Hyperconnectivity and Slow Synapses during Early Development of Medial Prefrontal Cortex in a Mouse Model for Mental Retardation and Autism

PubMed Central

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

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

PubMed

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

2013-08-21

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

Tracing neuronal circuits in transgenic animals by transneuronal control of transcription (TRACT)

PubMed Central

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

Optimal degrees of synaptic connectivity

PubMed Central

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

Microglomerular Synaptic Complexes in the Sky-Compass Network of the Honeybee Connect Parallel Pathways from the Anterior Optic Tubercle to the Central Complex.

PubMed

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.

Monosynaptic rabies virus reveals premotor network organization and synaptic specificity of cholinergic partition cells.

PubMed

Stepien, Anna E; Tripodi, Marco; Arber, Silvia

2010-11-04

Movement is the behavioral output of neuronal activity in the spinal cord. Motor neurons are grouped into motor neuron pools, the functional units innervating individual muscles. Here we establish an anatomical rabies virus-based connectivity assay in early postnatal mice. We employ it to study the connectivity scheme of premotor neurons, the neuronal cohorts monosynaptically connected to motor neurons, unveiling three aspects of organization. First, motor neuron pools are connected to segmentally widely distributed yet stereotypic interneuron populations, differing for pools innervating functionally distinct muscles. Second, depending on subpopulation identity, interneurons take on local or segmentally distributed positions. Third, cholinergic partition cells involved in the regulation of motor neuron excitability segregate into ipsilaterally and bilaterally projecting populations, the latter exhibiting preferential connections to functionally equivalent motor neuron pools bilaterally. Our study visualizes the widespread yet precise nature of the connectivity matrix for premotor interneurons and reveals exquisite synaptic specificity for bilaterally projecting cholinergic partition cells. Copyright © 2010 Elsevier Inc. All rights reserved.

An algorithm to predict the connectome of neural microcircuits

PubMed Central

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

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.

Forced neuronal interactions cause poor communication.

PubMed

Krzisch, Marine; Toni, Nicolas

2017-01-01

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

From induction to conduction: how intrinsic transcriptional priming of extrinsic neuronal connectivity shapes neuronal identity.

PubMed

Russ, Jeffrey B; Kaltschmidt, Julia A

2014-10-01

Every behaviour of an organism relies on an intricate and vastly diverse network of neurons whose identity and connectivity must be specified with extreme precision during development. Intrinsically, specification of neuronal identity depends heavily on the expression of powerful transcription factors that direct numerous features of neuronal identity, including especially properties of neuronal connectivity, such as dendritic morphology, axonal targeting or synaptic specificity, ultimately priming the neuron for incorporation into emerging circuitry. As the neuron's early connectivity is established, extrinsic signals from its pre- and postsynaptic partners feedback on the neuron to further refine its unique characteristics. As a result, disruption of one component of the circuitry during development can have vital consequences for the proper identity specification of its synaptic partners. Recent studies have begun to harness the power of various transcription factors that control neuronal cell fate, including those that specify a neuron's subtype-specific identity, seeking insight for future therapeutic strategies that aim to reconstitute damaged circuitry through neuronal reprogramming.

Increased Cell-Intrinsic Excitability Induces Synaptic Changes in New Neurons in the Adult Dentate Gyrus That Require Npas4

PubMed Central

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

A scalable neural chip with synaptic electronics using CMOS integrated memristors.

PubMed

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.

Distinct roles of neuroligin-1 and SynCAM1 in synapse formation and function in primary hippocampal neuronal cultures.

PubMed

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.

Delayed and Temporally Imprecise Neurotransmission in Reorganizing Cortical Microcircuits

PubMed Central

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

Cliques of Neurons Bound into Cavities Provide a Missing Link between Structure and Function.

PubMed

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.

Experimental implementation of a biometric laser synaptic sensor.

PubMed

Pisarchik, Alexander N; Sevilla-Escoboza, Ricardo; Jaimes-Reátegui, Rider; Huerta-Cuellar, Guillermo; García-Lopez, J Hugo; Kazantsev, Victor B

2013-12-16

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

The NG2 Protein Is Not Required for Glutamatergic Neuron-NG2 Cell Synaptic Signaling.

PubMed

Passlick, Stefan; Trotter, Jacqueline; Seifert, Gerald; Steinhäuser, Christian; Jabs, Ronald

2016-01-01

NG2 glial cells (as from now NG2 cells) are unique in receiving synaptic input from neurons. However, the components regulating formation and maintenance of these neuron-glia synapses remain elusive. The transmembrane protein NG2 has been considered a potential mediator of synapse formation and alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR) clustering, because it contains 2 extracellular Laminin G/Neurexin/Sex Hormone-Binding Globulin domains, which in neurons are crucial for formation of transsynaptic neuroligin-neurexin complexes. NG2 is connected via Glutamate Receptor-Interacting Protein with GluA2/3-containing AMPARs, thereby possibly mediating receptor clustering in glial postsynaptic density. To elucidate the role of NG2 in neuron-glia communication, we investigated glutamatergic synaptic transmission in juvenile and aged hippocampal NG2 cells of heterozygous and homozygous NG2 knockout mice. Neuron-NG2 cell synapses readily formed in the absence of NG2. Short-term plasticity, synaptic connectivity, postsynaptic AMPAR current kinetics, and density were not affected by NG2 deletion. During development, an NG2-independent acceleration of AMPAR current kinetics and decreased synaptic connectivity were observed. Our results indicate that the lack of NG2 does not interfere with genesis and basic properties of neuron-glia synapses. In addition, we demonstrate frequent expression of neuroligins 1-3 in juvenile and aged NG2 cells, suggesting a role of these molecules in synapse formation between NG2 glia and neurons. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

GRASP1 regulates synaptic plasticity and learning through endosomal recycling of AMPA receptors

PubMed Central

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

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

PubMed

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

2015-05-26

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

A quantitative analysis of the local connectivity between pyramidal neurons in layers 2/3 of the rat visual cortex.

PubMed

Hellwig, B

2000-02-01

This study provides a detailed quantitative estimate for local synaptic connectivity between neocortical pyramidal neurons. A new way of obtaining such an estimate is presented. In acute slices of the rat visual cortex, four layer 2 and four layer 3 pyramidal neurons were intracellularly injected with biocytin. Axonal and dendritic arborizations were three-dimensionally reconstructed with the aid of a computer-based camera lucida system. In a computer experiment, pairs of pre- and postsynaptic neurons were formed and potential synaptic contacts were calculated. For each pair, the calculations were carried out for a whole range of distances (0 to 500 microm) between the presynaptic and the postsynaptic neuron, in order to estimate cortical connectivity as a function of the spatial separation of neurons. It was also differentiated whether neurons were situated in the same or in different cortical layers. The data thus obtained was used to compute connection probabilities, the average number of contacts between neurons, the frequency of specific numbers of contacts and the total number of contacts a dendritic tree receives from the surrounding cortical volume. Connection probabilities ranged from 50% to 80% for directly adjacent neurons and from 0% to 15% for neurons 500 microm apart. In many cases, connections were mediated by one contact only. However, close neighbors made on average up to 3 contacts with each other. The question as to whether the method employed in this study yields a realistic estimate of synaptic connectivity is discussed. It is argued that the results can be used as a detailed blueprint for building artificial neural networks with a cortex-like architecture.

Modeling somatic and dendritic spike mediated plasticity at the single neuron and network level.

PubMed

Bono, Jacopo; Clopath, Claudia

2017-09-26

Synaptic plasticity is thought to be the principal neuronal mechanism underlying learning. Models of plastic networks typically combine point neurons with spike-timing-dependent plasticity (STDP) as the learning rule. However, a point neuron does not capture the local non-linear processing of synaptic inputs allowed for by dendrites. Furthermore, experimental evidence suggests that STDP is not the only learning rule available to neurons. By implementing biophysically realistic neuron models, we study how dendrites enable multiple synaptic plasticity mechanisms to coexist in a single cell. In these models, we compare the conditions for STDP and for synaptic strengthening by local dendritic spikes. We also explore how the connectivity between two cells is affected by these plasticity rules and by different synaptic distributions. Finally, we show that how memory retention during associative learning can be prolonged in networks of neurons by including dendrites.Synaptic plasticity is the neuronal mechanism underlying learning. Here the authors construct biophysical models of pyramidal neurons that reproduce observed plasticity gradients along the dendrite and show that dendritic spike dependent LTP which is predominant in distal sections can prolong memory retention.

Estimating neuronal connectivity from axonal and dendritic density fields

PubMed Central

van Pelt, Jaap; van Ooyen, Arjen

2013-01-01

Neurons innervate space by extending axonal and dendritic arborizations. When axons and dendrites come in close proximity of each other, synapses between neurons can be formed. Neurons vary greatly in their morphologies and synaptic connections with other neurons. The size and shape of the arborizations determine the way neurons innervate space. A neuron may therefore be characterized by the spatial distribution of its axonal and dendritic “mass.” A population mean “mass” density field of a particular neuron type can be obtained by averaging over the individual variations in neuron geometries. Connectivity in terms of candidate synaptic contacts between neurons can be determined directly on the basis of their arborizations but also indirectly on the basis of their density fields. To decide when a candidate synapse can be formed, we previously developed a criterion defining that axonal and dendritic line pieces should cross in 3D and have an orthogonal distance less than a threshold value. In this paper, we developed new methodology for applying this criterion to density fields. We show that estimates of the number of contacts between neuron pairs calculated from their density fields are fully consistent with the number of contacts calculated from the actual arborizations. However, the estimation of the connection probability and the expected number of contacts per connection cannot be calculated directly from density fields, because density fields do not carry anymore the correlative structure in the spatial distribution of synaptic contacts. Alternatively, these two connectivity measures can be estimated from the expected number of contacts by using empirical mapping functions. The neurons used for the validation studies were generated by our neuron simulator NETMORPH. An example is given of the estimation of average connectivity and Euclidean pre- and postsynaptic distance distributions in a network of neurons represented by their population mean density fields. PMID:24324430

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

NASA Astrophysics Data System (ADS)

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

1993-07-01

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

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.

Synaptic connections of PDF-immunoreactive lateral neurons projecting to the dorsal protocerebrum of Drosophila melanogaster.

PubMed

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.

Strong, reliable and precise synaptic connections between thalamic relay cells and neurones of the nucleus reticularis in juvenile rats.

PubMed

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.

Mapping chromatic pathways in the Drosophila visual system.

PubMed

Lin, Tzu-Yang; Luo, Jiangnan; Shinomiya, Kazunori; Ting, Chun-Yuan; Lu, Zhiyuan; Meinertzhagen, Ian A; Lee, Chi-Hon

2016-02-01

In Drosophila, color vision and wavelength-selective behaviors are mediated by the compound eye's narrow-spectrum photoreceptors R7 and R8 and their downstream medulla projection (Tm) neurons Tm5a, Tm5b, Tm5c, and Tm20 in the second optic neuropil or medulla. These chromatic Tm neurons project axons to a deeper optic neuropil, the lobula, which in insects has been implicated in processing and relaying color information to the central brain. The synaptic targets of the chromatic Tm neurons in the lobula are not known, however. Using a modified GFP reconstitution across synaptic partners (GRASP) method to probe connections between the chromatic Tm neurons and 28 known and novel types of lobula neurons, we identify anatomically the visual projection neurons LT11 and LC14 and the lobula intrinsic neurons Li3 and Li4 as synaptic targets of the chromatic Tm neurons. Single-cell GRASP analyses reveal that Li4 receives synaptic contacts from over 90% of all four types of chromatic Tm neurons, whereas LT11 is postsynaptic to the chromatic Tm neurons, with only modest selectivity and at a lower frequency and density. To visualize synaptic contacts at the ultrastructural level, we develop and apply a "two-tag" double-labeling method to label LT11's dendrites and the mitochondria in Tm5c's presynaptic terminals. Serial electron microscopic reconstruction confirms that LT11 receives direct contacts from Tm5c. This method would be generally applicable to map the connections of large complex neurons in Drosophila and other animals. © 2015 Wiley Periodicals, Inc.

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

PubMed Central

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

2013-01-01

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

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

PubMed

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

2011-06-01

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

Excitatory interneurons dominate sensory processing in the spinal substantia gelatinosa of rat

PubMed Central

Santos, Sónia F A; Rebelo, Sandra; Derkach, Victor A; Safronov, Boris V

2007-01-01

Substantia gelatinosa (SG, lamina II) is a spinal cord region where most unmyelinated primary afferents terminate and the central nociceptive processing begins. It is formed by several distinct groups of interneurons whose functional properties and synaptic connections are poorly understood, in part, because recordings from synaptically coupled pairs of SG neurons are quite challenging due to a very low probability of finding connected cells. Here, we describe an efficient method for identifying synaptically coupled interneurons in rat spinal cord slices and characterizing their excitatory or inhibitory function. Using tight-seal whole-cell recordings and a cell-attached stimulation technique, we routinely tested about 1500 SG interneurons, classifying 102 of them as monosynaptically connected to neurons in lamina I–III. Surprisingly, the vast majority of SG interneurons (n = 87) were excitatory and glutamatergic, while only 15 neurons were inhibitory. According to their intrinsic firing properties, these 102 SG neurons were also classified as tonic (n = 49), adapting (n = 17) or delayed-firing neurons (n = 36). All but two tonic neurons and all adapting neurons were excitatory interneurons. Of 36 delayed-firing neurons, 23 were excitatory and 13 were inhibitory. We conclude that sensory integration in the intrinsic SG neuronal network is dominated by excitatory interneurons. Such organization of neuronal circuitries in the spinal SG can be important for nociceptive encoding. PMID:17331995

Mapping sensory circuits by anterograde trans-synaptic transfer of recombinant rabies virus

PubMed Central

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

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

PubMed Central

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

Weighing the Evidence in Peters' Rule: Does Neuronal Morphology Predict Connectivity?

PubMed

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.

Strong, reliable and precise synaptic connections between thalamic relay cells and neurones of the nucleus reticularis in juvenile rats

PubMed Central

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

Memory formation orchestrates the wiring of adult-born hippocampal neurons into brain circuits.

PubMed

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.

Control of Abnormal Synchronization in Neurological Disorders

PubMed Central

Popovych, Oleksandr V.; Tass, Peter A.

2014-01-01

In the nervous system, synchronization processes play an important role, e.g., in the context of information processing and motor control. However, pathological, excessive synchronization may strongly impair brain function and is a hallmark of several neurological disorders. This focused review addresses the question of how an abnormal neuronal synchronization can specifically be counteracted by invasive and non-invasive brain stimulation as, for instance, by deep brain stimulation for the treatment of Parkinson’s disease, or by acoustic stimulation for the treatment of tinnitus. On the example of coordinated reset (CR) neuromodulation, we illustrate how insights into the dynamics of complex systems contribute to successful model-based approaches, which use methods from synergetics, non-linear dynamics, and statistical physics, for the development of novel therapies for normalization of brain function and synaptic connectivity. Based on the intrinsic multistability of the neuronal populations induced by spike timing-dependent plasticity (STDP), CR neuromodulation utilizes the mutual interdependence between synaptic connectivity and dynamics of the neuronal networks in order to restore more physiological patterns of connectivity via desynchronization of neuronal activity. The very goal is to shift the neuronal population by stimulation from an abnormally coupled and synchronized state to a desynchronized regime with normalized synaptic connectivity, which significantly outlasts the stimulation cessation, so that long-lasting therapeutic effects can be achieved. PMID:25566174

Synaptic dynamics and neuronal network connectivity are reflected in the distribution of times in Up states.

PubMed

Dao Duc, Khanh; Parutto, Pierre; Chen, Xiaowei; Epsztein, Jérôme; Konnerth, Arthur; Holcman, David

2015-01-01

The dynamics of neuronal networks connected by synaptic dynamics can sustain long periods of depolarization that can last for hundreds of milliseconds such as Up states recorded during sleep or anesthesia. Yet the underlying mechanism driving these periods remain unclear. We show here within a mean-field model that the residence time of the neuronal membrane potential in cortical Up states does not follow a Poissonian law, but presents several peaks. Furthermore, the present modeling approach allows extracting some information about the neuronal network connectivity from the time distribution histogram. Based on a synaptic-depression model, we find that these peaks, that can be observed in histograms of patch-clamp recordings are not artifacts of electrophysiological measurements, but rather are an inherent property of the network dynamics. Analysis of the equations reveals a stable focus located close to the unstable limit cycle, delimiting a region that defines the Up state. The model further shows that the peaks observed in the Up state time distribution are due to winding around the focus before escaping from the basin of attraction. Finally, we use in vivo recordings of intracellular membrane potential and we recover from the peak distribution, some information about the network connectivity. We conclude that it is possible to recover the network connectivity from the distribution of times that the neuronal membrane voltage spends in Up states.

Modulation of synaptic transmission in the rabbit coeliac ganglia by gastric and duodenal mechanoreceptors.

PubMed

Mazet, B; Miolan, J P; Niel, J P; Julé, Y; Roman, C

1989-01-01

The involvement of duodenal and gastric mechanoreceptors in the modulation of synaptic transmission was investigated in a rabbit sympathetic prevertebral ganglion. The present study was performed in vitro on the coeliac plexus connected to the stomach and the duodenum. The electrical activity of ganglionic neurons was recorded using intracellular recording techniques. The patterns of synaptic activation of these ganglionic neurons in response to the activation of mechanoreceptors by gastric or duodenal distension were investigated. Although gastric or duodenal distension was unable to elicit any fast synaptic activity in ganglionic neurons, it produced either an inhibition or a facilitation of the fast nicotinic excitatory postsynaptic potentials elicited by stimulation of the thoracic splanchnic nerves. In addition, this distension triggered long-lasting (3-11 min) modifications in the electrical properties of the ganglionic neurons, i.e. slow depolarizations (6-18 mV) or slow hyperpolarizations (3-6 mV), which were sometimes associated with a decrease in the input membrane resistance. After cooling of the nerves connecting the coeliac ganglia to the stomach, the activation of gastric or duodenal mechanoreceptors was no longer able to modify the fast synaptic activation or the electrical properties of the ganglionic neurons. The results demonstrate that gastric and duodenal mechanoreceptors project onto neurons of the coeliac ganglia and change their excitability as well as the central inputs they receive. The long duration of these modifications suggests that gastric and duodenal mechanoreceptors can modulate the activity of the neurons of the coeliac ganglia.

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

PubMed

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

2014-01-01

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

On the continuous differentiability of inter-spike intervals of synaptically connected cortical spiking neurons in a neuronal network.

PubMed

Kumar, Gautam; Kothare, Mayuresh V

2013-12-01

We derive conditions for continuous differentiability of inter-spike intervals (ISIs) of spiking neurons with respect to parameters (decision variables) of an external stimulating input current that drives a recurrent network of synaptically connected neurons. The dynamical behavior of individual neurons is represented by a class of discontinuous single-neuron models. We report here that ISIs of neurons in the network are continuously differentiable with respect to decision variables if (1) a continuously differentiable trajectory of the membrane potential exists between consecutive action potentials with respect to time and decision variables and (2) the partial derivative of the membrane potential of spiking neurons with respect to time is not equal to the partial derivative of their firing threshold with respect to time at the time of action potentials. Our theoretical results are supported by showing fulfillment of these conditions for a class of known bidimensional spiking neuron models.

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

PubMed

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

2003-01-01

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

Design of memristive interface between electronic neurons

NASA Astrophysics Data System (ADS)

Gerasimova, S. A.; Mikhaylov, A. N.; Belov, A. I.; Korolev, D. S.; Guseinov, D. V.; Lebedeva, A. V.; Gorshkov, O. N.; Kazantsev, V. B.

2018-05-01

Nonlinear dynamics of two electronic oscillators coupled via a memristive device has been investigated. Such model mimics the interaction between synaptically coupled brain neurons with the memristive device imitating neuron axon. The synaptic connection is provided by the adaptive behavior of memristive device that changes its resistance under the action of spike-like activity. Mathematical model of such a memristive interface has been developed to describe and predict the experimentally observed regularities of forced synchronization of neuron-like oscillators.

Generalized Adaptive Artificial Neural Networks

NASA Technical Reports Server (NTRS)

Tawel, Raoul

1993-01-01

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

Adaptive enhancement of learning protocol in hippocampal cultured networks grown on multielectrode arrays

PubMed Central

Pimashkin, Alexey; Gladkov, Arseniy; Mukhina, Irina; Kazantsev, Victor

2013-01-01

Learning in neuronal networks can be investigated using dissociated cultures on multielectrode arrays supplied with appropriate closed-loop stimulation. It was shown in previous studies that weakly respondent neurons on the electrodes can be trained to increase their evoked spiking rate within a predefined time window after the stimulus. Such neurons can be associated with weak synaptic connections in nearby culture network. The stimulation leads to the increase in the connectivity and in the response. However, it was not possible to perform the learning protocol for the neurons on electrodes with relatively strong synaptic inputs and responding at higher rates. We proposed an adaptive closed-loop stimulation protocol capable to achieve learning even for the highly respondent electrodes. It means that the culture network can reorganize appropriately its synaptic connectivity to generate a desired response. We introduced an adaptive reinforcement condition accounting for the response variability in control stimulation. It significantly enhanced the learning protocol to a large number of responding electrodes independently on its base response level. We also found that learning effect preserved after 4–6 h after training. PMID:23745105

Modelling Feedback Excitation, Pacemaker Properties and Sensory Switching of Electrically Coupled Brainstem Neurons Controlling Rhythmic Activity

PubMed Central

Hull, Michael J.; Soffe, Stephen R.; Willshaw, David J.; Roberts, Alan

2016-01-01

What cellular and network properties allow reliable neuronal rhythm generation or firing that can be started and stopped by brief synaptic inputs? We investigate rhythmic activity in an electrically-coupled population of brainstem neurons driving swimming locomotion in young frog tadpoles, and how activity is switched on and off by brief sensory stimulation. We build a computational model of 30 electrically-coupled conditional pacemaker neurons on one side of the tadpole hindbrain and spinal cord. Based on experimental estimates for neuron properties, population sizes, synapse strengths and connections, we show that: long-lasting, mutual, glutamatergic excitation between the neurons allows the network to sustain rhythmic pacemaker firing at swimming frequencies following brief synaptic excitation; activity persists but rhythm breaks down without electrical coupling; NMDA voltage-dependency doubles the range of synaptic feedback strengths generating sustained rhythm. The network can be switched on and off at short latency by brief synaptic excitation and inhibition. We demonstrate that a population of generic Hodgkin-Huxley type neurons coupled by glutamatergic excitatory feedback can generate sustained asynchronous firing switched on and off synaptically. We conclude that networks of neurons with NMDAR mediated feedback excitation can generate self-sustained activity following brief synaptic excitation. The frequency of activity is limited by the kinetics of the neuron membrane channels and can be stopped by brief inhibitory input. Network activity can be rhythmic at lower frequencies if the neurons are electrically coupled. Our key finding is that excitatory synaptic feedback within a population of neurons can produce switchable, stable, sustained firing without synaptic inhibition. PMID:26824331

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

PubMed

Ito, Shoko; Takeichi, Masatoshi

2009-08-04

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

Excitatory and inhibitory synaptic connectivity to layer V fast-spiking interneurons in the freeze lesion model of cortical microgyria

PubMed Central

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

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.

The process of learning in neural net models with Poisson and Gauss connectivities.

PubMed

Sivridis, L; Kotini, A; Anninos, P

2008-01-01

In this study we examined the dynamic behavior of isolated and non-isolated neural networks with chemical markers that follow a Poisson or Gauss distribution of connectivity. The Poisson distribution shows higher activity in comparison to the Gauss distribution although the latter has more connections that obliterated due to randomness. We examined 57 hematoxylin and eosin stained sections from an equal number of autopsy specimens with a diagnosis of "cerebral matter within normal limits". Neural counting was carried out in 5 continuous optic fields, with the use of a simple optical microscope connected to a computer (software programmer Nikon Act-1 vers-2). The number of neurons that corresponded to a surface was equal to 0.15 mm(2). There was a gradual reduction in the number of neurons as age increased. A mean value of 45.8 neurons /0.15 mm(2) was observed within the age range 21-25, 33 neurons /0.15 mm(2) within the age range 41-45, 19.3 neurons /0.15 mm(2) within the age range 56-60 years. After the age of 60 it was observed that the number of neurons per unit area stopped decreasing. A correlation was observed between these experimental findings and the theoretical neural model developed by professor Anninos and his colleagues. Equivalence between the mean numbers of neurons of the above mentioned age groups and the highest possible number of synaptic connections per neuron (highest number of synaptic connections corresponded to the age group 21-25) was created. We then used both inhibitory and excitatory post-synaptic potentials and applied these values to the Poisson and Gauss distributions, whereas the neuron threshold was varied between 3 and 5. According to the obtained phase diagrams, the hysteresis loops decrease as age increases. These findings were significant as the hysteresis loops can be regarded as the basis for short-term memory.

Extending Transfer Entropy Improves Identification of Effective Connectivity in a Spiking Cortical Network Model

PubMed Central

Ito, Shinya; Hansen, Michael E.; Heiland, Randy; Lumsdaine, Andrew; Litke, Alan M.; Beggs, John M.

2011-01-01

Transfer entropy (TE) is an information-theoretic measure which has received recent attention in neuroscience for its potential to identify effective connectivity between neurons. Calculating TE for large ensembles of spiking neurons is computationally intensive, and has caused most investigators to probe neural interactions at only a single time delay and at a message length of only a single time bin. This is problematic, as synaptic delays between cortical neurons, for example, range from one to tens of milliseconds. In addition, neurons produce bursts of spikes spanning multiple time bins. To address these issues, here we introduce a free software package that allows TE to be measured at multiple delays and message lengths. To assess performance, we applied these extensions of TE to a spiking cortical network model (Izhikevich, 2006) with known connectivity and a range of synaptic delays. For comparison, we also investigated single-delay TE, at a message length of one bin (D1TE), and cross-correlation (CC) methods. We found that D1TE could identify 36% of true connections when evaluated at a false positive rate of 1%. For extended versions of TE, this dramatically improved to 73% of true connections. In addition, the connections correctly identified by extended versions of TE accounted for 85% of the total synaptic weight in the network. Cross correlation methods generally performed more poorly than extended TE, but were useful when data length was short. A computational performance analysis demonstrated that the algorithm for extended TE, when used on currently available desktop computers, could extract effective connectivity from 1 hr recordings containing 200 neurons in ∼5 min. We conclude that extending TE to multiple delays and message lengths improves its ability to assess effective connectivity between spiking neurons. These extensions to TE soon could become practical tools for experimentalists who record hundreds of spiking neurons. PMID:22102894

Emergence of small-world structure in networks of spiking neurons through STDP plasticity.

PubMed

Basalyga, Gleb; Gleiser, Pablo M; Wennekers, Thomas

2011-01-01

In this work, we use a complex network approach to investigate how a neural network structure changes under synaptic plasticity. In particular, we consider a network of conductance-based, single-compartment integrate-and-fire excitatory and inhibitory neurons. Initially the neurons are connected randomly with uniformly distributed synaptic weights. The weights of excitatory connections can be strengthened or weakened during spiking activity by the mechanism known as spike-timing-dependent plasticity (STDP). We extract a binary directed connection matrix by thresholding the weights of the excitatory connections at every simulation step and calculate its major topological characteristics such as the network clustering coefficient, characteristic path length and small-world index. We numerically demonstrate that, under certain conditions, a nontrivial small-world structure can emerge from a random initial network subject to STDP learning.

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.

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

PubMed Central

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

2014-01-01

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

Identified Serotonergic Modulatory Neurons Have Heterogeneous Synaptic Connectivity within the Olfactory System of Drosophila.

PubMed

Coates, Kaylynn E; Majot, Adam T; Zhang, Xiaonan; Michael, Cole T; Spitzer, Stacy L; Gaudry, Quentin; Dacks, Andrew M

2017-08-02

Modulatory neurons project widely throughout the brain, dynamically altering network processing based on an animal's physiological state. The connectivity of individual modulatory neurons can be complex, as they often receive input from a variety of sources and are diverse in their physiology, structure, and gene expression profiles. To establish basic principles about the connectivity of individual modulatory neurons, we examined a pair of identified neurons, the "contralaterally projecting, serotonin-immunoreactive deutocerebral neurons" (CSDns), within the olfactory system of Drosophila Specifically, we determined the neuronal classes providing synaptic input to the CSDns within the antennal lobe (AL), an olfactory network targeted by the CSDns, and the degree to which CSDn active zones are uniformly distributed across the AL. Using anatomical techniques, we found that the CSDns received glomerulus-specific input from olfactory receptor neurons (ORNs) and projection neurons (PNs), and networkwide input from local interneurons (LNs). Furthermore, we quantified the number of CSDn active zones in each glomerulus and found that CSDn output is not uniform, but rather heterogeneous, across glomeruli and stereotyped from animal to animal. Finally, we demonstrate that the CSDns synapse broadly onto LNs and PNs throughout the AL but do not synapse upon ORNs. Our results demonstrate that modulatory neurons do not necessarily provide purely top-down input but rather receive neuron class-specific input from the networks that they target, and that even a two cell modulatory network has highly heterogeneous, yet stereotyped, pattern of connectivity. SIGNIFICANCE STATEMENT Modulatory neurons often project broadly throughout the brain to alter processing based on physiological state. However, the connectivity of individual modulatory neurons to their target networks is not well understood, as modulatory neuron populations are heterogeneous in their physiology, morphology, and gene expression. In this study, we use a pair of identified serotonergic neurons within the Drosophila olfactory system as a model to establish a framework for modulatory neuron connectivity. We demonstrate that individual modulatory neurons can integrate neuron class-specific input from their target network, which is often nonreciprocal. Additionally, modulatory neuron output can be stereotyped, yet nonuniform, across network regions. Our results provide new insight into the synaptic relationships that underlie network function of modulatory neurons. Copyright © 2017 the authors 0270-6474/17/377318-14$15.00/0.

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

PubMed

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

2018-05-30

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

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

PubMed

Saez, Ignacio; Friedlander, Michael J

2016-01-01

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

Synapse Formation in Monosynaptic Sensory–Motor Connections Is Regulated by Presynaptic Rho GTPase Cdc42

PubMed Central

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

The emergence of spontaneous activity in neuronal cultures

NASA Astrophysics Data System (ADS)

Orlandi, J. G.; Alvarez-Lacalle, E.; Teller, S.; Soriano, J.; Casademunt, J.

2013-01-01

In vitro neuronal networks of dissociated hippocampal or cortical tissues are one of the most attractive model systems for the physics and neuroscience communities. Cultured neurons grow and mature, develop axons and dendrites, and quickly connect to their neighbors to establish a spontaneously active network within a week. The resulting neuronal network is characterized by a combination of excitatory and inhibitory neurons coupled through synaptic connections that interact in a highly nonlinear manner. The nonlinear behavior emerges from the dynamics of both the neurons' spiking activity and synaptic transmission, together with biological noise. These ingredients give rise to a rich repertoire of phenomena that are still poorly understood, including the emergence and maintenance of periodic spontaneous activity, avalanches, propagation of fronts and synchronization. In this work we present an overview on the rich activity of cultured neuronal networks, and detail the minimal theoretical considerations needed to describe experimental observations.

A Model of Self-Organizing Head-Centered Visual Responses in Primate Parietal Areas

PubMed Central

Mender, Bedeho M. W.; Stringer, Simon M.

2013-01-01

We present a hypothesis for how head-centered visual representations in primate parietal areas could self-organize through visually-guided learning, and test this hypothesis using a neural network model. The model consists of a competitive output layer of neurons that receives afferent synaptic connections from a population of input neurons with eye position gain modulated retinal receptive fields. The synaptic connections in the model are trained with an associative trace learning rule which has the effect of encouraging output neurons to learn to respond to subsets of input patterns that tend to occur close together in time. This network architecture and synaptic learning rule is hypothesized to promote the development of head-centered output neurons during periods of time when the head remains fixed while the eyes move. This hypothesis is demonstrated to be feasible, and each of the core model components described is tested and found to be individually necessary for successful self-organization. PMID:24349064

CROSS-DISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY: Mechanism for propagation of rate signals through a 10-layer feedforward neuronal network

NASA Astrophysics Data System (ADS)

Li, Jie; Yu, Wan-Qing; Xu, Ding; Liu, Feng; Wang, Wei

2009-12-01

Using numerical simulations, we explore the mechanism for propagation of rate signals through a 10-layer feedforward network composed of Hodgkin-Huxley (HH) neurons with sparse connectivity. When white noise is afferent to the input layer, neuronal firing becomes progressively more synchronous in successive layers and synchrony is well developed in deeper layers owing to the feedforward connections between neighboring layers. The synchrony ensures the successful propagation of rate signals through the network when the synaptic conductance is weak. As the synaptic time constant τsyn varies, coherence resonance is observed in the network activity due to the intrinsic property of HH neurons. This makes the output firing rate single-peaked as a function of τsyn, suggesting that the signal propagation can be modulated by the synaptic time constant. These results are consistent with experimental results and advance our understanding of how information is processed in feedforward networks.

Unsupervised learning in neural networks with short range synapses

NASA Astrophysics Data System (ADS)

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

2013-01-01

Different areas of the brain are involved in specific aspects of the information being processed both in learning and in memory formation. For example, the hippocampus is important in the consolidation of information from short-term memory to long-term memory, while emotional memory seems to be dealt by the amygdala. On the microscopic scale the underlying structures in these areas differ in the kind of neurons involved, in their connectivity, or in their clustering degree but, at this level, learning and memory are attributed to neuronal synapses mediated by longterm potentiation and long-term depression. In this work we explore the properties of a short range synaptic connection network, a nearest neighbor lattice composed mostly by excitatory neurons and a fraction of inhibitory ones. The mechanism of synaptic modification responsible for the emergence of memory is Spike-Timing-Dependent Plasticity (STDP), a Hebbian-like rule, where potentiation/depression is acquired when causal/non-causal spikes happen in a synapse involving two neurons. The system is intended to store and recognize memories associated to spatial external inputs presented as simple geometrical forms. The synaptic modifications are continuously applied to excitatory connections, including a homeostasis rule and STDP. In this work we explore the different scenarios under which a network with short range connections can accomplish the task of storing and recognizing simple connected patterns.

Cellular resolution circuit mapping with temporal-focused excitation of soma-targeted channelrhodopsin

PubMed Central

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

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

PubMed

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

2009-12-01

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

A modeling framework for deriving the structural and functional architecture of a short-term memory microcircuit.

PubMed

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.

Patterns of fast synaptic cholinergic activation of neurons in the celiac ganglia of cats.

PubMed

Niel, J P; Clerc, N; Jule, Y

1988-12-01

Fast nicotinic transmission was studied in vitro in neurons of isolated cat celiac ganglia. In the absence of nerve stimulation, neurons could be classified into three types: silent neurons, synaptically activated neurons, and spontaneously discharging neurons. In all three types, fast synaptic activation could be obtained in single neurons by stimulating with a single pulse both the splanchnic nerves or one of the peripheral nerves connected to the ganglia. During repetitive nerve stimulation, a gradual depression of the central and peripheral fast nicotinic activation occurred, which was not affected by phentolamine plus propranolol, domperidone, atropine, or naloxone. Repetitive nerve stimulation was followed by a long lasting discharge of excitatory postsynaptic potentials and action potentials that decreased gradually with time. This discharge, which was probably due to presynaptic or prejunctional facilitation of acetylcholine release from cholinergic terminals, was reduced by the application of phentolamine plus propranolol, domperidone, or atropine and increased with naloxone. The existence of the mechanisms described in this study reflects the complexity of the integrative processes at work in neurons of the cat celiac ganglia that involve fast synaptic cholinergic activation.

Theory of correlation in a network with synaptic depression

NASA Astrophysics Data System (ADS)

Igarashi, Yasuhiko; Oizumi, Masafumi; Okada, Masato

2012-01-01

Synaptic depression affects not only the mean responses of neurons but also the correlation of response variability in neural populations. Although previous studies have constructed a theory of correlation in a spiking neuron model by using the mean-field theory framework, synaptic depression has not been taken into consideration. We expanded the previous theoretical framework in this study to spiking neuron models with short-term synaptic depression. On the basis of this theory we analytically calculated neural correlations in a ring attractor network with Mexican-hat-type connectivity, which was used as a model of the primary visual cortex. The results revealed that synaptic depression reduces neural correlation, which could be beneficial for sensory coding. Furthermore, our study opens the way for theoretical studies on the effect of interaction change on the linear response function in large stochastic networks.

Persistent ERK Activation Maintains Learning-Induced Long-Lasting Modulation of Synaptic Connectivity

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…

[Neuronal and synaptic properties: fundamentals of network plasticity].

PubMed

Le Masson, G

2000-02-01

Neurons, within the nervous system, are organized in different neural networks through synaptic connections. Two fundamental components are dynamically interacting in these functional units. The first one are the neurons themselves, and far from being simple action potential generators, they are capable of complex electrical integrative properties due to various types, number, distribution and modulation of voltage-gated ionic channels. The second elements are the synapses where a similar complexity and plasticity is found. Identifying both cellular and synaptic intrinsic properties is necessary to understand the links between neural networks behavior and physiological function, and is a useful step towards a better control of neurological diseases.

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

PubMed Central

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

2013-01-01

Chemical synapses contain multitudes of proteins, which in common with all proteins, have finite lifetimes and therefore need to be continuously replaced. Given the huge numbers of synaptic connections typical neurons form, the demand to maintain the protein contents of these connections might be expected to place considerable metabolic demands on each neuron. Moreover, synaptic proteostasis might differ according to distance from global protein synthesis sites, the availability of distributed protein synthesis facilities, trafficking rates and synaptic protein dynamics. To date, the turnover kinetics of synaptic proteins have not been studied or analyzed systematically, and thus metabolic demands or the aforementioned relationships remain largely unknown. In the current study we used dynamic Stable Isotope Labeling with Amino acids in Cell culture (SILAC), mass spectrometry (MS), Fluorescent Non–Canonical Amino acid Tagging (FUNCAT), quantitative immunohistochemistry and bioinformatics to systematically measure the metabolic half-lives of hundreds of synaptic proteins, examine how these depend on their pre/postsynaptic affiliation or their association with particular molecular complexes, and assess the metabolic load of synaptic proteostasis. We found that nearly all synaptic proteins identified here exhibited half-lifetimes in the range of 2–5 days. Unexpectedly, metabolic turnover rates were not significantly different for presynaptic and postsynaptic proteins, or for proteins for which mRNAs are consistently found in dendrites. Some functionally or structurally related proteins exhibited very similar turnover rates, indicating that their biogenesis and degradation might be coupled, a possibility further supported by bioinformatics-based analyses. The relatively low turnover rates measured here (∼0.7% of synaptic protein content per hour) are in good agreement with imaging-based studies of synaptic protein trafficking, yet indicate that the metabolic load synaptic protein turnover places on individual neurons is very substantial. PMID:23658807

Control of neuronal morphology and connectivity: emerging developmental roles for gap junctional proteins.

PubMed

Baker, Michael W; Macagno, Eduardo R

2014-04-17

Recent evidence indicates that gap junction (GJ) proteins can play a critical role in controlling neuronal connectivity as well as cell morphology in the developing nervous system. GJ proteins may function analogously to cell adhesion molecules, mediating cellular recognition and selective neurite adhesion. Moreover, during synaptogenesis electrical synapses often herald the later establishment of chemical synapses, and thus may help facilitate activity-dependent sculpting of synaptic terminals. Recent findings suggest that the morphology and connectivity of embryonic leech neurons are fundamentally organized by the type and perhaps location of the GJ proteins they express. For example, ectopic expression in embryonic leech neurons of certain innexins that define small GJ-linked networks of cells leads to the novel coupling of the expressing cell into that network. Moreover, gap junctions appear to mediate interactions among homologous neurons that modulate process outgrowth and stability. We propose that the selective formation of GJs between developing neurons and perhaps glial cells in the CNS helps orchestrate not only cellular synaptic connectivity but also can have a pronounced effect on the arborization and morphology of those cells involved. Copyright © 2014 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Comparison of NMDA and AMPA Channel Expression and Function between Embryonic and Adult Neurons Utilizing Microelectrode Array Systems.

PubMed

Edwards, Darin; Sommerhage, Frank; Berry, Bonnie; Nummer, Hanna; Raquet, Martina; Clymer, Brad; Stancescu, Maria; Hickman, James J

2017-12-11

Microelectrode arrays (MEAs) are innovative tools used to perform electrophysiological experiments for the study of electrical activity and connectivity in populations of neurons from dissociated cultures. Reliance upon neurons derived from embryonic tissue is a common limitation of neuronal/MEA hybrid systems and perhaps of neuroscience research in general, and the use of adult neurons could model fully functional in vivo parameters more closely. Spontaneous network activity was concurrently recorded from both embryonic and adult rat neurons cultured on MEAs for up to 10 weeks in vitro to characterize the synaptic connections between cell types. The cultures were exposed to synaptic transmission antagonists against NMDA and AMPA channels, which revealed significantly different receptor profiles of adult and embryonic networks in vitro. In addition, both embryonic and adult neurons were evaluated for NMDA and AMPA channel subunit expression over five weeks in vitro. The results established that neurons derived from embryonic tissue did not express mature synaptic channels for several weeks in vitro under defined conditions. Consequently, the embryonic response to synaptic antagonists was significantly different than that of neurons derived from adult tissue sources. These results are especially significant because most studies reported with embryonic hippocampal neurons do not begin at two to four weeks in culture. In addition, the utilization of MEAs in lieu of patch-clamp electrophysiology avoided a large-scale, labor-intensive study. These results establish the utility of this unique hybrid system derived from adult hippocampal tissue in combination with MEAs and offer a more appropriate representation of in vivo function for drug discovery. It has application for neuronal development and regeneration as well as for investigations into neurodegenerative disease, traumatic brain injury, and stroke.

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.

Toward heterogeneity in feedforward network with synaptic delays based on FitzHugh-Nagumo model

NASA Astrophysics Data System (ADS)

Qin, Ying-Mei; Men, Cong; Zhao, Jia; Han, Chun-Xiao; Che, Yan-Qiu

2018-01-01

We focus on the role of heterogeneity on the propagation of firing patterns in feedforward network (FFN). Effects of heterogeneities both in parameters of neuronal excitability and synaptic delays are investigated systematically. Neuronal heterogeneity is found to modulate firing rates and spiking regularity by changing the excitability of the network. Synaptic delays are strongly related with desynchronized and synchronized firing patterns of the FFN, which indicate that synaptic delays may play a significant role in bridging rate coding and temporal coding. Furthermore, quasi-coherence resonance (quasi-CR) phenomenon is observed in the parameter domain of connection probability and delay-heterogeneity. All these phenomena above enable a detailed characterization of neuronal heterogeneity in FFN, which may play an indispensable role in reproducing the important properties of in vivo experiments.

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

PubMed

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

PubMed Central

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

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

Mechanisms of Anesthetic Action and Neurotoxicity: Lessons from Molluscs

PubMed Central

Armstrong, Ryden; Riaz, Saba; Hasan, Sean; Iqbal, Fahad; Rice, Tiffany; Syed, Naweed

2018-01-01

Anesthesia is a prerequisite for most surgical procedures in both animals and humans. Significant strides have been made in search of effective and safer compounds that elicit rapid induction and recovery from anesthesia. However, recent studies have highlighted possible negative effects of several anesthetic agents on the developing brain. The precise nature of this cytotoxicity remains to be determined mainly due to the complexity and the intricacies of the mammalian brain. Various invertebrates have contributed significantly toward our understanding of how both local and general anesthetics affect intrinsic membrane and synaptic properties. Moreover, the ability to reconstruct in vitro synapses between individually identifiable pre- and postsynaptic neurons is a unique characteristic of molluscan neurons allowing us to ask fundamental questions vis-à-vis the long-term effects of anesthetics on neuronal viability and synaptic connectivity. Here, we highlight some of the salient aspects of various molluscan organisms and their contributions toward our understanding of the fundamental mechanisms underlying the actions of anesthetic agents as well as their potential detrimental effects on neuronal growth and synaptic connectivity. We also present some novel preliminary data regarding a newer anesthetic agent, dexmedetomidine, and its effects on synaptic transmission between Lymnaea neurons. The findings presented here underscore the importance of invertebrates for research in the field of anesthesiology while highlighting their relevance to both vertebrates and humans. PMID:29410627

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

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

Tanamoto, Ryo; Shindo, Yutaka; Niwano, Mariko

2016-03-18

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

Reliability and synchronization in a delay-coupled neuronal network with synaptic plasticity

NASA Astrophysics Data System (ADS)

Pérez, Toni; Uchida, Atsushi

2011-06-01

We investigate the characteristics of reliability and synchronization of a neuronal network of delay-coupled integrate and fire neurons. Reliability and synchronization appear in separated regions of the phase space of the parameters considered. The effect of including synaptic plasticity and different delay values between the connections are also considered. We found that plasticity strongly changes the characteristics of reliability and synchronization in the parameter space of the coupling strength and the drive amplitude for the neuronal network. We also found that delay does not affect the reliability of the network but has a determinant influence on the synchronization of the neurons.

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.

Memory replay in balanced recurrent networks

PubMed Central

Chenkov, Nikolay; Sprekeler, Henning; Kempter, Richard

2017-01-01

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

Synaptic plasticity modulates autonomous transitions between waking and sleep states: Insights from a Morris-Lecar model

NASA Astrophysics Data System (ADS)

Ciszak, Marzena; Bellesi, Michele

2011-12-01

The transitions between waking and sleep states are characterized by considerable changes in neuronal firing. During waking, neurons fire tonically at irregular intervals and a desynchronized activity is observed at the electroencephalogram. This activity becomes synchronized with slow wave sleep onset when neurons start to oscillate between periods of firing (up-states) and periods of silence (down-states). Recently, it has been proposed that the connections between neurons undergo potentiation during waking, whereas they weaken during slow wave sleep. Here, we propose a dynamical model to describe basic features of the autonomous transitions between such states. We consider a network of coupled neurons in which the strength of the interactions is modulated by synaptic long term potentiation and depression, according to the spike time-dependent plasticity rule (STDP). The model shows that the enhancement of synaptic strength between neurons occurring in waking increases the propensity of the network to synchronize and, conversely, desynchronization appears when the strength of the connections become weaker. Both transitions appear spontaneously, but the transition from sleep to waking required a slight modification of the STDP rule with the introduction of a mechanism which becomes active during sleep and changes the proportion between potentiation and depression in accordance with biological data. At the neuron level, transitions from desynchronization to synchronization and vice versa can be described as a bifurcation between two different states, whose dynamical regime is modulated by synaptic strengths, thus suggesting that transition from a state to an another can be determined by quantitative differences between potentiation and depression.

Contributions of diverse excitatory and inhibitory neurons to recurrent network activity in cerebral cortex.

PubMed

Neske, Garrett T; Patrick, Saundra L; Connors, Barry W

2015-01-21

The recurrent synaptic architecture of neocortex allows for self-generated network activity. One form of such activity is the Up state, in which neurons transiently receive barrages of excitatory and inhibitory synaptic inputs that depolarize many neurons to spike threshold before returning to a relatively quiescent Down state. The extent to which different cell types participate in Up states is still unclear. Inhibitory interneurons have particularly diverse intrinsic properties and synaptic connections with the local network, suggesting that different interneurons might play different roles in activated network states. We have studied the firing, subthreshold behavior, and synaptic conductances of identified cell types during Up and Down states in layers 5 and 2/3 in mouse barrel cortex in vitro. We recorded from pyramidal cells and interneurons expressing parvalbumin (PV), somatostatin (SOM), vasoactive intestinal peptide (VIP), or neuropeptide Y. PV cells were the most active interneuron subtype during the Up state, yet the other subtypes also received substantial synaptic conductances and often generated spikes. In all cell types except PV cells, the beginning of the Up state was dominated by synaptic inhibition, which decreased thereafter; excitation was more persistent, suggesting that inhibition is not the dominant force in terminating Up states. Compared with barrel cortex, SOM and VIP cells were much less active in entorhinal cortex during Up states. Our results provide a measure of functional connectivity of various neuron types in barrel cortex and suggest differential roles for interneuron types in the generation and control of persistent network activity. Copyright © 2015 the authors 0270-6474/15/351089-17$15.00/0.

Structure and function of the amygdaloid NPY system: NPY Y2 receptors regulate excitatory and inhibitory synaptic transmission in the centromedial amygdala.

PubMed

Wood, J; Verma, D; Lach, G; Bonaventure, P; Herzog, H; Sperk, G; Tasan, R O

2016-09-01

The amygdala is essential for generating emotional-affective behaviors. It consists of several nuclei with highly selective, elaborate functions. In particular, the central extended amygdala, consisting of the central amygdala (CEA) and the bed nucleus of the stria terminalis (BNST) is an essential component actively controlling efferent connections to downstream effectors like hypothalamus and brain stem. Both, CEA and BNST contain high amounts of different neuropeptides that significantly contribute to synaptic transmission. Among these, neuropeptide Y (NPY) has emerged as an important anxiolytic and fear-reducing neuromodulator. Here, we characterized the expression, connectivity and electrophysiological function of NPY and Y2 receptors within the CEA. We identified several NPY-expressing neuronal populations, including somatostatin- and calretinin-expressing neurons. Furthermore, in the main intercalated nucleus, NPY is expressed primarily in dopamine D1 receptor-expressing neurons but also in interspersed somatostatin-expressing neurons. Interestingly, NPY neurons did not co-localize with the Y2 receptor. Retrograde tract tracing experiments revealed that NPY neurons reciprocally connect the CEA and BNST. Functionally, the Y2 receptor agonist PYY3-36, reduced both, inhibitory as well as excitatory synaptic transmission in the centromedial amygdala (CEm). However, we also provide evidence that lack of NPY or Y2 receptors results in increased GABA release specifically at inhibitory synapses in the CEm. Taken together, our findings suggest that NPY expressed by distinct populations of neurons can modulate afferent and efferent projections of the CEA via presynaptic Y2 receptors located at inhibitory and excitatory synapses.

Spike timing precision of neuronal circuits.

PubMed

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.

Transcriptional Architecture of Synaptic Communication Delineates GABAergic Neuron Identity.

PubMed

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.

Regulation of neuronal communication by G protein-coupled receptors.

PubMed

Huang, Yunhong; Thathiah, Amantha

2015-06-22

Neuronal communication plays an essential role in the propagation of information in the brain and requires a precisely orchestrated connectivity between neurons. Synaptic transmission is the mechanism through which neurons communicate with each other. It is a strictly regulated process which involves membrane depolarization, the cellular exocytosis machinery, neurotransmitter release from synaptic vesicles into the synaptic cleft, and the interaction between ion channels, G protein-coupled receptors (GPCRs), and downstream effector molecules. The focus of this review is to explore the role of GPCRs and G protein-signaling in neurotransmission, to highlight the function of GPCRs, which are localized in both presynaptic and postsynaptic membrane terminals, in regulation of intrasynaptic and intersynaptic communication, and to discuss the involvement of astrocytic GPCRs in the regulation of neuronal communication. Copyright © 2015 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

On the Teneurin track: a new synaptic organization molecule emerges

PubMed Central

Mosca, Timothy J.

2015-01-01

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

Astroglial Metabolic Networks Sustain Hippocampal Synaptic Transmission

NASA Astrophysics Data System (ADS)

Rouach, Nathalie; Koulakoff, Annette; Abudara, Veronica; Willecke, Klaus; Giaume, Christian

2008-12-01

Astrocytes provide metabolic substrates to neurons in an activity-dependent manner. However, the molecular mechanisms involved in this function, as well as its role in synaptic transmission, remain unclear. Here, we show that the gap-junction subunit proteins connexin 43 and 30 allow intercellular trafficking of glucose and its metabolites through astroglial networks. This trafficking is regulated by glutamatergic synaptic activity mediated by AMPA receptors. In the absence of extracellular glucose, the delivery of glucose or lactate to astrocytes sustains glutamatergic synaptic transmission and epileptiform activity only when they are connected by gap junctions. These results indicate that astroglial gap junctions provide an activity-dependent intercellular pathway for the delivery of energetic metabolites from blood vessels to distal neurons.

