in the hippocampus, we tested heterozygous and homozygous VGF knock-out mice in two different learning tasks, assessed long-term potentiation (LTP) and depression (LTD) in hippocampal slices from VGF mutant mice, and investigated how VGF C-terminal peptides modulate synaptic plasticity. Treatment of rat hippocampal slices with the VGF-derived peptide TLQP62 resulted in transient potentiation through a mechanism that was selectively blocked by the BDNF scavenger TrkB-Fc, the Trk tyrosine kinase inhibitor K252a (100 nm), and tPA STOP, an inhibitor of tissue plasminogen activator (tPA), an enzyme involved in pro-BDNF cleavage to BDNF, but was not blocked by the NMDA receptor antagonist APV, anti-p75(NTR) function-blocking antiserum, or previous tetanic stimulation. Although LTP was normal in slices from VGF knock-out mice, LTD could not be induced, and VGF mutant mice were impaired in hippocampal-dependent spatial learning and contextual fear conditioning tasks. Our studies indicate that the VGF C-terminal peptide TLQP62 modulates hippocampal synaptic transmission through a BDNF-dependent mechanism and that VGF deficiency in mice impacts synaptic plasticity and memory in addition to depressive behavior.
Bozdagi, Ozlem; Rich, Erin; Tronel, Sophie; Sadahiro, Masato; Patterson, Kamara; Shapiro, Matthew L.; Alberini, Cristina M.; Huntley, George W.; Salton, Stephen R. J.
2009-01-01
VGF is a neurotrophin-inducible, activity-regulated gene product that is expressed in CNS and PNS neurons, where it is processed into peptides and secreted. VGF synthesis is stimulated by BDNF, a critical regulator of hippocampal development and function, and two VGF C-terminal peptides increase synaptic activity in cultured hippocampal neurons. To assess VGF function in the hippocampus, we tested heterozygous and homozygous VGF knockout mice in two different learning tasks, assessed long-term potentiation (LTP) and depression (LTD) in hippocampal slices from VGF mutant mice, and investigated how VGF C-terminal peptides modulate synaptic plasticity. Treatment of rat hippocampal slices with the VGF-derived peptide TLQP62 resulted in transient potentiation through a mechanism that was selectively blocked by the BDNF scavenger TrkB-Fc, the Trk tyrosine kinase inhibitor K252a (100 nM), and by tPASTOP, an inhibitor of tissue plasminogen activator (tPA), an enzyme involved in pro-BDNF cleavage to BDNF, but was not blocked by the NMDA receptor antagonist APV, anti-p75NTR function-blocking antiserum, nor by prior tetanic stimulation. Although LTP was normal in slices from VGF knockout mice, LTD could not be induced, and VGF mutant mice were impaired in hippocampal-dependent spatial learning and contextual fear conditioning tasks. Our studies indicate that the VGF C-terminal peptide TLQP62 modulates hippocampal synaptic transmission through a BDNF-dependent mechanism, and that VGF deficiency in mice impacts synaptic plasticity and memory in addition to depressive behavior. PMID:18815270
Self-Organization of Microcircuits in Networks of Spiking Neurons with Plastic Synapses.
Ocker, Gabriel Koch; Litwin-Kumar, Ashok; Doiron, Brent
2015-08-01
The synaptic connectivity of cortical networks features an overrepresentation of certain wiring motifs compared to simple random-network models. This structure is shaped, in part, by synaptic plasticity that promotes or suppresses connections between neurons depending on their joint spiking activity. Frequently, theoretical studies focus on how feedforward inputs drive plasticity to create this network structure. We study the complementary scenario of self-organized structure in a recurrent network, with spike timing-dependent plasticity driven by spontaneous dynamics. We develop a self-consistent theory for the evolution of network structure by combining fast spiking covariance with a slow evolution of synaptic weights. Through a finite-size expansion of network dynamics we obtain a low-dimensional set of nonlinear differential equations for the evolution of two-synapse connectivity motifs. With this theory in hand, we explore how the form of the plasticity rule drives the evolution of microcircuits in cortical networks. When potentiation and depression are in approximate balance, synaptic dynamics depend on weighted divergent, convergent, and chain motifs. For additive, Hebbian STDP these motif interactions create instabilities in synaptic dynamics that either promote or suppress the initial network structure. Our work provides a consistent theoretical framework for studying how spiking activity in recurrent networks interacts with synaptic plasticity to determine network structure.
Self-Organization of Microcircuits in Networks of Spiking Neurons with Plastic Synapses
Ocker, Gabriel Koch; Litwin-Kumar, Ashok; Doiron, Brent
2015-01-01
The synaptic connectivity of cortical networks features an overrepresentation of certain wiring motifs compared to simple random-network models. This structure is shaped, in part, by synaptic plasticity that promotes or suppresses connections between neurons depending on their joint spiking activity. Frequently, theoretical studies focus on how feedforward inputs drive plasticity to create this network structure. We study the complementary scenario of self-organized structure in a recurrent network, with spike timing-dependent plasticity driven by spontaneous dynamics. We develop a self-consistent theory for the evolution of network structure by combining fast spiking covariance with a slow evolution of synaptic weights. Through a finite-size expansion of network dynamics we obtain a low-dimensional set of nonlinear differential equations for the evolution of two-synapse connectivity motifs. With this theory in hand, we explore how the form of the plasticity rule drives the evolution of microcircuits in cortical networks. When potentiation and depression are in approximate balance, synaptic dynamics depend on weighted divergent, convergent, and chain motifs. For additive, Hebbian STDP these motif interactions create instabilities in synaptic dynamics that either promote or suppress the initial network structure. Our work provides a consistent theoretical framework for studying how spiking activity in recurrent networks interacts with synaptic plasticity to determine network structure. PMID:26291697
Raven, Frank; Van der Zee, Eddy A; Meerlo, Peter; Havekes, Robbert
2018-06-01
Dendritic spines are the major sites of synaptic transmission in the central nervous system. Alterations in the strength of synaptic connections directly affect the neuronal communication, which is crucial for brain function as well as the processing and storage of information. Sleep and sleep loss bidirectionally alter structural plasticity, by affecting spine numbers and morphology, which ultimately can affect the functional output of the brain in terms of alertness, cognition, and mood. Experimental data from studies in rodents suggest that sleep deprivation may impact structural plasticity in different ways. One of the current views, referred to as the synaptic homeostasis hypothesis, suggests that wake promotes synaptic potentiation whereas sleep facilitates synaptic downscaling. On the other hand, several studies have now shown that sleep deprivation can reduce spine density and attenuate synaptic efficacy in the hippocampus. These data are the basis for the view that sleep promotes hippocampal structural plasticity critical for memory formation. Altogether, the impact of sleep and sleep loss may vary between regions of the brain. A better understanding of the role that sleep plays in regulating structural plasticity may ultimately lead to novel therapeutic approaches for brain disorders that are accompanied by sleep disturbances and sleep loss. Copyright © 2017 Elsevier Ltd. All rights reserved.
Cdk5 Is Required for Memory Function and Hippocampal Plasticity via the cAMP Signaling Pathway
Gao, Jun; Joseph, Nadine; Xie, Zhigang; Zhou, Ying; Durak, Omer; Zhang, Lei; Zhu, J. Julius; Clauser, Karl R.; Carr, Steven A.; Tsai, Li-Huei
2011-01-01
Memory formation is modulated by pre- and post-synaptic signaling events in neurons. The neuronal protein kinase Cyclin-Dependent Kinase 5 (Cdk5) phosphorylates a variety of synaptic substrates and is implicated in memory formation. It has also been shown to play a role in homeostatic regulation of synaptic plasticity in cultured neurons. Surprisingly, we found that Cdk5 loss of function in hippocampal circuits results in severe impairments in memory formation and retrieval. Moreover, Cdk5 loss of function in the hippocampus disrupts cAMP signaling due to an aberrant increase in phosphodiesterase (PDE) proteins. Dysregulation of cAMP is associated with defective CREB phosphorylation and disrupted composition of synaptic proteins in Cdk5-deficient mice. Rolipram, a PDE4 inhibitor that prevents cAMP depletion, restores synaptic plasticity and memory formation in Cdk5-deficient mice. Collectively, our results demonstrate a critical role for Cdk5 in the regulation of cAMP-mediated hippocampal functions essential for synaptic plasticity and memory formation. PMID:21984943
Roles of somatic A-type K(+) channels in the synaptic plasticity of hippocampal neurons.
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.
The role of nitric oxide in pre-synaptic plasticity and homeostasis
Hardingham, Neil; Dachtler, James; Fox, Kevin
2013-01-01
Since the observation that nitric oxide (NO) can act as an intercellular messenger in the brain, the past 25 years have witnessed the steady accumulation of evidence that it acts pre-synaptically at both glutamatergic and GABAergic synapses to alter release-probability in synaptic plasticity. NO does so by acting on the synaptic machinery involved in transmitter release and, in a coordinated fashion, on vesicular recycling mechanisms. In this review, we examine the body of evidence for NO acting as a retrograde factor at synapses, and the evidence from in vivo and in vitro studies that specifically establish NOS1 (neuronal nitric oxide synthase) as the important isoform of NO synthase in this process. The NOS1 isoform is found at two very different locations and at two different spatial scales both in the cortex and hippocampus. On the one hand it is located diffusely in the cytoplasm of a small population of GABAergic neurons and on the other hand the alpha isoform is located discretely at the post-synaptic density (PSD) in spines of pyramidal cells. The present evidence is that the number of NOS1 molecules that exist at the PSD are so low that a spine can only give rise to modest concentrations of NO and therefore only exert a very local action. The NO receptor guanylate cyclase is located both pre- and post-synaptically and this suggests a role for NO in the coordination of local pre- and post-synaptic function during plasticity at individual synapses. Recent evidence shows that NOS1 is also located post-synaptic to GABAergic synapses and plays a pre-synaptic role in GABAergic plasticity as well as glutamatergic plasticity. Studies on the function of NO in plasticity at the cellular level are corroborated by evidence that NO is also involved in experience-dependent plasticity in the cerebral cortex. PMID:24198758
Plasticity in the prefrontal cortex of adult rats
Kolb, Bryan; Gibb, Robbin
2015-01-01
We review the plastic changes of the prefrontal cortex of the rat in response to a wide range of experiences including sensory and motor experience, gonadal hormones, psychoactive drugs, learning tasks, stress, social experience, metaplastic experiences, and brain injury. Our focus is on synaptic changes (dendritic morphology and spine density) in pyramidal neurons and the relationship to behavioral changes. The most general conclusion we can reach is that the prefrontal cortex is extremely plastic and that the medial and orbital prefrontal regions frequently respond very differently to the same experience in the same brain and the rules that govern prefrontal plasticity appear to differ for those of other cortical regions. PMID:25691857
Moran, Rosalyn J; Symmonds, Mkael; Dolan, Raymond J; Friston, Karl J
2014-01-01
The aging brain shows a progressive loss of neuropil, which is accompanied by subtle changes in neuronal plasticity, sensory learning and memory. Neurophysiologically, aging attenuates evoked responses--including the mismatch negativity (MMN). This is accompanied by a shift in cortical responsivity from sensory (posterior) regions to executive (anterior) regions, which has been interpreted as a compensatory response for cognitive decline. Theoretical neurobiology offers a simpler explanation for all of these effects--from a Bayesian perspective, as the brain is progressively optimized to model its world, its complexity will decrease. A corollary of this complexity reduction is an attenuation of Bayesian updating or sensory learning. Here we confirmed this hypothesis using magnetoencephalographic recordings of the mismatch negativity elicited in a large cohort of human subjects, in their third to ninth decade. Employing dynamic causal modeling to assay the synaptic mechanisms underlying these non-invasive recordings, we found a selective age-related attenuation of synaptic connectivity changes that underpin rapid sensory learning. In contrast, baseline synaptic connectivity strengths were consistently strong over the decades. Our findings suggest that the lifetime accrual of sensory experience optimizes functional brain architectures to enable efficient and generalizable predictions of the world.
DREAM/Calsenilin/KChIP3 Modulates Strategy Selection and Estradiol-Dependent Learning and Memory
ERIC Educational Resources Information Center
Tunur, Tumay; Stelly, Claire E.; Schrader, Laura Ann
2013-01-01
Downstream regulatory element antagonist modulator (DREAM)/calsenilin(C)/K+ channel interacting protein 3 (KChIP3) is a multifunctional Ca[superscript 2+]-binding protein highly expressed in the hippocampus that inhibits hippocampus-sensitive memory and synaptic plasticity in male mice. Initial studies in our lab suggested opposing effects of…
Thyroid hormones (TH) are critical for nervous system development. Deficiency of TH during development impair performance on tasks of learning and memory that rely upon the hippocampus, but the mechanism underlying this impairment is not well understood. The present study was ...
Maladaptive spinal plasticity opposes spinal learning and recovery in spinal cord injury
Ferguson, Adam R.; Huie, J. Russell; Crown, Eric D.; Baumbauer, Kyle M.; Hook, Michelle A.; Garraway, Sandra M.; Lee, Kuan H.; Hoy, Kevin C.; Grau, James W.
