Gerhard, Stephan; Andrade, Ingrid; Fetter, Richard D; Cardona, Albert; Schneider-Mizell, Casey M
2017-10-23
During postembryonic development, the nervous system must adapt to a growing body. How changes in neuronal structure and connectivity contribute to the maintenance of appropriate circuit function remains unclear. Previously , we measured the cellular neuroanatomy underlying synaptic connectivity in Drosophila (Schneider-Mizell et al., 2016). Here, we examined how neuronal morphology and connectivity change between first instar and third instar larval stages using serial section electron microscopy. We reconstructed nociceptive circuits in a larva of each stage and found consistent topographically arranged connectivity between identified neurons. Five-fold increases in each size, number of terminal dendritic branches, and total number of synaptic inputs were accompanied by cell type-specific connectivity changes that preserved the fraction of total synaptic input associated with each pre-synaptic partner. We propose that precise patterns of structural growth act to conserve the computational function of a circuit, for example determining the location of a dangerous stimulus.
Activity-Induced Remodeling of Olfactory Bulb Microcircuits Revealed by Monosynaptic Tracing
Arenkiel, Benjamin R.; Hasegawa, Hiroshi; Yi, Jason J.; Larsen, Rylan S.; Wallace, Michael L.; Philpot, Benjamin D.; Wang, Fan; Ehlers, Michael D.
2011-01-01
The continued addition of new neurons to mature olfactory circuits represents a remarkable mode of cellular and structural brain plasticity. However, the anatomical configuration of newly established circuits, the types and numbers of neurons that form new synaptic connections, and the effect of sensory experience on synaptic connectivity in the olfactory bulb remain poorly understood. Using in vivo electroporation and monosynaptic tracing, we show that postnatal-born granule cells form synaptic connections with centrifugal inputs and mitral/tufted cells in the mouse olfactory bulb. In addition, newly born granule cells receive extensive input from local inhibitory short axon cells, a poorly understood cell population. The connectivity of short axon cells shows clustered organization, and their synaptic input onto newborn granule cells dramatically and selectively expands with odor stimulation. Our findings suggest that sensory experience promotes the synaptic integration of new neurons into cell type-specific olfactory circuits. PMID:22216277
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
Integrated neuron circuit for implementing neuromorphic system with synaptic device
NASA Astrophysics Data System (ADS)
Lee, Jeong-Jun; Park, Jungjin; Kwon, Min-Woo; Hwang, Sungmin; Kim, Hyungjin; Park, Byung-Gook
2018-02-01
In this paper, we propose and fabricate Integrate & Fire neuron circuit for implementing neuromorphic system. Overall operation of the circuit is verified by measuring discrete devices and the output characteristics of the circuit. Since the neuron circuit shows asymmetric output characteristic that can drive synaptic device with Spike-Timing-Dependent-Plasticity (STDP) characteristic, the autonomous weight update process is also verified by connecting the synaptic device and the neuron circuit. The timing difference of the pre-neuron and the post-neuron induce autonomous weight change of the synaptic device. Unlike 2-terminal devices, which is frequently used to implement neuromorphic system, proposed scheme of the system enables autonomous weight update and simple configuration by using 4-terminal synapse device and appropriate neuron circuit. Weight update process in the multi-layer neuron-synapse connection ensures implementation of the hardware-based artificial intelligence, based on Spiking-Neural- Network (SNN).
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
A scalable neural chip with synaptic electronics using CMOS integrated memristors.
Cruz-Albrecht, Jose M; Derosier, Timothy; Srinivasa, Narayan
2013-09-27
The design and simulation of a scalable neural chip with synaptic electronics using nanoscale memristors fully integrated with complementary metal-oxide-semiconductor (CMOS) is presented. The circuit consists of integrate-and-fire neurons and synapses with spike-timing dependent plasticity (STDP). The synaptic conductance values can be stored in memristors with eight levels, and the topology of connections between neurons is reconfigurable. The circuit has been designed using a 90 nm CMOS process with via connections to on-chip post-processed memristor arrays. The design has about 16 million CMOS transistors and 73 728 integrated memristors. We provide circuit level simulations of the entire chip performing neuronal and synaptic computations that result in biologically realistic functional behavior.
From a meso- to micro-scale connectome: array tomography and mGRASP
Rah, Jong-Cheol; Feng, Linqing; Druckmann, Shaul; Lee, Hojin; Kim, Jinhyun
2015-01-01
Mapping mammalian synaptic connectivity has long been an important goal of neuroscience because knowing how neurons and brain areas are connected underpins an understanding of brain function. Meeting this goal requires advanced techniques with single synapse resolution and large-scale capacity, especially at multiple scales tethering the meso- and micro-scale connectome. Among several advanced LM-based connectome technologies, Array Tomography (AT) and mammalian GFP-Reconstitution Across Synaptic Partners (mGRASP) can provide relatively high-throughput mapping synaptic connectivity at multiple scales. AT- and mGRASP-assisted circuit mapping (ATing and mGRASPing), combined with techniques such as retrograde virus, brain clearing techniques, and activity indicators will help unlock the secrets of complex neural circuits. Here, we discuss these useful new tools to enable mapping of brain circuits at multiple scales, some functional implications of spatial synaptic distribution, and future challenges and directions of these endeavors. PMID:26089781
Tracing neuronal circuits in transgenic animals by transneuronal control of transcription (TRACT)
Huang, Ting-hao; Niesman, Peter; Arasu, Deepshika; Lee, Donghyung; De La Cruz, Aubrie L; Callejas, Antuca; Hong, Elizabeth J
2017-01-01
Understanding the computations that take place in brain circuits requires identifying how neurons in those circuits are connected to one another. We describe a technique called TRACT (TRAnsneuronal Control of Transcription) based on ligand-induced intramembrane proteolysis to reveal monosynaptic connections arising from genetically labeled neurons of interest. In this strategy, neurons expressing an artificial ligand (‘donor’ neurons) bind to and activate a genetically-engineered artificial receptor on their synaptic partners (‘receiver’ neurons). Upon ligand-receptor binding at synapses the receptor is cleaved in its transmembrane domain and releases a protein fragment that activates transcription in the synaptic partners. Using TRACT in Drosophila we have confirmed the connectivity between olfactory receptor neurons and their postsynaptic targets, and have discovered potential new connections between neurons in the circadian circuit. Our results demonstrate that the TRACT method can be used to investigate the connectivity of neuronal circuits in the brain. PMID:29231171
Stereotyped Synaptic Connectivity Is Restored during Circuit Repair in the Adult Mammalian Retina.
Beier, Corinne; Palanker, Daniel; Sher, Alexander
2018-06-04
Proper function of the central nervous system (CNS) depends on the specificity of synaptic connections between cells of various types. Cellular and molecular mechanisms responsible for the establishment and refinement of these connections during development are the subject of an active area of research [1-6]. However, it is unknown if the adult mammalian CNS can form new type-selective synapses following neural injury or disease. Here, we assess whether selective synaptic connections can be reestablished after circuit disruption in the adult mammalian retina. The stereotyped circuitry at the first synapse in the retina, as well as the relatively short distances new neurites must travel compared to other areas of the CNS, make the retina well suited to probing for synaptic specificity during circuit reassembly. Selective connections between short-wavelength sensitive cone photoreceptors (S-cones) and S-cone bipolar cells provides the foundation of the primordial blue-yellow vision, common to all mammals [7-18]. We take advantage of the ground squirrel retina, which has a one-to-one S-cone-to-S-cone-bipolar-cell connection, to test if this connectivity can be reestablished following local photoreceptor loss [8, 19]. We find that after in vivo selective photoreceptor ablation, deafferented S-cone bipolar cells expand their dendritic trees. The new dendrites randomly explore the proper synaptic layer, bypass medium-wavelength sensitive cone photoreceptors (M-cones), and selectively synapse with S-cones. However, non-connected dendrites are not pruned back to resemble unperturbed S-cone bipolar cells. We show, for the first time, that circuit repair in the adult mammalian retina can recreate stereotypic selective wiring. Copyright © 2018 Elsevier Ltd. All rights reserved.
Fisher, Dimitry; Olasagasti, Itsaso; Tank, David W; Aksay, Emre R F; Goldman, Mark S
2013-09-04
Although many studies have identified neural correlates of memory, relatively little is known about the circuit properties connecting single-neuron physiology to behavior. Here we developed a modeling framework to bridge this gap and identify circuit interactions capable of maintaining short-term memory. Unlike typical studies that construct a phenomenological model and test whether it reproduces select aspects of neuronal data, we directly fit the synaptic connectivity of an oculomotor memory circuit to a broad range of anatomical, electrophysiological, and behavioral data. Simultaneous fits to all data, combined with sensitivity analyses, revealed complementary roles of synaptic and neuronal recruitment thresholds in providing the nonlinear interactions required to generate the observed circuit behavior. This work provides a methodology for identifying the cellular and synaptic mechanisms underlying short-term memory and demonstrates how the anatomical structure of a circuit may belie its functional organization. Copyright © 2013 Elsevier Inc. All rights reserved.
Edwards, Darin; Stancescu, Maria; Molnar, Peter; Hickman, James J
2013-08-21
In this study, we demonstrate the directed formation of small circuits of electrically active, synaptically connected neurons derived from the hippocampus of adult rats through the use of engineered chemically modified culture surfaces that orient the polarity of the neuronal processes. Although synaptogenesis, synaptic communication, synaptic plasticity, and brain disease pathophysiology can be studied using brain slice or dissociated embryonic neuronal culture systems, the complex elements found in neuronal synapses makes specific studies difficult in these random cultures. The study of synaptic transmission in mature adult neurons and factors affecting synaptic transmission are generally studied in organotypic cultures, in brain slices, or in vivo. However, engineered neuronal networks would allow these studies to be performed instead on simple functional neuronal circuits derived from adult brain tissue. Photolithographic patterned self-assembled monolayers (SAMs) were used to create the two-cell "bidirectional polarity" circuit patterns. This pattern consisted of a cell permissive SAM, N-1[3-(trimethoxysilyl)propyl] diethylenetriamine (DETA), and was composed of two 25 μm somal adhesion sites connected with 5 μm lines acting as surface cues for guided axonal and dendritic regeneration. Surrounding the DETA pattern was a background of a non-cell-permissive poly(ethylene glycol) (PEG) SAM. Adult hippocampal neurons were first cultured on coverslips coated with DETA monolayers and were later passaged onto the PEG-DETA bidirectional polarity patterns in serum-free medium. These neurons followed surface cues, attaching and regenerating only along the DETA substrate to form small engineered neuronal circuits. These circuits were stable for more than 21 days in vitro (DIV), during which synaptic connectivity was evaluated using basic electrophysiological methods.
Attractor neural networks with resource-efficient synaptic connectivity
NASA Astrophysics Data System (ADS)
Pehlevan, Cengiz; Sengupta, Anirvan
Memories are thought to be stored in the attractor states of recurrent neural networks. Here we explore how resource constraints interplay with memory storage function to shape synaptic connectivity of attractor networks. We propose that given a set of memories, in the form of population activity patterns, the neural circuit choses a synaptic connectivity configuration that minimizes a resource usage cost. We argue that the total synaptic weight (l1-norm) in the network measures the resource cost because synaptic weight is correlated with synaptic volume, which is a limited resource, and is proportional to neurotransmitter release and post-synaptic current, both of which cost energy. Using numerical simulations and replica theory, we characterize optimal connectivity profiles in resource-efficient attractor networks. Our theory explains several experimental observations on cortical connectivity profiles, 1) connectivity is sparse, because synapses are costly, 2) bidirectional connections are overrepresented and 3) are stronger, because attractor states need strong recurrence.
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.
Synchrony dynamics underlying effective connectivity reconstruction of neuronal circuits
NASA Astrophysics Data System (ADS)
Yu, Haitao; Guo, Xinmeng; Qin, Qing; Deng, Yun; Wang, Jiang; Liu, Jing; Cao, Yibin
2017-04-01
Reconstruction of effective connectivity between neurons is essential for neural systems with function-related significance, characterizing directionally causal influences among neurons. In this work, causal interactions between neurons in spinal dorsal root ganglion, activated by manual acupuncture at Zusanli acupoint of experimental rats, are estimated using Granger causality (GC) method. Different patterns of effective connectivity are obtained for different frequencies and types of acupuncture. Combined with synchrony analysis between neurons, we show a dependence of effective connection on the synchronization dynamics. Based on the experimental findings, a neuronal circuit model with synaptic connections is constructed. The variation of neuronal effective connectivity with respect to its structural connectivity and synchronization dynamics is further explored. Simulation results show that reciprocally causal interactions with statistically significant are formed between well-synchronized neurons. The effective connectivity may be not necessarily equivalent to synaptic connections, but rather depend on the synchrony relationship. Furthermore, transitions of effective interaction between neurons are observed following the synchronization transitions induced by conduction delay and synaptic conductance. These findings are helpful to further investigate the dynamical mechanisms underlying the reconstruction of effective connectivity of neuronal population.
Activity Regulates the Incidence of Heteronymous Sensory-Motor Connections
Mendelsohn, Alana I.; Simon, Christian M.; Abbott, L. F.; Mentis, George Z.; Jessell, Thomas M.
2015-01-01
Summary The construction of spinal sensory-motor circuits involves the selection of appropriate synaptic partners and the allocation of precise synaptic input densities. Many aspects of spinal sensory-motor selectivity appear to be preserved when peripheral sensory activation is blocked, which has led to a view that sensory-motor circuits are assembled in an activity-independent manner. Yet it remains unclear whether activity-dependent refinement has a role in the establishment of connections between sensory afferents and those motor pools that have synergistic biomechanical functions. We show here that genetically abolishing central sensory-motor neurotransmission leads to a selective enhancement in the number and density of such “heteronymous” connections, whereas other aspects of sensory-motor connectivity are preserved. Spike-timing dependent synaptic refinement represents one possible mechanism for the changes in connectivity observed after activity blockade. Our findings therefore reveal that sensory activity does have a limited and selective role in the establishment of patterned monosynaptic sensory-motor connections. PMID:26094608
Spontaneous network activity and synaptic development
Kerschensteiner, Daniel
2014-01-01
Throughout development, the nervous system produces patterned spontaneous activity. Research over the last two decades has revealed a core group of mechanisms that mediate spontaneous activity in diverse circuits. Many circuits engage several of these mechanisms sequentially to accommodate developmental changes in connectivity. In addition to shared mechanisms, activity propagates through developing circuits and neuronal pathways (i.e. linked circuits in different brain areas) in stereotypic patterns. Increasing evidence suggests that spontaneous network activity shapes synaptic development in vivo. Variations in activity-dependent plasticity may explain how similar mechanisms and patterns of activity can be employed to establish diverse circuits. Here, I will review common mechanisms and patterns of spontaneous activity in emerging neural networks and discuss recent insights into their contribution to synaptic development. PMID:24280071
Mapping sensory circuits by anterograde trans-synaptic transfer of recombinant rabies virus
Zampieri, Niccolò; Jessell, Thomas M.; Murray, Andrew J.
2014-01-01
Summary Primary sensory neurons convey information from the external world to relay circuits within the central nervous system (CNS), but the identity and organization of the neurons that process incoming sensory information remains sketchy. Within the CNS viral tracing techniques that rely on retrograde trans-synaptic transfer provide a powerful tool for delineating circuit organization. Viral tracing of the circuits engaged by primary sensory neurons has, however, been hampered by the absence of a genetically tractable anterograde transfer system. In this study we demonstrate that rabies virus can infect sensory neurons in the somatosensory system, is subject to anterograde trans-synaptic transfer from primary sensory to spinal target neurons, and can delineate output connectivity with third-order neurons. Anterograde trans-synaptic transfer is a feature shared by other classes of primary sensory neurons, permitting the identification and potentially the manipulation of neural circuits processing sensory feedback within the mammalian CNS. PMID:24486087
Optogenetic Examination of Prefrontal-Amygdala Synaptic Development.
Arruda-Carvalho, Maithe; Wu, Wan-Chen; Cummings, Kirstie A; Clem, Roger L
2017-03-15
A brain network comprising the medial prefrontal cortex (mPFC) and amygdala plays important roles in developmentally regulated cognitive and emotional processes. However, very little is known about the maturation of mPFC-amygdala circuitry. We conducted anatomical tracing of mPFC projections and optogenetic interrogation of their synaptic connections with neurons in the basolateral amygdala (BLA) at neonatal to adult developmental stages in mice. Results indicate that mPFC-BLA projections exhibit delayed emergence relative to other mPFC pathways and establish synaptic transmission with BLA excitatory and inhibitory neurons in late infancy, events that coincide with a massive increase in overall synaptic drive. During subsequent adolescence, mPFC-BLA circuits are further modified by excitatory synaptic strengthening as well as a transient surge in feedforward inhibition. The latter was correlated with increased spontaneous inhibitory currents in excitatory neurons, suggesting that mPFC-BLA circuit maturation culminates in a period of exuberant GABAergic transmission. These findings establish a time course for the onset and refinement of mPFC-BLA transmission and point to potential sensitive periods in the development of this critical network. SIGNIFICANCE STATEMENT Human mPFC-amygdala functional connectivity is developmentally regulated and figures prominently in numerous psychiatric disorders with a high incidence of adolescent onset. However, it remains unclear when synaptic connections between these structures emerge or how their properties change with age. Our work establishes developmental windows and cellular substrates for synapse maturation in this pathway involving both excitatory and inhibitory circuits. The engagement of these substrates by early life experience may support the ontogeny of fundamental behaviors but could also lead to inappropriate circuit refinement and psychopathology in adverse situations. Copyright © 2017 the authors 0270-6474/17/372976-10$15.00/0.
Baker, Christopher A; Elyada, Yishai M; Parra, Andres; Bolton, M McLean
2016-01-01
We describe refinements in optogenetic methods for circuit mapping that enable measurements of functional synaptic connectivity with single-neuron resolution. By expanding a two-photon beam in the imaging plane using the temporal focusing method and restricting channelrhodopsin to the soma and proximal dendrites, we are able to reliably evoke action potentials in individual neurons, verify spike generation with GCaMP6s, and determine the presence or absence of synaptic connections with patch-clamp electrophysiological recording. DOI: http://dx.doi.org/10.7554/eLife.14193.001 PMID:27525487
Sim, Shuyin; Antolin, Salome; Lin, Chia-Wei; Lin, Ying-Xi
2013-01-01
Electrical activity regulates the manner in which neurons mature and form connections to each other. However, it remains unclear whether increased single-cell activity is sufficient to alter the development of synaptic connectivity of that neuron or whether a global increase in circuit activity is necessary. To address this question, we genetically increased neuronal excitability of in vivo individual adult-born neurons in the mouse dentate gyrus via expression of a voltage-gated bacterial sodium channel. We observed that increasing the excitability of new neurons in an otherwise unperturbed circuit leads to changes in both their input and axonal synapses. Furthermore, the activity-dependent transcription factor Npas4 is necessary for the changes in the input synapses of these neurons, but it is not involved in changes to their axonal synapses. Our results reveal that an increase in cell-intrinsic activity during maturation is sufficient to alter the synaptic connectivity of a neuron with the hippocampal circuit and that Npas4 is required for activity-dependent changes in input synapses. PMID:23637184
Illuminating the multifaceted roles of neurotransmission in shaping neuronal circuitry.
Okawa, Haruhisa; Hoon, Mrinalini; Yoshimatsu, Takeshi; Della Santina, Luca; Wong, Rachel O L
2014-09-17
Across the nervous system, neurons form highly stereotypic patterns of synaptic connections that are designed to serve specific functions. Mature wiring patterns are often attained upon the refinement of early, less precise connectivity. Much work has led to the prevailing view that many developing circuits are sculpted by activity-dependent competition among converging afferents, which results in the elimination of unwanted synapses and the maintenance and strengthening of desired connections. Studies of the vertebrate retina, however, have recently revealed that activity can play a role in shaping developing circuits without engaging competition among converging inputs that differ in their activity levels. Such neurotransmission-mediated processes can produce stereotypic wiring patterns by promoting selective synapse formation rather than elimination. We discuss how the influence of transmission may also be limited by circuit design and further highlight the importance of transmission beyond development in maintaining wiring specificity and synaptic organization of neural circuits. Copyright © 2014 Elsevier Inc. All rights reserved.
Delayed and Temporally Imprecise Neurotransmission in Reorganizing Cortical Microcircuits
Barnes, Samuel J.; Cheetham, Claire E.; Liu, Yan; Bennett, Sophie H.; Albieri, Giorgia; Jorstad, Anne A.; Knott, Graham W.
2015-01-01
Synaptic neurotransmission is modified at cortical connections throughout life. Varying the amplitude of the postsynaptic response is one mechanism that generates flexible signaling in neural circuits. The timing of the synaptic response may also play a role. Here, we investigated whether weakening and loss of an entire connection between excitatory cortical neurons was foreshadowed in the timing of the postsynaptic response. We made electrophysiological recordings in rat primary somatosensory cortex that was undergoing experience-dependent loss of complete local excitatory connections. The synaptic latency of pyramid–pyramid connections, which typically comprise multiple synapses, was longer and more variable. Connection strength and latency were not correlated. Instead, prolonged latency was more closely related to progression of connection loss. The action potential waveform and axonal conduction velocity were unaffected, suggesting that the altered timing of neurotransmission was attributable to a synaptic mechanism. Modeling studies indicated that increasing the latency and jitter at a subset of synapses reduced the number of action potentials fired by a postsynaptic neuron. We propose that prolonged synaptic latency and diminished temporal precision of neurotransmission are hallmarks of impending loss of a cortical connection. PMID:26085628
The neural circuit and synaptic dynamics underlying perceptual decision-making
NASA Astrophysics Data System (ADS)
Liu, Feng
2015-03-01
Decision-making with several choice options is central to cognition. To elucidate the neural mechanisms of multiple-choice motion discrimination, we built a continuous recurrent network model to represent a local circuit in the lateral intraparietal area (LIP). The network is composed of pyramidal cells and interneurons, which are directionally tuned. All neurons are reciprocally connected, and the synaptic connectivity strength is heterogeneous. Specifically, we assume two types of inhibitory connectivity to pyramidal cells: opposite-feature and similar-feature inhibition. The model accounted for both physiological and behavioral data from monkey experiments. The network is endowed with slow excitatory reverberation, which subserves the buildup and maintenance of persistent neural activity, and predominant feedback inhibition, which underlies the winner-take-all competition and attractor dynamics. The opposite-feature and opposite-feature inhibition have different effects on decision-making, and only their combination allows for a categorical choice among 12 alternatives. Together, our work highlights the importance of structured synaptic inhibition in multiple-choice decision-making processes.
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
Neural learning circuits utilizing nano-crystalline silicon transistors and memristors.
Cantley, Kurtis D; Subramaniam, Anand; Stiegler, Harvey J; Chapman, Richard A; Vogel, Eric M
2012-04-01
Properties of neural circuits are demonstrated via SPICE simulations and their applications are discussed. The neuron and synapse subcircuits include ambipolar nano-crystalline silicon transistor and memristor device models based on measured data. Neuron circuit characteristics and the Hebbian synaptic learning rule are shown to be similar to biology. Changes in the average firing rate learning rule depending on various circuit parameters are also presented. The subcircuits are then connected into larger neural networks that demonstrate fundamental properties including associative learning and pulse coincidence detection. Learned extraction of a fundamental frequency component from noisy inputs is demonstrated. It is then shown that if the fundamental sinusoid of one neuron input is out of phase with the rest, its synaptic connection changes differently than the others. Such behavior indicates that the system can learn to detect which signals are important in the general population, and that there is a spike-timing-dependent component of the learning mechanism. Finally, future circuit design and considerations are discussed, including requirements for the memristive device.
Kurup, Naina; Kono, Karina
2017-01-01
Neural circuits are dynamic, with activity-dependent changes in synapse density and connectivity peaking during different phases of animal development. In C. elegans, young larvae form mature motor circuits through a dramatic switch in GABAergic neuron connectivity, by concomitant elimination of existing synapses and formation of new synapses that are maintained throughout adulthood. We have previously shown that an increase in microtubule dynamics during motor circuit rewiring facilitates new synapse formation. Here, we further investigate cellular control of circuit rewiring through the analysis of mutants obtained in a forward genetic screen. Using live imaging, we characterize novel mutations that alter cargo binding in the dynein motor complex and enhance anterograde synaptic vesicle movement during remodeling, providing in vivo evidence for the tug-of-war between kinesin and dynein in fast axonal transport. We also find that a casein kinase homolog, TTBK-3, inhibits stabilization of nascent synapses in their new locations, a previously unexplored facet of structural plasticity of synapses. Our study delineates temporally distinct signaling pathways that are required for effective neural circuit refinement. PMID:28636662
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
Sha, Fern; Johenning, Friedrich W.; Schreiter, Eric R.; Looger, Loren L.; Larkum, Matthew E.
2016-01-01
Key points The genetically encoded fluorescent calcium integrator calcium‐modulated photoactivatable ratiobetric integrator (CaMPARI) reports calcium influx induced by synaptic and neural activity. Its fluorescence is converted from green to red in the presence of violet light and calcium.The rate of conversion – the sensitivity to activity – is tunable and depends on the intensity of violet light.Synaptic activity and action potentials can independently initiate significant CaMPARI conversion.The level of conversion by subthreshold synaptic inputs is correlated to the strength of input, enabling optical readout of relative synaptic strength.When combined with optogenetic activation of defined presynaptic neurons, CaMPARI provides an all‐optical method to map synaptic connectivity. Abstract The calcium‐modulated photoactivatable ratiometric integrator (CaMPARI) is a genetically encoded calcium integrator that facilitates the study of neural circuits by permanently marking cells active during user‐specified temporal windows. Permanent marking enables measurement of signals from large swathes of tissue and easy correlation of activity with other structural or functional labels. One potential application of CaMPARI is labelling neurons postsynaptic to specific populations targeted for optogenetic stimulation, giving rise to all‐optical functional connectivity mapping. Here, we characterized the response of CaMPARI to several common types of neuronal calcium signals in mouse acute cortical brain slices. Our experiments show that CaMPARI is effectively converted by both action potentials and subthreshold synaptic inputs, and that conversion level is correlated to synaptic strength. Importantly, we found that conversion rate can be tuned: it is linearly related to light intensity. At low photoconversion light levels CaMPARI offers a wide dynamic range due to slower conversion rate; at high light levels conversion is more rapid and more sensitive to activity. Finally, we employed CaMPARI and optogenetics for functional circuit mapping in ex vivo acute brain slices, which preserve in vivo‐like connectivity of axon terminals. With a single light source, we stimulated channelrhodopsin‐2‐expressing long‐range posteromedial (POm) thalamic axon terminals in cortex and induced CaMPARI conversion in recipient cortical neurons. We found that POm stimulation triggers robust photoconversion of layer 5 cortical neurons and weaker conversion of layer 2/3 neurons. Thus, CaMPARI enables network‐wide, tunable, all‐optical functional circuit mapping that captures supra‐ and subthreshold depolarization. PMID:27861906
Li, Wen-Chang; Cooke, Tom; Sautois, Bart; Soffe, Stephen R; Borisyuk, Roman; Roberts, Alan
2007-09-10
How specific are the synaptic connections formed as neuronal networks develop and can simple rules account for the formation of functioning circuits? These questions are assessed in the spinal circuits controlling swimming in hatchling frog tadpoles. This is possible because detailed information is now available on the identity and synaptic connections of the main types of neuron. The probabilities of synapses between 7 types of identified spinal neuron were measured directly by making electrical recordings from 500 pairs of neurons. For the same neuron types, the dorso-ventral distributions of axons and dendrites were measured and then used to calculate the probabilities that axons would encounter particular dendrites and so potentially form synaptic connections. Surprisingly, synapses were found between all types of neuron but contact probabilities could be predicted simply by the anatomical overlap of their axons and dendrites. These results suggested that synapse formation may not require axons to recognise specific, correct dendrites. To test the plausibility of simpler hypotheses, we first made computational models that were able to generate longitudinal axon growth paths and reproduce the axon distribution patterns and synaptic contact probabilities found in the spinal cord. To test if probabilistic rules could produce functioning spinal networks, we then made realistic computational models of spinal cord neurons, giving them established cell-specific properties and connecting them into networks using the contact probabilities we had determined. A majority of these networks produced robust swimming activity. Simple factors such as morphogen gradients controlling dorso-ventral soma, dendrite and axon positions may sufficiently constrain the synaptic connections made between different types of neuron as the spinal cord first develops and allow functional networks to form. Our analysis implies that detailed cellular recognition between spinal neuron types may not be necessary for the reliable formation of functional networks to generate early behaviour like swimming.
The Impact of Structural Heterogeneity on Excitation-Inhibition Balance in Cortical Networks.
Landau, Itamar D; Egger, Robert; Dercksen, Vincent J; Oberlaender, Marcel; Sompolinsky, Haim
2016-12-07
Models of cortical dynamics often assume a homogeneous connectivity structure. However, we show that heterogeneous input connectivity can prevent the dynamic balance between excitation and inhibition, a hallmark of cortical dynamics, and yield unrealistically sparse and temporally regular firing. Anatomically based estimates of the connectivity of layer 4 (L4) rat barrel cortex and numerical simulations of this circuit indicate that the local network possesses substantial heterogeneity in input connectivity, sufficient to disrupt excitation-inhibition balance. We show that homeostatic plasticity in inhibitory synapses can align the functional connectivity to compensate for structural heterogeneity. Alternatively, spike-frequency adaptation can give rise to a novel state in which local firing rates adjust dynamically so that adaptation currents and synaptic inputs are balanced. This theory is supported by simulations of L4 barrel cortex during spontaneous and stimulus-evoked conditions. Our study shows how synaptic and cellular mechanisms yield fluctuation-driven dynamics despite structural heterogeneity in cortical circuits. Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.
Gerhard, Felipe; Kispersky, Tilman; Gutierrez, Gabrielle J.; Marder, Eve; Kramer, Mark; Eden, Uri
2013-01-01
Identifying the structure and dynamics of synaptic interactions between neurons is the first step to understanding neural network dynamics. The presence of synaptic connections is traditionally inferred through the use of targeted stimulation and paired recordings or by post-hoc histology. More recently, causal network inference algorithms have been proposed to deduce connectivity directly from electrophysiological signals, such as extracellularly recorded spiking activity. Usually, these algorithms have not been validated on a neurophysiological data set for which the actual circuitry is known. Recent work has shown that traditional network inference algorithms based on linear models typically fail to identify the correct coupling of a small central pattern generating circuit in the stomatogastric ganglion of the crab Cancer borealis. In this work, we show that point process models of observed spike trains can guide inference of relative connectivity estimates that match the known physiological connectivity of the central pattern generator up to a choice of threshold. We elucidate the necessary steps to derive faithful connectivity estimates from a model that incorporates the spike train nature of the data. We then apply the model to measure changes in the effective connectivity pattern in response to two pharmacological interventions, which affect both intrinsic neural dynamics and synaptic transmission. Our results provide the first successful application of a network inference algorithm to a circuit for which the actual physiological synapses between neurons are known. The point process methodology presented here generalizes well to larger networks and can describe the statistics of neural populations. In general we show that advanced statistical models allow for the characterization of effective network structure, deciphering underlying network dynamics and estimating information-processing capabilities. PMID:23874181
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.
Spike timing precision of neuronal circuits.
Kilinc, Deniz; Demir, Alper
2018-06-01
Spike timing is believed to be a key factor in sensory information encoding and computations performed by the neurons and neuronal circuits. However, the considerable noise and variability, arising from the inherently stochastic mechanisms that exist in the neurons and the synapses, degrade spike timing precision. Computational modeling can help decipher the mechanisms utilized by the neuronal circuits in order to regulate timing precision. In this paper, we utilize semi-analytical techniques, which were adapted from previously developed methods for electronic circuits, for the stochastic characterization of neuronal circuits. These techniques, which are orders of magnitude faster than traditional Monte Carlo type simulations, can be used to directly compute the spike timing jitter variance, power spectral densities, correlation functions, and other stochastic characterizations of neuronal circuit operation. We consider three distinct neuronal circuit motifs: Feedback inhibition, synaptic integration, and synaptic coupling. First, we show that both the spike timing precision and the energy efficiency of a spiking neuron are improved with feedback inhibition. We unveil the underlying mechanism through which this is achieved. Then, we demonstrate that a neuron can improve on the timing precision of its synaptic inputs, coming from multiple sources, via synaptic integration: The phase of the output spikes of the integrator neuron has the same variance as that of the sample average of the phases of its inputs. Finally, we reveal that weak synaptic coupling among neurons, in a fully connected network, enables them to behave like a single neuron with a larger membrane area, resulting in an improvement in the timing precision through cooperation.
GaAs Optoelectronic Integrated-Circuit Neurons
NASA Technical Reports Server (NTRS)
Lin, Steven H.; Kim, Jae H.; Psaltis, Demetri
1992-01-01
Monolithic GaAs optoelectronic integrated circuits developed for use as artificial neurons. Neural-network computer contains planar arrays of optoelectronic neurons, and variable synaptic connections between neurons effected by diffraction of light from volume hologram in photorefractive material. Basic principles of neural-network computers explained more fully in "Optoelectronic Integrated Circuits For Neural Networks" (NPO-17652). In present circuits, devices replaced by metal/semiconductor field effect transistors (MESFET's), which consume less power.
Zhang-Hooks, Ying-Xin; Roos, Hannah
2017-01-01
Hearing loss leads to a host of cellular and synaptic changes in auditory brain areas that are thought to give rise to auditory perception deficits such as temporal processing impairments, hyperacusis, and tinnitus. However, little is known about possible changes in synaptic circuit connectivity that may underlie these hearing deficits. Here, we show that mild hearing loss as a result of brief noise exposure leads to a pronounced reorganization of local excitatory and inhibitory circuits in the mouse inferior colliculus. The exact nature of these reorganizations correlated with the presence or absence of the animals' impairments in detecting brief sound gaps, a commonly used behavioral sign for tinnitus in animal models. Mice with gap detection deficits (GDDs) showed a shift in the balance of synaptic excitation and inhibition that was present in both glutamatergic and GABAergic neurons, whereas mice without GDDs showed stable excitation–inhibition balances. Acoustic enrichment (AE) with moderate intensity, pulsed white noise immediately after noise trauma prevented both circuit reorganization and GDDs, raising the possibility of using AE immediately after cochlear damage to prevent or alleviate the emergence of central auditory processing deficits. SIGNIFICANCE STATEMENT Noise overexposure is a major cause of central auditory processing disorders, including tinnitus, yet the changes in synaptic connectivity underlying these disorders remain poorly understood. Here, we find that brief noise overexposure leads to distinct reorganizations of excitatory and inhibitory synaptic inputs onto glutamatergic and GABAergic neurons and that the nature of these reorganizations correlates with animals' impairments in detecting brief sound gaps, which is often considered a sign of tinnitus. Acoustic enrichment immediately after noise trauma prevents circuit reorganizations and gap detection deficits, highlighting the potential for using sound therapy soon after cochlear damage to prevent the development of central processing deficits. PMID:28583912
Plasticity in single neuron and circuit computations
NASA Astrophysics Data System (ADS)
Destexhe, Alain; Marder, Eve
2004-10-01
Plasticity in neural circuits can result from alterations in synaptic strength or connectivity, as well as from changes in the excitability of the neurons themselves. To better understand the role of plasticity in the brain, we need to establish how brain circuits work and the kinds of computations that different circuit structures achieve. By linking theoretical and experimental studies, we are beginning to reveal the consequences of plasticity mechanisms for network dynamics, in both simple invertebrate circuits and the complex circuits of mammalian cerebral cortex.
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
Imai, Fumiyasu; Ladle, David R.; Leslie, Jennifer R.; Duan, Xin; Rizvi, Tilat A.; Ciraolo, Georgianne M.; Zheng, Yi
2016-01-01
Spinal reflex circuit development requires the precise regulation of axon trajectories, synaptic specificity, and synapse formation. Of these three crucial steps, the molecular mechanisms underlying synapse formation between group Ia proprioceptive sensory neurons and motor neurons is the least understood. Here, we show that the Rho GTPase Cdc42 controls synapse formation in monosynaptic sensory–motor connections in presynaptic, but not postsynaptic, neurons. In mice lacking Cdc42 in presynaptic sensory neurons, proprioceptive sensory axons appropriately reach the ventral spinal cord, but significantly fewer synapses are formed with motor neurons compared with wild-type mice. Concordantly, electrophysiological analyses show diminished EPSP amplitudes in monosynaptic sensory–motor circuits in these mutants. Temporally targeted deletion of Cdc42 in sensory neurons after sensory–motor circuit establishment reveals that Cdc42 does not affect synaptic transmission. Furthermore, addition of the synaptic organizers, neuroligins, induces presynaptic differentiation of wild-type, but not Cdc42-deficient, proprioceptive sensory neurons in vitro. Together, our findings demonstrate that Cdc42 in presynaptic neurons is required for synapse formation in monosynaptic sensory–motor circuits. SIGNIFICANCE STATEMENT Group Ia proprioceptive sensory neurons form direct synapses with motor neurons, but the molecular mechanisms underlying synapse formation in these monosynaptic sensory–motor connections are unknown. We show that deleting Cdc42 in sensory neurons does not affect proprioceptive sensory axon targeting because axons reach the ventral spinal cord appropriately, but these neurons form significantly fewer presynaptic terminals on motor neurons. Electrophysiological analysis further shows that EPSPs are decreased in these mice. Finally, we demonstrate that Cdc42 is involved in neuroligin-dependent presynaptic differentiation of proprioceptive sensory neurons in vitro. These data suggest that Cdc42 in presynaptic sensory neurons is essential for proper synapse formation in the development of monosynaptic sensory–motor circuits. PMID:27225763
Berryer, Martin H.; Chattopadhyaya, Bidisha; Xing, Paul; Riebe, Ilse; Bosoi, Ciprian; Sanon, Nathalie; Antoine-Bertrand, Judith; Lévesque, Maxime; Avoli, Massimo; Hamdan, Fadi F.; Carmant, Lionel; Lamarche-Vane, Nathalie; Lacaille, Jean-Claude; Michaud, Jacques L.; Di Cristo, Graziella
2016-01-01
Haploinsufficiency of the SYNGAP1 gene, which codes for a Ras GTPase-activating protein, impairs cognition both in humans and in mice. Decrease of Syngap1 in mice has been previously shown to cause cognitive deficits at least in part by inducing alterations in glutamatergic neurotransmission and premature maturation of excitatory connections. Whether Syngap1 plays a role in the development of cortical GABAergic connectivity and function remains unclear. Here, we show that Syngap1 haploinsufficiency significantly reduces the formation of perisomatic innervations by parvalbumin-positive basket cells, a major population of GABAergic neurons, in a cell-autonomous manner. We further show that Syngap1 haploinsufficiency in GABAergic cells derived from the medial ganglionic eminence impairs their connectivity, reduces inhibitory synaptic activity and cortical gamma oscillation power, and causes cognitive deficits. Our results indicate that Syngap1 plays a critical role in GABAergic circuit function and further suggest that Syngap1 haploinsufficiency in GABAergic circuits may contribute to cognitive deficits. PMID:27827368
Quantitative neuroanatomy for connectomics in Drosophila
Schneider-Mizell, Casey M; Gerhard, Stephan; Longair, Mark; Kazimiers, Tom; Li, Feng; Zwart, Maarten F; Champion, Andrew; Midgley, Frank M; Fetter, Richard D; Saalfeld, Stephan; Cardona, Albert
2016-01-01
Neuronal circuit mapping using electron microscopy demands laborious proofreading or reconciliation of multiple independent reconstructions. Here, we describe new methods to apply quantitative arbor and network context to iteratively proofread and reconstruct circuits and create anatomically enriched wiring diagrams. We measured the morphological underpinnings of connectivity in new and existing reconstructions of Drosophila sensorimotor (larva) and visual (adult) systems. Synaptic inputs were preferentially located on numerous small, microtubule-free 'twigs' which branch off a single microtubule-containing 'backbone'. Omission of individual twigs accounted for 96% of errors. However, the synapses of highly connected neurons were distributed across multiple twigs. Thus, the robustness of a strong connection to detailed twig anatomy was associated with robustness to reconstruction error. By comparing iterative reconstruction to the consensus of multiple reconstructions, we show that our method overcomes the need for redundant effort through the discovery and application of relationships between cellular neuroanatomy and synaptic connectivity. DOI: http://dx.doi.org/10.7554/eLife.12059.001 PMID:26990779
Transition to Chaos in Random Neuronal Networks
NASA Astrophysics Data System (ADS)
Kadmon, Jonathan; Sompolinsky, Haim
2015-10-01
Firing patterns in the central nervous system often exhibit strong temporal irregularity and considerable heterogeneity in time-averaged response properties. Previous studies suggested that these properties are the outcome of the intrinsic chaotic dynamics of the neural circuits. Indeed, simplified rate-based neuronal networks with synaptic connections drawn from Gaussian distribution and sigmoidal nonlinearity are known to exhibit chaotic dynamics when the synaptic gain (i.e., connection variance) is sufficiently large. In the limit of an infinitely large network, there is a sharp transition from a fixed point to chaos, as the synaptic gain reaches a critical value. Near the onset, chaotic fluctuations are slow, analogous to the ubiquitous, slow irregular fluctuations observed in the firing rates of many cortical circuits. However, the existence of a transition from a fixed point to chaos in neuronal circuit models with more realistic architectures and firing dynamics has not been established. In this work, we investigate rate-based dynamics of neuronal circuits composed of several subpopulations with randomly diluted connections. Nonzero connections are either positive for excitatory neurons or negative for inhibitory ones, while single neuron output is strictly positive with output rates rising as a power law above threshold, in line with known constraints in many biological systems. Using dynamic mean field theory, we find the phase diagram depicting the regimes of stable fixed-point, unstable-dynamic, and chaotic-rate fluctuations. We focus on the latter and characterize the properties of systems near this transition. We show that dilute excitatory-inhibitory architectures exhibit the same onset to chaos as the single population with Gaussian connectivity. In these architectures, the large mean excitatory and inhibitory inputs dynamically balance each other, amplifying the effect of the residual fluctuations. Importantly, the existence of a transition to chaos and its critical properties depend on the shape of the single-neuron nonlinear input-output transfer function, near firing threshold. In particular, for nonlinear transfer functions with a sharp rise near threshold, the transition to chaos disappears in the limit of a large network; instead, the system exhibits chaotic fluctuations even for small synaptic gain. Finally, we investigate transition to chaos in network models with spiking dynamics. We show that when synaptic time constants are slow relative to the mean inverse firing rates, the network undergoes a transition from fast spiking fluctuations with constant rates to a state where the firing rates exhibit chaotic fluctuations, similar to the transition predicted by rate-based dynamics. Systems with finite synaptic time constants and firing rates exhibit a smooth transition from a regime dominated by stationary firing rates to a regime of slow rate fluctuations. This smooth crossover obeys scaling properties, similar to crossover phenomena in statistical mechanics. The theoretical results are supported by computer simulations of several neuronal architectures and dynamics. Consequences for cortical circuit dynamics are discussed. These results advance our understanding of the properties of intrinsic dynamics in realistic neuronal networks and their functional consequences.
Memory formation orchestrates the wiring of adult-born hippocampal neurons into brain circuits.
Petsophonsakul, Petnoi; Richetin, Kevin; Andraini, Trinovita; Roybon, Laurent; Rampon, Claire
2017-08-01
During memory formation, structural rearrangements of dendritic spines provide a mean to durably modulate synaptic connectivity within neuronal networks. New neurons generated throughout the adult life in the dentate gyrus of the hippocampus contribute to learning and memory. As these neurons become incorporated into the network, they generate huge numbers of new connections that modify hippocampal circuitry and functioning. However, it is yet unclear as to how the dynamic process of memory formation influences their synaptic integration into neuronal circuits. New memories are established according to a multistep process during which new information is first acquired and then consolidated to form a stable memory trace. Upon recall, memory is transiently destabilized and vulnerable to modification. Using contextual fear conditioning, we found that learning was associated with an acceleration of dendritic spines formation of adult-born neurons, and that spine connectivity becomes strengthened after memory consolidation. Moreover, we observed that afferent connectivity onto adult-born neurons is enhanced after memory retrieval, while extinction training induces a change of spine shapes. Together, these findings reveal that the neuronal activity supporting memory processes strongly influences the structural dendritic integration of adult-born neurons into pre-existing neuronal circuits. Such change of afferent connectivity is likely to impact the overall wiring of hippocampal network, and consequently, to regulate hippocampal function.
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.
A conserved juxtacrine signal regulates synaptic partner recognition in Caenorhabditis elegans
2011-01-01
Background An essential stage of neural development involves the assembly of neural circuits via formation of inter-neuronal connections. Early steps in neural circuit formation, including cell migration, axon guidance, and the localization of synaptic components, are well described. However, upon reaching their target region, most neurites still contact many potential partners. In order to assemble functional circuits, it is critical that within this group of cells, neurons identify and form connections only with their appropriate partners, a process we call synaptic partner recognition (SPR). To understand how SPR is mediated, we previously developed a genetically encoded fluorescent trans-synaptic marker called NLG-1 GRASP, which labels synaptic contacts between individual neurons of interest in dense cellular environments in the genetic model organism Caenorhabditis elegans. Results Here, we describe the first use of NLG-1 GRASP technology, to identify SPR genes that function in this critical process. The NLG-1 GRASP system allows us to assess synaptogenesis between PHB sensory neurons and AVA interneurons instantly in live animals, making genetic analysis feasible. Additionally, we employ a behavioral assay to specifically test PHB sensory circuit function. Utilizing this approach, we reveal a new role for the secreted UNC-6/Netrin ligand and its transmembrane receptor UNC-40/Deleted in colorectal cancer (DCC) in SPR. Synapses between PHB and AVA are severely reduced in unc-6 and unc-40 animals despite normal axon guidance and subcellular localization of synaptic components. Additionally, behavioral defects indicate a complete disruption of PHB circuit function in unc-40 mutants. Our data indicate that UNC-40 and UNC-6 function in PHB and AVA, respectively, to specify SPR. Strikingly, overexpression of UNC-6 in postsynaptic neurons is sufficient to promote increased PHB-AVA synaptogenesis and to potentiate the behavioral response beyond wild-type levels. Furthermore, an artificially membrane-tethered UNC-6 expressed in the postsynaptic neurons promotes SPR, consistent with a short-range signal between adjacent synaptic partners. Conclusions These results indicate that the conserved UNC-6/Netrin-UNC-40/DCC ligand-receptor pair has a previously unknown function, acting in a juxtacrine manner to specify recognition of individual postsynaptic neurons. Furthermore, they illustrate the potential of this new approach, combining NLG-1 GRASP and behavioral analysis, in gene discovery and characterization. PMID:21663630
ERIC Educational Resources Information Center
Schacher, Samuel; Hu, Jiang-Yuan
2014-01-01
An important cellular mechanism contributing to the strength and duration of memories is activity-dependent alterations in the strength of synaptic connections within the neural circuit encoding the memory. Reversal of the memory is typically correlated with a reversal of the cellular changes to levels expressed prior to the stimulation. Thus, for…
Solanka, Lukas; van Rossum, Mark CW; Nolan, Matthew F
2015-01-01
Neural computations underlying cognitive functions require calibration of the strength of excitatory and inhibitory synaptic connections and are associated with modulation of gamma frequency oscillations in network activity. However, principles relating gamma oscillations, synaptic strength and circuit computations are unclear. We address this in attractor network models that account for grid firing and theta-nested gamma oscillations in the medial entorhinal cortex. We show that moderate intrinsic noise massively increases the range of synaptic strengths supporting gamma oscillations and grid computation. With moderate noise, variation in excitatory or inhibitory synaptic strength tunes the amplitude and frequency of gamma activity without disrupting grid firing. This beneficial role for noise results from disruption of epileptic-like network states. Thus, moderate noise promotes independent control of multiplexed firing rate- and gamma-based computational mechanisms. Our results have implications for tuning of normal circuit function and for disorders associated with changes in gamma oscillations and synaptic strength. DOI: http://dx.doi.org/10.7554/eLife.06444.001 PMID:26146940
McNamara, Robert K; Vannest, Jennifer J; Valentine, Christina J
2015-01-01
Accumulating translational evidence suggests that the long-chain omega-3 fatty acid docosahexaenoic acid (DHA) plays a role in the maturation and stability of cortical circuits that are impaired in different recurrent psychiatric disorders. Specifically, rodent and cell culture studies find that DHA preferentially accumulates in synaptic and growth cone membranes and promotes neurite outgrowth, dendritic spine stability, and synaptogenesis. Additional evidence suggests that DHA may play a role in microglia-mediated synaptic pruning, as well as myelin development and resilience. In non-human primates n-3 fatty acid insufficiency during perinatal development leads to widespread deficits in functional connectivity in adult frontal cortical networks compared to primates raised on DHA-fortified diet. Preterm delivery in non-human primates and humans is associated with early deficits in cortical DHA accrual. Human preterm birth is associated with long-standing deficits in myelin integrity and cortical circuit connectivity and increased risk for attention deficit/hyperactivity disorder (ADHD), mood, and psychotic disorders. In general, ADHD and mood and psychotic disorders initially emerge during rapid periods of cortical circuit maturation and are characterized by DHA deficits, myelin pathology, and impaired cortical circuit connectivity. Together these associations suggest that early and uncorrected deficits in fetal brain DHA accrual may represent a modifiable risk factor for cortical circuit maturation deficits in psychiatric disorders, and could therefore have significant implications for informing early intervention and prevention strategies. PMID:25815252
Spatiotemporal discrimination in neural networks with short-term synaptic plasticity
NASA Astrophysics Data System (ADS)
Shlaer, Benjamin; Miller, Paul
2015-03-01
Cells in recurrently connected neural networks exhibit bistability, which allows for stimulus information to persist in a circuit even after stimulus offset, i.e. short-term memory. However, such a system does not have enough hysteresis to encode temporal information about the stimuli. The biophysically described phenomenon of synaptic depression decreases synaptic transmission strengths due to increased presynaptic activity. This short-term reduction in synaptic strengths can destabilize attractor states in excitatory recurrent neural networks, causing the network to move along stimulus dependent dynamical trajectories. Such a network can successfully separate amplitudes and durations of stimuli from the number of successive stimuli. Stimulus number, duration and intensity encoding in randomly connected attractor networks with synaptic depression. Front. Comput. Neurosci. 7:59., and so provides a strong candidate network for the encoding of spatiotemporal information. Here we explicitly demonstrate the capability of a recurrent neural network with short-term synaptic depression to discriminate between the temporal sequences in which spatial stimuli are presented.
From synapses to behavior: development of a sensory-motor circuit in the leech.
Marin-Burgin, Antonia; Kristan, William B; French, Kathleen A
2008-05-01
The development of neuronal circuits has been advanced greatly by the use of imaging techniques that reveal the activity of neurons during the period when they are constructing synapses and forming circuits. This review focuses on experiments performed in leech embryos to characterize the development of a neuronal circuit that produces a simple segmental behavior called "local bending." The experiments combined electrophysiology, anatomy, and FRET-based voltage-sensitive dyes (VSDs). The VSDs offered two major advantages in these experiments: they allowed us to record simultaneously the activity of many neurons, and unlike other imaging techniques, they revealed inhibition as well as excitation. The results indicated that connections within the circuit are formed in a predictable sequence: initially neurons in the circuit are connected by electrical synapses, forming a network that itself generates an embryonic behavior and prefigures the adult circuit; later chemical synapses, including inhibitory connections, appear, "sculpting" the circuit to generate a different, mature behavior. In this developmental process, some of the electrical connections are completely replaced by chemical synapses, others are maintained into adulthood, and still others persist and share their targets with chemical synaptic connections.
Kwon, Osung; Feng, Linqing; Druckmann, Shaul; Kim, Jinhyun
2018-05-30
Neural circuits, governed by a complex interplay between excitatory and inhibitory neurons, are the substrate for information processing, and the organization of synaptic connectivity in neural network is an important determinant of circuit function. Here, we analyzed the fine structure of connectivity in hippocampal CA1 excitatory and inhibitory neurons innervated by Schaffer collaterals (SCs) using mGRASP in male mice. Our previous study revealed spatially structured synaptic connectivity between CA3 and CA1 pyramidal cells (PCs). Surprisingly, parvalbumin-positive interneurons (PVs) showed a significantly more random pattern spatial structure. Notably, application of Peters' rule for synapse prediction by random overlap between axons and dendrites enhanced structured connectivity in PCs, but, by contrast, made the connectivity pattern in PVs more random. In addition, PCs in a deep sublayer of striatum pyramidale appeared more highly structured than PCs in superficial layers, and little or no sublayer specificity was found in PVs. Our results show that CA1 excitatory PCs and inhibitory PVs innervated by the same SC inputs follow different connectivity rules. The different organizations of fine scale structured connectivity in hippocampal excitatory and inhibitory neurons provide important insights into the development and functions of neural networks. SIGNIFICANCE STATEMENT Understanding how neural circuits generate behavior is one of the central goals of neuroscience. An important component of this endeavor is the mapping of fine-scale connection patterns that underlie, and help us infer, signal processing in the brain. Here, using our recently developed synapse detection technology (mGRASP and neuTube), we provide detailed profiles of synaptic connectivity in excitatory (CA1 pyramidal) and inhibitory (CA1 parvalbumin-positive) neurons innervated by the same presynaptic inputs (CA3 Schaffer collaterals). Our results reveal that these two types of CA1 neurons follow different connectivity patterns. Our new evidence for differently structured connectivity at a fine scale in hippocampal excitatory and inhibitory neurons provides a better understanding of hippocampal networks and will guide theoretical and experimental studies. Copyright © 2018 the authors 0270-6474/18/385140-13$15.00/0.
Signal processing in local neuronal circuits based on activity-dependent noise and competition
NASA Astrophysics Data System (ADS)
Volman, Vladislav; Levine, Herbert
2009-09-01
We study the characteristics of weak signal detection by a recurrent neuronal network with plastic synaptic coupling. It is shown that in the presence of an asynchronous component in synaptic transmission, the network acquires selectivity with respect to the frequency of weak periodic stimuli. For nonperiodic frequency-modulated stimuli, the response is quantified by the mutual information between input (signal) and output (network's activity) and is optimized by synaptic depression. Introducing correlations in signal structure resulted in the decrease in input-output mutual information. Our results suggest that in neural systems with plastic connectivity, information is not merely carried passively by the signal; rather, the information content of the signal itself might determine the mode of its processing by a local neuronal circuit.
Axonal synapse sorting in medial entorhinal cortex
NASA Astrophysics Data System (ADS)
Schmidt, Helene; Gour, Anjali; Straehle, Jakob; Boergens, Kevin M.; Brecht, Michael; Helmstaedter, Moritz
2017-09-01
Research on neuronal connectivity in the cerebral cortex has focused on the existence and strength of synapses between neurons, and their location on the cell bodies and dendrites of postsynaptic neurons. The synaptic architecture of individual presynaptic axonal trees, however, remains largely unknown. Here we used dense reconstructions from three-dimensional electron microscopy in rats to study the synaptic organization of local presynaptic axons in layer 2 of the medial entorhinal cortex, the site of grid-like spatial representations. We observe path-length-dependent axonal synapse sorting, such that axons of excitatory neurons sequentially target inhibitory neurons followed by excitatory neurons. Connectivity analysis revealed a cellular feedforward inhibition circuit involving wide, myelinated inhibitory axons and dendritic synapse clustering. Simulations show that this high-precision circuit can control the propagation of synchronized activity in the medial entorhinal cortex, which is known for temporally precise discharges.
Pirri, Jennifer K; Rayes, Diego; Alkema, Mark J
2015-01-01
Behavioral output of neural networks depends on a delicate balance between excitatory and inhibitory synaptic connections. However, it is not known whether network formation and stability is constrained by the sign of synaptic connections between neurons within the network. Here we show that switching the sign of a synapse within a neural circuit can reverse the behavioral output. The inhibitory tyramine-gated chloride channel, LGC-55, induces head relaxation and inhibits forward locomotion during the Caenorhabditis elegans escape response. We switched the ion selectivity of an inhibitory LGC-55 anion channel to an excitatory LGC-55 cation channel. The engineered cation channel is properly trafficked in the native neural circuit and results in behavioral responses that are opposite to those produced by activation of the LGC-55 anion channel. Our findings indicate that switches in ion selectivity of ligand-gated ion channels (LGICs) do not affect network connectivity or stability and may provide an evolutionary and a synthetic mechanism to change behavior.
Kim, Byunghyuk; Emmons, Scott W
2017-09-13
Nervous system function relies on precise synaptic connections. A number of widely-conserved cell adhesion proteins are implicated in cell recognition between synaptic partners, but how these proteins act as a group to specify a complex neural network is poorly understood. Taking advantage of known connectivity in C. elegans , we identified and studied cell adhesion genes expressed in three interacting neurons in the mating circuits of the adult male. Two interacting pairs of cell surface proteins independently promote fasciculation between sensory neuron HOA and its postsynaptic target interneuron AVG: BAM-2/neurexin-related in HOA binds to CASY-1/calsyntenin in AVG; SAX-7/L1CAM in sensory neuron PHC binds to RIG-6/contactin in AVG. A third, basal pathway results in considerable HOA-AVG fasciculation and synapse formation in the absence of the other two. The features of this multiplexed mechanism help to explain how complex connectivity is encoded and robustly established during nervous system development.
Relaxation oscillator-realized artificial electronic neurons, their responses, and noise
NASA Astrophysics Data System (ADS)
Lim, Hyungkwang; Ahn, Hyung-Woo; Kornijcuk, Vladimir; Kim, Guhyun; Seok, Jun Yeong; Kim, Inho; Hwang, Cheol Seong; Jeong, Doo Seok
2016-05-01
A proof-of-concept relaxation oscillator-based leaky integrate-and-fire (ROLIF) neuron circuit is realized by using an amorphous chalcogenide-based threshold switch and non-ideal operational amplifier (op-amp). The proposed ROLIF neuron offers biologically plausible features such as analog-type encoding, signal amplification, unidirectional synaptic transmission, and Poisson noise. The synaptic transmission between pre- and postsynaptic neurons is achieved through a passive synapse (simple resistor). The synaptic resistor coupled to the non-ideal op-amp realizes excitatory postsynaptic potential (EPSP) evolution that evokes postsynaptic neuron spiking. In an attempt to generalize our proposed model, we theoretically examine ROLIF neuron circuits adopting different non-ideal op-amps having different gains and slew rates. The simulation results indicate the importance of gain in postsynaptic neuron spiking, irrespective of the slew rate (as long as the rate exceeds a particular value), providing the basis for the ROLIF neuron circuit design. Eventually, the behavior of a postsynaptic neuron in connection to multiple presynaptic neurons via synapses is highlighted in terms of EPSP evolution amid simultaneously incident asynchronous presynaptic spikes, which in fact reveals an important role of the random noise in spatial integration.A proof-of-concept relaxation oscillator-based leaky integrate-and-fire (ROLIF) neuron circuit is realized by using an amorphous chalcogenide-based threshold switch and non-ideal operational amplifier (op-amp). The proposed ROLIF neuron offers biologically plausible features such as analog-type encoding, signal amplification, unidirectional synaptic transmission, and Poisson noise. The synaptic transmission between pre- and postsynaptic neurons is achieved through a passive synapse (simple resistor). The synaptic resistor coupled to the non-ideal op-amp realizes excitatory postsynaptic potential (EPSP) evolution that evokes postsynaptic neuron spiking. In an attempt to generalize our proposed model, we theoretically examine ROLIF neuron circuits adopting different non-ideal op-amps having different gains and slew rates. The simulation results indicate the importance of gain in postsynaptic neuron spiking, irrespective of the slew rate (as long as the rate exceeds a particular value), providing the basis for the ROLIF neuron circuit design. Eventually, the behavior of a postsynaptic neuron in connection to multiple presynaptic neurons via synapses is highlighted in terms of EPSP evolution amid simultaneously incident asynchronous presynaptic spikes, which in fact reveals an important role of the random noise in spatial integration. Electronic supplementary information (ESI) available. See DOI: 10.1039/c6nr01278g
[Structural plasticity associated with drugs addiction].
Zhu, Jie; Cao, Guo-fen; Dang, Yong-hui; Chen, Teng
2011-12-01
An essential feature of drug addiction is that an individual continues to use drug despite the threat of severely adverse physical or psychosocial consequences. Persistent changes in behavior and psychological function that occur as a function of drugs of abuse are thought to be due to the reorganization of synaptic connections (structural plasticity) in relevant brain circuits (especially the brains reward circuits). In this paper we summarized evidence that, indeed, exposure to amphetamine, cocaine, nicotine or morphine produced persistent changes in the structure of dendrites and dendritic spines on cells in relevant brain regions. We also approached the potential molecular mechanisms of these changes. It is suggested that structural plasticity associated with exposure to drugs of abuse reflects a reorganization of patterns of synaptic connectivity in these neural systems, a reorganization that alters their operation, thus contributing to some of the persistent sequela associated with drug use-including addiction.
Macpherson, Lindsey J.; Zaharieva, Emanuela E.; Kearney, Patrick J.; Alpert, Michael H.; Lin, Tzu-Yang; Turan, Zeynep; Lee, Chi-Hon; Gallio, Marco
2015-01-01
Determining the pattern of activity of individual connections within a neural circuit could provide insights into the computational processes that underlie brain function. Here, we develop new strategies to label active synapses by trans-synaptic fluorescence complementation in Drosophila. First, we demonstrate that a synaptobrevin-GRASP chimera functions as a powerful activity-dependent marker for synapses in vivo. Next, we create cyan and yellow variants, achieving activity-dependent, multi-colour fluorescence reconstitution across synapses (X-RASP). Our system allows for the first time retrospective labelling of synapses (rather than whole neurons) based on their activity, in multiple colours, in the same animal. As individual synapses often act as computational units in the brain, our method will promote the design of experiments that are not possible using existing techniques. Moreover, our strategies are easily adaptable to circuit mapping in any genetic system. PMID:26635273
Fife organizes synaptic vesicles and calcium channels for high-probability neurotransmitter release
Rao, Monica; Ukken, Fiona
2017-01-01
The strength of synaptic connections varies significantly and is a key determinant of communication within neural circuits. Mechanistic insight into presynaptic factors that establish and modulate neurotransmitter release properties is crucial to understanding synapse strength, circuit function, and neural plasticity. We previously identified Drosophila Piccolo-RIM-related Fife, which regulates neurotransmission and motor behavior through an unknown mechanism. Here, we demonstrate that Fife localizes and interacts with RIM at the active zone cytomatrix to promote neurotransmitter release. Loss of Fife results in the severe disruption of active zone cytomatrix architecture and molecular organization. Through electron tomographic and electrophysiological studies, we find a decrease in the accumulation of release-ready synaptic vesicles and their release probability caused by impaired coupling to Ca2+ channels. Finally, we find that Fife is essential for the homeostatic modulation of neurotransmission. We propose that Fife organizes active zones to create synaptic vesicle release sites within nanometer distance of Ca2+ channel clusters for reliable and modifiable neurotransmitter release. PMID:27998991
Mapping Inhibitory Neuronal Circuits by Laser Scanning Photostimulation
Ikrar, Taruna; Olivas, Nicholas D.; Shi, Yulin; Xu, Xiangmin
2011-01-01
Inhibitory neurons are crucial to cortical function. They comprise about 20% of the entire cortical neuronal population and can be further subdivided into diverse subtypes based on their immunochemical, morphological, and physiological properties1-4. Although previous research has revealed much about intrinsic properties of individual types of inhibitory neurons, knowledge about their local circuit connections is still relatively limited3,5,6. Given that each individual neuron's function is shaped by its excitatory and inhibitory synaptic input within cortical circuits, we have been using laser scanning photostimulation (LSPS) to map local circuit connections to specific inhibitory cell types. Compared to conventional electrical stimulation or glutamate puff stimulation, LSPS has unique advantages allowing for extensive mapping and quantitative analysis of local functional inputs to individually recorded neurons3,7-9. Laser photostimulation via glutamate uncaging selectively activates neurons perisomatically, without activating axons of passage or distal dendrites, which ensures a sub-laminar mapping resolution. The sensitivity and efficiency of LSPS for mapping inputs from many stimulation sites over a large region are well suited for cortical circuit analysis. Here we introduce the technique of LSPS combined with whole-cell patch clamping for local inhibitory circuit mapping. Targeted recordings of specific inhibitory cell types are facilitated by use of transgenic mice expressing green fluorescent proteins (GFP) in limited inhibitory neuron populations in the cortex3,10, which enables consistent sampling of the targeted cell types and unambiguous identification of the cell types recorded. As for LSPS mapping, we outline the system instrumentation, describe the experimental procedure and data acquisition, and present examples of circuit mapping in mouse primary somatosensory cortex. As illustrated in our experiments, caged glutamate is activated in a spatially restricted region of the brain slice by UV laser photolysis; simultaneous voltage-clamp recordings allow detection of photostimulation-evoked synaptic responses. Maps of either excitatory or inhibitory synaptic input to the targeted neuron are generated by scanning the laser beam to stimulate hundreds of potential presynaptic sites. Thus, LSPS enables the construction of detailed maps of synaptic inputs impinging onto specific types of inhibitory neurons through repeated experiments. Taken together, the photostimulation-based technique offers neuroscientists a powerful tool for determining the functional organization of local cortical circuits. PMID:22006064
Optogenetic rewiring of thalamocortical circuits to restore function in the stroke injured brain
Tennant, Kelly A.; Taylor, Stephanie L.; White, Emily R.; Brown, Craig E.
2017-01-01
To regain sensorimotor functions after stroke, surviving neural circuits must reorganize and form new connections. Although the thalamus is critical for processing and relaying sensory information to the cortex, little is known about how stroke affects the structure and function of these connections, or whether a therapeutic approach targeting these circuits can improve recovery. Here we reveal with in vivo calcium imaging that stroke in somatosensory cortex dampens the excitability of surviving thalamocortical circuits. Given this deficit, we hypothesized that chronic transcranial window optogenetic stimulation of thalamocortical axons could facilitate recovery. Using two-photon imaging, we show that optogenetic stimulation promotes the formation of new and stable thalamocortical synaptic boutons, without impacting axon branch dynamics. Stimulation also enhances the recovery of somatosensory cortical circuit function and forepaw sensorimotor abilities. These results demonstrate that an optogenetic approach can rewire thalamocortical circuits and restore function in the damaged brain. PMID:28643802
Bennett, James E. M.; Bair, Wyeth
2015-01-01
Traveling waves in the developing brain are a prominent source of highly correlated spiking activity that may instruct the refinement of neural circuits. A candidate mechanism for mediating such refinement is spike-timing dependent plasticity (STDP), which translates correlated activity patterns into changes in synaptic strength. To assess the potential of these phenomena to build useful structure in developing neural circuits, we examined the interaction of wave activity with STDP rules in simple, biologically plausible models of spiking neurons. We derive an expression for the synaptic strength dynamics showing that, by mapping the time dependence of STDP into spatial interactions, traveling waves can build periodic synaptic connectivity patterns into feedforward circuits with a broad class of experimentally observed STDP rules. The spatial scale of the connectivity patterns increases with wave speed and STDP time constants. We verify these results with simulations and demonstrate their robustness to likely sources of noise. We show how this pattern formation ability, which is analogous to solutions of reaction-diffusion systems that have been widely applied to biological pattern formation, can be harnessed to instruct the refinement of postsynaptic receptive fields. Our results hold for rich, complex wave patterns in two dimensions and over several orders of magnitude in wave speeds and STDP time constants, and they provide predictions that can be tested under existing experimental paradigms. Our model generalizes across brain areas and STDP rules, allowing broad application to the ubiquitous occurrence of traveling waves and to wave-like activity patterns induced by moving stimuli. PMID:26308406
Bennett, James E M; Bair, Wyeth
2015-08-01
Traveling waves in the developing brain are a prominent source of highly correlated spiking activity that may instruct the refinement of neural circuits. A candidate mechanism for mediating such refinement is spike-timing dependent plasticity (STDP), which translates correlated activity patterns into changes in synaptic strength. To assess the potential of these phenomena to build useful structure in developing neural circuits, we examined the interaction of wave activity with STDP rules in simple, biologically plausible models of spiking neurons. We derive an expression for the synaptic strength dynamics showing that, by mapping the time dependence of STDP into spatial interactions, traveling waves can build periodic synaptic connectivity patterns into feedforward circuits with a broad class of experimentally observed STDP rules. The spatial scale of the connectivity patterns increases with wave speed and STDP time constants. We verify these results with simulations and demonstrate their robustness to likely sources of noise. We show how this pattern formation ability, which is analogous to solutions of reaction-diffusion systems that have been widely applied to biological pattern formation, can be harnessed to instruct the refinement of postsynaptic receptive fields. Our results hold for rich, complex wave patterns in two dimensions and over several orders of magnitude in wave speeds and STDP time constants, and they provide predictions that can be tested under existing experimental paradigms. Our model generalizes across brain areas and STDP rules, allowing broad application to the ubiquitous occurrence of traveling waves and to wave-like activity patterns induced by moving stimuli.