Astroglial metabolic networks sustain hippocampal synaptic transmission.

PubMed

Rouach, Nathalie; Koulakoff, Annette; Abudara, Veronica; Willecke, Klaus; Giaume, Christian

2008-12-05

Astrocytes provide metabolic substrates to neurons in an activity-dependent manner. However, the molecular mechanisms involved in this function, as well as its role in synaptic transmission, remain unclear. Here, we show that the gap-junction subunit proteins connexin 43 and 30 allow intercellular trafficking of glucose and its metabolites through astroglial networks. This trafficking is regulated by glutamatergic synaptic activity mediated by AMPA receptors. In the absence of extracellular glucose, the delivery of glucose or lactate to astrocytes sustains glutamatergic synaptic transmission and epileptiform activity only when they are connected by gap junctions. These results indicate that astroglial gap junctions provide an activity-dependent intercellular pathway for the delivery of energetic metabolites from blood vessels to distal neurons.

Octopamine Neuromodulation Regulates Gr32a-Linked Aggression and Courtship Pathways in Drosophila Males

PubMed Central

Andrews, Jonathan C.; Fernández, María Paz; Yu, Qin; Leary, Greg P.; Leung, Adelaine K. W.; Kavanaugh, Michael P.; Kravitz, Edward A.; Certel, Sarah J.

2014-01-01

Chemosensory pheromonal information regulates aggression and reproduction in many species, but how pheromonal signals are transduced to reliably produce behavior is not well understood. Here we demonstrate that the pheromonal signals detected by Gr32a-expressing chemosensory neurons to enhance male aggression are filtered through octopamine (OA, invertebrate equivalent of norepinephrine) neurons. Using behavioral assays, we find males lacking both octopamine and Gr32a gustatory receptors exhibit parallel delays in the onset of aggression and reductions in aggression. Physiological and anatomical experiments identify Gr32a to octopamine neuron synaptic and functional connections in the suboesophageal ganglion. Refining the Gr32a-expressing population indicates that mouth Gr32a neurons promote male aggression and form synaptic contacts with OA neurons. By restricting the monoamine neuron target population, we show that three previously identified OA-FruM neurons involved in behavioral choice are among the Gr32a-OA connections. Our findings demonstrate that octopaminergic neuromodulatory neurons function as early as a second-order step in this chemosensory-driven male social behavior pathway. PMID:24852170

Optogenetic Examination of Prefrontal-Amygdala Synaptic Development.

PubMed

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.

Investigation of synapse formation and function in a glutamatergic-GABAergic two-neuron microcircuit.

PubMed

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.

Spontaneous Activity Drives Local Synaptic Plasticity In Vivo.

PubMed

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.

[Neuroeffector connections of multimodal neurons in the African snail (Achatina fulica)].

PubMed

Bugaĭ, V V; Zhuravlev, V L; Safonova, T A

2004-02-01

Using a new method of animal preparation, the efferent connections of giant paired neurons on the dorsal surface of visceral and right parietal ganglia of snail, Achatina fulica, were examined. It was found that spikes in giant neurons d-VLN and d-RPLN evoke postjunctional potentials in different points of the snail body and viscerae (in the heart, in pericardium, in lung cavity and kidney walls, in mantle and body wall muscles, in tentacle retractors and in cephalic artery). The preliminary analysis of synaptic latency and facilitation suggests a direct connections between giant neurons and investigated efferents.

Complex-learning Induced Modifications in Synaptic Inhibition: Mechanisms and Functional Significance.

PubMed

Reuveni, Iris; Lin, Longnian; Barkai, Edi

2018-06-15

Following training in a difficult olfactory-discrimination (OD) task rats acquire the capability to perform the task easily, with little effort. This new acquired skill, of 'learning how to learn' is termed 'rule learning'. At the single-cell level, rule learning is manifested in long-term enhancement of intrinsic neuronal excitability of piriform cortex (PC) pyramidal neurons, and in excitatory synaptic connections between these neurons to maintain cortical stability, such long-lasting increase in excitability must be accompanied by paralleled increase in inhibitory processes that would prevent hyper-excitable activation. In this review we describe the cellular and molecular mechanisms underlying complex-learning-induced long-lasting modifications in GABA A -receptors and GABA B -receptor-mediated synaptic inhibition. Subsequently we discuss how such modifications support the induction and preservation of long-term memories in the in the mammalian brain. Based on experimental results, computational analysis and modeling, we propose that rule learning is maintained by doubling the strength of synaptic inputs, excitatory as well as inhibitory, in a sub-group of neurons. This enhanced synaptic transmission, which occurs in all (or almost all) synaptic inputs onto these neurons, activates specific stored memories. At the molecular level, such rule-learning-relevant synaptic strengthening is mediated by doubling the conductance of synaptic channels, but not their numbers. This post synaptic process is controlled by a whole-cell mechanism via particular second messenger systems. This whole-cell mechanism enables memory amplification when required and memory extinction when not relevant. Copyright © 2018 IBRO. Published by Elsevier Ltd. All rights reserved.

Amygdala connections with jaw, tongue and laryngo-pharyngeal premotor neurons.

PubMed

Van Daele, D J; Fazan, V P S; Agassandian, K; Cassell, M D

2011-03-17

As the central nucleus (CE) is the only amygdaloid nucleus to send axons to the pons and medulla, it is thought to be involved in the expression of conditioned responses by accessing hindbrain circuitry generating stereotypic responses to aversive stimuli. Responses to aversive oral stimuli include gaping and tongue protrusion generated by central pattern generators and other premotor neurons in the ponto-medullary reticular formation. We investigated central nucleus connections with the reticular formation by identifying premotor reticular formation neurons through the retrograde trans-synaptic transport of pseudorabies virus (PRV) inoculated into masseter, genioglossus, thyroarytenoid or inferior constrictor muscles in combination with anterograde labeling of CE axons with biotinylated dextran amine. Three dimensional mapping of PRV infected premotor neurons revealed specific clusters of these neurons associated with different oro-laryngo-pharyngeal muscles, particularly in the parvicellular reticular formation. CE axon terminals were concentrated in certain parvicellular clusters but overall putative contacts were identified with premotor neurons associated with all four oro-laryngo-pharyngeal muscles investigated. We also mapped the retrograde trans-synaptic spread of PRV through the various nuclei of the amygdaloid complex. Medial CE was the first amygdala structure infected (4 days post-inoculation) with trans-synaptic spread to the lateral CE and the caudomedial parvicellular basolateral nucleus by day 5 post-inoculation. Infected neurons were only very rarely found in the lateral capsular CE and the lateral nucleus and then at only the latest time points. The data demonstrate that the CE is directly connected with clusters of reticular premotor neurons that may represent complex pattern generators and/or switching elements for the generation of stereotypic oral and laryngo-pharyngeal movements during aversive oral stimulation. Serial connections through the amygdaloid complex linked with the oro-laryngo-pharyngeal musculature appear quite distinct from those believed to sub-serve fear responses, suggesting there are distinct "channels" for the acquisition and expression of particular conditioned behaviors. Copyright © 2011 IBRO. Published by Elsevier Ltd. All rights reserved.

Temporal identity in axonal target layer recognition.

PubMed

Petrovic, Milan; Hummel, Thomas

2008-12-11

The segregation of axon and dendrite projections into distinct synaptic layers is a fundamental principle of nervous system organization and the structural basis for information processing in the brain. Layer-specific recognition molecules that allow projecting neurons to stabilize transient contacts and initiate synaptogenesis have been identified. However, most of the neuronal cell-surface molecules critical for layer organization are expressed broadly in the developing nervous system, raising the question of how these so-called permissive adhesion molecules support synaptic specificity. Here we show that the temporal expression dynamics of the zinc-finger protein sequoia is the major determinant of Drosophila photoreceptor connectivity into distinct synaptic layers. Neighbouring R8 and R7 photoreceptors show consecutive peaks of elevated sequoia expression, which correspond to their sequential target-layer innervation. Loss of sequoia in R7 leads to a projection switch into the R8 recipient layer, whereas a prolonged expression in R8 induces a redirection of their axons into the R7 layer. The sequoia-induced axon targeting is mediated through the ubiquitously expressed Cadherin-N cell adhesion molecule. Our data support a model in which recognition specificity during synaptic layer formation is generated through a temporally restricted axonal competence to respond to broadly expressed adhesion molecules. Because developing neurons innervating the same target area often project in a distinct, birth-order-dependent sequence, temporal identity seems to contain crucial information in generating not only cell type diversity during neuronal division but also connection diversity of projecting neurons.

Shining light on neurons--elucidation of neuronal functions by photostimulation.

PubMed

Eder, Matthias; Zieglgänsberger, Walter; Dodt, Hans-Ulrich

2004-01-01

Many neuronal functions can be elucidated by techniques that allow for a precise stimulation of defined regions of a neuron and its afferents. Photolytic release of neurotransmitters from 'caged' derivates in the vicinity of visualized neurons in living brain slices meets this request. This technique allows the study of the subcellular distribution and properties of functional native neurotransmitter receptors. These are prerequisites for a detailed analysis of the expression and spatial specificity of synaptic plasticity. Photostimulation can further be used to fast map the synaptic connectivity between nearby and, more importantly, distant cells in a neuronal network. Here we give a personal review of some of the technical aspects of photostimulation and recent findings, which illustrate the advantages of this technique.

Effects of Calcium Spikes in the Layer 5 Pyramidal Neuron on Coincidence Detection and Activity Propagation

PubMed Central

Chua, Yansong; Morrison, Abigail

2016-01-01

The role of dendritic spiking mechanisms in neural processing is so far poorly understood. To investigate the role of calcium spikes in the functional properties of the single neuron and recurrent networks, we investigated a three compartment neuron model of the layer 5 pyramidal neuron with calcium dynamics in the distal compartment. By performing single neuron simulations with noisy synaptic input and occasional large coincident input at either just the distal compartment or at both somatic and distal compartments, we show that the presence of calcium spikes confers a substantial advantage for coincidence detection in the former case and a lesser advantage in the latter. We further show that the experimentally observed critical frequency phenomenon, in which action potentials triggered by stimuli near the soma above a certain frequency trigger a calcium spike at distal dendrites, leading to further somatic depolarization, is not exhibited by a neuron receiving realistically noisy synaptic input, and so is unlikely to be a necessary component of coincidence detection. We next investigate the effect of calcium spikes in propagation of spiking activities in a feed-forward network (FFN) embedded in a balanced recurrent network. The excitatory neurons in the network are again connected to either just the distal, or both somatic and distal compartments. With purely distal connectivity, activity propagation is stable and distinguishable for a large range of recurrent synaptic strengths if the feed-forward connections are sufficiently strong, but propagation does not occur in the absence of calcium spikes. When connections are made to both the somatic and the distal compartments, activity propagation is achieved for neurons with active calcium dynamics at a much smaller number of neurons per pool, compared to a network of passive neurons, but quickly becomes unstable as the strength of recurrent synapses increases. Activity propagation at higher scaling factors can be stabilized by increasing network inhibition or introducing short term depression in the excitatory synapses, but the signal to noise ratio remains low. Our results demonstrate that the interaction of synchrony with dendritic spiking mechanisms can have profound consequences for the dynamics on the single neuron and network level. PMID:27499740

Effects of Calcium Spikes in the Layer 5 Pyramidal Neuron on Coincidence Detection and Activity Propagation.

PubMed

Chua, Yansong; Morrison, Abigail

2016-01-01

The role of dendritic spiking mechanisms in neural processing is so far poorly understood. To investigate the role of calcium spikes in the functional properties of the single neuron and recurrent networks, we investigated a three compartment neuron model of the layer 5 pyramidal neuron with calcium dynamics in the distal compartment. By performing single neuron simulations with noisy synaptic input and occasional large coincident input at either just the distal compartment or at both somatic and distal compartments, we show that the presence of calcium spikes confers a substantial advantage for coincidence detection in the former case and a lesser advantage in the latter. We further show that the experimentally observed critical frequency phenomenon, in which action potentials triggered by stimuli near the soma above a certain frequency trigger a calcium spike at distal dendrites, leading to further somatic depolarization, is not exhibited by a neuron receiving realistically noisy synaptic input, and so is unlikely to be a necessary component of coincidence detection. We next investigate the effect of calcium spikes in propagation of spiking activities in a feed-forward network (FFN) embedded in a balanced recurrent network. The excitatory neurons in the network are again connected to either just the distal, or both somatic and distal compartments. With purely distal connectivity, activity propagation is stable and distinguishable for a large range of recurrent synaptic strengths if the feed-forward connections are sufficiently strong, but propagation does not occur in the absence of calcium spikes. When connections are made to both the somatic and the distal compartments, activity propagation is achieved for neurons with active calcium dynamics at a much smaller number of neurons per pool, compared to a network of passive neurons, but quickly becomes unstable as the strength of recurrent synapses increases. Activity propagation at higher scaling factors can be stabilized by increasing network inhibition or introducing short term depression in the excitatory synapses, but the signal to noise ratio remains low. Our results demonstrate that the interaction of synchrony with dendritic spiking mechanisms can have profound consequences for the dynamics on the single neuron and network level.

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

PubMed Central

Effenberger, Felix; Jost, Jürgen; Levina, Anna

2015-01-01

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

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

PubMed

Burbank, Kendra S

2015-12-01

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

Mirrored STDP Implements Autoencoder Learning in a Network of Spiking Neurons

PubMed Central

Burbank, Kendra S.

2015-01-01

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

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

PubMed Central

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

2011-01-01

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

Ensemble stacking mitigates biases in inference of synaptic connectivity.

PubMed

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

2018-01-01

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

Can simple rules control development of a pioneer vertebrate neuronal network generating behavior?

PubMed

Roberts, Alan; Conte, Deborah; Hull, Mike; Merrison-Hort, Robert; al Azad, Abul Kalam; Buhl, Edgar; Borisyuk, Roman; Soffe, Stephen R

2014-01-08

How do the pioneer networks in the axial core of the vertebrate nervous system first develop? Fundamental to understanding any full-scale neuronal network is knowledge of the constituent neurons, their properties, synaptic interconnections, and normal activity. Our novel strategy uses basic developmental rules to generate model networks that retain individual neuron and synapse resolution and are capable of reproducing correct, whole animal responses. We apply our developmental strategy to young Xenopus tadpoles, whose brainstem and spinal cord share a core vertebrate plan, but at a tractable complexity. Following detailed anatomical and physiological measurements to complete a descriptive library of each type of spinal neuron, we build models of their axon growth controlled by simple chemical gradients and physical barriers. By adding dendrites and allowing probabilistic formation of synaptic connections, we reconstruct network connectivity among up to 2000 neurons. When the resulting "network" is populated by model neurons and synapses, with properties based on physiology, it can respond to sensory stimulation by mimicking tadpole swimming behavior. This functioning model represents the most complete reconstruction of a vertebrate neuronal network that can reproduce the complex, rhythmic behavior of a whole animal. The findings validate our novel developmental strategy for generating realistic networks with individual neuron- and synapse-level resolution. We use it to demonstrate how early functional neuronal connectivity and behavior may in life result from simple developmental "rules," which lay out a scaffold for the vertebrate CNS without specific neuron-to-neuron recognition.

Large-scale automated histology in the pursuit of connectomes.

PubMed

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

PubMed Central

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

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

PubMed Central

Bi, Zedong; Zhou, Changsong

2016-01-01

In neural systems, synaptic plasticity is usually driven by spike trains. Due to the inherent noises of neurons and synapses as well as the randomness of connection details, spike trains typically exhibit variability such as spatial randomness and temporal stochasticity, resulting in variability of synaptic changes under plasticity, which we call efficacy variability. How the variability of spike trains influences the efficacy variability of synapses remains unclear. In this paper, we try to understand this influence under pair-wise additive spike-timing dependent plasticity (STDP) when the mean strength of plastic synapses into a neuron is bounded (synaptic homeostasis). Specifically, we systematically study, analytically and numerically, how four aspects of statistical features, i.e., synchronous firing, burstiness/regularity, heterogeneity of rates and heterogeneity of cross-correlations, as well as their interactions influence the efficacy variability in converging motifs (simple networks in which one neuron receives from many other neurons). Neurons (including the post-synaptic neuron) in a converging motif generate spikes according to statistical models with tunable parameters. In this way, we can explicitly control the statistics of the spike patterns, and investigate their influence onto the efficacy variability, without worrying about the feedback from synaptic changes onto the dynamics of the post-synaptic neuron. We separate efficacy variability into two parts: the drift part (DriftV) induced by the heterogeneity of change rates of different synapses, and the diffusion part (DiffV) induced by weight diffusion caused by stochasticity of spike trains. Our main findings are: (1) synchronous firing and burstiness tend to increase DiffV, (2) heterogeneity of rates induces DriftV when potentiation and depression in STDP are not balanced, and (3) heterogeneity of cross-correlations induces DriftV together with heterogeneity of rates. We anticipate our work important for understanding functional processes of neuronal networks (such as memory) and neural development. PMID:26941634

The up and down states of cortical networks

NASA Astrophysics Data System (ADS)

Ghorbani, Maryam; Levine, Alex J.; Mehta, Mayank; Bruinsma, Robijn

2011-03-01

The cortical networks show a collective activity of alternating active and silent states known as up and down states during slow wave sleep or anesthesia. The mechanism of this spontaneous activity as well as the anesthesia or sleep are still not clear. Here, using a mean field approach, we present a simple model to study the spontaneous activity of a homogenous cortical network of excitatory and inhibitory neurons that are recurrently connected. A key new ingredient in this model is that the activity-dependant synaptic depression is considered only for the excitatory neurons. We find depending on the strength of the synaptic depression and synaptic efficacies, the phase space contains strange attractors or stable fixed points at active or quiescent regimes. At the strange attractor phase, we can have oscillations similar to up and down states with flat and noisy up states. Moreover, we show that by increasing the synaptic efficacy corresponding to the connections between the excitatory neurons, the characteristics of the up and down states change in agreement with the changes that we observe in the intracellular recordings of the membrane potential from the entorhinal cortex by varying the depth of anesthesia. Thus, we propose that by measuring the value of this synaptic efficacy, one can quantify the depth of anesthesia which is clinically very important. These findings provide a simple, analytical understanding of the spontaneous cortical dynamics.

Lateral assembly of the immunoglobulin protein SynCAM 1 controls its adhesive function and instructs synapse formation.

PubMed

Fogel, Adam I; Stagi, Massimiliano; Perez de Arce, Karen; Biederer, Thomas

2011-09-16

Synapses are specialized adhesion sites between neurons that are connected by protein complexes spanning the synaptic cleft. These trans-synaptic interactions can organize synapse formation, but their macromolecular properties and effects on synaptic morphology remain incompletely understood. Here, we demonstrate that the synaptic cell adhesion molecule SynCAM 1 self-assembles laterally via its extracellular, membrane-proximal immunoglobulin (Ig) domains 2 and 3. This cis oligomerization generates SynCAM oligomers with increased adhesive capacity and instructs the interactions of this molecule across the nascent and mature synaptic cleft. In immature neurons, cis assembly promotes the adhesive clustering of SynCAM 1 at new axo-dendritic contacts. Interfering with the lateral self-assembly of SynCAM 1 in differentiating neurons strongly impairs its synaptogenic activity. At later stages, the lateral oligomerization of SynCAM 1 restricts synaptic size, indicating that this adhesion molecule contributes to the structural organization of synapses. These results support that lateral interactions assemble SynCAM complexes within the synaptic cleft to promote synapse induction and modulate their structure. These findings provide novel insights into synapse development and the adhesive mechanisms of Ig superfamily members.

Dynamics of Competition between Subnetworks of Spiking Neuronal Networks in the Balanced State.

PubMed

Lagzi, Fereshteh; Rotter, Stefan

2015-01-01

We explore and analyze the nonlinear switching dynamics of neuronal networks with non-homogeneous connectivity. The general significance of such transient dynamics for brain function is unclear; however, for instance decision-making processes in perception and cognition have been implicated with it. The network under study here is comprised of three subnetworks of either excitatory or inhibitory leaky integrate-and-fire neurons, of which two are of the same type. The synaptic weights are arranged to establish and maintain a balance between excitation and inhibition in case of a constant external drive. Each subnetwork is randomly connected, where all neurons belonging to a particular population have the same in-degree and the same out-degree. Neurons in different subnetworks are also randomly connected with the same probability; however, depending on the type of the pre-synaptic neuron, the synaptic weight is scaled by a factor. We observed that for a certain range of the "within" versus "between" connection weights (bifurcation parameter), the network activation spontaneously switches between the two sub-networks of the same type. This kind of dynamics has been termed "winnerless competition", which also has a random component here. In our model, this phenomenon is well described by a set of coupled stochastic differential equations of Lotka-Volterra type that imply a competition between the subnetworks. The associated mean-field model shows the same dynamical behavior as observed in simulations of large networks comprising thousands of spiking neurons. The deterministic phase portrait is characterized by two attractors and a saddle node, its stochastic component is essentially given by the multiplicative inherent noise of the system. We find that the dwell time distribution of the active states is exponential, indicating that the noise drives the system randomly from one attractor to the other. A similar model for a larger number of populations might suggest a general approach to study the dynamics of interacting populations of spiking networks.

Dynamics of Competition between Subnetworks of Spiking Neuronal Networks in the Balanced State

PubMed Central

Lagzi, Fereshteh; Rotter, Stefan

2015-01-01

We explore and analyze the nonlinear switching dynamics of neuronal networks with non-homogeneous connectivity. The general significance of such transient dynamics for brain function is unclear; however, for instance decision-making processes in perception and cognition have been implicated with it. The network under study here is comprised of three subnetworks of either excitatory or inhibitory leaky integrate-and-fire neurons, of which two are of the same type. The synaptic weights are arranged to establish and maintain a balance between excitation and inhibition in case of a constant external drive. Each subnetwork is randomly connected, where all neurons belonging to a particular population have the same in-degree and the same out-degree. Neurons in different subnetworks are also randomly connected with the same probability; however, depending on the type of the pre-synaptic neuron, the synaptic weight is scaled by a factor. We observed that for a certain range of the “within” versus “between” connection weights (bifurcation parameter), the network activation spontaneously switches between the two sub-networks of the same type. This kind of dynamics has been termed “winnerless competition”, which also has a random component here. In our model, this phenomenon is well described by a set of coupled stochastic differential equations of Lotka-Volterra type that imply a competition between the subnetworks. The associated mean-field model shows the same dynamical behavior as observed in simulations of large networks comprising thousands of spiking neurons. The deterministic phase portrait is characterized by two attractors and a saddle node, its stochastic component is essentially given by the multiplicative inherent noise of the system. We find that the dwell time distribution of the active states is exponential, indicating that the noise drives the system randomly from one attractor to the other. A similar model for a larger number of populations might suggest a general approach to study the dynamics of interacting populations of spiking networks. PMID:26407178

A conserved juxtacrine signal regulates synaptic partner recognition in Caenorhabditis elegans

PubMed Central

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

Neuroeffector connections of giant multimodal neurons in the African snail Achatina fulica.

PubMed

Bugai, V V; Zhuravlev, V L; Safonova, T A

2005-07-01

A new method of making preparations was used to analyse the neuroeffector connections of the paired giant neurons of the African snail Achatina fulica. These neurons were found to induce postsynaptic potentials in the muscles of the mantle, heart, the wall of the pulmonary cavity, and the muscular elements of the renal complex, the pericardium, the sexual apparatus, the walls of the cerebral arteries, the filaments of the columellar muscles, the wall of the abdomen, and the tentacle retractor muscles. Rhythmic neuron activity led to the development of marked facilitation and long-term potentiation of synaptic potentials. The possible significance of the multiple neuroeffector connections of giant neurons is discussed.

Cdk5-dependent phosphorylation of liprinα1 mediates neuronal activity-dependent synapse development

PubMed Central

Huang, Huiqian; Lin, Xiaochen; Liang, Zhuoyi; Zhao, Teng; Du, Shengwang; Loy, Michael M. T.; Lai, Kwok-On; Fu, Amy K. Y.

2017-01-01

The experience-dependent modulation of brain circuitry depends on dynamic changes in synaptic connections that are guided by neuronal activity. In particular, postsynaptic maturation requires changes in dendritic spine morphology, the targeting of postsynaptic proteins, and the insertion of synaptic neurotransmitter receptors. Thus, it is critical to understand how neuronal activity controls postsynaptic maturation. Here we report that the scaffold protein liprinα1 and its phosphorylation by cyclin-dependent kinase 5 (Cdk5) are critical for the maturation of excitatory synapses through regulation of the synaptic localization of the major postsynaptic organizer postsynaptic density (PSD)-95. Whereas Cdk5 phosphorylates liprinα1 at Thr701, this phosphorylation decreases in neurons in response to neuronal activity. Blockade of liprinα1 phosphorylation enhances the structural and functional maturation of excitatory synapses. Nanoscale superresolution imaging reveals that inhibition of liprinα1 phosphorylation increases the colocalization of liprinα1 with PSD-95. Furthermore, disruption of liprinα1 phosphorylation by a small interfering peptide, siLIP, promotes the synaptic localization of PSD-95 and enhances synaptic strength in vivo. Our findings collectively demonstrate that the Cdk5-dependent phosphorylation of liprinα1 is important for the postsynaptic organization during activity-dependent synapse development. PMID:28760951

Synchronization of action potentials during low-magnesium-induced bursting

PubMed Central

Johnson, Sarah E.; Hudson, John L.

2015-01-01

The relationship between mono- and polysynaptic strength and action potential synchronization was explored using a reduced external Mg2+ model. Single and dual whole cell patch-clamp recordings were performed in hippocampal cultures in three concentrations of external Mg2+. In decreased Mg2+ medium, the individual cells transitioned to spontaneous bursting behavior. In lowered Mg2+ media the larger excitatory synaptic events were observed more frequently and fewer transmission failures occurred, suggesting strengthened synaptic transmission. The event synchronization was calculated for the neural action potentials of the cell pairs, and it increased in media where Mg2+ concentration was lowered. Analysis of surrogate data where bursting was present, but no direct or indirect connections existed between the neurons, showed minimal action potential synchronization. This suggests the synchronization of action potentials is a product of the strengthening synaptic connections within neuronal networks. PMID:25609103

Synchronization of action potentials during low-magnesium-induced bursting.

PubMed

Johnson, Sarah E; Hudson, John L; Kapur, Jaideep

2015-04-01

The relationship between mono- and polysynaptic strength and action potential synchronization was explored using a reduced external Mg(2+) model. Single and dual whole cell patch-clamp recordings were performed in hippocampal cultures in three concentrations of external Mg(2+). In decreased Mg(2+) medium, the individual cells transitioned to spontaneous bursting behavior. In lowered Mg(2+) media the larger excitatory synaptic events were observed more frequently and fewer transmission failures occurred, suggesting strengthened synaptic transmission. The event synchronization was calculated for the neural action potentials of the cell pairs, and it increased in media where Mg(2+) concentration was lowered. Analysis of surrogate data where bursting was present, but no direct or indirect connections existed between the neurons, showed minimal action potential synchronization. This suggests the synchronization of action potentials is a product of the strengthening synaptic connections within neuronal networks. Copyright © 2015 the American Physiological Society.

Random synaptic feedback weights support error backpropagation for deep learning

NASA Astrophysics Data System (ADS)

Lillicrap, Timothy P.; Cownden, Daniel; Tweed, Douglas B.; Akerman, Colin J.

2016-11-01

The brain processes information through multiple layers of neurons. This deep architecture is representationally powerful, but complicates learning because it is difficult to identify the responsible neurons when a mistake is made. In machine learning, the backpropagation algorithm assigns blame by multiplying error signals with all the synaptic weights on each neuron's axon and further downstream. However, this involves a precise, symmetric backward connectivity pattern, which is thought to be impossible in the brain. Here we demonstrate that this strong architectural constraint is not required for effective error propagation. We present a surprisingly simple mechanism that assigns blame by multiplying errors by even random synaptic weights. This mechanism can transmit teaching signals across multiple layers of neurons and performs as effectively as backpropagation on a variety of tasks. Our results help reopen questions about how the brain could use error signals and dispel long-held assumptions about algorithmic constraints on learning.

Random synaptic feedback weights support error backpropagation for deep learning

PubMed Central

Lillicrap, Timothy P.; Cownden, Daniel; Tweed, Douglas B.; Akerman, Colin J.

2016-01-01

The brain processes information through multiple layers of neurons. This deep architecture is representationally powerful, but complicates learning because it is difficult to identify the responsible neurons when a mistake is made. In machine learning, the backpropagation algorithm assigns blame by multiplying error signals with all the synaptic weights on each neuron's axon and further downstream. However, this involves a precise, symmetric backward connectivity pattern, which is thought to be impossible in the brain. Here we demonstrate that this strong architectural constraint is not required for effective error propagation. We present a surprisingly simple mechanism that assigns blame by multiplying errors by even random synaptic weights. This mechanism can transmit teaching signals across multiple layers of neurons and performs as effectively as backpropagation on a variety of tasks. Our results help reopen questions about how the brain could use error signals and dispel long-held assumptions about algorithmic constraints on learning. PMID:27824044

Toward a Neurocentric View of Learning.

PubMed

Titley, Heather K; Brunel, Nicolas; Hansel, Christian

2017-07-05

Synaptic plasticity (e.g., long-term potentiation [LTP]) is considered the cellular correlate of learning. Recent optogenetic studies on memory engram formation assign a critical role in learning to suprathreshold activation of neurons and their integration into active engrams ("engram cells"). Here we review evidence that ensemble integration may result from LTP but also from cell-autonomous changes in membrane excitability. We propose that synaptic plasticity determines synaptic connectivity maps, whereas intrinsic plasticity-possibly separated in time-amplifies neuronal responsiveness and acutely drives engram integration. Our proposal marks a move away from an exclusively synaptocentric toward a non-exclusive, neurocentric view of learning. Copyright © 2017 Elsevier Inc. All rights reserved.

Plasticity of Neuron-Glial Transmission: Equipping Glia for Long-Term Integration of Network Activity.

PubMed

Croft, Wayne; Dobson, Katharine L; Bellamy, Tomas C

2015-01-01

The capacity of synaptic networks to express activity-dependent changes in strength and connectivity is essential for learning and memory processes. In recent years, glial cells (most notably astrocytes) have been recognized as active participants in the modulation of synaptic transmission and synaptic plasticity, implicating these electrically nonexcitable cells in information processing in the brain. While the concept of bidirectional communication between neurons and glia and the mechanisms by which gliotransmission can modulate neuronal function are well established, less attention has been focussed on the computational potential of neuron-glial transmission itself. In particular, whether neuron-glial transmission is itself subject to activity-dependent plasticity and what the computational properties of such plasticity might be has not been explored in detail. In this review, we summarize current examples of plasticity in neuron-glial transmission, in many brain regions and neurotransmitter pathways. We argue that induction of glial plasticity typically requires repetitive neuronal firing over long time periods (minutes-hours) rather than the short-lived, stereotyped trigger typical of canonical long-term potentiation. We speculate that this equips glia with a mechanism for monitoring average firing rates in the synaptic network, which is suited to the longer term roles proposed for astrocytes in neurophysiology.

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.

Spike-timing dependent plasticity in primate corticospinal connections induced during free behavior

PubMed Central

Nishimura, Yukio; Perlmutter, Steve I.; Eaton, Ryan W.; Fetz, Eberhard E.

2014-01-01

Motor learning and functional recovery from brain damage involve changes in the strength of synaptic connections between neurons. Relevant in vivo evidence on the underlying cellular mechanisms remains limited and indirect. We found that the strength of neural connections between motor cortex and spinal cord in monkeys can be modified with an autonomous recurrent neural interface that delivers electrical stimuli in the spinal cord triggered by action potentials of corticospinal cells during free behavior. The activity-dependent stimulation modified the strength of the terminal connections of single corticomotoneuronal cells, consistent with a bidirectional spike-timing dependent plasticity rule previously derived from in vitro experiments. For some cells the changes lasted for days after the end of conditioning, but most effects eventually reverted to preconditioning levels. These results provide the first direct evidence of corticospinal synaptic plasticity in vivo at the level of single neurons induced by normal firing patterns during free behavior. PMID:24210907

Multiple effects of β-amyloid on single excitatory synaptic connections in the PFC.

PubMed

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.

In Vitro Studies of Neuronal Networks and Synaptic Plasticity in Invertebrates and in Mammals Using Multielectrode Arrays

PubMed Central

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

Multiple conserved cell adhesion protein interactions mediate neural wiring of a sensory circuit in C. elegans.

PubMed

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.

Hyperconnectivity of local neocortical microcircuitry induced by prenatal exposure to valproic acid.

PubMed

Rinaldi, Tania; Silberberg, Gilad; Markram, Henry

2008-04-01

Exposure to valproic acid (VPA) during embryogenesis can cause several teratogenic effects, including developmental delays and in particular autism in humans if exposure occurs during the third week of gestation. We examined the postnatal effects of embryonic exposure to VPA on microcircuit properties of juvenile rat neocortex using in vitro electrophysiology. We found that a single prenatal injection of VPA on embryonic day 11.5 causes a significant enhancement of the local recurrent connectivity formed by neocortical pyramidal neurons. The study of the biophysical properties of these connections revealed weaker excitatory synaptic responses. A marked decrease of the intrinsic excitability of pyramidal neurons was also observed. Furthermore, we demonstrate a diminished number of putative synaptic contacts in connection between layer 5 pyramidal neurons. Local hyperconnectivity may render cortical modules more sensitive to stimulation and once activated, more autonomous, isolated, and more difficult to command. This could underlie some of the core symptoms observed in humans prenatally exposed to valproic acid.

Behavioral plasticity through the modulation of switch neurons.

PubMed

Vassiliades, Vassilis; Christodoulou, Chris

2016-02-01

A central question in artificial intelligence is how to design agents capable of switching between different behaviors in response to environmental changes. Taking inspiration from neuroscience, we address this problem by utilizing artificial neural networks (NNs) as agent controllers, and mechanisms such as neuromodulation and synaptic gating. The novel aspect of this work is the introduction of a type of artificial neuron we call "switch neuron". A switch neuron regulates the flow of information in NNs by selectively gating all but one of its incoming synaptic connections, effectively allowing only one signal to propagate forward. The allowed connection is determined by the switch neuron's level of modulatory activation which is affected by modulatory signals, such as signals that encode some information about the reward received by the agent. An important aspect of the switch neuron is that it can be used in appropriate "switch modules" in order to modulate other switch neurons. As we show, the introduction of the switch modules enables the creation of sequences of gating events. This is achieved through the design of a modulatory pathway capable of exploring in a principled manner all permutations of the connections arriving on the switch neurons. We test the model by presenting appropriate architectures in nonstationary binary association problems and T-maze tasks. The results show that for all tasks, the switch neuron architectures generate optimal adaptive behaviors, providing evidence that the switch neuron model could be a valuable tool in simulations where behavioral plasticity is required. Copyright © 2015 Elsevier Ltd. All rights reserved.

Dynamical estimation of neuron and network properties III: network analysis using neuron spike times.

PubMed

Knowlton, Chris; Meliza, C Daniel; Margoliash, Daniel; Abarbanel, Henry D I

2014-06-01

Estimating the behavior of a network of neurons requires accurate models of the individual neurons along with accurate characterizations of the connections among them. Whereas for a single cell, measurements of the intracellular voltage are technically feasible and sufficient to characterize a useful model of its behavior, making sufficient numbers of simultaneous intracellular measurements to characterize even small networks is infeasible. This paper builds on prior work on single neurons to explore whether knowledge of the time of spiking of neurons in a network, once the nodes (neurons) have been characterized biophysically, can provide enough information to usefully constrain the functional architecture of the network: the existence of synaptic links among neurons and their strength. Using standardized voltage and synaptic gating variable waveforms associated with a spike, we demonstrate that the functional architecture of a small network of model neurons can be established.

Stochastic Synapses Enable Efficient Brain-Inspired Learning Machines.

PubMed

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

2016-01-01

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

Stochastic Synapses Enable Efficient Brain-Inspired Learning Machines

PubMed Central

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

2016-01-01

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

Characterization of emergent synaptic topologies in noisy neural networks

NASA Astrophysics Data System (ADS)

Miller, Aaron James

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

Spatial dynamics of action potentials estimated by dendritic Ca(2+) signals in insect projection neurons.

PubMed

Ogawa, Hiroto; Mitani, Ruriko

2015-11-13

The spatial dynamics of action potentials, including their propagation and the location of spike initiation zone (SIZ), are crucial for the computation of a single neuron. Compared with mammalian central neurons, the spike dynamics of invertebrate neurons remain relatively unknown. Thus, we examined the spike dynamics based on single spike-induced Ca(2+) signals in the dendrites of cricket mechanosensory projection neurons, known as giant interneurons (GIs). The Ca(2+) transients induced by a synaptically evoked single spike were larger than those induced by an antidromic spike, whereas subthreshold synaptic potentials caused no elevation of Ca(2+). These results indicate that synaptic activity enhances the dendritic Ca(2+) influx through voltage-gated Ca(2+) channels. Stimulation of the presynaptic sensory afferents ipsilateral to the recording site evoked a dendritic spike with higher amplitude than contralateral stimulation, thereby suggesting that alteration of the spike waveform resulted in synaptic enhancement of the dendritic Ca(2+) transients. The SIZ estimated from the spatial distribution of the difference in the Ca(2+) amplitude was distributed throughout the right and left dendritic branches across the primary neurite connecting them in GIs. Copyright © 2015 Elsevier Inc. All rights reserved.

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

PubMed Central

Lavigne, Frédéric; Avnaïm, Francis; Dumercy, Laurent

2014-01-01

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

Visual patch clamp recording of neurons in thick portions of the adult spinal cord.

PubMed

Munch, Anders Sonne; Smith, Morten; Moldovan, Mihai; Perrier, Jean-François

2010-07-15

The study of visually identified neurons in slice preparations from the central nervous system offers considerable advantages over in vivo preparations including high mechanical stability in the absence of anaesthesia and full control of the extracellular medium. However, because of their relative thinness, slices are not appropriate for investigating how individual neurons integrate synaptic inputs generated by large numbers of neurons. Here we took advantage of the exceptional resistance of the turtle to anoxia to make slices of increasing thicknesses (from 300 to 3000 microm) from the lumbar enlargement of the spinal cord. With a conventional upright microscope in which the light condenser was carefully adjusted, we could visualize neurons present at the surface of the slice and record them with the whole-cell patch clamp technique. We show that neurons present in the middle of the preparation remain alive and capable of generating action potentials. By stimulating the lateral funiculus we can evoke intense synaptic activity associated with large increases in conductance of the recorded neurons. The conductance increases substantially more in neurons recorded in thick slices suggesting that the size of the network recruited with the stimulation increases with the thickness of the slices. We also find that that the number of spontaneous excitatory postsynaptic currents (EPSCs) is higher in thick slices compared with thin slices while the number of spontaneous inhibitory postsynaptic currents (IPSCs) remains constant. These preliminary data suggest that inhibitory and excitatory synaptic connections are balanced locally while excitation dominates long-range connections in the spinal cord. Copyright 2010 Elsevier B.V. All rights reserved.

Sexually dimorphic differentiation of a C. elegans hub neuron is cell-autonomously controlled by a conserved transcription factor

PubMed Central

Serrano-Saiz, Esther; Oren-Suissa, Meital; Bayer, Emily A.; Hobert, Oliver

2018-01-01

SUMMARY Functional and anatomical sexual dimorphisms in the brain are either the result of cells that are generated only in one sex, or a manifestation of sex-specific differentiation of neurons present in both sexes. The PHC neurons of the nematode C. elegans differentiate in a strikingly sex-specific manner. While in hermaphrodites the PHC neurons display a canonical pattern of synaptic connectivity similar to that of other sensory neurons, PHC differentiates into a densely connected hub sensory/interneuron in males, integrating a large number of male-specific synaptic inputs and conveying them to both male-specific and sex-shared circuitry. We show that the differentiation into such a hub neuron involves the sex-specific scaling of several components of the synaptic vesicle machinery, including the vesicular glutamate transporter eat-4/VGLUT, induction of neuropeptide expression, changes in axonal projection morphology and a switch in neuronal function. We demonstrate that these molecular and anatomical remodeling events are controlled cell-autonomously by the phylogenetically conserved Doublesex homolog dmd-3, which is both required and sufficient for sex-specific PHC differentiation. Cellular specificity of dmd-3 action is ensured by its collaboration with non-sex specific terminal selector-type transcription factors whereas sex-specificity of dmd-3 action is ensured by the hermaphrodite-specific, transcriptional master regulator of hermaphroditic cell identity, tra-1, which represses transcription of dmd-3 in hermaphrodite PHC. Taken together, our studies provide mechanistic insights into how neurons are specified in a sexually dimorphic manner. PMID:28065609

Shaping Neuronal Network Activity by Presynaptic Mechanisms

PubMed Central

Ashery, Uri

2015-01-01

Neuronal microcircuits generate oscillatory activity, which has been linked to basic functions such as sleep, learning and sensorimotor gating. Although synaptic release processes are well known for their ability to shape the interaction between neurons in microcircuits, most computational models do not simulate the synaptic transmission process directly and hence cannot explain how changes in synaptic parameters alter neuronal network activity. In this paper, we present a novel neuronal network model that incorporates presynaptic release mechanisms, such as vesicle pool dynamics and calcium-dependent release probability, to model the spontaneous activity of neuronal networks. The model, which is based on modified leaky integrate-and-fire neurons, generates spontaneous network activity patterns, which are similar to experimental data and robust under changes in the model's primary gain parameters such as excitatory postsynaptic potential and connectivity ratio. Furthermore, it reliably recreates experimental findings and provides mechanistic explanations for data obtained from microelectrode array recordings, such as network burst termination and the effects of pharmacological and genetic manipulations. The model demonstrates how elevated asynchronous release, but not spontaneous release, synchronizes neuronal network activity and reveals that asynchronous release enhances utilization of the recycling vesicle pool to induce the network effect. The model further predicts a positive correlation between vesicle priming at the single-neuron level and burst frequency at the network level; this prediction is supported by experimental findings. Thus, the model is utilized to reveal how synaptic release processes at the neuronal level govern activity patterns and synchronization at the network level. PMID:26372048

Increased Excitatory Synaptic Transmission of Dentate Granule Neurons in Mice Lacking PSD-95-Interacting Adhesion Molecule Neph2/Kirrel3 during the Early Postnatal Period.

PubMed

Roh, Junyeop D; Choi, Su-Yeon; Cho, Yi Sul; Choi, Tae-Yong; Park, Jong-Sil; Cutforth, Tyler; Chung, Woosuk; Park, Hanwool; Lee, Dongsoo; Kim, Myeong-Heui; Lee, Yeunkum; Mo, Seojung; Rhee, Jeong-Seop; Kim, Hyun; Ko, Jaewon; Choi, Se-Young; Bae, Yong Chul; Shen, Kang; Kim, Eunjoon; Han, Kihoon

2017-01-01

Copy number variants and point mutations of NEPH2 (also called KIRREL3 ) gene encoding an immunoglobulin (Ig) superfamily adhesion molecule have been linked to autism spectrum disorders, intellectual disability and neurocognitive delay associated with Jacobsen syndrome, but the physiological roles of Neph2 in the mammalian brain remain largely unknown. Neph2 is highly expressed in the dentate granule (DG) neurons of the hippocampus and is localized in both dendrites and axons. It was recently shown that Neph2 is required for the formation of mossy fiber filopodia, the axon terminal structure of DG neurons forming synapses with GABAergic neurons of CA3. In contrast, however, it is unknown whether Neph2 also has any roles in the postsynaptic compartments of DG neurons. We here report that, through its C-terminal PDZ domain-binding motif, Neph2 directly interacts with postsynaptic density (PSD)-95, an abundant excitatory postsynaptic scaffolding protein. Moreover, Neph2 protein is detected in the brain PSD fraction and interacts with PSD-95 in synaptosomal lysates. Functionally, loss of Neph2 in mice leads to age-specific defects in the synaptic connectivity of DG neurons. Specifically, Neph2 -/- mice show significantly increased spontaneous excitatory synaptic events in DG neurons at postnatal week 2 when the endogenous Neph2 protein expression peaks, but show normal excitatory synaptic transmission at postnatal week 3. The evoked excitatory synaptic transmission and synaptic plasticity of medial perforant pathway (MPP)-DG synapses are also normal in Neph2 -/- mice at postnatal week 3, further confirming the age-specific synaptic defects. Together, our results provide some evidence for the postsynaptic function of Neph2 in DG neurons during the early postnatal period, which might be implicated in neurodevelopmental and cognitive disorders caused by NEPH2 mutations.

Input transformation by dendritic spines of pyramidal neurons

PubMed Central

Araya, Roberto

2014-01-01

In the mammalian brain, most inputs received by a neuron are formed on the dendritic tree. In the neocortex, the dendrites of pyramidal neurons are covered by thousands of tiny protrusions known as dendritic spines, which are the major recipient sites for excitatory synaptic information in the brain. Their peculiar morphology, with a small head connected to the dendritic shaft by a slender neck, has inspired decades of theoretical and more recently experimental work in an attempt to understand how excitatory synaptic inputs are processed, stored and integrated in pyramidal neurons. Advances in electrophysiological, optical and genetic tools are now enabling us to unravel the biophysical and molecular mechanisms controlling spine function in health and disease. Here I highlight relevant findings, challenges and hypotheses on spine function, with an emphasis on the electrical properties of spines and on how these affect the storage and integration of excitatory synaptic inputs in pyramidal neurons. In an attempt to make sense of the published data, I propose that the raison d'etre for dendritic spines lies in their ability to undergo activity-dependent structural and molecular changes that can modify synaptic strength, and hence alter the gain of the linearly integrated sub-threshold depolarizations in pyramidal neuron dendrites before the generation of a dendritic spike. PMID:25520626

Measuring Symmetry, Asymmetry and Randomness in Neural Network Connectivity

PubMed Central

Esposito, Umberto; Giugliano, Michele; van Rossum, Mark; Vasilaki, Eleni

2014-01-01

Cognitive functions are stored in the connectome, the wiring diagram of the brain, which exhibits non-random features, so-called motifs. In this work, we focus on bidirectional, symmetric motifs, i.e. two neurons that project to each other via connections of equal strength, and unidirectional, non-symmetric motifs, i.e. within a pair of neurons only one neuron projects to the other. We hypothesise that such motifs have been shaped via activity dependent synaptic plasticity processes. As a consequence, learning moves the distribution of the synaptic connections away from randomness. Our aim is to provide a global, macroscopic, single parameter characterisation of the statistical occurrence of bidirectional and unidirectional motifs. To this end we define a symmetry measure that does not require any a priori thresholding of the weights or knowledge of their maximal value. We calculate its mean and variance for random uniform or Gaussian distributions, which allows us to introduce a confidence measure of how significantly symmetric or asymmetric a specific configuration is, i.e. how likely it is that the configuration is the result of chance. We demonstrate the discriminatory power of our symmetry measure by inspecting the eigenvalues of different types of connectivity matrices. We show that a Gaussian weight distribution biases the connectivity motifs to more symmetric configurations than a uniform distribution and that introducing a random synaptic pruning, mimicking developmental regulation in synaptogenesis, biases the connectivity motifs to more asymmetric configurations, regardless of the distribution. We expect that our work will benefit the computational modelling community, by providing a systematic way to characterise symmetry and asymmetry in network structures. Further, our symmetry measure will be of use to electrophysiologists that investigate symmetry of network connectivity. PMID:25006663

Measuring symmetry, asymmetry and randomness in neural network connectivity.

PubMed

Esposito, Umberto; Giugliano, Michele; van Rossum, Mark; Vasilaki, Eleni

2014-01-01

Cognitive functions are stored in the connectome, the wiring diagram of the brain, which exhibits non-random features, so-called motifs. In this work, we focus on bidirectional, symmetric motifs, i.e. two neurons that project to each other via connections of equal strength, and unidirectional, non-symmetric motifs, i.e. within a pair of neurons only one neuron projects to the other. We hypothesise that such motifs have been shaped via activity dependent synaptic plasticity processes. As a consequence, learning moves the distribution of the synaptic connections away from randomness. Our aim is to provide a global, macroscopic, single parameter characterisation of the statistical occurrence of bidirectional and unidirectional motifs. To this end we define a symmetry measure that does not require any a priori thresholding of the weights or knowledge of their maximal value. We calculate its mean and variance for random uniform or Gaussian distributions, which allows us to introduce a confidence measure of how significantly symmetric or asymmetric a specific configuration is, i.e. how likely it is that the configuration is the result of chance. We demonstrate the discriminatory power of our symmetry measure by inspecting the eigenvalues of different types of connectivity matrices. We show that a Gaussian weight distribution biases the connectivity motifs to more symmetric configurations than a uniform distribution and that introducing a random synaptic pruning, mimicking developmental regulation in synaptogenesis, biases the connectivity motifs to more asymmetric configurations, regardless of the distribution. We expect that our work will benefit the computational modelling community, by providing a systematic way to characterise symmetry and asymmetry in network structures. Further, our symmetry measure will be of use to electrophysiologists that investigate symmetry of network connectivity.

Neurons with hysteresis form a network that can learn without any changes in synaptic connection strengths

NASA Astrophysics Data System (ADS)

Hoffmann, Geoffrey W.; Benson, Maurice W.

1986-08-01

A neural network concept derived from an analogy between the immune system and the central nerous system is outlined. The theory is based on a nervous that is slightly more complicated than the conventional McCullogh-Pitts type of neuron, in that it exhibits hysteresis at the single cell level. This added complication is compensated by the fact that a network of such neurons is able to learn without the necessity for any changes in synaptic connection strengths. The learning occurs as a natural consequence of interactions between the network and its enviornment, with environmental stimuli moving the system around in an N-dimensional phase space, until a point in phase space is reached such that the system's responses are appropriate for dealing with the stimuli. Due to the hysteresis associated with each neuron, the system tends to stay in the region of phase space where it is located. The theory includes a role for sleep in learning.

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

PubMed Central

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

2015-01-01

A key aspect of nervous system development, including that of the cerebral cortex, is the formation of higher-order neural networks. Developing neural networks undergo several phases with distinct activity patterns in vivo, which are thought to prune and fine-tune network connectivity. We report here that human pluripotent stem cell (hPSC)-derived cerebral cortex neurons form large-scale networks that reflect those found in the developing cerebral cortex in vivo. Synchronised oscillatory networks develop in a highly stereotyped pattern over several weeks in culture. An initial phase of increasing frequency of oscillations is followed by a phase of decreasing frequency, before giving rise to non-synchronous, ordered activity patterns. hPSC-derived cortical neural networks are excitatory, driven by activation of AMPA- and NMDA-type glutamate receptors, and can undergo NMDA-receptor-mediated plasticity. Investigating single neuron connectivity within PSC-derived cultures, using rabies-based trans-synaptic tracing, we found two broad classes of neuronal connectivity: most neurons have small numbers (<10) of presynaptic inputs, whereas a small set of hub-like neurons have large numbers of synaptic connections (>40). These data demonstrate that the formation of hPSC-derived cortical networks mimics in vivo cortical network development and function, demonstrating the utility of in vitro systems for mechanistic studies of human forebrain neural network biology. PMID:26395144

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

PubMed

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

2015-09-15

A key aspect of nervous system development, including that of the cerebral cortex, is the formation of higher-order neural networks. Developing neural networks undergo several phases with distinct activity patterns in vivo, which are thought to prune and fine-tune network connectivity. We report here that human pluripotent stem cell (hPSC)-derived cerebral cortex neurons form large-scale networks that reflect those found in the developing cerebral cortex in vivo. Synchronised oscillatory networks develop in a highly stereotyped pattern over several weeks in culture. An initial phase of increasing frequency of oscillations is followed by a phase of decreasing frequency, before giving rise to non-synchronous, ordered activity patterns. hPSC-derived cortical neural networks are excitatory, driven by activation of AMPA- and NMDA-type glutamate receptors, and can undergo NMDA-receptor-mediated plasticity. Investigating single neuron connectivity within PSC-derived cultures, using rabies-based trans-synaptic tracing, we found two broad classes of neuronal connectivity: most neurons have small numbers (<10) of presynaptic inputs, whereas a small set of hub-like neurons have large numbers of synaptic connections (>40). These data demonstrate that the formation of hPSC-derived cortical networks mimics in vivo cortical network development and function, demonstrating the utility of in vitro systems for mechanistic studies of human forebrain neural network biology. © 2015. Published by The Company of Biologists Ltd.