2012-01-01
Synaptic plasticity within the spinal cord has great potential to facilitate recovery of function after spinal cord injury (SCI). Spinal plasticity can be induced in an activity-dependent manner even without input from the brain after complete SCI. A mechanistic basis for these effects is provided by research demonstrating that spinal synapses have many of the same plasticity mechanisms that are known to underlie learning and memory in the brain. In addition, the lumbar spinal cord can sustain several forms of learning and memory, including limb-position training. However, not all spinal plasticity promotes recovery of function. Central sensitization of nociceptive (pain) pathways in the spinal cord may emerge in response to various noxious inputs, demonstrating that plasticity within the spinal cord may contribute to maladaptive pain states. In this review we discuss interactions between adaptive and maladaptive forms of activity-dependent plasticity in the spinal cord below the level of SCI. The literature demonstrates that activity-dependent plasticity within the spinal cord must be carefully tuned to promote adaptive spinal training. Prior work from our group has shown that stimulation that is delivered in a limb position-dependent manner or on a fixed interval can induce adaptive plasticity that promotes future spinal cord learning and reduces nociceptive hyper-reactivity. On the other hand, stimulation that is delivered in an unsynchronized fashion, such as randomized electrical stimulation or peripheral skin injuries, can generate maladaptive spinal plasticity that undermines future spinal cord learning, reduces recovery of locomotor function, and promotes nociceptive hyper-reactivity after SCI. We review these basic phenomena, how these findings relate to the broader spinal plasticity literature, discuss the cellular and molecular mechanisms, and finally discuss implications of these and other findings for improved rehabilitative therapies after SCI. PMID:23087647
Emerging Synaptic Molecules as Candidates in the Etiology of Neurological Disorders
Torres, Viviana I.; Vallejo, Daniela
2017-01-01
Synapses are complex structures that allow communication between neurons in the central nervous system. Studies conducted in vertebrate and invertebrate models have contributed to the knowledge of the function of synaptic proteins. The functional synapse requires numerous protein complexes with specialized functions that are regulated in space and time to allow synaptic plasticity. However, their interplay during neuronal development, learning, and memory is poorly understood. Accumulating evidence links synapse proteins to neurodevelopmental, neuropsychiatric, and neurodegenerative diseases. In this review, we describe the way in which several proteins that participate in cell adhesion, scaffolding, exocytosis, and neurotransmitter reception from presynaptic and postsynaptic compartments, mainly from excitatory synapses, have been associated with several synaptopathies, and we relate their functions to the disease phenotype. PMID:28331639
The homeostatic astroglia emerges from evolutionary specialization of neural cells
Verkhratsky, Alexei; Nedergaard, Maiken
2016-01-01
Evolution of the nervous system progressed through cellular diversification and specialization of functions. Conceptually, the nervous system is composed from electrically excitable neuronal networks connected with chemical synapses and non-excitable glial cells that provide for homeostasis and defence. Astrocytes are integrated into neural networks through multipartite synapses; astroglial perisynaptic processes closely enwrap synaptic contacts and control homeostasis of the synaptic cleft, supply neurons with glutamate and GABA obligatory precursor glutamine and contribute to synaptic plasticity, learning and memory. In neuropathology, astrocytes may undergo reactive remodelling or degeneration; to a large extent, astroglial reactions define progression of the pathology and neurological outcome. This article is part of the themed issue ‘Evolution brings Ca2+ and ATP together to control life and death’. PMID:27377722
Minge, Daniel; Senkov, Oleg; Kaushik, Rahul; Herde, Michel K; Tikhobrazova, Olga; Wulff, Andreas B; Mironov, Andrey; van Kuppevelt, Toin H; Oosterhof, Arie; Kochlamazashvili, Gaga; Dityatev, Alexander; Henneberger, Christian
2017-02-01
Heparan sulfate (HS) proteoglycans represent a major component of the extracellular matrix and are critical for brain development. However, their function in the mature brain remains to be characterized. Here, acute enzymatic digestion of HS side chains was used to uncover how HSs support hippocampal function in vitro and in vivo. We found that long-term potentiation (LTP) of synaptic transmission at CA3-CA1 Schaffer collateral synapses was impaired after removal of highly sulfated HSs with heparinase 1. This reduction was associated with decreased Ca2+ influx during LTP induction, which was the consequence of a reduced excitability of CA1 pyramidal neurons. At the subcellular level, heparinase treatment resulted in reorganization of the distal axon initial segment, as detected by a reduction in ankyrin G expression. In vivo, digestion of HSs impaired context discrimination in a fear conditioning paradigm and oscillatory network activity in the low theta band after fear conditioning. Thus, HSs maintain neuronal excitability and, as a consequence, support synaptic plasticity and learning. © The Author 2017. Published by Oxford University Press.
Jaafar, Ayoub H; Gray, Robert J; Verrelli, Emanuele; O'Neill, Mary; Kelly, Stephen M; Kemp, Neil T
2017-11-09
Optical control of memristors opens the route to new applications in optoelectronic switching and neuromorphic computing. Motivated by the need for reversible and latched optical switching we report on the development of a memristor with electronic properties tunable and switchable by wavelength and polarization specific light. The device consists of an optically active azobenzene polymer, poly(disperse red 1 acrylate), overlaying a forest of vertically aligned ZnO nanorods. Illumination induces trans-cis isomerization of the azobenzene molecules, which expands or contracts the polymer layer and alters the resistance of the off/on states, their ratio and retention time. The reversible optical effect enables dynamic control of a memristor's learning properties including control of synaptic potentiation and depression, optical switching between short-term and long-term memory and optical modulation of the synaptic efficacy via spike timing dependent plasticity. The work opens the route to the dynamic patterning of memristor networks both spatially and temporally by light, thus allowing the development of new optically reconfigurable neural networks and adaptive electronic circuits.
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.
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.
Plasticity in the Human Visual Cortex: An Ophthalmology-Based Perspective
Rosa, Andreia Martins; Silva, Maria Fátima; Murta, Joaquim
2013-01-01
Neuroplasticity refers to the ability of the brain to reorganize the function and structure of its connections in response to changes in the environment. Adult human visual cortex shows several manifestations of plasticity, such as perceptual learning and adaptation, working under the top-down influence of attention. Plasticity results from the interplay of several mechanisms, including the GABAergic system, epigenetic factors, mitochondrial activity, and structural remodeling of synaptic connectivity. There is also a downside of plasticity, that is, maladaptive plasticity, in which there are behavioral losses resulting from plasticity changes in the human brain. Understanding plasticity mechanisms could have major implications in the diagnosis and treatment of ocular diseases, such as retinal disorders, cataract and refractive surgery, amblyopia, and in the evaluation of surgical materials and techniques. Furthermore, eliciting plasticity could open new perspectives in the development of strategies that trigger plasticity for better medical and surgical outcomes. PMID:24205505
Synaptic Plasticity and Translation Initiation
ERIC Educational Resources Information Center
Klann, Eric; Antion, Marcia D.; Banko, Jessica L.; Hou, Lingfei
2004-01-01
It is widely accepted that protein synthesis, including local protein synthesis at synapses, is required for several forms of synaptic plasticity. Local protein synthesis enables synapses to control synaptic strength independent of the cell body via rapid protein production from pre-existing mRNA. Therefore, regulation of translation initiation is…
Prospective Coding by Spiking Neurons
Brea, Johanni; Gaál, Alexisz Tamás; Senn, Walter
2016-01-01
Animals learn to make predictions, such as associating the sound of a bell with upcoming feeding or predicting a movement that a motor command is eliciting. How predictions are realized on the neuronal level and what plasticity rule underlies their learning is not well understood. Here we propose a biologically plausible synaptic plasticity rule to learn predictions on a single neuron level on a timescale of seconds. The learning rule allows a spiking two-compartment neuron to match its current firing rate to its own expected future discounted firing rate. For instance, if an originally neutral event is repeatedly followed by an event that elevates the firing rate of a neuron, the originally neutral event will eventually also elevate the neuron’s firing rate. The plasticity rule is a form of spike timing dependent plasticity in which a presynaptic spike followed by a postsynaptic spike leads to potentiation. Even if the plasticity window has a width of 20 milliseconds, associations on the time scale of seconds can be learned. We illustrate prospective coding with three examples: learning to predict a time varying input, learning to predict the next stimulus in a delayed paired-associate task and learning with a recurrent network to reproduce a temporally compressed version of a sequence. We discuss the potential role of the learning mechanism in classical trace conditioning. In the special case that the signal to be predicted encodes reward, the neuron learns to predict the discounted future reward and learning is closely related to the temporal difference learning algorithm TD(λ). PMID:27341100
[Changes of the neuronal membrane excitability as cellular mechanisms of learning and memory].
Gaĭnutdinov, Kh L; Andrianov, V V; Gaĭnutdinova, T Kh
2011-01-01
In the presented review given literature and results of own studies of dynamics of electrical characteristics of neurons, which change are included in processes both an elaboration of learning, and retention of the long-term memory. Literary datas and our results allow to conclusion, that long-term retention of behavioural reactions during learning is accompanied not only by changing efficiency of synaptic transmission, as well as increasing of excitability of command neurons of the defensive reflex. This means, that in the process of learning are involved long-term changes of the characteristics a membrane of certain elements of neuronal network, dependent from the metabolism of the cells. see text). Thou phenomena possible mark as cellular (electrophysiological) correlates of long-term plastic modifications of the behaviour. The analyses of having results demonstrates an important role of membrane characteristics of neurons (their excitability) and parameters an synaptic transmission not only in initial stage of learning, as well as in long-term modifications of the behaviour (long-term memory).
The Ubiquitin-Proteasome Pathway and Synaptic Plasticity
ERIC Educational Resources Information Center
Hegde, Ashok N.
2010-01-01
Proteolysis by the ubiquitin-proteasome pathway (UPP) has emerged as a new molecular mechanism that controls wide-ranging functions in the nervous system, including fine-tuning of synaptic connections during development and synaptic plasticity in the adult organism. In the UPP, attachment of a small protein, ubiquitin, tags the substrates for…
Kida, Hiroyuki; Tsuda, Yasumasa; Ito, Nana; Yamamoto, Yui; Owada, Yuji; Kamiya, Yoshinori; Mitsushima, Dai
2016-01-01
Motor skill training induces structural plasticity at dendritic spines in the primary motor cortex (M1). To further analyze both synaptic and intrinsic plasticity in the layer II/III area of M1, we subjected rats to a rotor rod test and then prepared acute brain slices. Motor skill consistently improved within 2 days of training. Voltage clamp analysis showed significantly higher α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid/N-methyl-d-aspartate (AMPA/NMDA) ratios and miniature EPSC amplitudes in 1-day trained rats compared with untrained rats, suggesting increased postsynaptic AMPA receptors in the early phase of motor learning. Compared with untrained controls, 2-days trained rats showed significantly higher miniature EPSC amplitude and frequency. Paired-pulse analysis further demonstrated lower rates in 2-days trained rats, suggesting increased presynaptic glutamate release during the late phase of learning. One-day trained rats showed decreased miniature IPSC frequency and increased paired-pulse analysis of evoked IPSC, suggesting a transient decrease in presynaptic γ-aminobutyric acid (GABA) release. Moreover, current clamp analysis revealed lower resting membrane potential, higher spike threshold, and deeper afterhyperpolarization in 1-day trained rats—while 2-days trained rats showed higher membrane potential, suggesting dynamic changes in intrinsic properties. Our present results indicate dynamic changes in glutamatergic, GABAergic, and intrinsic plasticity in M1 layer II/III neurons after the motor training. PMID:27193420
Kida, Hiroyuki; Tsuda, Yasumasa; Ito, Nana; Yamamoto, Yui; Owada, Yuji; Kamiya, Yoshinori; Mitsushima, Dai
2016-08-01
Motor skill training induces structural plasticity at dendritic spines in the primary motor cortex (M1). To further analyze both synaptic and intrinsic plasticity in the layer II/III area of M1, we subjected rats to a rotor rod test and then prepared acute brain slices. Motor skill consistently improved within 2 days of training. Voltage clamp analysis showed significantly higher α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid/N-methyl-d-aspartate (AMPA/NMDA) ratios and miniature EPSC amplitudes in 1-day trained rats compared with untrained rats, suggesting increased postsynaptic AMPA receptors in the early phase of motor learning. Compared with untrained controls, 2-days trained rats showed significantly higher miniature EPSC amplitude and frequency. Paired-pulse analysis further demonstrated lower rates in 2-days trained rats, suggesting increased presynaptic glutamate release during the late phase of learning. One-day trained rats showed decreased miniature IPSC frequency and increased paired-pulse analysis of evoked IPSC, suggesting a transient decrease in presynaptic γ-aminobutyric acid (GABA) release. Moreover, current clamp analysis revealed lower resting membrane potential, higher spike threshold, and deeper afterhyperpolarization in 1-day trained rats-while 2-days trained rats showed higher membrane potential, suggesting dynamic changes in intrinsic properties. Our present results indicate dynamic changes in glutamatergic, GABAergic, and intrinsic plasticity in M1 layer II/III neurons after the motor training. © The Author 2016. Published by Oxford University Press.