Convergent synaptic and circuit substrates underlying autism genetic risks.
McGee, Aaron; Li, Guohui; Lu, Zhongming; Qiu, Shenfeng
2014-02-01
There has been a surge of diagnosis of autism spectrum disorders (ASD) over the past decade. While large, high powered genome screening studies of children with ASD have identified numerous genetic risk factors, research efforts to understanding how each of these risk factors contributes to the development autism has met with limited success. Revealing the mechanisms by which these genetic risk factors affect brain development and predispose a child to autism requires mechanistic understanding of the neurobiological changes underlying this devastating group of developmental disorders at multifaceted molecular, cellular and system levels. It has been increasingly clear that the normal trajectory of neurodevelopment is compromised in autism, in multiple domains as much as aberrant neuronal production, growth, functional maturation, patterned connectivity, and balanced excitation and inhibition of brain networks. Many autism risk factors identified in humans have been now reconstituted in experimental mouse models to allow mechanistic interrogation of the biological role of the risk gene. Studies utilizing these mouse models have revealed that underlying the enormous heterogeneity of perturbed cellular events, mechanisms directing synaptic and circuit assembly may provide a unifying explanation for the pathophysiological changes and behavioral endophenotypes seen in autism, although synaptic perturbations are far from being the only alterations relevant for ASD. In this review, we discuss synaptic and circuit abnormalities obtained from several prevalent mouse models, particularly those reflecting syndromic forms of ASD that are caused by single gene perturbations. These compiled results reveal that ASD risk genes contribute to proper signaling of the developing gene networks that maintain synaptic and circuit homeostasis, which is fundamental to normal brain development.
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.
Lou, Xuelin
2018-01-01
The intact synaptic structure is critical for information processing in neural circuits. During synaptic transmission, rapid vesicle exocytosis increases the size of never terminals and endocytosis counteracts the increase. Accumulating evidence suggests that SV exocytosis and endocytosis are tightly connected in time and space during SV recycling, and this process is essential for synaptic function and structural stability. Research in the past has illustrated the molecular details of synaptic vesicle (SV) exocytosis and endocytosis; however, the mechanisms that timely connect these two fundamental events are poorly understood at central synapses. Here we discuss recent progress in SV recycling and summarize several emerging mechanisms by which synapses can “sense” the occurrence of exocytosis and timely initiate compensatory endocytosis. They include Ca2+ sensing, SV proteins sensing, and local membrane stress sensing. In addition, the spatial organization of endocytic zones adjacent to active zones provides a structural basis for efficient coupling between SV exocytosis and endocytosis. Through linking different endocytosis pathways with SV fusion, these mechanisms ensure necessary plasticity and robustness of nerve terminals to meet diverse physiological needs. PMID:29593500
Barrows, Caitlynn M; McCabe, Matthew P; Chen, Hongmei; Swann, John W; Weston, Matthew C
2017-09-06
Changes in synaptic strength and connectivity are thought to be a major mechanism through which many gene variants cause neurological disease. Hyperactivation of the PI3K-mTOR signaling network, via loss of function of repressors such as PTEN, causes epilepsy in humans and animal models, and altered mTOR signaling may contribute to a broad range of neurological diseases. Changes in synaptic transmission have been reported in animal models of PTEN loss; however, the full extent of these changes, and their effect on network function, is still unknown. To better understand the scope of these changes, we recorded from pairs of mouse hippocampal neurons cultured in a two-neuron microcircuit configuration that allowed us to characterize all four major connection types within the hippocampus. Loss of PTEN caused changes in excitatory and inhibitory connectivity, and these changes were postsynaptic, presynaptic, and transynaptic, suggesting that disruption of PTEN has the potential to affect most connection types in the hippocampal circuit. Given the complexity of the changes at the synaptic level, we measured changes in network behavior after deleting Pten from neurons in an organotypic hippocampal slice network. Slices containing Pten -deleted neurons showed increased recruitment of neurons into network bursts. Importantly, these changes were not confined to Pten -deleted neurons, but involved the entire network, suggesting that the extensive changes in synaptic connectivity rewire the entire network in such a way that promotes a widespread increase in functional connectivity. SIGNIFICANCE STATEMENT Homozygous deletion of the Pten gene in neuronal subpopulations in the mouse serves as a valuable model of epilepsy caused by mTOR hyperactivation. To better understand how gene deletions lead to altered neuronal activity, we investigated the synaptic and network effects that occur 1 week after Pten deletion. PTEN loss increased the connectivity of all four types of hippocampal synaptic connections, including two forms of increased inhibition of inhibition, and increased network functional connectivity. These data suggest that single gene mutations that cause neurological diseases such as epilepsy may affect a surprising range of connection types. Moreover, given the robustness of homeostatic plasticity, these diverse effects on connection types may be necessary to cause network phenotypes such as increased synchrony. Copyright © 2017 the authors 0270-6474/17/378595-17$15.00/0.
McCabe, Matthew P.; Chen, Hongmei; Swann, John W.
2017-01-01
Changes in synaptic strength and connectivity are thought to be a major mechanism through which many gene variants cause neurological disease. Hyperactivation of the PI3K-mTOR signaling network, via loss of function of repressors such as PTEN, causes epilepsy in humans and animal models, and altered mTOR signaling may contribute to a broad range of neurological diseases. Changes in synaptic transmission have been reported in animal models of PTEN loss; however, the full extent of these changes, and their effect on network function, is still unknown. To better understand the scope of these changes, we recorded from pairs of mouse hippocampal neurons cultured in a two-neuron microcircuit configuration that allowed us to characterize all four major connection types within the hippocampus. Loss of PTEN caused changes in excitatory and inhibitory connectivity, and these changes were postsynaptic, presynaptic, and transynaptic, suggesting that disruption of PTEN has the potential to affect most connection types in the hippocampal circuit. Given the complexity of the changes at the synaptic level, we measured changes in network behavior after deleting Pten from neurons in an organotypic hippocampal slice network. Slices containing Pten-deleted neurons showed increased recruitment of neurons into network bursts. Importantly, these changes were not confined to Pten-deleted neurons, but involved the entire network, suggesting that the extensive changes in synaptic connectivity rewire the entire network in such a way that promotes a widespread increase in functional connectivity. SIGNIFICANCE STATEMENT Homozygous deletion of the Pten gene in neuronal subpopulations in the mouse serves as a valuable model of epilepsy caused by mTOR hyperactivation. To better understand how gene deletions lead to altered neuronal activity, we investigated the synaptic and network effects that occur 1 week after Pten deletion. PTEN loss increased the connectivity of all four types of hippocampal synaptic connections, including two forms of increased inhibition of inhibition, and increased network functional connectivity. These data suggest that single gene mutations that cause neurological diseases such as epilepsy may affect a surprising range of connection types. Moreover, given the robustness of homeostatic plasticity, these diverse effects on connection types may be necessary to cause network phenotypes such as increased synchrony. PMID:28751459
Input clustering in the normal and learned circuits of adult barn owls.
McBride, Thomas J; DeBello, William M
2015-05-01
Experience-dependent formation of synaptic input clusters can occur in juvenile brains. Whether this also occurs in adults is largely unknown. We previously reconstructed the normal and learned circuits of prism-adapted barn owls and found that changes in clustering of axo-dendritic contacts (putative synapses) predicted functional circuit strength. Here we asked whether comparable changes occurred in normal and prism-removed adults. Across all anatomical zones, no systematic differences in the primary metrics for within-branch or between-branch clustering were observed: 95-99% of contacts resided within clusters (<10-20 μm from nearest neighbor) regardless of circuit strength. Bouton volumes, a proxy measure of synaptic strength, were on average larger in the functionally strong zones, indicating that changes in synaptic efficacy contributed to the differences in circuit strength. Bootstrap analysis showed that the distribution of inter-contact distances strongly deviated from random not in the functionally strong zones but in those that had been strong during the sensitive period (60-250 d), indicating that clusters formed early in life were preserved regardless of current value. While cluster formation in juveniles appeared to require the production of new synapses, cluster formation in adults did not. In total, these results support a model in which high cluster dynamics in juveniles sculpt a potential connectivity map that is refined in adulthood. We propose that preservation of clusters in functionally weak adult circuits provides a storage mechanism for disused but potentially useful pathways. Copyright © 2015 Elsevier Inc. All rights reserved.
Simmons, Aaron B.; Bloomsburg, Samuel J.; Sukeena, Joshua M.; Miller, Calvin J.; Ortega-Burgos, Yohaniz; Borghuis, Bart G.
2017-01-01
Mature mammalian neurons have a limited ability to extend neurites and make new synaptic connections, but the mechanisms that inhibit such plasticity remain poorly understood. Here, we report that OFF-type retinal bipolar cells in mice are an exception to this rule, as they form new anatomical connections within their tiled dendritic fields well after retinal maturity. The Down syndrome cell-adhesion molecule (Dscam) confines these anatomical rearrangements within the normal tiled fields, as conditional deletion of the gene permits extension of dendrite and axon arbors beyond these borders. Dscam deletion in the mature retina results in expanded dendritic fields and increased cone photoreceptor contacts, demonstrating that DSCAM actively inhibits circuit-level plasticity. Electrophysiological recordings from Dscam−/− OFF bipolar cells showed enlarged visual receptive fields, demonstrating that expanded dendritic territories comprise functional synapses. Our results identify cell-adhesion molecule-mediated inhibition as a regulator of circuit-level neuronal plasticity in the adult retina. PMID:29114051
Weighing the Evidence in Peters' Rule: Does Neuronal Morphology Predict Connectivity?
Rees, Christopher L; Moradi, Keivan; Ascoli, Giorgio A
2017-02-01
Although the importance of network connectivity is increasingly recognized, identifying synapses remains challenging relative to the routine characterization of neuronal morphology. Thus, researchers frequently employ axon-dendrite colocations as proxies of potential connections. This putative equivalence, commonly referred to as Peters' rule, has been recently studied at multiple levels and scales, fueling passionate debates regarding its validity. Our critical literature review identifies three conceptually distinct but often confused applications: inferring neuron type circuitry, predicting synaptic contacts among individual cells, and estimating synapse numbers within neuron pairs. Paradoxically, at the originally proposed cell-type level, Peters' rule remains largely untested. Leveraging Hippocampome.org, we validate and refine the relationship between axonal-dendritic colocations and synaptic circuits, clarifying the interpretation of existing and forthcoming data. Copyright © 2016 Elsevier Ltd. All rights reserved.
Nomura, Toshihiro; Zhu, Yiwen; Remmers, Christine L.; Xu, Jian; Nicholson, Daniel A.
2017-01-01
Fragile X syndrome (FXS) is a neurodevelopmental disorder that is a leading cause of inherited intellectual disability, and the most common known cause of autism spectrum disorder. FXS is broadly characterized by sensory hypersensitivity and several developmental alterations in synaptic and circuit function have been uncovered in the sensory cortex of the mouse model of FXS (Fmr1 KO). GABA-mediated neurotransmission and fast-spiking (FS) GABAergic interneurons are central to cortical circuit development in the neonate. Here we demonstrate that there is a delay in the maturation of the intrinsic properties of FS interneurons in the sensory cortex, and a deficit in the formation of excitatory synaptic inputs on to these neurons in neonatal Fmr1 KO mice. Both these delays in neuronal and synaptic maturation were rectified by chronic administration of a TrkB receptor agonist. These results demonstrate that the maturation of the GABAergic circuit in the sensory cortex is altered during a critical developmental period due in part to a perturbation in BDNF-TrkB signaling, and could contribute to the alterations in cortical development underlying the sensory pathophysiology of FXS. SIGNIFICANCE STATEMENT Fragile X (FXS) individuals have a range of sensory related phenotypes, and there is growing evidence of alterations in neuronal circuits in the sensory cortex of the mouse model of FXS (Fmr1 KO). GABAergic interneurons are central to the correct formation of circuits during cortical critical periods. Here we demonstrate a delay in the maturation of the properties and synaptic connectivity of interneurons in Fmr1 KO mice during a critical period of cortical development. The delays both in cellular and synaptic maturation were rectified by administration of a TrkB receptor agonist, suggesting reduced BDNF-TrkB signaling as a contributing factor. These results provide evidence that the function of fast-spiking interneurons is disrupted due to a deficiency in neurotrophin signaling during early development in FXS. PMID:29038238
Tarusawa, Etsuko; Sanbo, Makoto; Okayama, Atsushi; Miyashita, Toshio; Kitsukawa, Takashi; Hirayama, Teruyoshi; Hirabayashi, Takahiro; Hasegawa, Sonoko; Kaneko, Ryosuke; Toyoda, Shunsuke; Kobayashi, Toshihiro; Kato-Itoh, Megumi; Nakauchi, Hiromitsu; Hirabayashi, Masumi; Yagi, Takeshi; Yoshimura, Yumiko
2016-12-02
The specificity of synaptic connections is fundamental for proper neural circuit function. Specific neuronal connections that underlie information processing in the sensory cortex are initially established without sensory experiences to a considerable extent, and then the connections are individually refined through sensory experiences. Excitatory neurons arising from the same single progenitor cell are preferentially connected in the postnatal cortex, suggesting that cell lineage contributes to the initial wiring of neurons. However, the postnatal developmental process of lineage-dependent connection specificity is not known, nor how clonal neurons, which are derived from the same neural stem cell, are stamped with the identity of their common neural stem cell and guided to form synaptic connections. We show that cortical excitatory neurons that arise from the same neural stem cell and reside within the same layer preferentially establish reciprocal synaptic connections in the mouse barrel cortex. We observed a transient increase in synaptic connections between clonal but not nonclonal neuron pairs during postnatal development, followed by selective stabilization of the reciprocal connections between clonal neuron pairs. Furthermore, we demonstrate that selective stabilization of the reciprocal connections between clonal neuron pairs is impaired by the deficiency of DNA methyltransferase 3b (Dnmt3b), which determines DNA-methylation patterns of genes in stem cells during early corticogenesis. Dnmt3b regulates the postnatal expression of clustered protocadherin (cPcdh) isoforms, a family of adhesion molecules. We found that cPcdh deficiency in clonal neuron pairs impairs the whole process of the formation and stabilization of connections to establish lineage-specific connection reciprocity. Our results demonstrate that local, reciprocal neural connections are selectively formed and retained between clonal neurons in layer 4 of the barrel cortex during postnatal development, and that Dnmt3b and cPcdhs are required for the establishment of lineage-specific reciprocal connections. These findings indicate that lineage-specific connection reciprocity is predetermined by Dnmt3b during embryonic development, and that the cPcdhs contribute to postnatal cortical neuron identification to guide lineage-dependent synaptic connections in the neocortex.
Transsynaptic Coordination of Synaptic Growth, Function, and Stability by the L1-Type CAM Neuroglian
Moreno, Eliza; Stephan, Raiko; Boerner, Jana; Godenschwege, Tanja A.; Pielage, Jan
2013-01-01
The precise control of synaptic connectivity is essential for the development and function of neuronal circuits. While there have been significant advances in our understanding how cell adhesion molecules mediate axon guidance and synapse formation, the mechanisms controlling synapse maintenance or plasticity in vivo remain largely uncharacterized. In an unbiased RNAi screen we identified the Drosophila L1-type CAM Neuroglian (Nrg) as a central coordinator of synapse growth, function, and stability. We demonstrate that the extracellular Ig-domains and the intracellular Ankyrin-interaction motif are essential for synapse development and stability. Nrg binds to Ankyrin2 in vivo and mutations reducing the binding affinities to Ankyrin2 cause an increase in Nrg mobility in motoneurons. We then demonstrate that the Nrg–Ank2 interaction controls the balance of synapse growth and stability at the neuromuscular junction. In contrast, at a central synapse, transsynaptic interactions of pre- and postsynaptic Nrg require a dynamic, temporal and spatial, regulation of the intracellular Ankyrin-binding motif to coordinate pre- and postsynaptic development. Our study at two complementary model synapses identifies the regulation of the interaction between the L1-type CAM and Ankyrin as an important novel module enabling local control of synaptic connectivity and function while maintaining general neuronal circuit architecture. PMID:23610557
Enneking, Eva-Maria; Kudumala, Sirisha R; Moreno, Eliza; Stephan, Raiko; Boerner, Jana; Godenschwege, Tanja A; Pielage, Jan
2013-01-01
The precise control of synaptic connectivity is essential for the development and function of neuronal circuits. While there have been significant advances in our understanding how cell adhesion molecules mediate axon guidance and synapse formation, the mechanisms controlling synapse maintenance or plasticity in vivo remain largely uncharacterized. In an unbiased RNAi screen we identified the Drosophila L1-type CAM Neuroglian (Nrg) as a central coordinator of synapse growth, function, and stability. We demonstrate that the extracellular Ig-domains and the intracellular Ankyrin-interaction motif are essential for synapse development and stability. Nrg binds to Ankyrin2 in vivo and mutations reducing the binding affinities to Ankyrin2 cause an increase in Nrg mobility in motoneurons. We then demonstrate that the Nrg-Ank2 interaction controls the balance of synapse growth and stability at the neuromuscular junction. In contrast, at a central synapse, transsynaptic interactions of pre- and postsynaptic Nrg require a dynamic, temporal and spatial, regulation of the intracellular Ankyrin-binding motif to coordinate pre- and postsynaptic development. Our study at two complementary model synapses identifies the regulation of the interaction between the L1-type CAM and Ankyrin as an important novel module enabling local control of synaptic connectivity and function while maintaining general neuronal circuit architecture.
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.
Structure and plasticity potential of neural networks in the cerebral cortex
NASA Astrophysics Data System (ADS)
Fares, Tarec Edmond
In this thesis, we first described a theoretical framework for the analysis of spine remodeling plasticity. We provided a quantitative description of two models of spine remodeling in which the presence of a bouton is either required or not for the formation of a new synapse. We derived expressions for the density of potential synapses in the neuropil, the connectivity fraction, which is the ratio of actual to potential synapses, and the number of structurally different circuits attainable with spine remodeling. We calculated these parameters in mouse occipital cortex, rat CA1, monkey V1, and human temporal cortex. We found that on average a dendritic spine can choose among 4-7 potential targets in rodents and 10-20 potential targets in primates. The neuropil's potential for structural circuit remodeling is highest in rat CA1 (7.1-8.6 bits/mum3) and lowest in monkey V1 (1.3-1.5 bits/mum 3 We next studied the role neuron morphology plays in defining synaptic connectivity. As previously stated it is clear that only pairs of neurons with closely positioned axonal and dendritic branches can be synaptically coupled. For excitatory neurons in the cerebral cortex, ). We also evaluated the lower bound of neuron selectivity in the choice of synaptic partners. 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. We next studied the role neuron morphology plays in defining synaptic connectivity. As previously stated it is clear that only pairs of neurons with closely positioned axonal and dendritic branches can be synaptically coupled. For excitatory neurons in the cerebral cortex, such axo-dendritic oppositions, or potential synapses, must be bridged by dendritic spines to form synaptic connections. To explore the rules by which synaptic connections are formed within the constraints imposed by neuron morphology, we compared the distributions of the numbers of actual and potential synapses between pre- and post-synaptic neurons forming different laminar projections in rat barrel cortex. Quantitative comparison explicitly ruled out the hypothesis that individual synapses between neurons are formed independently of each other. Instead, the data are consistent with a cooperative scheme of synapse formation, where multiple-synaptic connections between neurons are stabilized, while neurons that do not establish a critical number of synapses are not likely to remain synaptically coupled. In the above two projects, analysis of potential synapse numbers played an important role in shaping our understanding of connectivity and structural plasticity. In the third part of this thesis, we shift our attention to the study of the distribution of potential synapse numbers. This distribution is dependent on the details of neuron morphology and it defines synaptic connectivity patterns attainable with spine remodeling. To better understand how the distribution of potential synapse numbers is influenced by the overlap and the shapes of axonal and dendritic arbors, we first analyzed uniform disconnected arbors generated in silico. The resulting distributions are well described by binomial functions. We used a dataset of neurons reconstructed in 3D and generated the potential synapse distributions for neurons of different classes. Quantitative analysis showed that the binomial distribution is a good fit to this data as well. All distributions considered clustered into two categories, inhibitory to inhibitory and excitatory to excitatory projections. We showed that the distributions of potential synapse numbers are universally described by a family of single parameter (p) binomial functions, where p = 0.08, and for the inhibitory and p = 0.19 for the excitatory projections. In the last part of this thesis an attempt is made to incorporate some of the biological constraints we considered thus far, into an artificial neural network model. It became clear that several features of synaptic connectivity are ubiquitous among different cortical networks: (1) neural networks are predominately excitatory, containing roughly 80% of excitatory neurons and synapses, (2) neural networks are only sparsely interconnected, where the probabilities of finding connected neurons are always less than 50% even for neighboring cells, (3) the distribution of connection strengths has been shown to have a slow non-exponential decay. In the attempt to understand the advantage of such network architecture for learning and memory, we analyzed the associative memory capacity of a biologically constrained perceptron-like neural network model. The artificial neural network we consider consists of robust excitatory and inhibitory McCulloch and Pitts neurons with a constant firing threshold. Our theoretical results show that the capacity for associative memory storage in such networks increases with an addition of a small fraction of inhibitory neurons, while the connection probability remains below 50%. (Abstract shortened by UMI.)
Zhou, Li; Liu, Ming-Zhe; Li, Qing; Deng, Juan; Mu, Di; Sun, Yan-Gang
2017-03-21
Serotonergic neurons play key roles in various biological processes. However, circuit mechanisms underlying tight control of serotonergic neurons remain largely unknown. Here, we systematically investigated the organization of long-range synaptic inputs to serotonergic neurons and GABAergic neurons in the dorsal raphe nucleus (DRN) of mice with a combination of viral tracing, slice electrophysiological, and optogenetic techniques. We found that DRN serotonergic neurons and GABAergic neurons receive largely comparable synaptic inputs from six major upstream brain areas. Upon further analysis of the fine functional circuit structures, we found both bilateral and ipsilateral patterns of topographic connectivity in the DRN for the axons from different inputs. Moreover, the upstream brain areas were found to bidirectionally control the activity of DRN serotonergic neurons by recruiting feedforward inhibition or via a push-pull mechanism. Our study provides a framework for further deciphering the functional roles of long-range circuits controlling the activity of serotonergic neurons in the DRN. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.
Laminar- and Target-Specific Amygdalar Inputs in Rat Primary Gustatory Cortex.
Haley, Melissa S; Fontanini, Alfredo; Maffei, Arianna
2016-03-02
The primary gustatory cortex (GC) receives projections from the basolateral nucleus of the amygdala (BLA). Behavioral and electrophysiological studies demonstrated that this projection is involved in encoding the hedonic value of taste and is a source of anticipatory activity in GC. Anatomically, this projection is largest in the agranular portion of GC; however, its synaptic targets and synaptic properties are currently unknown. In vivo electrophysiological recordings report conflicting evidence about BLA afferents either selectively activating excitatory neurons or driving a compound response consistent with the activation of inhibitory circuits. Here we demonstrate that BLA afferents directly activate excitatory neurons and two distinct populations of inhibitory neurons in both superficial and deep layers of rat GC. BLA afferents recruit different proportions of excitatory and inhibitory neurons and show distinct patterns of circuit activation in the superficial and deep layers of GC. These results provide the first circuit-level analysis of BLA inputs to a sensory area. Laminar- and target-specific differences of BLA inputs likely explain the complexity of amygdalocortical interactions during sensory processing. Projections from the basolateral nucleus of the amygdala (BLA) to the cortex convey information about the emotional value and the expectation of a sensory stimulus. Although much work has been done to establish the behavioral role of BLA inputs to sensory cortices, very little is known about the circuit organization of BLA projections. Here we provide the first in-depth analysis of connectivity and synaptic properties of the BLA input to the gustatory cortex. We show that BLA afferents activate excitatory and inhibitory circuits in a layer-specific and pattern-specific manner. Our results provide important new information about how neural circuits establishing the hedonic value of sensory stimuli and driving anticipatory behaviors are organized at the synaptic level. Copyright © 2016 the authors 0270-6474/16/362623-15$15.00/0.
Gu, Zirong; Serradj, Najet; Ueno, Masaki; Liang, Mishi; Li, Jie; Baccei, Mark L.; Martin, John H.; Yoshida, Yutaka
2017-01-01
Early postnatal mammals, including human babies, can perform only basic motor tasks. The acquisition of skilled behaviors occurs later, requiring anatomical changes in neural circuitry to support the development of coordinated activation or suppression of functionally related muscle groups. How this circuit reorganization occurs during postnatal development remains poorly understood. Here we explore the connectivity between corticospinal (CS) neurons in the motor cortex and muscles in mice. Using trans-synaptic viral and electrophysiological assays, we identify the early postnatal reorganization of CS circuitry for antagonistic muscle pairs. We further show that this synaptic rearrangement requires the activity-dependent, non-apoptotic Bax/Bak-caspase signaling cascade. Adult Bax/Bak mutant mice exhibit aberrant co-activation of antagonistic muscle pairs and skilled grasping deficits but normal reaching and retrieval behaviors. Our findings reveal key cellular and molecular mechanisms driving postnatal motor circuit reorganization and the resulting impacts on muscle activation patterns and the execution of skilled movements. PMID:28472660
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
de Kock, Christiaan P. J.; Bruno, Randy M.; Ramirez, Alejandro; Meyer, Hanno S.; Dercksen, Vincent J.; Helmstaedter, Moritz; Sakmann, Bert
2012-01-01
Soma location, dendrite morphology, and synaptic innervation may represent key determinants of functional responses of individual neurons, such as sensory-evoked spiking. Here, we reconstruct the 3D circuits formed by thalamocortical afferents from the lemniscal pathway and excitatory neurons of an anatomically defined cortical column in rat vibrissal cortex. We objectively classify 9 cortical cell types and estimate the number and distribution of their somata, dendrites, and thalamocortical synapses. Somata and dendrites of most cell types intermingle, while thalamocortical connectivity depends strongly upon the cell type and the 3D soma location of the postsynaptic neuron. Correlating dendrite morphology and thalamocortical connectivity to functional responses revealed that the lemniscal afferents can account for some of the cell type- and location-specific subthreshold and spiking responses after passive whisker touch (e.g., in layer 4, but not for other cell types, e.g., in layer 5). Our data provides a quantitative 3D prediction of the cell type–specific lemniscal synaptic wiring diagram and elucidates structure–function relationships of this physiologically relevant pathway at single-cell resolution. PMID:22089425
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.
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.
Inhibitory Gating of Basolateral Amygdala Inputs to the Prefrontal Cortex
McGarry, Laura M.
2016-01-01
Interactions between the prefrontal cortex (PFC) and basolateral amygdala (BLA) regulate emotional behaviors. However, a circuit-level understanding of functional connections between these brain regions remains incomplete. The BLA sends prominent glutamatergic projections to the PFC, but the overall influence of these inputs is predominantly inhibitory. Here we combine targeted recordings and optogenetics to examine the synaptic underpinnings of this inhibition in the mouse infralimbic PFC. We find that BLA inputs preferentially target layer 2 corticoamygdala over neighboring corticostriatal neurons. However, these inputs make even stronger connections onto neighboring parvalbumin and somatostatin expressing interneurons. Inhibitory connections from these two populations of interneurons are also much stronger onto corticoamygdala neurons. Consequently, BLA inputs are able to drive robust feedforward inhibition via two parallel interneuron pathways. Moreover, the contributions of these interneurons shift during repetitive activity, due to differences in short-term synaptic dynamics. Thus, parvalbumin interneurons are activated at the start of stimulus trains, whereas somatostatin interneuron activation builds during these trains. Together, these results reveal how the BLA impacts the PFC through a complex interplay of direct excitation and feedforward inhibition. They also highlight the roles of targeted connections onto multiple projection neurons and interneurons in this cortical circuit. Our findings provide a mechanistic understanding for how the BLA can influence the PFC circuit, with important implications for how this circuit participates in the regulation of emotion. SIGNIFICANCE STATEMENT The prefrontal cortex (PFC) and basolateral amygdala (BLA) interact to control emotional behaviors. Here we show that BLA inputs elicit direct excitation and feedforward inhibition of layer 2 projection neurons in infralimbic PFC. BLA inputs are much stronger at corticoamygdala neurons compared with nearby corticostriatal neurons. However, these inputs are even more powerful at parvalbumin and somatostatin expressing interneurons. BLA inputs thus activate two parallel inhibitory networks, whose contributions change during repetitive activity. Finally, connections from these interneurons are also more powerful at corticoamygdala neurons compared with corticostriatal neurons. Together, our results demonstrate how the BLA predominantly inhibits the PFC via a complex sequence involving multiple cell-type and input-specific connections. PMID:27605614
Inhibitory Gating of Basolateral Amygdala Inputs to the Prefrontal Cortex.
McGarry, Laura M; Carter, Adam G
2016-09-07
Interactions between the prefrontal cortex (PFC) and basolateral amygdala (BLA) regulate emotional behaviors. However, a circuit-level understanding of functional connections between these brain regions remains incomplete. The BLA sends prominent glutamatergic projections to the PFC, but the overall influence of these inputs is predominantly inhibitory. Here we combine targeted recordings and optogenetics to examine the synaptic underpinnings of this inhibition in the mouse infralimbic PFC. We find that BLA inputs preferentially target layer 2 corticoamygdala over neighboring corticostriatal neurons. However, these inputs make even stronger connections onto neighboring parvalbumin and somatostatin expressing interneurons. Inhibitory connections from these two populations of interneurons are also much stronger onto corticoamygdala neurons. Consequently, BLA inputs are able to drive robust feedforward inhibition via two parallel interneuron pathways. Moreover, the contributions of these interneurons shift during repetitive activity, due to differences in short-term synaptic dynamics. Thus, parvalbumin interneurons are activated at the start of stimulus trains, whereas somatostatin interneuron activation builds during these trains. Together, these results reveal how the BLA impacts the PFC through a complex interplay of direct excitation and feedforward inhibition. They also highlight the roles of targeted connections onto multiple projection neurons and interneurons in this cortical circuit. Our findings provide a mechanistic understanding for how the BLA can influence the PFC circuit, with important implications for how this circuit participates in the regulation of emotion. The prefrontal cortex (PFC) and basolateral amygdala (BLA) interact to control emotional behaviors. Here we show that BLA inputs elicit direct excitation and feedforward inhibition of layer 2 projection neurons in infralimbic PFC. BLA inputs are much stronger at corticoamygdala neurons compared with nearby corticostriatal neurons. However, these inputs are even more powerful at parvalbumin and somatostatin expressing interneurons. BLA inputs thus activate two parallel inhibitory networks, whose contributions change during repetitive activity. Finally, connections from these interneurons are also more powerful at corticoamygdala neurons compared with corticostriatal neurons. Together, our results demonstrate how the BLA predominantly inhibits the PFC via a complex sequence involving multiple cell-type and input-specific connections. Copyright © 2016 the authors 0270-6474/16/369391-16$15.00/0.
Retrieval Property of Attractor Network with Synaptic Depression
NASA Astrophysics Data System (ADS)
Matsumoto, Narihisa; Ide, Daisuke; Watanabe, Masataka; Okada, Masato
2007-08-01
Synaptic connections are known to change dynamically. High-frequency presynaptic inputs induce decrease of synaptic weights. This process is known as short-term synaptic depression. The synaptic depression controls a gain for presynaptic inputs. However, it remains a controversial issue what are functional roles of this gain control. We propose a new hypothesis that one of the functional roles is to enlarge basins of attraction. To verify this hypothesis, we employ a binary discrete-time associative memory model which consists of excitatory and inhibitory neurons. It is known that the excitatory-inhibitory balance controls an overall activity of the network. The synaptic depression might incorporate an activity control mechanism. Using a mean-field theory and computer simulations, we find that the synaptic depression enlarges the basins at a small loading rate while the excitatory-inhibitory balance enlarges them at a large loading rate. Furthermore the synaptic depression does not affect the steady state of the network if a threshold is set at an appropriate value. These results suggest that the synaptic depression works in addition to the effect of the excitatory-inhibitory balance, and it might improve an error-correcting ability in cortical circuits.
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.
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
Nomura, Toshihiro; Musial, Timothy F; Marshall, John J; Zhu, Yiwen; Remmers, Christine L; Xu, Jian; Nicholson, Daniel A; Contractor, Anis
2017-11-22
Fragile X syndrome (FXS) is a neurodevelopmental disorder that is a leading cause of inherited intellectual disability, and the most common known cause of autism spectrum disorder. FXS is broadly characterized by sensory hypersensitivity and several developmental alterations in synaptic and circuit function have been uncovered in the sensory cortex of the mouse model of FXS ( Fmr1 KO). GABA-mediated neurotransmission and fast-spiking (FS) GABAergic interneurons are central to cortical circuit development in the neonate. Here we demonstrate that there is a delay in the maturation of the intrinsic properties of FS interneurons in the sensory cortex, and a deficit in the formation of excitatory synaptic inputs on to these neurons in neonatal Fmr1 KO mice. Both these delays in neuronal and synaptic maturation were rectified by chronic administration of a TrkB receptor agonist. These results demonstrate that the maturation of the GABAergic circuit in the sensory cortex is altered during a critical developmental period due in part to a perturbation in BDNF-TrkB signaling, and could contribute to the alterations in cortical development underlying the sensory pathophysiology of FXS. SIGNIFICANCE STATEMENT Fragile X (FXS) individuals have a range of sensory related phenotypes, and there is growing evidence of alterations in neuronal circuits in the sensory cortex of the mouse model of FXS ( Fmr1 KO). GABAergic interneurons are central to the correct formation of circuits during cortical critical periods. Here we demonstrate a delay in the maturation of the properties and synaptic connectivity of interneurons in Fmr1 KO mice during a critical period of cortical development. The delays both in cellular and synaptic maturation were rectified by administration of a TrkB receptor agonist, suggesting reduced BDNF-TrkB signaling as a contributing factor. These results provide evidence that the function of fast-spiking interneurons is disrupted due to a deficiency in neurotrophin signaling during early development in FXS. Copyright © 2017 the authors 0270-6474/17/3711298-13$15.00/0.
Long-Term Memory Shapes the Primary Olfactory Center of an Insect Brain
ERIC Educational Resources Information Center
Hourcade, Benoit; Perisse, Emmanuel; Devaud, Jean-Marc; Sandoz, Jean-Christophe
2009-01-01
The storage of stable memories is generally considered to rely on changes in the functional properties and/or the synaptic connectivity of neural networks. However, these changes are not easily tractable given the complexity of the learning procedures and brain circuits studied. Such a search can be narrowed down by studying memories of specific…
Selective synaptic remodeling of amygdalocortical connections associated with fear memory.
Yang, Yang; Liu, Dan-Qian; Huang, Wei; Deng, Juan; Sun, Yangang; Zuo, Yi; Poo, Mu-Ming
2016-10-01
Neural circuits underlying auditory fear conditioning have been extensively studied. Here we identified a previously unexplored pathway from the lateral amygdala (LA) to the auditory cortex (ACx) and found that selective silencing of this pathway using chemo- and optogenetic approaches impaired fear memory retrieval. Dual-color in vivo two-photon imaging of mouse ACx showed pathway-specific increases in the formation of LA axon boutons, dendritic spines of ACx layer 5 pyramidal cells, and putative LA-ACx synaptic pairs after auditory fear conditioning. Furthermore, joint imaging of pre- and postsynaptic structures showed that essentially all new synaptic contacts were made by adding new partners to existing synaptic elements. Together, these findings identify an amygdalocortical projection that is important to fear memory expression and is selectively modified by associative fear learning, and unravel a distinct architectural rule for synapse formation in the adult brain.
Attention Enhances Synaptic Efficacy and Signal-to-Noise in Neural Circuits
Briggs, Farran; Mangun, George R.; Usrey, W. Martin
2013-01-01
Summary Attention is a critical component of perception. However, the mechanisms by which attention modulates neuronal communication to guide behavior are poorly understood. To elucidate the synaptic mechanisms of attention, we developed a sensitive assay of attentional modulation of neuronal communication. In alert monkeys performing a visual spatial attention task, we probed thalamocortical communication by electrically stimulating neurons in the lateral geniculate nucleus of the thalamus while simultaneously recording shock-evoked responses from monosynaptically connected neurons in primary visual cortex. We found that attention enhances neuronal communication by (1) increasing the efficacy of presynaptic input in driving postsynaptic responses, (2) increasing synchronous responses among ensembles of postsynaptic neurons receiving independent input, and (3) decreasing redundant signals between postsynaptic neurons receiving common input. These results demonstrate that attention finely tunes neuronal communication at the synaptic level by selectively altering synaptic weights, enabling enhanced detection of salient events in the noisy sensory milieu. PMID:23803766
Synaptogenesis Is Modulated by Heparan Sulfate in Caenorhabditis elegans
Lázaro-Peña, María I.; Díaz-Balzac, Carlos A.; Bülow, Hannes E.; Emmons, Scott W.
2018-01-01
The nervous system regulates complex behaviors through a network of neurons interconnected by synapses. How specific synaptic connections are genetically determined is still unclear. Male mating is the most complex behavior in Caenorhabditis elegans. It is composed of sequential steps that are governed by > 3000 chemical connections. Here, we show that heparan sulfates (HS) play a role in the formation and function of the male neural network. HS, sulfated in position 3 by the HS modification enzyme HST-3.1/HS 3-O-sulfotransferase and attached to the HS proteoglycan glypicans LON-2/glypican and GPN-1/glypican, functions cell-autonomously and nonautonomously for response to hermaphrodite contact during mating. Loss of 3-O sulfation resulted in the presynaptic accumulation of RAB-3, a molecule that localizes to synaptic vesicles, and disrupted the formation of synapses in a component of the mating circuits. We also show that the neural cell adhesion protein NRX-1/neurexin promotes and the neural cell adhesion protein NLG-1/neuroligin inhibits the formation of the same set of synapses in a parallel pathway. Thus, neural cell adhesion proteins and extracellular matrix components act together in the formation of synaptic connections. PMID:29559501
Multi-electrode array technologies for neuroscience and cardiology
NASA Astrophysics Data System (ADS)
Spira, Micha E.; Hai, Aviad
2013-02-01
At present, the prime methodology for studying neuronal circuit-connectivity, physiology and pathology under in vitro or in vivo conditions is by using substrate-integrated microelectrode arrays. Although this methodology permits simultaneous, cell-non-invasive, long-term recordings of extracellular field potentials generated by action potentials, it is 'blind' to subthreshold synaptic potentials generated by single cells. On the other hand, intracellular recordings of the full electrophysiological repertoire (subthreshold synaptic potentials, membrane oscillations and action potentials) are, at present, obtained only by sharp or patch microelectrodes. These, however, are limited to single cells at a time and for short durations. Recently a number of laboratories began to merge the advantages of extracellular microelectrode arrays and intracellular microelectrodes. This Review describes the novel approaches, identifying their strengths and limitations from the point of view of the end users -- with the intention to help steer the bioengineering efforts towards the needs of brain-circuit research.
Multi-electrode array technologies for neuroscience and cardiology.
Spira, Micha E; Hai, Aviad
2013-02-01
At present, the prime methodology for studying neuronal circuit-connectivity, physiology and pathology under in vitro or in vivo conditions is by using substrate-integrated microelectrode arrays. Although this methodology permits simultaneous, cell-non-invasive, long-term recordings of extracellular field potentials generated by action potentials, it is 'blind' to subthreshold synaptic potentials generated by single cells. On the other hand, intracellular recordings of the full electrophysiological repertoire (subthreshold synaptic potentials, membrane oscillations and action potentials) are, at present, obtained only by sharp or patch microelectrodes. These, however, are limited to single cells at a time and for short durations. Recently a number of laboratories began to merge the advantages of extracellular microelectrode arrays and intracellular microelectrodes. This Review describes the novel approaches, identifying their strengths and limitations from the point of view of the end users--with the intention to help steer the bioengineering efforts towards the needs of brain-circuit research.
Reward Circuitry in Addiction.
Cooper, Sarah; Robison, A J; Mazei-Robison, Michelle S
2017-07-01
Understanding the brain circuitry that underlies reward is critical to improve treatment for many common health issues, including obesity, depression, and addiction. Here we focus on insights into the organization and function of reward circuitry and its synaptic and structural adaptations in response to cocaine exposure. While the importance of certain circuits, such as the mesocorticolimbic dopamine pathway, are well established in drug reward, recent studies using genetics-based tools have revealed functional changes throughout the reward circuitry that contribute to different facets of addiction, such as relapse and craving. The ability to observe and manipulate neuronal activity within specific cell types and circuits has led to new insight into not only the basic connections between brain regions, but also the molecular changes within these specific microcircuits, such as neurotrophic factor and GTPase signaling or α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor function, that underlie synaptic and structural plasticity evoked by drugs of abuse. Excitingly, these insights from preclinical rodent work are now being translated into the clinic, where transcranial magnetic simulation and deep brain stimulation therapies are being piloted in human cocaine dependence. Thus, this review seeks to summarize current understanding of the major brain regions implicated in drug-related behaviors and the molecular mechanisms that contribute to altered connectivity between these regions, with the postulation that increased knowledge of the plasticity within the drug reward circuit will lead to new and improved treatments for addiction.
Feedforward and feedback inhibition in neostriatal GABAergic spiny neurons.
Tepper, James M; Wilson, Charles J; Koós, Tibor
2008-08-01
There are two distinct inhibitory GABAergic circuits in the neostriatum. The feedforward circuit consists of a relatively small population of GABAergic interneurons that receives excitatory input from the neocortex and exerts monosynaptic inhibition onto striatal spiny projection neurons. The feedback circuit comprises the numerous spiny projection neurons and their interconnections via local axon collaterals. This network has long been assumed to provide the majority of striatal GABAergic inhibition and to sharpen and shape striatal output through lateral inhibition, producing increased activity in the most strongly excited spiny cells at the expense of their less strongly excited neighbors. Recent results, mostly from recording experiments of synaptically connected pairs of neurons, have revealed that the two GABAergic circuits differ markedly in terms of the total number of synapses made by each, the strength of the postsynaptic response detected at the soma, the extent of presynaptic convergence and divergence and the net effect of the activation of each circuit on the postsynaptic activity of the spiny neuron. These data have revealed that the feedforward inhibition is powerful and widespread, with spiking in a single interneuron being capable of significantly delaying or even blocking the generation of spikes in a large number of postsynaptic spiny neurons. In contrast, the postsynaptic effects of spiking in a single presynaptic spiny neuron on postsynaptic spiny neurons are weak when measured at the soma, and unable to significantly affect spike timing or generation. Further, reciprocity of synaptic connections between spiny neurons is only rarely observed. These results suggest that the bulk of the fast inhibition that has the strongest effects on spiny neuron spike timing comes from the feedforward interneuronal system whereas the axon collateral feedback system acts principally at the dendrites to control local excitability as well as the overall level of activity of the spiny neuron.
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.
Wang, Xiaoming; Bey, Alexandra L; Katz, Brittany M; Badea, Alexandra; Kim, Namsoo; David, Lisa K; Duffney, Lara J; Kumar, Sunil; Mague, Stephen D; Hulbert, Samuel W; Dutta, Nisha; Hayrapetyan, Volodya; Yu, Chunxiu; Gaidis, Erin; Zhao, Shengli; Ding, Jin-Dong; Xu, Qiong; Chung, Leeyup; Rodriguiz, Ramona M; Wang, Fan; Weinberg, Richard J; Wetsel, William C; Dzirasa, Kafui; Yin, Henry; Jiang, Yong-Hui
2016-05-10
Human neuroimaging studies suggest that aberrant neural connectivity underlies behavioural deficits in autism spectrum disorders (ASDs), but the molecular and neural circuit mechanisms underlying ASDs remain elusive. Here, we describe a complete knockout mouse model of the autism-associated Shank3 gene, with a deletion of exons 4-22 (Δe4-22). Both mGluR5-Homer scaffolds and mGluR5-mediated signalling are selectively altered in striatal neurons. These changes are associated with perturbed function at striatal synapses, abnormal brain morphology, aberrant structural connectivity and ASD-like behaviour. In vivo recording reveals that the cortico-striatal-thalamic circuit is tonically hyperactive in mutants, but becomes hypoactive during social behaviour. Manipulation of mGluR5 activity attenuates excessive grooming and instrumental learning differentially, and rescues impaired striatal synaptic plasticity in Δe4-22(-/-) mice. These findings show that deficiency of Shank3 can impair mGluR5-Homer scaffolding, resulting in cortico-striatal circuit abnormalities that underlie deficits in learning and ASD-like behaviours. These data suggest causal links between genetic, molecular, and circuit mechanisms underlying the pathophysiology of ASDs.
Wang, Xiaoming; Bey, Alexandra L.; Katz, Brittany M.; Badea, Alexandra; Kim, Namsoo; David, Lisa K.; Duffney, Lara J.; Kumar, Sunil; Mague, Stephen D.; Hulbert, Samuel W.; Dutta, Nisha; Hayrapetyan, Volodya; Yu, Chunxiu; Gaidis, Erin; Zhao, Shengli; Ding, Jin-Dong; Xu, Qiong; Chung, Leeyup; Rodriguiz, Ramona M.; Wang, Fan; Weinberg, Richard J.; Wetsel, William C.; Dzirasa, Kafui; Yin, Henry; Jiang, Yong-hui
2016-01-01
Human neuroimaging studies suggest that aberrant neural connectivity underlies behavioural deficits in autism spectrum disorders (ASDs), but the molecular and neural circuit mechanisms underlying ASDs remain elusive. Here, we describe a complete knockout mouse model of the autism-associated Shank3 gene, with a deletion of exons 4–22 (Δe4–22). Both mGluR5-Homer scaffolds and mGluR5-mediated signalling are selectively altered in striatal neurons. These changes are associated with perturbed function at striatal synapses, abnormal brain morphology, aberrant structural connectivity and ASD-like behaviour. In vivo recording reveals that the cortico-striatal-thalamic circuit is tonically hyperactive in mutants, but becomes hypoactive during social behaviour. Manipulation of mGluR5 activity attenuates excessive grooming and instrumental learning differentially, and rescues impaired striatal synaptic plasticity in Δe4–22−/− mice. These findings show that deficiency of Shank3 can impair mGluR5-Homer scaffolding, resulting in cortico-striatal circuit abnormalities that underlie deficits in learning and ASD-like behaviours. These data suggest causal links between genetic, molecular, and circuit mechanisms underlying the pathophysiology of ASDs. PMID:27161151
From structure to function, via dynamics
NASA Astrophysics Data System (ADS)
Stetter, O.; Soriano, J.; Geisel, T.; Battaglia, D.
2013-01-01
Neurons in the brain are wired into a synaptic network that spans multiple scales, from local circuits within cortical columns to fiber tracts interconnecting distant areas. However, brain function require the dynamic control of inter-circuit interactions on time-scales faster than synaptic changes. In particular, strength and direction of causal influences between neural populations (described by the so-called directed functional connectivity) must be reconfigurable even when the underlying structural connectivity is fixed. Such directed functional influences can be quantified resorting to causal analysis of time-series based on tools like Granger Causality or Transfer Entropy. The ability to quickly reorganize inter-areal interactions is a chief requirement for performance in a changing natural environment. But how can manifold functional networks stem "on demand" from an essentially fixed structure? We explore the hypothesis that the self-organization of neuronal synchronous activity underlies the control of brain functional connectivity. Based on simulated and real recordings of critical neuronal cultures in vitro, as well as on mean-field and spiking network models of interacting brain areas, we have found that "function follows dynamics", rather than structure. Different dynamic states of a same structural network, characterized by different synchronization properties, are indeed associated to different functional digraphs (functional multiplicity). We also highlight the crucial role of dynamics in establishing a structure-to-function link, by showing that whenever different structural topologies lead to similar dynamical states, than the associated functional connectivities are also very similar (structural degeneracy).
Bosch, Carles; Masachs, Nuria; Exposito-Alonso, David; Martínez, Albert; Teixeira, Cátia M.; Fernaud, Isabel; Pujadas, Lluís; Ulloa, Fausto; Comella, Joan X.; DeFelipe, Javier; Merchán-Pérez, Angel; Soriano, Eduardo
2016-01-01
The Reelin pathway is essential for both neural migration and for the development and maturation of synaptic connections. However, its role in adult synaptic formation and remodeling is still being investigated. Here, we investigated the impact of the Reelin/Dab1 pathway on the synaptogenesis of newborn granule cells (GCs) in the young-adult mouse hippocampus. We show that neither Reelin overexpression nor the inactivation of its intracellular adapter, Dab1, substantially alters dendritic spine numbers in these neurons. In contrast, 3D-electron microscopy (focused ion beam milling/scanning electron microscope) revealed that dysregulation of the Reelin/Dab1 pathway leads to both transient and permanent changes in the types and morphology of dendritic spines, mainly altering mushroom, filopodial, and branched GC spines. We also found that the Reelin/Dab1 pathway controls synaptic configuration of presynaptic boutons in the dentate gyrus, with its dysregulation leading to a substantial decrease in multi-synaptic bouton innervation. Lastly, we show that the Reelin/Dab1 pathway controls astroglial ensheathment of synapses. Thus, the Reelin pathway is a key regulator of adult-generated GC integration, by controlling dendritic spine types and shapes, their synaptic innervation patterns, and glial ensheathment. These findings may help to better understanding of hippocampal circuit alterations in neurological disorders in which the Reelin pathway is implicated. Significance Statement The extracellular protein Reelin has an important role in neurological diseases, including epilepsy, Alzheimer's disease and psychiatric diseases, targeting hippocampal circuits. Here we address the role of Reelin in the development of synaptic contacts in adult-generated granule cells (GCs), a neuronal population that is crucial for learning and memory and implicated in neurological and psychiatric diseases. We found that the Reelin pathway controls the shapes, sizes, and types of dendritic spines, the complexity of multisynaptic innervations and the degree of the perisynaptic astroglial ensheathment that controls synaptic homeostasis. These findings show a pivotal role of Reelin in GC synaptogenesis and provide a foundation for structural circuit alterations caused by Reelin deregulation that may occur in neurological and psychiatric disorders. PMID:27624722
Mechanisms Underlying Development of Visual Maps and Receptive Fields
Huberman, Andrew D.; Feller, Marla B.; Chapman, Barbara
2008-01-01
Patterns of synaptic connections in the visual system are remarkably precise. These connections dictate the receptive field properties of individual visual neurons and ultimately determine the quality of visual perception. Spontaneous neural activity is necessary for the development of various receptive field properties and visual feature maps. In recent years, attention has shifted to understanding the mechanisms by which spontaneous activity in the developing retina, lateral geniculate nucleus, and visual cortex instruct the axonal and dendritic refinements that give rise to orderly connections in the visual system. Axon guidance cues and a growing list of other molecules, including immune system factors, have also recently been implicated in visual circuit wiring. A major goal now is to determine how these molecules cooperate with spontaneous and visually evoked activity to give rise to the circuits underlying precise receptive field tuning and orderly visual maps. PMID:18558864
Persistent activity in a recurrent circuit underlies courtship memory in Drosophila.
Zhao, Xiaoliang; Lenek, Daniela; Dag, Ugur; Dickson, Barry J; Keleman, Krystyna
2018-01-11
Recurrent connections are thought to be a common feature of the neural circuits that encode memories, but how memories are laid down in such circuits is not fully understood. Here we present evidence that courtship memory in Drosophila relies on the recurrent circuit between mushroom body gamma (MBγ), M6 output, and aSP13 dopaminergic neurons. We demonstrate persistent neuronal activity of aSP13 neurons and show that it transiently potentiates synaptic transmission from MBγ>M6 neurons. M6 neurons in turn provide input to aSP13 neurons, prolonging potentiation of MB γ >M6 synapses over time periods that match short-term memory. These data support a model in which persistent aSP13 activity within a recurrent circuit lays the foundation for a short-term memory. © 2018, Zhao et al.
Persistent activity in a recurrent circuit underlies courtship memory in Drosophila
Zhao, Xiaoliang; Lenek, Daniela; Dag, Ugur; Dickson, Barry J
2018-01-01
Recurrent connections are thought to be a common feature of the neural circuits that encode memories, but how memories are laid down in such circuits is not fully understood. Here we present evidence that courtship memory in Drosophila relies on the recurrent circuit between mushroom body gamma (MBγ), M6 output, and aSP13 dopaminergic neurons. We demonstrate persistent neuronal activity of aSP13 neurons and show that it transiently potentiates synaptic transmission from MBγ>M6 neurons. M6 neurons in turn provide input to aSP13 neurons, prolonging potentiation of MBγ>M6 synapses over time periods that match short-term memory. These data support a model in which persistent aSP13 activity within a recurrent circuit lays the foundation for a short-term memory. PMID:29322941
Visual Circuit Development Requires Patterned Activity Mediated by Retinal Acetylcholine Receptors
Burbridge, Timothy J.; Xu, Hong-Ping; Ackman, James B.; Ge, Xinxin; Zhang, Yueyi; Ye, Mei-Jun; Zhou, Z. Jimmy; Xu, Jian; Contractor, Anis; Crair, Michael C.
2014-01-01
SUMMARY The elaboration of nascent synaptic connections into highly ordered neural circuits is an integral feature of the developing vertebrate nervous system. In sensory systems, patterned spontaneous activity before the onset of sensation is thought to influence this process, but this conclusion remains controversial largely due to the inherent difficulty recording neural activity in early development. Here, we describe novel genetic and pharmacological manipulations of spontaneous retinal activity, assayed in vivo, that demonstrate a causal link between retinal waves and visual circuit refinement. We also report a de-coupling of downstream activity in retinorecipient regions of the developing brain after retinal wave disruption. Significantly, we show that the spatiotemporal characteristics of retinal waves affect the development of specific visual circuits. These results conclusively establish retinal waves as necessary and instructive for circuit refinement in the developing nervous system and reveal how neural circuits adjust to altered patterns of activity prior to experience. PMID:25466916
Functional Maps of Neocortical Local Circuitry
Thomson, Alex M.; Lamy, Christophe
2007-01-01
This review aims to summarize data obtained with different techniques to provide a functional map of the local circuit connections made by neocortical neurones, a reference for those interested in cortical circuitry and the numerical information required by those wishing to model the circuit. A brief description of the main techniques used to study circuitry is followed by outline descriptions of the major classes of neocortical excitatory and inhibitory neurones and the connections that each layer makes with other cortical and subcortical regions. Maps summarizing the projection patterns of each class of neurone within the local circuit and tables of the properties of these local circuit connections are provided. This review relies primarily on anatomical studies that have identified the classes of neurones and their local and long distance connections and on paired intracellular and whole-cell recordings which have documented the properties of the connections between them. A large number of different types of synaptic connections have been described, but for some there are only a few published examples and for others the details that can only be obtained with paired recordings and dye-filling are lacking. A further complication is provided by the range of species, technical approaches and age groups used in these studies. Wherever possible the range of available data are summarised and compared. To fill some of the more obvious gaps for the less well-documented cases, data obtained with other methods are also summarized. PMID:18982117
Chatterjee, Nivedita; Sinha, Sitabhra
2008-01-01
The nervous system of the nematode C. elegans provides a unique opportunity to understand how behavior ('mind') emerges from activity in the nervous system ('brain') of an organism. The hermaphrodite worm has only 302 neurons, all of whose connections (synaptic and gap junctional) are known. Recently, many of the functional circuits that make up its behavioral repertoire have begun to be identified. In this paper, we investigate the hierarchical structure of the nervous system through k-core decomposition and find it to be intimately related to the set of all known functional circuits. Our analysis also suggests a vital role for the lateral ganglion in processing information, providing an essential connection between the sensory and motor components of the C. elegans nervous system.
On the Synchronization of EEG Spindle Waves
NASA Astrophysics Data System (ADS)
Long, Wen; Zhang, ChengFu; Zhao, SiLan; Shi, RuiHong
2000-06-01
Based on recently sleeping cellular substrates, a network model synaptically coupled by N three-cell circuits is provided. Simulation results show that: (i) the dynamic behavior of every circuit is chaotic; (ii) the synchronization of the network is incomplete; (iii) the incomplete synchronization can integrate burst firings of cortical cells into waxing-and-wanning EEG spindle waves. These results enlighten us that this kind of incomplete synchronization may integrate microscopic, electrical activities of neurons in billions into macroscopic, functional states in human brain. In addition, the effects of coupling strength, connectional mode and noise to the synchronization are discussed.
Feedforward, high density, programmable read only neural network based memory system
NASA Technical Reports Server (NTRS)
Daud, Taher; Moopenn, Alex; Lamb, James; Thakoor, Anil; Khanna, Satish
1988-01-01
Neural network-inspired, nonvolatile, programmable associative memory using thin-film technology is demonstrated. The details of the architecture, which uses programmable resistive connection matrices in synaptic arrays and current summing and thresholding amplifiers as neurons, are described. Several synapse configurations for a high-density array of a binary connection matrix are also described. Test circuits are evaluated for operational feasibility and to demonstrate the speed of the read operation. The results are discussed to highlight the potential for a read data rate exceeding 10 megabits/sec.
Chang, Chia-Ling; Trimbuch, Thorsten; Chao, Hsiao-Tuan; Jordan, Julia-Christine; Herman, Melissa A; Rosenmund, Christian
2014-01-15
Neural circuits are composed of mainly glutamatergic and GABAergic neurons, which communicate through synaptic connections. Many factors instruct the formation and function of these synapses; however, it is difficult to dissect the contribution of intrinsic cell programs from that of extrinsic environmental effects in an intact network. Here, we perform paired recordings from two-neuron microculture preparations of mouse hippocampal glutamatergic and GABAergic neurons to investigate how synaptic input and output of these two principal cells develop. In our reduced preparation, we found that glutamatergic neurons showed no change in synaptic output or input regardless of partner neuron cell type or neuronal activity level. In contrast, we found that glutamatergic input caused the GABAergic neuron to modify its output by way of an increase in synapse formation and a decrease in synaptic release efficiency. These findings are consistent with aspects of GABAergic synapse maturation observed in many brain regions. In addition, changes in GABAergic output are cell wide and not target-cell specific. We also found that glutamatergic neuronal activity determined the AMPA receptor properties of synapses on the partner GABAergic neuron. All modifications of GABAergic input and output required activity of the glutamatergic neuron. Because our system has reduced extrinsic factors, the changes we saw in the GABAergic neuron due to glutamatergic input may reflect initiation of maturation programs that underlie the formation and function of in vivo neural circuits.
Phase Difference between Model Cortical Areas Determines Level of Information Transfer
ter Wal, Marije; Tiesinga, Paul H.
2017-01-01
Communication between cortical sites is mediated by long-range synaptic connections. However, these connections are relatively static, while everyday cognitive tasks demand a fast and flexible routing of information in the brain. Synchronization of activity between distant cortical sites has been proposed as the mechanism underlying such a dynamic communication structure. Here, we study how oscillatory activity affects the excitability and input-output relation of local cortical circuits and how it alters the transmission of information between cortical circuits. To this end, we develop model circuits showing fast oscillations by the PING mechanism, of which the oscillatory characteristics can be altered. We identify conditions for synchronization between two brain circuits and show that the level of intercircuit coherence and the phase difference is set by the frequency difference between the intrinsic oscillations. We show that the susceptibility of the circuits to inputs, i.e., the degree of change in circuit output following input pulses, is not uniform throughout the oscillation period and that both firing rate, frequency and power are differentially modulated by inputs arriving at different phases. As a result, an appropriate phase difference between the circuits is critical for the susceptibility windows of the circuits in the network to align and for information to be efficiently transferred. We demonstrate that changes in synchrony and phase difference can be used to set up or abolish information transfer in a network of cortical circuits. PMID:28232796
Yasuyama, Kouji; Meinertzhagen, Ian A
2010-02-01
Recent studies in Drosophila melanogaster indicate that the neuropeptide pigment-dispersing factor (PDF) is an important output signal from a set of major clock neurons, s-LN(v)s (small ventral lateral neurons), which transmit the circadian phase to subsets of other clock neurons, DNs (dorsal neurons). Both s-LN(v)s and DNs have fiber projections to the dorsal protocerebrum of the brain, so that this area is a conspicuous locus for coupling between different subsets of clock neurons. To unravel the neural circuits underlying the fly's circadian rhythms, we examined the detailed subcellular morphology of the PDF-positive fibers of the s-LN(v)s in the dorsal protocerebrum, focusing on their synaptic connections, using preembedding immunoelectron microscopy. To examine the distribution of synapses, we also reconstructed the three-dimensional morphology of PDF-positive varicosities from fiber profiles in the dorsal protocerebrum. The varicosities contained large dense-core vesicles (DCVs), and also numerous small clear vesicles, forming divergent output synapses onto unlabeled neurites. The DCVs apparently dock at nonsynaptic sites, suggesting their nonsynaptic release. In addition, a 3D reconstruction revealed the presence of input synapses onto the PDF-positive fibers. These were detected less frequently than output sites. These observations suggest that the PDF-positive clock neurons receive neural inputs directly through synaptic connections in the dorsal protocerebrum, in addition to supplying dual outputs, either synaptic or via paracrine release of the DCV contents, to unidentified target neurons.
Ito, Shoko; Takeichi, Masatoshi
2009-08-04
Neural circuits are generated by precisely ordered synaptic connections among neurons, and this process is thought to rely on the ability of neurons to recognize specific partners. However, it is also known that neurons promiscuously form synapses with nonspecific partners, in particular when cultured in vitro, causing controversies about neural recognition mechanisms. Here we reexamined whether neurons can or cannot select particular partners in vitro. In the cerebellum, granule cell (GC) dendrites form synaptic connections specifically with mossy fibers, but not with climbing fibers. We cocultured GC neurons with pontine or inferior olivary axons, the major sources for mossy and climbing fibers, respectively, as well as with hippocampal axons as a control. The GC neurons formed synapses with pontine axons predominantly at the distal ends of their dendrites, reproducing the characteristic morphology of their synapses observed in vivo, whereas they failed to do so when combined with other axons. In the latter case, synaptic proteins could accumulate between axons and dendrites, but these synapses were randomly distributed throughout the contact sites, and also their synaptic vesicle recycling was anomalous. These observations suggest that GC dendrites can select their authentic partners for synaptogenesis even in vitro, forming the synapses with a GC-specific nature only with them.
Large-scale automated histology in the pursuit of connectomes.
Kleinfeld, David; Bharioke, Arjun; Blinder, Pablo; Bock, Davi D; Briggman, Kevin L; Chklovskii, Dmitri B; Denk, Winfried; Helmstaedter, Moritz; Kaufhold, John P; Lee, Wei-Chung Allen; Meyer, Hanno S; Micheva, Kristina D; Oberlaender, Marcel; Prohaska, Steffen; Reid, R Clay; Smith, Stephen J; Takemura, Shinya; Tsai, Philbert S; Sakmann, Bert
2011-11-09
How does the brain compute? Answering this question necessitates neuronal connectomes, annotated graphs of all synaptic connections within defined brain areas. Further, understanding the energetics of the brain's computations requires vascular graphs. The assembly of a connectome requires sensitive hardware tools to measure neuronal and neurovascular features in all three dimensions, as well as software and machine learning for data analysis and visualization. We present the state of the art on the reconstruction of circuits and vasculature that link brain anatomy and function. Analysis at the scale of tens of nanometers yields connections between identified neurons, while analysis at the micrometer scale yields probabilistic rules of connection between neurons and exact vascular connectivity.
Large-Scale Automated Histology in the Pursuit of Connectomes
Bharioke, Arjun; Blinder, Pablo; Bock, Davi D.; Briggman, Kevin L.; Chklovskii, Dmitri B.; Denk, Winfried; Helmstaedter, Moritz; Kaufhold, John P.; Lee, Wei-Chung Allen; Meyer, Hanno S.; Micheva, Kristina D.; Oberlaender, Marcel; Prohaska, Steffen; Reid, R. Clay; Smith, Stephen J.; Takemura, Shinya; Tsai, Philbert S.; Sakmann, Bert
2011-01-01
How does the brain compute? Answering this question necessitates neuronal connectomes, annotated graphs of all synaptic connections within defined brain areas. Further, understanding the energetics of the brain's computations requires vascular graphs. The assembly of a connectome requires sensitive hardware tools to measure neuronal and neurovascular features in all three dimensions, as well as software and machine learning for data analysis and visualization. We present the state of the art on the reconstruction of circuits and vasculature that link brain anatomy and function. Analysis at the scale of tens of nanometers yields connections between identified neurons, while analysis at the micrometer scale yields probabilistic rules of connection between neurons and exact vascular connectivity. PMID:22072665
Electrical coupling regulates layer 1 interneuron microcircuit formation in the neocortex
Yao, Xing-Hua; Wang, Min; He, Xiang-Nan; He, Fei; Zhang, Shu-Qing; Lu, Wenlian; Qiu, Zi-Long; Yu, Yong-Chun
2016-01-01
The coexistence of electrical and chemical synapses among interneurons is essential for interneuron function in the neocortex. However, it remains largely unclear whether electrical coupling between interneurons influences chemical synapse formation and microcircuit assembly during development. Here, we show that electrical and GABAergic chemical connections robustly develop between interneurons in neocortical layer 1 over a similar time course. Electrical coupling promotes action potential generation and synchronous firing between layer 1 interneurons. Furthermore, electrically coupled interneurons exhibit strong GABA-A receptor-mediated synchronous synaptic activity. Disruption of electrical coupling leads to a loss of bidirectional, but not unidirectional, GABAergic connections. Moreover, a reduction in electrical coupling induces an increase in excitatory synaptic inputs to layer 1 interneurons. Together, these findings strongly suggest that electrical coupling between neocortical interneurons plays a critical role in regulating chemical synapse development and precise formation of circuits. PMID:27510304
Differential expression of neuroligin genes in the nervous system of zebrafish.
Davey, Crystal; Tallafuss, Alexandra; Washbourne, Philip
2010-02-01
The establishment and maturation of appropriate synaptic connections is crucial in the development of neuronal circuits. Cellular adhesion is believed to play a central role in this process. Neuroligins are neuronal cell adhesion molecules that are hypothesized to act in the initial formation and maturation of synaptic connections. In order to establish the zebrafish as a model to investigate the in vivo role of Neuroligin proteins in nervous system development, we identified the zebrafish orthologs of neuroligin family members and characterized their expression. Zebrafish possess seven neuroligin genes. Synteny analysis and sequence comparisons show that NLGN2, NLGN3, and NLGN4X are duplicated in zebrafish, but NLGN1 has a single zebrafish ortholog. All seven zebrafish neuroligins are expressed in complex patterns in the developing nervous system and in the adult brain. The spatial and temporal expression patterns of these genes suggest that they occupy a role in nervous system development and maintenance.
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.