Synaptic Mechanisms of Memory Consolidation during Sleep Slow Oscillations

PubMed Central

Wei, Yina; Krishnan, Giri P.

2016-01-01

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

Intrinsic Cellular Properties and Connectivity Density Determine Variable Clustering Patterns in Randomly Connected Inhibitory Neural Networks

PubMed Central

Rich, Scott; Booth, Victoria; Zochowski, Michal

2016-01-01

The plethora of inhibitory interneurons in the hippocampus and cortex play a pivotal role in generating rhythmic activity by clustering and synchronizing cell firing. Results of our simulations demonstrate that both the intrinsic cellular properties of neurons and the degree of network connectivity affect the characteristics of clustered dynamics exhibited in randomly connected, heterogeneous inhibitory networks. We quantify intrinsic cellular properties by the neuron's current-frequency relation (IF curve) and Phase Response Curve (PRC), a measure of how perturbations given at various phases of a neurons firing cycle affect subsequent spike timing. We analyze network bursting properties of networks of neurons with Type I or Type II properties in both excitability and PRC profile; Type I PRCs strictly show phase advances and IF curves that exhibit frequencies arbitrarily close to zero at firing threshold while Type II PRCs display both phase advances and delays and IF curves that have a non-zero frequency at threshold. Type II neurons whose properties arise with or without an M-type adaptation current are considered. We analyze network dynamics under different levels of cellular heterogeneity and as intrinsic cellular firing frequency and the time scale of decay of synaptic inhibition are varied. Many of the dynamics exhibited by these networks diverge from the predictions of the interneuron network gamma (ING) mechanism, as well as from results in all-to-all connected networks. Our results show that randomly connected networks of Type I neurons synchronize into a single cluster of active neurons while networks of Type II neurons organize into two mutually exclusive clusters segregated by the cells' intrinsic firing frequencies. Networks of Type II neurons containing the adaptation current behave similarly to networks of either Type I or Type II neurons depending on network parameters; however, the adaptation current creates differences in the cluster dynamics compared to those in networks of Type I or Type II neurons. To understand these results, we compute neuronal PRCs calculated with a perturbation matching the profile of the synaptic current in our networks. Differences in profiles of these PRCs across the different neuron types reveal mechanisms underlying the divergent network dynamics. PMID:27812323

Just-in-time connectivity for large spiking networks.

PubMed

Lytton, William W; Omurtag, Ahmet; Neymotin, Samuel A; Hines, Michael L

2008-11-01

The scale of large neuronal network simulations is memory limited due to the need to store connectivity information: connectivity storage grows as the square of neuron number up to anatomically relevant limits. Using the NEURON simulator as a discrete-event simulator (no integration), we explored the consequences of avoiding the space costs of connectivity through regenerating connectivity parameters when needed: just in time after a presynaptic cell fires. We explored various strategies for automated generation of one or more of the basic static connectivity parameters: delays, postsynaptic cell identities, and weights, as well as run-time connectivity state: the event queue. Comparison of the JitCon implementation to NEURON's standard NetCon connectivity method showed substantial space savings, with associated run-time penalty. Although JitCon saved space by eliminating connectivity parameters, larger simulations were still memory limited due to growth of the synaptic event queue. We therefore designed a JitEvent algorithm that added items to the queue only when required: instead of alerting multiple postsynaptic cells, a spiking presynaptic cell posted a callback event at the shortest synaptic delay time. At the time of the callback, this same presynaptic cell directly notified the first postsynaptic cell and generated another self-callback for the next delay time. The JitEvent implementation yielded substantial additional time and space savings. We conclude that just-in-time strategies are necessary for very large network simulations but that a variety of alternative strategies should be considered whose optimality will depend on the characteristics of the simulation to be run.

Effects of spike-time-dependent plasticity on the stochastic resonance of small-world neuronal networks

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

Yu, Haitao; Guo, Xinmeng; Wang, Jiang, E-mail: jiangwang@tju.edu.cn

2014-09-01

The phenomenon of stochastic resonance in Newman-Watts small-world neuronal networks is investigated when the strength of synaptic connections between neurons is adaptively adjusted by spike-time-dependent plasticity (STDP). It is shown that irrespective of the synaptic connectivity is fixed or adaptive, the phenomenon of stochastic resonance occurs. The efficiency of network stochastic resonance can be largely enhanced by STDP in the coupling process. Particularly, the resonance for adaptive coupling can reach a much larger value than that for fixed one when the noise intensity is small or intermediate. STDP with dominant depression and small temporal window ratio is more efficient formore » the transmission of weak external signal in small-world neuronal networks. In addition, we demonstrate that the effect of stochastic resonance can be further improved via fine-tuning of the average coupling strength of the adaptive network. Furthermore, the small-world topology can significantly affect stochastic resonance of excitable neuronal networks. It is found that there exists an optimal probability of adding links by which the noise-induced transmission of weak periodic signal peaks.« less

A distance constrained synaptic plasticity model of C. elegans neuronal network

NASA Astrophysics Data System (ADS)

Badhwar, Rahul; Bagler, Ganesh

2017-03-01

Brain research has been driven by enquiry for principles of brain structure organization and its control mechanisms. The neuronal wiring map of C. elegans, the only complete connectome available till date, presents an incredible opportunity to learn basic governing principles that drive structure and function of its neuronal architecture. Despite its apparently simple nervous system, C. elegans is known to possess complex functions. The nervous system forms an important underlying framework which specifies phenotypic features associated to sensation, movement, conditioning and memory. In this study, with the help of graph theoretical models, we investigated the C. elegans neuronal network to identify network features that are critical for its control. The 'driver neurons' are associated with important biological functions such as reproduction, signalling processes and anatomical structural development. We created 1D and 2D network models of C. elegans neuronal system to probe the role of features that confer controllability and small world nature. The simple 1D ring model is critically poised for the number of feed forward motifs, neuronal clustering and characteristic path-length in response to synaptic rewiring, indicating optimal rewiring. Using empirically observed distance constraint in the neuronal network as a guiding principle, we created a distance constrained synaptic plasticity model that simultaneously explains small world nature, saturation of feed forward motifs as well as observed number of driver neurons. The distance constrained model suggests optimum long distance synaptic connections as a key feature specifying control of the network.

From a meso- to micro-scale connectome: array tomography and mGRASP

PubMed Central

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

Interregional synaptic maps among engram cells underlie memory formation.

PubMed

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.

Generation of dense statistical connectomes from sparse morphological data

PubMed Central

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

Multiple effects of β-amyloid on single excitatory synaptic connections in the PFC

PubMed Central

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

Astrocytes refine cortical connectivity at dendritic spines

PubMed Central

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

Rapid Neocortical Dynamics: Cellular and Network Mechanisms

PubMed Central

Haider, Bilal; McCormick, David A.

2011-01-01

The highly interconnected local and large-scale networks of the neocortical sheet rapidly and dynamically modulate their functional connectivity according to behavioral demands. This basic operating principle of the neocortex is mediated by the continuously changing flow of excitatory and inhibitory synaptic barrages that not only control participation of neurons in networks but also define the networks themselves. The rapid control of neuronal responsiveness via synaptic bombardment is a fundamental property of cortical dynamics that may provide the basis of diverse behaviors, including sensory perception, motor integration, working memory, and attention. PMID:19409263

Plasticity of synaptic connections in sensory-motor pathways of the adult locust flight system.

PubMed

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.

Direct connections assist neurons to detect correlation in small amplitude noises

PubMed Central

Bolhasani, E.; Azizi, Y.; Valizadeh, A.

2013-01-01

We address a question on the effect of common stochastic inputs on the correlation of the spike trains of two neurons when they are coupled through direct connections. We show that the change in the correlation of small amplitude stochastic inputs can be better detected when the neurons are connected by direct excitatory couplings. Depending on whether intrinsic firing rate of the neurons is identical or slightly different, symmetric or asymmetric connections can increase the sensitivity of the system to the input correlation by changing the mean slope of the correlation transfer function over a given range of input correlation. In either case, there is also an optimum value for synaptic strength which maximizes the sensitivity of the system to the changes in input correlation. PMID:23966940

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.

Structural versus dynamical origins of mean-field behavior in a self-organized critical model of neuronal avalanches

NASA Astrophysics Data System (ADS)

Moosavi, S. Amin; Montakhab, Afshin

2015-11-01

Critical dynamics of cortical neurons have been intensively studied over the past decade. Neuronal avalanches provide the main experimental as well as theoretical tools to consider criticality in such systems. Experimental studies show that critical neuronal avalanches show mean-field behavior. There are structural as well as recently proposed [Phys. Rev. E 89, 052139 (2014), 10.1103/PhysRevE.89.052139] dynamical mechanisms that can lead to mean-field behavior. In this work we consider a simple model of neuronal dynamics based on threshold self-organized critical models with synaptic noise. We investigate the role of high-average connectivity, random long-range connections, as well as synaptic noise in achieving mean-field behavior. We employ finite-size scaling in order to extract critical exponents with good accuracy. We conclude that relevant structural mechanisms responsible for mean-field behavior cannot be justified in realistic models of the cortex. However, strong dynamical noise, which can have realistic justifications, always leads to mean-field behavior regardless of the underlying structure. Our work provides a different (dynamical) origin than the conventionally accepted (structural) mechanisms for mean-field behavior in neuronal avalanches.

The impact of perinatal stress on the functional maturation of prefronto-cortical synaptic circuits: implications for the pathophysiology of ADHD?

PubMed

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.

When Long-Range Zero-Lag Synchronization is Feasible in Cortical Networks

PubMed Central

Viriyopase, Atthaphon; Bojak, Ingo; Zeitler, Magteld; Gielen, Stan

2012-01-01

Many studies have reported long-range synchronization of neuronal activity between brain areas, in particular in the beta and gamma bands with frequencies in the range of 14–30 and 40–80 Hz, respectively. Several studies have reported synchrony with zero phase lag, which is remarkable considering the synaptic and conduction delays inherent in the connections between distant brain areas. This result has led to many speculations about the possible functional role of zero-lag synchrony, such as for neuronal communication, attention, memory, and feature binding. However, recent studies using recordings of single-unit activity and local field potentials report that neuronal synchronization may occur with non-zero phase lags. This raises the questions whether zero-lag synchrony can occur in the brain and, if so, under which conditions. We used analytical methods and computer simulations to investigate which connectivity between neuronal populations allows or prohibits zero-lag synchrony. We did so for a model where two oscillators interact via a relay oscillator. Analytical results and computer simulations were obtained for both type I Mirollo–Strogatz neurons and type II Hodgkin–Huxley neurons. We have investigated the dynamics of the model for various types of synaptic coupling and importantly considered the potential impact of Spike-Timing Dependent Plasticity (STDP) and its learning window. We confirm previous results that zero-lag synchrony can be achieved in this configuration. This is much easier to achieve with Hodgkin–Huxley neurons, which have a biphasic phase response curve, than for type I neurons. STDP facilitates zero-lag synchrony as it adjusts the synaptic strengths such that zero-lag synchrony is feasible for a much larger range of parameters than without STDP. PMID:22866034

Quantitative neuroanatomy for connectomics in Drosophila

PubMed Central

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

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

PubMed

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

2018-07-01

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

The laminar organization of the Drosophila ellipsoid body is semaphorin-dependent and prevents the formation of ectopic synaptic connections

PubMed Central

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

Endogenous cannabinoids mediate retrograde signals from depolarized postsynaptic neurons to presynaptic terminals.

PubMed

Ohno-Shosaku, T; Maejima, T; Kano, M

2001-03-01

Endogenous cannabinoids are considered to function as diffusible and short-lived modulators that may transmit signals retrogradely from postsynaptic to presynaptic neurons. To evaluate this possibility, we have made a paired whole-cell recording from cultured hippocampal neurons with inhibitory synaptic connections. In about 60% of pairs, a cannabinoid agonist greatly reduced the release of the inhibitory neurotransmitter GABA from presynaptic terminals. In most of such pairs but not in those insensitive to the agonist, depolarization of postsynaptic neurons and the resultant elevation of intracellular Ca2+ concentration caused transient suppression of inhibitory synaptic currents, which is mainly due to reduction of GABA release. This depolarization-induced suppression was completely blocked by selective cannabinoid antagonists. Our results reveal that endogenous cannabinoids mediate retrograde signals from depolarized postsynaptic neurons to presynaptic terminals to cause the reduction of transmitter release.

Sonic Hedgehog Expression in Corticofugal Projection Neurons Directs Cortical Microcircuit Formation

PubMed Central

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

Direct connection of the nucleus reticularis gigantocellularis neurons with neck motoneurons in cats.

PubMed

Sasaki, S

1999-10-01

Functional connections of single reticulospinal neurons (RSNs) in the nucleus reticularis gigantocellularis (NRG) with ipsilateral dorsal neck motoneurons were examined with the spike-triggered averaging technique. Extracellular spikes of single NRG-RSNs activated antidromically from the C6, but not from the L1 segment (C-RSNs) were used as the trigger. These neurons were monosynaptically activated from the superior colliculus and the cerebral peduncle. Single-RSN PSPs were recorded in 43 dorsal neck motoneurons [biventer cervicis and complexus (BCC) and splenius (SPL)] for 21 NRG-RSNs and 135 motoneurons tested. All synaptic potentials were EPSPs, and most of their latencies, measured from the triggering spikes, were 0.8-1.5 ms, which is in a monosynaptic range. The amplitudes of single-RSN EPSPs were 10-360 microV. Spike-triggered averaging revealed single-RSN EPSPs in multiple motoneurons of the same species (SPL or BCC), their locations extending up to nearly 1 mm rostrocaudally. Synaptic connections of single RSNs with both SPL and BCC motoneurons were also found with some predominance for one of them. The results provide direct evidence that NRG-RSNs make monosynaptic excitatory connections with SPL and BCC motoneurons. It appears that some NRG-RSNs connect predominantly with SPL motoneurons and others with BCC motoneurons.

The homeostatic astroglia emerges from evolutionary specialization of neural cells

PubMed Central

Verkhratsky, Alexei; Nedergaard, Maiken

2016-01-01

Evolution of the nervous system progressed through cellular diversification and specialization of functions. Conceptually, the nervous system is composed from electrically excitable neuronal networks connected with chemical synapses and non-excitable glial cells that provide for homeostasis and defence. Astrocytes are integrated into neural networks through multipartite synapses; astroglial perisynaptic processes closely enwrap synaptic contacts and control homeostasis of the synaptic cleft, supply neurons with glutamate and GABA obligatory precursor glutamine and contribute to synaptic plasticity, learning and memory. In neuropathology, astrocytes may undergo reactive remodelling or degeneration; to a large extent, astroglial reactions define progression of the pathology and neurological outcome. This article is part of the themed issue ‘Evolution brings Ca2+ and ATP together to control life and death’. PMID:27377722

Heteroassociative storage of hippocampal pattern sequences in the CA3 subregion

PubMed Central

Recio, Renan S.; Reyes, Marcelo B.

2018-01-01

Background Recent research suggests that the CA3 subregion of the hippocampus has properties of both autoassociative network, due to its ability to complete partial cues, tolerate noise, and store associations between memories, and heteroassociative one, due to its ability to store and retrieve sequences of patterns. Although there are several computational models of the CA3 as an autoassociative network, more detailed evaluations of its heteroassociative properties are missing. Methods We developed a model of the CA3 subregion containing 10,000 integrate-and-fire neurons with both recurrent excitatory and inhibitory connections, and which exhibits coupled oscillations in the gamma and theta ranges. We stored thousands of pattern sequences using a heteroassociative learning rule with competitive synaptic scaling. Results We showed that a purely heteroassociative network model can (i) retrieve pattern sequences from partial cues with external noise and incomplete connectivity, (ii) achieve homeostasis regarding the number of connections per neuron when many patterns are stored when using synaptic scaling, (iii) continuously update the set of retrievable patterns, guaranteeing that the last stored patterns can be retrieved and older ones can be forgotten. Discussion Heteroassociative networks with synaptic scaling rules seem sufficient to achieve many desirable features regarding connectivity homeostasis, pattern sequence retrieval, noise tolerance and updating of the set of retrievable patterns. PMID:29312826

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

PubMed

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

2012-03-01

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

Regulation of the Proteasome by Neuronal Activity and Calcium/Calmodulin-dependent Protein Kinase II*

PubMed Central

Djakovic, Stevan N.; Schwarz, Lindsay A.; Barylko, Barbara; DeMartino, George N.; Patrick, Gentry N.

2009-01-01

Protein degradation via the ubiquitin proteasome system has been shown to regulate changes in synaptic strength that underlie multiple forms of synaptic plasticity. It is plausible, therefore, that the ubiquitin proteasome system is itself regulated by synaptic activity. By utilizing live-cell imaging strategies we report the rapid and dynamic regulation of the proteasome in hippocampal neurons by synaptic activity. We find that the blockade of action potentials (APs) with tetrodotoxin inhibited the activity of the proteasome, whereas the up-regulation of APs with bicuculline dramatically increased the activity of the proteasome. In addition, the regulation of the proteasome is dependent upon external calcium entry in part through N-methyl-d-aspartate receptors and L-type voltage-gated calcium channels and requires the activity of calcium/calmodulin-dependent protein kinase II (CaMKII). Using in vitro and in vivo assays we find that CaMKII stimulates proteasome activity and directly phosphorylates Rpt6, a subunit of the 19 S (PA700) subcomplex of the 26 S proteasome. Our data provide a novel mechanism whereby CaMKII may regulate the proteasome in neurons to facilitate remodeling of synaptic connections through protein degradation. PMID:19638347

The roles of protein expression in synaptic plasticity and memory consolidation

PubMed Central

Rosenberg, Tali; Gal-Ben-Ari, Shunit; Dieterich, Daniela C.; Kreutz, Michael R.; Ziv, Noam E.; Gundelfinger, Eckart D.; Rosenblum, Kobi

2014-01-01

The amount and availability of proteins are regulated by their synthesis, degradation, and transport. These processes can specifically, locally, and temporally regulate a protein or a population of proteins, thus affecting numerous biological processes in health and disease states. Accordingly, malfunction in the processes of protein turnover and localization underlies different neuronal diseases. However, as early as a century ago, it was recognized that there is a specific need for normal macromolecular synthesis in a specific fragment of the learning process, memory consolidation, which takes place minutes to hours following acquisition. Memory consolidation is the process by which fragile short-term memory is converted into stable long-term memory. It is accepted today that synaptic plasticity is a cellular mechanism of learning and memory processes. Interestingly, similar molecular mechanisms subserve both memory and synaptic plasticity consolidation. In this review, we survey the current view on the connection between memory consolidation processes and proteostasis, i.e., maintaining the protein contents at the neuron and the synapse. In addition, we describe the technical obstacles and possible new methods to determine neuronal proteostasis of synaptic function and better explain the process of memory and synaptic plasticity consolidation. PMID:25429258

Regulation of the proteasome by neuronal activity and calcium/calmodulin-dependent protein kinase II.

PubMed

Djakovic, Stevan N; Schwarz, Lindsay A; Barylko, Barbara; DeMartino, George N; Patrick, Gentry N

2009-09-25

Protein degradation via the ubiquitin proteasome system has been shown to regulate changes in synaptic strength that underlie multiple forms of synaptic plasticity. It is plausible, therefore, that the ubiquitin proteasome system is itself regulated by synaptic activity. By utilizing live-cell imaging strategies we report the rapid and dynamic regulation of the proteasome in hippocampal neurons by synaptic activity. We find that the blockade of action potentials (APs) with tetrodotoxin inhibited the activity of the proteasome, whereas the up-regulation of APs with bicuculline dramatically increased the activity of the proteasome. In addition, the regulation of the proteasome is dependent upon external calcium entry in part through N-methyl-D-aspartate receptors and L-type voltage-gated calcium channels and requires the activity of calcium/calmodulin-dependent protein kinase II (CaMKII). Using in vitro and in vivo assays we find that CaMKII stimulates proteasome activity and directly phosphorylates Rpt6, a subunit of the 19 S (PA700) subcomplex of the 26 S proteasome. Our data provide a novel mechanism whereby CaMKII may regulate the proteasome in neurons to facilitate remodeling of synaptic connections through protein degradation.

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

PubMed

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

2010-05-01

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

Tracking the Fear Memory Engram: Discrete Populations of Neurons within Amygdala, Hypothalamus, and Lateral Septum Are Specifically Activated by Auditory Fear Conditioning

ERIC Educational Resources Information Center

Butler, Christopher W.; Wilson, Yvette M.; Gunnersen, Jenny M.; Murphy, Mark

2015-01-01

Memory formation is thought to occur via enhanced synaptic connectivity between populations of neurons in the brain. However, it has been difficult to localize and identify the neurons that are directly involved in the formation of any specific memory. We have previously used "fos-tau-lacZ" ("FTL") transgenic mice to identify…

Cytoarchitectonic and quantitative Golgi study of the hedgehog supraoptic nucleus.

PubMed

Caminero, A A; Machín, C; Sanchez-Toscano, F

1992-02-01

A cytoarchitectural study was made of the supraoptic nucleus (SON) of the hedgehog with special attention to the quantitative comparison of its main neuronal types. The main purposes were (1) to relate the characteristics of this nucleus in the hedgehog (a primitive mammalian insectivorous brain) with those in the SONs of more evolutionarily advanced species; (2) to identify quantitatively the dendritic fields of the main neuronal types in the hedgehog SON and to study their synaptic connectivity. From a descriptive standpoint, 3 neuronal types were found with respect to the number of dendritic stems arising from the neuronal soma: bipolar neurons (48%), multipolar neurons (45.5%) and monopolar neurons (6.5%). Within the multipolar type 2 subtypes could be distinguished, taking into account the number of dendritic spines: (a) with few spines (93%) and (b) very spiny (7%). These results indicate that the hedgehog SON is similar to that in other species except for the very spiny neurons, the significance of which is discussed. In order to characterise the main types more satisfactorily (bipolar and multipolars with few spines) we undertook a quantitative Golgi study of their dendritic fields. Although the patterns of the dendritic field are similar in both neuronal types, the differences in the location of their connectivity can reflect functional changes and alterations in relation to the synaptic afferences.

Beyond the cortical column: abundance and physiology of horizontal connections imply a strong role for inputs from the surround.

PubMed

Boucsein, Clemens; Nawrot, Martin P; Schnepel, Philipp; Aertsen, Ad

2011-01-01

Current concepts of cortical information processing and most cortical network models largely rest on the assumption that well-studied properties of local synaptic connectivity are sufficient to understand the generic properties of cortical networks. This view seems to be justified by the observation that the vertical connectivity within local volumes is strong, whereas horizontally, the connection probability between pairs of neurons drops sharply with distance. Recent neuroanatomical studies, however, have emphasized that a substantial fraction of synapses onto neocortical pyramidal neurons stems from cells outside the local volume. Here, we discuss recent findings on the signal integration from horizontal inputs, showing that they could serve as a substrate for reliable and temporally precise signal propagation. Quantification of connection probabilities and parameters of synaptic physiology as a function of lateral distance indicates that horizontal projections constitute a considerable fraction, if not the majority, of inputs from within the cortical network. Taking these non-local horizontal inputs into account may dramatically change our current view on cortical information processing.

Diversity in Long-Term Synaptic Plasticity at Inhibitory Synapses of Striatal Spiny Neurons

ERIC Educational Resources Information Center

Rueda-Orozco, Pavel E.; Mendoza, Ernesto; Hernandez, Ricardo; Aceves, Jose J.; Ibanez-Sandoval, Osvaldo; Galarraga, Elvira; Bargas, Jose

2009-01-01

Procedural memories and habits are posited to be stored in the basal ganglia, whose intrinsic circuitries possess important inhibitory connections arising from striatal spiny neurons. However, no information about long-term plasticity at these synapses is available. Therefore, this work describes a novel postsynaptically dependent long-term…

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

PubMed Central

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

2014-01-01

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

Neuroanatomy goes viral!

PubMed Central

Nassi, Jonathan J.; Cepko, Constance L.; Born, Richard T.; Beier, Kevin T.

2015-01-01

The nervous system is complex not simply because of the enormous number of neurons it contains but by virtue of the specificity with which they are connected. Unraveling this specificity is the task of neuroanatomy. In this endeavor, neuroanatomists have traditionally exploited an impressive array of tools ranging from the Golgi method to electron microscopy. An ideal method for studying anatomy would label neurons that are interconnected, and, in addition, allow expression of foreign genes in these neurons. Fortuitously, nature has already partially developed such a method in the form of neurotropic viruses, which have evolved to deliver their genetic material between synaptically connected neurons while largely eluding glia and the immune system. While these characteristics make some of these viruses a threat to human health, simple modifications allow them to be used in controlled experimental settings, thus enabling neuroanatomists to trace multi-synaptic connections within and across brain regions. Wild-type neurotropic viruses, such as rabies and alpha-herpes virus, have already contributed greatly to our understanding of brain connectivity, and modern molecular techniques have enabled the construction of recombinant forms of these and other viruses. These newly engineered reagents are particularly useful, as they can target genetically defined populations of neurons, spread only one synapse to either inputs or outputs, and carry instructions by which the targeted neurons can be made to express exogenous proteins, such as calcium sensors or light-sensitive ion channels, that can be used to study neuronal function. In this review, we address these uniquely powerful features of the viruses already in the neuroanatomist’s toolbox, as well as the aspects of their biology that currently limit their utility. Based on the latter, we consider strategies for improving viral tracing methods by reducing toxicity, improving control of transsynaptic spread, and extending the range of species that can be studied. PMID:26190977

High Content Analysis of Hippocampal Neuron-Astrocyte Co-cultures Shows a Positive Effect of Fortasyn Connect on Neuronal Survival and Postsynaptic Maturation.

PubMed

van Deijk, Anne-Lieke F; Broersen, Laus M; Verkuyl, J Martin; Smit, August B; Verheijen, Mark H G

2017-01-01

Neuronal and synaptic membranes are composed of a phospholipid bilayer. Supplementation with dietary precursors for phospholipid synthesis -docosahexaenoic acid (DHA), uridine and choline- has been shown to increase neurite outgrowth and synaptogenesis both in vivo and in vitro . A role for multi-nutrient intervention with specific precursors and cofactors has recently emerged in early Alzheimer's disease, which is characterized by decreased synapse numbers in the hippocampus. Moreover, the medical food Souvenaid, containing the specific nutrient combination Fortasyn Connect (FC), improves memory performance in early Alzheimer's disease patients, possibly via maintaining brain connectivity. This suggests an effect of FC on synapses, but the underlying cellular mechanism is not fully understood. Therefore, we investigated the effect of FC (consisting of DHA, eicosapentaenoic acid (EPA), uridine, choline, phospholipids, folic acid, vitamins B12, B6, C and E, and selenium), on synaptogenesis by supplementing it to primary neuron-astrocyte co-cultures, a cellular model that mimics metabolic dependencies in the brain. We measured neuronal developmental processes using high content screening in an automated manner, including neuronal survival, neurite morphology, as well as the formation and maturation of synapses. Here, we show that FC supplementation resulted in increased numbers of neurons without affecting astrocyte number. Furthermore, FC increased postsynaptic PSD95 levels in both immature and mature synapses. These findings suggest that supplementation with FC to neuron-astrocyte co-cultures increased both neuronal survival and the maturation of postsynaptic terminals, which might aid the functional interpretation of FC-based intervention strategies in neurological diseases characterized by neuronal loss and impaired synaptic functioning.

High Content Analysis of Hippocampal Neuron-Astrocyte Co-cultures Shows a Positive Effect of Fortasyn Connect on Neuronal Survival and Postsynaptic Maturation

PubMed Central

van Deijk, Anne-Lieke F.; Broersen, Laus M.; Verkuyl, J. Martin; Smit, August B.; Verheijen, Mark H. G.

2017-01-01

Neuronal and synaptic membranes are composed of a phospholipid bilayer. Supplementation with dietary precursors for phospholipid synthesis –docosahexaenoic acid (DHA), uridine and choline– has been shown to increase neurite outgrowth and synaptogenesis both in vivo and in vitro. A role for multi-nutrient intervention with specific precursors and cofactors has recently emerged in early Alzheimer's disease, which is characterized by decreased synapse numbers in the hippocampus. Moreover, the medical food Souvenaid, containing the specific nutrient combination Fortasyn Connect (FC), improves memory performance in early Alzheimer's disease patients, possibly via maintaining brain connectivity. This suggests an effect of FC on synapses, but the underlying cellular mechanism is not fully understood. Therefore, we investigated the effect of FC (consisting of DHA, eicosapentaenoic acid (EPA), uridine, choline, phospholipids, folic acid, vitamins B12, B6, C and E, and selenium), on synaptogenesis by supplementing it to primary neuron-astrocyte co-cultures, a cellular model that mimics metabolic dependencies in the brain. We measured neuronal developmental processes using high content screening in an automated manner, including neuronal survival, neurite morphology, as well as the formation and maturation of synapses. Here, we show that FC supplementation resulted in increased numbers of neurons without affecting astrocyte number. Furthermore, FC increased postsynaptic PSD95 levels in both immature and mature synapses. These findings suggest that supplementation with FC to neuron-astrocyte co-cultures increased both neuronal survival and the maturation of postsynaptic terminals, which might aid the functional interpretation of FC-based intervention strategies in neurological diseases characterized by neuronal loss and impaired synaptic functioning. PMID:28824363

Examining Neuronal Connectivity and Its Role in Learning and Memory

NASA Astrophysics Data System (ADS)

Gala, Rohan

Learning and long-term memory formation are accompanied with changes in the patterns and weights of synaptic connections in the underlying neuronal network. However, the fundamental rules that drive connectivity changes, and the precise structure-function relationships within neuronal networks remain elusive. Technological improvements over the last few decades have enabled the observation of large but specific subsets of neurons and their connections in unprecedented detail. Devising robust and automated computational methods is critical to distill information from ever-increasing volumes of raw experimental data. Moreover, statistical models and theoretical frameworks are required to interpret the data and assemble evidence into understanding of brain function. In this thesis, I first describe computational methods to reconstruct connectivity based on light microscopy imaging experiments. Next, I use these methods to quantify structural changes in connectivity based on in vivo time-lapse imaging experiments. Finally, I present a theoretical model of associative learning that can explain many stereotypical features of experimentally observed connectivity.

New Insights on Temporal Lobe Epilepsy Based on Plasticity-Related Network Changes and High-Order Statistics.

PubMed

Kinjo, Erika Reime; Rodríguez, Pedro Xavier Royero; Dos Santos, Bianca Araújo; Higa, Guilherme Shigueto Vilar; Ferraz, Mariana Sacrini Ayres; Schmeltzer, Christian; Rüdiger, Sten; Kihara, Alexandre Hiroaki

2018-05-01

Epilepsy is a disorder of the brain characterized by the predisposition to generate recurrent unprovoked seizures, which involves reshaping of neuronal circuitries based on intense neuronal activity. In this review, we first detailed the regulation of plasticity-associated genes, such as ARC, GAP-43, PSD-95, synapsin, and synaptophysin. Indeed, reshaping of neuronal connectivity after the primary, acute epileptogenesis event increases the excitability of the temporal lobe. Herein, we also discussed the heterogeneity of neuronal populations regarding the number of synaptic connections, which in the theoretical field is commonly referred as degree. Employing integrate-and-fire neuronal model, we determined that in addition to increased synaptic strength, degree correlations might play essential and unsuspected roles in the control of network activity. Indeed, assortativity, which can be described as a condition where high-degree correlations are observed, increases the excitability of neural networks. In this review, we summarized recent topics in the field, and data were discussed according to newly developed or unusual tools, as provided by mathematical graph analysis and high-order statistics. With this, we were able to present new foundations for the pathological activity observed in temporal lobe epilepsy.

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.

Neural learning circuits utilizing nano-crystalline silicon transistors and memristors.

PubMed

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.

The Nanoscale Observation of the Three-Dimensional Structures of Neurosynapses, Membranous Conjunctions Between Cultured Hippocampal Neurons and Their Significance in the Development of Epilepsy.

PubMed

Sun, Lan; Jiang, Shuang; Tang, Xianhua; Zhang, Yingge; Qin, Luye; Jiang, Xia; Yu, Albert Cheung Hoi

2016-12-01

The nanoscale three-dimensional structures of neurosynapses are unknown, and the neuroanatomical basis of epilepsy remains to be elucidated. Here, we studied the nanoscale three-dimensional synapses between hippocampal neurons, and membranous conjunctions between neurons were found with atomic force microscopy (AFM) and confirmed by transmission electron microscope (TEM), and their pathophysiological significance was primarily investigated. The neurons and dendrites were marked by MAP-2, axons by neurofilament 200, and synapses by synapsin I immunological staining. In the synapsin I-positive neurite ends of the neurons positively stained with MAP-2 and neurofilament 200, neurosynapses with various nanoscale morphology and structure could be found by AFM. The neurosynapses had typical three-dimensional structures of synaptic triplet including the presynaptic neurite end, synaptic cleft of 30 ∼ 40 in chemical synapses and 2 ∼ 6 nm in electrical ones, the postsynaptic neurite or dendrite spine, the typical neurite end button, the distinct pre- and postsynaptic membranes, and the obvious thickening of the postsynaptic membranes or neurites. Some membranous connections including membrane-like junctions (MLJ) and fiber-tube links (FTL) without triplet structures and cleft were found between neurons. The development frequencies of the two membranous conjunctions increased while those of the synaptic conjunctions decreased between the neurons from Otx1 knock-out mice in comparison with those between the neurons from normal mice. These results suggested that the neuroanatomical basis of Otx1 knock-out epilepsy is the combination of the decreased synaptic conjunctions and the increased membranous conjunctions.

Contribution of sublinear and supralinear dendritic integration to neuronal computations

PubMed Central

Tran-Van-Minh, Alexandra; Cazé, Romain D.; Abrahamsson, Therése; Cathala, Laurence; Gutkin, Boris S.; DiGregorio, David A.

2015-01-01

Nonlinear dendritic integration is thought to increase the computational ability of neurons. Most studies focus on how supralinear summation of excitatory synaptic responses arising from clustered inputs within single dendrites result in the enhancement of neuronal firing, enabling simple computations such as feature detection. Recent reports have shown that sublinear summation is also a prominent dendritic operation, extending the range of subthreshold input-output (sI/O) transformations conferred by dendrites. Like supralinear operations, sublinear dendritic operations also increase the repertoire of neuronal computations, but feature extraction requires different synaptic connectivity strategies for each of these operations. In this article we will review the experimental and theoretical findings describing the biophysical determinants of the three primary classes of dendritic operations: linear, sublinear, and supralinear. We then review a Boolean algebra-based analysis of simplified neuron models, which provides insight into how dendritic operations influence neuronal computations. We highlight how neuronal computations are critically dependent on the interplay of dendritic properties (morphology and voltage-gated channel expression), spiking threshold and distribution of synaptic inputs carrying particular sensory features. Finally, we describe how global (scattered) and local (clustered) integration strategies permit the implementation of similar classes of computations, one example being the object feature binding problem. PMID:25852470

[Physical activity: positive impact on brain plasticity].

PubMed

Achiron, Anat; Kalron, Alon

2008-03-01

The central nervous system has a unique capability of plasticity that enables a single neuron or a group of neurons to undergo functional and constructional changes that are important to learning processes and for compensation of brain damage. The current review aims to summarize recent data related to the effects of physical activity on brain plasticity. In the last decade it was reported that physical activity can affect and manipulate neuronal connections, synaptic activity and adaptation to new neuronal environment following brain injury. One of the most significant neurotrophic factors that is critical for synaptic re-organization and is influenced by physical activity is brain-derived neurotrophic factor (BDNF). The frequency of physical activity and the intensity of exercises are of importance to brain remodeling, support neuronal survival and positively affect rehabilitation therapy. Physical activity should be employed as a tool to improve neural function in healthy subjects and in patients suffering from neurological damage.

Matrix stiffness modulates formation and activity of neuronal networks of controlled architectures.

PubMed

Lantoine, Joséphine; Grevesse, Thomas; Villers, Agnès; Delhaye, Geoffrey; Mestdagh, Camille; Versaevel, Marie; Mohammed, Danahe; Bruyère, Céline; Alaimo, Laura; Lacour, Stéphanie P; Ris, Laurence; Gabriele, Sylvain

2016-05-01

The ability to construct easily in vitro networks of primary neurons organized with imposed topologies is required for neural tissue engineering as well as for the development of neuronal interfaces with desirable characteristics. However, accumulating evidence suggests that the mechanical properties of the culture matrix can modulate important neuronal functions such as growth, extension, branching and activity. Here we designed robust and reproducible laminin-polylysine grid micropatterns on cell culture substrates that have similar biochemical properties but a 100-fold difference in Young's modulus to investigate the role of the matrix rigidity on the formation and activity of cortical neuronal networks. We found that cell bodies of primary cortical neurons gradually accumulate in circular islands, whereas axonal extensions spread on linear tracks to connect circular islands. Our findings indicate that migration of cortical neurons is enhanced on soft substrates, leading to a faster formation of neuronal networks. Furthermore, the pre-synaptic density was two times higher on stiff substrates and consistently the number of action potentials and miniature synaptic currents was enhanced on stiff substrates. Taken together, our results provide compelling evidence to indicate that matrix stiffness is a key parameter to modulate the growth dynamics, synaptic density and electrophysiological activity of cortical neuronal networks, thus providing useful information on scaffold design for neural tissue engineering. Copyright © 2016 Elsevier Ltd. All rights reserved.

Cerebral-buccal pathways in Aplysia californica: synaptic connections, cooperative interneuronal effects and feedback during buccal motor programs.

PubMed

Sánchez, J A; Kirk, M D

2001-12-01

Ingestion of seaweed by Aplysia is in part mediated by cerebral-buccal interneurons that drive rhythmic motor output from the buccal ganglia and in some cases cerebral-buccal interneurons act as members of the feeding central pattern generator. Here we document cooperative interactions between cerebral-buccal interneuron 2 and cerebral-buccal interneuron 12, characterize synaptic input to cerebral-buccal interneuron 2 and cerebral-buccal interneuron 12 from buccal peripheral nerve 2,3, describe a synaptic connection between cerebral-buccal interneuron 1 and buccal neuron B34, further characterize connections made by cerebral-buccal interneurons 2 and -12 with B34 and B61/62, and describe a novel, inhibitory connection made by cerebral-buccal interneuron 2 with a buccal neuron. When cerebral-buccal interneurons 2 and 12 were driven synchronously at low frequencies, ingestion-like buccal motor programs were elicited, and if either was driven alone, indirect synaptic input was recruited in the other cerebral-buccal interneuron. Stimulation of BN2,3 recruited both ingestion and rejection-like motor programs without firing in cerebral-buccal interneurons 2 or 12. During motor programs elicited by cerebral-buccal interneurons 2 or 12, high-voltage stimulation of BN2,3 inhibited firing in both cerebral-buccal interneurons. Our results suggest that cerebral-buccal interneurons 2 and 12 use cooperative interactions to modulate buccal motor programs, yet firing in cerebral-buccal interneurons 2 or 12 is not necessary for recruiting motor programs by buccal peripheral nerve BN2,3, even in preparations with intact cerebral-buccal pathways.

Synaptic inhibition and γ-aminobutyric acid in the mammalian central nervous system

PubMed Central

OBATA, Kunihiko

2013-01-01

Signal transmission through synapses connecting two neurons is mediated by release of neurotransmitter from the presynaptic axon terminals and activation of its receptor at the postsynaptic neurons. γ-Aminobutyric acid (GABA), non-protein amino acid formed by decarboxylation of glutamic acid, is a principal neurotransmitter at inhibitory synapses of vertebrate and invertebrate nervous system. On one hand glutamic acid serves as a principal excitatory neurotransmitter. This article reviews GABA researches on; (1) synaptic inhibition by membrane hyperpolarization, (2) exclusive localization in inhibitory neurons, (3) release from inhibitory neurons, (4) excitatory action at developmental stage, (5) phenotype of GABA-deficient mouse produced by gene-targeting, (6) developmental adjustment of neural network and (7) neurological/psychiatric disorder. In the end, GABA functions in simple nervous system and plants, and non-amino acid neurotransmitters were supplemented. PMID:23574805

Method Accelerates Training Of Some Neural Networks

NASA Technical Reports Server (NTRS)

Shelton, Robert O.

1992-01-01

Three-layer networks trained faster provided two conditions are satisfied: numbers of neurons in layers are such that majority of work done in synaptic connections between input and hidden layers, and number of neurons in input layer at least as great as number of training pairs of input and output vectors. Based on modified version of back-propagation method.

Mapping Inhibitory Neuronal Circuits by Laser Scanning Photostimulation

PubMed Central

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

Natural Firing Patterns Imply Low Sensitivity of Synaptic Plasticity to Spike Timing Compared with Firing Rate

PubMed Central

Wallisch, Pascal; Ostojic, Srdjan

2016-01-01

Synaptic plasticity is sensitive to the rate and the timing of presynaptic and postsynaptic action potentials. In experimental protocols inducing plasticity, the imposed spike trains are typically regular and the relative timing between every presynaptic and postsynaptic spike is fixed. This is at odds with firing patterns observed in the cortex of intact animals, where cells fire irregularly and the timing between presynaptic and postsynaptic spikes varies. To investigate synaptic changes elicited by in vivo-like firing, we used numerical simulations and mathematical analysis of synaptic plasticity models. We found that the influence of spike timing on plasticity is weaker than expected from regular stimulation protocols. Moreover, when neurons fire irregularly, synaptic changes induced by precise spike timing can be equivalently induced by a modest firing rate variation. Our findings bridge the gap between existing results on synaptic plasticity and plasticity occurring in vivo, and challenge the dominant role of spike timing in plasticity. SIGNIFICANCE STATEMENT Synaptic plasticity, the change in efficacy of connections between neurons, is thought to underlie learning and memory. The dominant paradigm posits that the precise timing of neural action potentials (APs) is central for plasticity induction. This concept is based on experiments using highly regular and stereotyped patterns of APs, in stark contrast with natural neuronal activity. Using synaptic plasticity models, we investigated how irregular, in vivo-like activity shapes synaptic plasticity. We found that synaptic changes induced by precise timing of APs are much weaker than suggested by regular stimulation protocols, and can be equivalently induced by modest variations of the AP rate alone. Our results call into question the dominant role of precise AP timing for plasticity in natural conditions. PMID:27807166

Comparison of the dynamics of neural interactions between current-based and conductance-based integrate-and-fire recurrent networks

PubMed Central

Cavallari, Stefano; Panzeri, Stefano; Mazzoni, Alberto

2014-01-01

Models of networks of Leaky Integrate-and-Fire (LIF) neurons are a widely used tool for theoretical investigations of brain function. These models have been used both with current- and conductance-based synapses. However, the differences in the dynamics expressed by these two approaches have been so far mainly studied at the single neuron level. To investigate how these synaptic models affect network activity, we compared the single neuron and neural population dynamics of conductance-based networks (COBNs) and current-based networks (CUBNs) of LIF neurons. These networks were endowed with sparse excitatory and inhibitory recurrent connections, and were tested in conditions including both low- and high-conductance states. We developed a novel procedure to obtain comparable networks by properly tuning the synaptic parameters not shared by the models. The so defined comparable networks displayed an excellent and robust match of first order statistics (average single neuron firing rates and average frequency spectrum of network activity). However, these comparable networks showed profound differences in the second order statistics of neural population interactions and in the modulation of these properties by external inputs. The correlation between inhibitory and excitatory synaptic currents and the cross-neuron correlation between synaptic inputs, membrane potentials and spike trains were stronger and more stimulus-modulated in the COBN. Because of these properties, the spike train correlation carried more information about the strength of the input in the COBN, although the firing rates were equally informative in both network models. Moreover, the network activity of COBN showed stronger synchronization in the gamma band, and spectral information about the input higher and spread over a broader range of frequencies. These results suggest that the second order statistics of network dynamics depend strongly on the choice of synaptic model. PMID:24634645

Comparison of the dynamics of neural interactions between current-based and conductance-based integrate-and-fire recurrent networks.

PubMed

Cavallari, Stefano; Panzeri, Stefano; Mazzoni, Alberto

2014-01-01

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

Just in time connectivity for large spiking networks

PubMed Central

Lytton, William W.; Omurtag, Ahmet; Neymotin, Samuel A; Hines, Michael L

2008-01-01

The scale of large neuronal network simulations is memory-limited due to the need to store connectivity information: connectivity storage grows as the square of neuron number up to anatomically-relevant limits. Using the NEURON simulator as a discrete-event simulator (no integration), we explored the consequences of avoiding the space costs of connectivity through regenerating connectivity parameters when needed – just-in-time after a presynaptic cell fires. We explored various strategies for automated generation of one or more of the basic static connectivity parameters: delays, postsynaptic cell identities and weights, as well as run-time connectivity state: the event queue. Comparison of the JitCon implementation to NEURON’s standard NetCon connectivity method showed substantial space savings, with associated run-time penalty. Although JitCon saved space by eliminating connectivity parameters, larger simulations were still memory-limited due to growth of the synaptic event queue. We therefore designed a JitEvent algorithm that only added items to the queue when required: instead of alerting multiple postsynaptic cells, a spiking presynaptic cell posted a callback event at the shortest synaptic delay time. At the time of the callback, this same presynaptic cell directly notified the first postsynaptic cell and generated another self-callback for the next delay time. The JitEvent implementation yielded substantial additional time and space savings. We conclude that just-in-time strategies are necessary for very large network simulations but that a variety of alternative strategies should be considered whose optimality will depend on the characteristics of the simulation to be run. PMID:18533821

Cascaded VLSI Chips Help Neural Network To Learn

NASA Technical Reports Server (NTRS)

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

1993-01-01

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

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.

Illuminating the multifaceted roles of neurotransmission in shaping neuronal circuitry.

PubMed

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.

Organization of Functional Long-Range Circuits Controlling the Activity of Serotonergic Neurons in the Dorsal Raphe Nucleus.

PubMed

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.

Sequential estimation of intrinsic activity and synaptic input in single neurons by particle filtering with optimal importance density

NASA Astrophysics Data System (ADS)

Closas, Pau; Guillamon, Antoni

2017-12-01

This paper deals with the problem of inferring the signals and parameters that cause neural activity to occur. The ultimate challenge being to unveil brain's connectivity, here we focus on a microscopic vision of the problem, where single neurons (potentially connected to a network of peers) are at the core of our study. The sole observation available are noisy, sampled voltage traces obtained from intracellular recordings. We design algorithms and inference methods using the tools provided by stochastic filtering that allow a probabilistic interpretation and treatment of the problem. Using particle filtering, we are able to reconstruct traces of voltages and estimate the time course of auxiliary variables. By extending the algorithm, through PMCMC methodology, we are able to estimate hidden physiological parameters as well, like intrinsic conductances or reversal potentials. Last, but not least, the method is applied to estimate synaptic conductances arriving at a target cell, thus reconstructing the synaptic excitatory/inhibitory input traces. Notably, the performance of these estimations achieve the theoretical lower bounds even in spiking regimes.

Round-window delivery of neurotrophin 3 regenerates cochlear synapses after acoustic overexposure.

PubMed

Suzuki, Jun; Corfas, Gabriel; Liberman, M Charles

2016-04-25

In acquired sensorineural hearing loss, such as that produced by noise or aging, there can be massive loss of the synaptic connections between cochlear sensory cells and primary sensory neurons, without loss of the sensory cells themselves. Because the cell bodies and central projections of these cochlear neurons survive for months to years, there is a long therapeutic window in which to re-establish functional connections and improve hearing ability. Here we show in noise-exposed mice that local delivery of neurotrophin-3 (NT-3) to the round window niche, 24 hours after an exposure that causes an immediate loss of up to 50% loss of synapses in the cochlear basal region, can regenerate pre- and post-synaptic elements at the hair cell / cochlear nerve interface. This synaptic regeneration, as documented by confocal microscopy of immunostained cochlear sensory epithelia, was coupled with a corresponding functional recovery, as seen in the suprathreshold amplitude of auditory brainstem response Wave 1. Cochlear delivery of neurotrophins in humans is likely achievable as an office procedure via transtympanic injection, making our results highly significant in a translational context.

Very long transients, irregular firing, and chaotic dynamics in networks of randomly connected inhibitory integrate-and-fire neurons.

PubMed

Zillmer, Rüdiger; Brunel, Nicolas; Hansel, David

2009-03-01

We present results of an extensive numerical study of the dynamics of networks of integrate-and-fire neurons connected randomly through inhibitory interactions. We first consider delayed interactions with infinitely fast rise and decay. Depending on the parameters, the network displays transients which are short or exponentially long in the network size. At the end of these transients, the dynamics settle on a periodic attractor. If the number of connections per neuron is large ( approximately 1000) , this attractor is a cluster state with a short period. In contrast, if the number of connections per neuron is small ( approximately 100) , the attractor has complex dynamics and very long period. During the long transients the neurons fire in a highly irregular manner. They can be viewed as quasistationary states in which, depending on the coupling strength, the pattern of activity is asynchronous or displays population oscillations. In the first case, the average firing rates and the variability of the single-neuron activity are well described by a mean-field theory valid in the thermodynamic limit. Bifurcations of the long transient dynamics from asynchronous to synchronous activity are also well predicted by this theory. The transient dynamics display features reminiscent of stable chaos. In particular, despite being linearly stable, the trajectories of the transient dynamics are destabilized by finite perturbations as small as O(1/N) . We further show that stable chaos is also observed for postsynaptic currents with finite decay time. However, we report in this type of network that chaotic dynamics characterized by positive Lyapunov exponents can also be observed. We show in fact that chaos occurs when the decay time of the synaptic currents is long compared to the synaptic delay, provided that the network is sufficiently large.

Effects of tamoxifen on neuronal morphology, connectivity and biochemistry of hypothalamic ventromedial neurons: Impact on the modulators of sexual behavior.

PubMed

Sá, Susana I; Teixeira, Natércia; Fonseca, Bruno M

2018-01-01

Tamoxifen (TAM) is a selective estrogen receptor modulator, widely used in the treatment and prevention of estrogen-dependent breast cancer. Although with great clinical results, women on TAM therapy still report several side effects, such as sexual dysfunction, which impairs quality of life. The anatomo-functional substrates of the human sexual behavior are still unknown; however, these same substrates are very well characterized in the rodent female sexual behavior, which has advantage of being a very simple reflexive response, dependent on the activation of estrogen receptors (ERs) in the ventrolateral division of the hypothalamic ventromedial nucleus (VMNvl). In fact, in the female rodent, the sexual behavior is triggered by increasing circulation levels of estradiol that changes the nucleus neurochemistry and modulates its intricate neuronal network. Therefore, we considered of notice the examination of the possible neurochemical alterations and the synaptic plasticity impairment in VMNvl neurons of estradiol-primed female rats treated with TAM that may be in the basis of this neurological disorder. Accordingly, we used stereological and biochemical methods to study the action of TAM in axospinous and axodendritic synaptic plasticity and on ER expression. The administration of TAM changed the VMNvl neurochemistry by reducing ERα mRNA and increasing ERβ mRNA expression. Furthermore, present results show that TAM induced neuronal atrophy and reduced synaptic connectivity, favoring electrical inactivity. These data suggest that these cellular and molecular changes may be a possible neuronal mechanism of TAM action in the disruption of the VMNvl network, leading to the development of behavioral disorders. Copyright © 2017 Elsevier Inc. All rights reserved.