Maggi, Laura; Scianni, Maria; Branchi, Igor; D’Andrea, Ivana; Lauro, Clotilde; Limatola, Cristina
2011-01-01
In recent years several evidence demonstrated that some features of hippocampal biology, like neurogenesis, synaptic transmission, learning, and memory performances are deeply modulated by social, motor, and sensorial experiences. Fractalkine/CX3CL1 is a transmembrane chemokine abundantly expressed in the brain by neurons, where it modulates glutamatergic transmission and long-term plasticity processes regulating the intercellular communication between glia and neurons, being its specific receptor CX3CR1 expressed by microglia. In this paper we investigated the role of CX3CL1/CX3CR1 signaling on experience-dependent hippocampal plasticity processes. At this aim wt and CX3CR1GFP/GFP mice were exposed to long-lasting-enriched environment (EE) and the effects on hippocampal functions were studied by electrophysiological recordings of long-term potentiation of synaptic activity, behavioral tests of learning and memory in the Morris water maze paradigm and analysis of neurogenesis in the subgranular zone of the dentate gyrus (DG). We found that CX3CR1 deficiency increases hippocampal plasticity and spatial memory, blunting the potentiating effects of EE. In contrast, exposure to EE increased the number and migration of neural progenitors in the DG of both wt and CX3CR1GFP/GFP mice. These data indicate that CX3CL1/CX3CR1-mediated signaling is crucial for a normal experience-dependent modulation of hippocampal functions. PMID:22025910
Geminiani, Alice; Casellato, Claudia; Antonietti, Alberto; D'Angelo, Egidio; Pedrocchi, Alessandra
2018-06-01
The cerebellum plays a crucial role in sensorimotor control and cerebellar disorders compromise adaptation and learning of motor responses. However, the link between alterations at network level and cerebellar dysfunction is still unclear. In principle, this understanding would benefit of the development of an artificial system embedding the salient neuronal and plastic properties of the cerebellum and operating in closed-loop. To this aim, we have exploited a realistic spiking computational model of the cerebellum to analyze the network correlates of cerebellar impairment. The model was modified to reproduce three different damages of the cerebellar cortex: (i) a loss of the main output neurons (Purkinje Cells), (ii) a lesion to the main cerebellar afferents (Mossy Fibers), and (iii) a damage to a major mechanism of synaptic plasticity (Long Term Depression). The modified network models were challenged with an Eye-Blink Classical Conditioning test, a standard learning paradigm used to evaluate cerebellar impairment, in which the outcome was compared to reference results obtained in human or animal experiments. In all cases, the model reproduced the partial and delayed conditioning typical of the pathologies, indicating that an intact cerebellar cortex functionality is required to accelerate learning by transferring acquired information to the cerebellar nuclei. Interestingly, depending on the type of lesion, the redistribution of synaptic plasticity and response timing varied greatly generating specific adaptation patterns. Thus, not only the present work extends the generalization capabilities of the cerebellar spiking model to pathological cases, but also predicts how changes at the neuronal level are distributed across the network, making it usable to infer cerebellar circuit alterations occurring in cerebellar pathologies.
Biologically plausible learning in neural networks: a lesson from bacterial chemotaxis.
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.
Mechanisms of dendritic mRNA transport and its role in synaptic tagging
Doyle, Michael; Kiebler, Michael A
2011-01-01
The localization of RNAs critically contributes to many important cellular processes in an organism, such as the establishment of polarity, asymmetric division and migration during development. Moreover, in the central nervous system, the local translation of mRNAs is thought to induce plastic changes that occur at synapses triggered by learning and memory. Here, we will critically review the physiological functions of well-established dendritically localized mRNAs and their associated factors, which together form ribonucleoprotein particles (RNPs). Second, we will discuss the life of a localized transcript from transcription in the nucleus to translation at the synapse and introduce the concept of the ‘RNA signature' that is characteristic for each transcript. Finally, we present the ‘sushi belt model' of how localized RNAs within neuronal RNPs may dynamically patrol multiple synapses rather than being anchored at a single synapse. This new model integrates our current understanding of synaptic function ranging from synaptic tagging and capture to functional and structural reorganization of the synapse upon learning and memory. PMID:21878995
Morimura, Naoko; Yasuda, Hiroki; Yamaguchi, Kazuhiko; Katayama, Kei-Ichi; Hatayama, Minoru; Tomioka, Naoko H; Odagawa, Maya; Kamiya, Akiko; Iwayama, Yoshimi; Maekawa, Motoko; Nakamura, Kazuhiko; Matsuzaki, Hideo; Tsujii, Masatsugu; Yamada, Kazuyuki; Yoshikawa, Takeo; Aruga, Jun
2017-06-12
Lrfn2/SALM1 is a PSD-95-interacting synapse adhesion molecule, and human LRFN2 is associated with learning disabilities. However its role in higher brain function and underlying mechanisms remain unknown. Here, we show that Lrfn2 knockout mice exhibit autism-like behavioural abnormalities, including social withdrawal, decreased vocal communications, increased stereotyped activities and prepulse inhibition deficits, together with enhanced learning and memory. In the hippocampus, the levels of synaptic PSD-95 and GluA1 are decreased. The synapses are structurally and functionally immature with spindle shaped spines, smaller postsynaptic densities, reduced AMPA/NMDA ratio, and enhanced LTP. In vitro experiments reveal that synaptic surface expression of AMPAR depends on the direct interaction between Lrfn2 and PSD-95. Furthermore, we detect functionally defective LRFN2 missense mutations in autism and schizophrenia patients. Together, these findings indicate that Lrfn2/LRFN2 serve as core components of excitatory synapse maturation and maintenance, and their dysfunction causes immature/silent synapses with pathophysiological state.
Duran, Jordi; Saez, Isabel; Gruart, Agnès; Guinovart, Joan J; Delgado-García, José M
2013-01-01
Glycogen is the only carbohydrate reserve of the brain, but its overall contribution to brain functions remains unclear. Although it has traditionally been considered as an emergency energetic reservoir, increasing evidence points to a role of glycogen in the normal activity of the brain. To address this long-standing question, we generated a brain-specific Glycogen Synthase knockout (GYS1Nestin-KO) mouse and studied the functional consequences of the lack of glycogen in the brain under alert behaving conditions. These animals showed a significant deficiency in the acquisition of an associative learning task and in the concomitant activity-dependent changes in hippocampal synaptic strength. Long-term potentiation (LTP) evoked in the hippocampal CA3-CA1 synapse was also decreased in behaving GYS1Nestin-KO mice. These results unequivocally show a key role of brain glycogen in the proper acquisition of new motor and cognitive abilities and in the underlying changes in synaptic strength. PMID:23281428
Marwarha, Gurdeep; Ghribi, Othman
2017-01-01
NF-κB is a ubiquitous transcription factor that was discovered three decades ago. Since its discovery, this protein complex has been implicated in numerous physiological and pathophysiological processes such as synaptic plasticity, learning and memory, inflammation, insulin resistance, and oxidative stress among other factors that are intricately involved and dysregulated in Alzheimer's disease (AD). We embarked on a methodical and an objective review of contemporary literature to integrate the indispensable physiological functions of NF-κB in neuronal phsyiology with the undesirable pathophysiological attributes of NF-κB in the etiopathogenesis of Alzheimer's disease. In our approach, we first introduced Alzheimer's disease and subsequently highlighted the multifaceted roles of NF-κB in the biological processes altered in the progression of Alzheimer's disease including synaptic transmission, synaptic plasticity, learning, and memory, neuronal survival and apoptosis, adult neurogenesis, regulation of neural processes and structural plasticity, inflammation, and Amyloid-β production and toxicity. Our comprehensive review highlights and dissects the physiological role of NF-κB from its pathological role in the brain and delineates both, its beneficial as well as deleterious, role in the etiopathogenesis of Alzheimer's disease. In light of our understanding of the duality of the role of NF-κB in the pathogenesis of Alzheimer's disease, further studies are warranted to dissect and understand the basis of the dichotomous effects of NF-κB, so that certain selective benevolent and benign attributes of NF-κB can be spared while targeting its deleterious attributes and facets that are integral in the pathogenesis of Alzheimer's disease. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.
Ménard, Caroline; Quirion, Rémi
2012-01-01
Normal aging is generally characterized by a slow decline of cognitive abilities albeit with marked individual differences. Several animal models have been studied to explore the molecular and cellular mechanisms underlying this phenomenon. The excitatory neurotransmitter glutamate and its receptors have been closely linked to spatial learning and hippocampus-dependent memory processes. For decades, ionotropic glutamate receptors have been known to play a critical role in synaptic plasticity, a form of adaptation regulating memory formation. Over the past 10 years, several groups have shown the importance of group 1 metabotropic glutamate receptor (mGluR) in successful cognitive aging. These G-protein-coupled receptors are enriched in the hippocampal formation and interact physically with other proteins in the membrane including glutamate ionotropic receptors. Synaptic plasticity is crucial to maintain cognitive abilities and long-term depression (LTD) induced by group 1 mGluR activation, which has been linked to memory in the aging brain. The translation and synthesis of proteins by mGluR-LTD modulate ionotropic receptor trafficking and expression of immediate early genes related to cognition. Fragile X syndrome, a genetic form of autism characterized by memory deficits, has been associated to mGluR receptor malfunction and aberrant activation of its downstream signaling pathways. Dysfunction of mGluR could also be involved in neurodegenerative disorders like Alzheimer’s disease (AD). Indeed, beta-amyloid, the main component of insoluble senile plaques and one of the hallmarks of AD, occludes mGluR-dependent LTD leading to diminished functional synapses. This review highlights recent findings regarding mGluR signaling, related synaptic plasticity, and their potential involvement in normal aging and neurological disorders. PMID:23091460
Ménard, Caroline; Quirion, Rémi
2012-01-01
Normal aging is generally characterized by a slow decline of cognitive abilities albeit with marked individual differences. Several animal models have been studied to explore the molecular and cellular mechanisms underlying this phenomenon. The excitatory neurotransmitter glutamate and its receptors have been closely linked to spatial learning and hippocampus-dependent memory processes. For decades, ionotropic glutamate receptors have been known to play a critical role in synaptic plasticity, a form of adaptation regulating memory formation. Over the past 10 years, several groups have shown the importance of group 1 metabotropic glutamate receptor (mGluR) in successful cognitive aging. These G-protein-coupled receptors are enriched in the hippocampal formation and interact physically with other proteins in the membrane including glutamate ionotropic receptors. Synaptic plasticity is crucial to maintain cognitive abilities and long-term depression (LTD) induced by group 1 mGluR activation, which has been linked to memory in the aging brain. The translation and synthesis of proteins by mGluR-LTD modulate ionotropic receptor trafficking and expression of immediate early genes related to cognition. Fragile X syndrome, a genetic form of autism characterized by memory deficits, has been associated to mGluR receptor malfunction and aberrant activation of its downstream signaling pathways. Dysfunction of mGluR could also be involved in neurodegenerative disorders like Alzheimer's disease (AD). Indeed, beta-amyloid, the main component of insoluble senile plaques and one of the hallmarks of AD, occludes mGluR-dependent LTD leading to diminished functional synapses. This review highlights recent findings regarding mGluR signaling, related synaptic plasticity, and their potential involvement in normal aging and neurological disorders.
Structural Basis of Arc Binding to Synaptic Proteins: Implications for Cognitive Disease
Zhang, Wenchi; Wu, Jing; Ward, Matthew D.; ...
2015-04-09
Arc is a cellular immediate-early gene (IEG) that functions at excitatory synapses and is required for learning and memory. Here we report crystal structures of Arc subdomains that form a bi-lobar architecture remarkably similar to the capsid domain of human immunodeficiency virus (HIV) gag protein. Analysis indicates Arc originated from the Ty3/Gypsy retrotransposon family and was “domesticated” in higher vertebrates for synaptic functions. The Arc N-terminal lobe evolved a unique hydrophobic pocket that mediates intermolecular binding with synaptic proteins as resolved in complexes with TARPγ2 (Stargazin) and CaMKII peptides and is essential for Arc’s synaptic function. A consensus sequence formore » Arc binding identifies several additional partners that include genes implicated in schizophrenia. Arc N-lobe binding is inhibited by small chemicals suggesting Arc’s synaptic action may be druggable. Finally, these studies reveal the remarkable evolutionary origin of Arc and provide a structural basis for understanding Arc’s contribution to neural plasticity and disease.« less
Structural Basis of Arc Binding to Synaptic Proteins: Implications for Cognitive Disease
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhang, Wenchi; Wu, Jing; Ward, Matthew D.