Developmental metaplasticity in neural circuit codes of firing and structure.
Baram, Yoram
2017-01-01
Firing-rate dynamics have been hypothesized to mediate inter-neural information transfer in the brain. While the Hebbian paradigm, relating learning and memory to firing activity, has put synaptic efficacy variation at the center of cortical plasticity, we suggest that the external expression of plasticity by changes in the firing-rate dynamics represents a more general notion of plasticity. Hypothesizing that time constants of plasticity and firing dynamics increase with age, and employing the filtering property of the neuron, we obtain the elementary code of global attractors associated with the firing-rate dynamics in each developmental stage. We define a neural circuit connectivity code as an indivisible set of circuit structures generated by membrane and synapse activation and silencing. Synchronous firing patterns under parameter uniformity, and asynchronous circuit firing are shown to be driven, respectively, by membrane and synapse silencing and reactivation, and maintained by the neuronal filtering property. Analytic, graphical and simulation representation of the discrete iteration maps and of the global attractor codes of neural firing rate are found to be consistent with previous empirical neurobiological findings, which have lacked, however, a specific correspondence between firing modes, time constants, circuit connectivity and cortical developmental stages. Copyright © 2016 Elsevier Ltd. All rights reserved.
The wiring diagram of a glomerular olfactory system
Berck, Matthew E; Khandelwal, Avinash; Claus, Lindsey; Hernandez-Nunez, Luis; Si, Guangwei; Tabone, Christopher J; Li, Feng; Truman, James W; Fetter, Rick D; Louis, Matthieu; Samuel, Aravinthan DT; Cardona, Albert
2016-01-01
The sense of smell enables animals to react to long-distance cues according to learned and innate valences. Here, we have mapped with electron microscopy the complete wiring diagram of the Drosophila larval antennal lobe, an olfactory neuropil similar to the vertebrate olfactory bulb. We found a canonical circuit with uniglomerular projection neurons (uPNs) relaying gain-controlled ORN activity to the mushroom body and the lateral horn. A second, parallel circuit with multiglomerular projection neurons (mPNs) and hierarchically connected local neurons (LNs) selectively integrates multiple ORN signals already at the first synapse. LN-LN synaptic connections putatively implement a bistable gain control mechanism that either computes odor saliency through panglomerular inhibition, or allows some glomeruli to respond to faint aversive odors in the presence of strong appetitive odors. This complete wiring diagram will support experimental and theoretical studies towards bridging the gap between circuits and behavior. DOI: http://dx.doi.org/10.7554/eLife.14859.001 PMID:27177418
Cellular and Synaptic Properties of Local Inhibitory Circuits.
Hull, Court
2017-05-01
Inhibitory interneurons play a key role in sculpting the information processed by neural circuits. Despite the wide range of physiologically and morphologically distinct types of interneurons that have been identified, common principles have emerged that have shed light on how synaptic inhibition operates, both mechanistically and functionally, across cell types and circuits. This introduction summarizes how electrophysiological approaches have been used to illuminate these key principles, including basic interneuron circuit motifs, the functional properties of inhibitory synapses, and the main roles for synaptic inhibition in regulating neural circuit function. It also highlights how some key electrophysiological methods and experiments have advanced our understanding of inhibitory synapse function. © 2017 Cold Spring Harbor Laboratory Press.
Qiu, Shenfeng; Anderson, Charles T.; Levitt, Pat; Shepherd, Gordon M. G.
2011-01-01
Local hyperconnectivity in the neocortex is a hypothesized pathophysiological state in autism spectrum disorder (ASD). MET, a receptor tyrosine kinase that regulates dendrite and spine morphogenesis, has been established as a risk gene for ASD. Here, we analyzed the synaptic circuit organization of identified pyramidal neurons in the anterior frontal cortex of mice with a dorsal pallium derived, conditional knockout (cKO) of Met. Synaptic mapping by glutamate uncaging identified layer 2/3 as the main source of local excitatory input to layer 5 projection neurons in controls. In both cKO and heterozygotes this pathway was stronger by a factor of ~2. This increase was both sub-layer and projection-class specific, restricted to corticostriatal neurons in upper layer 5B, and not neighboring corticopontine neurons. Paired recordings in cKO slices demonstrated increased unitary connectivity. We propose that excitatory hyperconnectivity in specific neocortical microcircuits constitutes a physiological basis for Met-mediated ASD risk. PMID:21490227
Qiu, Shenfeng; Anderson, Charles T; Levitt, Pat; Shepherd, Gordon M G
2011-04-13
Local hyperconnectivity in the neocortex is a hypothesized pathophysiological state in autism spectrum disorder (ASD). MET, a receptor tyrosine kinase that regulates dendrite and spine morphogenesis, has been established as a risk gene for ASD. Here, we analyzed the synaptic circuit organization of identified pyramidal neurons in the anterior frontal cortex of mice with a dorsal pallium-derived, conditional knock-out (cKO) of Met. Synaptic mapping by glutamate uncaging identified layer 2/3 as the main source of local excitatory input to layer 5 projection neurons in controls. In both cKO and heterozygotes, this pathway was stronger by a factor of approximately 2. This increase was both sublayer and projection-class specific, restricted to corticostriatal neurons in upper layer 5B and not neighboring corticopontine neurons. Paired recordings in cKO slices demonstrated increased unitary connectivity. We propose that excitatory hyperconnectivity in specific neocortical microcircuits constitutes a physiological basis for Met-mediated ASD risk.
Rohrbough, Jeffrey; Broadie, Kendal
2010-10-01
Bidirectional trans-synaptic signals induce synaptogenesis and regulate subsequent synaptic maturation. Presynaptically secreted Mind the gap (Mtg) molds the synaptic cleft extracellular matrix, leading us to hypothesize that Mtg functions to generate the intercellular environment required for efficient signaling. We show in Drosophila that secreted Jelly belly (Jeb) and its receptor tyrosine kinase Anaplastic lymphoma kinase (Alk) are localized to developing synapses. Jeb localizes to punctate aggregates in central synaptic neuropil and neuromuscular junction (NMJ) presynaptic terminals. Secreted Jeb and Mtg accumulate and colocalize extracellularly in surrounding synaptic boutons. Alk concentrates in postsynaptic domains, consistent with an anterograde, trans-synaptic Jeb-Alk signaling pathway at developing synapses. Jeb synaptic expression is increased in Alk mutants, consistent with a requirement for Alk receptor function in Jeb uptake. In mtg null mutants, Alk NMJ synaptic levels are reduced and Jeb expression is dramatically increased. NMJ synapse morphology and molecular assembly appear largely normal in jeb and Alk mutants, but larvae exhibit greatly reduced movement, suggesting impaired functional synaptic development. jeb mutant movement is significantly rescued by neuronal Jeb expression. jeb and Alk mutants display normal NMJ postsynaptic responses, but a near loss of patterned, activity-dependent NMJ transmission driven by central excitatory output. We conclude that Jeb-Alk expression and anterograde trans-synaptic signaling are modulated by Mtg and play a key role in establishing functional synaptic connectivity in the developing motor circuit.
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
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.
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.
Action-based sensory encoding in spinal sensorimotor circuits.
Schouenborg, Jens
2008-01-01
The concept of a modular organisation of the spinal withdrawal reflex circuits has proven to be fundamental for the understanding of how the spinal cord is organised and how the sensorimotor circuits translate sensory information into adequate movement corrections. Recent studies indicate that a task-related body representation is engraved at the network level through learning-dependent mechanisms involving an active probing procedure termed 'somatosensory imprinting' during development. It was found that somatosensory imprinting depends on the tactile input that is associated with spontaneous movements that occur during sleep and results in elimination of erroneous connections and establishment of correct connections. In parallel studies it was found that the strength of the first order tactile synapses in rostrocaudally elongated zones in the adult dorsal horn in the lower lumbar cord is related to the modular organisation of the withdrawal reflexes. Hence, the topographical organisation of the tactile input to this spinal area seems to be action-based rather than a simple body map as previously thought. Far from being innate and adult like at birth, the adult organisation seems to emerge from an initial 'floating' and diffuse body representation with many inappropriate connections through profound activity-dependent rearrangements of afferent synaptic connections. It is suggested that somatosensory imprinting plays a key role in the self-organisation of the spinal cord during development.
COMPENSATION FOR VARIABLE INTRINSIC NEURONAL EXCITABILITY BY CIRCUIT-SYNAPTIC INTERACTIONS
Grashow, Rachel; Brookings, Ted; Marder, Eve
2010-01-01
Recent theoretical and experimental work indicates that neurons tune themselves to maintain target levels of excitation by modulating ion channel expression and synaptic strengths. As a result, functionally equivalent circuits can produce similar activity despite disparate underlying network and cellular properties. To experimentally test the extent to which synaptic and intrinsic conductances can produce target activity in the presence of variability in neuronal intrinsic properties, we used the dynamic clamp to create hybrid two-cell circuits built from four types of stomatogastric (STG) neurons coupled to the same model Morris-Lecar neuron by reciprocal inhibition. We measured six intrinsic properties (input resistance, minimum membrane potential, firing rate in response to +1nA of injected current, slope of the FI curve, spike height and spike voltage threshold) of Dorsal Gastric (DG), Gastric Mill (GM), Lateral Pyloric (LP) and Pyloric Dilator (PD) neurons from male crabs, Cancer borealis. The intrinsic properties varied two to seven-fold in each cell type. We coupled each biological neuron to the Morris-Lecar model with seven different values of inhibitory synaptic conductance, and also used the dynamic clamp to add seven different values of an artificial h-conductance, thus creating 49 different circuits for each biological neuron. Despite the variability in intrinsic excitability, networks formed from each neuron produced similar circuit performance at some values of synaptic and h-conductances. This work experimentally confirms results from previous modeling studies; tuning synaptic and intrinsic conductances can yield similar circuit output from neurons with variable intrinsic excitability. PMID:20610748
Synaptic Circuit Organization of Motor Corticothalamic Neurons
Yamawaki, Naoki
2015-01-01
Corticothalamic (CT) neurons in layer 6 constitute a large but enigmatic class of cortical projection neurons. How they are integrated into intracortical and thalamo-cortico-thalamic circuits is incompletely understood, especially outside of sensory cortex. Here, we investigated CT circuits in mouse forelimb motor cortex (M1) using multiple circuit-analysis methods. Stimulating and recording from CT, intratelencephalic (IT), and pyramidal tract (PT) projection neurons, we found strong CT↔ CT and CT↔ IT connections; however, CT→IT connections were limited to IT neurons in layer 6, not 5B. There was strikingly little CT↔ PT excitatory connectivity. Disynaptic inhibition systematically accompanied excitation in these pathways, scaling with the amplitude of excitation according to both presynaptic (class-specific) and postsynaptic (cell-by-cell) factors. In particular, CT neurons evoked proportionally more inhibition relative to excitation (I/E ratio) than IT neurons. Furthermore, the amplitude of inhibition was tuned to match the amount of excitation at the level of individual neurons; in the extreme, neurons receiving no excitation received no inhibition either. Extending these studies to dissect the connectivity between cortex and thalamus, we found that M1-CT neurons and thalamocortical neurons in the ventrolateral (VL) nucleus were remarkably unconnected in either direction. Instead, VL axons in the cortex excited both IT and PT neurons, and CT axons in the thalamus excited other thalamic neurons, including those in the posterior nucleus, which additionally received PT excitation. These findings, which contrast in several ways with previous observations in sensory areas, illuminate the basic circuit organization of CT neurons within M1 and between M1 and thalamus. PMID:25653383
A network model of behavioural performance in a rule learning task.
Hasselmo, Michael E; Stern, Chantal E
2018-04-19
Humans demonstrate differences in performance on cognitive rule learning tasks which could involve differences in properties of neural circuits. An example model is presented to show how gating of the spread of neural activity could underlie rule learning and the generalization of rules to previously unseen stimuli. This model uses the activity of gating units to regulate the pattern of connectivity between neurons responding to sensory input and subsequent gating units or output units. This model allows analysis of network parameters that could contribute to differences in cognitive rule learning. These network parameters include differences in the parameters of synaptic modification and presynaptic inhibition of synaptic transmission that could be regulated by neuromodulatory influences on neural circuits. Neuromodulatory receptors play an important role in cognitive function, as demonstrated by the fact that drugs that block cholinergic muscarinic receptors can cause cognitive impairments. In discussions of the links between neuromodulatory systems and biologically based traits, the issue of mechanisms through which these linkages are realized is often missing. This model demonstrates potential roles of neural circuit parameters regulated by acetylcholine in learning context-dependent rules, and demonstrates the potential contribution of variation in neural circuit properties and neuromodulatory function to individual differences in cognitive function.This article is part of the theme issue 'Diverse perspectives on diversity: multi-disciplinary approaches to taxonomies of individual differences'. © 2018 The Author(s).
Genetic address book for retinal cell types.
Siegert, Sandra; Scherf, Brigitte Gross; Del Punta, Karina; Didkovsky, Nick; Heintz, Nathaniel; Roska, Botond
2009-09-01
The mammalian brain is assembled from thousands of neuronal cell types that are organized in distinct circuits to perform behaviorally relevant computations. Transgenic mouse lines with selectively marked cell types would facilitate our ability to dissect functional components of complex circuits. We carried out a screen for cell type-specific green fluorescent protein expression in the retina using BAC transgenic mice from the GENSAT project. Among others, we identified mouse lines in which the inhibitory cell types of the night vision and directional selective circuit were selectively labeled. We quantified the stratification patterns to predict potential synaptic connectivity between marked cells of different lines and found that some of the lines enabled targeted recordings and imaging of cell types from developing or mature retinal circuits. Our results suggest the potential use of a stratification-based screening approach for characterizing neuronal circuitry in other layered brain structures, such as the neocortex.
Hox Genes: Choreographers in Neural Development, Architects of Circuit Organization
Philippidou, Polyxeni; Dasen, Jeremy S.
2013-01-01
Summary The neural circuits governing vital behaviors, such as respiration and locomotion, are comprised of discrete neuronal populations residing within the brainstem and spinal cord. Work over the past decade has provided a fairly comprehensive understanding of the developmental pathways that determine the identity of major neuronal classes within the neural tube. However, the steps through which neurons acquire the subtype diversities necessary for their incorporation into a particular circuit are still poorly defined. Studies on the specification of motor neurons indicate that the large family of Hox transcription factors has a key role in generating the subtypes required for selective muscle innervation. There is also emerging evidence that Hox genes function in multiple neuronal classes to shape synaptic specificity during development, suggesting a broader role in circuit assembly. This review highlights the functions and mechanisms of Hox gene networks, and their multifaceted roles during neuronal specification and connectivity. PMID:24094100
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.
Mixed Signal Learning by Spike Correlation Propagation in Feedback Inhibitory Circuits
Hiratani, Naoki; Fukai, Tomoki
2015-01-01
The brain can learn and detect mixed input signals masked by various types of noise, and spike-timing-dependent plasticity (STDP) is the candidate synaptic level mechanism. Because sensory inputs typically have spike correlation, and local circuits have dense feedback connections, input spikes cause the propagation of spike correlation in lateral circuits; however, it is largely unknown how this secondary correlation generated by lateral circuits influences learning processes through STDP, or whether it is beneficial to achieve efficient spike-based learning from uncertain stimuli. To explore the answers to these questions, we construct models of feedforward networks with lateral inhibitory circuits and study how propagated correlation influences STDP learning, and what kind of learning algorithm such circuits achieve. We derive analytical conditions at which neurons detect minor signals with STDP, and show that depending on the origin of the noise, different correlation timescales are useful for learning. In particular, we show that non-precise spike correlation is beneficial for learning in the presence of cross-talk noise. We also show that by considering excitatory and inhibitory STDP at lateral connections, the circuit can acquire a lateral structure optimal for signal detection. In addition, we demonstrate that the model performs blind source separation in a manner similar to the sequential sampling approximation of the Bayesian independent component analysis algorithm. Our results provide a basic understanding of STDP learning in feedback circuits by integrating analyses from both dynamical systems and information theory. PMID:25910189
Spontaneous cortical activity alternates between motifs defined by regional axonal projections
Mohajerani, Majid H.; Chan, Allen W.; Mohsenvand, Mostafa; LeDue, Jeffrey; Liu, Rui; McVea, David A.; Boyd, Jamie D.; Wang, Yu Tian; Reimers, Mark; Murphy, Timothy H.
2014-01-01
In lightly anaesthetized or awake adult mice using millisecond timescale voltage sensitive dye imaging, we show that a palette of sensory-evoked and hemisphere-wide activity motifs are represented in spontaneous activity. These motifs can reflect multiple modes of sensory processing including vision, audition, and touch. Similar cortical networks were found with direct cortical activation using channelrhodopsin-2. Regional analysis of activity spread indicated modality specific sources such as primary sensory areas, and a common posterior-medial cortical sink where sensory activity was extinguished within the parietal association area, and a secondary anterior medial sink within the cingulate/secondary motor cortices for visual stimuli. Correlation analysis between functional circuits and intracortical axonal projections indicated a common framework corresponding to long-range mono-synaptic connections between cortical regions. Maps of intracortical mono-synaptic structural connections predicted hemisphere-wide patterns of spontaneous and sensory-evoked depolarization. We suggest that an intracortical monosynaptic connectome shapes the ebb and flow of spontaneous cortical activity. PMID:23974708
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
Mouse Visual Neocortex Supports Multiple Stereotyped Patterns of Microcircuit Activity
Sadovsky, Alexander J.
2014-01-01
Spiking correlations between neocortical neurons provide insight into the underlying synaptic connectivity that defines cortical microcircuitry. Here, using two-photon calcium fluorescence imaging, we observed the simultaneous dynamics of hundreds of neurons in slices of mouse primary visual cortex (V1). Consistent with a balance of excitation and inhibition, V1 dynamics were characterized by a linear scaling between firing rate and circuit size. Using lagged firing correlations between neurons, we generated functional wiring diagrams to evaluate the topological features of V1 microcircuitry. We found that circuit connectivity exhibited both cyclic graph motifs, indicating recurrent wiring, and acyclic graph motifs, indicating feedforward wiring. After overlaying the functional wiring diagrams onto the imaged field of view, we found properties consistent with Rentian scaling: wiring diagrams were topologically efficient because they minimized wiring with a modular architecture. Within single imaged fields of view, V1 contained multiple discrete circuits that were overlapping and highly interdigitated but were still distinct from one another. The majority of neurons that were shared between circuits displayed peri-event spiking activity whose timing was specific to the active circuit, whereas spike times for a smaller percentage of neurons were invariant to circuit identity. These data provide evidence that V1 microcircuitry exhibits balanced dynamics, is efficiently arranged in anatomical space, and is capable of supporting a diversity of multineuron spike firing patterns from overlapping sets of neurons. PMID:24899701
Kozuka, Takashi; Chaya, Taro; Tamalu, Fuminobu; Shimada, Mariko; Fujimaki-Aoba, Kayo; Kuwahara, Ryusuke; Watanabe, Shu-Ichi; Furukawa, Takahisa
2017-10-11
Neurotransmission plays an essential role in neural circuit formation in the central nervous system (CNS). Although neurotransmission has been recently clarified as a key modulator of retinal circuit development, the roles of individual synaptic transmissions are not yet fully understood. In the current study, we investigated the role of neurotransmission from photoreceptor cells to ON bipolar cells in development using mutant mouse lines of both sexes in which this transmission is abrogated. We found that deletion of the ON bipolar cation channel TRPM1 results in the abnormal contraction of rod bipolar terminals and a decreased number of their synaptic connections with amacrine cells. In contrast, these histological alterations were not caused by a disruption of total glutamate transmission due to loss of the ON bipolar glutamate receptor mGluR6 or the photoreceptor glutamate transporter VGluT1. In addition, TRPM1 deficiency led to the reduction of total dendritic length, branch numbers, and cell body size in AII amacrine cells. Activated Goα, known to close the TRPM1 channel, interacted with TRPM1 and induced the contraction of rod bipolar terminals. Furthermore, overexpression of Channelrhodopsin-2 partially rescued rod bipolar cell development in the TRPM1 -/- retina, whereas the rescue effect by a constitutively closed form of TRPM1 was lower than that by the native form. Our results suggest that TRPM1 channel opening is essential for rod bipolar pathway establishment in development. SIGNIFICANCE STATEMENT Neurotransmission has been recognized recently as a key modulator of retinal circuit development in the CNS. However, the roles of individual synaptic transmissions are not yet fully understood. In the current study, we focused on neurotransmission between rod photoreceptor cells and rod bipolar cells in the retina. We used genetically modified mouse models which abrogate each step of neurotransmission: presynaptic glutamate release, postsynaptic glutamate reception, or transduction channel function. We found that the TRPM1 transduction channel is required for the development of rod bipolar cells and their synaptic formation with subsequent neurons, independently of glutamate transmission. This study advances our understanding of neurotransmission-mediated retinal circuit refinement. Copyright © 2017 the authors 0270-6474/17/379889-12$15.00/0.
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.
Age–dependent regulation of synaptic connections by dopamine D2 receptors
Jia, Jie–Min; Zhao, Jun; Hu, Zhonghua; Lindberg, Daniel; Li, Zheng
2013-01-01
Dopamine D2 receptors (D2R) are G protein–coupled receptors that modulate synaptic transmission and play an important role in various brain functions including affect learning and working memory. Abnormal D2R signaling has been implicated in psychiatric disorders such as schizophrenia. Here we report a new function of D2R in dendritic spine morphogenesis. Activation of D2R reduces spine number via GluN2B– and cAMP–dependent mechanisms in mice. Notably, this regulation takes place only during adolescence. During this period, D2R overactivation caused by mutations in the schizophrenia–risk–gene dysbindin leads to spine deficiency, dysconnectivity within the entorhinal–hippocampal circuit and impairment of spatial working memory. Notably, these defects can be ameliorated by D2R blockers administered during adolescence. These findings uncover a novel age–dependent function of D2R in spine development, provide evidence that D2R dysfunction during adolescence impairs neuronal circuits and working memory, and suggest that adolescent interventions of aberrant D2R activity protect against cognitive impairment. PMID:24121738
Wang, Guangfu; Wyskiel, Daniel R; Yang, Weiguo; Wang, Yiqing; Milbern, Lana C; Lalanne, Txomin; Jiang, Xiaolong; Shen, Ying; Sun, Qian-Quan; Zhu, J Julius
2015-01-01
Deciphering neuronal circuitry is central to understanding brain function and dysfunction, yet it remains a daunting task. To facilitate the dissection of neuronal circuits, a process requiring functional analysis of synaptic connections and morphological identification of interconnected neurons, we present here a method for stable simultaneous octuple patch-clamp recordings. This method allows physiological analysis of synaptic interconnections among 4–8 simultaneously recorded neurons and/or 10–30 sequentially recorded neurons, and it allows anatomical identification of >85% of recorded interneurons and >99% of recorded principal neurons. We describe how to apply the method to rodent tissue slices; however, it can be used on other model organisms. We also describe the latest refinements and optimizations of mechanics, electronics, optics and software programs that are central to the realization of a combined single- and two-photon microscopy–based, optogenetics- and imaging-assisted, stable, simultaneous quadruple–viguple patch-clamp recording system. Setting up the system, from the beginning of instrument assembly and software installation to full operation, can be completed in 3–4 d. PMID:25654757
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 Regulation of a Thalamocortical Circuit Controls Depression-Related Behavior.
Miller, Oliver H; Bruns, Andreas; Ben Ammar, Imen; Mueggler, Thomas; Hall, Benjamin J
2017-08-22
The NMDA receptor (NMDAR) antagonist ketamine elicits a long-lasting antidepressant response in patients with treatment-resistant depression. Understanding how antagonism of NMDARs alters synapse and circuit function is pivotal to developing circuit-based therapies for depression. Using virally induced gene deletion, ex vivo optogenetic-assisted circuit analysis, and in vivo chemogenetics and fMRI, we assessed the role of NMDARs in the medial prefrontal cortex (mPFC) in controlling depression-related behavior in mice. We demonstrate that post-developmental genetic deletion of the NMDAR subunit GluN2B from pyramidal neurons in the mPFC enhances connectivity between the mPFC and limbic thalamus, but not the ventral hippocampus, and reduces depression-like behavior. Using intersectional chemogenetics, we show that activation of this thalamocortical circuit is sufficient to elicit a decrease in despair-like behavior. Our findings reveal that GluN2B exerts input-specific control of pyramidal neuron innervation and identify a medial dorsal thalamus (MDT)→mPFC circuit that controls depression-like behavior. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.
Ruggiero, Rafael N; Rossignoli, Matheus T; Lopes-Aguiar, Cleiton; Leite, João P; Bueno-Junior, Lezio S; Romcy-Pereira, Rodrigo N
2018-06-01
Mood disorders are associated to functional unbalance in mesolimbic and frontal cortical circuits. As a commonly used mood stabilizer, lithium acts through multiple biochemical pathways, including those activated by muscarinic cholinergic receptors crucial for hippocampal-prefrontal communication. Therefore, here we investigated the effects of lithium on prefrontal cortex responses under cholinergic drive. Lithium-treated rats were anesthetized with urethane and implanted with a ventricular cannula for muscarinic activation, a recording electrode in the medial prefrontal cortex (mPFC), and a stimulating electrode in the intermediate hippocampal CA1. Either of two forms of synaptic plasticity, long-term potentiation (LTP) or depression (LTD), were induced during pilocarpine effects, which were monitored in real time through local field potentials. We found that lithium attenuates the muscarinic potentiation of cortical LTP (<20 min) but enhances the muscarinic potentiation of LTD maintenance (>80 min). Moreover, lithium treatment promoted significant cross-frequency coupling between CA1 theta (3-5 Hz) and mPFC low-gamma (30-55 Hz) oscillations. Interestingly, lithium by itself did not affect any of these measures. Thus, lithium pretreatment and muscarinic activation synergistically modulate the hippocampal-prefrontal connectivity. Because these alterations varied with time, oscillatory parameters, and type of synaptic plasticity, our study suggests that lithium influences prefrontal-related circuits through intricate dynamics, informing future experiments on mood disorders. Copyright © 2018. Published by Elsevier Inc.
Transcriptional Architecture of Synaptic Communication Delineates GABAergic Neuron Identity.
Paul, Anirban; Crow, Megan; Raudales, Ricardo; He, Miao; Gillis, Jesse; Huang, Z Josh
2017-10-19
Understanding the organizational logic of neural circuits requires deciphering the biological basis of neuronal diversity and identity, but there is no consensus on how neuron types should be defined. We analyzed single-cell transcriptomes of a set of anatomically and physiologically characterized cortical GABAergic neurons and conducted a computational genomic screen for transcriptional profiles that distinguish them from one another. We discovered that cardinal GABAergic neuron types are delineated by a transcriptional architecture that encodes their synaptic communication patterns. This architecture comprises 6 categories of ∼40 gene families, including cell-adhesion molecules, transmitter-modulator receptors, ion channels, signaling proteins, neuropeptides and vesicular release components, and transcription factors. Combinatorial expression of select members across families shapes a multi-layered molecular scaffold along the cell membrane that may customize synaptic connectivity patterns and input-output signaling properties. This molecular genetic framework of neuronal identity integrates cell phenotypes along multiple axes and provides a foundation for discovering and classifying neuron types. Copyright © 2017 Elsevier Inc. All rights reserved.
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
Bock, Jörg; Braun, Katharina
2011-01-01
Enriched as well as impoverished or adverse perinatal environment plays an essential role in the development and refinement of neuronal pathways, which are the neural substrate of intellectual capacity and socioemotional competence. Perinatal experience and learning events continuously interact with the adaptive shaping of excitatory, inhibitory, and neuromodulatory synaptic as well as the endocrine stress systems, including the neuronal corticotropin-releasing factor (CRF) pathways. Adverse environments, such as stress and emotional deprivation can not only delay experience-dependent maturation of these pathways, but also induce permanent changes in prefronto-cortical wiring patterns. We assume that such dysfunctional connections are the neuronal basis for the development of psychosocially induced mental disorders during later life. The aim of this review is to focus on the impact of perinatal stress on the neuronal and synaptic reorganization during brain development and possible implications for the etiology and therapy of mental disorders such as ADHD. Copyright © 2011 Elsevier B.V. All rights reserved.
Synapse maintenance and restoration in the retina by NGL2
Zhao, Lei
2018-01-01
Synaptic cell adhesion molecules (CAMs) promote synapse formation in the developing nervous system. To what extent they maintain and can restore connections in the mature nervous system is unknown. Furthermore, how synaptic CAMs affect the growth of synapse-bearing neurites is unclear. Here, we use adeno-associated viruses (AAVs) to delete, re-, and overexpress the synaptic CAM NGL2 in individual retinal horizontal cells. When we removed NGL2 from horizontal cells, their axons overgrew and formed fewer synapses, irrespective of whether Ngl2 was deleted during development or in mature circuits. When we re-expressed NGL2 in knockout mice, horizontal cell axon territories and synapse numbers were restored, even if AAVs were injected after phenotypes had developed. Finally, overexpression of NGL2 in wild-type horizontal cells elevated synapse numbers above normal levels. Thus, NGL2 promotes the formation, maintenance, and restoration of synapses in the developing and mature retina, and restricts axon growth throughout life. PMID:29553369
Laser programmable integrated circuit for forming synapses in neural networks
Fu, C.Y.
1997-02-11
Customizable neural network in which one or more resistors form each synapse is disclosed. All the resistors in the synaptic array are identical, thus simplifying the processing issues. Highly doped, amorphous silicon is used as the resistor material, to create extremely high resistances occupying very small spaces. Connected in series with each resistor in the array is at least one severable conductor whose uppermost layer has a lower reflectivity of laser energy than typical metal conductors at a desired laser wavelength. 5 figs.
Local and Long-Range Circuit Connections to Hilar Mossy Cells in the Dentate Gyrus
Sun, Yanjun; Grieco, Steven F.; Holmes, Todd C.
2017-01-01
Abstract Hilar mossy cells are the prominent glutamatergic cell type in the dentate hilus of the dentate gyrus (DG); they have been proposed to have critical roles in the DG network. To better understand how mossy cells contribute to DG function, we have applied new viral genetic and functional circuit mapping approaches to quantitatively map and compare local and long-range circuit connections of mossy cells and dentate granule cells in the mouse. The great majority of inputs to mossy cells consist of two parallel inputs from within the DG: an excitatory input pathway from dentate granule cells and an inhibitory input pathway from local DG inhibitory neurons. Mossy cells also receive a moderate degree of excitatory and inhibitory CA3 input from proximal CA3 subfields. Long range inputs to mossy cells are numerically sparse, and they are only identified readily from the medial septum and the septofimbrial nucleus. In comparison, dentate granule cells receive most of their inputs from the entorhinal cortex. The granule cells receive significant synaptic inputs from the hilus and the medial septum, and they also receive direct inputs from both distal and proximal CA3 subfields, which has been underdescribed in the existing literature. Our slice-based physiological mapping studies further supported the identified circuit connections of mossy cells and granule cells. Together, our data suggest that hilar mossy cells are major local circuit integrators and they exert modulation of the activity of dentate granule cells as well as the CA3 region through “back-projection” pathways. PMID:28451637
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.
Ilinsky, I A; Ambardekar, A V; Kultas-Ilinsky, K
1999-07-05
Projections to the motor-related thalamic nuclei from the anterior pole of the reticular thalamic nucleus (NRT) were studied after injections of biotinylated dextran amine and wheat germ agglutinin conjugated horseradish peroxidase at light and electron microscopic levels, respectively. Each injection resulted in anterograde labeling in the three subdivisions of the ventral anterior nucleus (pars parvicellularis, VApc; pars densicellularis, VAdc; and pars magnocellularis, VAmc) and in the ventral lateral nucleus (VL). NRT fibers had beaded shapes and coursed in a posterior direction giving rise to relatively diffuse terminal plexuses. The average size of the beads (0.7 microm2) and their density per 100 microm of fiber length (23.7-25.7) were similar between the nuclei studied. At the electron microscopic level, anterogradely labeled boutons displayed positive immunoreactivity for gamma-aminobutyric acid (GABA), contained pleomorphic synaptic vesicles, and formed relatively long (approximately 0.4 microm) symmetric synaptic contacts. Usually, a single terminal formed synapses on more than one postsynaptic structure. Synaptic contacts were on projection and local circuit neurons and targeted mainly their distal dendrites. In the VAmc, synapses on local circuit neurons composed 48% of the total sample, in the VAdc/VApc and in the VL the proportion was higher, 65% and 62%, respectively. The results suggest that the input from the anterior pole of the monkey reticular nucleus to the motor-related thalamic nuclei is organized differently from what is known on the organization of connections of NRT with sensory thalamic nuclei in other species in that the terminal fields of individual fibers are diffuse rather than focal and that at least 50% of synapses are established on GABAergic local circuit neurons.
Changed Synaptic Plasticity in Neural Circuits of Depressive-Like and Escitalopram-Treated Rats
Li, Xiao-Li; Yuan, Yong-Gui; Xu, Hua; Wu, Di; Gong, Wei-Gang; Geng, Lei-Yu; Wu, Fang-Fang; Tang, Hao; Xu, Lin
2015-01-01
Background: Although progress has been made in the detection and characterization of neural plasticity in depression, it has not been fully understood in individual synaptic changes in the neural circuits under chronic stress and antidepressant treatment. Methods: Using electron microscopy and Western-blot analyses, the present study quantitatively examined the changes in the Gray’s Type I synaptic ultrastructures and the expression of synapse-associated proteins in the key brain regions of rats’ depressive-related neural circuit after chronic unpredicted mild stress and/or escitalopram administration. Meanwhile, their depressive behaviors were also determined by several tests. Results: The Type I synapses underwent considerable remodeling after chronic unpredicted mild stress, which resulted in the changed width of the synaptic cleft, length of the active zone, postsynaptic density thickness, and/or synaptic curvature in the subregions of medial prefrontal cortex and hippocampus, as well as the basolateral amygdaloid nucleus of the amygdala, accompanied by changed expression of several synapse-associated proteins. Chronic escitalopram administration significantly changed the above alternations in the chronic unpredicted mild stress rats but had little effect on normal controls. Also, there was a positive correlation between the locomotor activity and the maximal synaptic postsynaptic density thickness in the stratum radiatum of the Cornu Ammonis 1 region and a negative correlation between the sucrose preference and the length of the active zone in the basolateral amygdaloid nucleus region in chronic unpredicted mild stress rats. Conclusion: These findings strongly indicate that chronic stress and escitalopram can alter synaptic plasticity in the neural circuits, and the remodeled synaptic ultrastructure was correlated with the rats’ depressive behaviors, suggesting a therapeutic target for further exploration. PMID:25899067
Generation of dense statistical connectomes from sparse morphological data
Egger, Robert; Dercksen, Vincent J.; Udvary, Daniel; Hege, Hans-Christian; Oberlaender, Marcel
2014-01-01
Sensory-evoked signal flow, at cellular and network levels, is primarily determined by the synaptic wiring of the underlying neuronal circuitry. Measurements of synaptic innervation, connection probabilities and subcellular organization of synaptic inputs are thus among the most active fields of research in contemporary neuroscience. Methods to measure these quantities range from electrophysiological recordings over reconstructions of dendrite-axon overlap at light-microscopic levels to dense circuit reconstructions of small volumes at electron-microscopic resolution. However, quantitative and complete measurements at subcellular resolution and mesoscopic scales to obtain all local and long-range synaptic in/outputs for any neuron within an entire brain region are beyond present methodological limits. Here, we present a novel concept, implemented within an interactive software environment called NeuroNet, which allows (i) integration of sparsely sampled (sub)cellular morphological data into an accurate anatomical reference frame of the brain region(s) of interest, (ii) up-scaling to generate an average dense model of the neuronal circuitry within the respective brain region(s) and (iii) statistical measurements of synaptic innervation between all neurons within the model. We illustrate our approach by generating a dense average model of the entire rat vibrissal cortex, providing the required anatomical data, and illustrate how to measure synaptic innervation statistically. Comparing our results with data from paired recordings in vitro and in vivo, as well as with reconstructions of synaptic contact sites at light- and electron-microscopic levels, we find that our in silico measurements are in line with previous results. PMID:25426033
A circuit mechanism for the propagation of waves of muscle contraction in Drosophila
Fushiki, Akira; Zwart, Maarten F; Kohsaka, Hiroshi; Fetter, Richard D; Cardona, Albert; Nose, Akinao
2016-01-01
Animals move by adaptively coordinating the sequential activation of muscles. The circuit mechanisms underlying coordinated locomotion are poorly understood. Here, we report on a novel circuit for the propagation of waves of muscle contraction, using the peristaltic locomotion of Drosophila larvae as a model system. We found an intersegmental chain of synaptically connected neurons, alternating excitatory and inhibitory, necessary for wave propagation and active in phase with the wave. The excitatory neurons (A27h) are premotor and necessary only for forward locomotion, and are modulated by stretch receptors and descending inputs. The inhibitory neurons (GDL) are necessary for both forward and backward locomotion, suggestive of different yet coupled central pattern generators, and its inhibition is necessary for wave propagation. The circuit structure and functional imaging indicated that the commands to contract one segment promote the relaxation of the next segment, revealing a mechanism for wave propagation in peristaltic locomotion. DOI: http://dx.doi.org/10.7554/eLife.13253.001 PMID:26880545
Multiple Independent Oscillatory Networks in the Degenerating Retina
Euler, Thomas; Schubert, Timm
2015-01-01
During neuronal degenerative diseases, microcircuits undergo severe structural alterations, leading to remodeling of synaptic connectivity. This can be particularly well observed in the retina, where photoreceptor degeneration triggers rewiring of connections in the retina’s first synaptic layer (e.g., Strettoi et al., 2003; Haq et al., 2014), while the synaptic organization of inner retinal circuits appears to be little affected (O’Brien et al., 2014; Figures 1A,B). Remodeling of (outer) retinal circuits and diminishing light-driven activity due to the loss of functional photoreceptors lead to spontaneous activity that can be observed at different retinal levels (Figure 1C), including the retinal ganglion cells, which display rhythmic spiking activity in the degenerative retina (Margolis et al., 2008; Stasheff, 2008; Menzler and Zeck, 2011; Stasheff et al., 2011). Two networks have been suggested to drive the oscillatory activity in the degenerating retina: a network of remnant cone photoreceptors, rod bipolar cells (RBCs) and horizontal cells in the outer retina (Haq et al., 2014), and the AII amacrine cell-cone bipolar cell network in the inner retina (Borowska et al., 2011). Notably, spontaneous rhythmic activity in the inner retinal network can be triggered in the absence of synaptic remodeling in the outer retina, for example, in the healthy retina after photo-bleaching (Menzler et al., 2014). In addition, the two networks show remarkable differences in their dominant oscillation frequency range as well as in the types and numbers of involved cells (Menzler and Zeck, 2011; Haq et al., 2014). Taken together this suggests that the two networks are self-sustained and can be active independently from each other. However, it is not known if and how they modulate each other. In this mini review, we will discuss: (i) commonalities and differences between these two oscillatory networks as well as possible interaction pathways; (ii) how multiple self-sustained networks may hamper visual restoration strategies employing, for example, microelectronic implants, optogenetics or stem cells, and briefly; and (iii) how the finding of diverse (independent) networks in the degenerative retina may relate to other parts of the neurodegenerative central nervous system. PMID:26617491
Postsynaptic Synaptotagmins Mediate AMPA Receptor Exocytosis During LTP
Wu, Dick; Bacaj, Taulant; Morishita, Wade; Goswami, Debanjan; Arendt, Kristin L.; Xu, Wei; Chen, Lu; Malenka, Robert C.; Südhof, Thomas C.
2017-01-01
Strengthening of synaptic connections by NMDA-receptor-dependent long-term potentiation (LTP) shapes neural circuits and mediates learning and memory. During NMDA-receptor-dependent LTP induction, Ca2+-influx stimulates recruitment of synaptic AMPA-receptors, thereby strengthening synapses. How Ca2+ induces AMPA-receptor recruitment, however, remains unclear. Here we show that, in pyramidal neurons of the hippocampal CA1-region, blocking postsynaptic expression of both synaptotagmin-1 and synaptotagmin-7, but not of synaptotagmin-1 or synaptotagmin-7 alone, abolished LTP. LTP was rescued by wild-type but not by Ca2+-binding-deficient mutant synaptotagmin-7. Blocking postsynaptic synaptotagmin-1/7 expression did not impair basal synaptic transmission, synaptic or extrasynaptic AMPA-receptor levels, or other AMPA-receptor trafficking events. Moreover, expression of dominant-negative mutant synaptotagmin-1 that inhibited Ca2+-dependent presynaptic vesicle exocytosis also blocked Ca2+-dependent postsynaptic AMPA-receptor exocytosis, thereby abolishing LTP. Our results suggest that postsynaptic synaptotagmin-1 and synaptotagmin-7 act as redundant Ca2+-sensors for Ca2+-dependent exocytosis of AMPA-receptors during LTP, thus delineating a simple mechanism for the recruitment of AMPA-receptors that mediates LTP. PMID:28355182
Heap, Lucy A.; Goh, Chi Ching; Kassahn, Karin S.; Scott, Ethan K.
2013-01-01
The cerebellum is a brain region responsible for motor coordination and for refining motor programs. While a great deal is known about the structure and connectivity of the mammalian cerebellum, fundamental questions regarding its function in behavior remain unanswered. Recently, the zebrafish has emerged as a useful model organism for cerebellar studies, owing in part to the similarity in cerebellar circuits between zebrafish and mammals. While the cell types composing their cerebellar cortical circuits are generally conserved with mammals, zebrafish lack deep cerebellar nuclei, and instead a majority of cerebellar output comes from a single type of neuron: the eurydendroid cell. To describe spatial patterns of cerebellar output in zebrafish, we have used genetic techniques to label and trace eurydendroid cells individually and en masse. We have found that cerebellar output targets the thalamus and optic tectum, and have confirmed the presence of pre-synaptic terminals from eurydendroid cells in these structures using a synaptically targeted GFP. By observing individual eurydendroid cells, we have shown that different medial-lateral regions of the cerebellum have eurydendroid cells projecting to different targets. Finally, we found topographic organization in the connectivity between the cerebellum and the optic tectum, where more medial eurydendroid cells project to the rostral tectum while lateral cells project to the caudal tectum. These findings indicate that there is spatial logic underpinning cerebellar output in zebrafish with likely implications for cerebellar function. PMID:23554587
EDITORIAL: Synaptic electronics Synaptic electronics
NASA Astrophysics Data System (ADS)
Demming, Anna; Gimzewski, James K.; Vuillaume, Dominique
2013-09-01
Conventional computers excel in logic and accurate scientific calculations but make hard work of open ended problems that human brains handle easily. Even von Neumann—the mathematician and polymath who first developed the programming architecture that forms the basis of today's computers—was already looking to the brain for future developments before his death in 1957 [1]. Neuromorphic computing uses approaches that better mimic the working of the human brain. Recent developments in nanotechnology are now providing structures with very accommodating properties for neuromorphic approaches. This special issue, with guest editors James K Gimzewski and Dominique Vuillaume, is devoted to research at the serendipitous interface between the two disciplines. 'Synaptic electronics', looks at artificial devices with connections that demonstrate behaviour similar to synapses in the nervous system allowing a new and more powerful approach to computing. Synapses and connecting neurons respond differently to incident signals depending on the history of signals previously experienced, ultimately leading to short term and long term memory behaviour. The basic characteristics of a synapse can be replicated with around ten simple transistors. However with the human brain having around 1011 neurons and 1015 synapses, artificial neurons and synapses from basic transistors are unlikely to accommodate the scalability required. The discovery of nanoscale elements that function as 'memristors' has provided a key tool for the implementation of synaptic connections [2]. Leon Chua first developed the concept of the 'The memristor—the missing circuit element' in 1971 [3]. In this special issue he presents a tutorial describing how memristor research has fed into our understanding of synaptic behaviour and how they can be applied in information processing [4]. He also describes, 'The new principle of local activity, which uncovers a minuscule life-enabling "Goldilocks zone", dubbed the edge of chaos, where complex phenomena, including creativity and intelligence, may emerge'. Also in this issue R Stanley Williams and colleagues report results from simulations that demonstrate the potential for using Mott transistors as building blocks for scalable neuristor-based integrated circuits without transistors [5]. The scalability of neural chip designs is also tackled in the design reported by Narayan Srinivasa and colleagues in the US [6]. Meanwhile Carsten Timm and Massimiliano Di Ventra describe simulations of a molecular transistor in which electrons strongly coupled to a vibrational mode lead to a Franck-Condon (FC) blockade that mimics the spiking action potentials in synaptic memory behaviour [7]. The 'atomic switches' used to demonstrate synaptic behaviour by a collaboration of researchers in California and Japan also come under further scrutiny in this issue. James K Gimzewski and colleagues consider the difference between the behaviour of an atomic switch in isolation and in a network [8]. As the authors point out, 'The work presented represents steps in a unified approach of experimentation and theory of complex systems to make atomic switch networks a uniquely scalable platform for neuromorphic computing'. Researchers in Germany [9] and Sweden [10] also report on theoretical approaches to modelling networks of memristive elements and complementary resistive switches for synaptic devices. As Vincent Derycke and colleagues in France point out, 'Actual experimental demonstrations of neural network type circuits based on non-conventional/non-CMOS memory devices and displaying function learning capabilities remain very scarce'. They describe how their work using carbon nanotubes provides a rare demonstration of actual function learning with synapses based on nanoscale building blocks [11]. However, this is far from the only experimental work reported in this issue, others include: short-term memory of TiO2-based electrochemical capacitors [12]; a neuromorphic circuit composed of a nanoscale 1-kbit resistive random-access memory (RRAM) cross-point array of synapses and complementary metal-oxide-semiconductor (CMOS) neuron circuits [13]; a WO3-x-based nanoionics device from Masakazu Aono's group with a wide scale of reprogrammable memorization functions [14]; a new spike-timing dependent plasticity scheme based on a MOS transistor as a selector and a RRAM as a variable resistance device [15]; a new hybrid memristor-CMOS neuromorphic circuit [16]; and a photo-assisted atomic switch [17]. Synaptic electronics evidently has many emerging facets, and Duygu Kuzum, Shimeng Yu, and H-S Philip Wong in the US provide a review of the field, including the materials, devices and applications [18]. In embracing the expertise acquired over thousands of years of evolution, biomimetics and bio-inspired design is a common, smart approach to technological innovation. Yet in successfully mimicking the physiological mechanisms of the human mind synaptic electronics research has a potential impact that is arguably unprecedented. That the quirks and eccentricities recently unearthed in the behaviour of nanomaterials should lend themselves so accommodatingly to emulating synaptic functions promises some very exciting developments in the field, as the articles in this special issue emphasize. References [1] von Neumann J (ed) 2012 The Computer and the Brain 3rd edn (Yale: Yale University Press) [2] Strukov D B, Snider G S, Stewart D R and Williams R S 2008 The missing memristor found Nature 453 80-3 [3] Chua L O 1971 Memristor—the missing circuit element IEEE Trans. Circuit Theory 18 507-19 [4] Chua L O 2013 Memristor, Hodgkin-Huxley, and Edge of Chaos Nanotechnology 24 383001 [5] Pickett M D and Williams R S 2013 Phase transitions enable computational universality in neuristor-based cellular automata Nanotechnology 24 384002 [6] Cruz-Albrecht J M, Derosier T and Srinivasa N 2013 Scalable neural chip with synaptic electronics using CMOS integrated memristors Nanotechnology 24 384011 [7] Timm C and Di Ventra M 2013 Molecular neuron based on the Franck-Condon blockade Nanotechnology 24 384001 [8] Sillin H O, Aguilera R, Shieh H-H, Avizienis A V, Aono M, Stieg A Z and Gimzewski J K 2013 A theoretical and experimental study of neuromorphic atomic switch networks for reservoir computing Nanotechnology 24 384004 [9] Linn E, Menzel S, Ferch S and Waser R 2013 Compact modeling of CRS devices based on ECM cells for memory, logic and neuromorphic applications Nanotechnology 24 384008 [10] Konkoli Z and Wendin G 2013 A generic simulator for large networks of memristive elements Nanotechnology 24 384007 [11] Gacem K, Retrouvey J-M, Chabi D, Filoramo A, Zhao W, Klein J-O and Derycke V 2013 Neuromorphic function learning with carbon nanotube-based synapses Nanotechnology 24 384013 [12] Lim H, Kim I, Kim J-S, Hwang C S and Jeong D S 2013 Short-term memory of TiO2-based electrochemical capacitors: empirical analysis with adoption of a sliding threshold Nanotechnology 24 384005 [13] Park S, Noh J, Choo M-L, Sheri A M, Chang M, Kim Y-B, Kim C J, Jeon M, Lee B-G, Lee B H and Hwang H 2013 Nanoscale RRAM-based synaptic electronics: toward a neuromorphic computing device Nanotechnology 24 384009 [14] Yang R, Terabe K, Yao Y, Tsuruoka T, Hasegawa T, Gimzewski J K and Aono M 2013 Synaptic plasticity and memory functions achieved in WO3-x-based nanoionics device by using principle of atomic switch operation Nanotechnology 24 384002 [15] Ambrogio S, Balatti S, Nardi F, Facchinetti S and Ielmini D 2013 Spike-timing dependent plasticity in a transistor-selected resistive switching memory Nanotechnology 24 384012 [16] Indiveria G, Linares-Barranco B, Legenstein R, Deligeorgis G and Prodromakise T 2013 Integration of nanoscale memristor synapses in neuromorphic computing architectures Nanotechnology 24 384010 [17] Hino T, Hasegawa T, Tanaka H, Tsuruoka T, Terabe K, Ogawa T and Aono M 2013 Volatile and nonvolatile selective switching of a photo-assited initialized atomic switch Nanotechnology 24 384006 [18] Kuzum D, Yu S and Wong H-S P 2013 Synaptic electronics: materials, devices and applications Nanotechnology 24 382001
Luccioli, Stefano; Ben-Jacob, Eshel; Barzilai, Ari; Bonifazi, Paolo; Torcini, Alessandro
2014-01-01
It has recently been discovered that single neuron stimulation can impact network dynamics in immature and adult neuronal circuits. Here we report a novel mechanism which can explain in neuronal circuits, at an early stage of development, the peculiar role played by a few specific neurons in promoting/arresting the population activity. For this purpose, we consider a standard neuronal network model, with short-term synaptic plasticity, whose population activity is characterized by bursting behavior. The addition of developmentally inspired constraints and correlations in the distribution of the neuronal connectivities and excitabilities leads to the emergence of functional hub neurons, whose stimulation/deletion is critical for the network activity. Functional hubs form a clique, where a precise sequential activation of the neurons is essential to ignite collective events without any need for a specific topological architecture. Unsupervised time-lagged firings of supra-threshold cells, in connection with coordinated entrainments of near-threshold neurons, are the key ingredients to orchestrate population activity. PMID:25255443
Memory switches based on metal oxide thin films
NASA Technical Reports Server (NTRS)
Ramesham, Rajeshuni (Inventor); Thakoor, Anilkumar P. (Inventor); Lambe, John J. (Inventor)
1990-01-01
MnO.sub.2-x thin films (12) exhibit irreversible memory switching (28) with an OFF/ON resistance ratio of at least about 10.sup.3 and the tailorability of ON state (20) resistance. Such films are potentially extremely useful as a connection element in a variety of microelectronic circuits and arrays (24). Such films provide a pre-tailored, finite, non-volatile resistive element at a desired place in an electric circuit, which can be electrically turned OFF (22) or disconnected as desired, by application of an electrical pulse. Microswitch structures (10) constitute the thin film element, contacted by a pair of separate electrodes (16a, 16b) and have a finite, pre-selected ON resistance which is ideally suited, for example, as a programmable binary synaptic connection for electronic implementation of neural network architectures. The MnO.sub.2-x microswitch is non-volatile, patternable, insensitive to ultraviolet light, and adherent to a variety of insulating substrates (14), such as glass and silicon dioxide-coated silicon substrates.
Network-driven design principles for neuromorphic systems.
Partzsch, Johannes; Schüffny, Rene
2015-01-01
Synaptic connectivity is typically the most resource-demanding part of neuromorphic systems. Commonly, the architecture of these systems is chosen mainly on technical considerations. As a consequence, the potential for optimization arising from the inherent constraints of connectivity models is left unused. In this article, we develop an alternative, network-driven approach to neuromorphic architecture design. We describe methods to analyse performance of existing neuromorphic architectures in emulating certain connectivity models. Furthermore, we show step-by-step how to derive a neuromorphic architecture from a given connectivity model. For this, we introduce a generalized description for architectures with a synapse matrix, which takes into account shared use of circuit components for reducing total silicon area. Architectures designed with this approach are fitted to a connectivity model, essentially adapting to its connection density. They are guaranteeing faithful reproduction of the model on chip, while requiring less total silicon area. In total, our methods allow designers to implement more area-efficient neuromorphic systems and verify usability of the connectivity resources in these systems.
Network-driven design principles for neuromorphic systems
Partzsch, Johannes; Schüffny, Rene
2015-01-01
Synaptic connectivity is typically the most resource-demanding part of neuromorphic systems. Commonly, the architecture of these systems is chosen mainly on technical considerations. As a consequence, the potential for optimization arising from the inherent constraints of connectivity models is left unused. In this article, we develop an alternative, network-driven approach to neuromorphic architecture design. We describe methods to analyse performance of existing neuromorphic architectures in emulating certain connectivity models. Furthermore, we show step-by-step how to derive a neuromorphic architecture from a given connectivity model. For this, we introduce a generalized description for architectures with a synapse matrix, which takes into account shared use of circuit components for reducing total silicon area. Architectures designed with this approach are fitted to a connectivity model, essentially adapting to its connection density. They are guaranteeing faithful reproduction of the model on chip, while requiring less total silicon area. In total, our methods allow designers to implement more area-efficient neuromorphic systems and verify usability of the connectivity resources in these systems. PMID:26539079
Adult-born neurons modify excitatory synaptic transmission to existing neurons
Adlaf, Elena W; Vaden, Ryan J; Niver, Anastasia J; Manuel, Allison F; Onyilo, Vincent C; Araujo, Matheus T; Dieni, Cristina V; Vo, Hai T; King, Gwendalyn D; Wadiche, Jacques I; Overstreet-Wadiche, Linda
2017-01-01
Adult-born neurons are continually produced in the dentate gyrus but it is unclear whether synaptic integration of new neurons affects the pre-existing circuit. Here we investigated how manipulating neurogenesis in adult mice alters excitatory synaptic transmission to mature dentate neurons. Enhancing neurogenesis by conditional deletion of the pro-apoptotic gene Bax in stem cells reduced excitatory postsynaptic currents (EPSCs) and spine density in mature neurons, whereas genetic ablation of neurogenesis increased EPSCs in mature neurons. Unexpectedly, we found that Bax deletion in developing and mature dentate neurons increased EPSCs and prevented neurogenesis-induced synaptic suppression. Together these results show that neurogenesis modifies synaptic transmission to mature neurons in a manner consistent with a redistribution of pre-existing synapses to newly integrating neurons and that a non-apoptotic function of the Bax signaling pathway contributes to ongoing synaptic refinement within the dentate circuit. DOI: http://dx.doi.org/10.7554/eLife.19886.001 PMID:28135190
An algorithm to predict the connectome of neural microcircuits
Reimann, Michael W.; King, James G.; Muller, Eilif B.; Ramaswamy, Srikanth; Markram, Henry
2015-01-01
Experimentally mapping synaptic connections, in terms of the numbers and locations of their synapses and estimating connection probabilities, is still not a tractable task, even for small volumes of tissue. In fact, the six layers of the neocortex contain thousands of unique types of synaptic connections between the many different types of neurons, of which only a handful have been characterized experimentally. Here we present a theoretical framework and a data-driven algorithmic strategy to digitally reconstruct the complete synaptic connectivity between the different types of neurons in a small well-defined volume of tissue—the micro-scale connectome of a neural microcircuit. By enforcing a set of established principles of synaptic connectivity, and leveraging interdependencies between fundamental properties of neural microcircuits to constrain the reconstructed connectivity, the algorithm yields three parameters per connection type that predict the anatomy of all types of biologically viable synaptic connections. The predictions reproduce a spectrum of experimental data on synaptic connectivity not used by the algorithm. We conclude that an algorithmic approach to the connectome can serve as a tool to accelerate experimental mapping, indicating the minimal dataset required to make useful predictions, identifying the datasets required to improve their accuracy, testing the feasibility of experimental measurements, and making it possible to test hypotheses of synaptic connectivity. PMID:26500529
A differential memristive synapse circuit for on-line learning in neuromorphic computing systems
NASA Astrophysics Data System (ADS)
Nair, Manu V.; Muller, Lorenz K.; Indiveri, Giacomo
2017-12-01
Spike-based learning with memristive devices in neuromorphic computing architectures typically uses learning circuits that require overlapping pulses from pre- and post-synaptic nodes. This imposes severe constraints on the length of the pulses transmitted in the network, and on the network’s throughput. Furthermore, most of these circuits do not decouple the currents flowing through memristive devices from the one stimulating the target neuron. This can be a problem when using devices with high conductance values, because of the resulting large currents. In this paper, we propose a novel circuit that decouples the current produced by the memristive device from the one used to stimulate the post-synaptic neuron, by using a novel differential scheme based on the Gilbert normalizer circuit. We show how this circuit is useful for reducing the effect of variability in the memristive devices, and how it is ideally suited for spike-based learning mechanisms that do not require overlapping pre- and post-synaptic pulses. We demonstrate the features of the proposed synapse circuit with SPICE simulations, and validate its learning properties with high-level behavioral network simulations which use a stochastic gradient descent learning rule in two benchmark classification tasks.
Synaptic up-scaling preserves motor circuit output after chronic, natural inactivity
Vallejo, Mauricio; Hartzler, Lynn K
2017-01-01
Neural systems use homeostatic plasticity to maintain normal brain functions and to prevent abnormal activity. Surprisingly, homeostatic mechanisms that regulate circuit output have mainly been demonstrated during artificial and/or pathological perturbations. Natural, physiological scenarios that activate these stabilizing mechanisms in neural networks of mature animals remain elusive. To establish the extent to which a naturally inactive circuit engages mechanisms of homeostatic plasticity, we utilized the respiratory motor circuit in bullfrogs that normally remains inactive for several months during the winter. We found that inactive respiratory motoneurons exhibit a classic form of homeostatic plasticity, up-scaling of AMPA-glutamate receptors. Up-scaling increased the synaptic strength of respiratory motoneurons and acted to boost motor amplitude from the respiratory network following months of inactivity. Our results show that synaptic scaling sustains strength of the respiratory motor output following months of inactivity, thereby supporting a major neuroscience hypothesis in a normal context for an adult animal. PMID:28914603
Dendritic nonlinearities are tuned for efficient spike-based computations in cortical circuits.
Ujfalussy, Balázs B; Makara, Judit K; Branco, Tiago; Lengyel, Máté
2015-12-24
Cortical neurons integrate thousands of synaptic inputs in their dendrites in highly nonlinear ways. It is unknown how these dendritic nonlinearities in individual cells contribute to computations at the level of neural circuits. Here, we show that dendritic nonlinearities are critical for the efficient integration of synaptic inputs in circuits performing analog computations with spiking neurons. We developed a theory that formalizes how a neuron's dendritic nonlinearity that is optimal for integrating synaptic inputs depends on the statistics of its presynaptic activity patterns. Based on their in vivo preynaptic population statistics (firing rates, membrane potential fluctuations, and correlations due to ensemble dynamics), our theory accurately predicted the responses of two different types of cortical pyramidal cells to patterned stimulation by two-photon glutamate uncaging. These results reveal a new computational principle underlying dendritic integration in cortical neurons by suggesting a functional link between cellular and systems--level properties of cortical circuits.
Kast, Ryan J; Wu, Hsiao-Huei; Levitt, Pat
2017-11-28
The complex circuitry and cell-type diversity of the cerebral cortex are required for its high-level functions. The mechanisms underlying the diversification of cortical neurons during prenatal development have received substantial attention, but understanding of neuronal heterogeneity is more limited during later periods of cortical circuit maturation. To address this knowledge gap, connectivity analysis and molecular phenotyping of cortical neuron subtypes that express the developing synapse-enriched MET receptor tyrosine kinase were performed. Experiments used a MetGFP transgenic mouse line, combined with coexpression analysis of class-specific molecular markers and retrograde connectivity mapping. The results reveal that MET is expressed by a minor subset of subcerebral and a larger number of intratelencephalic projection neurons. Remarkably, MET is excluded from most layer 6 corticothalamic neurons. These findings are particularly relevant for understanding the maturation of discrete cortical circuits, given converging evidence that MET influences dendritic elaboration and glutamatergic synapse maturation. The data suggest that classically defined cortical projection classes can be further subdivided based on molecular characteristics that likely influence synaptic maturation and circuit wiring. Additionally, given that MET is classified as a high confidence autism risk gene, the data suggest that projection neuron subpopulations may be differentially vulnerable to disorder-associated genetic variation. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
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.
Graph Theoretic and Motif Analyses of the Hippocampal Neuron Type Potential Connectome.
Rees, Christopher L; Wheeler, Diek W; Hamilton, David J; White, Charise M; Komendantov, Alexander O; Ascoli, Giorgio A
2016-01-01
We computed the potential connectivity map of all known neuron types in the rodent hippocampal formation by supplementing scantly available synaptic data with spatial distributions of axons and dendrites from the open-access knowledge base Hippocampome.org. The network that results from this endeavor, the broadest and most complete for a mammalian cortical region at the neuron-type level to date, contains more than 3200 connections among 122 neuron types across six subregions. Analyses of these data using graph theory metrics unveil the fundamental architectural principles of the hippocampal circuit. Globally, we identify a highly specialized topology minimizing communication cost; a modular structure underscoring the prominence of the trisynaptic loop; a core set of neuron types serving as information-processing hubs as well as a distinct group of particular antihub neurons; a nested, two-tier rich club managing much of the network traffic; and an innate resilience to random perturbations. At the local level, we uncover the basic building blocks, or connectivity patterns, that combine to produce complex global functionality, and we benchmark their utilization in the circuit relative to random networks. Taken together, these results provide a comprehensive connectivity profile of the hippocampus, yielding novel insights on its functional operations at the computationally crucial level of neuron types.
Xie, Xiaojun; Tabuchi, Masashi; Brown, Matthew P; Mitchell, Sarah P; Wu, Mark N; Kolodkin, Alex L
2017-01-01
The ellipsoid body (EB) in the Drosophila brain is a central complex (CX) substructure that harbors circumferentially laminated ring (R) neuron axons and mediates multifaceted sensory integration and motor coordination functions. However, what regulates R axon lamination and how lamination affects R neuron function remain unknown. We show here that the EB is sequentially innervated by small-field and large-field neurons and that early developing EB neurons play an important regulatory role in EB laminae formation. The transmembrane proteins semaphorin-1a (Sema-1a) and plexin A function together to regulate R axon lamination. R neurons recruit both GABA and GABA-A receptors to their axon terminals in the EB, and optogenetic stimulation coupled with electrophysiological recordings show that Sema-1a-dependent R axon lamination is required for preventing the spread of synaptic inhibition between adjacent EB lamina. These results provide direct evidence that EB lamination is critical for local pre-synaptic inhibitory circuit organization. DOI: http://dx.doi.org/10.7554/eLife.25328.001 PMID:28632130
Glover, J C
2009-11-10
The first Kavli Prize in Neuroscience recognizes a confluence of career achievements that together provide a fundamental understanding of how brain and spinal cord circuits are assembled during development and function in the adult. The members of the Kavli Neuroscience Prize Committee have decided to reward three scientists (Sten Grillner, Thomas Jessell, and Pasko Rakic) jointly "for discoveries on the developmental and functional logic of neuronal circuits". Pasko Rakic performed groundbreaking studies of the developing cerebral cortex, including the discovery of how radial glia guide the neuronal migration that establishes cortical layers and for the radial unit hypothesis and its implications for cortical connectivity and evolution. Thomas Jessell discovered molecular principles governing the specification and patterning of different neuron types and the development of their synaptic interconnection into sensorimotor circuits. Sten Grillner elucidated principles of network organization in the vertebrate locomotor central pattern generator, along with its command systems and sensory and higher order control. The discoveries of Rakic, Jessell and Grillner provide a framework for how neurons obtain their identities and ultimate locations, establish appropriate connections with each other, and how the resultant neuronal networks operate. Their work has significantly advanced our understanding of brain development and function and created new opportunities for the treatment of neurological disorders. Each has pioneered an important area of neuroscience research and left a legacy of exceptional scientific achievement, insight, communication, mentoring and leadership.
From the connectome to the synaptome: an epic love story.
DeFelipe, Javier
2010-11-26
A major challenge in neuroscience is to decipher the structural layout of the brain. The term "connectome" has recently been proposed to refer to the highly organized connection matrix of the human brain. However, defining how information flows through such a complex system represents so difficult a task that it seems unlikely it could be achieved in the near future or, for the most pessimistic, perhaps ever. Circuit diagrams of the nervous system can be considered at different levels, although they are surely impossible to complete at the synaptic level. Nevertheless, advances in our capacity to marry macro- and microscopic data may help establish a realistic statistical model that could describe connectivity at the ultrastructural level, the "synaptome," giving us cause for optimism.
Short-Term Plasticity in a Computational Model of the Tail-Withdrawal Circuit in Aplysia
Baxter, Douglas A.; Byrne, John H.
2007-01-01
The tail-withdrawal circuit of Aplysia provides a useful model system for investigating synaptic dynamics. Sensory neurons within the circuit manifest several forms of synaptic plasticity. Here, we developed a model of the circuit and investigated the ways in which depression (DEP) and potentiation (POT) contributed to information processing. DEP limited the amount of motor neuron activity that could be elicited by the monosynaptic pathway alone. POT within the monosynaptic pathway did not compensate for DEP. There was, however, a synergistic interaction between POT and the polysynaptic pathway. This synergism extended the dynamic range of the network, and the interplay between DEP and POT made the circuit responded preferentially to long-duration, low-frequency inputs. PMID:17957237
Karmakar, Kajari; Narita, Yuichi; Fadok, Jonathan; Ducret, Sebastien; Loche, Alberto; Kitazawa, Taro; Genoud, Christel; Di Meglio, Thomas; Thierry, Raphael; Bacelo, Joao; Lüthi, Andreas; Rijli, Filippo M
2017-01-03
Tonotopy is a hallmark of auditory pathways and provides the basis for sound discrimination. Little is known about the involvement of transcription factors in brainstem cochlear neurons orchestrating the tonotopic precision of pre-synaptic input. We found that in the absence of Hoxa2 and Hoxb2 function in Atoh1-derived glutamatergic bushy cells of the anterior ventral cochlear nucleus, broad input topography and sound transmission were largely preserved. However, fine-scale synaptic refinement and sharpening of isofrequency bands of cochlear neuron activation upon pure tone stimulation were impaired in Hox2 mutants, resulting in defective sound-frequency discrimination in behavioral tests. These results establish a role for Hox factors in tonotopic refinement of connectivity and in ensuring the precision of sound transmission in the mammalian auditory circuit. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.
Sex differences in the neural circuit that mediates female sexual receptivity
Flanagan-Cato, Loretta M.