Inhibitory Gating of Basolateral Amygdala Inputs to the Prefrontal Cortex

PubMed Central

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.

PubMed

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.

Analysis of nonlocal neural fields for both general and gamma-distributed connectivities

NASA Astrophysics Data System (ADS)

Hutt, Axel; Atay, Fatihcan M.

2005-04-01

This work studies the stability of equilibria in spatially extended neuronal ensembles. We first derive the model equation from statistical properties of the neuron population. The obtained integro-differential equation includes synaptic and space-dependent transmission delay for both general and gamma-distributed synaptic connectivities. The latter connectivity type reveals infinite, finite, and vanishing self-connectivities. The work derives conditions for stationary and nonstationary instabilities for both kernel types. In addition, a nonlinear analysis for general kernels yields the order parameter equation of the Turing instability. To compare the results to findings for partial differential equations (PDEs), two typical PDE-types are derived from the examined model equation, namely the general reaction-diffusion equation and the Swift-Hohenberg equation. Hence, the discussed integro-differential equation generalizes these PDEs. In the case of the gamma-distributed kernels, the stability conditions are formulated in terms of the mean excitatory and inhibitory interaction ranges. As a novel finding, we obtain Turing instabilities in fields with local inhibition-lateral excitation, while wave instabilities occur in fields with local excitation and lateral inhibition. Numerical simulations support the analytical results.

Neurobiomimetic constructs for intelligent unmanned systems and robotics

NASA Astrophysics Data System (ADS)

Braun, Jerome J.; Shah, Danelle C.; DeAngelus, Marianne A.

2014-06-01

This paper discusses a paradigm we refer to as neurobiomimetic, which involves emulations of brain neuroanatomy and neurobiology aspects and processes. Neurobiomimetic constructs include rudimentary and down-scaled computational representations of brain regions, sub-regions, and synaptic connectivity. Many different instances of neurobiomimetic constructs are possible, depending on various aspects such as the initial conditions of synaptic connectivity, number of neuron elements in regions, connectivity specifics, and more, and we refer to these instances as `animats'. While downscaled for computational feasibility, the animats are very large constructs; the animats implemented in this work contain over 47,000 neuron elements and over 720,000 synaptic connections. The paper outlines aspects of the animats implemented, spatial memory and learning cognitive task, the virtual-reality environment constructed to study the animat performing that task, and discussion of results. In a broad sense, we argue that the neurobiomimetic paradigm pursued in this work constitutes a particularly promising path to artificial cognition and intelligent unmanned systems. Biological brains readily cope with challenges of real-life tasks that consistently prove beyond even the most sophisticated algorithmic approaches known. At the cross-over point of neuroscience, cognitive science and computer science, paradigms such as the one pursued in this work aim to mimic the mechanisms of biological brains and as such, we argue, may lead to machines with abilities closer to those of biological species.

Parallel processing of afferent olfactory sensory information

PubMed Central

Vaaga, Christopher E.

2016-01-01

Key points The functional synaptic connectivity between olfactory receptor neurons and principal cells within the olfactory bulb is not well understood.One view suggests that mitral cells, the primary output neuron of the olfactory bulb, are solely activated by feedforward excitation.Using focal, single glomerular stimulation, we demonstrate that mitral cells receive direct, monosynaptic input from olfactory receptor neurons.Compared to external tufted cells, mitral cells have a prolonged afferent‐evoked EPSC, which serves to amplify the synaptic input.The properties of presynaptic glutamate release from olfactory receptor neurons are similar between mitral and external tufted cells.Our data suggest that afferent input enters the olfactory bulb in a parallel fashion. Abstract Primary olfactory receptor neurons terminate in anatomically and functionally discrete cortical modules known as olfactory bulb glomeruli. The synaptic connectivity and postsynaptic responses of mitral and external tufted cells within the glomerulus may involve both direct and indirect components. For example, it has been suggested that sensory input to mitral cells is indirect through feedforward excitation from external tufted cells. We also observed feedforward excitation of mitral cells with weak stimulation of the olfactory nerve layer; however, focal stimulation of an axon bundle entering an individual glomerulus revealed that mitral cells receive monosynaptic afferent inputs. Although external tufted cells had a 4.1‐fold larger peak EPSC amplitude, integration of the evoked currents showed that the synaptic charge was 5‐fold larger in mitral cells, reflecting the prolonged response in mitral cells. Presynaptic afferents onto mitral and external tufted cells had similar quantal amplitude and release probability, suggesting that the larger peak EPSC in external tufted cells was the result of more synaptic contacts. The results of the present study indicate that the monosynaptic afferent input to mitral cells depends on the strength of odorant stimulation. The enhanced spiking that we observed in response to brief afferent input provides a mechanism for amplifying sensory information and contrasts with the transient response in external tufted cells. These parallel input paths may have discrete functions in processing olfactory sensory input. PMID:27377344

Early functional impairment of sensory-motor connectivity in a mouse model of spinal muscular atrophy

PubMed Central

Mentis, George Z.; Blivis, Dvir; Liu, Wenfang; Drobac, Estelle; Crowder, Melissa E.; Kong, Lingling; Alvarez, Francisco J.; Sumner, Charlotte J.; O'Donovan, Michael J.

2011-01-01

SUMMARY To define alterations of neuronal connectivity that occur during motor neuron degeneration, we characterized the function and structure of spinal circuitry in spinal muscular atrophy (SMA) model mice. SMA motor neurons show reduced proprioceptive reflexes that correlate with decreased number and function of synapses on motor neuron somata and proximal dendrites. These abnormalities occur at an early stage of disease in motor neurons innervating proximal hindlimb muscles and medial motor neurons innervating axial muscles, but only at end-stage disease in motor neurons innervating distal hindlimb muscles. Motor neuron loss follows afferent synapse loss with the same temporal and topographical pattern. Trichostatin A, which improves motor behavior and survival of SMA mice, partially restores spinal reflexes illustrating the reversibility of these synaptic defects. De-afferentation of motor neurons is an early event in SMA and may be a primary cause of motor dysfunction that is amenable to therapeutic intervention. PMID:21315257

Self-organization of synchronous activity propagation in neuronal networks driven by local excitation

PubMed Central

Bayati, Mehdi; Valizadeh, Alireza; Abbassian, Abdolhossein; Cheng, Sen

2015-01-01

Many experimental and theoretical studies have suggested that the reliable propagation of synchronous neural activity is crucial for neural information processing. The propagation of synchronous firing activity in so-called synfire chains has been studied extensively in feed-forward networks of spiking neurons. However, it remains unclear how such neural activity could emerge in recurrent neuronal networks through synaptic plasticity. In this study, we investigate whether local excitation, i.e., neurons that fire at a higher frequency than the other, spontaneously active neurons in the network, can shape a network to allow for synchronous activity propagation. We use two-dimensional, locally connected and heterogeneous neuronal networks with spike-timing dependent plasticity (STDP). We find that, in our model, local excitation drives profound network changes within seconds. In the emergent network, neural activity propagates synchronously through the network. This activity originates from the site of the local excitation and propagates through the network. The synchronous activity propagation persists, even when the local excitation is removed, since it derives from the synaptic weight matrix. Importantly, once this connectivity is established it remains stable even in the presence of spontaneous activity. Our results suggest that synfire-chain-like activity can emerge in a relatively simple way in realistic neural networks by locally exciting the desired origin of the neuronal sequence. PMID:26089794

A Novel Form of Compensation in the Tg2576 Amyloid Mouse Model of Alzheimer’s Disease

PubMed Central

Somogyi, Attila; Katonai, Zoltán; Alpár, Alán; Wolf, Ervin

2016-01-01

One century after its first description, pathology of Alzheimer’s disease (AD) is still poorly understood. Amyloid-related dendritic atrophy and membrane alterations of susceptible brain neurons in AD, and in animal models of AD are widely recognized. However, little effort has been made to study the potential effects of combined morphological and membrane alterations on signal transfer and synaptic integration in neurons that build up affected neural networks in AD. In this study spatial reconstructions and electrophysiological measurements of layer II/III pyramidal neurons of the somatosensory cortex from wild-type (WT) and transgenic (TG) human amyloid precursor protein (hAPP) overexpressing Tg2576 mice were used to build faithful segmental cable models of these neurons. Local synaptic activities were simulated in various points of the dendritic arbors and properties of subthreshold dendritic impulse propagation and predictors of synaptic input pattern recognition ability were quantified and compared in modeled WT and TG neurons. Despite the widespread dendritic degeneration and membrane alterations in mutant mouse neurons, surprisingly little, or no change was detected in steady-state and 50 Hz sinusoidal voltage transfers, current transfers, and local and propagation delays of PSPs traveling along dendrites of TG neurons. Synaptic input pattern recognition ability was also predicted to be unaltered in TG neurons in two different soma-dendritic membrane models investigated. Our simulations predict the way how subthreshold dendritic signaling and pattern recognition are preserved in TG neurons: amyloid-related membrane alterations compensate for the pathological effects that dendritic atrophy has on subthreshold dendritic signal transfer and integration in layer II/III somatosensory neurons of this hAPP mouse model for AD. Since neither propagation of single PSPs nor integration of multiple PSPs (pattern recognition) changes in TG neurons, we conclude that AD-related neuronal hyperexcitability cannot be accounted for by altered subthreshold dendritic signaling in these neurons but hyperexcitability is related to changes in active membrane properties and network connectivity. PMID:27378850

A Novel Form of Compensation in the Tg2576 Amyloid Mouse Model of Alzheimer's Disease.

PubMed

Somogyi, Attila; Katonai, Zoltán; Alpár, Alán; Wolf, Ervin

2016-01-01

One century after its first description, pathology of Alzheimer's disease (AD) is still poorly understood. Amyloid-related dendritic atrophy and membrane alterations of susceptible brain neurons in AD, and in animal models of AD are widely recognized. However, little effort has been made to study the potential effects of combined morphological and membrane alterations on signal transfer and synaptic integration in neurons that build up affected neural networks in AD. In this study spatial reconstructions and electrophysiological measurements of layer II/III pyramidal neurons of the somatosensory cortex from wild-type (WT) and transgenic (TG) human amyloid precursor protein (hAPP) overexpressing Tg2576 mice were used to build faithful segmental cable models of these neurons. Local synaptic activities were simulated in various points of the dendritic arbors and properties of subthreshold dendritic impulse propagation and predictors of synaptic input pattern recognition ability were quantified and compared in modeled WT and TG neurons. Despite the widespread dendritic degeneration and membrane alterations in mutant mouse neurons, surprisingly little, or no change was detected in steady-state and 50 Hz sinusoidal voltage transfers, current transfers, and local and propagation delays of PSPs traveling along dendrites of TG neurons. Synaptic input pattern recognition ability was also predicted to be unaltered in TG neurons in two different soma-dendritic membrane models investigated. Our simulations predict the way how subthreshold dendritic signaling and pattern recognition are preserved in TG neurons: amyloid-related membrane alterations compensate for the pathological effects that dendritic atrophy has on subthreshold dendritic signal transfer and integration in layer II/III somatosensory neurons of this hAPP mouse model for AD. Since neither propagation of single PSPs nor integration of multiple PSPs (pattern recognition) changes in TG neurons, we conclude that AD-related neuronal hyperexcitability cannot be accounted for by altered subthreshold dendritic signaling in these neurons but hyperexcitability is related to changes in active membrane properties and network connectivity.

Sonic hedgehog expression in corticofugal projection neurons directs cortical microcircuit formation.

PubMed

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.

Cytoarchitectonic and quantitative Golgi study of the hedgehog supraoptic nucleus.

PubMed Central

Caminero, A A; Machín, C; Sanchez-Toscano, F

1992-01-01

A cytoarchitectural study was made of the supraoptic nucleus (SON) of the hedgehog with special attention to the quantitative comparison of its main neuronal types. The main purposes were (1) to relate the characteristics of this nucleus in the hedgehog (a primitive mammalian insectivorous brain) with those in the SONs of more evolutionarily advanced species; (2) to identify quantitatively the dendritic fields of the main neuronal types in the hedgehog SON and to study their synaptic connectivity. From a descriptive standpoint, 3 neuronal types were found with respect to the number of dendritic stems arising from the neuronal soma: bipolar neurons (48%), multipolar neurons (45.5%) and monopolar neurons (6.5%). Within the multipolar type 2 subtypes could be distinguished, taking into account the number of dendritic spines: (a) with few spines (93%) and (b) very spiny (7%). These results indicate that the hedgehog SON is similar to that in other species except for the very spiny neurons, the significance of which is discussed. In order to characterise the main types more satisfactorily (bipolar and multipolars with few spines) we undertook a quantitative Golgi study of their dendritic fields. Although the patterns of the dendritic field are similar in both neuronal types, the differences in the location of their connectivity can reflect functional changes and alterations in relation to the synaptic afferences. Images Fig. 2 Fig. 3 Fig. 5 Fig. 6 Fig. 7 Fig. 8 Fig. 9 PMID:1452481

Sensory Optimization by Stochastic Tuning

PubMed Central

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

Synaptic Plasticity and Spike Synchronisation in Neuronal Networks

NASA Astrophysics Data System (ADS)

Borges, Rafael R.; Borges, Fernando S.; Lameu, Ewandson L.; Protachevicz, Paulo R.; Iarosz, Kelly C.; Caldas, Iberê L.; Viana, Ricardo L.; Macau, Elbert E. N.; Baptista, Murilo S.; Grebogi, Celso; Batista, Antonio M.

2017-12-01

Brain plasticity, also known as neuroplasticity, is a fundamental mechanism of neuronal adaptation in response to changes in the environment or due to brain injury. In this review, we show our results about the effects of synaptic plasticity on neuronal networks composed by Hodgkin-Huxley neurons. We show that the final topology of the evolved network depends crucially on the ratio between the strengths of the inhibitory and excitatory synapses. Excitation of the same order of inhibition revels an evolved network that presents the rich-club phenomenon, well known to exist in the brain. For initial networks with considerably larger inhibitory strengths, we observe the emergence of a complex evolved topology, where neurons sparsely connected to other neurons, also a typical topology of the brain. The presence of noise enhances the strength of both types of synapses, but if the initial network has synapses of both natures with similar strengths. Finally, we show how the synchronous behaviour of the evolved network will reflect its evolved topology.

Simultaneous stability and sensitivity in model cortical networks is achieved through anti-correlations between the in- and out-degree of connectivity

PubMed Central

Vasquez, Juan C.; Houweling, Arthur R.; Tiesinga, Paul

2013-01-01

Neuronal networks in rodent barrel cortex are characterized by stable low baseline firing rates. However, they are sensitive to the action potentials of single neurons as suggested by recent single-cell stimulation experiments that reported quantifiable behavioral responses in response to short spike trains elicited in single neurons. Hence, these networks are stable against internally generated fluctuations in firing rate but at the same time remain sensitive to similarly-sized externally induced perturbations. We investigated stability and sensitivity in a simple recurrent network of stochastic binary neurons and determined numerically the effects of correlation between the number of afferent (“in-degree”) and efferent (“out-degree”) connections in neurons. The key advance reported in this work is that anti-correlation between in-/out-degree distributions increased the stability of the network in comparison to networks with no correlation or positive correlations, while being able to achieve the same level of sensitivity. The experimental characterization of degree distributions is difficult because all pre-synaptic and post-synaptic neurons have to be identified and counted. We explored whether the statistics of network motifs, which requires the characterization of connections between small subsets of neurons, could be used to detect evidence for degree anti-correlations. We find that the sample frequency of the 3-neuron “ring” motif (1→2→3→1), can be used to detect degree anti-correlation for sub-networks of size 30 using about 50 samples, which is of significance because the necessary measurements are achievable experimentally in the near future. Taken together, we hypothesize that barrel cortex networks exhibit degree anti-correlations and specific network motif statistics. PMID:24223550

Synaptic activation patterns of the perirhinal-entorhinal inter-connections.

PubMed

de Villers-Sidani, E; Tahvildari, B; Alonso, A

2004-01-01

Ample neuropsychological evidence supports the role of rhinal cortices in memory. The perirhinal cortex (PRC) represents one of the main conduits for the bi-directional flow of information between the entorhinal-hippocampal network and the cortical mantle, a process essential in memory formation. However, despite anatomical evidence for a robust reciprocal connectivity between the perirhinal and entorhinal cortices, neurophysiological understanding of this circuitry is lacking. We now present the results of a series of electrophysiological experiments in rats that demonstrate robust synaptic activation patterns of the perirhinal-entorhinal inter-connections. First, using silicon multi-electrode arrays placed under visual guidance in vivo we performed current source density (CSD) analysis of lateral entorhinal cortex (LEC) responses to PRC stimulation, which demonstrated a current sink in layers II-III of the LEC with a latency consistent with monosynaptic activation. To further substantiate and extend this conclusion, we developed a PRC-LEC slice preparation where CSD analysis also revealed a current sink in superficial LEC layers in response to PRC stimulation. Importantly, intracellular recording of superficial LEC layer neurons confirmed that they receive a major monosynaptic excitatory input from the PRC. Finally, CSD analysis of the LEC to PRC projection in vivo also allowed us to document robust feedback synaptic activation of PRC neurons to deep LEC layer activation. We conclude that a clear bidirectional pattern of synaptic interactions exists between the PRC and LEC that would support a dynamic flow of information subserving memory function in the temporal lobe.

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.

Resting-state activity in development and maintenance of normal brain function.

PubMed

Pizoli, Carolyn E; Shah, Manish N; Snyder, Abraham Z; Shimony, Joshua S; Limbrick, David D; Raichle, Marcus E; Schlaggar, Bradley L; Smyth, Matthew D

2011-07-12

One of the most intriguing recent discoveries concerning brain function is that intrinsic neuronal activity manifests as spontaneous fluctuations of the blood oxygen level-dependent (BOLD) functional MRI signal. These BOLD fluctuations exhibit temporal synchrony within widely distributed brain regions known as resting-state networks. Resting-state networks are present in the waking state, during sleep, and under general anesthesia, suggesting that spontaneous neuronal activity plays a fundamental role in brain function. Despite its ubiquitous presence, the physiological role of correlated, spontaneous neuronal activity remains poorly understood. One hypothesis is that this activity is critical for the development of synaptic connections and maintenance of synaptic homeostasis. We had a unique opportunity to test this hypothesis in a 5-y-old boy with severe epileptic encephalopathy. The child developed marked neurologic dysfunction in association with a seizure disorder, resulting in a 1-y period of behavioral regression and progressive loss of developmental milestones. His EEG showed a markedly abnormal pattern of high-amplitude, disorganized slow activity with frequent generalized and multifocal epileptiform discharges. Resting-state functional connectivity MRI showed reduced BOLD fluctuations and a pervasive lack of normal connectivity. The child underwent successful corpus callosotomy surgery for treatment of drop seizures. Postoperatively, the patient's behavior returned to baseline, and he resumed development of new skills. The waking EEG revealed a normal background, and functional connectivity MRI demonstrated restoration of functional connectivity architecture. These results provide evidence that intrinsic, coherent neuronal signaling may be essential to the development and maintenance of the brain's functional organization.

Repeated pulses of serotonin required for long-term facilitation activate mitogen-activated protein kinase in sensory neurons of Aplysia

PubMed Central

Michael, Dan; Martin, Kelsey C.; Seger, Rony; Ning, Ming-Ming; Baston, Rene; Kandel, Eric R.

1998-01-01

Long-term facilitation of the connections between the sensory and motor neurons of the gill-withdrawal reflex in Aplysia requires five repeated pulses of serotonin (5-HT). The repeated pulses of 5-HT initiate a cascade of gene activation that leads ultimately to the growth of new synaptic connections. Several genes in this process have been identified, including the transcriptional regulators apCREB-1, apCREB-2, apC/EBP, and the cell adhesion molecule apCAM, which is thought to be involved in the formation of new synaptic connections. Here we report that the transcriptional regulators apCREB-2 and apC/EBP, as well as a peptide derived from the cytoplasmic domain of apCAM, are phosphorylated in vitro by Aplysia mitogen-activated protein kinase (apMAPK). We have cloned the cDNA encoding apMAPK and show that apMAPK activity is increased in sensory neurons treated with repeated pulses of 5-HT and by the cAMP pathway. These results suggest that apMAPK may participate with cAMP-dependent protein kinase during long-term facilitation in sensory cells by modifying some of the key elements involved in the consolidation of short- to long-lasting changes in synaptic strength. PMID:9465108

Fornix lesions decouple the induction of hippocampal arc transcription from behavior but not plasticity.

PubMed

Fletcher, Bonnie R; Calhoun, Michael E; Rapp, Peter R; Shapiro, Matthew L

2006-02-01

The immediate-early gene (IEG) Arc is transcribed after behavioral and physiological treatments that induce synaptic plasticity and is implicated in memory consolidation. The relative contributions of neuronal activity and learning-related plasticity to the behavioral induction of Arc remain to be defined. To differentiate the contributions of each, we assessed the induction of Arc transcription in rats with fornix lesions that impair hippocampal learning yet leave cortical connectivity and neuronal firing essentially intact. Arc expression was assessed after exploration of novel environments and performance of a novel water maze task during which normal rats learned the spatial location of an escape platform. During the same task, rats with fornix lesions learned to approach a visible platform but did not learn its spatial location. Rats with fornix lesions had normal baseline levels of hippocampal Arc mRNA, but unlike normal rats, expression was not increased in response to water maze training. The integrity of signaling pathways controlling Arc expression was demonstrated by stimulation of the medial perforant path, which induced normal synaptic potentiation and Arc in rats with fornix lesions. Together, the results demonstrate that Arc induction can be decoupled from behavior and is more likely to indicate the engagement of synaptic plasticity mechanisms than synaptic or neuronal activity per se. The results further imply that fornix lesions may impair memory in part by decoupling neuronal activity from signaling pathways required for long-lasting hippocampal synaptic plasticity.

Synaptic Correlates of Low-Level Perception in V1.

PubMed

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

2016-04-06

The computational role of primary visual cortex (V1) in low-level perception remains largely debated. A dominant view assumes the prevalence of higher cortical areas and top-down processes in binding information across the visual field. Here, we investigated the role of long-distance intracortical connections in form and motion processing by measuring, with intracellular recordings, their synaptic impact on neurons in area 17 (V1) of the anesthetized cat. By systematically mapping synaptic responses to stimuli presented in the nonspiking surround of V1 receptive fields, we provide the first quantitative characterization of the lateral functional connectivity kernel of V1 neurons. Our results revealed at the population level two structural-functional biases in the synaptic integration and dynamic association properties of V1 neurons. First, subthreshold responses to oriented stimuli flashed in isolation in the nonspiking surround exhibited a geometric organization around the preferred orientation axis mirroring the psychophysical "association field" for collinear contour perception. Second, apparent motion stimuli, for which horizontal and feedforward synaptic inputs summed in-phase, evoked dominantly facilitatory nonlinear interactions, specifically during centripetal collinear activation along the preferred orientation axis, at saccadic-like speeds. This spatiotemporal integration property, which could constitute the neural correlate of a human perceptual bias in speed detection, suggests that local (orientation) and global (motion) information is already linked within V1. We propose the existence of a "dynamic association field" in V1 neurons, whose spatial extent and anisotropy are transiently updated and reshaped as a function of changes in the retinal flow statistics imposed during natural oculomotor exploration. The computational role of primary visual cortex in low-level perception remains debated. The expression of this "pop-out" perception is often assumed to require attention-related processes, such as top-down feedback from higher cortical areas. Using intracellular techniques in the anesthetized cat and novel analysis methods, we reveal unexpected structural-functional biases in the synaptic integration and dynamic association properties of V1 neurons. These structural-functional biases provide a substrate, within V1, for contour detection and, more unexpectedly, global motion flow sensitivity at saccadic speed, even in the absence of attentional processes. We argue for the concept of a "dynamic association field" in V1 neurons, whose spatial extent and anisotropy changes with retinal flow statistics, and more generally for a renewed focus on intracortical computation. Copyright © 2016 the authors 0270-6474/16/363925-18$15.00/0.

Continuous and lurching traveling pulses in neuronal networks with delay and spatially decaying connectivity

PubMed Central

Golomb, David; Ermentrout, G. Bard

1999-01-01

Propagation of discharges in cortical and thalamic systems, which is used as a probe for examining network circuitry, is studied by constructing a one-dimensional model of integrate-and-fire neurons that are coupled by excitatory synapses with delay. Each neuron fires only one spike. The velocity and stability of propagating continuous pulses are calculated analytically. Above a certain critical value of the constant delay, these pulses lose stability. Instead, lurching pulses propagate with discontinuous and periodic spatio-temporal characteristics. The parameter regime for which lurching occurs is strongly affected by the footprint (connectivity) shape; bistability may occur with a square footprint shape but not with an exponential footprint shape. For strong synaptic coupling, the velocity of both continuous and lurching pulses increases logarithmically with the synaptic coupling strength gsyn for an exponential footprint shape, and it is bounded for a step footprint shape. We conclude that the differences in velocity and shape between the front of thalamic spindle waves in vitro and cortical paroxysmal discharges stem from their different effective delay; in thalamic networks, large effective delay between inhibitory neurons arises from their effective interaction via the excitatory cells which display postinhibitory rebound. PMID:10557346

Black Holes as Brains: Neural Networks with Area Law Entropy

NASA Astrophysics Data System (ADS)

Dvali, Gia

2018-04-01

Motivated by the potential similarities between the underlying mechanisms of the enhanced memory storage capacity in black holes and in brain networks, we construct an artificial quantum neural network based on gravity-like synaptic connections and a symmetry structure that allows to describe the network in terms of geometry of a d-dimensional space. We show that the network possesses a critical state in which the gapless neurons emerge that appear to inhabit a (d-1)-dimensional surface, with their number given by the surface area. In the excitations of these neurons, the network can store and retrieve an exponentially large number of patterns within an arbitrarily narrow energy gap. The corresponding micro-state entropy of the brain network exhibits an area law. The neural network can be described in terms of a quantum field, via identifying the different neurons with the different momentum modes of the field, while identifying the synaptic connections among the neurons with the interactions among the corresponding momentum modes. Such a mapping allows to attribute a well-defined sense of geometry to an intrinsically non-local system, such as the neural network, and vice versa, it allows to represent the quantum field model as a neural network.

Super Resolution Imaging of Genetically Labeled Synapses in Drosophila Brain Tissue

PubMed Central

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.

PubMed

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.

Synaptic Plasticity in Cardiac Innervation and Its Potential Role in Atrial Fibrillation

PubMed Central

Ashton, Jesse L.; Burton, Rebecca A. B.; Bub, Gil; Smaill, Bruce H.; Montgomery, Johanna M.

2018-01-01

Synaptic plasticity is defined as the ability of synapses to change their strength of transmission. Plasticity of synaptic connections in the brain is a major focus of neuroscience research, as it is the primary mechanism underpinning learning and memory. Beyond the brain however, plasticity in peripheral neurons is less well understood, particularly in the neurons innervating the heart. The atria receive rich innervation from the autonomic branch of the peripheral nervous system. Sympathetic neurons are clustered in stellate and cervical ganglia alongside the spinal cord and extend fibers to the heart directly innervating the myocardium. These neurons are major drivers of hyperactive sympathetic activity observed in heart disease, ventricular arrhythmias, and sudden cardiac death. Both pre- and postsynaptic changes have been observed to occur at synapses formed by sympathetic ganglion neurons, suggesting that plasticity at sympathetic neuro-cardiac synapses is a major contributor to arrhythmias. Less is known about the plasticity in parasympathetic neurons located in clusters on the heart surface. These neuronal clusters, termed ganglionated plexi, or “little brains,” can independently modulate neural control of the heart and stimulation that enhances their excitability can induce arrhythmia such as atrial fibrillation. The ability of these neurons to alter parasympathetic activity suggests that plasticity may indeed occur at the synapses formed on and by ganglionated plexi neurons. Such changes may not only fine-tune autonomic innervation of the heart, but could also be a source of maladaptive plasticity during atrial fibrillation. PMID:29615932

Differential expression of neuroligin genes in the nervous system of zebrafish.

PubMed

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.

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

PubMed Central

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

2015-01-01

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

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

PubMed Central

Whittington, James C. R.; Bogacz, Rafal

2017-01-01

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

PSD-95 promotes the stabilization of young synaptic contacts.

PubMed

Taft, Christine E; Turrigiano, Gina G

2014-01-05

Maintaining a population of stable synaptic connections is probably of critical importance for the preservation of memories and functional circuitry, but the molecular dynamics that underlie synapse stabilization is poorly understood. Here, we use simultaneous time-lapse imaging of post synaptic density-95 (PSD-95) and Ca(2+)/calmodulin-dependent protein kinase II (CaMKII) to investigate the dynamics of protein composition at axodendritic (AD) contacts. Our data reveal that this composition is highly dynamic, with both proteins moving into and out of the same synapse independently, so that synapses cycle rapidly between states in which they are enriched for none, one or both proteins. We assessed how PSD-95 and CaMKII interact at stable and transient AD sites and found that both phospho-CaMKII and PSD-95 are present more often at stable than labile contacts. Finally, we found that synaptic contacts are more stable in older neurons, and this process can be mimicked in younger neurons by overexpression of PSD-95. Taken together, these data show that synaptic protein composition is highly variable over a time-scale of hours, and that PSD-95 is probably a key synaptic protein that promotes synapse stability.

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

PubMed

Whittington, James C R; Bogacz, Rafal

2017-05-01

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

Excitatory neuronal connectivity in the barrel cortex

PubMed Central

Feldmeyer, Dirk

2012-01-01

Neocortical areas are believed to be organized into vertical modules, the cortical columns, and the horizontal layers 1–6. In the somatosensory barrel cortex these columns are defined by the readily discernible barrel structure in layer 4. Information processing in the neocortex occurs along vertical and horizontal axes, thereby linking individual barrel-related columns via axons running through the different cortical layers of the barrel cortex. Long-range signaling occurs within the neocortical layers but also through axons projecting through the white matter to other neocortical areas and subcortical brain regions. Because of the ease of identification of barrel-related columns, the rodent barrel cortex has become a prototypical system to study the interactions between different neuronal connections within a sensory cortical area and between this area and other cortical as well subcortical regions. Such interactions will be discussed specifically for the feed-forward and feedback loops between the somatosensory and the somatomotor cortices as well as the different thalamic nuclei. In addition, recent advances concerning the morphological characteristics of excitatory neurons and their impact on the synaptic connectivity patterns and signaling properties of neuronal microcircuits in the whisker-related somatosensory cortex will be reviewed. In this context, their relationship between the structural properties of barrel-related columns and their function as a module in vertical synaptic signaling in the whisker-related cortical areas will be discussed. PMID:22798946

Microfluidic local perfusion chambers for the visualization and manipulation of synapses

PubMed Central

Taylor, Anne M.; Dieterich, Daniela C.; Ito, Hiroshi T.; Kim, Sally A.; Schuman, Erin M.

2010-01-01

Summary The polarized nature of neurons as well as the size and density of synapses complicates the manipulation and visualization of cell biological processes that control synaptic function. Here we developed a microfluidic local perfusion (μLP) chamber to access and manipulate synaptic regions and pre- and post-synaptic compartments in vitro. This chamber directs the formation of synapses in >100 parallel rows connecting separate neuron populations. A perfusion channel transects the parallel rows allowing access to synaptic regions with high spatial and temporal resolution. We used this chamber to investigate synapse-to-nucleus signaling. Using the calcium indicator dye, Fluo-4, we measured changes in calcium at dendrites and somata, following local perfusion of glutamate. Exploiting the high temporal resolution of the chamber, we exposed synapses to “spaced” or “massed” application of glutamate and then examined levels of pCREB in somata. Lastly, we applied the metabotropic receptor agonist, DHPG, to dendrites and observed increases in Arc transcription and Arc transcript localization. PMID:20399729

Long term potentiation, but not depression, in interlamellar hippocampus CA1.

PubMed

Sun, Duk-Gyu; Kang, Hyeri; Tetteh, Hannah; Su, Junfeng; Lee, Jihwan; Park, Sung-Won; He, Jufang; Jo, Jihoon; Yang, Sungchil; Yang, Sunggu

2018-03-26

Synaptic plasticity in the lamellar CA3 to CA1 circuitry has been extensively studied while interlamellar CA1 to CA1 connections have not yet received much attention. One of our earlier studies demonstrated that axons of CA1 pyramidal neurons project to neighboring CA1 neurons, implicating information transfer along a longitudinal interlamellar network. Still, it remains unclear whether long-term synaptic plasticity is present within this longitudinal CA1 network. Here, we investigate long-term synaptic plasticity between CA1 pyramidal cells, using in vitro and in vivo extracellular recordings and 3D holography glutamate uncaging. We found that the CA1-CA1 network exhibits NMDA receptor-dependent long-term potentiation (LTP) without direction or layer selectivity. By contrast, we find no significant long-term depression (LTD) under various LTD induction protocols. These results implicate unique synaptic properties in the longitudinal projection suggesting that the interlamellar CA1 network could be a promising structure for hippocampus-related information processing and brain diseases.

Balance within the Neurexin Trans-Synaptic Connexus Stabilizes Behavioral Control

PubMed Central

Clarke, Raymond A.; Eapen, Valsamma

2014-01-01

Autism spectrum disorder (ASD) is characterized by a broad spectrum of behavioral deficits of unknown etiology. ASD associated mutations implicate numerous neurological pathways including a common association with the neurexin trans-synaptic connexus (NTSC) which regulates neuronal cell-adhesion, neuronal circuitry, and neurotransmission. Comparable DNA lesions affecting the NTSC, however, associate with a diversity of behavioral deficits within and without the autism spectrum including a very strong association with Tourette syndrome. The NTSC is comprised of numerous post-synaptic ligands competing for trans-synaptic connection with one of the many different neurexin receptors yet no apparent association exists between specific NTSC molecules/complexes and specific behavioral deficits. Together these findings indicate a fundamental role for NTSC-balance in stabilizing pre-behavioral control. Further molecular and clinical characterization and stratification of ASD and TS on the basis of NTSC status will help elucidate the molecular basis of behavior – and define how the NTSC functions in combination with other molecular determinates to strengthen behavioral control and specify behavioral deficits. PMID:24578685

Integrative Mechanisms of Oriented Neuronal Migration in the Developing Brain

PubMed Central

Evsyukova, Irina; Plestant, Charlotte; Anton, E.S.

2014-01-01

The emergence of functional neuronal connectivity in the developing cerebral cortex depends on neuronal migration. This process enables appropriate positioning of neurons and the emergence of neuronal identity so that the correct patterns of functional synaptic connectivity between the right types and numbers of neurons can emerge. Delineating the complexities of neuronal migration is critical to our understanding of normal cerebral cortical formation and neurodevelopmental disorders resulting from neuronal migration defects. For the most part, the integrated cell biological basis of the complex behavior of oriented neuronal migration within the developing mammalian cerebral cortex remains an enigma. This review aims to analyze the integrative mechanisms that enable neurons to sense environmental guidance cues and translate them into oriented patterns of migration toward defined areas of the cerebral cortex. We discuss how signals emanating from different domains of neurons get integrated to control distinct aspects of migratory behavior and how different types of cortical neurons coordinate their migratory activities within the developing cerebral cortex to produce functionally critical laminar organization. PMID:23937349

Peripheral oxygen-sensing cells directly modulate the output of an identified respiratory central pattern generating neuron.

PubMed

Bell, Harold J; Inoue, Takuya; Shum, Kelly; Luk, Collin; Syed, Naweed I

2007-06-01

Breathing is an essential homeostatic behavior regulated by central neuronal networks, often called central pattern generators (CPGs). Despite ongoing advances in our understanding of the neural control of breathing, the basic mechanisms by which peripheral input modulates the activities of the central respiratory CPG remain elusive. This lack of fundamental knowledge vis-à-vis the role of peripheral influences in the control of the respiratory CPG is due in large part to the complexity of mammalian respiratory control centres. We have therefore developed a simpler invertebrate model to study the basic cellular and synaptic mechanisms by which a peripheral chemosensory input affects the central respiratory CPG. Here we report on the identification and characterization of peripheral chemoreceptor cells (PCRCs) that relay hypoxia-sensitive chemosensory information to the known respiratory CPG neuron right pedal dorsal 1 in the mollusk Lymnaea stagnalis. Selective perfusion of these PCRCs with hypoxic saline triggered bursting activity in these neurons and when isolated in cell culture these cells also demonstrated hypoxic sensitivity that resulted in membrane depolarization and spiking activity. When cocultured with right pedal dorsal 1, the PCRCs developed synapses that exhibited a form of short-term synaptic plasticity in response to hypoxia. Finally, osphradial denervation in intact animals significantly perturbed respiratory activity compared with their sham counterparts. This study provides evidence for direct synaptic connectivity between a peripheral regulatory element and a central respiratory CPG neuron, revealing a potential locus for hypoxia-induced synaptic plasticity underlying breathing behavior.

Successful Reconstruction of a Physiological Circuit with Known Connectivity from Spiking Activity Alone

PubMed Central

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

In vivo imaging of neural reactive plasticity after laser axotomy in cerebellar cortex

NASA Astrophysics Data System (ADS)

Allegra Mascaro, A. L.; Sacconi, L.; Maco, B.; Knott, G. W.; Pavone, F. S.

2014-03-01

Multi-photon imaging provides valuable insights into the continuous reshaping of neuronal connectivity in live brain. We previously showed that single neuron or even single spine ablation can be achieved by laser-mediated dissection. Furthermore, single axonal branches can be dissected avoiding collateral damage to the adjacent dendrite and the formation of a persistent glial scar. Here, we describe the procedure to address the structural plasticity of cerebellar climbing fibers by combining two-photon in vivo imaging with laser axotomy in a mouse model. This method is a powerful tool to study the basic mechanisms of axonal rewiring after single branch axotomy in vivo. In fact, despite the denervated area being very small, the injured axons consistently reshape the connectivity with surrounding neurons, as indicated by the increase in the turnover of synaptic boutons. In addition, time-lapse imaging reveals the sprouting of new branches from the injured axon. Newly formed branches with varicosities suggest the possible formation of synaptic contacts. Correlative light and electron microscopy revealed that the sprouted branch contains large numbers of vesicles, with varicosities in the close vicinity of Purkinje dendrites.

Cell Type–Specific Three-Dimensional Structure of Thalamocortical Circuits in a Column of Rat Vibrissal Cortex

PubMed Central

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

A chimeric path to neuronal synchronization

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

Essaki Arumugam, Easwara Moorthy; Spano, Mark L.

2015-01-15

Synchronization of neuronal activity is associated with neurological disorders such as epilepsy. This process of neuronal synchronization is not fully understood. To further our understanding, we have experimentally studied the progression of this synchronization from normal neuronal firing to full synchronization. We implemented nine FitzHugh-Nagumo neurons (a simplified Hodgkin-Huxley model) via discrete electronics. For different coupling parameters (synaptic strengths), the neurons in the ring were either unsynchronized or completely synchronized when locally coupled in a ring. When a single long-range connection (nonlocal coupling) was introduced, an intermediate state known as a chimera appeared. The results indicate that (1) epilepsy ismore » likely not only a dynamical disease but also a topological disease, strongly tied to the connectivity of the underlying network of neurons, and (2) the synchronization process in epilepsy may not be an “all or none” phenomenon, but can pass through an intermediate stage (chimera)« less

A chimeric path to neuronal synchronization

NASA Astrophysics Data System (ADS)

Essaki Arumugam, Easwara Moorthy; Spano, Mark L.

2015-01-01

Synchronization of neuronal activity is associated with neurological disorders such as epilepsy. This process of neuronal synchronization is not fully understood. To further our understanding, we have experimentally studied the progression of this synchronization from normal neuronal firing to full synchronization. We implemented nine FitzHugh-Nagumo neurons (a simplified Hodgkin-Huxley model) via discrete electronics. For different coupling parameters (synaptic strengths), the neurons in the ring were either unsynchronized or completely synchronized when locally coupled in a ring. When a single long-range connection (nonlocal coupling) was introduced, an intermediate state known as a chimera appeared. The results indicate that (1) epilepsy is likely not only a dynamical disease but also a topological disease, strongly tied to the connectivity of the underlying network of neurons, and (2) the synchronization process in epilepsy may not be an "all or none" phenomenon, but can pass through an intermediate stage (chimera).

The intellectual disability gene Kirrel3 regulates target-specific mossy fiber synapse development in the hippocampus.

PubMed

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.

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

PubMed Central

Srinivasa, Narayan; Cho, Youngkwan

2014-01-01

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

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

PubMed

Srinivasa, Narayan; Cho, Youngkwan

2014-01-01

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

Dopamine loss alters the hippocampus-nucleus accumbens synaptic transmission in the Tg2576 mouse model of Alzheimer's disease.

PubMed

Cordella, Alberto; Krashia, Paraskevi; Nobili, Annalisa; Pignataro, Annabella; La Barbera, Livia; Viscomi, Maria Teresa; Valzania, Alessandro; Keller, Flavio; Ammassari-Teule, Martine; Mercuri, Nicola Biagio; Berretta, Nicola; D'Amelio, Marcello

2018-08-01

The functional loop involving the ventral tegmental area (VTA), dorsal hippocampus and nucleus accumbens (NAc) plays a pivotal role in the formation of spatial memory and persistent memory traces. In particular, the dopaminergic innervation from the VTA to the hippocampus is critical for hippocampal-related memory function and alterations in the midbrain dopaminergic system are frequently reported in Alzheimer's disease (AD), contributing to age-related decline in memory and non-cognitive functions. However, much less is known about the hippocampus-NAc connectivity in AD. Here, we evaluated the functioning of the hippocampus-to-NAc core connectivity in the Tg2576 mouse model of AD that shows a selective and progressive degeneration of VTA dopaminergic neurons. We show that reduced dopaminergic innervation in the Tg2576 hippocampus results in reduced synaptic plasticity and excitability of dorsal subiculum pyramidal neurons. Importantly, the glutamatergic transmission from the hippocampus to the NAc core is also impaired. Chemogenetic depolarisation of Tg2576 subicular pyramidal neurons with an excitatory Designer Receptor Exclusively Activated by Designer Drugs, or systemic administration of the DA precursor levodopa, can both rescue the deficits in Tg2576 mice. Our data suggest that the dopaminergic signalling in the hippocampus is essential for the proper functioning of the hippocampus-NAc excitatory synaptic transmission. Copyright © 2018 Elsevier Inc. All rights reserved.

Predicting the synaptic information efficacy in cortical layer 5 pyramidal neurons using a minimal integrate-and-fire model.

PubMed

London, Michael; Larkum, Matthew E; Häusser, Michael

2008-11-01

Synaptic information efficacy (SIE) is a statistical measure to quantify the efficacy of a synapse. It measures how much information is gained, on the average, about the output spike train of a postsynaptic neuron if the input spike train is known. It is a particularly appropriate measure for assessing the input-output relationship of neurons receiving dynamic stimuli. Here, we compare the SIE of simulated synaptic inputs measured experimentally in layer 5 cortical pyramidal neurons in vitro with the SIE computed from a minimal model constructed to fit the recorded data. We show that even with a simple model that is far from perfect in predicting the precise timing of the output spikes of the real neuron, the SIE can still be accurately predicted. This arises from the ability of the model to predict output spikes influenced by the input more accurately than those driven by the background current. This indicates that in this context, some spikes may be more important than others. Lastly we demonstrate another aspect where using mutual information could be beneficial in evaluating the quality of a model, by measuring the mutual information between the model's output and the neuron's output. The SIE, thus, could be a useful tool for assessing the quality of models of single neurons in preserving input-output relationship, a property that becomes crucial when we start connecting these reduced models to construct complex realistic neuronal networks.

An Algorithm for Finding Candidate Synaptic Sites in Computer Generated Networks of Neurons with Realistic Morphologies

PubMed Central

van Pelt, Jaap; Carnell, Andrew; de Ridder, Sander; Mansvelder, Huibert D.; van Ooyen, Arjen

2010-01-01

Neurons make synaptic connections at locations where axons and dendrites are sufficiently close in space. Typically the required proximity is based on the dimensions of dendritic spines and axonal boutons. Based on this principle one can search those locations in networks formed by reconstructed neurons or computer generated neurons. Candidate synapses are then located where axons and dendrites are within a given criterion distance from each other. Both experimentally reconstructed and model generated neurons are usually represented morphologically by piecewise-linear structures (line pieces or cylinders). Proximity tests are then performed on all pairs of line pieces from both axonal and dendritic branches. Applying just a test on the distance between line pieces may result in local clusters of synaptic sites when more than one pair of nearby line pieces from axonal and dendritic branches is sufficient close, and may introduce a dependency on the length scale of the individual line pieces. The present paper describes a new algorithm for defining locations of candidate synapses which is based on the crossing requirement of a line piece pair, while the length of the orthogonal distance between the line pieces is subjected to the distance criterion for testing 3D proximity. PMID:21160548

Cerebellin 4, a synaptic protein, enhances inhibitory activity and resistance of neurons to amyloid-β toxicity.

PubMed

Chacón, Pedro J; del Marco, Ángel; Arévalo, Ángeles; Domínguez-Giménez, Paloma; García-Segura, Luis Miguel; Rodríguez-Tébar, Alfredo

2015-02-01

Imbalances between excitatory and inhibitory transmissions in the brain anticipate the neuronal damage and death that occur in the neurodegenerative diseases like Alzheimer's disease (AD). We previously showed that amyloid-β (Aß), a natural peptide involved in the onset and development of AD, counteracts the neurotrophic activity of the nerve growth factor (NGF) by dampening the γ-aminobutyric acid (GABA)ergic connectivity of cultured hippocampal neurons. Neuronal plasticity is partly controlled by the NGF-promoted expression of the homologue of enhancer-of-split 1 (Hes1), a transcription factor that regulates the formation of GABAergic synapses. We now show that Hes1 controls the expression of cerebellin 4 (Cbln4), a member of a small family of secreted synaptic proteins, and we present the evidence that Cbln4 plays an essential role in the formation and maintenance of inhibitory GABAergic connections. Cbln4 immunoreactivity was found in the hippocampus, mostly in the dendrites and somata of pyramidal neurons. In the CA1, the hippocampal region where the first neurons degenerate in AD, Cbln4 immunoreactivity was associated with GABAergic synapses (detected by vesicular inhibitory amino acid transporter [VGAT] immunostaining), which appear to surround and embrace the somata of CA1 pyramidal neurons (basket cells). Moreover, significant decreases of Hes1, Cbln4, and VGAT immunoreactivities and messenger RNA expression were found in the hippocampus of a mouse model of AD. We also found that either the overexpression of Cbln4 in cultured hippocampal neurons or the application of recombinant Cbln4 to the cultures increased the number of GABAergic varicosities, rescuing neurons from Aß-induced death. In contrast, knockdown of Cbln4 gene in cultured neurons was followed by a large reduction of GABAergic connections. Such an effect was reverted by exogenously added Cbln4. These findings suggest a therapeutic potential for Cbln4 in the treatment of AD. Copyright © 2015 Elsevier Inc. All rights reserved.

Lack of Intrinsic GABAergic Connections in the Thalamic Reticular Nucleus of the Mouse.

PubMed

Hou, Guoqiang; Smith, Alison G; Zhang, Zhong-Wei

2016-07-06

It is generally thought that neurons in the thalamic reticular nucleus (TRN) form GABAergic synapses with other TRN neurons and that these interconnections are important for the function of the TRN. However, the existence of such intrinsic connections is controversial. We combine two complementary approaches to examine intrinsic GABAergic connections in the TRN of the mouse. We find that optogenetic stimulation of TRN neurons and their axons evokes GABAergic IPSCs in TRN neurons in mice younger than 2 weeks of age but fails to do so after that age. Blocking synaptic release from TRN neurons through conditional deletion of vesicular GABA transporter has no effect on spontaneous IPSCs recorded in TRN neurons aged 2 weeks or older while dramatically reducing GABAergic transmission in thalamic relay neurons. These results demonstrate that except for a short period after birth, the TRN of the mouse lacks intrinsic GABAergic connections. The thalamic reticular nucleus has a critical role in modulating information transfer from the thalamus to the cortex. It has been proposed that neurons in the thalamic reticular nucleus are interconnected through GABAergic synapses and that these connections serve important functions. Our results show that except for the first 2 weeks after birth, the thalamic reticular nucleus of the mouse lacks intrinsic GABAergic connections. Copyright © 2016 the authors 0270-6474/16/367246-07$15.00/0.

Connexin-Dependent Neuroglial Networking as a New Therapeutic Target.

PubMed

Charvériat, Mathieu; Naus, Christian C; Leybaert, Luc; Sáez, Juan C; Giaume, Christian

2017-01-01

Astrocytes and neurons dynamically interact during physiological processes, and it is now widely accepted that they are both organized in plastic and tightly regulated networks. Astrocytes are connected through connexin-based gap junction channels, with brain region specificities, and those networks modulate neuronal activities, such as those involved in sleep-wake cycle, cognitive, or sensory functions. Additionally, astrocyte domains have been involved in neurogenesis and neuronal differentiation during development; they participate in the "tripartite synapse" with both pre-synaptic and post-synaptic neurons by tuning down or up neuronal activities through the control of neuronal synaptic strength. Connexin-based hemichannels are also involved in those regulations of neuronal activities, however, this feature will not be considered in the present review. Furthermore, neuronal processes, transmitting electrical signals to chemical synapses, stringently control astroglial connexin expression, and channel functions. Long-range energy trafficking toward neurons through connexin-coupled astrocytes and plasticity of those networks are hence largely dependent on neuronal activity. Such reciprocal interactions between neurons and astrocyte networks involve neurotransmitters, cytokines, endogenous lipids, and peptides released by neurons but also other brain cell types, including microglial and endothelial cells. Over the past 10 years, knowledge about neuroglial interactions has widened and now includes effects of CNS-targeting drugs such as antidepressants, antipsychotics, psychostimulants, or sedatives drugs as potential modulators of connexin function and thus astrocyte networking activity. In physiological situations, neuroglial networking is consequently resulting from a two-way interaction between astrocyte gap junction-mediated networks and those made by neurons. As both cell types are modulated by CNS drugs we postulate that neuroglial networking may emerge as new therapeutic targets in neurological and psychiatric disorders.

A modeling approach on why simple central pattern generators are built of irregular neurons.

PubMed

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.

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

PubMed

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

2017-01-01

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

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

PubMed Central

2017-01-01

Abstract Humans instantly recognize a previously seen face as “familiar.” To deepen our understanding of familiarity-novelty detection, we simulated biologically plausible neural network models of generic cortical microcircuits consisting of spiking neurons with random recurrent synaptic connections. NMDA receptor (NMDAR)-dependent synaptic plasticity was implemented to allow for unsupervised learning and bidirectional modifications. Network spiking activity evoked by sensory inputs consisting of face images altered synaptic efficacy, which resulted in the network responding more strongly to a previously seen face than a novel face. Network size determined how many faces could be accurately recognized as familiar. When the simulated model became sufficiently complex in structure, multiple familiarity traces could be retained in the same network by forming partially-overlapping subnetworks that differ slightly from each other, thereby resulting in a high storage capacity. Fisher’s discriminant analysis was applied to identify critical neurons whose spiking activity predicted familiar input patterns. Intriguingly, as sensory exposure was prolonged, the selected critical neurons tended to appear at deeper layers of the network model, suggesting recruitment of additional circuits in the network for incremental information storage. We conclude that generic cortical microcircuits with bidirectional synaptic plasticity have an intrinsic ability to detect familiar inputs. This ability does not require a specialized wiring diagram or supervision and can therefore be expected to emerge naturally in developing cortical circuits. PMID:28534043

Presynaptic ionotropic receptors controlling and modulating the rules for spike timing-dependent plasticity.

PubMed

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.