Arc is a cellular immediate-early gene (IEG) that functions at excitatory synapses and is required for learning and memory. Here we report crystal structures of Arc subdomains that form a bi-lobar architecture remarkably similar to the capsid domain of human immunodeficiency virus (HIV) gag protein. Analysis indicates Arc originated from the Ty3/Gypsy retrotransposon family and was “domesticated” in higher vertebrates for synaptic functions. The Arc N-terminal lobe evolved a unique hydrophobic pocket that mediates intermolecular binding with synaptic proteins as resolved in complexes with TARPγ2 (Stargazin) and CaMKII peptides and is essential for Arc’s synaptic function. A consensus sequence formore » Arc binding identifies several additional partners that include genes implicated in schizophrenia. Arc N-lobe binding is inhibited by small chemicals suggesting Arc’s synaptic action may be druggable. Finally, these studies reveal the remarkable evolutionary origin of Arc and provide a structural basis for understanding Arc’s contribution to neural plasticity and disease.« less
Structural Basis of Arc Binding to Synaptic Proteins: Implications for Cognitive Disease
Zhang, Wenchi; Wu, Jing; Ward, Matthew D.; Yang, Sunggu; Chuang, Yang-An; Xiao, Meifang; Li, Ruojing; Leahy, Daniel J.; Worley, Paul F.
2015-01-01
SUMMARY Arc is a cellular immediate early gene (IEG) that functions at excitatory synapses and is required for learning and memory. We report crystal structures of Arc subdomains that form a bi-lobar architecture remarkably similar to the capsid domain of human immunodeficiency virus (HIV) gag protein. Analysis indicates Arc originated from the Ty3/Gypsy retrotransposon family and was “domesticated” in higher vertebrates for synaptic functions. The Arc N-terminal lobe evolved a unique hydrophobic pocket that mediates intermolecular binding with synaptic proteins as resolved in complexes with TARPγ2 (Stargazin) and CaMKII peptides, and is essential for Arc’s synaptic function. A consensus sequence for Arc binding identifies several additional partners that include genes implicated in schizophrenia. Arc N-lobe binding is inhibited by small chemicals suggesting Arc’s synaptic action may be druggable. These studies reveal the remarkable evolutionary origin of Arc and provide a structural basis for understanding Arc’s contribution to neural plasticity and disease. PMID:25864631
Ephrin-B2 prevents N-methyl-D-aspartate receptor antibody effects on memory and neuroplasticity.
Planagumà, Jesús; Haselmann, Holger; Mannara, Francesco; Petit-Pedrol, Mar; Grünewald, Benedikt; Aguilar, Esther; Röpke, Luise; Martín-García, Elena; Titulaer, Maarten J; Jercog, Pablo; Graus, Francesc; Maldonado, Rafael; Geis, Christian; Dalmau, Josep
2016-09-01
To demonstrate that ephrin-B2 (the ligand of EphB2 receptor) antagonizes the pathogenic effects of patients' N-methyl-D-aspartate receptor (NMDAR) antibodies on memory and synaptic plasticity. One hundred twenty-two C57BL/6J mice infused with cerebrospinal fluid (CSF) from patients with anti-NMDAR encephalitis or controls, with or without ephrin-B2, were investigated. CSF was infused through ventricular catheters connected to subcutaneous osmotic pumps over 14 days. Memory, behavioral tasks, locomotor activity, presence of human antibodies specifically bound to hippocampal NMDAR, and antibody effects on the density of cell-surface and synaptic NMDAR and EphB2 were examined at different time points using reported techniques. Short- and long-term synaptic plasticity were determined in acute brain sections; the Schaffer collateral pathway was stimulated and the field excitatory postsynaptic potentials were recorded in the CA1 region of the hippocampus. Mice infused with patients' CSF, but not control CSF, developed progressive memory deficit and depressive-like behavior along with deposits of NMDAR antibodies in the hippocampus. These findings were associated with a decrease of the density of cell-surface and synaptic NMDAR and EphB2, and marked impairment of long-term synaptic plasticity without altering short-term plasticity. Administration of ephrin-B2 prevented the pathogenic effects of the antibodies in all the investigated paradigms assessing memory, depressive-like behavior, density of cell-surface and synaptic NMDAR and EphB2, and long-term synaptic plasticity. Administration of ephrin-B2 prevents the pathogenic effects of anti-NMDAR encephalitis antibodies on memory and behavior, levels of cell-surface NMDAR, and synaptic plasticity. These findings reveal a strategy beyond immunotherapy to antagonize patients' antibody effects. Ann Neurol 2016;80:388-400. © 2016 American Neurological Association.
High abundance of BDNF within glutamatergic presynapses of cultured hippocampal neurons
Andreska, Thomas; Aufmkolk, Sarah; Sauer, Markus; Blum, Robert
2014-01-01
In the mammalian brain, the neurotrophin brain-derived neurotrophic factor (BDNF) has emerged as a key factor for synaptic refinement, plasticity and learning. Although BDNF-induced signaling cascades are well known, the spatial aspects of the synaptic BDNF localization remained unclear. Recent data provide strong evidence for an exclusive presynaptic location and anterograde secretion of endogenous BDNF at synapses of the hippocampal circuit. In contrast, various studies using BDNF overexpression in cultured hippocampal neurons support the idea that postsynaptic elements and other dendritic structures are the preferential sites of BDNF localization and release. In this study we used rigorously tested anti-BDNF antibodies and achieved a dense labeling of endogenous BDNF close to synapses. Confocal microscopy showed natural BDNF close to many, but not all glutamatergic synapses, while neither GABAergic synapses nor postsynaptic structures carried a typical synaptic BDNF label. To visualize the BDNF distribution within the fine structure of synapses, we implemented super resolution fluorescence imaging by direct stochastic optical reconstruction microscopy (dSTORM). Two-color dSTORM images of neurites were acquired with a spatial resolution of ~20 nm. At this resolution, the synaptic scaffold proteins Bassoon and Homer exhibit hallmarks of mature synapses and form juxtaposed bars, separated by a synaptic cleft. BDNF imaging signals form granule-like clusters with a mean size of ~60 nm and are preferentially found within the fine structure of the glutamatergic presynapse. Individual glutamatergic presynapses carried up to 90% of the synaptic BDNF immunoreactivity, and only a minor fraction of BDNF molecules was found close to the postsynaptic bars. Our data proof that hippocampal neurons are able to enrich and store high amounts of BDNF in small granules within the mature glutamatergic presynapse, at a principle site of synaptic plasticity. PMID:24782711
Subacute ibuprofen treatment rescues the synaptic and cognitive deficits in advanced-aged mice
Rogers, Justin T.; Liu, Chia-Chen; Zhao, Na; Wang, Jian; Putzke, Travis; Yang, Longyu; Shinohara, Mitsuru; Fryer, John D.; Kanekiyo, Takahisa; Bu, Guojun
2017-01-01
Aging is accompanied by increased neuroinflammation, synaptic dysfunction and cognitive deficits both in rodents and humans, yet the onset and progression of these deficits throughout the life span remain unknown. These aging-related deficits affect the quality of life and present challenges to our aging society. Here, we defined age-dependent and progressive impairments of synaptic and cognitive functions and showed that reducing astrocyte-related neuroinflammation through anti-inflammatory drug treatment in aged mice reverses these events. By comparing young (3 months), middle-aged (18 months), aged (24 months) and advanced-aged wild-type mice (30 months), we found that the levels of an astrocytic marker, GFAP, progressively increased after 18 months of age, which preceded the decreases of the synaptic marker PSD-95. Hippocampal long-term potentiation (LTP) was also suppressed in an age-dependent manner, where significant deficits were observed after 24 months of age. Fear conditioning tests demonstrated that associative memory in the context and cued conditions was decreased starting at the ages of 18 and 30 months, respectively. When the mice were tested on hidden platform water maze, spatial learning memory was significantly impaired after 24 months of age. Importantly, subacute treatment with the anti-inflammatory drug ibuprofen suppressed astrocyte activation, and restored synaptic plasticity and memory function in advanced-aged mice. These results support the critical contribution of aging-related inflammatory responses to hippocampal-dependent cognitive function and synaptic plasticity, in particular during advanced aging. Our findings provide strong evidence that suppression of neuroinflammation could be a promising treatment strategy to preserve cognition during aging. PMID:28254590
Shi, Bitao; Bourne, Jennifer; Harris, Kristen M
2011-03-01
Serial section electron microscopy (ssEM) is rapidly expanding as a primary tool to investigate synaptic circuitry and plasticity. The ultrastructural images collected through ssEM are content rich and their comprehensive analysis is beyond the capacity of an individual laboratory. Hence, sharing ultrastructural data is becoming crucial to visualize, analyze, and discover the structural basis of synaptic circuitry and function in the brain. We devised a web-based management system called SynapticDB (http://synapses.clm.utexas.edu/synapticdb/) that catalogues, extracts, analyzes, and shares experimental data from ssEM. The management strategy involves a library with check-in, checkout and experimental tracking mechanisms. We developed a series of spreadsheet templates (MS Excel, Open Office spreadsheet, etc) that guide users in methods of data collection, structural identification, and quantitative analysis through ssEM. SynapticDB provides flexible access to complete templates, or to individual columns with instructional headers that can be selected to create user-defined templates. New templates can also be generated and uploaded. Research progress is tracked via experimental note management and dynamic PDF forms that allow new investigators to follow standard protocols and experienced researchers to expand the range of data collected and shared. The combined use of templates and tracking notes ensures that the supporting experimental information is populated into the database and associated with the appropriate ssEM images and analyses. We anticipate that SynapticDB will serve future meta-analyses towards new discoveries about the composition and circuitry of neurons and glia, and new understanding about structural plasticity during development, behavior, learning, memory, and neuropathology.
Dysregulated expression of neuregulin-1 by cortical pyramidal neurons disrupts synaptic plasticity.
Agarwal, Amit; Zhang, Mingyue; Trembak-Duff, Irina; Unterbarnscheidt, Tilmann; Radyushkin, Konstantin; Dibaj, Payam; Martins de Souza, Daniel; Boretius, Susann; Brzózka, Magdalena M; Steffens, Heinz; Berning, Sebastian; Teng, Zenghui; Gummert, Maike N; Tantra, Martesa; Guest, Peter C; Willig, Katrin I; Frahm, Jens; Hell, Stefan W; Bahn, Sabine; Rossner, Moritz J; Nave, Klaus-Armin; Ehrenreich, Hannelore; Zhang, Weiqi; Schwab, Markus H
2014-08-21
Neuregulin-1 (NRG1) gene variants are associated with increased genetic risk for schizophrenia. It is unclear whether risk haplotypes cause elevated or decreased expression of NRG1 in the brains of schizophrenia patients, given that both findings have been reported from autopsy studies. To study NRG1 functions in vivo, we generated mouse mutants with reduced and elevated NRG1 levels and analyzed the impact on cortical functions. Loss of NRG1 from cortical projection neurons resulted in increased inhibitory neurotransmission, reduced synaptic plasticity, and hypoactivity. Neuronal overexpression of cysteine-rich domain (CRD)-NRG1, the major brain isoform, caused unbalanced excitatory-inhibitory neurotransmission, reduced synaptic plasticity, abnormal spine growth, altered steady-state levels of synaptic plasticity-related proteins, and impaired sensorimotor gating. We conclude that an "optimal" level of NRG1 signaling balances excitatory and inhibitory neurotransmission in the cortex. Our data provide a potential pathomechanism for impaired synaptic plasticity and suggest that human NRG1 risk haplotypes exert a gain-of-function effect. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.
Hebbian Plasticity in CPG Controllers Facilitates Self-Synchronization for Human-Robot Handshaking.
Jouaiti, Melanie; Caron, Lancelot; Hénaff, Patrick
2018-01-01
It is well-known that human social interactions generate synchrony phenomena which are often unconscious. If the interaction between individuals is based on rhythmic movements, synchronized and coordinated movements will emerge from the social synchrony. This paper proposes a plausible model of plastic neural controllers that allows the emergence of synchronized movements in physical and rhythmical interactions. The controller is designed with central pattern generators (CPG) based on rhythmic Rowat-Selverston neurons endowed with neuronal and synaptic Hebbian plasticity. To demonstrate the interest of the proposed model, the case of handshaking is considered because it is a very common, both physically and socially, but also, a very complex act in the point of view of robotics, neuroscience and psychology. Plastic CPGs controllers are implemented in the joints of a simulated robotic arm that has to learn the frequency and amplitude of an external force applied to its effector, thus reproducing the act of handshaking with a human. Results show that the neural and synaptic Hebbian plasticity are working together leading to a natural and autonomous synchronization between the arm and the external force even if the frequency is changing during the movement. Moreover, a power consumption analysis shows that, by offering emergence of synchronized and coordinated movements, the plasticity mechanisms lead to a significant decrease in the energy spend by the robot actuators thus generating a more adaptive and natural human/robot handshake.
Li, Li; MaBouDi, HaDi; Egertová, Michaela; Elphick, Maurice R.