2011-01-01
Female sexual behavior in rodents, typified by the lordosis posture, is hormone-dependent and sex-specific. Ovarian hormones control this behavior via receptors in the hypothalamic ventromedial nucleus (VMH). This review considers the sex differences in the morphology, neurochemistry and neural circuitry of the VMH to gain insights into the mechanisms that control lordosis. The VMH is larger in males compared with females, due to more synaptic connections. Another sex difference is the responsiveness to estradiol, with males exhibiting muted, and in some cases reverse, effects compared with females. The lack of lordosis in males may be explained by differences in synaptic organization or estrogen responsiveness, or both, in the VMH. However, given that damage to other brain regions unmasks lordosis behavior in males, a male-typical VMH is unlikely the main factor that prevents lordosis. In females, key questions remain regarding the mechanisms whereby ovarian hormones modulate VMH function to promote lordosis. PMID:21338620
Synaptic organization of the Drosophila antennal lobe and its regulation by the Teneurins
Mosca, Timothy J; Luo, Liqun
2014-01-01
Understanding information flow through neuronal circuits requires knowledge of their synaptic organization. In this study, we utilized fluorescent pre- and postsynaptic markers to map synaptic organization in the Drosophila antennal lobe, the first olfactory processing center. Olfactory receptor neurons (ORNs) produce a constant synaptic density across different glomeruli. Each ORN within a class contributes nearly identical active zone number. Active zones from ORNs, projection neurons (PNs), and local interneurons have distinct subglomerular and subcellular distributions. The correct number of ORN active zones and PN acetylcholine receptor clusters requires the Teneurins, conserved transmembrane proteins involved in neuromuscular synapse organization and synaptic partner matching. Ten-a acts in ORNs to organize presynaptic active zones via the spectrin cytoskeleton. Ten-m acts in PNs autonomously to regulate acetylcholine receptor cluster number and transsynaptically to regulate ORN active zone number. These studies advanced our ability to assess synaptic architecture in complex CNS circuits and their underlying molecular mechanisms. DOI: http://dx.doi.org/10.7554/eLife.03726.001 PMID:25310239
Circuit mechanisms of hippocampal reactivation during sleep.
Malerba, Paola; Bazhenov, Maxim
2018-05-01
The hippocampus is important for memory and learning, being a brain site where initial memories are formed and where sharp wave - ripples (SWR) are found, which are responsible for mapping recent memories to long-term storage during sleep-related memory replay. While this conceptual schema is well established, specific intrinsic and network-level mechanisms driving spatio-temporal patterns of hippocampal activity during sleep, and specifically controlling off-line memory reactivation are unknown. In this study, we discuss a model of hippocampal CA1-CA3 network generating spontaneous characteristic SWR activity. Our study predicts the properties of CA3 input which are necessary for successful CA1 ripple generation and the role of synaptic interactions and intrinsic excitability in spike sequence replay during SWRs. Specifically, we found that excitatory synaptic connections promote reactivation in both CA3 and CA1, but the different dynamics of sharp waves in CA3 and ripples in CA1 result in a differential role for synaptic inhibition in modulating replay: promoting spike sequence specificity in CA3 but not in CA1 areas. Finally, we describe how awake learning of spatial trajectories leads to synaptic changes sufficient to drive hippocampal cells' reactivation during sleep, as required for sleep-related memory consolidation. Copyright © 2018 Elsevier Inc. All rights reserved.
Experience-Dependent Rewiring of Specific Inhibitory Connections in Adult Neocortex
Kätzel, Dennis; Miesenböck, Gero
2014-01-01
Although neocortical connectivity is remarkably stereotyped, the abundance of some wiring motifs varies greatly between cortical areas. To examine if regional wiring differences represent functional adaptations, we have used optogenetic raster stimulation to map the laminar distribution of GABAergic interneurons providing inhibition to pyramidal cells in layer 2/3 (L2/3) of adult mouse barrel cortex during sensory deprivation and recovery. Whisker trimming caused large, motif-specific changes in inhibitory synaptic connectivity: ascending inhibition from deep layers 4 and 5 was attenuated to 20%–45% of baseline, whereas inhibition from superficial layers remained stable (L2/3) or increased moderately (L1). The principal mechanism of deprivation-induced plasticity was motif-specific changes in inhibitory-to-excitatory connection probabilities; the strengths of extant connections were left unaltered. Whisker regrowth restored the original balance of inhibition from deep and superficial layers. Targeted, reversible modifications of specific inhibitory wiring motifs thus contribute to the adaptive remodeling of cortical circuits. PMID:24586113
Rawson, Randi L; Martin, E Anne; Williams, Megan E
2017-08-01
For most neurons to function properly, they need to develop synaptic specificity. This requires finding specific partner neurons, building the correct types of synapses, and fine-tuning these synapses in response to neural activity. Synaptic specificity is common at both a neuron's input and output synapses, whereby unique synapses are built depending on the partnering neuron. Neuroscientists have long appreciated the remarkable specificity of neural circuits but identifying molecular mechanisms mediating synaptic specificity has only recently accelerated. Here, we focus on recent progress in understanding input and output synaptic specificity in the mammalian brain. We review newly identified circuit examples for both and the latest research identifying molecular mediators including Kirrel3, FGFs, and DGLα. Lastly, we expect the pace of research on input and output specificity to continue to accelerate with the advent of new technologies in genomics, microscopy, and proteomics. Copyright © 2017 Elsevier Ltd. All rights reserved.
Oliva, Carolina A; Inestrosa, Nibaldo C
2015-07-01
During early and late postnatal developments, the establishment of functional neuronal connectivity depends on molecules like Wnt that help the recently formed synapses to establish and consolidate their new cellular interactions. However, unlike other molecules, whether Wnt can modulate the firing properties of cells is unknown. Here, for the first time we explore the physiological effect of the canonical and non-canonical Wnt pathways on a circuit that is currently generating oscillatory activity, the entorhinal cortex-hippocampal circuit. Our results indicate that Wnt pathways have strong influence in the circuital and cellular properties depending on the Wnt protein isoforms, concentration, and type of neuronal circuit. Antibodies against canonical and non-canonical ligands, as well as WASP-1 and sFRP-2, demonstrate that constitutive release of Wnts contributes to the maintenance of the network and intrinsic properties of the circuit. Furthermore, we found that the excess of Wnt3a or the permanent intracellular activation of the pathway with BIO-6 accelerates the period of the oscillation by disrupting the oscillatory units (Up states) in short units, presumably by affecting the synaptic mechanisms that couples neurons into the oscillatory cycle, but without affecting the spike generation. Instead, low doses of Wnt5a increase the period of the oscillation in EC by incorporating new cells into the network activity, probably modifying firing activity in other places of the circuit. Moreover, we found that Wnt signaling operates under different principles in the hippocampus. Using pyrvinium pamoate, a Wnt/β-catenin dependent pathway inhibitor, we demonstrated that this pathway is essential to keep the firing activity in the circuit CA3, and in less degree of CA1 circuit. However, CA1 circuit possesses homeostatic mechanisms to up-regulate the firing activity when it has been suppressed in CA3, and to down-modulate the cellular excitability when exacerbated circuital activity has dominated. In summary, the amount of Wnt that is being released can exert a fine tuning of the physiological output, modulating firing activity, improving reliability of communication between neurons, and maintaining a continuous self-regulatory cycle of synaptic structure-function that can be present during all postnatal life. Copyright © 2015 Elsevier Inc. All rights reserved.
Marijuana and cannabinoid regulation of brain reward circuits.
Lupica, Carl R; Riegel, Arthur C; Hoffman, Alexander F
2004-09-01
The reward circuitry of the brain consists of neurons that synaptically connect a wide variety of nuclei. Of these brain regions, the ventral tegmental area (VTA) and the nucleus accumbens (NAc) play central roles in the processing of rewarding environmental stimuli and in drug addiction. The psychoactive properties of marijuana are mediated by the active constituent, Delta(9)-THC, interacting primarily with CB1 cannabinoid receptors in a large number of brain areas. However, it is the activation of these receptors located within the central brain reward circuits that is thought to play an important role in sustaining the self-administration of marijuana in humans, and in mediating the anxiolytic and pleasurable effects of the drug. Here we describe the cellular circuitry of the VTA and the NAc, define the sites within these areas at which cannabinoids alter synaptic processes, and discuss the relevance of these actions to the regulation of reinforcement and reward. In addition, we compare the effects of Delta(9)-THC with those of other commonly abused drugs on these reward circuits, and we discuss the roles that endogenous cannabinoids may play within these brain pathways, and their possible involvement in regulating ongoing brain function, independently of marijuana consumption. We conclude that, whereas Delta(9)-THC alters the activity of these central reward pathways in a manner that is consistent with other abused drugs, the cellular mechanism through which this occurs is likely different, relying upon the combined regulation of several afferent pathways to the VTA.
Dendritic nonlinearities are tuned for efficient spike-based computations in cortical circuits
Ujfalussy, Balázs B; Makara, Judit K; Branco, Tiago; Lengyel, Máté
2015-01-01
Cortical neurons integrate thousands of synaptic inputs in their dendrites in highly nonlinear ways. It is unknown how these dendritic nonlinearities in individual cells contribute to computations at the level of neural circuits. Here, we show that dendritic nonlinearities are critical for the efficient integration of synaptic inputs in circuits performing analog computations with spiking neurons. We developed a theory that formalizes how a neuron's dendritic nonlinearity that is optimal for integrating synaptic inputs depends on the statistics of its presynaptic activity patterns. Based on their in vivo preynaptic population statistics (firing rates, membrane potential fluctuations, and correlations due to ensemble dynamics), our theory accurately predicted the responses of two different types of cortical pyramidal cells to patterned stimulation by two-photon glutamate uncaging. These results reveal a new computational principle underlying dendritic integration in cortical neurons by suggesting a functional link between cellular and systems--level properties of cortical circuits. DOI: http://dx.doi.org/10.7554/eLife.10056.001 PMID:26705334
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
Kaufman, Alon; Dror, Gideon; Meilijson, Isaac; Ruppin, Eytan
2006-12-08
The claim that genetic properties of neurons significantly influence their synaptic network structure is a common notion in neuroscience. The nematode Caenorhabditis elegans provides an exciting opportunity to approach this question in a large-scale quantitative manner. Its synaptic connectivity network has been identified, and, combined with cellular studies, we currently have characteristic connectivity and gene expression signatures for most of its neurons. By using two complementary analysis assays we show that the expression signature of a neuron carries significant information about its synaptic connectivity signature, and identify a list of putative genes predicting neural connectivity. The current study rigorously quantifies the relation between gene expression and synaptic connectivity signatures in the C. elegans nervous system and identifies subsets of neurons where this relation is highly marked. The results presented and the genes identified provide a promising starting point for further, more detailed computational and experimental investigations.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jung, Jinwoo; Lee, Jewon; Song, Hanjung
2011-03-15
This paper presents a fully integrated circuit implementation of an operational amplifier (op-amp) based chaotic neuron model with a bipolar output function, experimental measurements, and analyses of its chaotic behavior. The proposed chaotic neuron model integrated circuit consists of several op-amps, sample and hold circuits, a nonlinear function block for chaotic signal generation, a clock generator, a nonlinear output function, etc. Based on the HSPICE (circuit program) simulation results, approximated empirical equations for analyses were formulated. Then, the chaotic dynamical responses such as bifurcation diagrams, time series, and Lyapunov exponent were calculated using these empirical equations. In addition, we performedmore » simulations about two chaotic neuron systems with four synapses to confirm neural network connections and got normal behavior of the chaotic neuron such as internal state bifurcation diagram according to the synaptic weight variation. The proposed circuit was fabricated using a 0.8-{mu}m single poly complementary metal-oxide semiconductor technology. Measurements of the fabricated single chaotic neuron with {+-}2.5 V power supplies and a 10 kHz sampling clock frequency were carried out and compared with the simulated results.« less
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
Role of mechanical cues in shaping neuronal morphology and connectivity.
Gangatharan, Girisaran; Schneider-Maunoury, Sylvie; Breau, Marie Anne
2018-06-01
Neuronal circuits, the functional building blocks of the nervous system, assemble during development through a series of dynamic processes including the migration of neurons to their final position, the growth and navigation of axons and their synaptic connection with target cells. While the role of chemical cues in guiding neuronal migration and axonal development has been extensively analysed, the contribution of mechanical inputs, such as forces and stiffness, has received far less attention. In this article, we review the in vitro and more recent in vivo studies supporting the notion that mechanical signals are critical for multiple aspects of neuronal circuit assembly, from the emergence of axons to the formation of functional synapses. By combining live imaging approaches with tools designed to measure and manipulate the mechanical environment of neurons, the emerging field of neuromechanics will add a new paradigm in our understanding of neuronal development and potentially inspire novel regenerative therapies. © 2018 Société Française des Microscopies and Société de Biologie Cellulaire de France. Published by John Wiley & Sons Ltd.
Rahimi Azghadi, Mostafa; Iannella, Nicolangelo; Al-Sarawi, Said; Abbott, Derek
2014-01-01
Cortical circuits in the brain have long been recognised for their information processing capabilities and have been studied both experimentally and theoretically via spiking neural networks. Neuromorphic engineers are primarily concerned with translating the computational capabilities of biological cortical circuits, using the Spiking Neural Network (SNN) paradigm, into in silico applications that can mimic the behaviour and capabilities of real biological circuits/systems. These capabilities include low power consumption, compactness, and relevant dynamics. In this paper, we propose a new accelerated-time circuit that has several advantages over its previous neuromorphic counterparts in terms of compactness, power consumption, and capability to mimic the outcomes of biological experiments. The presented circuit simulation results demonstrate that, in comparing the new circuit to previous published synaptic plasticity circuits, reduced silicon area and lower energy consumption for processing each spike is achieved. In addition, it can be tuned in order to closely mimic the outcomes of various spike timing- and rate-based synaptic plasticity experiments. The proposed circuit is also investigated and compared to other designs in terms of tolerance to mismatch and process variation. Monte Carlo simulation results show that the proposed design is much more stable than its previous counterparts in terms of vulnerability to transistor mismatch, which is a significant challenge in analog neuromorphic design. All these features make the proposed design an ideal circuit for use in large scale SNNs, which aim at implementing neuromorphic systems with an inherent capability that can adapt to a continuously changing environment, thus leading to systems with significant learning and computational abilities. PMID:24551089
Rahimi Azghadi, Mostafa; Iannella, Nicolangelo; Al-Sarawi, Said; Abbott, Derek
2014-01-01
Cortical circuits in the brain have long been recognised for their information processing capabilities and have been studied both experimentally and theoretically via spiking neural networks. Neuromorphic engineers are primarily concerned with translating the computational capabilities of biological cortical circuits, using the Spiking Neural Network (SNN) paradigm, into in silico applications that can mimic the behaviour and capabilities of real biological circuits/systems. These capabilities include low power consumption, compactness, and relevant dynamics. In this paper, we propose a new accelerated-time circuit that has several advantages over its previous neuromorphic counterparts in terms of compactness, power consumption, and capability to mimic the outcomes of biological experiments. The presented circuit simulation results demonstrate that, in comparing the new circuit to previous published synaptic plasticity circuits, reduced silicon area and lower energy consumption for processing each spike is achieved. In addition, it can be tuned in order to closely mimic the outcomes of various spike timing- and rate-based synaptic plasticity experiments. The proposed circuit is also investigated and compared to other designs in terms of tolerance to mismatch and process variation. Monte Carlo simulation results show that the proposed design is much more stable than its previous counterparts in terms of vulnerability to transistor mismatch, which is a significant challenge in analog neuromorphic design. All these features make the proposed design an ideal circuit for use in large scale SNNs, which aim at implementing neuromorphic systems with an inherent capability that can adapt to a continuously changing environment, thus leading to systems with significant learning and computational abilities.
Somatostatin-Expressing Inhibitory Interneurons in Cortical Circuits
Yavorska, Iryna; Wehr, Michael
2016-01-01
Cortical inhibitory neurons exhibit remarkable diversity in their morphology, connectivity, and synaptic properties. Here, we review the function of somatostatin-expressing (SOM) inhibitory interneurons, focusing largely on sensory cortex. SOM neurons also comprise a number of subpopulations that can be distinguished by their morphology, input and output connectivity, laminar location, firing properties, and expression of molecular markers. Several of these classes of SOM neurons show unique dynamics and characteristics, such as facilitating synapses, specific axonal projections, intralaminar input, and top-down modulation, which suggest possible computational roles. SOM cells can be differentially modulated by behavioral state depending on their class, sensory system, and behavioral paradigm. The functional effects of such modulation have been studied with optogenetic manipulation of SOM cells, which produces effects on learning and memory, task performance, and the integration of cortical activity. Different classes of SOM cells participate in distinct disinhibitory circuits with different inhibitory partners and in different cortical layers. Through these disinhibitory circuits, SOM cells help encode the behavioral relevance of sensory stimuli by regulating the activity of cortical neurons based on subcortical and intracortical modulatory input. Associative learning leads to long-term changes in the strength of connectivity of SOM cells with other neurons, often influencing the strength of inhibitory input they receive. Thus despite their heterogeneity and variability across cortical areas, current evidence shows that SOM neurons perform unique neural computations, forming not only distinct molecular but also functional subclasses of cortical inhibitory interneurons. PMID:27746722
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
Sonic Hedgehog Expression in Corticofugal Projection Neurons Directs Cortical Microcircuit Formation
Harwell, Corey C.; Parker, Philip R.L.; Gee, Steven M.; Okada, Ami; McConnell, Susan K.; Kreitzer, Anatol C.; Kriegstein, Arnold R.
2012-01-01
SUMMARY The precise connectivity of inputs and outputs is critical for cerebral cortex function; however, the cellular mechanisms that establish these connections are poorly understood. Here, we show that the secreted molecule Sonic Hedgehog (Shh) is involved in synapse formation of a specific cortical circuit. Shh is expressed in layer V corticofugal projection neurons and the Shh receptor, Brother of CDO (Boc), is expressed in local and callosal projection neurons of layer II/III that synapse onto the subcortical projection neurons. Layer V neurons of mice lacking functional Shh exhibit decreased synapses. Conversely, the loss of functional Boc leads to a reduction in the strength of synaptic connections onto layer Vb, but not layer II/III, pyramidal neurons. These results demonstrate that Shh is expressed in postsynaptic target cells while Boc is expressed in a complementary population of presynaptic input neurons, and they function to guide the formation of cortical microcircuitry. PMID:22445340
Frank Beach Award Winner: Steroids as Neuromodulators of Brain Circuits and Behavior
Remage-Healey, Luke
2014-01-01
Neurons communicate primarily via action potentials that transmit information on the timescale of milliseconds. Neurons also integrate information via alterations in gene transcription and protein translation that are sustained for hours to days after initiation. Positioned between these two signaling timescales are the minute-by-minute actions of neuromodulators. Over the course of minutes, the classical neuromodulators (such as serotonin, dopamine, octopamine, and norepinephrine) can alter and/or stabilize neural circuit patterning as well as behavioral states. Neuromodulators allow many flexible outputs from neural circuits and can encode information content into the firing state of neural networks. The idea that steroid molecules can operate as genuine behavioral neuromodulators - synthesized by and acting within brain circuits on a minute-by-minute timescale - has gained traction in recent years. Evidence for brain steroid synthesis at synaptic terminals has converged with evidence for the rapid actions of brain-derived steroids on neural circuits and behavior. The general principle emerging from this work is that the production of steroid hormones within brain circuits can alter their functional connectivity and shift sensory representations by enhancing their information coding. Steroids produced in the brain can therefore change the information content of neuronal networks to rapidly modulate sensory experience and sensorimotor functions. PMID:25110187
Disruption of visual circuit formation and refinement in a mouse model of autism
Khanbabaei, Maryam; Murari, Kartikeya; Rho, Jong M.
2016-01-01
Aberrant connectivity is believed to contribute to the pathophysiology of autism spectrum disorder (ASD). Recent neuroimaging studies have increasingly identified such impairments in patients with ASD, including alterations in sensory systems. However, the cellular substrates and molecular underpinnings of disrupted connectivity remain poorly understood. Utilizing eye‐specific segregation in the dorsal lateral geniculate nucleus (dLGN) as a model system, we investigated the formation and refinement of precise patterning of synaptic connections in the BTBR T + tf/J (BTBR) mouse model of ASD. We found that at the neonatal stage, the shape of the dLGN occupied by retinal afferents was altered in the BTBR group compared to C57BL/6J (B6) animals. Notably, the degree of overlap between the ipsi‐ and contralateral afferents was significantly greater in the BTBR mice. Moreover, these abnormalities continued into mature stage in the BTBR animals, suggesting persistent deficits rather than delayed maturation of axonal refinement. Together, these results indicate disrupted connectivity at the synaptic patterning level in the BTBR mice, suggesting that in general, altered neural circuitry may contribute to autistic behaviours seen in this animal model. In addition, these data are consistent with the notion that lower‐level, primary processing mechanisms contribute to altered visual perception in ASD. Autism Res 2017, 10: 212–223. © 2016 The Authors Autism Research published by Wiley Periodicals, Inc. on behalf of International Society for Autism Research. PMID:27529416
Asymmetry in electrical coupling between neurons alters multistable firing behavior
NASA Astrophysics Data System (ADS)
Pisarchik, A. N.; Jaimes-Reátegui, R.; García-Vellisca, M. A.
2018-03-01
The role of asymmetry in electrical synaptic connection between two neuronal oscillators is studied in the Hindmarsh-Rose model. We demonstrate that the asymmetry induces multistability in spiking dynamics of the coupled neuronal oscillators. The coexistence of at least three attractors, one chaotic and two periodic orbits, for certain coupling strengths is demonstrated with time series, phase portraits, bifurcation diagrams, basins of attraction of the coexisting states, Lyapunov exponents, and standard deviations of peak amplitudes and interspike intervals. The experimental results with analog electronic circuits are in good agreement with the results of numerical simulations.
Bouamrane, Lamine; Scheyer, Andrew F.; Lassalle, Olivier; Iafrati, Jillian; Thomazeau, Aurore; Chavis, Pascale
2017-01-01
The reelin gene is a strong candidate in the etiology of several psychiatric disorders such as schizophrenia, major depression, bipolar disorders, and autism spectrum disorders. Most of these diseases are accompanied by cognitive and executive-function deficits associated with prefrontal dysfunctions. Mammalian prefrontal cortex (PFC) development is characterized by a protracted postnatal maturation constituting a period of enhanced vulnerability to psychiatric insults. The identification of the molecular components underlying this prolonged postnatal development is necessary to understand the synaptic properties of defective circuits participating in these psychiatric disorders. We have recently shown that reelin plays a key role in the maturation of glutamatergic functions in the postnatal PFC, but no data are available regarding the GABAergic circuits. Here, we undertook a cross-sectional analysis of GABAergic function in deep layer pyramidal neurons of the medial PFC of wild-type and haploinsufficient heterozygous reeler mice. Using electrophysiological approaches, we showed that decreased reelin levels impair the maturation of GABAergic synaptic transmission without affecting the inhibitory nature of GABA. This phenotype consequently impacted the developmental sequence of the synaptic excitation/inhibition (E/I) balance. These data indicate that reelin is necessary for the correct maturation and refinement of GABAergic synaptic circuits in the postnatal PFC and therefore provide a mechanism for altered E/I balance of prefrontal circuits associated with psychiatric disorders. PMID:28127276
Gatto, Cheryl L.; Broadie, Kendal
2011-01-01
Fragile X syndrome (FXS), caused by loss of fragile X mental retardation 1 (FMR1) gene function, is the most common heritable cause of intellectual disability and autism spectrum disorders. The FMR1 product (FMRP) is an RNA-binding protein best established to function in activity-dependent modulation of synaptic connections. In the Drosophila FXS disease model, loss of functionally-conserved dFMRP causes synaptic overgrowth and overelaboration in pigment dispersing factor (PDF) peptidergic neurons in the adult brain. Here, we identify a very different component of PDF neuron misregulation in dfmr1 mutants: the aberrant retention of normally developmentally-transient PDF tritocerebral (PDF-TRI) neurons. In wild-type animals, PDF-TRI neurons in the central brain undergo programmed cell death and complete, processive clearance within days of eclosion. In the absence of dFMRP, a defective apoptotic program leads to constitutive maintenance of these peptidergic neurons. We tested whether this apoptotic defect is circuit-specific by examining crustacean cardioactive peptide (CCAP) and bursicon circuits, which are similarly developmentally-transient and normally eliminated immediately post-eclosion. In dfmr1 null mutants, CCAP/bursicon neurons also exhibit significantly delayed clearance dynamics, but are subsequently eliminated from the nervous system, in contrast to the fully persistent PDF-TRI neurons. Thus, the requirement of dFMRP for the retention of transitory peptidergic neurons shows evident circuit specificity. The novel defect of impaired apoptosis and aberrant neuron persistence in the Drosophila FXS model suggests an entirely new level of “pruning” dysfunction may contribute to the FXS disease state. PMID:21596027
Cascade Back-Propagation Learning in Neural Networks
NASA Technical Reports Server (NTRS)
Duong, Tuan A.
2003-01-01
The cascade back-propagation (CBP) algorithm is the basis of a conceptual design for accelerating learning in artificial neural networks. The neural networks would be implemented as analog very-large-scale integrated (VLSI) circuits, and circuits to implement the CBP algorithm would be fabricated on the same VLSI circuit chips with the neural networks. Heretofore, artificial neural networks have learned slowly because it has been necessary to train them via software, for lack of a good on-chip learning technique. The CBP algorithm is an on-chip technique that provides for continuous learning in real time. Artificial neural networks are trained by example: A network is presented with training inputs for which the correct outputs are known, and the algorithm strives to adjust the weights of synaptic connections in the network to make the actual outputs approach the correct outputs. The input data are generally divided into three parts. Two of the parts, called the "training" and "cross-validation" sets, respectively, must be such that the corresponding input/output pairs are known. During training, the cross-validation set enables verification of the status of the input-to-output transformation learned by the network to avoid over-learning. The third part of the data, termed the "test" set, consists of the inputs that are required to be transformed into outputs; this set may or may not include the training set and/or the cross-validation set. Proposed neural-network circuitry for on-chip learning would be divided into two distinct networks; one for training and one for validation. Both networks would share the same synaptic weights.
Lin, Hong; Magrane, Jordi; Clark, Elisia M; Halawani, Sarah M; Warren, Nathan; Rattelle, Amy; Lynch, David R
2017-12-19
Friedreich ataxia (FRDA) is an autosomal recessive neurodegenerative disorder with progressive ataxia that affects both the peripheral and central nervous system (CNS). While later CNS neuropathology involves loss of large principal neurons and glutamatergic and GABAergic synaptic terminals in the cerebellar dentate nucleus, early pathological changes in FRDA cerebellum remain largely uncharacterized. Here, we report early cerebellar VGLUT1 (SLC17A7)-specific parallel fiber (PF) synaptic deficits and dysregulated cerebellar circuit in the frataxin knock-in/knockout (KIKO) FRDA mouse model. At asymptomatic ages, VGLUT1 levels in cerebellar homogenates are significantly decreased, whereas VGLUT2 (SLC17A6) levels are significantly increased, in KIKO mice compared with age-matched controls. Additionally, GAD65 (GAD2) levels are significantly increased, while GAD67 (GAD1) levels remain unaltered. This suggests early VGLUT1-specific synaptic input deficits, and dysregulation of VGLUT2 and GAD65 synaptic inputs, in the cerebellum of asymptomatic KIKO mice. Immunohistochemistry and electron microscopy further show specific reductions of VGLUT1-containing PF presynaptic terminals in the cerebellar molecular layer, demonstrating PF synaptic input deficiency in asymptomatic and symptomatic KIKO mice. Moreover, the parvalbumin levels in cerebellar homogenates and Purkinje neurons are significantly reduced, but preserved in other interneurons of the cerebellar molecular layer, suggesting specific parvalbumin dysregulation in Purkinje neurons of these mice. Furthermore, a moderate loss of large principal neurons is observed in the dentate nucleus of asymptomatic KIKO mice, mimicking that of FRDA patients. Our findings thus identify early VGLUT1-specific PF synaptic input deficits and dysregulated cerebellar circuit as potential mediators of cerebellar dysfunction in KIKO mice, reflecting developmental features of FRDA in this mouse model. © 2017. Published by The Company of Biologists Ltd.
Creation of defined single cell resolution neuronal circuits on microelectrode arrays
NASA Astrophysics Data System (ADS)
Pirlo, Russell Kirk
2009-12-01
The way cell-cell organization of neuronal networks influences activity and facilitates function is not well understood. Microelectrode arrays (MEAs) and advancing cell patterning technologies have enabled access to and control of in vitro neuronal networks spawning much new research in neuroscience and neuroengineering. We propose that small, simple networks of neurons with defined circuitry may serve as valuable research models where every connection can be analyzed, controlled and manipulated. Towards the goal of creating such neuronal networks we have applied microfabricated elastomeric membranes, surface modification and our unique laser cell patterning system to create defined neuronal circuits with single-cell precision on MEAs. Definition of synaptic connectivity was imposed by the 3D physical constraints of polydimethylsiloxane elastomeric membranes. The membranes had 20mum clear-through holes and 2-3mum deep channels which when applied to the surface of the MEA formed microwells to confine neurons to electrodes connected via shallow tunnels to direct neurite outgrowth. Tapering and turning of channels was used to influence neurite polarity. Biocompatibility of the membranes was increased by vacuum baking, oligomer extraction, and autoclaving. Membranes were bound to the MEA by oxygen plasma treatment and heated pressure. The MEA/membrane surface was treated with oxygen plasma, poly-D-lysine and laminin to improve neuron attachment, survival and neurite outgrowth. Prior to cell patterning the outer edge of culture area was seeded with 5x10 5 cells per cm and incubated for 2 days. Single embryonic day 7 chick forebrain neurons were then patterned into the microwells and onto the electrodes using our laser cell patterning system. Patterned neurons successfully attached to and were confined to the electrodes. Neurites extended through the interconnecting channels and connected with adjacent neurons. These results demonstrate that neuronal circuits can be created with clearly defined circuitry and a one-to-one neuron-electrode ratio. The techniques and processes described here may be used in future research to create defined neuronal circuits to model in vivo circuits and study neuronal network processing.
Multiple effects of β-amyloid on single excitatory synaptic connections in the PFC.
Wang, Yun; Zhou, Thomas H; Zhi, Zhina; Barakat, Amey; Hlatky, Lynn; Querfurth, Henry
2013-01-01
Prefrontal cortex (PFC) is recognized as an AD-vulnerable region responsible for defects in cognitive functioning. Pyramidal cell (PC) connections are typically facilitating (F) or depressing (D) in PFC. Excitatory post-synaptic potentials (EPSPs) were recorded using patch-clamp from single connections in PFC slices of rats and ferrets in the presence of β-amyloid (Aβ). Synaptic transmission was significantly enhanced or reduced depending on their intrinsic type (facilitating or depressing), Aβ species (Aβ 40 or Aβ 42) and concentration (1-200 nM vs. 0.3-1 μ M). Nanomolar Aβ 40 and Aβ 42 had opposite effects on F-connections, resulting in fewer or increased EPSP failure rates, strengthening or weakening EPSPs and enhancing or inhibiting short-term potentiation [STP: synaptic augmentation (SA) and post-tetanic potentiation (PTP)], respectively. High Aβ 40 concentrations induced inhibition regardless of synaptic type. D-connections were inhibited regardless of Aβ species or concentration. The inhibition induced with bath application was hard to recover by washout, but a complete recovery was obtained with brief local application and prompt washout. Our data suggests that Aβ 40 acts on the prefrontal neuronal network by modulating facilitating and depressing synapses. At higher levels, both Aβ 40 and Aβ 42 inhibit synaptic activity and cause irreversible toxicity once diffusely accumulated in the synaptic environment.
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.
Kyuyoung, Christine L; Huguenard, John R
2014-01-08
Recurrent connections in the corticothalamic circuit underlie oscillatory behavior in this network and range from normal sleep rhythms to the abnormal spike-wave discharges seen in absence epilepsy. The propensity of thalamic neurons to fire postinhibitory rebound bursts mediated by low-threshold calcium spikes renders the circuit vulnerable to both increased excitation and increased inhibition, such as excessive excitatory cortical drive to thalamic reticular (RT) neurons or heightened inhibition of thalamocortical relay (TC) neurons by RT. In this context, a protective role may be played by group III metabotropic receptors (mGluRs), which are uniquely located in the presynaptic active zone and typically act as autoreceptors or heteroceptors to depress synaptic release. Here, we report that these receptors regulate short-term plasticity at two loci in the corticothalamic circuit in rats: glutamatergic cortical synapses onto RT neurons and GABAergic synapses onto TC neurons in somatosensory ventrobasal thalamus. The net effect of group III mGluR activation at these synapses is to suppress thalamic oscillations as assayed in vitro. These findings suggest a functional role of these receptors to modulate corticothalamic transmission and protect against prolonged activity in the network.
Biologically based neural circuit modelling for the study of fear learning and extinction
NASA Astrophysics Data System (ADS)
Nair, Satish S.; Paré, Denis; Vicentic, Aleksandra
2016-11-01
The neuronal systems that promote protective defensive behaviours have been studied extensively using Pavlovian conditioning. In this paradigm, an initially neutral-conditioned stimulus is paired with an aversive unconditioned stimulus leading the subjects to display behavioural signs of fear. Decades of research into the neural bases of this simple behavioural paradigm uncovered that the amygdala, a complex structure comprised of several interconnected nuclei, is an essential part of the neural circuits required for the acquisition, consolidation and expression of fear memory. However, emerging evidence from the confluence of electrophysiological, tract tracing, imaging, molecular, optogenetic and chemogenetic methodologies, reveals that fear learning is mediated by multiple connections between several amygdala nuclei and their distributed targets, dynamical changes in plasticity in local circuit elements as well as neuromodulatory mechanisms that promote synaptic plasticity. To uncover these complex relations and analyse multi-modal data sets acquired from these studies, we argue that biologically realistic computational modelling, in conjunction with experiments, offers an opportunity to advance our understanding of the neural circuit mechanisms of fear learning and to address how their dysfunction may lead to maladaptive fear responses in mental disorders.
Programmable synaptic chip for electronic neural networks
NASA Technical Reports Server (NTRS)
Moopenn, A.; Langenbacher, H.; Thakoor, A. P.; Khanna, S. K.
1988-01-01
A binary synaptic matrix chip has been developed for electronic neural networks. The matrix chip contains a programmable 32X32 array of 'long channel' NMOSFET binary connection elements implemented in a 3-micron bulk CMOS process. Since the neurons are kept off-chip, the synaptic chip serves as a 'cascadable' building block for a multi-chip synaptic network as large as 512X512 in size. As an alternative to the programmable NMOSFET (long channel) connection elements, tailored thin film resistors are deposited, in series with FET switches, on some CMOS test chips, to obtain the weak synaptic connections. Although deposition and patterning of the resistors require additional processing steps, they promise substantial savings in silicon area. The performance of synaptic chip in a 32-neuron breadboard system in an associative memory test application is discussed.
Gainey, Melanie A; Aman, Joseph W; Feldman, Daniel E
2018-04-20
Rapid plasticity of layer (L) 2/3 inhibitory circuits is an early step in sensory cortical map plasticity, but its cellular basis is unclear. We show that, in mice of either sex, 1 day whisker deprivation drives rapid loss of L4-evoked feedforward inhibition and more modest loss of feedforward excitation in L2/3 pyramidal (PYR) cells, increasing E-I conductance ratio. Rapid disinhibition was due to reduced L4-evoked spiking by L2/3 parvalbumin (PV) interneurons, caused by reduced PV intrinsic excitability. This included elevated PV spike threshold, associated with an increase in low-threshold, voltage activated delayed rectifier (presumed Kv1) and A-type potassium currents. Excitatory synaptic input and unitary inhibitory output of PV cells were unaffected. Functionally, the loss of feedforward inhibition and excitation were precisely coordinated in L2/3 PYR cells, so that peak feedforward synaptic depolarization remained stable. Thus, rapid plasticity of PV intrinsic excitability offsets early weakening of excitatory circuits to homeostatically stabilize synaptic potentials in PYR cells of sensory cortex. SIGNIFICANCE STATEMENT Inhibitory circuits in cerebral cortex are highly plastic, but the cellular mechanisms and functional importance of this plasticity are incompletely understood. We show that brief (1-day) sensory deprivation rapidly weakens parvalbumin (PV) inhibitory circuits by reducing the intrinsic excitability of PV neurons. This involved a rapid increase in voltage-gated potassium conductances that control near-threshold spiking excitability. Functionally, the loss of PV-mediated feedforward inhibition in L2/3 pyramidal cells was precisely balanced with the separate loss of feedforward excitation, resulting in a net homeostatic stabilization of synaptic potentials. Thus, rapid plasticity of PV intrinsic excitability implements network-level homeostasis to stabilize synaptic potentials in sensory cortex. Copyright © 2018 the authors.
Synapse-specific astrocyte gating of amygdala-related behavior.
Martin-Fernandez, Mario; Jamison, Stephanie; Robin, Laurie M; Zhao, Zhe; Martin, Eduardo D; Aguilar, Juan; Benneyworth, Michael A; Marsicano, Giovanni; Araque, Alfonso
2017-11-01
The amygdala plays key roles in fear and anxiety. Studies of the amygdala have largely focused on neuronal function and connectivity. Astrocytes functionally interact with neurons, but their role in the amygdala remains largely unknown. We show that astrocytes in the medial subdivision of the central amygdala (CeM) determine the synaptic and behavioral outputs of amygdala circuits. To investigate the role of astrocytes in amygdala-related behavior and identify the underlying synaptic mechanisms, we used exogenous or endogenous signaling to selectively activate CeM astrocytes. Astrocytes depressed excitatory synapses from basolateral amygdala via A 1 adenosine receptor activation and enhanced inhibitory synapses from the lateral subdivision of the central amygdala via A 2A receptor activation. Furthermore, astrocytic activation decreased the firing rate of CeM neurons and reduced fear expression in a fear-conditioning paradigm. Therefore, we conclude that astrocyte activity determines fear responses by selectively regulating specific synapses, which indicates that animal behavior results from the coordinated activity of neurons and astrocytes.
Spike-timing-dependent plasticity in the human dorso-lateral prefrontal cortex.
Casula, Elias Paolo; Pellicciari, Maria Concetta; Picazio, Silvia; Caltagirone, Carlo; Koch, Giacomo
2016-12-01
Changes in the synaptic strength of neural connections are induced by repeated coupling of activity of interconnected neurons with precise timing, a phenomenon known as spike-timing-dependent plasticity (STDP). It is debated if this mechanism exists in large-scale cortical networks in humans. We combined transcranial magnetic stimulation (TMS) with concurrent electroencephalography (EEG) to directly investigate the effects of two paired associative stimulation (PAS) protocols (fronto-parietal and parieto-frontal) of pre and post-synaptic inputs within the human fronto-parietal network. We found evidence that the dorsolateral prefrontal cortex (DLPFC) has the potential to form robust STDP. Long-term potentiation/depression of TMS-evoked cortical activity is prompted after that DLPFC stimulation is followed/preceded by posterior parietal stimulation. Such bidirectional changes are paralleled by sustained increase/decrease of high-frequency oscillatory activity, likely reflecting STDP responsivity. The current findings could be important to drive plasticity of damaged cortical circuits in patients with cognitive or psychiatric disorders. Copyright © 2016 Elsevier Inc. All rights reserved.
Sensory Optimization by Stochastic Tuning
Jurica, Peter; Gepshtein, Sergei; Tyukin, Ivan; van Leeuwen, Cees
2013-01-01
Individually, visual neurons are each selective for several aspects of stimulation, such as stimulus location, frequency content, and speed. Collectively, the neurons implement the visual system’s preferential sensitivity to some stimuli over others, manifested in behavioral sensitivity functions. We ask how the individual neurons are coordinated to optimize visual sensitivity. We model synaptic plasticity in a generic neural circuit, and find that stochastic changes in strengths of synaptic connections entail fluctuations in parameters of neural receptive fields. The fluctuations correlate with uncertainty of sensory measurement in individual neurons: the higher the uncertainty the larger the amplitude of fluctuation. We show that this simple relationship is sufficient for the stochastic fluctuations to steer sensitivities of neurons toward a characteristic distribution, from which follows a sensitivity function observed in human psychophysics, and which is predicted by a theory of optimal allocation of receptive fields. The optimal allocation arises in our simulations without supervision or feedback about system performance and independently of coupling between neurons, making the system highly adaptive and sensitive to prevailing stimulation. PMID:24219849
Martin, E Anne; Muralidhar, Shruti; Wang, Zhirong; Cervantes, Diégo Cordero; Basu, Raunak; Taylor, Matthew R; Hunter, Jennifer; Cutforth, Tyler; Wilke, Scott A; Ghosh, Anirvan; Williams, Megan E
2015-11-17
Synaptic target specificity, whereby neurons make distinct types of synapses with different target cells, is critical for brain function, yet the mechanisms driving it are poorly understood. In this study, we demonstrate Kirrel3 regulates target-specific synapse formation at hippocampal mossy fiber (MF) synapses, which connect dentate granule (DG) neurons to both CA3 and GABAergic neurons. Here, we show Kirrel3 is required for formation of MF filopodia; the structures that give rise to DG-GABA synapses and that regulate feed-forward inhibition of CA3 neurons. Consequently, loss of Kirrel3 robustly increases CA3 neuron activity in developing mice. Alterations in the Kirrel3 gene are repeatedly associated with intellectual disabilities, but the role of Kirrel3 at synapses remained largely unknown. Our findings demonstrate that subtle synaptic changes during development impact circuit function and provide the first insight toward understanding the cellular basis of Kirrel3-dependent neurodevelopmental disorders.
AgRP to Kiss1 neuron signaling links nutritional state and fertility
Padilla, Stephanie L.; Qiu, Jian; Nestor, Casey C; Zhang, Chunguang; Smith, Arik W.; Whiddon, Benjamin B.; Rønnekleiv, Oline K.; Kelly, Martin J.; Palmiter, Richard D.
2017-01-01
Mammalian reproductive function depends upon a neuroendocrine circuit that evokes the pulsatile release of gonadotropin hormones (luteinizing hormone and follicle-stimulating hormone) from the pituitary. This reproductive circuit is sensitive to metabolic perturbations. When challenged with starvation, insufficient energy reserves attenuate gonadotropin release, leading to infertility. The reproductive neuroendocrine circuit is well established, composed of two populations of kisspeptin-expressing neurons (located in the anteroventral periventricular hypothalamus, Kiss1AVPV, and arcuate hypothalamus, Kiss1ARH), which drive the pulsatile activity of gonadotropin-releasing hormone (GnRH) neurons. The reproductive axis is primarily regulated by gonadal steroid and circadian cues, but the starvation-sensitive input that inhibits this circuit during negative energy balance remains controversial. Agouti-related peptide (AgRP)-expressing neurons are activated during starvation and have been implicated in leptin-associated infertility. To test whether these neurons relay information to the reproductive circuit, we used AgRP-neuron ablation and optogenetics to explore connectivity in acute slice preparations. Stimulation of AgRP fibers revealed direct, inhibitory synaptic connections with Kiss1ARH and Kiss1AVPV neurons. In agreement with this finding, Kiss1ARH neurons received less presynaptic inhibition in the absence of AgRP neurons (neonatal toxin-induced ablation). To determine whether enhancing the activity of AgRP neurons is sufficient to attenuate fertility in vivo, we artificially activated them over a sustained period and monitored fertility. Chemogenetic activation with clozapine N-oxide resulted in delayed estrous cycles and decreased fertility. These findings are consistent with the idea that, during metabolic deficiency, AgRP signaling contributes to infertility by inhibiting Kiss1 neurons. PMID:28196880
Interneuronal Mechanism for Tinbergen’s Hierarchical Model of Behavioral Choice
Pirger, Zsolt; Crossley, Michael; László, Zita; Naskar, Souvik; Kemenes, György; O’Shea, Michael; Benjamin, Paul R.; Kemenes, Ildikó
2014-01-01
Summary Recent studies of behavioral choice support the notion that the decision to carry out one behavior rather than another depends on the reconfiguration of shared interneuronal networks [1]. We investigated another decision-making strategy, derived from the classical ethological literature [2, 3], which proposes that behavioral choice depends on competition between autonomous networks. According to this model, behavioral choice depends on inhibitory interactions between incompatible hierarchically organized behaviors. We provide evidence for this by investigating the interneuronal mechanisms mediating behavioral choice between two autonomous circuits that underlie whole-body withdrawal [4, 5] and feeding [6] in the pond snail Lymnaea. Whole-body withdrawal is a defensive reflex that is initiated by tactile contact with predators. As predicted by the hierarchical model, tactile stimuli that evoke whole-body withdrawal responses also inhibit ongoing feeding in the presence of feeding stimuli. By recording neurons from the feeding and withdrawal networks, we found no direct synaptic connections between the interneuronal and motoneuronal elements that generate the two behaviors. Instead, we discovered that behavioral choice depends on the interaction between two unique types of interneurons with asymmetrical synaptic connectivity that allows withdrawal to override feeding. One type of interneuron, the Pleuro-Buccal (PlB), is an extrinsic modulatory neuron of the feeding network that completely inhibits feeding when excited by touch-induced monosynaptic input from the second type of interneuron, Pedal-Dorsal12 (PeD12). PeD12 plays a critical role in behavioral choice by providing a synaptic pathway joining the two behavioral networks that underlies the competitive dominance of whole-body withdrawal over feeding. PMID:25155505
Arriaga, Gustavo; Macopson, Joshua J; Jarvis, Erich D
2015-09-14
Transsynaptic tracing has become a powerful tool used to analyze central efferents that regulate peripheral targets through multi-synaptic circuits. This approach has been most extensively used in the brain by utilizing the swine pathogen pseudorabies virus (PRV)(1). PRV does not infect great apes, including humans, so it is most commonly used in studies on small mammals, especially rodents. The pseudorabies strain PRV152 expresses the enhanced green fluorescent protein (eGFP) reporter gene and only crosses functional synapses retrogradely through the hierarchical sequence of synaptic connections away from the infection site(2,3). Other PRV strains have distinct microbiological properties and may be transported in both directions (PRV-Becker and PRV-Kaplan)(4,5). This protocol will deal exclusively with PRV152. By delivering the virus at a peripheral site, such as muscle, it is possible to limit the entry of the virus into the brain through a specific set of neurons. The resulting pattern of eGFP signal throughout the brain then resolves the neurons that are connected to the initially infected cells. As the distributed nature of transsynaptic tracing with pseudorabies virus makes interpreting specific connections within an identified network difficult, we present a sensitive and reliable method employing biotinylated dextran amines (BDA) and cholera toxin subunit b (CTb) for confirming the connections between cells identified using PRV152. Immunochemical detection of BDA and CTb with peroxidase and DAB (3, 3'-diaminobenzidine) was chosen because they are effective at revealing cellular processes including distal dendrites(6-11).
Wang, Peng; Knösche, Thomas R.
2013-01-01
In this work we propose a biologically realistic local cortical circuit model (LCCM), based on neural masses, that incorporates important aspects of the functional organization of the brain that have not been covered by previous models: (1) activity dependent plasticity of excitatory synaptic couplings via depleting and recycling of neurotransmitters and (2) realistic inter-laminar dynamics via laminar-specific distribution of and connections between neural populations. The potential of the LCCM was demonstrated by accounting for the process of auditory habituation. The model parameters were specified using Bayesian inference. It was found that: (1) besides the major serial excitatory information pathway (layer 4 to layer 2/3 to layer 5/6), there exists a parallel “short-cut” pathway (layer 4 to layer 5/6), (2) the excitatory signal flow from the pyramidal cells to the inhibitory interneurons seems to be more intra-laminar while, in contrast, the inhibitory signal flow from inhibitory interneurons to the pyramidal cells seems to be both intra- and inter-laminar, and (3) the habituation rates of the connections are unsymmetrical: forward connections (from layer 4 to layer 2/3) are more strongly habituated than backward connections (from Layer 5/6 to layer 4). Our evaluation demonstrates that the novel features of the LCCM are of crucial importance for mechanistic explanations of brain function. The incorporation of these features into a mass model makes them applicable to modeling based on macroscopic data (like EEG or MEG), which are usually available in human experiments. Our LCCM is therefore a valuable building block for future realistic models of human cognitive function. PMID:24205009
Billeh, Yazan N.; Bernard, Amy; de Vivo, Luisa; Honjoh, Sakiko; Mihalas, Stefan; Ng, Lydia; Koch, Christof
2016-01-01
Abstract Cortical circuits mature in stages, from early synaptogenesis and synaptic pruning to late synaptic refinement, resulting in the adult anatomical connection matrix. Because the mature matrix is largely fixed, genetic or environmental factors interfering with its establishment can have irreversible effects. Sleep disruption is rarely considered among those factors, and previous studies have focused on very young animals and the acute effects of sleep deprivation on neuronal morphology and cortical plasticity. Adolescence is a sensitive time for brain remodeling, yet whether chronic sleep restriction (CSR) during adolescence has long-term effects on brain connectivity remains unclear. We used viral-mediated axonal labeling and serial two-photon tomography to measure brain-wide projections from secondary motor cortex (MOs), a high-order area with diffuse projections. For each MOs target, we calculated the projection fraction, a combined measure of passing fibers and axonal terminals normalized for the size of each target. We found no homogeneous differences in MOs projection fraction between mice subjected to 5 days of CSR during early adolescence (P25–P30, ≥50% decrease in daily sleep, n=14) and siblings that slept undisturbed (n=14). Machine learning algorithms, however, classified animals at significantly above chance levels, indicating that differences between the two groups exist, but are subtle and heterogeneous. Thus, sleep disruption in early adolescence may affect adult brain connectivity. However, because our method relies on a global measure of projection density and was not previously used to measure connectivity changes due to behavioral manipulations, definitive conclusions on the long-term structural effects of early CSR require additional experiments. PMID:27351022
Park, Sang Mee; Park, Hae Ryoun; Lee, Ji Hye
2017-02-01
Proper synaptic function in neural circuits requires precise pairings between correct pre- and post-synaptic partners. Errors in this process may underlie development of neuropsychiatric disorders, such as autism spectrum disorder (ASD). Development of ASD can be influenced by genetic factors, including copy number variations (CNVs). In this study, we focused on a CNV occurring at the 16p11.2 locus in the human genome and investigated potential defects in synaptic connectivity caused by reduced activities of genes located in this region at Drosophila larval neuromuscular junctions, a well-established model synapse with stereotypic synaptic structures. A mutation of rolled , a Drosophila homolog of human mitogen-activated protein kinase 3 ( MAPK3 ) at the 16p11.2 locus, caused ectopic innervation of axonal branches and their abnormal defasciculation. The specificity of these phenotypes was confirmed by expression of wild-type rolled in the mutant background. Albeit to a lesser extent, we also observed ectopic innervation patterns in mutants defective in Cdk2, Gα q , and Gp93, all of which were expected to interact with Rolled MAPK3. A further genetic analysis in double heterozygous combinations revealed a synergistic interaction between rolled and Gp93 . In addition, results from RT-qPCR analyses indicated consistently reduced rolled mRNA levels in Cdk2 , Gα q , and Gp93 mutants. Taken together, these data suggest a central role of MAPK3 in regulating the precise targeting of presynaptic axons to proper postsynaptic targets, a critical step that may be altered significantly in ASD.
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
Pattern classification by memristive crossbar circuits using ex situ and in situ training.
Alibart, Fabien; Zamanidoost, Elham; Strukov, Dmitri B
2013-01-01
Memristors are memory resistors that promise the efficient implementation of synaptic weights in artificial neural networks. Whereas demonstrations of the synaptic operation of memristors already exist, the implementation of even simple networks is more challenging and has yet to be reported. Here we demonstrate pattern classification using a single-layer perceptron network implemented with a memrisitive crossbar circuit and trained using the perceptron learning rule by ex situ and in situ methods. In the first case, synaptic weights, which are realized as conductances of titanium dioxide memristors, are calculated on a precursor software-based network and then imported sequentially into the crossbar circuit. In the second case, training is implemented in situ, so the weights are adjusted in parallel. Both methods work satisfactorily despite significant variations in the switching behaviour of the memristors. These results give hope for the anticipated efficient implementation of artificial neuromorphic networks and pave the way for dense, high-performance information processing systems.
Pattern classification by memristive crossbar circuits using ex situ and in situ training
NASA Astrophysics Data System (ADS)
Alibart, Fabien; Zamanidoost, Elham; Strukov, Dmitri B.
2013-06-01
Memristors are memory resistors that promise the efficient implementation of synaptic weights in artificial neural networks. Whereas demonstrations of the synaptic operation of memristors already exist, the implementation of even simple networks is more challenging and has yet to be reported. Here we demonstrate pattern classification using a single-layer perceptron network implemented with a memrisitive crossbar circuit and trained using the perceptron learning rule by ex situ and in situ methods. In the first case, synaptic weights, which are realized as conductances of titanium dioxide memristors, are calculated on a precursor software-based network and then imported sequentially into the crossbar circuit. In the second case, training is implemented in situ, so the weights are adjusted in parallel. Both methods work satisfactorily despite significant variations in the switching behaviour of the memristors. These results give hope for the anticipated efficient implementation of artificial neuromorphic networks and pave the way for dense, high-performance information processing systems.
Nikolaev, Anton; Zheng, Lei; Wardill, Trevor J; O'Kane, Cahir J; de Polavieja, Gonzalo G; Juusola, Mikko
2009-01-01
Retinal networks must adapt constantly to best present the ever changing visual world to the brain. Here we test the hypothesis that adaptation is a result of different mechanisms at several synaptic connections within the network. In a companion paper (Part I), we showed that adaptation in the photoreceptors (R1-R6) and large monopolar cells (LMC) of the Drosophila eye improves sensitivity to under-represented signals in seconds by enhancing both the amplitude and frequency distribution of LMCs' voltage responses to repeated naturalistic contrast series. In this paper, we show that such adaptation needs both the light-mediated conductance and feedback-mediated synaptic conductance. A faulty feedforward pathway in histamine receptor mutant flies speeds up the LMC output, mimicking extreme light adaptation. A faulty feedback pathway from L2 LMCs to photoreceptors slows down the LMC output, mimicking dark adaptation. These results underline the importance of network adaptation for efficient coding, and as a mechanism for selectively regulating the size and speed of signals in neurons. We suggest that concert action of many different mechanisms and neural connections are responsible for adaptation to visual stimuli. Further, our results demonstrate the need for detailed circuit reconstructions like that of the Drosophila lamina, to understand how networks process information.
Permitted and forbidden sets in symmetric threshold-linear networks.
Hahnloser, Richard H R; Seung, H Sebastian; Slotine, Jean-Jacques
2003-03-01
The richness and complexity of recurrent cortical circuits is an inexhaustible source of inspiration for thinking about high-level biological computation. In past theoretical studies, constraints on the synaptic connection patterns of threshold-linear networks were found that guaranteed bounded network dynamics, convergence to attractive fixed points, and multistability, all fundamental aspects of cortical information processing. However, these conditions were only sufficient, and it remained unclear which were the minimal (necessary) conditions for convergence and multistability. We show that symmetric threshold-linear networks converge to a set of attractive fixed points if and only if the network matrix is copositive. Furthermore, the set of attractive fixed points is nonconnected (the network is multiattractive) if and only if the network matrix is not positive semidefinite. There are permitted sets of neurons that can be coactive at a stable steady state and forbidden sets that cannot. Permitted sets are clustered in the sense that subsets of permitted sets are permitted and supersets of forbidden sets are forbidden. By viewing permitted sets as memories stored in the synaptic connections, we provide a formulation of long-term memory that is more general than the traditional perspective of fixed-point attractor networks. There is a close correspondence between threshold-linear networks and networks defined by the generalized Lotka-Volterra equations.
Energy-efficient neuron, synapse and STDP integrated circuits.
Cruz-Albrecht, Jose M; Yung, Michael W; Srinivasa, Narayan
2012-06-01
Ultra-low energy biologically-inspired neuron and synapse integrated circuits are presented. The synapse includes a spike timing dependent plasticity (STDP) learning rule circuit. These circuits have been designed, fabricated and tested using a 90 nm CMOS process. Experimental measurements demonstrate proper operation. The neuron and the synapse with STDP circuits have an energy consumption of around 0.4 pJ per spike and synaptic operation respectively.
Shapley, Robert M.; Xing, Dajun
2012-01-01
Theoretical considerations have led to the concept that the cerebral cortex is operating in a balanced state in which synaptic excitation is approximately balanced by synaptic inhibition from the local cortical circuit. This paper is about the functional consequences of the balanced state in sensory cortex. One consequence is gain control: there is experimental evidence and theoretical support for the idea that local circuit inhibition acts as a local automatic gain control throughout the cortex. Second, inhibition increases cortical feature selectivity: many studies of different sensory cortical areas have reported that suppressive mechanisms contribute to feature selectivity. Synaptic inhibition from the local microcircuit should be untuned (or broadly tuned) for stimulus features because of the microarchitecture of the cortical microcircuit. Untuned inhibition probably is the source of Untuned Suppression that enhances feature selectivity. We studied inhibition’s function in our experiments, guided by a neuronal network model, on orientation selectivity in the primary visual cortex, V1, of the Macaque monkey. Our results revealed that Untuned Suppression, generated by local circuit inhibition, is crucial for the generation of highly orientation-selective cells in V1 cortex. PMID:23036513
Multiple effects of β-amyloid on single excitatory synaptic connections in the PFC
Wang, Yun; Zhou, Thomas H.; Zhi, Zhina; Barakat, Amey; Hlatky, Lynn; Querfurth, Henry
2013-01-01
Prefrontal cortex (PFC) is recognized as an AD-vulnerable region responsible for defects in cognitive functioning. Pyramidal cell (PC) connections are typically facilitating (F) or depressing (D) in PFC. Excitatory post-synaptic potentials (EPSPs) were recorded using patch-clamp from single connections in PFC slices of rats and ferrets in the presence of β-amyloid (Aβ). Synaptic transmission was significantly enhanced or reduced depending on their intrinsic type (facilitating or depressing), Aβ species (Aβ 40 or Aβ 42) and concentration (1–200 nM vs. 0.3–1 μ M). Nanomolar Aβ 40 and Aβ 42 had opposite effects on F-connections, resulting in fewer or increased EPSP failure rates, strengthening or weakening EPSPs and enhancing or inhibiting short-term potentiation [STP: synaptic augmentation (SA) and post-tetanic potentiation (PTP)], respectively. High Aβ 40 concentrations induced inhibition regardless of synaptic type. D-connections were inhibited regardless of Aβ species or concentration. The inhibition induced with bath application was hard to recover by washout, but a complete recovery was obtained with brief local application and prompt washout. Our data suggests that Aβ 40 acts on the prefrontal neuronal network by modulating facilitating and depressing synapses. At higher levels, both Aβ 40 and Aβ 42 inhibit synaptic activity and cause irreversible toxicity once diffusely accumulated in the synaptic environment. PMID:24027495
Tracking slow modulations in synaptic gain using dynamic causal modelling: validation in epilepsy.
Papadopoulou, Margarita; Leite, Marco; van Mierlo, Pieter; Vonck, Kristl; Lemieux, Louis; Friston, Karl; Marinazzo, Daniele
2015-02-15
In this work we propose a proof of principle that dynamic causal modelling can identify plausible mechanisms at the synaptic level underlying brain state changes over a timescale of seconds. As a benchmark example for validation we used intracranial electroencephalographic signals in a human subject. These data were used to infer the (effective connectivity) architecture of synaptic connections among neural populations assumed to generate seizure activity. Dynamic causal modelling allowed us to quantify empirical changes in spectral activity in terms of a trajectory in parameter space - identifying key synaptic parameters or connections that cause observed signals. Using recordings from three seizures in one patient, we considered a network of two sources (within and just outside the putative ictal zone). Bayesian model selection was used to identify the intrinsic (within-source) and extrinsic (between-source) connectivity. Having established the underlying architecture, we were able to track the evolution of key connectivity parameters (e.g., inhibitory connections to superficial pyramidal cells) and test specific hypotheses about the synaptic mechanisms involved in ictogenesis. Our key finding was that intrinsic synaptic changes were sufficient to explain seizure onset, where these changes showed dissociable time courses over several seconds. Crucially, these changes spoke to an increase in the sensitivity of principal cells to intrinsic inhibitory afferents and a transient loss of excitatory-inhibitory balance. Copyright © 2014. Published by Elsevier Inc.
Aberrant excitatory rewiring of layer V pyramidal neurons early after neocortical trauma
Takahashi, D. Koji; Isabel, Feng Gu; Parada, Shri Vyas; Prince, David A.
2016-01-01
Lesioned neuronal circuits form new functional connections after a traumatic brain injury (TBI). In humans and animal models, aberrant excitatory connections that form after TBI may contribute to the pathogenesis of post-traumatic epilepsy. Partial neocortical isolation (“undercut” or “UC”) leads to altered neuronal circuitry and network hyperexcitability recorded in vivo and in brain slices from chronically lesioned neocortex. Recent data suggest a critical period for maladaptive excitatory circuit formation within the first 3 days post UC injury (Graber and Prince, 1999, 2004; Li et al., 2011, 2012b). The present study focuses on alterations in excitatory connectivity within this critical period. Immunoreactivity (IR) for growth-associated protein (GAP)-43 was increased in the UC cortex 3 days after injury. Some GAP-43-expressing excitatory terminals targeted the somata of layer V pyramidal (Pyr) neurons, a domain usually innervated predominantly by inhibitory terminals. Immunocytochemical analysis of pre- and postsynaptic markers showed that putative excitatory synapses were present on somata of these neurons in UC neocortex. Excitatory postsynaptic currents from UC layer V Pyr cells displayed properties consistent with perisomatic inputs and also reflected an increase in the number of synaptic contacts. Laser scanning photostimulation (LSPS) experiments demonstrated reorganized excitatory connectivity after injury within the UC. Concurrent with these changes, spontaneous epileptiform bursts developed in UC slices. Results suggest that aberrant reorganization of excitatory connectivity contributes to early neocortical hyperexcitability in this model. The findings are relevant for understanding the pathophysiology of neocortical post-traumatic epileptogenesis and are important in terms of the timing of potential prophylactic treatments. PMID:26956396
Aberrant excitatory rewiring of layer V pyramidal neurons early after neocortical trauma.
Takahashi, D Koji; Gu, Feng; Parada, Isabel; Vyas, Shri; Prince, David A
2016-07-01
Lesioned neuronal circuits form new functional connections after a traumatic brain injury (TBI). In humans and animal models, aberrant excitatory connections that form after TBI may contribute to the pathogenesis of post-traumatic epilepsy. Partial neocortical isolation ("undercut" or "UC") leads to altered neuronal circuitry and network hyperexcitability recorded in vivo and in brain slices from chronically lesioned neocortex. Recent data suggest a critical period for maladaptive excitatory circuit formation within the first 3days post UC injury (Graber and Prince 1999, 2004; Li et al. 2011, 2012b). The present study focuses on alterations in excitatory connectivity within this critical period. Immunoreactivity (IR) for growth-associated protein (GAP)-43 was increased in the UC cortex 3days after injury. Some GAP-43-expressing excitatory terminals targeted the somata of layer V pyramidal (Pyr) neurons, a domain usually innervated predominantly by inhibitory terminals. Immunocytochemical analysis of pre- and postsynaptic markers showed that putative excitatory synapses were present on somata of these neurons in UC neocortex. Excitatory postsynaptic currents from UC layer V Pyr cells displayed properties consistent with perisomatic inputs and also reflected an increase in the number of synaptic contacts. Laser scanning photostimulation (LSPS) experiments demonstrated reorganized excitatory connectivity after injury within the UC. Concurrent with these changes, spontaneous epileptiform bursts developed in UC slices. Results suggest that aberrant reorganization of excitatory connectivity contributes to early neocortical hyperexcitability in this model. The findings are relevant for understanding the pathophysiology of neocortical post-traumatic epileptogenesis and are important in terms of the timing of potential prophylactic treatments. Copyright © 2016 Elsevier Inc. All rights reserved.
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.
Harwell, Corey C; Parker, Philip R L; Gee, Steven M; Okada, Ami; McConnell, Susan K; Kreitzer, Anatol C; Kriegstein, Arnold R
2012-03-22
The precise connectivity of inputs and outputs is critical for cerebral cortex function; however, the cellular mechanisms that establish these connections are poorly understood. Here, we show that the secreted molecule Sonic Hedgehog (Shh) is involved in synapse formation of a specific cortical circuit. Shh is expressed in layer V corticofugal projection neurons and the Shh receptor, Brother of CDO (Boc), is expressed in local and callosal projection neurons of layer II/III that synapse onto the subcortical projection neurons. Layer V neurons of mice lacking functional Shh exhibit decreased synapses. Conversely, the loss of functional Boc leads to a reduction in the strength of synaptic connections onto layer Vb, but not layer II/III, pyramidal neurons. These results demonstrate that Shh is expressed in postsynaptic target cells while Boc is expressed in a complementary population of presynaptic input neurons, and they function to guide the formation of cortical microcircuitry. Copyright © 2012 Elsevier Inc. All rights reserved.
Cohen, Yaniv; Wilson, Donald A.; Barkai, Edi
2015-01-01
Learning of a complex olfactory discrimination (OD) task results in acquisition of rule learning after prolonged training. Previously, we demonstrated enhanced synaptic connectivity between the piriform cortex (PC) and its ascending and descending inputs from the olfactory bulb (OB) and orbitofrontal cortex (OFC) following OD rule learning. Here, using recordings of evoked field postsynaptic potentials in behaving animals, we examined the dynamics by which these synaptic pathways are modified during rule acquisition. We show profound differences in synaptic connectivity modulation between the 2 input sources. During rule acquisition, the ascending synaptic connectivity from the OB to the anterior and posterior PC is simultaneously enhanced. Furthermore, post-training stimulation of the OB enhanced learning rate dramatically. In sharp contrast, the synaptic input in the descending pathway from the OFC was significantly reduced until training completion. Once rule learning was established, the strength of synaptic connectivity in the 2 pathways resumed its pretraining values. We suggest that acquisition of olfactory rule learning requires a transient enhancement of ascending inputs to the PC, synchronized with a parallel decrease in the descending inputs. This combined short-lived modulation enables the PC network to reorganize in a manner that enables it to first acquire and then maintain the rule. PMID:23960200
Sornborger, Andrew T.; Wang, Zhuo; Tao, Louis
2015-01-01
Neural oscillations can enhance feature recognition [1], modulate interactions between neurons [2], and improve learning and memory [3]. Numerical studies have shown that coherent spiking can give rise to windows in time during which information transfer can be enhanced in neuronal networks [4–6]. Unanswered questions are: 1) What is the transfer mechanism? And 2) how well can a transfer be executed? Here, we present a pulse-based mechanism by which a graded current amplitude may be exactly propagated from one neuronal population to another. The mechanism relies on the downstream gating of mean synaptic current amplitude from one population of neurons to another via a pulse. Because transfer is pulse-based, information may be dynamically routed through a neural circuit with fixed connectivity. We demonstrate the transfer mechanism in a realistic network of spiking neurons and show that it is robust to noise in the form of pulse timing inaccuracies, random synaptic strengths and finite size effects. We also show that the mechanism is structurally robust in that it may be implemented using biologically realistic pulses. The transfer mechanism may be used as a building block for fast, complex information processing in neural circuits. We show that the mechanism naturally leads to a framework wherein neural information coding and processing can be considered as a product of linear maps under the active control of a pulse generator. Distinct control and processing components combine to form the basis for the binding, propagation, and processing of dynamically routed information within neural pathways. Using our framework, we construct example neural circuits to 1) maintain a short-term memory, 2) compute time-windowed Fourier transforms, and 3) perform spatial rotations. We postulate that such circuits, with automatic and stereotyped control and processing of information, are the neural correlates of Crick and Koch’s zombie modes. PMID:26227067
Cocas, Laura A.; Fernandez, Gloria; Barch, Mariya; Doll, Jason; Zamora Diaz, Ivan
2016-01-01
The mammalian cerebral cortex is a dense network composed of local, subcortical, and intercortical synaptic connections. As a result, mapping cell type-specific neuronal connectivity in the cerebral cortex in vivo has long been a challenge for neurobiologists. In particular, the development of excitatory and inhibitory interneuron presynaptic input has been hard to capture. We set out to analyze the development of this connectivity in the first postnatal month using a murine model. First, we surveyed the connectivity of one of the earliest populations of neurons in the brain, the Cajal-Retzius (CR) cells in the neocortex, which are known to be critical for cortical layer formation and are hypothesized to be important in the establishment of early cortical networks. We found that CR cells receive inputs from deeper-layer excitatory neurons and inhibitory interneurons in the first postnatal week. We also found that both excitatory pyramidal neurons and inhibitory interneurons received broad inputs in the first postnatal week, including inputs from CR cells. Expanding our analysis into the more mature brain, we assessed the inputs onto inhibitory interneurons and excitatory projection neurons, labeling neuronal progenitors with Cre drivers to study discrete populations of neurons in older cortex, and found that excitatory cortical and subcortical inputs are refined by the fourth week of development, whereas local inhibitory inputs increase during this postnatal period. Cell type-specific circuit mapping is specific, reliable, and effective, and can be used on molecularly defined subtypes to determine connectivity in the cortex. SIGNIFICANCE STATEMENT Mapping cortical connectivity in the developing mammalian brain has been an intractable problem, in part because it has not been possible to analyze connectivity with cell subtype precision. Our study systematically targets the presynaptic connections of discrete neuronal subtypes in both the mature and developing cerebral cortex. We analyzed the connections that Cajal-Retzius cells make and receive, and found that these cells receive inputs from deeper-layer excitatory neurons and inhibitory interneurons in the first postnatal week. We assessed the inputs onto inhibitory interneurons and excitatory projection neurons, the major two types of neurons in the cortex, and found that excitatory inputs are refined by the fourth week of development, whereas local inhibitory inputs increase during this postnatal period. PMID:26985044
Organization of the Drosophila larval visual circuit
Gendre, Nanae; Neagu-Maier, G Larisa; Fetter, Richard D; Schneider-Mizell, Casey M; Truman, James W; Zlatic, Marta; Cardona, Albert
2017-01-01
Visual systems transduce, process and transmit light-dependent environmental cues. Computation of visual features depends on photoreceptor neuron types (PR) present, organization of the eye and wiring of the underlying neural circuit. Here, we describe the circuit architecture of the visual system of Drosophila larvae by mapping the synaptic wiring diagram and neurotransmitters. By contacting different targets, the two larval PR-subtypes create two converging pathways potentially underlying the computation of ambient light intensity and temporal light changes already within this first visual processing center. Locally processed visual information then signals via dedicated projection interneurons to higher brain areas including the lateral horn and mushroom body. The stratified structure of the larval optic neuropil (LON) suggests common organizational principles with the adult fly and vertebrate visual systems. The complete synaptic wiring diagram of the LON paves the way to understanding how circuits with reduced numerical complexity control wide ranges of behaviors.