Voltage-sensitive dye recording from networks of cultured neurons

NASA Astrophysics Data System (ADS)

Chien, Chi-Bin

This thesis describes the development and testing of a sensitive apparatus for recording electrical activity from microcultures of rat superior cervical ganglion (SCG) neurons by using voltage-sensitive fluorescent dyes.The apparatus comprises a feedback-regulated mercury arc light source, an inverted epifluorescence microscope, a novel fiber-optic camera with discrete photodiode detectors, and low-noise preamplifiers. Using an NA 0.75 objective and illuminating at 10 W/cm2 with the 546 nm mercury line, a typical SCG neuron stained with the styryl dye RH423 gives a detected photocurrent of 1 nA; the light source and optical detectors are quiet enough that the shot noise in this photocurrent--about.03% rms--dominates. The design, theory, and performance of this dye-recording apparatus are discussed in detail.Styryl dyes such as RH423 typically give signals of 1%/100 mV on these cells; the signals are linear in membrane potential, but do not appear to arise from a purely electrochromic mechanism. Given this voltage sensitivity and the noise level of the apparatus, it should be possible to detect both action potentials and subthreshold synaptic potentials from SCG cell bodies. In practice, dye recording can easily detect action potentials from every neuron in an SCG microculture, but small synaptic potentials are obscured by dye signals from the dense network of axons.In another microculture system that does not have such long and complex axons, this dye-recording apparatus should be able to detect synaptic potentials, making it possible to noninvasively map the synaptic connections in a microculture, and thus to study long-term synaptic plasticity.

Feedforward and feedback inhibition in neostriatal GABAergic spiny neurons.

PubMed

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.

Clique of Functional Hubs Orchestrates Population Bursts in Developmentally Regulated Neural Networks

PubMed Central

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

Sensory optimization by stochastic tuning.

PubMed

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.

An optogenetics- and imaging-assisted simultaneous multiple patch-clamp recording system for decoding complex neural circuits

PubMed Central

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

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

PubMed

Uzunova, Genoveva; Hollander, Eric; Shepherd, Jason

2014-01-01

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

[Morphometric analysis of the differentiation process of hippocampal neurons in vitro].

PubMed

Correa, Gisselle; Longart, Marines

2010-12-01

Neuronal cultures of the central nervous system are widely used to study the molecular mechanisms that rule the differentiation process. These cultures have also been used to evaluate drugs and to develop new therapies. From this we can infer the relevance of performing an extended characterization that involves the main aspects driving such process. To carry out such characterization in the present study we prepared primary cultures from hippocampal cells to study cell identity, development of neuronal processes (dendrites and axons), density of synaptic vesicles and development of growth cones. Using immunofluorescence techniques, specific antibodies and non-immunological probes, we studied the changes experienced by the structures under study during different temporal stages (1-21 days). We observed a major proportion of neurons over glia, normal development of neuronal networks (formed by dendrites and axons), increase in the length of dendrites and axons and establishment of synaptic connections. Synaptic vesicles also showed an increase in their densities as long as the time of the culture progressed. Finally, we studied the morphological changes of the growth cones and observed that those were mostly closed at the beginning of the culture period. As neurons matured we observed an increase in the proportion of open growth cones. This work represents an advance in the morphometric characterization of neuronal cultures, since it gathers the main aspects that outline the neuronal differentiation process. In this study, measurement of these morphological features made possible to establish quantitative markers that will allow establishing more precisely the different stages of neuronal differentiation.

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.

Cholinergic Axons in the Rat Ventral Tegmental Area Synapse Preferentially onto Mesoaccumbens Dopamine Neurons

PubMed Central

Omelchenko, Natalia; Sesack, Susan R.

2008-01-01

Cholinergic afferents to the ventral tegmental area (VTA) contribute substantially to the regulation of motivated behaviors and the rewarding properties of nicotine. These actions are believed to involve connections with dopamine (DA) neurons projecting to the nucleus accumbens (NAc). However, this direct synaptic link has never been investigated, nor is it known whether cholinergic inputs innervate other populations of DA and GABA neurons, including those projecting to the prefrontal cortex (PFC). We addressed these questions using electron microscopic analysis of retrograde tract-tracing and immunocytochemistry for the vesicular acetylcholine transporter (VAChT) and for tyrosine hydroxylase (TH) and GABA. In tissue labeled for TH, VAChT+ terminals frequently synapsed onto DA mesoaccumbens neurons but only seldom contacted DA mesoprefrontal cells. In tissue labeled for GABA, one third of VAChT+ terminals innervated GABA-labeled dendrites, including both mesoaccumbens and mesoprefrontal populations. VAChT+ synapses onto DA and mesoaccumbens neurons were more commonly of the asymmetric (presumed excitatory) morphological type, whereas VAChT+ synapses onto GABA cells were more frequently symmetric (presumed inhibitory or modulatory). These findings suggest that cholinergic inputs to the VTA mediate complex synaptic actions, with a major portion of this effect likely to involve an excitatory influence on DA mesoaccumbens neurons. As such, the results suggest that natural and drug rewards operating through cholinergic afferents to the VTA have a direct synaptic link to the mesoaccumbens DA neurons that modulate approach behaviors. PMID:16385486

The neural representation of the gender of faces in the primate visual system: A computer modeling study.

PubMed

Minot, Thomas; Dury, Hannah L; Eguchi, Akihiro; Humphreys, Glyn W; Stringer, Simon M

2017-03-01

We use an established neural network model of the primate visual system to show how neurons might learn to encode the gender of faces. The model consists of a hierarchy of 4 competitive neuronal layers with associatively modifiable feedforward synaptic connections between successive layers. During training, the network was presented with many realistic images of male and female faces, during which the synaptic connections are modified using biologically plausible local associative learning rules. After training, we found that different subsets of output neurons have learned to respond exclusively to either male or female faces. With the inclusion of short range excitation within each neuronal layer to implement a self-organizing map architecture, neurons representing either male or female faces were clustered together in the output layer. This learning process is entirely unsupervised, as the gender of the face images is not explicitly labeled and provided to the network as a supervisory training signal. These simulations are extended to training the network on rotating faces. It is found that by using a trace learning rule incorporating a temporal memory trace of recent neuronal activity, neurons responding selectively to either male or female faces were also able to learn to respond invariantly over different views of the faces. This kind of trace learning has been previously shown to operate within the primate visual system by neurophysiological and psychophysical studies. The computer simulations described here predict that similar neurons encoding the gender of faces will be present within the primate visual system. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Adult-born neurons modify excitatory synaptic transmission to existing neurons

PubMed Central

Adlaf, Elena W; Vaden, Ryan J; Niver, Anastasia J; Manuel, Allison F; Onyilo, Vincent C; Araujo, Matheus T; Dieni, Cristina V; Vo, Hai T; King, Gwendalyn D; Wadiche, Jacques I; Overstreet-Wadiche, Linda

2017-01-01

Adult-born neurons are continually produced in the dentate gyrus but it is unclear whether synaptic integration of new neurons affects the pre-existing circuit. Here we investigated how manipulating neurogenesis in adult mice alters excitatory synaptic transmission to mature dentate neurons. Enhancing neurogenesis by conditional deletion of the pro-apoptotic gene Bax in stem cells reduced excitatory postsynaptic currents (EPSCs) and spine density in mature neurons, whereas genetic ablation of neurogenesis increased EPSCs in mature neurons. Unexpectedly, we found that Bax deletion in developing and mature dentate neurons increased EPSCs and prevented neurogenesis-induced synaptic suppression. Together these results show that neurogenesis modifies synaptic transmission to mature neurons in a manner consistent with a redistribution of pre-existing synapses to newly integrating neurons and that a non-apoptotic function of the Bax signaling pathway contributes to ongoing synaptic refinement within the dentate circuit. DOI: http://dx.doi.org/10.7554/eLife.19886.001 PMID:28135190

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.

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.

Morphological, electrophysiological, and synaptic properties of corticocallosal pyramidal cells in the neonatal rat neocortex.

PubMed

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.

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

From synapses to behavior: development of a sensory-motor circuit in the leech.

PubMed

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.

Molecular Mechanisms for Synaptic Modification in the Visual Cortex: Interaction between Theory and Experiment

DTIC Science & Technology

1989-02-03

known that the large majority of neurons in layers Ill, IV and VI receive direct monosynaptic input from the lateral geniculate nucleus (Toyama et al...1974; Ferster and Lindstrom, 1983; Martin, 1987). The receptive fields of lateral geniculate nucleus (LGN) neurons resemble those of retinal ganglion...the lateral geniculate nucleus only. The second stage of the theoretical analysis requires that relevant intracortical connections be incorporated

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

PubMed Central

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?

PubMed

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.

Abeta oligomer-induced aberrations in synapse composition, shape, and density provide a molecular basis for loss of connectivity in Alzheimer's disease.

PubMed

Lacor, Pascale N; Buniel, Maria C; Furlow, Paul W; Clemente, Antonio Sanz; Velasco, Pauline T; Wood, Margaret; Viola, Kirsten L; Klein, William L

2007-01-24

The basis for memory loss in early Alzheimer's disease (AD) seems likely to involve synaptic damage caused by soluble Abeta-derived oligomers (ADDLs). ADDLs have been shown to build up in the brain and CSF of AD patients and are known to interfere with mechanisms of synaptic plasticity, acting as gain-of-function ligands that attach to synapses. Because of the correlation between AD dementia and synaptic degeneration, we investigated here the ability of ADDLs to affect synapse composition, structure, and abundance. Using highly differentiated cultures of hippocampal neurons, a preferred model for studies of synapse cell biology, we found that ADDLs bound to neurons with specificity, attaching to presumed excitatory pyramidal neurons but not GABAergic neurons. Fractionation of ADDLs bound to forebrain synaptosomes showed association with postsynaptic density complexes containing NMDA receptors, consistent with observed attachment of ADDLs to dendritic spines. During binding to hippocampal neurons, ADDLs promoted a rapid decrease in membrane expression of memory-related receptors (NMDA and EphB2). Continued exposure resulted in abnormal spine morphology, with induction of long thin spines reminiscent of the morphology found in mental retardation, deafferentation, and prionoses. Ultimately, ADDLs caused a significant decrease in spine density. Synaptic deterioration, which was accompanied by decreased levels of the spine cytoskeletal protein drebrin, was blocked by the Alzheimer's therapeutic drug Namenda. The observed disruption of dendritic spines links ADDLs to a major facet of AD pathology, providing strong evidence that ADDLs in AD brain cause neuropil damage believed to underlie dementia.

Neuronal avalanches of a self-organized neural network with active-neuron-dominant structure.

PubMed

Li, Xiumin; Small, Michael

2012-06-01

Neuronal avalanche is a spontaneous neuronal activity which obeys a power-law distribution of population event sizes with an exponent of -3/2. It has been observed in the superficial layers of cortex both in vivo and in vitro. In this paper, we analyze the information transmission of a novel self-organized neural network with active-neuron-dominant structure. Neuronal avalanches can be observed in this network with appropriate input intensity. We find that the process of network learning via spike-timing dependent plasticity dramatically increases the complexity of network structure, which is finally self-organized to be active-neuron-dominant connectivity. Both the entropy of activity patterns and the complexity of their resulting post-synaptic inputs are maximized when the network dynamics are propagated as neuronal avalanches. This emergent topology is beneficial for information transmission with high efficiency and also could be responsible for the large information capacity of this network compared with alternative archetypal networks with different neural connectivity.

Cell-type specific circuit connectivity of hippocampal CA1 revealed through Cre-dependent rabies tracing

PubMed Central

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

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

PubMed Central

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

2015-01-01

Understanding the theoretical foundations of how memories are encoded and retrieved in neural populations is a central challenge in neuroscience. A popular theoretical scenario for modeling memory function is the attractor neural network scenario, whose prototype is the Hopfield model. The model simplicity and the locality of the synaptic update rules come at the cost of a poor storage capacity, compared with the capacity achieved with perceptron learning algorithms. Here, by transforming the perceptron learning rule, we present an online learning rule for a recurrent neural network that achieves near-maximal storage capacity without an explicit supervisory error signal, relying only upon locally accessible information. The fully-connected network consists of excitatory binary neurons with plastic recurrent connections and non-plastic inhibitory feedback stabilizing the network dynamics; the memory patterns to be memorized are presented online as strong afferent currents, producing a bimodal distribution for the neuron synaptic inputs. Synapses corresponding to active inputs are modified as a function of the value of the local fields with respect to three thresholds. Above the highest threshold, and below the lowest threshold, no plasticity occurs. In between these two thresholds, potentiation/depression occurs when the local field is above/below an intermediate threshold. We simulated and analyzed a network of binary neurons implementing this rule and measured its storage capacity for different sizes of the basins of attraction. The storage capacity obtained through numerical simulations is shown to be close to the value predicted by analytical calculations. We also measured the dependence of capacity on the strength of external inputs. Finally, we quantified the statistics of the resulting synaptic connectivity matrix, and found that both the fraction of zero weight synapses and the degree of symmetry of the weight matrix increase with the number of stored patterns. PMID:26291608

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

PubMed

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

2015-08-01

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

The effects of dynamical synapses on firing rate activity: a spiking neural network model.

PubMed

Khalil, Radwa; Moftah, Marie Z; Moustafa, Ahmed A

2017-11-01

Accumulating evidence relates the fine-tuning of synaptic maturation and regulation of neural network activity to several key factors, including GABA A signaling and a lateral spread length between neighboring neurons (i.e., local connectivity). Furthermore, a number of studies consider short-term synaptic plasticity (STP) as an essential element in the instant modification of synaptic efficacy in the neuronal network and in modulating responses to sustained ranges of external Poisson input frequency (IF). Nevertheless, evaluating the firing activity in response to the dynamical interaction between STP (triggered by ranges of IF) and these key parameters in vitro remains elusive. Therefore, we designed a spiking neural network (SNN) model in which we incorporated the following parameters: local density of arbor essences and a lateral spread length between neighboring neurons. We also created several network scenarios based on these key parameters. Then, we implemented two classes of STP: (1) short-term synaptic depression (STD) and (2) short-term synaptic facilitation (STF). Each class has two differential forms based on the parametric value of its synaptic time constant (either for depressing or facilitating synapses). Lastly, we compared the neural firing responses before and after the treatment with STP. We found that dynamical synapses (STP) have a critical differential role on evaluating and modulating the firing rate activity in each network scenario. Moreover, we investigated the impact of changing the balance between excitation (E) and inhibition (I) on stabilizing this firing activity. © 2017 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Targeting synaptic dysfunction in Alzheimer's disease by administering a specific nutrient combination.

PubMed

van Wijk, Nick; Broersen, Laus M; de Wilde, Martijn C; Hageman, Robert J J; Groenendijk, Martine; Sijben, John W C; Kamphuis, Patrick J G H

2014-01-01

Synapse loss and synaptic dysfunction are pathological processes already involved in the early stages of Alzheimer's disease (AD). Synapses consist principally of neuronal membranes, and the neuronal and synaptic losses observed in AD have been linked to the degeneration and altered composition and structure of these membranes. Consequently, synapse loss and membrane-related pathology provide viable targets for intervention in AD. The specific nutrient combination Fortasyn Connect (FC) is designed to ameliorate synapse loss and synaptic dysfunction in AD by addressing distinct nutritional needs believed to be present in these patients. This nutrient combination comprises uridine, docosahexaenoic acid, eicosapentaenoic acid, choline, phospholipids, folic acid, vitamins B12, B6, C, and E, and selenium, and is present in Souvenaid, a medical food intended for use in early AD. It has been hypothesized that FC counteracts synaptic loss and reduces membrane-related pathology in AD by providing nutritional precursors and cofactors that act together to support neuronal membrane formation and function. Preclinical studies formed the basis of this hypothesis which is being validated in a broad clinical study program investigating the potential of this nutrient combination in AD. Memory dysfunction is one key early manifestation in AD and is associated with synapse loss. The clinical studies to date show that the FC-containing medical food improves memory function and preserves functional brain network organization in mild AD compared with controls, supporting the hypothesis that this intervention counteracts synaptic dysfunction. This review provides a comprehensive overview of basic scientific studies that led to the creation of FC and of its effects in various preclinical models.

Novel Fast Adapting Interneurons Mediate Cholinergic-Induced Fast GABAA IPSCs In Striatal Spiny Neurons

PubMed Central

Faust, Thomas W.; Assous, Maxime; Shah, Fulva; Tepper, James M.; Koós, Tibor

2015-01-01

Previous work suggests that neostriatal cholinergic interneurons control the activity of several classes of GABAergic interneurons through fast nicotinic receptor mediated synaptic inputs. Although indirect evidence has suggested the existence of several classes of interneurons controlled by this mechanism only one such cell type, the neuropeptide-Y expressing neurogliaform neuron, has been identified to date. Here we tested the hypothesis that in addition to the neurogliaform neurons that elicit slow GABAergic inhibitory responses, another interneuron type exists in the striatum that receives strong nicotinic cholinergic input and elicits conventional fast GABAergic synaptic responses in projection neurons. We obtained in vitro slice recordings from double transgenic mice in which Channelrhodopsin-2 was natively expressed in cholinergic neurons and a population of serotonin receptor-3a-Cre expressing GABAergic interneurons were visualized with tdTomato. We show that among the targeted GABAergic interneurons a novel type of interneuron, termed the fast-adapting interneuron, can be identified that is distinct from previously known interneurons based on immunocytochemical and electrophysiological criteria. We show using optogenetic activation of cholinergic inputs that fast-adapting interneurons receive a powerful supra-threshold nicotinic cholinergic input in vitro. Moreover, fast adapting neurons are densely connected to projection neurons and elicit fast, GABAA receptor mediated inhibitory postsynaptic responses. The nicotinic receptor mediated activation of fast-adapting interneurons may constitute an important mechanism through which cholinergic interneurons control the activity of projection neurons and perhaps the plasticity of their synaptic inputs when animals encounter reinforcing or otherwise salient stimuli. PMID:25865337

Death and rebirth of neural activity in sparse inhibitory networks

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

Npas4 Is a Critical Regulator of Learning-Induced Plasticity at Mossy Fiber-CA3 Synapses during Contextual Memory Formation.

PubMed

Weng, Feng-Ju; Garcia, Rodrigo I; Lutzu, Stefano; Alviña, Karina; Zhang, Yuxiang; Dushko, Margaret; Ku, Taeyun; Zemoura, Khaled; Rich, David; Garcia-Dominguez, Dario; Hung, Matthew; Yelhekar, Tushar D; Sørensen, Andreas Toft; Xu, Weifeng; Chung, Kwanghun; Castillo, Pablo E; Lin, Yingxi

2018-03-07

Synaptic connections between hippocampal mossy fibers (MFs) and CA3 pyramidal neurons are essential for contextual memory encoding, but the molecular mechanisms regulating MF-CA3 synapses during memory formation and the exact nature of this regulation are poorly understood. Here we report that the activity-dependent transcription factor Npas4 selectively regulates the structure and strength of MF-CA3 synapses by restricting the number of their functional synaptic contacts without affecting the other synaptic inputs onto CA3 pyramidal neurons. Using an activity-dependent reporter, we identified CA3 pyramidal cells that were activated by contextual learning and found that MF inputs on these cells were selectively strengthened. Deletion of Npas4 prevented both contextual memory formation and this learning-induced synaptic modification. We further show that Npas4 regulates MF-CA3 synapses by controlling the expression of the polo-like kinase Plk2. Thus, Npas4 is a critical regulator of experience-dependent, structural, and functional plasticity at MF-CA3 synapses during contextual memory formation. Copyright © 2018 Elsevier Inc. All rights reserved.

Synapse-specific astrocyte gating of amygdala-related behavior.

PubMed

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.

Circuit-specific intracortical hyperconnectivity in mice with deletion of the autism-associated Met receptor tyrosine kinase

PubMed Central

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

Neuron Specific Rab4 Effector GRASP-1 Coordinates Membrane Specialization and Maturation of Recycling Endosomes

PubMed Central

Hoogenraad, Casper C.; Popa, Ioana; Futai, Kensuke; Sanchez-Martinez, Emma; Wulf, Phebe S.; van Vlijmen, Thijs; Dortland, Bjorn R.; Oorschot, Viola; Govers, Roland; Monti, Maria; Heck, Albert J. R.; Sheng, Morgan; Klumperman, Judith; Rehmann, Holger; Jaarsma, Dick; Kapitein, Lukas C.; van der Sluijs, Peter

2010-01-01

The endosomal pathway in neuronal dendrites is essential for membrane receptor trafficking and proper synaptic function and plasticity. However, the molecular mechanisms that organize specific endocytic trafficking routes are poorly understood. Here, we identify GRIP-associated protein-1 (GRASP-1) as a neuron-specific effector of Rab4 and key component of the molecular machinery that coordinates recycling endosome maturation in dendrites. We show that GRASP-1 is necessary for AMPA receptor recycling, maintenance of spine morphology, and synaptic plasticity. At the molecular level, GRASP-1 segregates Rab4 from EEA1/Neep21/Rab5-positive early endosomal membranes and coordinates the coupling to Rab11-labelled recycling endosomes by interacting with the endosomal SNARE syntaxin 13. We propose that GRASP-1 connects early and late recycling endosomal compartments by forming a molecular bridge between Rab-specific membrane domains and the endosomal SNARE machinery. The data uncover a new mechanism to achieve specificity and directionality in neuronal membrane receptor trafficking. PMID:20098723

Circuit-specific intracortical hyperconnectivity in mice with deletion of the autism-associated Met receptor tyrosine kinase.

PubMed

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.

The hypothalamic slice approach to neuroendocrinology.

PubMed

Hatton, G I

1983-07-01

The magnocellular peptidergic cells of the supraoptic and paraventricular nuclei comprise much of what is known as the hypothalamo-neurohypophysial system and is involved in several functions, including body fluid balance, parturition and lactation. While we have learned much from experiments in vivo, they have not produced a clear understanding of some of the crucial features associated with the functioning of this system. In particular, questions relating to the osmosensitivity of magnocellular neurones and the mechanism(s) by which their characteristic firing patterns are generated have not been answered using the older approaches. Electrophysiological studies with brain slices present direct evidence for osmosensitivity, and perhaps even osmoreceptivity, of magnocellular neurones. Other evidence indicates that the phasic bursting patterns of activity associated with vasopressin-releasing neurones (a) occur in the absence of patterned chemical synaptic input, (b) may be modulated by electrotonic conduction across gap junctions connecting magnocellular neurones and (c) are likely to be generated by endogenous membrane currents. These results make untenable the formerly held idea that phasic bursting activity is dependent upon recurrent synaptic inhibition.

Biological conservation law as an emerging functionality in dynamical neuronal networks.

PubMed

Podobnik, Boris; Jusup, Marko; Tiganj, Zoran; Wang, Wen-Xu; Buldú, Javier M; Stanley, H Eugene

2017-11-07

Scientists strive to understand how functionalities, such as conservation laws, emerge in complex systems. Living complex systems in particular create high-ordered functionalities by pairing up low-ordered complementary processes, e.g., one process to build and the other to correct. We propose a network mechanism that demonstrates how collective statistical laws can emerge at a macro (i.e., whole-network) level even when they do not exist at a unit (i.e., network-node) level. Drawing inspiration from neuroscience, we model a highly stylized dynamical neuronal network in which neurons fire either randomly or in response to the firing of neighboring neurons. A synapse connecting two neighboring neurons strengthens when both of these neurons are excited and weakens otherwise. We demonstrate that during this interplay between the synaptic and neuronal dynamics, when the network is near a critical point, both recurrent spontaneous and stimulated phase transitions enable the phase-dependent processes to replace each other and spontaneously generate a statistical conservation law-the conservation of synaptic strength. This conservation law is an emerging functionality selected by evolution and is thus a form of biological self-organized criticality in which the key dynamical modes are collective.

Biological conservation law as an emerging functionality in dynamical neuronal networks

PubMed Central

Podobnik, Boris; Tiganj, Zoran; Wang, Wen-Xu; Buldú, Javier M.

2017-01-01

Scientists strive to understand how functionalities, such as conservation laws, emerge in complex systems. Living complex systems in particular create high-ordered functionalities by pairing up low-ordered complementary processes, e.g., one process to build and the other to correct. We propose a network mechanism that demonstrates how collective statistical laws can emerge at a macro (i.e., whole-network) level even when they do not exist at a unit (i.e., network-node) level. Drawing inspiration from neuroscience, we model a highly stylized dynamical neuronal network in which neurons fire either randomly or in response to the firing of neighboring neurons. A synapse connecting two neighboring neurons strengthens when both of these neurons are excited and weakens otherwise. We demonstrate that during this interplay between the synaptic and neuronal dynamics, when the network is near a critical point, both recurrent spontaneous and stimulated phase transitions enable the phase-dependent processes to replace each other and spontaneously generate a statistical conservation law—the conservation of synaptic strength. This conservation law is an emerging functionality selected by evolution and is thus a form of biological self-organized criticality in which the key dynamical modes are collective. PMID:29078286

A potential reservoir of immature dopaminergic replacement neurons in the adult mammalian olfactory bulb.

PubMed

Pignatelli, Angela; Ackman, James B; Vigetti, Davide; Beltrami, Antonio P; Zucchini, Silvia; Belluzzi, Ottorino

2009-02-01

A significant fraction of the interneurons added in adulthood to the glomerular layer (GL) of the olfactory bulb (OB) are dopaminergic (DA). In the OB, DA neurons are restricted to the GL, but using transgenic mice expressing eGFP under the tyrosine hydroxylase (TH) promoter, we also detected the presence of TH-GFP+ cells in the mitral and external plexiform layers. We hypothesized that these could be adult-generated neurons committed to become DA but not yet entirely differentiated. Accordingly, TH-GFP+ cells outside the GL exhibit functional properties (appearance of pacemaker currents, synaptic connection with the olfactory nerve, intracellular chloride concentration, and other) marking a gradient of maturity toward the dopaminergic phenotype along the mitral-glomerular axis. Finally, we propose that the establishment of a synaptic contact with the olfactory nerve is the key event allowing these cells to complete their differentiation toward the DA phenotype and to reach their final destination.

DSCAM-mediated control of dendritic and axonal arbor outgrowth enforces tiling and inhibits synaptic plasticity

PubMed Central

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

Molecular Mechanisms at the Basis of Plasticity in the Developing Visual Cortex: Epigenetic Processes and Gene Programs

PubMed Central

Maya-Vetencourt, José Fernando; Pizzorusso, Tommaso

2013-01-01

Neuronal circuitries in the mammalian visual system change as a function of experience. Sensory experience modifies neuronal networks connectivity via the activation of different physiological processes such as excitatory/inhibitory synaptic transmission, neurotrophins, and signaling of extracellular matrix molecules. Long-lasting phenomena of plasticity occur when intracellular signal transduction pathways promote epigenetic alterations of chromatin structure that regulate the induction of transcription factors that in turn drive the expression of downstream targets, the products of which then work via the activation of structural and functional mechanisms that modify synaptic connectivity. Here, we review recent findings in the field of visual cortical plasticity while focusing on how physiological mechanisms associated with experience promote structural changes that determine functional modifications of neural circuitries in V1. We revise the role of microRNAs as molecular transducers of environmental stimuli and the role of immediate early genes that control gene expression programs underlying plasticity in the developing visual cortex. PMID:25157210

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).

Synaptic input correlations leading to membrane potential decorrelation of spontaneous activity in cortex.

PubMed

Graupner, Michael; Reyes, Alex D

2013-09-18

Correlations in the spiking activity of neurons have been found in many regions of the cortex under multiple experimental conditions and are postulated to have important consequences for neural population coding. While there is a large body of extracellular data reporting correlations of various strengths, the subthreshold events underlying the origin and magnitude of signal-independent correlations (called noise or spike count correlations) are unknown. Here we investigate, using intracellular recordings, how synaptic input correlations from shared presynaptic neurons translate into membrane potential and spike-output correlations. Using a pharmacologically activated thalamocortical slice preparation, we perform simultaneous recordings from pairs of layer IV neurons in the auditory cortex of mice and measure synaptic potentials/currents, membrane potentials, and spiking outputs. We calculate cross-correlations between excitatory and inhibitory inputs to investigate correlations emerging from the network. We furthermore evaluate membrane potential correlations near resting potential to study how excitation and inhibition combine and affect spike-output correlations. We demonstrate directly that excitation is correlated with inhibition thereby partially canceling each other and resulting in weak membrane potential and spiking correlations between neurons. Our data suggest that cortical networks are set up to partially cancel correlations emerging from the connections between neurons. This active decorrelation is achieved because excitation and inhibition closely track each other. Our results suggest that the numerous shared presynaptic inputs do not automatically lead to increased spiking correlations.

The Intrinsic Electrophysiological Properties of Mammalian Neurons: Insights into Central Nervous System Function

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.

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

PubMed

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

2016-03-01

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

“Rapid Estrogen Signaling in the Brain: Implications for the Fine-Tuning of Neuronal Circuitry”

PubMed Central

Srivastava, Deepak P.; Waters, Elizabeth M.; Mermelstein, Paul G.; Kramár, Enikö A.; Shors, Tracey J.; Liu, Feng

2011-01-01

Rapid actions of estrogens were first described over 40 years ago. However, the importance of rapid estrogen-mediated actions in the central nervous system (CNS) has only now becoming apparent. Several lines of evidence demonstrate that rapid estrogen-mediated signaling elicits potent effects on molecular and cellular events, resulting in the fine-tuning of neuronal circuitry. At an ultrastructural level, the details of estrogen receptor localization and how these are regulated by the circulating hormone and age, are now becoming evident. Furthermore, the mechanisms that allow membrane-associated estrogen receptors to couple with intracellular signaling pathways are also now being revealed. Elucidation of complex actions of rapid estrogen-mediated signaling on synaptic proteins, connectivity and synaptic function in pyramidal neurons has demonstrated that this neurosteroid engage specific mechanisms in different areas of the brain. The regulation of synaptic properties most likely underlies the ‘fine-tuning’ of neuronal circuitry. This in turn may influence how learned behaviors are encoded by different circuitry in male and female subjects. Importantly, as estrogens have been suggested as potential treatments of a number of disorders of the CNS, advancements in our understanding of rapid estrogen signaling in the brain will serve to aid in the development of potential novel estrogen-based treatments. PMID:22072656

Prevention of posttraumatic axon sprouting by blocking CRMP2-mediated neurite outgrowth and tubulin polymerization

PubMed Central

Wilson, Sarah M.; Xiong, Wenhui; Wang, Yuying; Ping, Xingjie; Head, Jessica D.; Brittain, Joel M.; Gagare, Pravin D.; Ramachandran, P. Veeraraghavan; Jin, Xiaoming; Khanna, Rajesh

2012-01-01

Epileptogenesis following traumatic brain injury (TBI) is likely due to a combination of increased excitability, disinhibition, and increased excitatory connectivity via aberrant axon sprouting. Targeting these pathways could be beneficial in the prevention and treatment of posttraumatic epilepsy. Here, we tested this possibility using the novel anticonvulsant (R)-N-benzyl 2-acetamido-3-methoxypropionamide ((R)-lacosamide (LCM) which acts on both voltage-gated sodium channels and collapsin response mediator protein 2 (CRMP2), an axonal growth/guidance protein. LCM inhibited CRMP2-mediated neurite outgrowth, an effect phenocopied by CRMP2 knockdown. Mutation of LCM binding sites in CRMP2 reduced the neurite inhibitory effect of LCM by ~8-fold. LCM also reduced CRMP2-mediated tubulin polymerization. Thus, LCM selectively impairs CRMP2-mediated microtubule polymerization which underlies its neurite outgrowth and branching. To determine whether LCM inhibits axon sprouting in vivo, LCM was injected into rats subjected to partial cortical isolation, an animal model of posttraumatic epileptogenesis that exhibits axon sprouting in cortical pyramidal neurons. Two weeks following injury, excitatory synaptic connectivity of cortical layer V pyramidal neurons was mapped using patch clamp recordings and laser scanning photostimulation of caged glutamate. In comparison to injured control animals, there was a significant decrease in the map size of excitatory synaptic connectivity in LCM-treated rats, suggesting that LCM treatment prevented enhanced excitatory synaptic connectivity due to posttraumatic axon sprouting. These findings suggest, for the first time, that LCM’s mode of action involves interactions with CRMP2 to inhibit posttraumatic axon sprouting. PMID:22433297

Graph Theoretic and Motif Analyses of the Hippocampal Neuron Type Potential Connectome.

PubMed

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.

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

PubMed Central

Abbott, L. F.; Sompolinsky, Haim

2017-01-01

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

Hybrid Scheme for Modeling Local Field Potentials from Point-Neuron Networks.

PubMed

Hagen, Espen; Dahmen, David; Stavrinou, Maria L; Lindén, Henrik; Tetzlaff, Tom; van Albada, Sacha J; Grün, Sonja; Diesmann, Markus; Einevoll, Gaute T

2016-12-01

With rapidly advancing multi-electrode recording technology, the local field potential (LFP) has again become a popular measure of neuronal activity in both research and clinical applications. Proper understanding of the LFP requires detailed mathematical modeling incorporating the anatomical and electrophysiological features of neurons near the recording electrode, as well as synaptic inputs from the entire network. Here we propose a hybrid modeling scheme combining efficient point-neuron network models with biophysical principles underlying LFP generation by real neurons. The LFP predictions rely on populations of network-equivalent multicompartment neuron models with layer-specific synaptic connectivity, can be used with an arbitrary number of point-neuron network populations, and allows for a full separation of simulated network dynamics and LFPs. We apply the scheme to a full-scale cortical network model for a ∼1 mm 2 patch of primary visual cortex, predict laminar LFPs for different network states, assess the relative LFP contribution from different laminar populations, and investigate effects of input correlations and neuron density on the LFP. The generic nature of the hybrid scheme and its public implementation in hybridLFPy form the basis for LFP predictions from other and larger point-neuron network models, as well as extensions of the current application with additional biological detail. © The Author 2016. Published by Oxford University Press.

Cell Class-Dependent Intracortical Connectivity and Output Dynamics of Layer 6 Projection Neurons of the Rat Primary Visual Cortex.

PubMed

Cotel, Florence; Fletcher, Lee N; Kalita-de Croft, Simon; Apergis-Schoute, John; Williams, Stephen R

2018-07-01

Neocortical information processing is powerfully influenced by the activity of layer 6 projection neurons through control of local intracortical and subcortical circuitry. Morphologically distinct classes of layer 6 projection neuron have been identified in the mammalian visual cortex, which exhibit contrasting receptive field properties, but little information is available on their functional specificity. To address this we combined anatomical tracing techniques with high-resolution patch-clamp recording to identify morphological and functional distinct classes of layer 6 projection neurons in the rat primary visual cortex, which innervated separable subcortical territories. Multisite whole-cell recordings in brain slices revealed that corticoclaustral and corticothalamic layer 6 projection neurons exhibited similar somatically recorded electrophysiological properties. These classes of layer 6 projection neurons were sparsely and reciprocally synaptically interconnected, but could be differentiated by cell-class, but not target-cell-dependent rules of use-dependent depression and facilitation of unitary excitatory synaptic output. Corticoclaustral and corticothalamic layer 6 projection neurons were differentially innervated by columnar excitatory circuitry, with corticoclaustral, but not corticothalamic, neurons powerfully driven by layer 4 pyramidal neurons, and long-range pathways conveyed in neocortical layer 1. Our results therefore reveal projection target-specific, functionally distinct, streams of layer 6 output in the rodent neocortex.

Exploring the limits of learning: Segregation of information integration and response selection is required for learning a serial reversal task

PubMed Central

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

Constrained synaptic connectivity in functional mammalian neuronal networks grown on patterned surfaces.

PubMed

Wyart, Claire; Ybert, Christophe; Bourdieu, Laurent; Herr, Catherine; Prinz, Christelle; Chatenay, Didier

2002-06-30

The use of ordered neuronal networks in vitro is a promising approach to study the development and the activity of small neuronal assemblies. However, in previous attempts, sufficient growth control and physiological maturation of neurons could not be achieved. Here we describe an original protocol in which polylysine patterns confine the adhesion of cellular bodies to prescribed spots and the neuritic growth to thin lines. Hippocampal neurons in these networks are maintained healthy in serum free medium up to 5 weeks in vitro. Electrophysiology and immunochemistry show that neurons exhibit mature excitatory and inhibitory synapses and calcium imaging reveals spontaneous activity of neurons in isolated networks. We demonstrate that neurons in these geometrical networks form functional synapses preferentially to their first neighbors. We have, therefore, established a simple and robust protocol to constrain both the location of neuronal cell bodies and their pattern of connectivity. Moreover, the long term maintenance of the geometry and the physiology of the networks raises the possibility of new applications for systematic screening of pharmacological agents and for electronic to neuron devices.

Combining microfluidics, optogenetics and calcium imaging to study neuronal communication in vitro.

PubMed

Renault, Renaud; Sukenik, Nirit; Descroix, Stéphanie; Malaquin, Laurent; Viovy, Jean-Louis; Peyrin, Jean-Michel; Bottani, Samuel; Monceau, Pascal; Moses, Elisha; Vignes, Maéva

2015-01-01

In this paper we report the combination of microfluidics, optogenetics and calcium imaging as a cheap and convenient platform to study synaptic communication between neuronal populations in vitro. We first show that Calcium Orange indicator is compatible in vitro with a commonly used Channelrhodopsine-2 (ChR2) variant, as standard calcium imaging conditions did not alter significantly the activity of transduced cultures of rodent primary neurons. A fast, robust and scalable process for micro-chip fabrication was developed in parallel to build micro-compartmented cultures. Coupling optical fibers to each micro-compartment allowed for the independent control of ChR2 activation in the different populations without crosstalk. By analyzing the post-stimuli activity across the different populations, we finally show how this platform can be used to evaluate quantitatively the effective connectivity between connected neuronal populations.

Toward a Neurobiology of Child Psychotherapy

ERIC Educational Resources Information Center

Kay, Jerald

2009-01-01

Brain imaging studies have demonstrated that psychotherapy alters brain structure and function. Learning and memory, both implicit and explicit, play central roles in this process through the creation of new genetic material that leads to increased synaptic efficiency through the creation of new neuronal connections. Although there is substantial…

Electron microscopic immunocytochemical study of somatostatin neurons in the periventricular nucleus of the rat hypothalamus with special reference to their relationships with homologous neuronal processes.

PubMed

Alonso, G; Tapia-Arancibia, L; Assenmacher, I

1985-10-01

The neurons containing somatostatin in the rat periventricular nucleus were studied by using a modified electron microscopic immunocytochemical technique that improves both the penetration of immunoreagents into unembedded immunostained tissues and the preservation of ultrastructural morphology. Inside perikarya and dendrites, immunostaining was not only associated with neurosecretory granules but also with ribosomes and saccules of the cis face of the Golgi apparatus. In the axonal profiles found in this region the labeling was observed both on neurosecretory granule cores and on the limiting membrane of small synaptic-like vesicles. Throughout the periventricular nucleus, both non-synaptic and synaptic relationships were shown between labeled neurons. Non-synaptic relationships mainly consisted of direct apposition of the membranes of neighboring neurons by dendrosomatic, somasomatic or dendrodendritic contacts. These labeled perikarya and dendrites were also synaptically contacted by labeled axonal endings containing numerous aggregated synaptic-like vesicles. The physiological significance of the synaptic and non-synaptic relationships between somatostatinergic neurons is discussed in terms of possible synchronization between homologous neurons of the somatostatin neuroendocrine system and control of these neurons by a central ultra-short loop feedback mechanism.

A neural mechanism of dynamic gating of task-relevant information by top-down influence in primary visual cortex.

PubMed

Kamiyama, Akikazu; Fujita, Kazuhisa; Kashimori, Yoshiki

2016-12-01

Visual recognition involves bidirectional information flow, which consists of bottom-up information coding from retina and top-down information coding from higher visual areas. Recent studies have demonstrated the involvement of early visual areas such as primary visual area (V1) in recognition and memory formation. V1 neurons are not passive transformers of sensory inputs but work as adaptive processor, changing their function according to behavioral context. Top-down signals affect tuning property of V1 neurons and contribute to the gating of sensory information relevant to behavior. However, little is known about the neuronal mechanism underlying the gating of task-relevant information in V1. To address this issue, we focus on task-dependent tuning modulations of V1 neurons in two tasks of perceptual learning. We develop a model of the V1, which receives feedforward input from lateral geniculate nucleus and top-down input from a higher visual area. We show here that the change in a balance between excitation and inhibition in V1 connectivity is necessary for gating task-relevant information in V1. The balance change well accounts for the modulations of tuning characteristic and temporal properties of V1 neuronal responses. We also show that the balance change of V1 connectivity is shaped by top-down signals with temporal correlations reflecting the perceptual strategies of the two tasks. We propose a learning mechanism by which synaptic balance is modulated. To conclude, top-down signal changes the synaptic balance between excitation and inhibition in V1 connectivity, enabling early visual area such as V1 to gate context-dependent information under multiple task performances. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Stimulus-specific adaptation in a recurrent network model of primary auditory cortex

PubMed Central

2017-01-01

Stimulus-specific adaptation (SSA) occurs when neurons decrease their responses to frequently-presented (standard) stimuli but not, or not as much, to other, rare (deviant) stimuli. SSA is present in all mammalian species in which it has been tested as well as in birds. SSA confers short-term memory to neuronal responses, and may lie upstream of the generation of mismatch negativity (MMN), an important human event-related potential. Previously published models of SSA mostly rely on synaptic depression of the feedforward, thalamocortical input. Here we study SSA in a recurrent neural network model of primary auditory cortex. When the recurrent, intracortical synapses display synaptic depression, the network generates population spikes (PSs). SSA occurs in this network when deviants elicit a PS but standards do not, and we demarcate the regions in parameter space that allow SSA. While SSA based on PSs does not require feedforward depression, we identify feedforward depression as a mechanism for expanding the range of parameters that support SSA. We provide predictions for experiments that could help differentiate between SSA due to synaptic depression of feedforward connections and SSA due to synaptic depression of recurrent connections. Similar to experimental data, the magnitude of SSA in the model depends on the frequency difference between deviant and standard, probability of the deviant, inter-stimulus interval and input amplitude. In contrast to models based on feedforward depression, our model shows true deviance sensitivity as found in experiments. PMID:28288158

Dendritic nonlinearities reduce network size requirements and mediate ON and OFF states of persistent activity in a PFC microcircuit model.

PubMed

Papoutsi, Athanasia; Sidiropoulou, Kyriaki; Poirazi, Panayiota

2014-07-01

Technological advances have unraveled the existence of small clusters of co-active neurons in the neocortex. The functional implications of these microcircuits are in large part unexplored. Using a heavily constrained biophysical model of a L5 PFC microcircuit, we recently showed that these structures act as tunable modules of persistent activity, the cellular correlate of working memory. Here, we investigate the mechanisms that underlie persistent activity emergence (ON) and termination (OFF) and search for the minimum network size required for expressing these states within physiological regimes. We show that (a) NMDA-mediated dendritic spikes gate the induction of persistent firing in the microcircuit. (b) The minimum network size required for persistent activity induction is inversely proportional to the synaptic drive of each excitatory neuron. (c) Relaxation of connectivity and synaptic delay constraints eliminates the gating effect of NMDA spikes, albeit at a cost of much larger networks. (d) Persistent activity termination by increased inhibition depends on the strength of the synaptic input and is negatively modulated by dADP. (e) Slow synaptic mechanisms and network activity contain predictive information regarding the ability of a given stimulus to turn ON and/or OFF persistent firing in the microcircuit model. Overall, this study zooms out from dendrites to cell assemblies and suggests a tight interaction between dendritic non-linearities and network properties (size/connectivity) that may facilitate the short-memory function of the PFC.

PTEN regulation of local and long-range connections in mouse auditory cortex

PubMed Central

Xiong, Qiaojie; Oviedo, Hysell V; Trotman, Lloyd C; Zador, Anthony M

2012-01-01

Autism Spectrum Disorders (ASDs) are highly heritable developmental disorders caused by a heterogeneous collection of genetic lesions. Here we use a mouse model to study the effect on cortical connectivity of disrupting the ASD candidate gene PTEN. Through Cre-mediated recombination we conditionally knocked out PTEN expression in a subset of auditory cortical neurons. Analysis of long range connectivity using channelrhodopsin-2 (ChR2) revealed that the strength of synaptic inputs from both the contralateral auditory cortex and from the thalamus onto PTEN-cko neurons was enhanced compared with nearby neurons with normal PTEN expression. Laser scanning photostimulation (LSPS) showed that local inputs onto PTEN-cko neurons in the auditory cortex were similarly enhanced. The hyperconnectivity caused by PTEN-cko could be blocked by rapamycin, a specific inhibitor of the PTEN downstream molecule mTORC1. Together our results suggest that local and long-range hyperconnectivity may constitute a physiological basis for the effects of mutations in PTEN and possibly other ASD candidate genes. PMID:22302806

Robust spatial memory maps in flickering neuronal networks: a topological model

NASA Astrophysics Data System (ADS)

Dabaghian, Yuri; Babichev, Andrey; Memoli, Facundo; Chowdhury, Samir; Rice University Collaboration; Ohio State University Collaboration

It is widely accepted that the hippocampal place cells provide a substrate of the neuronal representation of the environment--the ``cognitive map''. However, hippocampal network, as any other network in the brain is transient: thousands of hippocampal neurons die every day and the connections formed by these cells constantly change due to various forms of synaptic plasticity. What then explains the remarkable reliability of our spatial memories? We propose a computational approach to answering this question based on a couple of insights. First, we propose that the hippocampal cognitive map is fundamentally topological, and hence it is amenable to analysis by topological methods. We then apply several novel methods from homology theory, to understand how dynamic connections between cells influences the speed and reliability of spatial learning. We simulate the rat's exploratory movements through different environments and study how topological invariants of these environments arise in a network of simulated neurons with ``flickering'' connectivity. We find that despite transient connectivity the network of place cells produces a stable representation of the topology of the environment.

Synchronization in a noise-driven developing neural network

NASA Astrophysics Data System (ADS)

Lin, I.-H.; Wu, R.-K.; Chen, C.-M.

2011-11-01

We use computer simulations to investigate the structural and dynamical properties of a developing neural network whose activity is driven by noise. Structurally, the constructed neural networks in our simulations exhibit the small-world properties that have been observed in several neural networks. The dynamical change of neuronal membrane potential is described by the Hodgkin-Huxley model, and two types of learning rules, including spike-timing-dependent plasticity (STDP) and inverse STDP, are considered to restructure the synaptic strength between neurons. Clustered synchronized firing (SF) of the network is observed when the network connectivity (number of connections/maximal connections) is about 0.75, in which the firing rate of neurons is only half of the network frequency. At the connectivity of 0.86, all neurons fire synchronously at the network frequency. The network SF frequency increases logarithmically with the culturing time of a growing network and decreases exponentially with the delay time in signal transmission. These conclusions are consistent with experimental observations. The phase diagrams of SF in a developing network are investigated for both learning rules.

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

PubMed

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

2017-03-22

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

Transsynaptic Coordination of Synaptic Growth, Function, and Stability by the L1-Type CAM Neuroglian

PubMed Central

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

Transsynaptic coordination of synaptic growth, function, and stability by the L1-type CAM Neuroglian.

PubMed

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.

The interplay between neurons and glia in synapse development and plasticity.

PubMed

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.

The role of propriospinal neuronal network in transmitting the alternating muscular activities of flexor and extensor in parkinsonian tremor.

PubMed

Hao, M; He, X; Lan, N

2012-01-01

It has been shown that normal cyclic movement of human arm and resting limb tremor in Parkinson's disease (PD) are associated with the oscillatory neuronal activities in different cerebral networks, which are transmitted to the antagonistic muscles via the same spinal pathway. There are mono-synaptic and multi-synaptic corticospinal pathways for conveying motor commands. This study investigates the plausible role of propriospinal neuronal (PN) network in the C3-C4 levels in multi-synaptic transmission of cortical commands for oscillatory movements. A PN network model is constructed based on known neurophysiological connections, and is hypothesized to achieve the conversion of cortical oscillations into alternating antagonistic muscle bursts. Simulations performed with a virtual arm (VA) model indicate that without the PN network, the alternating bursts of antagonistic muscle EMG could not be reliably generated, whereas with the PN network, the alternating pattern of bursts were naturally displayed in the three pairs of antagonist muscles. Thus, it is suggested that oscillations in the primary motor cortex (M1) of single and double tremor frequencies are processed at the PN network to compute the alternating burst pattern in the flexor and extensor muscles.

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

PubMed Central

Uzunova, Genoveva; Hollander, Eric; Shepherd, Jason

2014-01-01

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

Implementation of a spike-based perceptron learning rule using TiO2-x memristors.

PubMed

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.

Presynaptic Ionotropic Receptors Controlling and Modulating the Rules for Spike Timing-Dependent Plasticity

PubMed Central

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

Astrocytes regulate heterogeneity of presynaptic strengths in hippocampal networks

PubMed Central

Letellier, Mathieu; Park, Yun Kyung; Chater, Thomas E.; Chipman, Peter H.; Gautam, Sunita Ghimire; Oshima-Takago, Tomoko; Goda, Yukiko

2016-01-01

Dendrites are neuronal structures specialized for receiving and processing information through their many synaptic inputs. How input strengths are modified across dendrites in ways that are crucial for synaptic integration and plasticity remains unclear. We examined in single hippocampal neurons the mechanism of heterosynaptic interactions and the heterogeneity of synaptic strengths of pyramidal cell inputs. Heterosynaptic presynaptic plasticity that counterbalances input strengths requires N-methyl-d-aspartate receptors (NMDARs) and astrocytes. Importantly, this mechanism is shared with the mechanism for maintaining highly heterogeneous basal presynaptic strengths, which requires astrocyte Ca2+ signaling involving NMDAR activation, astrocyte membrane depolarization, and L-type Ca2+ channels. Intracellular infusion of NMDARs or Ca2+-channel blockers into astrocytes, conditionally ablating the GluN1 NMDAR subunit, or optogenetically hyperpolarizing astrocytes with archaerhodopsin promotes homogenization of convergent presynaptic inputs. Our findings support the presence of an astrocyte-dependent cellular mechanism that enhances the heterogeneity of presynaptic strengths of convergent connections, which may help boost the computational power of dendrites. PMID:27118849

Synaptic Circuit Organization of Motor Corticothalamic Neurons

PubMed Central

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

The Balance of Excitatory and Inhibitory Synaptic Inputs for Coding Sound Location

PubMed Central

Ono, Munenori

2014-01-01

The localization of high-frequency sounds in the horizontal plane uses an interaural-level difference (ILD) cue, yet little is known about the synaptic mechanisms that underlie processing this cue in the inferior colliculus (IC) of mouse. Here, we study the synaptic currents that process ILD in vivo and use stimuli in which ILD varies around a constant average binaural level (ABL) to approximate sounds on the horizontal plane. Monaural stimulation in either ear produced EPSCs and IPSCs in most neurons. The temporal properties of monaural responses were well matched, suggesting connected functional zones with matched inputs. The EPSCs had three patterns in response to ABL stimuli, preference for the sound field with the highest level stimulus: (1) contralateral; (2) bilateral highly lateralized; or (3) at the center near 0 ILD. EPSCs and IPSCs were well correlated except in center-preferred neurons. Summation of the monaural EPSCs predicted the binaural excitatory response but less well than the summation of monaural IPSCs. Binaural EPSCs often showed a nonlinearity that strengthened the response to specific ILDs. Extracellular spike and intracellular current recordings from the same neuron showed that the ILD tuning of the spikes was sharper than that of the EPSCs. Thus, in the IC, balanced excitatory and inhibitory inputs may be a general feature of synaptic coding for many types of sound processing. PMID:24599475

Untangling Basal Ganglia Network Dynamics and Function: Role of Dopamine Depletion and Inhibition Investigated in a Spiking Network Model.