2017-01-01
Synaptic plasticity is considered to be a basis for learning and memory. However, the relationship between synaptic arrangements and individual differences in learning and memory is poorly understood. Here, we explored how the density of microglomeruli (synaptic complexes) within specific regions of the bumblebee (Bombus terrestris) brain relates to both visual learning and inter-individual differences in learning and memory performance on a visual discrimination task. Using whole-brain immunolabelling, we measured the density of microglomeruli in the collar region (visual association areas) of the mushroom bodies of the bumblebee brain. We found that bumblebees which made fewer errors during training in a visual discrimination task had higher microglomerular density. Similarly, bumblebees that had better retention of the learned colour-reward associations two days after training had higher microglomerular density. Further experiments indicated experience-dependent changes in neural circuitry: learning a colour-reward contingency with 10 colours (but not two colours) does result, and exposure to many different colours may result, in changes to microglomerular density in the collar region of the mushroom bodies. These results reveal the varying roles that visual experience, visual learning and foraging activity have on neural structure. Although our study does not provide a causal link between microglomerular density and performance, the observed positive correlations provide new insights for future studies into how neural structure may relate to inter-individual differences in learning and memory. PMID:28978727
Li, Li; MaBouDi, HaDi; Egertová, Michaela; Elphick, Maurice R; Chittka, Lars; Perry, Clint J
2017-10-11
Synaptic plasticity is considered to be a basis for learning and memory. However, the relationship between synaptic arrangements and individual differences in learning and memory is poorly understood. Here, we explored how the density of microglomeruli (synaptic complexes) within specific regions of the bumblebee ( Bombus terrestris ) brain relates to both visual learning and inter-individual differences in learning and memory performance on a visual discrimination task. Using whole-brain immunolabelling, we measured the density of microglomeruli in the collar region (visual association areas) of the mushroom bodies of the bumblebee brain. We found that bumblebees which made fewer errors during training in a visual discrimination task had higher microglomerular density. Similarly, bumblebees that had better retention of the learned colour-reward associations two days after training had higher microglomerular density. Further experiments indicated experience-dependent changes in neural circuitry: learning a colour-reward contingency with 10 colours (but not two colours) does result, and exposure to many different colours may result, in changes to microglomerular density in the collar region of the mushroom bodies. These results reveal the varying roles that visual experience, visual learning and foraging activity have on neural structure. Although our study does not provide a causal link between microglomerular density and performance, the observed positive correlations provide new insights for future studies into how neural structure may relate to inter-individual differences in learning and memory. © 2017 The Authors.
Zhou, Xin; Fu, Xin; Lin, Chun; Zhou, Xiaojuan; Liu, Jin; Wang, Li; Zhang, Xinwen; Zuo, Mingxue; Fan, Xiaolong; Li, Dapeng; Sun, Yingyu
2017-05-01
Deafening elicits a deterioration of learned vocalization, in both humans and songbirds. In songbirds, learned vocal plasticity has been shown to depend on the basal ganglia-cortical circuit, but the underlying cellular basis remains to be clarified. Using confocal imaging and electron microscopy, we examined the effect of deafening on dendritic spines in avian vocal motor cortex, the robust nucleus of the arcopallium (RA), and investigated the role of the basal ganglia circuit in motor cortex plasticity. We found rapid structural changes to RA dendritic spines in response to hearing loss, accompanied by learned song degradation. In particular, the morphological characters of RA spine synaptic contacts between 2 major pathways were altered differently. However, experimental disruption of the basal ganglia circuit, through lesions in song-specialized basal ganglia nucleus Area X, largely prevented both the observed changes to RA dendritic spines and the song deterioration after hearing loss. Our results provide cellular evidence to highlight a key role of the basal ganglia circuit in the motor cortical plasticity that underlies learned vocal plasticity. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Maass, Wolfgang
2008-01-01
Reward-modulated spike-timing-dependent plasticity (STDP) has recently emerged as a candidate for a learning rule that could explain how behaviorally relevant adaptive changes in complex networks of spiking neurons could be achieved in a self-organizing manner through local synaptic plasticity. However, the capabilities and limitations of this learning rule could so far only be tested through computer simulations. This article provides tools for an analytic treatment of reward-modulated STDP, which allows us to predict under which conditions reward-modulated STDP will achieve a desired learning effect. These analytical results imply that neurons can learn through reward-modulated STDP to classify not only spatial but also temporal firing patterns of presynaptic neurons. They also can learn to respond to specific presynaptic firing patterns with particular spike patterns. Finally, the resulting learning theory predicts that even difficult credit-assignment problems, where it is very hard to tell which synaptic weights should be modified in order to increase the global reward for the system, can be solved in a self-organizing manner through reward-modulated STDP. This yields an explanation for a fundamental experimental result on biofeedback in monkeys by Fetz and Baker. In this experiment monkeys were rewarded for increasing the firing rate of a particular neuron in the cortex and were able to solve this extremely difficult credit assignment problem. Our model for this experiment relies on a combination of reward-modulated STDP with variable spontaneous firing activity. Hence it also provides a possible functional explanation for trial-to-trial variability, which is characteristic for cortical networks of neurons but has no analogue in currently existing artificial computing systems. In addition our model demonstrates that reward-modulated STDP can be applied to all synapses in a large recurrent neural network without endangering the stability of the network dynamics. PMID:18846203
Zagrebelsky, Marta; Lonnemann, Niklas; Fricke, Steffen; Kellner, Yves; Preuß, Eike; Michaelsen-Preusse, Kristin; Korte, Martin
2017-02-01
Behavioral learning has been shown to involve changes in the function and structure of synaptic connections of the central nervous system (CNS). On the other hand, the neuronal circuitry in the mature brain is characterized by a high degree of stability possibly providing a correlate for long-term storage of information. This observation indicates the requirement for a set of molecules inhibiting plasticity and promoting stability thereby providing temporal and spatial specificity to plastic processes. Indeed, signaling of Nogo-A via its receptors has been shown to play a crucial role in restricting activity-dependent functional and structural plasticity in the adult CNS. However, whether Nogo-A controls learning and memory formation and what are the cellular and molecular mechanisms underlying this function is still unclear. Here we show that Nogo-A signaling controls spatial learning and reference memory formation upon training in the Morris water maze and negatively modulates structural changes at spines in the mouse hippocampus. Learning processes and the correlated structural plasticity have been shown to involve changes in excitatory as well as in inhibitory neuronal connections. We show here that Nogo-A is highly expressed not only in excitatory, but also in inhibitory, Parvalbumin positive neurons in the adult hippocampus. By this means our current and previous data indicate that Nogo-A loss-of-function positively influences spatial learning by priming the neuronal structure to a higher plasticity level. Taken together our results link the role of Nogo-A in negatively regulating plastic processes to a physiological function in controlling learning and memory processes in the mature hippocampus and open the interesting possibility that it might mainly act by controlling the function of the hippocampal inhibitory circuitry. Copyright © 2016 Elsevier Inc. All rights reserved.
Wang, Quan; Rothkopf, Constantin A; Triesch, Jochen
2017-08-01
The ability to learn sequential behaviors is a fundamental property of our brains. Yet a long stream of studies including recent experiments investigating motor sequence learning in adult human subjects have produced a number of puzzling and seemingly contradictory results. In particular, when subjects have to learn multiple action sequences, learning is sometimes impaired by proactive and retroactive interference effects. In other situations, however, learning is accelerated as reflected in facilitation and transfer effects. At present it is unclear what the underlying neural mechanism are that give rise to these diverse findings. Here we show that a recently developed recurrent neural network model readily reproduces this diverse set of findings. The self-organizing recurrent neural network (SORN) model is a network of recurrently connected threshold units that combines a simplified form of spike-timing dependent plasticity (STDP) with homeostatic plasticity mechanisms ensuring network stability, namely intrinsic plasticity (IP) and synaptic normalization (SN). When trained on sequence learning tasks modeled after recent experiments we find that it reproduces the full range of interference, facilitation, and transfer effects. We show how these effects are rooted in the network's changing internal representation of the different sequences across learning and how they depend on an interaction of training schedule and task similarity. Furthermore, since learning in the model is based on fundamental neuronal plasticity mechanisms, the model reveals how these plasticity mechanisms are ultimately responsible for the network's sequence learning abilities. In particular, we find that all three plasticity mechanisms are essential for the network to learn effective internal models of the different training sequences. This ability to form effective internal models is also the basis for the observed interference and facilitation effects. This suggests that STDP, IP, and SN may be the driving forces behind our ability to learn complex action sequences.
Daroles, Laura; Gribaudo, Simona; Doulazmi, Mohamed; Scotto-Lomassese, Sophie; Dubacq, Caroline; Mandairon, Nathalie; Greer, Charles August; Didier, Anne; Trembleau, Alain; Caillé, Isabelle
2016-07-15
In the adult brain, structural plasticity allowing gain or loss of synapses remodels circuits to support learning. In fragile X syndrome, the absence of fragile X mental retardation protein (FMRP) leads to defects in plasticity and learning deficits. FMRP is a master regulator of local translation but its implication in learning-induced structural plasticity is unknown. Using an olfactory learning task requiring adult-born olfactory bulb neurons and cell-specific ablation of FMRP, we investigated whether learning shapes adult-born neuron morphology during their synaptic integration and its dependence on FMRP. We used alpha subunit of the calcium/calmodulin-dependent kinase II (αCaMKII) mutant mice with altered dendritic localization of αCaMKII messenger RNA, as well as a reporter of αCaMKII local translation to investigate the role of this FMRP messenger RNA target in learning-dependent structural plasticity. Learning induces profound changes in dendritic architecture and spine morphology of adult-born neurons that are prevented by ablation of FMRP in adult-born neurons and rescued by an metabotropic glutamate receptor 5 antagonist. Moreover, dendritically translated αCaMKII is necessary for learning and associated structural modifications and learning triggers an FMRP-dependent increase of αCaMKII dendritic translation in adult-born neurons. Our results strongly suggest that FMRP mediates structural plasticity of olfactory bulb adult-born neurons to support olfactory learning through αCaMKII local translation. This reveals a new role for FMRP-regulated dendritic local translation in learning-induced structural plasticity. This might be of clinical relevance for the understanding of critical periods disruption in autism spectrum disorder patients, among which fragile X syndrome is the primary monogenic cause. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.
The Ubiquitin-Specific Protease 14 (USP14) Is a Critical Regulator of Long-Term Memory Formation
ERIC Educational Resources Information Center
Jarome, Timothy J.; Kwapis, Janine L.; Hallengren, Jada J.; Wilson, Scott M.; Helmstetter, Fred J.
2014-01-01
Numerous studies have suggested a role for ubiquitin-proteasome-mediated protein degradation in learning-dependent synaptic plasticity; however, very little is known about how protein degradation is regulated at the level of the proteasome during memory formation. The ubiquitin-specific protease 14 (USP14) is a proteasomal deubiquitinating enzyme…
ERIC Educational Resources Information Center
Kodirov, Sodikdjon A.; Jasiewicz, Julia; Amirmahani, Parisa; Psyrakis, Dimitrios; Bonni, Kathrin; Wehrmeister, Michael; Lutz, Beat
2010-01-01
The amygdala is a key area of the brain where the emotional memories are stored throughout the lifespan. It is well established that synapses in the lateral nucleus of amygdala (LA) can undergo long-term potentiation, a putative cellular correlate of learning and memory. However, a type of short-term synaptic plasticity, known as…
Effect of Sirtuin-1 on Synaptic Plasticity in Nucleus Accumbens in a Rat Model of Heroin Addiction.
Xia, Baijuan; Li, Yixin; Li, Rongrong; Yin, Dan; Chen, Xingqiang; Li, Jie; Liang, Wenmei
2018-06-05
BACKGROUND Synaptic plasticity plays an important role in the process of addiction. This study investigated the relationship between synaptic plasticity and changes in addictive behavior and examined the expression of synaptic plasticity-associated proteins and genes in the nucleus accumbens (NAc) region in different rat models. MATERIAL AND METHODS Heroin addiction, SIRT1-overexpression, and SIRT1-silenced rat models were established. Polymerase chain reaction gene chip technology, immunohistochemistry, Western blotting, and transmission electron microscopy were used to detect changes in synaptic plasticity-related gene and protein expression, and changes in the ultrastructure of synapses, in the NAc. RESULTS Naloxone withdrawal symptoms appeared in the SIRT1-overexpression group. In the SIRT1-silenced group the symptoms were reduced. Immunohistochemistry and Western blotting results showed that FOXO1 expression decreased in the heroin addiction (HA) group but increased in the SIRT1-silenced group (p<0.05). The expression of Cdk5, Nf-κB, PSD95, and Syn was enhanced in the HA group (p<0.05) and further increased in the SIRT1-overexpression group but were reduced in the SIRT1-silenced group (p<0.05). The number of synapses increased in the HA group (p<0.05) along with mitochondrial swelling in the presynaptic membrane and obscuring of the synaptic cleft. CONCLUSIONS SIRT1 and other synaptic plasticity-related genes in NAc are involved in the regulation of heroin addiction. SIRT1 overexpression can increase behavioral sensitization in the NAc of rats, and SIRT1 silencing might ease withdrawal symptoms and reduce conditioned place preferences.
The protein kinase Mζ network as a bistable switch to store neuronal memory.