NASA Astrophysics Data System (ADS)
Llinas, Rodolfo R.
1988-12-01
This article reviews the electroresponsive properties of single neurons in the mammalian central nervous system (CNS). In some of these cells the ionic conductances responsible for their excitability also endow them with autorhythmic electrical oscillatory properties. Chemical or electrical synaptic contacts between these neurons often result in network oscillations. In such networks, autorhytmic neurons may act as true oscillators (as pacemakers) or as resonators (responding preferentially to certain firing frequencies). Oscillations and resonance in the CNS are proposed to have diverse functional roles, such as (i) determining global functional states (for example, sleep-wakefulness or attention), (ii) timing in motor coordination, and (iii) specifying connectivity during development. Also, oscillation, especially in the thalamo-cortical circuits, may be related to certain neurological and psychiatric disorders. This review proposes that the autorhythmic electrical properties of central neurons and their connectivity form the basis for an intrinsic functional coordinate system that provides internal context to sensory input.
A synaptic organizing principle for cortical neuronal groups
Perin, Rodrigo; Berger, Thomas K.; Markram, Henry
2011-01-01
Neuronal circuitry is often considered a clean slate that can be dynamically and arbitrarily molded by experience. However, when we investigated synaptic connectivity in groups of pyramidal neurons in the neocortex, we found that both connectivity and synaptic weights were surprisingly predictable. Synaptic weights follow very closely the number of connections in a group of neurons, saturating after only 20% of possible connections are formed between neurons in a group. When we examined the network topology of connectivity between neurons, we found that the neurons cluster into small world networks that are not scale-free, with less than 2 degrees of separation. We found a simple clustering rule where connectivity is directly proportional to the number of common neighbors, which accounts for these small world networks and accurately predicts the connection probability between any two neurons. This pyramidal neuron network clusters into multiple groups of a few dozen neurons each. The neurons composing each group are surprisingly distributed, typically more than 100 μm apart, allowing for multiple groups to be interlaced in the same space. In summary, we discovered a synaptic organizing principle that groups neurons in a manner that is common across animals and hence, independent of individual experiences. We speculate that these elementary neuronal groups are prescribed Lego-like building blocks of perception and that acquired memory relies more on combining these elementary assemblies into higher-order constructs. PMID:21383177
Wang, Yan-Yan; Wang, Yong; Jiang, Hai-Fei; Liu, Jun-Hua; Jia, Jun; Wang, Ke; Zhao, Fei; Luo, Min-Hua; Luo, Min-Min; Wang, Xiao-Min
2018-02-01
The glutamatergic projection from the motor cortex to the subthalamic nucleus (STN) constitutes the cortico-basal ganglia circuit and plays a critical role in the control of movement. Emerging evidence shows that the cortico-STN pathway is susceptible to dopamine depletion. Specifically in Parkinson's disease (PD), abnormal electrophysiological activities were observed in the motor cortex and STN, while the STN serves as a key target of deep brain stimulation for PD therapy. However, direct morphological changes in the cortico-STN connectivity in response to PD progress are poorly understood at present. In the present study, we used a trans-synaptic anterograde tracing method with herpes simplex virus-green fluorescent protein (HSV-GFP) to monitor the cortico-STN connectivity in a rat model of PD. We found that the connectivity from the primary motor cortex (M1) to the STN was impaired in parkinsonian rats as manifested by a marked decrease in trans-synaptic infection of HSV-GFP from M1 neurons to STN neurons in unilateral 6-hydroxydopamine (6-OHDA)-lesioned rats. Ultrastructural analysis with electron microscopy revealed that excitatory synapses in the STN were also impaired in parkinsonian rats. Glutamatergic terminals identified by a specific marker (vesicular glutamate transporter 1) were reduced in the STN, while glutamatergic neurons showed an insignificant change in their total number in both the M1 and STN regions. These results indicate that the M1-STN glutamatergic connectivity is downregulated in parkinsonian rats. This downregulation is mediated probably via a mechanism involving the impairments of excitatory terminals and synapses in the STN. Copyright © 2017. Published by Elsevier Inc.
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
Gatto, Cheryl L.; Broadie, Kendal
2009-01-01
Loss of fragile X mental retardation 1 (FMR1) gene function is the most common cause of inherited mental retardation and autism spectrum disorders, characterized by attention disorder, hyperactivity and disruption of circadian activity cycles. Pursuit of effective intervention strategies requires determining when the FMR1 product (FMRP) is required in the regulation of neuronal circuitry controlling these behaviors. In the well-characterized Drosophila disease model, loss of the highly conserved dFMRP causes circadian arrhythmicity and conspicuous abnormalities in the circadian clock circuitry. Here, a novel Sholl Analysis was used to quantify over-elaborated synaptic architecture in dfmr1-null small ventrolateral neurons (sLNvs), a key subset of clock neurons. The transgenic Gene-Switch system was employed to drive conditional neuronal dFMRP expression in the dfmr1-null mutant background in order to dissect temporal requirements within the clock circuit. Introduction of dFMRP during early brain development, including the stages of neurogenesis, neuronal fate specification and early pathfinding, provided no rescue of dfmr1 mutant phenotypes. Similarly, restoring normal dFMRP expression in the adult failed to restore circadian circuit architecture. In sharp contrast, supplying dFMRP during a transient window of very late brain development, wherein synaptogenesis and substantial subsequent synaptic reorganization (e.g. use-dependent pruning) occur, provided strong morphological rescue to reestablish normal sLNvs synaptic arbors. We conclude that dFMRP plays a developmentally restricted role in sculpting synaptic architecture in these neurons that cannot be compensated for by later reintroduction of the protein at maturity. PMID:19738924
Analog hardware for learning neural networks
NASA Technical Reports Server (NTRS)
Eberhardt, Silvio P. (Inventor)
1991-01-01
This is a recurrent or feedforward analog neural network processor having a multi-level neuron array and a synaptic matrix for storing weighted analog values of synaptic connection strengths which is characterized by temporarily changing one connection strength at a time to determine its effect on system output relative to the desired target. That connection strength is then adjusted based on the effect, whereby the processor is taught the correct response to training examples connection by connection.
Stabilization of memory States by stochastic facilitating synapses.
Miller, Paul
2013-12-06
Bistability within a small neural circuit can arise through an appropriate strength of excitatory recurrent feedback. The stability of a state of neural activity, measured by the mean dwelling time before a noise-induced transition to another state, depends on the neural firing-rate curves, the net strength of excitatory feedback, the statistics of spike times, and increases exponentially with the number of equivalent neurons in the circuit. Here, we show that such stability is greatly enhanced by synaptic facilitation and reduced by synaptic depression. We take into account the alteration in times of synaptic vesicle release, by calculating distributions of inter-release intervals of a synapse, which differ from the distribution of its incoming interspike intervals when the synapse is dynamic. In particular, release intervals produced by a Poisson spike train have a coefficient of variation greater than one when synapses are probabilistic and facilitating, whereas the coefficient of variation is less than one when synapses are depressing. However, in spite of the increased variability in postsynaptic input produced by facilitating synapses, their dominant effect is reduced synaptic efficacy at low input rates compared to high rates, which increases the curvature of neural input-output functions, leading to wider regions of bistability in parameter space and enhanced lifetimes of memory states. Our results are based on analytic methods with approximate formulae and bolstered by simulations of both Poisson processes and of circuits of noisy spiking model neurons.
Using high-throughput barcode sequencing to efficiently map connectomes
Peikon, Ian D.; Kebschull, Justus M.; Vagin, Vasily V.; Ravens, Diana I.; Sun, Yu-Chi; Brouzes, Eric; Corrêa, Ivan R.; Bressan, Dario
2017-01-01
Abstract The function of a neural circuit is determined by the details of its synaptic connections. At present, the only available method for determining a neural wiring diagram with single synapse precision—a ‘connectome’—is based on imaging methods that are slow, labor-intensive and expensive. Here, we present SYNseq, a method for converting the connectome into a form that can exploit the speed and low cost of modern high-throughput DNA sequencing. In SYNseq, each neuron is labeled with a unique random nucleotide sequence—an RNA ‘barcode’—which is targeted to the synapse using engineered proteins. Barcodes in pre- and postsynaptic neurons are then associated through protein-protein crosslinking across the synapse, extracted from the tissue, and joined into a form suitable for sequencing. Although our failure to develop an efficient barcode joining scheme precludes the widespread application of this approach, we expect that with further development SYNseq will enable tracing of complex circuits at high speed and low cost. PMID:28449067
Genetic dissection of GABAergic neural circuits in mouse neocortex
Taniguchi, Hiroki
2014-01-01
Diverse and flexible cortical functions rely on the ability of neural circuits to perform multiple types of neuronal computations. GABAergic inhibitory interneurons significantly contribute to this task by regulating the balance of activity, synaptic integration, spiking, synchrony, and oscillation in a neural ensemble. GABAergic interneurons display a high degree of cellular diversity in morphology, physiology, connectivity, and gene expression. A considerable number of subtypes of GABAergic interneurons diversify modes of cortical inhibition, enabling various types of information processing in the cortex. Thus, comprehensively understanding fate specification, circuit assembly, and physiological function of GABAergic interneurons is a key to elucidate the principles of cortical wiring and function. Recent advances in genetically encoded molecular tools have made a breakthrough to systematically study cortical circuitry at the molecular, cellular, circuit, and whole animal levels. However, the biggest obstacle to fully applying the power of these to analysis of GABAergic circuits was that there were no efficient and reliable methods to express them in subtypes of GABAergic interneurons. Here, I first summarize cortical interneuron diversity and current understanding of mechanisms, by which distinct classes of GABAergic interneurons are generated. I then review recent development in genetically encoded molecular tools for neural circuit research, and genetic targeting of GABAergic interneuron subtypes, particularly focusing on our recent effort to develop and characterize Cre/CreER knockin lines. Finally, I highlight recent success in genetic targeting of chandelier cells, the most unique and distinct GABAergic interneuron subtype, and discuss what kind of questions need to be addressed to understand development and function of cortical inhibitory circuits. PMID:24478631
Pinzon-Morales, Ruben-Dario; Hirata, Yutaka
2015-01-01
The cerebellar granule cells (GCs) have been proposed to perform lossless, adaptive spatio-temporal coding of incoming sensory/motor information required by downstream cerebellar circuits to support motor learning, motor coordination, and cognition. Here we use a physio-anatomically inspired bi-hemispheric cerebellar neuronal network (biCNN) to selectively enable/disable the output of GCs and evaluate the behavioral and neural consequences during three different control scenarios. The control scenarios are a simple direct current motor (1 degree of freedom: DOF), an unstable two-wheel balancing robot (2 DOFs), and a simulation model of a quadcopter (6 DOFs). Results showed that adequate control was maintained with a relatively small number of GCs (< 200) in all the control scenarios. However, the minimum number of GCs required to successfully govern each control plant increased with their complexity (i.e., DOFs). It was also shown that increasing the number of GCs resulted in higher robustness against changes in the initialization parameters of the biCNN model (i.e., synaptic connections and synaptic weights). Therefore, we suggest that the abundant GCs in the cerebellar cortex provide the computational power during the large repertoire of motor activities and motor plants the cerebellum is involved with, and bring robustness against changes in the cerebellar microcircuit (e.g., neuronal connections).
Sensory optimization by stochastic tuning.
Jurica, Peter; Gepshtein, Sergei; Tyukin, Ivan; van Leeuwen, Cees
2013-10-01
Individually, visual neurons are each selective for several aspects of stimulation, such as stimulus location, frequency content, and speed. Collectively, the neurons implement the visual system's preferential sensitivity to some stimuli over others, manifested in behavioral sensitivity functions. We ask how the individual neurons are coordinated to optimize visual sensitivity. We model synaptic plasticity in a generic neural circuit and find that stochastic changes in strengths of synaptic connections entail fluctuations in parameters of neural receptive fields. The fluctuations correlate with uncertainty of sensory measurement in individual neurons: The higher the uncertainty the larger the amplitude of fluctuation. We show that this simple relationship is sufficient for the stochastic fluctuations to steer sensitivities of neurons toward a characteristic distribution, from which follows a sensitivity function observed in human psychophysics and which is predicted by a theory of optimal allocation of receptive fields. The optimal allocation arises in our simulations without supervision or feedback about system performance and independently of coupling between neurons, making the system highly adaptive and sensitive to prevailing stimulation. PsycINFO Database Record (c) 2013 APA, all rights reserved.
Structural and synaptic plasticity in stress-related disorders
Christoffel, Daniel J.; Golden, Sam A.; Russo, Scott J.
2011-01-01
Stress can have a lasting impact on the structure and function of brain circuitry that results in long-lasting changes in the behavior of an organism. Synaptic plasticity is the mechanism by which information is stored and maintained within individual synapses, neurons, and neuronal circuits to guide the behavior of an organism. Although these mechanisms allow the organism to adapt to its constantly evolving environment, not all of these adaptations are beneficial. Under prolonged bouts of physical or psychological stress, these mechanisms become dysregulated, and the connectivity between brain regions becomes unbalanced, resulting in pathological behaviors. In this review, we highlight the effects of stress on the structure and function of neurons within the mesocorticolimbic brain systems known to regulate mood and motivation. We then discuss the implications of these spine adaptations on neuronal activity and pathological behaviors implicated in mood disorders. Finally, we end by discussing recent brain imaging studies in human depression within the context of these basic findings to provide insight into the underlying mechanisms leading to neural dysfunction in depression. PMID:21967517
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.
Brain repair after stroke—a novel neurological model
Small, Steven L.; Buccino, Giovanni; Solodkin, Ana
2017-01-01
Following stroke, patients are commonly left with debilitating motor and speech impairments. This article reviews the state of the art in neurological repair for stroke and proposes a new model for the future. We suggest that stroke treatment—from the time of the ictus itself to living with the consequences—must be fundamentally neurological, from limiting the extent of injury at the outset, to repairing the consequent damage. Our model links brain and behaviour by targeting brain circuits, and we illustrate the model though action observation treatment, which aims to enhance brain network connectivity. The model is based on the assumptions that the mechanisms of neural repair inherently involve cellular and circuit plasticity, that brain plasticity is a synaptic phenomenon that is largely stimulus-dependent, and that brain repair required both physical and behavioural interventions that are tailored to reorganize specific brain circuits. We review current approaches to brain repair after stroke and present our new model, and discuss the biological foundations, rationales, and data to support our novel approach to upper-extremity and language rehabilitation. We believe that by enhancing plasticity at the level of brain network interactions, this neurological model for brain repair could ultimately lead to a cure for stroke. PMID:24217509
Bendels, Michael H K; Beed, Prateep; Leibold, Christian; Schmitz, Dietmar; Johenning, Friedrich W
2008-10-30
Optical uncaging of caged compounds is a well-established method to study the functional anatomy of a brain region on the circuit level. We present an alternative approach to existing experimental setups. Using a low-magnification objective we acquire images for planning the spatial patterns of stimulation. Then high-magnification objectives are used during laser stimulation providing a laser spot between 2 microm and 20 microm size. The core of this system is a video-based control software that monitors and controls the connected devices, allows for planning of the experiment, coordinates the stimulation process and manages automatic data storage. This combines a high-resolution analysis of neuronal circuits with flexible and efficient online planning and execution of a grid of spatial stimulation patterns on a larger scale. The software offers special optical features that enable the system to achieve a maximum degree of spatial reliability. The hardware is mainly built upon standard laboratory devices and thus ideally suited to cost-effectively complement existing electrophysiological setups with a minimal amount of additional equipment. Finally, we demonstrate the performance of the system by mapping the excitatory and inhibitory connections of entorhinal cortex layer II stellate neurons and present an approach for the analysis of photo-induced synaptic responses in high spontaneous activity.
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
Rothwell, Patrick E; Fuccillo, Marc V; Maxeiner, Stephan; Hayton, Scott J; Gokce, Ozgun; Lim, Byung Kook; Fowler, Stephen C; Malenka, Robert C; Südhof, Thomas C
2014-07-03
In humans, neuroligin-3 mutations are associated with autism, whereas in mice, the corresponding mutations produce robust synaptic and behavioral changes. However, different neuroligin-3 mutations cause largely distinct phenotypes in mice, and no causal relationship links a specific synaptic dysfunction to a behavioral change. Using rotarod motor learning as a proxy for acquired repetitive behaviors in mice, we found that different neuroligin-3 mutations uniformly enhanced formation of repetitive motor routines. Surprisingly, neuroligin-3 mutations caused this phenotype not via changes in the cerebellum or dorsal striatum but via a selective synaptic impairment in the nucleus accumbens/ventral striatum. Here, neuroligin-3 mutations increased rotarod learning by specifically impeding synaptic inhibition onto D1-dopamine receptor-expressing but not D2-dopamine receptor-expressing medium spiny neurons. Our data thus suggest that different autism-associated neuroligin-3 mutations cause a common increase in acquired repetitive behaviors by impairing a specific striatal synapse and thereby provide a plausible circuit substrate for autism pathophysiology. Copyright © 2014 Elsevier Inc. All rights reserved.
Luo, Sarah X; Timbang, Leah; Kim, Jae-Ick; Shang, Yulei; Sandoval, Kadellyn; Tang, Amy A; Whistler, Jennifer L; Ding, Jun B; Huang, Eric J
2016-12-20
Neural circuits involving midbrain dopaminergic (DA) neurons regulate reward and goal-directed behaviors. Although local GABAergic input is known to modulate DA circuits, the mechanism that controls excitatory/inhibitory synaptic balance in DA neurons remains unclear. Here, we show that DA neurons use autocrine transforming growth factor β (TGF-β) signaling to promote the growth of axons and dendrites. Surprisingly, removing TGF-β type II receptor in DA neurons also disrupts the balance in TGF-β1 expression in DA neurons and neighboring GABAergic neurons, which increases inhibitory input, reduces excitatory synaptic input, and alters phasic firing patterns in DA neurons. Mice lacking TGF-β signaling in DA neurons are hyperactive and exhibit inflexibility in relinquishing learned behaviors and re-establishing new stimulus-reward associations. These results support a role for TGF-β in regulating the delicate balance of excitatory/inhibitory synaptic input in local microcircuits involving DA and GABAergic neurons and its potential contributions to neuropsychiatric disorders. Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.
Nere, Andrew; Hashmi, Atif; Cirelli, Chiara; Tononi, Giulio
2013-01-01
Sleep can favor the consolidation of both procedural and declarative memories, promote gist extraction, help the integration of new with old memories, and desaturate the ability to learn. It is often assumed that such beneficial effects are due to the reactivation of neural circuits in sleep to further strengthen the synapses modified during wake or transfer memories to different parts of the brain. A different possibility is that sleep may benefit memory not by further strengthening synapses, but rather by renormalizing synaptic strength to restore cellular homeostasis after net synaptic potentiation in wake. In this way, the sleep-dependent reactivation of neural circuits could result in the competitive down-selection of synapses that are activated infrequently and fit less well with the overall organization of memories. By using computer simulations, we show here that synaptic down-selection is in principle sufficient to explain the beneficial effects of sleep on the consolidation of procedural and declarative memories, on gist extraction, and on the integration of new with old memories, thereby addressing the plasticity-stability dilemma. PMID:24137153
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.
Burton, S D; Johnson, J W; Zeringue, H C; Meriney, S D
2012-07-26
Neuroligins are a family of cell adhesion molecules critical in establishing proper central nervous system connectivity; disruption of neuroligin signaling in vivo precipitates a broad range of cognitive deficits. Despite considerable recent progress, the specific synaptic function of neuroligin-1 (NL1) remains unclear. A current model proposes that NL1 acts exclusively to mature pre-existent synaptic connections in an activity-dependent manner. A second element of this activity-dependent maturation model is that an alternate molecule acts upstream of NL1 to initiate synaptic connections. SynCAM1 (SC1) is hypothesized to function in this capacity, though several uncertainties remain regarding SC1 function. Using overexpression and chronic pharmacological blockade of synaptic activity, we now demonstrate that NL1 is capable of robustly recruiting synapsin-positive terminals independent of synaptic maturation and activity in 2-week old primary hippocampal neuronal cultures. We further report that neither SC1 overexpression nor knockdown of endogenous SC1 impacts synapsin punctum densities, suggesting that SC1 is not a limiting factor of synapse initiation in maturing hippocampal neurons in vitro. Consistent with these findings, we observed profoundly greater recruitment of synapsin-positive presynaptic terminals by NL1 than SC1 in a mixed-culture assay of artificial synaptogenesis between primary neurons and heterologous cells. Collectively, our results contend multiple aspects of the proposed model of NL1 and SC1 function and motivate an alternative model whereby SC1 may mature synaptic connections forged by NL1. Supporting this model, we present evidence that combined NL1 and SC1 overexpression triggers excitotoxic neurodegeneration through SC1 signaling at synaptic connections initiated by NL1. Copyright © 2012 IBRO. Published by Elsevier Ltd. All rights reserved.
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.
Cell-specific gain modulation by synaptically released zinc in cortical circuits of audition.
Anderson, Charles T; Kumar, Manoj; Xiong, Shanshan; Tzounopoulos, Thanos
2017-09-09
In many excitatory synapses, mobile zinc is found within glutamatergic vesicles and is coreleased with glutamate. Ex vivo studies established that synaptically released (synaptic) zinc inhibits excitatory neurotransmission at lower frequencies of synaptic activity but enhances steady state synaptic responses during higher frequencies of activity. However, it remains unknown how synaptic zinc affects neuronal processing in vivo. Here, we imaged the sound-evoked neuronal activity of the primary auditory cortex in awake mice. We discovered that synaptic zinc enhanced the gain of sound-evoked responses in CaMKII-expressing principal neurons, but it reduced the gain of parvalbumin- and somatostatin-expressing interneurons. This modulation was sound intensity-dependent and, in part, NMDA receptor-independent. By establishing a previously unknown link between synaptic zinc and gain control of auditory cortical processing, our findings advance understanding about cortical synaptic mechanisms and create a new framework for approaching and interpreting the role of the auditory cortex in sound processing.
Sadaf, Sufia; Birman, Serge; Hasan, Gaiti
2012-01-01
Background Flight is an integral component of many complex behavioral patterns in insects. The giant fiber circuit has been well studied in several insects including Drosophila. However, components of the insect flight circuit that respond to an air-puff stimulus and comprise the flight central pattern generator are poorly defined. Aminergic neurons have been implicated in locust, moth and Drosophila flight. Here we have investigated the requirement of neuronal activity in serotonergic neurons, during development and in adults, on air-puff induced flight in Drosophila. Methodology/Principal Findings To target serotonergic neurons specifically, a Drosophila strain that contains regulatory regions from the TRH (Tryptophan Hydroxylase) gene linked to the yeast transcription factor GAL4 was used. By blocking synaptic transmission from serotonergic neurons with a tetanus toxin transgene or by hyperpolarisation with Kir2.1, close to 50% adults became flightless. Temporal expression of a temperature sensitive Dynamin mutant transgene (Shits) suggests that synaptic function in serotonergic neurons is required both during development and in adults. Depletion of IP3R in serotonergic neurons via RNAi did not affect flight. Interestingly, at all stages a partial requirement for synaptic activity in serotonergic neurons was observed. The status of serotonergic neurons was investigated in the central nervous system of larvae and adults expressing tetanus toxin. A small but significant reduction was observed in serotonergic cell number in adult second thoracic segments from flightless tetanus toxin expressing animals. Conclusions These studies show that loss of synaptic activity in serotonergic neurons causes a flight deficit. The temporal focus of the flight deficit is during pupal development and in adults. The cause of the flight deficit is likely to be loss of neurons and reduced synaptic function. Based on the partial phenotypes, serotonergic neurons appear to be modulatory, rather than an intrinsic part of the flight circuit. PMID:23029511
Sedlacek, Miloslav; Brenowitz, Stephan D
2014-01-01
Feed-forward inhibition (FFI) represents a powerful mechanism by which control of the timing and fidelity of action potentials in local synaptic circuits of various brain regions is achieved. In the cochlear nucleus, the auditory nerve provides excitation to both principal neurons and inhibitory interneurons. Here, we investigated the synaptic circuit associated with fusiform cells (FCs), principal neurons of the dorsal cochlear nucleus (DCN) that receive excitation from auditory nerve fibers and inhibition from tuberculoventral cells (TVCs) on their basal dendrites in the deep layer of DCN. Despite the importance of these inputs in regulating fusiform cell firing behavior, the mechanisms determining the balance of excitation and FFI in this circuit are not well understood. Therefore, we examined the timing and plasticity of auditory nerve driven FFI onto FCs. We find that in some FCs, excitatory and inhibitory components of FFI had the same stimulation thresholds indicating they could be triggered by activation of the same fibers. In other FCs, excitation and inhibition exhibit different stimulus thresholds, suggesting FCs and TVCs might be activated by different sets of fibers. In addition, we find that during repetitive activation, synapses formed by the auditory nerve onto TVCs and FCs exhibit distinct modes of short-term plasticity. Feed-forward inhibitory post-synaptic currents (IPSCs) in FCs exhibit short-term depression because of prominent synaptic depression at the auditory nerve-TVC synapse. Depression of this feedforward inhibitory input causes a shift in the balance of fusiform cell synaptic input towards greater excitation and suggests that fusiform cell spike output will be enhanced by physiological patterns of auditory nerve activity.
Python scripting in the nengo simulator.
Stewart, Terrence C; Tripp, Bryan; Eliasmith, Chris
2009-01-01
Nengo (http://nengo.ca) is an open-source neural simulator that has been greatly enhanced by the recent addition of a Python script interface. Nengo provides a wide range of features that are useful for physiological simulations, including unique features that facilitate development of population-coding models using the neural engineering framework (NEF). This framework uses information theory, signal processing, and control theory to formalize the development of large-scale neural circuit models. Notably, it can also be used to determine the synaptic weights that underlie observed network dynamics and transformations of represented variables. Nengo provides rich NEF support, and includes customizable models of spike generation, muscle dynamics, synaptic plasticity, and synaptic integration, as well as an intuitive graphical user interface. All aspects of Nengo models are accessible via the Python interface, allowing for programmatic creation of models, inspection and modification of neural parameters, and automation of model evaluation. Since Nengo combines Python and Java, it can also be integrated with any existing Java or 100% Python code libraries. Current work includes connecting neural models in Nengo with existing symbolic cognitive models, creating hybrid systems that combine detailed neural models of specific brain regions with higher-level models of remaining brain areas. Such hybrid models can provide (1) more realistic boundary conditions for the neural components, and (2) more realistic sub-components for the larger cognitive models.
Python Scripting in the Nengo Simulator
Stewart, Terrence C.; Tripp, Bryan; Eliasmith, Chris
2008-01-01
Nengo (http://nengo.ca) is an open-source neural simulator that has been greatly enhanced by the recent addition of a Python script interface. Nengo provides a wide range of features that are useful for physiological simulations, including unique features that facilitate development of population-coding models using the neural engineering framework (NEF). This framework uses information theory, signal processing, and control theory to formalize the development of large-scale neural circuit models. Notably, it can also be used to determine the synaptic weights that underlie observed network dynamics and transformations of represented variables. Nengo provides rich NEF support, and includes customizable models of spike generation, muscle dynamics, synaptic plasticity, and synaptic integration, as well as an intuitive graphical user interface. All aspects of Nengo models are accessible via the Python interface, allowing for programmatic creation of models, inspection and modification of neural parameters, and automation of model evaluation. Since Nengo combines Python and Java, it can also be integrated with any existing Java or 100% Python code libraries. Current work includes connecting neural models in Nengo with existing symbolic cognitive models, creating hybrid systems that combine detailed neural models of specific brain regions with higher-level models of remaining brain areas. Such hybrid models can provide (1) more realistic boundary conditions for the neural components, and (2) more realistic sub-components for the larger cognitive models. PMID:19352442
Robustness effect of gap junctions between Golgi cells on cerebellar cortex oscillations
2011-01-01
Background Previous one-dimensional network modeling of the cerebellar granular layer has been successfully linked with a range of cerebellar cortex oscillations observed in vivo. However, the recent discovery of gap junctions between Golgi cells (GoCs), which may cause oscillations by themselves, has raised the question of how gap-junction coupling affects GoC and granular-layer oscillations. To investigate this question, we developed a novel two-dimensional computational model of the GoC-granule cell (GC) circuit with and without gap junctions between GoCs. Results Isolated GoCs coupled by gap junctions had a strong tendency to generate spontaneous oscillations without affecting their mean firing frequencies in response to distributed mossy fiber input. Conversely, when GoCs were synaptically connected in the granular layer, gap junctions increased the power of the oscillations, but the oscillations were primarily driven by the synaptic feedback loop between GoCs and GCs, and the gap junctions did not change oscillation frequency or the mean firing rate of either GoCs or GCs. Conclusion Our modeling results suggest that gap junctions between GoCs increase the robustness of cerebellar cortex oscillations that are primarily driven by the feedback loop between GoCs and GCs. The robustness effect of gap junctions on synaptically driven oscillations observed in our model may be a general mechanism, also present in other regions of the brain. PMID:22330240
Altered Neuronal and Circuit Excitability in Fragile X Syndrome.
Contractor, Anis; Klyachko, Vitaly A; Portera-Cailliau, Carlos
2015-08-19
Fragile X syndrome (FXS) results from a genetic mutation in a single gene yet produces a phenotypically complex disorder with a range of neurological and psychiatric problems. Efforts to decipher how perturbations in signaling pathways lead to the myriad alterations in synaptic and cellular functions have provided insights into the molecular underpinnings of this disorder. From this large body of data, the theme of circuit hyperexcitability has emerged as a potential explanation for many of the neurological and psychiatric symptoms in FXS. The mechanisms for hyperexcitability range from alterations in the expression or activity of ion channels to changes in neurotransmitters and receptors. Contributions of these processes are often brain region and cell type specific, resulting in complex effects on circuit function that manifest as altered excitability. Here, we review the current state of knowledge of the molecular, synaptic, and circuit-level mechanisms underlying hyperexcitability and their contributions to the FXS phenotypes. Copyright © 2015 Elsevier Inc. All rights reserved.
Sleep Drive Is Encoded by Neural Plastic Changes in a Dedicated Circuit.
Liu, Sha; Liu, Qili; Tabuchi, Masashi; Wu, Mark N
2016-06-02
Prolonged wakefulness leads to an increased pressure for sleep, but how this homeostatic drive is generated and subsequently persists is unclear. Here, from a neural circuit screen in Drosophila, we identify a subset of ellipsoid body (EB) neurons whose activation generates sleep drive. Patch-clamp analysis indicates these EB neurons are highly sensitive to sleep loss, switching from spiking to burst-firing modes. Functional imaging and translational profiling experiments reveal that elevated sleep need triggers reversible increases in cytosolic Ca(2+) levels, NMDA receptor expression, and structural markers of synaptic strength, suggesting these EB neurons undergo "sleep-need"-dependent plasticity. Strikingly, the synaptic plasticity of these EB neurons is both necessary and sufficient for generating sleep drive, indicating that sleep pressure is encoded by plastic changes within this circuit. These studies define an integrator circuit for sleep homeostasis and provide a mechanism explaining the generation and persistence of sleep drive. Copyright © 2016 Elsevier Inc. All rights reserved.
Yu, Lianchun; Shen, Zhou; Wang, Chen; Yu, Yuguo
2018-01-01
Selective pressure may drive neural systems to process as much information as possible with the lowest energy cost. Recent experiment evidence revealed that the ratio between synaptic excitation and inhibition (E/I) in local cortex is generally maintained at a certain value which may influence the efficiency of energy consumption and information transmission of neural networks. To understand this issue deeply, we constructed a typical recurrent Hodgkin-Huxley network model and studied the general principles that governs the relationship among the E/I synaptic current ratio, the energy cost and total amount of information transmission. We observed in such a network that there exists an optimal E/I synaptic current ratio in the network by which the information transmission achieves the maximum with relatively low energy cost. The coding energy efficiency which is defined as the mutual information divided by the energy cost, achieved the maximum with the balanced synaptic current. Although background noise degrades information transmission and imposes an additional energy cost, we find an optimal noise intensity that yields the largest information transmission and energy efficiency at this optimal E/I synaptic transmission ratio. The maximization of energy efficiency also requires a certain part of energy cost associated with spontaneous spiking and synaptic activities. We further proved this finding with analytical solution based on the response function of bistable neurons, and demonstrated that optimal net synaptic currents are capable of maximizing both the mutual information and energy efficiency. These results revealed that the development of E/I synaptic current balance could lead a cortical network to operate at a highly efficient information transmission rate at a relatively low energy cost. The generality of neuronal models and the recurrent network configuration used here suggest that the existence of an optimal E/I cell ratio for highly efficient energy costs and information maximization is a potential principle for cortical circuit networks. Summary We conducted numerical simulations and mathematical analysis to examine the energy efficiency of neural information transmission in a recurrent network as a function of the ratio of excitatory and inhibitory synaptic connections. We obtained a general solution showing that there exists an optimal E/I synaptic ratio in a recurrent network at which the information transmission as well as the energy efficiency of this network achieves a global maximum. These results reflect general mechanisms for sensory coding processes, which may give insight into the energy efficiency of neural communication and coding. PMID:29773979
Yu, Lianchun; Shen, Zhou; Wang, Chen; Yu, Yuguo
2018-01-01
Selective pressure may drive neural systems to process as much information as possible with the lowest energy cost. Recent experiment evidence revealed that the ratio between synaptic excitation and inhibition (E/I) in local cortex is generally maintained at a certain value which may influence the efficiency of energy consumption and information transmission of neural networks. To understand this issue deeply, we constructed a typical recurrent Hodgkin-Huxley network model and studied the general principles that governs the relationship among the E/I synaptic current ratio, the energy cost and total amount of information transmission. We observed in such a network that there exists an optimal E/I synaptic current ratio in the network by which the information transmission achieves the maximum with relatively low energy cost. The coding energy efficiency which is defined as the mutual information divided by the energy cost, achieved the maximum with the balanced synaptic current. Although background noise degrades information transmission and imposes an additional energy cost, we find an optimal noise intensity that yields the largest information transmission and energy efficiency at this optimal E/I synaptic transmission ratio. The maximization of energy efficiency also requires a certain part of energy cost associated with spontaneous spiking and synaptic activities. We further proved this finding with analytical solution based on the response function of bistable neurons, and demonstrated that optimal net synaptic currents are capable of maximizing both the mutual information and energy efficiency. These results revealed that the development of E/I synaptic current balance could lead a cortical network to operate at a highly efficient information transmission rate at a relatively low energy cost. The generality of neuronal models and the recurrent network configuration used here suggest that the existence of an optimal E/I cell ratio for highly efficient energy costs and information maximization is a potential principle for cortical circuit networks. We conducted numerical simulations and mathematical analysis to examine the energy efficiency of neural information transmission in a recurrent network as a function of the ratio of excitatory and inhibitory synaptic connections. We obtained a general solution showing that there exists an optimal E/I synaptic ratio in a recurrent network at which the information transmission as well as the energy efficiency of this network achieves a global maximum. These results reflect general mechanisms for sensory coding processes, which may give insight into the energy efficiency of neural communication and coding.
Tanaka, Nobuaki K.; Dye, Louis; Stopfer, Mark
2010-01-01
Light and electron microscopy (LM and EM) both offer important advantages for characterizing neuronal circuitry in intact brains: LM can reveal the general patterns neurons trace between brain areas, and EM can confirm synaptic connections between identified neurons within a small area. In a few species, genetic labeling with fluorescent proteins has been used with LM to visualize many kinds of neurons and to analyze their morphologies and projection patterns. However, combining these large-scale patterns with the fine detail available in EM analysis has been a technical challenge. To analyze the synaptic connectivity of neurons expressing fluorescent markers with EM, we developed a dual-labeling method for use with pre-embedded brains. In Drosophila expressing genetic labels and also injected with markers we visualized synaptic connections among two populations of neurons in the AL, one of which has been shown to mediate a specific function, odor evoked neural oscillation. PMID:21074556
Astrocytes refine cortical connectivity at dendritic spines
Risher, W Christopher; Patel, Sagar; Kim, Il Hwan; Uezu, Akiyoshi; Bhagat, Srishti; Wilton, Daniel K; Pilaz, Louis-Jan; Singh Alvarado, Jonnathan; Calhan, Osman Y; Silver, Debra L; Stevens, Beth; Calakos, Nicole; Soderling, Scott H; Eroglu, Cagla
2014-01-01
During cortical synaptic development, thalamic axons must establish synaptic connections despite the presence of the more abundant intracortical projections. How thalamocortical synapses are formed and maintained in this competitive environment is unknown. Here, we show that astrocyte-secreted protein hevin is required for normal thalamocortical synaptic connectivity in the mouse cortex. Absence of hevin results in a profound, long-lasting reduction in thalamocortical synapses accompanied by a transient increase in intracortical excitatory connections. Three-dimensional reconstructions of cortical neurons from serial section electron microscopy (ssEM) revealed that, during early postnatal development, dendritic spines often receive multiple excitatory inputs. Immuno-EM and confocal analyses revealed that majority of the spines with multiple excitatory contacts (SMECs) receive simultaneous thalamic and cortical inputs. Proportion of SMECs diminishes as the brain develops, but SMECs remain abundant in Hevin-null mice. These findings reveal that, through secretion of hevin, astrocytes control an important developmental synaptic refinement process at dendritic spines. DOI: http://dx.doi.org/10.7554/eLife.04047.001 PMID:25517933
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
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
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…
Integrated plasticity at inhibitory and excitatory synapses in the cerebellar circuit.
Mapelli, Lisa; Pagani, Martina; Garrido, Jesus A; D'Angelo, Egidio
2015-01-01
The way long-term potentiation (LTP) and depression (LTD) are integrated within the different synapses of brain neuronal circuits is poorly understood. In order to progress beyond the identification of specific molecular mechanisms, a system in which multiple forms of plasticity can be correlated with large-scale neural processing is required. In this paper we take as an example the cerebellar network, in which extensive investigations have revealed LTP and LTD at several excitatory and inhibitory synapses. Cerebellar LTP and LTD occur in all three main cerebellar subcircuits (granular layer, molecular layer, deep cerebellar nuclei) and correspondingly regulate the function of their three main neurons: granule cells (GrCs), Purkinje cells (PCs) and deep cerebellar nuclear (DCN) cells. All these neurons, in addition to be excited, are reached by feed-forward and feed-back inhibitory connections, in which LTP and LTD may either operate synergistically or homeostatically in order to control information flow through the circuit. Although the investigation of individual synaptic plasticities in vitro is essential to prove their existence and mechanisms, it is insufficient to generate a coherent view of their impact on network functioning in vivo. Recent computational models and cell-specific genetic mutations in mice are shedding light on how plasticity at multiple excitatory and inhibitory synapses might regulate neuronal activities in the cerebellar circuit and contribute to learning and memory and behavioral control.
Decision making in recurrent neuronal circuits.
Wang, Xiao-Jing
2008-10-23
Decision making has recently emerged as a central theme in neurophysiological studies of cognition, and experimental and computational work has led to the proposal of a cortical circuit mechanism of elemental decision computations. This mechanism depends on slow recurrent synaptic excitation balanced by fast feedback inhibition, which not only instantiates attractor states for forming categorical choices but also long transients for gradually accumulating evidence in favor of or against alternative options. Such a circuit endowed with reward-dependent synaptic plasticity is able to produce adaptive choice behavior. While decision threshold is a core concept for reaction time tasks, it can be dissociated from a general decision rule. Moreover, perceptual decisions and value-based economic choices are described within a unified framework in which probabilistic choices result from irregular neuronal activity as well as iterative interactions of a decision maker with an uncertain environment or other unpredictable decision makers in a social group.
A decision-making model based on a spiking neural circuit and synaptic plasticity.
Wei, Hui; Bu, Yijie; Dai, Dawei
2017-10-01
To adapt to the environment and survive, most animals can control their behaviors by making decisions. The process of decision-making and responding according to cues in the environment is stable, sustainable, and learnable. Understanding how behaviors are regulated by neural circuits and the encoding and decoding mechanisms from stimuli to responses are important goals in neuroscience. From results observed in Drosophila experiments, the underlying decision-making process is discussed, and a neural circuit that implements a two-choice decision-making model is proposed to explain and reproduce the observations. Compared with previous two-choice decision making models, our model uses synaptic plasticity to explain changes in decision output given the same environment. Moreover, biological meanings of parameters of our decision-making model are discussed. In this paper, we explain at the micro-level (i.e., neurons and synapses) how observable decision-making behavior at the macro-level is acquired and achieved.
Interregional synaptic maps among engram cells underlie memory formation.
Choi, Jun-Hyeok; Sim, Su-Eon; Kim, Ji-Il; Choi, Dong Il; Oh, Jihae; Ye, Sanghyun; Lee, Jaehyun; Kim, TaeHyun; Ko, Hyoung-Gon; Lim, Chae-Seok; Kaang, Bong-Kiun
2018-04-27
Memory resides in engram cells distributed across the brain. However, the site-specific substrate within these engram cells remains theoretical, even though it is generally accepted that synaptic plasticity encodes memories. We developed the dual-eGRASP (green fluorescent protein reconstitution across synaptic partners) technique to examine synapses between engram cells to identify the specific neuronal site for memory storage. We found an increased number and size of spines on CA1 engram cells receiving input from CA3 engram cells. In contextual fear conditioning, this enhanced connectivity between engram cells encoded memory strength. CA3 engram to CA1 engram projections strongly occluded long-term potentiation. These results indicate that enhanced structural and functional connectivity between engram cells across two directly connected brain regions forms the synaptic correlate for memory formation. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.
Signaling in large-scale neural networks.
Berg, Rune W; Hounsgaard, Jørn
2009-02-01
We examine the recent finding that neurons in spinal motor circuits enter a high conductance state during functional network activity. The underlying concomitant increase in random inhibitory and excitatory synaptic activity leads to stochastic signal processing. The possible advantages of this metabolically costly organization are analyzed by comparing with synaptically less intense networks driven by the intrinsic response properties of the network neurons.
Connectivity of Pacemaker Neurons in the Neonatal Rat Superficial Dorsal Horn
Ford, Neil C.; Arbabi, Shahriar; Baccei, Mark L.
2014-01-01
Pacemaker neurons with an intrinsic ability to generate rhythmic burst-firing have been characterized in lamina I of the neonatal spinal cord, where they are innervated by high-threshold sensory afferents. However, little is known about the output of these pacemakers, as the neuronal populations which are targeted by pacemaker axons have yet to be identified. The present study combines patch clamp recordings in the intact neonatal rat spinal cord with tract-tracing to demonstrate that lamina I pacemaker neurons contact multiple spinal motor pathways during early life. Retrograde labeling of premotor interneurons with the trans-synaptic virus PRV-152 revealed the presence of burst-firing in PRV-infected lamina I neurons, thereby confirming that pacemakers are synaptically coupled to motor networks in the spinal ventral horn. Notably, two classes of pacemakers could be distinguished in lamina I based on cell size and the pattern of their axonal projections. While small pacemaker neurons possessed ramified axons which contacted ipsilateral motor circuits, large pacemaker neurons had unbranched axons which crossed the midline and ascended rostrally in the contralateral white matter. Recordings from identified spino-parabrachial and spino-PAG neurons indicated the presence of pacemaker activity within neonatal lamina I projection neurons. Overall, these results show that lamina I pacemakers are positioned to regulate both the level of activity in developing motor circuits as well as the ascending flow of nociceptive information to the brain, thus highlighting a potential role for pacemaker activity in the maturation of pain and sensorimotor networks in the CNS. PMID:25380417
Mechanisms underlying a thalamocortical transformation during active tactile sensation
Gutnisky, Diego Adrian; Yu, Jianing; Hires, Samuel Andrew; To, Minh-Son; Svoboda, Karel
2017-01-01
During active somatosensation, neural signals expected from movement of the sensors are suppressed in the cortex, whereas information related to touch is enhanced. This tactile suppression underlies low-noise encoding of relevant tactile features and the brain’s ability to make fine tactile discriminations. Layer (L) 4 excitatory neurons in the barrel cortex, the major target of the somatosensory thalamus (VPM), respond to touch, but have low spike rates and low sensitivity to the movement of whiskers. Most neurons in VPM respond to touch and also show an increase in spike rate with whisker movement. Therefore, signals related to self-movement are suppressed in L4. Fast-spiking (FS) interneurons in L4 show similar dynamics to VPM neurons. Stimulation of halorhodopsin in FS interneurons causes a reduction in FS neuron activity and an increase in L4 excitatory neuron activity. This decrease of activity of L4 FS neurons contradicts the "paradoxical effect" predicted in networks stabilized by inhibition and in strongly-coupled networks. To explain these observations, we constructed a model of the L4 circuit, with connectivity constrained by in vitro measurements. The model explores the various synaptic conductance strengths for which L4 FS neurons actively suppress baseline and movement-related activity in layer 4 excitatory neurons. Feedforward inhibition, in concert with recurrent intracortical circuitry, produces tactile suppression. Synaptic delays in feedforward inhibition allow transmission of temporally brief volleys of activity associated with touch. Our model provides a mechanistic explanation of a behavior-related computation implemented by the thalamocortical circuit. PMID:28591219
Label-free volumetric optical imaging of intact murine brains
NASA Astrophysics Data System (ADS)
Ren, Jian; Choi, Heejin; Chung, Kwanghun; Bouma, Brett E.
2017-04-01
A central effort of today’s neuroscience is to study the brain’s ’wiring diagram’. The nervous system is believed to be a network of neurons interacting with each other through synaptic connection between axons and dendrites, therefore the neuronal connectivity map not only depicts the underlying anatomy, but also has important behavioral implications. Different approaches have been utilized to decipher neuronal circuits, including electron microscopy (EM) and light microscopy (LM). However, these approaches typically demand extensive sectioning and reconstruction for a brain sample. Recently, tissue clearing methods have enabled the investigation of a fully assembled biological system with greatly improved light penetration. Yet, most of these implementations, still require either genetic or exogenous contrast labeling for light microscopy. Here we demonstrate a high-speed approach, termed as Clearing Assisted Scattering Tomography (CAST), where intact brains can be imaged at optical resolution without labeling by leveraging tissue clearing and the scattering contrast of optical frequency domain imaging (OFDI).
Astrocytes mediate synapse elimination through MEGF10 and MERTK pathways
NASA Astrophysics Data System (ADS)
Chung, Won-Suk; Clarke, Laura E.; Wang, Gordon X.; Stafford, Benjamin K.; Sher, Alexander; Chakraborty, Chandrani; Joung, Julia; Foo, Lynette C.; Thompson, Andrew; Chen, Chinfei; Smith, Stephen J.; Barres, Ben A.
2013-12-01
To achieve its precise neural connectivity, the developing mammalian nervous system undergoes extensive activity-dependent synapse remodelling. Recently, microglial cells have been shown to be responsible for a portion of synaptic pruning, but the remaining mechanisms remain unknown. Here we report a new role for astrocytes in actively engulfing central nervous system synapses. This process helps to mediate synapse elimination, requires the MEGF10 and MERTK phagocytic pathways, and is strongly dependent on neuronal activity. Developing mice deficient in both astrocyte pathways fail to refine their retinogeniculate connections normally and retain excess functional synapses. Finally, we show that in the adult mouse brain, astrocytes continuously engulf both excitatory and inhibitory synapses. These studies reveal a novel role for astrocytes in mediating synapse elimination in the developing and adult brain, identify MEGF10 and MERTK as critical proteins in the synapse remodelling underlying neural circuit refinement, and have important implications for understanding learning and memory as well as neurological disease processes.
Sun, Yanjun; Nguyen, Amanda; Nguyen, Joseph; Le, Luc; Saur, Dieter; Choi, Jiwon; Callaway, Edward M.; Xu, Xiangmin
2014-01-01
Summary We applied a new Cre-dependent, genetically modified rabies-based tracing system to map direct synaptic connections to CA1 excitatory and inhibitory neuron types in mouse hippocampus. We found common inputs to excitatory and inhibitory CA1 neurons from CA3, CA2, entorhinal cortex and the medial septum (MS), and unexpectedly also from the subiculum. Excitatory CA1 neurons receive inputs from both cholinergic and GABAergic MS neurons while inhibitory CA1 neurons receive a great majority of input from GABAergic MS neurons; both cell types also receive weaker input from glutamatergic MS neurons. Comparisons of inputs to CA1 PV+ interneurons versus SOM+ interneurons showed similar strengths of input from the subiculum, but PV+ interneurons receive much stronger input than SOM+ neurons from CA3, entorhinal cortex and MS. Differential input from CA3 to specific CA1 cell types was also demonstrated functionally using laser scanning photostimulation and whole cell recordings. PMID:24656815
Hanson, Jesse E; Madison, Daniel V
2010-08-13
Diverse Mouse genetic models of neurodevelopmental, neuropsychiatric, and neurodegenerative causes of impaired cognition exhibit at least four convergent points of synaptic malfunction: 1) Strength of long-term potentiation (LTP), 2) Strength of long-term depression (LTD), 3) Relative inhibition levels (Inhibition), and 4) Excitatory connectivity levels (Connectivity). To test the hypothesis that pathological increases or decreases in these synaptic properties could underlie imbalances at the level of basic neural network function, we explored each type of malfunction in a simulation of autoassociative memory. These network simulations revealed that one impact of impairments or excesses in each of these synaptic properties is to shift the trade-off between pattern separation and pattern completion performance during memory storage and recall. Each type of synaptic pathology either pushed the network balance towards intolerable error in pattern separation or intolerable error in pattern completion. Imbalances caused by pathological impairments or excesses in LTP, LTD, inhibition, or connectivity, could all be exacerbated, or rescued, by the simultaneous modulation of any of the other three synaptic properties. Because appropriate modulation of any of the synaptic properties could help re-balance network function, regardless of the origins of the imbalance, we propose a new strategy of personalized cognitive therapeutics guided by assay of pattern completion vs. pattern separation function. Simulated examples and testable predictions of this theorized approach to cognitive therapeutics are presented.
O'Connor, Eoin C; Bariselli, Sebastiano; Bellone, Camilla
2014-04-01
Most of us engage in social interactions on a daily basis and the repertoire of social behaviors we acquire during development and later in life are incredibly varied. However, in many neurodevelopmental disorders, including autism spectrum disorders (ASDs), social behavior is severely compromised and indeed this represents a key diagnostic component for such conditions. From genetic association studies, it is increasingly apparent that genes identified as altered in individuals with ASDs often encode synaptic proteins. Moreover, these synaptic proteins typically serve to scaffold group-I metabotropic glutamate receptors (group-I mGluRs) and ionotropic glutamate receptors (iGluRs; AMPARs and NMDARs), or to enable group-I mGluR to iGluR crosstalk via protein synthesis. Here we aim to explore the possibility of a causal link between altered function of such synaptic proteins and impaired social behaviors that feature in neurodevelopmental disorders, such as ASDs. We review the known synaptic function and role in social behaviors of selected post-synaptic structural proteins (Shank, SAPAP and neuroligin) and regulators of protein synthesis (TSC1/2, FMRP and PTEN). While manipulations of proteins involved in group-I mGluR and iGluR scaffolding or crosstalk frequently lead to profound alterations in synaptic function and one or more components of social behavior, the neuronal circuits responsible for impairments in specific social behaviors are often poorly defined. We argue for an improved understanding of the neuronal circuits underlying specific social behaviors to aid the development of new ASD therapies. © 2014 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.
Mean Field Analysis of Stochastic Neural Network Models with Synaptic Depression
NASA Astrophysics Data System (ADS)
Yasuhiko Igarashi,; Masafumi Oizumi,; Masato Okada,
2010-08-01
We investigated the effects of synaptic depression on the macroscopic behavior of stochastic neural networks. Dynamical mean field equations were derived for such networks by taking the average of two stochastic variables: a firing-state variable and a synaptic variable. In these equations, the average product of thesevariables is decoupled as the product of their averages because the two stochastic variables are independent. We proved the independence of these two stochastic variables assuming that the synaptic weight Jij is of the order of 1/N with respect to the number of neurons N. Using these equations, we derived macroscopic steady-state equations for a network with uniform connections and for a ring attractor network with Mexican hat type connectivity and investigated the stability of the steady-state solutions. An oscillatory uniform state was observed in the network with uniform connections owing to a Hopf instability. For the ring network, high-frequency perturbations were shown not to affect system stability. Two mechanisms destabilize the inhomogeneous steady state, leading to two oscillatory states. A Turing instability leads to a rotating bump state, while a Hopf instability leads to an oscillatory bump state, which was previously unreported. Various oscillatory states take place in a network with synaptic depression depending on the strength of the interneuron connections.
Synaptic unreliability facilitates information transmission in balanced cortical populations
NASA Astrophysics Data System (ADS)
Gatys, Leon A.; Ecker, Alexander S.; Tchumatchenko, Tatjana; Bethge, Matthias
2015-06-01
Synaptic unreliability is one of the major sources of biophysical noise in the brain. In the context of neural information processing, it is a central question how neural systems can afford this unreliability. Here we examine how synaptic noise affects signal transmission in cortical circuits, where excitation and inhibition are thought to be tightly balanced. Surprisingly, we find that in this balanced state synaptic response variability actually facilitates information transmission, rather than impairing it. In particular, the transmission of fast-varying signals benefits from synaptic noise, as it instantaneously increases the amount of information shared between presynaptic signal and postsynaptic current. Furthermore we show that the beneficial effect of noise is based on a very general mechanism which contrary to stochastic resonance does not reach an optimum at a finite noise level.
Speed of feedforward and recurrent processing in multilayer networks of integrate-and-fire neurons.
Panzeri, S; Rolls, E T; Battaglia, F; Lavis, R
2001-11-01
The speed of processing in the visual cortical areas can be fast, with for example the latency of neuronal responses increasing by only approximately 10 ms per area in the ventral visual system sequence V1 to V2 to V4 to inferior temporal visual cortex. This has led to the suggestion that rapid visual processing can only be based on the feedforward connections between cortical areas. To test this idea, we investigated the dynamics of information retrieval in multiple layer networks using a four-stage feedforward network modelled with continuous dynamics with integrate-and-fire neurons, and associative synaptic connections between stages with a synaptic time constant of 10 ms. Through the implementation of continuous dynamics, we found latency differences in information retrieval of only 5 ms per layer when local excitation was absent and processing was purely feedforward. However, information latency differences increased significantly when non-associative local excitation was included. We also found that local recurrent excitation through associatively modified synapses can contribute significantly to processing in as little as 15 ms per layer, including the feedforward and local feedback processing. Moreover, and in contrast to purely feed-forward processing, the contribution of local recurrent feedback was useful and approximately this rapid even when retrieval was made difficult by noise. These findings suggest that cortical information processing can benefit from recurrent circuits when the allowed processing time per cortical area is at least 15 ms long.
Linear summation of outputs in a balanced network model of motor cortex.
Capaday, Charles; van Vreeswijk, Carl
2015-01-01
Given the non-linearities of the neural circuitry's elements, we would expect cortical circuits to respond non-linearly when activated. Surprisingly, when two points in the motor cortex are activated simultaneously, the EMG responses are the linear sum of the responses evoked by each of the points activated separately. Additionally, the corticospinal transfer function is close to linear, implying that the synaptic interactions in motor cortex must be effectively linear. To account for this, here we develop a model of motor cortex composed of multiple interconnected points, each comprised of reciprocally connected excitatory and inhibitory neurons. We show how non-linearities in neuronal transfer functions are eschewed by strong synaptic interactions within each point. Consequently, the simultaneous activation of multiple points results in a linear summation of their respective outputs. We also consider the effects of reduction of inhibition at a cortical point when one or more surrounding points are active. The network response in this condition is linear over an approximately two- to three-fold decrease of inhibitory feedback strength. This result supports the idea that focal disinhibition allows linear coupling of motor cortical points to generate movement related muscle activation patterns; albeit with a limitation on gain control. The model also explains why neural activity does not spread as far out as the axonal connectivity allows, whilst also explaining why distant cortical points can be, nonetheless, functionally coupled by focal disinhibition. Finally, we discuss the advantages that linear interactions at the cortical level afford to motor command synthesis.
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.
Characterization and Modeling of Nonfilamentary Ta/TaOx/TiO2/Ti Analog Synaptic Device
Wang, Yu-Fen; Lin, Yen-Chuan; Wang, I-Ting; Lin, Tzu-Ping; Hou, Tuo-Hung
2015-01-01
A two-terminal analog synaptic device that precisely emulates biological synaptic features is expected to be a critical component for future hardware-based neuromorphic computing. Typical synaptic devices based on filamentary resistive switching face severe limitations on the implementation of concurrent inhibitory and excitatory synapses with low conductance and state fluctuation. For overcoming these limitations, we propose a Ta/TaOx/TiO2/Ti device with superior analog synaptic features. A physical simulation based on the homogeneous (nonfilamentary) barrier modulation induced by oxygen ion migration accurately reproduces various DC and AC evolutions of synaptic states, including the spike-timing-dependent plasticity and paired-pulse facilitation. Furthermore, a physics-based compact model for facilitating circuit-level design is proposed on the basis of the general definition of memristor devices. This comprehensive experimental and theoretical study of the promising electronic synapse can facilitate realizing large-scale neuromorphic systems. PMID:25955658
Hosseiny, Salma; Pietri, Mariel; Petit-Paitel, Agnès; Zarif, Hadi; Heurteaux, Catherine; Chabry, Joëlle; Guyon, Alice
2015-11-01
Enriched environment (EE) is characterized by improved conditions for enhanced exploration, cognitive activity, social interaction and physical exercise. It has been shown that EE positively regulates the remodeling of neural circuits, memory consolidation, long-term changes in synaptic strength and neurogenesis. However, the fine mechanisms by which environment shapes the brain at different postnatal developmental stages and the duration required to induce such changes are still a matter of debate. In EE, large groups of mice were housed in bigger cages and were given toys, nesting materials and other equipment that promote physical activity to provide a stimulating environment. Weaned mice were housed in EE for 4, 6 or 8 weeks and compared with matched control mice that were raised in a standard environment. To investigate the differential effects of EE on immature and mature brains, we also housed young adult mice (8 weeks old) for 4 weeks in EE. We studied the influence of onset and duration of EE housing on the structure and function of hippocampal neurons. We found that: (1) EE enhances neurogenesis in juvenile, but not young adult mice; (2) EE increases the number of synaptic contacts at every stage; (3) long-term potentiation (LTP) and spontaneous and miniature activity at the glutamatergic synapses are affected differently by EE depending on its onset and duration. Our study provides an integrative view of the role of EE during postnatal development in various mechanisms of plasticity in the hippocampus including neurogenesis, synaptic morphology and electrophysiological parameters of synaptic connectivity. This work provides an explanation for discrepancies found in the literature about the effects of EE on LTP and emphasizes the importance of environment on hippocampal plasticity.
Computer simulations of stimulus dependent state switching in basic circuits of bursting neurons
NASA Astrophysics Data System (ADS)
Rabinovich, Mikhail; Huerta, Ramón; Bazhenov, Maxim; Kozlov, Alexander K.; Abarbanel, Henry D. I.
1998-11-01
We investigate the ability of oscillating neural circuits to switch between different states of oscillation in two basic neural circuits. We model two quite distinct small neural circuits. The first circuit is based on invertebrate central pattern generator (CPG) studies [A. I. Selverston and M. Moulins, The Crustacean Stomatogastric System (Springer-Verlag, Berlin, 1987)] and is composed of two neurons coupled via both gap junction and inhibitory synapses. The second consists of coupled pairs of interconnected thalamocortical relay and thalamic reticular neurons with both inhibitory and excitatory synaptic coupling. The latter is an elementary unit of the thalamic networks passing sensory information to the cerebral cortex [M. Steriade, D. A. McCormick, and T. J. Sejnowski, Science 262, 679 (1993)]. Both circuits have contradictory coupling between symmetric parts. The thalamocortical model has excitatory and inhibitory connections and the CPG has reciprocal inhibitory and electrical coupling. We describe the dynamics of the individual neurons in these circuits by conductance based ordinary differential equations of Hodgkin-Huxley type [J. Physiol. (London) 117, 500 (1952)]. Both model circuits exhibit bistability and hysteresis in a wide region of coupling strengths. The two main modes of behavior are in-phase and out-of-phase oscillations of the symmetric parts of the network. We investigate the response of these circuits, while they are operating in bistable regimes, to externally imposed excitatory spike trains with varying interspike timing and small amplitude pulses. These are meant to represent spike trains received by the basic circuits from sensory neurons. Circuits operating in a bistable region are sensitive to the frequency of these excitatory inputs. Frequency variations lead to changes from in-phase to out-of-phase coordination or vice versa. The signaling information contained in a spike train driving the network can place the circuit into one or another state depending on the interspike interval and this happens within a few spikes. These states are maintained by the basic circuit after the input signal is ended. When a new signal of the correct frequency enters the circuit, it can be switched to another state with the same ease.
Krystal, John H.; Abdallah, Chadi G.; Averill, Lynette A.; Kelmendi, Benjamin; Harpaz-Rotem, Ilan; Sanacora, Gerard; Southwick, Steven M.; Duman, Ronald S.
2018-01-01
Purpose of Review Studies of the neurobiology and treatment of PTSD have highlighted many aspects of the pathophysiology of this disorder that might be relevant to treatment. The purpose of this review is to highlight the potential clinical importance of an often-neglected consequence of stress models in animals that may be relevant to PTSD: the stress-related loss of synaptic connectivity. Recent Findings Here, we will briefly review evidence that PTSD might be a “synaptic disconnection syndrome” and highlight the importance of this perspective for the emerging therapeutic application of ketamine as a potential rapid-acting treatment for this disorder that may work, in part, by restoring synaptic connectivity. Summary Synaptic disconnection may contribute to the profile of PTSD symptoms that may be targeted by novel pharmacotherapeutics. PMID:28844076
Suen, Jonathan Y; Navlakha, Saket
2017-05-01
Controlling the flow and routing of data is a fundamental problem in many distributed networks, including transportation systems, integrated circuits, and the Internet. In the brain, synaptic plasticity rules have been discovered that regulate network activity in response to environmental inputs, which enable circuits to be stable yet flexible. Here, we develop a new neuro-inspired model for network flow control that depends only on modifying edge weights in an activity-dependent manner. We show how two fundamental plasticity rules, long-term potentiation and long-term depression, can be cast as a distributed gradient descent algorithm for regulating traffic flow in engineered networks. We then characterize, both by simulation and analytically, how different forms of edge-weight-update rules affect network routing efficiency and robustness. We find a close correspondence between certain classes of synaptic weight update rules derived experimentally in the brain and rules commonly used in engineering, suggesting common principles to both.
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.
Memristor-based cellular nonlinear/neural network: design, analysis, and applications.
Duan, Shukai; Hu, Xiaofang; Dong, Zhekang; Wang, Lidan; Mazumder, Pinaki
2015-06-01
Cellular nonlinear/neural network (CNN) has been recognized as a powerful massively parallel architecture capable of solving complex engineering problems by performing trillions of analog operations per second. The memristor was theoretically predicted in the late seventies, but it garnered nascent research interest due to the recent much-acclaimed discovery of nanocrossbar memories by engineers at the Hewlett-Packard Laboratory. The memristor is expected to be co-integrated with nanoscale CMOS technology to revolutionize conventional von Neumann as well as neuromorphic computing. In this paper, a compact CNN model based on memristors is presented along with its performance analysis and applications. In the new CNN design, the memristor bridge circuit acts as the synaptic circuit element and substitutes the complex multiplication circuit used in traditional CNN architectures. In addition, the negative differential resistance and nonlinear current-voltage characteristics of the memristor have been leveraged to replace the linear resistor in conventional CNNs. The proposed CNN design has several merits, for example, high density, nonvolatility, and programmability of synaptic weights. The proposed memristor-based CNN design operations for implementing several image processing functions are illustrated through simulation and contrasted with conventional CNNs. Monte-Carlo simulation has been used to demonstrate the behavior of the proposed CNN due to the variations in memristor synaptic weights.
Extinction Partially Reverts Structural Changes Associated with Remote Fear Memory
ERIC Educational Resources Information Center
Vetere, Gisella; Restivo, Leonardo; Novembre, Giovanni; Aceti, Massimiliano; Lumaca, Massimo; Ammassari-Teule, Martine
2011-01-01
Structural synaptic changes occur in medial prefrontal cortex circuits during remote memory formation. Whether extinction reverts or further reshapes these circuits is, however, unknown. Here we show that the number and the size of spines were enhanced in anterior cingulate (aCC) and infralimbic (ILC) cortices 36 d following contextual fear…
Gasperini, Robert J; Pavez, Macarena; Thompson, Adrian C; Mitchell, Camilla B; Hardy, Holly; Young, Kaylene M; Chilton, John K; Foa, Lisa
2017-10-01
The precision with which neurons form connections is crucial for the normal development and function of the nervous system. The development of neuronal circuitry in the nervous system is accomplished by axon pathfinding: a process where growth cones guide axons through the embryonic environment to connect with their appropriate synaptic partners to form functional circuits. Despite intense efforts over many years to understand how this process is regulated, the complete repertoire of molecular mechanisms that govern the growth cone cytoskeleton and hence motility, remain unresolved. A central tenet in the axon guidance field is that calcium signals regulate growth cone behaviours such as extension, turning and pausing by regulating rearrangements of the growth cone cytoskeleton. Here, we provide evidence that not only the amplitude of a calcium signal is critical for growth cone motility but also the source of calcium mobilisation. We provide an example of this idea by demonstrating that manipulation of calcium signalling via L-type voltage gated calcium channels can perturb sensory neuron motility towards a source of netrin-1. Understanding how calcium signals can be transduced to initiate cytoskeletal changes represents a significant gap in our current knowledge of the mechanisms that govern axon guidance, and consequently the formation of functional neural circuits in the developing nervous system. Crown Copyright © 2017. Published by Elsevier Inc. All rights reserved.