PubMed

Lindahl, Mikael; Hellgren Kotaleski, Jeanette

2016-01-01

The basal ganglia are a crucial brain system for behavioral selection, and their function is disturbed in Parkinson's disease (PD), where neurons exhibit inappropriate synchronization and oscillations. We present a spiking neural model of basal ganglia including plausible details on synaptic dynamics, connectivity patterns, neuron behavior, and dopamine effects. Recordings of neuronal activity in the subthalamic nucleus and Type A (TA; arkypallidal) and Type I (TI; prototypical) neurons in globus pallidus externa were used to validate the model. Simulation experiments predict that both local inhibition in striatum and the existence of an indirect pathway are important for basal ganglia to function properly over a large range of cortical drives. The dopamine depletion-induced increase of AMPA efficacy in corticostriatal synapses to medium spiny neurons (MSNs) with dopamine receptor D2 synapses (CTX-MSN D2) and the reduction of MSN lateral connectivity (MSN-MSN) were found to contribute significantly to the enhanced synchrony and oscillations seen in PD. Additionally, reversing the dopamine depletion-induced changes to CTX-MSN D1, CTX-MSN D2, TA-MSN, and MSN-MSN couplings could improve or restore basal ganglia action selection ability. In summary, we found multiple changes of parameters for synaptic efficacy and neural excitability that could improve action selection ability and at the same time reduce oscillations. Identification of such targets could potentially generate ideas for treatments of PD and increase our understanding of the relation between network dynamics and network function.

The Role of Neurotrophins in Neurotransmitter Release

PubMed Central

Tyler, William J.; Perrett, Stephen P.; Pozzo-Miller, Lucas D.

2009-01-01

The neurotrophins (NTs) have recently been shown to elicit pronounced effects on quantal neurotransmitter release at both central and peripheral nervous system synapses. Due to their activity-dependent release, as well as the subcellular localization of both protein and receptor, NTs are ideally suited to modify the strength of neuronal connections by “fine-tuning” synaptic activity through direct actions at presynaptic terminals. Here, using BDNF as a prototypical example, the authors provide an update of recent evidence demonstrating that NTs enhance quantal neurotransmitter release at synapses through presynaptic mechanisms. The authors further propose that a potential target for NT actions at presynaptic terminals is the mechanism by which terminals retrieve synaptic vesicles after exocytosis. Depending on the temporal demands placed on synapses during high-frequency synaptic transmission, synapses may use two alternative modes of synaptic vesicle retrieval, the conventional slow endosomal recycling or a faster rapid retrieval at the active zone, referred to as “kiss-and-run.” By modulating Ca2+ microdomains associated with voltage-gated Ca2+ channels at active zones, NTs may elicit a switch from the slow to the fast mode of endocytosis of vesicles at presynaptic terminals during high-frequency synaptic transmission, allowing more reliable information transfer and neuronal signaling in the central nervous system. PMID:12467374

The role of neurotrophins in neurotransmitter release.

PubMed

Tyler, William J; Perrett, Stephen P; Pozzo-Miller, Lucas D

2002-12-01

The neurotrophins (NTs) have recently been shown to elicit pronounced effects on quantal neurotransmitter release at both central and peripheral nervous system synapses. Due to their activity-dependent release, as well as the subcellular localization of both protein and receptor, NTs are ideally suited to modify the strength of neuronal connections by "fine-tuning" synaptic activity through direct actions at presynaptic terminals. Here, using BDNF as a prototypical example, the authors provide an update of recent evidence demonstrating that NTs enhance quantal neurotransmitter release at synapses through presynaptic mechanisms. The authors further propose that a potential target for NT actions at presynaptic terminals is the mechanism by which terminals retrieve synaptic vesicles after exocytosis. Depending on the temporal demands placed on synapses during high-frequency synaptic transmission, synapses may use two alternative modes of synaptic vesicle retrieval, the conventional slow endosomal recycling or a faster rapid retrieval at the active zone, referred to as "kiss-and-run." By modulating Ca2+ microdomains associated with voltage-gated Ca2+ channels at active zones, NTs may elicit a switch from the slow to the fast mode of endocytosis of vesicles at presynaptic terminals during high-frequency synaptic transmission, allowing more reliable information transfer and neuronal signaling in the central nervous system.

Patterns of innervation of neurones in the inferior mesenteric ganglion of the cat.

PubMed Central

Julé, Y; Krier, J; Szurszewski, J H

1983-01-01

The patterns of peripheral and central synaptic input to non-spontaneous, irregular discharging and regular discharging neurones in the inferior mesenteric ganglion of the cat were studied in vitro using intracellular recording techniques. All three types of neurones in rostral and caudal lobes received central synaptic input primarily from L3 and L4 spinal cord segments. Since irregular discharging neurones received synaptic input from intraganglionic regular discharging neurones, some of the central input to irregular discharging neurones may have been relayed through the regular discharging neurones. In the rostral lobes of the ganglion, more than 70% of the non-spontaneous and irregular discharging neurones tested received peripheral synaptic input from the lumbar colonic, intermesenteric and left and right hypogastric nerves. Most of the regular discharging neurones tested received synaptic input from the intermesenteric and lumbar colonic nerves; none of the regular discharging neurones received synaptic input from the hypogastric nerves. Some of the peripheral synaptic input from the lumbar colonic and intermesenteric nerves to irregular discharging neurones may have been relayed through the regular discharging neurones. Axons of non-spontaneous and irregular discharging neurones located in the rostral lobes travelled to the periphery exclusively in the lumbar colonic nerves. Antidromic responses were not observed in regular discharging neurones during stimulation of any of the major peripheral nerve trunks. This suggests these neurones were intraganglionic. In the caudal lobes, irregular discharging neurones received a similar pattern of peripheral synaptic input as did irregular discharging neurones located in the rostral lobes. The majority of irregular discharging neurones in the caudal lobes projected their axons to the periphery through the lumbar colonic nerves. Non-spontaneous neurones in the caudal lobes, in contrast to those located in the rostral lobes, received peripheral synaptic input primarily from the hypogastric nerves. Axons of the majority of non-spontaneous neurones located in the caudal lobes travelled to the periphery through hypogastric nerves. The results suggest that non-spontaneous neurones and irregular discharging neurones in the rostral lobes and the majority of irregular discharging neurones in the caudal lobes transact and integrate neural commands destined for abdominal viscera supplied by the lumbar colonic nerves. Non-spontaneous neurones in the caudal lobes transact and integrate neural commands destined for pelvic viscera supplied by the hypogastric nerves. PMID:6655582

Patterns of innervation of neurones in the inferior mesenteric ganglion of the cat.

PubMed

Julé, Y; Krier, J; Szurszewski, J H

1983-11-01

The patterns of peripheral and central synaptic input to non-spontaneous, irregular discharging and regular discharging neurones in the inferior mesenteric ganglion of the cat were studied in vitro using intracellular recording techniques. All three types of neurones in rostral and caudal lobes received central synaptic input primarily from L3 and L4 spinal cord segments. Since irregular discharging neurones received synaptic input from intraganglionic regular discharging neurones, some of the central input to irregular discharging neurones may have been relayed through the regular discharging neurones. In the rostral lobes of the ganglion, more than 70% of the non-spontaneous and irregular discharging neurones tested received peripheral synaptic input from the lumbar colonic, intermesenteric and left and right hypogastric nerves. Most of the regular discharging neurones tested received synaptic input from the intermesenteric and lumbar colonic nerves; none of the regular discharging neurones received synaptic input from the hypogastric nerves. Some of the peripheral synaptic input from the lumbar colonic and intermesenteric nerves to irregular discharging neurones may have been relayed through the regular discharging neurones. Axons of non-spontaneous and irregular discharging neurones located in the rostral lobes travelled to the periphery exclusively in the lumbar colonic nerves. Antidromic responses were not observed in regular discharging neurones during stimulation of any of the major peripheral nerve trunks. This suggests these neurones were intraganglionic. In the caudal lobes, irregular discharging neurones received a similar pattern of peripheral synaptic input as did irregular discharging neurones located in the rostral lobes. The majority of irregular discharging neurones in the caudal lobes projected their axons to the periphery through the lumbar colonic nerves. Non-spontaneous neurones in the caudal lobes, in contrast to those located in the rostral lobes, received peripheral synaptic input primarily from the hypogastric nerves. Axons of the majority of non-spontaneous neurones located in the caudal lobes travelled to the periphery through hypogastric nerves. The results suggest that non-spontaneous neurones and irregular discharging neurones in the rostral lobes and the majority of irregular discharging neurones in the caudal lobes transact and integrate neural commands destined for abdominal viscera supplied by the lumbar colonic nerves. Non-spontaneous neurones in the caudal lobes transact and integrate neural commands destined for pelvic viscera supplied by the hypogastric nerves.

Computational implications of activity-dependent neuronal processes

NASA Astrophysics Data System (ADS)

Goldman, Mark Steven

Synapses, the connections between neurons, often fail to transmit a large percentage of the action potentials that they receive. I describe several models of synaptic transmission at a single stochastic synapse with an activity-dependent probability of transmission and demonstrate how synaptic transmission failures may increase the efficiency with which a synapse transmits information. Spike trains in the visual cortex of freely viewing monkeys have positive auto correlations that are indicative of a redundant representation of the information they contain. I show how a synapse with activity-dependent transmission failures modeled after those occurring in visual cortical synapses can remove this redundancy by transmitting a decorrelated subset of the spike trains it receives. I suggest that redundancy reduction at individual synapses saves synaptic resources while increasing the sensitivity of the postsynaptic neuron to information arriving along many inputs. For a neuron receiving input from many decorrelating synapses, my analysis leads to a prediction of the number of visual inputs to a neuron and the cross-correlations between these inputs and suggests that the time scale of synaptic dynamics observed in sensory areas corresponds to a fundamental time scale for processing sensory information. Systems with activity-dependent changes in their parameters, or plasticity, often display a wide variability in their individual components that belies the stability of their function, Motivated by experiments demonstrating that identified neurons with stereotyped function can have a large variability in the densities of their ion channels, or ionic conductances, I build a conductance-based model of a single neuron. The neuron's firing activity is relatively insensitive to changes in certain combinations of conductances, but markedly sensitive to changes in other combinations. Using a combined modeling and experimental approach, I show that neuromodulators and regulatory processes target sensitive combinations of conductances. I suggest that the variability observed in conductance measurements occurs along insensitive combinations of conductances and could result from homeostatic processes that allow the neuron's conductances to drift without triggering activity- dependent feedback mechanisms. These results together suggest that plastic systems may have a high degree of flexibility and variability in their components without a loss of robustness in their response properties.

Diverse modes of synaptic signaling, regulation, and plasticity distinguish two classes of C. elegans glutamatergic neurons.

PubMed

Ventimiglia, Donovan; Bargmann, Cornelia I

2017-11-21

Synaptic vesicle release properties vary between neuronal cell types, but in most cases the molecular basis of this heterogeneity is unknown. Here, we compare in vivo synaptic properties of two neuronal classes in the C. elegans central nervous system, using VGLUT-pHluorin to monitor synaptic vesicle exocytosis and retrieval in intact animals. We show that the glutamatergic sensory neurons AWC ON and ASH have distinct synaptic dynamics associated with tonic and phasic synaptic properties, respectively. Exocytosis in ASH and AWC ON is differentially affected by SNARE-complex regulators that are present in both neurons: phasic ASH release is strongly dependent on UNC-13, whereas tonic AWC ON release relies upon UNC-18 and on the protein kinase C homolog PKC-1. Strong stimuli that elicit high calcium levels increase exocytosis and retrieval rates in AWC ON , generating distinct tonic and evoked synaptic modes. These results highlight the differential deployment of shared presynaptic proteins in neuronal cell type-specific functions.

Diverse modes of synaptic signaling, regulation, and plasticity distinguish two classes of C. elegans glutamatergic neurons

PubMed Central

Ventimiglia, Donovan

2017-01-01

Synaptic vesicle release properties vary between neuronal cell types, but in most cases the molecular basis of this heterogeneity is unknown. Here, we compare in vivo synaptic properties of two neuronal classes in the C. elegans central nervous system, using VGLUT-pHluorin to monitor synaptic vesicle exocytosis and retrieval in intact animals. We show that the glutamatergic sensory neurons AWCON and ASH have distinct synaptic dynamics associated with tonic and phasic synaptic properties, respectively. Exocytosis in ASH and AWCON is differentially affected by SNARE-complex regulators that are present in both neurons: phasic ASH release is strongly dependent on UNC-13, whereas tonic AWCON release relies upon UNC-18 and on the protein kinase C homolog PKC-1. Strong stimuli that elicit high calcium levels increase exocytosis and retrieval rates in AWCON, generating distinct tonic and evoked synaptic modes. These results highlight the differential deployment of shared presynaptic proteins in neuronal cell type-specific functions. PMID:29160768

From Understanding Cellular Function to Novel Drug Discovery: The Role of Planar Patch-Clamp Array Chip Technology

PubMed Central

Py, Christophe; Martina, Marzia; Diaz-Quijada, Gerardo A.; Luk, Collin C.; Martinez, Dolores; Denhoff, Mike W.; Charrier, Anne; Comas, Tanya; Monette, Robert; Krantis, Anthony; Syed, Naweed I.; Mealing, Geoffrey A. R.

2011-01-01

All excitable cell functions rely upon ion channels that are embedded in their plasma membrane. Perturbations of ion channel structure or function result in pathologies ranging from cardiac dysfunction to neurodegenerative disorders. Consequently, to understand the functions of excitable cells and to remedy their pathophysiology, it is important to understand the ion channel functions under various experimental conditions – including exposure to novel drug targets. Glass pipette patch-clamp is the state of the art technique to monitor the intrinsic and synaptic properties of neurons. However, this technique is labor intensive and has low data throughput. Planar patch-clamp chips, integrated into automated systems, offer high throughputs but are limited to isolated cells from suspensions, thus limiting their use in modeling physiological function. These chips are therefore not most suitable for studies involving neuronal communication. Multielectrode arrays (MEAs), in contrast, have the ability to monitor network activity by measuring local field potentials from multiple extracellular sites, but specific ion channel activity is challenging to extract from these multiplexed signals. Here we describe a novel planar patch-clamp chip technology that enables the simultaneous high-resolution electrophysiological interrogation of individual neurons at multiple sites in synaptically connected neuronal networks, thereby combining the advantages of MEA and patch-clamp techniques. Each neuron can be probed through an aperture that connects to a dedicated subterranean microfluidic channel. Neurons growing in networks are aligned to the apertures by physisorbed or chemisorbed chemical cues. In this review, we describe the design and fabrication process of these chips, approaches to chemical patterning for cell placement, and present physiological data from cultured neuronal cells. PMID:22007170

From understanding cellular function to novel drug discovery: the role of planar patch-clamp array chip technology.

PubMed

Py, Christophe; Martina, Marzia; Diaz-Quijada, Gerardo A; Luk, Collin C; Martinez, Dolores; Denhoff, Mike W; Charrier, Anne; Comas, Tanya; Monette, Robert; Krantis, Anthony; Syed, Naweed I; Mealing, Geoffrey A R

2011-01-01

All excitable cell functions rely upon ion channels that are embedded in their plasma membrane. Perturbations of ion channel structure or function result in pathologies ranging from cardiac dysfunction to neurodegenerative disorders. Consequently, to understand the functions of excitable cells and to remedy their pathophysiology, it is important to understand the ion channel functions under various experimental conditions - including exposure to novel drug targets. Glass pipette patch-clamp is the state of the art technique to monitor the intrinsic and synaptic properties of neurons. However, this technique is labor intensive and has low data throughput. Planar patch-clamp chips, integrated into automated systems, offer high throughputs but are limited to isolated cells from suspensions, thus limiting their use in modeling physiological function. These chips are therefore not most suitable for studies involving neuronal communication. Multielectrode arrays (MEAs), in contrast, have the ability to monitor network activity by measuring local field potentials from multiple extracellular sites, but specific ion channel activity is challenging to extract from these multiplexed signals. Here we describe a novel planar patch-clamp chip technology that enables the simultaneous high-resolution electrophysiological interrogation of individual neurons at multiple sites in synaptically connected neuronal networks, thereby combining the advantages of MEA and patch-clamp techniques. Each neuron can be probed through an aperture that connects to a dedicated subterranean microfluidic channel. Neurons growing in networks are aligned to the apertures by physisorbed or chemisorbed chemical cues. In this review, we describe the design and fabrication process of these chips, approaches to chemical patterning for cell placement, and present physiological data from cultured neuronal cells.

Long-term sensitization training in Aplysia leads to an increase in the expression of BiP, the major protein chaperon of the ER.

PubMed

Kuhl, D; Kennedy, T E; Barzilai, A; Kandel, E R

1992-12-01

Long-term memory for sensitization of the gill- and siphon-withdrawal reflexes in Aplysia californica requires RNA and protein synthesis. These long-term behavioral changes are accompanied by long-term facilitation of the synaptic connections between the gill and siphon sensory and motor neurons, which are similarly dependent on transcription and translation. In addition to showing an increase in over-all protein synthesis, long-term facilitation is associated with changes in the expression of specific early, intermediate, and late proteins, and with the growth of new synaptic connections between the sensory and motor neurons of the reflex. We previously focused on early proteins and have identified four proteins as members of the immunoglobulin family of cell adhesion molecules related to NCAM and fasciclin II. We have now cloned the cDNA corresponding to one of the late proteins, and identified it as the Aplysia homolog of BiP, an ER resident protein involved in the folding and assembly of secretory and membrane proteins. Behavioral training increases the steady-state level of BiP mRNA in the sensory neurons. The increase in the synthesis of BiP protein is first detected 3 h after the onset of facilitation, when the increase in overall protein synthesis reaches its peak and the formation of new synaptic terminals becomes apparent. These findings suggest that the chaperon function of BiP might serve to fold proteins and assemble protein complexes necessary for the structural changes characteristic of long-term memory.

Chronic spinal cord stimulation modifies intrinsic cardiac synaptic efficacy in the suppression of atrial fibrillation

PubMed Central

Ardell, Jeffrey L.; Cardinal, René; Beaumont, Eric; Vermeulen, Michel; Smith, Frank M.; Armour, J. Andrew

2014-01-01

We sought to determine whether spinal cord stimulation (SCS) therapy, when applied chronically to canines, imparts long-lasting cardio-protective effects on neurogenic atrial tachyarrhythmia induction and, if so, whether its effects can be attributable to i) changes in intrinsic cardiac (IC) neuronal transmembrane properties vs ii) modification of their interneuronal stochastic interactivity that initiates such pathology. Data derived from canines subjected to long-term SCS [(group 1 studied after 3–4 weeks SCS; n=5) (group 2: studied 5 weeks SCS; n=11)] were compared to data derived from 10 control animals (including 4 sham SCS electrode implantations). During terminal studies conducted under anesthesia, chronotropic and inotropic responses to vagal nerve or stellate ganglion stimulation were similar in all 3 groups. Chronic SCS suppressed atrial tachyarrhythmia induction evoked by mediastinal nerve stimulation. When induced, arrhythmia durations were shortened (controls: median of 27s; SCS 3–4 weeks: median of 16s; SCS 5 weeks: median of 7s). Phasic and accommodating right atrial neuronal somata displayed similar passive and active membrane properties in vitro, whether derived from sham or either chronic SCS groups. Synaptic efficacy was differentially enhanced in accommodating (not phasic) IC neurons by chronic SCS. Taken together these data indicate that chronic SCS therapy modifies IC neuronal stochastic inter-connectivity in atrial fibrillation suppression by altering synaptic function without directly targeting the transmembrane properties of individual IC neuronal somata. PMID:25301713

Glycinergic dysfunction in a subpopulation of dorsal horn interneurons in a rat model of neuropathic pain

PubMed Central

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

Spontaneously emerging direction selectivity maps in visual cortex through STDP.

PubMed

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

2005-10-01

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

Coseeded Schwann cells myelinate neurites from differentiated neural stem cells in neurotrophin-3-loaded PLGA carriers

PubMed Central

Xiong, Yi; Zhu, Ji-Xiang; Fang, Zheng-Yu; Zeng, Cheng-Guang; Zhang, Chao; Qi, Guo-Long; Li, Man-Hui; Zhang, Wei; Quan, Da-Ping; Wan, Jun

2012-01-01

Biomaterials and neurotrophic factors represent promising guidance for neural repair. In this study, we combined poly-(lactic acid-co-glycolic acid) (PLGA) conduits and neurotrophin-3 (NT-3) to generate NT-3-loaded PLGA carriers in vitro. Bioactive NT-3 was released stably and constantly from PLGA conduits for up to 4 weeks. Neural stem cells (NSCs) and Schwann cells (SCs) were coseeded into an NT-releasing scaffold system and cultured for 14 days. Immunoreactivity against Map2 showed that most of the grafted cells (>80%) were differentiated toward neurons. Double-immunostaining for synaptogenesis and myelination revealed the formation of synaptic structures and myelin sheaths in the coculture, which was also observed under electron microscope. Furthermore, under depolarizing conditions, these synapses were excitable and capable of releasing synaptic vesicles labeled with FM1-43 or FM4-64. Taken together, coseeding NSCs and SCs into NT-3-loaded PLGA carriers increased the differentiation of NSCs into neurons, developed synaptic connections, exhibited synaptic activities, and myelination of neurites by the accompanying SCs. These results provide an experimental basis that supports transplantation of functional neural construction in spinal cord injury. PMID:22619535

Network Disruption and Cerebrospinal Fluid Amyloid-Beta and Phospho-Tau Levels in Mild Cognitive Impairment.

PubMed

Canuet, Leonides; Pusil, Sandra; López, María Eugenia; Bajo, Ricardo; Pineda-Pardo, José Ángel; Cuesta, Pablo; Gálvez, Gerardo; Gaztelu, José María; Lourido, Daniel; García-Ribas, Guillermo; Maestú, Fernando

2015-07-15

Synaptic dysfunction is a core deficit in Alzheimer's disease, preceding hallmark pathological abnormalities. Resting-state magnetoencephalography (MEG) was used to assess whether functional connectivity patterns, as an index of synaptic dysfunction, are associated with CSF biomarkers [i.e., phospho-tau (p-tau) and amyloid beta (Aβ42) levels]. We studied 12 human subjects diagnosed with mild cognitive impairment due to Alzheimer's disease, comparing those with normal and abnormal CSF levels of the biomarkers. We also evaluated the association between aberrant functional connections and structural connectivity abnormalities, measured with diffusion tensor imaging, as well as the convergent impact of cognitive deficits and CSF variables on network disorganization. One-third of the patients converted to Alzheimer's disease during a follow-up period of 2.5 years. Patients with abnomal CSF p-tau and Aβ42 levels exhibited both reduced and increased functional connectivity affecting limbic structures such as the anterior/posterior cingulate cortex, orbitofrontal cortex, and medial temporal areas in different frequency bands. A reduction in posterior cingulate functional connectivity mediated by p-tau was associated with impaired axonal integrity of the hippocampal cingulum. We noted that several connectivity abnormalities were predicted by CSF biomarkers and cognitive scores. These preliminary results indicate that CSF markers of amyloid deposition and neuronal injury in early Alzheimer's disease associate with a dual pattern of cortical network disruption, affecting key regions of the default mode network and the temporal cortex. MEG is useful to detect early synaptic dysfunction associated with Alzheimer's disease brain pathology in terms of functional network organization. In this preliminary study, we used magnetoencephalography and an integrative approach to explore the impact of CSF biomarkers, neuropsychological scores, and white matter structural abnormalities on neural function in mild cognitive impairment. Disruption in functional connectivity between several pairs of cortical regions associated with abnormal levels of biomarkers, cognitive deficits, or with impaired axonal integrity of hippocampal tracts. Amyloid deposition and tau protein-related neuronal injury in early Alzheimer's disease are associated with synaptic dysfunction and a dual pattern of cortical network disorganization (i.e., desynchronization and hypersynchronization) that affects key regions of the default mode network and temporal areas. Copyright © 2015 the authors 0270-6474/15/3510326-06$15.00/0.

Distribution of Orientation Selectivity in Recurrent Networks of Spiking Neurons with Different Random Topologies

PubMed Central

Sadeh, Sadra; Rotter, Stefan

2014-01-01

Neurons in the primary visual cortex are more or less selective for the orientation of a light bar used for stimulation. A broad distribution of individual grades of orientation selectivity has in fact been reported in all species. A possible reason for emergence of broad distributions is the recurrent network within which the stimulus is being processed. Here we compute the distribution of orientation selectivity in randomly connected model networks that are equipped with different spatial patterns of connectivity. We show that, for a wide variety of connectivity patterns, a linear theory based on firing rates accurately approximates the outcome of direct numerical simulations of networks of spiking neurons. Distance dependent connectivity in networks with a more biologically realistic structure does not compromise our linear analysis, as long as the linearized dynamics, and hence the uniform asynchronous irregular activity state, remain stable. We conclude that linear mechanisms of stimulus processing are indeed responsible for the emergence of orientation selectivity and its distribution in recurrent networks with functionally heterogeneous synaptic connectivity. PMID:25469704

A modeling comparison of projection neuron- and neuromodulator-elicited oscillations in a central pattern generating network.

PubMed

Kintos, Nickolas; Nusbaum, Michael P; Nadim, Farzan

2008-06-01

Many central pattern generating networks are influenced by synaptic input from modulatory projection neurons. The network response to a projection neuron is sometimes mimicked by bath applying the neuronally-released modulator, despite the absence of network interactions with the projection neuron. One interesting example occurs in the crab stomatogastric ganglion (STG), where bath applying the neuropeptide pyrokinin (PK) elicits a gastric mill rhythm which is similar to that elicited by the projection neuron modulatory commissural neuron 1 (MCN1), despite the absence of PK in MCN1 and the fact that MCN1 is not active during the PK-elicited rhythm. MCN1 terminals have fast and slow synaptic actions on the gastric mill network and are presynaptically inhibited by this network in the STG. These local connections are inactive in the PK-elicited rhythm, and the mechanism underlying this rhythm is unknown. We use mathematical and biophysically-realistic modeling to propose potential mechanisms by which PK can elicit a gastric mill rhythm that is similar to the MCN1-elicited rhythm. We analyze slow-wave network oscillations using simplified mathematical models and, in parallel, develop biophysically-realistic models that account for fast, action potential-driven oscillations and some spatial structure of the network neurons. Our results illustrate how the actions of bath-applied neuromodulators can mimic those of descending projection neurons through mathematically similar but physiologically distinct mechanisms.

Wnt signaling pathway improves central inhibitory synaptic transmission in a mouse model of Duchenne muscular dystrophy.

PubMed

Fuenzalida, Marco; Espinoza, Claudia; Pérez, Miguel Ángel; Tapia-Rojas, Cheril; Cuitino, Loreto; Brandan, Enrique; Inestrosa, Nibaldo C

2016-02-01

The dystrophin-associated glycoprotein complex (DGC) that connects the cytoskeleton, plasma membrane and the extracellular matrix has been related to the maintenance and stabilization of channels and synaptic receptors, which are both essential for synaptogenesis and synaptic transmission. The dystrophin-deficient (mdx) mouse model of Duchenne muscular dystrophy (DMD) exhibits a significant reduction in hippocampal GABA efficacy, which may underlie the altered synaptic function and abnormal hippocampal long-term plasticity exhibited by mdx mice. Emerging studies have implicated Wnt signaling in the modulation of synaptic efficacy, neuronal plasticity and cognitive function. We report here that the activation of the non-canonical Wnt-5a pathway and Andrographolide, improves hippocampal mdx GABAergic efficacy by increasing the number of inhibitory synapses and GABA(A) receptors or GABA release. These results indicate that Wnt signaling modulates GABA synaptic efficacy and could be a promising novel target for DMD cognitive therapy. Copyright © 2015 Elsevier Inc. All rights reserved.

Microelectrode array recordings of cultured hippocampal networks reveal a simple model for transcription and protein synthesis-dependent plasticity

PubMed Central

Arnold, Fiona JL; Hofmann, Frank; Bengtson, C. Peter; Wittmann, Malte; Vanhoutte, Peter; Bading, Hilmar

2005-01-01

A simplified cell culture system was developed to study neuronal plasticity. As changes in synaptic strength may alter network activity patterns, we grew hippocampal neurones on a microelectrode array (MEA) and monitored their collective behaviour with 60 electrodes simultaneously. We found that exposure of the network for 15 min to the GABAA receptor antagonist bicuculline induced an increase in synaptic efficacy at excitatory synapses that was associated with an increase in the frequency of miniature AMPA receptor-mediated EPSCs and a change in network activity from uncoordinated firing of neurones (lacking any recognizable pattern) to a highly organized, periodic and synchronous burst pattern. Induction of recurrent synchronous bursting was dependent on NMDA receptor activation and required extracellular signal-regulated kinase (ERK)1/2 signalling and translation of pre-existing mRNAs. Once induced, the burst pattern persisted for several days; its maintenance phase (> 4 h) was dependent on gene transcription taking place in a critical period of 120 min following induction. Thus, cultured hippocampal neurones display a simple, transcription and protein synthesis-dependent form of plasticity. The non-invasive nature of MEA recordings provides a significant advantage over traditional assays for synaptic connectivity (i.e. long-term potentiation in brain slices) and facilitates the search for activity-regulated genes critical for late-phase plasticity. PMID:15618268

Microelectrode array recordings of cultured hippocampal networks reveal a simple model for transcription and protein synthesis-dependent plasticity.

PubMed

Arnold, Fiona J L; Hofmann, Frank; Bengtson, C Peter; Wittmann, Malte; Vanhoutte, Peter; Bading, Hilmar

2005-04-01

A simplified cell culture system was developed to study neuronal plasticity. As changes in synaptic strength may alter network activity patterns, we grew hippocampal neurones on a microelectrode array (MEA) and monitored their collective behaviour with 60 electrodes simultaneously. We found that exposure of the network for 15 min to the GABA(A) receptor antagonist bicuculline induced an increase in synaptic efficacy at excitatory synapses that was associated with an increase in the frequency of miniature AMPA receptor-mediated EPSCs and a change in network activity from uncoordinated firing of neurones (lacking any recognizable pattern) to a highly organized, periodic and synchronous burst pattern. Induction of recurrent synchronous bursting was dependent on NMDA receptor activation and required extracellular signal-regulated kinase (ERK)1/2 signalling and translation of pre-existing mRNAs. Once induced, the burst pattern persisted for several days; its maintenance phase (> 4 h) was dependent on gene transcription taking place in a critical period of 120 min following induction. Thus, cultured hippocampal neurones display a simple, transcription and protein synthesis-dependent form of plasticity. The non-invasive nature of MEA recordings provides a significant advantage over traditional assays for synaptic connectivity (i.e. long-term potentiation in brain slices) and facilitates the search for activity-regulated genes critical for late-phase plasticity.

Structural and synaptic plasticity in stress-related disorders

PubMed Central

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

The effects of neuron morphology on graph theoretic measures of network connectivity: the analysis of a two-level statistical model.

PubMed

Aćimović, Jugoslava; Mäki-Marttunen, Tuomo; Linne, Marja-Leena

2015-01-01

We developed a two-level statistical model that addresses the question of how properties of neurite morphology shape the large-scale network connectivity. We adopted a low-dimensional statistical description of neurites. From the neurite model description we derived the expected number of synapses, node degree, and the effective radius, the maximal distance between two neurons expected to form at least one synapse. We related these quantities to the network connectivity described using standard measures from graph theory, such as motif counts, clustering coefficient, minimal path length, and small-world coefficient. These measures are used in a neuroscience context to study phenomena from synaptic connectivity in the small neuronal networks to large scale functional connectivity in the cortex. For these measures we provide analytical solutions that clearly relate different model properties. Neurites that sparsely cover space lead to a small effective radius. If the effective radius is small compared to the overall neuron size the obtained networks share similarities with the uniform random networks as each neuron connects to a small number of distant neurons. Large neurites with densely packed branches lead to a large effective radius. If this effective radius is large compared to the neuron size, the obtained networks have many local connections. In between these extremes, the networks maximize the variability of connection repertoires. The presented approach connects the properties of neuron morphology with large scale network properties without requiring heavy simulations with many model parameters. The two-steps procedure provides an easier interpretation of the role of each modeled parameter. The model is flexible and each of its components can be further expanded. We identified a range of model parameters that maximizes variability in network connectivity, the property that might affect network capacity to exhibit different dynamical regimes.

Roles of octopaminergic and dopaminergic neurons in appetitive and aversive memory recall in an insect.

PubMed

Mizunami, Makoto; Unoki, Sae; Mori, Yasuhiro; Hirashima, Daisuke; Hatano, Ai; Matsumoto, Yukihisa

2009-08-04

In insect classical conditioning, octopamine (the invertebrate counterpart of noradrenaline) or dopamine has been suggested to mediate reinforcing properties of appetitive or aversive unconditioned stimulus, respectively. However, the roles of octopaminergic and dopaminergic neurons in memory recall have remained unclear. We studied the roles of octopaminergic and dopaminergic neurons in appetitive and aversive memory recall in olfactory and visual conditioning in crickets. We found that pharmacological blockade of octopamine and dopamine receptors impaired aversive memory recall and appetitive memory recall, respectively, thereby suggesting that activation of octopaminergic and dopaminergic neurons and the resulting release of octopamine and dopamine are needed for appetitive and aversive memory recall, respectively. On the basis of this finding, we propose a new model in which it is assumed that two types of synaptic connections are formed by conditioning and are activated during memory recall, one type being connections from neurons representing conditioned stimulus to neurons inducing conditioned response and the other being connections from neurons representing conditioned stimulus to octopaminergic or dopaminergic neurons representing appetitive or aversive unconditioned stimulus, respectively. The former is called 'stimulus-response connection' and the latter is called 'stimulus-stimulus connection' by theorists studying classical conditioning in higher vertebrates. Our model predicts that pharmacological blockade of octopamine or dopamine receptors during the first stage of second-order conditioning does not impair second-order conditioning, because it impairs the formation of the stimulus-response connection but not the stimulus-stimulus connection. The results of our study with a cross-modal second-order conditioning were in full accordance with this prediction. We suggest that insect classical conditioning involves the formation of two kinds of memory traces, which match to stimulus-stimulus connection and stimulus-response connection. This is the first study to suggest that classical conditioning in insects involves, as does classical conditioning in higher vertebrates, the formation of stimulus-stimulus connection and its activation for memory recall, which are often called cognitive processes.

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.

Roles of Aminergic Neurons in Formation and Recall of Associative Memory in Crickets

PubMed Central

Mizunami, Makoto; Matsumoto, Yukihisa

2010-01-01

We review recent progress in the study of roles of octopaminergic (OA-ergic) and dopaminergic (DA-ergic) signaling in insect classical conditioning, focusing on our studies on crickets. Studies on olfactory learning in honey bees and fruit-flies have suggested that OA-ergic and DA-ergic neurons convey reinforcing signals of appetitive unconditioned stimulus (US) and aversive US, respectively. Our work suggested that this is applicable to olfactory, visual pattern, and color learning in crickets, indicating that this feature is ubiquitous in learning of various sensory stimuli. We also showed that aversive memory decayed much faster than did appetitive memory, and we proposed that this feature is common in insects and humans. Our study also suggested that activation of OA- or DA-ergic neurons is needed for appetitive or aversive memory recall, respectively. To account for this finding, we proposed a model in which it is assumed that two types of synaptic connections are strengthened by conditioning and are activated during memory recall, one type being connections from neurons representing conditioned stimulus (CS) to neurons inducing conditioned response and the other being connections from neurons representing CS to OA- or DA-ergic neurons representing appetitive or aversive US, respectively. The former is called stimulus–response (S–R) connection and the latter is called stimulus–stimulus (S–S) connection by theorists studying classical conditioning in vertebrates. Results of our studies using a second-order conditioning procedure supported our model. We propose that insect classical conditioning involves the formation of S–S connection and its activation for memory recall, which are often called cognitive processes. PMID:21119781

Synaptic plasticity associated with a memory engram in the basolateral amygdala.

PubMed

Nonaka, Ayako; Toyoda, Takeshi; Miura, Yuki; Hitora-Imamura, Natsuko; Naka, Masamitsu; Eguchi, Megumi; Yamaguchi, Shun; Ikegaya, Yuji; Matsuki, Norio; Nomura, Hiroshi

2014-07-09

Synaptic plasticity is a cellular mechanism putatively underlying learning and memory. However, it is unclear whether learning induces synaptic modification globally or only in a subset of neurons in associated brain regions. In this study, we genetically identified neurons activated during contextual fear learning and separately recorded synaptic efficacy from recruited and nonrecruited neurons in the mouse basolateral amygdala (BLA). We found that the fear learning induces presynaptic potentiation, which was reflected by an increase in the miniature EPSC frequency and by a decrease in the paired-pulse ratio. Changes occurred only in the cortical synapses targeting the BLA neurons that were recruited into the fear memory trace. Furthermore, we found that fear learning reorganizes the neuronal ensemble responsive to the conditioning context in conjunction with the synaptic plasticity. In particular, the neuronal activity during learning was associated with the neuronal recruitment into the context-responsive ensemble. These findings suggest that synaptic plasticity in a subset of BLA neurons contributes to fear memory expression through ensemble reorganization. Copyright © 2014 the authors 0270-6474/14/349305-05$15.00/0.

Modification of a neuronal network direction using stepwise photo-thermal etching of an agarose architecture.

PubMed

Suzuki, Ikurou; Sugio, Yoshihiro; Moriguchi, Hiroyuki; Jimbo, Yasuhiko; Yasuda, Kenji

2004-07-01

Control over spatial distribution of individual neurons and the pattern of neural network provides an important tool for studying information processing pathways during neural network formation. Moreover, the knowledge of the direction of synaptic connections between cells in each neural network can provide detailed information on the relationship between the forward and feedback signaling. We have developed a method for topographical control of the direction of synaptic connections within a living neuronal network using a new type of individual-cell-based on-chip cell-cultivation system with an agarose microchamber array (AMCA). The advantages of this system include the possibility to control positions and number of cultured cells as well as flexible control of the direction of elongation of axons through stepwise melting of narrow grooves. Such micrometer-order microchannels are obtained by photo-thermal etching of agarose where a portion of the gel is melted with a 1064-nm infrared laser beam. Using this system, we created neural network from individual Rat hippocampal cells. We were able to control elongation of individual axons during cultivation (from cells contained within the AMCA) by non-destructive stepwise photo-thermal etching. We have demonstrated the potential of our on-chip AMCA cell cultivation system for the controlled development of individual cell-based neural networks.

Visualizing the Effects of a Positive Early Experience, Tactile Stimulation, on Dendritic Morphology and Synaptic Connectivity with Golgi-Cox Staining

PubMed Central

Mychasiuk, Richelle; Gibb, Robbin; Kolb, Bryan

2013-01-01

To generate longer-term changes in behavior, experiences must be producing stable changes in neuronal morphology and synaptic connectivity. Tactile stimulation is a positive early experience that mimics maternal licking and grooming in the rat. Exposing rat pups to this positive experience can be completed easily and cost-effectively by using highly accessible materials such as a household duster. Using a cross-litter design, pups are either stroked or left undisturbed, for 15 min, three times per day throughout the perinatal period. To measure the neuroplastic changes related to this positive early experience, Golgi-Cox staining of brain tissue is utilized. Owing to the fact that Golgi-Cox impregnation stains a discrete number of neurons rather than all of the cells, staining of the rodent brain with Golgi-Cox solution permits the visualization of entire neuronal elements, including the cell body, dendrites, axons, and dendritic spines. The staining procedure is carried out over several days and requires that the researcher pay close attention to detail. However, once staining is completed, the entire brain has been impregnated and can be preserved indefinitely for ongoing analysis. Therefore, Golgi-Cox staining is a valuable resource for studying experience-dependent plasticity. PMID:24121525

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.

Reduced sensory synaptic excitation impairs motor neuron function via Kv2.1 in spinal muscular atrophy.

PubMed

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.

Reduced sensory synaptic excitation impairs motor neuron function via Kv2.1 in spinal muscular atrophy

PubMed Central

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

Improving and accelerating the differentiation and functional maturation of human stem cell-derived neurons: role of extracellular calcium and GABA.

PubMed

Kemp, Paul J; Rushton, David J; Yarova, Polina L; Schnell, Christian; Geater, Charlene; Hancock, Jane M; Wieland, Annalena; Hughes, Alis; Badder, Luned; Cope, Emma; Riccardi, Daniela; Randall, Andrew D; Brown, Jonathan T; Allen, Nicholas D; Telezhkin, Vsevolod

2016-11-15

Neurons differentiated from pluripotent stem cells using established neural culture conditions often exhibit functional deficits. Recently, we have developed enhanced media which both synchronize the neurogenesis of pluripotent stem cell-derived neural progenitors and accelerate their functional maturation; together these media are termed SynaptoJuice. This pair of media are pro-synaptogenic and generate authentic, mature synaptic networks of connected forebrain neurons from a variety of induced pluripotent and embryonic stem cell lines. Such enhanced rate and extent of synchronized maturation of pluripotent stem cell-derived neural progenitor cells generates neurons which are characterized by a relatively hyperpolarized resting membrane potential, higher spontaneous and induced action potential activity, enhanced synaptic activity, more complete development of a mature inhibitory GABA A receptor phenotype and faster production of electrical network activity when compared to standard differentiation media. This entire process - from pre-patterned neural progenitor to active neuron - takes 3 weeks or less, making it an ideal platform for drug discovery and disease modelling in the fields of human neurodegenerative and neuropsychiatric disorders, such as Huntington's disease, Parkinson's disease, Alzheimer's disease and Schizophrenia. © 2016 The Authors. The Journal of Physiology © 2016 The Physiological Society.

Synaptic Plasticity Enables Adaptive Self-Tuning Critical Networks

PubMed Central

Stepp, Nigel; Plenz, Dietmar; Srinivasa, Narayan

2015-01-01

During rest, the mammalian cortex displays spontaneous neural activity. Spiking of single neurons during rest has been described as irregular and asynchronous. In contrast, recent in vivo and in vitro population measures of spontaneous activity, using the LFP, EEG, MEG or fMRI suggest that the default state of the cortex is critical, manifested by spontaneous, scale-invariant, cascades of activity known as neuronal avalanches. Criticality keeps a network poised for optimal information processing, but this view seems to be difficult to reconcile with apparently irregular single neuron spiking. Here, we simulate a 10,000 neuron, deterministic, plastic network of spiking neurons. We show that a combination of short- and long-term synaptic plasticity enables these networks to exhibit criticality in the face of intrinsic, i.e. self-sustained, asynchronous spiking. Brief external perturbations lead to adaptive, long-term modification of intrinsic network connectivity through long-term excitatory plasticity, whereas long-term inhibitory plasticity enables rapid self-tuning of the network back to a critical state. The critical state is characterized by a branching parameter oscillating around unity, a critical exponent close to -3/2 and a long tail distribution of a self-similarity parameter between 0.5 and 1. PMID:25590427

High-yield in vitro recordings from neurons functionally characterized in vivo.

PubMed

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.

On the performance of voltage stepping for the simulation of adaptive, nonlinear integrate-and-fire neuronal networks.

PubMed

Kaabi, Mohamed Ghaith; Tonnelier, Arnaud; Martinez, Dominique

2011-05-01

In traditional event-driven strategies, spike timings are analytically given or calculated with arbitrary precision (up to machine precision). Exact computation is possible only for simplified neuron models, mainly the leaky integrate-and-fire model. In a recent paper, Zheng, Tonnelier, and Martinez (2009) introduced an approximate event-driven strategy, named voltage stepping, that allows the generic simulation of nonlinear spiking neurons. Promising results were achieved in the simulation of single quadratic integrate-and-fire neurons. Here, we assess the performance of voltage stepping in network simulations by considering more complex neurons (quadratic integrate-and-fire neurons with adaptation) coupled with multiple synapses. To handle the discrete nature of synaptic interactions, we recast voltage stepping in a general framework, the discrete event system specification. The efficiency of the method is assessed through simulations and comparisons with a modified time-stepping scheme of the Runge-Kutta type. We demonstrated numerically that the original order of voltage stepping is preserved when simulating connected spiking neurons, independent of the network activity and connectivity.

Role of mechanical cues in shaping neuronal morphology and connectivity.

PubMed

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.

A gustatory second-order neuron that connects sucrose-sensitive primary neurons and a distinct region of the gnathal ganglion in the Drosophila brain

PubMed Central

Miyazaki, Takaaki; Lin, Tzu-Yang; Ito, Kei; Lee, Chi-Hon; Stopfer, Mark

2016-01-01

Although the gustatory system provides animals with sensory cues important for food choice and other critical behaviors, little is known about neural circuitry immediately following gustatory sensory neurons (GSNs). Here, we identify and characterize a bilateral pair of gustatory second-order neurons in Drosophila. Previous studies identified GSNs that relay taste information to distinct subregions of the primary gustatory center (PGC) in the gnathal ganglia (GNG). To identify candidate gustatory second-order neurons (G2Ns) we screened ~5,000 GAL4 driver strains for lines that label neural fibers innervating the PGC. We then combined GRASP (GFP reconstitution across synaptic partners) with presynaptic labeling to visualize potential synaptic contacts between the dendrites of the candidate G2Ns and the axonal terminals of Gr5a-expressing GSNs, which are known to respond to sucrose. Results of the GRASP analysis, followed by a single cell analysis by FLPout recombination, revealed a pair of neurons that contact Gr5a axon terminals in both brain hemispheres, and send axonal arborizations to a distinct region outside the PGC but within the GNG. To characterize the input and output branches, respectively, we expressed fluorescence-tagged acetylcholine receptor subunit (Dα7) and active-zone marker (Brp) in the G2Ns. We found that G2N input sites overlaid GRASP-labeled synaptic contacts to Gr5a neurons, while presynaptic sites were broadly distributed throughout the neurons’ arborizations. GRASP analysis and further tests with the Syb-GRASP method suggested that the identified G2Ns receive synaptic inputs from Gr5a-expressing GSNs, but not Gr66a-expressing GSNs, which respond to caffeine. The identified G2Ns relay information from Gr5a-expressing GSNs to distinct regions in the GNG, and are distinct from other, recently identified gustatory projection neurons, which relay information about sugars to a brain region called the antennal mechanosensory and motor center (AMMC). Our findings suggest unexpected complexity for taste information processing in the first relay of the gustatory system. PMID:26004543

Neuronal modelling of baroreflex response to orthostatic stress

NASA Astrophysics Data System (ADS)

Samin, Azfar

The accelerations experienced in aerial combat can cause pilot loss of consciousness (GLOC) due to a critical reduction in cerebral blood circulation. The development of smart protective equipment requires understanding of how the brain processes blood pressure (BP) information in response to acceleration. We present a biologically plausible model of the Baroreflex to investigate the neural correlates of short-term BP control under acceleration or orthostatic stress. The neuronal network model, which employs an integrate-and-fire representation of a biological neuron, comprises the sensory, motor, and the central neural processing areas that form the Baroreflex. Our modelling strategy is to test hypotheses relating to the encoding mechanisms of multiple sensory inputs to the nucleus tractus solitarius (NTS), the site of central neural processing. The goal is to run simulations and reproduce model responses that are consistent with the variety of available experimental data. Model construction and connectivity are inspired by the available anatomical and neurophysiological evidence that points to a barotopic organization in the NTS, and the presence of frequency-dependent synaptic depression, which provides a mechanism for generating non-linear local responses in NTS neurons that result in quantifiable dynamic global baroreflex responses. The entire physiological range of BP and rate of change of BP variables is encoded in a palisade of NTS neurons in that the spike responses approximate Gaussian 'tuning' curves. An adapting weighted-average decoding scheme computes the motor responses and a compensatory signal regulates the heart rate (HR). Model simulations suggest that: (1) the NTS neurons can encode the hydrostatic pressure difference between two vertically separated sensory receptor regions at +Gz, and use changes in that difference for the regulation of HR; (2) even though NTS neurons do not fire with a cardiac rhythm seen in the afferents, pulse-rhythmic activity is regained downstream provided the input phase information in preserved centrally; (3) frequency-dependent synaptic depression, which causes temporal variations in synaptic strength due to changes in input frequency, is a possible mechanism of non-linear dynamic baroreflex gain control. Synaptic depression enables the NTS neuron to encode dBP/dt but to lose information about the steady state firing of the afferents.

A gustatory second-order neuron that connects sucrose-sensitive primary neurons and a distinct region of the gnathal ganglion in the Drosophila brain.

PubMed

Miyazaki, Takaaki; Lin, Tzu-Yang; Ito, Kei; Lee, Chi-Hon; Stopfer, Mark

2015-01-01

Although the gustatory system provides animals with sensory cues important for food choice and other critical behaviors, little is known about neural circuitry immediately following gustatory sensory neurons (GSNs). Here, we identify and characterize a bilateral pair of gustatory second-order neurons (G2Ns) in Drosophila. Previous studies identified GSNs that relay taste information to distinct subregions of the primary gustatory center (PGC) in the gnathal ganglia (GNG). To identify candidate G2Ns, we screened ∼5,000 GAL4 driver strains for lines that label neural fibers innervating the PGC. We then combined GRASP (GFP reconstitution across synaptic partners) with presynaptic labeling to visualize potential synaptic contacts between the dendrites of the candidate G2Ns and the axonal terminals of Gr5a-expressing GSNs, which are known to respond to sucrose. Results of the GRASP analysis, followed by a single-cell analysis by FLP-out recombination, revealed a pair of neurons that contact Gr5a axon terminals in both brain hemispheres and send axonal arborizations to a distinct region outside the PGC but within the GNG. To characterize the input and output branches, respectively, we expressed fluorescence-tagged acetylcholine receptor subunit (Dα7) and active-zone marker (Brp) in the G2Ns. We found that G2N input sites overlaid GRASP-labeled synaptic contacts to Gr5a neurons, while presynaptic sites were broadly distributed throughout the neurons' arborizations. GRASP analysis and further tests with the Syb-GRASP method suggested that the identified G2Ns receive synaptic inputs from Gr5a-expressing GSNs, but not Gr66a-expressing GSNs, which respond to caffeine. The identified G2Ns relay information from Gr5a-expressing GSNs to distinct regions in the GNG, and are distinct from other, recently identified gustatory projection neurons, which relay information about sugars to a brain region called the antennal mechanosensory and motor center (AMMC). Our findings suggest unexpected complexity for taste information processing in the first relay of the gustatory system.

Synapse Specificity of Long-Term Potentiation Breaks Down with Aging

ERIC Educational Resources Information Center

Ris, Laurence; Godaux, Emile

2007-01-01

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

Surface Expression of NMDA Receptor Changes during Memory Consolidation in the Crab "Neohelice granulata"

ERIC Educational Resources Information Center

Hepp, Yanil; Salles, Angeles; Carbo-Tano, Martin; Pedreira, Maria Eugenia; Freudenthal, Ramiro

2016-01-01

The aim of the present study was to analyze the surface expression of the NMDA-like receptors during the consolidation of contextual learning in the crab "Neohelice granulata". Memory storage is based on alterations in the strength of synaptic connections between neurons. The glutamatergic synapses undergo various forms of…

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

DTIC Science & Technology

2013-06-06

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

Neurons on the couch.

PubMed

Marić, Nadja P; Jašović-Gašić, Miroslava

2010-12-01

A hundred years after psychoanalysis was introduced, neuroscience has taken a giant step forward. It seems nowadays that effects of psychotherapy could be monitored and measured by state-of-the art brain imaging techniques. Today, the psychotherapy is considered as a strategic and purposeful environmental influence intended to enhance learning. Since gene expression is regulated by environmental influences throughout life and these processes create brain architecture and influence the strength of synaptic connections, psychotherapy (as a kind of learning) should be explored in the context of aforementioned paradigm. In other words, when placing a client on the couch, therapist actually placed client's neuronal network; while listening and talking, expressing and analyzing, experiencing transference and counter transference, therapist tends to stabilize synaptic connections and influence dendritic growth by regulating gene-transcriptional activity. Therefore, we strongly believe that, in the near future, an increasing knowledge on cellular and molecular interactions and mechanisms of action of different psycho- and pharmaco-therapeutic procedures will enable us to tailor a sophisticated therapeutic approach toward a person, by combining major therapeutic strategies in psychiatry on the basis of rational goals and evidence-based therapeutic expectations.