Ogasawara, Hideaki; Kawato, Mitsuo
2010-12-31
Protein kinase Mζ (PKMζ), the brain-specific, atypical protein kinase C isoform, plays a key role in long-term maintenance of memory. This molecule is essential for long-term potentiation of the neuron and various modalities of learning such as spatial memory and fear conditioning. It is unknown, however, how PKMζ stores information for long periods of time despite molecular turnover. We hypothesized that PKMζ forms a bistable switch because it appears to constitute a positive feedback loop (PKMζ induces its local synthesis) part of which is ultrasensitive (PKMζ stimulates its synthesis through dual pathways). To examine this hypothesis, we modeled the biochemical network of PKMζ with realistic kinetic parameters. Bifurcation analyses of the model showed that the system maintains either the up state or the down state according to previous inputs. Furthermore, the model was able to reproduce a variety of previous experimental results regarding synaptic plasticity and learning, which suggested that it captures the essential mechanism for neuronal memory. We proposed in vitro and in vivo experiments that would critically examine the validity of the model and illuminate the pivotal role of PKMζ in synaptic plasticity and learning. This study revealed bistability of the PKMζ network and supported its pivotal role in long-term storage of memory.
Qi, Z; Kikuchi, S; Tretter, F; Voit, E O
2011-05-01
Major depressive disorder (MDD) affects about 16% of the general population and is a leading cause of death in the United States and around the world. Aggravating the situation is the fact that "drug use disorders" are highly comorbid in MDD patients, and VICE VERSA. Drug use and MDD share a common component, the dopamine system, which is critical in many motivation and reward processes, as well as in the regulation of stress responses in MDD. A potentiating mechanism in drug use disorders appears to be synaptic plasticity, which is regulated by dopamine transmission. In this article, we describe a computational model of the synaptic plasticity of GABAergic medium spiny neurons in the nucleus accumbens, which is critical in the reward system. The model accounts for effects of both dopamine and glutamate transmission. Model simulations show that GABAergic medium spiny neurons tend to respond to dopamine stimuli with synaptic potentiation and to glutamate signals with synaptic depression. Concurrent dopamine and glutamate signals cause various types of synaptic plasticity, depending on input scenarios. Interestingly, the model shows that a single 0.5 mg/kg dose of amphetamine can cause synaptic potentiation for over 2 h, a phenomenon that makes synaptic plasticity of medium spiny neurons behave quasi as a bistable system. The model also identifies mechanisms that could potentially be critical to correcting modifications of synaptic plasticity caused by drugs in MDD patients. An example is the feedback loop between protein kinase A, phosphodiesterase, and the second messenger cAMP in the postsynapse. Since reward mechanisms activated by psychostimulants could be crucial in establishing addiction comorbidity in patients with MDD, this model might become an aid for identifying and targeting specific modules within the reward system and lead to a better understanding and potential treatment of comorbid drug use disorders in MDD. © Georg Thieme Verlag KG Stuttgart · New York.
ERIC Educational Resources Information Center
Hawkins, Robert D.
2013-01-01
Recent studies in "Aplysia" have identified a new variation of synaptic plasticity in which modulatory transmitters enhance spontaneous release of glutamate, which then acts on postsynaptic receptors to recruit mechanisms of intermediate- and long-term plasticity. In this review I suggest the hypothesis that similar plasticity occurs in…
Ortiz-Matamoros, Abril; Salcedo-Tello, Pamela; Avila-Muñoz, Evangelina; Zepeda, Angélica; Arias, Clorinda
2013-01-01
It is well recognized the role of the Wnt pathway in many developmental processes such as neuronal maturation, migration, neuronal connectivity and synaptic formation. Growing evidence is also demonstrating its function in the mature brain where is associated with modulation of axonal remodeling, dendrite outgrowth, synaptic activity, neurogenesis and behavioral plasticity. Proteins involved in Wnt signaling have been found expressed in the adult hippocampus suggesting that Wnt pathway plays a role in the hippocampal function through life. Indeed, Wnt ligands act locally to regulate neurogenesis, neuronal cell shape and pre- and postsynaptic assembly, events that are thought to underlie changes in synaptic function associated with long-term potentiation and with cognitive tasks such as learning and memory. Recent data have demonstrated the increased expression of the Wnt antagonist Dickkopf-1 (DKK1) in brains of Alzheimer´s disease (AD) patients suggesting that dysfunction of Wnt signaling could also contribute to AD pathology. We review here evidence of Wnt-associated molecules expression linked to physiological and pathological hippocampal functioning in the adult brain. The basic aspects of Wnt related mechanisms underlying hippocampal plasticity as well as evidence of how hippocampal dysfunction may rely on Wnt dysregulation is analyzed. This information would provide some clues about the possible therapeutic targets for developing treatments for neurodegenerative diseases associated with aberrant brain plasticity. PMID:24403870
Ortiz-Matamoros, Abril; Salcedo-Tello, Pamela; Avila-Muñoz, Evangelina; Zepeda, Angélica; Arias, Clorinda
2013-09-01
It is well recognized the role of the Wnt pathway in many developmental processes such as neuronal maturation, migration, neuronal connectivity and synaptic formation. Growing evidence is also demonstrating its function in the mature brain where is associated with modulation of axonal remodeling, dendrite outgrowth, synaptic activity, neurogenesis and behavioral plasticity. Proteins involved in Wnt signaling have been found expressed in the adult hippocampus suggesting that Wnt pathway plays a role in the hippocampal function through life. Indeed, Wnt ligands act locally to regulate neurogenesis, neuronal cell shape and pre- and postsynaptic assembly, events that are thought to underlie changes in synaptic function associated with long-term potentiation and with cognitive tasks such as learning and memory. Recent data have demonstrated the increased expression of the Wnt antagonist Dickkopf-1 (DKK1) in brains of Alzheimer´s disease (AD) patients suggesting that dysfunction of Wnt signaling could also contribute to AD pathology. We review here evidence of Wnt-associated molecules expression linked to physiological and pathological hippocampal functioning in the adult brain. The basic aspects of Wnt related mechanisms underlying hippocampal plasticity as well as evidence of how hippocampal dysfunction may rely on Wnt dysregulation is analyzed. This information would provide some clues about the possible therapeutic targets for developing treatments for neurodegenerative diseases associated with aberrant brain plasticity.
Gating of Long-Term Potentiation by Nicotinic Acetylcholine Receptors at the Cerebellum Input Stage
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
Cognitive Neuroscience of Sleep
Poe, Gina R.; Walsh, Christine M.; Bjorness, Theresa E.
2014-01-01
Mechanism is at the heart of understanding, and this chapter addresses underlying brain mechanisms and pathways of cognition and the impact of sleep on these processes, especially those serving learning and memory. This chapter reviews the current understanding of the relationship between sleep/waking states and cognition from the perspective afforded by basic neurophysiological investigations. The extensive overlap between sleep mechanisms and the neurophysiology of learning and memory processes provide a foundation for theories of a functional link between the sleep and learning systems. Each of the sleep states, with its attendant alterations in neurophysiology, is associated with facilitation of important functional learning and memory processes. For rapid eye movement (REM) sleep, salient features such as PGO waves, theta synchrony, increased acetylcholine, reduced levels of monoamines and, within the neuron, increased transcription of plasticity-related genes, cumulatively allow for freely occurring bidirectional plasticity (long-term potentiation (LTP) and its reversal, depotentiation). Thus, REM sleep provides a novel neural environment in which the synaptic remodeling essential to learning and cognition can occur, at least within the hippocampal complex. During nonREM sleep Stage 2 spindles, the cessation and subsequent strong bursting of noradrenergic cells and coincident reactivation of hippocampal and cortical targets would also increase synaptic plasticity, allowing targeted bidirectional plasticity in the neocortex as well. In delta nonREM sleep, orderly neuronal reactivation events in phase with slow wave delta activity, together with high protein synthesis levels, would facilitate the events that convert early LTP to long lasting LTP. Conversely, delta sleep does not activate immediate early genes associated with de novo LTP. This nonREM sleep-unique genetic environment combined with low acetylcholine levels may serve to reduce the strength of cortical circuits that activate in the ~50% of delta-coincident reactivation events that do not appear in their waking firing sequence. The chapter reviews the results of manipulation studies, typically total sleep or REM sleep deprivation, that serve to underscore the functional significance of the phenomenological associations. Finally, the implications of sleep neurophysiology for learning and memory will be considered from a larger perspective in which the association of specific sleep states with both potentiation or depotentiation is integrated into mechanistic models of cognition. PMID:21075230
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.
Liu, Mengying; Huangfu, Xuhong; Zhao, Yangang; Zhang, Dongmei; Zhang, Jiqiang
2015-11-01
Hippocampus local estrogen which is converted from androgen that catalyzed by aromatase has been shown to play important roles in the regulation of learning and memory as well as cognition through action on synaptic plasticity, but the underlying mechanisms are poorly understood. Steroid receptor coactivator-1 (SRC-1) is one of the coactivators of steroid nuclear receptors; it is widely distributed in brain areas that related to learning and memory, reproductive regulation, sensory and motor information integration. Previous studies have revealed high levels of SRC-1 immunoreactivities in the hippocampus; it is closely related to the levels of synaptic proteins such as PSD-95 under normal development or gonadectomy, but its exact roles in the regulation of these proteins remains unclear. In this study, we used aromatase inhibitor letrozole in vivo and SRC-1 RNA interference in vitro to investigate whether SRC-1 mediated endogenous estrogen regulation of hippocampal PSD-95. The results revealed that letrozole injection synchronously decreased hippocampal SRC-1 and PSD-95 in a dose-dependant manner. Furthermore, when SRC-1 specific shRNA pool was applied to block the expression of SRC-1 in the primary hippocampal neuron culture, both immunocytochemistry and Western blot revealed that levels of PSD-95 were also decreased significantly. Taking together, these results provided the first evidence that SRC-1 mediated endogenous estrogen regulation of hippocampal synaptic plasticity by targeting the expression of synaptic protein PSD-95. Additionally, since letrozole is frequently used to treat estrogen-sensitive breast cancer, the above results also indicate its potential side effects in clinical administration. Copyright © 2015 Elsevier Ltd. All rights reserved.
Differential splicing and glycosylation of Apoer2 alters synaptic plasticity and fear learning.
Wasser, Catherine R; Masiulis, Irene; Durakoglugil, Murat S; Lane-Donovan, Courtney; Xian, Xunde; Beffert, Uwe; Agarwala, Anandita; Hammer, Robert E; Herz, Joachim
2014-11-25
Apoer2 is an essential receptor in the central nervous system that binds to the apolipoprotein ApoE. Various splice variants of Apoer2 are produced. We showed that Apoer2 lacking exon 16, which encodes the O-linked sugar (OLS) domain, altered the proteolytic processing and abundance of Apoer2 in cells and synapse number and function in mice. In cultured cells expressing this splice variant, extracellular cleavage of OLS-deficient Apoer2 was reduced, consequently preventing γ-secretase-dependent release of the intracellular domain of Apoer2. Mice expressing Apoer2 lacking the OLS domain had increased Apoer2 abundance in the brain, hippocampal spine density, and glutamate receptor abundance, but decreased synaptic efficacy. Mice expressing a form of Apoer2 lacking the OLS domain and containing an alternatively spliced cytoplasmic tail region that promotes glutamate receptor signaling showed enhanced hippocampal long-term potentiation (LTP), a phenomenon associated with learning and memory. However, these mice did not display enhanced spatial learning in the Morris water maze, and cued fear conditioning was reduced. Reducing the expression of the mutant Apoer2 allele so that the abundance of the protein was similar to that of Apoer2 in wild-type mice normalized spine density, hippocampal LTP, and cued fear learning. These findings demonstrated a role for ApoE receptors as regulators of synaptic glutamate receptor activity and established differential receptor glycosylation as a potential regulator of synaptic function and memory. Copyright © 2014, American Association for the Advancement of Science.
Differential splicing and glycosylation of Apoer2 alters synaptic plasticity and fear learning
Wasser, Catherine R.; Masiulis, Irene; Durakoglugil, Murat S.; Lane-Donovan, Courtney; Xian, Xunde; Beffert, Uwe; Agarwala, Anandita; Hammer, Robert E.; Herz, Joachim
2015-01-01
Apoer2 is an essential receptor in the central nervous system that binds to the apolipoprotein ApoE. Various splice variants of Apoer2 are produced. We showed that Apoer2 lacking exon 16, which encodes the O-linked sugar (OLS) domain, altered the proteolytic processing and abundance of Apoer2 in cells and synapse number and function in mice. In cultured cells expressing this splice variant, extracellular cleavage of OLS-deficient Apoer2 was reduced, consequently preventing γ-secretase-dependent release of the intracellular domain of Apoer2. Mice expressing Apoer2 lacking the OLS domain had increased Apoer2 abundance in the brain, hippocampal spine density, and glutamate receptor abundance, but decreased synaptic efficacy. Mice expressing a form of Apoer2 lacking the OLS domain and containing an alternatively spliced cytoplasmic tail region that promotes glutamate receptor signaling showed enhanced hippocampal long-term potentiation (LTP), a phenomenon associated with learning and memory. However, these mice did not display enhanced spatial learning in the Morris water maze, and cued fear conditioning was reduced. Reducing the expression of the mutant Apoer2 allele so that the abundance of the protein was similar to that of Apoer2 in wild-type mice normalized spine density, hippocampal LTP, and cued fear learning. These findings demonstrated a role for ApoE receptors as regulators of synaptic glutamate receptor activity and established differential receptor glycosylation as a potential regulator of synaptic function and memory. PMID:25429077
Distinct cerebellar engrams in short-term and long-term motor learning.