Self-organised criticality via retro-synaptic signals
NASA Astrophysics Data System (ADS)
Hernandez-Urbina, Victor; Herrmann, J. Michael
2016-12-01
The brain is a complex system par excellence. In the last decade the observation of neuronal avalanches in neocortical circuits suggested the presence of self-organised criticality in brain networks. The occurrence of this type of dynamics implies several benefits to neural computation. However, the mechanisms that give rise to critical behaviour in these systems, and how they interact with other neuronal processes such as synaptic plasticity are not fully understood. In this paper, we present a long-term plasticity rule based on retro-synaptic signals that allows the system to reach a critical state in which clusters of activity are distributed as a power-law, among other observables. Our synaptic plasticity rule coexists with other synaptic mechanisms such as spike-timing-dependent plasticity, which implies that the resulting synaptic modulation captures not only the temporal correlations between spiking times of pre- and post-synaptic units, which has been suggested as requirement for learning and memory in neural systems, but also drives the system to a state of optimal neural information processing.
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
Joshi, Ankur; Middleton, Jason W.; Anderson, Charles T.; Borges, Katharine; Suter, Benjamin A.; Shepherd, Gordon M. G.
2015-01-01
Auditory cortex (AC) layer 5B (L5B) contains both corticocollicular neurons, a type of pyramidal-tract neuron projecting to the inferior colliculus, and corticocallosal neurons, a type of intratelencephalic neuron projecting to contralateral AC. Although it is known that these neuronal types have distinct roles in auditory processing and different response properties to sound, the synaptic and intrinsic mechanisms shaping their input–output functions remain less understood. Here, we recorded in brain slices of mouse AC from retrogradely labeled corticocollicular and neighboring corticocallosal neurons in L5B. Corticocollicular neurons had, on average, lower input resistance, greater hyperpolarization-activated current (Ih), depolarized resting membrane potential, faster action potentials, initial spike doublets, and less spike-frequency adaptation. In paired recordings between single L2/3 and labeled L5B neurons, the probabilities of connection, amplitude, latency, rise time, and decay time constant of the unitary EPSC were not different for L2/3→corticocollicular and L2/3→corticocallosal connections. However, short trains of unitary EPSCs showed no synaptic depression in L2/3→corticocollicular connections, but substantial depression in L2/3→corticocallosal connections. Synaptic potentials in L2/3→corticocollicular connections decayed faster and showed less temporal summation, consistent with increased Ih in corticocollicular neurons, whereas synaptic potentials in L2/3→corticocallosal connections showed more temporal summation. Extracellular L2/3 stimulation at two different rates resulted in spiking in L5B neurons; for corticocallosal neurons the spike rate was frequency dependent, but for corticocollicular neurons it was not. Together, these findings identify cell-specific intrinsic and synaptic mechanisms that divide intracortical synaptic excitation from L2/3 to L5B into two functionally distinct pathways with different input–output functions. PMID:25698747
Neuronal synchrony: Peculiarity and generality
Nowotny, Thomas; Huerta, Ramon; Rabinovich, Mikhail I.
2008-01-01
Synchronization in neuronal systems is a new and intriguing application of dynamical systems theory. Why are neuronal systems different as a subject for synchronization? (1) Neurons in themselves are multidimensional nonlinear systems that are able to exhibit a wide variety of different activity patterns. Their “dynamical repertoire” includes regular or chaotic spiking, regular or chaotic bursting, multistability, and complex transient regimes. (2) Usually, neuronal oscillations are the result of the cooperative activity of many synaptically connected neurons (a neuronal circuit). Thus, it is necessary to consider synchronization between different neuronal circuits as well. (3) The synapses that implement the coupling between neurons are also dynamical elements and their intrinsic dynamics influences the process of synchronization or entrainment significantly. In this review we will focus on four new problems: (i) the synchronization in minimal neuronal networks with plastic synapses (synchronization with activity dependent coupling), (ii) synchronization of bursts that are generated by a group of nonsymmetrically coupled inhibitory neurons (heteroclinic synchronization), (iii) the coordination of activities of two coupled neuronal networks (partial synchronization of small composite structures), and (iv) coarse grained synchronization in larger systems (synchronization on a mesoscopic scale). PMID:19045493
Using high-throughput barcode sequencing to efficiently map connectomes.
Peikon, Ian D; Kebschull, Justus M; Vagin, Vasily V; Ravens, Diana I; Sun, Yu-Chi; Brouzes, Eric; Corrêa, Ivan R; Bressan, Dario; Zador, Anthony M
2017-07-07
The function of a neural circuit is determined by the details of its synaptic connections. At present, the only available method for determining a neural wiring diagram with single synapse precision-a 'connectome'-is based on imaging methods that are slow, labor-intensive and expensive. Here, we present SYNseq, a method for converting the connectome into a form that can exploit the speed and low cost of modern high-throughput DNA sequencing. In SYNseq, each neuron is labeled with a unique random nucleotide sequence-an RNA 'barcode'-which is targeted to the synapse using engineered proteins. Barcodes in pre- and postsynaptic neurons are then associated through protein-protein crosslinking across the synapse, extracted from the tissue, and joined into a form suitable for sequencing. Although our failure to develop an efficient barcode joining scheme precludes the widespread application of this approach, we expect that with further development SYNseq will enable tracing of complex circuits at high speed and low cost. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.
Animal models of speech and vocal communication deficits associated with psychiatric disorders
Konopka, Genevieve; Roberts, Todd F.
2015-01-01
Disruptions in speech, language and vocal communication are hallmarks of several neuropsychiatric disorders, most notably autism spectrum disorders. Historically, the use of animal models to dissect molecular pathways and connect them to behavioral endophenotypes in cognitive disorders has proven to be an effective approach for developing and testing disease-relevant therapeutics. The unique aspects of human language when compared to vocal behaviors in other animals make such an approach potentially more challenging. However, the study of vocal learning in species with analogous brain circuits to humans may provide entry points for understanding this human-specific phenotype and diseases. Here, we review animal models of vocal learning and vocal communication, and specifically link phenotypes of psychiatric disorders to relevant model systems. Evolutionary constraints in the organization of neural circuits and synaptic plasticity result in similarities in the brain mechanisms for vocal learning and vocal communication. Comparative approaches and careful consideration of the behavioral limitations among different animal models can provide critical avenues for dissecting the molecular pathways underlying cognitive disorders that disrupt speech, language and vocal communication. PMID:26232298
Rohrbough, Jeffrey; Rushton, Emma; Woodruff, Elvin; Fergestad, Tim; Vigneswaran, Krishanthan; Broadie, Kendal
2007-01-01
Formation and regulation of excitatory glutamatergic synapses is essential for shaping neural circuits throughout development. In a Drosophila genetic screen for synaptogenesis mutants, we identified mind the gap (mtg), which encodes a secreted, extracellular N-glycosaminoglycan-binding protein. MTG is expressed neuronally and detected in the synaptic cleft, and is required to form the specialized transsynaptic matrix that links the presynaptic active zone with the post-synaptic glutamate receptor (GluR) domain. Null mtg embryonic mutant synapses exhibit greatly reduced GluR function, and a corresponding loss of localized GluR domains. All known post-synaptic signaling/scaffold proteins functioning upstream of GluR localization are also grossly reduced or mislocalized in mtg mutants, including the dPix–dPak–Dock cascade and the Dlg/PSD-95 scaffold. Ubiquitous or neuronally targeted mtg RNA interference (RNAi) similarly reduce post-synaptic assembly, whereas post-synaptically targeted RNAi has no effect, indicating that presynaptic MTG induces and maintains the post-synaptic pathways driving GluR domain formation. These findings suggest that MTG is secreted from the presynaptic terminal to shape the extracellular synaptic cleft domain, and that the cleft domain functions to mediate transsynaptic signals required for post-synaptic development. PMID:17901219
Martens, Marijn B; Houweling, Arthur R; E Tiesinga, Paul H
2017-02-01
Neuronal circuits in the rodent barrel cortex are characterized by stable low firing rates. However, recent experiments show that short spike trains elicited by electrical stimulation in single neurons can induce behavioral responses. Hence, the underlying neural networks provide stability against internal fluctuations in the firing rate, while simultaneously making the circuits sensitive to small external perturbations. Here we studied whether stability and sensitivity are affected by the connectivity structure in recurrently connected spiking networks. We found that anti-correlation between the number of afferent (in-degree) and efferent (out-degree) synaptic connections of neurons increases stability against pathological bursting, relative to networks where the degrees were either positively correlated or uncorrelated. In the stable network state, stimulation of a few cells could lead to a detectable change in the firing rate. To quantify the ability of networks to detect the stimulation, we used a receiver operating characteristic (ROC) analysis. For a given level of background noise, networks with anti-correlated degrees displayed the lowest false positive rates, and consequently had the highest stimulus detection performance. We propose that anti-correlation in the degree distribution may be a computational strategy employed by sensory cortices to increase the detectability of external stimuli. We show that networks with anti-correlated degrees can in principle be formed by applying learning rules comprised of a combination of spike-timing dependent plasticity, homeostatic plasticity and pruning to networks with uncorrelated degrees. To test our prediction we suggest a novel experimental method to estimate correlations in the degree distribution.
Nonvolatile Array Of Synapses For Neural Network
NASA Technical Reports Server (NTRS)
Tawel, Raoul
1993-01-01
Elements of array programmed with help of ultraviolet light. A 32 x 32 very-large-scale integrated-circuit array of electronic synapses serves as building-block chip for analog neural-network computer. Synaptic weights stored in nonvolatile manner. Makes information content of array invulnerable to loss of power, and, by eliminating need for circuitry to refresh volatile synaptic memory, makes architecture simpler and more compact.
The cerebellar Golgi cell and spatiotemporal organization of granular layer activity
D'Angelo, Egidio; Solinas, Sergio; Mapelli, Jonathan; Gandolfi, Daniela; Mapelli, Lisa; Prestori, Francesca
2013-01-01
The cerebellar granular layer has been suggested to perform a complex spatiotemporal reconfiguration of incoming mossy fiber signals. Central to this role is the inhibitory action exerted by Golgi cells over granule cells: Golgi cells inhibit granule cells through both feedforward and feedback inhibitory loops and generate a broad lateral inhibition that extends beyond the afferent synaptic field. This characteristic connectivity has recently been investigated in great detail and been correlated with specific functional properties of these neurons. These include theta-frequency pacemaking, network entrainment into coherent oscillations and phase resetting. Important advances have also been made in terms of determining the membrane and synaptic properties of the neuron, and clarifying the mechanisms of activation by input bursts. Moreover, voltage sensitive dye imaging and multi-electrode array (MEA) recordings, combined with mathematical simulations based on realistic computational models, have improved our understanding of the impact of Golgi cell activity on granular layer circuit computations. These investigations have highlighted the critical role of Golgi cells in: generating dense clusters of granule cell activity organized in center-surround structures, implementing combinatorial operations on multiple mossy fiber inputs, regulating transmission gain, and cut-off frequency, controlling spike timing and burst transmission, and determining the sign, intensity and duration of long-term synaptic plasticity at the mossy fiber-granule cell relay. This review considers recent advances in the field, highlighting the functional implications of Golgi cells for granular layer network computation and indicating new challenges for cerebellar research. PMID:23730271
Array tomography of physiologically-characterized CNS synapses.
Valenzuela, Ricardo A; Micheva, Kristina D; Kiraly, Marianna; Li, Dong; Madison, Daniel V
2016-08-01
The ability to correlate plastic changes in synaptic physiology with changes in synaptic anatomy has been very limited in the central nervous system because of shortcomings in existing methods for recording the activity of specific CNS synapses and then identifying and studying the same individual synapses on an anatomical level. We introduce here a novel approach that combines two existing methods: paired neuron electrophysiological recording and array tomography, allowing for the detailed molecular and anatomical study of synapses with known physiological properties. The complete mapping of a neuronal pair allows determining the exact number of synapses in the pair and their location. We have found that the majority of close appositions between the presynaptic axon and the postsynaptic dendrite in the pair contain synaptic specializations. The average release probability of the synapses between the two neurons in the pair is low, below 0.2, consistent with previous studies of these connections. Other questions, such as receptor distribution within synapses, can be addressed more efficiently by identifying only a subset of synapses using targeted partial reconstructions. In addition, time sensitive events can be captured with fast chemical fixation. Compared to existing methods, the present approach is the only one that can provide detailed molecular and anatomical information of electrophysiologically-characterized individual synapses. This method will allow for addressing specific questions about the properties of identified CNS synapses, even when they are buried within a cloud of millions of other brain circuit elements. Copyright © 2016. Published by Elsevier B.V.
Asghari Adib, Elham; Stanchev, Doychin T; Xiong, Xin; Klinedinst, Susan; Soppina, Pushpanjali; Jahn, Thomas Robert; Hume, Richard I
2017-01-01
The kinesin-3 family member Unc-104/KIF1A is required for axonal transport of many presynaptic components to synapses, and mutation of this gene results in synaptic dysfunction in mice, flies and worms. Our studies at the Drosophila neuromuscular junction indicate that many synaptic defects in unc-104-null mutants are mediated independently of Unc-104’s transport function, via the Wallenda (Wnd)/DLK MAP kinase axonal damage signaling pathway. Wnd signaling becomes activated when Unc-104’s function is disrupted, and leads to impairment of synaptic structure and function by restraining the expression level of active zone (AZ) and synaptic vesicle (SV) components. This action concomitantly suppresses the buildup of synaptic proteins in neuronal cell bodies, hence may play an adaptive role to stresses that impair axonal transport. Wnd signaling also becomes activated when pre-synaptic proteins are over-expressed, suggesting the existence of a feedback circuit to match synaptic protein levels to the transport capacity of the axon. PMID:28925357
The interplay between neurons and glia in synapse development and plasticity.
Stogsdill, Jeff A; Eroglu, Cagla
2017-02-01
In the brain, the formation of complex neuronal networks amenable to experience-dependent remodeling is complicated by the diversity of neurons and synapse types. The establishment of a functional brain depends not only on neurons, but also non-neuronal glial cells. Glia are in continuous bi-directional communication with neurons to direct the formation and refinement of synaptic connectivity. This article reviews important findings, which uncovered cellular and molecular aspects of the neuron-glia cross-talk that govern the formation and remodeling of synapses and circuits. In vivo evidence demonstrating the critical interplay between neurons and glia will be the major focus. Additional attention will be given to how aberrant communication between neurons and glia may contribute to neural pathologies. Copyright © 2016 Elsevier Ltd. All rights reserved.
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.
Neural plasticity and behavior - sixty years of conceptual advances.
Sweatt, J David
2016-10-01
This brief review summarizes 60 years of conceptual advances that have demonstrated a role for active changes in neuronal connectivity as a controller of behavior and behavioral change. Seminal studies in the first phase of the six-decade span of this review firmly established the cellular basis of behavior - a concept that we take for granted now, but which was an open question at the time. Hebbian plasticity, including long-term potentiation and long-term depression, was then discovered as being important for local circuit refinement in the context of memory formation and behavioral change and stabilization in the mammalian central nervous system. Direct demonstration of plasticity of neuronal circuit function in vivo, for example, hippocampal neurons forming place cell firing patterns, extended this concept. However, additional neurophysiologic and computational studies demonstrated that circuit development and stabilization additionally relies on non-Hebbian, homoeostatic, forms of plasticity, such as synaptic scaling and control of membrane intrinsic properties. Activity-dependent neurodevelopment was found to be associated with cell-wide adjustments in post-synaptic receptor density, and found to occur in conjunction with synaptic pruning. Pioneering cellular neurophysiologic studies demonstrated the critical roles of transmembrane signal transduction, NMDA receptor regulation, regulation of neural membrane biophysical properties, and back-propagating action potential in critical time-dependent coincidence detection in behavior-modifying circuits. Concerning the molecular mechanisms underlying these processes, regulation of gene transcription was found to serve as a bridge between experience and behavioral change, closing the 'nature versus nurture' divide. Both active DNA (de)methylation and regulation of chromatin structure have been validated as crucial regulators of gene transcription during learning. The discovery of protein synthesis dependence on the acquisition of behavioral change was an influential discovery in the neurochemistry of behavioral modification. Higher order cognitive functions such as decision making and spatial and language learning were also discovered to hinge on neural plasticity mechanisms. The role of disruption of these processes in intellectual disabilities, memory disorders, and drug addiction has recently been clarified based on modern genetic techniques, including in the human. The area of neural plasticity and behavior has seen tremendous advances over the last six decades, with many of those advances being specifically in the neurochemistry domain. This review provides an overview of the progress in the area of neuroplasticity and behavior over the life-span of the Journal of Neurochemistry. To organize the broad literature base, the review collates progress into fifteen broad categories identified as 'conceptual advances', as viewed by the author. The fifteen areas are delineated in the figure above. This article is part of the 60th Anniversary special issue. © 2016 International Society for Neurochemistry.
Plasticity of synaptic connections in sensory-motor pathways of the adult locust flight system.
Wolf, H; Büschges, A
1997-09-01
We investigated possible roles of retrograde signals and competitive interactions in the lesion-induced reorganization of synaptic contacts in the locust CNS. Neuronal plasticity is elicited in the adult flight system by removal of afferents from the tegula, a mechanoreceptor organ at the base of the wing. We severed one hindwing organ and studied the resulting rearrangement of synaptic contacts between flight interneurons and afferent neurons from the remaining three tegulae (2 forewing, 1 hindwing). This was done by electric stimulation of afferents and intracellular recording from interneurons (and occasionally motoneurons). Two to three weeks after unilateral tegula lesion, connections between tegula afferents and flight interneurons were altered in the following way. 1) Axons from the forewing tegula on the operated side had established new synaptic contacts with metathoracic elevator interneurons. In addition, the amplitude of compound excitatory postsynaptic potentials elicited by electric stimulation was increased, indicating that a larger number of afferents connected to any given interneuron. 2) On the side contralateral to the lesion, connectivity between axons from the forewing tegula and elevator interneurons was decreased. 3) The efficacy of the (remaining) hindwing afferents appeared to be increased with regard to both synaptic transmission to interneurons and impact on flight motor pattern. 4) Flight motoneurons, which are normally restricted to the ipsilateral hemiganglion, sprouted across the ganglion midline after unilateral tegula removal and apparently established new synaptic contacts with tegula afferents on that side. The changes on the operated side are interpreted as occupation of synaptic space vacated on the interneurons by the severed hindwing afferents. On the contralateral side, the changes in synaptic contact must be elicited by retrograde signals from bilaterally arborizing flight interneurons, because tegula projections remain strictly ipsilateral. The pattern of changes suggests competitive interactions between forewing and hindwing afferents. The present investigation thus presents evidence that the CNS of the mature locust is capable of extensive synaptic rearrangement in response to injury and indicates for the first time the action of retrograde signals from interneurons.
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
Jin, Xiaoming; Jiang, Kewen
2014-01-01
A variety of major developmental cortical malformations are closely associated with clinically intractable epilepsy. Pathophysiological aspects of one such disorder, human polymicrogyria, can be modeled by making neocortical freeze lesions (FL) in neonatal rodents, resulting in the formation of microgyri. Previous studies showed enhanced excitatory and inhibitory synaptic transmission and connectivity in cortical layer V pyramidal neurons in the paramicrogyral cortex. In young adult transgenic mice that express green fluorescent protein (GFP) specifically in parvalbumin positive fast-spiking (FS) interneurons, we used laser scanning photostimulation (LSPS) of caged glutamate to map excitatory and inhibitory synaptic connectivity onto FS interneurons in layer V of paramicrogyral cortex in control and FL groups. The proportion of uncaging sites from which excitatory postsynaptic currents (EPSCs) could be evoked (hotspot ratio) increased slightly but significantly in FS cells of the FL vs. control cortex, while the mean amplitude of LSPS-evoked EPSCs at hotspots did not change. In contrast, the hotspot ratio of inhibitory postsynaptic currents (IPSCs) was significantly decreased in FS neurons of the FL cortex. These alterations in synaptic inputs onto FS interneurons may result in an enhanced inhibitory output. We conclude that alterations in synaptic connectivity to cortical layer V FS interneurons do not contribute to hyperexcitability of the FL model. Instead, the enhanced inhibitory output from these neurons may partially offset an earlier demonstrated increase in synaptic excitation of pyramidal cells and thereby maintain a relative balance between excitation and inhibition in the affected cortical circuitry. PMID:24990567
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
Testa-Silva, Guilherme; Loebel, Alex; Giugliano, Michele; de Kock, Christiaan P J; Mansvelder, Huibert D; Meredith, Rhiannon M
2012-06-01
Neuronal theories of neurodevelopmental disorders (NDDs) of autism and mental retardation propose that abnormal connectivity underlies deficits in attentional processing. We tested this theory by studying unitary synaptic connections between layer 5 pyramidal neurons within medial prefrontal cortex (mPFC) networks in the Fmr1-KO mouse model for mental retardation and autism. In line with predictions from neurocognitive theory, we found that neighboring pyramidal neurons were hyperconnected during a critical period in early mPFC development. Surprisingly, excitatory synaptic connections between Fmr1-KO pyramidal neurons were significantly slower and failed to recover from short-term depression as quickly as wild type (WT) synapses. By 4-5 weeks of mPFC development, connectivity rates were identical for both KO and WT pyramidal neurons and synapse dynamics changed from depressing to facilitating responses with similar properties in both groups. We propose that the early alteration in connectivity and synaptic recovery are tightly linked: using a network model, we show that slower synapses are essential to counterbalance hyperconnectivity in order to maintain a dynamic range of excitatory activity. However, the slow synaptic time constants induce decreased responsiveness to low-frequency stimulation, which may explain deficits in integration and early information processing in attentional neuronal networks in NDDs.
Testa-Silva, Guilherme; Loebel, Alex; Giugliano, Michele; de Kock, Christiaan P.J.; Mansvelder, Huibert D.; Meredith, Rhiannon M.
2013-01-01
Neuronal theories of neurodevelopmental disorders (NDDs) of autism and mental retardation propose that abnormal connectivity underlies deficits in attentional processing. We tested this theory by studying unitary synaptic connections between layer 5 pyramidal neurons within medial prefrontal cortex (mPFC) networks in the Fmr1-KO mouse model for mental retardation and autism. In line with predictions from neurocognitive theory, we found that neighboring pyramidal neurons were hyperconnected during a critical period in early mPFC development. Surprisingly, excitatory synaptic connections between Fmr1-KO pyramidal neurons were significantly slower and failed to recover from short-term depression as quickly as wild type (WT) synapses. By 4--5 weeks of mPFC development, connectivity rates were identical for both KO and WT pyramidal neurons and synapse dynamics changed from depressing to facilitating responses with similar properties in both groups. We propose that the early alteration in connectivity and synaptic recovery are tightly linked: using a network model, we show that slower synapses are essential to counterbalance hyperconnectivity in order to maintain a dynamic range of excitatory activity. However, the slow synaptic time constants induce decreased responsiveness to low-frequency stimulation, which may explain deficits in integration and early information processing in attentional neuronal networks in NDDs. PMID:21856714
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.
Katz, P S; Frost, W N
1995-12-01
1. Neuromodulation has previously been shown to be intrinsic to the central pattern generator (CPG) circuit that generates the escape swim of the nudibranch mollusk Tritonia diomedea; the dorsal swim interneurons (DSIs) make conventional monosynaptic connections and evoke neuromodulatory effects within the swim motor circuit. The conventional synaptic potentials evoked by a DSI onto cerebral neuron 2 (C2) and onto the dorsal flexion neurons (DFNs) consist of a fast excitatory postsynaptic potential (EPSP) followed by a prolonged slow EPSP. In their neuromodulatory role, the DSIs produce an enhancement of the monosynaptic connections made by C2 onto other CPG circuit interneurons and onto efferent flexion neurons. Previous work showed that the DSIs are immunoreactive for serotonin. Here we provide evidence that both the neurotransmission and the neuromodulation evoked by the DSIs are produced by serotonin, and that these effects may be pharmacologically separable. 2. Previously it was shown that bath-applied serotonin both mimics and occludes the modulation of the C2 synapses by the DSIs. Here we find that pressure-applied puffs of serotonin mimic both the fast and slow EPSPs evoked by a DSI onto a DFN, whereas high concentrations of bath-applied serotonin occlude both of these synaptic components. 3. Consistent with the hypothesis that serotonin mediates the actions of the DSIs, the serotonin reuptake inhibitor imipramine prolongs the duration of the fast DSI-DFN EPSP, increases the amplitude of the slow DSI-DFN EPSP, and increases both the amplitude and duration of the modulation of the C2-DFN synapse by the DSIs. 4. Two serotonergic antagonists were found that block the actions of the DSIs. Gramine blocks the fast DSI-DFN EPSP, and has far less of an effect on the slow EPSP and the modulation. Gramine also diminishes the depolarization evoked by pressure-applied serotonin, showing that it is a serotonin antagonist in this system. In contrast, methysergide greatly reduces both the slow EPSP and the modulation evoked by the DSIs, but has mixed effects on the fast EPSP. Methysergide also blocks the ability of exogenous serotonin to enhance the C2-DFN EPSP, demonstrating that it antagonizes the serotonin receptors responsible for this modulation. 5. Taken together with previous work, these results indicate that serotonin is likely to be responsible for all three actions of the DSIs that were examined: the fast and slow DSI-DFN EPSPs and the neuromodulation of the C2-DFN synapse. These results also indicate that the conventional and neuromodulatory effects of the DSIs may be pharmacologically separable. In future work it may be possible to determine the functional role of each in the swim circuit.
Schoch, Hannah; Kreibich, Arati S; Ferri, Sarah L; White, Rachel S; Bohorquez, Dominique; Banerjee, Anamika; Port, Russell G; Dow, Holly C; Cordero, Lucero; Pallathra, Ashley A; Kim, Hyong; Li, Hongzhe; Bilker, Warren B; Hirano, Shinji; Schultz, Robert T; Borgmann-Winter, Karin; Hahn, Chang-Gyu; Feldmeyer, Dirk; Carlson, Gregory C; Abel, Ted; Brodkin, Edward S
2017-02-01
Behavioral symptoms in individuals with autism spectrum disorder (ASD) have been attributed to abnormal neuronal connectivity, but the molecular bases of these behavioral and brain phenotypes are largely unknown. Human genetic studies have implicated PCDH10, a member of the δ2 subfamily of nonclustered protocadherin genes, in ASD. PCDH10 expression is enriched in the basolateral amygdala, a brain region implicated in the social deficits of ASD. Previous reports indicate that Pcdh10 plays a role in axon outgrowth and glutamatergic synapse elimination, but its roles in social behaviors and amygdala neuronal connectivity are unknown. We hypothesized that haploinsufficiency of Pcdh10 would reduce social approach behavior and alter the structure and function of amygdala circuits. Mice lacking one copy of Pcdh10 (Pcdh10 +/- ) and wild-type littermates were assessed for social approach and other behaviors. The lateral/basolateral amygdala was assessed for dendritic spine number and morphology, and amygdala circuit function was studied using voltage-sensitive dye imaging. Expression of Pcdh10 and N-methyl-D-aspartate receptor (NMDAR) subunits was assessed in postsynaptic density fractions of the amygdala. Male Pcdh10 +/- mice have reduced social approach behavior, as well as impaired gamma synchronization, abnormal spine morphology, and reduced levels of NMDAR subunits in the amygdala. Social approach deficits in Pcdh10 +/- male mice were rescued with acute treatment with the NMDAR partial agonist d-cycloserine. Our studies reveal that male Pcdh10 +/- mice have synaptic and behavioral deficits, and establish Pcdh10 +/- mice as a novel genetic model for investigating neural circuitry and behavioral changes relevant to ASD. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.
'The genetic analysis of functional connectomics in Drosophila'
Meinertzhagen, Ian A.; Lee, Chi-Hon
2014-01-01
Fly and vertebrate nervous systems share many organization characteristics, such as layers, columns and glomeruli, and utilize similar synaptic components, such ion channels and receptors. Both also exhibit similar network features. Recent technological advances, especially in electron microscopy, now allow us to determine synaptic circuits and identify pathways cell-by-cell, as part of the fly’s connectome. Genetic tools provide the means to identify synaptic components, as well as to record and manipulate neuronal activity, adding function to the connectome. This review discusses technical advances in these emerging areas of functional connectomics, offering prognoses in each and identifying the challenges in bridging structural connectomics to molecular biology and synaptic physiology, thereby determining fundamental computation mechanisms that underlie behaviour. PMID:23084874
Kilinc, Deniz; Demir, Alper
2017-08-01
The brain is extremely energy efficient and remarkably robust in what it does despite the considerable variability and noise caused by the stochastic mechanisms in neurons and synapses. Computational modeling is a powerful tool that can help us gain insight into this important aspect of brain mechanism. A deep understanding and computational design tools can help develop robust neuromorphic electronic circuits and hybrid neuroelectronic systems. In this paper, we present a general modeling framework for biological neuronal circuits that systematically captures the nonstationary stochastic behavior of ion channels and synaptic processes. In this framework, fine-grained, discrete-state, continuous-time Markov chain models of both ion channels and synaptic processes are treated in a unified manner. Our modeling framework features a mechanism for the automatic generation of the corresponding coarse-grained, continuous-state, continuous-time stochastic differential equation models for neuronal variability and noise. Furthermore, we repurpose non-Monte Carlo noise analysis techniques, which were previously developed for analog electronic circuits, for the stochastic characterization of neuronal circuits both in time and frequency domain. We verify that the fast non-Monte Carlo analysis methods produce results with the same accuracy as computationally expensive Monte Carlo simulations. We have implemented the proposed techniques in a prototype simulator, where both biological neuronal and analog electronic circuits can be simulated together in a coupled manner.
Superconducting Optoelectronic Circuits for Neuromorphic Computing
NASA Astrophysics Data System (ADS)
Shainline, Jeffrey M.; Buckley, Sonia M.; Mirin, Richard P.; Nam, Sae Woo
2017-03-01
Neural networks have proven effective for solving many difficult computational problems, yet implementing complex neural networks in software is computationally expensive. To explore the limits of information processing, it is necessary to implement new hardware platforms with large numbers of neurons, each with a large number of connections to other neurons. Here we propose a hybrid semiconductor-superconductor hardware platform for the implementation of neural networks and large-scale neuromorphic computing. The platform combines semiconducting few-photon light-emitting diodes with superconducting-nanowire single-photon detectors to behave as spiking neurons. These processing units are connected via a network of optical waveguides, and variable weights of connection can be implemented using several approaches. The use of light as a signaling mechanism overcomes fanout and parasitic constraints on electrical signals while simultaneously introducing physical degrees of freedom which can be employed for computation. The use of supercurrents achieves the low power density (1 mW /cm2 at 20-MHz firing rate) necessary to scale to systems with enormous entropy. Estimates comparing the proposed hardware platform to a human brain show that with the same number of neurons (1 011) and 700 independent connections per neuron, the hardware presented here may achieve an order of magnitude improvement in synaptic events per second per watt.
ERIC Educational Resources Information Center
Cohen-Matsliah, Sivan Ida; Seroussi, Yaron; Rosenblum, Kobi; Barkai, Edi
2008-01-01
Pyramidal neurons in the piriform cortex from olfactory-discrimination (OD) trained rats undergo synaptic modifications that last for days after learning. A particularly intriguing modification is reduced paired-pulse facilitation (PPF) in the synapses interconnecting these cells; a phenomenon thought to reflect enhanced synaptic release. The…
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…
Automatic Adaptation to Fast Input Changes in a Time-Invariant Neural Circuit
Bharioke, Arjun; Chklovskii, Dmitri B.
2015-01-01
Neurons must faithfully encode signals that can vary over many orders of magnitude despite having only limited dynamic ranges. For a correlated signal, this dynamic range constraint can be relieved by subtracting away components of the signal that can be predicted from the past, a strategy known as predictive coding, that relies on learning the input statistics. However, the statistics of input natural signals can also vary over very short time scales e.g., following saccades across a visual scene. To maintain a reduced transmission cost to signals with rapidly varying statistics, neuronal circuits implementing predictive coding must also rapidly adapt their properties. Experimentally, in different sensory modalities, sensory neurons have shown such adaptations within 100 ms of an input change. Here, we show first that linear neurons connected in a feedback inhibitory circuit can implement predictive coding. We then show that adding a rectification nonlinearity to such a feedback inhibitory circuit allows it to automatically adapt and approximate the performance of an optimal linear predictive coding network, over a wide range of inputs, while keeping its underlying temporal and synaptic properties unchanged. We demonstrate that the resulting changes to the linearized temporal filters of this nonlinear network match the fast adaptations observed experimentally in different sensory modalities, in different vertebrate species. Therefore, the nonlinear feedback inhibitory network can provide automatic adaptation to fast varying signals, maintaining the dynamic range necessary for accurate neuronal transmission of natural inputs. PMID:26247884
Nonvolatile programmable neural network synaptic array
NASA Technical Reports Server (NTRS)
Tawel, Raoul (Inventor)
1994-01-01
A floating-gate metal oxide semiconductor (MOS) transistor is implemented for use as a nonvolatile analog storage element of a synaptic cell used to implement an array of processing synaptic cells. These cells are based on a four-quadrant analog multiplier requiring both X and Y differential inputs, where one Y input is UV programmable. These nonvolatile synaptic cells are disclosed fully connected in a 32 x 32 synaptic cell array using standard very large scale integration (VLSI) complementary MOS (CMOS) technology.
Happel, Max F. K.; Ohl, Frank W.
2017-01-01
Robust perception of auditory objects over a large range of sound intensities is a fundamental feature of the auditory system. However, firing characteristics of single neurons across the entire auditory system, like the frequency tuning, can change significantly with stimulus intensity. Physiological correlates of level-constancy of auditory representations hence should be manifested on the level of larger neuronal assemblies or population patterns. In this study we have investigated how information of frequency and sound level is integrated on the circuit-level in the primary auditory cortex (AI) of the Mongolian gerbil. We used a combination of pharmacological silencing of corticocortically relayed activity and laminar current source density (CSD) analysis. Our data demonstrate that with increasing stimulus intensities progressively lower frequencies lead to the maximal impulse response within cortical input layers at a given cortical site inherited from thalamocortical synaptic inputs. We further identified a temporally precise intercolumnar synaptic convergence of early thalamocortical and horizontal corticocortical inputs. Later tone-evoked activity in upper layers showed a preservation of broad tonotopic tuning across sound levels without shifts towards lower frequencies. Synaptic integration within corticocortical circuits may hence contribute to a level-robust representation of auditory information on a neuronal population level in the auditory cortex. PMID:28046062
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.
46 CFR 111.55-3 - Circuit connections.
Code of Federal Regulations, 2011 CFR
2011-10-01
... 46 Shipping 4 2011-10-01 2011-10-01 false Circuit connections. 111.55-3 Section 111.55-3 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) ELECTRICAL ENGINEERING ELECTRIC SYSTEMS-GENERAL REQUIREMENTS Switches § 111.55-3 Circuit connections. The load side of each circuit must be connected to the...
46 CFR 111.55-3 - Circuit connections.
Code of Federal Regulations, 2012 CFR
2012-10-01
... 46 Shipping 4 2012-10-01 2012-10-01 false Circuit connections. 111.55-3 Section 111.55-3 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) ELECTRICAL ENGINEERING ELECTRIC SYSTEMS-GENERAL REQUIREMENTS Switches § 111.55-3 Circuit connections. The load side of each circuit must be connected to the...
46 CFR 111.55-3 - Circuit connections.
Code of Federal Regulations, 2010 CFR
2010-10-01
... 46 Shipping 4 2010-10-01 2010-10-01 false Circuit connections. 111.55-3 Section 111.55-3 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) ELECTRICAL ENGINEERING ELECTRIC SYSTEMS-GENERAL REQUIREMENTS Switches § 111.55-3 Circuit connections. The load side of each circuit must be connected to the...
46 CFR 111.55-3 - Circuit connections.
Code of Federal Regulations, 2013 CFR
2013-10-01
... 46 Shipping 4 2013-10-01 2013-10-01 false Circuit connections. 111.55-3 Section 111.55-3 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) ELECTRICAL ENGINEERING ELECTRIC SYSTEMS-GENERAL REQUIREMENTS Switches § 111.55-3 Circuit connections. The load side of each circuit must be connected to the...
46 CFR 111.55-3 - Circuit connections.
Code of Federal Regulations, 2014 CFR
2014-10-01
... 46 Shipping 4 2014-10-01 2014-10-01 false Circuit connections. 111.55-3 Section 111.55-3 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) ELECTRICAL ENGINEERING ELECTRIC SYSTEMS-GENERAL REQUIREMENTS Switches § 111.55-3 Circuit connections. The load side of each circuit must be connected to the...
Lanore, Frederic; Labrousse, Virginie F; Szabo, Zsolt; Normand, Elisabeth; Blanchet, Christophe; Mulle, Christophe
2012-12-05
The grik2 gene, coding for the kainate receptor subunit GluK2 (formerly GluR6), is associated with autism spectrum disorders and intellectual disability. Here, we tested the hypothesis that GluK2 could play a role in the appropriate maturation of synaptic circuits involved in learning and memory. We show that both the functional and morphological maturation of hippocampal mossy fiber to CA3 pyramidal cell (mf-CA3) synapses is delayed in mice deficient for the GluK2 subunit (GluK2⁻/⁻). In GluK2⁻/⁻ mice this deficit is manifested by a transient reduction in the amplitude of AMPA-EPSCs at a critical time point of postnatal development, whereas the NMDA component is spared. By combining multiple probability peak fluctuation analysis and immunohistochemistry, we have provided evidence that the decreased amplitude reflects a decrease in the quantal size per mf-CA3 synapse and in the number of active synaptic sites. Furthermore, we analyzed the time course of structural maturation of CA3 synapses by confocal imaging of YFP-expressing cells followed by tridimensional (3D) anatomical reconstruction of thorny excrescences and presynaptic boutons. We show that major changes in synaptic structures occur subsequently to the sharp increase in synaptic transmission, and more importantly that the course of structural maturation of synaptic elements is impaired in GluK2⁻/⁻ mice. This study highlights how a mutation in a gene linked to intellectual disability in the human may lead to a transient reduction of synaptic strength during postnatal development, impacting on the proper formation of neural circuits linked to memory.
Cahill, Michael E.; Bagot, Rosemary C.; Gancarz, Amy M.; Walker, Deena M.; Sun, HaoSheng; Wang, Zi-Jun; Heller, Elizabeth A.; Feng, Jian; Kennedy, Pamela J.; Koo, Ja Wook; Cates, Hannah M.; Neve, Rachael L.; Shen, Li; Dietz, David M.
2016-01-01
Summary Dendritic spines are the sites of most excitatory synapses in the CNS, and opposing alterations in the synaptic structure of medium spiny neurons (MSNs) of the nucleus accumbens, a primary brain reward region, are seen at early vs. late time points after cocaine administration. Here we investigate the time-dependent molecular and biochemical processes that regulate this bidirectional synaptic structural plasticity of NAc MSNs and associated changes in cocaine reward in response to chronic cocaine exposure. Our findings reveal key roles for the bidirectional synaptic expression of the Rap1b small GTPase and an associated local-synaptic protein translation network in this process. The transcriptional mechanisms and pathway-specific inputs to NAc that regulate Rap1b expression are also characterized. Collectively, these findings provide a precise mechanism by which nuclear to synaptic interactions induce “metaplasticity” in NAc MSNs, and we reveal the specific effects of this plasticity on reward behavior in a brain circuit-specific manner. PMID:26844834
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
High density printed electrical circuit board card connection system
Baumbaugh, Alan E.
1997-01-01
A zero insertion/extraction force printed circuit board card connection system comprises a cam-operated locking mechanism disposed along an edge portion of the printed circuit board. The extrusions along the circuit board mate with an extrusion fixed to the card cage having a plurality of electrical connectors. The card connection system allows the connectors to be held away from the circuit board during insertion/extraction and provides a constant mating force once the circuit board is positioned. The card connection system provides a simple solution to the need for a greater number of electrical signal connections.
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.
Exploring the Nature of Cortical Recurrent Interactions
NASA Astrophysics Data System (ADS)
Morita, Kenji; Kalra, Rita; Aihara, Kazuyuki; Robinson, Hugh P. C.
2011-09-01
Fast rhythmic activity of neural population has been frequently observed in cortical circuits, and suggested to be associated with various cognitive functions including working memory and selective attention. However, precisely how recurrent synaptic interactions, that are prominent in these circuits, shape and/or modulate such population rhythm has not been fully elucidated. We have addressed this issue by combining electrophysiological and computational approaches.
Netrin-G1 regulates fear-like and anxiety-like behaviors in dissociable neural circuits.
Zhang, Qi; Sano, Chie; Masuda, Akira; Ando, Reiko; Tanaka, Mika; Itohara, Shigeyoshi
2016-06-27
In vertebrate mammals, distributed neural circuits in the brain are involved in emotion-related behavior. Netrin-G1 is a glycosyl-phosphatidylinositol-anchored synaptic adhesion molecule whose deficiency results in impaired fear-like and anxiety-like behaviors under specific circumstances. To understand the cell type and circuit specificity of these responses, we generated netrin-G1 conditional knockout mice with loss of expression in cortical excitatory neurons, inhibitory neurons, or thalamic neurons. Genetic deletion of netrin-G1 in cortical excitatory neurons resulted in altered anxiety-like behavior, but intact fear-like behavior, whereas loss of netrin-G1 in inhibitory neurons resulted in attenuated fear-like behavior, but intact anxiety-like behavior. These data indicate a remarkable double dissociation of fear-like and anxiety-like behaviors involving netrin-G1 in excitatory and inhibitory neurons, respectively. Our findings support a crucial role for netrin-G1 in dissociable neural circuits for the modulation of emotion-related behaviors, and provide genetic models for investigating the mechanisms underlying the dissociation. The results also suggest the involvement of glycosyl-phosphatidylinositol-anchored synaptic adhesion molecules in the development and pathogenesis of emotion-related behavior.
Zhou, Mu; Liang, Feixue; Xiong, Xiaorui R.; Li, Lu; Li, Haifu; Xiao, Zhongju; Tao, Huizhong W.; Zhang, Li I.
2014-01-01
Cortical sensory processing is modulated by behavioral and cognitive states. How the modulation is achieved through impacting synaptic circuits remains largely unknown. In awake mouse auditory cortex, we reported that sensory-evoked spike responses of layer 2/3 (L2/3) excitatory cells were scaled down with preserved sensory tuning when animals transitioned from quiescence to active behaviors, while L4 and thalamic responses were unchanged. Whole-cell voltage-clamp recordings further revealed that tone-evoked synaptic excitation and inhibition exhibited a robust functional balance. Changes of behavioral state caused scaling down of excitation and inhibition at an approximately equal level in L2/3 cells, but no synaptic changes in L4 cells. This laminar-specific gain control could be attributed to an enhancement of L1–mediated inhibitory tone, with L2/3 parvalbumin inhibitory neurons suppressed as well. Thus, L2/3 circuits can adjust the salience of output in accordance with momentary behavioral demands while maintaining the sensitivity and quality of sensory processing. PMID:24747575
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
Linear summation of outputs in a balanced network model of motor cortex
Capaday, Charles; van Vreeswijk, Carl
2015-01-01
Given the non-linearities of the neural circuitry's elements, we would expect cortical circuits to respond non-linearly when activated. Surprisingly, when two points in the motor cortex are activated simultaneously, the EMG responses are the linear sum of the responses evoked by each of the points activated separately. Additionally, the corticospinal transfer function is close to linear, implying that the synaptic interactions in motor cortex must be effectively linear. To account for this, here we develop a model of motor cortex composed of multiple interconnected points, each comprised of reciprocally connected excitatory and inhibitory neurons. We show how non-linearities in neuronal transfer functions are eschewed by strong synaptic interactions within each point. Consequently, the simultaneous activation of multiple points results in a linear summation of their respective outputs. We also consider the effects of reduction of inhibition at a cortical point when one or more surrounding points are active. The network response in this condition is linear over an approximately two- to three-fold decrease of inhibitory feedback strength. This result supports the idea that focal disinhibition allows linear coupling of motor cortical points to generate movement related muscle activation patterns; albeit with a limitation on gain control. The model also explains why neural activity does not spread as far out as the axonal connectivity allows, whilst also explaining why distant cortical points can be, nonetheless, functionally coupled by focal disinhibition. Finally, we discuss the advantages that linear interactions at the cortical level afford to motor command synthesis. PMID:26097452
Eisele, Yvonne S; Duyckaerts, Charles
2016-01-01
In brains of patients with Alzheimer's disease (AD), Aβ peptides accumulate in parenchyma and, almost invariably, also in the vascular walls. Although Aβ aggregation is, by definition, present in AD, its impact is only incompletely understood. It occurs in a stereotypical spatiotemporal distribution within neuronal networks in the course of the disease. This suggests a role for synaptic connections in propagating Aβ pathology, and possibly of axonal transport in an antero- or retrograde way-although, there is also evidence for passive, extracellular diffusion. Striking, in AD, is the conjunction of tau and Aβ pathology. Tau pathology in the cell body of neurons precedes Aβ deposition in their synaptic endings in several circuits such as the entorhino-dentate, cortico-striatal or subiculo-mammillary connections. However, genetic evidence suggests that Aβ accumulation is the first step in AD pathogenesis. To model the complexity and consequences of Aβ aggregation in vivo, various transgenic (tg) rodents have been generated. In rodents tg for the human Aβ precursor protein, focal injections of preformed Aβ aggregates can induce Aβ deposits in the vicinity of the injection site, and over time in more distant regions of the brain. This suggests that Aβ shares with α-synuclein, tau and other proteins the property to misfold and aggregate homotypic molecules. We propose to group those proteins under the term "propagons". Propagons may lack the infectivity of prions. We review findings from neuropathological examinations of human brains in different stages of AD and from studies in rodent models of Aβ aggregation and discuss putative mechanisms underlying the initiation and spread of Aβ pathology.
Pinto, Aline; Fuentes, Cesar; Paré, Denis
2006-04-20
The rhinal cortices constitute the main route for impulse traffic to and from the hippocampus. Tracing studies have revealed that the perirhinal cortex forms strong reciprocal connections with the neo- and entorhinal cortex (EC). However, physiological investigations indicate that perirhinal transmission of neocortical and EC inputs occurs with a low probability. In search of an explanation for these contradictory findings, we have analyzed synaptic connections in this network by combining injections of the anterograde tracer Phaseolus vulgaris-leucoagglutinin (PHAL) into the neocortex, area 36, or area 35 with gamma-aminobutyric acid (GABA) immunocytochemistry and electron microscopic observations. Within area 36, neocortical axon terminals formed only asymmetric synapses, usually with GABA-negative spines (87%), and less frequently with GABA-immunopositive (GABA+) dendrites (13%). A similar synaptic distribution was observed within area 35 except that asymmetric synapses onto GABA+ dendrites were more frequent (23% of synapses). Examination of the projections from area 36 to area 35 and from both regions to the EC revealed an even higher incidence of asymmetric synapses onto GABA+ dendrites (35 and 32%, respectively) than what was observed in the neocortical projection to areas 36 and 35. Furthermore, some of the neocortical and perirhinal terminals containing PHAL and GABA immunolabeling formed symmetric synapses onto GABA-negative dendrites in their projection sites (neocortex to area 35, 16%; area 36 to 35, 7%; areas 36-35 to EC, 12%). Taken together, these findings suggest that impulse transmission through the rhinal circuit is subjected to strong inhibitory influences, reconciling anatomical and physiological data about this network.
Pinto, Aline; Fuentes, Cesar; Paré, Denis
2008-01-01
The rhinal cortices constitute the main route for impulse traffic to and from the hippocampus. Tracing studies have revealed that the perirhinal cortex forms strong reciprocal connections with the neo- and entorhinal cortex (EC). Yet, physiological investigations indicate that perirhinal transmission of neocortical and EC inputs occurs with a low probability. In search of an explanation for these contradictory findings, we have analyzed synaptic connections in this network by combining injections of the anterograde tracer Phaseolus vulgaris-leucoagglutinin (PHAL) into the neocortex, area 36, or area 35 with GABA immunocytochemistry and electron microscopic observations. Within area 36, neocortical axon terminals formed only asymmetric synapses, usually with GABA negative spines (87%), and less frequently with GABA immunopositive (GABA+) dendrites (13%). A similar synaptic distribution was observed within area 35 except that asymmetric synapses onto GABA+ dendrites were more frequent (23% of synapses). Examination of the projections from area 36 to area 35 and from both regions to the EC revealed an even higher incidence of asymmetric synapses onto GABA+ dendrites (35% and 32% respectively) than what was observed in the neocortical projection to areas 36 and 35. Furthermore, a proportion of neocortical and perirhinal terminals containing PHAL and GABA immunolabeling formed symmetric synapses onto GABA negative dendrites in their projection sites (neocortex to area 35, 16%; area 36 to 35, 7%; areas 36–35 to EC, 12%). Taken together, these findings suggest that impulse transmission through the rhinal circuit is subjected to strong inhibitory influences, reconciling anatomical and physiological data about this network. PMID:16506192
Gentet, Luc J; Ulrich, Daniel
2003-02-01
The thalamic reticular nucleus (nRT) is composed entirely of GABAergic inhibitory neurones that receive input from pyramidal cortical neurones and excitatory relay cells of the ventrobasal complex of the thalamus (VB). It plays a major role in the synchrony of thalamic networks, yet the synaptic connections it receives from VB cells have never been fully physiologically characterised. Here, whole-cell current-clamp recordings were obtained from 22 synaptically connected VB-nRT cell pairs in slices of juvenile (P14-20) rats. At 34-36 degrees C, single presynaptic APs evoked unitary EPSPs in nRT cells with a peak amplitude of 7.4 +/- 1.5 mV (mean +/- S.E.M.) and a decay time constant of 15.1 +/- 0.9 ms. Only four out of 22 pairs showed transmission failures at a mean rate of 6.8 +/- 1.1 %. An NMDA receptor (NMDAR)-mediated component was significant at rest and subsequent EPSPs in a train were depressed. Only one out of 14 pairs tested was reciprocally connected; the observed IPSPs in the VB cell had a peak amplitude of 0.8 mV and were completely abolished in the presence of 10 microM bicuculline. Thus, synaptic connections from VB cells to nRT neurones are mainly 'drivers', while a small subset of cells form closed disynaptic loops.
Lai, Jih-Sheng; Liu, Changrong; Ridenour, Amy
2009-04-14
DC/DC converter has a transformer having primary coils connected to an input side and secondary coils connected to an output side. Each primary coil connects a full-bridge circuit comprising two switches on two legs, the primary coil being connected between the switches on each leg, each full-bridge circuit being connected in parallel wherein each leg is disposed parallel to one another, and the secondary coils connected to a rectifying circuit. An outer loop control circuit that reduces ripple in a voltage reference has a first resistor connected in series with a second resistor connected in series with a first capacitor which are connected in parallel with a second capacitor. An inner loop control circuit that reduces ripple in a current reference has a third resistor connected in series with a fourth resistor connected in series with a third capacitor which are connected in parallel with a fourth capacitor.
Cohen, Laurie D.; Zuchman, Rina; Sorokina, Oksana; Müller, Anke; Dieterich, Daniela C.; Armstrong, J. Douglas; Ziv, Tamar; Ziv, Noam E.
2013-01-01
Chemical synapses contain multitudes of proteins, which in common with all proteins, have finite lifetimes and therefore need to be continuously replaced. Given the huge numbers of synaptic connections typical neurons form, the demand to maintain the protein contents of these connections might be expected to place considerable metabolic demands on each neuron. Moreover, synaptic proteostasis might differ according to distance from global protein synthesis sites, the availability of distributed protein synthesis facilities, trafficking rates and synaptic protein dynamics. To date, the turnover kinetics of synaptic proteins have not been studied or analyzed systematically, and thus metabolic demands or the aforementioned relationships remain largely unknown. In the current study we used dynamic Stable Isotope Labeling with Amino acids in Cell culture (SILAC), mass spectrometry (MS), Fluorescent Non–Canonical Amino acid Tagging (FUNCAT), quantitative immunohistochemistry and bioinformatics to systematically measure the metabolic half-lives of hundreds of synaptic proteins, examine how these depend on their pre/postsynaptic affiliation or their association with particular molecular complexes, and assess the metabolic load of synaptic proteostasis. We found that nearly all synaptic proteins identified here exhibited half-lifetimes in the range of 2–5 days. Unexpectedly, metabolic turnover rates were not significantly different for presynaptic and postsynaptic proteins, or for proteins for which mRNAs are consistently found in dendrites. Some functionally or structurally related proteins exhibited very similar turnover rates, indicating that their biogenesis and degradation might be coupled, a possibility further supported by bioinformatics-based analyses. The relatively low turnover rates measured here (∼0.7% of synaptic protein content per hour) are in good agreement with imaging-based studies of synaptic protein trafficking, yet indicate that the metabolic load synaptic protein turnover places on individual neurons is very substantial. PMID:23658807
Spinal Endocannabinoids and CB1 Receptors Mediate C-Fiber-Induced Heterosynaptic Pain Plasticity
Pernía-Andrade, Alejandro J.; Kato, Ako; Witschi, Robert; Nyilas, Rita; Katona, István; Freund, Tamás F.; Watanabe, Masahiko; Filitz, Jörg; Koppert, Wolfgang; Schüttler, Jürgen; Ji, Guangchen; Neugebauer, Volker; Marsicano, Giovanni; Lutz, Beat; Vanegas, Horacio; Zeilhofer, Hanns Ulrich
2010-01-01
Diminished synaptic inhibition in the spinal dorsal horn is a major contributor to chronic pain. Pathways, which reduce synaptic inhibition in inflammatory and neuropathic pain states, have been identified, but central hyperalgesia and diminished dorsal horn synaptic inhibition also occur in the absence of inflammation or neuropathy, solely triggered by intense nociceptive (C–fiber) input to the spinal dorsal horn. We found that endocannabinoids produced upon strong nociceptive stimulation activated CB1 receptors on inhibitory dorsal horn neurons to reduce the synaptic release of GABA and glycine and thus rendered nociceptive neurons excitable by non-painful stimuli. Spinal endocannabinoids and CB1 receptors on inhibitory dorsal horn interneurons act as mediators of heterosynaptic pain sensitization and play an unexpected role in dorsal horn pain controlling circuits. PMID:19661434
Dendritic protein synthesis in the normal and diseased brain
Swanger, Sharon A.; Bassell, Gary J.
2015-01-01
Synaptic activity is a spatially-limited process that requires a precise, yet dynamic, complement of proteins within the synaptic micro-domain. The maintenance and regulation of these synaptic proteins is regulated, in part, by local mRNA translation in dendrites. Protein synthesis within the postsynaptic compartment allows neurons tight spatial and temporal control of synaptic protein expression, which is critical for proper functioning of synapses and neural circuits. In this review, we discuss the identity of proteins synthesized within dendrites, the receptor-mediated mechanisms regulating their synthesis, and the possible roles for these locally synthesized proteins. We also explore how our current understanding of dendritic protein synthesis in the hippocampus can be applied to new brain regions and to understanding the pathological mechanisms underlying varied neurological diseases. PMID:23262237
Transgenic FingRs for Live Mapping of Synaptic Dynamics in Genetically-Defined Neurons
Son, Jong-Hyun; Keefe, Matthew D.; Stevenson, Tamara J.; Barrios, Joshua P.; Anjewierden, Scott; Newton, James B.; Douglass, Adam D.; Bonkowsky, Joshua L.
2016-01-01
Tools for genetically-determined visualization of synaptic circuits and interactions are necessary to build connectomics of the vertebrate brain and to screen synaptic properties in neurological disease models. Here we develop a transgenic FingR (fibronectin intrabodies generated by mRNA display) technology for monitoring synapses in live zebrafish. We demonstrate FingR labeling of defined excitatory and inhibitory synapses, and show FingR applicability for dissecting synapse dynamics in normal and disease states. Using our system we show that chronic hypoxia, associated with neurological defects in preterm birth, affects dopaminergic neuron synapse number depending on the developmental timing of hypoxia. PMID:26728131
Balsters, Joshua H; Mantini, Dante; Wenderoth, Nicole
2018-04-15
Autism Spectrum Disorder (ASD) has been associated with abnormal synaptic development causing a breakdown in functional connectivity. However, when measured at the macro scale using resting state fMRI, these alterations are subtle and often difficult to detect due to the large heterogeneity of the pathology. Recently, we outlined a novel approach for generating robust biomarkers of resting state functional magnetic resonance imaging (RS-fMRI) using connectivity based parcellation of gross morphological structures to improve single-subject reproducibility and generate more robust connectivity fingerprints. Here we apply this novel approach to investigating the organization and connectivity strength of the cortico-striatal system in a large sample of ASD individuals and typically developed (TD) controls (N=130 per group). Our results showed differences in the parcellation of the striatum in ASD. Specifically, the putamen was found to be one single structure in ASD, whereas this was split into anterior and posterior segments in an age, IQ, and head movement matched TD group. An analysis of the connectivity fingerprints revealed that the group differences in clustering were driven by differential connectivity between striatum and the supplementary motor area, posterior cingulate cortex, and posterior insula. Our approach for analysing RS-fMRI in clinical populations has provided clear evidence that cortico-striatal circuits are organized differently in ASD. Based on previous task-based segmentations of the striatum, we believe that the anterior putamen cluster present in TD, but not in ASD, likely contributes to social and language processes. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.
Le Bé, Jean-Vincent; Silberberg, Gilad; Wang, Yun; Markram, Henry
2007-09-01
Neocortical pyramidal cells (PCs) project to various cortical and subcortical targets. In layer V, the population of thick tufted PCs (TTCs) projects to subcortical targets such as the tectum, brainstem, and spinal cord. Another population of layer V PCs projects via the corpus callosum to the contralateral neocortical hemisphere mediating information transfer between the hemispheres. This subpopulation (corticocallosally projecting cells [CCPs]) has been previously described in terms of their morphological properties, but less is known about their electrophysiological properties, and their synaptic connectivity is unknown. We studied the morphological, electrophysiological, and synaptic properties of CCPs by retrograde labeling with fluorescent microbeads in P13-P16 Wistar rats. CCPs were characterized by shorter, untufted apical dendrites, which reached only up to layers II/III, confirming previous reports. Synaptic connections between CCPs were different from those observed between TTCs, both in probability of occurrence and dynamic properties. We found that the CCP network is about 4 times less interconnected than the TTC network and the probability of release is 24% smaller, resulting in a more linear synaptic transmission. The study shows that layer V pyramidal neurons projecting to different targets form subnetworks with specialized connectivity profiles, in addition to the specialized morphological and electrophysiological intrinsic properties.
Patrick, Gentry N
2006-02-01
The formation of synaptic connections during the development of the nervous system requires the precise targeting of presynaptic and postsynaptic compartments. Furthermore, synapses are continually modified in the brain by experience. Recently, the ubiquitin proteasome system has emerged as a key regulator of synaptic development and function. The modification of proteins by ubiquitin, and in many cases their subsequent proteasomal degradation, has proven to be an important mechanism to control protein stability, activity and localization at synapses. Recent work has highlighted key questions of the UPS during the development and remodeling of synaptic connections in the nervous system.
Glutamatergic synaptic plasticity in the mesocorticolimbic system in addiction
van Huijstee, Aile N.; Mansvelder, Huibert D.
2015-01-01
Addictive drugs remodel the brain’s reward circuitry, the mesocorticolimbic dopamine (DA) system, by inducing widespread adaptations of glutamatergic synapses. This drug-induced synaptic plasticity is thought to contribute to both the development and the persistence of addiction. This review highlights the synaptic modifications that are induced by in vivo exposure to addictive drugs and describes how these drug-induced synaptic changes may contribute to the different components of addictive behavior, such as compulsive drug use despite negative consequences and relapse. Initially, exposure to an addictive drug induces synaptic changes in the ventral tegmental area (VTA). This drug-induced synaptic potentiation in the VTA subsequently triggers synaptic changes in downstream areas of the mesocorticolimbic system, such as the nucleus accumbens (NAc) and the prefrontal cortex (PFC), with further drug exposure. These glutamatergic synaptic alterations are then thought to mediate many of the behavioral symptoms that characterize addiction. The later stages of glutamatergic synaptic plasticity in the NAc and in particular in the PFC play a role in maintaining addiction and drive relapse to drug-taking induced by drug-associated cues. Remodeling of PFC glutamatergic circuits can persist into adulthood, causing a lasting vulnerability to relapse. We will discuss how these neurobiological changes produced by drugs of abuse may provide novel targets for potential treatment strategies for addiction. PMID:25653591
Gutierrez, Gabrielle J; O'Leary, Timothy; Marder, Eve
2013-03-06
Rhythmic oscillations are common features of nervous systems. One of the fundamental questions posed by these rhythms is how individual neurons or groups of neurons are recruited into different network oscillations. We modeled competing fast and slow oscillators connected to a hub neuron with electrical and inhibitory synapses. We explore the patterns of coordination shown in the network as a function of the electrical coupling and inhibitory synapse strengths with the help of a novel visualization method that we call the "parameterscape." The hub neuron can be switched between the fast and slow oscillators by multiple network mechanisms, indicating that a given change in network state can be achieved by degenerate cellular mechanisms. These results have importance for interpreting experiments employing optogenetic, genetic, and pharmacological manipulations to understand circuit dynamics. Copyright © 2013 Elsevier Inc. All rights reserved.
Neuronal replacement therapy: previous achievements and challenges ahead
NASA Astrophysics Data System (ADS)
Grade, Sofia; Götz, Magdalena
2017-10-01
Lifelong neurogenesis and incorporation of newborn neurons into mature neuronal circuits operates in specialized niches of the mammalian brain and serves as role model for neuronal replacement strategies. However, to which extent can the remaining brain parenchyma, which never incorporates new neurons during the adulthood, be as plastic and readily accommodate neurons in networks that suffered neuronal loss due to injury or neurological disease? Which microenvironment is permissive for neuronal replacement and synaptic integration and which cells perform best? Can lost function be restored and how adequate is the participation in the pre-existing circuitry? Could aberrant connections cause malfunction especially in networks dominated by excitatory neurons, such as the cerebral cortex? These questions show how important connectivity and circuitry aspects are for regenerative medicine, which is the focus of this review. We will discuss the impressive advances in neuronal replacement strategies and success from exogenous as well as endogenous cell sources. Both have seen key novel technologies, like the groundbreaking discovery of induced pluripotent stem cells and direct neuronal reprogramming, offering alternatives to the transplantation of fetal neurons, and both herald great expectations. For these to become reality, neuronal circuitry analysis is key now. As our understanding of neuronal circuits increases, neuronal replacement therapy should fulfill those prerequisites in network structure and function, in brain-wide input and output. Now is the time to incorporate neural circuitry research into regenerative medicine if we ever want to truly repair brain injury.
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
NASA Technical Reports Server (NTRS)
Chang, T. N.; Keshishian, H.
1996-01-01
We have tested the effects of neuromuscular denervation in Drosophila by laser-ablating the RP motoneurons in intact embryos before synaptogenesis. We examined the consequences of this ablation on local synaptic connectivity in both 1st and 3rd instar larvae. We find that the partial or complete loss of native innervation correlates with the appearance of alternate inputs from neighboring motor endings and axons. These collateral inputs are found at ectopic sites on the denervated target muscle fibers. The foreign motor endings are electrophysiologically functional and are observed on the denervated muscle fibers by the 1st instar larval stage. Our data are consistent with the existence of a local signal from the target environment, which is regulated by innervation and influences synaptic connectivity. Our results show that, despite the stereotypy of Drosophila neuromuscular connections, denervation can induce local changes in connectivity in wild-type Drosophila, suggesting that mechanisms of synaptic plasticity may also be involved in normal Drosophila neuromuscular development.
Lajoie, Guillaume; Krouchev, Nedialko I; Kalaska, John F; Fairhall, Adrienne L; Fetz, Eberhard E
2017-02-01
Experiments show that spike-triggered stimulation performed with Bidirectional Brain-Computer-Interfaces (BBCI) can artificially strengthen connections between separate neural sites in motor cortex (MC). When spikes from a neuron recorded at one MC site trigger stimuli at a second target site after a fixed delay, the connections between sites eventually strengthen. It was also found that effective spike-stimulus delays are consistent with experimentally derived spike-timing-dependent plasticity (STDP) rules, suggesting that STDP is key to drive these changes. However, the impact of STDP at the level of circuits, and the mechanisms governing its modification with neural implants remain poorly understood. The present work describes a recurrent neural network model with probabilistic spiking mechanisms and plastic synapses capable of capturing both neural and synaptic activity statistics relevant to BBCI conditioning protocols. Our model successfully reproduces key experimental results, both established and new, and offers mechanistic insights into spike-triggered conditioning. Using analytical calculations and numerical simulations, we derive optimal operational regimes for BBCIs, and formulate predictions concerning the efficacy of spike-triggered conditioning in different regimes of cortical activity.
Lajoie, Guillaume; Kalaska, John F.; Fairhall, Adrienne L.; Fetz, Eberhard E.
2017-01-01
Experiments show that spike-triggered stimulation performed with Bidirectional Brain-Computer-Interfaces (BBCI) can artificially strengthen connections between separate neural sites in motor cortex (MC). When spikes from a neuron recorded at one MC site trigger stimuli at a second target site after a fixed delay, the connections between sites eventually strengthen. It was also found that effective spike-stimulus delays are consistent with experimentally derived spike-timing-dependent plasticity (STDP) rules, suggesting that STDP is key to drive these changes. However, the impact of STDP at the level of circuits, and the mechanisms governing its modification with neural implants remain poorly understood. The present work describes a recurrent neural network model with probabilistic spiking mechanisms and plastic synapses capable of capturing both neural and synaptic activity statistics relevant to BBCI conditioning protocols. Our model successfully reproduces key experimental results, both established and new, and offers mechanistic insights into spike-triggered conditioning. Using analytical calculations and numerical simulations, we derive optimal operational regimes for BBCIs, and formulate predictions concerning the efficacy of spike-triggered conditioning in different regimes of cortical activity. PMID:28151957
Symmetry Breaking in Space-Time Hierarchies Shapes Brain Dynamics and Behavior.
Pillai, Ajay S; Jirsa, Viktor K
2017-06-07
In order to maintain brain function, neural activity needs to be tightly coordinated within the brain network. How this coordination is achieved and related to behavior is largely unknown. It has been previously argued that the study of the link between brain and behavior is impossible without a guiding vision. Here we propose behavioral-level concepts and mechanisms embodied as structured flows on manifold (SFM) that provide a formal description of behavior as a low-dimensional process emerging from a network's dynamics dependent on the symmetry and invariance properties of the network connectivity. Specifically, we demonstrate that the symmetry breaking of network connectivity constitutes a timescale hierarchy resulting in the emergence of an attractive functional subspace. We show that behavior emerges when appropriate conditions imposed upon the couplings are satisfied, justifying the conductance-based nature of synaptic couplings. Our concepts propose design principles for networks predicting how behavior and task rules are represented in real neural circuits and open new avenues for the analyses of neural data. Copyright © 2017 Elsevier Inc. All rights reserved.
Mechanisms of physiological and epileptic HFO generation
Jefferys, John G.R.; de la Prida, Liset Menendez; Wendling, Fabrice; Bragin, Anatol; Avoli, Massimo; Timofeev, Igor; Lopes da Silva, Fernando H.