A new simple /spl infin/OH neuron model as a biologically plausible principal component analyzer.

PubMed

Jankovic, M V

2003-01-01

A new approach to unsupervised learning in a single-layer neural network is discussed. An algorithm for unsupervised learning based upon the Hebbian learning rule is presented. A simple neuron model is analyzed. A dynamic neural model, which contains both feed-forward and feedback connections between the input and the output, has been adopted. The, proposed learning algorithm could be more correctly named self-supervised rather than unsupervised. The solution proposed here is a modified Hebbian rule, in which the modification of the synaptic strength is proportional not to pre- and postsynaptic activity, but instead to the presynaptic and averaged value of postsynaptic activity. It is shown that the model neuron tends to extract the principal component from a stationary input vector sequence. Usually accepted additional decaying terms for the stabilization of the original Hebbian rule are avoided. Implementation of the basic Hebbian scheme would not lead to unrealistic growth of the synaptic strengths, thanks to the adopted network structure.

GABA Neurons and the Mechanisms of Network Oscillations: Implications for Understanding Cortical Dysfunction in Schizophrenia

PubMed Central

Gonzalez-Burgos, Guillermo; Lewis, David A.

2008-01-01

Synchronization of neuronal activity in the neocortex may underlie the coordination of neural representations and thus is critical for optimal cognitive function. Because cognitive deficits are the major determinant of functional outcome in schizophrenia, identifying their neural basis is important for the development of new therapeutic interventions. Here we review the data suggesting that phasic synaptic inhibition mediated by specific subtypes of cortical γ-aminobutyric acid (GABA) neurons is essential for the production of synchronized network oscillations. We also discuss evidence indicating that GABA neurotransmission is altered in schizophrenia and propose mechanisms by which such alterations can decrease the strength of inhibitory connections in a cell-type–specific manner. We suggest that some alterations observed in the neocortex of schizophrenia subjects may be compensatory responses that partially restore inhibitory synaptic efficacy. The findings of altered neural synchrony and impaired cognitive function in schizophrenia suggest that such compensatory responses are insufficient and that interventions aimed at augmenting the efficacy of GABA neurotransmission might be of therapeutic value. PMID:18586694

GABA neurons and the mechanisms of network oscillations: implications for understanding cortical dysfunction in schizophrenia.

PubMed

Gonzalez-Burgos, Guillermo; Lewis, David A

2008-09-01

Synchronization of neuronal activity in the neocortex may underlie the coordination of neural representations and thus is critical for optimal cognitive function. Because cognitive deficits are the major determinant of functional outcome in schizophrenia, identifying their neural basis is important for the development of new therapeutic interventions. Here we review the data suggesting that phasic synaptic inhibition mediated by specific subtypes of cortical gamma-aminobutyric acid (GABA) neurons is essential for the production of synchronized network oscillations. We also discuss evidence indicating that GABA neurotransmission is altered in schizophrenia and propose mechanisms by which such alterations can decrease the strength of inhibitory connections in a cell-type-specific manner. We suggest that some alterations observed in the neocortex of schizophrenia subjects may be compensatory responses that partially restore inhibitory synaptic efficacy. The findings of altered neural synchrony and impaired cognitive function in schizophrenia suggest that such compensatory responses are insufficient and that interventions aimed at augmenting the efficacy of GABA neurotransmission might be of therapeutic value.

Quantitation of Contacts Among Sensory, Motor, and Serotonergic Neurons in the Pedal Ganglion of Aplysia

PubMed Central

Zhang, Han; Wainwright, Marcy; Byrne, John H.; Cleary, Leonard J.

2003-01-01

Present models of long-term sensitization in Aplysia californica indicate that the enhanced behavioral response is due, at least in part, to outgrowth of sensory neurons mediating defensive withdrawal reflexes. Presumably, this outgrowth strengthens pre-existing connections by formation of newsynapses with follower neurons. However, the relationship between the number of sensorimotor contacts and the physiological strength of the connection has never been examined in intact ganglia. As a first step in addressing this issue, we used confocal microscopy to examine sites of contact between sensory and motor neurons in naive animals. Our results revealed relatively fewcontacts between physiologically connected cells. In addition, the number of contact sites was proportional to the amplitude of the EPSP elicited in the follower motor neuron by direct stimulation of the sensory neuron. This is the first time such a correlation has been observed in the central nervous system. Serotonin is the neurotransmitter most closely examined for its role in modulating synaptic strength at the sensorimotor synapse. However, the structural relationship of serotonergic processes and sensorimotor synapses has never been examined. Surprisingly, serotonergic processes usually made contact with sensory and motor neurons at sites located relatively distant from the sensorimotor synapse. This result implies that heterosynaptic regulation is due to nondirected release of serotonin into the neuropil. PMID:14557611

Excitatory signal flow and connectivity in a cortical column: focus on barrel cortex.

PubMed

Lübke, Joachim; Feldmeyer, Dirk

2007-07-01

A basic feature of the neocortex is its organization in functional, vertically oriented columns, recurring modules of signal processing and a system of transcolumnar long-range horizontal connections. These columns, together with their network of neurons, present in all sensory cortices, are the cellular substrate for sensory perception in the brain. Cortical columns contain thousands of neurons and span all cortical layers. They receive input from other cortical areas and subcortical brain regions and in turn their neurons provide output to various areas of the brain. The modular concept presumes that the neuronal network in a cortical column performs basic signal transformations, which are then integrated with the activity in other networks and more extended brain areas. To understand how sensory signals from the periphery are transformed into electrical activity in the neocortex it is essential to elucidate the spatial-temporal dynamics of cortical signal processing and the underlying neuronal 'microcircuits'. In the last decade the 'barrel' field in the rodent somatosensory cortex, which processes sensory information arriving from the mysticial vibrissae, has become a quite attractive model system because here the columnar structure is clearly visible. In the neocortex and in particular the barrel cortex, numerous neuronal connections within or between cortical layers have been studied both at the functional and structural level. Besides similarities, clear differences with respect to both physiology and morphology of synaptic transmission and connectivity were found. It is therefore necessary to investigate each neuronal connection individually, in order to develop a realistic model of neuronal connectivity and organization of a cortical column. This review attempts to summarize recent advances in the study of individual microcircuits and their functional relevance within the framework of a cortical column, with emphasis on excitatory signal flow.

Contributions of Bcl-xL to acute and long term changes in bioenergetics during neuronal plasticity.

PubMed

Jonas, Elizabeth A

2014-08-01

Mitochondria manufacture and release metabolites and manage calcium during neuronal activity and synaptic transmission, but whether long term alterations in mitochondrial function contribute to the neuronal plasticity underlying changes in organism behavior patterns is still poorly understood. Although normal neuronal plasticity may determine learning, in contrast a persistent decline in synaptic strength or neuronal excitability may portend neurite retraction and eventual somatic death. Anti-death proteins such as Bcl-xL not only provide neuroprotection at the neuronal soma during cell death stimuli, but also appear to enhance neurotransmitter release and synaptic growth and development. It is proposed that Bcl-xL performs these functions through its ability to regulate mitochondrial release of bioenergetic metabolites and calcium, and through its ability to rapidly alter mitochondrial positioning and morphology. Bcl-xL also interacts with proteins that directly alter synaptic vesicle recycling. Bcl-xL translocates acutely to sub-cellular membranes during neuronal activity to achieve changes in synaptic efficacy. After stressful stimuli, pro-apoptotic cleaved delta N Bcl-xL (ΔN Bcl-xL) induces mitochondrial ion channel activity leading to synaptic depression and this is regulated by caspase activation. During physiological states of decreased synaptic stimulation, loss of mitochondrial Bcl-xL and low level caspase activation occur prior to the onset of long term decline in synaptic efficacy. The degree to which Bcl-xL changes mitochondrial membrane permeability may control the direction of change in synaptic strength. The small molecule Bcl-xL inhibitor ABT-737 has been useful in defining the role of Bcl-xL in synaptic processes. Bcl-xL is crucial to the normal health of neurons and synapses and its malfunction may contribute to neurodegenerative disease. Copyright © 2013. Published by Elsevier B.V.

Rich-Club Organization in Effective Connectivity among Cortical Neurons.

PubMed

Nigam, Sunny; Shimono, Masanori; Ito, Shinya; Yeh, Fang-Chin; Timme, Nicholas; Myroshnychenko, Maxym; Lapish, Christopher C; Tosi, Zachary; Hottowy, Pawel; Smith, Wesley C; Masmanidis, Sotiris C; Litke, Alan M; Sporns, Olaf; Beggs, John M

2016-01-20

The performance of complex networks, like the brain, depends on how effectively their elements communicate. Despite the importance of communication, it is virtually unknown how information is transferred in local cortical networks, consisting of hundreds of closely spaced neurons. To address this, it is important to record simultaneously from hundreds of neurons at a spacing that matches typical axonal connection distances, and at a temporal resolution that matches synaptic delays. We used a 512-electrode array (60 μm spacing) to record spontaneous activity at 20 kHz from up to 500 neurons simultaneously in slice cultures of mouse somatosensory cortex for 1 h at a time. We applied a previously validated version of transfer entropy to quantify information transfer. Similar to in vivo reports, we found an approximately lognormal distribution of firing rates. Pairwise information transfer strengths also were nearly lognormally distributed, similar to reports of synaptic strengths. Some neurons transferred and received much more information than others, which is consistent with previous predictions. Neurons with the highest outgoing and incoming information transfer were more strongly connected to each other than chance, thus forming a "rich club." We found similar results in networks recorded in vivo from rodent cortex, suggesting the generality of these findings. A rich-club structure has been found previously in large-scale human brain networks and is thought to facilitate communication between cortical regions. The discovery of a small, but information-rich, subset of neurons within cortical regions suggests that this population will play a vital role in communication, learning, and memory. Significance statement: Many studies have focused on communication networks between cortical brain regions. In contrast, very few studies have examined communication networks within a cortical region. This is the first study to combine such a large number of neurons (several hundred at a time) with such high temporal resolution (so we can know the direction of communication between neurons) for mapping networks within cortex. We found that information was not transferred equally through all neurons. Instead, ∼70% of the information passed through only 20% of the neurons. Network models suggest that this highly concentrated pattern of information transfer would be both efficient and robust to damage. Therefore, this work may help in understanding how the cortex processes information and responds to neurodegenerative diseases. Copyright © 2016 Nigam et al.

Rich-Club Organization in Effective Connectivity among Cortical Neurons

PubMed Central

Shimono, Masanori; Ito, Shinya; Yeh, Fang-Chin; Timme, Nicholas; Myroshnychenko, Maxym; Lapish, Christopher C.; Tosi, Zachary; Hottowy, Pawel; Smith, Wesley C.; Masmanidis, Sotiris C.; Litke, Alan M.; Sporns, Olaf; Beggs, John M.

2016-01-01

The performance of complex networks, like the brain, depends on how effectively their elements communicate. Despite the importance of communication, it is virtually unknown how information is transferred in local cortical networks, consisting of hundreds of closely spaced neurons. To address this, it is important to record simultaneously from hundreds of neurons at a spacing that matches typical axonal connection distances, and at a temporal resolution that matches synaptic delays. We used a 512-electrode array (60 μm spacing) to record spontaneous activity at 20 kHz from up to 500 neurons simultaneously in slice cultures of mouse somatosensory cortex for 1 h at a time. We applied a previously validated version of transfer entropy to quantify information transfer. Similar to in vivo reports, we found an approximately lognormal distribution of firing rates. Pairwise information transfer strengths also were nearly lognormally distributed, similar to reports of synaptic strengths. Some neurons transferred and received much more information than others, which is consistent with previous predictions. Neurons with the highest outgoing and incoming information transfer were more strongly connected to each other than chance, thus forming a “rich club.” We found similar results in networks recorded in vivo from rodent cortex, suggesting the generality of these findings. A rich-club structure has been found previously in large-scale human brain networks and is thought to facilitate communication between cortical regions. The discovery of a small, but information-rich, subset of neurons within cortical regions suggests that this population will play a vital role in communication, learning, and memory. SIGNIFICANCE STATEMENT Many studies have focused on communication networks between cortical brain regions. In contrast, very few studies have examined communication networks within a cortical region. This is the first study to combine such a large number of neurons (several hundred at a time) with such high temporal resolution (so we can know the direction of communication between neurons) for mapping networks within cortex. We found that information was not transferred equally through all neurons. Instead, ∼70% of the information passed through only 20% of the neurons. Network models suggest that this highly concentrated pattern of information transfer would be both efficient and robust to damage. Therefore, this work may help in understanding how the cortex processes information and responds to neurodegenerative diseases. PMID:26791200

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.

Remodeling Functional Connectivity in Multiple Sclerosis: A Challenging Therapeutic Approach.

PubMed

Stampanoni Bassi, Mario; Gilio, Luana; Buttari, Fabio; Maffei, Pierpaolo; Marfia, Girolama A; Restivo, Domenico A; Centonze, Diego; Iezzi, Ennio

2017-01-01

Neurons in the central nervous system are organized in functional units interconnected to form complex networks. Acute and chronic brain damage disrupts brain connectivity producing neurological signs and/or symptoms. In several neurological diseases, particularly in Multiple Sclerosis (MS), structural imaging studies cannot always demonstrate a clear association between lesion site and clinical disability, originating the "clinico-radiological paradox." The discrepancy between structural damage and disability can be explained by a complex network perspective. Both brain networks architecture and synaptic plasticity may play important roles in modulating brain networks efficiency after brain damage. In particular, long-term potentiation (LTP) may occur in surviving neurons to compensate network disconnection. In MS, inflammatory cytokines dramatically interfere with synaptic transmission and plasticity. Importantly, in addition to acute and chronic structural damage, inflammation could contribute to reduce brain networks efficiency in MS leading to worse clinical recovery after a relapse and worse disease progression. These evidence suggest that removing inflammation should represent the main therapeutic target in MS; moreover, as synaptic plasticity is particularly altered by inflammation, specific strategies aimed at promoting LTP mechanisms could be effective for enhancing clinical recovery. Modulation of plasticity with different non-invasive brain stimulation (NIBS) techniques has been used to promote recovery of MS symptoms. Better knowledge of features inducing brain disconnection in MS is crucial to design specific strategies to promote recovery and use NIBS with an increasingly tailored approach.

Dscam2 mediates axonal tiling in the Drosophila visual system

PubMed Central

Millard, S. Sean; Flanagan, John J.; Pappu, Kartik S.; Wu, Wei; Zipursky, S. Lawrence

2009-01-01

Sensory processing centres in both the vertebrate and the invertebrate brain are often organized into reiterated columns, thus facilitating an internal topographic representation of the external world. Cells within each column are arranged in a stereotyped fashion and form precise patterns of synaptic connections within discrete layers. These connections are largely confined to a single column, thereby preserving the spatial information from the periphery. Other neurons integrate this information by connecting to multiple columns. Restricting axons to columns is conceptually similar to tiling. Axons and dendrites of neighbouring neurons of the same class use tiling to form complete, yet non-overlapping, receptive fields1-3. It is thought that, at the molecular level, cell-surface proteins mediate tiling through contact-dependent repulsive interactions1,2,4,5, but proteins serving this function have not yet been identified. Here we show that the immunoglobulin superfamily member Dscam2 restricts the connections formed by L1 lamina neurons to columns in the Drosophila visual system. Our data support a model in which Dscam2 homophilic interactions mediate repulsion between neurites of L1 cells in neighbouring columns. We propose that Dscam2 is a tiling receptor for L1 neurons. PMID:17554308

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.

Decrease of SYNGAP1 in GABAergic cells impairs inhibitory synapse connectivity, synaptic inhibition and cognitive function

PubMed Central

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

Physiological Concentrations of Amyloid Beta Regulate Recycling of Synaptic Vesicles via Alpha7 Acetylcholine Receptor and CDK5/Calcineurin Signaling

PubMed Central

Lazarevic, Vesna; Fieńko, Sandra; Andres-Alonso, Maria; Anni, Daniela; Ivanova, Daniela; Montenegro-Venegas, Carolina; Gundelfinger, Eckart D.; Cousin, Michael A.; Fejtova, Anna

2017-01-01

Despite the central role of amyloid β (Aβ) peptide in the etiopathogenesis of Alzheimer’s disease (AD), its physiological function in healthy brain is still debated. It is well established that elevated levels of Aβ induce synaptic depression and dismantling, connected with neurotoxicity and neuronal loss. Growing evidence suggests a positive regulatory effect of Aβ on synaptic function and cognition; however the exact cellular and molecular correlates are still unclear. In this work, we tested the effect of physiological concentrations of Aβ species of endogenous origin on neurotransmitter release in rat cortical and hippocampal neurons grown in dissociated cultures. Modulation of production and degradation of the endogenous Aβ species as well as applications of the synthetic rodent Aβ40 and Aβ42 affected efficacy of neurotransmitter release from individual presynapses. Low picomolar Aβ40 and Aβ42 increased, while Aβ depletion or application of low micromolar concentration decreased synaptic vesicle recycling, showing a hormetic effect of Aβ on neurotransmitter release. These Aβ-mediated modulations required functional alpha7 acetylcholine receptors as well as extracellular and intracellular calcium, involved regulation of CDK5 and calcineurin signaling and increased recycling of synaptic vesicles. These data indicate that Aβ regulates neurotransmitter release from presynapse and suggest that failure of the normal physiological function of Aβ in the fine-tuning of SV cycling could disrupt synaptic function and homeostasis, which would, eventually, lead to cognitive decline and neurodegeneration. PMID:28785201

Untangling Basal Ganglia Network Dynamics and Function: Role of Dopamine Depletion and Inhibition Investigated in a Spiking Network Model

PubMed Central

2016-01-01

Abstract The basal ganglia are a crucial brain system for behavioral selection, and their function is disturbed in Parkinson’s disease (PD), where neurons exhibit inappropriate synchronization and oscillations. We present a spiking neural model of basal ganglia including plausible details on synaptic dynamics, connectivity patterns, neuron behavior, and dopamine effects. Recordings of neuronal activity in the subthalamic nucleus and Type A (TA; arkypallidal) and Type I (TI; prototypical) neurons in globus pallidus externa were used to validate the model. Simulation experiments predict that both local inhibition in striatum and the existence of an indirect pathway are important for basal ganglia to function properly over a large range of cortical drives. The dopamine depletion–induced increase of AMPA efficacy in corticostriatal synapses to medium spiny neurons (MSNs) with dopamine receptor D2 synapses (CTX-MSN D2) and the reduction of MSN lateral connectivity (MSN–MSN) were found to contribute significantly to the enhanced synchrony and oscillations seen in PD. Additionally, reversing the dopamine depletion–induced changes to CTX–MSN D1, CTX–MSN D2, TA–MSN, and MSN–MSN couplings could improve or restore basal ganglia action selection ability. In summary, we found multiple changes of parameters for synaptic efficacy and neural excitability that could improve action selection ability and at the same time reduce oscillations. Identification of such targets could potentially generate ideas for treatments of PD and increase our understanding of the relation between network dynamics and network function. PMID:28101525

Synaptic dynamics contribute to long-term single neuron response fluctuations.

PubMed

Reinartz, Sebastian; Biro, Istvan; Gal, Asaf; Giugliano, Michele; Marom, Shimon

2014-01-01

Firing rate variability at the single neuron level is characterized by long-memory processes and complex statistics over a wide range of time scales (from milliseconds up to several hours). Here, we focus on the contribution of non-stationary efficacy of the ensemble of synapses-activated in response to a given stimulus-on single neuron response variability. We present and validate a method tailored for controlled and specific long-term activation of a single cortical neuron in vitro via synaptic or antidromic stimulation, enabling a clear separation between two determinants of neuronal response variability: membrane excitability dynamics vs. synaptic dynamics. Applying this method we show that, within the range of physiological activation frequencies, the synaptic ensemble of a given neuron is a key contributor to the neuronal response variability, long-memory processes and complex statistics observed over extended time scales. Synaptic transmission dynamics impact on response variability in stimulation rates that are substantially lower compared to stimulation rates that drive excitability resources to fluctuate. Implications to network embedded neurons are discussed.

Epigenetic Basis of Neuronal and Synaptic Plasticity.

PubMed

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

2017-01-01

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

Spontaneous network activity and synaptic development

PubMed Central

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

PTEN regulation of local and long-range connections in mouse auditory cortex.

PubMed

Xiong, Qiaojie; Oviedo, Hysell V; Trotman, Lloyd C; Zador, Anthony M

2012-02-01

Autism spectrum disorders (ASDs) are highly heritable developmental disorders caused by a heterogeneous collection of genetic lesions. Here we use a mouse model to study the effect on cortical connectivity of disrupting the ASD candidate gene PTEN (phosphatase and tensin homolog deleted on chromosome 10). Through Cre-mediated recombination, we conditionally knocked out PTEN expression in a subset of auditory cortical neurons. Analysis of long-range connectivity using channelrhodopsin-2 revealed that the strength of synaptic inputs from both the contralateral auditory cortex and from the thalamus onto PTEN-cko neurons was enhanced compared with nearby neurons with normal PTEN expression. Laser-scanning photostimulation showed that local inputs onto PTEN-cko neurons in the auditory cortex were similarly enhanced. The hyperconnectivity caused by PTEN-cko could be blocked by rapamycin, a specific inhibitor of the PTEN downstream molecule mammalian target of rapamycin complex 1. Together, our results suggest that local and long-range hyperconnectivity may constitute a physiological basis for the effects of mutations in PTEN and possibly other ASD candidate genes.

Developmentally regulated switch in alternatively spliced SNAP-25 isoforms alters facilitation of synaptic transmission.

PubMed

Bark, Christina; Bellinger, Frederick P; Kaushal, Ashutosh; Mathews, James R; Partridge, L Donald; Wilson, Michael C

2004-10-06

Although the basic molecular components that promote regulated neurotransmitter release are well established, the contribution of these proteins as regulators of the plasticity of neurotransmission and refinement of synaptic connectivity during development is elaborated less fully. For example, during the period of synaptic growth and maturation in brain, the expression of synaptosomal protein 25 kDa (SNAP-25), a neuronal t-SNARE (soluble N-ethylmaleimide-sensitive factor attachment protein receptor) essential for action potential-dependent neuroexocytosis, is altered through alternative splicing of pre-mRNA transcripts. We addressed the role of the two splice-variant isoforms of SNAP-25 with a targeted mouse mutation that impairs the shift from SNAP-25a to SNAP-25b. Most of these mutant mice die between 3 and 5 weeks of age, which coincides with the time when SNAP-25b expression normally reaches mature levels in brain and synapse formation is essentially completed. The altered expression of these SNAP-25 isoforms influences short-term synaptic function by affecting facilitation but not the initial probability of release. This suggests that mechanisms controlling alternative splicing between SNAP-25 isoforms contribute to a molecular switch important for survival that helps to guide the transition from immature to mature synaptic connections, as well as synapse regrowth and remodeling after neural injury.

Low excitatory innervation balances high intrinsic excitability of immature dentate neurons

PubMed Central

Dieni, Cristina V.; Panichi, Roberto; Aimone, James B.; Kuo, Chay T.; Wadiche, Jacques I.; Overstreet-Wadiche, Linda

2016-01-01

Persistent neurogenesis in the dentate gyrus produces immature neurons with high intrinsic excitability and low levels of inhibition that are predicted to be more broadly responsive to afferent activity than mature neurons. Mounting evidence suggests that these immature neurons are necessary for generating distinct neural representations of similar contexts, but it is unclear how broadly responsive neurons help distinguish between similar patterns of afferent activity. Here we show that stimulation of the entorhinal cortex in mouse brain slices paradoxically generates spiking of mature neurons in the absence of immature neuron spiking. Immature neurons with high intrinsic excitability fail to spike due to insufficient excitatory drive that results from low innervation rather than silent synapses or low release probability. Our results suggest that low synaptic connectivity prevents immature neurons from responding broadly to cortical activity, potentially enabling excitable immature neurons to contribute to sparse and orthogonal dentate representations. PMID:27095423

Low excitatory innervation balances high intrinsic excitability of immature dentate neurons

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

Dieni, Cristina V.; Panichi, Roberto; Aimone, James B.

Persistent neurogenesis in the dentate gyrus produces immature neurons with high intrinsic excitability and low levels of inhibition that are predicted to be more broadly responsive to afferent activity than mature neurons. Mounting evidence suggests that these immature neurons are necessary for generating distinct neural representations of similar contexts, but it is unclear how broadly responsive neurons help distinguish between similar patterns of afferent activity. Here we show that stimulation of the entorhinal cortex in mouse brain slices paradoxically generates spiking of mature neurons in the absence of immature neuron spiking. Immature neurons with high intrinsic excitability fail to spikemore » due to insufficient excitatory drive that results from low innervation rather than silent synapses or low release probability. Here, our results suggest that low synaptic connectivity prevents immature neurons from responding broadly to cortical activity, potentially enabling excitable immature neurons to contribute to sparse and orthogonal dentate representations.« less

Low excitatory innervation balances high intrinsic excitability of immature dentate neurons

DOE PAGES

Dieni, Cristina V.; Panichi, Roberto; Aimone, James B.; ...

2016-04-20

Persistent neurogenesis in the dentate gyrus produces immature neurons with high intrinsic excitability and low levels of inhibition that are predicted to be more broadly responsive to afferent activity than mature neurons. Mounting evidence suggests that these immature neurons are necessary for generating distinct neural representations of similar contexts, but it is unclear how broadly responsive neurons help distinguish between similar patterns of afferent activity. Here we show that stimulation of the entorhinal cortex in mouse brain slices paradoxically generates spiking of mature neurons in the absence of immature neuron spiking. Immature neurons with high intrinsic excitability fail to spikemore » due to insufficient excitatory drive that results from low innervation rather than silent synapses or low release probability. Here, our results suggest that low synaptic connectivity prevents immature neurons from responding broadly to cortical activity, potentially enabling excitable immature neurons to contribute to sparse and orthogonal dentate representations.« less

The spiral ganglion: connecting the peripheral and central auditory systems

PubMed Central

Nayagam, Bryony A; Muniak, Michael A; Ryugo, David K

2011-01-01

In mammals, the initial bridge between the physical world of sound and perception of that sound is established by neurons of the spiral ganglion. The cell bodies of these neurons give rise to peripheral processes that contact acoustic receptors in the organ of Corti, and the central processes collect together to form the auditory nerve that projects into the brain. In order to better understand hearing at this initial stage, we need to know the following about spiral ganglion neurons: (1) their cell biology including cytoplasmic, cytoskeletal, and membrane properties, (2) their peripheral and central connections including synaptic structure; (3) the nature of their neural signaling; and (4) their capacity for plasticity and rehabilitation. In this report, we will update the progress on these topics and indicate important issues still awaiting resolution. PMID:21530629

Late onset deficits in synaptic plasticity in the valproic acid rat model of autism.

PubMed

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.

Ultrastructure of spines and associated terminals on brainstem neurons controlling auditory input

PubMed Central

Brown, M. Christian; Lee, Daniel J.; Benson, Thane E.

2013-01-01

Spines are unique cellular appendages that isolate synaptic input to neurons and play a role in synaptic plasticity. Using the electron microscope, we studied spines and their associated synaptic terminals on three groups of brainstem neurons: tensor tympani motoneurons, stapedius motoneurons, and medial olivocochlear neurons, all of which exert reflexive control of processes in the auditory periphery. These spines are generally simple in shape; they are infrequent and found on the somata as well as the dendrites. Spines do not differ in volume among the three groups of neurons. In all cases, the spines are associated with a synaptic terminal that engulfs the spine rather than abuts its head. The positions of the synapses are variable, and some are found at a distance from the spine, suggesting that the isolation of synaptic input is of diminished importance for these spines. Each group of neurons receives three common types of synaptic terminals. The type of terminal associated with spines of the motoneurons contains pleomorphic vesicles, whereas the type associated with spines of olivocochlear neurons contains large round vesicles. Thus, spine-associated terminals in the motoneurons appear to be associated with inhibitory processes but in olivocochlear neurons they are associated with excitatory processes. PMID:23602963

Odors regulate Arc expression in neuronal ensembles engaged in odor processing.

PubMed

Guthrie, K; Rayhanabad, J; Kuhl, D; Gall, C

2000-06-26

Synaptic activity is critical to developmental and plastic processes that produce long-term changes in neuronal connectivity and function. Genes expressed by neurons in an activity-dependent fashion are of particular interest since the proteins they encode may mediate neuronal plasticity. One such gene encodes the activity-regulated cytoskeleton-associated protein, Arc. The present study evaluated the effects of odor stimulation on Arc expression in rat olfactory bulb. Arc mRNA was rapidly increased in functionally linked cohorts of neurons topographically activated by odor stimuli. These included neurons surrounding individual glomeruli, mitral cells and transynaptically activated granule cells. Dendritic Arc immunoreactivity was also increased in odor-activated glomeruli. Our results suggest that odor regulation of Arc expression may contribute to activity-dependent structural changes associated with olfactory experience.

Electronic neuron within a ganglion of a leech (Hirudo medicinalis).

PubMed

Aliaga, J; Busca, N; Minces, V; Mindlin, G B; Pando, B; Salles, A; Sczcupak, L

2003-06-01

We report the construction of an electronic device that models and replaces a neuron in a midbody ganglion of the leech Hirudo medicinalis. In order to test the behavior of our device, we used a well-characterized synaptic interaction between the mechanosensory, sensitive to pressure, (P) cell and the anteropagoda (because of the action potential shape) (AP) neuron. We alternatively stimulated a P neuron and our device connected to the AP neuron, and studied the response of the latter. The number and timing of the AP spikes were the same when the electronic parameters were properly adjusted. Moreover, after changes in the depolarization of the AP cell, the responses under the stimulation of both the biological neuron and the electronic device vary in a similar manner.

Temperature manipulation of neuronal dynamics in a forebrain motor control nucleus

PubMed Central

Mindlin, Gabriel B.

2017-01-01

Different neuronal types within brain motor areas contribute to the generation of complex motor behaviors. A widely studied songbird forebrain nucleus (HVC) has been recognized as fundamental in shaping the precise timing characteristics of birdsong. This is based, among other evidence, on the stretching and the “breaking” of song structure when HVC is cooled. However, little is known about the temperature effects that take place in its neurons. To address this, we investigated the dynamics of HVC both experimentally and computationally. We developed a technique where simultaneous electrophysiological recordings were performed during temperature manipulation of HVC. We recorded spontaneous activity and found three effects: widening of the spike shape, decrease of the firing rate and change in the interspike interval distribution. All these effects could be explained with a detailed conductance based model of all the neurons present in HVC. Temperature dependence of the ionic channel time constants explained the first effect, while the second was based in the changes of the maximal conductance using single synaptic excitatory inputs. The last phenomenon, only emerged after introducing a more realistic synaptic input to the inhibitory interneurons. Two timescales were present in the interspike distributions. The behavior of one timescale was reproduced with different input balances received form the excitatory neurons, whereas the other, which disappears with cooling, could not be found assuming poissonian synaptic inputs. Furthermore, the computational model shows that the bursting of the excitatory neurons arises naturally at normal brain temperature and that they have an intrinsic delay at low temperatures. The same effect occurs at single synapses, which may explain song stretching. These findings shed light on the temperature dependence of neuronal dynamics and present a comprehensive framework to study neuronal connectivity. This study, which is based on intrinsic neuronal characteristics, may help to understand emergent behavioral changes. PMID:28829769

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

PubMed Central

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

2007-01-01

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

The Rich Club of the C. elegans Neuronal Connectome

PubMed Central

Vértes, Petra E.; Ahnert, Sebastian E.; Schafer, William R.; Bullmore, Edward T.

2013-01-01

There is increasing interest in topological analysis of brain networks as complex systems, with researchers often using neuroimaging to represent the large-scale organization of nervous systems without precise cellular resolution. Here we used graph theory to investigate the neuronal connectome of the nematode worm Caenorhabditis elegans, which is defined anatomically at a cellular scale as 2287 synaptic connections between 279 neurons. We identified a small number of highly connected neurons as a rich club (N = 11) interconnected with high efficiency and high connection distance. Rich club neurons comprise almost exclusively the interneurons of the locomotor circuits, with known functional importance for coordinated movement. The rich club neurons are connector hubs, with high betweenness centrality, and many intermodular connections to nodes in different modules. On identifying the shortest topological paths (motifs) between pairs of peripheral neurons, the motifs that are found most frequently traverse the rich club. The rich club neurons are born early in development, before visible movement of the animal and before the main phase of developmental elongation of its body. We conclude that the high wiring cost of the globally integrative rich club of neurons in the C. elegans connectome is justified by the adaptive value of coordinated movement of the animal. The economical trade-off between physical cost and behavioral value of rich club organization in a cellular connectome confirms theoretical expectations and recapitulates comparable results from human neuroimaging on much larger scale networks, suggesting that this may be a general and scale-invariant principle of brain network organization. PMID:23575836

Synaptic Tagging During Memory Allocation

PubMed Central

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

2014-01-01

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

Synaptic Failure: Focus in an Integrative View of ALS

PubMed Central

Casas, Caty; Manzano, Raquel; Vaz, Rita; Osta, Rosario; Brites, Dora

2015-01-01

From early description by Charcot, the classification of the Amyotrophic Lateral Sclerosis (ALS) is evolving from a subtype of Motor Neuron (MN) Disease to be considered rather a multi-systemic, non-cell autonomous and complex neurodegenerative disease. In the last decade, the huge amount of knowledge acquired has shed new insights on the pathological mechanisms underlying ALS from different perspectives. However, a whole vision on the multiple dysfunctional pathways is needed with the inclusion of information often excluded in other published revisions. We propose an integrative view of ALS pathology, although centered on the synaptic failure as a converging and crucial player to the etiology of the disease. Homeostasis of input and output synaptic activity of MNs has been proved to be severely and early disrupted and to definitively contribute to microcircuitry alterations at the spinal cord. Several cells play roles in synaptic communication across the MNs network system such as interneurons, astrocytes, microglia, Schwann and skeletal muscle cells. Microglia are described as highly dynamic surveying cells of the nervous system but also as determinant contributors to the synaptic plasticity linked to neuronal activity. Several signaling axis such as TNFα/TNFR1 and CX3CR1/CX3CL1 that characterize MN-microglia cross talk contribute to synaptic scaling and maintenance, have been found altered in ALS. The presence of dystrophic and atypical microglia in late stages of ALS, with a decline in their dynamic motility and phagocytic ability, together with less synaptic and neuronal contacts disrupts the MN-microglia dialogue, decreases homeostatic regulation of neuronal activity, perturbs “on/off” signals and accelerates disease progression associated to impaired synaptic function and regeneration. Other hotspot in the ALS affected network system is the unstable neuromuscular junction (NMJ) leading to distal axonal degeneration. Reduced neuromuscular spontaneous synaptic activity in ALS mice models was also suggested to account for the selective vulnerability of MNs and decreased regenerative capability. Synaptic destabilization may as well derive from increased release of molecules by muscle cells (e.g. NogoA) and by terminal Schwann cells (e.g. semaphorin 3A) conceivably causing nerve terminal retraction and denervation, as well as inhibition of re-connection to muscle fibers. Indeed, we have overviewed the alterations on the metabolic pathways and self-regenerative capacity presented in skeletal muscle cells that contribute to muscle wasting in ALS. Finally, a detailed footpath of pathologic changes on MNs and associated dysfunctional and synaptic alterations is provided. The oriented motivation in future ALS studies as outlined in the present article will help in fruitful novel achievements on the mechanisms involved and in developing more target-driven therapies that will bring new hope in halting or delaying disease progression in ALS patients. PMID:29765840

Unitary synaptic connections among substantia nigra pars reticulata neurons

PubMed Central

Wilson, Charles J.

2016-01-01

Neurons in substantia nigra pars reticulata (SNr) are synaptically coupled by local axon collaterals, providing a potential mechanism for local signal processing. Because SNr neurons fire spontaneously, these synapses are constantly active. To investigate their properties, we recorded spontaneous inhibitory postsynaptic currents (sIPSCs) from SNr neurons in brain slices, in which afferents from upstream nuclei are severed, and the cells fire rhythmically. The sIPSC trains contained a mixture of periodic and aperiodic events. Autocorrelation analysis of sIPSC trains showed that a majority of cells had one to four active unitary inputs. The properties of the unitary IPSCs (uIPSCs) were analyzed for cells with one unitary input, using a model of periodic presynaptic firing and stochastic synaptic transmission. The inferred presynaptic firing rates and coefficient of variation of interspike intervals (ISIs) corresponded well with direct measurements of spiking in SNr neurons. Methods were developed to estimate the success probability, amplitude distributions, and kinetics of the uIPSCs, while removing the contribution from aperiodic sIPSCs. The sIPSC amplitudes were not increased upon release from halorhodopsin silencing, suggesting that most synapses were not depressed at the spontaneous firing rate. Gramicidin perforated-patch recordings indicated that the average reversal potential of spontaneous inhibitory postsynaptic potentials was −64 mV. Because of the change in driving force across the ISI, the unitary inputs are predicted to have a larger postsynaptic impact when they arrive late in the ISI. Simulations of network activity suggest that this very sparse inhibitory coupling may act to desynchronize the activity of SNr neurons while having only a small effect on firing rate. PMID:26961101

Intrahippocampal Pathways Involved in Learning/Memory Mechanisms are Affected by Intracerebral Infusions of Amyloid-β25-35 Peptide and Hydrated Fullerene C60 in Rats.

PubMed

Gordon, Rita; Podolski, Igor; Makarova, Ekaterina; Deev, Alexander; Mugantseva, Ekaterina; Khutsyan, Sergey; Sengpiel, Frank; Murashev, Arkady; Vorobyov, Vasily

2017-01-01

Primary memory impairments associated with increased level of amyloid-β (Aβ) in the brain have been shown to be linked, partially, with early pathological changes in the entorhinal cortex (EC) which spread on the whole limbic system. While the hippocampus is known to play a key role in learning and memory mechanisms, it is as yet unclear how its structures are involved in the EC pathology. In this study, changes in memory and neuronal morphology in male Wistar rats intrahippocampally injected with Aβ25-35 were correlated on days 14 and 45 after the injection to reveal specific cognitive-structural associations. The main focus was on the dentate gyrus (DG) and hippocampal areas of CA1 and CA3 because of their involvement in afferent flows from EC to the hippocampus through tri-synaptic (EC → DG → CA3 → CA1) and/or mono-synaptic (EC → CA1) pathways. Evident memory impairments were observed at both time points after Aβ25-35 injection. However, on day 14, populations of morphological intact neurons were decreased in CA3 and, drastically, in CA1, and the DG supramedial bundle was significantly damaged. On day 45, this bundle largely and CA1 neurons partially recovered, whereas CA3 neurons remained damaged. We suggest that Aβ25-35 primarily affects the tri-synaptic pathway, destroying the granular cells in the DG supramedial area and neurons in CA3 and, through the Schaffer collaterals, in CA1. Intrahippocampal pretreatment with hydrated fullerene C60 allows the neurons and their connections to survive the amyloidosis, thus supporting the memory mechanisms.

Impaired glutamatergic projection from the motor cortex to the subthalamic nucleus in 6-hydroxydopamine-lesioned hemi-parkinsonian rats.

PubMed

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.

Group III metabotropic glutamate receptors and exocytosed protons inhibit L-type calcium currents in cones but not in rods.

PubMed

Hosoi, Nobutake; Arai, Itaru; Tachibana, Masao

2005-04-20

Light responses of photoreceptors (rods and cones) are transmitted to the second-order neurons (bipolar cells and horizontal cells) via glutamatergic synapses located in the outer plexiform layer of the retina. Although it has been well established that postsynaptic group III metabotropic glutamate receptors (mGluRs) of ON bipolar cells contribute to generating the ON signal, presynaptic roles of group III mGluRs remain to be elucidated at this synaptic connection. We addressed this issue by applying the slice patch-clamp technique to the newt retina. OFF bipolar cells and horizontal cells generate a steady inward current in the dark and a transient inward current at light offset, both of which are mediated via postsynaptic non-NMDA receptors. A group III mGluR-specific agonist, L-2-amino-4-phosphonobutyric acid (L-AP-4), inhibited both the steady and off-transient inward currents but did not affect the glutamate-induced current in these postsynaptic neurons. L-AP-4 inhibited the presynaptic L-type calcium current (ICa) in cones by shifting the voltage dependence of activation to more positive membrane potentials. The inhibition of ICa was most prominent around the physiological range of cone membrane potentials. In contrast, L-AP-4 did not affect L-type ICa in rods. Paired recordings from photoreceptors and the synaptically connected second-order neurons confirmed that L-AP-4 inhibited both ICa and glutamate release in cones but not in rods. Furthermore, we found that exocytosed protons also inhibited ICa in cones but not in rods. Selective modulation of ICa in cones may help broaden the dynamic range of synaptic transfer by controlling the amount of transmitter release from cones.

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

PubMed

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

2012-06-20

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

Population equations for degree-heterogenous neural networks

NASA Astrophysics Data System (ADS)

Kähne, M.; Sokolov, I. M.; Rüdiger, S.

2017-11-01

We develop a statistical framework for studying recurrent networks with broad distributions of the number of synaptic links per neuron. We treat each group of neurons with equal input degree as one population and derive a system of equations determining the population-averaged firing rates. The derivation rests on an assumption of a large number of neurons and, additionally, an assumption of a large number of synapses per neuron. For the case of binary neurons, analytical solutions can be constructed, which correspond to steps in the activity versus degree space. We apply this theory to networks with degree-correlated topology and show that complex, multi-stable regimes can result for increasing correlations. Our work is motivated by the recent finding of subnetworks of highly active neurons and the fact that these neurons tend to be connected to each other with higher probability.

Optimal and Local Connectivity Between Neuron and Synapse Array in the Quantum Dot/Silicon Brain

NASA Technical Reports Server (NTRS)

Duong, Tuan A.; Assad, Christopher; Thakoor, Anikumar P.

2010-01-01

This innovation is used to connect between synapse and neuron arrays using nanowire in quantum dot and metal in CMOS (complementary metal oxide semiconductor) technology to enable the density of a brain-like connection in hardware. The hardware implementation combines three technologies: 1. Quantum dot and nanowire-based compact synaptic cell (50x50 sq nm) with inherently low parasitic capacitance (hence, low dynamic power approx.l0(exp -11) watts/synapse), 2. Neuron and learning circuits implemented in 50-nm CMOS technology, to be integrated with quantum dot and nanowire synapse, and 3. 3D stacking approach to achieve the overall numbers of high density O(10(exp 12)) synapses and O(10(exp 8)) neurons in the overall system. In a 1-sq cm of quantum dot layer sitting on a 50-nm CMOS layer, innovators were able to pack a 10(exp 6)-neuron and 10(exp 10)-synapse array; however, the constraint for the connection scheme is that each neuron will receive a non-identical 10(exp 4)-synapse set, including itself, via its efficacy of the connection. This is not a fully connected system where the 100x100 synapse array only has a 100-input data bus and 100-output data bus. Due to the data bus sharing, it poses a great challenge to have a complete connected system, and its constraint within the quantum dot and silicon wafer layer. For an effective connection scheme, there are three conditions to be met: 1. Local connection. 2. The nanowire should be connected locally, not globally from which it helps to maximize the data flow by sharing the same wire space location. 3. Each synapse can have an alternate summation line if needed (this option is doable based on the simple mask creation). The 10(exp 3)x10(exp 3)-neuron array was partitioned into a 10-block, 10(exp 2)x10(exp 3)-neuron array. This building block can be completely mapped within itself (10,000 synapses to a neuron).

Response of integrate-and-fire neurons to noisy inputs filtered by synapses with arbitrary timescales: firing rate and correlations.

PubMed

Moreno-Bote, Rubén; Parga, Néstor

2010-06-01

Delivery of neurotransmitter produces on a synapse a current that flows through the membrane and gets transmitted into the soma of the neuron, where it is integrated. The decay time of the current depends on the synaptic receptor's type and ranges from a few (e.g., AMPA receptors) to a few hundred milliseconds (e.g., NMDA receptors). The role of the variety of synaptic timescales, several of them coexisting in the same neuron, is at present not understood. A prime question to answer is which is the effect of temporal filtering at different timescales of the incoming spike trains on the neuron's response. Here, based on our previous work on linear synaptic filtering, we build a general theory for the stationary firing response of integrate-and-fire (IF) neurons receiving stochastic inputs filtered by one, two, or multiple synaptic channels, each characterized by an arbitrary timescale. The formalism applies to arbitrary IF model neurons and arbitrary forms of input noise (i.e., not required to be gaussian or to have small amplitude), as well as to any form of synaptic filtering (linear or nonlinear). The theory determines with exact analytical expressions the firing rate of an IF neuron for long synaptic time constants using the adiabatic approach. The correlated spiking (cross-correlations function) of two neurons receiving common as well as independent sources of noise is also described. The theory is illustrated using leaky, quadratic, and noise-thresholded IF neurons. Although the adiabatic approach is exact when at least one of the synaptic timescales is long, it provides a good prediction of the firing rate even when the timescales of the synapses are comparable to that of the leak of the neuron; it is not required that the synaptic time constants are longer than the mean interspike intervals or that the noise has small variance. The distribution of the potential for general IF neurons is also characterized. Our results provide powerful analytical tools that can allow a quantitative description of the dynamics of neuronal networks with realistic synaptic dynamics.

Synaptogenesis Is Modulated by Heparan Sulfate in Caenorhabditis elegans

PubMed Central

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

Activity Regulates Functional Connectivity from the Vomeronasal Organ to the Accessory Olfactory Bulb

PubMed Central

Hovis, Kenneth R.; Ramnath, Rohit; Dahlen, Jeffrey E.; Romanova, Anna L.; LaRocca, Greg; Bier, Mark E.; Urban, Nathaniel N.

2012-01-01

The mammalian accessory olfactory system is specialized for the detection of chemicals that identify kin and conspecifics. Vomeronasal sensory neurons (VSNs), residing in the vomeronasal organ, project axons to the accessory olfactory bulb (AOB) where they form synapses with principle neurons, known as mitral cells. The organization of this projection is quite precise and is believed to be essential for appropriate function of this system. However, how this precise connectivity is established is unknown. We show here that in mice the vomeronasal duct is open at birth, allowing external chemical stimuli access to sensory neurons, and that these sensory neurons are capable of releasing neurotransmitter to downstream neurons as early as the first post-natal day. Using major histocompatibility complex class I (MHC-1) peptides to activate a selective subset of VSNs during the first few post-natal days of development, we show that increased activity results in exuberant VSN axonal projections and a delay in axonal coalescence into well-defined glomeruli in the AOB. Finally, we show that mitral cell dendritic refinement occurs just after the coalescence of pre-synaptic axons. Such a mechanism may allow the formation of precise connectivity with specific glomeruli that receive input from sensory neurons expressing the same receptor type. PMID:22674266

Slow synaptic dynamics in a network: From exponential to power-law forgetting

NASA Astrophysics Data System (ADS)

Luck, J. M.; Mehta, A.

2014-09-01

We investigate a mean-field model of interacting synapses on a directed neural network. Our interest lies in the slow adaptive dynamics of synapses, which are driven by the fast dynamics of the neurons they connect. Cooperation is modeled from the usual Hebbian perspective, while competition is modeled by an original polarity-driven rule. The emergence of a critical manifold culminating in a tricritical point is crucially dependent on the presence of synaptic competition. This leads to a universal 1/t power-law relaxation of the mean synaptic strength along the critical manifold and an equally universal 1/√t relaxation at the tricritical point, to be contrasted with the exponential relaxation that is otherwise generic. In turn, this leads to the natural emergence of long- and short-term memory from different parts of parameter space in a synaptic network, which is the most original and important result of our present investigations.

A Burst-Based “Hebbian” Learning Rule at Retinogeniculate Synapses Links Retinal Waves to Activity-Dependent Refinement

PubMed Central

Butts, Daniel A; Kanold, Patrick O; Shatz, Carla J

2007-01-01

Patterned spontaneous activity in the developing retina is necessary to drive synaptic refinement in the lateral geniculate nucleus (LGN). Using perforated patch recordings from neurons in LGN slices during the period of eye segregation, we examine how such burst-based activity can instruct this refinement. Retinogeniculate synapses have a novel learning rule that depends on the latencies between pre- and postsynaptic bursts on the order of one second: coincident bursts produce long-lasting synaptic enhancement, whereas non-overlapping bursts produce mild synaptic weakening. It is consistent with “Hebbian” development thought to exist at this synapse, and we demonstrate computationally that such a rule can robustly use retinal waves to drive eye segregation and retinotopic refinement. Thus, by measuring plasticity induced by natural activity patterns, synaptic learning rules can be linked directly to their larger role in instructing the patterning of neural connectivity. PMID:17341130

Electrophysical properties, synaptic transmission and neuromodulation in serotonergic caudal raphe neurons.

PubMed

Li, Y W; Bayliss, D A

1998-06-01

1. We studied electrophysiological properties, synaptic transmission and modulation by 5-hydroxytryptamine (5-HT) of caudal raphe neurons using whole-cell recording in a neonatal rat brain slice preparation; recorded neurons were identified as serotonergic by post-hoc immunohistochemical detection of tryptophan hydroxylase, the 5-HT-synthesizing enzyme. 2. Serotonergic neurons fired spontaneously (approximately 1 Hz), with maximal steady state firing rates of < 4 Hz. 5-Hydroxytryptamine caused hyperpolarization and cessation of spike activity in these neurons by activating inwardly rectifying K+ conductance via somatodendritic 5-HT1A receptors. 3. Unitary glutamatergic excitatory post-synaptic potentials (EPSP) and currents (EPSC) were evoked in serotonergic neurons by local electrical stimulation. Evoked EPSC were potently inhibited by 5-HT, an effect mediated by presynaptic 5-HT1B receptors. 4. In conclusion, serotonergic caudal raphe neurons are spontaneously active in vitro; they receive prominent glutamatergic synaptic inputs. 5-Hydroxytryptamine regulates serotonergic neuronal activity of the caudal raphe by decreasing spontaneous activity via somatodendritic 5-HT1A receptors and by inhibiting excitatory synaptic transmission onto these neurons via presynaptic 5-HT1B receptors. These local modulatory mechanisms provide multiple levels of feedback autoregulation of serotonergic raphe neurons by 5-HT.

A Single Aplysia Neurotrophin Mediates Synaptic Facilitation via Differentially Processed Isoforms Secreted as Mature or Precursor Forms

PubMed Central

Kassabov, Stefan R.; Choi, Yun-Beom; Karl, Kevin A.; Vishwasrao, Harshad D.; Bailey, Craig H.; Kandel, Eric R.

2014-01-01

Summary Neurotrophins control the development and adult plasticity of the vertebrate nervous system. Failure to identify invertebrate neurotrophin orthologs, however, has precluded studies in invertebrate models, limiting understanding of fundamental aspects of neurotrophin biology and function. We identified a neurotrophin (ApNT) and Trk receptor (ApTrk) in the mollusk Aplysia and find they play a central role in learning related synaptic plasticity. ApNT increases the magnitude and lowers the threshold for induction of long-term facilitation and initiates the growth of new synaptic varicosities at the monosynaptic connection between sensory and motor neurons of the gill-withdrawal reflex. Unlike vertebrate neurotrophins, ApNT has multiple coding exons and exerts distinct synaptic effects through differentially processed and secreted splice isoforms. Our findings demonstrate the existence of bona-fide neurotrophin signaling in invertebrates and reveal a novel, post-transcriptional mechanism, regulating neurotrophin processing and the release of pro- and mature neurotrophins which differentially modulate synaptic plasticity. PMID:23562154

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

PubMed

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

2018-03-07

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

Spontaneous and evoked release are independently regulated at individual active zones.