Wang, Wen; Nakadate, Kazuhiko; Masugi-Tokita, Miwako; Shutoh, Fumihiro; Aziz, Wajeeha; Tarusawa, Etsuko; Lorincz, Andrea; Molnár, Elek; Kesaf, Sebnem; Li, Yun-Qing; Fukazawa, Yugo; Nagao, Soichi; Shigemoto, Ryuichi
2014-01-07
Cerebellar motor learning is suggested to be caused by long-term plasticity of excitatory parallel fiber-Purkinje cell (PF-PC) synapses associated with changes in the number of synaptic AMPA-type glutamate receptors (AMPARs). However, whether the AMPARs decrease or increase in individual PF-PC synapses occurs in physiological motor learning and accounts for memory that lasts over days remains elusive. We combined quantitative SDS-digested freeze-fracture replica labeling for AMPAR and physical dissector electron microscopy with a simple model of cerebellar motor learning, adaptation of horizontal optokinetic response (HOKR) in mouse. After 1-h training of HOKR, short-term adaptation (STA) was accompanied with transient decrease in AMPARs by 28% in target PF-PC synapses. STA was well correlated with AMPAR decrease in individual animals and both STA and AMPAR decrease recovered to basal levels within 24 h. Surprisingly, long-term adaptation (LTA) after five consecutive daily trainings of 1-h HOKR did not alter the number of AMPARs in PF-PC synapses but caused gradual and persistent synapse elimination by 45%, with corresponding PC spine loss by the fifth training day. Furthermore, recovery of LTA after 2 wk was well correlated with increase of PF-PC synapses to the control level. Our findings indicate that the AMPARs decrease in PF-PC synapses and the elimination of these synapses are in vivo engrams in short- and long-term motor learning, respectively, showing a unique type of synaptic plasticity that may contribute to memory consolidation.
ERIC Educational Resources Information Center
Dong, Chenghai; Upadhya, Sudarshan C.; Ding, Lan; Smith, Thuy K.; Hegde, Ashok N.
2008-01-01
Protein degradation by the ubiquitin-proteasome pathway plays important roles in synaptic plasticity, but the molecular mechanisms by which proteolysis regulates synaptic strength are not well understood. We investigated the role of the proteasome in hippocampal late-phase long-term potentiation (L-LTP), a model for enduring synaptic plasticity.…
Chronic Ampakine Treatments Stimulate Dendritic Growth and Promote Learning in Middle-Aged Rats.
Lauterborn, Julie C; Palmer, Linda C; Jia, Yousheng; Pham, Danielle T; Hou, Bowen; Wang, Weisheng; Trieu, Brian H; Cox, Conor D; Kantorovich, Svetlana; Gall, Christine M; Lynch, Gary
2016-02-03
Positive allosteric modulators of AMPA-type glutamate receptors (ampakines) have been shown to rescue synaptic plasticity and reduce neuropathology in rodent models of cognitive disorders. Here we tested whether chronic ampakine treatment offsets age-related dendritic retraction in middle-aged (MA) rats. Starting at 10 months of age, rats were housed in an enriched environment and given daily treatment with a short half-life ampakine or vehicle for 3 months. Dendritic branching and spine measures were collected from 3D reconstructions of Lucifer yellow-filled CA1 pyramidal cells. There was a substantial loss of secondary branches, relative to enriched 2.5-month-old rats, in apical and basal dendritic fields of vehicle-treated, but not ampakine-treated, 13-month-old rats. Baseline synaptic responses in CA1 were only subtly different between the two MA groups, but long-term potentiation was greater in ampakine-treated rats. Unsupervised learning of a complex environment was used to assess treatment effects on behavior. Vehicle- and drug-treated rats behaved similarly during a first 30 min session in the novel environment but differed markedly on subsequent measures of long-term memory. Markov sequence analysis uncovered a clear increase in the predictability of serial movements between behavioral sessions 2 and 3 in the ampakine, but not vehicle, group. These results show that a surprising degree of dendritic retraction occurs by middle age and that this can be mostly offset by pharmacological treatments without evidence for unwanted side effects. The functional consequences of rescue were prominent with regard to memory but also extended to self-organization of behavior. Brain aging is characterized by a progressive loss of dendritic arbors and the emergence of impairments to learning-related synaptic plasticity. The present studies show that dendritic losses are evident by middle age despite housing in an enriched environment and can be mostly reversed by long-term, oral administration of a positive allosteric modulator of AMPA-type glutamate receptors. Dendritic recovery was accompanied by improvements to both synaptic plasticity and the encoding of long-term memory of a novel, complex environment. Because the short half-life compound had no evident negative effects, the results suggest a plausible strategy for treating age-related neuronal deterioration. Copyright © 2016 the authors 0270-6474/16/361636-11$15.00/0.
Chronic Ampakine Treatments Stimulate Dendritic Growth and Promote Learning in Middle-Aged Rats
Lauterborn, Julie C.; Palmer, Linda C.; Jia, Yousheng; Pham, Danielle T.; Hou, Bowen; Wang, Weisheng; Trieu, Brian H.; Cox, Conor D.; Kantorovich, Svetlana
2016-01-01
Positive allosteric modulators of AMPA-type glutamate receptors (ampakines) have been shown to rescue synaptic plasticity and reduce neuropathology in rodent models of cognitive disorders. Here we tested whether chronic ampakine treatment offsets age-related dendritic retraction in middle-aged (MA) rats. Starting at 10 months of age, rats were housed in an enriched environment and given daily treatment with a short half-life ampakine or vehicle for 3 months. Dendritic branching and spine measures were collected from 3D reconstructions of Lucifer yellow-filled CA1 pyramidal cells. There was a substantial loss of secondary branches, relative to enriched 2.5-month-old rats, in apical and basal dendritic fields of vehicle-treated, but not ampakine-treated, 13-month-old rats. Baseline synaptic responses in CA1 were only subtly different between the two MA groups, but long-term potentiation was greater in ampakine-treated rats. Unsupervised learning of a complex environment was used to assess treatment effects on behavior. Vehicle- and drug-treated rats behaved similarly during a first 30 min session in the novel environment but differed markedly on subsequent measures of long-term memory. Markov sequence analysis uncovered a clear increase in the predictability of serial movements between behavioral sessions 2 and 3 in the ampakine, but not vehicle, group. These results show that a surprising degree of dendritic retraction occurs by middle age and that this can be mostly offset by pharmacological treatments without evidence for unwanted side effects. The functional consequences of rescue were prominent with regard to memory but also extended to self-organization of behavior. SIGNIFICANCE STATEMENT Brain aging is characterized by a progressive loss of dendritic arbors and the emergence of impairments to learning-related synaptic plasticity. The present studies show that dendritic losses are evident by middle age despite housing in an enriched environment and can be mostly reversed by long-term, oral administration of a positive allosteric modulator of AMPA-type glutamate receptors. Dendritic recovery was accompanied by improvements to both synaptic plasticity and the encoding of long-term memory of a novel, complex environment. Because the short half-life compound had no evident negative effects, the results suggest a plausible strategy for treating age-related neuronal deterioration. PMID:26843645
Learning and memory disabilities in IUGR babies: Functional and molecular analysis in a rat model.
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.
Network, cellular, and molecular mechanisms underlying long-term memory formation.
Carasatorre, Mariana; Ramírez-Amaya, Víctor
2013-01-01
The neural network stores information through activity-dependent synaptic plasticity that occurs in populations of neurons. Persistent forms of synaptic plasticity may account for long-term memory storage, and the most salient forms are the changes in the structure of synapses. The theory proposes that encoding should use a sparse code and evidence suggests that this can be achieved through offline reactivation or by sparse initial recruitment of the network units. This idea implies that in some cases the neurons that underwent structural synaptic plasticity might be a subpopulation of those originally recruited; However, it is not yet clear whether all the neurons recruited during acquisition are the ones that underwent persistent forms of synaptic plasticity and responsible for memory retrieval. To determine which neural units underlie long-term memory storage, we need to characterize which are the persistent forms of synaptic plasticity occurring in these neural ensembles and the best hints so far are the molecular signals underlying structural modifications of the synapses. Structural synaptic plasticity can be achieved by the activity of various signal transduction pathways, including the NMDA-CaMKII and ACh-MAPK. These pathways converge with the Rho family of GTPases and the consequent ERK 1/2 activation, which regulates multiple cellular functions such as protein translation, protein trafficking, and gene transcription. The most detailed explanation may come from models that allow us to determine the contribution of each piece of this fascinating puzzle that is the neuron and the neural network.
Wu, Aiguo; Ying, Zhe; Schubert, David; Gomez-Pinilla, Fernando
2011-05-01
In addition to cognitive dysfunction, locomotor deficits are prevalent in traumatic brain injured (TBI) patients; however, it is unclear how a concussive injury can affect spinal cord centers. Moreover, there are no current efficient treatments that can counteract the broad pathology associated with TBI. The authors have investigated potential molecular basis for the disruptive effects of TBI on spinal cord and hippocampus and the neuroprotection of a curcumin derivative to reduce the effects of experimental TBI. The authors performed fluid percussion injury (FPI) and then rats were exposed to dietary supplementation of the curcumin derivative (CNB-001; 500 ppm). The curry spice curcumin has protective capacity in animal models of neurodegenerative diseases, and the curcumin derivative has enhanced brain absorption and biological activity. The results show that FPI in rats, in addition to reducing learning ability, reduced locomotor performance. Behavioral deficits were accompanied by reductions in molecular systems important for synaptic plasticity underlying behavioral plasticity in the brain and spinal cord. The post-TBI dietary supplementation of the curcumin derivative normalized levels of BDNF, and its downstream effectors on synaptic plasticity (CREB, synapsin I) and neuronal signaling (CaMKII), as well as levels of oxidative stress-related molecules (SOD, Sir2). These studies define a mechanism by which TBI can compromise centers related to cognitive processing and locomotion. The findings also show the influence of the curcumin derivative on synaptic plasticity events in the brain and spinal cord and emphasize the therapeutic potential of this noninvasive dietary intervention for TBI.
Reinforcement learning of targeted movement in a spiking neuronal model of motor cortex.
Chadderdon, George L; Neymotin, Samuel A; Kerr, Cliff C; Lytton, William W
2012-01-01
Sensorimotor control has traditionally been considered from a control theory perspective, without relation to neurobiology. In contrast, here we utilized a spiking-neuron model of motor cortex and trained it to perform a simple movement task, which consisted of rotating a single-joint "forearm" to a target. Learning was based on a reinforcement mechanism analogous to that of the dopamine system. This provided a global reward or punishment signal in response to decreasing or increasing distance from hand to target, respectively. Output was partially driven by Poisson motor babbling, creating stochastic movements that could then be shaped by learning. The virtual forearm consisted of a single segment rotated around an elbow joint, controlled by flexor and extensor muscles. The model consisted of 144 excitatory and 64 inhibitory event-based neurons, each with AMPA, NMDA, and GABA synapses. Proprioceptive cell input to this model encoded the 2 muscle lengths. Plasticity was only enabled in feedforward connections between input and output excitatory units, using spike-timing-dependent eligibility traces for synaptic credit or blame assignment. Learning resulted from a global 3-valued signal: reward (+1), no learning (0), or punishment (-1), corresponding to phasic increases, lack of change, or phasic decreases of dopaminergic cell firing, respectively. Successful learning only occurred when both reward and punishment were enabled. In this case, 5 target angles were learned successfully within 180 s of simulation time, with a median error of 8 degrees. Motor babbling allowed exploratory learning, but decreased the stability of the learned behavior, since the hand continued moving after reaching the target. Our model demonstrated that a global reinforcement signal, coupled with eligibility traces for synaptic plasticity, can train a spiking sensorimotor network to perform goal-directed motor behavior.
Fontán-Lozano, Angela; Suárez-Pereira, Irene; Delgado-García, José María; Carrión, Angel Manuel
2011-01-01
Aging, mental retardation, number of psychiatric and neurological disorders are all associated with learning and memory impairments. As the underlying causes of such conditions are very heterogeneous, manipulations that can enhance learning and memory in mice under different circumstances might be able to overcome the cognitive deficits in patients. The M-current regulates neuronal excitability and action potential firing, suggesting that its inhibition may increase cognitive capacities. We demonstrate that XE991, a specific M-current blocker, enhances learning and memory in healthy mice. This effect may be achieved by altering basal hippocampal synaptic activity and by diminishing the stimulation threshold for long-term changes in synaptic efficacy and learning-related gene expression. We also show that training sessions regulate the M-current by transiently decreasing the levels of KCNQ/Kv7.3 protein, a pivotal subunit for the M-current. Furthermore, we found that XE991 can revert the cognitive impairment associated with acetylcholine depletion and the neurodegeneration induced by kainic acid. Together, these results show that inhibition of the M-current as a general strategy may be useful to enhance cognitive capacities in healthy and aging individuals, as well as in those with neurodegenerative diseases. Copyright © 2010 Wiley-Liss, Inc.