2016-01-01
High frequency oscillations (HFO) have a variety of characteristics: band-limited or broad-band, transient burst-like phenomenon or steady-state. HFOs may be encountered under physiological or under pathological conditions (pHFO). Here we review the underlying mechanisms of oscillations, at the level of cells and networks, investigated in a variety of experimental in vitro and in vivo models. Diverse mechanisms are described, from intrinsic membrane oscillations to network processes involving different types of synaptic interactions, gap junctions and ephaptic coupling. HFOs with similar frequency ranges can differ considerably in their physiological mechanisms. The fact that in most cases the combination of intrinsic neuronal membrane oscillations and synaptic circuits are necessary to sustain network oscillations is emphasized. Evidence for pathological HFOs, particularly fast ripples, in experimental models of epilepsy and in human epileptic patients is scrutinized. The underlying mechanisms of fast ripples are examined both in the light of animal observations, in vivo and in vitro, and in epileptic patients, with emphasis on single cell dynamics. Experimental observations and computational modeling have led to hypotheses for these mechanisms, several of which are considered here, namely the role of out-of-phase firing in neuronal clusters, the importance of strong excitatory AMPA-synaptic currents and recurrent inhibitory connectivity in combination with the fast time scales of IPSPs, ephaptic coupling and the contribution of interneuronal coupling through gap junctions. The statistical behaviour of fast ripple events can provide useful information on the underlying mechanism and can help to further improve classification of the diverse forms of HFOs. PMID:22420980
Transcriptional control of behavior: Engrailed knockout changes cockroach escape trajectories
Booth, David; Marie, Bruno; Domenici, Paolo; Blagburn, Jonathan M; Bacon, Jonathan P
2009-01-01
The cerci of the cockroach are covered with identified sensory hairs, which detect air movements. The sensory neurons which innervate these hairs synapse with giant interneurons (GIs) in the terminal ganglion which in turn synapse with interneurons and leg motorneurons in thoracic ganglia. This neural circuit mediates the animal's escape behavior. The transcription factor Engrailed (En) is expressed only in the medially born sensory neurons, which suggested it could work as a positional determinant of sensory neuron identity. Previously, we used dsRNA interference to abolish En expression, and found that the axonal arborization and synaptic outputs of an identified En-positive sensory neuron changed so that it came to resemble a nearby En-negative cell, which was itself unaffected. We thus demonstrated directly that En controls synaptic choice, as well as axon projections. Is escape behavior affected as a result of this mis-wiring? We recently showed that adult cockroaches keep each escape unpredictable by running along one of a set of preferred escape trajectories (ETs) at fixed angles from the direction of the threatening stimulus. The probability of selecting a particular ET is influenced by wind direction. In this present study we show that early instar juvenile cockroaches also use those same ETs. En knockout significantly perturbs the animals' perception of posterior wind, altering the choice of ETs to one more appropriate for anterior wind. This is the first time that it has been shown that knockout of a transcription factor controlling synaptic connectivity can alter the perception of a directional stimulus. PMID:19494140
2009-01-01
A breakthrough for studying the neuronal basis of learning emerged when invertebrates with simple nervous systems, such as the sea slug Hermissenda crassicornis, were shown to exhibit classical conditioning. Hermissenda learns to associate light with turbulence: prior to learning, naive animals move toward light (phototaxis) and contract their foot in response to turbulence; after learning, conditioned animals delay phototaxis in response to light. The photoreceptors of the eye, which receive monosynaptic inputs from statocyst hair cells, are both sensory neurons and the first site of sensory convergence. The memory of light associated with turbulence is stored as changes in intrinsic and synaptic currents in these photoreceptors. The subcellular mechanisms producing these changes include activation of protein kinase C and MAP kinase, which act as coincidence detectors because they are activated by convergent signaling pathways. Pathways of interneurons and motorneurons, where additional changes in excitability and synaptic connections are found, contribute to delayed phototaxis. Bursting activity recorded at several points suggest the existence of small networks that produce complex spatio-temporal firing patterns. Thus, the change in behavior may be produced by a non-linear transformation of spatio-temporal firing patterns caused by plasticity of synaptic and intrinsic channels. The change in currents and the activation of PKC and MAPK produced by associative learning are similar to that observed in hippocampal and cerebellar neurons after rabbit classical conditioning, suggesting that these represent general mechanisms of memory storage. Thus, the knowledge gained from further study of Hermissenda will continue to illuminate mechanisms of mammalian learning. PMID:16437555
Spontaneously emerging direction selectivity maps in visual cortex through STDP.
Wenisch, Oliver G; Noll, Joachim; Hemmen, J Leo van
2005-10-01
It is still an open question as to whether, and how, direction-selective neuronal responses in primary visual cortex are generated by feedforward thalamocortical or recurrent intracortical connections, or a combination of both. Here we present an investigation that concentrates on and, only for the sake of simplicity, restricts itself to intracortical circuits, in particular, with respect to the developmental aspects of direction selectivity through spike-timing-dependent synaptic plasticity. We show that directional responses can emerge in a recurrent network model of visual cortex with spiking neurons that integrate inputs mainly from a particular direction, thus giving rise to an asymmetrically shaped receptive field. A moving stimulus that enters the receptive field from this (preferred) direction will activate a neuron most strongly because of the increased number and/or strength of inputs from this direction and since delayed isotropic inhibition will neither overlap with, nor cancel excitation, as would be the case for other stimulus directions. It is demonstrated how direction-selective responses result from spatial asymmetries in the distribution of synaptic contacts or weights of inputs delivered to a neuron by slowly conducting intracortical axonal delay lines. By means of spike-timing-dependent synaptic plasticity with an asymmetric learning window this kind of coupling asymmetry develops naturally in a recurrent network of stochastically spiking neurons in a scenario where the neurons are activated by unidirectionally moving bar stimuli and even when only intrinsic spontaneous activity drives the learning process. We also present simulation results to show the ability of this model to produce direction preference maps similar to experimental findings.
Synaptic physiology of the flow of information in the cat's visual cortex in vivo
Hirsch, Judith A; Martinez, Luis M; Alonso, José-Manuel; Desai, Komal; Pillai, Cinthi; Pierre, Carhine
2002-01-01
Each stage of the striate cortical circuit extracts novel information about the visual environment. We asked if this analytic process reflected laminar variations in synaptic physiology by making whole-cell recording with dye-filled electrodes from the cat's visual cortex and thalamus; the stimuli were flashed spots. Thalamic afferents terminate in layer 4, which contains two types of cell, simple and complex, distinguished by the spatial structure of the receptive field. Previously, we had found that the postsynaptic and spike responses of simple cells reliably followed the time course of flash-evoked thalamic activity. Here we report that complex cells in layer 4 (or cells intermediate between simple and complex) similarly reprised thalamic activity (response/trial, 99 ± 1.9 %; response duration 159 ± 57 ms; latency 25 ± 4 ms; average ± standard deviation; n = 7). Thus, all cells in layer 4 share a common synaptic physiology that allows secure integration of thalamic input. By contrast, at the second cortical stage (layer 2+3), where layer 4 directs its output, postsynaptic responses did not track simple patterns of antecedent activity. Typical responses to the static stimulus were intermittent and brief (response/trial, 31 ± 40 %; response duration 72 ± 60 ms, latency 39 ± 7 ms; n = 11). Only richer stimuli like those including motion evoked reliable responses. All told, the second level of cortical processing differs markedly from the first. At that later stage, ascending information seems strongly gated by connections between cortical neurons. Inputs must be combined in newly specified patterns to influence intracortical stages of processing. PMID:11927691
30 CFR 75.1323 - Blasting circuits.
Code of Federal Regulations, 2010 CFR
2010-07-01
...) Blasting circuits shall be protected from sources of stray electric current. (b) Detonators made by...) Each wire connection in a blasting circuit shall be— (1) Properly spliced; and (2) Separated from other connections in the circuit to prevent accidental contact and arcing. (h) Uninsulated connections in each...
30 CFR 75.1323 - Blasting circuits.
Code of Federal Regulations, 2011 CFR
2011-07-01
...) Blasting circuits shall be protected from sources of stray electric current. (b) Detonators made by...) Each wire connection in a blasting circuit shall be— (1) Properly spliced; and (2) Separated from other connections in the circuit to prevent accidental contact and arcing. (h) Uninsulated connections in each...
New tools for targeted disruption of cholinergic synaptic transmission in Drosophila melanogaster.
Mejia, Monica; Heghinian, Mari D; Marí, Frank; Godenschwege, Tanja A
2013-01-01
Nicotinic acetylcholine receptors (nAChRs) are pentameric ligand-gated ion channels. The α7 subtype of nAChRs is involved in neurological pathologies such as Parkinson's disease, Alzheimer's disease, addiction, epilepsy and autism spectrum disorders. The Drosophila melanogaster α7 (Dα7) has the closest sequence homology to the vertebrate α7 subunit and it can form homopentameric receptors just as the vertebrate counterpart. The Dα7 subunits are essential for the function of the Giant Fiber circuit, which mediates the escape response of the fly. To further characterize the receptor function, we generated different missense mutations in the Dα7 nAChR's ligand binding domain. We characterized the effects of targeted expression of two UAS-constructs carrying a single mutation, D197A and Y195T, as well as a UAS-construct carrying a triple D77T, L117Q, I196P mutation in a Dα7 null mutant and in a wild type background. Expression of the triple mutation was able to restore the function of the circuit in Dα7 null mutants and had no disruptive effects when expressed in wild type. In contrast, both single mutations severely disrupted the synaptic transmission of Dα7-dependent but not glutamatergic or gap junction dependent synapses in wild type background, and did not or only partially rescued the synaptic defects of the null mutant. These observations are consistent with the formation of hybrid receptors, consisting of D197A or Y195T subunits and wild type Dα7 subunits, in which the binding of acetylcholine or acetylcholine-induced conformational changes of the Dα7 receptor are altered and causes inhibition of cholinergic responses. Thus targeted expression of D197A or Y195T can be used to selectively disrupt synaptic transmission of Dα7-dependent synapses in neuronal circuits. Hence, these constructs can be used as tools to study learning and memory or addiction associated behaviors by allowing the manipulation of neuronal processing in the circuits without affecting other cellular signaling.
New Tools for Targeted Disruption of Cholinergic Synaptic Transmission in Drosophila melanogaster
Mejia, Monica; Heghinian, Mari D.; Marí, Frank; Godenschwege, Tanja A.
2013-01-01
Nicotinic acetylcholine receptors (nAChRs) are pentameric ligand-gated ion channels. The α7 subtype of nAChRs is involved in neurological pathologies such as Parkinson’s disease, Alzheimer’s disease, addiction, epilepsy and autism spectrum disorders. The Drosophila melanogaster α7 (Dα7) has the closest sequence homology to the vertebrate α7 subunit and it can form homopentameric receptors just as the vertebrate counterpart. The Dα7 subunits are essential for the function of the Giant Fiber circuit, which mediates the escape response of the fly. To further characterize the receptor function, we generated different missense mutations in the Dα7 nAChR’s ligand binding domain. We characterized the effects of targeted expression of two UAS-constructs carrying a single mutation, D197A and Y195T, as well as a UAS-construct carrying a triple D77T, L117Q, I196P mutation in a Dα7 null mutant and in a wild type background. Expression of the triple mutation was able to restore the function of the circuit in Dα7 null mutants and had no disruptive effects when expressed in wild type. In contrast, both single mutations severely disrupted the synaptic transmission of Dα7-dependent but not glutamatergic or gap junction dependent synapses in wild type background, and did not or only partially rescued the synaptic defects of the null mutant. These observations are consistent with the formation of hybrid receptors, consisting of D197A or Y195T subunits and wild type Dα7 subunits, in which the binding of acetylcholine or acetylcholine-induced conformational changes of the Dα7 receptor are altered and causes inhibition of cholinergic responses. Thus targeted expression of D197A or Y195T can be used to selectively disrupt synaptic transmission of Dα7-dependent synapses in neuronal circuits. Hence, these constructs can be used as tools to study learning and memory or addiction associated behaviors by allowing the manipulation of neuronal processing in the circuits without affecting other cellular signaling. PMID:23737994
Siller, Saul S.; Broadie, Kendal
2011-01-01
SUMMARY Fragile X syndrome (FXS), caused by loss of the fragile X mental retardation 1 (FMR1) product (FMRP), is the most common cause of inherited intellectual disability and autism spectrum disorders. FXS patients suffer multiple behavioral symptoms, including hyperactivity, disrupted circadian cycles, and learning and memory deficits. Recently, a study in the mouse FXS model showed that the tetracycline derivative minocycline effectively remediates the disease state via a proposed matrix metalloproteinase (MMP) inhibition mechanism. Here, we use the well-characterized Drosophila FXS model to assess the effects of minocycline treatment on multiple neural circuit morphological defects and to investigate the MMP hypothesis. We first treat Drosophila Fmr1 (dfmr1) null animals with minocycline to assay the effects on mutant synaptic architecture in three disparate locations: the neuromuscular junction (NMJ), clock neurons in the circadian activity circuit and Kenyon cells in the mushroom body learning and memory center. We find that minocycline effectively restores normal synaptic structure in all three circuits, promising therapeutic potential for FXS treatment. We next tested the MMP hypothesis by assaying the effects of overexpressing the sole Drosophila tissue inhibitor of MMP (TIMP) in dfmr1 null mutants. We find that TIMP overexpression effectively prevents defects in the NMJ synaptic architecture in dfmr1 mutants. Moreover, co-removal of dfmr1 similarly rescues TIMP overexpression phenotypes, including cellular tracheal defects and lethality. To further test the MMP hypothesis, we generated dfmr1;mmp1 double null mutants. Null mmp1 mutants are 100% lethal and display cellular tracheal defects, but co-removal of dfmr1 allows adult viability and prevents tracheal defects. Conversely, co-removal of mmp1 ameliorates the NMJ synaptic architecture defects in dfmr1 null mutants, despite the lack of detectable difference in MMP1 expression or gelatinase activity between the single dfmr1 mutants and controls. These results support minocycline as a promising potential FXS treatment and suggest that it might act via MMP inhibition. We conclude that FMRP and TIMP pathways interact in a reciprocal, bidirectional manner. PMID:21669931
Oxide-based synaptic transistors gated by solution-processed gelatin electrolytes
NASA Astrophysics Data System (ADS)
He, Yinke; Sun, Jia; Qian, Chuan; Kong, Ling-An; Gou, Guangyang; Li, Hongjian
2017-04-01
In human brain, a large number of neurons are connected via synapses. Simulation of the synaptic behaviors using electronic devices is the most important step for neuromorphic systems. In this paper, proton conducting gelatin electrolyte-gated oxide field-effect transistors (FETs) were used for emulating synaptic functions, in which the gate electrode is regarded as pre-synaptic neuron and the channel layer as the post-synaptic neuron. In analogy to the biological synapse, a potential spike can be applied at the gate electrode and trigger ionic motion in the gelatin electrolyte, which in turn generates excitatory post-synaptic current (EPSC) in the channel layer. Basic synaptic behaviors including spike time-dependent EPSC, paired-pulse facilitation (PPF), self-adaptation, and frequency-dependent synaptic transmission were successfully mimicked. Such ionic/electronic hybrid devices are beneficial for synaptic electronics and brain-inspired neuromorphic systems.
Radiation Hardened 10BASE-T Ethernet Physical Layer (PHY)
NASA Technical Reports Server (NTRS)
Lin, Michael R. (Inventor); Petrick, David J. (Inventor); Ballou, Kevin M. (Inventor); Espinosa, Daniel C. (Inventor); James, Edward F. (Inventor); Kliesner, Matthew A. (Inventor)
2017-01-01
Embodiments may provide a radiation hardened 10BASE-T Ethernet interface circuit suitable for space flight and in compliance with the IEEE 802.3 standard for Ethernet. The various embodiments may provide a 10BASE-T Ethernet interface circuit, comprising a field programmable gate array (FPGA), a transmitter circuit connected to the FPGA, a receiver circuit connected to the FPGA, and a transformer connected to the transmitter circuit and the receiver circuit. In the various embodiments, the FPGA, transmitter circuit, receiver circuit, and transformer may be radiation hardened.
Current limiter circuit system
Witcher, Joseph Brandon; Bredemann, Michael V.
2017-09-05
An apparatus comprising a steady state sensing circuit, a switching circuit, and a detection circuit. The steady state sensing circuit is connected to a first, a second and a third node. The first node is connected to a first device, the second node is connected to a second device, and the steady state sensing circuit causes a scaled current to flow at the third node. The scaled current is proportional to a voltage difference between the first and second node. The switching circuit limits an amount of current that flows between the first and second device. The detection circuit is connected to the third node and the switching circuit. The detection circuit monitors the scaled current at the third node and controls the switching circuit to limit the amount of the current that flows between the first and second device when the scaled current is greater than a desired level.
Granger causality network reconstruction of conductance-based integrate-and-fire neuronal systems.
Zhou, Douglas; Xiao, Yanyang; Zhang, Yaoyu; Xu, Zhiqin; Cai, David
2014-01-01
Reconstruction of anatomical connectivity from measured dynamical activities of coupled neurons is one of the fundamental issues in the understanding of structure-function relationship of neuronal circuitry. Many approaches have been developed to address this issue based on either electrical or metabolic data observed in experiment. The Granger causality (GC) analysis remains one of the major approaches to explore the dynamical causal connectivity among individual neurons or neuronal populations. However, it is yet to be clarified how such causal connectivity, i.e., the GC connectivity, can be mapped to the underlying anatomical connectivity in neuronal networks. We perform the GC analysis on the conductance-based integrate-and-fire (I&F) neuronal networks to obtain their causal connectivity. Through numerical experiments, we find that the underlying synaptic connectivity amongst individual neurons or subnetworks, can be successfully reconstructed by the GC connectivity constructed from voltage time series. Furthermore, this reconstruction is insensitive to dynamical regimes and can be achieved without perturbing systems and prior knowledge of neuronal model parameters. Surprisingly, the synaptic connectivity can even be reconstructed by merely knowing the raster of systems, i.e., spike timing of neurons. Using spike-triggered correlation techniques, we establish a direct mapping between the causal connectivity and the synaptic connectivity for the conductance-based I&F neuronal networks, and show the GC is quadratically related to the coupling strength. The theoretical approach we develop here may provide a framework for examining the validity of the GC analysis in other settings.
Granger Causality Network Reconstruction of Conductance-Based Integrate-and-Fire Neuronal Systems
Zhou, Douglas; Xiao, Yanyang; Zhang, Yaoyu; Xu, Zhiqin; Cai, David
2014-01-01
Reconstruction of anatomical connectivity from measured dynamical activities of coupled neurons is one of the fundamental issues in the understanding of structure-function relationship of neuronal circuitry. Many approaches have been developed to address this issue based on either electrical or metabolic data observed in experiment. The Granger causality (GC) analysis remains one of the major approaches to explore the dynamical causal connectivity among individual neurons or neuronal populations. However, it is yet to be clarified how such causal connectivity, i.e., the GC connectivity, can be mapped to the underlying anatomical connectivity in neuronal networks. We perform the GC analysis on the conductance-based integrate-and-fire (IF) neuronal networks to obtain their causal connectivity. Through numerical experiments, we find that the underlying synaptic connectivity amongst individual neurons or subnetworks, can be successfully reconstructed by the GC connectivity constructed from voltage time series. Furthermore, this reconstruction is insensitive to dynamical regimes and can be achieved without perturbing systems and prior knowledge of neuronal model parameters. Surprisingly, the synaptic connectivity can even be reconstructed by merely knowing the raster of systems, i.e., spike timing of neurons. Using spike-triggered correlation techniques, we establish a direct mapping between the causal connectivity and the synaptic connectivity for the conductance-based IF neuronal networks, and show the GC is quadratically related to the coupling strength. The theoretical approach we develop here may provide a framework for examining the validity of the GC analysis in other settings. PMID:24586285
Alteration of synaptic connectivity of oligodendrocyte precursor cells following demyelination
Sahel, Aurélia; Ortiz, Fernando C.; Kerninon, Christophe; Maldonado, Paloma P.; Angulo, María Cecilia; Nait-Oumesmar, Brahim
2015-01-01
Oligodendrocyte precursor cells (OPCs) are a major source of remyelinating oligodendrocytes in demyelinating diseases such as Multiple Sclerosis (MS). While OPCs are innervated by unmyelinated axons in the normal brain, the fate of such synaptic contacts after demyelination is still unclear. By combining electrophysiology and immunostainings in different transgenic mice expressing fluorescent reporters, we studied the synaptic innervation of OPCs in the model of lysolecithin (LPC)-induced demyelination of corpus callosum. Synaptic innervation of reactivated OPCs in the lesion was revealed by the presence of AMPA receptor-mediated synaptic currents, VGluT1+ axon-OPC contacts in 3D confocal reconstructions and synaptic junctions observed by electron microscopy. Moreover, 3D confocal reconstructions of VGluT1 and NG2 immunolabeling showed the existence of glutamatergic axon-OPC contacts in post-mortem MS lesions. Interestingly, patch-clamp recordings in LPC-induced lesions demonstrated a drastic decrease in spontaneous synaptic activity of OPCs early after demyelination that was not caused by an impaired conduction of compound action potentials. A reduction in synaptic connectivity was confirmed by the lack of VGluT1+ axon-OPC contacts in virtually all rapidly proliferating OPCs stained with EdU (50-ethynyl-20-deoxyuridine). At the end of the massive proliferation phase in lesions, the proportion of innervated OPCs rapidly recovers, although the frequency of spontaneous synaptic currents did not reach control levels. In conclusion, our results demonstrate that newly-generated OPCs do not receive synaptic inputs during their active proliferation after demyelination, but gain synapses during the remyelination process. Hence, glutamatergic synaptic inputs may contribute to inhibit OPC proliferation and might have a physiopathological relevance in demyelinating disorders. PMID:25852473
Pten Knockdown in vivo Increases Excitatory Drive onto Dentate Granule Cells
Luikart, Bryan W.; Schnell, Eric; Washburn, Eric K.; Bensen, AeSoon L.; Tovar, Kenneth R.; Westbrook, Gary L.
2011-01-01
Some cases of autism spectrum disorder (ASD) have mutations in the lipid phosphatase, Pten (phosphatase and tensin homolog on chromosome 10). Tissue specific deletion of Pten in the hippocampus and cortex of mice causes anatomical and behavioral abnormalities similar to human autism. However, the impact of reductions in Pten on synaptic and circuit function remains unexplored. We used in vivo stereotaxic injections of lentivirus expressing an shRNA to knockdown Pten in mouse neonatal and young adult dentate granule cells. We then assessed the morphology and synaptic physiology between two weeks and four months later. Confocal imaging of the hippocampus revealed a marked increase in granule cell size and an increase in dendritic spine density. The onset of morphological changes occurred earlier in neonatal mice than in young adults. We used whole-cell recordings from granule cells in acute slices to assess synaptic function following Pten knockdown. Consistent with the increase in dendritic spines, the frequency of excitatory miniature and spontaneous postsynaptic currents increased. However, there was little or no effect on inhibitory postsynaptic currents. Thus Pten knockdown results in an imbalance between excitatory and inhibitory synaptic activity. Because reductions in Pten affected mature granule cells as well as developing granule cells, we suggest that the disruption of circuit function by Pten hypofunction may be ongoing well beyond early development. PMID:21411674
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
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.
Imlach, Wendy L.; Bhola, Rebecca F.; Mohammadi, Sarasa A.; Christie, Macdonald J.
2016-01-01
The development of neuropathic pain involves persistent changes in signalling within pain pathways. Reduced inhibitory signalling in the spinal cord following nerve-injury has been used to explain sensory signs of neuropathic pain but specific circuits that lose inhibitory input have not been identified. This study shows a specific population of spinal cord interneurons, radial neurons, lose glycinergic inhibitory input in a rat partial sciatic nerve ligation (PNL) model of neuropathic pain. Radial neurons are excitatory neurons located in lamina II of the dorsal horn, and are readily identified by their morphology. The amplitude of electrically-evoked glycinergic inhibitory post-synaptic currents (eIPSCs) was greatly reduced in radial neurons following nerve-injury associated with increased paired-pulse ratio. There was also a reduction in frequency of spontaneous IPSCs (sIPSCs) and miniature IPSCs (mIPSC) in radial neurons without significantly affecting mIPSC amplitude. A subtype selective receptor antagonist and western blots established reversion to expression of the immature glycine receptor subunit GlyRα2 in radial neurons after PNL, consistent with slowed decay times of IPSCs. This study has important implications as it identifies a glycinergic synaptic connection in a specific population of dorsal horn neurons where loss of inhibitory signalling may contribute to signs of neuropathic pain. PMID:27841371
Cortical Dynamics in Presence of Assemblies of Densely Connected Weight-Hub Neurons
Setareh, Hesam; Deger, Moritz; Petersen, Carl C. H.; Gerstner, Wulfram
2017-01-01
Experimental measurements of pairwise connection probability of pyramidal neurons together with the distribution of synaptic weights have been used to construct randomly connected model networks. However, several experimental studies suggest that both wiring and synaptic weight structure between neurons show statistics that differ from random networks. Here we study a network containing a subset of neurons which we call weight-hub neurons, that are characterized by strong inward synapses. We propose a connectivity structure for excitatory neurons that contain assemblies of densely connected weight-hub neurons, while the pairwise connection probability and synaptic weight distribution remain consistent with experimental data. Simulations of such a network with generalized integrate-and-fire neurons display regular and irregular slow oscillations akin to experimentally observed up/down state transitions in the activity of cortical neurons with a broad distribution of pairwise spike correlations. Moreover, stimulation of a model network in the presence or absence of assembly structure exhibits responses similar to light-evoked responses of cortical layers in optogenetically modified animals. We conclude that a high connection probability into and within assemblies of excitatory weight-hub neurons, as it likely is present in some but not all cortical layers, changes the dynamics of a layer of cortical microcircuitry significantly. PMID:28690508
Dynamic microtubules drive circuit rewiring in the absence of neurite remodeling
Kurup, Naina; Yan, Dong; Goncharov, Alexandr; Jin, Yishi
2015-01-01
A striking neuronal connectivity change in C. elegans involves the coordinated elimination of existing synapses and formation of synapses at new locations, without altering neuronal morphology. Here, we investigate the tripartite interaction between dynamic microtubules (MTs), kinesin-1, and vesicular cargo during this synapse remodeling. We find that a reduction in the dynamic MT population in motor neuron axons, resulting from genetic interaction between loss of function in the conserved MAPKKK dlk-1 and an α-tubulin mutation, specifically blocks synapse remodeling. Using live imaging and pharmacological modulation of the MT cytoskeleton, we show that dynamic MTs are increased at the onset of remodeling and are critical for new synapse formation. DLK-1 acts during synapse remodeling, and its function involves MT catastrophe factors including kinesin-13/KLP-7 and spastin/SPAS-1. Through a forward genetic screen, we identify gain-of-function mutations in kinesin-1 that can compensate for reduced dynamic MTs to promote synaptic vesicle transport during remodeling. Our data provide in vivo evidence supporting the requirement of dynamic MTs for kinesin-1 dependent axonal transport and shed insight on the role of the MT cytoskeleton in facilitating neural circuit plasticity. PMID:26051896
Control system for a wound-rotor motor
Ellis, James N.
1983-01-01
A load switching circuit for switching two or more transformer taps under load carrying conditions includes first and second parallel connected bridge rectifier circuits which control the selective connection of a direct current load to taps of a transformer. The first bridge circuit is normally conducting so that the load is connected to a first tap through the first bridge circuit. To transfer the load to the second tap, a switch is operable to connect the second bridge circuit to a second tap, and when the second bridge circuit begins to conduct, the first bridge circuit ceases conduction because the potential at the second tap is higher than the potential at the first tap, and the load is thus connected to the second tap through the second bridge circuit. The load switching circuit is applicable in a motor speed controller for a wound-rotor motor for effecting tap switching as a function of motor speed while providing a stepless motor speed control characteristic.
Experimental implementation of a biometric laser synaptic sensor.
Pisarchik, Alexander N; Sevilla-Escoboza, Ricardo; Jaimes-Reátegui, Rider; Huerta-Cuellar, Guillermo; García-Lopez, J Hugo; Kazantsev, Victor B
2013-12-16
We fabricate a biometric laser fiber synaptic sensor to transmit information from one neuron cell to the other by an optical way. The optical synapse is constructed on the base of an erbium-doped fiber laser, whose pumped diode current is driven by a pre-synaptic FitzHugh-Nagumo electronic neuron, and the laser output controls a post-synaptic FitzHugh-Nagumo electronic neuron. The implemented laser synapse displays very rich dynamics, including fixed points, periodic orbits with different frequency-locking ratios and chaos. These regimes can be beneficial for efficient biorobotics, where behavioral flexibility subserved by synaptic connectivity is a challenge.
Doll, Caleb A.; Broadie, Kendal
2014-01-01
Early-use activity during circuit-specific critical periods refines brain circuitry by the coupled processes of eliminating inappropriate synapses and strengthening maintained synapses. We theorize these activity-dependent (A-D) developmental processes are specifically impaired in autism spectrum disorders (ASDs). ASD genetic models in both mouse and Drosophila have pioneered our insights into normal A-D neural circuit assembly and consolidation, and how these developmental mechanisms go awry in specific genetic conditions. The monogenic fragile X syndrome (FXS), a common cause of heritable ASD and intellectual disability, has been particularly well linked to defects in A-D critical period processes. The fragile X mental retardation protein (FMRP) is positively activity-regulated in expression and function, in turn regulates excitability and activity in a negative feedback loop, and appears to be required for the A-D remodeling of synaptic connectivity during early-use critical periods. The Drosophila FXS model has been shown to functionally conserve the roles of human FMRP in synaptogenesis, and has been centrally important in generating our current mechanistic understanding of the FXS disease state. Recent advances in Drosophila optogenetics, transgenic calcium reporters, highly-targeted transgenic drivers for individually-identified neurons, and a vastly improved connectome of the brain are now being combined to provide unparalleled opportunities to both manipulate and monitor A-D processes during critical period brain development in defined neural circuits. The field is now poised to exploit this new Drosophila transgenic toolbox for the systematic dissection of A-D mechanisms in normal versus ASD brain development, particularly utilizing the well-established Drosophila FXS disease model. PMID:24570656
Bidirectional control of social hierarchy by synaptic efficacy in medial prefrontal cortex.
Wang, Fei; Zhu, Jun; Zhu, Hong; Zhang, Qi; Lin, Zhanmin; Hu, Hailan
2011-11-04
Dominance hierarchy has a profound impact on animals' survival, health, and reproductive success, but its neural circuit mechanism is virtually unknown. We found that dominance ranking in mice is transitive, relatively stable, and highly correlates among multiple behavior measures. Recording from layer V pyramidal neurons of the medial prefrontal cortex (mPFC) showed higher strength of excitatory synaptic inputs in mice with higher ranking, as compared with their subordinate cage mates. Furthermore, molecular manipulations that resulted in an increase and decrease in the synaptic efficacy in dorsal mPFC neurons caused an upward and downward movement in the social rank, respectively. These results provide direct evidence for mPFC's involvement in social hierarchy and suggest that social rank is plastic and can be tuned by altering synaptic strength in mPFC pyramidal cells.
Tomasello, Rosario; Garagnani, Max; Wennekers, Thomas; Pulvermüller, Friedemann
2017-04-01
Neuroimaging and patient studies show that different areas of cortex respectively specialize for general and selective, or category-specific, semantic processing. Why are there both semantic hubs and category-specificity, and how come that they emerge in different cortical regions? Can the activation time-course of these areas be predicted and explained by brain-like network models? In this present work, we extend a neurocomputational model of human cortical function to simulate the time-course of cortical processes of understanding meaningful concrete words. The model implements frontal and temporal cortical areas for language, perception, and action along with their connectivity. It uses Hebbian learning to semantically ground words in aspects of their referential object- and action-related meaning. Compared with earlier proposals, the present model incorporates additional neuroanatomical links supported by connectivity studies and downscaled synaptic weights in order to control for functional between-area differences purely due to the number of in- or output links of an area. We show that learning of semantic relationships between words and the objects and actions these symbols are used to speak about, leads to the formation of distributed circuits, which all include neuronal material in connector hub areas bridging between sensory and motor cortical systems. Therefore, these connector hub areas acquire a role as semantic hubs. By differentially reaching into motor or visual areas, the cortical distributions of the emergent 'semantic circuits' reflect aspects of the represented symbols' meaning, thus explaining category-specificity. The improved connectivity structure of our model entails a degree of category-specificity even in the 'semantic hubs' of the model. The relative time-course of activation of these areas is typically fast and near-simultaneous, with semantic hubs central to the network structure activating before modality-preferential areas carrying semantic information. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.
Bosch, Carles; Masachs, Nuria; Exposito-Alonso, David; Martínez, Albert; Teixeira, Cátia M; Fernaud, Isabel; Pujadas, Lluís; Ulloa, Fausto; Comella, Joan X; DeFelipe, Javier; Merchán-Pérez, Angel; Soriano, Eduardo
2016-10-17
The extracellular protein Reelin has an important role in neurological diseases, including epilepsy, Alzheimer's disease and psychiatric diseases, targeting hippocampal circuits. Here we address the role of Reelin in the development of synaptic contacts in adult-generated granule cells (GCs), a neuronal population that is crucial for learning and memory and implicated in neurological and psychiatric diseases. We found that the Reelin pathway controls the shapes, sizes, and types of dendritic spines, the complexity of multisynaptic innervations and the degree of the perisynaptic astroglial ensheathment that controls synaptic homeostasis. These findings show a pivotal role of Reelin in GC synaptogenesis and provide a foundation for structural circuit alterations caused by Reelin deregulation that may occur in neurological and psychiatric disorders. © The Author 2016. Published by Oxford University Press.
Gentet, Luc J; Ulrich, Daniel
2003-01-01
The thalamic reticular nucleus (nRT) is composed entirely of GABAergic inhibitory neurones that receive input from pyramidal cortical neurones and excitatory relay cells of the ventrobasal complex of the thalamus (VB). It plays a major role in the synchrony of thalamic networks, yet the synaptic connections it receives from VB cells have never been fully physiologically characterised. Here, whole-cell current-clamp recordings were obtained from 22 synaptically connected VB-nRT cell pairs in slices of juvenile (P14–20) rats. At 34–36 °C, single presynaptic APs evoked unitary EPSPs in nRT cells with a peak amplitude of 7.4 ± 1.5 mV (mean ± s.e.m.) and a decay time constant of 15.1 ± 0.9 ms. Only four out of 22 pairs showed transmission failures at a mean rate of 6.8 ± 1.1 %. An NMDA receptor (NMDAR)-mediated component was significant at rest and subsequent EPSPs in a train were depressed. Only one out of 14 pairs tested was reciprocally connected; the observed IPSPs in the VB cell had a peak amplitude of 0.8 mV and were completely abolished in the presence of 10 μm bicuculline. Thus, synaptic connections from VB cells to nRT neurones are mainly ‘drivers’, while a small subset of cells form closed disynaptic loops. PMID:12563005
Moscato, Emilia H.; Jain, Ankit; Peng, Xiaoyu; Hughes, Ethan G.; Dalmau, Josep; Balice-Gordon, Rita J.
2010-01-01
Recently, several novel, potentially lethal, and treatment-responsive syndromes that affect hippocampal and cortical function have been shown to be associated with auto-antibodies against synaptic antigens, notably glutamate or GABA-B receptors. Patients with these auto-antibodies, sometimes associated with teratomas and other neoplasms, present with psychiatric symptoms, seizures, memory deficits, and decreased level of consciousness. These symptoms often improve dramatically after immunotherapy or tumor resection. Here we discuss studies of the cellular and synaptic effects of these antibodies in hippocampal neurons in vitro and preliminary work in rodent models. Our work suggests that patient antibodies lead to rapid and reversible removal of neurotransmitter receptors from synaptic sites, leading to changes in synaptic and circuit function that in turn are likely to lead to behavioral deficits. We also discuss several of the many questions raised by these and related disorders. Determining the mechanisms underlying these novel anti-neurotransmitter receptor encephalopathies will provide insights into the cellular and synaptic bases of the memory and cognitive deficits that are hallmarks of these disorders, and potentially suggest avenues for therapeutic intervention. PMID:20646055
The role of muscle spindles in the development of the monosynaptic stretch reflex
Wang, Zhi; Li, LingYing
2012-01-01
Muscle sensory axons induce the development of specialized intrafusal muscle fibers in muscle spindles during development, but the role that the intrafusal fibers may play in the development of the central projections of these Ia sensory axons is unclear. In the present study, we assessed the influence of intrafusal fibers in muscle spindles on the formation of monosynaptic connections between Ia (muscle spindle) sensory axons and motoneurons (MNs) using two transgenic strains of mice. Deletion of the ErbB2 receptor from developing myotubes disrupts the formation of intrafusal muscle fibers and causes a nearly complete absence of functional synaptic connections between Ia axons and MNs. Monosynaptic connectivity can be fully restored by postnatal administration of neurotrophin-3 (NT-3), and the synaptic connections in NT-3-treated mice are as specific as in wild-type mice. Deletion of the Egr3 transcription factor also impairs the development of intrafusal muscle fibers and disrupts synaptic connectivity between Ia axons and MNs. Postnatal injections of NT-3 restore the normal strengths and specificity of Ia–motoneuronal connections in these mice as well. Severe deficits in intrafusal fiber development, therefore, do not disrupt the establishment of normal, selective patterns of connections between Ia axons and MNs, although these connections require the presence of NT-3, normally supplied by intrafusal fibers, to be functional. PMID:22490553
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.
Cliques of Neurons Bound into Cavities Provide a Missing Link between Structure and Function.
Reimann, Michael W; Nolte, Max; Scolamiero, Martina; Turner, Katharine; Perin, Rodrigo; Chindemi, Giuseppe; Dłotko, Paweł; Levi, Ran; Hess, Kathryn; Markram, Henry
2017-01-01
The lack of a formal link between neural network structure and its emergent function has hampered our understanding of how the brain processes information. We have now come closer to describing such a link by taking the direction of synaptic transmission into account, constructing graphs of a network that reflect the direction of information flow, and analyzing these directed graphs using algebraic topology. Applying this approach to a local network of neurons in the neocortex revealed a remarkably intricate and previously unseen topology of synaptic connectivity. The synaptic network contains an abundance of cliques of neurons bound into cavities that guide the emergence of correlated activity. In response to stimuli, correlated activity binds synaptically connected neurons into functional cliques and cavities that evolve in a stereotypical sequence toward peak complexity. We propose that the brain processes stimuli by forming increasingly complex functional cliques and cavities.
Synaptic noise is an information bottleneck in the inner retina during dynamic visual stimulation
Freed, Michael A; Liang, Zhiyin
2014-01-01
In daylight, noise generated by cones determines the fidelity with which visual signals are initially encoded. Subsequent stages of visual processing require synapses from bipolar cells to ganglion cells, but whether these synapses generate a significant amount of noise was unknown. To characterize noise generated by these synapses, we recorded excitatory postsynaptic currents from mammalian retinal ganglion cells and subjected them to a computational noise analysis. The release of transmitter quanta at bipolar cell synapses contributed substantially to the noise variance found in the ganglion cell, causing a significant loss of fidelity from bipolar cell array to postsynaptic ganglion cell. Virtually all the remaining noise variance originated in the presynaptic circuit. Circuit noise had a frequency content similar to noise shared by ganglion cells but a very different frequency content from noise from bipolar cell synapses, indicating that these synapses constitute a source of independent noise not shared by ganglion cells. These findings contribute a picture of daylight retinal circuits where noise from cones and noise generated by synaptic transmission of cone signals significantly limit visual fidelity. PMID:24297850
Neuromimetic Circuits with Synaptic Devices Based on Strongly Correlated Electron Systems
NASA Astrophysics Data System (ADS)
Ha, Sieu D.; Shi, Jian; Meroz, Yasmine; Mahadevan, L.; Ramanathan, Shriram
2014-12-01
Strongly correlated electron systems such as the rare-earth nickelates (R NiO3 , R denotes a rare-earth element) can exhibit synapselike continuous long-term potentiation and depression when gated with ionic liquids; exploiting the extreme sensitivity of coupled charge, spin, orbital, and lattice degrees of freedom to stoichiometry. We present experimental real-time, device-level classical conditioning and unlearning using nickelate-based synaptic devices in an electronic circuit compatible with both excitatory and inhibitory neurons. We establish a physical model for the device behavior based on electric-field-driven coupled ionic-electronic diffusion that can be utilized for design of more complex systems. We use the model to simulate a variety of associate and nonassociative learning mechanisms, as well as a feedforward recurrent network for storing memory. Our circuit intuitively parallels biological neural architectures, and it can be readily generalized to other forms of cellular learning and extinction. The simulation of neural function with electronic device analogs may provide insight into biological processes such as decision making, learning, and adaptation, while facilitating advanced parallel information processing in hardware.
Lin, Chia-Wei; Sim, Shuyin; Ainsworth, Alice; Okada, Masayoshi; Kelsch, Wolfgang; Lois, Carlos
2009-01-01
New neurons are added to the adult brain throughout life, but only half ultimately integrate into existing circuits. Sensory experience is an important regulator of the selection of new neurons but it remains unknown whether experience provides specific patterns of synaptic input, or simply a minimum level of overall membrane depolarization critical for integration. To investigate this issue, we genetically modified intrinsic electrical properties of adult-generated neurons in the mammalian olfactory bulb. First, we observed that suppressing levels of cell-intrinsic neuronal activity via expression of ESKir2.1 potassium channels decreases, whereas enhancing activity via expression of NaChBac sodium channels increases survival of new neurons. Neither of these modulations affects synaptic formation. Furthermore, even when neurons are induced to fire dramatically altered patterns of action potentials, increased levels of cell-intrinsic activity completely blocks cell death triggered by NMDA receptor deletion. These findings demonstrate that overall levels of cell-intrinsic activity govern survival of new neurons and precise firing patterns are not essential for neuronal integration into existing brain circuits. PMID:20152111
PSD-95 regulates synaptic kainate receptors at mouse hippocampal mossy fiber-CA3 synapses.
Suzuki, Etsuko; Kamiya, Haruyuki
2016-06-01
Kainate-type glutamate receptors (KARs) are the third class of ionotropic glutamate receptors whose activation leads to the unique roles in regulating synaptic transmission and circuit functions. In contrast to AMPA receptors (AMPARs), little is known about the mechanism of synaptic localization of KARs. PSD-95, a major scaffold protein of the postsynaptic density, is a candidate molecule that regulates the synaptic KARs. Although PSD-95 was shown to bind directly to KARs subunits, it has not been tested whether PSD-95 regulates synaptic KARs in intact synapses. Using PSD-95 knockout mice, we directly investigated the role of PSD-95 in the KARs-mediated components of synaptic transmission at hippocampal mossy fiber-CA3 synapse, one of the synapses with the highest density of KARs. Mossy fiber EPSCs consist of AMPA receptor (AMPAR)-mediated fast component and KAR-mediated slower component, and the ratio was significantly reduced in PSD-95 knockout mice. The size of KARs-mediated field EPSP reduced in comparison with the size of the fiber volley. Analysis of KARs-mediated miniature EPSCs also suggested reduced synaptic KARs. All the evidence supports critical roles of PSD-95 in regulating synaptic KARs. Copyright © 2015 Elsevier Ireland Ltd and Japan Neuroscience Society. All rights reserved.
Guidi, Sandra; Ciani, Elisabetta; Mangano, Chiara; Calzà, Laura; Bartesaghi, Renata
2013-01-01
Down syndrome (DS) is a high-incidence genetic pathology characterized by severe impairment of cognitive functions, including declarative memory. Impairment of hippocampus-dependent long-term memory in DS appears to be related to anatomo-functional alterations of the hippocampal trisynaptic circuit formed by the dentate gyrus (DG) granule cells - CA3 pyramidal neurons - CA1 pyramidal neurons. No therapies exist to improve cognitive disability in individuals with DS. In previous studies we demonstrated that pharmacotherapy with fluoxetine restores neurogenesis, granule cell number and dendritic morphology in the DG of the Ts65Dn mouse model of DS. The goal of the current study was to establish whether treatment rescues the impairment of synaptic connectivity between the DG and CA3 that characterizes the trisomic condition. Euploid and Ts65Dn mice were treated with fluoxetine during the first two postnatal weeks and examined 45–60 days after treatment cessation. Untreated Ts65Dn mice had a hypotrophyc mossy fiber bundle, fewer synaptic contacts, fewer glutamatergic contacts, and fewer dendritic spines in the stratum lucidum of CA3, the terminal field of the granule cell projections. Electrophysiological recordings from CA3 pyramidal neurons showed that in Ts65Dn mice the frequency of both mEPSCs and mIPSCs was reduced, indicating an overall impairment of excitatory and inhibitory inputs to CA3 pyramidal neurons. In treated Ts65Dn mice all these aberrant features were fully normalized, indicating that fluoxetine can rescue functional connectivity between the DG and CA3. The positive effects of fluoxetine on the DG-CA3 system suggest that early treatment with this drug could be a suitable therapy, possibly usable in humans, to restore the physiology of the hippocampal networks and, hence, memory functions. PMID:23620781
Acute Fasting Regulates Retrograde Synaptic Enhancement through a 4E-BP-Dependent Mechanism.
Kauwe, Grant; Tsurudome, Kazuya; Penney, Jay; Mori, Megumi; Gray, Lindsay; Calderon, Mario R; Elazouzzi, Fatima; Chicoine, Nicole; Sonenberg, Nahum; Haghighi, A Pejmun
2016-12-21
While beneficial effects of fasting on organismal function and health are well appreciated, we know little about the molecular details of how fasting influences synaptic function and plasticity. Our genetic and electrophysiological experiments demonstrate that acute fasting blocks retrograde synaptic enhancement that is normally triggered as a result of reduction in postsynaptic receptor function at the Drosophila larval neuromuscular junction (NMJ). This negative regulation critically depends on transcriptional enhancement of eukaryotic initiation factor 4E binding protein (4E-BP) under the control of the transcription factor Forkhead box O (Foxo). Furthermore, our findings indicate that postsynaptic 4E-BP exerts a constitutive negative input, which is counteracted by a positive regulatory input from the Target of Rapamycin (TOR). This combinatorial retrograde signaling plays a key role in regulating synaptic strength. Our results provide a mechanistic insight into how cellular stress and nutritional scarcity could acutely influence synaptic homeostasis and functional stability in neural circuits. Copyright © 2016 Elsevier Inc. All rights reserved.
Kulkarni, Abhishek; Ertekin, Deniz; Lee, Chi-Hon; Hummel, Thomas
2016-03-17
The precise recognition of appropriate synaptic partner neurons is a critical step during neural circuit assembly. However, little is known about the developmental context in which recognition specificity is important to establish synaptic contacts. We show that in the Drosophila visual system, sequential segregation of photoreceptor afferents, reflecting their birth order, lead to differential positioning of their growth cones in the early target region. By combining loss- and gain-of-function analyses we demonstrate that relative differences in the expression of the transcription factor Sequoia regulate R cell growth cone segregation. This initial growth cone positioning is consolidated via cell-adhesion molecule Capricious in R8 axons. Further, we show that the initial growth cone positioning determines synaptic layer selection through proximity-based axon-target interactions. Taken together, we demonstrate that birth order dependent pre-patterning of afferent growth cones is an essential pre-requisite for the identification of synaptic partner neurons during visual map formation in Drosophila.
The Synapse as a Central Target for Neurodevelopmental Susceptibility to Pesticides
Vester, Aimee; Caudle, W. Michael
2016-01-01
The developmental period of the nervous system is carefully orchestrated and highly vulnerable to alterations. One crucial factor of a properly-functioning nervous system is the synapse, as synaptic signaling is critical for the formation and maturation of neural circuits. Studies show that genetic and environmental impacts can affect diverse components of synaptic function. Importantly, synaptic dysfunction is known to be associated with neurologic and psychiatric disorders, as well as more subtle cognitive, psychomotor, and sensory defects. Given the importance of the synapse in numerous domains, we wanted to delineate the effects of pesticide exposure on synaptic function. In this review, we summarize current epidemiologic and molecular studies that demonstrate organochlorine, organophosphate, and pyrethroid pesticide exposures target the developing synapse. We postulate that the synapse plays a central role in synaptic vulnerability to pesticide exposure during neurodevelopment, and the synapse is a worthy candidate for investigating more subtle effects of chronic pesticide exposure in future studies. PMID:29051423
Fletcher, Emily V; Simon, Christian M; Pagiazitis, John G; Chalif, Joshua I; Vukojicic, Aleksandra; Drobac, Estelle; Wang, Xiaojian; Mentis, George Z
2017-07-01
Behavioral deficits in neurodegenerative diseases are often attributed to the selective dysfunction of vulnerable neurons via cell-autonomous mechanisms. Although vulnerable neurons are embedded in neuronal circuits, the contributions of their synaptic partners to disease process are largely unknown. Here we show that, in a mouse model of spinal muscular atrophy (SMA), a reduction in proprioceptive synaptic drive leads to motor neuron dysfunction and motor behavior impairments. In SMA mice or after the blockade of proprioceptive synaptic transmission, we observed a decrease in the motor neuron firing that could be explained by the reduction in the expression of the potassium channel Kv2.1 at the surface of motor neurons. Chronically increasing neuronal activity pharmacologically in vivo led to a normalization of Kv2.1 expression and an improvement in motor function. Our results demonstrate a key role of excitatory synaptic drive in shaping the function of motor neurons during development and the contribution of its disruption to a neurodegenerative disease.
Fletcher, Emily V.; Simon, Christian M.; Pagiazitis, John G.; Chalif, Joshua I.; Vukojicic, Aleksandra; Drobac, Estelle; Wang, Xiaojian; Mentis, George Z.
2017-01-01
Behavioral deficits in neurodegenerative diseases are often attributed to the selective dysfunction of vulnerable neurons via cell-autonomous mechanisms. Although vulnerable neurons are embedded in neuronal circuits, the contribution of their synaptic partners to the disease process is largely unknown. Here, we show that in a mouse model of spinal muscular atrophy (SMA), a reduction in proprioceptive synaptic drive leads to motor neuron dysfunction and motor behavior impairments. In SMA mice or after the blockade of proprioceptive synaptic transmission we observed a decrease in the motor neuron firing which could be explained by the reduction in the expression of the potassium channel Kv2.1 at the surface of motor neurons. Increasing neuronal activity pharmacologically by chronic exposure in vivo led to a normalization of Kv2.1 expression and an improvement in motor function. Our results demonstrate a key role of excitatory synaptic drive in shaping the function of motor neurons during development and the contribution of its disruption to a neurodegenerative disease. PMID:28504671
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
Theory of electric resonance in the neocortical apical dendrite.
Kasevich, Ray S; LaBerge, David
2011-01-01
Pyramidal neurons of the neocortex display a wide range of synchronous EEG rhythms, which arise from electric activity along the apical dendrites of neocortical pyramidal neurons. Here we present a theoretical description of oscillation frequency profiles along apical dendrites which exhibit resonance frequencies in the range of 10 to 100 Hz. The apical dendrite is modeled as a leaky coaxial cable coated with a dielectric, in which a series of compartments act as coupled electric circuits that gradually narrow the resonance profile. The tuning of the peak frequency is assumed to be controlled by the average amplitude of voltage-gated outward currents, which in turn are regulated by the subthreshold noise in the thousands of synaptic spines that are continuously bombarded by local circuits. The results of simulations confirmed the ability of the model both to tune the peak frequency in the 10-100 Hz range and to gradually narrow the resonance profile. Considerable additional narrowing of the resonance profile is provided by repeated looping through the apical dendrite via the corticothalamocortical circuit, which reduced the width of each resonance curve (at half-maximum) to approximately 1 Hz. Synaptic noise in the neural circuit is discussed in relation to the ways it can influence the narrowing process.
Theory of Electric Resonance in the Neocortical Apical Dendrite
Kasevich, Ray S.; LaBerge, David
2011-01-01
Pyramidal neurons of the neocortex display a wide range of synchronous EEG rhythms, which arise from electric activity along the apical dendrites of neocortical pyramidal neurons. Here we present a theoretical description of oscillation frequency profiles along apical dendrites which exhibit resonance frequencies in the range of 10 to 100 Hz. The apical dendrite is modeled as a leaky coaxial cable coated with a dielectric, in which a series of compartments act as coupled electric circuits that gradually narrow the resonance profile. The tuning of the peak frequency is assumed to be controlled by the average amplitude of voltage-gated outward currents, which in turn are regulated by the subthreshold noise in the thousands of synaptic spines that are continuously bombarded by local circuits. The results of simulations confirmed the ability of the model both to tune the peak frequency in the 10–100 Hz range and to gradually narrow the resonance profile. Considerable additional narrowing of the resonance profile is provided by repeated looping through the apical dendrite via the corticothalamocortical circuit, which reduced the width of each resonance curve (at half-maximum) to approximately 1 Hz. Synaptic noise in the neural circuit is discussed in relation to the ways it can influence the narrowing process. PMID:21853129
Chittajallu, R; Wester, J C; Craig, M T; Barksdale, E; Yuan, X Q; Akgül, G; Fang, C; Collins, D; Hunt, S; Pelkey, K A; McBain, C J
2017-07-28
Appropriate integration of GABAergic interneurons into nascent cortical circuits is critical for ensuring normal information processing within the brain. Network and cognitive deficits associated with neurological disorders, such as schizophrenia, that result from NMDA receptor-hypofunction have been mainly attributed to dysfunction of parvalbumin-expressing interneurons that paradoxically express low levels of synaptic NMDA receptors. Here, we reveal that throughout postnatal development, thalamic, and entorhinal cortical inputs onto hippocampal neurogliaform cells are characterized by a large NMDA receptor-mediated component. This NMDA receptor-signaling is prerequisite for developmental programs ultimately responsible for the appropriate long-range AMPAR-mediated recruitment of neurogliaform cells. In contrast, AMPAR-mediated input at local Schaffer-collateral synapses on neurogliaform cells remains normal following NMDA receptor-ablation. These afferent specific deficits potentially impact neurogliaform cell mediated inhibition within the hippocampus and our findings reveal circuit loci implicating this relatively understudied interneuron subtype in the etiology of neurodevelopmental disorders characterized by NMDA receptor-hypofunction.Proper brain function depends on the correct assembly of excitatory and inhibitory neurons into neural circuits. Here the authors show that during early postnatal development in mice, NMDAR signaling via activity of long-range synaptic inputs onto neurogliaform cells is required for their appropriate integration into the hippocampal circuitry.
Reinhard, Sarah M; Razak, Khaleel; Ethell, Iryna M
2015-01-01
The extracellular matrix (ECM) is a critical regulator of neural network development and plasticity. As neuronal circuits develop, the ECM stabilizes synaptic contacts, while its cleavage has both permissive and active roles in the regulation of plasticity. Matrix metalloproteinase 9 (MMP-9) is a member of a large family of zinc-dependent endopeptidases that can cleave ECM and several cell surface receptors allowing for synaptic and circuit level reorganization. It is becoming increasingly clear that the regulated activity of MMP-9 is critical for central nervous system (CNS) development. In particular, MMP-9 has a role in the development of sensory circuits during early postnatal periods, called 'critical periods.' MMP-9 can regulate sensory-mediated, local circuit reorganization through its ability to control synaptogenesis, axonal pathfinding and myelination. Although activity-dependent activation of MMP-9 at specific synapses plays an important role in multiple plasticity mechanisms throughout the CNS, misregulated activation of the enzyme is implicated in a number of neurodegenerative disorders, including traumatic brain injury, multiple sclerosis, and Alzheimer's disease. Growing evidence also suggests a role for MMP-9 in the pathophysiology of neurodevelopmental disorders including Fragile X Syndrome. This review outlines the various actions of MMP-9 during postnatal brain development, critical for future studies exploring novel therapeutic strategies for neurodevelopmental disorders.
Latchney, Sarah E.; Masiulis, Irene; Zaccaria, Kimberly J.; Lagace, Diane C.; Powell, Craig M.; McCasland, James S.; Eisch, Amelia J.
2014-01-01
Growth Associated Protein-43 (GAP-43) is a pre-synaptic protein that plays key roles in axonal growth and guidance and in modulating synapse formation. Previous work has demonstrated that mice lacking one allele of this gene [GAP-43(+/-) mice] exhibit hippocampal structural abnormalities and impaired spatial learning and stress-induced behavioral withdrawal and anxiety (Zaccaria et al., 2010), behaviors that are dependent on proper hippocampal circuitry and function. Given the correlation between hippocampal function, synaptic connectivity, and neurogenesis, we tested if behaviorally-naïve GAP-43(+/-) mice had alterations in either neurogenesis or synaptic connectivity in the hippocampus during early postnatal development and young adulthood, and following behavior testing in older adults. To test our hypothesis, we examined hippocampal cell proliferation (Ki67), number of immature neuroblasts (DCX), and mossy fiber volume (synaptoporin) in behaviorally-naïve postnatal (P) day 9 (P9), P26, and behaviorally-experienced 5-7 month old GAP-43(+/-) and (+/+) littermate mice. P9 GAP-43(+/-) mice had fewer Ki67+ and DCX+ cells compared to (+/+) mice, particularly in the posterior dentate gyrus, and smaller mossy fiber volume in the same region. In young adulthood, however, male GAP-43(+/-) mice had more Ki67+ and DCX+ cells and greater mossy fiber volume in the posterior dentate gyrus relative to male (+/+). These increases were not seen in females. In 5-7 month old GAP-43(+/-) mice whose behaviors were the focus of our prior publication (Zaccaria et al., 2010), there was no global change in number of proliferating or immature neurons relative to (+/+) mice. However, more detailed analysis revealed fewer proliferative DCX+ cells in the anterior dentate gyrus of male GAP-43(+/-) mice compared to male (+/+) mice. This reduction was not observed in females. These results suggest that young GAP-43(+/-) mice have decreased hippocampal neurogenesis and synaptic connectivity, but slightly older mice have greater hippocampal neurogenesis and synaptic connectivity. In conjunction with our previous study, these findings suggest GAP-43 is dynamically involved in early postnatal and adult hippocampal neurogenesis and synaptic connectivity, possibly contributing to the GAP-43(+/-) behavioral phenotype. PMID:24576816
Spontaneous Activity Drives Local Synaptic Plasticity In Vivo.
Winnubst, Johan; Cheyne, Juliette E; Niculescu, Dragos; Lohmann, Christian
2015-07-15
Spontaneous activity fine-tunes neuronal connections in the developing brain. To explore the underlying synaptic plasticity mechanisms, we monitored naturally occurring changes in spontaneous activity at individual synapses with whole-cell patch-clamp recordings and simultaneous calcium imaging in the mouse visual cortex in vivo. Analyzing activity changes across large populations of synapses revealed a simple and efficient local plasticity rule: synapses that exhibit low synchronicity with nearby neighbors (<12 μm) become depressed in their transmission frequency. Asynchronous electrical stimulation of individual synapses in hippocampal slices showed that this is due to a decrease in synaptic transmission efficiency. Accordingly, experimentally increasing local synchronicity, by stimulating synapses in response to spontaneous activity at neighboring synapses, stabilized synaptic transmission. Finally, blockade of the high-affinity proBDNF receptor p75(NTR) prevented the depression of asynchronously stimulated synapses. Thus, spontaneous activity drives local synaptic plasticity at individual synapses in an "out-of-sync, lose-your-link" fashion through proBDNF/p75(NTR) signaling to refine neuronal connectivity. VIDEO ABSTRACT. Copyright © 2015 Elsevier Inc. All rights reserved.
D’Esposito, Mark
2017-01-01
Recent work has established that visual working memory is subject to serial dependence: current information in memory blends with that from the recent past as a function of their similarity. This tuned temporal smoothing likely promotes the stability of memory in the face of noise and occlusion. Serial dependence accumulates over several seconds in memory and deteriorates with increased separation between trials. While this phenomenon has been extensively characterized in behavior, its neural mechanism is unknown. In the present study, we investigate the circuit-level origins of serial dependence in a biophysical model of cortex. We explore two distinct kinds of mechanisms: stable persistent activity during the memory delay period and dynamic “activity-silent” synaptic plasticity. We find that networks endowed with both strong reverberation to support persistent activity and dynamic synapses can closely reproduce behavioral serial dependence. Specifically, elevated activity drives synaptic augmentation, which biases activity on the subsequent trial, giving rise to a spatiotemporally tuned shift in the population response. Our hybrid neural model is a theoretical advance beyond abstract mathematical characterizations, offers testable hypotheses for physiological research, and demonstrates the power of biological insights to provide a quantitative explanation of human behavior. PMID:29244810
Ensemble stacking mitigates biases in inference of synaptic connectivity.
Chambers, Brendan; Levy, Maayan; Dechery, Joseph B; MacLean, Jason N
2018-01-01
A promising alternative to directly measuring the anatomical connections in a neuronal population is inferring the connections from the activity. We employ simulated spiking neuronal networks to compare and contrast commonly used inference methods that identify likely excitatory synaptic connections using statistical regularities in spike timing. We find that simple adjustments to standard algorithms improve inference accuracy: A signing procedure improves the power of unsigned mutual-information-based approaches and a correction that accounts for differences in mean and variance of background timing relationships, such as those expected to be induced by heterogeneous firing rates, increases the sensitivity of frequency-based methods. We also find that different inference methods reveal distinct subsets of the synaptic network and each method exhibits different biases in the accurate detection of reciprocity and local clustering. To correct for errors and biases specific to single inference algorithms, we combine methods into an ensemble. Ensemble predictions, generated as a linear combination of multiple inference algorithms, are more sensitive than the best individual measures alone, and are more faithful to ground-truth statistics of connectivity, mitigating biases specific to single inference methods. These weightings generalize across simulated datasets, emphasizing the potential for the broad utility of ensemble-based approaches.
Khalil, Reem; Levitt, Jonathan B
2013-09-01
A critical question in brain development is whether different brain circuits mature concurrently or with different timescales. To characterize the anatomical and functional development of different visual cortical areas, one must be able to distinguish these areas. Here, we show that zinc histochemistry, which reveals a subset of glutamatergic processes, can be used to reliably distinguish visual areas in juvenile and adult ferret cerebral cortex, and that the postnatal decline in levels of synaptic zinc follows a broadly similar developmental trajectory in multiple areas of ferret visual cortex. Zinc staining in all areas examined (17, 18, 19, 21, and Suprasylvian) is greater in the 5-week-old than in the adult. Furthermore, there is less laminar variation in zinc staining in the 5-week-old visual cortex than in the adult. Despite differences in staining intensity, areal boundaries can be discerned in the juvenile as in the adult. By 6 weeks of age, we observe a significant decline in visual cortical synaptic zinc; this decline was most pronounced in layer IV of areas 17 and 18, with much less change in higher-order extrastriate areas during the important period in visual cortical development following eye opening. By 10 weeks of age, the laminar pattern of zinc staining in all visual areas is essentially adultlike. The decline in synaptic zinc in the supra- and infragranular layers in all areas proceeds at the same rate, though the decline in layer IV does not. These results suggest that the timecourse of synaptic zinc decline is lamina specific, and further confirm and extend the notion that at least some aspects of cortical maturation follow a similar developmental timecourse in multiple areas. The postnatal decline in synaptic zinc we observe during the second postnatal month begins after eye opening, consistent with evidence that synaptic zinc is regulated by sensory experience.
Dynamic simulation of perturbation responses in a closed-loop virtual arm model.
Du, Yu-Fan; He, Xin; Lan, Ning
2010-01-01
A closed-loop virtual arm (VA) model has been developed in SIMULINK environment by adding spinal reflex circuits and propriospinal neural networks to the open-loop VA model developed in early study [1]. An improved virtual muscle model (VM4.0) is used to speed up simulation and to generate more precise recruitment of muscle force at low levels of muscle activation. Time delays in the reflex loops are determined by their synaptic connections and afferent transmission back to the spinal cord. Reflex gains are properly selected so that closed-loop responses are stable. With the closed-loop VA model, we are developing an approach to evaluate system behaviors by dynamic simulation of perturbation responses. Joint stiffness is calculated based on simulated perturbation responses by a least-squares algorithm in MATLAB. This method of dynamic simulation will be essential for further evaluation of feedforward and reflex control of arm movement and position.
Neuropeptide transmission in brain circuits
van den Pol, Anthony N.
2014-01-01
Neuropeptides are found in many mammalian CNS neurons where they play key roles in modulating neuronal activity. In contrast to amino acid transmitter release at the synapse, neuropeptide release is not restricted to the synaptic specialization, and after release, a neuropeptide may diffuse some distance to exert its action through a G-protein coupled receptor. Some neuropeptides such as hypocretin/orexin are synthesized only in single regions of the brain, and the neurons releasing these peptides probably have similar functional roles. Other peptides such as neuropeptide Y (NPY) are synthesized throughout the brain, and neurons that synthesize the peptide in one region have no anatomical or functional connection with NPY neurons in other brain regions. Here, I review converging data revealing a complex interaction between slow-acting neuromodulator peptides and fast-acting amino acid transmitters in the control of energy homeostasis, drug addiction, mood and motivation, sleep-wake states, and neuroendocrine regulation. PMID:23040809
A subcortical inhibitory signal for behavioral arrest in the thalamus
Dugué, Guillaume P.; Bokor, Hajnalka; Rousseau, Charly V.; Maglóczky, Zsófia; Havas, László; Hangya, Balázs; Wildner, Hendrik; Zeilhofer, Hanns Ulrich; Dieudonné, Stéphane; Acsády, László
2016-01-01
Organization of behavior requires rapid coordination of brainstem and forebrain activity. The exact mechanisms of effective communication between these regions are presently unclear. The intralaminar thalamus (IL) probably serves as a central hub in this circuit by connecting the critical brainstem and forebrain areas. Here we found that GABAergic/glycinergic fibers ascending from the pontine reticular formation (PRF) of the brainstem evoke fast and reliable inhibition in the IL thalamus via large, multisynaptic terminals. This inhibition was fine-tuned through heterogeneous GABAergic/glycinergic receptor ratios expressed at individual synapses. Optogenetic activation of PRF axons in the IL of freely moving mice led to behavioral arrest and transient interruption of awake cortical activity. An afferent system with comparable morphological features was also found in the human IL. These data reveal an evolutionarily conserved ascending system which gates forebrain activity through fast and powerful synaptic inhibition of the IL thalamus. PMID:25706472
Presynaptic Partners of Dorsal Raphe Serotonergic and GABAergic Neurons
Weissbourd, Brandon; Ren, Jing; DeLoach, Katherine E.; Guenthner, Casey J.; Miyamichi, Kazunari; Luo, Liqun
2016-01-01
SUMMARY The serotonin system powerfully modulates physiology and behavior in health and disease, yet the circuit mechanisms underlying serotonin neuron activity are poorly understood. The major source of forebrain serotonergic innervation is from the dorsal raphe nucleus (DR), which contains both serotonin and GABA neurons. Using viral tracing combined with electrophysiology, we found that GABA and serotonin neurons in the DR receive excitatory, inhibitory, and peptidergic inputs from the same specific brain regions. Embedded in this overall similarity are important differences. Serotonin neurons are more likely to receive synaptic inputs from anterior neocortex while GABA neurons receive disproportionally higher input from the central amygdala. Local input mapping revealed extensive serotonin-serotonin as well as GABA-serotonin connectivity with a distinct spatial organization. Covariance analysis suggests heterogeneity of both serotonin and GABA neurons with respect to the inputs they receive. These analyses provide a foundation for further functional dissection of the serotonin system. PMID:25102560
Developmental Self-Construction and -Configuration of Functional Neocortical Neuronal Networks
Bauer, Roman; Zubler, Frédéric; Pfister, Sabina; Hauri, Andreas; Pfeiffer, Michael; Muir, Dylan R.; Douglas, Rodney J.