PubMed

Melom, Jan E; Akbergenova, Yulia; Gavornik, Jeffrey P; Littleton, J Troy

2013-10-30

Neurotransmitter release from synaptic vesicle fusion is the fundamental mechanism for neuronal communication at synapses. Evoked release following an action potential has been well characterized for its function in activating the postsynaptic cell, but the significance of spontaneous release is less clear. Using transgenic tools to image single synaptic vesicle fusion events at individual release sites (active zones) in Drosophila, we characterized the spatial and temporal dynamics of exocytotic events that occur spontaneously or in response to an action potential. We also analyzed the relationship between these two modes of fusion at single release sites. A majority of active zones participate in both modes of fusion, although release probability is not correlated between the two modes of release and is highly variable across the population. A subset of active zones is specifically dedicated to spontaneous release, indicating a population of postsynaptic receptors is uniquely activated by this mode of vesicle fusion. Imaging synaptic transmission at individual release sites also revealed general rules for spontaneous and evoked release, and indicate that active zones with similar release probability can cluster spatially within individual synaptic boutons. These findings suggest neuronal connections contain two information channels that can be spatially segregated and independently regulated to transmit evoked or spontaneous fusion signals.

Memory Maintenance in Synapses with Calcium-Based Plasticity in the Presence of Background Activity

PubMed Central

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

Theoretical Neuroanatomy:Analyzing the Structure, Dynamics,and Function of Neuronal Networks

NASA Astrophysics Data System (ADS)

Seth, Anil K.; Edelman, Gerald M.

The mammalian brain is an extraordinary object: its networks give rise to our conscious experiences as well as to the generation of adaptive behavior for the organism within its environment. Progress in understanding the structure, dynamics and function of the brain faces many challenges. Biological neural networks change over time, their detailed structure is difficult to elucidate, and they are highly heterogeneous both in their neuronal units and synaptic connections. In facing these challenges, graph-theoretic and information-theoretic approaches have yielded a number of useful insights and promise many more.

Examining Hippocampal Mossy Fiber Synapses by 3D Electron Microscopy in Wildtype and Kirrel3 Knockout Mice

PubMed Central

Rawson, Randi L.

2017-01-01

Neural circuits balance excitatory and inhibitory activity and disruptions in this balance are commonly found in neurodevelopmental disorders. Mice lacking the intellectual disability and autism-associated gene Kirrel3 have an excitation-inhibition imbalance in the hippocampus but the precise synaptic changes underlying this functional defect are unknown. Kirrel3 is a homophilic adhesion molecule expressed in dentate gyrus (DG) and GABA neurons. It was suggested that the excitation-inhibition imbalance of hippocampal neurons in Kirrel3 knockout mice is due to loss of mossy fiber (MF) filopodia, which are DG axon protrusions thought to excite GABA neurons and thereby provide feed-forward inhibition to CA3 pyramidal neurons. Fewer filopodial structures were observed in Kirrel3 knockout mice but neither filopodial synapses nor DG en passant synapses, which also excite GABA neurons, were examined. Here, we used serial block-face scanning electron microscopy (SBEM) with 3D reconstruction to define the precise connectivity of MF filopodia and elucidate synaptic changes induced by Kirrel3 loss. Surprisingly, we discovered wildtype MF filopodia do not synapse exclusively onto GABA neurons as previously thought, but instead synapse with similar frequency onto GABA neurons and CA3 neurons. Moreover, Kirrel3 loss selectively reduces MF filopodial synapses onto GABA neurons but not those made onto CA3 neurons or en passant synapses. In sum, the selective loss of MF filopodial synapses with GABA neurons likely underlies the hippocampal activity imbalance observed in Kirrel3 knockout mice and may impact neural function in patients with Kirrel3-dependent neurodevelopmental disorders. PMID:28670619

Reinstatement of long-term memory following erasure of its behavioral and synaptic expression in Aplysia

PubMed Central

Chen, Shanping; Cai, Diancai; Pearce, Kaycey; Sun, Philip Y-W; Roberts, Adam C; Glanzman, David L

2014-01-01

Long-term memory (LTM) is believed to be stored in the brain as changes in synaptic connections. Here, we show that LTM storage and synaptic change can be dissociated. Cocultures of Aplysia sensory and motor neurons were trained with spaced pulses of serotonin, which induces long-term facilitation. Serotonin (5HT) triggered growth of new presynaptic varicosities, a synaptic mechanism of long-term sensitization. Following 5HT training, two antimnemonic treatments—reconsolidation blockade and inhibition of PKM—caused the number of presynaptic varicosities to revert to the original, pretraining value. Surprisingly, the final synaptic structure was not achieved by targeted retraction of the 5HT-induced varicosities but, rather, by an apparently arbitrary retraction of both 5HT-induced and original synapses. In addition, we find evidence that the LTM for sensitization persists covertly after its apparent elimination by the same antimnemonic treatments that erase learning-related synaptic growth. These results challenge the idea that stable synapses store long-term memories. DOI: http://dx.doi.org/10.7554/eLife.03896.001 PMID:25402831

Clustered Dynamics of Inhibitory Synapses and Dendritic Spines in the Adult Neocortex

PubMed Central

Chen, Jerry L.; Villa, Katherine L; Cha, Jae Won; So, Peter T.C.; Kubota, Yoshiyuki; Nedivi, Elly

2012-01-01

A key feature of the mammalian brain is its capacity to adapt in response to experience, in part by remodeling of synaptic connections between neurons. Excitatory synapse rearrangements have been monitored in vivo by observation of dendritic spine dynamics, but lack of a vital marker for inhibitory synapses has precluded their observation. Here, we simultaneously monitor in vivo inhibitory synapse and dendritic spine dynamics across the entire dendritic arbor of pyramidal neurons in the adult mammalian cortex using large volume high-resolution dual color two-photon microscopy. We find that inhibitory synapses on dendritic shafts and spines differ in their distribution across the arbor and in their remodeling kinetics during normal and altered sensory experience. Further, we find inhibitory synapse and dendritic spine remodeling to be spatially clustered, and that clustering is influenced by sensory input. Our findings provide in vivo evidence for local coordination of inhibitory and excitatory synaptic rearrangements. PMID:22542188

Hox2 Genes Are Required for Tonotopic Map Precision and Sound Discrimination in the Mouse Auditory Brainstem.

PubMed

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.

BDNF in fragile X syndrome.

PubMed

Castrén, Maija L; Castrén, Eero

2014-01-01

Fragile X syndrome (FXS) is a monogenic disorder that is caused by the absence of FMR1 protein (FMRP). FXS serves as an excellent model disorder for studies investigating disturbed molecular mechanisms and synapse function underlying cognitive impairment, autism, and behavioral disturbance. Abnormalities in dendritic spines and synaptic transmission in the brain of FXS individuals and mouse models for FXS indicate perturbations in the development, maintenance, and plasticity of neuronal network connectivity. However, numerous alterations are found during the early development in FXS, including abnormal differentiation of neural progenitors and impaired migration of newly born neurons. Several aspects of FMRP function are modulated by brain-derived neurotrophic factor (BDNF) signaling. Here, we review the evidence of the role for BDNF in the developing and adult FXS brain. This article is part of the Special Issue entitled 'BDNF Regulation of Synaptic Structure, Function, and Plasticity'. Copyright © 2013 Elsevier Ltd. All rights reserved.

Nitric Oxide Is an Activity-Dependent Regulator of Target Neuron Intrinsic Excitability

PubMed Central

Steinert, Joern R.; Robinson, Susan W.; Tong, Huaxia; Haustein, Martin D.; Kopp-Scheinpflug, Cornelia; Forsythe, Ian D.

2011-01-01

Summary Activity-dependent changes in synaptic strength are well established as mediating long-term plasticity underlying learning and memory, but modulation of target neuron excitability could complement changes in synaptic strength and regulate network activity. It is thought that homeostatic mechanisms match intrinsic excitability to the incoming synaptic drive, but evidence for involvement of voltage-gated conductances is sparse. Here, we show that glutamatergic synaptic activity modulates target neuron excitability and switches the basis of action potential repolarization from Kv3 to Kv2 potassium channel dominance, thereby adjusting neuronal signaling between low and high activity states, respectively. This nitric oxide-mediated signaling dramatically increases Kv2 currents in both the auditory brain stem and hippocampus (>3-fold) transforming synaptic integration and information transmission but with only modest changes in action potential waveform. We conclude that nitric oxide is a homeostatic regulator, tuning neuronal excitability to the recent history of excitatory synaptic inputs over intervals of minutes to hours. PMID:21791288

Orientation selectivity and the functional clustering of synaptic inputs in primary visual cortex

PubMed Central

Wilson, Daniel E.; Whitney, David E.; Scholl, Benjamin; Fitzpatrick, David

2016-01-01

The majority of neurons in primary visual cortex are tuned for stimulus orientation, but the factors that account for the range of orientation selectivities exhibited by cortical neurons remain unclear. To address this issue, we used in vivo 2-photon calcium imaging to characterize the orientation tuning and spatial arrangement of synaptic inputs to the dendritic spines of individual pyramidal neurons in layer 2/3 of ferret visual cortex. The summed synaptic input to individual neurons reliably predicted the neuron’s orientation preference, but did not account for differences in orientation selectivity among neurons. These differences reflected a robust input-output nonlinearity that could not be explained by spike threshold alone, and was strongly correlated with the spatial clustering of co-tuned synaptic inputs within the dendritic field. Dendritic branches with more co-tuned synaptic clusters exhibited greater rates of local dendritic calcium events supporting a prominent role for functional clustering of synaptic inputs in dendritic nonlinearities that shape orientation selectivity. PMID:27294510

Enabling Functional Neural Circuit Simulations with Distributed Computing of Neuromodulated Plasticity

PubMed Central

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

Cell Type-Specific Circuit Mapping Reveals the Presynaptic Connectivity of Developing Cortical Circuits

PubMed Central

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

Synaptic multistability and network synchronization induced by the neuron-glial interaction in the brain

NASA Astrophysics Data System (ADS)

Lazarevich, I. A.; Stasenko, S. V.; Kazantsev, V. B.

2017-02-01

The dynamics of a synaptic contact between neurons that forms a feedback loop through the interaction with glial cells of the brain surrounding the neurons is studied. It is shown that, depending on the character of the neuron-glial interaction, the dynamics of the signal transmission frequency in the synaptic contact can be bistable with two stable steady states or spiking with the regular generation of spikes with various amplitudes and durations. It is found that such a synaptic contact at the network level is responsible for the appearance of quasisynchronous network bursts.

Effects of microgravity on vestibular development and function in rats: genetics and environment

NASA Technical Reports Server (NTRS)

Ronca, A. E.; Fritzsch, B.; Alberts, J. R.; Bruce, L. L.

2000-01-01

Our anatomical and behavioral studies of embryonic rats that developed in microgravity suggest that the vestibular sensory system, like the visual system, has genetically mediated processes of development that establish crude connections between the periphery and the brain. Environmental stimuli also regulate connection formation including terminal branch formation and fine-tuning of synaptic contacts. Axons of vestibular sensory neurons from gravistatic as well as linear acceleration receptors reach their targets in both microgravity and normal gravity, suggesting that this is a genetically regulated component of development. However, microgravity exposure delays the development of terminal branches and synapses in gravistatic but not linear acceleration-sensitive neurons and also produces behavioral changes. These latter changes reflect environmentally controlled processes of development.

How Attention Can Create Synaptic Tags for the Learning of Working Memories in Sequential Tasks

PubMed Central

Rombouts, Jaldert O.; Bohte, Sander M.; Roelfsema, Pieter R.

2015-01-01

Intelligence is our ability to learn appropriate responses to new stimuli and situations. Neurons in association cortex are thought to be essential for this ability. During learning these neurons become tuned to relevant features and start to represent them with persistent activity during memory delays. This learning process is not well understood. Here we develop a biologically plausible learning scheme that explains how trial-and-error learning induces neuronal selectivity and working memory representations for task-relevant information. We propose that the response selection stage sends attentional feedback signals to earlier processing levels, forming synaptic tags at those connections responsible for the stimulus-response mapping. Globally released neuromodulators then interact with tagged synapses to determine their plasticity. The resulting learning rule endows neural networks with the capacity to create new working memory representations of task relevant information as persistent activity. It is remarkably generic: it explains how association neurons learn to store task-relevant information for linear as well as non-linear stimulus-response mappings, how they become tuned to category boundaries or analog variables, depending on the task demands, and how they learn to integrate probabilistic evidence for perceptual decisions. PMID:25742003

Dendrites are dispensable for basic motoneuron function but essential for fine tuning of behavior.

PubMed

Ryglewski, Stefanie; Kadas, Dimitrios; Hutchinson, Katie; Schuetzler, Natalie; Vonhoff, Fernando; Duch, Carsten

2014-12-16

Dendrites are highly complex 3D structures that define neuronal morphology and connectivity and are the predominant sites for synaptic input. Defects in dendritic structure are highly consistent correlates of brain diseases. However, the precise consequences of dendritic structure defects for neuronal function and behavioral performance remain unknown. Here we probe dendritic function by using genetic tools to selectively abolish dendrites in identified Drosophila wing motoneurons without affecting other neuronal properties. We find that these motoneuron dendrites are unexpectedly dispensable for synaptic targeting, qualitatively normal neuronal activity patterns during behavior, and basic behavioral performance. However, significant performance deficits in sophisticated motor behaviors, such as flight altitude control and switching between discrete courtship song elements, scale with the degree of dendritic defect. To our knowledge, our observations provide the first direct evidence that complex dendrite architecture is critically required for fine-tuning and adaptability within robust, evolutionarily constrained behavioral programs that are vital for mating success and survival. We speculate that the observed scaling of performance deficits with the degree of structural defect is consistent with gradual increases in intellectual disability during continuously advancing structural deficiencies in progressive neurological disorders.

The synaptic plasticity and memory hypothesis: encoding, storage and persistence

PubMed Central

Takeuchi, Tomonori; Duszkiewicz, Adrian J.; Morris, Richard G. M.

2014-01-01

The synaptic plasticity and memory hypothesis asserts that activity-dependent synaptic plasticity is induced at appropriate synapses during memory formation and is both necessary and sufficient for the encoding and trace storage of the type of memory mediated by the brain area in which it is observed. Criteria for establishing the necessity and sufficiency of such plasticity in mediating trace storage have been identified and are here reviewed in relation to new work using some of the diverse techniques of contemporary neuroscience. Evidence derived using optical imaging, molecular-genetic and optogenetic techniques in conjunction with appropriate behavioural analyses continues to offer support for the idea that changing the strength of connections between neurons is one of the major mechanisms by which engrams are stored in the brain. PMID:24298167

Developmental Connectivity and Molecular Phenotypes of Unique Cortical Projection Neurons that Express a Synapse-Associated Receptor Tyrosine Kinase.

PubMed

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.

mGluR5 Ablation in Cortical Glutamatergic Neurons Increases Novelty-Induced Locomotion

PubMed Central

Zhu, Jie; Huang, Jui-Yen; Yu, Dinghui; Justice, Nicholas J.; Lu, Hui-Chen

2013-01-01

The group I metabotropic glutamate receptor 5 (mGluR5) has been implicated in the pathology of various neurological disorders including schizophrenia, ADHD, and autism. mGluR5-dependent synaptic plasticity has been described at a variety of neural connections and its signaling has been implicated in several behaviors. These behaviors include locomotor reactivity to novel environment, sensorimotor gating, anxiety, and cognition. mGluR5 is expressed in glutamatergic neurons, inhibitory neurons, and glia in various brain regions. In this study, we show that deleting mGluR5 expression only in principal cortical neurons leads to defective cannabinoid receptor 1 (CB1R) dependent synaptic plasticity in the prefrontal cortex. These cortical glutamatergic mGluR5 knockout mice exhibit increased novelty-induced locomotion, and their locomotion can be further enhanced by treatment with the psychostimulant methylphenidate. Despite a modest reduction in repetitive behaviors, cortical glutamatergic mGluR5 knockout mice are normal in sensorimotor gating, anxiety, motor balance/learning and fear conditioning behaviors. These results show that mGluR5 signaling in cortical glutamatergic neurons is required for precisely modulating locomotor reactivity to a novel environment but not for sensorimotor gating, anxiety, motor coordination, several forms of learning or social interactions. PMID:23940572

Functional regeneration of the ex-vivo reconstructed mesocorticolimbic dopaminergic system.

PubMed

Dossi, Elena; Heine, Claudia; Servettini, Ilenio; Gullo, Francesca; Sygnecka, Katja; Franke, Heike; Illes, Peter; Wanke, Enzo

2013-12-01

CNS reparative-medicine therapeutic strategies need answers on the putative recapitulation of the basic rules leading to mammalian CNS development. To achieve this aim, we focus on the regeneration of functional connections in the mesocorticolimbic dopaminergic system. We used organotypic slice cocultures of ventral tegmental area/substantia nigra (VTA/SN) and prefrontal cortex (PFC) on a multielectrode array (MEA) platform to record spikes and local field potentials. The spontaneously growing synaptically based bidirectional bursting activity was followed from 2 to 28 days in vitro (DIV). A statistical analysis of excitatory and inhibitory neurons properties of the physiological firing activity demonstrated a remarkable, exponentially increasing maturation with a time constant of about 5-7 DIV. Immunohistochemistry demonstrated that the ratio of excitatory/inhibitory neurons (3:1) was in line with the functional results obtained. Exemplary pharmacology suggested that GABAA receptors were able to exert phasic and tonic inhibition typical of an adulthood network. Moreover, dopamine D2 receptor inactivation was equally inhibitory both on the spontaneous neuronal activity recorded by MEA and on patch-clamp electrophysiology in PFC pyramidal neurons. These results demonstrate that axon growth cones reach synaptic targets up to full functionality and that organotypic cocultures of the VTA/SN-PFC perfectly model their newly born dopaminergic, glutamatergic and GABAergic neuronal circuitries.

Methylene-Cycloalkylacetate (MCA) Scaffold-Based Compounds as Novel Neurotropic Agents.

PubMed

Lankri, David; Haham, Dikla; Lahiani, Adi; Lazarovici, Philip; Tsvelikhovsky, Dmitry

2018-04-18

One of the main symptoms in degenerative diseases is death of neuronal cell followed by the loss of neuronal pathways. In neuronal cultures, neurite outgrowths are cell sprouts capable of transforming into either axons or dendrites, to further form functional neuronal synaptic connections. Such connections have an important role in brain cognition, neuronal plasticity, neuronal survival, and regeneration. Therefore, drugs that stimulate neurite outgrowth may be found beneficial in ameliorating neural degeneration. Here, we establish the existence of a unique family of methylene-cycloalkylacetate-based molecules (MCAs) that interface with neuronal cell properties and operate as acceptable pharmacophores for a novel neurotropic (neurite outgrowth inducing) lead compounds. Using an established PC12 cell bioassay, we investigated the neurotropic effect of methylene-cycloalkylacetate compounds by comparison to NGF, a known neurotropic factor. Micrographs of the cells were collected by using a light microscope camera, and digitized photographs were analyzed for compound-induced neurotropic activity using an NIH image protocol. The results indicate that the alkene element, integrated within the cycloalkylacetate core, is indispensable for neurotropic activity. The discovered lead compounds need further mechanistic investigation and may be improved toward development of a neurotropic drug.

Persistent activity in a recurrent circuit underlies courtship memory in Drosophila.

PubMed

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

PubMed Central

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

Noise Trauma-Induced Behavioral Gap Detection Deficits Correlate with Reorganization of Excitatory and Inhibitory Local Circuits in the Inferior Colliculus and Are Prevented by Acoustic Enrichment

PubMed Central

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

COMPENSATION FOR VARIABLE INTRINSIC NEURONAL EXCITABILITY BY CIRCUIT-SYNAPTIC INTERACTIONS

PubMed Central

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

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

PubMed

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

2010-06-01

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

Disruption of the non-canonical Wnt gene PRICKLE2 leads to autism-like behaviors with evidence for hippocampal synaptic dysfunction

PubMed Central

Sowers, L. P.; Loo, L.; Wu, Y.; Campbell, E.; Ulrich, J. D.; Wu, S.; Paemka, L.; Wassink, T.; Meyer, K.; Bing, X.; El-Shanti, H.; Usachev, Y. M.; Ueno, N.; Manak, R. J.; Shepherd, A. J.; Ferguson, P. J.; Darbro, B. W.; Richerson, G. B.; Mohapatra, D. P.; Wemmie, J. A.; Bassuk, A. G.

2014-01-01

Autism spectrum disorders (ASDs) have been suggested to arise from abnormalities in the canonical and non-canonical Wnt signaling pathways. However, a direct connection between a human variant in a Wnt pathway gene and ASD-relevant brain pathology has not been established. Prickle2 (Pk2) is a post-synaptic non-canonical Wnt signaling protein shown to interact with post synaptic density 95 (PSD-95). Here we show that mice with disruption in Prickle2 display behavioral abnormalities including altered social interaction, learning abnormalities, and behavioral inflexibility. Prickle2 disruption in mouse hippocampal neurons led to reductions in dendrite branching, synapse number, and post-synaptic density size. Consistent with these findings, Prickle2 null neurons show decreased frequency and size of spontaneous miniature synaptic currents. These behavioral and physiological abnormalities in Prickle2 disrupted mice are consistent with ASD-like phenotypes present in other mouse models of ASDs. In 384 individuals with autism, we identified two with distinct, heterozygous, rare, non-synonymous PRICKLE2 variants (p.E8Q and p.V153I) that were shared by their affected siblings and inherited paternally. Unlike wild-type PRICKLE2, the PRICKLE2 variants found in ASD patients exhibit deficits in morphological and electrophysiological assays. These data suggest that these PRICKLE2 variants cause a critical loss of PRICKLE2 function. The data presented here provide new insight into the biological roles of Prickle2, its behavioral importance, and suggest disruptions in non-canonical Wnt genes such as PRICKLE2 may contribute to synaptic abnormalities underlying ASDs. PMID:23711981

Cusps enable line attractors for neural computation

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

Xiao, Zhuocheng; Zhang, Jiwei; Sornborger, Andrew T.

Here, line attractors in neuronal networks have been suggested to be the basis of many brain functions, such as working memory, oculomotor control, head movement, locomotion, and sensory processing. In this paper, we make the connection between line attractors and pulse gating in feed-forward neuronal networks. In this context, because of their neutral stability along a one-dimensional manifold, line attractors are associated with a time-translational invariance that allows graded information to be propagated from one neuronal population to the next. To understand how pulse-gating manifests itself in a high-dimensional, nonlinear, feedforward integrate-and-fire network, we use a Fokker-Planck approach to analyzemore » system dynamics. We make a connection between pulse-gated propagation in the Fokker-Planck and population-averaged mean-field (firing rate) models, and then identify an approximate line attractor in state space as the essential structure underlying graded information propagation. An analysis of the line attractor shows that it consists of three fixed points: a central saddle with an unstable manifold along the line and stable manifolds orthogonal to the line, which is surrounded on either side by stable fixed points. Along the manifold defined by the fixed points, slow dynamics give rise to a ghost. We show that this line attractor arises at a cusp catastrophe, where a fold bifurcation develops as a function of synaptic noise; and that the ghost dynamics near the fold of the cusp underly the robustness of the line attractor. Understanding the dynamical aspects of this cusp catastrophe allows us to show how line attractors can persist in biologically realistic neuronal networks and how the interplay of pulse gating, synaptic coupling, and neuronal stochasticity can be used to enable attracting one-dimensional manifolds and, thus, dynamically control the processing of graded information.« less

Cusps enable line attractors for neural computation

NASA Astrophysics Data System (ADS)

Xiao, Zhuocheng; Zhang, Jiwei; Sornborger, Andrew T.; Tao, Louis

2017-11-01

Line attractors in neuronal networks have been suggested to be the basis of many brain functions, such as working memory, oculomotor control, head movement, locomotion, and sensory processing. In this paper, we make the connection between line attractors and pulse gating in feed-forward neuronal networks. In this context, because of their neutral stability along a one-dimensional manifold, line attractors are associated with a time-translational invariance that allows graded information to be propagated from one neuronal population to the next. To understand how pulse-gating manifests itself in a high-dimensional, nonlinear, feedforward integrate-and-fire network, we use a Fokker-Planck approach to analyze system dynamics. We make a connection between pulse-gated propagation in the Fokker-Planck and population-averaged mean-field (firing rate) models, and then identify an approximate line attractor in state space as the essential structure underlying graded information propagation. An analysis of the line attractor shows that it consists of three fixed points: a central saddle with an unstable manifold along the line and stable manifolds orthogonal to the line, which is surrounded on either side by stable fixed points. Along the manifold defined by the fixed points, slow dynamics give rise to a ghost. We show that this line attractor arises at a cusp catastrophe, where a fold bifurcation develops as a function of synaptic noise; and that the ghost dynamics near the fold of the cusp underly the robustness of the line attractor. Understanding the dynamical aspects of this cusp catastrophe allows us to show how line attractors can persist in biologically realistic neuronal networks and how the interplay of pulse gating, synaptic coupling, and neuronal stochasticity can be used to enable attracting one-dimensional manifolds and, thus, dynamically control the processing of graded information.

Cusps enable line attractors for neural computation

DOE PAGES

Xiao, Zhuocheng; Zhang, Jiwei; Sornborger, Andrew T.; ...

2017-11-07

Here, line attractors in neuronal networks have been suggested to be the basis of many brain functions, such as working memory, oculomotor control, head movement, locomotion, and sensory processing. In this paper, we make the connection between line attractors and pulse gating in feed-forward neuronal networks. In this context, because of their neutral stability along a one-dimensional manifold, line attractors are associated with a time-translational invariance that allows graded information to be propagated from one neuronal population to the next. To understand how pulse-gating manifests itself in a high-dimensional, nonlinear, feedforward integrate-and-fire network, we use a Fokker-Planck approach to analyzemore » system dynamics. We make a connection between pulse-gated propagation in the Fokker-Planck and population-averaged mean-field (firing rate) models, and then identify an approximate line attractor in state space as the essential structure underlying graded information propagation. An analysis of the line attractor shows that it consists of three fixed points: a central saddle with an unstable manifold along the line and stable manifolds orthogonal to the line, which is surrounded on either side by stable fixed points. Along the manifold defined by the fixed points, slow dynamics give rise to a ghost. We show that this line attractor arises at a cusp catastrophe, where a fold bifurcation develops as a function of synaptic noise; and that the ghost dynamics near the fold of the cusp underly the robustness of the line attractor. Understanding the dynamical aspects of this cusp catastrophe allows us to show how line attractors can persist in biologically realistic neuronal networks and how the interplay of pulse gating, synaptic coupling, and neuronal stochasticity can be used to enable attracting one-dimensional manifolds and, thus, dynamically control the processing of graded information.« less

Coherent periodic activity in excitatory Erdös-Renyi neural networks: the role of network connectivity.

PubMed

Tattini, Lorenzo; Olmi, Simona; Torcini, Alessandro

2012-06-01

In this article, we investigate the role of connectivity in promoting coherent activity in excitatory neural networks. In particular, we would like to understand if the onset of collective oscillations can be related to a minimal average connectivity and how this critical connectivity depends on the number of neurons in the networks. For these purposes, we consider an excitatory random network of leaky integrate-and-fire pulse coupled neurons. The neurons are connected as in a directed Erdös-Renyi graph with average connectivity scaling as a power law with the number of neurons in the network. The scaling is controlled by a parameter γ, which allows to pass from massively connected to sparse networks and therefore to modify the topology of the system. At a macroscopic level, we observe two distinct dynamical phases: an asynchronous state corresponding to a desynchronized dynamics of the neurons and a regime of partial synchronization (PS) associated with a coherent periodic activity of the network. At low connectivity, the system is in an asynchronous state, while PS emerges above a certain critical average connectivity (c). For sufficiently large networks, (c) saturates to a constant value suggesting that a minimal average connectivity is sufficient to observe coherent activity in systems of any size irrespectively of the kind of considered network: sparse or massively connected. However, this value depends on the nature of the synapses: reliable or unreliable. For unreliable synapses, the critical value required to observe the onset of macroscopic behaviors is noticeably smaller than for reliable synaptic transmission. Due to the disorder present in the system, for finite number of neurons we have inhomogeneities in the neuronal behaviors, inducing a weak form of chaos, which vanishes in the thermodynamic limit. In such a limit, the disordered systems exhibit regular (non chaotic) dynamics and their properties correspond to that of a homogeneous fully connected network for any γ-value. Apart for the peculiar exception of sparse networks, which remain intrinsically inhomogeneous at any system size.

Upregulation of transmitter release probability improves a conversion of synaptic analogue signals into neuronal digital spikes

PubMed Central

2012-01-01

Action potentials at the neurons and graded signals at the synapses are primary codes in the brain. In terms of their functional interaction, the studies were focused on the influence of presynaptic spike patterns on synaptic activities. How the synapse dynamics quantitatively regulates the encoding of postsynaptic digital spikes remains unclear. We investigated this question at unitary glutamatergic synapses on cortical GABAergic neurons, especially the quantitative influences of release probability on synapse dynamics and neuronal encoding. Glutamate release probability and synaptic strength are proportionally upregulated by presynaptic sequential spikes. The upregulation of release probability and the efficiency of probability-driven synaptic facilitation are strengthened by elevating presynaptic spike frequency and Ca2+. The upregulation of release probability improves spike capacity and timing precision at postsynaptic neuron. These results suggest that the upregulation of presynaptic glutamate release facilitates a conversion of synaptic analogue signals into digital spikes in postsynaptic neurons, i.e., a functional compatibility between presynaptic and postsynaptic partners. PMID:22852823

Microglia as Biosensors and Effectors of Neurodysfunction

DTIC Science & Technology

2010-04-01

induce or exacerbate the onset and progression of autism spectrum disorders. Dendritic spines receive the majority of excitatory synapses in the brain... autism spectrum disorders, synaptogenesis 15. NUMBER OF PAGES 24 synaptogenesis 16. PRICE CODE 17. SECURITY CLASSIFICATION OF REPORT...4/1/09-4/30/10 INTRODUCTION: Autism occurs during the post-natal period that neurons form new experience-dependent synaptic connections

Fragile X Mental Retardation Protein is Required for Programmed Cell Death and Clearance of Developmentally-Transient Peptidergic Neurons

PubMed Central

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

Synaptic remodeling generates synchronous oscillations in the degenerated outer mouse retina

PubMed Central

Haq, Wadood; Arango-Gonzalez, Blanca; Zrenner, Eberhart; Euler, Thomas; Schubert, Timm

2014-01-01

During neuronal degenerative diseases, neuronal microcircuits undergo severe structural alterations, leading to remodeling of synaptic connectivity. The functional consequences of such remodeling are mostly unknown. For instance, in mutant rd1 mouse retina, a common model for Retinitis Pigmentosa, rod bipolar cells (RBCs) establish contacts with remnant cone photoreceptors (cones) as a consequence of rod photoreceptor cell death and the resulting lack of presynaptic input. To assess the functional connectivity in the remodeled, light-insensitive outer rd1 retina, we recorded spontaneous population activity in retinal wholemounts using Ca2+ imaging and identified the participating cell types. Focusing on cones, RBCs and horizontal cells (HCs), we found that these cell types display spontaneous oscillatory activity and form synchronously active clusters. Overall activity was modulated by GABAergic inhibition from interneurons such as HCs and/or possibly interplexiform cells. Many of the activity clusters comprised both cones and RBCs. Opposite to what is expected from the intact (wild-type) cone-ON bipolar cell pathway, cone and RBC activity was positively correlated and, at least partially, mediated by glutamate transporters expressed on RBCs. Deletion of gap junctional coupling between cones reduced the number of clusters, indicating that electrical cone coupling plays a crucial role for generating the observed synchronized oscillations. In conclusion, degeneration-induced synaptic remodeling of the rd1 retina results in a complex self-sustained outer retinal oscillatory network, that complements (and potentially modulates) the recently described inner retinal oscillatory network consisting of amacrine, bipolar and ganglion cells. PMID:25249942

Effect of presynaptic membrane potential on electrical vs. chemical synaptic transmission

PubMed Central

Evans, Colin G.; Ludwar, Bjoern Ch.; Kang, Timothy

2011-01-01

The growing realization that electrical coupling is present in the mammalian brain has sparked renewed interest in determining its functional significance and contrasting it with chemical transmission. One question of interest is whether the two types of transmission can be selectively regulated, e.g., if a cell makes both types of connections can electrical transmission occur in the absence of chemical transmission? We explore this issue in an experimentally advantageous preparation. B21, the neuron we study, is an Aplysia sensory neuron involved in feeding that makes electrical and chemical connections with other identified cells. Previously we demonstrated that chemical synaptic transmission is membrane potential dependent. It occurs when B21 is centrally depolarized prior to and during peripheral activation, but does not occur if B21 is peripherally activated at its resting membrane potential. In this article we study effects of membrane potential on electrical transmission. We demonstrate that maximal potentiation occurs in different voltage ranges for the two types of transmission, with potentiation of electrical transmission occurring at more hyperpolarized potentials (i.e., requiring less central depolarization). Furthermore, we describe a physiologically relevant type of stimulus that induces both spiking and an envelope of depolarization in the somatic region of B21. This depolarization does not induce functional chemical synaptic transmission but is comparable to the depolarization needed to maximally potentiate electrical transmission. In this study we therefore characterize a situation in which electrical and chemical transmission can be selectively controlled by membrane potential. PMID:21593394

Presynaptic Partners of Dorsal Raphe Serotonergic and GABAergic Neurons

PubMed Central

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

Tracking the fear memory engram: discrete populations of neurons within amygdala, hypothalamus, and lateral septum are specifically activated by auditory fear conditioning

PubMed Central

Wilson, Yvette M.; Gunnersen, Jenny M.; Murphy, Mark

2015-01-01

Memory formation is thought to occur via enhanced synaptic connectivity between populations of neurons in the brain. However, it has been difficult to localize and identify the neurons that are directly involved in the formation of any specific memory. We have previously used fos-tau-lacZ (FTL) transgenic mice to identify discrete populations of neurons in amygdala and hypothalamus, which were specifically activated by fear conditioning to a context. Here we have examined neuronal activation due to fear conditioning to a more specific auditory cue. Discrete populations of learning-specific neurons were identified in only a small number of locations in the brain, including those previously found to be activated in amygdala and hypothalamus by context fear conditioning. These populations, each containing only a relatively small number of neurons, may be directly involved in fear learning and memory. PMID:26179231

Reciprocal synapses between mushroom body and dopamine neurons form a positive feedback loop required for learning.

PubMed

Cervantes-Sandoval, Isaac; Phan, Anna; Chakraborty, Molee; Davis, Ronald L

2017-05-10

Current thought envisions dopamine neurons conveying the reinforcing effect of the unconditioned stimulus during associative learning to the axons of Drosophila mushroom body Kenyon cells for normal olfactory learning. Here, we show using functional GFP reconstitution experiments that Kenyon cells and dopamine neurons from axoaxonic reciprocal synapses. The dopamine neurons receive cholinergic input via nicotinic acetylcholine receptors from the Kenyon cells; knocking down these receptors impairs olfactory learning revealing the importance of these receptors at the synapse. Blocking the synaptic output of Kenyon cells during olfactory conditioning reduces presynaptic calcium transients in dopamine neurons, a finding consistent with reciprocal communication. Moreover, silencing Kenyon cells decreases the normal chronic activity of the dopamine neurons. Our results reveal a new and critical role for positive feedback onto dopamine neurons through reciprocal connections with Kenyon cells for normal olfactory learning.

Wiring economy and volume exclusion determine neuronal placement in the Drosophila brain.

PubMed

Rivera-Alba, Marta; Vitaladevuni, Shiv N; Mishchenko, Yuriy; Mischenko, Yuriy; Lu, Zhiyuan; Takemura, Shin-Ya; Scheffer, Lou; Meinertzhagen, Ian A; Chklovskii, Dmitri B; de Polavieja, Gonzalo G

2011-12-06

Wiring economy has successfully explained the individual placement of neurons in simple nervous systems like that of Caenorhabditis elegans [1-3] and the locations of coarser structures like cortical areas in complex vertebrate brains [4]. However, it remains unclear whether wiring economy can explain the placement of individual neurons in brains larger than that of C. elegans. Indeed, given the greater number of neuronal interconnections in larger brains, simply minimizing the length of connections results in unrealistic configurations, with multiple neurons occupying the same position in space. Avoiding such configurations, or volume exclusion, repels neurons from each other, thus counteracting wiring economy. Here we test whether wiring economy together with volume exclusion can explain the placement of neurons in a module of the Drosophila melanogaster brain known as lamina cartridge [5-13]. We used newly developed techniques for semiautomated reconstruction from serial electron microscopy (EM) [14] to obtain the shapes of neurons, the location of synapses, and the resultant synaptic connectivity. We show that wiring length minimization and volume exclusion together can explain the structure of the lamina microcircuit. Therefore, even in brains larger than that of C. elegans, at least for some circuits, optimization can play an important role in individual neuron placement. Copyright © 2011 Elsevier Ltd. All rights reserved.

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

PubMed Central

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

2014-01-01

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

Retrograde Semaphorin-Plexin Signaling Drives Homeostatic Synaptic Plasticity

PubMed Central

Orr, Brian O.; Fetter, Richard D.; Davis, Graeme W.

2017-01-01

Homeostatic signaling systems ensure stable, yet flexible neural activity and animal behavior1–4. Defining the underlying molecular mechanisms of neuronal homeostatic signaling will be essential in order to establish clear connections to the causes and progression of neurological disease. Presynaptic homeostatic plasticity (PHP) is a conserved form of neuronal homeostatic signaling, observed in organisms ranging from Drosophila to human1,5. Here, we demonstrate that Semaphorin2b (Sema2b) is target-derived signal that acts upon presynaptic PlexinB (PlexB) receptors to mediate the retrograde, homeostatic control of presynaptic neurotransmitter release at the Drosophila neuromuscular junction. Sema2b-PlexB signaling regulates the expression of PHP via the cytoplasmic protein Mical and the oxoreductase-dependent control of presynaptic actin6,7. During neural development, Semaphorin-Plexin signaling instructs axon guidance and neuronal morphogenesis8–10. Yet, Semaphorins and Plexins are also expressed in the adult brain11–16. Here we demonstrate that Semaphorin-Plexin signaling controls presynaptic neurotransmitter release. We propose that Sema2b-PlexB signaling is an essential platform for the stabilization of synaptic transmission throughout life. PMID:28953869

Graph theoretical model of a sensorimotor connectome in zebrafish.

PubMed

Stobb, Michael; Peterson, Joshua M; Mazzag, Borbala; Gahtan, Ethan

2012-01-01

Mapping the detailed connectivity patterns (connectomes) of neural circuits is a central goal of neuroscience. The best quantitative approach to analyzing connectome data is still unclear but graph theory has been used with success. We present a graph theoretical model of the posterior lateral line sensorimotor pathway in zebrafish. The model includes 2,616 neurons and 167,114 synaptic connections. Model neurons represent known cell types in zebrafish larvae, and connections were set stochastically following rules based on biological literature. Thus, our model is a uniquely detailed computational representation of a vertebrate connectome. The connectome has low overall connection density, with 2.45% of all possible connections, a value within the physiological range. We used graph theoretical tools to compare the zebrafish connectome graph to small-world, random and structured random graphs of the same size. For each type of graph, 100 randomly generated instantiations were considered. Degree distribution (the number of connections per neuron) varied more in the zebrafish graph than in same size graphs with less biological detail. There was high local clustering and a short average path length between nodes, implying a small-world structure similar to other neural connectomes and complex networks. The graph was found not to be scale-free, in agreement with some other neural connectomes. An experimental lesion was performed that targeted three model brain neurons, including the Mauthner neuron, known to control fast escape turns. The lesion decreased the number of short paths between sensory and motor neurons analogous to the behavioral effects of the same lesion in zebrafish. This model is expandable and can be used to organize and interpret a growing database of information on the zebrafish connectome.

Learning neural connectivity from firing activity: efficient algorithms with provable guarantees on topology.

PubMed

Karbasi, Amin; Salavati, Amir Hesam; Vetterli, Martin

2018-04-01

The connectivity of a neuronal network has a major effect on its functionality and role. It is generally believed that the complex network structure of the brain provides a physiological basis for information processing. Therefore, identifying the network's topology has received a lot of attentions in neuroscience and has been the center of many research initiatives such as Human Connectome Project. Nevertheless, direct and invasive approaches that slice and observe the neural tissue have proven to be time consuming, complex and costly. As a result, the inverse methods that utilize firing activity of neurons in order to identify the (functional) connections have gained momentum recently, especially in light of rapid advances in recording technologies; It will soon be possible to simultaneously monitor the activities of tens of thousands of neurons in real time. While there are a number of excellent approaches that aim to identify the functional connections from firing activities, the scalability of the proposed techniques plays a major challenge in applying them on large-scale datasets of recorded firing activities. In exceptional cases where scalability has not been an issue, the theoretical performance guarantees are usually limited to a specific family of neurons or the type of firing activities. In this paper, we formulate the neural network reconstruction as an instance of a graph learning problem, where we observe the behavior of nodes/neurons (i.e., firing activities) and aim to find the links/connections. We develop a scalable learning mechanism and derive the conditions under which the estimated graph for a network of Leaky Integrate and Fire (LIf) neurons matches the true underlying synaptic connections. We then validate the performance of the algorithm using artificially generated data (for benchmarking) and real data recorded from multiple hippocampal areas in rats.

Chimera states in a multilayer network of coupled and uncoupled neurons

NASA Astrophysics Data System (ADS)

Majhi, Soumen; Perc, Matjaž; Ghosh, Dibakar

2017-07-01

We study the emergence of chimera states in a multilayer neuronal network, where one layer is composed of coupled and the other layer of uncoupled neurons. Through the multilayer structure, the layer with coupled neurons acts as the medium by means of which neurons in the uncoupled layer share information in spite of the absence of physical connections among them. Neurons in the coupled layer are connected with electrical synapses, while across the two layers, neurons are connected through chemical synapses. In both layers, the dynamics of each neuron is described by the Hindmarsh-Rose square wave bursting dynamics. We show that the presence of two different types of connecting synapses within and between the two layers, together with the multilayer network structure, plays a key role in the emergence of between-layer synchronous chimera states and patterns of synchronous clusters. In particular, we find that these chimera states can emerge in the coupled layer regardless of the range of electrical synapses. Even in all-to-all and nearest-neighbor coupling within the coupled layer, we observe qualitatively identical between-layer chimera states. Moreover, we show that the role of information transmission delay between the two layers must not be neglected, and we obtain precise parameter bounds at which chimera states can be observed. The expansion of the chimera region and annihilation of cluster and fully coherent states in the parameter plane for increasing values of inter-layer chemical synaptic time delay are illustrated using effective range measurements. These results are discussed in the light of neuronal evolution, where the coexistence of coherent and incoherent dynamics during the developmental stage is particularly likely.

Synaptic Spinules in the Olfactory Circuit of Drosophila melanogaster

PubMed Central

Gruber, Lydia; Rybak, Jürgen; Hansson, Bill S.; Cantera, Rafael

2018-01-01

Here we report on ultrastructural features of brain synapses in the fly Drosophila melanogaster and outline a perspective for the study of their functional significance. Images taken with the aid of focused ion beam-scanning electron microscopy (EM) at 20 nm intervals across olfactory glomerulus DA2 revealed that some synaptic boutons are penetrated by protrusions emanating from other neurons. Similar structures in the brain of mammals are known as synaptic spinules. A survey with transmission EM (TEM) disclosed that these structures are frequent throughout the antennal lobe. Detailed neuronal tracings revealed that spinules are formed by all three major types of neurons innervating glomerulus DA2 but the olfactory sensory neurons (OSNs) receive significantly more spinules than other olfactory neurons. Double-membrane vesicles (DMVs) that appear to represent material that has pinched-off from spinules are also most abundant in presynaptic boutons of OSNs. Inside the host neuron, a close association was observed between spinules, the endoplasmic reticulum (ER) and mitochondria. We propose that by releasing material into the host neuron, through a process triggered by synaptic activity and analogous to axonal pruning, synaptic spinules could function as a mechanism for synapse tagging, synaptic remodeling and neural plasticity. Future directions of experimental work to investigate this theory are proposed. PMID:29636666

Synaptic Spinules in the Olfactory Circuit of Drosophila melanogaster.

PubMed

Gruber, Lydia; Rybak, Jürgen; Hansson, Bill S; Cantera, Rafael

2018-01-01

Here we report on ultrastructural features of brain synapses in the fly Drosophila melanogaster and outline a perspective for the study of their functional significance. Images taken with the aid of focused ion beam-scanning electron microscopy (EM) at 20 nm intervals across olfactory glomerulus DA2 revealed that some synaptic boutons are penetrated by protrusions emanating from other neurons. Similar structures in the brain of mammals are known as synaptic spinules. A survey with transmission EM (TEM) disclosed that these structures are frequent throughout the antennal lobe. Detailed neuronal tracings revealed that spinules are formed by all three major types of neurons innervating glomerulus DA2 but the olfactory sensory neurons (OSNs) receive significantly more spinules than other olfactory neurons. Double-membrane vesicles (DMVs) that appear to represent material that has pinched-off from spinules are also most abundant in presynaptic boutons of OSNs. Inside the host neuron, a close association was observed between spinules, the endoplasmic reticulum (ER) and mitochondria. We propose that by releasing material into the host neuron, through a process triggered by synaptic activity and analogous to axonal pruning, synaptic spinules could function as a mechanism for synapse tagging, synaptic remodeling and neural plasticity. Future directions of experimental work to investigate this theory are proposed.

Developmental and Adult GAP-43 Deficiency in Mice Dynamically Alters Hippocampal Neurogenesis and Mossy Fiber Volume

PubMed Central

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

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

PubMed Central

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

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

PubMed

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.

The Influence of Synaptic Weight Distribution on Neuronal Population Dynamics

PubMed Central

Buice, Michael; Koch, Christof; Mihalas, Stefan

2013-01-01

The manner in which different distributions of synaptic weights onto cortical neurons shape their spiking activity remains open. To characterize a homogeneous neuronal population, we use the master equation for generalized leaky integrate-and-fire neurons with shot-noise synapses. We develop fast semi-analytic numerical methods to solve this equation for either current or conductance synapses, with and without synaptic depression. We show that its solutions match simulations of equivalent neuronal networks better than those of the Fokker-Planck equation and we compute bounds on the network response to non-instantaneous synapses. We apply these methods to study different synaptic weight distributions in feed-forward networks. We characterize the synaptic amplitude distributions using a set of measures, called tail weight numbers, designed to quantify the preponderance of very strong synapses. Even if synaptic amplitude distributions are equated for both the total current and average synaptic weight, distributions with sparse but strong synapses produce higher responses for small inputs, leading to a larger operating range. Furthermore, despite their small number, such synapses enable the network to respond faster and with more stability in the face of external fluctuations. PMID:24204219

A Change in the Ion Selectivity of Ligand-Gated Ion Channels Provides a Mechanism to Switch Behavior.

PubMed

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.

Role of Wnt Signaling in the Control of Adult Hippocampal Functioning in Health and Disease: Therapeutic Implications

PubMed Central

Ortiz-Matamoros, Abril; Salcedo-Tello, Pamela; Avila-Muñoz, Evangelina; Zepeda, Angélica; Arias, Clorinda

2013-01-01

It is well recognized the role of the Wnt pathway in many developmental processes such as neuronal maturation, migration, neuronal connectivity and synaptic formation. Growing evidence is also demonstrating its function in the mature brain where is associated with modulation of axonal remodeling, dendrite outgrowth, synaptic activity, neurogenesis and behavioral plasticity. Proteins involved in Wnt signaling have been found expressed in the adult hippocampus suggesting that Wnt pathway plays a role in the hippocampal function through life. Indeed, Wnt ligands act locally to regulate neurogenesis, neuronal cell shape and pre- and postsynaptic assembly, events that are thought to underlie changes in synaptic function associated with long-term potentiation and with cognitive tasks such as learning and memory. Recent data have demonstrated the increased expression of the Wnt antagonist Dickkopf-1 (DKK1) in brains of Alzheimer´s disease (AD) patients suggesting that dysfunction of Wnt signaling could also contribute to AD pathology. We review here evidence of Wnt-associated molecules expression linked to physiological and pathological hippocampal functioning in the adult brain. The basic aspects of Wnt related mechanisms underlying hippocampal plasticity as well as evidence of how hippocampal dysfunction may rely on Wnt dysregulation is analyzed. This information would provide some clues about the possible therapeutic targets for developing treatments for neurodegenerative diseases associated with aberrant brain plasticity. PMID:24403870

Role of wnt signaling in the control of adult hippocampal functioning in health and disease: therapeutic implications.

PubMed

Ortiz-Matamoros, Abril; Salcedo-Tello, Pamela; Avila-Muñoz, Evangelina; Zepeda, Angélica; Arias, Clorinda

2013-09-01

It is well recognized the role of the Wnt pathway in many developmental processes such as neuronal maturation, migration, neuronal connectivity and synaptic formation. Growing evidence is also demonstrating its function in the mature brain where is associated with modulation of axonal remodeling, dendrite outgrowth, synaptic activity, neurogenesis and behavioral plasticity. Proteins involved in Wnt signaling have been found expressed in the adult hippocampus suggesting that Wnt pathway plays a role in the hippocampal function through life. Indeed, Wnt ligands act locally to regulate neurogenesis, neuronal cell shape and pre- and postsynaptic assembly, events that are thought to underlie changes in synaptic function associated with long-term potentiation and with cognitive tasks such as learning and memory. Recent data have demonstrated the increased expression of the Wnt antagonist Dickkopf-1 (DKK1) in brains of Alzheimer´s disease (AD) patients suggesting that dysfunction of Wnt signaling could also contribute to AD pathology. We review here evidence of Wnt-associated molecules expression linked to physiological and pathological hippocampal functioning in the adult brain. The basic aspects of Wnt related mechanisms underlying hippocampal plasticity as well as evidence of how hippocampal dysfunction may rely on Wnt dysregulation is analyzed. This information would provide some clues about the possible therapeutic targets for developing treatments for neurodegenerative diseases associated with aberrant brain plasticity.

Optogenetic approaches to characterize the long-range synaptic pathways from the hypothalamus to brain stem autonomic nuclei

PubMed Central

Piñol, Ramón A.; Bateman, Ryan; Mendelowitz, David

2012-01-01

Recent advances in optogenetic methods demonstrate the feasibility of selective photoactivation at the soma of neurons that express channelrhodopsin-2 (ChR2), but a comprehensive evaluation of different methods to selectively evoke transmitter release from distant synapses using optogenetic approaches is needed. Here we compared different lentiviral vectors, with sub-population-specific and strong promoters, and transgenic methods to express and photostimulate ChR2 in the long-range projections of paraventricular nucleus of the hypothalamus (PVN) neurons to brain stem cardiac vagal neurons (CVNs). Using PVN subpopulation-specific promoters for vasopressin and oxytocin, we were able to depolarize the soma of these neurons upon photostimulation, but these promoters were not strong enough to drive sufficient expression for optogenetic stimulation and synaptic release from the distal axons. However, utilizing the synapsin promoter photostimulation of distal PVN axons successfully evoked glutamatergic excitatory post-synaptic currents in CVNs. Employing the Cre/loxP system, using the Sim-1 Cre-driver mouse line, we found that the Rosa-CAG-LSL-ChR2-EYFP Cre-responder mice expressed higher levels of ChR2 than the Rosa-CAG-LSL-ChR2-tdTomato line in the PVN, judged by photo-evoked currents at the soma. However, neither was able to drive sufficient expression to observe and photostimulate the long-range projections to brainstem autonomic regions. We conclude that a viral vector approach with a strong promoter is required for successful optogenetic stimulation of distal axons to evoke transmitter release in pre-autonomic PVN neurons. This approach can be very useful to study important hypothalamus-brainstem connections, and can be easily modified to selectively activate other long-range projections within the brain. PMID:22890236