How Attention Can Create Synaptic Tags for the Learning of Working Memories in Sequential Tasks
Rombouts, Jaldert O.; Bohte, Sander M.; Roelfsema, Pieter R.
2015-01-01
Intelligence is our ability to learn appropriate responses to new stimuli and situations. Neurons in association cortex are thought to be essential for this ability. During learning these neurons become tuned to relevant features and start to represent them with persistent activity during memory delays. This learning process is not well understood. Here we develop a biologically plausible learning scheme that explains how trial-and-error learning induces neuronal selectivity and working memory representations for task-relevant information. We propose that the response selection stage sends attentional feedback signals to earlier processing levels, forming synaptic tags at those connections responsible for the stimulus-response mapping. Globally released neuromodulators then interact with tagged synapses to determine their plasticity. The resulting learning rule endows neural networks with the capacity to create new working memory representations of task relevant information as persistent activity. It is remarkably generic: it explains how association neurons learn to store task-relevant information for linear as well as non-linear stimulus-response mappings, how they become tuned to category boundaries or analog variables, depending on the task demands, and how they learn to integrate probabilistic evidence for perceptual decisions. PMID:25742003
Neuronal plasticity and thalamocortical sleep and waking oscillations
Timofeev, Igor
2011-01-01
Throughout life, thalamocortical (TC) network alternates between activated states (wake or rapid eye movement sleep) and slow oscillatory state dominating slow-wave sleep. The patterns of neuronal firing are different during these distinct states. I propose that due to relatively regular firing, the activated states preset some steady state synaptic plasticity and that the silent periods of slow-wave sleep contribute to a release from this steady state synaptic plasticity. In this respect, I discuss how states of vigilance affect short-, mid-, and long-term synaptic plasticity, intrinsic neuronal plasticity, as well as homeostatic plasticity. Finally, I suggest that slow oscillation is intrinsic property of cortical network and brain homeostatic mechanisms are tuned to use all forms of plasticity to bring cortical network to the state of slow oscillation. However, prolonged and profound shift from this homeostatic balance could lead to development of paroxysmal hyperexcitability and seizures as in the case of brain trauma. PMID:21854960
Toutounji, Hazem; Pipa, Gordon
2014-01-01
It is a long-established fact that neuronal plasticity occupies the central role in generating neural function and computation. Nevertheless, no unifying account exists of how neurons in a recurrent cortical network learn to compute on temporally and spatially extended stimuli. However, these stimuli constitute the norm, rather than the exception, of the brain's input. Here, we introduce a geometric theory of learning spatiotemporal computations through neuronal plasticity. To that end, we rigorously formulate the problem of neural representations as a relation in space between stimulus-induced neural activity and the asymptotic dynamics of excitable cortical networks. Backed up by computer simulations and numerical analysis, we show that two canonical and widely spread forms of neuronal plasticity, that is, spike-timing-dependent synaptic plasticity and intrinsic plasticity, are both necessary for creating neural representations, such that these computations become realizable. Interestingly, the effects of these forms of plasticity on the emerging neural code relate to properties necessary for both combating and utilizing noise. The neural dynamics also exhibits features of the most likely stimulus in the network's spontaneous activity. These properties of the spatiotemporal neural code resulting from plasticity, having their grounding in nature, further consolidate the biological relevance of our findings. PMID:24651447
Aberrant learning in Parkinson's disease: A neurocomputational study on bradykinesia.
Ursino, Mauro; Baston, Chiara
2018-05-22
Parkinson's disease (PD) is a neurodegenerative disorder characterized by a progressive decline in motor functions, such as bradykinesia, caused by the pathological denervation of nigrostriatal dopaminergic neurons within the basal ganglia (BG). It is acknowledged that dopamine (DA) directly affects the modulatory role of BG towards the cortex. However, a growing body of literature is suggesting that DA-induced aberrant synaptic plasticity could play a role in the core symptoms of PD, thus recalling for a "reconceptualization" of the pathophysiology. The aim of this work was to investigate DA-driven aberrant learning as a concurrent cause of bradykinesia, using a comprehensive, biologically inspired neurocomputational model of action selection in the BG. The model includes the three main pathways operating in the BG circuitry, that is the direct, indirect and hyperdirect pathways, and use a two-term Hebb rule to train synapses in the striatum, based on previous history of rewards and punishments. Levodopa pharmacodynamics is also incorporated. Through model simulations of the Alternate Finger Tapping motor task, we assessed the role of aberrant learning on bradykinesia. The results show that training under drug medication (levodopa) provides not only immediate but also delayed benefit lasting in time. Conversely, if performed in conditions of vanishing levodopa efficacy, training may result in dysfunctional corticostriatal synaptic plasticity, further worsening motor performances in PD subjects. This suggests that bradykinesia may result from the concurrent effects of low DA levels and dysfunctional plasticity and that training can be exploited in medicated subjects to improve levodopa treatment. © 2018 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.
Normann, Claus; Frase, Sibylle; Haug, Verena; von Wolff, Gregor; Clark, Kristin; Münzer, Patrick; Dorner, Alexandra; Scholliers, Jonas; Horn, Max; Vo Van, Tanja; Seifert, Gabriel; Serchov, Tsvetan; Biber, Knut; Nissen, Christoph; Klugbauer, Norbert; Bischofberger, Josef
2017-10-19
Long-term synaptic plasticity is a basic ability of the brain to dynamically adapt to external stimuli and regulate synaptic strength and ultimately network function. It is dysregulated by behavioral stress in animal models of depression and in humans with major depressive disorder. Antidepressants have been shown to restore disrupted synaptic plasticity in both animal models and humans; however, the underlying mechanism is unclear. We examined modulation of synaptic plasticity by selective serotonin reuptake inhibitors (SSRIs) in hippocampal brain slices from wild-type rats and serotonin transporter (SERT) knockout mice. Recombinant voltage-gated calcium (Ca 2+ ) channels in heterologous expression systems were used to determine the modulation of Ca 2+ channels by SSRIs. We tested the behavioral effects of SSRIs in the chronic behavioral despair model of depression both in the presence and in the absence of SERT. SSRIs selectively inhibited hippocampal long-term depression. The inhibition of long-term depression by SSRIs was mediated by a direct block of voltage-activated L-type Ca 2+ channels and was independent of SERT. Furthermore, SSRIs protected both wild-type and SERT knockout mice from behavioral despair induced by chronic stress. Finally, long-term depression was facilitated in animals subjected to the behavioral despair model, which was prevented by SSRI treatment. These results showed that antidepressants protected synaptic plasticity and neuronal circuitry from the effects of stress via a modulation of Ca 2+ channels and synaptic plasticity independent of SERT. Thus, L-type Ca 2+ channels might constitute an important signaling hub for stress response and for pathophysiology and treatment of depression. Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Zhang, Honghui; Su, Jianzhong; Wang, Qingyun; Liu, Yueming; Good, Levi; Pascual, Juan M.
2018-03-01
This paper explores the internal dynamical mechanisms of epileptic seizures through quantitative modeling based on full brain electroencephalogram (EEG) signals. Our goal is to provide seizure prediction and facilitate treatment for epileptic patients. Motivated by an earlier mathematical model with incorporated synaptic plasticity, we studied the nonlinear dynamics of inherited seizures through a differential equation model. First, driven by a set of clinical inherited electroencephalogram data recorded from a patient with diagnosed Glucose Transporter Deficiency, we developed a dynamic seizure model on a system of ordinary differential equations. The model was reduced in complexity after considering and removing redundancy of each EEG channel. Then we verified that the proposed model produces qualitatively relevant behavior which matches the basic experimental observations of inherited seizure, including synchronization index and frequency. Meanwhile, the rationality of the connectivity structure hypothesis in the modeling process was verified. Further, through varying the threshold condition and excitation strength of synaptic plasticity, we elucidated the effect of synaptic plasticity to our seizure model. Results suggest that synaptic plasticity has great effect on the duration of seizure activities, which support the plausibility of therapeutic interventions for seizure control.
Molecular bases of caloric restriction regulation of neuronal synaptic plasticity.
Fontán-Lozano, Angela; López-Lluch, Guillermo; Delgado-García, José María; Navas, Placido; Carrión, Angel Manuel
2008-10-01
Aging is associated with the decline of cognitive properties. This situation is magnified when neurodegenerative processes associated with aging appear in human patients. Neuronal synaptic plasticity events underlie cognitive properties in the central nervous system. Caloric restriction (CR; either a decrease in food intake or an intermittent fasting diet) can extend life span and increase disease resistance. Recent studies have shown that CR can have profound effects on brain function and vulnerability to injury and disease. Moreover, CR can stimulate the production of new neurons from stem cells (neurogenesis) and can enhance synaptic plasticity, which modulate pain sensation, enhance cognitive function, and may increase the ability of the brain to resist aging. The beneficial effects of CR appear to be the result of a cellular stress response stimulating the production of proteins that enhance neuronal plasticity and resistance to oxidative and metabolic insults; they include neurotrophic factors, neurotransmitter receptors, protein chaperones, and mitochondrial biosynthesis regulators. In this review, we will present and discuss the effect of CR in synaptic processes underlying analgesia and cognitive improvement in healthy, sick, and aging animals. We will also discuss the possible role of mitochondrial biogenesis induced by CR in regulation of neuronal synaptic plasticity.
Gene Expression Changes in the Motor Cortex Mediating Motor Skill Learning
Cheung, Vincent C. K.; DeBoer, Caroline; Hanson, Elizabeth; Tunesi, Marta; D'Onofrio, Mara; Arisi, Ivan; Brandi, Rossella; Cattaneo, Antonino; Goosens, Ki A.
2013-01-01
The primary motor cortex (M1) supports motor skill learning, yet little is known about the genes that contribute to motor cortical plasticity. Such knowledge could identify candidate molecules whose targeting might enable a new understanding of motor cortical functions, and provide new drug targets for the treatment of diseases which impair motor function, such as ischemic stroke. Here, we assess changes in the motor-cortical transcriptome across different stages of motor skill acquisition. Adult rats were trained on a gradually acquired appetitive reach and grasp task that required different strategies for successful pellet retrieval, or a sham version of the task in which the rats received pellet reward without needing to develop the reach and grasp skill. Tissue was harvested from the forelimb motor-cortical area either before training commenced, prior to the initial rise in task performance, or at peak performance. Differential classes of gene expression were observed at the time point immediately preceding motor task improvement. Functional clustering revealed that gene expression changes were related to the synapse, development, intracellular signaling, and the fibroblast growth factor (FGF) family, with many modulated genes known to regulate synaptic plasticity, synaptogenesis, and cytoskeletal dynamics. The modulated expression of synaptic genes likely reflects ongoing network reorganization from commencement of training till the point of task improvement, suggesting that motor performance improves only after sufficient modifications in the cortical circuitry have accumulated. The regulated FGF-related genes may together contribute to M1 remodeling through their roles in synaptic growth and maturation. PMID:23637843
GABAergic interneurons: The orchestra or the conductor in fear learning and memory?
Lucas, Elizabeth K; Clem, Roger L
2017-12-02
Fear conditioning is a form of associative learning that is fundamental to survival and involves potentiation of activity in excitatory projection neurons (PNs). Current models stipulate that the mechanisms underlying this process involve plasticity of PN synapses, which exhibit strengthening in response to fear conditioning. However, excitatory PNs are extensively modulated by a diverse array of GABAergic interneurons whose contributions to acquisition, storage, and expression of fear memory remain poorly understood. Here we review emerging evidence that genetically-defined interneurons play important subtype-specific roles in processing of fear-related stimuli and that these dynamics shape PN firing through both inhibition and disinhibition. Furthermore, interneurons exhibit structural, molecular, and electrophysiological evidence of fear learning-induced synaptic plasticity. These studies warrant discarding the notion of interneurons as passive bystanders in long-term memory. Copyright © 2017. Published by Elsevier Inc.
Reactivation of stalled polyribosomes in synaptic plasticity
Graber, Tyson E.; Hébert-Seropian, Sarah; Khoutorsky, Arkady; David, Alexandre; Yewdell, Jonathan W.; Lacaille, Jean-Claude; Sossin, Wayne S.
2013-01-01
Some forms of synaptic plasticity require rapid, local activation of protein synthesis. Although this is thought to reflect recruitment of mRNAs to free ribosomes, this would limit the speed and magnitude of translational activation. Here we provide compelling in situ evidence supporting an alternative model in which synaptic mRNAs are transported as stably paused polyribosomes. Remarkably, we show that metabotropic glutamate receptor activation allows the synthesis of proteins that lead to a functional long-term depression phenotype even when translation initiation has been greatly reduced. Thus, neurons evolved a unique mechanism to swiftly translate synaptic mRNAs into functional protein upon synaptic signaling using stalled polyribosomes to bypass the rate-limiting step of translation initiation. Because dysregulated plasticity is implicated in neurodevelopmental and psychiatric disorders such as fragile X syndrome, this work uncovers a unique translational target for therapies. PMID:24043809
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.