2014-01-01
The prenatal development of neural circuits must provide sufficient configuration to support at least a set of core postnatal behaviors. Although knowledge of various genetic and cellular aspects of development is accumulating rapidly, there is less systematic understanding of how these various processes play together in order to construct such functional networks. Here we make some steps toward such understanding by demonstrating through detailed simulations how a competitive co-operative (‘winner-take-all’, WTA) network architecture can arise by development from a single precursor cell. This precursor is granted a simplified gene regulatory network that directs cell mitosis, differentiation, migration, neurite outgrowth and synaptogenesis. Once initial axonal connection patterns are established, their synaptic weights undergo homeostatic unsupervised learning that is shaped by wave-like input patterns. We demonstrate how this autonomous genetically directed developmental sequence can give rise to self-calibrated WTA networks, and compare our simulation results with biological data. PMID:25474693
Bazhenov, Maxim; Huerta, Ramon; Smith, Brian H.
2013-01-01
Nonassociative and associative learning rules simultaneously modify neural circuits. However, it remains unclear how these forms of plasticity interact to produce conditioned responses. Here we integrate nonassociative and associative conditioning within a uniform model of olfactory learning in the honeybee. Honeybees show a fairly abrupt increase in response after a number of conditioning trials. The occurrence of this abrupt change takes many more trials after exposure to nonassociative trials than just using associative conditioning. We found that the interaction of unsupervised and supervised learning rules is critical for explaining latent inhibition phenomenon. Associative conditioning combined with the mutual inhibition between the output neurons produces an abrupt increase in performance despite smooth changes of the synaptic weights. The results show that an integrated set of learning rules implemented using fan-out connectivities together with neural inhibition can explain the broad range of experimental data on learning behaviors. PMID:23536082
Exercise-enhanced Neuroplasticity Targeting Motor and Cognitive Circuitry in Parkinson’s Disease
Petzinger, G. M.; Fisher, B. E.; McEwen, S.; Beeler, J. A.; Walsh, J. P.; Jakowec, M. W.
2013-01-01
The purpose of this review is to highlight the potential role of exercise in promoting neuroplasticity and repair in Parkinson’s disease (PD). Exercise interventions in individuals with PD incorporate goal-based motor skill training in order to engage cognitive circuitry important in motor learning. Using this exercise approach, physical therapy facilitates learning through instruction and feedback (reinforcement), and encouragement to perform beyond self-perceived capability. Individuals with PD become more cognitively engaged with the practice and learning of movements and skills that were previously automatic and unconscious. Studies that have incorporated both goal-based training and aerobic exercise have supported the potential for improving both cognitive and automatic components of motor control. Utilizing animal models, basic research is beginning to reveal exercise-induced effects on neuroplasticity. Since neuroplasticity occurs at the level of circuits and synaptic connections, we examine the effects of exercise from this perspective. PMID:23769598
Ma, Xiaofeng; Kohashi, Tsunehiko; Carlson, Bruce A
2013-07-01
Many sensory brain regions are characterized by extensive local network interactions. However, we know relatively little about the contribution of this microcircuitry to sensory coding. Detailed analyses of neuronal microcircuitry are usually performed in vitro, whereas sensory processing is typically studied by recording from individual neurons in vivo. The electrosensory pathway of mormyrid fish provides a unique opportunity to link in vitro studies of synaptic physiology with in vivo studies of sensory processing. These fish communicate by actively varying the intervals between pulses of electricity. Within the midbrain posterior exterolateral nucleus (ELp), the temporal filtering of afferent spike trains establishes interval tuning by single neurons. We characterized pairwise neuronal connectivity among ELp neurons with dual whole cell recording in an in vitro whole brain preparation. We found a densely connected network in which single neurons influenced the responses of other neurons throughout the network. Similarly tuned neurons were more likely to share an excitatory synaptic connection than differently tuned neurons, and synaptic connections between similarly tuned neurons were stronger than connections between differently tuned neurons. We propose a general model for excitatory network interactions in which strong excitatory connections both reinforce and adjust tuning and weak excitatory connections make smaller modifications to tuning. The diversity of interval tuning observed among this population of neurons can be explained, in part, by each individual neuron receiving a different complement of local excitatory inputs.
High density electrical card connector system
Haggard, J. Eric; Trotter, Garrett R.
2000-01-01
An electrical circuit board card connection system is disclosed which comprises a wedge-operated locking mechanism disposed along an edge portion of the printed circuit board. An extrusion along the edge of the circuit board mates with an extrusion fixed to the card cage having a plurality of electrical connectors. The connection system allows the connectors to be held away from the circuit board during insertion/extraction and provides a constant mating force once the circuit board is positioned and the wedge inserted. The disclosed connection system is a simple solution to the need for a greater number of electrical signal connections.
Circuit for high resolution decoding of multi-anode microchannel array detectors
NASA Technical Reports Server (NTRS)
Kasle, David B. (Inventor)
1995-01-01
A circuit for high resolution decoding of multi-anode microchannel array detectors consisting of input registers accepting transient inputs from the anode array; anode encoding logic circuits connected to the input registers; midpoint pipeline registers connected to the anode encoding logic circuits; and pixel decoding logic circuits connected to the midpoint pipeline registers is described. A high resolution algorithm circuit operates in parallel with the pixel decoding logic circuit and computes a high resolution least significant bit to enhance the multianode microchannel array detector's spatial resolution by halving the pixel size and doubling the number of pixels in each axis of the anode array. A multiplexer is connected to the pixel decoding logic circuit and allows a user selectable pixel address output according to the actual multi-anode microchannel array detector anode array size. An output register concatenates the high resolution least significant bit onto the standard ten bit pixel address location to provide an eleven bit pixel address, and also stores the full eleven bit pixel address. A timing and control state machine is connected to the input registers, the anode encoding logic circuits, and the output register for managing the overall operation of the circuit.
Critical period plasticity is disrupted in the barrel cortex of Fmr1 knockout mice
Harlow, Emily G.; Till, Sally M.; Russell, Theron A.; Wijetunge, Lasani S.; Kind, Peter; Contractor, Anis
2010-01-01
Summary Alterations in sensory processing constitute prominent symptoms of Fragile X syndrome; however, little is known about how disrupted synaptic and circuit development in sensory cortex contributes to these deficits. To investigate how the loss of fragile X mental retardation protein (FMRP) impacts the development of cortical synapses, we examined excitatory thalamocortical synapses in somatosensory cortex during the perinatal critical period in Fmr1 knockout mice. FMRP ablation resulted in dysregulation of glutamatergic signaling maturation. The fraction of silent synapses persisting to later developmental times was increased, there was a temporal delay in the window for synaptic plasticity, while other forms of developmental plasticity were not altered in Fmr1 knockout mice. Our results indicate that FMRP is required for the normal developmental progression of synaptic maturation, and loss of this important RNA binding protein impacts the timing of the critical period for layer IV synaptic plasticity. PMID:20159451
Pomeranz, Lisa E.; Ekstrand, Mats I.; Latcha, Kaamashri N.; Smith, Gregory A.; Enquist, Lynn W.
2017-01-01
The mesolimbic dopamine pathway receives inputs from numerous regions of the brain as part of a neural system that detects rewarding stimuli and coordinates a behavioral response. The capacity to simultaneously map and molecularly define the components of this complex multisynaptic circuit would thus advance our understanding of the determinants of motivated behavior. To accomplish this, we have constructed pseudorabies virus (PRV) strains in which viral propagation and fluorophore expression are activated only after exposure to Cre recombinase. Once activated in Cre-expressing neurons, the virus serially labels chains of presynaptic neurons. Dual injection of GFP and mCherry tracing viruses simultaneously illuminates nigrostriatal and mesolimbic circuitry and shows no overlap, demonstrating that PRV transmission is confined to synaptically connected neurons. To molecularly profile mesolimbic dopamine neurons and their presynaptic inputs, we injected Cre-conditional GFP virus into the NAc of (anti-GFP) nanobody-L10 transgenic mice and immunoprecipitated translating ribosomes from neurons infected after retrograde tracing. Analysis of purified RNA revealed an enrichment of transcripts expressed in neurons of the dorsal raphe nuclei and lateral hypothalamus that project to the mesolimbic dopamine circuit. These studies identify important inputs to the mesolimbic dopamine pathway and further show that PRV circuit-directed translating ribosome affinity purification can be broadly applied to identify molecularly defined neurons comprising complex, multisynaptic circuits. SIGNIFICANCE STATEMENT The mesolimbic dopamine circuit integrates signals from key brain regions to detect and respond to rewarding stimuli. To further define this complex multisynaptic circuit, we constructed a panel of Cre recombinase-activated pseudorabies viruses (PRVs) that enabled retrograde tracing of neural inputs that terminate on Cre-expressing neurons. Using these viruses and Retro-TRAP (translating ribosome affinity purification), a previously reported molecular profiling method, we developed a novel technique that provides anatomic as well as molecular information about the neural components of polysynaptic circuits. We refer to this new method as PRV-Circuit-TRAP (PRV circuit-directed TRAP). Using it, we have identified major projections to the mesolimbic dopamine circuit from the lateral hypothalamus and dorsal raphe nucleus and defined a discrete subset of transcripts expressed in these projecting neurons, which will allow further characterization of this important pathway. Moreover, the method we report is general and can be applied to the study of other neural circuits. PMID:28283558
Distinct cortical circuit mechanisms for complex forelimb movement and motor map topography.
Harrison, Thomas C; Ayling, Oliver G S; Murphy, Timothy H
2012-04-26
Cortical motor maps are the basis of voluntary movement, but they have proven difficult to understand in the context of their underlying neuronal circuits. We applied light-based motor mapping of Channelrhodopsin-2 mice to reveal a functional subdivision of the forelimb motor cortex based on the direction of movement evoked by brief (10 ms) pulses. Prolonged trains of electrical or optogenetic stimulation (100-500 ms) targeted to anterior or posterior subregions of motor cortex evoked reproducible complex movements of the forelimb to distinct positions in space. Blocking excitatory cortical synaptic transmission did not abolish basic motor map topography, but the site-specific expression of complex movements was lost. Our data suggest that the topography of movement maps arises from their segregated output projections, whereas complex movements evoked by prolonged stimulation require intracortical synaptic transmission. Copyright © 2012 Elsevier Inc. All rights reserved.
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
Deconstruction of a neural circuit for hunger.
Atasoy, Deniz; Betley, J Nicholas; Su, Helen H; Sternson, Scott M
2012-08-09
Hunger is a complex behavioural state that elicits intense food seeking and consumption. These behaviours are rapidly recapitulated by activation of starvation-sensitive AGRP neurons, which present an entry point for reverse-engineering neural circuits for hunger. Here we mapped synaptic interactions of AGRP neurons with multiple cell populations in mice and probed the contribution of these distinct circuits to feeding behaviour using optogenetic and pharmacogenetic techniques. An inhibitory circuit with paraventricular hypothalamus (PVH) neurons substantially accounted for acute AGRP neuron-evoked eating, whereas two other prominent circuits were insufficient. Within the PVH, we found that AGRP neurons target and inhibit oxytocin neurons, a small population that is selectively lost in Prader-Willi syndrome, a condition involving insatiable hunger. By developing strategies for evaluating molecularly defined circuits, we show that AGRP neuron suppression of oxytocin neurons is critical for evoked feeding. These experiments reveal a new neural circuit that regulates hunger state and pathways associated with overeating disorders.
Deconstruction of a neural circuit for hunger
Atasoy, Deniz; Betley, J. Nicholas; Su, Helen H.; Sternson, Scott M.
2012-01-01
Hunger is a complex behavioural state that elicits intense food seeking and consumption. These behaviours are rapidly recapitulated by activation of starvation-sensitive AGRP neurons, which present an entry point for reverse-engineering neural circuits for hunger. We mapped synaptic interactions of AGRP neurons with multiple cell populations and probed the contribution of these distinct circuits to feeding behaviour using optogenetic and pharmacogenetic techniques. An inhibitory circuit with paraventricular hypothalamus (PVH) neurons substantially accounted for acute AGRP neuron-evoked eating, whereas two other prominent circuits were insufficient. Within the PVH, we found that AGRP neurons target and inhibit oxytocin neurons, a small population that is selectively lost in Prader-Willi syndrome, a condition involving insatiable hunger. By developing strategies for evaluating molecularly-defined circuits, we show that AGRP neuron suppression of oxytocin neurons is critical for evoked feeding. These experiments reveal a new neural circuit that regulates hunger state and pathways associated with overeating disorders. PMID:22801496
Oxytocin modulation of neural circuits for social behavior.
Marlin, Bianca J; Froemke, Robert C
2017-02-01
Oxytocin is a hypothalamic neuropeptide that has gained attention for the effects on social behavior. Recent findings shed new light on the mechanisms of oxytocin in synaptic plasticity and adaptively modifying neural circuits for social interactions such as conspecific recognition, pair bonding, and maternal care. Here, we review several of these newer studies on oxytocin in the context of previous findings, with an emphasis on social behavior and circuit plasticity in various brain regions shown to be enriched for oxytocin receptors. We provide a framework that highlights current circuit-level mechanisms underlying the widespread action of oxytocin. © 2016 Wiley Periodicals, Inc. Develop Neurobiol 77: 169-189, 2017. © 2016 Wiley Periodicals, Inc.
Levy, Manuel; Schramm, Adrien E.; Kara, Prakash
2012-01-01
Uncovering the functional properties of individual synaptic inputs on single neurons is critical for understanding the computational role of synapses and dendrites. Previous studies combined whole-cell patch recording to load neurons with a fluorescent calcium indicator and two-photon imaging to map subcellular changes in fluorescence upon sensory stimulation. By hyperpolarizing the neuron below spike threshold, the patch electrode ensured that changes in fluorescence associated with synaptic events were isolated from those caused by back-propagating action potentials. This technique holds promise for determining whether the existence of unique cortical feature maps across different species may be associated with distinct wiring diagrams. However, the use of whole-cell patch for mapping inputs on dendrites is challenging in large mammals, due to brain pulsations and the accumulation of fluorescent dye in the extracellular milieu. Alternatively, sharp intracellular electrodes have been used to label neurons with fluorescent dyes, but the current passing capabilities of these high impedance electrodes may be insufficient to prevent spiking. In this study, we tested whether sharp electrode recording is suitable for mapping functional inputs on dendrites in the cat visual cortex. We compared three different strategies for suppressing visually evoked spikes: (1) hyperpolarization by intracellular current injection, (2) pharmacological blockade of voltage-gated sodium channels by intracellular QX-314, and (3) GABA iontophoresis from a perisomatic electrode glued to the intracellular electrode. We found that functional inputs on dendrites could be successfully imaged using all three strategies. However, the best method for preventing spikes was GABA iontophoresis with low currents (5–10 nA), which minimally affected the local circuit. Our methods advance the possibility of determining functional connectivity in preparations where whole-cell patch may be impractical. PMID:23248588
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.
A modeling approach on why simple central pattern generators are built of irregular neurons.
Reyes, Marcelo Bussotti; Carelli, Pedro Valadão; Sartorelli, José Carlos; Pinto, Reynaldo Daniel
2015-01-01
The crustacean pyloric Central Pattern Generator (CPG) is a nervous circuit that endogenously provides periodic motor patterns. Even after about 40 years of intensive studies, the rhythm genesis is still not rigorously understood in this CPG, mainly because it is made of neurons with irregular intrinsic activity. Using mathematical models we addressed the question of using a network of irregularly behaving elements to generate periodic oscillations, and we show some advantages of using non-periodic neurons with intrinsic behavior in the transition from bursting to tonic spiking (as found in biological pyloric CPGs) as building components. We studied two- and three-neuron model CPGs built either with Hindmarsh-Rose or with conductance-based Hodgkin-Huxley-like model neurons. By changing a model's parameter we could span the neuron's intrinsic dynamical behavior from slow periodic bursting to fast tonic spiking, passing through a transition where irregular bursting was observed. Two-neuron CPG, half center oscillator (HCO), was obtained for each intrinsic behavior of the neurons by coupling them with mutual symmetric synaptic inhibition. Most of these HCOs presented regular antiphasic bursting activity and the changes of the bursting frequencies was studied as a function of the inhibitory synaptic strength. Among all HCOs, those made of intrinsic irregular neurons presented a wider burst frequency range while keeping a reliable regular oscillatory (bursting) behavior. HCOs of periodic neurons tended to be either hard to change their behavior with synaptic strength variations (slow periodic burster neurons) or unable to perform a physiologically meaningful rhythm (fast tonic spiking neurons). Moreover, 3-neuron CPGs with connectivity and output similar to those of the pyloric CPG presented the same results.
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
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.
Binary synaptic connections based on memory switching in a-Si:H for artificial neural networks
NASA Technical Reports Server (NTRS)
Thakoor, A. P.; Lamb, J. L.; Moopenn, A.; Khanna, S. K.
1987-01-01
A scheme for nonvolatile associative electronic memory storage with high information storage density is proposed which is based on neural network models and which uses a matrix of two-terminal passive interconnections (synapses). It is noted that the massive parallelism in the architecture would require the ON state of a synaptic connection to be unusually weak (highly resistive). Memory switching using a-Si:H along with ballast resistors patterned from amorphous Ge-metal alloys is investigated for a binary programmable read only memory matrix. The fabrication of a 1600 synapse test array of uniform connection strengths and a-Si:H switching elements is discussed.
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
Memory replay in balanced recurrent networks
Chenkov, Nikolay; Sprekeler, Henning; Kempter, Richard
2017-01-01
Complex patterns of neural activity appear during up-states in the neocortex and sharp waves in the hippocampus, including sequences that resemble those during prior behavioral experience. The mechanisms underlying this replay are not well understood. How can small synaptic footprints engraved by experience control large-scale network activity during memory retrieval and consolidation? We hypothesize that sparse and weak synaptic connectivity between Hebbian assemblies are boosted by pre-existing recurrent connectivity within them. To investigate this idea, we connect sequences of assemblies in randomly connected spiking neuronal networks with a balance of excitation and inhibition. Simulations and analytical calculations show that recurrent connections within assemblies allow for a fast amplification of signals that indeed reduces the required number of inter-assembly connections. Replay can be evoked by small sensory-like cues or emerge spontaneously by activity fluctuations. Global—potentially neuromodulatory—alterations of neuronal excitability can switch between network states that favor retrieval and consolidation. PMID:28135266
Energy-efficient neural information processing in individual neurons and neuronal networks.
Yu, Lianchun; Yu, Yuguo
2017-11-01
Brains are composed of networks of an enormous number of neurons interconnected with synapses. Neural information is carried by the electrical signals within neurons and the chemical signals among neurons. Generating these electrical and chemical signals is metabolically expensive. The fundamental issue raised here is whether brains have evolved efficient ways of developing an energy-efficient neural code from the molecular level to the circuit level. Here, we summarize the factors and biophysical mechanisms that could contribute to the energy-efficient neural code for processing input signals. The factors range from ion channel kinetics, body temperature, axonal propagation of action potentials, low-probability release of synaptic neurotransmitters, optimal input and noise, the size of neurons and neuronal clusters, excitation/inhibition balance, coding strategy, cortical wiring, and the organization of functional connectivity. Both experimental and computational evidence suggests that neural systems may use these factors to maximize the efficiency of energy consumption in processing neural signals. Studies indicate that efficient energy utilization may be universal in neuronal systems as an evolutionary consequence of the pressure of limited energy. As a result, neuronal connections may be wired in a highly economical manner to lower energy costs and space. Individual neurons within a network may encode independent stimulus components to allow a minimal number of neurons to represent whole stimulus characteristics efficiently. This basic principle may fundamentally change our view of how billions of neurons organize themselves into complex circuits to operate and generate the most powerful intelligent cognition in nature. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
Optimizing the 3D-reconstruction technique for serial block-face scanning electron microscopy.
Wernitznig, Stefan; Sele, Mariella; Urschler, Martin; Zankel, Armin; Pölt, Peter; Rind, F Claire; Leitinger, Gerd
2016-05-01
Elucidating the anatomy of neuronal circuits and localizing the synaptic connections between neurons, can give us important insights in how the neuronal circuits work. We are using serial block-face scanning electron microscopy (SBEM) to investigate the anatomy of a collision detection circuit including the Lobula Giant Movement Detector (LGMD) neuron in the locust, Locusta migratoria. For this, thousands of serial electron micrographs are produced that allow us to trace the neuronal branching pattern. The reconstruction of neurons was previously done manually by drawing cell outlines of each cell in each image separately. This approach was very time consuming and troublesome. To make the process more efficient a new interactive software was developed. It uses the contrast between the neuron under investigation and its surrounding for semi-automatic segmentation. For segmentation the user sets starting regions manually and the algorithm automatically selects a volume within the neuron until the edges corresponding to the neuronal outline are reached. Internally the algorithm optimizes a 3D active contour segmentation model formulated as a cost function taking the SEM image edges into account. This reduced the reconstruction time, while staying close to the manual reference segmentation result. Our algorithm is easy to use for a fast segmentation process, unlike previous methods it does not require image training nor an extended computing capacity. Our semi-automatic segmentation algorithm led to a dramatic reduction in processing time for the 3D-reconstruction of identified neurons. Copyright © 2016 Elsevier B.V. All rights reserved.
Sears, James C.; Broadie, Kendal
2018-01-01
Fragile X syndrome (FXS) is the leading monogenic cause of autism and intellectual disability. The disease arises through loss of fragile X mental retardation protein (FMRP), which normally exhibits peak expression levels in early-use critical periods, and is required for activity-dependent synaptic remodeling during this transient developmental window. FMRP canonically binds mRNA to repress protein translation, with targets that regulate cytoskeleton dynamics, membrane trafficking, and trans-synaptic signaling. We focus here on recent advances emerging in these three areas from the Drosophila disease model. In the well-characterized central brain mushroom body (MB) olfactory learning/memory circuit, FMRP is required for activity-dependent synaptic remodeling of projection neurons innervating the MB calyx, with function tightly restricted to an early-use critical period. FMRP loss is phenocopied by conditional removal of FMRP only during this critical period, and rescued by FMRP conditional expression only during this critical period. Consistent with FXS hyperexcitation, FMRP loss defects are phenocopied by heightened sensory experience and targeted optogenetic hyperexcitation during this critical period. FMRP binds mRNA encoding Drosophila ESCRTIII core component Shrub (human CHMP4 homolog) to restrict Shrub translation in an activity-dependent mechanism only during this same critical period. Shrub mediates endosomal membrane trafficking, and perturbing Shrub expression is known to interfere with neuronal process pruning. Consistently, FMRP loss and Shrub overexpression targeted to projection neurons similarly causes endosomal membrane trafficking defects within synaptic boutons, and genetic reduction of Shrub strikingly rescues Drosophila FXS model defects. In parallel work on the well-characterized giant fiber (GF) circuit, FMRP limits iontophoretic dye loading into central interneurons, demonstrating an FMRP role controlling core neuronal properties through the activity-dependent repression of translation. In the well-characterized Drosophila neuromuscular junction (NMJ) model, developmental synaptogenesis and activity-dependent synaptic remodeling both require extracellular matrix metalloproteinase (MMP) enzymes interacting with the heparan sulfate proteoglycan (HSPG) glypican dally-like protein (Dlp) to restrict trans-synaptic Wnt signaling, with FXS synaptogenic defects alleviated by both MMP and HSPG reduction. This new mechanistic axis spanning from activity to FMRP to HSPG-dependent MMP regulation modulates activity-dependent synaptogenesis. We discuss future directions for these mechanisms, and intersecting research priorities for FMRP in glial and signaling interactions. PMID:29375303
Over-voltage protection system and method
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chi, Song; Dong, Dong; Lai, Rixin
An over-voltage protection system includes an electronic valve connected across two terminals of a circuit and an over-voltage detection circuit connected across one of the plurality of semiconductor devices for detecting an over-voltage across the circuit. The electronic valve includes a plurality of semiconductor devices connected in series. The over-voltage detection circuit includes a voltage divider circuit connected to a break-over diode in a way to provide a representative low voltage to the break-over diode and an optocoupler configured to receive a current from the break-over diode when the representative low voltage exceeds a threshold voltage of the break-over diodemore » indicating an over-voltage condition. The representative low voltage provided to the break-over diode represents a voltage across the one semiconductor device. A plurality of self-powered gate drive circuits are connected to the plurality of semiconductor devices, wherein the plurality of self-powered gate drive circuits receive over-voltage triggering pulses from the optocoupler during the over-voltage condition and switch on the plurality of semiconductor devices to bypass the circuit.« less
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.
Long-term potentiation and long-term depression: a clinical perspective
Bliss, Timothy V.P.; Cooke, Sam F
2011-01-01
Long-term potentiation and long-term depression are enduring changes in synaptic strength, induced by specific patterns of synaptic activity, that have received much attention as cellular models of information storage in the central nervous system. Work in a number of brain regions, from the spinal cord to the cerebral cortex, and in many animal species, ranging from invertebrates to humans, has demonstrated a reliable capacity for chemical synapses to undergo lasting changes in efficacy in response to a variety of induction protocols. In addition to their physiological relevance, long-term potentiation and depression may have important clinical applications. A growing insight into the molecular mechanisms underlying these processes, and technological advances in non-invasive manipulation of brain activity, now puts us at the threshold of harnessing long-term potentiation and depression and other forms of synaptic, cellular and circuit plasticity to manipulate synaptic strength in the human nervous system. Drugs may be used to erase or treat pathological synaptic states and non-invasive stimulation devices may be used to artificially induce synaptic plasticity to ameliorate conditions arising from disrupted synaptic drive. These approaches hold promise for the treatment of a variety of neurological conditions, including neuropathic pain, epilepsy, depression, amblyopia, tinnitus and stroke. PMID:21779718
Dynamic Control of Synaptic Adhesion and Organizing Molecules in Synaptic Plasticity
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rudenko, Gabby
Synapses play a critical role in establishing and maintaining neural circuits, permitting targeted information transfer throughout the brain. A large portfolio of synaptic adhesion/organizing molecules (SAMs) exists in the mammalian brain involved in synapse development and maintenance. SAMs bind protein partners, formingtrans-complexes spanning the synaptic cleft orcis-complexes attached to the same synaptic membrane. SAMs play key roles in cell adhesion and in organizing protein interaction networks; they can also provide mechanisms of recognition, generate scaffolds onto which partners can dock, and likely take part in signaling processes as well. SAMs are regulated through a portfolio of different mechanisms that affectmore » their protein levels, precise localization, stability, and the availability of their partners at synapses. Interaction of SAMs with their partners can further be strengthened or weakened through alternative splicing, competing protein partners, ectodomain shedding, or astrocytically secreted factors. Given that numerous SAMs appear altered by synaptic activity, in vivo, these molecules may be used to dynamically scale up or scale down synaptic communication. Many SAMs, including neurexins, neuroligins, cadherins, and contactins, are now implicated in neuropsychiatric and neurodevelopmental diseases, such as autism spectrum disorder, schizophrenia, and bipolar disorder and studying their molecular mechanisms holds promise for developing novel therapeutics.« less
Dynamic Control of Synaptic Adhesion and Organizing Molecules in Synaptic Plasticity
2017-01-01
Synapses play a critical role in establishing and maintaining neural circuits, permitting targeted information transfer throughout the brain. A large portfolio of synaptic adhesion/organizing molecules (SAMs) exists in the mammalian brain involved in synapse development and maintenance. SAMs bind protein partners, forming trans-complexes spanning the synaptic cleft or cis-complexes attached to the same synaptic membrane. SAMs play key roles in cell adhesion and in organizing protein interaction networks; they can also provide mechanisms of recognition, generate scaffolds onto which partners can dock, and likely take part in signaling processes as well. SAMs are regulated through a portfolio of different mechanisms that affect their protein levels, precise localization, stability, and the availability of their partners at synapses. Interaction of SAMs with their partners can further be strengthened or weakened through alternative splicing, competing protein partners, ectodomain shedding, or astrocytically secreted factors. Given that numerous SAMs appear altered by synaptic activity, in vivo, these molecules may be used to dynamically scale up or scale down synaptic communication. Many SAMs, including neurexins, neuroligins, cadherins, and contactins, are now implicated in neuropsychiatric and neurodevelopmental diseases, such as autism spectrum disorder, schizophrenia, and bipolar disorder and studying their molecular mechanisms holds promise for developing novel therapeutics. PMID:28255461
Federal Register 2010, 2011, 2012, 2013, 2014
2013-05-07
... gigabyte Copper circuit; $750 per physical port that connects to the System via a 1 gigabyte Fiber circuit; and $1,000 per physical port that connects to the System via a 10 gigabyte Fiber circuit. The Exchange... physical port that connects to the System via a 1 gigabyte Fiber circuit from $750 to $1,000; (ii) increase...
Held, Martina; Berz, Annuska; Hensgen, Ronja; Muenz, Thomas S; Scholl, Christina; Rössler, Wolfgang; Homberg, Uwe; Pfeiffer, Keram
2016-01-01
While the ability of honeybees to navigate relying on sky-compass information has been investigated in a large number of behavioral studies, the underlying neuronal system has so far received less attention. The sky-compass pathway has recently been described from its input region, the dorsal rim area (DRA) of the compound eye, to the anterior optic tubercle (AOTU). The aim of this study is to reveal the connection from the AOTU to the central complex (CX). For this purpose, we investigated the anatomy of large microglomerular synaptic complexes in the medial and lateral bulbs (MBUs/LBUs) of the lateral complex (LX). The synaptic complexes are formed by tubercle-lateral accessory lobe neuron 1 (TuLAL1) neurons of the AOTU and GABAergic tangential neurons of the central body's (CB) lower division (TL neurons). Both TuLAL1 and TL neurons strongly resemble neurons forming these complexes in other insect species. We further investigated the ultrastructure of these synaptic complexes using transmission electron microscopy. We found that single large presynaptic terminals of TuLAL1 neurons enclose many small profiles (SPs) of TL neurons. The synaptic connections between these neurons are established by two types of synapses: divergent dyads and divergent tetrads. Our data support the assumption that these complexes are a highly conserved feature in the insect brain and play an important role in reliable signal transmission within the sky-compass pathway.
Circuits Protect Against Incorrect Power Connections
NASA Technical Reports Server (NTRS)
Delombard, Richard
1992-01-01
Simple circuits prevent application of incorrectly polarized or excessive voltages. Connected temporarily or permanently at power-connecting terminals. Devised to protect electrical and electronic equipment installed in spacecraft and subjected to variety of tests in different facilities prior to installation. Basic concept of protective circuits also applied easily to many kinds of electrical and electronic equipment that must be protected against incorrect power connections.
Audiovisual Rehabilitation in Hemianopia: A Model-Based Theoretical Investigation
Magosso, Elisa; Cuppini, Cristiano; Bertini, Caterina
2017-01-01
Hemianopic patients exhibit visual detection improvement in the blind field when audiovisual stimuli are given in spatiotemporally coincidence. Beyond this “online” multisensory improvement, there is evidence of long-lasting, “offline” effects induced by audiovisual training: patients show improved visual detection and orientation after they were trained to detect and saccade toward visual targets given in spatiotemporal proximity with auditory stimuli. These effects are ascribed to the Superior Colliculus (SC), which is spared in these patients and plays a pivotal role in audiovisual integration and oculomotor behavior. Recently, we developed a neural network model of audiovisual cortico-collicular loops, including interconnected areas representing the retina, striate and extrastriate visual cortices, auditory cortex, and SC. The network simulated unilateral V1 lesion with possible spared tissue and reproduced “online” effects. Here, we extend the previous network to shed light on circuits, plastic mechanisms, and synaptic reorganization that can mediate the training effects and functionally implement visual rehabilitation. The network is enriched by the oculomotor SC-brainstem route, and Hebbian mechanisms of synaptic plasticity, and is used to test different training paradigms (audiovisual/visual stimulation in eye-movements/fixed-eyes condition) on simulated patients. Results predict different training effects and associate them to synaptic changes in specific circuits. Thanks to the SC multisensory enhancement, the audiovisual training is able to effectively strengthen the retina-SC route, which in turn can foster reinforcement of the SC-brainstem route (this occurs only in eye-movements condition) and reinforcement of the SC-extrastriate route (this occurs in presence of survived V1 tissue, regardless of eye condition). The retina-SC-brainstem circuit may mediate compensatory effects: the model assumes that reinforcement of this circuit can translate visual stimuli into short-latency saccades, possibly moving the stimuli into visual detection regions. The retina-SC-extrastriate circuit is related to restitutive effects: visual stimuli can directly elicit visual detection with no need for eye movements. Model predictions and assumptions are critically discussed in view of existing behavioral and neurophysiological data, forecasting that other oculomotor compensatory mechanisms, beyond short-latency saccades, are likely involved, and stimulating future experimental and theoretical investigations. PMID:29326578
Audiovisual Rehabilitation in Hemianopia: A Model-Based Theoretical Investigation.
Magosso, Elisa; Cuppini, Cristiano; Bertini, Caterina
2017-01-01
Hemianopic patients exhibit visual detection improvement in the blind field when audiovisual stimuli are given in spatiotemporally coincidence. Beyond this "online" multisensory improvement, there is evidence of long-lasting, "offline" effects induced by audiovisual training: patients show improved visual detection and orientation after they were trained to detect and saccade toward visual targets given in spatiotemporal proximity with auditory stimuli. These effects are ascribed to the Superior Colliculus (SC), which is spared in these patients and plays a pivotal role in audiovisual integration and oculomotor behavior. Recently, we developed a neural network model of audiovisual cortico-collicular loops, including interconnected areas representing the retina, striate and extrastriate visual cortices, auditory cortex, and SC. The network simulated unilateral V1 lesion with possible spared tissue and reproduced "online" effects. Here, we extend the previous network to shed light on circuits, plastic mechanisms, and synaptic reorganization that can mediate the training effects and functionally implement visual rehabilitation. The network is enriched by the oculomotor SC-brainstem route, and Hebbian mechanisms of synaptic plasticity, and is used to test different training paradigms (audiovisual/visual stimulation in eye-movements/fixed-eyes condition) on simulated patients. Results predict different training effects and associate them to synaptic changes in specific circuits. Thanks to the SC multisensory enhancement, the audiovisual training is able to effectively strengthen the retina-SC route, which in turn can foster reinforcement of the SC-brainstem route (this occurs only in eye-movements condition) and reinforcement of the SC-extrastriate route (this occurs in presence of survived V1 tissue, regardless of eye condition). The retina-SC-brainstem circuit may mediate compensatory effects: the model assumes that reinforcement of this circuit can translate visual stimuli into short-latency saccades, possibly moving the stimuli into visual detection regions. The retina-SC-extrastriate circuit is related to restitutive effects: visual stimuli can directly elicit visual detection with no need for eye movements. Model predictions and assumptions are critically discussed in view of existing behavioral and neurophysiological data, forecasting that other oculomotor compensatory mechanisms, beyond short-latency saccades, are likely involved, and stimulating future experimental and theoretical investigations.
Nlgn4 knockout induces network hypo-excitability in juvenile mouse somatosensory cortex in vitro.
Delattre, V; La Mendola, D; Meystre, J; Markram, H; Markram, K
2013-10-09
Neuroligins (Nlgns) are postsynaptic cell adhesion molecules that form transynaptic complexes with presynaptic neurexins and regulate synapse maturation and plasticity. We studied the impact of the loss of Nlgn4 on the excitatory and inhibitory circuits in somatosensory cortical slices of juvenile mice by electrically stimulating these circuits using a multi-electrode array and recording the synaptic input to single neurons using the patch-clamp technique. We detected a decreased network response to stimulation in both excitatory and inhibitory circuits of Nlgn4 knock-out animals as compared to wild-type controls, and a decreased excitation-inhibition ratio. These data indicate that Nlgn4 is involved in the regulation of excitatory and inhibitory circuits and contributes to a balanced circuit response to stimulation.
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2012-08-17
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Law, Chris; Schaan Profes, Marcos; Levesque, Martin; Kaltschmidt, Julia A; Verhage, Matthijs; Kania, Artur
2016-01-13
The role of synaptic activity during early formation of neural circuits is a topic of some debate; genetic ablation of neurotransmitter release by deletion of the Munc18-1 gene provides an excellent model to answer the question of whether such activity is required for early circuit formation. Previous analysis of Munc18-1(-/-) mouse mutants documented their grossly normal nervous system, but its molecular differentiation has not been assessed. Munc18-1 deletion in mice also results in widespread neurodegeneration that remains poorly characterized. In this study, we demonstrate that the early stages of spinal motor circuit formation, including motor neuron specification, axon growth and pathfinding, and mRNA expression, are unaffected in Munc18-1(-/-) mice, demonstrating that synaptic activity is dispensable for early nervous system development. Furthermore, we show that the neurodegeneration caused by Munc18-1 loss is cell autonomous, consistent with apparently normal expression of several neurotrophic factors and normal GDNF signaling. Consistent with cell-autonomous degeneration, we demonstrate defects in the trafficking of the synaptic proteins Syntaxin1a and PSD-95 and the TrkB and DCC receptors in Munc18-1(-/-) neurons; these defects do not appear to cause ER stress, suggesting other mechanisms for degeneration. Finally, we demonstrate pathological similarities to Alzheimer's disease, such as altered Tau phosphorylation, neurofibrillary tangles, and accumulation of insoluble protein plaques. Together, our results shed new light upon the neurodegeneration observed in Munc18-1(-/-) mice and argue that this phenomenon shares parallels with neurodegenerative diseases. In this work, we demonstrate the absence of a requirement for regulated neurotransmitter release in the assembly of early neuronal circuits by assaying transcriptional identity, axon growth and guidance, and mRNA expression in Munc18-1-null mice. Furthermore, we characterize the neurodegeneration observed in Munc18-1 mutants and demonstrate that this cell-autonomous process does not appear to be a result of defects in growth factor signaling or ER stress caused by protein trafficking defects. However, we find the presence of various pathological hallmarks of Alzheimer's disease that suggest parallels between the degeneration in these mutants and neurodegenerative conditions. Copyright © 2016 the authors 0270-6474/16/360562-16$15.00/0.
An automated detection for axonal boutons in vivo two-photon imaging of mouse
NASA Astrophysics Data System (ADS)
Li, Weifu; Zhang, Dandan; Xie, Qiwei; Chen, Xi; Han, Hua
2017-02-01
Activity-dependent changes in the synaptic connections of the brain are tightly related to learning and memory. Previous studies have shown that essentially all new synaptic contacts were made by adding new partners to existing synaptic elements. To further explore synaptic dynamics in specific pathways, concurrent imaging of pre and postsynaptic structures in identified connections is required. Consequently, considerable attention has been paid for the automated detection of axonal boutons. Different from most previous methods proposed in vitro data, this paper considers a more practical case in vivo neuron images which can provide real time information and direct observation of the dynamics of a disease process in mouse. Additionally, we present an automated approach for detecting axonal boutons by starting with deconvolving the original images, then thresholding the enhanced images, and reserving the regions fulfilling a series of criteria. Experimental result in vivo two-photon imaging of mouse demonstrates the effectiveness of our proposed method.
Apparatus for and method of testing an electrical ground fault circuit interrupt device
Andrews, L.B.
1998-08-18
An apparatus for testing a ground fault circuit interrupt device includes a processor, an input device connected to the processor for receiving input from an operator, a storage media connected to the processor for storing test data, an output device connected to the processor for outputting information corresponding to the test data to the operator, and a calibrated variable load circuit connected between the processor and the ground fault circuit interrupt device. The ground fault circuit interrupt device is configured to trip a corresponding circuit breaker. The processor is configured to receive signals from the calibrated variable load circuit and to process the signals to determine a trip threshold current and/or a trip time. A method of testing the ground fault circuit interrupt device includes a first step of providing an identification for the ground fault circuit interrupt device. Test data is then recorded in accordance with the identification. By comparing test data from an initial test with test data from a subsequent test, a trend of performance for the ground fault circuit interrupt device is determined. 17 figs.
Apparatus for and method of testing an electrical ground fault circuit interrupt device
Andrews, Lowell B.
1998-01-01
An apparatus for testing a ground fault circuit interrupt device includes a processor, an input device connected to the processor for receiving input from an operator, a storage media connected to the processor for storing test data, an output device connected to the processor for outputting information corresponding to the test data to the operator, and a calibrated variable load circuit connected between the processor and the ground fault circuit interrupt device. The ground fault circuit interrupt device is configured to trip a corresponding circuit breaker. The processor is configured to receive signals from the calibrated variable load circuit and to process the signals to determine a trip threshold current and/or a trip time. A method of testing the ground fault circuit interrupt device includes a first step of providing an identification for the ground fault circuit interrupt device. Test data is then recorded in accordance with the identification. By comparing test data from an initial test with test data from a subsequent test, a trend of performance for the ground fault circuit interrupt device is determined.
Synaptic E-I Balance Underlies Efficient Neural Coding.
Zhou, Shanglin; Yu, Yuguo
2018-01-01
Both theoretical and experimental evidence indicate that synaptic excitation and inhibition in the cerebral cortex are well-balanced during the resting state and sensory processing. Here, we briefly summarize the evidence for how neural circuits are adjusted to achieve this balance. Then, we discuss how such excitatory and inhibitory balance shapes stimulus representation and information propagation, two basic functions of neural coding. We also point out the benefit of adopting such a balance during neural coding. We conclude that excitatory and inhibitory balance may be a fundamental mechanism underlying efficient coding.
Synaptic E-I Balance Underlies Efficient Neural Coding
Zhou, Shanglin; Yu, Yuguo
2018-01-01
Both theoretical and experimental evidence indicate that synaptic excitation and inhibition in the cerebral cortex are well-balanced during the resting state and sensory processing. Here, we briefly summarize the evidence for how neural circuits are adjusted to achieve this balance. Then, we discuss how such excitatory and inhibitory balance shapes stimulus representation and information propagation, two basic functions of neural coding. We also point out the benefit of adopting such a balance during neural coding. We conclude that excitatory and inhibitory balance may be a fundamental mechanism underlying efficient coding. PMID:29456491
Late onset deficits in synaptic plasticity in the valproic acid rat model of autism.
Martin, Henry G S; Manzoni, Olivier J
2014-01-01
Valproic acid (VPA) is a frequently used drug in the treatment of epilepsy, bipolar disorders and migraines; however it is also a potent teratogen. Prenatal exposure increases the risk of childhood malformations and can result in cognitive deficits. In rodents in utero exposure to VPA also causes neurodevelopmental abnormalities and is an important model of autism. In early postnatal life VPA exposed rat pups show changes in medial prefrontal cortex (mPFC) physiology and synaptic connectivity. Specifically, principal neurons show decreased excitability but increased local connectivity, coupled with an increase in long-term potentiation (LTP) due to an up-regulation of NMDA receptor (NMDAR) expression. However recent evidence suggests compensatory homeostatic mechanisms lead to normalization of synaptic NMDARs during later postnatal development. Here we have extended study of mPFC synaptic physiology into adulthood to better understand the longitudinal consequences of early developmental abnormalities in VPA exposed rats. Surprisingly in contrast to early postnatal life and adolescence, we find that adult VPA exposed rats show reduced synaptic function. Both NMDAR mediated currents and LTP are lower in adult VPA rats, although spontaneous activity and endocannabinoid dependent long-term depression are normal. We conclude that rather than correcting, synaptic abnormalities persist into adulthood in VPA exposed rats, although a quite different synaptic phenotype is present. This switch from hyper to hypo function in mPFC may be linked to some of the neurodevelopmental defects found in prenatal VPA exposure and autism spectrum disorders in general.
Alexeeva, Vera; Chen, Song-an; Yu, Ke; Due, Michael R.; Tan, Li-nuo; Chen, Ting-ting; Liu, Dan-dan; Cropper, Elizabeth C.; Vilim, Ferdinand S.; Weiss, Klaudiusz R.
2015-01-01
Understanding circuit function requires the characterization of component neurons and their neurotransmitters. Previous work on radula protraction in the Aplysia feeding circuit demonstrated that critical neurons initiate feeding via cholinergic excitation. In contrast, it is less clear how retraction is mediated at the interneuronal level. In particular, glutamate involvement was suggested, but was not directly confirmed. Here we study a suspected glutamatergic retraction interneuron, B64. We used the representational difference analysis (RDA) method to successfully clone an Aplysia vesicular glutamate transporter (ApVGLUT) from B64 and from a glutamatergic motor neuron B38. Previously, RDA was used to characterize novel neuropeptides. Here we demonstrate its utility for characterizing other types of molecules. Bioinformatics suggests that ApVGLUT is more closely related to mammalian VGLUTs than to Drosophila and Caenorhabditis elegans VGLUTs. We expressed ApVGLUT in a cell line, and demonstrated that it indeed transports glutamate in an ATP and proton gradient-dependent manner. We mapped the ApVGLUT distribution in the CNS using in situ hybridization and immunocytochemistry. Further, we demonstrated that B64 is ApVGLUT positive, supporting the idea that it is glutamatergic. Although glutamate is primarily an excitatory transmitter in the mammalian CNS, B64 elicits inhibitory PSPs in protraction neurons to terminate protraction and excitatory PSPs in retraction neurons to maintain retraction. Pharmacological data indicated that both types of PSPs are mediated by glutamate. Thus, glutamate mediates the dual function of B64 in Aplysia. More generally, our systematic approaches based on RDA may facilitate analyses of transmitter actions in small circuits with identifiable neurons. PMID:26085636
Inhibition to excitation ratio regulates visual system responses and behavior in vivo.
Shen, Wanhua; McKeown, Caroline R; Demas, James A; Cline, Hollis T
2011-11-01
The balance of inhibitory to excitatory (I/E) synaptic inputs is thought to control information processing and behavioral output of the central nervous system. We sought to test the effects of the decreased or increased I/E ratio on visual circuit function and visually guided behavior in Xenopus tadpoles. We selectively decreased inhibitory synaptic transmission in optic tectal neurons by knocking down the γ2 subunit of the GABA(A) receptors (GABA(A)R) using antisense morpholino oligonucleotides or by expressing a peptide corresponding to an intracellular loop of the γ2 subunit, called ICL, which interferes with anchoring GABA(A)R at synapses. Recordings of miniature inhibitory postsynaptic currents (mIPSCs) and miniature excitatory PSCs (mEPSCs) showed that these treatments decreased the frequency of mIPSCs compared with control tectal neurons without affecting mEPSC frequency, resulting in an ∼50% decrease in the ratio of I/E synaptic input. ICL expression and γ2-subunit knockdown also decreased the ratio of optic nerve-evoked synaptic I/E responses. We recorded visually evoked responses from optic tectal neurons, in which the synaptic I/E ratio was decreased. Decreasing the synaptic I/E ratio in tectal neurons increased the variance of first spike latency in response to full-field visual stimulation, increased recurrent activity in the tectal circuit, enlarged spatial receptive fields, and lengthened the temporal integration window. We used the benzodiazepine, diazepam (DZ), to increase inhibitory synaptic activity. DZ increased optic nerve-evoked inhibitory transmission but did not affect evoked excitatory currents, resulting in an increase in the I/E ratio of ∼30%. Increasing the I/E ratio with DZ decreased the variance of first spike latency, decreased spatial receptive field size, and lengthened temporal receptive fields. Sequential recordings of spikes and excitatory and inhibitory synaptic inputs to the same visual stimuli demonstrated that decreasing or increasing the I/E ratio disrupted input/output relations. We assessed the effect of an altered I/E ratio on a visually guided behavior that requires the optic tectum. Increasing and decreasing I/E in tectal neurons blocked the tectally mediated visual avoidance behavior. Because ICL expression, γ2-subunit knockdown, and DZ did not directly affect excitatory synaptic transmission, we interpret the results of our study as evidence that partially decreasing or increasing the ratio of I/E disrupts several measures of visual system information processing and visually guided behavior in an intact vertebrate.
Pathological circuit function underlying addiction and anxiety disorders.
Lüthi, Andreas; Lüscher, Christian
2014-12-01
Current models of addiction and anxiety stem from the idea that aberrant function and remodeling of neural circuits cause the pathological behaviors. According to this hypothesis, a disease-defining experience (for example, drug reward or stress) would trigger specific forms of synaptic plasticity, which in susceptible subjects would become persistent and lead to the disease. While the notion of synaptic diseases has received much attention, no candidate disorder has been sufficiently investigated to yield new, rational therapies that could be tested in the clinic. Here we review the arguments in favor of abnormal neuronal plasticity underlying addiction and anxiety disorders, with a focus on the functional diversity of neurons that make up the circuits involved. We argue that future research must strive to obtain a comprehensive description of the relevant functional anatomy. This will allow identification of molecular mechanisms that govern the induction and expression of disease-relevant plasticity in identified neurons. To establish causality, one will have to test whether normalization of function can reverse pathological behavior. With these elements in hand, it will be possible to propose blueprints for manipulations to be tested in translational studies. The challenge is daunting, but new techniques, above all optogenetics, may enable decisive advances.
Corticostriatal circuit defects in Hoxb8 mutant mice
Nagarajan, Naveen; Jones, Bryan W.; West, Peter J.; Marc, Robert; Capecchi, Mario R.
2018-01-01
Hoxb8 mutant mice exhibit compulsive grooming and hair removal dysfunction similar to humans with the OCD-spectrum disorder, trichotillomania. Since, in the mouse brain, the only detectable cells that label with Hoxb8 cell lineage appear to be microglia, we suggested that defective microglia cause the neuropsychiatric disorder. Does the Hoxb8 mutation in microglia lead to neural circuit dysfunctions? We demonstrate that Hoxb8 mutants contain corticostriatal circuit defects. Golgi staining, ultra-structural, and electrophysiological studies of mutants reveal excess dendritic spines, pre- and post-synaptic structural defects, long-term potentiation and miniature postsynaptic current defects. Hoxb8 mutants also exhibit hyperanxiety and social behavioral deficits similar to mice with neuronal mutations in Sapap3, Slitrk5 and Shank3, reported models of OCD and autism spectrum disorders (ASD’s). Long-term treatment of Hoxb8 mutants with fluoxetine, a serotonin reuptake inhibitor (SSRI), reduces excessive grooming, hyperanxiety and social behavioral impairments. These studies provide linkage between the neuronal defects induced by defective Hoxb8-microglia, and neuronal dysfunctions directly generated by mutations in synaptic components that result in mice that display similar pathological grooming, hyperanxiety and social impairment deficits. Our results shed light on Hoxb8 microglia driven circuit-specific defects and therapeutic approaches that will become essential to developing novel therapies for neuropsychiatric diseases such as OCD and ASD’s with Hoxb8-microglia being the central target. PMID:28948967
Reinhard, Sarah M.; Razak, Khaleel; Ethell, Iryna M.
2015-01-01
The extracellular matrix (ECM) is a critical regulator of neural network development and plasticity. As neuronal circuits develop, the ECM stabilizes synaptic contacts, while its cleavage has both permissive and active roles in the regulation of plasticity. Matrix metalloproteinase 9 (MMP-9) is a member of a large family of zinc-dependent endopeptidases that can cleave ECM and several cell surface receptors allowing for synaptic and circuit level reorganization. It is becoming increasingly clear that the regulated activity of MMP-9 is critical for central nervous system (CNS) development. In particular, MMP-9 has a role in the development of sensory circuits during early postnatal periods, called ‘critical periods.’ MMP-9 can regulate sensory-mediated, local circuit reorganization through its ability to control synaptogenesis, axonal pathfinding and myelination. Although activity-dependent activation of MMP-9 at specific synapses plays an important role in multiple plasticity mechanisms throughout the CNS, misregulated activation of the enzyme is implicated in a number of neurodegenerative disorders, including traumatic brain injury, multiple sclerosis, and Alzheimer’s disease. Growing evidence also suggests a role for MMP-9 in the pathophysiology of neurodevelopmental disorders including Fragile X Syndrome. This review outlines the various actions of MMP-9 during postnatal brain development, critical for future studies exploring novel therapeutic strategies for neurodevelopmental disorders. PMID:26283917
Kulkarni, Abhishek; Ertekin, Deniz; Lee, Chi-Hon; Hummel, Thomas
2016-01-01
The precise recognition of appropriate synaptic partner neurons is a critical step during neural circuit assembly. However, little is known about the developmental context in which recognition specificity is important to establish synaptic contacts. We show that in the Drosophila visual system, sequential segregation of photoreceptor afferents, reflecting their birth order, lead to differential positioning of their growth cones in the early target region. By combining loss- and gain-of-function analyses we demonstrate that relative differences in the expression of the transcription factor Sequoia regulate R cell growth cone segregation. This initial growth cone positioning is consolidated via cell-adhesion molecule Capricious in R8 axons. Further, we show that the initial growth cone positioning determines synaptic layer selection through proximity-based axon-target interactions. Taken together, we demonstrate that birth order dependent pre-patterning of afferent growth cones is an essential pre-requisite for the identification of synaptic partner neurons during visual map formation in Drosophila. DOI: http://dx.doi.org/10.7554/eLife.13715.001 PMID:26987017
Diode-quad bridge circuit means
NASA Technical Reports Server (NTRS)
Harrison, D. R.; Dimeff, J. (Inventor)
1975-01-01
Diode-quad bridge circuit means is described for use as a transducer circuit or as a discriminator circuit. It includes: (1) a diode bridge having first, second, third, and fourth bridge terminals consecutively coupled together by four diodes polarized in circulating relationship; (2) a first impedance connected between the second bridge terminal and a circuit ground; (3) a second impedance connected between the fourth bridge terminal and the circuit ground; (4) a signal source having a first source terminal capacitively coupled to the first and third bridge terminals, and a second source terminal connected to the circuit ground; and (5) an output terminal coupled to the first bridge terminal and at which an output signal may be taken.
Wireless power transfer system
Wu, Hunter; Sealy, Kylee; Gilchrist, Aaron
2016-02-23
A system includes a first stage of an inductive power transfer system with an LCL load resonant converter with a switching section, an LCL tuning circuit, and a primary receiver pad. The IPT system includes a second stage with a secondary receiver pad, a secondary resonant circuit, a secondary rectification circuit, and a secondary decoupling converter. The secondary receiver pad connects to the secondary resonant circuit. The secondary resonant circuit connects to the secondary rectification circuit. The secondary rectification circuit connects to the secondary decoupling converter. The second stage connects to a load. The load includes an energy storage element. The second stage and load are located on a vehicle and the first stage is located at a fixed location. The primary receiver pad wirelessly transfers power to the secondary receiver pad across a gap when the vehicle positions the secondary receiver pad with respect to the primary receiver pad.
On the Teneurin track: a new synaptic organization molecule emerges
Mosca, Timothy J.
2015-01-01
To achieve proper synaptic development and function, coordinated signals must pass between the pre- and postsynaptic membranes. Such transsynaptic signals can be comprised of receptors and secreted ligands, membrane associated receptors, and also pairs of synaptic cell adhesion molecules. A critical open question bridging neuroscience, developmental biology, and cell biology involves identifying those signals and elucidating how they function. Recent work in Drosophila and vertebrate systems has implicated a family of proteins, the Teneurins, as a new transsynaptic signal in both the peripheral and central nervous systems. The Teneurins have established roles in neuronal wiring, but studies now show their involvement in regulating synaptic connections between neurons and bridging the synaptic membrane and the cytoskeleton. This review will examine the Teneurins as synaptic cell adhesion molecules, explore how they regulate synaptic organization, and consider how some consequences of human Teneurin mutations may have synaptopathic origins. PMID:26074772
Distributed synaptic weights in a LIF neural network and learning rules
NASA Astrophysics Data System (ADS)
Perthame, Benoît; Salort, Delphine; Wainrib, Gilles
2017-09-01
Leaky integrate-and-fire (LIF) models are mean-field limits, with a large number of neurons, used to describe neural networks. We consider inhomogeneous networks structured by a connectivity parameter (strengths of the synaptic weights) with the effect of processing the input current with different intensities. We first study the properties of the network activity depending on the distribution of synaptic weights and in particular its discrimination capacity. Then, we consider simple learning rules and determine the synaptic weight distribution it generates. We outline the role of noise as a selection principle and the capacity to memorize a learned signal.
Thalamic synchrony and dynamic regulation of global forebrain oscillations.
Huguenard, John R; McCormick, David A
2007-07-01
The circuitry within the thalamus creates an intrinsic oscillatory unit whose function depends critically on reciprocal synaptic connectivity between excitatory thalamocortical relay neurons and inhibitory thalamic reticular neurons along with a robust post-inhibitory rebound mechanism in relay neurons. Feedforward and feedback connections between cortex and thalamus reinforce the thalamic oscillatory activity into larger thalamocortical networks to generate sleep spindles and spike-wave discharge of generalized absence epilepsy. The degree of synchrony within the thalamic network seems to be crucial in determining whether normal (spindle) or pathological (spike-wave) oscillations occur, and recent studies show that regulation of excitability in the reticular nucleus leads to dynamical modulation of the state of the thalamic circuit and provide a basis for explaining how a variety of unrelated genetic alterations might lead to the spike-wave phenotype. In addition, given the central role of the reticular nucleus in generating spike-wave discharge, these studies have suggested specific interventions that would prevent seizures while still allowing normal spindle generation to occur. This review is part of the INMED/TINS special issue Physiogenic and pathogenic oscillations: the beauty and the beast, based on presentations at the annual INMED/TINS symposium (http://inmednet.com).
High-yield in vitro recordings from neurons functionally characterized in vivo.
Weiler, Simon; Bauer, Joel; Hübener, Mark; Bonhoeffer, Tobias; Rose, Tobias; Scheuss, Volker
2018-06-01
In vivo two-photon calcium imaging provides detailed information about the activity and response properties of individual neurons. However, in vitro methods are often required to study the underlying neuronal connectivity and physiology at the cellular and synaptic levels at high resolution. This protocol provides a fast and reliable workflow for combining the two approaches by characterizing the response properties of individual neurons in mice in vivo using genetically encoded calcium indicators (GECIs), followed by retrieval of the same neurons in brain slices for further analysis in vitro (e.g., circuit mapping). In this approach, a reference frame is provided by fluorescent-bead tracks and sparsely transduced neurons expressing a structural marker in order to re-identify the same neurons. The use of GECIs provides a substantial advancement over previous approaches by allowing for repeated in vivo imaging. This opens the possibility of directly correlating experience-dependent changes in neuronal activity and feature selectivity with changes in neuronal connectivity and physiology. This protocol requires expertise both in in vivo two-photon calcium imaging and in vitro electrophysiology. It takes 3 weeks or more to complete, depending on the time allotted for repeated in vivo imaging of neuronal activity.
Beier, Kevin T.; Mundell, Nathan A.; Pan, Y. Albert; Cepko, Constance L.
2016-01-01
Viruses have been used as transsynaptic tracers, allowing one to map the inputs and outputs of neuronal populations, due to their ability to replicate in neurons and transmit in vivo only across synaptically connected cells. To date, their use has been largely restricted to mammals. In order to explore the use of such viruses in an expanded host range, we tested the transsynaptic tracing ability of recombinant vesicular stomatitis virus (rVSV) vectors in a variety of organisms. Successful infection and gene expression were achieved in a wide range of organisms, including vertebrate and invertebrate model organisms. Moreover, rVSV enabled transsynaptic tracing of neural circuitry in predictable directions dictated by the viral envelope glycoprotein (G), derived from either VSV or rabies virus (RABV). Anterograde and retrograde labeling, from initial infection and/or viral replication and transmission, was observed in Old and New World monkeys, seahorses, jellyfish, zebrafish, chickens, and mice. These vectors are widely applicable for gene delivery, afferent tract tracing, and/or directional connectivity mapping. Here, we detail the use of these vectors and provide protocols for propagating virus, changing the surface glycoprotein, and infecting multiple organisms using several injection strategies. PMID:26729030
Beier, Kevin T; Mundell, Nathan A; Pan, Y Albert; Cepko, Constance L
2016-01-04
Viruses have been used as transsynaptic tracers, allowing one to map the inputs and outputs of neuronal populations, due to their ability to replicate in neurons and transmit in vivo only across synaptically connected cells. To date, their use has been largely restricted to mammals. In order to explore the use of such viruses in an expanded host range, we tested the transsynaptic tracing ability of recombinant vesicular stomatitis virus (rVSV) vectors in a variety of organisms. Successful infection and gene expression were achieved in a wide range of organisms, including vertebrate and invertebrate model organisms. Moreover, rVSV enabled transsynaptic tracing of neural circuitry in predictable directions dictated by the viral envelope glycoprotein (G), derived from either VSV or rabies virus (RABV). Anterograde and retrograde labeling, from initial infection and/or viral replication and transmission, was observed in Old and New World monkeys, seahorses, jellyfish, zebrafish, chickens, and mice. These vectors are widely applicable for gene delivery, afferent tract tracing, and/or directional connectivity mapping. Here, we detail the use of these vectors and provide protocols for propagating virus, changing the surface glycoprotein, and infecting multiple organisms using several injection strategies. Copyright © 2016 John Wiley & Sons, Inc.
NASA Astrophysics Data System (ADS)
Shalaginova, Z. I.
2016-03-01
The mathematical model and calculation method of the thermal-hydraulic modes of heat points, based on the theory of hydraulic circuits, being developed at the Melentiev Energy Systems Institute are presented. The redundant circuit of the heat point was developed, in which all possible connecting circuits (CC) of the heat engineering equipment and the places of possible installation of control valve were inserted. It allows simulating the operating modes both at central heat points (CHP) and individual heat points (IHP). The configuration of the desired circuit is carried out automatically by removing the unnecessary links. The following circuits connecting the heating systems (HS) are considered: the dependent circuit (direct and through mixing elevator) and independent one (through the heater). The following connecting circuits of the load of hot water supply (HWS) were considered: open CC (direct water pumping from pipelines of heat networks) and a closed CC with connecting the HWS heaters on single-level (serial and parallel) and two-level (sequential and combined) circuits. The following connecting circuits of the ventilation systems (VS) were also considered: dependent circuit and independent one through a common heat exchanger with HS load. In the heat points, water temperature regulators for the hot water supply and ventilation and flow regulators for the heating system, as well as to the inlet as a whole, are possible. According to the accepted decomposition, the model of the heat point is an integral part of the overall heat-hydraulic model of the heat-supplying system having intermediate control stages (CHP and IHP), which allows to consider the operating modes of the heat networks of different levels connected with each other through CHP as well as connected through IHP of consumers with various connecting circuits of local systems of heat consumption: heating, ventilation and hot water supply. The model is implemented in the Angara data-processing complex. An example of the multilevel calculation of the heat-hydraulic modes of main heat networks and those connected to them through central heat point distribution networks in Petropavlovsk-Kamchatskii is examined.
Zador, Anthony M.; Dubnau, Joshua; Oyibo, Hassana K.; Zhan, Huiqing; Cao, Gang; Peikon, Ian D.
2012-01-01
Connectivity determines the function of neural circuits. Historically, circuit mapping has usually been viewed as a problem of microscopy, but no current method can achieve high-throughput mapping of entire circuits with single neuron precision. Here we describe a novel approach to determining connectivity. We propose BOINC (“barcoding of individual neuronal connections”), a method for converting the problem of connectivity into a form that can be read out by high-throughput DNA sequencing. The appeal of using sequencing is that its scale—sequencing billions of nucleotides per day is now routine—is a natural match to the complexity of neural circuits. An inexpensive high-throughput technique for establishing circuit connectivity at single neuron resolution could transform neuroscience research. PMID:23109909
Synchronization and long-time memory in neural networks with inhibitory hubs and synaptic plasticity
NASA Astrophysics Data System (ADS)
Bertolotti, Elena; Burioni, Raffaella; di Volo, Matteo; Vezzani, Alessandro
2017-01-01
We investigate the dynamical role of inhibitory and highly connected nodes (hub) in synchronization and input processing of leaky-integrate-and-fire neural networks with short term synaptic plasticity. We take advantage of a heterogeneous mean-field approximation to encode the role of network structure and we tune the fraction of inhibitory neurons fI and their connectivity level to investigate the cooperation between hub features and inhibition. We show that, depending on fI, highly connected inhibitory nodes strongly drive the synchronization properties of the overall network through dynamical transitions from synchronous to asynchronous regimes. Furthermore, a metastable regime with long memory of external inputs emerges for a specific fraction of hub inhibitory neurons, underlining the role of inhibition and connectivity also for input processing in neural networks.
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.
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
Hoxha, Eriola; Lippiello, Pellegrino; Scelfo, Bibiana; Tempia, Filippo; Ghirardi, Mirella; Miniaci, Maria Concetta
2017-01-01
The formation of the complex cerebellar cortical circuits follows different phases, with initial synaptogenesis and subsequent processes of refinement guided by a variety of mechanisms. The regularity of the cellular and synaptic organization of the cerebellar cortex allowed detailed studies of the structural plasticity mechanisms underlying the formation of new synapses and retraction of redundant ones. For the attainment of the monoinnervation of the Purkinje cell by a single climbing fiber, several signals are involved, including electrical activity, contact signals, homosynaptic and heterosynaptic interaction, calcium transients, postsynaptic receptors, and transduction pathways. An important role in this developmental program is played by serotonergic projections that, acting on temporally and spatially regulated postsynaptic receptors, induce and modulate the phases of synaptic formation and maturation. In the adult cerebellar cortex, many developmental mechanisms persist but play different roles, such as supporting synaptic plasticity during learning and formation of cerebellar memory traces. A dysfunction at any stage of this process can lead to disorders of cerebellar origin, which include autism spectrum disorders but are not limited to motor deficits. Recent evidence in animal models links impairment of Purkinje cell function with autism-like symptoms including sociability deficits, stereotyped movements, and interspecific communication by vocalization.
Traub, Roger D; Cunningham, Mark O; Whittington, Miles A
2011-08-01
Field potential signals, corresponding to electrographic seizures in cortical structures, often contain two components, which sometimes appear to be separable and other times to be superimposed. The first component consists of low-amplitude very fast oscillations (VFO, >70-80 Hz); the second component consists of larger amplitude transients, lasting tens to hundreds of ms, and variously called population spikes, EEG spikes, or bursts--terms chosen in part because of the cellular correlates of the field events. To first approximation, the two components arise because of distinctive types of cellular interactions: gap junctions for VFO (a model of which is reviewed in the following), and recurrent synaptic excitation and/or inhibition for the transients. With in vitro studies of epileptic human neocortical tissue, it is possible to elicit VFO alone, or VFO superimposed on a large transient, but not a large transient without the VFO. If such observations prove to be general, they would imply that gap junction-mediated interactions are the primary factor in epileptogenesis. It appears to be the case then, that in the setting of seizure initiation (but not necessarily under physiological conditions), the gain of gap junction-mediated circuits can actually be larger than the gain in excitatory synaptic circuits. Copyright © 2010 Elsevier Ltd. All rights reserved.
Lippiello, Pellegrino; Scelfo, Bibiana
2017-01-01
The formation of the complex cerebellar cortical circuits follows different phases, with initial synaptogenesis and subsequent processes of refinement guided by a variety of mechanisms. The regularity of the cellular and synaptic organization of the cerebellar cortex allowed detailed studies of the structural plasticity mechanisms underlying the formation of new synapses and retraction of redundant ones. For the attainment of the monoinnervation of the Purkinje cell by a single climbing fiber, several signals are involved, including electrical activity, contact signals, homosynaptic and heterosynaptic interaction, calcium transients, postsynaptic receptors, and transduction pathways. An important role in this developmental program is played by serotonergic projections that, acting on temporally and spatially regulated postsynaptic receptors, induce and modulate the phases of synaptic formation and maturation. In the adult cerebellar cortex, many developmental mechanisms persist but play different roles, such as supporting synaptic plasticity during learning and formation of cerebellar memory traces. A dysfunction at any stage of this process can lead to disorders of cerebellar origin, which include autism spectrum disorders but are not limited to motor deficits. Recent evidence in animal models links impairment of Purkinje cell function with autism-like symptoms including sociability deficits, stereotyped movements, and interspecific communication by vocalization. PMID:28894610